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The Oxford Handbook of Industrial Policy
 9780198862420, 0198862423

Table of contents :
Cover
The Oxford Handbook of Industrial Policy
Copyright
Acknowledgements
Contents
List of Figures
List of Tables
List of Contributors
Part I: Introduction
Chapter 1: Intoruction to Industrial Policy and Development
1.1 An Overview of Industrial Policy and Development
1.1.1 History and Debate in Industrial Policy
1.1.2 Evolving Challenges to Industrial Policy
1.1.3 The Shifting Terrain of Industrial Policy
1.1.4 Political Economy and Industrial Policy
1.1.5 The Cabinet of Policy Errors
1.2. Aims and Approaches of the Handbook
1.2.1 Aims and Approaches
1.2.2 Process
1.3 Organization and Structure
1.3.1 Part I: Introduction
1.3.2 Part II: Theoretical Perspectives
1.3.3 Part III: Context and Connections
1.3.4 Part IV: Experiences in Advanced Economies
1.3.5 Part V: Experiences in Emerging and Developing Countries
References
Chapter 2: The Theory and Practice of Industrial Policy
2.1 Introudction to the Theory and Practice of Industrial Policy
2.2 Theoretical Perspectives of Industrial Policy
2.2.1 The Concept of Industrial Policy
2.2.2 Structural Transformation and Industrial Policy
2.2.2.1 Perspectives on Structural Transformation
2.2.2.2 Manufacturing as an Engine of Growth and Structural Change
2.2.2.2.1 Linkages and Complementarities
2.2.2.3 The Strategic Role of Exports
2.2.2.4 Structural Transformation and its Implications for Industrial Policy
2.2.3 The Infant Industry Theory
2.3 Evolving Thinking on Industrial Policy: Technological Learning and Catch-up
2.3.1 Technical Change and Economic Development
2.3.2 Theoretical Underpinning of Catch-up and Late Development
2.3.3 Technological Learning and Industrial Policy
2.3.3.1 Technological Learning
2.3.3.2 Innovation Systems and Infrastructure
2.3.3.3 Implications for Technological Learning and Industrial Policy
2.4 The State and the Politics of Industrial Policy
2.4.1 The Dynamics of the State‒Market Mechanism
2.4.2 Politics and Political Economy
2.4.3 Disciplining the Private Sector and Reciprocity
2.4.4 Conflict and Political Stability
2.4.5 Myths Surrounding Industrial Policy
2.5 The Practice of Industrial Polciy: Dynamics, Adaptability, and Principles
2.5.1 Linkage Dynamics and Interdependence
2.5.2 Industrial Ecosystem and Cluster Dynamics
2.5.3 Tensions in Industrial Policy
2.5.3.1 Strategic Compatibility and Coherence
2.5.3.2 Synergy and Connections to Other Policies
2.5.3.3 Competitiveness and Discipline
2.5.4 Summary
2.6. Concluding Remarks: Observations and Emerging Issues
2.6.1 The Middle-income Trap
2.6.2 Changing Patterns of Global Production and World Economy
2.6.3 Accelerated Technological Advancement
2.6.4 Sustainability and Green Industrial Policy
Acknowledgements
References
Part II: Theoretical Perspectives
Chapter 3: Industrial Policy, Macroeconomics, and Structural Change
3.1. Introduction
3.2 Growth Patterns
3.3 The Dynamics of Production Structures
3.3.1 Innovations
3.3.2 Complementarities
3.3.3 The Interplay of Innovations and Complementarities
3.3.4 The Links between Productivity and Growth
3.4 Commodity Dependence
3.5 Macroeconomics, Finance, and Structural Change
3.6 Policy Implications
Acknowledgements
References
Chapter 4: Industrial Policies, Patterns of Learning, and Development: An
Evolutionary Perspective
4.1. Introduction
4.2 The Fundamental Properties of Technology
4.2.1 Technological Paradigms and Trajectories
4.2.2 Paradigms, Routines, Organizations
4.3 Technological Dominance, Micro-Heterogeneity, and Non-substitution
4.4 Some General Interpretative Implications
4.5 Structural Changes as a Fundamental Feature of Catching up
4.5.1 The Evolution of Technological Capabilitiesa nd Production Specializations
4.6 The Crucial Role of Industrial Polices
4.6.1 Emulation and, sometimes, Leapfrogging as a General Principle Inspiring Policies
4.6.2 The Complementarity between Technological Learning and the Development of Production Capacity
4.6.3 The Necessity of Nurturing Infant Industries
4.6.4 Industrial Policies in a Sino-centric World: Some Conclusions
4.7 Appendix: Shift-and-Share Decompoistion Methodology
Acknowledgements
References
Chapter 5: Neoclassical Economic Perspectives on Industrial Policy
5.1 Introduction
5.2 Theory of Domestic Distortions and the Policy Hierarchy
5.3 Structural Adjustment Era
5.4 Revival of Interest in Neoclassical Industrial Policy after 2000
5.5 New Structural Economics
5.6 Doomed to Choose: How to Implement Selectivity
5.7 Efficiency Indicators
5.8 Product Space
5.9 Dothese Calculations have any Role?
5.10 Conclusions
References
Chapter 6: Enterprises and Industrial Policy: Firm-based Perspectives
6.1 Introduction
6.2 Theory of the Firm and Enterprises in Industrial Development
6.2.1 Resource-based Theory of the Firm
6.3 Marret Power, Competition, and Enterprise Strategies
6.3.1 Competition and Productivity
6.3.2 Economic Power of Companies
6.3.3 Economic Power, Rents, and Political Settlement
6.4 Dimensions of the Internationalization of Production
6.5 Digitalization of Production, Enterprises, and Industrial Policy
6.5.1 Digitalization of Production
6.5.2 Digital Platforms
6.5.3 Industrial Policy Implications
6.6. Conclusion
References
Chapter 7: Radical Perspectives on Industrial Policy
7.1. Introduction
7.2 Radical Approaches to the Role of Manufacturing and Industrialization
7.2.1 Kaldorian and Structuralist Approaches: Manufacturing as a Special Engine of Growth
7.2.2 A Marxist Approach to Manufacturing and Industrialization
7.3 Marxism and Industrial Policy: Beyond Sectors and Developmen
7.3.1 Value, Exploitation, and Power in Capitalism
7.3.2 Industrial Policy: The Analytic and the Prescriptive
7.3.3 Climate Change: The Potential and Necessity of Radical Industrial Policy Today
7.4 Experiences of 'Radical' Industrial Policies
7.4.1 Statist Models of Industrialization
7.4.2 Labour-centred Industrial Development: Worker Co-operatives
7.4.3 Models of Industrial Policy with Participatory Planning
7.5 Conclusion
References
Part III: Context and Connections
Chapter 8: Global Value Chains and Regionally Coordinated Industrial Policy: The Case of ASEAN
8.1 Regional Economic Integration, The Core of ASEAN Industrial Policy
8.2 The Deepening of GVC Integraion: ASEAN, by Numbers
8.3. The Evolution of ASEAN Industrial Policy: From Import-substitution Industrialization to Export-oriented Industrialization to The Deepening of GVC Integraion
8.4 A Closer Look at ASEAN Industrial Policy in the Era of GVCs
8.4.1 Reshaping ASEAN Industrial Policy in the Era of GVCs: Towards a more Inclusive Participation
8.4.2 ASEAN Industrial Policy in GVCs: Success or Failure?
8.5 ASEAN's Regional Policy Coordination: The Case of the Auto Industry in Indonesia and Thailand
8.5.1 The GVC in the Automotive Industry
8.5.2 A Path to Development and Industrial Upgrading
8.5.3 ASEAN’s Regional Policy Coordination in the Automotive Industry
8.6 The Future Milestones in ASEAN Industrial Policy
References
Chapter 9: Managing Trade through Productive Integration: Industrial
Policy in an Interdependent World
9.1 Introduction
9.2 The Multifaceted Connections Between Trade Integration and Development
9.2.1 Gains from Trade?
9.2.2 Trade Composition, Structural Transformation, and Diversification
9.3 Productive Integration: The Emergence of Global Value Chains
9.3.1 Mapping GVCs
9.3.2 Assessing the Impact of GVCs
9.4 Managing Integration, Facing the Policy Challenges Ahead
9.4.1 Active versus Passive Policies
9.4.2 Upgrading and Sophistication
9.4.3 Regional Value Chains
9.5. Conclusion
References
Chapter 10: Greening Industrial Policy
10.1 Why Green Industrial Polciy?
10.2 General Features of the Greening of Industrial Policy
10.2.1 Energy
10.2.2 Materials/Resources
10.2.3 Finance
10.3 Effective Industrial Policy/Green Growth Initiatives in India and China
10.3.1 Green Industrial Policy in India and its Impact on Trade
10.3.2 Green Industrial Policy in China and its Impact on Trade
10.4 Opportunities for Late Latecomers to Apply Green Industrial Policies to Drive Development
10.5 Why Would any Country Wish to Continue with Fossil-Fuelled D evelopment?
10.6 Greening as Enhancing Energy and Resource Security: Working with the Differential Principle
10.7 Concluding Comments
References
Chapter 11: Globalization Narratives and Industrial Policy
11.1 The Approach Adopted in this Chapter
11.2 Theoretical Persectives
11.3 Hyper-Globalization and De-Globalization
11.4 Narratives in Action I: Globalization Indices
11. 5 Narratives in Action II: Three Storylines
11.5.1 Globalization as Inexorable yet Malleable
11.5.2 Regionalization as a Process that can Refract Global Neo-liberalism
11.5.3 Digital Industrialization: Distant Promise or Catalyst of Inequality?
11.6 Next Steps
11.7 Leveraging Storylines as Policy Space
Acknowledgements
References
Chapter 12: Grand Challenges, Industrial Policy, and Public Value
12.1 Introduction
12.2 From Marret Failure to Marret Shaping
12.3 Learning from History:The Evolution of Mission-oriented Policies
12.4 Instrumentalizing Missions as Industrial Policy
12.5 R: Routes and Directionality—A Mission-oriented Approach
12.6 O: Organizational Capabilities in the Public Sector
12.7 A: Assessment and Evaluation
12.8 R: Risks and Rewards
12.9 Conclusion
Acknowledgements
References
Chapter 13: The Political Economy of Development Banking
13.1 Introduction
13.2 The Economic Rationale for Development Banking
13.3 Lessons from Effective Development Banks
13.4 Diversification of Development Financing Matters for Industrial
Policy
13.5 Case Study: The Political Economy of Development Banking in Brazil
13.5.1 The Positive Side of Development Banking in Brazil
13.5.2 The Limitations of BNDES and the Importance of Broad Political Economy Factors
13.5.3 Policy Debates: Assessing the Role and Effectiveness of BNDES in Brazil
13.5.4 The Politics of Development Banking in Brazil
13.6 General Policy Considerations
References
Chapter 14: Technical Change, the Shifting ‘Terrain of the Industrial’,
and Digital Industrial Policy
14.1 Introduction
14.2 Technical Change and the Concepts of Sector: 'The What', 'The How', and 'The Where'
14.3 'Shifting Terrains': Technical Change and Digitalization within Industrial Ecosystems
14.4 Industrial Policy: Challenges and Opportunities in the New Digital Terrain
14.4.1 Technology Absorption, Deployment, and Technical Change: 'Capability Threshold'
14.4.2 Production System: Retrofitting and Integration
14.4.3 Infrastructure: Basic and Digital
14.4.4 Technology Diffusion: 4IR Islands and the Digital Capability Gap
14.4.5 Technology Access and Affordability: Endogenous Asymmetries
14.5 Conclusions
Acknowledgements
References
Chapter 15: An Industrial Policy Framework to Advance a Global Green
New Deal
15.1 Introduction
15.2 What is Clean Energy?
15.2.1 Natural Gas
15.2.2 Nuclear Energy
15.2.3 Geoengineering
15.2.4 Energy Efficiency and Clean Renewable Energy
15.2.5 Energy Efficiency
15.2.6 Estimating Costs of Efficiency Gains
15.2.7 Rebound Effects
15.2.8 Renewable Energy
15.2.9 Costs of Expanding Renewable Capacity
15.3 Economic Growth and Emissions Reductions
15.3.1 Global Model Framework and Calculations
15.4 Industrial and Financial Policies
15.4.1 Industrial Policies
15.4.2 Providing Cheap and Accessible Financing
15.4.3 Sources of Aggregate Funding
15.4.4 Channelling Financial Resources into Specific Investment Projects
15.5. Domestic Resource Capacities for Clean Energy Investiments
15.5.1 Fossil Fuel Consumption and Imports/Exports
15.6 Conclusion
17.7 Appendix
References
Chapter 16: Industrial Policy and Gender Inclusivity
16.1 Introduction
16.2 The Impact of Industrial Policy and Structural Change on Gender Equality
16.2.1 Gender, Employment, and Industrialization
16.3 Gender Equality Feedback Loops: Impact on Success of Industrial
Policies
16.3.1 Gender and Labour Productivity Growth
16.3.2 Gender and Knowledge Production
16.3.3 Gender, Diversity, and Technical Design
16.4 Conclusion
Acknowledgements
References
Chapter 17: Macro-Policy, Labour Markets, and Industrial Policy
17.1. Introduction
17.2 Setting the Stage: An Export-led Model of Economic Growth
172.1 Enter the Balance-of-Payments Constraint
17.3 'Big Push' Industrialization
17.3.1 The ‘Wage-Goods Inflation’ Barrier: A Ricardian–Kaleckian Mechanism
17.3.2 A Drop in Domestic Expenditure Growth: A Robinsonian Mechanism
17.3.3 Forced Savings, Restrictive Monetary Policy, and Destabilizing Austerity: Three Keynesian Mechanisms
17.4 Vicissitudes in the Life of Export-led Industrialization Strategies
17.4.1 The ‘Dutch Disease’
17.4.2 Escaping the Primary-Commodity Specialization Trap
17.5 Labour Laws as Instruments of Industrial Policy
17.5.1 Wages and Demand
17.5.2 ‘Technology-forcing’ Labour-Market Regulation
17.5.3 The Wage and the Profit Rate
17.6 Macro-Policy Lessons for Late I ndustrialization
References
Chapter 18: Technological Disruptions, GVCs, and Industrial Policy
18. 1 Introduction
18.2 Technological Change and the Fourth Industrial Revolution
18.3 GVCs and Manufacturing Hollowing Out
18.4 Signs of De - globalization
18.5 Industrial Policy and Beyond
18.6 Transformative Industrial Policy
18.7 Conclusions
Acknowledgements
References
Part IV: Experiences in Advanced Economies
Chapter 19: Industrial Policy: A Long-term Perspective and Overview
of Theoretical Arguments
19.1 New Perspectives on Cold War Economic Theory: Adam Smith, David Ricardo, and Paul Samuelson Revisited
19.2 The Historical Roots of Industrial Policy Theory
19. 3 The Key to Wealth as Urban Synergies Created by Adding Value to Raw Materials under a Large Division of Labour: Giovanni Botero (1589)
19.4 Increasing Returns: From Antonio Serra (1613) to Alfred Marshall (1890) and Paul Krugman (19181)
19.5 How Economic Activities Differ,
Learning Curves, and the Sequencing of Technological Change
19.6 On the 'Quality' of Economic Activities: Barriers to Entry, Hierarchies of Skills, and Dynamic Imperfect Competition
19.7 Colonialism and Industrial Policy
19.8 The Marshall Plan and the Need to Rediscover the Economics of Industry, Trade, and Population Density
19.9 'Institutions': A Failed Attempt to Reverse the Arrows of Causality of Economic Development
19.10 When Industrial Policy Intuition Clashes With Ricardian Trade Theory
19.11 Nichification:An 'Industrial' Policy Strategy for Agriculture
19.12 What's New in the Present Industrial Policy Game?
19.13 Conclusion: Unrealistic Utopias that Boomerang as the Curse of Europe and the West
References
Chapter 20: Post-war American Industrial Policy: Market Myths and
Production Realities
20.1 I Introduction To The Economics Of Production And Strategic Policy Frameworks
20.2 The US Second World War Production-informed Policy Framework
20.3 Post-War Policymaking Legacy
20.4 The Japanese Economic Miracle: Rival Technology Management Paradigms
20.5 Production System Legacies: The North versus the South
20.5.1 The Manufacturing Belt
20.5.2 The Sun Belt
20.5.3 The Gun Belt
20.5.4 The Rust Belt
20.6 Neo-Liberalism And Dismantling The 'American System'
20.7 The Capability Triad As Policy Framework
20.8 Appendix: Major Contributors To The Capability And Innovation Perspective
Acknowledgements
References
Chapter 21: European Industrial Policy: A Comparative Perspective
21.1 Introduction
21.2 Industrial Policy: Definition and Taxonomy
21.3 Industrialization and Industrial Policy
21.3.1 The United Kingdom
21.3.2 Germany
21.3.3 France
21.3.4 Italy
21.4 Industrial Policy from 1945 to the Twenty-first Century
21.4.1 Italy
21.4.2 France
21.4.3 The United Kingdom
21.4.4 Germany
21.4.5 Finland
21.4.6 Ireland
21.5 New Industrial Policy at the Turn of the Century
21.5.1 Germany
21.5.2 The United Kingdom
21.5.3 Italy
21.5.4 France
21.6 Conclusions
References
Chapter 22: The European Union’s Industrial Policy
22.1 Introduction
22.2 The Evolution of EU Industrial Policy in a Nutshell
22.2.1 The Interventionist Phase (1950-80)
22.2.2 The Liberal Phase (1980-2005)
22.2.3 The Pragmatic Phase (Since 2005)
22.3 EU Industrial Policy Priorities: The Numbers
22.3.1 The Level Dimension: Industrial Policy Spending at EU and Member-state Levels
22.3.2 The Thematic Dimension: Priorities in Industrial Policy
22.3.3 The Country Dimension: Substantial Differences in Industrial Policy Expenditure
22.4 EU Industrial Policy Efforts in Light of the Major Challenges Ahead
22.4.1 The Technological/Innovation Challenge
22.4.2 The Emerging Markets Challenge
22.4.3 The Cohesion Challenge
22.4.4 The Environmental Challenge
22.5 Conclusions
22.6 Appendix
22.6.1 Member States and Country Groupings
22.6.2 Selection of EU Budget Items and Assignment to Industrial Policy Themes
22.6.2.1 Mapping of budget items in the MFF 2014-20 to the industrial policy themes
22.6.2.2 Mapping of thematic objectives in the ESIF to the industrial policy themes
22.6.2.3 Assumption made for the co-financing by member states of ESIF projects
References
Chapter 23: Diverse Tools of Industrial Policy in Korea: A Schumpeterian
and Capability-based View
23.1 Introduction
23.2 Technology Licensing for Absorptive Capacity
23.3 Infant Industry Protection by Tariffs and Entry Control
23.4 Public-Private Joint R&D
23.5 Concluding Remarks
Acknowledgements
References
Part V: Experiences in Emerging and Deveoping Countries
Chapter 24: Industrial Policy and Industrialization in South East Asia
24.1 Introduction
24.2 Theoretical Considerations
24.3 Import-substitution Policies
24.3.1 Indonesia
24.3.2 Malaysia
24.3.3 The Philippines
24.3.4 Thailand
24.3.5 Summary
24.4 Export-oriented Policies
24.4.1 Indonesia
24.4.2 Malaysia
24.4.3 The Philippines
24.4.4 Singapore
24.4.5 Thailand
24.4.6 Summary
24. 5 Industrialization And De -Industrialization
24.5.1 Indonesia
24.5.2 Malaysia
24.5.3 The Philippines
24.5.4 Singapore
24.5.5 Thailand
24.5.6 Summary
24.6 Technological Upgrading Initiatives
24.6.1 Indonesia
24.6.2 Malaysia
24.6.3 The Philippines
24.6.4 Singapore
24.6.5 Thailand
24.6.6 Summary
24.7 Cconclusions
References
Chapter 25: National Champions, Reforms, and Industrial Policy in China
25.1 Introduction
25.2 Industrial Policy, Big Business, and China's Economic Reforms
25.2.1 The Mainstream Transition Economics View
25.2.2 The State Capitalism View
25.2.3 The Late Industrialization and Developmental State View
25.3 Industrial Policy and the Rise of China's National Champions
25.3.1 The Rise of China's National Champions in Industrial Sectors
25.3.2 The Rise of China's National Champions in Finance
25.4 State-Business Relations And The Governance Of China'S National Champions
25.4.1 Government Capability and Learning
25.4.2 Enterprise Capability and Learning
25.4.3 Networked Hierarchy, Institutional Bridging, and Reciprocal Control
25. 5 International Competitiveness of China's National Champions
25.6 Concluding Remarks
References
Chapter 26: Industrial Policies in the Brics
26.1 Introduction
26.2 The Tradition of Industrial Policy in the Brics
26.3 To Brics or not to Brics
26.3.1 From Bric to Brics
26.3.2 Brics to Build an Economic Block?
26.3.3 Industrial Policy Coordination
26.4 The Challenge of Heterogeneous Industrial Performances
26.4.1 Contribution to Global Economic Activity
26.4.2 Structural Change and Capability Accumulation
26.4.2.1 Productive Capabilities
26.4.2.2 Innovation Capabilities
26.4.3 Integration through Trade and Investment
26.5 Brics and the 4IR
26.5.1 Collective Responses
26.5.1.1 Building Basic Framework Conditions
26.5.1.2 Fostering Demand and Adoption of 4IR Technologies
26.5.1.3 Strengthening Skills and Research Capabilities
26.6 The International Dimension
26.6.1 Africa in Focus
26.7 Conclusions
Acknowledgements
References
Chapter 27: Successes and Failures of Industrial Policy in Transition Economies of Europe and Asia
27.1 Introduction: Industrial Policy and Economic Diversification
27.2 Overview of Changes in the Structure of Economies in Post-Communist Countries
27.3 Structural Economic Transformation and Industrial Policy
27.4 Industrial Policy: Which Industries to Support?
27.5 Industrial Policy: What Tools to Use?
27.6 Industrial Policy in Resource-rich Countries
27.7 Innovation, Research, and Development
27.8 State versus Private Sector, Government, Private, and Foreign Investment
27.9 International Trade and Trade Policy
27.9.1 Trade Liberalization
27.9.2 Import Substitution versus Export Orientation
27.10 Conclusion
References
Chapter 28: Latin American Industrial Policies: A Comparative Perspective
28.1 Introduction
28.2 Tacitness, Localized Technical Change, and Structural Inertia
28.2.1 The Dynamics of Learning and Industrial Policy
28.2.2 The Links between Macroeconomic and Industrial Policies
28.3 Policies in a Comparative Perspective: Industrial Policy in the Different Phases of Latin American Development
28.3.1 Industrial Policy: From State-led Industrialization to the Washington Consensus
28.3.2 From State-led Industrialization to the Debt Crisis
28.3.3 The Washington Consensus Years
28.3.4 The Timid Return of Industrial Policy in the 2000s
28.4 Korea as a Benchmark
28.5 Stylized Facts: A Comparative View on Productivity and Specialization in Latin America
28.5.1 Phases of Convergence and Divergence
28.5.2 Structural Change and Convergence
28.6 Concluding Remarks
Acknowledgements
References
Chapter 29: Phases and Uneven Experiences in African Industrial Policy
29.1 Introduction
29.2 Limited Progress with Structural Transformation in Sub-Saharan Africa
29.3 Theoretical Perspective: Using Industrial Policy to Escape the Learning Trap
29.4 Import-substitution Industrial Policy: The Cement Sector in Nigeria and Ethiopia
29.5 Industrial Policy in Labour-intensive Export Manufactures: Apparel Exports in Ethiopia
29.6 Leapfrogging Manufacturing? Knowledge-based Services in Kenya and Rwanda
29.7 Combining Export-oriented and Import-replacement Policies: Automobiles and Apparel in South Africa
29.8 Conclusion
References
Chapter 30: The Political Economy of Industrialization and Industrial Policy in Africa, 1960‒2018
30.1 Introduction
30.2 Colonial Industrial Policy: The Birth of Import-substitution Industrialization
30.3 Import-substitution Industrialization in Africa: The Early Post-colonial Experience
30.4 The Political and Economic Objectives of Import-substitution Industrialization in Africa
30.5 Industrial Policies for Import-substitution Industrialization
30.6 Industrial Performance Under Import-substitution Industrialization
30.7 Resources- and Needs-based Basic Industry Policy: An Alternative Strategy?
30.8 Liberalization and Industrial Policy
30.9 Renewed Potential for Second- and Third-Stage Import-substitution Industrialization?
30.10 Towards an African Developmental State and Effective Industrial Policy?
30.11 Conclusion
References
Index of Names
General Index

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PART I: INTRODUCTION . Introduction to Industrial Policy and Development



A O, C C, H-J C,  R K-W

. The Theory and Practice of Industrial Policy



A O

P A R T II : TH E O R E TI C A L PE R SPE C T I V E S . Industrial Policy, Macroeconomics, and Structural Change



J´ A O

. Industrial Policies, Patterns of Learning, and Development: An Evolutionary Perspective



M C, G D,  X Y

. Neoclassical Economic Perspectives on Industrial Policy



J W

. Enterprises and Industrial Policy: Firm-based Perspectives



S R

. Radical Perspectives on Industrial Policy S A, S N,  F T



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

P A R T I I I : C O N T E X T AN D C O N N E C T I O N S . Global Value Chains and Regionally Coordinated Industrial Policy: The Case of ASEAN



B A. D  W M

. Managing Trade through Productive Integration: Industrial Policy in an Interdependent World



R K-W  P F

. Greening Industrial Policy



J A. M

. Globalization Narratives and Industrial Policy



D E. E  J H. M

. Grand Challenges, Industrial Policy, and Public Value



M M  R K

. The Political Economy of Development Banking



J D J

. Technical Change, the Shifting ‘Terrain of the Industrial’, and Digital Industrial Policy



A A

. An Industrial Policy Framework to Advance a Global Green New Deal



R P

. Industrial Policy and Gender Inclusivity



S S

. Macro-Policy, Labour Markets, and Industrial Policy



S S

. Technological Disruptions, GVCs, and Industrial Policy D B  L D P



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P A R T I V : E X P E R IE N C E S I N A DV A N C E D ECONOMIES . Industrial Policy: A Long-term Perspective and Overview of Theoretical Arguments



E S. R

. Post-war American Industrial Policy: Market Myths and Production Realities



M H. B

. European Industrial Policy: A Comparative Perspective



P B  S L

. The European Union’s Industrial Policy



M A. L  R Sö

. Diverse Tools of Industrial Policy in Korea: A Schumpeterian and Capability-based View



K L

P A R T V : E X P E R I E N C E S I N E M E R G I N G AN D DEVELOPING COUNTRIES . Industrial Policy and Industrialization in South East Asia



R R

. National Champions, Reforms, and Industrial Policy in China



C L  M C

. Industrial Policies in the BRICS



F S

. Successes and Failures of Industrial Policy in Transition Economies of Europe and Asia



V P

. Latin American Industrial Policies: A Comparative Perspective J´ A O  G P



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

. Phases and Uneven Experiences in African Industrial Policy



L W  N Z

. The Political Economy of Industrialization and Industrial Policy in Africa, –



H C  P L

Index of Names General Index

 

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L  F .......................................................................

. Productivity and GDP dynamics



. Empirical density (Pr, vertical axis) of labour productivities, whole manufacturing of China, France, and Italy, , , and 



. Scatterplot of log (VA/L) versus log (K/L) for corn milling sector (CIC ), 



. Empirical density of (log) labour productivity of exporters and non-exporters of transport equipment (CIC ) and electrical machinery and equipment (CIC ) sectors in selected years (, , and )



. Stylized manufacturing value chain smile curve



. Evolution of GVC positioning in selected developing economies (participation and upstreamness), –



. Evolution of GVC positioning in selected developing economies (downstreamness and upstreamness), –



. Sectoral positioning of BRIC economies, –



. Learning curve associated with solar PV power



. India’s solar PV installed capacity, –



. China: Rising proportion of electric power sourced from water, wind, and sun, –



. A mission-oriented approach to cleaning the oceans



. Industrial ecosystem framework



. Change in women’s relative concentration in industrial-sector employment, –



. An export-led growth model with cumulative causation



. Successful industrial policy raises equilibrium output growth and productivity growth but reduces employment growth



. Trade-off between labour productivity growth and employment growth in twenty-four late industrializing countries, –



. An export-led growth model with cumulative causation and a balance-of-payments constraint



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  

. Successful industrial policy raises equilibrium output growth above the BoP-constrained growth rate



. The macroeconomic impacts of a commodity-price boom



. Escaping the primary-commodity specialization trap



. The (+/–) impacts of a higher real wage on the profit rate (ρ)



. Industry .+



. The sad curve



. The frequency of ‘David Ricardo’ (in English) during the first  years after the  publication of his main work, Principles of Economics, compared to that of two other, then much more famous, English economists



. Frequency of the term ‘comparative advantage’ (in English) from  until today



. The cover of the first edition of the book that laid the earliest foundations for a theory of industrial policy: Botero’s  volume



. An example of the practical consequences of ‘the cult of value added’



. von Thünen’s map of a modern state, with the industrial city at its core



. How industries differ



. Productivity explosion: cotton spinning



. US learning curve in men’s shoes, ‒



. The quality index of economic activities



. Increasing diversity and specialization over time (= ‘tid’)



. Economic growth since  (fall of the Berlin Wall), selected countries: percentiles of population with income growth above/below the  level / the G average level



. Manufacturing value added as a percentage of GDP, selected countries, –



. The industrial policy structure of the EU



. Spending on industrial policy in the European Union, average –



. Funding of industrial policy in the European Union by themes, average –



. Spending on industrial policy from the EU and from member states, by country groups, average –



. Spending on industrial policy from the EU budget, by country groups and themes, average –



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. Share of Horizon  applications per EU member state, average –



. Innovation-driven industrial policy



. Manufacturing value added share in GDP, selected economies, –



. Manufactured exports share in total merchandise exports, selected economies, –



. Electric and electronics exports, selected economies, –



. Motor vehicle exports, selected economies, –



. Trade balance, electric and electronics, selected economies, –



. Trade balance, motor vehicles, selected economies, –



. GERD in GDP, South East Asian market economies, – (%)



. Intellectual property trade balance, selected economies, –



. BRICS’ growing but heterogeneous contribution to global economic dynamics



. BRICS: structural change and catching up, ‒



. GDP change in economies of the former Soviet Union,  = %



. Share of manufacturing value added in GDP in post-communist transition countries between  and , %



. Share of industry value added in GDP of post-communist countries, –, %



. Share of service value added in GDP in selected post-communist countries, –, %



. Manufacturing exports, % of merchandise export, in some post-communist countries



. R&D (research and development) Expenditure in selected countries, % of GDP



. The share of private sector in GDP in some former Soviet republics, –, %



. Public, private, and gross investment in developing countries as a % of GDP, 



. Investment ratio and capital account openness in Latin America



. Real exchange rate ( = )



. Relative productivity vs. United States



. Latin America: Share of manufacturing in GDP, –



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  

. Share of manufacturing in GDP: Largest Latin American countries vs. Korea



. Index of the share of engineering industries in manufacturing value added vs. United States



. Research and development as % of GDP



. Strength of the National Systems of Innovation (NIS)



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L  T ...................................................................

. Annual growth rate of labour productivity amongst firms over –, and subperiods – and – amongst ‘continuing’ firms (i.e firms remaining in the same two-digit sector over the relevant period)  . Median capital intensity (capital/output ratios) by sector, China, Italy, and France, , , and 



. Ratio of the average labour productivity of the second highest decile over the second lowest decile, China, , , and 



. Contribution of each two-digit sector to total manufacturing value added, China, , , and  (percentages)



. Within-sector learning vs. structural change in productivity growth



. Policy hierarchy: industry support by alternative measures



. Uneven returns in the iPod value chain



. Thirty-year global GDP growth trajectory, –



. Global energy demand and energy-efficiency cost projections for 



. Global clean renewable energy expansion and cost projection for 



. Costs of thirty-year clean energy investment project as share of average GDP, –



A. Energy intensity ratios, global average and selected countries



A. Estimates of cost savings from energy-efficiency investments



A. Average global levellized costs of electricity from utility-scale renewable energy sources vs. fossil-fuel sources, –



A. Capital expenditure costs for building renewable electricity productive equipment, present values of total lump-sum capital costs per Q-BTU of electricity



A. Major funding sources for global clean energy investments



A. Change in overall domestic content of clean energy investment activities after  per cent import increase with tradable activities



A. Reliance on fossil fuels and imports as energy sources in selected countries, 



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  

. Gender regimes in BRICS and selected developing and developed countries



. Late industrializing economies: stylized facts and parameter values



. Income elasticity of exports (ε) and imports (μ): selected late industrializing countries, –/



. Impact on economic growth of a one percentage point increase in real wage growth, selected late industrializing countries



. Share of wages in the gross output price, selected regions and countries



. How the game changed



. Characteristics of the collusive and classical modes of diffusion of productivity improvements



. ‘Good’ and ‘bad’ economic activities



. Average wage per cluster category in Europe, based on  European regions



. The three phases of industrial policy in the European Union



. EU and member states’ spending on industrial policy by policy field, – (annual averages)



A. List of member states, country codes, and country groups



A. Industrial policy item within the MFF –



A. Categorization of the thematic objectives in the ESIF into industrial policies themes



. China’s National Champions in Fortune Global , 



. National Champions in the top  companies ranked by R&D in mainland China



. Composition of gross manufacturing exports by country of origin of value added, –



. UNCTAD FDI estimates by ultimate investor, share in inward FDI stock, 



. R&D expenditure in post-communist countries as a percentage of GDP, 



. Manufacturing performance during early ISI, –



. Manufacturing performance during SAPs, –



. Manufacturing performance post SAPs, ‒



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Arkebe Oqubay (PhD) is a senior minister and special adviser to the prime minister of Ethiopia and has been at the centre of policymaking for over twenty-five years. He is the former mayor of Addis Ababa, winner of the Best African Mayor of  and finalist in the World Mayor Award , for his work transforming the city. He is a recipient of the Order of the Rising Sun, Gold and Silver Star, presented by the Emperor of Japan. He currently serves as board chair of several leading public organizations and international advisory boards. He is an ODI Distinguished Fellow and a research associate at the Centre of African Studies in the University of London, and holds a PhD in development studies from SOAS, University of London. His recent works include the path-breaking Made in Africa: Industrial Policy in Ethiopia (OUP, ); The Oxford Handbook of the Ethiopian Economy (OUP, ); How Nations Learn: Technological Learning, Industrial Policy, and Catch-up (OUP, ); China‒ Africa and an Economic Transformation (OUP, ); African Economic Development: Evidence, Theory, and Policy (OUP, ); and The Oxford Handbook of Industrial Hubs and Economic Development (OUP, ). He was recognized as one of the  Most Influential Africans of , and a ‘leading thinker on Africa’s strategic development’ by the New African, for his work, both theoretical and practical, on industrial policies. Christopher Cramer is professor of the political economy of development at SOAS, University of London. He is a vice-chair of the Royal Africa Society and chair of the Scientific Committee of the African Programme on Rethinking Development Economics (APORDE). His publications include Civil War Is Not A Stupid Thing: Accounting for Violence in Developing Countries (Hurst Publishers, ), African Economic Development: Evidence, Theory, and Policy (OUP, ) and The Oxford Handbook of the Ethiopian Economy (OUP, , co-edited with Cheru and Oqubay). He led the research project Fairtrade, Employment, and Poverty Reduction in Ethiopia and Uganda. Ha-Joon Chang teaches economics at the University of Cambridge. His main books include Kicking Away the Ladder (), Bad Samaritans (),  Things They Don’t Tell You about Capitalism () and Economics: The User’s Guide (). His writing has been translated into forty-one languages in forty-four countries. Worldwide, his books have sold over  million copies. He is the winner of the  Gunnar Myrdal Prize and the  Wassily Leontief Prize.

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Richard Kozul-Wright is director of the Globalisation and Development Strategies Division in UNCTAD. He has worked at the United Nations in both New York and Geneva. He holds a PhD in economics from the University of Cambridge. He has published widely on economic issues including, inter alia, in The Economic Journal, Cambridge Journal of Economics, The Journal of Development Studies, and Oxford Review of Economic Policy. He is the author of many books, including The Rise and Fall of Global Microcredit: Development, Debt and Disillusion (, with S. Blankenburg and M. Bateman), Securing Peace: State-Building and Economic Development in Post-Conflict Countries (, with P. Fortunato), Climate Protection and Development (, with Frank Ackerman) and The Resistible Rise of Market Fundamentalism (, with Paul Rayment). His edited volumes include Transnational Corporations and the Global Economy, Economic Insecurity and Development, Securing Peace, Climate Protection and Development, and Industrial Policy. He is a frequent contributor to newspapers worldwide on economic issues, including the Financial Times, The Guardian, and Project Syndicate. Antonio Andreoni is associate professor in industrial economics at University College London (UCL), and research head of UCL Institute for Innovation and Public Purpose. He is also visiting associate professor SARChI Industrial Development, University of Johannesburg. He has acted as an adviser for the World Bank, OECD, DFID, UNIDO, UNCTAD, ILO, UNDP, UNECA, UNU-WIDER, EU Growth and Innovation, and to governments in South Africa, Tanzania, and the United Kingdom. His work on structural change, production, technology, innovation, financialization, corruption, political economy, and industrial policy has appeared in Cambridge Journal of Economics, Development and Change, Cambridge Journal of Regions, Economy and Society, Structural Change and Economic Dynamics, Oxford Review of Economic Policy, European Journal of Development Research, and Energy Policy. Sam Ashman is associate professor in the School of Economics at the University of Johannesburg where she is director of the UJ-IDEP MPhil in industrial policy programme. Her research focuses on the financialization of the world economy and its various impacts—on firm behaviour, patterns of development, the shaping of economic and social policy, and the worsening of inequality. She also researches industrial policy and development issues, including the impact of global value chains, the evolving political economy of South Africa, and the history and philosophy of economics and political economy. David Bailey is professor of business economics at the University of Birmingham and senior fellow of the ESRC’s ‘UK in the Changing Europe’ programme, exploring the impacts of Brexit on the UK automotive and manufacturing industries. He has written extensively on industrial and regional policy, especially in relation to manufacturing and the auto industry. Michael H. Best has been actively engaged in industrial restructuring policy in London, Massachusetts, Slovenia, Cyprus, Jamaica, Honduras, Malaysia, Northern

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Ireland, and the Republic of Ireland, and has written production audits based on extensive factory visits in many other countries. His three books on industrial policy are The New Competition: Institution of Industrial Restructuring (HUP, ), The New Competitive Advantage: The Renewal of American Industry (Oxford University Press, ), and How Growth Really Happens: The Making of Economic Miracles through Production, Governance, and Skills (Princeton University Press, ) which won the  Schumpeter Prize. Patrizio Bianchi is professor of economics at the University of Ferrara, Italy, and has been, since , minister for education and research in the regional government of the Emilia-Romagna region. Besides his academic activity, he has been an adviser to Italian institutions such as the Prime Minister’s Office, the Minister of Industry’s Cabinet and the regional government of Emilia-Romagna, and to international institutions such as the European Commission, the BID, and UNIDO. Patrizio has more than  publications, including books and articles in scientific journals. Publications on industrial policy include Industrial Policy after the Crisis: Seizing the Future (Edward Elgar, ) and Industrial Policy for the Manufacturing Revolution: Perspectives on Digital Globalisation (Edward Elgar, ) with Sandrine Labory. Muyang Chen is an assistant professor at the School of International Studies, Peking University. Her research interests include infrastructure finance, development banking, international development, and state‒market relations. She has been a visiting scholar at the National Graduate Institute for Policy Studies (Japan) and a pre-doctoral fellow at the Global Development Policy Center of Boston University. She received her PhD from the University of Washington, an MA from University of California, Berkeley, and BAs from Peking University and Waseda University. Horman Chitonge is a professor at the Centre for African Studies, University of Cape Town (UCT). His research interests include agrarian political economy, social welfare, and alternative strategies for economic growth in Africa. His most recent books include: Industrialising Africa: Unlocking the Economic Potential of the Continent (Peter Lang, ), Social Welfare Policy in South Africa: From the Poor White Problem to a Digitised Social Contract (Peter Lang, ), Contemporary Customary Land Issues in Africa: Navigating the Contours of Change (Cambridge Scholars Publishing, ) and Economic Growth and Development in Africa: Understanding Trends and Prospects (Routledge, ). Mario Cimoli is deputy executive secretary of the United Nations Economic Commission for Latin America and the Caribbean (ECLAC). In , he was appointed codirector (with Giovanni Dosi and Joseph Stiglitz) of two task forces: Industrial Policy and Intellectual Property Rights Regimes for Development (Initiative for Policy Dialogue, Columbia University, New York). Amongst his broad interests are economic development and its relationship to production structure, productivity growth, international trade, and structural change. His work analyses the linkages between industrial policy, technology development and innovation, and their role in shaping development trajectories.

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Lisa De Propris is professor of regional economic development, University of Birmingham. She has written extensively on competitiveness in clusters and regions; technological change and innovation; clusters and globalization; and regional and industrial policy. Jonathan Di John is a senior lecturer in the political economy of development at SOAS, University of London. His main areas of expertise are development economics, institutional economics, and the political economy of growth and development in Latin America, especially in Brazil and Venezuela. His research focuses on the political economy of industrial strategy, taxation, development strategies in oil economies, and social service delivery in violent contexts. He has undertaken consultancy work for the World Bank, United Nations Development Programme (UNDP), the UK Department for International Development (DFID), the Organisation of Economic Cooperation and Development (OECD) and the International Monetary Fund (IMF). Budi A. Djafar is a PhD candidate in economics at the New School for Social Research. His dissertation investigates the implications of international trade and the rise of global production networks for national income and gender-based employment in the manufacturing sector in Indonesia from  to . Budi previously served in the Ministry of Foreign Affairs of the Republic of Indonesia and the Presidential Advisor’s Council of the Republic of Indonesia, ‒. Giovanni Dosi is professor of economics at Sant’Anna School of Advanced Studies, Pisa, Italy, and continental Europe editor of the journal Industrial and Corporate Change. He is included in the ISI Highly Cited Research list of scholars who have made fundamental contributions to the advancement of science and technology, and is a corresponding member of the Accademia Nazionale dei Lincei, the first academy of sciences in Italy. In , he received the Wiley TIM Distinguished Scholar Award from the Technology and Innovation Management Division of the American Academy of Management. His major research areas, in which he is author and editor of several works, include the economics of innovation and technological change, industrial economics, evolutionary theory, economic growth and development, and organizational studies. Daniel E. Esser is an associate professor in the American University’s School of International Service in Washington, DC. He holds MSc and PhD degrees from the London School of Economics and Political Science. His current book project focuses on sociopolitical processes forging perceptions of legitimacy where democratic institutions are fractured or absent. He also continues to pursue scholarly interests in the politics of sub-national governance and communities’ responses to violence and terror. His research frequently takes him to Latin America and South Asia, and its findings have been published in leading international journals and two Oxford Handbooks. Piergiuseppe Fortunato is an economist at the United Nations Conference for Trade and Development. He previously worked in the Department of Economic and Social

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Affairs of the United Nations in New York and held positions at the University of Bologna and Université Paris I. His research interests include political economics, economic development, and industrial policy. In these fields he has published in journals including Journal of Economic Growth, The Economic Journal, and European Economic Review. He is also heavily involved in policy-oriented research, has edited a volume on post-conflict recovery, published in policy journals such as Global Policy and contributes to several blogs. Rainer Kattel is an Estonian academic and science administrator. He is deputy director and professor of innovation and public governance at the Institute for Innovation and Public Purpose, University College London. Sandrine Labory is associate professor of economics at the University of Ferrara, Italy. She has a MSc in economics from University College London, and a PhD from the European University Institute in Florence, Italy. Her research is focused on industrial economics and policy, including comparative analysis of national and regional industrial policies, innovative and productive processes at firm and territorial levels, structural changes and industrial development. She has published numerous articles in Italian and international journals, as well as books such as Industrial Policy after the Crisis: Seizing the Future (Edward Elgar, ) and Industrial Policy for the Manufacturing Revolution: Perspectives on Digital Globalisation (, Edward Elgar) with Patrizio Bianchi. Michael A. Landesmann was scientific director of the Vienna Institute for International Economic Studies (wiiw) from  to  and is professor of economics at Johannes Kepler University, where he is head of the Department of Economic Theory and Quantitative Research. His research focuses on international economic relations, European economic integration, globalization and labour markets, and migration. He has a DPhil from the University of Oxford, was a lecturer and fellow (Jesus College) at the University of Cambridge, and has held visiting professorships at Harvard University (Pierre Keller, Schumpeter) and a range of other universities (Brandeis, Jerusalem, Central European University, Padova, Basel, Osaka, Mumbai). Peter Lawrence is emeritus professor of economics at Keele University, United Kingdom. He holds a BA and MA from the University of Sussex and a PhD from the University of Leeds. He has taught and researched in several African countries and published variously on rural and industrial development, macroeconomic policy, and development strategy. Keun Lee is a professor of economics at the Seoul National University, fellow of the CIFAR programme on Innovation, Equity and Prosperity, and founding director of the Center for Economic Catch-up. He is an editor of Research Policy and an associate editor of Industrial and Corporate Change. He served as president of the International Schumpeter Society (‒), a member of the Committee for Development Policy of UN (‒), and a council member of the World Economic Forum (‒). He is

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the winner of the  Schumpeter Prize for his monograph Schumpeterian Analysis of Economic Catch-up (Cambridge University Press, ), as well as the  Kapp Prize from the EAEPE for his article on national innovation systems. He obtained his PhD in economics from the University of California, Berkeley. One of his most cited articles is the paper ‘Korea’s Technological Catch-up’ published in Research Policy, with , citations (Google Scholar). His H-index is , with about  papers with more than ten citations. His latest book is The Art of Economic Catch-up: Barriers, Detours, and Leapfrogging (Cambridge University Press, ). Chen Li is an assistant professor at the Centre for China Studies, The Chinese University of Hong Kong (CUHK). He is also an assistant professor (by courtesy) at CUHK’s Lau Chor Tak Institute of Global Economics and Finance (IGEF). He has researched and written extensively on issues related to China’s economic development, business environment, and public policies, such as China’s state-owned enterprise reform, financial regulatory reform, government‒business relations, and industrial and regional development. He received his PhD and MPhil in development studies from the University of Cambridge and dual bachelor’s degrees in law and economics from Peking University. John A. Mathews is professor emeritus in the Faculty of Business and Economics at Macquarie University, Sydney. He was a professor of strategy at Macquarie Graduate School of Management for twenty years, retiring from active teaching in . From – he held concurrently Enr Chair of Competitive Dynamics and Global Strategy at LUISS Gardo Carli University in Rome. For the past several years he has focused on the greening of industry with an emphasis on the role of China. The year  saw the publication of his Global Green Shift by Anthem Press, London. In July  he was awarded the bi-annual Schumpeter Prize in recognition of his work and most recent book. Mariana Mazzucato is professor of the economics of innovation and public value at University College London (UCL), where she is founding director of the UCL Institute for Innovation & Public Purpose (IIPP). She is winner of the  Leontief Prize for Advancing the Frontiers of Economic Thought and the  All European Academies Madame de Staël Prize for Cultural Values. She is author of many publications including The Entrepreneurial State: Debunking Public vs. Private Sector Myths () and The Value of Everything: Making and Taking in the Global Economy (). She advises global policymakers on innovation-led growth. William Milberg is dean and professor of economics at The New School for Social Research and director of the Heilbroner Center for Capitalism Studies at The New School. His research focuses on the relation between globalization, income distribution, and economic growth, and the history and philosophy of economics. His most recent book is Outsourcing Economics: Global Value Chains in Capitalist Development, coauthored with Deborah Winkler. He has served as a consultant to UNCTAD, ILO,

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WTO, and the World Bank. He is a member of the Advisory Board for the Center for Business and Human Rights at New York University. James H. Mittelman is distinguished research professor and university professor emeritus at the American University. Previously, he was professor and dean at Queens College, City University of New York; professor and dean, Graduate School of International Studies (today the Korbel School), University of Denver; and Pok Rafeah chair, National University of Malaysia. He received the International Studies Association’s Distinguished Scholar award in international political economy, and is an honorary fellow at the Helsinki Collegium for Advanced Studies. His books include The Globalization Syndrome: Transformation and Resistance (Princeton University Press, ) and Implausible Dream: The World-Class University and Repurposing Higher Education (Princeton University Press, ). Susan Newman is professor of economics at the Open University, United Kingdom. She has published in areas including finance and industrial policy, the political economy of industrial development in South Africa, and financialization and the restructuring of production. She is particularly interested in the dynamics of wealth and income distribution along global value chains. She is a member of Reteaching Economics and the International Initiative for Promoting Political Economy and is committed to the promotion of political economy in economics education. José Antonio Ocampo is professor at Columbia University’s School of International and Public Affairs, and chair of the Committee for Development Policy of the United Nations Economic and Social Council (ECOSOC). He has occupied numerous positions at the United Nations and his native Colombia, including UN under-secretarygeneral for economic and social affairs, executive secretary of the UN Economic Commission for Latin America and the Caribbean (ECLAC), and member of the board of directors of Banco de la República (Colombia’s central bank), minister of finance, minister of agriculture and director of the National Planning Office of Colombia. Robert Pollin is distinguished university professor of economics and co-director of the Political Economy Research Institute (PERI) at the University of MassachusettsAmherst. He is also the founder and president of PEAR (Pollin Energy and Retrofits), an Amherst, MA-based green energy company operating throughout the United States. His books include The Living Wage: Building a Fair Economy (co-authored, ), Contours of Descent: U.S. Economic Fractures and the Landscape of Global Austerity (), An Employment-Targeted Economic Program for South Africa (co-authored, ), Back to Full Employment (), Greening the Global Economy (), and The Political Economy of Climate Change and the Global Green New Deal (co-authored, forthcoming ). Vladimir Popov is a principal researcher in the Central Economics and Mathematics Institute of the Russian Academy of Sciences. He is also professor emeritus at the New Economic School in Moscow, and an adjunct research professor at the Institute of

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European and Russian Studies at Carleton University in Ottawa. He has published extensively on world economy and development issues; he is editor of four books, and author of hundreds of articles and ten books including Mixed Fortunes: An Economic History of China, Russia, and the West (Oxford University Press, ; also published in Chinese). Gabriel Porcile is an economic affairs officer at ECLAC and professor of economics at the Federal University of Parana, Brazil. He holds a PhD in economic history from the London School of Economics. He has been a visiting scholar at the University of Sao Paulo, Brazil, University of the Republic, Uruguay and Columbia University, United States. His main research topics are economic growth, distribution, structural change, and the political economy of development. His latest publications are ‘New Structuralism and the Balance-of-Payments Constraint’, Review of Keynesian Economics, ,  (with Giuliano Yajima) and ‘A Technology Gap Interpretation of Growth Paths in Latin America and Asia’, Research Policy, ,  (with Mario Cimoli and Joao Basilio Pereima). Rajah Rasiah currently holds the position of distinguished professor of economics at the University of Malaya. His previous positions were professor of industrial organization at National University of Malaysia, and senior research fellow at UNUINTECH, Maastricht. He obtained his doctorate in economics from the University of Cambridge in . He was awarded the Celso Furtado Prize by the World Academy of Sciences in  for advancing social science thought (economics). Erik S. Reinert a Norwegian citizen, is a professor at Tallinn University of Technology and guest researcher at the Centre for Sciences and the Humanities at the University of Bergen. His research area is the theory of uneven growth, that is, the factors which— contrary to the predictions of standard economic theory—cause world economic development to be such an uneven process. He holds a BA from Hochschule St. Gallen, Switzerland, an MBA from Harvard University and a PhD in economics from Cornell University. His book How Rich Countries Got Rich and Why Poor Countries Stay Poor has been published in more than twenty languages. Simon Roberts is a professor of economics at the University of Johannesburg and an economics director at the UK Competition and Markets Authority. He founded and directed the Centre for Competition, Regulation and Economic Development (CCRED) at the University of Johannesburg. Prior to this he was chief economist at Competition Commission South Africa. He has worked extensively on issues of industrial development, trade, regional value chains, competition and economic regulation in Southern and East Africa, advising governments, competition authorities, and regulators. He has also testified as an expert witness in a number of major competition cases. Fernando Santiago is an industrial policy officer at the United Nations Industrial Development Organization (UNIDO) where he specializes in the design, monitoring,

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and evaluation of industrial policies. He is also a member of the scientific board of the Latin American Network for the Study of Learning Systems, Innovation and Competency Building (LALICS). He has published on topics related to innovation and industrial policy. He is an economist from the National Autonomous University of Mexico and holds a master’s degree from SPRU-University of Sussex and a PhD in economics and policy studies of technical change from UNU-MERIT/University of Maastricht. Stephanie Seguino is professor of economics, University of Vermont, United States and fellow, Gund Institute for the Environment. Her research explores the relationship between intergroup inequality by class, race, and gender on the one hand, and economic growth and development on the other. She is past president of the International Association for Feminist Economics and an associate editor of Feminist Economics, Journal of Human Development and Capabilities and Review of Keynesian Economics. Her work has appeared in Cambridge Journal of Economics, Development and Change, Structural Change and Economic Dynamics, and World Development, amongst others. She has consulted with numerous international organizations, including the UNDP, UNRISD, UNCTAD, and the World Bank. Roman Stöllinger is a staff economist at the Vienna Institute for International Economic Studies (wiiw). In his research he focuses on issues related to international trade and global value chains, industrial policy and structural change. Recent publications include a paper on the impact of global value chains on structural change and the need for appropriate industrial policies in Europe and its neighbourhood. He is a regular contributor to research reports by international institutions such as the European Commission and UNIDO. He is strongly involved in the Research Centre International Economics (FIW), an Austrian think-tank and infrastructure platform in the field of international economics. Since  he has also been a lecturer at the Vienna University of Economics and Business, teaching international macroeconomics and industrial policy. Before joining wiiw in , he worked at OeKB, the Austrian Export Credit Agency, where he gained real-world experience in implementing state support policies. He holds a master’s degree in international economics from the University of Innsbruck and a PhD in economics from the University of Vienna. Servaas Storm is a senior lecturer at Delft University of Technology. He obtained a PhD in economics from Erasmus University Rotterdam. His work has appeared in scholarly journals including Cambridge Journal of Economics, Development and Change, Eastern Economic Review, Industrial Relations, International Journal of Political Economy, Journal of Post-Keynesian Economics, and Structural Change and Economic Dynamics. His latest book, co-authored with C.W.M. Naastepad, is Macroeconomics beyond the NAIRU (Harvard University Press, ), winner of the  Myrdal Prize of the European Association for Evolutionary Political Economy. He is one of the editors of Development and Change.

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Fiona Tregenna holds the DST/NRF South African Research Chair in Industrial Development and is also a professor of economics at the University of Johannesburg. She is appointed to policy bodies including the Competition Tribunal and the Presidential Economic Advisory Council, sits on a number of boards, and consults for various international organizations. She has a PhD in economics from the University of Cambridge, a master’s degree in economics from the University of Massachusetts, and earlier degrees from the Universities of the Witwatersrand and Natal (South Africa). Her primary research interest is in issues of structural change, deindustrialization, and industrial development. John Weiss is emeritus professor of development economics at the University of Bradford, United Kingdom. He has written extensively on issues of cost‒benefit analysis, industrialization, and industrial policy, publishing several textbooks, including Project Analysis in Developing Countries (with Steve Curry, MacMillan, ), Industry in Developing Countries (Routledge, ) and The Economics of Industrial Development (Routledge, ). He is the joint editor of the Routledge Handbook on Industry and Development (Routledge, ). He has been a consultant to, among others, the United Nations Industrial Development Organization (UNIDO), the World Bank, and the Asian Development Bank. Lindsay Whitfield is professor (with special responsibilities) in Global Studies and leader of the Centre of African Economies in the Department of Social Sciences and Business, Roskilde University, Denmark. She is author of several books on African politics and economies, including The Politics of African Industrial Policy: A Comparative Perspective (Cambridge University Press, ) and Economies after Colonialism: Ghana and the Struggle for Power (Cambridge University Press, ). Xiaodan Yu is an assistant professor in the Department of Entrepreneurship and Innovation at Nottingham University Business School, China. Prior to joining NUBS, she held research positions at the National Research Council and Scuola Superiore Sant’Anna in Italy. She received her BEng from Beihang University in China, MSc from University of Cincinnati, and PhD in economics from Scuola Superiore Sant’Anna in . Her research interests include the economics of innovation, industrial dynamics, firm growth, and entrepreneurship. Nimrod Zalk is industrial development adviser at the South African Department of Trade and Industry (DTI). Prior to this he was deputy director-general of the Industrial Development Division (IDD) of the DTI. He sits on the board of the South African Industrial Development Corporation (IDC) and chairs the steering committee of the Industrial Development Think Tank (ITT) at the University of Johannesburg.

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  .............................................................................................................

 .............................................................................................................

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  ......................................................................................................................

                                   

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 ,  , - ,   -

. A O  I P  D

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.. History and Debate in Industrial Policy I policy has a long history both in practice and in theory. Early practices of what would come to be regarded as industrial policy stretch back at least as far as Medieval Europe and can be found in Italian city-states or late medieval England. There is also a rich history of thinking and analysis about such policies, including sixteenth-century Italian texts, long before the more frequently referenced classic late eighteenth- and early nineteenth-century texts of Alexander Hamilton (who argued that Adam Smith’s theories were ‘geometrically true’ but ‘practically false’) and Friedrich List.¹ Industrial policy discussions resurfaced during the inter-war period, particularly against the backdrop of the decline of traditional industries in some advanced economies under threat from a mixture of emerging competitors and new technologies (Chick, ) and often connected to growing economic problems at the regional level. With the breakdown of the gold standard and the protectionist turn in the s, industrial policy was closely linked to a wider set of measures aimed at expanding local markets, particularly in poorer countries, where discussions around import-substitution ¹ See Chapter .

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, , ,  -

industrialization began to take root. Industrial policy became a staple of development research and policy analysis from the end of the Second World War.² Nonetheless, the most extensive theoretical and empirical perspectives on industrial policy date from the late twentieth century, often linked to a close examination of the policies adopted by the successful industrializing economies of East Asia (Johnson, ; Amsden, , ; Wade, ; Chang, , among others). These approaches highlighted the significance of ‘a country’s structure of production and trade, because different goods have different production and demand characteristics’ (Thirlwall, : ), and the role of state institutions in shifting those structures to support and sustain economic development (Haggard, ). But industrial policy has also been subject to sustained criticism. Especially from the late s onwards, in mainstream economic analysis, in the pronouncements of international development agencies, and in explicit policy statements by some (especially Anglo-Saxon) governments, industrial policy fell out of favour.³ Neoclassical growth economists tended to favour one-sector growth models and to argue that there were no special properties for any sector. They also pointed to the obvious potential for industrial policy to create ‘rent-seeking’ opportunities.⁴ The debates between proponents and opponents of industrial policy as a strategy of economic development, sustained growth, and competitiveness became sharply ideological and were not always supported by comprehensive, evidence-based analyses. Despite these criticisms, industrial policy never went away. Even in the most committed ‘neo-liberal’ policy environments—the United Kingdom and the United States, for example—industrial policies were implemented (often especially in the military-industrial policy arena), though they were not always advertised loudly as such (see Chapter ). In the United States, for example, the Department of Energy ‘has a program to provide low-interest loans to companies to encourage risky corporate innovation in alternative energy and energy efficiency . . . as a whole, since its inception in , the program has turned a profit . . . Its loans to early-stage solar energy companies launched the industry’ (Lewis, : –). Still, lingering hostility to industrial policy meant that these policies were often presented as ‘energy policy’ or ‘defence policy’, though they promoted some frontier technologies through the public funding of R&D and procurement preferences. This volume comes at a moment when industrial policy has returned to centre stage. Advanced-economy governments have been designing, implementing, and announcing a new generation of industrial policies with more confidence as part of their efforts to benefit from the Fourth Industrial Revolution—even to the point where there are concerns about ‘industrial policy wars’ alongside trade wars.⁵ International

² See Prebisch (), Myrdal (). ³ See Chapter . ⁴ See Chapter . ⁵ ‘Industrial Policy War—Capitalism with Chinese Characteristics’, Financial Times,  September .

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     



organizations have become more open to discussing industrial policy in lower- and middle-income countries, in Africa for example, in part thanks to China’s remarkable transformation over the last forty years (UNCTAD, ) but also in the context of a climate emergency that requires a rapid shift from high- to low-carbon growth paths in both developed and developing countries (UNIDO, ). Two IMF economists even attracted considerable attention for hailing the ‘return of the policy that shall not be named’ (Cherif and Hasanov, ). UNCTAD’s () World Investment Report identified eighty-four countries (accounting for  per cent of global GDP) that had adopted formal industrial policies in the five years to . Further, in recent years industrial policy has come to rely on an ‘expanded range of support measures and instruments that aim to improve infrastructure, education and training, enterprise development, the building of clusters and linkages, entrepreneurship, innovation, access to finance, and social policies’ (UNCTAD, : , citing Salazar-Xirinachs et al., ). At such a moment, this volume offers a comprehensive reference work that presents different schools of thought and reflects evolution in contemporary thinking on industrial policy, alongside theoretical and empirical evidence from both advanced and developing economies. It also makes the connection between industrial policy and other policies. When economists (and others) across a broad spectrum seem to agree on the relevance, desirability, and practicability of industrial policy, it is especially important to assess suggestions that there is a ‘consensus’ around what this means and involves. For some, industrial policy should still be seen as subordinate to other goals, such as competitiveness or structural reform, while others argue that this ‘mainstreaming’ of industrial policy amounts to a dilution of the idea. Hence the relevance of this book, which provides the historical background and conceptual underpinnings, and presents a range of perspectives on industrial policy, together with regional and individual country case studies.

.. Evolving Challenges to Industrial Policy This volume captures a range of perspectives on industrial policy at a very specific moment in the history of such policies. Another reason why this book is particularly relevant is that, just as industrial policy has become more popular again among both academic economists and policymakers, there are also new challenges to the viability of industrial policy, especially in developing countries. The upshot, for some observers, is that low-income countries, for example those in Africa, should not even try to industrialize any more, given the advent of a post-industrial age (IMF, ), or should simply limit their ambition to providing links in global value chains, given how impenetrable the global industrial hierarchy has become (Baldwin, ). The most significant of these threats is the spectre of ‘premature de-industrialization’: many countries have experienced a decline in the share of manufacturing in GDP— de-industrialization—at far lower levels of per capita GDP than has historically been

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, , ,  -

the case. This trend, and some of the factors that may lie behind it, suggests to some economists that manufacturing (and industrial policy) cannot be the ‘engine of growth’ that it historically has been (World Bank, ). But this is contested, and debates around the ineluctability of premature de-industrialization and about the continued role for manufacturing and industrial policy are taken up across different chapters in this book.⁶ Premature de-industrialization is just one of a number of features of the contemporary global political economy that affect the scope for industrial policy. Related arguments about automation and the Fourth Industrial Revolution suggest to some that it will be even more difficult, particularly in lower- and middle-income countries, successfully to pursue industrial policies geared towards competitiveness, productivity growth, and employment (Cramer and Tregenna, ). Others argue that there remains plenty of scope for industrial policies to harness the dynamics of new waves of technical change and that these may even in some respects make it easier to ‘catch up’.⁷ Meanwhile, there are arguments that recent developments in global political economy and governance, for example around the increased market power of large international firms, restrict policy space still further for developing countries in particular. And there are counter-arguments pointing to the opportunities for policy space that are created by a more multi-polar, fragmented global political order (Grabel, ). If the ‘rules of the game’ have become increasingly unstable, that may make the global economy both more hostile and more ‘permissive’ for developing countries. Finally, much production nowadays is organized through global value chains commanded by ‘systems integrators’ controlling a cascade of ‘tiers’ of suppliers, with very little scope for lower-income countries to occupy anything higher than the lower levels. There are complex debates about what scope there is for these lower-income countries to ‘move up’ within GVCs, about the ways in which GVCs have reshaped much industrial policy around foreign direct investment policy,⁸ and indeed about the implications of evidence of some ‘reshoring’ of production (bringing production and innovation physically closer together again) by firms based in advanced economies.⁹

.. The Shifting Terrain of Industrial Policy The spatial dimensions of firm decisions within a globalized economy are an important influence on the evolution of industrial policies. Another influence is the blurring of boundaries between ‘sectors’ traditionally treated as discrete categories of economic activity. One feature of modern capitalism is the way in which firms, especially those based in advanced economies, concentrate and control knowledge expertise in ways ⁶ ⁷ ⁸ ⁹

For instance, see For instance, see Chapters , , , and . For example, Naudé (), UNCTAD (). See also Mittelman (), Lee (), UNCTAD (). See Gereffi (). See also Chapters  and .

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     



that add to the advantages of first movers and economies of scale and scope, etc. This represents one facet of ‘servicification’, the increasing share of the value of final output of goods accounted for by service-sector activities—branding, design, R&D, logistics, etc., whether carried out in-house or contracted out. But economic data—for example, US production and employment statistics—have not adjusted to reflect accurately the relative weight of different activities. US statistics, for example, ‘do not include [in manufacturing statistics] pre-production services to manufacturing such as research and development or design or post-production services such as repair and maintenance or sales. Yet manufacturing firms invest heavily in these services’ (Whitefoot and Valdivia, : ). The basis of the North American Industry Classification System (NAICS) is the assumption that extractive industries, manufacturing, and service industries ‘rely on essentially different production processes and establishments in each of these three categories have similar processes’ (Whitefoot and Valdivia, : ). As a result, much that is fundamentally manufacturing-dependent economic activity is classified as non-manufacturing in service-sector data. Another way in which activities traditionally assigned to discrete ‘sectors’ have become increasingly imbricated is the ‘industrialization of freshness’ (Cramer, Di John, and Sender, ). Much production of ‘fresh’ and apparently unprocessed high-value agricultural commodities (e.g. avocados, blueberries, poinsettia, or pelargonium seedlings) is very different from traditionally conceived ‘primary commodity production’ and in its ‘roundabout’ production processes has many of the attributes of industrial activity.¹⁰

.. Political Economy and Industrial Policy The recent return of industrial policy to international policy discussions is not the result of new analytical insights into the process of structural transformation. Arguably, it has more to do with the weak outcomes of policies pursued by many developing countries under the guidance of the Washington Consensus,¹¹ the shock to market-friendly policies in the global financial crisis of  and its aftermath, the challenges to the welfare state and ‘normal’ politics in many advanced, de-industrialized economies, growing regional disparities, new sources and forms of global competition and market demand (in China above all),¹² and the questions posed by technological changes and climate change. Meanwhile, governments in developing countries are once again asking

¹⁰ On the enduring difficulties with the classification of economic activities, see also Marshall () and Schumpeter (). See also Chapter , which discusses this issue of the shifting terrain of industrial policy. ¹¹ Oqubay (), Cramer, Sender, and Oqubay (). ¹² Nolan (), Nayyar ().

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, , ,  -

how they can achieve their development goals by creating new sources of growth and dynamism, rather than simply trying to do the best with what they currently have.¹³ In discussing these and other issues, the present volume takes a political economy approach. For industrial policy cannot be reduced to a technical or ‘purely’ economic argument or set of instruments. Both more and less orthodox economists agree on this. But there are very different ways of taking account of the political economy of industrial policy. Public-choice theory may be one way of thinking about the political economy but it is not the same as more historically minded, less methodologically individualist frameworks, such as the political settlements literature or older (and to some extent more explicitly class-based) analyses like Hirschman’s discussion of the political economy of import-substitution industrialization (ISI) in Latin America (Hirschman, ). Arguably, the richest vein of the political economy of industrial policy is found in domestic class-based analysis and in analyses of particular countries’ positions in international alliances and hierarchies. From that perspective, domestic and international security has often been an important theme in accounting for governments resorting to and pushing industrial policy. For example, Doner, Ritchie, and Slater () analysed industrial policy and the ‘developmental state’ in North East Asia as responses to internal and external ‘threats’. In this volume, another kind of example is given in Mathews’ argument about the role of energy security in provoking innovative industrial policy in China which has created new, lower-cost technologies that over time can in turn help lower-income economies avoid reinventing a sustainable wheel.¹⁴

.. The Cabinet of Policy Errors One further feature distinguishing this volume is its commitment to highlighting learning from policy mistakes. While we are wary of simplistic labels of ‘failure’ and ‘success’, whose evaluative criteria are often not laid out clearly or are subjective, arbitrary, or unduly narrow, the issue of policy failure is a key theme in debates on industrial policy. Much of the hostile literature on industrial policy simply points to failures and uses these to argue against its adoption. Much of the literature more favourable to industrial policy picks out and explores the conditions behind obvious ‘successes’. Thus, the literature can become bifurcated and static, reduced to an unhelpful either/or of market failure or state failure. We argue for a more dynamic focus on ‘failure’. This stance is inspired not only by Hirschman’s () subtle investigation of the dynamics of the ‘Hiding Hand’ in large projects, but also by the experience of Enzo Ferrari. Ferrari often held board meetings in a room whose walls were lined with cabinets displaying the parts of racing cars that had malfunctioned ¹³ See Cimoli, Dosi, and Stiglitz (), Best (), and Lee (). ¹⁴ See Chapter .

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     



during races, to focus the board members’ minds on the obsessive need to learn from what had gone wrong and to improve. We advocate a wider institutional adoption of the policy official’s equivalent of the ‘cabinet of errors’.

. A  A   H

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.. Aims and Approaches No country has made the arduous journey from widespread rural poverty to postindustrial prosperity without employing targeted and selective government policies to shift the production structure towards activities and sectors with higher productivity, better-paid jobs, and greater technological potential.¹⁵ Alfred Marshall’s ‘principle of continuity’, that is, development through incremental changes (Marshall, ) has never been sufficient to bring about fundamental structural changes and rising productivity and has always been supplemented by the visible hand of policy intervention. Such policies are conventionally called industrial policies, although they are also termed ‘production/productive transformation policies’. Much of the discussion on industrial policy in recent years, however, has revolved around sterile debates on government failures or whether governments can pick winners. This volume focuses on theoretical foundations, on institutional conditions, and on emerging challenges. The Oxford Handbook of Industrial Policy introduces specialist research by a wide range of scholars and seeks to make a significant contribution to our understanding of industrial policies and their role in economic growth, development, and structural change, both historically and in today’s changing policy landscape. The volume reviews the conceptual underpinnings, theoretical perspectives, and methodologies of the study of industrial policies. It uses case studies of policies and practices to offer new insights for policymakers, practitioners, and policy researchers. The Handbook is forward looking while also drawing on long historical perspectives, and aims to serve as a single, comprehensive, and authentic reference on industrial policies. The book also highlights major themes and policy perspectives rather than speculating on recommendations that may not stand the test of time. The evolving debates on industrial policy and the perspectives of various schools of thought are presented, from the early Industrial Revolution to the adaptive industrial policy practices of the present day.¹⁶ Theoretical perspectives are integrated with empirical evidence from both advanced economies and developing and emerging economies, bridging the gap between the theory and practice of industrial policy. ¹⁵ See Chapters  and . ¹⁶ See Chapters , , and . See also Lin and Chang ().

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

, , ,  -

The volume’s critical examination of the progress and direction of debates lays the foundation for future research. It attempts to provide new perspectives for scholars and graduate students, as well as a collection of authoritative and original research.

.. Process The first step in ensuring the high standard and timely publication of this volume was the careful selection of topics and contributing authors. At an inception workshop in Addis Ababa, editors and contributors met to discuss the themes and chapters chosen, to review abstracts, and to discuss new ideas and suggestions. Contributors were encouraged to focus on mistakes and failures as well as successes, to consider connections and contexts, to be cognizant of unevenness in policy design and outcomes, and to highlight political economy issues. External and internal reviewers have carefully reviewed each chapter, providing a high level of peer review engagement (especially for an edited volume). A chapter review workshop reviewed all first drafts to improve chapters and ensure complementarity. A book project coordination team provided the necessary support service and a pre-publisher copy-editing service improved readability and ensured uniformity of style.

. O  S

.................................................................................................................................. The thirty chapters of the Handbook are organized in five sections: introduction; theoretical perspectives; context and connections; experiences in advanced economies; emerging economies and developing countries.

.. Part I: Introduction The background, purpose, approaches, and organization of the Handbook are introduced in Chapter , together with an outline of the evolving landscape of industrial policy and emerging research questions. The volume’s wide conceptualization of industrial policy includes the transformation of production, the development of technological and innovation capabilities, and the constant struggle to occupy more advantageous positions in international markets. In addition to industrial policy within national and sub-national structures, regional application of industrial policy can be seen, for example, in the European Union. Oqubay’s Chapter , ‘The Theory and Practice of Industrial Policy’, presents industrial policy as a driver of structural change and a conduit of technological catch-up, underlining the strategic

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     



role of exports and of sectors with higher dynamic efficiency.¹⁷ The dynamic and adaptive aspects of industrial policies are examined, together with their origins and the unevenness of policy design and outcomes. The chapter provides the groundwork for subsequent chapters that present theoretical perspectives, contexts and connections, and experiences from advanced, emerging, and developing countries.

.. Part II: Theoretical Perspectives The five chapters in this section present a comprehensive conceptual framework by reviewing the industrial policy perspectives of various schools and traditions. Ocampo (Chapter ) examines the macroeconomic dimension of industrial policy, arguing that structural change and active industrial policy or productive transformation policies must be at the centre of economic development strategy. The chapter underlines the centrality of state intervention in promoting the dynamic efficiency of economic structures and their capacity to generate new waves of structural change. Cimoli, Dosi, and Yu (Chapter ) discuss the role of industrial policy in the evolutionary view of innovation and learning as drivers of economic development. Technological paradigms and trajectories are considered, as well as the link between catch-up processes and the dynamics of capability accumulation within and across firms, and their embeddedness in national systems of innovation.¹⁸ Weiss (Chapter ) reviews neoclassical perspectives on industrial policy. The chapter discusses market imperfections and ‘distortions’, the idea of a ‘policy hierarchy’ that might lead to a case for industrial policy, and the neoclassical assumptions underlying recent work on ‘discovery process’, ‘export space’, and ‘facilitative’ interventions to exploit comparative advantage. Roberts (Chapter ) presents a firm-based perspective linking large firm strategies to industrial policies, and reviews relevant theories of the firm and capability development. Ashman, Newman, and Tregenna (Chapter ) look at various ‘radical’ economic traditions relating to industrial policy and industrialization and consider how these views differ from structuralist or evolutionary economics or other heterodox approaches. Their discussion gives greater attention, for example, to arguments about the ‘inherent contradiction of labour and capital’ and the ‘contradictory’ role of the state.

.. Part III: Context and Connections This section comprises eleven critical chapters on the context of industrial policy and its connections with other policies. Djafar and Milberg (Chapter ) discuss global value ¹⁷ See Hirschman (), Kaldor (), Amsden (), and Mazzucato (). ¹⁸ See Cimoli, Dosi, and Stigltiz (), Best (), and Oqubay and Ohno ().

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

, , ,  -

chains and the regionalization of industrial policy, based on the case of ASEAN. The changing nature of global production networks and their concentration is examined, together with regional coordination of industrial policy, which is strengthening production integration and promoting competitiveness. Kozul-Wright and Fortunato (Chapter ) examine industrial policy in an interdependent world and review debates around trade, participation in global value chains, and industrial policy. The chapter discusses the diversification of the export basket, the sophistication of export products, and the upgrading of productive capacities. Mathews (Chapter ) examines the greening of industrial policy, the shift to renewables, and the solutions offered by the circular economy.¹⁹ Case studies from advanced, emerging, and developing countries are presented, encompassing energy, materials and finance, and other green options. Esser and Mittelman (Chapter ) address the blind spot in the evolving and competing narratives of globalization and industrial policy, showing the importance of understanding these representations as they are objectified as policy. Mazzucato and Kattel (Chapter ), examining the ‘mission-oriented’ approach to industrial policy, which focuses on providing the direction for growth, argue for the importance of a new analytical framework to understand how policies can shape market forces. Di John (Chapter ) reviews the evolution and political economy of development banking as a catalyst of industrial policy in the context of late development and structural change (with particular attention to the case study of Brazil). Andreoni (Chapter ) reviews the role of technical change as a driver of the shifting terrain of industrial sectors and the industrial ecosystem. Pollin (Chapter ) identifies the prime contributors to climate change and examines viable routes to achieving agreed global emissions goals. The chapter also looks at the role of clean energy industrial policies and global investment, and how industrial policy will promote technical innovation and the expansion of investment. Seguino (Chapter ) explores the intersection of gender relations and industrialization and industrial policy, and argues that gender-inclusive industrial policies can ensure equitable and sustainable development. Storm (Chapter ) shows the importance of macroeconomic policy management for the effectiveness of industrial policy and argues that demand-side policies are crucial. He explores the ways in which food policy and wages and labour protection legislation can underpin industrial policy and shows how overvalued exchange rates and restrictive monetary policy have often undermined industrial policy efforts. Bailey and De Propris (Chapter ) review technological change in global value chains, the origins of internationalization strategies and global production networks, and the importance of appreciating the spatial dimensions of industrial policy.

¹⁹ See Mathews ().

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     



.. Part IV: Experiences in Advanced Economies The five chapters in Part IV focus on empirical evidence of industrial policies in selected advanced economies. Reinert (Chapter ) reviews historical perspectives on the origins of industrial policy and industrialization, the role of the state and key arguments ranging from before the Industrial Revolution up to the early twentieth century. Best (Chapter ) reviews the success of US industrial policy during the Second World War, and the country’s post-war de-industrialization, arguing that industrial policy has been integral to core production processes and innovation capability. Bianchi and Labory (Chapter ) examine the evolution of post-Second World War European industrial policy through a comparative review of three phases (strong and selective intervention, market-led approaches, and more recently, more interventionist), illustrating how the EU’s multilevel governance adapted to new technological disruptions. Landesmann and Stöllinger (Chapter ) review EU industrial policy, with a focus on contemporary Europe, and examine the key challenges of keeping pace with the frontiers of technology, responding to the fast catching-up by emerging economies, convergence and cohesion within the EU, and the climate challenge. Lee (Chapter ) reviews East Asian experiences with a focus on South Korea’s economic catch-up from the s to the s, showing how industrial policy was used to build innovation capability and upgrade the private sector during the four phases of transformation.

.. Part V: Experiences in Emerging and Developing Countries Part V focuses on industrial policy experiences and outcomes in emerging and developing countries, including South East Asia, post-communist transition economies, Latin America, and Africa. First, Rasiah (Chapter ) reviews industrial policy and industrialization in South East Asia, with a comparative analysis that shows the persistence of premature de-industrialization and the weakness of industrial policies in contrast to those of Japan, South Korea, and Taiwan. Li and Chen (Chapter ) examine the development of national champions as a key element of industrial policy, showing how China transformed and consolidated its big state-owned enterprises into world-class firms. Santiago (Chapter ) reviews industrial policy in the BRICS (Brazil, Russia, India, China, South Africa), exposing the asymmetry of these countries’ economic performances and divergent industrial policies, despite the cooperation between them. Popov (Chapter ) considers the lessons from the evolution of industrialization and industrial policy outcomes among (post-communist) transition economies of Europe and Asia. Ocampo and Porcile (Chapter ) present a comparative review of macroeconomic and industrial policies of Latin American countries and the outcomes in terms

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

, , ,  -

of catch-up and economic transformation. Whitfield and Zalk’s (Chapter ) comparative review of industrial policy in four African countries (Ethiopia, Nigeria, Rwanda, and South Africa) highlights their mixed outcomes and the limited economic development achieved. Chitonge and Lawrence (Chapter ) examine the different phases of industrial policy in post-independence Africa, reviewing the history through the lens of power relations and the state as the focus of political economy.

R Amsden, Alice H. () Asia’s Next Giant: South Korea and Late Industrialization. Oxford University Press on Demand. Amsden, Alice () The Rise of ‘the Rest’: Challenges to the West from Late-industrializing Economies. New York: Oxford University Press. Baldwin, Richard () The Great Convergence: Information Technology and the New Globalization. Cambridge, MA: Harvard University Press. Best, Michael H. () How Growth Really Happens: The Making of Economic Miracles through Production, Governance, and Skills. Princeton, NJ: Princeton University Press. Chang, Ha-Joon () Kicking away the Ladder: Development Strategy in Historical Perspective. London: Anthem Press. Cherif, Reda and Fuad Hasanov () ‘The Return of the Policy That Shall Not Be Named: Principles of Industrial Policy’. International Monetary Fund. Available at https://www.imf. org/en/Publications/WP/Issues////The-Return-of-the-Policy-That-Shall-Not-BeNamed-Principles-of-Industrial-Policy-. Chick, Victoria () ‘Industrial Policy, Then and Now’. Real-world Economics Review : –. Available at http://www.paecon.net/PAEReview/issue/Chick.pdf. Cimoli, Mario, Giovanni Dosi, and Joseph E. Stiglitz (eds) () Industrial Policy and Development: The Political Economy of Capabilities Accumulation. The Initiative for Policy Dialogue Series. Oxford: Oxford University Press. Cramer, Christopher and Fiona Tregenna () ‘Heterodox Approaches to Industrial Policy and Implications for Industrial Parks’, in Justin Yifu Lin and Arkebe Oqubay (eds) The Oxford Handbook of Industrial Hubs and Economic Development. Oxford: Oxford University Press. Cramer, Christopher, Jonathan Di John, and John Sender () ‘Poinsettia Assembly and Selling Emotion: High Value Agricultural Exports in Ethiopia’. AFD Research Papers Series No. –, September. Paris: Agence Française du Développement. Cramer, Christopher, John Sender, and Arkebe Oqubay () African Economic Development: Evidence, Theory, Policy. Oxford: Oxford University Press. Doner, Richard, Bryan Ritchie, and Dan Slater () ‘Systemic Vulnerability and the Origins of Developmental States: Northeast and Southeast Asia in Comparative Perspective’, International Organization (): –. Gereffi, Gary () Global Value Chains and Development: Redefining the Contours of stcentury Capitalism. Cambridge: Cambridge University Press. Grabel, Ilene () ‘The Rebranding of Capital Controls in an Era of Productive Incoherence’, Review of International Political Economy (): –. Haggard, Stephan () Developmental States. Cambridge: Cambridge University Press.

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

Hirschman, Albert O. () The Strategy of Economic Development. New Haven, CT: Yale University Press. Hirschman, Albert O. () Development Projects Observed. Washington, DC: Brookings Institution. Hirschman, Albert O. () ‘The Political Economy of Import-substituting Industrialization in Latin America’, The Quarterly Journal of Economics (): –. IMF () World Economic Outlook: Cyclical Upswing, Structural Change. Washington, DC: IMF. Johnson, Chalmers () MITI and the Japanese Miracle: The Growth of Industrial Policy, –. Stanford, CA: Stanford University Press. Kaldor, Nicolas () Causes of the Slow Rate of Economic Growth of the United Kingdom: An Inaugural Lecture. Cambridge: Cambridge University Press. Lee, Keun () The Art of Economic Catch-up: Barriers, Detours and Leapfrogging in Innovation Systems. Cambridge: Cambridge University Press. Lewis, Michael () The Fifth Risk. New York: W. W. Norton & Company. Lin, Justin Yifu and Ha-Joon Chang () ‘Should Industrial Policy in Developing Countries Conform to Comparative Advantage or Defy It? A Debate between Justin Lin and Ha-Joon Chang’, Development Policy Review, (): –. Marshall, Alfred () Principles of Economics. London: Palgrave Macmillan. Mathews, John () Greening of Capitalism: How Asia Is Driving the Next Great Transformation. Stanford, CA: Stanford University Press. Mazzucato, Mariana () The Entrepreneurial State: Debunking Public vs. Private Sector Myths, Vol. . London: Anthem Press. Mittelman, James H. () Implausible Dream: The World-class University and Repurposing Higher Education. Princeton, NJ: Princeton University Press. Myrdal, Gunnar (). Asian Drama: An Inquiry into the Poverty of Nations. New York: Pantheon. Naudé, Wim () ‘African Countries Can’t Industrialise? Yes, They Can’. The Conversation,  November. Available at https://theconversation.com/african-countries-cant-industrialiseyes-they-can-. Nayyar, Deepak () Asian Transformations: An Inquiry into the Development of Nations. Oxford: Oxford University Press. Nolan, Peter () China and the Global Economy: National Champions, Industrial Policy and the Big Business Revolution. Basingstoke: Palgrave. Oqubay, Arkebe () Made in Africa: Industrial Policy in Ethiopia. New York: Oxford University Press. Oqubay, Arkebe and Kenichi Ohno () How Nations Learn: Technological Learning, Industrial Policy, and Catch-up. New York: Oxford University Press. Prebisch, Raúl () The Economic Development of Latin America and its Principal Problems. New York: UN Department of Economic Affairs. Salazar-Xirinachs, José M., Irmgard Nübler, and Richard Kozul-Wright (eds) () Transforming Economies: Making Industrial Policy Work for Growth, Jobs and Development. ILO/UNCTAD. Schumpeter, Joseph () Theory of Economic Development. Cambridge, MA: Harvard University Press. Thirlwall, Anthony () ‘Thoughts on Balance-of-payments-constrained Growth after  Years’, Review of Keynesian Economics (): –.

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, , ,  -

UNCTAD () Trade and Development Report : Structural Transformation for Sustained and Inclusive Growth. Geneva: UNCTAD. UNCTAD () ‘Beyond Austerity: Towards a Global New Deal’, in Trade and Development Report . Geneva: UNCTAD. UNCTAD () World Investment Report . New York and Geneva: UNCTAD. UNIDO () Structural Change for Inclusive and Sustainable Development. Vienna: UNIDO. Wade, Robert () Governing the Market: Economic Theory and the Role of Government in East Asian Industrialization. Princeton, NJ: Princeton University Press. Whitefoot, Kate and Walter Valdivia () Innovation and Manufacturing Labor: A Valuechain Perspective. Washington, DC: Centre for Technology Innovation, Brookings. World Bank () Trouble in the Making? The Future of Manufacturing-led Development. Washington, DC: World Bank.

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  ......................................................................................................................

                     

.............................................................................................................

 

. I   T  P  I P

.................................................................................................................................. D on industrial policy and scholarly debates echoes global economic shifts, changes in the international power structure, and the ideological fervour of the period. Arguably, many governments have continued to use some form of industrial policy, although it appeared unfashionable in the s‒s with the rise of new liberal waves. Nonetheless, industrial policy has recently attracted growing attention from policymakers and researchers, and is now part of mainstream economic debate. A recent working paper by IMF researchers (Cherif and Hasanov, ) was entitled ‘The Return of the Policy That Shall Not Be Named: Principles of Industrial Policy’. Nonetheless, there is little agreement on the underlying conceptual perspectives and basic essence of industrial policies and empirical interpretation (Andreoni and Chang, ).¹ Pioneering theoretical work on industrial policy, particularly the theory of infant industry protection, is mainly associated with the classical political economy of the early capitalist economy in eighteenth-century England and the economic catch-up of continental Europe, the United States, and Japan in the nineteenth century

¹ According to Weiss (: ) two competing perspectives emerge, namely the ‘promotional’ that focuses on interventionist and leading role of government, and the ‘market-based’ approach which sees government as a facilitator with the role of addressing market failures and the malfunctioning of the market.

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

 

(Hamilton, [] ; List, ).² Industrial policy as a viable path to capitalist development has been practised by both forerunners and latecomers (Chang, ; Reinert, ; Reinert, Gosh, and Kattel, ), with sustained growth and economic transformation associated with industrial policy and the transformation of productive capability.³ However, the experience of industrial policies has been uneven across countries, sectors, and historical periods. Debate on industrial policy has tended to be influenced more by ideological contentions than by empirical evidence and economic history. The recent proliferation of literature brings the divergent underlying perspectives to the fore. From a long-term, strategic perspective, industrial policy underpins structural transformation and catch-up, sustained economic growth, productivity gains, technological advances, and broader socio-economic transformation. The approach taken in this chapter is based on a broader conceptualization of industrial policy incorporating production, international trade, technology, and innovation, rather than a narrower definition confined to government interventions or policy instruments. This means that the purpose and patterns of industrial policy and the perspectives underlying it are of paramount importance (Oqubay, ; Best, ; Andreoni and Chang, ). This chapter reviews the theory and practice of industrial policy and advances three sets of arguments. First, it presents industrial policy as a vehicle of structural transformation and wealth creation, in which manufacturing (and other dynamic, highproductivity, and knowledge-intensive activities) exhibits increasing returns (both static and dynamic) and drives structural change.⁴ It underlines the strategic role of exports, especially as a source of international learning and relaxing balance-ofpayment constraints. Second, it underlines the dynamics of industrial policy as a conduit for technological learning and the development of innovation capability (Best, ; Dosi and Nelson, ).⁵ Finally, it shows that unevenness and adaptability have been key aspects of the practice of industrial policies over the last two centuries, suggesting their continuing relevance for structural change, structural transformation, and catch-up, even in the radically transformed global economic landscape of the twenty-first century, where policy space is more restricted than in the past. The chapter is divided into six sections. Following the introduction, section . draws on classical political economy and structuralist development economics to examine structural transformation as the prime foundation of industrial policy, and reviews related concepts such as the infant industry protection theory. In section . we explore evolving thinking on industrial policy in the twentieth century with a focus on its role in technological learning and economic catch-up. The unprecedented rate of latecomer economy industrialization, together with rapid changes in technology, the

² See Komiya, Okuno, and Suzumura () and Ohno () on Meiji’s restoration and Japanese industrial policy in the nineteenth and twentieth centuries. ³ Reinert, Gosh, and Kattel (). See also Chapter . ⁴ See Mazzucato (). See also Chapter . ⁵ See Chapter .

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      



economic landscape, and firms’ domestic and international competition strategies, has influenced our understanding of industrial policy. Section . reviews the state‒market relationship, and the politics of industrial policy. Section . focuses on principles and practice, including linkage effects and industrial ecosystems. Section . presents a summary of observations and emerging issues in the changing landscape of industrial policy.

. T P  I P

..................................................................................................................................

.. The Concept of Industrial Policy An active industrial policy underpinning structural transformation and catch-up comprises measures to develop productive and technological capabilities and selective interventions to build new industries and activities with dynamic efficiency (UNCTAD-UNIDO, ; Chang, ; Johnson, ; Amsden, ; Wade, ; Oqubay, ).⁶ An industrial policy is ‘a strategy that includes a range of implicit or explicit policy actions and instruments selectively focused on specific industrial sectors and new activities for the purpose of shaping structural change and promoting catchup in line with a broader national vision and development strategy . . . Successful catching up has depended on active industrial policy. What distinguishes industrial policy is its “soul”, that is, the purpose and underlying pattern of industrial policy’ (Oqubay, : , ). This definition emphasizes economic development strategies as the prime point of departure for inducing productive investment and changing the political economy accordingly. This conception assists a long-term policy approach that emphasizes synergies and connections with macroeconomic policies (such as exchange rate regimes, saving and investment rates, financing systems), human capital development policies (including the orientation and quality of tertiary and vocational schools, the links between universities and industry, and the focus on engineering and technology), and the development of physical infrastructure (such as energy and modern transport). It also follows a tradition of strengthening industrial competitiveness and institutions. A key feature of industrial policy is that it constantly adapts to shifts in the international and domestic environment, including constraints posed by international governing institutions such as the WTO.⁷ However, while multilateral trade rules have ⁶ According to Ocampo, dynamic efficiency is the ‘capacity to generate new waves of structural change’ (see Chapter ). See also Ocampo (). ⁷ For example, the outlawing of local content requirements, which have been a staple of industrial policy. LDCs may find smart ways to get around imposed restrictions.

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

 

restricted the policy space of countries, with implications for industrial policymaking, it has been argued that many industrial policy instruments remain available to latecomer countries wishing to pursue an industrialization agenda (UNECA, ). For some countries, including least developed countries (LDCs), multilateral rules either do not apply at all or do so rather leniently. Environmental sustainability and the greening of industrial policy has increasingly gained importance in policy debates in the late twentieth century (Mathews, a, ).⁸ A pragmatic rather than dogmatic, doctrinaire approach to the design and execution of industrial policy is a key requirement. New ideas can be tested, and old policies discarded if the measures deviate from facts on the ground. Successful outcomes imply the substitution of new instruments for failed ones. Policy learning is rooted in learning by doing and learning by experimentation, augmented by the search for new solutions and learning from international experiences (Oqubay and Ohno, ). Pragmatism combined with long-term vision serves as a compass while allowing the trial-and-error approach and has been typical of industrial policy in East Asian economies.⁹ The post Chinese approach to industrial policy and reform has been characterized by pragmatism, learning by doing, and experimentation.¹⁰

.. Structural Transformation and Industrial Policy ... Perspectives on Structural Transformation Economic history shows that growth alone is not sufficient to sustain economic development. Structural change is characterized by sectoral shifts, sustained productivity growth, and technological spillover, accompanied by shifts in demand, occupations, and income levels, as well as institutional and socio-economic changes (Kuznets, ; Ocampo, Rada, and Taylor, ). Structural transformation involves shifts from low- to high-productivity activities and sectors, diversification into new activities and industries, and sector-specific industrial deepening and upgrading. A process of fundamental structural change necessitates the development and expansion of a country’s productive capacity, namely, accumulation of various types of capabilities.¹¹ Nonetheless, technical progress does not necessarily occur uniformly across sectors or during

⁸ See Chapters  and . For example, sustainability and the development of eco-industrial hubs has become a critical aspect of industrial policies. ⁹ See Chapters  and . ¹⁰ Axioms of Deng Xiaoping capture this thinking: ‘It doesn’t matter if a cat is black or white, so long as it catches mice’; ‘Seek truth from facts’; and ‘Crossing the river by feeling the stones’. See also Peerenboom (). ¹¹ According to UNCTAD (), productive capacity is ‘the productive resources, entrepreneurial capabilities and production linkages’ which together enable a country to develop the technological and production capabilities necessary to produce a wide range of goods (UNCTAD, ).

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      



different stages of industrialization (Ocampo, Rada, and Taylor, ; Andreoni and Chang, ).¹² Pasinetti states that structural transformation is not about temporary or short-term changes but rather about fundamental shifts, ‘those changes in the composition that are permanent and irreversible’ (Pasinetti, : ). Structural transformation implies the transformation of production and hence the need for a production-centred framework. Ocampo et al. (: ) highlight ‘the composition of production activities, the associated patterns of specialization in international trade, the technological capabilities of the economy, including the education level of the labour force, the structure of ownership of factors of production, the nature and development of basic state institutions, and the degree of development and constraints under which certain markets operate (the absence of certain segments of the financial market or the presence of a large underemployed labour force)’ (own emphasis). Thinkers and development economists have multiple views on how structural transformation takes shape. The Prebisch‒Singer hypothesis focuses on what prevents structural change in developing countries and leads to strategic implications for how to overcome this obstacle (Prebisch, ). The trade imbalances between developed and developing countries that are inherent in the economic structure and the core‒periphery relationship are articulated in economic dependency theory.¹³ This hypothesis suggests that in the long term the price of primary commodities declines relative to the price of manufactured goods, due to the greater income elasticity of demand observed relative to primary products, and emphasizes the importance of importsubstitution industrialization to kick-start the process of structural change.

... Manufacturing as an Engine of Growth and Structural Change A proposition widely argued by the structuralist perspective but not universally accepted is that the special properties of manufacturing, which are critical for the long-term dynamism of both industrial and broader economic systems, include the ability to generate linkage effects, increasing return to scale and productivity gains both in manufacturing itself and in the broader economy through linkages, technological spillovers, and job creation (both direct and indirect). The relative significance of these special features varies across manufacturing industries and phases of development. Kaldor’s pioneering work on growth laws underlines manufacturing’s special contribution to growth and productivity: The first law is that there exists a strong causal relation between the growth of manufacturing output and the growth of GDP. The second law states that there exists a strong positive causal relation between the growth of manufacturing output and the growth of productivity in manufacturing as a result of static and dynamic returns to scale. This is also known as Verdoorn’s law. The third law ¹² See Chapters  and . ¹³ This view influences economic views promoted by the United Nations Economic Commission for Latin America and the Caribbean (ECLAC) and in Latin American policymaking.

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

  states that there exists a strong positive causal relation between the rates at which the manufacturing sector expands and the growth of productivity outside the manufacturing sector because of diminishing returns in agriculture and many petty service activities which supply labour to the industrial sector. (Thirlwall, : ; own emphasis)

From Kaldor’s perspective, manufacturing is associated with an enormous increase in the ‘technical dynamism’ of the economic system, with the introduction of new knowledge inducing productive investment (Andreoni and Chang, ).¹⁴ This inextricable interaction between technical change and investment impels the accumulation of technology and capital, together with sustained productivity growth and dynamism. Capital intensity and economic viability are, however, determined by the size and nature of demand as well as technological advances. Kaldor highlights how ‘both technology and demand contribute to determining the degree of capital intensity of the economic system as a whole, and both the evolution of technology and the evolution of demand govern its movement through time. But no relevant role on these matters can be attributed to the rate of profit . . . The most important characteristic of capitalist business enterprises is the continuous change and improvement in the methods of production’ (: ). Hence, knowledge intensity and technology remain the key measures of development.¹⁵ As per Young (), manufacturing offers countries the opportunity to capture increasing returns as a result of manufacturing specialization.¹⁶ Historically, manufacturing has been viewed to have stronger elasticity of demand than primary commodities—though this distinction may be changing—and increasing returns to scale (Young, ; Prebisch, ). Pasinetti states that ‘The physical quantity of each commodity to be produced is determined by demand . . . the nature of human needs and preferences gives rise to entirely different compositions of demand, and, therefore, different structures of production and employment, at the various level of real per capita income’ (Pasinetti, : ). Young () highlights that the notion of increasing returns comprises static increasing returns, captured in firms, and dynamic increasing returns, generated in networks or connections of firms and clustering, driving specialization and differentiation. Kaldor () adds an important dimension, namely, the ‘scope for learningby-doing’ at the individual, firm-level, sector-level, and industrial workforce, which is evident in the ‘special properties’ of manufacturing activities. However, it is noteworthy that sectoral classification has evolved to reflect the changing

¹⁴ See Chapter . ¹⁵ Pasinetti underlines that industrial wealth is associated with technical knowledge and capability. In capitalism or industrial society, ‘wealth is not a stock of material goods (which only represent the external expression of it)—it is a stock of technical knowledge . . . today it has become to emulate them and do better’ (Pasinetti, : ). ‘It is only by absorbing technical knowledge that the poor countries will be able permanently to increase their wealth’ (: ). ¹⁶ See Kaldor’s laws as elaborated by Thirlwall () and Mathews (b).

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      



characteristics of production and technology, and the growing heterogeneity in the nature and characteristics of activities within sectors. Moreover, the nature of inter-sectoral linkages is evolving as the boundaries between sectors are changing; examples include the ‘servification’ featured in the linkage between services and manufacturing, and the ‘industrialization of freshness’ that shapes the linkage between agriculture and manufacturing (Cramer and Sender, ).¹⁷ While activities with dynamic efficiency and arguably a sectoral approach are a critical aspect of industrial policy, a systematic survey and analysis is essential to understand the nature of such activities (Cramer and Tregenna, ).¹⁸ These changes, including the blurred boundaries between sectors and the increasing breadth and heterogeneity of production activities, may arguably offer widening scope for industrial policies while calling for industrial policy to be adapted to the new environment.

....    It has been argued that manufacturing industries also complement agriculture and services, and are associated with stronger inter-sectoral forward and backward production linkage effects (see Hirschman, , among others). Historically, early industrialization is accompanied by the transformation of agriculture, both as the initial source of demand and as a provider of food surplus to urban populations.¹⁹ Agricultural productivity is increased through both research and widely applied technological advances, with high-productivity agriculture exhibiting the stronger dynamism of manufacturing. Manufacturing has similarly stimulated the growth of services, with the transfer of activities such as distribution, logistics, and marketing to the service sector and the outsourcing of other activities such as accounting and human resource management (Andreoni and Chang, ). Knowledge intensity in the service sector varies, ranging from the informal sector to high-productivity industries such as ICT and logistics, which are critical for the competitiveness of manufacturing. The potential and market of services is partly shaped by the scale and sophistication level of manufacturing.

... The Strategic Role of Exports There are conflicting views on the role of exports. A market-friendly or neo-liberal view regards opening to international markets and liberalization as a route to international competitiveness.²⁰ The other view argues that what matters is not trade liberalization or ¹⁷ Knowledge and technology intensity are increasing in some high-value activities in primary goods and services such as health care. ¹⁸ See also Chapters  and . ¹⁹ The intersectoral linkages are noticed through technical and mental shifts, as Kaldor highlights that ‘the key to an accelerated growth of the underdeveloped areas of the world lies in bringing about fundamental changes in both the mental outlook and the technical knowledge and skill of their peasant population’ (Kaldor, : ). ²⁰ For instance, see Serra and Stiglitz (). This view is represented in various publications of international financial institutions and proponents of free trade and economic liberalization.

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 

integration with the global market but how each country inserts itself into international trade (Ocampo, Rada, and Taylor, ). Hirschman ([] : ) argues that export is critical for late latecomers because of its implications for economic transformation: First, through exports they would overcome whatever obstacles of market size limit their growth or prevent their establishment. Second, through exports they would loosen the balance-of-payments constraint which may otherwise prevent capacity operation of existing industries as well as establishment of new industries. Finally, by competing in world markets, industries would be forced to attain and maintain high standards of efficiency and product quality and would thereby acquire defence against oligopolistic collusion and decay to which they often succumb in highly protected, small local markets.

Exports and positioning in international trade have been recognized as pivotal for growth, and exports have been associated with structural transformation, especially with industrialization and manufactured exports (Thirlwall, ). Policymakers may pursue a variety of export promotion strategies resulting in different outcomes. However, from a structuralist perspective, there are at least three fundamental reasons why exports play a strategic role in economic growth and structural change. First, exports are sources and propellers of international learning, as positioning in international trade requires competitiveness in terms of quality, delivery time, and cost. Exporters also serve as conduits for indirect exporters and domestic suppliers, and generate spillover effects in local firms through management skills, workforce transfer, and purposeful emulation. Although international learning is the principal gain from exports, knowledge transfer is less mobile than traded goods. Pasinetti highlights that: When firms in one country are challenged by lower priced products from abroad, they will either learn how to cut down costs or close down . . . a widespread failure to realise that the primary source of international gains is not mobility of goods but mobility of knowledge . . . International learning must therefore remain, for any country, the major and primary aim. This principle of economic policy is one of general and unconditional validity . . . it generally comes from its coincidence with the primary aim (learning) of any international policy. (Pasinetti, : , ‒)²¹

Second, exports represent the most sustainable response to the balance-of-payments constraints that can slow down economic growth and impede rapid industrialization, which ultimately slows down the process of fundamental structural change and can trigger macroeconomic crises. An economy that is unable to use exports to generate

²¹ Pasinetti states: ‘The real difficulty is that technological knowledge is far less mobile, or rather . . . far less quickly mobile, than goods, so that—when all possible efforts have been made to improve technical knowledge, and only when all such efforts have been made—a country can obtain further gains by expansion of international trade’ (Pasinetti, : ).

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      



foreign exchange is likely to be dependent on less reliable sources such as overseas aid and external loans.²² Third, where a country has limited capability to add value, exports can stimulate the local economy by creating markets for surplus domestic production as well as natural resources for which there is insufficient demand locally. This underlines the complementarity of export-led industrialization (ELI) and import-substitution industrialization (ISI) strategies. The ELI strategy, carefully synchronized with ISI, has offered an accelerated industrialization path to twentieth-century latecomers such as Japan, the East Asian newly industrializing economies (South Korea, Taiwan, Singapore), and China. In many instances, ISI is the precursor to ELI (Amsden, ).²³ Stiffening international competition and a crowded marketplace have led some observers to predict that ELI will be a difficult strategy to pursue successfully in the twenty-first century (UNCTAD, ).²⁴ However, this makes exports a more relevant and pressing source of learning than ever. Foreign direct investment (FDI), which has shown exponential growth since the s, is arguably associated with export growth and international learning.²⁵ However, the long-term contribution to the host economy is neither automatic nor inherent in FDI. Akyüz (: ‒) asserts that ‘the contribution of FDI to balance of payments and external financial stability, and growth and industrialization is highly contentious . . . none of these are intrinsic qualities of FDI. Rather policy in host countries plays a key role in determining the impacts of FDI in these areas.’ It is worth noting first, that countries like South Korea have placed little reliance on FDI, and second, that new research shows that a huge share of FDI is really ‘phantom’, being merely transfers of profits across countries but within firms. With a deliberate and effective industrial policy in the host economy, FDI can serve as a source of international learning and may have significant spillover effects (technological, management skills, and market capability), especially at earlier stages of industrialization, and these may be more important for economic catch-up than FDI’s contribution to capital formation and balance of payments (Lee, a; Amsden, ; Akyüz, ). However, maximizing the benefits from FDI requires ²² Thirlwall (: ) highlights that the constraint on balance of payments is the prime constraint for sustained growth in an open economy. The balance of payments constrained growth model is ‘the proposition that no country can grow faster than that rate consistent with balance of payments equilibrium on current account, unless it can finance ever-growing deficits, which in general it cannot. There is a limit to the deficit/GDP ratio, and international debt/GDP ratio, beyond which financial markets get nervous.’ ²³ Reinert states that import substitution has preceded exports in England (see Chapters  and ). ²⁴ See UNCTAD (: ‒). ²⁵ Hymer (), in his pioneering work on FDI and the importance of national origin, states that ‘direct investments are the capital movements associated with international operations and firms’ and ‘their nationality is of the utmost importance, for it affects the way they behave, and it affects the treatment they receive’ because of legal aspects of nationality, control of firm operations and taxation, the conversion of profit to the home currency, and a preference for building R&D at home (: , ).

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

 

local absorptive capacity both at the firm level and in the economy as a whole. Some economies, such as China and Singapore, have been more effective than others in their management of FDI. Governments of host economies have used policy innovation and strategies to promote and manage FDI, which reflects specific local conditions. These include careful identification of foreign firm capabilities, targeting specific industries, careful management of know-how transfer channels (such as joint ventures, licensing, management services), and enforcing performance requirements, incentives, and restrictions. Akyüz () states that competition, imitation, demonstration effects, labour turnover, forward and backward linkages, and R&D activities are all drivers of technological spillover.

... Structural Transformation and its Implications for Industrial Policy Perspectives on structural transformation have fundamental implications for the design and practice of industrial policy in three key areas. First, structural transformation reinforces the purpose of industrial policy and the strategic importance of exportled industrialization not only for small economies with a limited domestic market but also for those that enjoy a large domestic market. With manufacturing-led industrialization and exports, critical drivers of sustained growth and economic transformation, productive investment, industrial deepening, and upgrading within specific industries and across industrial sectors become critical. Second, a sectoral approach is essential for targeting industrial sectors and economic activities (products, production processes, technology, linkages) as foundations of industrial policy. Individual economic and industrial activities have different characteristics and growth dynamics. It is important to ensure that industrial sectors and activities are prioritized based on three characteristics: technological intensity and the scope for technological learning; the dynamics of linkage effects (such as forward and backward linkages); and demand elasticity. Third, supporting and nurturing industrial sectors requires appropriately aligned instruments that promote the move towards high-productivity activities and highly productive investments. Matching incentives with performance (Amsden () calls it a ‘reciprocal monitoring system’) is critical for industrial policy and exports are perfectly positioned to apply pressure for learning. Hobday (: ) highlights that ‘exports, whether with TNCs or from local firms, acted as a focusing device for technological learning and investment’. Understanding the structure of the industry is critical for designing industrial policy instruments that can adapt to the changing industrial structure. Firms can promote international learning as well as exploit increasing economies of scale and scope by implementing policies that both support big businesses and foster start-ups. As Hirschman () argues, industrial policy expedites structural change by anticipating developments and patterns, by removing binding constraints, and by championing emerging and new activities.

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      



.. The Infant Industry Theory The three pillars shaping the development and practice of industrial policy are, arguably, the theory of infant industry, the comparative advantage perspective, and the concept of dynamic and interdependent linkage effects (List, ; Hamilton, ; Hirschman, ; Andreoni and Chang, ). The aim of protecting infant industries is to provide time for the learning and accumulation of the experience that will enable them to reach international levels of competitiveness (Pasinetti, : ). The theory of infant industry originates in the classical political economy of the eighteenth century and the pioneering work of List and Hamilton. Alexander Hamilton (‒), the first secretary of the US Treasury, was the architect of US industrial policy who wrote a famous ‘Report on Manufacturers’ in .²⁶ In his comprehensive four-volume National System, Friedrich List (‒), a political economist and forefather of the German historical school of economics, set out an industrial policy that focused on national systems of production capacity, protection of domestic industry, and innovation. The key perspectives in these classical works refute David Ricardo’s notions of free trade and comparative advantage. List (: ) showed that England rose to a leading industrial and military power by adhering to three strategies: ‘First, to prefer constantly the importation of productive power to that of commodities; second, to maintain and carefully protect the development of productive power; third, to import only raw materials and agricultural products, and to export only manufactured articles.’²⁷ The central arguments relating to infant industry theory can be summarized as follows: a) Manufacturing as the key to wealth creation and building economic and military might. The analysis was based on the importance of economic diversification, modernization, and economic returns. Hamilton based his argument on full employment and labour productivity, increased demand and domestic supply of industrial products, and access to a secure domestic market. b) The notion that nations should develop national production systems rather than international or sub-national economies and should focus on production capacity in preference to exchanges and trade. c) The importance of selecting sectors with higher value addition and knowledge intensity, attracting talent, and providing incentives to support selected sectors. d) The necessity of protecting domestic industry until it is able to compete locally and then with advanced economies, the superiority of domestic manufacturing over the import of industrial goods, and the export of manufactured goods as a true indicator of economic power. ²⁶ See also Goodrich () and Cohen and DeLong (). ²⁷ Oqubay (: ) highlights that ‘the theory of infant industry is based on the assumption that the manufacturing sector should play the key role in the economy, and that its promotion requires jumping ahead of comparative advantage, thus necessitating protection of infant industries, the use of industrial policies, and an indispensable role for the state’.

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

 

Two centuries later, the infant industry hypothesis remains part of the debate around industrial policy (Chang, ). This notion is related to the issue of comparative advantage and its strategic implications for industrial policy.²⁸ Historical and empirical evidence shows there are countries that have achieved significant progress in climbing the development ladder by building competitive advantage to sustain catch-up and structural transformation without relying on their latent competitive advantage (Chang, ). This does not imply deviating from the external and internal environment to follow an irrational and unrealistic path. A plausible view is that conforming with and defying comparative advantages are not mutually exclusive, often occurring under the same national strategy but across different sectors and at different stages. Schwartz () argues that advanced economies and newly industrializing economies of the late twentieth century had to rely on both the Ricardian strategy of using latent comparative advantage and the Kaldorian strategy of creating new comparative advantage.²⁹ Oqubay (: ; emphasis added) highlights: An active industrial policy, while initially dependent on and overlapping with a Ricardian strategy (relying on comparative advantage in agricultural exports and low-value light manufacturing), will eventually shift its focus to a more Kaldorian strategy. A Ricardian strategy on its own can neither bring structural change to the economy nor achieve catch-up. Ultimately, it is the Kaldorian strategy (which partly ignores factor disadvantages and advantages, focuses on manufacturing exports, and is investment-driven) that can address the challenges of catch up in terms of investment concentration, learning, and innovation . . . This is what climbing the ladder means.

While it is necessary to fully exploit revealed latent comparative advantage, what matters most for economic catch-up and deepening of structural transformation is the capacity to create and shape comparative advantages. In a nutshell, structural transformation should underpin industrial policy. Nonetheless, this will be incomplete without an equivalent perspective on technological learning and catch-up which has become more marked in the twentieth century—the focus of the discussion in section ..

. E T  I P: T L  C-

.................................................................................................................................. Thinking on industrial policy evolved profoundly in the twentieth century, with an increasing number of latecomers recording accelerated industrialization and developing ²⁸ This is exemplified in Lin and Chang’s debate on the strategy of conformity (comparative advantage defying following, CAF) or defying comparative advantage defying (CAD) (Lin and Chang, ). ²⁹ As coined by Schwartz ().

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      



technological capabilities at an unprecedented rate (see Nayyar, , , among others). Key elements in this evolution are the rapidly changing global economic landscape, the unmatched pace and shift of technological advancements, and how firms and countries compete. This has encouraged empirical research and theoretical work on the uneven development of capitalism, the diversity of development paths and economic catch-up, the process of technological learning, and the centrality of productive and technological capabilities. The proliferation of debate has underpinned an evolving view of industrial policy as the right strategy to ensure technological learning and economic catch-up, which is the focus of this section. The rarity of middle-income countries escaping from the ‘middle-income trap’ has become an additional impetus to the study of the nexus between industrial policy and technological learning and catch-up.

.. Technical Change and Economic Development An evolutionary economics or Schumpeterian evolutionary tradition offers an important view of industrial policy as well as new concepts. Evolutionary theory builds on the centrality of technical change or technological change as the driver of capitalism and stresses the importance of learning and capability development as a key driver of competitiveness of firms (Dosi and Nelson, ; Nelson and Winter, ; Mowery and Rosenberg, ; Rosenberg, ). Classical political economy (Smith, ; Babbage, ; List, ) emphasizes the importance of technological and technical change and domestic technological capability for building an innovation-driven knowledge economy.³⁰ Although technological advancement accelerated in the early days of the first industrial revolution in England, it had already been dependent on science for many centuries, for example in China. Kuznets (: ) states that ‘the epochal innovation that distinguished the modern economic epoch is the intended application of science to problems of economic production’. According to Kaldor, innovation implies the introduction of new knowledge in which the eagerness to absorb technological change and the preparedness to invest in firms are central. Kaldor states that ‘the most important characteristic of capitalist business enterprise is the continuous change and improvement in the methods of production’ (Kaldor, : ). Pasinetti (: ) underscores the centrality of technical progress: ‘it is only by absorbing technical knowledge that the poor countries will be able to permanently increase their wealth.’ Technical change is the process by which new technologies are being constantly introduced into economic activities by incremental improvements and innovation. It usually comes in various forms and is path dependent. Rosenberg (: ) highlights that ‘the growth of technological knowledge is fundamental to the improvement of ³⁰ Marx ([] : ) highlights that ‘modern industry never looks upon and treats the existing form of a process as final’.

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

 

economic performance . . . technological changes are often “path dependent” in the sense that their form or direction tends to be influenced strongly by the particular sequence of earlier events, out of which a new technology has emerged’. The duality of diversity and path dependence is a process imbued with uncertainty.³¹ Kaldor (: ) highlights that technological progress and productivity increase, not in isolation, but alongside the growth of population and accumulation of capital. In his pioneering work on creative destruction, Schumpeter ([] , ) held that industrial capitalism constantly rejuvenates itself in a cycle of technical and economic progress involving heroic entrepreneurs or inventors, imitation by other firms, an investment boom, an ensuing depression, and new ‘innovating’ investment.³² Innovation is both incremental and radical, and includes products, processes, markets, and organizational set-ups that are new to the country or the firm (OECD, ).³³ Thus, innovation is defined as a process by which firms master and implement the design and production of goods and services that are new to them, irrespective of whether they are new to their competitors, their countries, or the world (see, for example, Mytelka and Tesfachew, ; Mytelka, ). Dosi and Nelson (), among others, highlight that tacit knowledge plays an important role in know-how transfer, technology diffusion, and innovation, and is nested in organizations; and also that innovation is not a technical exercise that can be detached from political economy.³⁴ They further emphasize that the focus on capability development is more valuable than financial incentives. Latecomer economies may focus on learning by doing or imitation, incremental innovations, and ultimately new innovations that require domestic R&D capability and the development of science and technology infrastructure (Amsden, ; Kim, ; Kim and Nelson, ). Learning ³¹ Veblen (: ) argues that ‘the prime mover among these factors [population growth, military power, industrial efficiency] of the nation’s unfolding power has been its increased industrial efficiency rather than either the other two factors’. Kim and Nelson (: ) state that ‘technology advance is the key driving force of economic growth’ and ‘technological advance accounted for the lion’s share of growth in worker productivity’. ³² Solow highlights the distinction between incremental and true innovations: ‘Innovation is the discretion or outcome of researches that bring those development changes to the nature of the product or the nature of the production process in existing industries, or may even lead to the creation of recognizably new industries. The less obvious process is usually described as “continuous improvement” of products and processes. It consists of an ongoing series of minor improvements in the design and manufacture of standard products. It leads to advances in customers’ satisfaction, in quality, durability, and reliability, and to continuing reductions in the cost of production.’ ³³ Paus (: ) states that ‘innovation is primarily the result of the incorporation of knowledge developed elsewhere: through the use of licenses, the incorporation of new capital goods, and spillovers from foreign investment in the developing country, if there is domestic absorptive capacity. The next step is an increase in the development of domestic innovation, where firms generate new processes and products that make them internationally competitive.’ The Oslo Manual (OECD, ) states that innovation ‘goes far beyond the confines of research labs to users, suppliers and consumers everywhere—in government, business and non-profit organisations, across borders, across sectors, and across institutions’ and proposes four types of innovation: product innovation, process innovation, marketing innovation, and organizational innovation. ³⁴ In contrast to articulated or explicit knowledge, tacit knowledge is neither codified nor explained.

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and technological catch-up, and building domestic capability, which also includes growing investment in R&D, were all essential components of successful cases of economic catch-up (Cimoli, Dosi, and Stiglitz, ; Lee, a). Absorptive capacity is an important component of innovation and technological capability. Cohen and Levinthal () define absorptive capacity as the ability to identify, assimilate, and apply knowledge; they make a distinction between learning capability and problem-solving capability. They also emphasize the importance of multi-functional teams, diversity of knowledge and experience within firms, and openness to the external environment of buyers, suppliers, and research centres. Contributions on innovation systems by Nelson and Winter () and Kim and Nelson () focus on national innovation systems as a proxy for building absorptive capacity, including the education system, the R&D system, government funding of research, universities, research centres, government agencies, and interactions between these, also captured by Best’s () production-centric ‘capability triad’, namely production systems, business governance, skill formation, and their interconnectedness. Chung and Lee () show the origins of absorptive capacity in latecomer economies such as South Korea. Breschi and Malerba () have emphasized the importance of addressing innovation systems at both national and sectoral levels. The market failure paradigm (derived from the neoclassical view of innovation and capability development) is based on information asymmetry and an assumption that knowledge is freely available to all firms, and ignores the dimension of ‘issues of utilization’ (Rosenberg, ; Mowery and Rosenberg, ).³⁵ The role of the state is confined to facilitation and financial rewards and incentives for innovation. This viewpoint ignores the inescapable truth that firms cannot capture all the benefits and risks of financing innovations, or the lags intrinsic in adopting technology. It views innovation as an exogenous factor, ignoring its multiple sources, complexity, path dependency, and unclear boundaries. It views innovation as dissociated from issues of practical application. Finally, it focuses on incentives rather than firms’ capabilities or innovation systems at both sectoral and national levels.³⁶

.. Theoretical Underpinning of Catch-up and Late Development Unevenness among economies and regions is an essential characteristic of capitalism and industrialization (Gerschenkron, ; Chang, ; Schwartz, ).³⁷ Economic ³⁵ Market fundamentalism advocates a laissez-faire approach and intellectual property protection (reflecting property rights and rewarding innovators), rejecting the role of the state. ³⁶ See Mowery and Rosenberg (), Lee (a), Dosi and Nelson (). ³⁷ It is useful to note that the notion of catch-up and late development is a notion which is old and neoclassical economists may well agree with some of this because of the assumption of diminishing returns and market-facilitated convergence.

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history shows that countries do not have uniform or linear development paths and there is no standard prescription. Late latecomers are compelled to rely on their abundant ‘backward’ resources and pursue a strategy that induces disequilibrium and imbalances (Hirschman, ). Gerschenkron’s (: ) pioneering work on catchup and late development shows that latecomers, despite the disadvantage of being followers, can exploit the advantages of backwardness or late development: ‘the more backward countries are, the great spurt of industrial development occurred despite the lack of these prerequisites . . . [and] the higher the degree of backwardness, the more discontinuous the development is likely to be.’ This hypothesis confirms that catch-up requires a deliberate strategy and policy, and active state intervention. Forerunners provide compelling learning for latecomers, and contact with forerunners is an essential condition for late development. Lee and Malerba () define economic catch-up as narrowing the distance between latecomers and frontrunners or leaders. Abramovitz, writing on catch-up and the advantages of backwardness, reviews three key aspects of the catch-up hypothesis: ) Its prime concern is a single aspect of economic relations among countries: technological borrowing by followers, meaning the level of technology embodied in a country’s capital stock (Abramovitz, : ). ) Being a latecomer carries with it the potential for faster productivity gains: ‘The catch-up hypothesis asserts that being backward in level of productivity carries a potential for rapid advance . . . Followers tend to catch up faster if they are initially more backward . . . Backwardness carries an opportunity for modernization in disembodied as well as embodied technology.’ Abramovitz further states: ‘those who are behind, however, have the potential to make a larger leap. New capital can embody the frontier of knowledge, but the capital it replaced was technologically superannuated’ (Abramovitz, : ). ) However, as the distance between latecomer and frontrunner narrows, productivity gains slow down. Abramovitz (: , ‒) highlights: ‘a follower’s potential for growth weakens as its productivity level converges toward that of the leader’; and ‘countries in the course of catching up, however, exploit the possibility of advance scale dependent technologies by import substitution and expansion of exports’. Learning has become the hallmark of economic catch-up and late development. Amsden () states that ‘diversity notwithstanding, all late industrializers have in common industrialization on the basis of learning, which has conditioned how they have behaved’ (Amsden, ). One stream of research has concentrated on both catch-up strategies and the development of productive and technological capabilities, based on empirical evidence from the late industrializers of the late twentieth century (Amsden, ; Best, ; Lee, , a). Lee’s work on East Asian, especially Korean, economic catch-up shows that it is not automatic and cannot be accomplished merely by imitating forerunners, because forerunners are also constantly advancing and developing higher capabilities. Hence, a different catch-up path is required.

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Different strategies are used for different stages of catch-up. Focus on imitation, learning from forerunners and insertion into the global value chain are essential in early-stage industrialization, but this alone will not enable sustained catch-up. According to Lee (b), latecomers face catch-up paradoxes: each latecomer has to be different, the pace of catch-up has to be faster and requires detour strategies, while leapfrogging requires exceptional innovation and development of R&D capabilities. In the early phases, relying on foreign firms, insertion into global value chains, and excelling in learning by doing and imitation is essential, together with growing investment in human capital, innovation capabilities, and the development of big businesses. In the second stage, where the focus is on adaptive imitation, the latecomer needs to work closely with frontrunner technology, even though this poses a significant threat. Strictly enforced intellectual property and other protections create new difficulties for latecomers seeking to move into innovation leadership. According to Lee (b), latecomers need to focus on leapfrogging in short-cycle industries, gradually moving to long-cycle technologies, and building local value chains into global ones. Recent research has shown that catch-up from middle-income to high-income levels rarely occurs, and a new term, ‘middle-income trap’ (MIT) has been coined. However, while it is true that more and more countries are remaining trapped at middle-income level, the evidence used to explain the notion of the middle-income trap is based on a partial premise.³⁸ The explanation focuses on conditions, rather than dynamic factors such as productive and technological capabilities, which are key drivers of productivity growth.³⁹ A more plausible explanation would be low investment in technological and innovation capability, which becomes more difficult as productivity converges to that of the frontrunners (see Abramovitz, , ; Paus, ; Lee, b). Paus (: ) highlights that ‘Productive transformation from commodity production to higher value added, more knowledge-intensive activities is at the heart of the transition from a middle-income to a high-income economy . . . Productivity growth is the distinguishing characteristic between upper middle-income countries which transitioned to highincome countries and those that did not.’ Similarly, according to Lin, ‘the middleincome trap is a result of a middle-income country’s failure to grow labour productivity through technological innovation and industrial upgrading’ (Lin, ). For UNCTAD, catch-up is dependent on the nature of the industrialization path or trajectory followed,

³⁸ According to the World Bank (), only thirteen of the  middle-income economies in  have escaped the middle-income trap. The methodology and data are flawed as the classification is based on GNI per capita; a static indicator based on a World Bank classification that was introduced in the late s for purposes other than analysing economic catch-up. It can be argued that this threshold for high-income economy is lower than present times warrant (i.e. about US$,). See also Lin and Treichel () and Lin (). ³⁹ The thirteen economies are Equatorial Guinea, Greece, Hong Kong SAR (China), Ireland, Israel, Japan, Mauritius, Portugal, Puerto Rico, the Republic of Korea, Singapore, Spain, and Taiwan, China. Some of these countries have low technological capability and their economy and exports are not based on diversification and technological intensity (for example, exports of crude oil account for  per cent of Equatorial Guinea’s economy).

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which may lead to successful catch-up or getting caught in the low- or middle-level development trap. UNCTAD classifies these stages as catch-up industrialization, stalled industrialization, and premature de-industrialization (UNCTAD, ).⁴⁰

.. Technological Learning and Industrial Policy ... Technological Learning From a catch-up perspective, learning is central in late development. It has two dimensions: technological learning in firms and policy learning by governments.⁴¹ Learning is the prime source of learning and learning is embedded in learning by doing (Oqubay and Ohno, ). Governments and firms learn from other firms or other governments, but also and perhaps more importantly, from themselves. Emulation involves learning from others in the form of copying or imitation, adaptive innovation, or radical or new innovations. Learning requires an open system, interfirm interactions, contact with foreign knowledge, the compulsion and readiness to learn, while depth of learning depends on absorptive capacity. The experience of the East Asian countries shows that they were not only pragmatic, but also strategic in their choices of policies and sectors, and in designing their industrial and international trade policies. Hence, pragmatism is at the heart of industrial policy as policy decisions have to be based on what works or does not, and no policy action is immune from the test of practice. Pragmatism rejects dogmatism or romanticism: it adopts what works and serves the long-term vision and strategy, while constantly adapting to international and domestic reality. The sources and dynamics of learning are diverse and constantly changing. Successful economies such as the East Asian newly industrialized economies have perfected ⁴⁰ See Tregenna (, ) on manufacturing properties and premature de-industrialization. See also UNCTAD (). According to UNCTAD (: ): Catch-up industrialization, with robust growth of production, investment, income, and technological and trade linkages built around a large and increasingly diversified manufacturing sector gives rise to a strong catch-up growth dynamic resulting in narrowing the productivity gap with lead economies. Stalled industrialization is characterized by stagnant shares of industrial output and employment, and sporadic growth episodes that generate linkages that are not large or strong enough for industrial growth to withstand shock and setbacks resulting in continued vulnerability. In general, such a trajectory results in a widening productivity gap with lead economies. Finally, there is premature deindustrialization in which the shares of industrial output and employment fall prematurely, at levels of per capita income much lower than those at which developed economies started to deindustrialize. This is accompanied by delinking along several dimensions and a sharp drop in relative productivity levels. ⁴¹ Arrow (: ) states that learning is ‘the acquisition of knowledge . . . learning is the product of experience. Learning can only take place through the attempt to solve a problem and therefore only takes place during activity.’ Moreover, Arrow emphasizes that a steadily evolving situation acts as stimulus to generate growing productivity.

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their trials and errors, and have strictly adhered to a pragmatic national vision and development strategy.⁴² The driver of technological learning and industrial policy is the synergy between industrialization or productive capacity, exports or market focus, and innovation. Exports provide the broader market opportunity to expand economies of scale and scope, and exploit productivity gains. In addition to their strategic role as a key driver of growth, exports remain a prime disciplining device for firms, promoting international learning, energizing technological learning and innovation, and attesting to their international competitiveness (Amsden, , ; Wade, ).⁴³ Advances in the technological and knowledge frontier are intimately tied to accumulation of capital. Hirschman highlights that ‘the complementary effect of investment is the essential mechanism by which new energies are channelled toward the development process . . . where one disequilibrium calls forth the development mover [which] in turn leads to a similar equilibrium and so on ad infinitum’ (: ). This is in line with the proposition of technological learning as the conduit of structural change and driver of economic catch-up, the foundations of the production-centric paradigm explored by leading thinkers on capability development (Best, , ; Lee, a). Michael Best’s How Growth Really Happens () describes the ‘capability triad’ of production capability, skills, and governance in firms. This perspective integrates the catch-up drive, the active role of the state as organizer of production, the dynamism of firms, and shifting production systems. The development of technological and innovation capabilities underpins the symbiotic and dynamic relationship between technological learning, industrial policy, and catch-up. A coherent and strategic approach to R&D, technology commercialization, support mechanisms, education, and skills targets key dynamic industries (and firms) and new technologies, rewarding learning and providing consistent and comprehensive support.

... Innovation Systems and Infrastructure The structure of innovation systems, and the science and technology infrastructure, are foundations for developing innovation and technological capability. The notion of innovation systems was popularized in the s by Nelson and Winter (), Mowery and Rosenburg (), and Kim and Nelson (), among others. The innovation system framework provides a holistic view of the conditions necessary to create an environment that supports innovative activities by enterprises. In this respect, it describes a nation’s capabilities, encompassing firms, industries, institutional networks, and the interaction among the key players.⁴⁴ National innovation systems (NISs) have become increasingly open with regard to knowledge flows, including ⁴² See also Mathews (b). ⁴³ Hobday (: ) confirms that in East Asia, ‘exports, whether within TNCs or from local firms, acted as a focusing device for technological learning and investment’. ⁴⁴ See also Hall and Soskice () on various national innovation systems that reflect the varieties of capitalism.

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technologies and know-how acquired from abroad through capital and intermediate goods, purchases of patents and licences, technical alliances between firms in different countries, trade in services such as technical consultancies, FDI, and so on. This has enhanced the abilities of local firms to innovate through, for example, learning, linkages, and demonstration effects. With the influence of external actors, the NIS framework is not as closed or ‘rigid’ as it was once perceived. Cohen and Levinthal (: ) highlight that ‘the ability to exploit external knowledge is a critical component of innovative capabilities’.⁴⁵

... Implications for Technological Learning and Industrial Policy This premise has important implications for technological learning and industrial policy. First, while national innovation systems focus on country or economy level, the NIS may be augmented by sectoral innovation systems as key shifts occur in industries. Malerba states that a wider view of industrial sectors that includes related support industries is critical for innovation and technological capabilities, and for ecosystems and cluster dynamics. Breschi and Malerba (: ) suggest ‘some key drivers of agglomeration are sector-specific, leading to distinct patterns of concentration’. This view has implications for the life cycle of industrial hubs, with distinct drivers of processes during the initiation of industrial hubs and their maintenance. Second, technological learning is associated with the evolving institutional structures of research systems. With the increasing role of big businesses in the twentieth and twenty-first centuries in the United States, Western Europe, Japan, the East Asian economies and China, national economies have single-mindedly pursued the development of national champions, for example, in South Korea and China (Lee, a; Nolan, ).⁴⁶ While the role of big business is critical for the exploitation of the global market, its increasing investment in R&D is also important and should be matched with support of new technology start-ups and spin-outs to continuously reinvigorate innovation.⁴⁷ It is through new start-ups, especially in the technology sphere, that the economy continuously renews and upgrades.

⁴⁵ Cohen and Levinthal associate absorptive capacity as like ‘creative capacity’ in the field of psychology. They emphasize the critical role of learning intensity, diverse background, knowledge diversity, and openness to external environment are critical for facilitating innovation capability. ‘Learning is cumulative, and learning performance is greatest when the object of learning is related to what is already known . . . Learning capabilities involve the development of the capacity to assimilate existing knowledge, while problem-solving skills represent a capacity to create new knowledge’ (: ). ⁴⁶ See Chandler (). See also Chapters  and . ⁴⁷ A policy choice of industrial policy is related to the focus on large firms in contrast to small and medium firms. Large firms are important for developing technological capability and engaging in international markets, while small and medium firms play an indispensable role in employment creation and in production networks with large firms. Germany and Japan are examples where such production networks are widely used and have contributed to international competitiveness.

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Third, collaboration among the key economic players (or actors) is critical for building and developing a dynamic innovation system. The roles of industrial firms, the academic community, and government-funded independent research centres (as well as some private ones), as well as the orientation and focus of higher education and industry‒university linkages, are critical elements of the science and technology infrastructure. The development of innovation and technological capabilities should not be separated from the development of production capacity and market promotion. Although policy innovations vary across countries and times, they enhance coordination among lead agencies and strengthen strategic development. Fourth, the ‘middle-income trap’ can be associated with inadequate investment in new innovations and technologies. Resource allocation is a proxy to measure the focus on innovation and should be reviewed with related issues, such as the contribution of firms, universities, and research centres. Finally, the distinction between innovative activities and the nature of innovation has significant implications for policy approaches.⁴⁸ At early stages of industrialization, copying, imitation, FDI, and global value chains may be used as prime sources of learning. However, economies increasingly need to develop their own capabilities, and add incremental innovation by moving to ‘adaptive imitation’ (a term coined by Linsu Kim, meaning internalization of knowledge and technology). Ultimately economies have to focus on new industries and technologies (‘leapfrogging’, as Keun Lee terms it) primarily by building on growing investment in innovation and production capability. The mechanisms and instruments vary depending on the context (industry, technology, external environment) and require thoroughly thought-out policy design. For instance, reverse engineering, licensing, insertion into GVCs, attraction of FDI, and sub-contracting are common during the early and middle stages of industrialization. Technological institutes, the targeted circulation of talent, and overseas training and education apply in the middle stages of industrialization. Ultimately, a focus on domestic capability and the promotion of big business, leapfrogging to new industries and technologies with a focus on short-cycle industries, massive investment in R&D, and the acquisition of foreign firms are critical for building an innovation-driven economy.⁴⁹ In the electronics and semiconductor industries, local firms have been used as original equipment manufacturer (OEM) during initial industrialization, upgrading to own design and manufacturer (ODM), and subsequently own brand manufacturer (OBM). This approach will, however, differ across sectors.⁵⁰ A commitment to structural transformation and developing technological capability requires the support and intervention of the state, a creative state–market interaction, and has to be embedded in political economy. This is discussed in section ..

⁴⁸ See Atkinson and Ezel (). ⁴⁹ For a thorough review on economic catch-up and leapfrogging strategies, see The Art of Economic Catch-up (Lee, b). ⁵⁰ See Amsden and Chu () on Taiwan’s industrial upgrading.

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. T S   P  I P

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.. The Dynamics of the State‒Market Mechanism The existence of self-regulating markets is a common myth; in reality the internal workings and consequences of capitalism cannot function without state intervention. Polanyi (: xxvi) highlights that ‘the idea of a self-adjusting market implied a stark utopia. Such an institution could not exist for any length of time without annihilating the human and natural substance of society . . . Real market societies need the state to play an active role in managing markets, and that role requires political decision making; it cannot be reduced to some kind of technical or administrative function.’ This perspective has significant implication for the nature of industrial policy (Mazzucato, ; Wade, ; Amsden, ). State‒market forces are in constant tension in various sectors, economic activities, and at different times, and a perfect match is always difficult to achieve. There are three variants on the state‒market mechanism relationship. The first is market fundamentalism which rejects government intervention as harmful. It advocates that governments should restrain themselves from intervening in the functioning of the market with the rational reallocation of resources. The neo-liberal Washington Consensus, orchestrated by IFIs and mainstream scholars, typified this laissez-faire (‘leave it to the market’) view, advocating the dismantling of state apparatus, privatization, and the opening up of markets. This view idolizes the free-market economy and rejects the need for industrial policy. A second variant is the market failure view, which argues that market mechanisms and the market economy do not function optimally in all times and conditions. This view accepts that the government should intervene selectively to stabilize the macro economy, for example, where there is market failure, such as infrastructure development, or development of human capital. The point of market failure policy recommendations is that they are designed to replicate how a perfectly competitive market would look. The state is confined to a ‘facilitative’ role, its interventions ‘qualified’, and is constrained to follow latent comparative advantage as this does not imply strategic intervention. This view has gained widespread influence in mainstream economics and has become dominant within neoclassical economics. A third variant is the state activism perspective that believes market mechanisms are institutions that need to be nurtured, and advocates that the state should intervene to enhance structural transformation and technological catch-up, playing a leading role as organizer of production, with the aim of promoting a dynamic private sector (Best, ; Lee and Malerba, ; Wade, ; Amsden, ). This view recognizes that capitalism involves economic players, primarily the state, firms, labour, families, and non-government players, and sees capitalism as a mixed economy where markets and

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

non-market forces function. The activist state intervenes beyond market failure to shape and create market forces, with strategic interventions to develop competitive advantage, and works hand in hand with the private sector. Mazzucato (: ) highlights that ‘When not taking a leading role, the State becomes a poor imitator of private-sector behaviours, rather than a real alternative. It is a key partner of the private sector—and often a more daring one, willing to take risks that business won’t.’ The purpose and modality of interventions are crucial, as Johnson (: ) highlights: ‘the issue is not one of state intervention in the economy . . . all states intervene in their economies for various reasons . . . the question is how the government intervenes and for what purpose’. The state activism view is supported by both economic history and deductive observations. Such governments are known variously as ‘activist’, ‘entrepreneurial’, and ‘developmental’ states. The term ‘developmental’ tends to be used as a neat and rigid characterization of a government. The purpose of a developmental state, however, changes during different stages of industrialization and economic catch-up, and across sectors. Existing literature on the developmental state takes two views: the static and the dynamic. Some scholarly works have seen the role of industrial policies as dependent on the quality of bureaucracy to the extent of being dissociated from politics. Another variant views developmental states as ‘pure prototypes’ detached from the international and national context where they function. A more dynamic perspective is to link developmental states with the deliberate pursuit of developmental goals, a grand vision interacting with society, in which the nature of the state constantly evolves on the predatory‒developmental state continuum (Chang, ; Oqubay, ; Thurbon and Weiss, ).⁵¹ It should be noted that there is a broader issue here. Not just that the very idea of a developmental state is usually ahistorical, but that industrial policy does not exist within an institutional and political vacuum. The policies that have ‘worked’ in one place may fail in other places, and this may be because of the political and institutional context (Haggard, ; Thurbon and Weiss, ). Schwartz () argues for the essential role of the state in latecomers or latelatecomers.

.. Politics and Political Economy While it is widely recognized that politics and political economy matters for economic policies, the various schools have divergent views. The Marxist view revolves around class struggle and exploitation, while market-friendly views (based on methodological individualism and rational choice theory) focus on profit maximization, ensuring market property rights and reducing transaction costs, and on abstract notions of good governance and institutions. A plausible analytical framework is offered in the ⁵¹ See also Evans (), Woo-Cummings (), and Wade ().

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developmental state literature (which focuses on ideological commitment and the nature of the ruling elite) and the political settlement framework, sharing common features such as the balance of power among elites, the features of institutions, and prevailing ideas.⁵² In the important, broader political and political economy dimension of industrial policy, power relations, and political variables shape the nature and outcomes of policies (Hall, ). Industrial policy shapes market structure and the nature and direction of private-sector growth. If industrial policy is focused on the transformation of production and positioning in international trade, it is more likely that privatesector manufacturing, exports, and technological advancement will grow and have greater political influence, which inversely affects economic policies. The development of production capabilities may slow down in situations where industrial policy is oriented towards extractive industries or the finance sector. The politics and political economy of industrial policy is a key variable shaping its design, execution, and outcomes at both sectoral and national level. Hence, understanding the internal and external political constraints is essential for the success of industrial policies. All economic policies affect the existing political economy, and industrial policymaking is in its turn shaped by politics. Hall (: i, ) highlights that ‘economic policymaking must be understood as an essentially political process . . . a process deeply conditioned by broader struggles between competing parties, ideologies, and social classes’. He adds that ‘economic policy is made by governments, and governments are political creatures’. Even when a consensus is less likely among key interest groups and political forces, they at least need to accept decisions even if they can’t shape them directly. The cohesion and historical intellectual formation and shared experiences of the political elite have a significant bearing on the functioning of government and the policymaking process, which has to be managed by the government through structures coordinated along horizontal and vertical divisions of power. An agreement among the ruling elites and key influencers is necessary to hold and impose power to pursue industrial policy as consensus on values and grand projects may not necessarily be achieved but it acts as a glue enabling the pursuit of industrial policies.

.. Disciplining the Private Sector and Reciprocity All economic policies, including industrial policy, are the outcome of power relations, and each policy generates losers and winners (Hirschman, , ). The stark contrast between the success of industrial policy in East Asia and weak performance in Latin America and Africa has been associated with the political economy variable

⁵² See Khan (), Amsden (), and Gray ().

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and state capacity (see, e.g. Kohli, ; Chang, ; Khan and Blankenburg, ). This is also true at the international level, where positions on environmental sustainability and climate change exemplify the political constraint, power relations, and interest groups. The constraints on policy space and the international governance system reflect political and power relations globally. A key aspect of the interaction of politics and political economy with industrial policy is disciplining the private sector; the provision of productive rent or incentives to shape its behaviour and promote learning is critical for the success of industrial policies. This is a critical political economy dimension. Incentives, to be productive, have to be carefully designed and adjusted to have a positive impact. However, the ability of the government to apply specific types of incentives depends on the political constraint of the state. Khan and Blankenburg (: ) highlight that ‘managing rents for technology acquisition is not just constrained by state capacities, but also and often primarily by political constraints that prevent specific strategies of rent management from being implemented . . . From a policy perspective, potentially growth-enhancing rents can become growth reducing if the rentmanagement capacities of the state are missing.’ Political ability has a direct and indirect bearing on the allocation of ‘development rents’ and this differs across sectors, different stages of development, and countries. Institutional strength, i.e. the capacity to design and administer rents, is also another dimension that is political. Hence, political considerations and understanding the political context of each sector is essential. The dynamism of economic players is a major variable that has an important impact on policymaking. The design of incentive structures and support schemes requires an understanding of reciprocity and the dynamics of sectors. Moreover, linking incentives with performance helps strengthen developmentalism and productive contribution. Inducements such as linkages and latitude for performance will also help to leverage activities in line with the desired political-economy and development outcomes. History and path dependency play an important role in shaping political economy and industrial policy. Land reform in East Asia significantly changed the political economy, making it conducive to export-led industrialization, while in Latin America it constrained the political economy (Kay, ; Ocampo, ; see Chapter ). Internal and external threats, diverse legacies of colonial rule, and cultural traditions also shape the political economy (Doner, Ritchie, and Slater, ).

.. Conflict and Political Stability Politics and political economy are significant because policies (like all economic policies) have conflicting distributional effects across sectors and regions (Hirschman, ). The rules of capitalism include conflict, and the outcomes of industrial policies produce winners and losers. Conflicts occur with considerable frequency, in a variety of forms,

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and navigating through them calls for constant compromise and bargaining, a process which society learns to manage. Hirschman (: ‒) states: Conflict is indeed a characteristic of pluralist market society that has come to the fore with remarkable persistence . . . many conflicts of market economy are over the distribution of the social product among different classes, sectors, or regions . . . all it can aspire to accomplish is to ‘muddle through’ from one conflict to the next.

Polanyi () and Hirschman argue that economic transformation and technical changes constantly generate new conflicts and social configurations across sectors or regions because of newly emerging inequalities. Such conflicts may involve sectors and regions as some decline and some rise. From this perspective, political stability is a much more complex issue than usually presented in ‘business climate’ literature. It could be argued that while efforts may be made to improve business climate and with it political stability and security, it is important to recognize the complexity and limitations of this approach. Even if political stability is secured, a focus on productive transformation and developing technological capability is what ultimately matters. Political stability and security, a critical and related issue, is the minimum but insufficient condition for economic growth and industrial policies. This is particularly important for long-term investments, productive FDI, and the attraction of talent. However, while this may be the case in most instances, many industrial policies and periods of economic growth and technical change have thrived amidst horrible instability and warfare.

.. Myths Surrounding Industrial Policy Myths around industrial policy arguably reflect the underlying political and ideological views of the role of the state in industrial policy. The most common misconception around industrial policy equates it with merely ‘picking winners’ rather than considering its wider perspectives. Another myth is the ideologically driven dichotomy between the role of the state and market forces. There has never been a market reality that has not been shaped by state intervention, although the type and nature of interventions differ. Economic history and empirical evidence point to the state’s role in promoting industrialization and structural transformation. Industrial policy is wrongly equated with state intervention, while the dominance of the state in a command economy does not necessarily guarantee an activist industrial policy aiming to build a dynamic private sector. There is often a dichotomy between export-led and import-substitution industrialization. In reality, however, they are complementary and industrial policy is not about ISI per se, as some scholars suggest. Similarly, FDI firms are seen as an enclave focused only on their own outcomes, while experience shows that FDI could be directed to support the development of domestic firms. Another myth confuses instruments with the nature of industrial policy. As this chapter has shown, a vigorous industrial policy is

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based on structural transformation and economic catch-up perspectives, the recognition of a dynamic view that emphasizes long-termism, synergy and connectivity, and constant adaptation to the changing external and domestic environment and the shifting dynamics of industrial policy. Wade () articulates clearly the reasons for the failure of neoclassical and neoliberal economists to design and apply industrial policies promoting structural transformation and catch-up. He writes: Neoclassical economics is a misleading guide to development policy. It thinks in terms of curves, not step changes. And it makes no distinction between activities (or sectors) according to their growth potential—it treats each unit of GDP as having equal potential for future growth. Yet the governments of virtually all the successful catch-up countries recognized that they had to nurture ‘superior’ or ‘star’ economic activities by means of trade protection, subsidies, and regulations, buffering them from—but not insulating them from—competitive pressures. (Wade, : )

Industrial policy is as essential for the pursuit of structural transformation and economic catch-up in the twenty-first century as it was in earlier centuries. Economic history and empirical evidence from advanced, emerging, and developing economies alike illustrate this reality. Industrial policies, like all economic policies, are influenced by experience; learning and building experiences is critical to their success. Furthermore, industrial policy is inseparable from politics and the political economy and forms an integral part of broader economic and social transformation. Learning from international and local experience needs to be supported by research that vigorously seeks to build knowledge on the subject, helping to constantly adapt industrial policy based on both lessons and the changing external environment and domestic reality. It is hoped that this Handbook will motivate researchers to undertake new studies to help policymakers and practitioners produce creative policies.

. T P  I P: D, A,  P

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A broad and comprehensive understanding of industrial policy has to be tied to structural transformation and to notions such as protection of infant industry and the state‒market mechanism. Industrial policies, far from being empty declarations and plans, underlying purposes and patterns, consist variously of structural change, employment, nationalism, or defence. Most industrial policies are designed and executed at a national level, though there are also regional levels (such as the European Union), and sub-national or provincial levels.⁵³ Instruments of industrial policy may ⁵³ See Chapters  and .

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vary and can involve mid- to long-term plans (five years and beyond), target setting and performance reviews, associated legislation (proclamations, bills, regulations), specific policies, executive decisions and directives, support institutions, and the organization of government‒private sector dialogue. This section reviews the principles and features of successful industrial policies, with structural transformation and technological catch-up as key frameworks. It also highlights the linkage dynamics, ecosystems, and the politics and principles of industrial policy that are needed to produce stronger dynamism, coherence, synergy, and complementarity.

.. Linkage Dynamics and Interdependence The pioneering work on linkage effects as a prime tool of industrialization was by Hirschman. Hirschman ([: ] ) states that linkage is a conceptual tool that assists in ‘detecting how one thing [activity] leads or fails to lead to another’, and is ‘a more or less compelling sequence of investment decisions occurring in the course of industrialization and, more generally, of economic development’ (Hirschman, [: ] ). The linkage effect is relevant for the selection and support of priority sectors likely to have the strongest or most lasting effect in accelerating structural change. According to Oqubay, ‘understanding the industrial structure of different sectors, and leveraging latitudes for performance are valuable in industrial policymaking. Hirschman’s linkage concept (the favouring of industries with strong linkages . . . ) is essential in bringing dynamics and impetus to new activities and increasing returns and in creating economic space in developing economies’ (Oqubay, : ; own emphasis). Hirschman () argued—though this was not widely accepted—that the key constraint in developing countries is not scarcity of resources as such but the inability to make decisions that promote investment and induce productive activities. Thus, for latecomer countries, the correct identification of linkage effects, the direction of the linkages and the various forms of linkages, and changing dynamics are important for industrial policy. Latitude for performance is an associated concept that helps to identify and exploit the internal dynamics (especially the technological and economic characteristics) present in the industrial structures of sectors, projects, and productive activities.⁵⁴ While linkage effect is central to the selection of sectors, it is essential that technical change or the potential for technological advancement and demand formation and elasticity are also considered. Ocampo, Rada, and Taylor () underline the importance of focusing on ‘innovative activities that generate domestic spill over’ in new industries, new products, new markets, new linkages, and new institutions.⁵⁵ ⁵⁴ See Hirschman () on latitude for performance. ⁵⁵ Oqubay underlines how ‘understanding the industrial structure of different sectors and leveraging latitudes for performance are valuable in industrial policymaking. Hirschman’s linkage concept (the favouring of industries with strong linkages . . . ) is essential in bringing dynamics and impetus to new

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From a linkage effects perspective, the prime focus is inducing investment for development, and promoting interdependencies and complementarities. There are three principal issues. First, the relationship between export-led and importsubstitution industrialization leads strategic choices and patterns of industrial policies. The increased density of players in the international market should not lead countries to discount the primary role of exports and abandon export-led industrialization. From a production-centric perspective, relying on exports to spearhead the industrialization drive generates more dynamism, with growth in productivity gains, larger market size and demand, and a source of international learning; by generating foreign exchange it also resolves the constraints hampering the growth of the economy.⁵⁶ While competition is naturally strongest in international markets, this choice is a prime guarantee of sustained growth and international competitiveness.⁵⁷ Complementarity is heightened by ensuring that the export sector leads all other sectors, including those in the domestic markets, and that domestic rivalries are fostered. A second interdependent and complementary relationship is that between manufacturing and agriculture, especially for late latecomers in the early stages of development. The alternatives of manufacturing and agriculture are usually regarded as mutually exclusive, but a plausible option is to search for an approach that maximizes their synergy and complementarity. All developing countries need to focus on boosting agriculture for their initial economic take-off, laying the foundations for accelerated industrialization. Kaldor highlights that ‘any relative growth of industry in an economy presupposes a corresponding growth in the excess of agricultural production . . . it is not an accident that all countries which succeeded in developing manufacturing industry on a large scale possess a highly efficient or largely “commercialized” agriculture, with high yields per acre and high productivity per man’ (Kaldor, : ). Kaldor thus argued that agriculture generates the initial demand for the manufacturing sector in the early stages of industrialization, before penetration of the international market. However, this may not be the case in all countries; the focus may be on meeting the demands of other priorities and on manufactured imports. It is important that the technologically intensive, high-productivity agricultural sub-sectors with stronger linkage dynamics should qualify as targeted sub-sectors. Research and study, supported by experiments and learning from experience and innovation elsewhere, should determine complementarities. Technological advances (in biotechnology, digitization, economics of freshness, and automation) are shaping and reshaping agricultural practices as we know them.⁵⁸ activities and increasing returns and in creating economic space in developing economies’ (Oqubay, : , own emphasis). ⁵⁶ See Drucker () on Germany’s industrial competitiveness in machinery and industrial goods exports. ⁵⁷ In a highly open economy, it is possible that the open domestic market can be as competitive as international markets. Thus, competition is naturally strangest in international markets if the domestic market is totally or partially protected. ⁵⁸ See Cramer and Sender ().

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A third important aspect of industrial policy is the relationship between FDI and domestic firms, a challenging balance that is often affected by political tension. Policy choices depend on the international environment, a dynamic domestic private sector, the nature of the specific industry, and the stage of industrialization. For instance, in the highly globalized production network, the role of FDI as a source of productive investment has increased immensely. However, building an innovation-driven economy requires a shift from imitation to innovation, which is driven by domestic capability. Different countries, for instance Japan, South Korea, Singapore, and Taiwan, China, have followed different paths, according to their technological capabilities and industrial structure.

.. Industrial Ecosystem and Cluster Dynamics Agglomeration economies and cluster dynamics foster specialization and division of labour, increasing returns and productivity gains, innovation and learning, and linkages, acting as critical drivers of positive externalities. Internal economy of scale applies to firms, while external economy of scale applies to agglomeration within the same industry and across industries (these are termed respectively localized and urbanization agglomeration).⁵⁹ Positive externalities are also associated with productive cities that are centres of new ideas and learning (Jacobs, , ). While the organic formation and evolution of industrial hubs is universal, the deliberate development of industrial hubs that offer a learning ecosystem and facilitate linkages is a post-Second World War phenomenon.⁶⁰ Developing dynamic industrial hubs that move beyond static benefits to become dynamic and organic evolving entities needs to be an integral part of the industrial policy framework (Best, ). Breschi and Malerba suggest that ‘clusters should not be examined only as a static framework and at a given point in time. Rather, clusters have specific stages of development and transformation’ (Breschi and Malerba, : ).⁶¹ The dynamics of these industrial hubs are shaped by a culture of learning and openness, and open systems involving a network of institutions such as universities, research centres, government bodies, standards authorities, and intermediary institutions. Empirical evidence shows that the cluster dynamics of industrial hubs promote learning and innovation, linkages, productivity gains, increasing returns to scale, and ⁵⁹ See Smith (), Babbage (), Marshall (), and Ohlin (), among others. For a comprehensive understanding of theories, context, and empirical perspectives, see The Oxford Handbook of Industrial Hubs and Economic Development (Oqubay and Lin, ). ⁶⁰ See UNCTAD (), which states there are more than , industrial hubs (special economic zones, export-processing zones, industrial parks, and technology parks) globally, the lion’s share of these are in Asia. ⁶¹ See Breschi and Malerba () and Best ().

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especially, technological and innovation capabilities. If built on an open culture, they will promote knowledge exchanges and combine collective efficiency, cooperation, and competition.⁶² Effective policies for cluster development include talent attraction and brain gain, a network of organizations, the attraction of new start-ups and enhanced spin-outs.⁶³ Different strategies are required during the initial stage and the growth and maturity stages.⁶⁴ Best (: ) highlights that: A static industrial district lacks the internal/external growth dynamic. Such districts can enjoy Marshall’s locational economies, but they do so within an unchanging ‘production chain’. Dynamic districts, in contrast, are continuously upgrading, redefining, and reconstituting the production chain. Most of the world’s industry is conducted within static industrial districts that lack entrepreneurial firms. Capabilities are not advancing and innovation is limited. They do not drive growth.⁶⁵

.. Tensions in Industrial Policy Different contexts (national or sectoral, or different stages) call for various industrial policy instruments to serve different goals and strategies. Despite their varied content, inherent tensions are evident during the design and execution stage which impact on the outcome of industrial policy. These tensions are exhibited in multiple ways.

... Strategic Compatibility and Coherence The overarching principle in the design and application of industrial policy is to choose instruments that serve the country’s grand vision, purpose, goals, and development strategy. Key to this decision is the targeting of priority sectors and new productive

⁶² See Oqubay and Lin, The Oxford Handbook of Industrial Hubs and Economic Development (). See also Marshall (); Jacobs (, ); Porter () among others. ⁶³ Babbage (: ): ‘It is found in every country, that the situation of large manufacturing establishments is confined to particular districts.’ Marshall (: ) states: ‘The mysteries of the trade become no mystery . . . good work is rightly appreciated, inventions and improvements in machinery, in processes and the general organization of business have their merits promptly discussed: If one man starts a new idea, it is taken up by others and combined with suggestions of their own; and thus it becomes a source of further new ideas.’ ⁶⁴ Breschi and Malerba (: –) highlight that ‘starting a cluster and sustaining clusters are different in processes and economies: a) availability of technical and managerial skills, exploiting technological and market opportunities, availability of government agencies and research institutions, importing intellectual, organizational, technical inputs from outside the local area’. They emphasize the importance of external linkages: ‘In particular, external linkages are vital in order to establish and maintain a dense local network of relationships, for both emerging and established clusters’ (Breschi and Malerba, : ). ⁶⁵ See also UNCTAD (: ): ‘Agglomeration and clustering facilitates economic benefit from GVC participation’, generating collective efficiency from geographical proximity, facilitating learning and business interaction.

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activities. Another aspect is engaging firms and dynamic social groups that have a high stake in the desired outcomes. Focus on the development of productive capacity, technological and domestic capability, and learning is critical to ensure that industrial policy serves as a conduit of transformation and catch-up. However, ensuring compatibility between the industrial goals, and picking and nurturing winners, or even establishing state-owned enterprises and transfers to the private sector, are in constant tension. Dynamic shifts in productivity require both learning by doing and ‘true’ innovations, which as key drivers of technological learning are highly complementary. Solow underlines that: Learning by doing would soon exhaust itself were it not for the intermittent occurrence of major innovations . . . The overall productivity trend will represent both true innovation and learning by doing. Innovations will bulk larger the faster they come and the larger they are. Learning by doing will bulk larger the more rapid the pace of investment and the greater the intensity of learning. (Solow, : , )

In the long term, what matters is not the design and content of a single instrument. In almost all situations, multiple instruments are needed for full and sustained impact, so coherence between them as well as between short-term and long-term directions is critical to achieving maximum benefits. However, coherence is not automatic and must be achieved through appropriate planning and design. Aligning plans to policy decisions, proclamations, regulations, and other executive directives and implementing institutions is a difficult exercise and is full of tensions. A major constraint on policy outcomes is inconsistency of policy execution, which can limit both effectiveness and learning opportunities. Inconsistencies across firms, time, regions, and sectors creates frustration and undermines effectiveness. Gaps should therefore be consistently identified to improve policy implementation. Enhancing coherence and consistency can be targeted during the design, execution, and review stages of the policy. Independent studies, continuous research, and curiosity are important for continuous improvement. However, one of the pitfalls is that many policymakers and practitioners perceive instruments as static.

... Synergy and Connections to Other Policies As we have seen, industrial policy clearly does not exist in a vacuum; it is related to other economic policies and the general political economy. Industrial policies will only have a partial effect and indeed are likely to fail in the long term if complementarity is not maximized. Of particular importance are policies that impact the transformation of productive capacity, export and domestic capacity, and the development of technological capability, and those associated with building human capital and the education system, the development of physical infrastructure, and ensuring macroeconomic stability.

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

Human capital and education have a direct bearing on the vigour and outcome of industrial policy. Empirical evidence and research show that education is a necessary condition for structural transformation and industrial catch-up. Its importance increases as the economy progresses towards the advanced stage when technological capability and innovation become more critical. However, experience elsewhere shows that education alone does not necessarily guarantee a breakthrough in the economic catch-up of late industrializers. At an early stage of development, access to general education is important to promote agriculture and shared growth. However, as industrialization advances, technical schools, technical and vocational education centres, and universities become more important. Skills formation, and engineering- and technology-driven courses become higher priorities. In an innovation-driven economy, links between research centres, universities, and industry become important. Education should focus not only on producing high-quality technicians and technologists, but also on nurturing the talent that will be needed for innovation. The tension inherent in this connection is exacerbated by the number of players—multiple organizations, political interests, and interest groups. Another critical policy dimension that has a direct bearing on the outcomes of industrial policies is the development of physical infrastructure. Infrastructure, including reliable and competitive energy and electricity supplies, transport and logistics, is the most important factor in the production process and in downstream and upstream activities, and it is relevant to both quality and cost competitiveness. Infrastructure requirements change during the different stages of development. At an early stage, road connectivity (especially rural and regional) and universal access to electricity, water, and telecommunications will be mandatory. At a later stage, high-speed road networks and high-productivity infrastructure such as large power supply, railways, and airports become necessary. Infrastructure development is capital intensive and requires not only long-term planning but also economic viability and full utilization, building international competitiveness and capacity in managing and maintaining infrastructure facilities. Equally important for the attraction of investment, performance, and viability of exports, labour costs, and productivity, is the presence of a stable and conducive macro economy, including favourable interest rates and sound monetary and fiscal policies. The connection of industrial policy and macro-policies is essential as macropolicies should be conducive to industrial policy and support the production-centric pathway and the production transformation. This implies arguably not only creating macroeconomic stability but also developing support for the production transformation in terms of exchange rates, taxation, fiscal policy, public investment, labour market institutions, and income distribution (Cimoli, Dosi, and Stiglitz, ). Imbalances and tensions are the basic feature of this relationship and the aim should not be to create harmony but to use the imbalances and tension to promote enduring economic transformation. Macroeconomic policy decisions should also aim to maximize synergy with industrial policy, ensuring that exchange rates do not undermine exports, that domestic savings and investment are conducive to the expansion of

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

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production capability, inflation is controlled so that wages are not undermined, and that the tax regime is directly linked to supporting production capability and innovation.⁶⁶

... Competitiveness and Discipline A vital principle of industrial policy is the support offered to industries and firms, and an incentive structure linked to performance standards and enhancing productivity, exports, learning, and innovation. One of the most important lessons from the East Asian experiences was the linking of incentives and support to performance and the control of hand-outs and unproductive rent. Amsden highlights that ‘the guiding principle of the best bureaucracies—politics permitting—was to give nothing away for free. Reciprocity was ideal . . . The reciprocity principle in Korea operated in almost every industry’ Amsden (: , ).⁶⁷ Outcomes are far from automatic if the principle of reciprocity is not strictly adhered to; its successful implementation depends above all on the state’s political support, a social base that ensures enforcement, and whether the government has the political clout and capability to insulate itself from interest groups. In addition, designing and managing incentives and support schemes is a complex process that requires careful selection, together with an effective bureaucracy, and continuous evaluation of its purpose and shortcomings during the implementation process. Instruments such as export discipline (linking incentives to exports to discipline firms and enhance international learning) and domestic rivalry (to ensure that incentives are tied to intense competitiveness) may also be beneficial. Devices such as latitude to performance are important; the system has to be measurable and execution as simple as possible. The nature of these incentives should be measured against international practices and policy space, and constantly renewed based on learning from others. These are critical decision areas that have strategic implications. The incentive structure should differentiate between big businesses, small businesses, and technology start-ups, and should focus on sectors with the strongest linkage effects. It should also be based on the principle of ‘creative destruction’ to ensure that the death of decaying firms is accelerated and new start-ups and spin-outs that generate new energy are supported. The point is that ensuring complementarity, coherence, and compatibility across policies and within industrial policy is a difficult exercise which is constrained by institutional capability and political constraints. Ensuring greater coherence at planning and during implementation stages may not be sufficient as these tensions and imbalances are constant. Arguably, thriving by creating tensions and imbalances is an alternative but complementary approach to produce better outcomes: ‘the view that ⁶⁶ See Chapters  and . ⁶⁷ See also Oqubay (: ) who highlights that ‘The principle of reciprocity is important in almost all conditions, despite the challenges of implementation and its dependence on the state’s political clout’.

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

economies should develop by prioritizing key sectors rather than relying on comprehensive, overarching plans’ (Hirschman, : ; see also Oqubay, ; Cramer, Sender, and Oqubay, ).⁶⁸

.. Summary The practice of industrial policy requires: a) Effective policy instruments which are relatively easy to design, measure, and adapt at sectoral level. This helps to link instruments with the sector’s life cycle and with upgrading and deepening of the industrial structure, and to create an ecosystem that offers growth opportunities and continuous learning. b) Not all instruments require the same level of execution capacity. For instance, devaluation is important for promoting exports, but it does not require sophisticated executive capacity at sectoral level. Nonetheless, some export incentives (such as the ‘voucher system’) may require higher professional bureaucracy. Understanding this variation is important for choosing and designing policy instruments. c) The purpose of these instruments is to promote productive investment, production capability, domestic capability, export performance, and linkage effects and innovation capability. It needs a balancing act so that not only productive investment, but more importantly international and local talents are targeted, accelerating creative destruction in terms of firm dynamism, and balancing the attraction of FDI against domestic firms, and big business against small firms.

. C R: O  E I

.................................................................................................................................. Industrial policy has not been static, and successful industrial policies have constantly adapted to the changing external environment and local conditions. Empirical evidence shows that industrial policy and outcomes are uneven across sectors and are primarily shaped by variations in the industrial structure, politics, and linkage effects of sectors (Oqubay, : , ).⁶⁹ However, three key factors carrying significant implications for policymakers emerge as drivers of unevenness and variation in ⁶⁸ See Hirschman (: ), who ‘emphasized the positive role of imbalance in economic development and of crisis in the achievement of social and economic reform in Latin America’. See also Hirschman (, ). ⁶⁹ See also Oqubay (a, b).

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

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industrial policies: the industrial structure of each sector; politics and the political economy; and linkage effects.

.. The Middle-income Trap More recently, new debates have emerged focusing on economic catch-up, and particularly on the difficulty and rare instances of climbing the development ladder from middle to high income. While there is less agreement on the ‘middle-income trap’ concept, increasing evidence shows that the vitality of technological capability and innovation are critical for avoiding it. This may be partly explained by Abramovitz’s hypothesis that catch-up slows as latecomers converge with the productivity levels of the leaders or forerunners (Abramovitz, ). Accelerated catch-up, dynamic transformation to an innovation-driven economic path, stalled industrialization, where technological catch-up has become impossible, and premature de-industrialization, where manufacturing has run out of steam for creating jobs, output, and export earnings (UNCTAD, ), can all be imagined. As China emerges as the world’s manufacturing and exports powerhouse, its shift to an innovation-driven economy, combined with its sheer size, continues to impact the intensity of global competition, and the struggle to escape the ‘middle-income trap’ (Paus, ).

.. Changing Patterns of Global Production and World Economy A major shift in the last five decades has been the internationalization of production, the rise of global value chains and global production networks, and the dominance of the global business revolution (Gereffi, ; Dicken, ; Coe and Yeung, ; Nolan, ). Major shifts in international governance systems that have had an uneven impact on developing, emerging, and advanced economies and on the policy space for designing industrial policy include the introduction of binding multilateral trade rules under the WTO, tighter protection of intellectual property through the TRIPS agreement, a Sino-centric global economy, and the post- global economic slowdown. Least developed economies face intensified competition to exploit limited opportunities. Wade characterizes this process as follows: ‘the combination of global value chains, knowledge monopoly, and financialization makes for slow or no long-run convergence upwards of the majority of emerging and developing economies’ (: ).⁷⁰ ⁷⁰ Wade further states that: ‘The key point is that the new phase of globalization characterized by GVCs (since the late s) tips the balance of power in the world economy firmly in favour of MNCs, because if one host government does not agree to their conditions, or if labour costs in one country rise too high, the firm can readily shift production elsewhere’ (: ).

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

Since the  economic crisis three tendencies have surfaced which reflect the contemporary global political economy. First, emerging economic powers and significant players in international markets have pursued a pro-WTO trading system advocating free trade and shrinking protection. This view is in line with multilateralism and the multi-polar global power structure. Second, however, there has also been a backlash against this trend with a preference for bilateral trade negotiations and a withdrawal from regional economic blocks. Third is increased integration of regional markets, such as ASEAN in the Asia Pacific, an inclusive initiative related to the Trans Pacific Partnership.⁷¹

.. Accelerated Technological Advancement The pace of technological change has accelerated the emergence and fusion of new technologies (such as ICT, artificial intelligence, G technology, automation, robotization, and digitization) that are shaping and shaking each industry in unexpected ways. While what is called the Fourth Industrial Revolution, or the digital economy, offers many opportunities, the unrestrained power these technologies offer to leading technology MNCs undermines the roles of government and the rights of citizens.⁷² ‘Technological romanticizing’ or ‘technology hype’ advocates technological determinism, ignoring the fact that technologies should serve the well-being of society and the indispensable role of social transformation. Technological advances do not shape all sectors uniformly, and understanding their scope at economy and sectoral level is critical. The implications for the development of human capital and the expansion of smart infrastructure, financial services, and R&D are particularly significant. Industrial policies should take this fundamental shift into account and provide effective mitigation and adjustment in response to these challenges.

.. Sustainability and Green Industrial Policy The early industrial revolution and twentieth-century industrialization were characterized by neglect of climate change and the critical role of environmental sustainability (Mathews, a, ).⁷³ The position taken by the corporate world has varied according to economic interests and economic power. Increased awareness on the part of consumers has still not been sufficient to pressure corporations and industries to refrain from damaging the environment. One perspective to emerge is that economic ⁷¹ The United States and the United Kingdom are typical examples. See also Chapters  and . ⁷² See Paus (). ⁷³ See Chapters  and .

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

 

growth and environmental sustainability are not mutually exclusive. Sustainable development requires environmental protection to be at the centre of economic policies. It involves education, a regulatory regime that does not reward polluters, industrial policy that rewards sustainability and resource savings, and increased innovation in environmental science for job creation and economic growth. From a long-term perspective, integrating environmental sustainability and putting it at the centre of industrial policy is a necessity.⁷⁴

A The author is grateful to Christopher Cramer, John Mathews, José A. Ocampo, and Taferre Tesfachew for their constructive comments and discussion, and inputs from the reviews workshop. The author thanks Deborah Kefale, Samuel Arkebe, and Binyam Arkebe for inputs to improve the draft and for their continued support.

R Abramovitz, Moses () ‘Catching up, Forging ahead, and Falling behind’, in Moses Abramovitz, Thinking About Growth: And Other Essays on Economic Growth and Welfare. Cambridge: Cambridge University Press, pp. –. Abramovitz, Moses () ‘Catch-up and Convergence in the Growth Boom and After’, in William Baumol, Richard Nelson, and Edward Wolf (eds), Convergence of Productivity: Cross-national Studies and Historical Evidence. Oxford: Oxford University Press, pp. –. Akyűz, Yilmaz () Playing with Fire: Deepened Financial Integration and Changing Vulnerabilities of the Global South. Oxford: Oxford University Press. Amsden, Alice () Asia’s Next Giant: South Korea and Late Industrialization. Oxford: Oxford University Press. Amsden, Alice () The ‘Rise of the Rest’: Challenges to the West from Late-Industrializing Economies. Oxford: Oxford University Press. Amsden, Alice () Escape from Empire: The Developing World’s Journey through Heaven and Hell. Cambridge, MA: MIT Press. Amsden, Alice () ‘Elites and Property Rights’, in Alice Amsden, Alisa DiCaprio, and James A. Robinson (eds) The Role of Elites in Economic Development. Oxford: Oxford University Press, pp. –. Amsden, Alice and Wan-wen Chu () Beyond Late Development: Taiwan’s Upgrading Policies. Cambridge, MA: MIT Press. Andreoni, Antonio and Ha-Joon Chang () ‘Bringing Production and Employment back into Development: Alice Amsden’s Legacy for a New Developmentalist Agenda’, Cambridge Journal of Regions, Economy and Society (): –.

⁷⁴ See also Mathews (a) Green Capitalism.

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      



Jacobs, Jane () Cities and the Wealth of Nations: Principles of Economic Life. New York: Vintage Books. Johnson, Chalmers () MITI and the Japanese Miracle: The Growth of Industrial Policy, –. Stanford, CA: Stanford University Press. Kaldor, Nicholas () Strategic Factors in Economic Development. Ithaca, NY: New York State School of Industrial and Labour Relations, Cornell University. Kaldor, Nicholas () Essays on Economic Stability and Growth. nd edition. New York: Holmes & Meier Publishers. Kay, Cristobal () ‘Why East Asia Overtook Latin America: Agrarian Reform, Industrialisation and Development’, Third World Quarterly (): –. Khan, Mushtaq H. () ‘Political Settlements and the Governance of Growth-Enhancing Institutions’. Available at https://eprints.soas.ac.uk///Political_Settlements_internet. pdf. Khan, Mushtaq H. and Stephanie Blankenburg () ‘The Political Economy of Industrial Policy in Asia and Latin America’, in Mario Cimoli, Giovanni Dosi, and Joseph E. Stiglitz (eds) Industrial Policy and Development: The Political Economy of Capabilities Accumulation. Oxford: Oxford University Press, pp. –. Kim, Linsu () ‘Korea’s National Innovation System in Transition’, in Linsu Kim and Richard Nelson (eds) Technology, Learning, and Innovation: Experiences of Newly Industrializing Economies. Cambridge: Cambridge University Press, pp. –. Kim, Linsu and Richard R. Nelson (eds) () Technology, Learning and Innovation: Experiences of Newly Industrializing Economies. Cambridge: Cambridge University Press. Kohli, Atul () State-Directed Development: Political Power and Industrialization in the Global Periphery. Cambridge: Cambridge University Press. Komiya, Ryutaro, Masahiro Okuno, and Kotaro Suzumura (eds) () Industrial Policy of Japan. London: Academic Press. Kuznets, Simon () Modern Economic Growth: Rate, Structure and Spread. New Haven, CT: Yale University Press. Kuznets, Simon () ‘Modern Economic Growth: Findings and Reflections’, American Economic Review : –. Lee, Keun () Schumpeterian Analysis of Economic Catch-up: Knowledge, Path-Creation, and the Middle-income Trap. Cambridge: Cambridge University Press. Lee, Keun (a) ‘The Origin of Absorptive Capacity in Korea: How Korean Industry Learnt’, in Arkebe Oqubay and Kenichi Ohno (ed.) How Nations Learn: Technological Learning, Industrial Policy, and Catch-up. Oxford: Oxford University Press, pp. –. Lee, Keun (b) The Art of Economic Catch-up: Barriers, Detours and Leapfrogging in Innovation Systems. Cambridge: Cambridge University Press. Lee, Keun and Franco Malerba () ‘Economic Catch-up by Latecomers as an Evolutionary Process’, in Richard Nelson (ed.) Modern Evolutionary Economics: An Overview. Cambridge: Cambridge University Press. Lin, Justin Yifu () ‘The Latecomer Advantages and Disadvantages: A New Structural Economics Perspective’, in Martin Andersson and Tobias Axelsson (eds) Diverse Development Paths and Structural Transformation in Escape from Poverty. Oxford: Oxford University Press, pp. –. Lin, Justin Yifu and Ha-Joon Chang () ‘Should Industrial Policy in Developing Countries Conform to Comparative Advantage or Defy It? A Debate between Justin Lin and Ha-Joon Chang’, Development Policy Review (): –.

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

 

Lin, Justin Yifu and Volker Treichel () ‘Learning from China’s Rise to Escape the Middleincome Trap: A New Structural Economics Approach to Latin America’. Policy Research Working Paper No. . Washington, DC: World Bank. List, Friedrich () National System of Political Economy, Vols I–IV. Memphis, TN: Lippincott. Marshall, Alfred () Principles of Economics. London: Palgrave Macmillan. Marx, Karl ([] ) Capital: A Critique of Political Economy, Volume I. London: Penguin Classics. Mathews, John (a) Greening of Capitalism: How Asia is Driving the Next Great Transformation. Stanford, CA: Stanford University Press. Mathews, John (b) ‘Latecomer Industrialization’, in Erik S. Reinert, Jayati Gosh, and Rainer Kattel (eds) Handbook of Alternative Theories of Economic Development. Cheltenham: Edward Elgar, pp. –. Mathews, John () Global Green Shift: When CERES Meet GAIA. London: Anthem Press. Mazzucato, Mariana () The Entrepreneurial State: Debunking Public vs. Private Sector Myths. London: Anthem Press. Mazzucato, Mariana () The Value of Everything: Making and Taking in the Global Economy. London: Allen Lane. Mowery, David C. and Nathan Rosenberg () Technology and the Pursuit of Economic Growth. Cambridge: Cambridge University Press. Mytelka, Lynn () ‘Local Systems of Innovation in a Globalized World Economy’, Industry and Innovation (): –. Mytelka, Lynn and Taffere Tesfachew () ‘The Role of Policy in Promoting Enterprise Learning during Early Industrialization: Lessons for African Countries’. UNCTAD/GDS/ MDPB/Misc.. Geneva: UNCTAD. Nayyar, Deepak () Catch Up: Developing Countries in the World Economy. Oxford: Oxford University Press. Nayyar, Deepak () ‘Foreword’, in Arkebe Oqubay and Kenichi Ohno (eds) How Nations Learn: Technological Learning, Industrial Policy, and Catch-up. Oxford: Oxford University Press, pp. vi–xi. Nelson, Richard and Sidney Winter () An Evolutionary Theory of Economic Change. Cambridge: Cambridge University Press. Nolan, Peter () Chinese Firms, Global Firms: Industrial Policy in the Age of Globalization. New York: Routledge. Ocampo, José Antonio () ‘Dynamic Efficiency: Structural Dynamics and Structural Change in Developing Countries’, in Akbar Noman and Joseph E. Stiglitz (eds) Efficiency, Finance, and Varieties of Industrial Policy. New York: Columbia University Press, pp. –. Ocampo, José Antonio () ‘The Transformation of Latin American Economies’, in Célestin Monga and Justin Yifu Lin (eds) The Oxford Handbook of Structural Transformation. Oxford: Oxford University Press, pp. –. Ocampo, José Antonio, Cordina Rada, and Lance Taylor () Growth and Policy in Developing Countries: A Structuralist Approach. New York: Columbia University Press. OECD () Guidelines for Collecting and Interpreting Innovation Data: Oslo Manual. OECD and Eurostat. Ohlin, Bertil () Interregional and International Trade. Cambridge: Cambridge University Press.

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      



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

 

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  .............................................................................................................

  .............................................................................................................

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  ......................................................................................................................

               ,              ,      .............................................................................................................

´  

. I

.................................................................................................................................. T chapter argues that structural change is at the heart of a dynamic process of economic development, and that active industrial (production-sector development) policies must be at the heart of an appropriate development strategy. The major policy focus of that strategy should, therefore, be on the dynamic efficiency of economic structures, defined as their capacity to generate new waves of structural change.¹ This concept is in sharp contrast with static efficiency, the central focus of traditional microeconomic and international trade theories. Dynamic efficiency requires degrees of state intervention that traditional defendants of static efficiency would also consider unacceptable. What this means is that economic growth in emerging and developing countries— the focus of this chapter—is intrinsically tied to the dynamics of production structures, the learning processes associated with technological catch-up and the capacity to gradually join the world of innovators, and the specific policies and institutions created to support these processes. The promotion of dynamic efficiency in these countries also includes the creation of linkages among domestic firms and sectors, and the adequate management of natural resources in countries that have a strong static comparative advantage in commodity production. It equally involves the reduction of the heterogeneity of their production structures, due to the coexistence of low-productivity (informal) activities alongside high-productivity (modern) firms—a phenomenon ¹ This concept is borrowed from Ocampo (b). Note that it is entirely different from that of ‘dynamic efficiency’ used in neoclassical optimal growth models.

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

´  

that has been alternatively called both ‘dualism’ and ‘structural heterogeneity’. Avoiding macroeconomic instability is also essential, particularly guaranteeing competitive and stable real exchange rates, which are critical for adequate structural change, in the face of terms-of-trade fluctuations and capital account volatility. These are basic ideas that have been advanced by all brands of—broadly defined— ‘structuralism’ in economic thinking.² The work of Schumpeter, the neo-Schumpeterian, and evolutionary schools are included within this concept. This encompasses the view, which originates in Schumpeter’s () analysis of business cycles, that technological revolutions come in waves of innovation that gradually spread through the economic system (Freeman and Soete, ; Pérez, : part I), replacing previous technologies and the firms and sectors that used them, and generating a process of ‘creative destruction’ (Schumpeter, : ch. VIII). In relation to developing economies, some of the ideas come from different brands of Latin American structuralism that followed the work of Raúl Prebisch and the United Nations Economic Commission for Latin America and the Caribbean (ECLAC), including its most recent brand, ‘neo-structuralism’. We should also embrace within this broad concept of structuralism the emphasis of classical development economics on industrialization and external economies as core elements of economic development, including the notions of backward and forward linkages associated with the work of Hirschman (). We can add the growth-productivity connections associated with Kaldor’s (: chs  and ) analysis of economic growth, as well as the role of increasing returns in contemporary neoclassical models of economic growth.³ Contextual conditions for a dynamic development process have also been emphasized in the literature. However, they generally play the role of background conditions rather than that of direct determinants of changes in the growth momentum.⁴ They include an adequate education system and a proper physical infrastructure. They also include an institutional context that guarantees a measure of stability in the basic social contract, a non-discretionary legal system, an impartial (and, ideally, efficient) state bureaucracy, and smooth business‒labour‒government relations. There are, however, significant differences in concepts about what constitutes a proper institutional context, and certain institutional features are fairly constant over decades in specific countries, whereas growth is not.⁵ This chapter therefore leaves aside the analysis of these contextual conditions, referring only to institutions that directly relate to structural change.

² See, among an extensive literature, Prebisch (, ), Furtado (), Nelson and Winter (), Dosi et al. (), Wade (), Taylor (), Chang (), Nelson (, ), Aghion and Howitt (), Rodrik (, ), Ros (, ), Amsden (), Ocampo et al. (), Lin (), Stiglitz and Greenwald (), and Cherif and Hasanov (). ³ See the classical contributions by Romer (), Lucas (), and Barro and Sala-i-Martin (). ⁴ See in this regard the differentiation between ‘proximate’ and ‘ultimate’ causality of growth processes by the economic historian Maddison (: ch. ). ⁵ See, for example, Easterly et al. () and Pritchett ().

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 , ,   



It should be added that the distributive effects of structural transformation strategies depend on how far such strategies help reduce the heterogeneity of production structures through training, technological diffusion, appropriate financing channels, the promotion of different forms of associations among small entrepreneurs, and commercial links between large and small firms. However, this is a subject that is only marginally covered here. The chapter is divided into six sections, the first of which is this introduction. The second takes a look at growth patterns identified in the old and more recent literature. The third focuses on the dynamics of production structures, and particularly on its two fundamental elements: innovations and complementarities. The fourth considers the specific issues raised by natural resource dependence. The fifth looks at the interrelated issues of financing structural change and managing financial fluctuations. The last section draws major policy implications.

. G P

.................................................................................................................................. The large empirical literature has identified that economic growth involves the simultaneous movement of a series of economic variables: improved technology, human capital accumulation, investment, savings, and systematic changes in production structures.⁶ Disentangling cause and effect is not always an easy task. Thus, higher investment and savings ratios are generally seen as essential for growth accelerations, but they may be the result rather than the cause of faster growth: the effects of the accelerator mechanism on investment, and higher savings associated with income growth and redistribution effects that go along with it, such as raising firms’ retained profits. In turn, the accumulation of skills, an essential element of human capital, is mainly the result of learning associated with production experience, and the expansion of education systems is facilitated by the increased social spending enabled by economic growth. Productivity improvements may also be the result of growth: learning processes, as well as technical improvements embedded in new equipment—the causal link emphasized by Kaldor (), which is the opposite of that assumed by neoclassical growth theory since Solow (, ). Thus, many of the regularities mentioned in the growth literature may be subject to sharply differing interpretations, depending on views on the causal links involved. A few ‘stylized facts’ may serve, however, as a point of departure for this chapter. The first is the persistence and even enhancement of the vast inequalities in the world economy that arose quite early in the history of modern economic growth. As Rodrik () has emphasized, convergence in per capita incomes has been the exception ⁶ Nonetheless, it has also been argued that there is much less association between some of these variables and economic growth than was traditionally assumed. This has been claimed particularly in relation to physical and human capital. See Easterly (: part II).

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

´  

rather than the rule. Indeed, using Maddison’s () data, we can estimate that slightly over  per cent of the variance of per capita income levels in the world at the end of the twentieth century can be explained by income differences that already existed in . This indicates that, although there have been changes in the world income hierarchy, these have been exceptions. Even in the case of developed countries, strong convergence took place during the post-Second World War ‘golden age’ of ‒, but not before the Second World War (Maddison, ).⁷ The most important feature, however, is the divergence of incomes between developed and developing countries in the nineteenth and twentieth centuries, which Pritchett () aptly characterized as ‘divergence, big time’. Among the exceptions to this rule, we can also include the rise of Latin America to middle-income levels since the late nineteenth and early twentieth centuries and through the inter-war period⁸ and, of course, the success of Asian newly industrializing economies since the s and that of China since the s. The first decade of the twenty-first century, and at a slower rate until the end of the ‘super-cycle’ of commodity prices in , is perhaps the only case of fairly broad convergence of per capita income between developed and developing countries in history. The reasons for divergence are well known. They include the ‘poverty trap’ analysed by classical development economists, as well as the ‘middle-income trap’ identified in the recent literature (see, for example, Gill and Kharas, , ; Eichengreen et al., , ). They also reflect basic international asymmetries: (i) prohibitive entry costs into mature sectors and technologically dynamic activities; (ii) differences in domestic financial development and in the stability or volatility of external financing; and (iii) macroeconomic asymmetries that generate quite different degrees of freedom to adopt countercyclical macroeconomic policies and even a tendency for developing countries to adopt procyclical policies, due to their dependence on unstable external financing (Ocampo, , ). The main implication of this fact is that economic opportunities are largely determined by the position that a particular country occupies within the world hierarchy. For this reason, economic development is not about following ‘stages’ of growth, but carrying out the associated structural transformations, and employing the appropriate macroeconomic and financial strategies within the restrictions that each country’s position within the world hierarchy creates. This was the essential insight of the Latin American structuralist school and the literature on late industrialization since Gerschenkron (see Gerschenkron, ; Amsden, ). As underscored in the classic work by Chenery and collaborators, growth is accompanied by regular changes in the sectoral composition of output and the patterns of international specialization (see Chenery et al., ). Episodes of convergence have ⁷ The development that took place in Japan after the Meiji Restoration, and the escalation of this country to the top group of developed countries in the post-Second World War years should be included as successful convergence processes. ⁸ In relation to Latin America, see Bértola and Ocampo (: ch. ).

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 , ,   



been generally associated with processes of industrialization and the reallocation of labour from low- to high-productivity sectors subject to economies of scale and scope (specialization), but many have also ended in truncated convergences or growth collapses (Ros, , ; Easterly, ).⁹ Furthermore, a significant feature of developing countries in recent decades has been the premature de-industrialization of Latin America and Africa, that is, the reduction in the share of manufacturing in employment and GDP at much lower levels of income per capita than has been typical in similar processes in developed countries—a concept and a trend that was first highlighted by Palma () and Dasgupta and Singh (), and more recently by Rodrik (). De-industrialization may have been generated by the way economic liberalization was undertaken, and by the ‘Dutch Disease’ effects of the super-cycle of commodity prices of the early twenty-first century. Such a trend is in sharp contrast with the persistent industrialization of East Asia and its spread to a group of middleand lower-income countries in South East and South Asia. Asian countries are also the only ones where recent growth accelerations have mixed structural change with improvements in labour productivity at the sectoral level, whereas Latin America has lacked the first element and Africa the second (Diao et al., ). Several authors have also pointed out that episodes of structural change come in spurts rather than as steady flows, an idea that may be seen as related to the concept of waves of innovation. The capacity to generate a wave of innovations or absorb one that has already been developed in advanced economies depends, in any case, on production experience, and follows, therefore, a process of path dependence (Arthur, ). The complementarities (externalities) among sectors are crucial for a strong growth process to take place (Rosenstein-Rodan, ; Taylor, ; Ros, , ) and, if they cannot be developed simultaneously, they may generate successive phases of disequilibrium (Hirschman, ). These views imply, in short, that the dynamics of production structures are an active determinant of economic growth and, therefore, that this process cannot be reduced to its aggregate dimensions. Elastic factor supplies play an essential role in facilitating a smooth expansion of dynamic activities. Financing facilities for innovative sectors are essential in this regard, as emphasized in the literature on late industrialization in the now developed countries; as we will see, public-sector development banks can play a crucial role in this regard. In turn, the reallocation of labour from traditional to modern sectors also plays an essential role, as underscored by Lewis (, ) and many later authors.¹⁰ At the same time, however, low economic growth may generate the opposite pattern, in which traditional or informal activities—or the public sector—absorb the labour that modern ⁹ The lasting effects of the debt crises of the s in Africa and Latin America are the most telling example in this regard, but that of several peripheral European countries (notably Greece) after the ‒ North Atlantic financial crisis has similar features (I use this term rather than the more commonly used ‘global financial crisis’, because although the crisis had global effects, it centred in the United States and Western Europe). ¹⁰ Interestingly, Kaldor (: ch. ) and Cripps and Tarling () show the importance that this process also had during the post-Second World War golden years in industrial countries.

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

´  

sectors do not demand (Ocampo et al., ). The interplay between labour mobility and economies of scale has also been the essential insight of regional economics since its origins, generating urban and regional growth poles (for a modern version, see Fujita et al., ). The ‘vent for surplus’ models of international trade, which go back to Adam Smith, also provide an alternative source of elastic factor supplies: un- or underexploited natural resources (Myint, : ch. ). The role of economic policy in these processes has been the subject of heated controversies. In recent decades, the orthodox emphasis has been on the positive role that trade openness plays in facilitating economic growth, but the simplistic relation between trade liberalization and growth has been shown to be incorrect, as underscored by several authors after the seminal paper by Rodríguez and Rodrik (). Indeed, to the extent that scale economies and learning play an important role in international specialization,¹¹ comparative advantages can be or even are generally created. More broadly, successful development experiences have been associated with variable policy packages involving different mixes of orthodox incentives with unorthodox institutional features (‘local heresies’) (see the comparative analyses of development experiences in Helleiner, , and Rodrik, , ). Thus, protection has been a source of growth in some periods in specific countries, but has blocked it in others; the same thing can be said of freer trade—the degree of openness in the world economy being critical in this regard. Export growth has been, of course, a crucial element of East Asian success in recent decades, but has involved significant elements of state intervention. Mixed strategies have worked well under many circumstances. Indeed, an interesting historical observation is the evidence that successful experiences of manufacturing export growth in the developing world were generally preceded by periods of import-substitution industrialization (Chenery et al., ). Bairoch (: part I) came to a similar view regarding the role of protection in the growth of the ‘late industrializers’ during the pre-First World War period, concluding that the fastest periods of growth in world trade before the First World War were not those characterized by the most liberal trade regimes. In macroeconomic terms, there is evidence that long-term growth in developing countries is positively associated with the capacity to guarantee a competitive real exchange rate, and thus with the idea that an active exchange rate policy can help foster structural change.¹² In this sense, a competitive exchange rate can be viewed as a type of industrial policy that can partially substitute for traditional industrial policies, particularly in the face of restrictions on subsidies to production and exports under World Trade Organization (WTO) rules. However, it should also be complemented by other industrial policies (e.g. on access to technology and credit) that increase the elasticity of the aggregate supply to the real exchange rate. ¹¹ See the seminal analysis of this issue in Krugman (), Grossman and Helpman (), and, in relation to developing countries, Ocampo (). ¹² See Rodrik (), Rapetti et al. (), Razmi et al. (), Rapetti (), and for a review of the literature, Frenkel and Rapetti () and Missio et al. ().

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 , ,   



. T D  P S

.................................................................................................................................. As stated in the introduction, the capacity to permanently generate new dynamic activities is the essence of successful economic development. In this sense, structural change is essentially a meso-economic process that includes the variations in the composition of production, intra- and inter-sectoral linkages, market structures, the functioning of factor markets, and the institutions that support all of them. Dynamic microeconomic changes are the building blocks, but it is system-wide structural change that matters. Furthermore, this process has a strong impact on macroeconomic dynamics through its effects on investment, employment, and trade, and macroeconomic policy can also affect this process. The dynamics of production structures may be visualized as the interaction between two basic forces: () innovations, broadly defined as new technologies, new activities and new ways of doing previous activities, and the learning processes that characterize their full realization and their diffusion through the economic system; and () the complementarities, linkages, or networks among firms and production activities. The institutions required to enhance these structural processes are crucial and also subject to learning. Elastic factor supplies are essential to guarantee that these dynamic processes can deploy their full potentialities. It is the combination of these factors that determines the dynamic efficiency of a given production system (Ocampo, b).

.. Innovations The definition of innovations used here follows the broad concept of ‘new combinations’ suggested by Schumpeter (: ch. II): new qualities of goods and services; new production methods or marketing strategies; opening up of new markets; new sources of raw materials; and new industrial structures. Today we would also add new ways of managing the environment, including mitigating the effects of climate change. The definition includes technological innovations—the more common use of the concept of innovations in the economic literature—but also a broader set of micro- and mesoeconomic processes. As we saw in the Introduction to this chapter, innovations include not only the creation of firms, production activities, and sectors, but also the destruction of others— or, using Easterly’s (: ch. ) terminology, complementary and substitution effects. Schumpeter’s ‘creative destruction’ is, of course, essential if innovations are to lead to growth. However, there may be other outcomes: limited destruction but also large-scale destruction or a mixed negative case, ‘destructive creation’, when the destruction prevails over the creative parts of the transformation. Also, some locations may

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

´  

concentrate the creative and others the destructive effects, for example, when a synthetic substitute is discovered in an industrial centre that puts producers of the natural raw material located elsewhere out of business. In industrial countries, the incentive to innovate is provided by the extraordinary profits that can be earned by the pioneering firms that introduce technical, commercial, or organizational changes, or which open new markets or find new sources of raw materials. This incentive is necessary to offset the uncertainties and risks involved in the innovators’ decisions, the incomplete nature of the knowledge they initially have, and the fact that, due to the externalities that the innovation generates, they may not be able to fully appropriate its benefits. In contrast, in developing countries, innovations are largely associated with the transfer of sectors, new products, technologies, and organizational or commercial strategies previously developed in the industrial centres. The industrial countries’ innovations thus represent the ‘moving targets’ which generate the windows of opportunity for developing countries (Pérez, ). The extraordinary profits that innovators enjoy in developed countries may be absent, as they may involve entry into mature activities with thinner profit margins. Thus, in the absence of policy incentives, there may be a suboptimal search for new economic activities (Hausmann and Rodrik, ). No innovative process is passive, as it requires investment and learning. It requires investments in physical capital as well as in intangibles, including technological learning. Technical know-how must indeed go through a maturing process that is closely linked to the production experience. Climbing up the ladder in the world hierarchy entails shortening transfer periods, taking ‘detours’ to manage existing intellectual property rights in place and, most importantly, gradually becoming a more active participant in technology generation (Lee, ). It requires national innovation systems to be built up, which should include an institutional framework to coordinate the various actors engaged in innovation and learning—research and development centres, universities and technology schools, extension services, and the innovating firms themselves—and to redirect investments over the long term towards new capabilities and, of course, an ambitious educational strategy that supports these processes. Essential insights into learning dynamics have been provided by ‘evolutionary’ theories of technical change.¹³ These theories emphasize the fact that technology is, to a great extent, tacit in nature, that is, that detailed ‘blueprints’ cannot be plotted. This has three major implications. The first is that technology is incompletely available and imperfectly tradable. This is associated with the fact that technology is, to a large extent, composed of intangible human and organizational capital, which implies that even

¹³ See Nelson and Winter (), Nelson (), and Dosi et al. () and, with respect to developing countries, Katz (), Lall (, ), and Lee (). Similar concepts have been developed in some versions of the new neoclassical growth theory, in which ‘knowledge capital’ is a form of ‘human capital’ with three specific attributes: it is ‘embodied’ in particular persons, it is capable of generating significant externalities, and it is costly to acquire (Lucas, ).

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 , ,   



firms that purchase or imitate it must invest in mastering the acquired or imitated technology, a process that involves adaptation and even redesigns and other secondary innovations. Since this process will be specific to each firm, heterogeneous producers will coexist in any sector of production. The second implication is that technology proficiency cannot be detached from production experience: it has a strong learningby-doing component. This will also apply, at least in part, to technology creation, which implies that the probability of major innovations would depend on the accumulated technological knowledge and production experience of firms, which in new technological fields would include new firms. The third feature of technical change, unrelated to tacitness, is that diffusion of innovations implies that innovative firms only imperfectly appropriate their benefits. Intellectual property rights provide a mechanism for appropriating those benefits more fully in the case of technological innovations, but they are not present in other forms of innovation (such as the development of new activities or a new marketing strategy). Innovations, therefore, have a mixture of private and public good attributes. It must be emphasized that these three features of technical change—imperfect tradability, close association with production experience, and private/public attributes—are equally characteristic of other forms of knowledge, particularly organizational and commercial know-how, and institutional development. Imperfect tradability, due to its social-capital attributes, is paramount in the case of organizational knowledge. In turn, commercial know-how and the development of commercial reputation (goodwill) plays a pivotal role in international trade (Keesing and Lall, ). Moreover, familiarity with the market enables producers to modify their products and their marketing channels and helps buyers learn about suppliers, generating client relations that are important to guarantee the stable growth of firms.

.. Complementarities Complementarities are associated with the development of networks of suppliers of goods and specialized services, marketing channels, and organizations and institutions that disseminate information and coordinate the relevant agents. This concept summarizes the role that backward and forward linkages play in economic growth (Hirschman, ) but also that of (private, public, or mixed) institutions that are created to reduce information costs (e.g. on technology and markets) and to mitigate the coordination failures that characterize interdependent investment decisions (Chang, ). Complementarities generate positive externalities among agents, which help reduce their costs. They are the basis of the dynamic meso-economic economies of scale that determine the competitiveness of production sectors in a given region or country—or the lack of it. Under these conditions, competitiveness involves more than microeconomic efficiency: it is essentially a meso-economic or even a system-wide feature (Fajnzylber, ).

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

´  

The cost and quality of the non-tradable inputs are particularly important in this regard. They contain specialized services, including knowledge, and logistic and marketing services, for which closeness to producers who use the inputs or services may be a critical factor. They may also include specialized financial services, where closeness can also be important due to asymmetric information. Also, and although importing tradable inputs from the best supplier worldwide can encourage export competitiveness, the capacity to generate value chains in which exports have a large domestic value-added content based on national clusters determines how much a given country benefits from trade. Such contents differ considerably among countries. According to OECD-WTO data, and focusing only on developing countries that are important manufacturing exporters, the share of value added in gross exports in  was . per cent for China, where it has been rising over the past decade, . per cent for the Republic of Korea, also rising, but . per cent and falling for Mexico, and only . per cent, also falling, for Vietnam.¹⁴ As we have seen, the ability of innovative activities to attract capital and labour, and to gain access to the natural resources they need, will be a critical factor in facilitating the growth of these activities. One factor is the role of national development banks in facilitating long-term finance for innovative activities. International capital mobility— particularly foreign direct investment—can also play an important role. International labour migration may be critical for skilled labour. Unemployed or, more typically, underemployed natural resources can facilitate the expansion of innovative sectors that require them—for example, innovative agricultural activities. And, of course, in the developing world, low-productivity activities, characterized by a considerable element of underemployment (or informality), act as a residual supplier of the labour required by a surge of economic growth. The distinction that dualistic models make between ‘traditional’ and ‘modern’ sectors is inappropriate for describing this feature of the developing world, as high- and low-productivity sectors are heterogeneous in their structure. The term ‘structural heterogeneity’, coined by Latin American structuralists (Pinto, ) to describe this phenomenon, is more appropriate and will thus be used in this chapter. Structural heterogeneity implies that the dynamism generated by innovative activities and the strength of the linkages they generate determine the efficiency with which the aggregate labour force is used (i.e. the extent of labour underemployment), as well as the underemployment of other factors of production, particularly land. A similar process can be generated by the better use of existing infrastructure. At the aggregate level, these processes give rise to Kaldorian growth–productivity links of similar characteristics, but in addition to the micro- and meso-economic dynamic economies of scales associated with learning and the development of complementarities. This means, of course, that aggregate productivity growth is both a cause and an effect of dynamic economic growth (see section .. below). ¹⁴ See OECD, Trade in value added database, https://www.oecd.org/sti/ind/measuring-trade-in-valueadded.htm#access.

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 , ,   



.. The Interplay of Innovations and Complementarities The interplay between these factors will determine the dynamic efficiency of a given process of structural transformation. Innovations accompanied by strong complementarities will be reflected in the absorption of an increasing number of workers into dynamic activities. The result will be a virtuous circle of high investment, accelerated technological learning, and institutional development. On the other hand, destructive forces may prevail, giving rise to a vicious circle of a slowdown in productivity and economic growth, decline in investment, increased structural heterogeneity as surplus manpower is absorbed into low-productivity activities, and loss of production experience that widens the technology gap vis-à-vis industrialized countries. A simple typology of different processes of structural transformation can be suggested (Ocampo, b). ‘Deep transformation’ is characterized by strong learning (including induced technological innovations) and complementarities (economies of agglomeration and specialization, and knowledge spillovers) and hence also by strong micro- and meso-economic dynamic economies of scale, and by the additional productivity effects generated by the reduction in underemployment. This tends to be the pattern in periods of rapid growth in the developing world and has characterized the East Asian success stories of recent decades. The opposite, which can be called ‘shallow structural transformation’, is characterized by the weakness of both learning and complementarities. A classic case is natural resource enclaves, but as we shall see, this may also be true today of certain forms of assembly manufacturing. A first mixed case combines strong learning with weak linkages, due to high import requirements. Some import-substitution activities of the past were of this type; in this case, the initial innovative effect may soon be exhausted due to its limited sectoral or systemic effects. A second mixed case is the combination of strong linkages with weak learning processes. In this case, productivity growth at the firm level may be low, but there may be significant aggregate productivity effects associated with reductions in underemployment and the development of complementarities. The expansion of labour-intensive export crops (e.g. coffee) is a case in point. The association with large-scale international networks of suppliers—global value chains¹⁵—that comes from very active foreign direct investment by multinational firms, and more codified technology that can be borrowed by paying the associated intellectual property rights, reduces the costs for developing countries to enter new activities. However, the centralization of research and development efforts and the marketing of the associated products—which can be seen as the two poles of the value chain—also risk ‘shallow’ structural transformation for the developing countries where assembly manufacturing takes place; the lack of domestic complementarities also makes these export activities footloose. Governments would have to challenge this outcome by promoting domestic complementarities and transition to new sectors that can benefit from existing specialization patterns. ¹⁵ Now, of course, being challenged by US protectionist policies and the coronavirus pandemic.

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

´  

Finally, the typology is useful for understanding some of the social effects of structural transformations. In this regard, deep transformations have better effects on formal employment and standards of living than shallow processes. However, if there is technical bias in the demand for labour in the first case, wage differentials may increase if the education policy does not rapidly increase the supply of skilled labour. Strong learning with weak linkages may lead to increased structural heterogeneity, whereas the opposite combination may generate strong demand for low-skilled labour.

.. The Links between Productivity and Growth The relationships between structural dynamics and long-term growth can be formalized as a dual link between economic growth and productivity (Ocampo and Taylor, ; Ocampo et al., : ch. ). On the one hand, economic growth has positive effects on productivity through four channels: (i) dynamic economies of scale of a microeconomic character, associated with learning and induced innovations; (ii) if technology is embodied in new equipment, a higher rate of investment induced by faster growth will also increase productivity; (iii) the productivity effects of the development of complementarities, associated with the exploitation of intra- and inter-sectoral external economies (economies of agglomeration and specialization, and knowledge spillovers); and (iv) the transfer of underemployed workers to higher-productivity activities. Kaldor (: chs  and ) called this link between productivity and production growth (shown as TT in Figure .) the ‘technical progress function’. Following the literature on the topic, it could also be referred to as the Kaldor-Verdoorn function.

G

G’

T’

D T B C

Productivity growth T’

A

T G

G’ GDP growth

 . Productivity and GDP dynamics

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 , ,   



It must be emphasized that the technical progress function is not an aggregate production function. Rather, its positive slope implies that there is some underutilization of resources at any point in time and, therefore, that growth induces a better allocation of resources—and the lack of growth reduces aggregate productivity, mainly through the underemployment of labour. The second relationship, shown as GG in Figure ., focuses on the reverse causality link: productivity growth increases economic growth. It can have diverse determinants, which alternately capture either aggregate supply or aggregate demand effects. First, technical change directly increases aggregate supply; this is the channel most emphasized in the growth literature. It also generates new investment that increases aggregate demand, generating a GG curve of a Keynesian nature. If the economy is foreign exchange constrained—a situation not uncommon in developing countries—the GG function would be effectively an aggregate supply function determined by the balanceof-payments restrictions (Thirlwall, a, b).¹⁶ Technical change also improves international competitiveness and thus the trade balance and aggregate demand; if the economy has a scarcity of foreign exchange, it weakens this constraint and has aggregate supply effects. As both curves have positive slopes, the effects that they capture reinforce each other, generating alternating positive feedbacks but also possible negative feedbacks. A stable equilibrium A exists when TT is flatter than GG, as shown in Figure ..¹⁷ Given the determinants of the technical progress function, TT will be flatter if micro- and mesoeconomic dynamic economies of scale are not too strong, or labour underemployment is moderate. In a Keynesian model, the slope of GG will depend on the elasticity of investment to productivity growth, whereas in foreign-exchange-constrained models, it will depend on the elasticities of exports and imports to productivity. In both cases, the higher the elasticities the flatter GG will be. It is important to emphasize that the relationships shown here are assumed to be medium or long term in character (some short-term macroeconomic effects associated with the balance of payments will be analysed below). If there is a new wave of innovations, the TT function will shift upward, to T’T´, accelerating both productivity and income growth at a new equilibrium point B. As this particular wave of innovations becomes fully exploited, the function may shift down. In turn, a favourable macroeconomic shock—improved investment financing in a Keynesian model, or improved export prospects or access to external financing in a foreign exchangeconstrained economy—will shift the GG function rightwards to G’G´, generating a new equilibrium at C; a negative macroeconomic shock will, of course, have the ¹⁶ See also the October  issue of the Review of Keynesian Economics in honour of Thirlwall. There may also be savings constraints. For a full analysis of the gaps in macroeconomic adjustment that may be reflected in the GG curve, see Taylor (). ¹⁷ Under significant initial labour underemployment or underutilization of other resources, the slope of TT could be steeper than that of GG, generating an unstable equilibrium at A. In this case, any displacement from saddle point A will lead the economy into explosive virtuous or vicious growth processes.

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

´  

opposite effect. With positive productivity and macro effects, the two curves could shift, generating a new equilibrium at D. In Ocampo (b), this simple framework is used to analyse the effects of trade liberalization on growth. The net effects are uncertain since they depend on many factors that affect both functions. In the orthodox view, that opening the economy to competition (including external competition) unleashes more innovations, then the TT function will shift up. However, if the response of firms to liberalization is a rationalization of their production (i.e. a defensive attitude) rather than a new wave of innovation and investment, the TT curve may not be affected; it may even be adversely affected if the static comparative advantages are in sectors with limited innovations and complementarities (see section .). On the other hand, through either Keynesian mechanisms or the supply effects characteristic of a foreignexchange-constrained economy, the increase in the propensity to import generated by a trade reform will lead to a leftward shift in the GG function, with adverse effects on equilibrium growth. Overall there is, therefore, no general presumption that trade liberalization will accelerate growth, as the positive microeconomic links emphasized by defenders of liberalization may be swamped by adverse structural and macroeconomic effects.

. C D

.................................................................................................................................. Commodities have been and will continue to be at the heart of development in several parts of the developing world, notably Africa, several parts of Latin America (particularly South America), the Middle East, and some other Asian countries. Furthermore, the recent commodity boom, which started in  and lasted for a decade, generated a ‘re-primarization’ (or ‘re-commoditization’) in several Latin American countries, understood as a growing share of natural resource goods in the export basket.¹⁸ The links between commodity dependence and development have been the subject of heated debate in the development literature as to whether commodity dependence promotes or obstructs structural change, and particularly whether it benefits or harms the development of manufacturing and modern services. There is also discussion on how the macroeconomic challenges associated with commodity price trends and fluctuations should be managed. The historical debate on these issues started with the Prebisch–Singer hypothesis, which claimed that commodity prices tended to deteriorate in the long term relative to those of manufactures (Prebisch, ; Singer, ). The original hypothesis involved two complementary ideas (Ocampo, ). The first was that commodities are characterized by low income and price elasticities of demand. The second and more interesting suggestion was that there is an asymmetry between the labour markets of ¹⁸ See Chapter  in this volume.

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 , ,   



advanced and developing countries, which implies that technological progress in manufactures tends to increase real wages in developed countries whereas, given the pool of unskilled labour, it tends to depress the prices of commodities in the developing world. This coincides with Lewis’s () analysis of the terms of trade of developing countries. It implies that manufactures exported from developing countries may face similar pressures. Focusing first on long-term commodity price trends, the Prebisch–Singer hypothesis was largely discarded on empirical and analytical grounds in the three decades after its formulation. Interestingly, it was revived by the work of Grilli and Yang () at the World Bank, who showed that real commodity prices had declined through the twentieth century. These findings triggered a significant flow of empirical contributions.¹⁹ A major conclusion of this literature is that the factors underlying such longterm trends and cycles vary through time, including, in recent decades, for example, the rising Chinese demand for commodities, notably for metals, and that this gives rise to specific features in different periods. Overall, Grilli and Yang’s view that the terms of trade have deteriorated through the twentieth century has been confirmed in the empirical literature. According to Erten and Ocampo (), the adverse trend was stronger in terms of length and intensity for tropical agricultural goods than for temperate-zone agriculture and metals, and short and weak for oil prices. However, there was no adverse long-term trend in the nineteenth century, and there has not been one in the early twenty-first century, where there has been rather an upward trend for metal and oil prices, which will probably come to an end due to the COVID- crisis. In turn, non-oil commodities have experienced four long-term thirty-to-forty-year cycles since the late nineteenth century (the last still ongoing), with substantial overlap among different commodity groups, as they are largely determined by trends in world GDP. The broader macroeconomic effects of commodity dependence should be analysed from both a short- and a long-term perspective. The short-term dimensions are closely associated with the cyclical patterns of commodity prices, which generate fluctuations in income levels, aggregate domestic demand, and the balance of payments. The procyclical patterns of investment tend to be particularly strong, and are enhanced by those of both external and domestic finance (see section .). In commodityexporting countries, financing cycles tend to follow those of commodity prices, and the recent ‘financialization’ of commodity markets has reinforced this pattern. Among the main implications of these cyclical fluctuations are their effects on the real exchange rate. The cyclical fluctuations of this variable tend to reinforce the variations of aggregate demand in economies with net liabilities in foreign currency: real exchange-rate appreciation during booms generates windfall wealth gains that enhance spending, whereas depreciation during crises generates wealth losses, which accentuates the contraction of spending. The distributive effects go in the same direction: if the appreciation benefits workers and the depreciation hurts them, there ¹⁹ See a review of the literature in Erten and Ocampo (), the conclusions of which are summarized in the next paragraph.

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

´  

will also be procyclical effects, given the higher propensity to spend out of wages. As the more traditional macroeconomic literature has argued, the effects of real exchange-rate fluctuations on the current account of the balance of payments will tend to be countercyclical (non-primary exports decreasing and imports rising during commodity booms, and the opposite evolution occurring during crises). However, if there is an initial surplus during the boom (e.g. due to macroeconomic adjustments adopted to manage the previous commodity crisis), or an initial deficit during the crisis (as a result of the strong expansion of aggregate demand during the boom), the initial effect would also be procyclical and the countercyclical effects will come with a lag. In terms of cyclical behaviour, the critical choice for governments is whether to adopt a countercyclical stance, as macroeconomic theory recommends, particularly in its Keynesian variants, or follow a procyclical pattern, associated with either economic or political-economy pressures, or both. In commodity-dependent economies, an important countercyclical instrument is a commodity stabilization fund through which the government saves, during the boom, some of the increased revenues from taxes on commodity sectors and the profits from state-owned enterprises active in those sectors (particularly important in oil and minerals sectors).²⁰ This also helps to mitigate the procyclical effects of commodity prices on real exchange rates if those revenues are kept abroad or saved as foreign exchange reserves by the central bank. There may, however, be strong political pressures to spend those revenues, in which case the procyclical effects of commodity prices will be transmitted in a stronger way to the domestic economy. As we will see in sections . and ., the government’s ability to counteract the procyclical effects of a mix of a commodity boom and procyclical financial flows with countercyclical monetary policy would be limited if there is free movement of capital; the use of some other instruments would, therefore, be necessary. The long-term structural effects of commodity dependence are associated, in turn, with whether the commodity sectors generate strong or weak linkages with other economic activities, and whether commodity dependence is associated with strong or weak productivity growth and learning. In classical analyses of commodity dependence, including those associated with Prebisch and Singer, the basic arguments were that manufacturing generates stronger linkages and is a better mechanism to transmit technical progress. As we have seen, the more recent literature has tended to confirm that rapid economic growth in emerging and developing countries continues to be associated with industrialization drives and, in contrast, that the de-industrialization that Latin America and Africa have experienced in recent decades is an adverse trend. It can be argued in favour of commodity dependence that the opportunities for technical progress and linkages with both the manufacturing and service sectors have been behind the capacity of commodity-dependent developed countries to prosper.²¹ ²⁰ This choice is part of a broader dilemma of how much to save or invest out of commodity booms. For an analysis of this choice in oil economies, see Cherif and Hasanov (). ²¹ One interesting analysis is the comparative history of Scandinavian vs. Latin American historical development, in the essays collected in Blomström and Meller ().

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 , ,   



Pérez () mounts a strong defence of the development opportunities provided to Latin America by its natural resources, arguing that there are ample technological opportunities—biotechnology, nanotechnology, environmentally friendly products— associated with natural resources and the opportunities to exploit the whole value chains of natural resource-intensive sectors. In contrast, states Pérez, Latin America is too far behind in other technology sectors and is no longer a low-wage region. There are also strong complementarities with Asia, an argument that applies even more strongly to Africa, where China is both a major market and investor. The major challenge in both cases is how to diversify into non-commodity sectors, using rising commodity revenues (including those from commodity-producing state-owned enterprises). The long-term effects are not independent of the cyclical effects of commodity dependence. This implies that the structural vulnerabilities associated with commodity dependence are combined with short-term macroeconomic vulnerabilities. Those associated with real exchange-rate fluctuations are particularly important. Real exchange-rate appreciation during commodity booms has a negative effect on noncommodity tradable sectors (both exporting and import competing) during booms— an effect that has been strongly emphasized by the ‘Dutch disease’ literature.²² Firms in non-resource tradable sectors may go bankrupt during commodity booms, generating permanent effects on economic structures and productivity if the latter is associated with production experience (Krugman, : ch. ). The unstable incentives associated with real exchange-rate fluctuations through the business cycle also make the profitability of those sectors highly volatile, reducing investment in structural diversification. Beyond the structural and macroeconomic vulnerabilities mentioned lie other vulnerabilities of a more political-economy or institutional character. In this regard, the literature on the ‘Dutch disease’ has emphasized the institutional effects of the rentierism associated with natural resources. There may also be significant distributive effects associated with land concentration in agriculture and, in the cases of hydrocarbons and mining, high industrial concentration.

. M, F,  S C

.................................................................................................................................. There are two crucial links between macroeconomics, finance, and structural change. The first is the positive contribution made by financial institutions that support innovative sectors with long-term risk capital and lend ‘patient capital’ (Mazzucato, ). Funding can, of course, be external or domestic, with national development banks (NDBs) having an important role to play in domestic financing. The second link, in ²² On the ‘Dutch disease’, see, among many others, Corden and Neary (), van Wijnbergen (), and Krugman (: ch. ).

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

´  

contrast, concerns whether finance risks undermining growth, because it generates boom‒bust macroeconomic cycles—again of external or domestic origin—that may end up in costly crises. Important links between capital flows and structural change are (i) the possible misalignment of exchange rates during booms and (ii) exchange-rate volatility through the business cycle, with a negative effect on innovative tradable sectors. Focusing first on international capital flows, the key question is which of two effects on the domestic economy will prevail. The first is the direct contribution to growth if it leads to higher domestic investment, and particularly to key areas of innovations or domestic competitiveness. The contrasting effect is the risk that growth is undermined because external financing can be consumed, and in that case substitutes domestic savings, but particularly because it is potentially reversible and can lead to ‘sudden stops’ that generate costly crises (Calvo, ). If investment is increased, whether it is channelled to sectors with higher productivity or faster productivity growth will generally depend on domestic economic structures rather than on capital flows as such. From a policy perspective, it may be possible, however, to encourage foreign direct investment which brings technological innovations, increases exports, and/or produces for the domestic and foreign markets with higher domestic value-added contents. Multilateral development banks (MDBs) can also play a role in supporting innovations, including the development of relevant domestic institutions. They can also support activities with significant externalities, notably infrastructure and investments that contribute to combatting climate change. Recent analyses have underscored the role of MDBs and sovereign wealth funds in providing financing to reduce the large infrastructure gaps that characterize the developing world, as well as the full development of infrastructure as an asset class (see, for example, Bhattarcharya et al., ). A major countercyclical role, recognized by all MDBs since the ‒ North Atlantic financial crisis, is that of increasing their lending or investments by their financial corporations in developing countries when international private capital flows experience a major downward swing or a sudden stop. MDBs significantly increased their financing during that crisis and its aftermath (Ocampo, a: table .). All MDBs were also capitalized during those years; two more recent institutions of this type are the Asia Infrastructure Investment Bank (AIIB) and the BRICS’ New Development Bank, in both of which China is playing a leading role. An extensive literature discusses the macroeconomic risks associated with crossborder capital flows and the policies required to manage them. The major risks are the volatility of international private capital flows, the procyclical pattern of country risk premiums, and the contagion that characterize both booms and sudden stops of external financing. The literature has identified a sort of hierarchy of volatility, with FDI being the more stable, and short-term bank lending and portfolio flows more unstable (Rodrik and Velasco, ).²³ These problems are particularly important in ²³ As the IMF (: ch. ) has shown, there is evidence that FDI has also become more volatile, largely because it has become partly financialized. This relates to greater use by multinationals of

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 , ,   



relation to emerging economies, but also affected peripheral Europe during the North Atlantic crisis, and are also increasingly important to low-income countries—the ‘frontier markets’ in current terminology. From a theoretical perspective, the major problem of volatile flows is that they have negative externalities, as individual investors and borrowers do not take into account the effects of their financial decisions on other investors and, overall, on the level of financial stability in a particular country (Jeanne and Korinek, ; Korinek, ). From an empirical perspective, the intellectual battle over the effects of capital market liberalization was settled by a major International Monetary Fund (IMF) study (Prasad et al., ), which showed that it generates stronger business cycles in developing countries, and to a lesser extent in developed countries. This was also a major conclusion of the Commission on Financial Stability convened by the Bank of International Settlements after the outbreak of the North Atlantic financial crisis (BIS, ). Strong evidence also comes from later studies. Gourinchas and Jeanne (), among others, have shown that countries that have grown more are the ones that have relied less, not more, on capital flows for growth, and have therefore run stronger current account balances; this result is, of course, related to the links between competitive exchange rates and growth. The ‘meta-regression’ analysis by Jeanne et al. (: ch. ) also found very limited evidence of a link between financial globalization and growth in the period ‒. In terms of macroeconomic and financial policy, the major implications of these effects are that capital account liberalization generates major risks in emerging and developing countries, and that a proper macroeconomic policy in these countries should include the use of capital account regulations (CARs) to manage the risks of cross-border flows, as part of the broader family of ‘macroprudential’ regulations (Ocampo, a: ch. ).²⁴ Section ., the final section of this chapter, provides an additional discussion of this issue. At the domestic level, the central problem in many (or even most) emerging and developing countries is that their financial markets are thin, that is, they are characterized by the strong prevalence of short-term financial assets and liabilities. This means that long-term financing is limited, forcing firms to rely on short-term loans for their investments, or limiting them to what they can finance with retained profits. From a stability perspective, the major issue is the variable mixes of maturity and currency mismatches in portfolios. This means that, during crises, creditors may not roll over short-term loans, thus generating a liquidity crunch, or may subject domestic borrowers to interest rate increases at a time when their revenues are falling. Domestic bond markets—if they have developed—will also shrink and be subject to shorter maturities and/or higher interest rates. For larger firms that have borrowed abroad, intra-corporate and other international loans to fund subsidiaries, as well as derivatives, both to hedge their exposure, but also to speculate on currencies. ²⁴ I prefer the term ‘capital account regulations’ to ‘controls’, because most are not direct regulation and are rather similar to other prudential regulations.

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

´  

debt ratios will rise if exchange rates depreciate. The limited development of future markets implies that the capacity of agents to cover these mismatches would be very limited. Given the limitations and stability issues that domestic financial sectors face, NDBs play an essential role from both growth and stability perspectives. As argued in Griffith-Jones and Ocampo (), NDBs should have five main functions, which help cover associated market failures: (i) providing countercyclical financing; (ii) promoting innovation and structural change; (iii) financing infrastructure investment; (iv) enhancing financial inclusion; and (v) supporting the provision of public goods, particularly combatting climate change. Function (ii) is particularly important for the topics analysed in this chapter, but other dimensions also potentially are. Function (i) makes development banks an additional instrument of countercyclical macroeconomic policy, and (iii) makes them an instrument of infrastructure financing, two functions we have discussed in relation to MDBs. Promoting small start-ups or SMEs that link to them, as part of the broader objective of financial inclusion (iv), may also be essential for structural change. And many of the activities associated with mitigating and adapting to climate change, included under (v), are innovative activities in themselves. But I will underscore the function of development banks as providers of ‘patient capital’ to support innovative sectors and firms. The failure of private financial markets to deliver adequate long-term funding is behind the history of NDBs in many developing but also developed countries. They are a crucial feature of financial sectors in successful emerging economies like China, India, and the Republic of Korea, but also in prosperous developed countries, notably Germany. After a long period of neglect in the academic and policy literature, they have been the subject of renewed interest by MDBs²⁵ and by policymakers in several developed and developing countries, some of which have created NDBs over the past decade. The evidence from World Bank data indicates that NDBs played a countercyclical role in the wake of the North Atlantic financial crisis (Luna-Martinez and Vicente, ). In turn, Mazzucato and Penna () have argued that there is mounting evidence that NDBs have fostered patient, long-term committed finance for mission-oriented investment in innovative activities. The case studies analysed in Griffith-Jones and Ocampo () corroborate this: the role of KfW, the German development bank, in the development of renewable energy; of the CDB, the Chinese NDB, in nurturing high-tech ventures since the s; of Brazil’s BNDES in financing programmes targeted at hightech firms and promoting a successful venture capital fund; and of the successful start-up programme of CORFO, the Chilean development agency, among others. One of the key features of successful NDBs is, of course, providing leverage to attract private investors and deepen domestic financial markets. The development of new

²⁵ See, for example, the work of the World Bank economists Luna-Martinez and Vicente ().

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 , ,   



instruments, such as guarantees, equity—including venture capital—and debt funds have been major innovations in this regard. Loan instruments continue to be important, though greater emphasis than in the past is placed on second-tier loans. A key is, of course, the long-term character of NDBs’ loans (over  per cent of their lending is for ten years’ maturity or more). In the area of financial inclusion, correspondent stores have also been an important new instrument that can be widely used by commercial banks (Colombia being a success story in this regard). In Mexico, NAFINSA also operates an online reverse factoring system called Productive Chains, which allows SMEs to sell their accounts receivables from large companies to private banks, providing themselves with working capital. Several NDBs have helped deepen financial markets by introducing local currency and green bonds into their local capital market. Expanding the role of NDBs in countries that have them, or creating them in those that do not, would therefore help create a financial system that better serves development needs. These activities should be linked to strong development policies with structural change at their heart, they should have adequate support from macroeconomic policies, and be buttressed by good governance structures that guarantee, in particular, that they are not used for rent-seeking. This does not necessarily imply large government resources, as the only public contributions would be an increase in their paid-in capital and special programmes that governments want to promote. NDBs would then fund their operations on the private domestic market, as well as international capital markets—including through the support of MDBs and their financial corporations.

. P I

.................................................................................................................................. The main conclusion of this chapter is that the key to rapid growth in the developing world is the dynamic efficiency of economic structures, defined as their capacity to generate new waves of innovative activities. The strategies aimed at promoting structural change should be mixed with appropriate macroeconomic and financial policies. They also require appropriate institutional frameworks, the formation of human capital, and the development of infrastructure, but these additional conditions (not analysed here) only serve as the context for the structural transformation and are not in themselves sufficient to guarantee dynamic economic growth. The focus on structural dynamics helps to identify the policy areas and specific institutions that authorities should target to accelerate economic development. The first is encouraging innovations—in the broad sense of the term—and the associated learning processes in the areas of technological development, productive organization, and marketing strategies. In emerging and developing countries, the diversification of production structures that this policy requires may be largely associated with the transfer of sectors of production from the industrialized world. The second policy area is the development of complementarities—backward and forward linkages in

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

´  

Hirschman’s terminology—aimed at guaranteeing that innovations spread through the economy, at the same time ensuring system-wide competitiveness. Non-tradable inputs and specialized services (knowledge, logistics, and marketing services) are particularly important, but tradable inputs also are, as part of a policy aimed at increasing the domestic value added of a given economic activity. An adequate structural transformation strategy should therefore develop a fair balance between individual entrepreneurial initiatives—microeconomic dynamics— and equally appropriate meso-economic processes that diffuse innovations through the economy and help create appropriate complementarities. This includes the establishment of institutions aimed at increasing information and coordination among agents; different mixes of public and private institutions can play that role, according to the tradition of each country. Moreover, different mixes of international, national, and local institutions can play a positive role in this regard. The appropriate strategies should mix horizontal and selective policies. Although a fundamental advantage of the former is their neutrality vis-à-vis individual agents, selective policies must be part of an effective structural diversification strategy that reinforces successful specialization patterns, helps nurture ‘infant sectors’, and creates comparative advantages. These policies must include support for research and development in the relevant sectors, the institutions that link firms in those sectors, their export strategies, and special long-term credit lines from NDBs. Furthermore, when there are limited resources, any ‘horizontal’ policy must be detailed and, hence, necessarily becomes selective. Clear examples are the allocation of resources from funds for technological development and export promotion. Recognizing that there is an implicit selectivity in horizontal policies will lead to a better allocation of resources than a supposedly neutral stance. Under current global conditions, emphasis should be placed on integrating into dynamic global markets and thus on developing competitive export sectors, as well as mixing industrial and competition policies. Incentives should be granted based on performance, generating ‘reciprocal control mechanisms’, to borrow Amsden’s () term. In this regard, the capacity to export is indeed the best control mechanism, as underlined by Oqubay in his contribution to this volume (see Chapter ) and by Cherif and Hasanov ()—and, of course, as the East Asian success stories indicate. The institutional structure that guarantees this should be subject to periodic evaluations, within its learning path.²⁶ A complex issue is the framework of international rules, especially those of the WTO and the wave of bilateral and plurilateral free-trade agreements. In this regard, although priority should be given to taking advantage of the manoeuvring room provided under existing agreements, there is a strong sense that a larger policy space (to borrow the term extensively used in UN debates) should be made available to the governments of developing countries, as policy autonomy has been severely restricted in

²⁶ See also on these issues Hausmann and Rodrik ().

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 , ,   



trade negotiations. In particular, according to the analysis presented in this chapter, they should be allowed to apply selective policies and performance criteria to encourage innovation and create the complementarities that are essential for development. To the extent that the current ongoing trade wars undermine the world trading system, regional integration processes among emerging and developing countries may be particularly attractive. According to our analysis, structural transformation is not a ‘once and for all’ process, but rather a persistent task, as the structural transformation process is continuous and may face obstacles at any stage. To the extent that in developing countries innovative activities are largely the result of the spread of new sectors and technologies previously created in the industrial centres, these activities may be regarded as the new set of ‘infant sectors’ to be promoted—particularly infant export activities. Furthermore, according to the analysis presented here, the process of transformation is by no means smooth: destruction is a constant companion of creation, and structural heterogeneity is a persistent feature that may increase at different stages. Distributive tensions are presumably associated with both factors. In this context, supporting the restructuring of firms in old sectors and regions that concentrate them, avoiding transformation processes that increase structural heterogeneity, and working to upgrade low-productivity activities and generate positive links with highproductivity sectors are critical for achieving a more equitable development process. As part of their broader set of functions, NDBs can play a crucial role in guaranteeing the availability of long-term financing for innovative sectors, and should interact closely with private financial agents. Private investment banking and venture capital can also play a role, but past and recent experience indicates that they do not automatically expand optimally in developing countries. Hence the importance of private financial agents working together with NDBs, which in their turn should help build deeper domestic financial sectors. Access to international financial services of this sort may also be important to guarantee funding of innovative activities, but this may generate a strong bias in favour of multinational and large domestic firms and against small and medium-sized enterprises. Macroeconomic policies should aim, in turn, at smoothing business and investment cycles, and guaranteeing a competitive and relatively stable real exchange rate. Smoothing cyclical commodity price fluctuations and external financing boom‒bust cycles is essential for the relative stability of the exchange rate. Absorbing part of the commodity booms with stabilization funds or taxes is critical for managing the first of these problems, while CARs are essential to regulate the second. The latter should be complemented at the domestic level with regulatory policies aimed at avoiding unsustainable credit booms, and managing the maturity and currency mismatches in portfolios, and the incompleteness of futures markets. NDBs should also be active in the provision of countercyclical financing at the national level, complementing the role played by MDBs at the international level. A competitive exchange rate can be seen as a type of industrial policy, indeed perhaps as the best ‘neutral’ industrial policy, particularly in the face of restrictions

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

´  

on subsidies to production and exports under WTO rules. However, exchange-rate policy alone may fail to encourage diversification: it should be complemented by other industrial policies that increase the elasticity of the aggregate supply of tradables to the real exchange rate. A competitive exchange rate may also benefit sectors, particularly natural resource sectors that should not be subject to specific incentives. This implies that an active exchange-rate policy must be combined with taxes on sectors with no externalities, smaller learning spillovers, and weak domestic complementarities (Guzman et al., ). The stability of the real exchange rate is also essential to provide stable profit incentives, which would help reduce the uncertainties that characterize investment in innovative sectors. The policy interventions necessary to guarantee a competitive and stable real exchange rate should include CARs and exchange-rate management; both aim at facilitating a more positive relationship between international capital flows and macroeconomic management (Ghosh et al., ; Ocampo, , a: ch. ). CARs play the dual roles of both macroeconomic and financial stability tools. As a macroeconomic instrument, they provide greater room for countercyclical monetary policies. During booms, they increase the space needed for contractionary monetary policies while mitigating the exchange-rate appreciation pressures that such monetary policies may generate. During crises, they can create space for expansionary monetary policies while constraining capital flight as well as excessive exchangerate depreciation that would otherwise partly translate into domestic inflation and rising debt/GDP ratios. In turn, when viewed as a financial stability tool, CARs recognize the fact that there is a ‘hierarchy’ of volatility, as reversibility is particularly important for portfolio flows and short-term bank lending. There is a broad consensus in the literature that CARs help improve the composition of capital flows towards less reversible flows, and provide room for countercyclical monetary policies. As Erten and Ocampo () have shown, they also reduce the ‘foreign exchange pressure’ generated by capital flows in emerging and developing countries. All these advantages mean that there is now a broad consensus in the international policy debate that the full liberalization of the capital account is not desirable and that CARs can play a positive macroeconomic role—views that can particularly be seen in the IMF’s ‘institutional view’ on capital account management (IMF, ). CARs can and should be combined with active intervention in foreign exchange markets and effective management of foreign exchange reserves in a countercyclical way: accumulation during booms and use of reserves as a stabilization tool during crises. Countercyclical foreign exchange reserve management has indeed been a widespread practice in emerging and developing countries since the East Asian crisis (Ocampo, a: ch. ). However, the ‘self-insurance’ that they provide is costly, as it involves accumulating an asset that has low yields (foreign exchange reserves) to compensate for the entry of private capital inflows, which have higher costs; if reserve accumulation is sterilized, central banks will also incur losses. CARs are, therefore, a less costly policy instrument, but countries may be reluctant to use them because they

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 , ,   



are seen as a distortion in financial markets, and there may be restrictions on their use associated with investment treaties. In summary, the combination of CARs with exchange-rate and foreign exchange management, the countercyclical monetary policy that they facilitate, and countercyclical fiscal policies, forms the appropriate macroeconomic policy package. Aside from its contributions to countercyclical management, this policy package has long-term development implications, in that it contributes to maintaining a competitive and relatively stable real exchange rate. It creates a positive relation between international capital flows, macroeconomic stability, structural transformation, and economic growth.

A This chapter borrows from the author’s previous work on the subject, and from joint work with Bilge Erten, Stephany Griffith-Jones, Martin Guzman, Codrina Rada, Joseph E. Stiglitz, and Lance Taylor, whose contributions are gratefully acknowledged. In particular, the section on the dynamics of production structures borrows from Ocampo (b) and my analysis of financing issues from my work with Stephany Griffith-Jones (Griffith-Jones and Ocampo ). The author thanks Reda Cherif, Fuad Hasanov, Arkebe Oqubay, Gabriel Porcile, and Rajah Rasiah for comments on a previous draft of this chapter, also Verónica Pérez for her support in its drafting.

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

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 , ,   



Macroeconomics and Development: Roberto Frenkel and the Economies of Latin America. New York: Columbia University Press, pp. –. Ocampo, José Antonio (a) Resetting the International Monetary (Non) System. Oxford and Helsinki: Oxford University Press and UNU-WIDER. Ocampo, José Antonio (b) ‘Dynamic Efficiency: Structural Dynamics and Structural Change in Developing Countries’, in Akbar Noman and Joseph E. Stiglitz (eds) Efficiency, Finance, and Varieties of Industrial Policy. New York: Columbia University Press, pp. –. Ocampo, José Antonio, Codrina Rada, and Lance Taylor () Growth and Policy in Developing Countries: A Structuralist Approach. New York: Columbia University Press. Ocampo, José Antonio and Lance Taylor () ‘Trade Liberalisation in Developing Economies: Modest Benefits but Problems with Productivity Growth, Macro Prices, and Income Distribution’, Economic Journal (): –. Palma, José Gabriel () ‘Four Sources of “De-Industrialization” and a New Concept of the “Dutch Disease” ’, in José Antonio Ocampo (ed.) Beyond Reforms: Structural Dynamics and Macroeconomic Vulnerability. Palo Alto, CA: Stanford University Press, ECLAC, and World Bank, pp. –. Pérez, Carlota () ‘Technological Change and Opportunities for Development as a Moving Target’, CEPAL Review , Santiago. Pérez, Carlota () Technological Revolutions and Financial Capital: The Dynamics of Bubbles and Golden Ages. Cheltenham: Edward Elgar. Pérez, Carlota () ‘Dinamismo tecnológico e inclusión social en América Latina: Una estrategia de desarrollo productivo basada en los recursos naturales’, Revista de la CEPAL : –. Pinto, Aníbal () ‘Naturaleza e implicaciones de la “heterogeneidad estructural” de la América Latina’, El Trimestre Económico (), México, DF: Fondo de Cultura Económica, January–March; reprinted in Cincuenta años del pensamiento en la CEPAL, vol. II, Santiago: CEPAL/Fondo de Cultura Económica, . Prasad, Eswar S., Kenneth Rogoff, S. J. Wei, and Ayhan Kose, M. () ‘Effects of Financial Globalization on Developing Countries: Some Empirical Evidence’. Occasional Paper No. . Washington, DC: International Monetary Fund. Prebisch, Raúl () ‘Theoretical and Practical Problems of Economic Growth’ (E/CN./ ). Mexico City: Economic Commission for Latin America (ECLA). Prebisch, Raúl () Interpretación del proceso de desarrollo latinoamericano en . nd edition. Santiago: ECLAC, Serie conmemorativa del XXV aniversario de la CEPAL. Pritchett, Lant () ‘Divergence, Big Time’, Journal of Economic Perspectives (): –. Pritchett, Lant () ‘Understanding Patterns of Economic Growth: Searching for Hills among Plateaus, Mountains and Plains’, World Bank Economic Review (): –. Rapetti, Martin () ‘Macroeconomic Policy Coordination in a Competitive Real Exchange Rate Strategy for Development’, Journal of Globalization and Development (): –. Rapetti, Martin, Peter Skott, and Arslan Razmi () ‘The Real Exchange Rate and Economic Growth: Are Developing Countries Different?’, International Review of Applied Economics (): –. Razmi, Arslan, Martin Rapetti, and Peter Skott () ‘The Real Exchange Rate and Economic Development’, Structural Change and Economic Dynamics (): –.

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

´  

Rodríguez, Francisco and Dani Rodrik () ‘Trade Policy and Economic Growth: A Skeptic’s Guide to the Cross-national Evidence’, in Ben S. Bernanke and Kenneth Rogoff (eds) NBER Macroeconomics Annual , Vol. . Cambridge: MIT Press, pp. –. Rodrik, Dani () The New Global Economy and Developing Countries: Making Openness Work. Washington, DC: Overseas Development Council. Rodrik, Dani () One Economics, Many Recipes: Globalization, Institutions and Economic Growth. Princeton, NJ: Princeton University Press. Rodrik, Dani () ‘The Real Exchange Rate and Economic Growth’, Brookings Papers on Economic Activity Fall: –. Rodrik, Dani () ‘The Past, Present and Future of Economic Growth’, in Franklin Allen et al. (eds) Toward a Better Global Economy. Oxford: Oxford University Press, pp. –. Rodrik, Dani () ‘Premature Deindustrialization’, Journal of Economic Growth : –. Rodrik, Dani and Andrés Velasco () ‘Short-Term Capital Flows’, in Boris Pleskovic and Joseph E. Stiglitz (eds) Annual World Bank Conference on Development Economics . Washington, DC: World Bank. Romer, Paul Michael () ‘Increasing Returns and Long-run Growth’, Journal of Political Economy (): –. Ros, Jaime () Development Theory and the Economics of Growth. Ann Arbor, MI: University of Michigan Press. Ros, Jaime () Rethinking Economic Development, Growth, and Institutions. Oxford: Oxford University Press. Rosenstein-Rodan, Paul N. () ‘Problems of Industrialization of Eastern and SouthEastern Europe’, The Economic Journal (/): –. Schumpeter, Joseph () Business Cycles. New York: McGraw-Hill. Schumpeter, Joseph () The Theory of Economic Development. Oxford: Oxford University Press. Schumpeter, Joseph () Capitalism, Socialism and Democracy. rd edition. New York: Harper Torchbooks. Singer, Hans W. () ‘The Distribution of Gains between Investing and Borrowing Countries’, American Economic Review, Papers and Proceedings (): –. Solow, Robert M. () ‘A Contribution to the Theory of Economic Growth’, Quarterly Journal of Economics (): –. Solow, Robert M. () Growth Theory: An Exposition. nd edition. New York: Oxford University Press. Stiglitz, Joseph E. and Bruce Greenwald () Creating a Learning Society: A New Approach to Growth, Development, and Social Progress. New York: Columbia University Press. Taylor, Lance () Income Distribution, Inflation, and Growth. Lectures on Structuralist Macroeconomic Theory. Cambridge, MA: MIT Press. Taylor, Lance () ‘Gap Models’, Journal of Development Economics : –. Thirlwall, Anthony Philip (a) The Economics of Development: Theory and Evidence. th edition. London: Macmillan. Thirlwall, Anthony Philip (b) ‘Balance of Payments Constrained Growth Models: History and Overview’, PSL Quarterly Review (): –. van Wijnbergen, Sweder () ‘The Dutch Disease: A Disease after All?’, Economic Journal (): –. Wade, Robert () Governing the Market: Economic Theory and the Role of Government in East Asian Industrialization. Princeton, NJ: Princeton University Press.

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  ......................................................................................................................

                ,                ,              An Evolutionary Perspective .............................................................................................................

 ,  ,   

. I

.................................................................................................................................. I is now generally acknowledged by both economists and economic historians that there is a strong relationship between technical change and economic development. However, the precise causal links are still a matter of debate. Although it is quite intuitive that improvements in the efficiency of production techniques and in product performances may be a determinant or at least a binding precondition of growth in per capita incomes and consumption, ‘what ultimately determines what’ remains debatable. Is it resource accumulation that primarily fosters the exploration of novel innovative opportunities, or, conversely, does innovation drive capital accumulation? Do new technological opportunities emerge mainly from an extra-economic domain (‘pure science’) or are they primarily driven by economic incentives? Should one assume that the institutions supporting technical change are sufficiently adaptive to adjust to the dynamics of market interactions, or, conversely, are they inertial enough to shape the rates and directions of innovation and diffusion? These are obviously quite complex questions. However, the last four decades have seen a profusion of studies on the sources, mechanisms, and patterns of technological innovation, diffusion, and imitation. And the opening of the technological ‘black box’ has often gone hand in hand with important insights into innovation-driven market competition. Business historians have finally achieved some cross-fertilization with (some breeds of) economic theorizing. And institutional understanding of the socio-

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

 ,  ,   

economic fabric of contemporary societies is starting to show fruitful complementarities with economic analyses. A number of these contributions have been made by evolutionist or institutionalist scholars. Indeed, the common threads linking these diverse streams of research highlight the co-evolution of technologies, corporate organizations, and institutions (more in Freeman and Louca, ; Freeman, ; and Reinert, ; but a few of the intuitions are already in the classics of development theory: cf. for example, Gerschenkron, ; Hirschman, ). These threads— linking evolutionary analyses of the microeconomics of innovation and learning all the way to generalizations on some invariant features of the process of development— are the subject of this contribution. It does not claim to be a comprehensive survey, but rather a sort of ‘roadmap’. We start by discussing the theoretical implications of what we know about the dynamics of innovative activities at micro and sectoral levels. Technical change is structured by technological paradigms and follows relatively ordered trajectories. In such a view, knowledge accumulation plays a central role. This view has major implications also for the theory of production. There are firms and countries that are simply ‘better’, that is, more efficient and more innovative, than others, irrespective of relative prices. This implies that technological asymmetries or gaps are permanent features across firms and, even more so, countries. Technical change can be viewed as an evolutionary process with invariances and specificities in patterns of change at sectoral and national level, which in turn can be interpreted in terms of some underlying features of the processes of collective learning, market selection, and institutional governance.

. T F P  T

..................................................................................................................................

.. Technological Paradigms and Trajectories A variety of concepts have been put forward in recent decades to define the nature of innovative activities: technological regimes, paradigms, trajectories, salients, guideposts, dominant designs, and so on. The names are not so important (although some standardization could make the diffusion of ideas easier). More crucially, these are overlapping concepts seeking to capture a few common features of the procedures and direction of technical change (for discussions and references, see Dosi, ; Dosi and Nelson, ). Let us consider some of them. The notion of technological paradigm is based on a view of technology grounded on three fundamental ideas. First, any satisfactory description of what technology is and how it changes must also embody the representation of the specific forms of knowledge

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 ,   ,  



on which a particular activity is based. In other words, technology cannot be reduced to the standard view of a set of well-defined blueprints; rather, it concerns problemsolving activities and also involves tacit forms of knowledge embodied in individuals and organizational procedures. Second, paradigms entail specific heuristics and visions of ‘how to do things’ and how to improve them, often shared by the community of practitioners in each particular activity (engineers, firms, technical societies, etc.) that share common cognitive frames (Constant, ). Third, paradigms generally also define basic models of artefacts and systems, which over time are progressively modified and improved. These basic artefacts can also be described in terms of some fundamental technological and economic characteristics For example, the basic attributes of an airplane are described in terms not only of inputs and production costs, but also on the basis of some salient technological features such as wing-load, take-off weight, speed, distance it can cover, etc. What is interesting is that technical progress seems to display patterns and invariances in terms of these product characteristics. Similar examples of technological invariances can be found, for example, in semiconductors, agricultural equipment, automobiles, and a few other micro-technological studies. Technological trajectories relate to the progressive realization of the innovative opportunities associated with each paradigm which can in principle be measured in terms of the changes in the fundamental techno-economic characteristics of artefacts and the production process. The core ideas involved in this notion of trajectories are the following. First, each particular body of knowledge (i.e. each paradigm) shapes and constrains the rates and direction of technological change irrespective of market inducements. Second, as a consequence, regularities and invariances can be seen in the patterns of technical change that hold under different market conditions and whose disruption is correlated with radical changes in knowledge bases (in paradigms). Third, technical change is partly driven by repeated attempts to cope with the technological imbalances which it itself creates. It is now widely acknowledged in the innovation literature that learning is local and cumulative. Local means that the exploration and development of new techniques is likely to occur in the neighbourhood of the techniques already in use. Cumulative means that current technological development—at least at the level of individual business units—often builds upon past experiences of production and innovation, and it proceeds via specific problem-solving sequences (Vincenti, ). Clearly, this is consistent with the ideas of paradigmatic knowledge and the ensuing trajectories. A crucial implication, however, is that at any point in time the agents involved in a particular production activity will have little scope for substitution among techniques, if by that we mean the easy availability of blueprints different from those actually in use, which could be put efficiently into operation according to relative input prices.

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

 ,  ,   

.. Paradigms, Routines, Organizations A locus classicus in the analysis of the profound intertwining between technological learning and organizational change is certainly Alfred Chandler’s reconstruction of the origins of the modern multi-divisional (the M-form) corporation and its ensuing effects on the American competitive leadership over several decades (Chandler, , a, ). And, as Chandler himself has argued, there are strict links between story and evolutionary theories (Chandler, b). While it is not possible to enter into the richness of the Chandlerian analysis here, let us just recall one of the main messages: It was the institutionalizing of the learning involved in product and process development that gave established managerial firms advantages over start-ups in the commercialization of technological innovations. Development remained a simple process involving a wide variety of usually highly product-specific skills, experience and information. It required a close interaction between functional specialists, such as designers, engineers, production managers, marketers and managers . . . Such individuals had to coordinate their activities, particularly during the scale-up processes and the initial introduction of the new products on the market . . . Existing firms with established core lines had retained earnings as a source of inexpensive capital and often had specialized organizational and technical competence not available to new entrepreneurial firms. (Chandler, : )

These organizational dynamics can be interpreted as an evolutionary story of competence accumulation and development of specific organizational routines (Chandler, b). Did seemingly superior organizational forms spread evenly throughout the world? The Chandlerian enterprise diffused, albeit slowly, through other OECD countries (Chandler, ; Kogut, ). However, organizational forms, strategies, and control methods have developed differently from nation to nation, because of the difference in national environments (Chandler, a: ). Moreover, the diffusion of the archetypical M-form corporation has been limited to around half a dozen already developed countries (and even in countries like Italy, it involved very few companies). Similar differences can be found in the processes of international diffusion of American principles of work organization—for example, Taylorism and Fordism—(for an analysis of the Japanese case, see Coriat, ). A growing literature looks at the early corporate histories of the German, Japanese, or Italian systems of production which continue to influence contemporary forms of organization and learning (see Chandler, ; Coriat, ; Kogut, ; Dornseifer and Kocka, ; Dosi, Giannetti, and Toninelli, ). Different initial organizational conditions, as well as different patterns of learning, can be seen across developing countries. The last three decades have witnessed increased technological dynamics in some of them (in primis China), with a subsequent development of the ‘modern’ industrial structures and an impressive technological catching up. The evolutionary path of technological learning involves both the capacity to acquire technologies (capital goods, know-how, etc.) and the capability to absorb these technologies and adopt them to the local conditions. Microeconomic/micro-technological

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 ,   ,  



evidence highlighting the mechanisms which stimulate and limit endogenous learning in the NIEs suggest the existence of some characteristics in the paths of technological learning at the firm level (see also Cimoli, ; Cimoli and Dosi, ). In particular, one might be able to identify some relatively invariant sequences in the learning processes, conditional on the initial organizational characteristics of the firms and the sectors of principal activity. A first set of regularities regards the varying combinations between acquisition of outside technologies and endogenous learning. As is well known, the transfer of technology to developing economies is a common source for the subsequent development of learning capabilities at the firm and sectoral levels. So, Amsden and Hikino identify the ability to acquire foreign technology as a central characteristic ‘of late industrialization at the core of which is borrowing technology that has already been developed by firms in more advanced countries. Whereas a driving force behind the First and Second Industrial Revolutions was the innovation of radically new products and processes, no major technological breakthrough has been associated with lateindustrializing economies. The imperative to learn from others, and then realize lower costs, higher productivity and better quality in mid-tech industries by means of incremental improvements, has given otherwise diverse twentieth-century industrializers a common set of properties’ (Amsden and Hikino : ).

. T D, M-H,  N

.................................................................................................................................. The notion of paradigm contains elements of both a theory of production and a theory of innovation. Loosely speaking, we should consider such a theory at the same level of abstraction as, say, a Cobb-Douglas production function or a production possibility set. That is, all of them are theories of what are deemed to be some stylized but fundamental features of technology and, relatedly, of production processes. In fact, one finds a few remarkable assumptions underlying conventional production theories. As already mentioned, technologies—at least in a first approximation—are conventionally seen as a set of blueprints describing alternative input combinations. Moreover, at any one time there must be many of them, in order to be able to interpret empirical observations as the outcome of a microeconomic process of optimal adjustment to relative prices. Information about these blueprints is generally assumed to be freely available (unless appropriated through the patent system). Finally, it is assumed that activities leading to the efficient exploitation of existing blueprints can be separated from those leading to the development of new ones (exogeneity of technical progress is its extreme version). Of course, this is only a trivialized account of a family of models that can be made much more sophisticated, by, for example, adding details

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

 ,  ,   

on how blueprints are ordered with respect to each other (more technically, issues like continuity and convexity come under this heading). However, it still seems fair to say that the basic vision of production—also carried over in aggregate growth and development models—focuses on questions of choice among well-defined techniques, generally available to all producers, who also know perfectly well what to do with all the recipes when they see them. The theory of production based on paradigms, however, is based on an opposing set of theoretical building blocks, many of which yield empirically testable hypotheses. Although it undertakes the same interpretations at the same level of generality, it is more in tune with the microeconomic evidence and is directly linked to theories of innovation. The evolutionary theory makes the following predictions: a) At any point in time there is one or very few best-practice techniques which dominate the others irrespective of relative prices. b) Different agents are characterized by persistently diverse (better and worse) techniques. c) Over time the observed aggregate dynamics of technical coefficients in each particular activity is the joint outcome of the process of imitation/diffusion of existing best-practice techniques, the search for new ones and of market selection among heterogeneous agents. d) Changes over time of the best-practice techniques themselves highlight regular paths (i.e. trajectories) both in the space of input coefficients and also in the space of the core technical characteristics of outputs. Catching-up in the productivity distribution is the first fundamental mark of successful catching-up processes more generally (more in Malerba and Nelson, ; Lee and Malerba, ; Landini and Malerba, ). The striking success of China is a case in point. Table . shows the dramatic labour productivity growth in incumbent manufacturing firms in China. The overall productivity of incumbents grew at . per cent per annum between  and . All sectors display positive productivity growth rates, (except petroleum refining, which had negative growth during the – period). Further, note the remarkable differences in productivity growth across sectors, as such circumstantial evidence of significant inter-sectoral differences in absorptive capacities (Cohen and Levinthal, ) of ‘frontier’, generally foreign, technologies, and of corresponding differences in the average catching-up rates. Figure . offers three snapshots of the non-parametric kernel density distribution of labour productivity in China, compared with Italy and France, illustrating the overall technology gap with two higher-income countries.¹ At a first glance readers might find such a comparison as somewhat far-fetched if one has in mind a ‘world production function’,

¹ We chose Italy and France as we have access to comparable micro data. Our informed guess, based on smaller samples like COMPUSTAT and Orbis firm-level evidence, supports the argument that the property applies to all advanced countries, including the United States and Germany.

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 ,   ,  



Table 4.1 Annual growth rate of labour productivity amongst firms over 1998–2007, and subperiods 1998–2002 and 2002–2007 amongst ‘continuing’ firms (i.e. firms remaining in the same two-digit sector over the relevant period) CIC

Sector

1998–2007

1998–2002

2002–07

13 14 15 16 17 18 19 20

Food processing of agricultural products Other foodstuffs Beverages Tobacco Textiles Garments, footwear, etc. Leather, fur, feather, etc. Processing of timber, manuf. of wood, bamboo, etc. Furniture Paper and paper products Printing, reproduction of recording media Articles for culture, education, and sports Processing of petroleum, cokeries, nuclear fuel Raw chemical materials and chemical products Pharmaceuticals Chemical fibres Rubber Plastics Non-metallic mineral products Smelting and processing of ferrous metals Smelting and processing of non-ferrous metals Metal products General purpose machinery Special purpose machinery Transport equipment Electrical machinery and equipment Communication equipment, computers, etc. Measuring instruments and machinery Artwork and other

11.25 8.87 10.63 15.29 9.79 7.84 7.55 11.87

8.55 5.73 6.20 11.08 10.14 4.84 6.52 7.61

13.46 11.22 12.80 10.65 10.54 10.57 10.29 14.43

6.19 10.33 8.92 8.39 3.77 11.40

4.82 9.48 7.54 7.06 -1.61 10.44

10.40 11.75 8.17 10.03 6.36 11.85

8.94 10.31 8.80 5.83 12.76 13.86 12.45

10.64 12.05 7.01 6.43 9.86 12.68 13.73

7.53 8.85 9.39 6.24 14.71 14.14 12.64

5.44 15.40 16.23 12.67 9.51 5.64 9.62 10.01

7.84 13.76 13.09 11.64 8.84 8.37 9.46 9.32

4.32 15.72 15.13 13.05 9.32 3.30 9.57 12.70

9.98

8.73

10.66

21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 39 40 41 42

Average Source: Yu et al. (2015).

possibly multiplied by some country-specific scalar. After all, Chinese wages have been/ are at least an order of magnitude lower than Italian and French ones. As a consequence, one would expect to see the three countries on very different positions on such production functions. But is it really the case? If it were so, one would also expect, first, major differences between China, on the one hand, and Italy and France, on the other, in capital/output ratios—the appropriate proxy for ‘capital intensities’ when

Year 1998

1

China France Italy

Pr

Year 2002

0.1

1

China France Italy

Pr

Year 2006

China France Italy

Pr

0.1

0.1

0.01

0.01

0.01 0.001

0.001 0.001

(log) labour Productivity

(log) labour Productivity

–6 1

–4

–2

0

2

4

Year 1998

6

8

10

–6

1

China France Italy

Pr

0.0001

–4

–2

0

2

4

Year 2002

6

8

10

0.0001

–6

1

China France Italy

Pr

0.1

(log) labour Productivity

–4

–2

0

2

4

Year 2006

0.1

0.01

0.01

8

10

8

10

China France Italy

Pr

0.1

6

0.01 0.001

0.001

(log) labour Productivity

0.001

(log) labour Productivity

(log) labour Productivity

0.0001 –6

–4

–2

0

2

4

6

8

10

0.0001 –6

–4

–2

0

2

4

6

8

10

–6

–4

–2

0

2

4

6

 . Empirical density (Pr, vertical axis) of labour productivities, whole manufacturing of China, France, and Italy, , , and  Note: The first row: constant  prices and exchange rates (IMF source); the second row: PPP adjusted price (World Bank source). Source: Yu et al. ().

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

1

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

 ,   ,  



‘production functions’ differ. And of course one should expect strong correlations between labour productivities and capital/labour ratios within each country and within each sector. Premise to the following discussion: the proxies for capital are very noisy on Italian and French data and just more so on the Chinese data.² Remarkably, what the evidence suggests is rather at odds with the conventional wisdom. First, capital/output ratios also at sectoral levels do not differ very much between China and the two European countries considered (Table .). Indeed they tend to be higher in China. Second, the within-country, within-sector micro correlations between labour productivities (VA/L) and capital/output ratios (K/VA), for whatever proxy for K is used, is robustly negative in China and is mildly negative in Italy and France (statistics available upon request). In other words, labour and capital productivity are strongly positively correlated. Indeed, conventional theories suggest that, given uniform relative prices, one should not expect distribution of productivities at all. However, they are persistently there even in developed countries (more in Syverson, ; Dosi and Grazzi, ) and much more so in developing ones. Third, even within China, labour productivities and capital/labour ratios—as a proxy of degrees of production mechanization/automation—are basically orthogonal (see Figure . for a sector illustration). Overall, the evidence suggests that very little action comes from ‘moving along isoquants’ in response to relative prices. Rather, ‘best practice’ techniques involve a more efficient use of both labour and capital, and relatedly, catching-up fundamentally involves improvements on both dimensions. It is a world of complementarities rather than substitution, in which technology-gaps and learning efforts are both reflected by labour productivity differences, quite independently from relative prices, while TFP proxies might well yield a quite distorted picture of the development process. Indeed, given the ubiquitous complementarities between labour and capital, labour productivities alone turn out to be a robust proxy for the lower bound of ‘true’ efficiency distributions within countries, but also across countries, with the added advantage of avoiding any explicit or implicit hypotheses on interfactor substitutability and capital measurements. In fact, the empirical elasticities of substitutions implied by the negative micro relation between labour productivities and capital/output ratios (i.e. positive correlations between labour and capital productivities) are positive in sign: the isoquants do not look like standard isoquants but are more similar to rays out of the origin. Granted all that, let us now focus on the micro picture offered by the data and its dynamics. First, note the different upper bounds of the three country distributions, as

² Measures of ‘capital’ are at best biased by construction: witness the old ‘capital controversy’ between Cambridge, United Kingdom and Cambridge, MA (more in Cohen and Harcourt,  and Shaikh, ). And more so are measures simply obtained from balance-sheets. In particular, ‘capital’ measures in the case of China (in firm’s balance-sheet) are calculated as the value of fixed capital stock at original purchase prices (these book values are the sum of nominal values for different years).

NACE

Sector

China

Italy

France

1998 173 175 182 193 203 212 221 222 241 243 244 246 251 252 261 266 275 281 284 285 286 287 291 292 294 295 311

Finishing of textiles Carpets, rugs, and other textiles Apparel Footwear Wood products for construction Paper and paperboard Publishing Printing Production of basic chemicals Paints, varnishes, inks, mastics Pharma., med. chemicals, botanical products Other chemical products Rubber products Plastic products Glass and glass products Concrete, plaster, and cement Casting of metals Structural metal products Forging, pressing, stamping of metal Treatment and coating of metals Cutlery, tools, and general hardware Other fabricated metal products Machinery for prod. use of mech. power Other general purpose machinery Machine tools Other special purpose machinery Electric motors, generators, and transformers

2.772 1.672 1.052 1.062 1.477 1.475 3.873 2.559 2.547 1.312 1.707 1.436 1.587 1.614 1.696 2.084 1.113 1.290 1.981 1.113 1.554 1.337 2.041 1.756 2.530 2.177 1.570

China

Italy

France

2002 1.971 1.327 0.785 0.885 0.954 1.367 5.250 2.456 1.784 1.086 1.514 1.167 1.479 1.394 1.442 1.643 0.937 1.176 1.289 0.980 1.068 1.018 1.524 1.321 1.669 1.486 1.200

1.863 0.789 0.620 0.529 0.629 1.123 5.716 2.084 1.049 0.852 1.508 0.707 0.974 1.055 1.079 1.676 0.698 0.870 0.820 0.923 0.940 0.788 1.012 0.905 0.961 0.977 0.767

0.732 0.752 0.268 0.29 0.728 0.824 0.259 0.508 0.977 0.584 0.57 0.588 0.514 0.714 0.579 0.93 0.669 0.433 0.574 0.452 0.471 0.586 0.48 0.323 0.343 0.358 0.369

China

Italy

Francea

1.512 0.987 0.318 0.631 0.744 1.206 0.204 0.797 2.443 0.936 0.83 1.004 1.088 0.991 1.169 1.399 1.127 0.505 0.913 0.762 0.861 0.921 0.76 0.364 0.465 0.585 0.526

1.546 1.055 0.336 0.645 0.736 1.217 0.192 0.792 2.811 1.052 0.837 1.072 1.03 1.035 1.198 1.253 1.128 0.569 0.967 0.803 0.892 0.871 0.714 0.361 0.466 0.614 0.501

2006 0.755 0.775 0.276 0.331 0.734 0.901 0.19 0.566 1.045 0.544 0.623 0.628 0.588 0.795 0.594 0.847 0.815 0.481 0.695 0.515 0.584 0.626 0.491 0.315 0.391 0.337 0.452

0.694 0.688 0.226 0.288 0.763 0.988 0.117 0.562 1.153 0.57 0.656 0.636 0.495 0.818 0.742 0.965 0.734 0.455 0.618 0.467 0.559 0.566 0.408 0.272 0.289 0.332 0.397

1.228 0.891 0.318 0.488 0.773 1.025 0.229 0.700 2.081 0.946 0.666 0.973 0.951 0.969 0.996 1.365 0.886 0.547 0.77 0.673 0.734 0.818 0.674 0.372 0.425 0.520 0.510

(Continued)

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

Table 4.2 Median capital intensity (capital/output ratios) by sector, China, Italy, and France, 1998, 2002, and 2006

Table 4.2 Continued NACE

Sector

China

Italy

France

1998 312 316 343 361 366

Manuf. of electricity distribution and control equip Electrical equipment not e/where classified Parts for motor vehicles and their engines Furniture Manufacturing n.e.c. Mean Median

China

Italy

France

2002

China

Italy

Francea

2006

1.409

1.127

0.781

0.335

0.453

0.352

0.640

0.648

0.553

1.163 1.781 1.293 0.793 1.713 1.578

0.863 1.336 1.092 0.830 1.419 1.305

0.671 1.094 0.798 0.808 1.127 0.914

0.299 0.526 0.593 0.467 0.534 0.520

0.288 0.63 0.61 0.485 0.574 0.586

0.275 0.534 0.564 0.405 0.550 0.561

0.498 1.088 0.633 0.576 0.780 0.717

0.516 1.311 0.674 0.669 0.871 0.814

0.497 1.185 0.722 0.781 0.888 0.820

Note: aData for France in the last column are for 2004. OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

Sources: Yu et al. (2015), CMM, INSEE (on France), and ISTAT-Micro 3 (on Italy).

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi



 ,  ,    10

CIC 131 (1998)

In(VA/L)

5

0

–5

In(K/L) –2

0

2

4

6

8

 . Scatterplot of log (VA/L) versus log (K/L) for corn milling sector (CIC ),  Note: OLS regression: coefficient = . (standard error .), R = ., number of observations = ,. Source: Yu et al. ().

such an impressionistic proxy of different inter-country lags and leads (together of course with different sectoral compositions of output). Second, the width of the support of the distribution of China is much larger, revealing much greater technological asymmetries across Chinese firms. The dynamics of catching-up in China’s manufacturing productivity are associated with (i) a rightward movement of the mean of the distributions; (ii) a corresponding rightward movement of the support; and (iii) as we shall analyse in more detail below, a shrinking of the support itself. Labour productivity distribution is asymmetric and left-skewed. The evolving pattern of the left-tail and that of the right-tail are also different, with a significant left-tail shift towards higher levels of productivity, compared with a relatively mild movement of the right tail. These dynamics match what, in the old development literature, was called a ‘reduction of the dualistic structure economy’ consisting of a shrinking traditional/relatively backward part of manufacturing and an expanding ‘modern’ one which, however, is only just beginning to push ‘frontier technologies’ further. An important piece of evidence on intra-sectoral asymmetries in efficiency and their changes over time is the top-to-bottom ratio of labour productivities. Table . displays the ratio of the th decile over the nd decile for each sector from  to . The ratios decrease in most sectors, indicating a reduction of productivity dispersion, plausibly due both to learning by laggard firms and selection (exit) of the worst performers. The ratios are generally lower in ‘traditional’ ones (CIC – including textile, garments, leather, furniture, paper manufacturing, etc.) and higher in relatively technology-intensive sectors (e.g. transport equipment, electrical machinery, and

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

 ,   ,  



Table 4.3 Ratio of the average labour productivity of the second highest decile over the second lowest decile, China, 1998, 2002, and 2007 CIC

Sector

1998

2002

2007

13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 39 40 41 42

Food processing of agricultural products Other foodstuffs Beverages Tobacco Textiles Garments, footwear etc. Leather, fur, feather etc. Processing of timber, manuf. of wood, bamboo etc. Furniture Paper and paper products Printing, reproduction of recording media Articles for culture, education, and sports Processing of petroleum, cokeries, nuclear fuel Raw chemical materials and chemical products Pharmaceuticals Chemical fibres Rubber Plastics Non-metallic mineral products Smelting and pressing of ferrous metals Smelting and pressing of non-ferrous metals Metal products General purpose machinery Special purpose machinery Transport equipment Electrical machinery and equipment Communication equipment, computers etc. Measuring instruments and machinery Artwork and other

15.62 19.12 14.89 17.05 8.61 6.51 7.80 11.25 9.29 7.44 12.47 6.91 8.82 10.30 10.65 10.05 6.56 8.65 8.32 9.57 9.70 8.36 8.77 12.24 11.69 9.39 13.52 12.38 8.88

11.35 12.20 11.82 22.95 7.01 5.45 7.17 6.91 7.15 6.16 9.49 6.10 12.26 9.19 9.71 6.87 7.49 7.18 7.91 8.58 8.43 7.21 6.68 9.59 8.19 7.71 11.08 9.00 7.38

10.02 9.04 9.06 26.44 6.07 5.42 6.80 6.51 6.93 6.27 6.12 5.52 11.23 8.42 8.96 7.98 7.42 7.02 8.23 8.40 12.72 7.12 6.56 7.25 7.09 8.24 8.36 8.70 6.59

Source: Yu et al. (2015).

communication equipment). The ratios drop more rapidly in the first part of the period under consideration, which is also a period of retreat by SOEs from the so-called ‘competitive sectors’. At the same time, the ratios in several ‘heavy industries’ such as petroleum refining and non-ferrous metals sectors grows, hinting at some sort of persistent ‘dualism’ within these industries (note that growing intra-sectoral asymmetries can and often do go hand in hand with high average growth rates). How much of the dynamics in overall productivity distribution is due to inter-sectoral relocation of production? Table . displays the time series of value-added shares of each two-digit sector in overall manufacturing. It is remarkable that relatively little structural change has

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi



 ,  ,   

Table 4.4 Contribution of each two-digit sector to total manufacturing value added, China, 1998, 2002, and 2007 (percentages) CIC

Sector

1998

2002

2007

13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 39 40 41 42

Food processing of agricultural products Other foodstuffs Beverages Tobacco Textiles Garments, footwear etc. Leather, fur, feather etc. Processing of timber, manuf. of wood, bamboo etc. Furniture Paper and paper products Printing, reproduction of recording media Articles for culture, education, and sports Processing of petroleum, cokeries, nuclear fuel Raw chemical materials and chemical products Pharmaceuticals Chemical fibres Rubber Plastics Non-metallic mineral products Smelting and pressing of ferrous metals Smelting and pressing of non-ferrous metals Metal products General purpose machinery Special purpose machinery Transport equipment Electrical machinery and equipment Communication equipment, computers etc. Measuring instruments and machinery Artwork and other

4.74 2.07 3.51 5.70 6.39 3.02 1.78 0.82 0.50 2.11 1.21 0.92 3.56 7.18 2.95 1.19 1.33 2.35 6.03 6.47 2.08 2.98 4.75 3.33 7.41 5.94 7.39 1.25 1.05

4.50 1.99 2.69 5.13 5.81 2.76 1.76 0.86 0.53 2.17 1.11 0.77 3.79 6.96 3.29 0.91 1.12 2.47 5.20 6.92 2.24 2.86 4.51 3.09 8.54 6.12 9.64 1.23 0.99

4.96 1.99 2.01 3.11 5.23 2.41 1.58 1.16 0.69 1.86 0.74 0.60 3.52 7.78 2.45 0.86 1.02 2.28 5.18 9.52 4.58 3.21 5.46 3.25 7.54 6.47 8.44 1.24 0.86

Total

100

100

100

Source: Yu et al. (2015).

occurred over the period under investigation, even if indeed in the ‘right direction’. So, for example, the shares of transport equipment, electrical machinery and equipment, and communication equipment, computers etc. are among the highest from the start of the period under consideration, and their total share just increases from . per cent in  to . per cent in . A synthetic view of the relative importance of the within- vs. between-sectors contributions to productivity growth is presented in Table . (for details on the shift-and-share decomposition method of productivity growth, see Appendix). Of course, the precise relative measures of sector-specific learning vs. structural change (what nowadays is often referred to as ‘re-allocation’) depend a great deal on

Table 4.5 Within-sector learning vs. structural change in productivity growth CIC Sector

P0

PT

Annual growth (%)

Intra (%)

Shift (%)

Total (%)

1998–2002

PT

Annual growth (%)

Intra (%)

Shift (%)

Total

2002–7 74.30

16.25

4.20

62.07 86.33 634.26 35.63 30.34 34.54 44.51

15.18 14.46 19.41 17.16 6.41 7.39 14.45

43.45 55.11 59.63

0.02

165.12

17.32

5.49

0.00

5.49

1.70 0.01 2.57 0.00 6.05 0.00 5.78 0.00 1.05 –0.91 0.73 –0.46 0.68 –0.06

1.71 62.07 128.80 2.57 86.33 174.04 6.05 634.26 1448.41 5.78 35.63 76.19 0.14 30.34 55.73 0.27 34.54 55.62 0.63 44.51 94.47

15.72 15.05 17.96 16.42 12.94 10.00 16.24

2.16 0.00 2.32 0.00 4.79 0.00 6.41 0.00 2.40 –0.56 1.22 –0.87 1.14 –0.42

2.16 2.32 4.79 6.41 1.85 0.36 0.72

7.65 19.23 18.29

0.22 –0.07 2.29 0.00 1.22 0.00

0.15 2.29 1.22

43.45 55.11 59.63

67.52 132.98 111.41

9.22 19.26 13.32

0.42 –0.67 2.77 0.00 0.95 0.00

–0.25 2.77 0.95

31.23

5.87

0.30 –0.27

0.03

31.23

53.91

11.54

0.65 -0.16

0.49

109.05 67.52

12.92 21.60

2.16 8.75

2.16 109.05 8.75 67.52

126.24 175.35

2.97 21.03

0.37 10.18

0.00 0.00

0.37 10.18

87.29 76.35 53.94 56.05 38.50 80.27

18.05 13.97 17.96 12.61 15.53 23.40

3.21 0.17 0.87 0.00 1.24 0.00 1.73 –0.03 4.96 0.00 8.70 0.00

3.38 0.87 1.24 1.70 4.96 8.70

150.83 158.49 98.40 85.31 108.60 208.33

11.56 15.73 12.78 8.76 23.05 21.01

2.21 0.00 0.92 0.00 0.92 0.00 1.43 –0.41 8.28 0.00 10.10 0.00

2.21 0.92 0.92 1.02 8.28 10.10

0.00 0.00

4.22

74.30

87.29 76.35 53.94 56.05 38.50 80.27

(Continued)

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

13 Food processing of agricultural 40.68 products 14 Other foodstuffs 35.26 15 Beverages 50.30 16 Tobacco 311.94 17 Textiles 18.91 18 Garments, footwear, etc. 23.66 19 Leather, fur, feather, etc. 25.97 20 Processing of timber, manuf. of 25.94 wood, bamboo, etc. 21 Furniture 32.34 22 Paper and paper products 27.27 23 Printing, reproduction of recording 30.45 media 24 Articles for culture, education, and 24.85 sport activity 25 Oil refining, coking, nuclear fuel 67.07 26 Raw chemical materials and 30.88 chemical products 27 Pharmaceuticals 44.94 28 Chemical fibres 45.25 29 Rubber 27.85 30 Plastics 34.86 31 Non-metallic mineral products 21.61 32 Smelting and processing of ferrous 34.62 metals

P0

CIC Sector

P0

PT

Annual growth (%)

Intra (%)

Shift (%)

Total (%)

1998–2002 33 Smelting and processing of nonferrous metals 34 Metal products 35 General purpose machinery 36 Special purpose machinery 37 Transport equipment 39 Electrical machinery and equipment 40 Communication equipment, computers, etc. 41 Measuring instruments and machinery 42 Artwork and other Whole manufacturing

P0

PT

Annual growth (%)

Intra (%)

Shift (%)

Total

2002–7

31.86

66.44

20.17

2.47

0.00

2.47

66.44

208.07

25.65

31.22 22.60 18.94 35.19 40.51

52.69 51.26 47.35 85.62 71.58

13.98 22.72 25.74 24.89 15.29

2.27 –0.04 6.01 0.00 4.73 0.00 11.35 0.00 5.13 0.14

2.22 6.01 4.73 11.35 5.26

52.69 51.26 47.35 85.62 71.58

78.37 145.54 144.79 202.69 116.70

68.28

123.44

15.96

7.53

9.51 123.44

31.29

58.45

16.91

1.21 –0.01

1.20

22.46 32.73

34.29 62.90

11.15 17.74

0.68 –0.25 0.43 99.89 0.21 100.00

1.98

4.70

0.01

4.70

8.26 23.21 25.05 18.81 10.27

1.52 –0.60 9.00 –0.10 6.01 0.00 11.73 0.00 4.30 –0.69

0.92 8.90 6.01 11.73 3.61

116.55

–1.14

–0.75 –0.05

–0.81

58.45

129.34

17.22

1.70 –0.06

1.63

34.29 62.90

74.24 126.15

16.71 14.93

1.25 0.00 1.25 104.58 –4.58 100.00

Note: P 0 is the aggregate productivity in the first year of the period. PT is the aggregate productivity in the last year of the period. Unit: 1000 yuan at 1998 constant prices. ‘Annual growth’ is the compound annual growth rate of aggregate labour productivity. ‘Intra’ is the percentage contribution of within-sector productivity growth to overall aggregate productivity growth. ‘Shift’ is the percentage contribution of between-sector employment reallocation to overall aggregate productivity growth. Total is the overall contribution (i.e. the sum of ‘Intra’ and ‘Shift’ effects) of each two-digit sector to aggregate productivity growth. The row ‘Whole manufacturing’ shows the contribution of ‘Intra’ and ‘Shift’ effects for the aggregated manufacturing sector. Sectors with zero shift effects are the shrinking ones. (For details on the shift-and-share decomposition method of productivity growth, see Appendix). Source: Authors’ elaboration on CMM data.

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

Table 4.5 Continued

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

 ,   ,  



the techniques of measurement (e.g. whether the sectoral weights are in terms of employment or value added). So, for example, Paus () finds a contribution of the latter of around  per cent. However, no matter the measure, the ‘within component’ dominates—a sign indeed that China achieves quite early a ‘modern’ industrial structure. However, as we shall discuss later, this is an exception in the overall picture of catching-up experiences. Interestingly, this evidence seems to contradict Kuznets’ view of increasing productivity due to a large extent to structural change, that is, movements from lowproductivity sectors to high-productivity ones also within manufacturing. On the contrary, our evidence suggests that, unlike what happened in the s (cf. Wang and Szirmai, ; see also Akkemik, ), the movement of the overall manufacturing means is mainly due to sector-specific dynamics. Incidentally, note that ‘virtuous’ structural change is by no means automatic or inevitable. Indeed, the apparent failure to undertake that path appears to be at the heart of the middle-income trap which, for example, Latin American countries have experienced: more in Paus (). Of course, the relative stability of sectoral shares at the two-digit sectoral level does not rule out much more turbulence at finer levels of disaggregation within each twodigit sector: indeed, there is very intensive ‘micro structural change’. However, the evidence marks a difference from other episodes of industrialization and catching-up, in that in the period of our observations, China appears to be already quite mature in terms of its broad manufacturing structure. For example, when South Korea had the same real per capita income that China had in , which was in  (Maddison’s historical statistics, www.ggdc.net/maddison/oriindex.htm), the share of around  per cent of textile and clothing in total manufacturing was around  per cent (World Development Indicators database), compared to a  Chinese share of  per cent. In the literature a quite common claim is that export and productivity growth go together (possibly with causality running in both directions). China displays a dramatic rise in the share of exports in total manufacturing output, coupled with a dramatic growth in productivity. However, the case of China lends little support to the notion of ‘learning by exporting’. Figure . shows the labour productivity distribution of exporters and non-exporters for the years  and  in selected sectors (chemical, electrical machinery, and communication equipment), which illustrates a more general pattern. Note that in  exporters have a higher level of productivity and their support of distribution is narrower than that of non-exporters. However, a significant catch-up by non-exporters takes place, so that in , exporters and non-exporters have similar productivity distributions and similar widths of support.³

³ We are currently exploring the conjecture that within the overall pattern of fast learning by Chinese manufacturing, many ‘non-frontier’ firms found it easier to enter export markets following the accession of China to the WTO.

0

2

8

0

2

4

6

8

–4

–2

–6

–4

–2

exporter non-exporter

–6

exporter non-exporter

0

0

2

2

6

4

6

CIC 39 (2003)

4

CIC 37 (2003)

8

8

0.001 –8

0.01

0.1

1

0.001 –8

0.01

0.1

1

–4

–2

–6

–4

–2

exporter non-exporter

–6

exporter non-exporter

0

0

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2

6

4

6

CIC 39 (2007)

4

CIC 37 (2007)

8

8

 . Empirical density of (log) labour productivity of exporters and non-exporters of transport equipment (CIC ) and electrical machinery and equipment (CIC ) sectors in selected years (, , and ) Source: Yu et al. ().

–2

0.001 –8

–4

0.001

–6

0.01

1

–8

0.01

–8

6

CIC 39 (1998)

4

0.1

exporter non-exporter

–2

0.1

1

–4

0.001

–6

0.001

–8

0.01

1

0.01

CIC 37 (1998)

0.1

exporter non-exporter

0.1

1

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

 ,   ,  



. S G I I

.................................................................................................................................. From a theoretical point of view, the above argument implies a radical de-linking of income distribution, production theory, and development. Conventionally, there is an obvious link between technological conditions, input availabilities, and remuneration. It is well known that if production functions are well behaved (homogeneous, degree-one, hence no increasing returns, etc.), relative scarcities determine relative input intensities. And if the estimates fall short of fully ‘explaining’ output, then that goes under the heading of the famous ‘Solow residual’, also renamed as Total Factor Productivity. The consequences also for trade theories are straightforward: The HeckscherOhlin-Samuelson theorems easily follow. And what about the interpretation of why per capita incomes differ so much across countries? Over the last few decades a disproportionate amount of effort has gone into the search for arguments to add to the Kamasutra of variables entering the ‘production function’ (nowadays not only questionable proxies for ‘culture’ and ‘institutions’ but also sinister notions like ‘genetic endowments’). Here we have taken the opposite route and explored the implications for development of ‘opening up the black box of technology’, to use the felicitous definition of Nate Rosenberg. Within the black box, there are no production functions, and even less so, CobbDouglas ones, but rather painstaking efforts aimed at knowledge accumulation, nested in more or less supportive organizations and institutions.

. S C   F F  C U

..................................................................................................................................

.. The Evolution of Technological Capabilities and Production Specializations With the mentioned partial exception of China—which in a sense entered the catchingup phase already ‘mature’ in terms of sectoral composition of output—most countries undergo major transformation in the sectors in which they operate and in the products they manufacture (and China is no exception). However, not every country is successful, with many remaining in the ‘middle-income trap’. In many respects, catching-up entails ‘climbing up the ladder’ not only of production efficiency—well captured by the dynamics in the productivity distributions discussed in section .—but also of product complexities and product demand elasticities.

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi



 ,  ,   

To recall a discussion of the s, the impact on competitiveness and growth of producing potato chips is not identical to that of producing computer chips! In turn, the climbing up is associated with the accumulation of technological and organizational capabilities, often against the country’s comparative advantages. That is, absolute technological levels (and not comparative ones) are a fundamental driver of trade performance, growth, and, ultimately, welfare. To clarify the point, Cimoli et al. (a) describe a thought experiment of opening up trade between a ‘Stone Age economy’ and an ICT-based one. As Ricardo would argue, the country coming from the Stone Age will be more likely to export ‘stone-intensive’ products in which it has a comparative advantage (and vice versa for the ICT-based economy with, say, computers). However, there could be no bilateral trade at all if the more advanced ICT economy will end up producing almost anything worth trading irrespective of the stone- or ICT-intensities of the products. What really matters for economic growth might ultimately be absolute levels of technological capabilities and how they interact with world demand for products. An interesting measure in this respect of the ‘fitness’ of a country in terms of the ‘complexity’ of the products in which it specializes as a predictor of its growth potential is presented in Tacchella et al. () and Cristelli et al. ().⁴ Comprehensive historical overviews of successful cases of structural transformation and industrialization is provided by Moses Abramovitz () and Ha-Joon Chang (). The most telling cases of successful latecomer industrialization are probably the United States, Germany, and more recently Japan, South Korea, and China. It was the First Secretary of the US Treasury, Alexander Hamilton, who systematically elaborated the infant industry argument in . In a nutshell, Hamilton argued that foreign competition would have prevented domestic industries from becoming internationally competitive, unless the state had intervened to compensate initial losses or to enforce import duties (Hamilton, ). American industries ended up being literally the most protected in the world until after the Second World War (Chang, ); needless to say, this goes a long way in explaining the US pattern of structural change. Furthermore, the role of the Federal Government in industrial development has been substantial even in the post-war era, thanks to extensive defence-related procurement and mission-oriented research (Mazzucato, ; Mowery, ). Similarly, List () lucidly discusses the shortcomings of simply adhering to comparative advantages: in his view, the true objective of Britain trying to impose free trade on Europe was simply ‘kicking away the ladder’ that they themselves had climbed (Chang, ). The German experience also points to the importance of ad hoc institutional innovations which facilitated catching-up and were the basis of the successive forging ahead with respect to Britain. Of particular importance was the introduction of the Humboldtian university model for the education of graduate engineers, which supplied human capital that proved essential for the diffusion of in-house industrial R&D ⁴ A germane attempt, characterized however by a few technical drawbacks, is in Hidalgo and Hausmann ().

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

 ,   ,  



departments (Dosi et al., ). Another pillar of German industrialization was the emulation of imported British machine tools (often thanks to British craftsmen attracted to Prussia; Freeman, ). More recently, Japan (Freeman, ) and the Asian Tigers (Nelson and Pack, ) were able to reap the benefits of rapidly growing markets for industrial machinery embodying ‘frontier’ knowledge. At the heart of the Japanese success lay the explicit decision by Japanese political authorities to neglect the ‘natural’ development path implied by comparative advantages (Freeman, ). In just a few years, Japan ceased being an importer of foreign technology and developed important indigenous innovation capabilities, even surpassing the United States in terms of R&D efforts. The secret of its success was building up one of the most successful innovation systems (which inspired the formulation of the concept itself, see Freeman, ), in which long-term planning by the Ministry of International Trade and Industry (MITI) fostered learning and spurred innovation in the export-led industrial complexes. The classic works mentioned above are detailed case studies of single countries and their historical experience. More recently, research leveraging natural quasiexperiments and new estimation techniques has allowed the precise causal identification of the effects of sectoral policies. For instance, China’s th Five-Year Plan (–) promoted shipbuilding as a strategic industry for defence-related purposes. Kalouptsidi () finds that the reduction in production costs associated with the policy explains China’s massive gains of global market share in ships: without the targeted subsidies, China’s production would be cut to less than half. Lane () studies the Heavy Chemical and Industry (HCI) policy that South Korea enacted in  as a response to the US troop withdrawal. Again, targeted industries were chosen for their military importance, and the comparison with otherwise similar industries shows that the policy promoted rapid development that lasted long after the measures were removed. Interestingly enough, downstream sectors also benefited from the lower prices induced by the policy, an instance of the policy-induced industrial externalities that Hirschman () termed ‘forward linkages’. The HCI entailed both industrial subsidies and targeted trade protection. Nonetheless, it must be noted that in certain situations trade protection alone can be sufficient to change the patterns of trade and allow industrialization. Juhasz () documents that the temporary protection from British imports caused by the Napoleonic Blockade was fundamental for the accumulation of technological capabilities in nineteenth-century France. The mechanized cotton-spinning industry rapidly developed in French départements that received more sheltering, in accordance with the predictions of the infant industry argument. Hanlon () complements this evidence by looking at production input advantages, instead of output market protection. Using twentieth-century metal shipbuilding data, he shows that even a temporary cost advantage can become the source of long-lasting competitive advantage due to dynamic localized learning effects and learning-bydoing. Head () studies the effects of infant-industry protection in the rail steel industry. And the list could be very long.

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi



 ,  ,   

Let us turn to the role of policies. Here we end by simply noting that technological catching-up (and of course straightforward innovation) goes hand in hand with organizational innovation.

. T C R  I P

.................................................................................................................................. Some general patterns can be distilled from these historical cases. (More in Cimoli et al., a, and especially c and d. For quite germane policy considerations cf. Paus, ; Reinert, .)

.. Emulation and, sometimes, Leapfrogging as a General Principle Inspiring Policies Emulation—to borrow Reinert’s () term—is the purposeful effort of imitation of ‘frontier’ technologies and production activities, irrespective of the incumbent’s comparative advantage profile. It often involves explicit public policies aimed at doing what rich countries are doing in terms of production, and it always involves microeconomic efforts—on the part of individuals and, more so, firms—to learn how to do things others in frontier countries are already able to do. It is a familiar story over the last three centuries. It dates back at least to the case of England vis-à-vis the Low Countries in the period preceding the Industrial Revolution, and it applies all the way to contemporary Chinese industrialization. Emulation primarily concerns products and processes based on new technological paradigms. At one time it meant mechanized textile production and the construction of related machines. Later it was steel production, electricity-based products and machinery, and the internal combustion engine. Nowadays it has to do first and foremost with information and telecommunication technologies, biotech, and nanotechnologies. It has sometimes happened that catching-up countries not only emulated the leading ones, but ‘leapfrogged’ them in some of the newest, most promising technologies. This occurred in the nineteenth-century United States and Germany, which forged ahead of England in electromechanical engineering, consumer durables, and synthetic chemistry. But why should everyone emulate frontier technologies in the first place, rather than being guided by one’s own ‘comparative advantages’? Or, as the sceptics often put it, isn’t it absurd to suggest that everybody should specialize in ICT production? We have answered this question above. Typically, relatively backward economies display an absolute disadvantage in everything, that is, they are less efficient in the production of

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

 ,   ,  



every commodity, and in fact the disadvantage in many commodities is likely to be infinite in the sense that they are not able to produce them at all. Catching up entails closing the gap in production knowledge and learning how to produce novel goods (which in the beginning are generally novel only for the catching-up country, even if ‘old’ for the world). This is particularly important with respect to new technological paradigms because such technologies are most often general purpose: they influence most production activities directly or indirectly. In the past this was the case for mechanical engineering and electricity as it is today for ICT technologies. Moreover, goods and equipment based on the new technological paradigms generally entail higher elasticity of demand and richer opportunities for further technological advance (cf. Dosi, Pavitt, and Soete, ; Castaldi et al., ; Cimoli et al., b). Hence emulation of frontier countries in these activities implies, other things being equal, higher growth possibilities and greater potential for productivity growth and, eventually, domestic product innovation.

.. The Complementarity between Technological Learning and the Development of Production Capacity We have emphasized above the difference between technological knowledge and pure information, with important implications in terms of ‘stickiness’ and difficulty in the transmission of the former—embodied as it generally is in specific people, organizations, and local networks. One consequence of this is that learning rarely occurs ‘offline’, especially in the initial phases of industrialization. Rather, it goes together with the acquisition of production equipment, and with the efforts of learning how to use it and how to adapt it to local conditions (more in Bell and Pavitt, ). In turn, this goes hand in hand with the training of workers and engineers and the professional development of managers capable of efficiently running complex organizations. These are also reasons why it is dangerous to see industrialization, even in its early stages, simply as a matter of ‘diffusion’, or the turnkey adoption and use of equipment acquired from abroad, all the more so when the technologies are in the form of blueprints or licences requiring much painstaking local learning. Of course, no policymaker is in a position to fine-tune the details of the production activities and patterns of learning which the economy has to exploit. The details of the actual dynamics depend a good deal on the details of corporate strategies—and chance. There was no way, for example, that the Korean policymakers could know or even less ‘plan’, say, a learning push in semiconductor memories rather than microprocessors. However, policymakers should be acutely aware of the fact that future capabilities build upon, refine, and modify incumbent ones: hence the policy goal of building good pathdependencies (the point resonates with similar advice by Hausmann and Rodrick () regarding patterns of product diversification along the development process).

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi



 ,  ,   

Two fundamental caveats must be kept in mind. First, a useful distinction can be made between production capacity—the knowledge and organizational routines needed to run, repair, and incrementally improve existing equipment and products—and technological capabilities—the skills, knowledge, and organizational routines needed to manage and generate technical change (Bell and Pavitt, : ). The kinds of activity that foster the accumulation of the latter increasingly involve also specialized R&D laboratories, design offices, production engineering departments, etc. Second, and relatedly, ‘while various forms of “doing” are central to technological accumulation, learning should not be seen simply as a doing-based process that yields additional knowledge simply as the by-product of activities undertaken with other objectives. It may need to be undertaken as a costly, explicit activity in its own right: various forms of technological training and deliberately managed experience accumulation’ (Bell and Pavitt, : ). Interestingly, the transition from the production capacity phase to the technological capabilities phase has been managed superbly by countries like Korea and Taiwan and it is where, on the contrary, most Latin American countries got stuck.

.. The Necessity of Nurturing Infant Industries Consider again the caricature of a Stone-Age economy and an ICT economy and allow them to interact. Two properties are quite straightforward. First, the patterns of economic signals will be biased in favour of stone-intensive product in one country, and ICT-intensive in the other (their current ‘comparative advantages’). Hence, if the former wants to enter the ICT age, it has to purposefully distort market signals as they come from international exchanges (on the assumption that there are some: it could well be that the ICT economy is unwilling to absorb any stone product!). Second, it is quite unlikely that the stone producers, even under the ‘right kind of signal’, will be able to instantly acquire the knowledge to competitively produce ICT products. Certainly, all individuals take a long time to learn new skills. Turning violinists into football players and vice versa is rather hard, if possible at all. And this applies even more so to organizations and organization-building. Even when transformations are possible, they require time, nurturing, and care. If a newly born violinist, ex-footballer, is made to compete with professional violinists, he will make a fool of himself. If a catching-up company is suddenly made to compete with world leaders it will most likely disappear. Often, it is a daunting enough task to learn how to make—no matter how inefficiently—a product which might indeed be rather standard in technologically more sophisticated economies: demanding competitive efficiency as well is like asking the violinist to run  metres in around ten seconds after some quick training rounds. Safeguarding the possibility of learning is the basic pillar of the infant industry logic. On the incentive side, market signals alone are often not enough, and indeed they frequently discourage the accumulation of technological capabilities in so far as they

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

 ,   ,  



ought to occur in activities currently displaying significant comparative disadvantages and thus also unfavourable current profitabilities. Incidentally note, also, that the existence of financial markets is a meagre instrument, if of any use at all, for translating a future and uncertain potential for learning into current investment decisions (more in Stiglitz, ). Thus, there are also sound learning-related reasons why, as the historical evidence shows, just prior to industrial catching-up, average industrial import tariffs are relatively low; they rise rapidly in the catching-up phase, and they fall after mature industrialization. Indeed, it is during the catching-up phase that the requirement to distort (international) market signals is more acute, precisely because there are young and still relatively fragile learning infants. Beforehand, there are no infants to speak of. Afterwards, there are adults able to swim into the wild international ocean by themselves. Doing so, however, involves more than just ‘signal distortion’. As many of the Latin American experiences have shown, this is far from enough. Partly it has to do with the fact that many forms of protection entail the possibility of learning but not, in the language of Khan and Blankenburg (), the compulsion to innovate as distinct from the sheer incentive to just exploit a monopoly rent, no matter how inefficient and lazy the potential ‘learner’. Partly, it has to do with the capabilities accumulation and the characteristics of the actors involved. (An archetypical example of purposefully ‘getting signals wrong’ and fostering capability accumulation is Korea: see Amsden, .) After all, even with the best of intentions and incentives, our violinist will not only take time to learn but will actually be able to develop his/her football skills only as part of a team. The team, in turn, will most often not be the making of sheer self-organization, especially when production entails relatively complex products, as it usually does. At the same time, violinists might not be the best candidates for playing football, irrespective of the incentive structure. Moving away from the metaphor, industrialization might have little to do with simply the award of property rights and with the establishment of firms as legal entities. It is quite misleading to think that the world is full of evenly distributed sources of technological knowledge just waiting to be exploited—the lag being due mainly to institutional and incentive-related forces. On the contrary, irrespective of the opportunities for the entrepreneurial exploitation of technological knowledge, which the ‘international knowledge frontier’ notionally offers, the fundamental gap is about the lack of capabilities to explore and exploit them. This is a crucial bottleneck for development. Even casual visitors to developing countries (whenever they walk out of hotels paid for by the IMF!) notice these gaps— which in the early stages of development concern even rather basic activities such as accessing the Internet or processing a credit card payment. They apply much more to firm-level capabilities such as drilling an oil well (or, in the early stages, even keeping an existing well working). As discussed in several contributions to Cimoli, Dosi, and Stiglitz (a), ‘horizontal’ education and training policies, together with technical support given to firms by public institutions, can go a long way to enhance capabilities. But even that is not likely to be enough. Policies are often bound to get their hands dirty with respect to the nature, internal structure, and strategies of a few

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi



 ,  ,   

corporate agents themselves. Fostering the emergence of, and occasionally explicitly building, technologically and organizationally competent firms are fundamental infant nurturing tasks. In fact, even the most developed countries only boast a fraction of technologically dynamic organizations within a much greater population of firms. (Note that all this applies to both ‘high tech’ and ‘low tech’ sectors as conventionally defined.) In a sense, industrialization involves changing the distribution between ‘progressive’ and ‘backward’ firms. Indeed, all this might not be enough: the state in the past often had to do more than just ‘pushing and pulling’ entrepreneurs into certain strategic sectors, and ended up acting as ‘entrepreneur of last resort’. We believe that this continues to be the case today. Indeed industrial policies for development and catching up are likely to involve the following ‘capital sins’ which the market faithful are supposed to avoid: (i) state ownership; (ii) selective credit allocation; (iii) favourable tax treatment for selected industries; (iv) restrictions (or some conditionalities) on foreign investment; (v) local context requirements; (vi) special IPR regimes; (vii) government procurement; and (viii) promotion of large domestic firms. (Dahlman, , discusses them for China and India, but the lessons are more general.) In a nutshell, this is the full list of the capital sins which the market faithful are supposed to avoid!

.. Industrial Policies in a Sino-centric World: Some Conclusions A combination of ‘infant nurturing’ measures has been a major ingredient of development policies throughout the history of industrialization, and it continues to be so today. Historically, the ‘infant learners’ had to be shielded in the domestic markets and helped in the international ones in their interactions with the more efficient and more innovative firms from ‘frontier’ countries. This happens to a large extent to also hold today. However, the unique feature of the current ‘Sino-centric’ world—as Castro () puts it—is that many catching-up countries are caught between a rock and a hard place: the developed world is still ahead of them, but at the same time China is rapidly eliminating its absolute disadvantages across the board, both in more traditional productions and in activities based on the newest technological paradigms. And it is doing so at a higher rate than it is catching up in wages (notwithstanding the fast growth of the latter). The outcome is an absolute cost advantage in an expanding set of goods, including those which were/are central to the industrial production of many low- and middle-income countries. In that respect the magnitude and speed of Chinese industrialization risks crowding out the industrializing potential of many other countries. So, for example, Brazil—a country on the upper tail of the distribution of industrializers in terms of its technological capabilities—is a very ‘high wage’ country

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 ,   ,  



compared to China, but so also are other less developed Latin America countries, and even African countries are losing cost-based international (and domestic) competitiveness vis-à-vis China. Is this a reason to give up the ‘infant nurturing’/capability accumulation philosophy? In our view it is not: on the contrary, it adds to the reasons for practising various combinations of the ‘capital policy sins’ mentioned above. And it ought to encourage a more explicit use of domestic or regional markets for cultivating emerging national industries, even when the latter are being squeezed in the international arena between ‘advanced producers’ and Chinese exports.

. A: S--S D M

.................................................................................................................................. To measure the contributions of structural change to aggregate productivity growth, it is crucial to distinguish between the contributions of shifts between sectors and the contributions of productivity growth within sectors. Notice that we use an aggregated dataset based on our firm-level dataset for the decomposition method described below. Recent studies using the shift-share technique include Ali Akkemik (), Timmer and Szirmai (), and Kumar and Russell (). We adopt van Ark and Timmer’s () shift-share model, in order to be comparable with the results of Wang and Szirmai (). The difference in aggregate labour productivity levels at time 0 and T can be written as PT  P 0 ¼

n n X X ðPiT  Pi0 ÞSi þ ðSTi  S0i ÞPi i¼1

ð1Þ

i¼1

with Pi0 and PiT the labour productivity of sector i at year 0 and T; S0i and STi the employment share of sector i at year  and T; Si sector’s period average share of total employment; and Pi sector’s period average labour productivity. The growth of aggregate productivity can be decomposed into intra-sectoral productivity growth (the first term on the right-hand side of equation (), called ‘intra-effect’) and the effects of changes in the sectoral allocation of labour (the second term, called ‘shift-effect’). Let Ci denote the contribution of sector i to the aggregate labour productivity growth. We have PT P0 ¼

n X i¼1

Ci ¼

n X shift ðCiintra þ Ci Þ

ð2Þ

i¼1

Van Ark and Timmer () reallocate all shift effects (C shift Þ from sectors that experienced shrinking labour shares to sectors that expanded their share in total

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

 ,  ,   

labour. Suppose K is the set of sectors which expand their labour shares; J is the set of sectors with declining labour share. For expanding sectors k and shrinking sectors j, shift

Ck ¼ Ckintra þ Ck

¼ ðPkT  Pk0 ÞSk þ ðSTk  S0k ÞðPk  PJ Þ

Cj ¼ Cjintra ¼ ðPjT  Pj0 ÞSj

8j ∈ J

8k ∈ K

ð3Þ ð4Þ

with average labour productivity overall shrinking sectors and averaging over years X ðST  S0j ÞPj j∈J j X PJ ¼ : ð5Þ ðST  S0j Þ j∈J j

A This work draws significantly on Cimoli and Dosi (), Cimoli, Dosi, and Stiglitz (a), Yu et al. () and Dosi and Tranchero (). We thank Eva Paus for her insightful comments. Support from the European Union Horizon  Research and Innovation programme under grant agreement No. -GROWINPRO is gratefully acknowledged.

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 ,   ,  



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

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

 ,  ,   

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  ......................................................................................................................

                  

.............................................................................................................

 

. I

.................................................................................................................................. I his book on economic development, Ian Little, perhaps the most prominent neoclassical author on development of the last century, characterized the neoclassical approach to economic development as a belief in the power of the price system to allocate resources efficiently and by implication to stimulate growth. Little labelled those who questioned the ability of markets to function in this way ‘structuralists’ (Little, ). Theoretically, neoclassical economics is associated with the concept of equilibrium and the achievement of allocative optimality through the market mechanism, which in policy terms implies a preference for laissez-faire and free trade. While much of modern economics is based on these ideas, once one allows for exceptions to these simple policy prescriptions based on the existence of market imperfections or ‘market failures’, the meaning of the term ‘neoclassical’ becomes less clear, and the most common use of the term is now as an alternative to heterodox positions (Colander, ).¹ This chapter focuses on what can be seen as ‘mainstream’ interpretations of industrial policy, which acknowledge that the existence of market imperfections or ¹ Little himself, in his earlier authoritative work on welfare economics, when writing of the marginal cost-pricing rule, brings out the policy ambiguity inherent in welfare theory: ‘We may sum up the present discussion by asking (as we have asked for the other “optimum” conditions) what is required for it to be sufficient for an improvement in welfare always to adjust output wherever and whenever possible until price is equal to marginal cost. Formally the answer is that it can be proved to be sufficient only if all the ‘optimum’ conditions are put into operation at once, and if the resultant redistribution of income is

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‘failures’ undermines simple policy prescriptions based on the assumptions of the pure competitive model. The limitation of markets as a means of fostering development was an assumption common to most early writers on problems of economic development. In the development context, key aspects of market failures included the inability of labour markets to clear at a socially acceptable wage rate associated with open unemployment and underemployment; lack of information and collateral in credit markets leading to unsatisfied demand for credit, particularly from small and medium-size firms; shortages of skills with under investment in training by individual producers because of the externality created for competitors; under investment in new technology because of lack of capital, financial and human, and the externality for non-innovating competitors. In principle all of these justify intervention to address the gap between market prices and economic or social values (sometimes termed ‘shadow prices’). Neoclassical industrial policy is usually interpreted as a minimalist approach to corrections to the functioning of markets through measures such as the provision of better information, regulation of monopolies, investment in infrastructure, and the loosening of government regulation. This is exemplified by the ‘business environment reform’ agenda introduced as part of structural adjustment programmes in the s and s, when the term ‘industrial policy’ did not figure in discussions around the Washington Consensus (Williamson, , ). This chapter discusses the tradition in welfare economics that can be used to justify a more interventionist version of industrial policy, and considers more recent restatements of the case for industrial policy based on a framework initially developed in the s.² The chapter begins with an overview of the neoclassical approach before discussing its neglect during the structural adjustment era. It then considers two recent contributions that revive the case for a neoclassical version of industrial policy. The application of such policies, in particular priority-setting techniques, is also discussed. A final section draws some conclusions.

. T  D D   P H

.................................................................................................................................. Neoclassical versions of economics have been dismissed as dogmatic assertions of the benefits of laissez-faire and free trade, but within the theoretical framework there is the possibility of an interventionist, if still limited, role for public policy. Building on considered to be not unfavourable, and if all external effects are absent. But we have seen that it is manifestly impossible to put all the conditions into operation’ (Little, : ; emphasis added). ² An interesting link between current suggestions and thinking in the s is found by comparing some of the arguments reviewed in this chapter and the work of Arthur Lewis in advising on the prospects for industrialization in the Gold Coast (now Ghana); see Weiss (a).

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  



Marshall’s idea of external effects, for which the initiating producers neither received recompense nor paid costs, Pigou () created the case for tax-subsidy interventions as a means of addressing the failures of markets. With reference to the taxing of ‘smoke nuisance’, he anticipated the case for environmental taxes by several decades.³ The application of these ideas to a broader policy context had to wait until the s, when a theoretical literature on policy in inefficient (or ‘distorted’) markets emerged from analysis of the conditions under which free trade remained the best policy, where competitive conditions did not hold domestically. Although generally argued in abstract terms, the issue was highly relevant in the development context as trade protection was a relatively easy way, at least in fiscal terms, for governments to compensate producers for factors like wage rates above the opportunity cost of labour or for externalities created by learning effects. This literature was termed the ‘theory of domestic distortions’, and seminal contributions were made by Meade (), Bhagwati and Ramaswami (), and Johnson (). However, it was Max Corden who generalized the approach beyond trade-related interventions to cover a range of possible measures to address different market failures in what he termed the ‘policy hierarchy’ (Corden, : ch. ). This offered the first general statement of the principles behind what can be seen as a neoclassical version of industrial policy, which in principle could be used to justify a relatively interventionist policy stance. Corden recognized that policy needs to address barriers to growth created by realworld features of imperfect markets, but argued that there are different ways to do this associated with different by-product costs in terms of their effects on incentives and prices in related markets. Policy will involve a trade-off between addressing a specific market failure and the costs arising from the intervention.⁴ The best solution for a given problem was judged to be the most direct—in the sense of addressing the specific market failure at source—as this would minimize distortionary by-product costs. Policy interventions could thus be ranked by the number (or more accurately) the scale of the by-product distortions they created. One of Corden’s original examples related to a labour-market distortion (such as a minimum wage or union pressure) which kept wages above labour’s opportunity cost. If labour-market reforms were ruled out as impractical, the most direct policy would be a subsidy for employment (for example through tax credits). Other alternatives, such as a subsidy to production, not employment, or import protection via tariffs or export subsidies, created increasing levels of by-product costs. A production subsidy would leave labour-intensity of production too low; an import tariff combined with an export subsidy would have the same effect and distort consumer choice; and an import tariff alone would leave labour-intensity of production too low, distort consumer choice, and bias sales against exports (Corden, : ). Corden was clear that similar analyses could be applied to different policy problems and combinations of policy instruments. For example, ³ Robinson and Eatwell (: ). ⁴ Implicitly (and sometimes explicitly) this involves a comparison of the likely benefits and costs of a policy intervention to address market failures (Tinbergen, ).

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 

Table 5.1 Policy hierarchy: industry support by alternative measures Rank

Policy measures

By-product distortions

1 2a 2b 3

Production subsidy Import tariff plus export subsidy Subsidy to inputs Import tariff

4

Import quotas

None Consumption distortion Factor intensity distortion Consumption distortion Anti-export bias Consumption distortion Anti-export bias Public revenue effect

Note: Items at 2a and 2b are equivalent in ranking since they have the same number of by-product distortions. Source: Adapted from Cody et al. (1990: table 4.1).

Corden () anticipated more recent discussions on the role of the real exchange rate as an instrument of industrial policy, contrasting ‘exchange rate protection’ with the use of import tariffs as means of encouraging tradable activities.⁵ Neoclassical economics as applied to development policy generally recognized infant industry policy as a possible exception to free trade; such a policy was viewed as a form of investment, with short-run costs to consumers as costs of imported goods are raised by import tariffs and non-tariff barriers being compared with long-run gains in productivity through successful learning (Baldwin, ).⁶ However, support for an infant can be provided in different ways. In terms of supporting new activities, following the logic of the policy hierarchy import tariffs were perceived as an inferior means of promoting a new activity because they distorted consumer choice and created a bias against exports by raising the relative profitability of home-market sales. The most direct intervention would be a production subsidy financed by raising taxes in as non-distortionary a way as possible.⁷ Table . ranks five alternative policy measures for supporting an infant activity, with the hierarchy determined by the number of byproduct distortions each creates. A combination of an import tariff and export subsidy ⁵ The original version of Corden () was delivered at a seminar in . Using the hierarchy approach, he suggested both created distortions, which for selective import tariffs was a consumer distortion and for an undervalued real exchange rate was the shift in producer prices for all tradables regardless of whether all needed support. In addition, with exchange rate undervaluation there would be the need to sterilize any resulting current account surplus. On balance he appeared to favour conventional tariff protection. ⁶ For example, one of the key neoclassical authors on trade policy, Bela Balassa, suggested a basic rate of  per cent protection for manufacturing in general with the possibility of a rate of  per cent for infant industries (Balassa, : ). Here rates refer to effective, not nominal, protection. It was usually understood that gains were based on ‘learning by doing’ rather than on conscious efforts at accumulation of production capabilities, as identified in empirical work and stressed in structuralist literature (Bell et al., ; Teitel, ). ⁷ This explains the recommendation in Little et al. () for support for new activities through ‘promotion’ by production subsidy rather than ‘protection’ by import tariff.

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  



at the same rate would avoid an anti-export bias but would create a consumption distortion by raising prices paid by consumers. A subsidy to a factor input, such as labour, power, or credit, would not affect consumer prices but would distort input selection. An import tariff would have an anti-export bias and would distort consumer choice. Finally, physical non-tariff barriers like quotas, prevalent in many countries in the s, were perceived as the most distorting of all forms of protection, creating not only biases in consumer choice, but also an anti-export bias and a loss of government revenue.⁸ The policy hierarchy approach has been and remains influential, although it has clear limitations. It is in the tradition of the theory of the second best, but establishing exactly what optimal measures will be in a realistic world full of market imperfections is theoretically highly complex, and the policy hierarchy rule is a way of simplifying the problem (Lipsey and Lancaster, ). Ranking inversely by number of by-product distortions a measure creates assumes both that each measure is equally effective in terms of its impact on the chosen policy objective and that the costs of each distortion are equal. Logically, where these conditions do not hold it is possible to prefer a more distortionary, but more effective policy over a less distortionary, but less effective one (Cody et al., ). In addition, the approach assumes away the fiscal costs and their associated distortionary effects where taxes are raised to fund subsidies, by assuming subsidies are financed by a tax package that minimizes tax distortions.⁹ The general point that the unexpected by-product effects of policies can be significant is important, but the policy hierarchy approach alone cannot provide a definitive choice between alternatives. Their relative effectiveness and their costs of implementation and funding need also to be considered in a simple overall cost‒benefit comparison. One of the key central arguments over trade protection, for example, has been that it can have a direct effect in blocking imports into the home market and that it does not require funding in the way that promotion by subsidies does. Despite these limitations, as discussed further below, the influence of the hierarchy approach is still found in policy discussions, which stress the importance of addressing a market distortion or failure as directly as possible.¹⁰

. S A E

.................................................................................................................................. The significance of market failures was largely ignored during the structural adjustment era of the s and s, with the counter-argument that, while markets can ⁸ Little et al. () is a classic analysis of the costs of protection from a neoclassical perspective. ⁹ Balassa (: ) argues that ignoring budgetary considerations is unrealistic and for that reason questions the feasibility of subsidy schemes. ¹⁰ For example, in its discussion of possible interventions World Bank (: ‒) suggests to ‘match the instrument to the rationale’, which is a restatement of the policy hierarchy approach.

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

 

fail, so can governments, in the sense that they can be captured by vested interests so that interventions become a means of delivering rents to favoured activities. The avoidance of cronyism, it was argued, required the avoidance of any major interventions to address market failures (Krueger, ). Only minor interventions, for example, to improve information flows, restrict administrative barriers, and improve infrastructure, were acceptable. In relation to foreign trade, there was unanimous support for removing non-tariff barriers and lowering the mean and dispersion of tariff rates, with the possibility of retaining above-average tariffs for activities with potential (the so-called infants). Low relatively uniform import tariffs were advocated, largely for revenue purposes; for example, in his summary of the Washington Consensus, Williamson () refers to rates in the range of ‒ per cent, with the lower end more likely to be applied. In terms of wider industrial policy issues, along with opening economies to foreign competition through major trade liberalization programmes, the thinking was that policy reform should aim at making markets work as competitively as possible by removing distortions directly. This meant that rather than accepting market failures and designing second-best policies based on taxes, subsidies, or other measures to work around them, the failures themselves should be removed. Put simply, for example, this meant that if wages were above the opportunity cost of labour, impediments to the free functioning of labour markets, such as restrictive legislation on hiring and firing, should be removed; alternatively, if firms had difficulty accessing credit, the system of financial intermediation should be improved by removing restrictions on the entry of new banks or by other regulatory measures to increase competition. The imposition of this type of liberalization reform across the major markets of economies as part of structural adjustment conditionality was highly controversial. For the present discussion, what is important is that if implemented effectively it removes the need for the type of industrial policy implied by the policy hierarchy discussion. What replaced industrial policy at this time was a focus on barriers to private-sector expansion as identified in ‘investment climate’ surveys. These were based on interviews with firms who were asked to rank the importance of different types of constraint on their growth, whether, for example, poor infrastructure, lack of finance, government regulation, or lack of skills. Specific measures to address these constraints, within the confines of an overall policy of liberalization, sometimes described as ‘business environment reform’ became the new industrial policy of this era (Weiss, ). The rationale for such measures was based on empirical evidence collected by the World Bank and others on the impact of various barriers to private-sector expansion (World Bank, ). The basis for policy at this stage was to overcome these various obstacles by investing in infrastructure and training, streamlining regulation, where possible lowering taxes, and improving the system of financial intermediation by banking reform. Improvements were as far as possible to benefit all producers equally through ‘horizontal’ interventions (as opposed to selective or ‘vertical’ measures). However, in practice a truly level playing field approach was difficult to implement, since differential impacts were inevitable as improvement in access to a given resource or service would

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  



benefit more those who used the resource or service intensively. In addition, firm surveys revealed that across firms from many countries there was a large gap between de jure and de facto business environment conditions, which in many instances was explained by corrupt or informal payments as means of evading controls. This meant that there could be large differences in the business environment between firms in the same country.¹¹ At this stage, therefore, the policy consensus was dominated by the primacy of market reform and the need to remove market failures and distortions at source. Behind this approach was a conception of the state as a facilitator for the private sector rather than as an active participant in a process to support long-term development, with its perceived risk of government failure and cronyism. However, a major omission of this version of policy, highlighted in more recent contributions to the neoclassical literature, is its failure to address issues of innovation and technical change.

. R  I  N I P   ..................................................................................................................................

If one believes that market failures in poor countries cannot be adequately addressed simply by measures to improve the business environment, the market failure/policy hierarchy framework, while largely neglected in the period from the mid-s to , can be used to justify a considerably more active policy than that practised during that time. From a neoclassical perspective, the revival of interest in industrial policy is largely due to the work of the Harvard-based economists Ricardo Hausmann and Dani Rodrik. Although the authors themselves depart from conventional (and therefore neoclassical) interpretations of causes of growth, their work follows the traditions of the policy hierarchy literature. Their theoretical approach is set out clearly in Hausmann and Rodrik (), and its policy implications are explored in a series of subsequent papers. The authors reject the standard interpretation of the route to economic growth set out by the Washington Consensus involving openness to foreign trade and capital flows, market liberalization, and improved governance and institutional development. They argue that while some of these measures individually may have positive effects, standard reform packages miss the key issue of dynamic entrepreneurship and its link with innovation and ‘product discovery’. To address this, additional support measures are required to help firms discover what they can produce competitively. This opens the door to a version of industrial policy that is based on dialogue between public agencies and representatives of the private sector and has been labelled ‘modern industrial policy’ (Felipe, ). ¹¹ Hallward-Driemeier and Pritchett () describe ‘favoured’ and ‘disfavoured’ firms, the former barely troubled by controls and regulations. In the African context Hallward-Driemeier et al. () show that variations in indicators like days to clear customs or time spent dealing with officials vary more within countries than between them.

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

 

The more ambitious side to this policy (what the authors term ‘in the large’) involves taking strategic bets on new activities, products, or processes and providing the risk capital—for example through development banks or venture capital funds—or loan guarantees to allow them to be established.¹² The authors base this on the externality effect created by innovation, defined as doing things in different ways and creating new products (or products new to an economy), since followers benefit from the cost incurred by the first entrant. This gives a rationale for supporting and subsidizing innovation, and while not referring explicitly to the policy hierarchy approach, their discussion of the costs and benefits of different policy options largely mirrors the discussion in Corden from thirty years earlier.¹³ In their analysis, import protection as a means of supporting innovators is the least attractive option. It does not discriminate between innovators and followers, raises prices to consumers, and has an anti-export bias. It will focus innovation on domestic markets which is expected to lower the return to innovation given their small size relative to the world market. Similarly, export subsidies may have weaker price effects for domestic consumers than import tariffs, but also do not discriminate between innovators, leading to over investment in the activity. As the key concern is to target innovators, while limiting any leakage of benefits to ‘copycats’, public-sector credit or loan guarantees is the preferred instrument for this. Loans or loan guarantees can transfer the risk of failure to governments as the loan is only repaid if the investment is successful. In subsequent papers it is clear that the authors also see the possibility of industrial policy helping to remove constraints to growth in existing activities (what the authors term ‘in the small’) and fostering linkages between producers and suppliers (Hausmann and Rodrik, ; Hausmann et al., , ). Here dialogue between the government and the relevant private-sector stakeholders is meant to identify both areas for expansion and the obstacles to this growth that can be removed by the government. Co-funding by private partners to remove bottlenecks is seen as helpful to reinforce the public‒private partnership element.¹⁴ Furthermore, Rodrik has made clear that he sees what Corden () called ‘exchange rate protection’ and others have

¹² In high-income economies it is now common for industrial policy to be rationalized by reference to externalities from pioneer activities and the need to support these by ‘socializing risk’. Thus, for example, to quote the most recent industrial strategy from the government of the United Kingdom: ‘Governments in successful economies have recognized their strategic power and leadership role, allowing them to coordinate and convene efforts to develop and assimilate new technologies and industries . . . Governments can make long-term investments that no single commercial or academic player can take alone. The modern nation state is the most powerful means we have of pooling risk’ (HMG, : ). ¹³ ‘In attempting to promote innovation governments have used a variety of instruments such as trade protection, public sector credit, tax holidays and investment and export subsidies . . . However, interventions typically create other distortions’ (Hausmann and Rodrik, : ). ¹⁴ In their policy advice to the government of South Africa, specific suggestions from the authors included the creation of a special fund to finance public inputs suggested on the basis of proposals from the private sector, with these public inputs defined broadly to cover infrastructure, training, administrative reform, R&D or regulatory reform, and the conversion of the existing Industrial Development Corporation into a risk-taking venture capital fund (Hausmann et al., ).

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  



called a ‘stable and competitive real exchange rate’ (Guzman et al., ) as an important component of industrial policy. He and other authors have shown a link between real exchange rates and economic growth (Rodrik, ). This association has been built on in recent discussions of industrial policy where setting a competitive rate (that is an undervalued rate for local currency) is seen as an important complement to supply-side interventions. The criticism that this implies supporting all tradable activities, not just those with learning externalities, can be addressed by a set of taxes on the non-externality-creating traded sectors.¹⁵ The focus on innovation and subsidizing innovating firms from Hausmann and Rodrik links with both the endogenous growth literature (Romer, ) and the capabilities approach to industrialization as seen, for example, in the discussion of national systems of innovation in Nelson () and the work of Lall () on industrial capabilities.¹⁶ It has been argued that if knowledge is firm specific or tacit then it will not be transferrable and that Hausmann and Rodrik therefore overplay the importance of knowledge transfer effects and underplay the importance of intersectoral linkages and systemic effects (Andreoni and Chang, : ). The empirical significance of the spread of a knowledge externality partly depends on what is to be transferred. The argument of Hausmann and Rodrik about innovation and product discovery appears to be a broader one, in that firms may follow an innovator in a particular product line or way of organizing production without having specific blueprints, as the key information that is transferred concerns what can be produced competitively in an economy. In relation to inter-sectoral linkages and systemic issues, such as fostering a culture of entrepreneurship and factory discipline, the charge that these are neglected overlooks the process or dialogue aspect of the authors’ policy, that is intended to establish the constraints to growth in a particular area, which can include lack of domestic input suppliers or a trained workforce. In so far as these are real issues and governments can relieve these constraints, concerns over linkages and aspects of the industrial culture should be addressed. The dialogue element of their policy introduces a potentially more interventionist slant to industrial policy absent from the ‘business environment reform’ approach. The most valid criticism of the Hausmann and Rodrik approach is that offering credit or credit guarantees to firms may not itself provide sufficient incentive for or

¹⁵ The distinguished authors of Guzman et al. () who advocate this approach would probably not wish to be described as neoclassical, but in so far as their policy recommendation on the real exchange rate is justified by learning externalities it falls under the definition of neoclassical industrial policy used here. ¹⁶ Andreoni and Chang (: ), reviewing the work of Hausmann and Rodrik, suggest that the focus on informational externalities is an example of a ‘clumsy translation of old ideas by nonneoclassical schools into the neoclassical language’. The point that the informational externality is an old argument is, of course, correct, but the concept of a ‘knowledge externality’ drawn on by Hausman and Rodrik was clearly cited in the earlier literature (Corden, : ‒; Johnson, ). The fact that many neoclassical authors tended to underplay its significance as the basis for special support for new activities is a different argument and illustrates the point that the potential for an active policy inherent in the market failure analysis was often not developed.

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

 

support to the development of indigenous technology. The national system of innovation perspective views firms’ technological capability as strongly influenced by their operating environment, including the education system and research institutions, and policy on foreign investment, technology transfer, and intellectual property. Here the role envisaged for industrial policy is much wider than supplying credit, but requires governments to fund and coordinate basic research, to support its dissemination and commercial development and support firms in their efforts at technological upgrading. Case studies from technologically successful economies reveal the key common denominators as learning within firms, access to foreign technology and skilled human capital, and an active government policy (Malerba and Nelson, : ). Similarly, evidence from East Asia on the development of electronics and information communication technology highlights the role of government support (Lee, ).

. N S E

.................................................................................................................................. A separate body of work influencing the neoclassical revival of industrial policy comes from the Chinese economist Justin Lin, who gained international prominence and influence from his time as chief economist of the World Bank. Lin’s case on industrial policy is part of a wider framework of ‘New Structural Economics’, which aims to marry a belief that economic structures are critical for development with an emphasis on the use of the price mechanism as the key to efficient resource allocation. The author himself terms this ‘a neoclassical approach to structure’, as opposed to traditional structuralist analysis with its suspicion of the effectiveness of markets (Lin, : ). The significance of this work for industrial policy is that it acknowledges the existence of market failures and thus revives the case for government intervention through a ‘facilitating state’. As in the Hausmann/Rodrik work, the importance of informational externalities created by pioneer firms, whose experience both positive and negative followers can learn from, is stressed. In addition to ensuring that pioneers are compensated in some way for these effects, the government’s roles cover provision of information to and coordination of private firms, investment in both hard and soft infrastructure and the nurturing of new potentially competitive industries, chiefly through foreign investment.¹⁷ Each of these roles are said to stem from a perceived market failure, so the argument is consistent with earlier neoclassical work.

¹⁷ ‘Historical evidence and economic theory suggest that while markets are indispensable mechanisms to allocate resources to the most productive sectors and industries, government intervention— through the provision of information, co-ordination of hard and soft infrastructure improvement and compensation for externalities—are equally indispensable for helping economies move from one stage of development to another’ (Lin, ).

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  



In terms of practical advice on the direction of structural change, Lin draws insights from the ‘flying geese’ pattern of migration within East Asia, as industries moved between economies in the region in response principally to wage differentials: with rising wages in Japan in the s, firms migrated to lower-wage locations like Thailand and Indonesia, and more recently to China and Vietnam (Lin, ). This pattern of migration lies behind his suggestion that when poor countries start to think about new sub-sectors in which to invest, they should start by examining sub-sectors in which similar countries have had export success in the recent past. A similar dialogue to that in Hausmann and Rodrik of identifying obstacles to expansion by existing firms or barriers to entry by new firms is recommended. In this approach new activities to be supported by governments should be those that are in line with existing factor endowments of an economy, but which are not yet profitable for private firms because of short-term market failures. The expectation is that the removal of these failures will be sufficient to create internationally competitive production, so that the activities can be described as those where there is a latent, but not current, comparative advantage.¹⁸ Hence investment in activities such as these is described as ‘comparative advantage conforming’. Investing in activities which require skills and capabilities that the economy does not yet possess is termed a ‘comparative advantage defying’ policy by Lin, who sees this as a characteristic mistake of traditional structuralism and by implication ‘old-style’ industrial policy.¹⁹ Investment in activities without latent comparative advantage needs to be postponed until the underlying endowment structure has changed sufficiently for them to be commercially viable with the support of the envisaged market-correcting industrial policy. The type of market-correcting industrial policy interventions envisaged by this approach is illustrated in a detailed study on the obstacles to light manufacturing in Africa, which looked at the constraints on development in a range of sub-sectors in several East African countries, with Ethiopia taken as a case study (Dinh et al., ). This focus on constraints can be interpreted as ‘industrial policy in the small’ in the terminology of Hausmann and Rodrik. The analysis is based around a form of sub-sector growth diagnostics highlighting what are identified as the key constraints and solutions to them based on cross-country cost comparisons and evidence from interviews.²⁰ ¹⁸ Lin and Monga (: ) argue that ‘by facilitating co-ordination and addressing externality issues, industrial policy helps many domestic and foreign firms to enter sectors that are consistent with the country’s latent comparative advantage and turn them into overt comparative advantages, and thereby intensifies competition within the industries and enhances the economy’s competitiveness’. ¹⁹ The debate between Lin and Chang (Development Policy Review, ) provides a helpful insight into alternative visions of technological upgrading and structural transformation in industrializing economies. While both agree on the need for government support, they disagree on how far and how fast it is wise for countries to move into ‘distant’ products in the sense of goods that are far removed from current comparative advantage. ²⁰ For example, for apparel, specific recommendations include streamlining customs procedures, eliminating all import tariffs on imported inputs, rehabilitating rail links to the port, and developing an industrial park near the port; for leather goods, recommendations include removing the import ban on processed leather and providing technical assistance in factory operations and product design.

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

 

. D  C: H  I S

.................................................................................................................................. Since it draws its rationale from the existence of significant market failures, neoclassical industrial policy is usually associated with horizontal as opposed to vertical measures available only selectively to priority activities. However, both Hausmann and Rodrik and Lin indicate that some form of selectivity is inevitable to allocate limited resources ex ante and both agree that perfect neutrality of outcome is impossible even if all policy is based ex ante on neutral, horizontal interventions.²¹ In principle, horizontal measures supporting innovation, available to all but with an in-built element of selectivity in that they offer benefits only to dynamic firms offering new products or processes of production, could be said to offer the greatest scope for neutrality. Hausmann and Rodrik are a little ambivalent on the balance between horizontal and vertical measures, although in one paper (Hausmann and Rodrik, ) they argue that due to limited resources and technical capacity governments are ‘doomed to choose’ the areas or firms to support. In Hausmann and Rodrik (: ) they suggest that ‘in principle, interventions should be as horizontal as possible and as sectoral as necessary’. Their key point is that measures—like support for innovation—that enhance growth can span a range of sectors and therefore access to these should not be restricted selectively. However, they acknowledge that in some circumstances it may be easier to support specific sectors, both as a way of coordinating firms and because different sectors have different needs.²² As noted above, a key argument against selectivity is the risk of cronyism and policy capture, which mean that differential support is not offered on the grounds of potential for competitiveness. While the neoclassical policy literature is cautious of the concept of priority areas, its emphasis on quantification and comparison of costs and benefits offers ways of guiding choice, which can be used in quite different policy settings with varying degrees of ambition for industrial policy. A starting point could be existing trade specialization as shown in revealed comparative advantage indicators. However, this has no dynamic component and does not in itself help to highlight future areas for growth. Of similarly limited value is the concept from the neoclassical growth literature of total factor productivity (TFP). TFP is meant to reflect efficiency gains, interpreted as technical progress. While used widely in growth-accounting exercises at the macro level, for some countries estimates are available at the sub-sector level and firm level, which in principle could be used to set priorities in resource allocation.²³ It has been

²¹ The arguments in this section draw on Weiss (b). ²² Andreoni (Chapter  in this volume) suggests a blurring of the division between conventionally defined sectors as a result of recent technical change, which makes sector-based policies less relevant. ²³ The KLEMS database originally constructed for OECD countries, but now extended to India and elsewhere, provides TFP estimates at the sub-sector level (O’Mahony and Timmer, ).

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  



known for some time that there is a wide variation in productivity levels between firms, particularly in low- and middle-income economies, so that policies that can reduce the gap have potentially high returns. However, there are empirical difficulties with estimation of TFP and controversy over what the unexplained residual actually captures. In practice, in terms of priority setting, given the high correlation between valueadded growth and TFP, setting priorities on the basis of such estimates would be simply assuming that past growth will be continued into the future.²⁴ Broad guidance might be found by looking at past patterns of development in the spirit of initial work by Chenery and his co-authors (Chenery and Syrquin, ; Chenery et al., ). This has been updated by more recent work at UNIDO, for example distinguishing ‘early’, ‘middle’, and ‘late’ manufacturing sub-sector branches by the level of real GDP per capita at which they reach their peak share of GDP (Haraguchi, : table .). However, as a guide to policy it may be of relatively little use to know that Food and Beverages peaks at a relatively low-income level or that Fabricated Metals is usually significant in middle-income economies. More specific, but still relatively general, guidance is provided in the simple rule of thumb put forward by Lin and Monga (). Any individual country should target activities that a country with similar structural characteristics and resource endowments and an income per capita of about double that of the country concerned (in purchasing power parity) has been able to export successfully in the past fifteen to twenty years. The argument is that the comparator country will have specialized in activities likely to require production capabilities that the follower country has or can develop readily, so that these are activities in which the follower has a latent comparative advantage. This is on the grounds that income per capita provides a proxy for skill sets and incomes more than double those of a country imply a currently unattainable skill set. As the comparator economy grows its wages will rise, potentially freeing space in the global market that the follower economy can fill. Industrial policy is therefore a two-stage procedure: finding a comparator economy with an income not too far ahead of the country concerned; and then identifying sectors in the comparator from which the follower economy can export successfully (Lin and Wang, ). The rule of thumb from Lin and Monga has the advantage of simplicity, but it is not clear how far it is possible to generalize this rule. It may make sense in relation to standardized, labour-intensive products, where wage costs dominate competitiveness. For example, in relation to garments, with rising wages in older-established production centres and the ending of the Multi Fibre Arrangement, new important exporter firms from countries such as Bangladesh and Cambodia have emerged. In sectors where technical change is rapid, however, products exported twenty years ago may have undergone significant redesign. Their technical content and the

²⁴ Felipe and McCombie () argue that TFP estimates in neoclassical growth models are based on an initial accounting identity and that the unexplained residual is simply a weighted average of the growth of wages and the rate of profit, with weights given by labour and capital shares.

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

 

required production capabilities may have changed as a result, making it less clear that the comparator‒follower path is straightforward as a guide to industrial targeting. Furthermore, based on East Asian experience, the relevance of the guidelines of twice per capita income and fifteen to twenty years’ export experience in the comparator country has been questioned. It is argued that effective industrial policy made it possible for firms in Japan and Korea to move into new industries which, on a simple reading of the rule, would be viewed as too ‘distant’ from their existing capabilities.²⁵ Such qualifications do not invalidate targeting export industries that are successful elsewhere, but they do imply that first, the simplicity of the rule needs to be qualified and second, even where it can be said to exist, latent comparative advantage may need to be supported through active policies, for example on technology and training, as well as significant financial support for the nascent activities, whether these policies are identified by the policy hierarchy approach or by other means. Other more detailed approaches to the identification of priorities are available from the neoclassical literature. Here we elaborate further on two approaches that continue to be used in policy planning: one traditional, based on measures of economic efficiency, and the other newer, based on ideas relating to the capability required for the export of different types of good.

. E I

.................................................................................................................................. Different versions of an efficiency indicator have been used as a guide to potential comparative advantage of either a particular branch of manufacturing, or of individual project proposals. In the s and s, the neoclassical literature on industrialization formalized a version of economic cost‒benefit analysis based on the fact that manufacturing goods are internationally tradable—with the option of importing or producing domestically for either export or domestic sale. Thus, for any individual manufacturing investment, benefits from foreign exchange savings by import substitution or generation by exports could be compared with the opportunity costs of the resources associated with their domestic production (Little and Mirrlees, , ; UNIDO, ). Adjusting prices used in the analysis to reflect opportunity costs (the use of shadow prices) meant that in principle the effect of key market failures—such as an overvalued wage or an undervalued exchange rate for foreign currency—would be removed from the analysis to allow an assessment of whether an investment was economically efficient over the operating life of the project. Application of the ²⁵ Chang () argues that Japan targeted its auto sector in the early s when its income was onesixth of the market leader economy, the United States, and Korea entered semiconductors in the mids when its income per capita was one-seventh of that of the United States. Lin argues that in the early s Japan’s income was  per cent of the United States’, so that the auto example fits his rule of thumb. Development Policy Review () sets out the contrasting views.

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  



methodology was part of a wider drive to shift industrialization strategy away from import substitution behind protective barriers towards a greater focus on exports. Projects with rates of return below a cut-off opportunity cost discount rate were to be rejected with the implication that they were activities where over the project’s life there was no comparative advantage. In terms of empirical work on trade policy and industrialization, the most widely used neoclassical technique of the s and s was the effective rate of protection (ERP), which was used primarily to show the distorting effect of import-substitution policies (Little et al., ; Balassa, ). As this showed the effect of trade policy in inflating value added above what it would have been in the absence of protection, it was strictly a measure of incentive, not of efficiency.²⁶ An offshoot of cost‒benefit analysis, the domestic resource cost (DRC) ratio is a more appropriate measure of trade efficiency that provides a relatively simple indicator to assess comparative advantage (Schydlowsky, ). Developed originally for planning decisions in Israel, it offers a direct measure of short-term trade efficiency and has been used to demonstrate the high costs of some import-substitution activities (Bruno, ; Krueger, ). It estimates the domestic resources required per unit of foreign exchange earned or saved by an activity, in an activity-specific exchange rate.²⁷ Using the DRC, a test of comparative advantage requires that the domestic resources involved when valued at their economic opportunity cost are less than the value of net foreign exchange generated by an activity. In policy discussions, relatively high DRC measures were also used to justify policies of trade liberalization. Although the inverse ranking of activities by the size of their DRC is only strictly valid under restrictive assumptions, such as constant returns to scale, activities with ratios well above unity or a DRC ratio well above the shadow exchange rate, will not be activities in which an economy has a current comparative advantage. Unless there is strong evidence that their productivity P P ²⁶ The ERP for output i was usually calculated from the formula (ti – aji.tj)/( – aji), where ti is the tariff on i (or tariff equivalent where direct controls were used), tj is the tariff or tariff equivalent on input j, summation covers all inputs j to n, and aji is the share of input j in the value of output i. Theoretical problems arise with this formula in relation to the treatment of non-traded inputs into i, whose price is also raised by protection and by the fact that strictly the coefficient aji should not be the observed coefficient at domestic prices, but the counterfactual coefficient at world prices under free trade (Corden, ). P ²⁷ DRCj = VADPj/(WPj – aijWPi), where WPj and WPi are the P world prices for the traded outputs j and inputs i involved, so for all traded inputs required (WPj – aiWPi) is the net foreign exchange effect per unit of j’s production after deducting the cost of traded inputs used in j. If the value-added content of j covering labour and non-traded goods is valued at their opportunity cost, VADPj gives the economic value of the domestic resources required to generate a given foreign exchange effect. P DRC can either be expressed as an exchange rate (where VADPj is in local currency and (WPj – aiWPi) is in P foreign currency) or as a number (where WPj – aiWPi is in local currency converted at an exchange rate taken to reflect the long-run or equilibrium value of foreign currency). Where the former approach of an exchange rate is used, an activity is efficient if the DRC ratio is below the economic value of foreign currency (the shadow exchange rate). If the DRC is expressed as a number, the net foreign exchange in P the denominator (WPj – aiWPi) should be converted to local currency at the shadow exchange rate and efficiency requires a ratio of below unity.

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

 

can be improved markedly over the life of new investments, expansion of these will be comparative advantage defying in the terminology of Lin ().²⁸ The DRC ratio thus provides a technique for distinguishing the short-term competitiveness of tradable activities. The DRC analysis gives a snapshot picture of efficiency at a point in time, and where accurate data can be collected it highlights where there is current or short-term efficiency. Its weakness as a guide to priorities is that ideally what is required is an indication of longer-term potential that is dynamic, not static, comparative advantage. In principle an element of dynamism can be introduced by projecting both sides of the DRC ratio into the future; for example, learning or technical change may reduce the domestic resources involved (and thus lower the numerator) or improved demand prospects or design may increase the net foreign exchange effect (and thus raise the denominator). The exchange rate used should be a projected equilibrium value and both future costs and benefits should be discounted to give present values. With further adjustments the analysis can be converted into a full cost‒benefit calculation. Any benefits from employment creation are picked by the lower valuation of surplus or underemployed labour either used directly in production or indirectly though the production of non-traded inputs. If externalities are involved, depending on their sign, they will add to or reduce the domestic resources in the ratio.²⁹ All of these adjustments are uncertain, particularly when big structural leaps are taken into completely new areas. Thus, despite the possibility of projecting into the future, DRC analysis as applied in practice is essentially static. Hence heterodox or structuralist authors tend to dismiss this approach as either impractical or having an in-built bias towards unambitious interventions (Chang, ).

. P S

.................................................................................................................................. Hausmann and Rodrik () highlight the need for countries and firms to discover what they are good at producing; however, practical policy requires some guidance on what this is likely to be and where dynamic comparative advantage lies. An addition to their work, ‘product space’ analysis, is intended to offer this. In the short term it is likely that a country will move into the production of goods that require similar skills, technology, and capital assets to those in which it is already competitive, but the authors argue that the conventional approach of simply looking at areas where there is already a revealed comparative advantage is insufficient. Within broad product ²⁸ An early example of the use of the DRC ratio is the study on the high cost of automobile engine assembly in India (Baranson, ). Weiss and Jalilian () give DRC estimates used in a more recent discussion of planning priorities in Tanzania. ²⁹ Little and Mirrlees (: ch. ) briefly showed the equivalence between their approach and the DRC analysis.

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  



categories (like textiles or clothing) there can be significant diversity between individual products in terms of technology content and branding. This implies that price, profit margins, and demand prospects can differ between products within the same broad category, offering scope for a country to upgrade into higher-value products. Patterns of trade specialization can affect growth and there is evidence that exporting highervalue or more sophisticated products is associated with faster economic growth, so that countries whose export basket is more sophisticated than expected for its income level experience faster growth (Hausmann et al., , ). If more sophisticated products are to be targeted by policy, a measure of sophistication is required at the individual product level to assess when changing the composition of exports adds to growth potential. Initial measures of the sophistication of products used a weighted average of the income per capita of countries which exported the goods, so the average income of the exporters became a proxy for the technological depth, complexity, and thus growth potential of a product.³⁰ Use of an income-based product-level indicator to explain growth of income across countries risks being tautological, hence a revised measure of product sophistication— termed ‘product complexity’—was developed (Hidalgo et al., ; Hausmann et al., ). This index number combines information on diversification—the number of products a country exports with revealed comparative advantage—and ubiquity—the number of countries which also specialize in these products. Complex products with a high score on this index are those where diversified economies with high levels of capability have a specialization.³¹ Rich countries are expected to export complex goods that few other countries export, while poor countries are expected to export goods of less complexity exported by many other countries. The most complex goods by this measure are machinery, chemicals, and metal products and the least complex are raw materials and primary commodities. As expected, there is a positive association between a country’s income per capita and the share of complex goods in exports. Product space analysis is based on the idea that there is a trade-off between moving to ‘close’ goods—which may not be highly sophisticated or complex—but which require capabilities close to an economy’s current set, and ‘distant’ goods with a higher potential value. This requires a measure of the economic distance between goods, which Hausmann and Klinger () base on the lower of the two probabilities that a good is exported with comparative advantage by pairs of countries.³² The argument is that close products require similar production capabilities for competitive production and that a country that specializes in goods that are close to other goods will find it easier to diversify its export basket. Export targets will be goods which add to the ³⁰ The weights were determined either by revealed comparative advantage (Hausmann et al., ) or share in world exports (Lall et al., ). Weiss () contrasts the two approaches. ³¹ An intuitive explanation, along with product complexity scores for over , products, is in Abdon et al. (). ³² Thus, for two goods, for example pig meat and copper, it is the minimum probability of all meat exporters exporting copper with revealed comparative advantage and all copper exporters exporting pig meat with revealed comparative advantage.

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

 

complexity of a country’s overall export basket but are not so far away in terms of capabilities required for their production that producing them competitively is not feasible in a realistic time frame. Product space analysis is intended to identify potential export products at a disaggregate level. The total product complexity of a country’s exports is the product complexity index for each good weighted by the share of goods in total exports. Distance is determined by the probability data on joint exports noted above, but what is not too far away is ambiguous. In practice crude approaches tend to be applied, for example, to require that target products have a distance from the current export basket which is below the median distance for all goods exported currently without revealed comparative advantage.³³ An efficient frontier is defined by goods which add to the product complexity of the export basket, meet the distance criteria, and add to the links with other complex products.³⁴ The products identified in this way should require capabilities for competitive production not too dissimilar from those required in areas where successful specialization has already been achieved, so the implication is that these are areas where there is a potential or latent comparative advantage. However, the authors stress that it is not designed to ‘pick winners’ as candidates for export subsidies or other forms of support (Hausmann and Klinger, , ). The idea is that the export priorities implied by this analysis identify areas for consideration, usually at the four-digit level, in discussion between public agencies and potential investors, including foreign investors. Product space analysis has been applied in a highly diverse set of countries and a limitation is that in some cases potential export products which emerge from this analysis cover a wide range of goods and simply match a priori expectations.³⁵ For Rwanda, for example, using this approach for exports to global markets, seventy-two potential export product categories at the four-digit level are identified (Hausmann and ³³ This is used in Hausmann and Chauvin (). Hausmann and Klinger () use different standard deviations from the mean distance to show the sensitivity of the results to the choice of distance. ³⁴ This last condition is met by a measure termed ‘opportunity gain’ by Hausmann and Chauvin (), although different terminology was used in earlier studies. Ideally a country should specialize in goods with the highest complexity, the shortest distance, and the largest opportunity gain. However, given the trade-offs between distance (as a measure of how feasible it is to move to new products) and the other two indicators, for consideration in the list of export targets, product j should have the following characteristics: PCIj > PCIav Djav < Dav OGj >  where PCI is the product complexity index, j is an individual product, PCIav is the average PCI for the export basket, Dj is the distance between j and the current export basket, Dav is the median distance between goods not currently exported with comparative advantage and the current export basket and OG is opportunity gain (a measure of what j adds to the links with other potential exports). ³⁵ See, for example, for Colombia (Hausmann and Klinger, ), Rwanda (Hausmann and Chauvin, ), and Tajikistan (ADB, ). The Asian Development Bank has used the product space approach in its country diagnoses for industrial development in several countries.

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  



Chauvin, ). Since they use local materials, are generally labour intensive, and have below-average transport costs, they are the type of goods that might be suggested by an a priori analysis of ‘early’ industries based on past international experience. Thus, in this case it is not clear what the product space analysis has added.³⁶ However, with the development of a large database of trade statistics and software to derive the relevant indicators, it has become much easier to apply this approach as a first screening of possible candidates for new exports, some of which might be of interest to private investors.³⁷

. D  C   R?

.................................................................................................................................. Given the uncertainty attached to all future projections and the clear limitations of these techniques, do they have any useful role in helping to choose areas to support in the context of an active industrial policy? Emphasis on quantification can be seen as the strength of a neoclassical approach to policy, since in its absence decisions will inevitably be taken on weaker grounds.³⁸ As an efficiency indicator, the DRC will inevitably be approximate and at best offers indicative guidelines for policy priorities. The most useful role of the analysis is as an initial screening device providing a loose form of ranking by the inverse of the DRC ratio—either between manufacturing branches or individual potential projects—with activities with a high domestic cost per unit of foreign exchange treated as unlikely candidates for support unless convincing arguments can be provided to demonstrate their long-term potential. Short-term costs associated with initially uncompetitive activities should not be ignored for priority setting and the indicator is useful as a means of gauging by how much productivity would need to improve for certain activities to justify support and to allow a judgement on how best, if at all, policy can help to bring these down. It has less of a role where genuinely new activities with no comparable reference price are under consideration. The product space analysis aims to link the capabilities needed for goods already exported successfully with those needed for new export target niches. Similarity in ³⁶ The classification of these priority areas into three categories groups them as: () processed agricultural products, beverages, tobacco, and agro-chemicals; () specialized textiles and garments; and () construction materials, metal, and wood products. The authors comment that their priority list does not differ markedly from the priorities in the National Export Strategy for non-traditional exports, which were derived from expert judgements. ³⁷ The website www.atlas.cid.harvard.edu provides information by country with an explanation of the methodology. ³⁸ As Little and Mirrlees (: ) wrote in the context of external effects: ‘Even a back of the envelope calculation may serve to show either that the initial suspicion was unjustified, or that further work might need to be done. If it is thought that the presence of external effects will be strongly claimed by opponents or proponents of a project, every effort to achieve a sensible, albeit rough quantification, should be made. Otherwise wild exaggeration is all too easy.’

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

 

capabilities in itself does not guarantee that efficient production can be established. Efficiency will be determined by a range of factors (such as access to technology, skilled labour, raw material supplies, or marketing links). Hence there is a role for industrial policy in engaging with producers to establish the constraints that need to be overcome to create competitive exports in these areas. The data from a product space analysis should be seen as a first step in a screening and identification process, with detailed discussions, plans, and appraisals required prior to final decisions.³⁹

. C

.................................................................................................................................. Overall, the ideas from this newer neoclassical policy literature have been taken seriously by both international agencies and governments in a number of countries, who see the need for a form of industrial policy.⁴⁰ This literature has served to remind policymakers that government can have an important role in economic transformation that goes well beyond that set out in the Washington Consensus of the s and s. As an example of the influence of this revival of interest, the Inter-American Development Bank has developed an approach to ‘productive development policies’ based on principles which draw heavily on the ideas behind neoclassical industrial policy, as defined here. Details of a variety of interventions are given in Crespi et al. (), while chapter  of that volume sets out the conceptual framework involved. The emphasis is on correcting market failures, addressing these as directly as possible, and conducting an implicit (or at times explicit) comparison of the costs and benefits involved. The influence of the policy hierarchy is evident as two tests are set out for policy analysis: ‘What is the plausible market failure that has been diagnosed to justify the policy? Is the alleged policy remedy—whether it entails alleviating the failure or redressing its impact—a good match for the diagnosis?’ (Crespi et al., : ). The work of Hausmann and Rodrik is also cited, particularly in relation to aiding selfdiscovery through support for innovation and encouraging public‒private dialogue to identify constraints to growth. The examples in the book can be seen as examples of what Ocampo and Porcile (Chapter  in this volume) describe as the ‘timid return’ of industrial policy post .⁴¹ ³⁹ Andreoni and Chang (: ) criticize the methodology for focusing on the characteristics of products rather than on links through use of similar technology and production processes, which may be more relevant in determining ease of moving into new areas. This point is valid but the product space analysis is meant as an operational guide and data unavailability would preclude a similarly detailed analysis based on technology. They also appear to imply that the product space analysis is not intended to be used as part of a supportive industrial policy, but of course it could be. ⁴⁰ Ansu () surveys approaches to ‘market-supporting industrial policy’ in five African economies. ⁴¹ Crespi et al. (: ch. ) highlight the difficulties involved including lack of institutional capacity, the risk of capture and rent seeking, and the intrinsic difficulty of identifying the best

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  



There are different ways of justifying industrial policy and mainstream welfare economics has always offered one based on market failures. In a development context the theoretical base for industrial policy was ignored during the era of structural adjustment, despite earlier work pointing out that real-world features of markets could be corrected in ways that minimized any negative allocative effects. Recent thinking has revived the case for industrial policy, as the limitations of market-driven growth as the basis for innovation and dynamic structural change have become apparent, with a new emphasis on dialogue between public agencies and the private sector to determine how the former can best support the latter to become competitive. However, this neoclassical version of industrial policy has its own limitations. By focusing on price adjustments through markets it can ignore more effective—but more distortionary—direct measures like import quotas, investment licences, or direct credit allocations. By highlighting individual markets, it may miss the bigger picture that supportive macro policies combined with more effective financial intermediation and an active policy on technology can be critical. By focusing on short-term costs and thus on activities with latent comparative advantage relatively close to competitiveness, where existing capabilities are not very different from those required at the efficiency frontier, this approach misses the possibility of skipping between generations of technology into new areas. Because of uncertainty the quantitative planning tools of the neoclassical approach can have an in-built conservative bias in that they will select activities with costs that can be estimated or policy interventions with predictable, if limited, outcomes. In this view, none of the big leaps or breakthroughs associated with the successful industrialization of the past would have been justified ex ante by neoclassical criteria. However, even ambitious ‘vision-based’ or ‘mission-oriented’ versions of industrial policy which aim at creating winners rather than picking them from existing firms, or creating markets as opposed to fixing them through tax-subsidy adjustments (Mazzucato and Kattel, Chapter  in this volume), still require some approximate comparison of benefits and costs. Experience suggests that industrial success requires a combination of a vision, well-designed support, and the application of some form of economic criteria to aid decision-taking. The neoclassical techniques referred to here, particularly cost‒benefit analysis and its offshoot the DRC ratio, have limitations. They may not be very effective in aiding thinking on the most dynamic new areas, but sensible application of the DRC indicator, for example, offers a way of weeding out obviously inefficient investments that have little prospect of competitiveness. Thus, they provide a check on the short-term costs of different investments associated with different policy options. In this sense there is scope for a synthesis between competing versions of industrial policy with the focus of specification and quantification of benefits and costs from the neoclassical tradition combined with ambitious programmes for industrial transformation that involve more substantial institutional change. steps to self-discovery. They also conclude, however, that some public-sector institutions in the region have had success in working closely with the private sector.

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 

R Abdon, Arnelyn, Marife Bacate, Jesus Felipe, and Utsav Kumar () ‘Product Complexity and Economic Development’. Levy Economics Institute Working Paper No. . ADB () Tajikistan: Promoting Export Diversification and Growth. Manila: Asian Development Bank. Andreoni, Antonio and Ha-Joon Chang () ‘The Political Economy of Industrial Policy: Structural Interdependencies, Policy Alignment and Conflict Management’, Structural Change and Economic Dynamics : –. Ansu, Yaw () ‘Industrial Policy and Economic Transformation in Africa: Strategies for Development and a Research Agenda’, in Joseph E. Stiglitz, Justin Yifu Lin, and Ebrahim Patel (eds) The Industrial Policy Revolution II: Africa in the st Century, International Economic Association Conference Volume –. Basingstoke: Palgrave Macmillan, pp. –. Balassa, Bela () Development Strategies in Semi-Industrialized Economies. Baltimore, MD: Johns Hopkins for the World Bank. Baldwin, Robert () ‘The Case against Infant Industry Tariff Protection’, Journal of Political Economy (): –. Baranson, Jack () Manufacturing Problems in India. Syracuse, NY: Syracuse University Press. Bell, Martin, Bruce Ross-Larson, and Larry Westphal () ‘Assessing the Performance of Infant Industries’, Journal of Development Economics (–): –. Bhagwati, Jagdish and V. K. Ramaswami () ‘Domestic Distortions, Tariffs and the Theory of Optimum Subsidy’, Journal of Political Economy (): –. Bruno, Michael () ‘Domestic Resource Cost and Effective Protection: Clarification and Synthesis’, Journal of Political Economy (): –. Chang, Ha-Joon () ‘Should Industrial Policy in Developing Countries Conform to Comparative Advantage or Defy It? A Debate between Justin Lin and Ha-Joon Chang’, Development Policy Review (): –. Chang, Ha-Joon () ‘Comments on “Comparative Advantage: The Silver Bullet of Industrial Policy” ’, in Joseph E. Stiglitz and Justin Yifu Lin (eds) The Industrial Policy Revolution , IEA Conference Volume –. New York: Palgrave Macmillan, pp. –. Chenery, Hollis and Moshe Syrquin () Patterns of Development –. Oxford: Oxford University Press for the World Bank. Chenery, Hollis, Sherman Robinson, and Moshe Syrquin (eds) () Industrialization and Growth: A Comparative Study. Oxford: Oxford University Press. Cody, John, Richard Kitchen, and John Weiss () Policy Design and Price Reform in Developing Countries. Hemel Hempstead: Harvester Wheatsheaf. Colander, David () ‘The Death of Neoclassical Economics’, Journal of History of Economic Thought (): –. Corden, W. Max () ‘The Structure of the Tariff System and the Effective Protection Rate’, Journal of Political Economy : –. Corden, W. Max () Trade Policy and Economic Welfare. Oxford: Oxford University Press. Corden, W. Max () ‘Protection and the Real Exchange Rate’, in W. Max Corden Protection, Growth and Trade. Oxford: Blackwell, pp. –.

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

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  ......................................................................................................................

    Firm-based Perspectives .............................................................................................................

 

. I

.................................................................................................................................. T chapter considers the central role of firm strategies in industrial policy. It focuses, in particular, on large firms which can make investments to realize economies of scale and scope, coordinate clusters of suppliers, and build capabilities. The productive resources, organizational capabilities and ability of big businesses to shape the policy environment in their interests are central to a production-centric understanding of industrial policy. The enterprise is at the centre of industrialization and the strategies of large enterprises, in particular, drive the development of productive capabilities. The theory of the firm is thus an essential part of the conceptual framework for understanding industrial policy and economic transformation. As emphasized by Ohno (), a dynamic private sector is critical for catch-up and supporting this is perhaps the key industrial policy challenge facing developing countries. Four different dimensions to this may be distinguished (Lall, ): technological upgrading within industries; entry into more complex activities; increasing local content involving local innovations and design; and mastering more complex technological tasks within industries. Neoclassical theories of the firm struggle to address these core concerns as their market-centric views simply posit the firm as a set of arrangements to minimize transaction costs. Firms are located in idealized perfectly competitive markets with many small rivals, and no economies of scale or substantial market power. Transaction-costs theories influence approaches to understanding the role of businesses in industrial development which abstract the firms from the political economy

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   



context and the reality of market power, and support simplistic ‘investor-friendly’ policy frameworks lowering the costs of doing business. It is therefore essential to critically evaluate alternative theories of the firm which explain the development of productive capabilities, and the ways in which businesses exert control and hold power over economic activity. The market power which firms hold in setting high prices if they have a monopoly position or collude with their competitors applies to arms-length market exchanges. However, value creation involves a range of relationships through which activities are organized in production networks and value chains. The coordination of the activities involves direct and diffuse power, which can be exerted in direct and indirect ways (Dallas et al., ). For example, international business organizations can shape sustainability codes through diverse lobbying activities which affect the competitiveness of industry in different countries and benefit some interests over others (Ponte, ). Business is increasingly transnational in nature as companies coordinate activities spread around the world. Industrial policies and regulations remain predominantly national. The ongoing digitalization of design, production, marketing, and logistics comes on top of the advances in information and communication technologies that have enabled international coordination by lead firms. It portends a further stepwise change to a hyper-globalized world where companies transcend national borders. At the same time, the dramatic growth of the Chinese economy and corporations stands as a counter-model, where the state is intimately involved in the strategic orientation of corporations to ensure consistency with the development vision (as addressed in Oqubay and Lin, ; Oqubay and Ohno, ). I start by reviewing the main schools of thought in the theory of the firm and the development of productive capabilities. This takes into account the literature on transaction costs and the resource-based theory of the firm. Large firms naturally have considerable political influence; a critical aspect is firms as agents in political settlements and the implications for industrial development. Substantive sections then cover the following key areas: market power, competition, and enterprise strategies; the internationalization of production and global value chains; and recent developments regarding the digitalization of production, digital platforms, and the implications for industrial policy.

. T   F  E  I D

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The theories of the firm in economics can essentially be divided into two main groups. Firms can be understood either in terms of their organizational capabilities and productive resources or as a set of coordinating arrangements which replace market exchange.

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The transaction-costs theory of the firm, based on the seminal article by Coase (), posits that the firm may essentially be viewed as the unified governance structure that results from the properties of different transactions. It thus takes exchange as its starting point and defines firms as sets of non-market relationships. The primary factors producing transactional difficulties include bounded rationality and imperfect information, opportunism, small-numbers bargaining, and asymmetric information. The costs associated with transactions increase with uncertainty and asset specificity (Williamson, ). Under the transaction-costs approach the firm is the result of fixed, structured, and open-ended relational contracting which internalizes the transactions, removing or ameliorating the conflict, and exerting the administrative control required for planning and coordination. The internationalization of production can be seen as a particular subset of the reasons for the formation of firms, in response to the costs of organizing cross-border markets (Dunning, ). The transnational corporation (TNC) is therefore essentially viewed as an efficient response to intrinsic market failures. The firm is, however, treated as a ‘black box’ and ‘[w]hat happens between the purchase of factors of production and the sale of goods that are produced by these factors is largely ignored’ (Coase, ). The firm is simply a nexus of contracts (Jensen and Meckling, ). When transaction costs are defined to subsume a broad range of issues with market relationships, it becomes unclear what exactly is being internalized. For example, we need to understand costs associated with transactions in products due to asset specificity or embodied technology (leading to intra-firm trade), the development of products through different stages of the product cycle, as well as factors such as managerial capabilities and organizational techniques. In fact, what are identified as market failures are intrinsic features of the organization of economic activity—they are not characteristics which, if somehow ‘corrected’, will mean an arms-length market relationship can exist. At the most basic level, there are economies of scale and scope, and network effects. Technological improvements at the firm level also need to be taken into account. These factors have effects on industrial development which depend on complementary changes, such as in management approaches, that need to be understood in a systems framework incorporating interindustry relationships (Rosenberg, ). Institutional-based theories of the firm suffer from being primarily concerned with explaining the types of contractual arrangements which govern exchange rather than understanding the way in which the production is organized and capabilities are developed over time. This relates to the factors which explain how firms are able to reconfigure their productive assets and processes (their dynamic capabilities) to produce new and better products and services (Teece, ; Teece and Pisano, ; Pisano, ). The institutional approach also ignores the power and political influence of large firms (Zingales, ). The literature on the resource-based theory of the firm, including critiques and extensions, has sought to address these issues head on.

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.. Resource-based Theory of the Firm The resource-based theory of the firm builds on the essential contribution of Edith Penrose () who focused on firms’ productive resources, organizational routines, capabilities, and competencies. There is a dynamic learning process through the interaction of technology capabilities and market opportunities that is at the heart of the principles of production and business organization. Penrose argued that experience builds the knowledge of productive opportunities on the part of firms and that ‘productive services’ (that is, capabilities) open up new productive opportunities. Firms shape markets through decisions which alter the parameters (technological, product, and organizational) of the market. The productive capabilities of the firms are heterogeneous and evolve depending on how they are used. This means that productive opportunities are unique for each firm and are shaped in dynamic processes (Penrose, ). Firms are competitive in so far as they are able to establish technological or market ‘bases’ (a distinctive technological capability). There can be innovation-driven increasing returns to scale in industry, which were identified by Babbage in the nineteenth century in his book originally published in  (Babbage, ), and are still highly relevant to considering the implications of the digitalization of production in the twenty-first. In a similar vein, Chandler () views the ‘modern business firm’ as a collection of ‘dynamic organizational capabilities’ which are the source of the firm’s competitiveness (see also Dosi, ). In this framework, the firm is an organization whose development depends primarily on its ability to continuously innovate and develop new products and ways of working. These capabilities are based on a firm’s internal organization and the extent to which the collective experiences from production are developed, shared, and learnt from. Cooperation and collaboration are therefore the basis for competition which is viewed not as aiming to be the lowest-cost producer, but as the ability to advance and produce better products, more quickly, than other groups of firms. These factors together describe differences in firms’ competitiveness, as well as the evolution of ‘business-enterprise systems’ (Fujimoto, ). The resource-based theory of the firm, however, insufficiently recognizes the extent to which firms may represent a locus of control and use this control to condition the environments within which they operate to extract rents. Large profits may be the reward for investment and innovation to generate or maintain competitiveness; however, they may also be due to the erection of barriers to entrants and strategies to entrench a position of market power over potentially more innovative rivals. These considerations point to the importance of understanding firms as part of the wider political economy, and to why large business groupings in some countries have built productive capabilities while in others they have simply extracted rents (as elucidated in different country/region chapters in this book). ‘Bringing production back-in’ (Amsden, ) requires locating a resource-based theory of the firm in relation to the wider society.

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The resource-based theory of the firm has been extended through a growing literature on firms understood in terms of their dynamic organizational capabilities (Chandler, ; Chandler et al., ; Dosi et al., ; Teece et al., ; Pisano, ). This includes learning, innovation, skills, and organizational resources, and the construction of competitive assets (Amsden, ; Lazonick, ; Khan, , ). Firms have been located within the evolution of business-enterprise systems and the institutional context (Dosi, ; Chandler et al., ; Best, ). Chandler drew on detailed analysis in business history to explain the rise in large industrial corporations in the United States, contrasted with the United Kingdom and Germany, setting out the dynamics of industrial capitalism (Chandler, ). This emphasized the central role of large industrial firms in the creation of wealth, and the organizational capabilities of the enterprise as a whole. The firms could make investments large enough to reap economies of scale. Firms are the bases for technological development and managerial skills. Large firms establish and coordinate a nexus of related small and medium-sized firms to ensure the flows of materials and information necessary to maintain production and distribution. The organizational capabilities were the collective physical facilities and human skills as they were organized within the enterprise and their careful coordination and integration to achieve the economies of scale and scope needed to compete locally and internationally. These organizational capabilities have to be created and maintained (Chandler, ; Lazonick, ; Teece, ). Changes in technology, learning and skills development, and capital are constitutive of the evolution of the firm itself. These are all associated with a reconceptualization of the business entity around its organizational capabilities which determines a firm’s scale (defined as ‘throughput’) and scope, being the production of related goods. This focus on the organizational aspects may be distinguished from the approach in much of the new institutional economics which views institutions as a collection of relationships that can be characterized by explicit or implicit contracts replacing market exchange (Amsden, ; Khan, ). The orientation of large firms is central to the nature of capitalism in different countries. Hikino and Chandler () contrast the US model, termed ‘competitive capitalism’ to reflect the highly developed managerial nature of firms and the vigorous competition between them, with the experience of Germany which is termed ‘cooperative capitalism’. In Germany it is argued that firms developed a management hierarchy capable of exploiting the opportunities of economies of scale from investing in heavy industries such as iron and steel, but cooperated closely together. The resource-based theory of the firm focuses on the ability to strategically deploy its resources, on which there is now a vast business-school literature following Porter (). However, the business-school adoption of the resource-based theory diverted attention from the importance of taking into account innovation and learning (Lazonick, ; Pisano, ) and the wider political economy instead of a narrow and functional focus on organizational structure (Dosi, ). Comparative country studies (such as in Chandler et al., , ) highlight the importance of understanding

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

different groupings within big business, particularly finance, as well as the complex relationships of business with the state, as addressed in other chapters in this Handbook. It is important to emphasize the diversity of outcomes, the inherent uncertainty, and that effects such as cumulative causation and path dependency need to be understood at the levels of production systems, institutional frameworks, and wider society, beyond individual firms. Teece and Pisano () draw on the definition of the firm in terms of capabilities and competencies to identify a firm’s ‘strategic dimensions’. These dimensions are identified as: a firm’s managerial and organizational processes (including patterns of practice and learning); its present position (including its technological and intellectual property, customer base, and relations with suppliers); and the paths available to it (the strategic alternatives and opportunities available to the firm). Strategy and organization are crucial to the choices firms make in identifying and selecting capabilities for future competitive advantage, including general-purpose capabilities enabling functional integration across specialist domains, and market-specific ones (Pisano, ). The uncertainty inherent in innovation means that finance plays a particularly important role in how some enterprises mobilize and deploy productive resources for the development of new products and services, as identified by Lazonick () in the theory of the innovative enterprise. This uncertainty includes: technological uncertainty relating to whether the firm will be able to develop the products and processes it envisages; market uncertainty in terms of the returns which will be made from the improved goods and services due to customer attraction; and competitive uncertainty, as rivals are engaged in similar strategies and may be more successful. The financial commitment is the set of relations that ensures allocation of funds to sustain cumulative innovation processes, in what has been termed ‘patient capital’. This is mainly about the availability of long-term development finance and the ability of the firms to retain and deploy earnings. The theory of an innovative enterprise must itself be embedded in a model of relations among industrial sectors, business enterprises, and economic institutions. In addition to the conditions for financial commitment (as opposed to financialization, discussed in other chapters in this volume), Lazonick identifies two other social conditions which are essential for the innovative enterprise to thrive. First, strategic control is the set of relations that gives decision makers the power to allocate the firm’s resources to confront the technological, market, and competitive uncertainties inherent in the innovation process. Second, organizational integration is the extent to which there are the incentives for people to apply skills and efforts to the learning required at the heart of the innovation process (see also Khan, ). There is an important interdependence of the organizational capabilities with formal knowledge and skills (Khan, ). While this conception of the firm grapples with issues of coordination and control, the performance of firms is based on the extent to which they are effective in terms of arrangements, given the competitive challenges of the time and industry in question. Drawing on resource-based theories, Best () identifies the ‘new competition’ as

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being where performance rests on the ‘resources and experience of the parent concern, including not only managerial and technical personnel but also the indefinable advantage in its internal operations which an efficient going concern usually has over a new one’. Firms also choose to collaborate (as well as to make or buy), and networked groupings will outcompete competing groups of firms (Richardson, ). This is because competition between firms does not support the emergence of specialized firms with networked complementarities as part of clusters. The extensions of the resource-based theory of the firm require enterprises to be located in production ecosystems if we are to take account of the social context and linkages which underpin dynamic capabilities (Andreoni, ). A successful industrial policy requires the articulation of public policy with the detailed mechanics of change that occur within businesses in a production-centric (rather than market-centric) framework (Best, ). Such a framework can be captured in a ‘capability triad’: business models; production capabilities, innovation, and skills; and clusters, networks, ecosystems, and learning. This triad underpins the creation of dynamic increasing returns and the innovation dynamics that underlie productivity growth. Industrial policies to alter a country’s development path need to realize external economies from stronger linkages, collective learning, and governance (Helmsing, ; Kaplinsky, ). Processes of learning and technical change involve the firm and the wider institutions of industrial policy (Lall and Teubal, ; Khan, ). A proactive industrial policy requires private dynamism and improving policy capability to ensure dynamic capacity development (Ohno, ). State policies reward value creation and innovation, while disciplining unproductive rent seeking. The focus in firms and industry clusters on knowledge, skills, and technologies needs to be mirrored by policy practitioners in government keeping up with industry developments and building effective engagement with industry. I identify three key areas for further in-depth assessment. First, the interaction of enterprises’ market power with the requirements of innovation and dynamic increasing returns is a key issue for understanding enterprises and industrial policy. Second, the evolving internationalization of production has fundamental implications for countries’ industrial development and policies. Third, digitalization is rapidly changing the organization and coordination of economic activity, including across borders. These are now addressed in turn. Other key issues, such as patterns of financialization, are equally important and are addressed by other contributions to this volume.

. M P, C,  E S

.................................................................................................................................. The significance of dynamic increasing returns to scale means that there will normally be only a few firms in key industries and that concentration is an inevitable feature of

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

industrial development. For example, large and internationalized firms have had a crucial role in developing key industries such as consumer electronics, automobiles, shipbuilding, steel, and basic chemicals around the world. Indeed, cross-industry regressions find scale economies is a strong explanatory factor for concentration (Sutton, , ). And smaller domestic markets relative to the minimum efficient scale of production in an industry means, other things being equal, that concentration will be higher in many developing countries. The importance of the large firms means they have considerable power over their suppliers and customers, as well as being important political actors. This has been emphasized in seminal work on the lead East Asian industrializers, where state support was contingent on performance expectations which could be enforced through disciplining mechanisms to ensure that the outcomes were in line with performance expectations (Amsden, ; Chang, ; Wade, ; Sakakibara and Porter, ). Competition in export markets was a key lever for discipline at the firm level and a way of measuring firms against each other even while offering protection in the domestic market (Rodrik, ; Singh, ). It also ensured that firms were forced to adopt and adapt more advanced technologies, production, and marketing methods, as they were being pitched against the international industry leaders in export markets. More generally, competitive rivalry between big business groups is a very important disciplining and motivating factor to ensure that state support does not lead to collusion and rent extraction. The nature of the rivalry is also an important element of Chandler’s characterizations of different capitalisms, although quite different from the neoclassical microeconomic elevation of competitive markets on the grounds of static allocative efficiency. Instead, it is part of the interaction of public policies and enterprise strategies to incentivize and support innovative capabilities. There is no ideal of maximum or perfect competition; rather, we can consider what is meant by an ‘optimal competition’ in terms of performance (Amsden and Singh, ; Singh, ). Management of the economic power of key companies requires reciprocal conditionalities (Amsden, , ). Rents are essential for inducing the effort and investment required on the part of firms to develop innovative capabilities. Once again, a neoclassical framing of markets which views market power as an aberration to be corrected is unable to take into account the real world of pervasive market power to differing degrees and, in particular, of those large firms required to undertake organization and technological learning. Competition and competitiveness are therefore a result of a successful industrial policy which involves the creation of productive rents, and discipline regarding their access. This can be equated with ‘performance competition’ where effort and innovation are rewarded rather than ‘handicap competition’ where firms seek to undermine their rivals (Gerber, ). There has been an increasing focus since the  publication of Piketty’s Capital in the Twenty-first Century on the implications of concentration of ownership and control for economic development and for inequality. It is argued that the returns from the exertion of market power go disproportionately to the wealthy and, on balance, market

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power discourages innovation and reduces productivity, as observed in the United States (Baker and Salop, ; Ennis et al., ; De Loecker and Eeckhout, ). Stronger competition law is sometimes recommended as the answer (see Stiglitz, ; Atkinson, ). There is little doubt that there has been a growing global concentration in the hands of transnational corporations. The largest TNCs have bigger revenues than many governments around the world. In , sixty-nine of the largest  corporate and government entities ranked by revenue were calculated to be corporations (Zingales, ).¹ This is not necessarily unprecedented. Under colonialism companies such as the British East India Company controlled the economies of countries with monopoly rights over trade in some commodities that lasted more than two centuries. Lobbying to maintain these rights turned firms away from improving productivity in a ‘Medici vicious circle’ where money is used to get power and power is used to make more money (Zingales, ). Control over global profits in major industries is in itself one drive for global concentration (Hymer, ). Network effects and the rise of digital platforms are one reason given for the increasing concentration in recent years. I discuss the implications of the digitalization of industry in section .. There are three main questions. First, under what terms will the concentration be accompanied by improved productivity rather than simply rent extraction? Second, how is the economic power of companies understood? Third, what is the nature of the political settlement with business which underpins learning and the development of dynamic capabilities?

.. Competition and Productivity While the promise of high monopolistic profits can spur innovation (in a Schumpeterian world), entrenched dominant firms have weaker incentives to invest, innovate, and improve productivity than if they are challenged by rivals (Schumpeter, ; Mathis and Sand-Zantman, ; Arrow, ; Bloom et al., ). Firms with substantial market power can earn returns from exertion of this power and protect their position by excluding rivals. As retained earnings are important for firms’ ability to make investments, smaller firms are typically more constrained in terms of the liquidity they can use to invest (Audretsch and Elston, ; Goergen and Renneboog, ). High entry barriers to rivals can weaken economy-wide investment, and can prevent new business models emerging and products being introduced (Shapiro, ; Cohen and Levin, ; Federico et al., ). Measuring and analysing productivity is complex precisely because of the different mechanisms at the firm and industry level that influence it. Management practices are ¹ These include corporations controlled by the Chinese state.

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one critical determinant. A major US study found substantial variations between different plants in the same firm, with four key factors explaining plant-level productivity: product competition; learning spillovers; education; and local business environment (Bloom et al., ). Policies required to support innovation by industries and address the weakening productivity performance in industrialized countries include support for R&D along with skills in science, technology, engineering, and mathematics, and measures to increase competitive rivalry (Bloom et al., ). The issue comes back to ensuring the right kind of rivalry (the ‘optimal competition’ of Amsden and Singh, ; Singh, ), which can spur large firms to continue to innovate and invest, rather than competition for its own sake (Van Reenen, ). A country does not arrive at such markets by magic. Indeed, it seems obvious that market power, imperfect competition, and market failures which can reinforce positions of market power are intrinsic features of economic life, and competition policy is a necessary complement to industrial policy (Roberts, ). We therefore need to understand how the process of evolving competitive rivalry is related to the nature of economic opportunity and outcomes. This has been an explicit but largely ignored aspect of competition regulation in South Korea, where the Korea Fair Trade Commission (KFTC) has monitored the conduct of chaebols, for example in subcontracting relationships to protect against exploitation of smaller firms (Hur, ; KFTC, ). Typically, in the short run such subcontracting arrangements would lower prices and hence not harm consumers. In the longer term, however, unfair subcontracting arrangements by large firms militate against the development of a dynamic base of small and medium firms able to invest in their own independent production capabilities.

.. Economic Power of Companies The power of companies to shape markets and influence policies over time is more important than the market power to charge high prices in any given period. A simplistic focus on market power measured in static terms as prices which are marked up over marginal cost is therefore as naïve and unhelpful as modelling the firm as a black-box internalization of transaction costs and even risks distracting attention from the more fundamental issues. The features of an industry, such as information asymmetries, scale economies and network effects, can provide scope for strategic behaviour on the part of dominant firms to lock in advantages through a range of different strategies (Rey and Tirole, ; Whinston, ; Vickers, ). Persistant dominance can suggest that it is not effort and creativity which are being rewarded but rather that the legacy position of large firms continues to earn them rewards. As Geroski and Jacquemin (: ) caution, ‘when, however, small asymmetries can be solidified into dominant positions that persist, the inequities they create become institutionalized, creating long-term problems in the performance of the

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 

economic system which cry out for policy attention’. In the context of small domestic markets, this is consistent with the significance of economies of scale, dynamic effects related to technology, and the importance of production linkages in processes of industrialization (Gal, ; Hur, ). The likelihood of entrenched dominant firms with extensive economic power depends on the country’s conditions and history which are reflected in different approaches to competition and industrial policy. For example, analyses have highlighted the importance of competitive discipline in the industrial development of East Asian countries such as Japan and South Korea (Amsden and Singh, ; Sakakibara and Porter, ). The objectives of South Korea’s KFTC have included promoting ‘balanced development’ in recognition that the early stages of rapid industrialization were viewed as ‘unbalanced’, requiring an active competition policy addressing dominant firms in that country (Fox, ; KFTC, ). Firms’ power exerted within markets extends to shaping vertical and horizontal relationships with other firms. This is incorporated in the coercive, dyadic power between firms, or between the state and firms, defined as ‘bargaining power’ by Dallas et al. (). Firms with substantial market power as buyers, for example, large supermarket groups, can undermine the ability and incentives of suppliers to reinvest and improve productive capabilities (Inderst and Mazzarotto, ; Inderst and Valletti, ). Through vertical arrangements lead firms are able to govern activities along value chains (Strange and Humphrey, ). Influence can also be more subtle at the horizontal level, as illustrated by findings on common ownership. Even relatively small common ownership stakes by private equity groups such as BlackRock and Vanguard in firms across economies have apparently influenced firm strategies to undermine investment and rivalry (Azar et al., , ; Newham et al., ; Seldeslachts et al., ). In industries such as airlines and pharmaceuticals there have been findings that common shareholdings reduce headto-head competition as it supports the alignment of incentives. Large firms exert power to shape markets in broader ways through collective groups such as business associations which lobby in direct ways, such as for a particular policy platform or regulation that favours some interests over others (Vilakazi and Roberts, ). Power is also exercised in more diffuse ways, such as by influencing accepted standards and best practices (Dallas et al., ; Ponte and Sturgeon, ). For example, the provisions adopted in competition legislation on abuse of dominance, or the nature of support for public research in industry, reflect a conceptual framework about markets and the role of the state in the economy. This is in turn an outcome of influence and ideas which are promoted within and through political parties, the media, and academia. This can be understood as part of the political settlement where elites exercise power through ‘informal institutions’, setting the agenda (Khan, ). The nature of the political settlement determines whether longer-term capabilities formation is rewarded, or coalitions of interests are made to enforce short-term rent extraction.

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.. Economic Power, Rents, and Political Settlement The orientation of large enterprises is thus intimately related to the balance of power between different interests in a country and the regulatory arrangements that are part of the wider political settlement (Khan, ). A settlement is defined as a combination of mutually compatible power relations and institutions that is sustainable in terms of economic and political viability (Khan, ). A given settlement depends on the coalitions of interests within countries and, for industrial development, whether this coalition supports the design and implementation of policies with incentives and conditions on firms to ensure high levels of effort in learning and technological upgrading, while disciplining the earning of rents from protection and subsidies (Khan, ). The political settlements framework emerged as a criticism of institutional economics and the position that competition with liberalized markets and independent institutions is the primary requirement for economic development. The grounds for this are that competition will erode rents which, along with liberalized markets, will move us to what North et al. () term ‘open access orders’. However, this supposes competition simply arises in the absence of obstacles and it fails to recognize the need to address entrenched inequality and economic power (Makhaya and Roberts, , ). And it does not properly explain what the underlying power arrangements and configuration of interests are that support a given institutional configuration (Khan, ). In addition, the institutional economics of North et al. () fails to recognize the important role that industrial policies and tariffs have played in countries’ industrialization—in other words, productive rents are required to induce investments in capabilities. We need to understand what coalitions of interests are required to sustain a policy framework for industrial development. Powerful elites organize through ‘informal institutions’, especially during development transitions, to sustain economic benefits for groups who would otherwise have lost out (Khan, ). They are thus the mechanisms through which social and political stability is maintained, helping to generate distributions of economic benefits that are more in line with existing distributions of power. In doing so they also sustain these distributions of power. The framework identifies four sources of ‘holding power’, which refers to the capacity to engage and survive conflicts—in other words, the ability to inflict costs and absorb costs inflicted by opposing groups. In addition to violence rights to exert control over populations, the sources of holding power include economic structure, ideology, and rents. The economic structure reflects a country’s economic history. This includes the construction of markets and the main participants, including the large incumbent businesses. The economic power of these companies, and how this influences the evolution of the political settlement, is central to whether the industrial policy will support the growth of diversified manufacturing sectors with higher levels of productivity (Khan and Blankenburg, ; Khan, ; Andreoni and Chang, ; Andreoni, ).

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 

The political settlement framework therefore allows us to assess how incumbent firms or groups of firms are able to lobby and enter into arrangements with political actors to shape regulation and the economic environment to ensure future rents. The evolving coalition of powerful interests effectively sets the rules of the game. Whether a country adopts a competition law appropriate for the country’s historical context, for example, with regard to the provisions on abuse of a dominant position, is part of this picture (Budzinski and Beigi, ; Roberts, ).

. D   I  P

.................................................................................................................................. The increased transnationalization of economic activity over the last fifty years has been driven by large international corporations. While big businesses were central to colonialism and earlier waves of globalization (Bairoch and Kozul-Wright, ), the internationalization of production which now exists is much more multi-dimensional, encompassing governance of trade, technology, value creation, brands, data, and the related rents. It is associated with the ability to coordinate productive resources through a multiplicity of governance arrangements beyond vertical integration of corporations. These blur the boundary of the firm, although not as a ‘nexus of contracts’ but as a ‘locus of control’. The exponential expansion in global trade (notwithstanding recent stalling) has far outpaced GDP growth. Information and communication technologies have enabled the global dispersion of economic activity while being centrally governed by ‘lead firms’, as described in the literature on global value chains (GVCs) and global production networks (Bair, ; Gereffi et al., ; Ponte and Sturgeon, ; Coe and Yeung, ). This has included rapid growth in trade in services, including under digitalization of processes within firms and along value chains (Baldwin, ). Large internationalized firms are pursuing low costs combined with flexibility and speed (Coe and Yeung, ). The digitalization of economic activity has further been associated with a shift in the proportions of value added—with a higher share going to pre- and post-production activities than to production activities (Baldwin, ; Rehnberg and Ponte, ). There have been major advances in technology in the fields of bio-tech, design, advanced manufacturing, and artificial intelligence, as well as the rise of digital platforms in e-commerce, online search, and social networking which merits a separate discussion in section ... The term ‘transnational’ is more appropriate for large internationalized corporations rather than ‘multinational’, as the corporate organization of economy activity transcends nation states. Profits are attributed to subsidiaries and associated companies according to the favourable tax treatment by different jurisdictions, while research activities, ownership of intellectual property, manufacture, marketing, branding, and

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head office functions may all be spread around the globe. Meanwhile regulation of TNCs and industrial policies remains predominantly national in scope, or at best regional in the case of the EU. There are notable exceptions to the transnational (as opposed to multinational) organization of production, in particular in the internationalization of Chinese corporations where the state plays a pivotal role (see Oqubay and Lin, ). The growing importance of intermediate goods in international trade, with prices being administratively determined as transfer prices within firms or agreed between related parties, reflects the importance of GVCs. Chapter  elsewhere in this book (Chapter , this volume) assess the importance of GVCs, including the implications for industrial policy to upgrade firms’ capabilities, create employment and support more inclusive growth. The emerging evidence is, however, that the organization of production in GVCs has further polarized income and wealth distribution in both developed and developing countries (UNCTAD, ). The reasons given for this include the nature of technological change (Rodrik, ; Ford, ) and the concentrated market structure and dominance of trade by large transnational corporations (UNCTAD, ). The implications of TNCs for industrial development and the design and implementation of industrial policy has been recognized for some time. For example, over twenty-five years ago Lall () identified five areas for future research with regard to TNCs: entrepreneurship and innovation; technological change; the conditions required to stimulate TNC activity as part of paths of dynamic comparative advantage; the different characteristics of TNCs from different countries and the evolution of less developed-country TNCs; and the relationship between FDI in services (such as communications and marketing) and economic development. These all remain extremely relevant today, with a particular extension to the implications of the international digitalization of economic activity, addressed in section .. The international spread of businesses has been described in terms of ownership, location and internalization (OLI) factors in Dunning’s eclectic framework (Dunning, ; Cantwell, ). This asks relevant questions related to the intra-firm location and organization of activities across countries. However, it is rooted in the transactioncosts theory of the firm (which drives internalization decisions, according to the framework), albeit combined with other factors such as technological advantages and agglomeration economies. In particular, it lacks a proper political economy understanding of large business and an assessment of the organization of production. The omission hides an apparent leaning of many writers within the paradigm towards seeing the firm as essentially an efficient response to conditions rather than a means to coordinate production and secure profits. This fits with a business-oriented policy agenda for the de-politicization of economic policy and promotion of a technocratic approach, which is not consistent with the observed reality, nor with businesses’ own behaviour (Vilakazi and Roberts, ; Hymer, ). Understanding the internationalization of production requires a framework which explains the evolving organization of production, drawing on resource-based theories

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 

of the firm in terms of firms’ productive resources, organizational capabilities, and competencies. The international competitiveness of business is determined to a significant extent by the position and power of the firm both with regard to competitors and within the production chain, which in turn depends on a range of non-/semi-market relationships, on dimensions of internationalization other than trade and ownership, and on the position of groupings of business in the domestic economy. The literature on GVCs analyses inter-firm linkages and vertical relations regarding design, production, and marketing of products as layers of value addition (Gereffi and Fernandez-Stark, ). These linked activities span different enterprises often located in both developed and developing countries. The geographic fragmentation of activities means that developing countries can attract some activities in a value chain. However, for this to be part of sustained productive capability building depends on local industrial clusters of producers of intermediate goods and services (Lee et al., ). The opening up of opportunities for process and product upgrading in developing countries depends on the overall governance and control of the value chain, and the ways in which industrial policies alter the governance of the chain by key firms (Ponte and Sturgeon, ). Lead firms coordinate activities to ensure the competitiveness of the end product and are able to exploit often extremely asymmetrical power relations between firms within value chains to control how, where, and by whom value is created and captured (Gereffi and Fernandez-Stark, ). The influence of the lead firm depends on the nature of the sector and the basis of competitiveness. Value chains such as automobiles have been identified as producer driven due to the importance of technology and design (Gereffi and Fernandez-Stark, ). In buyer-driven chains, such as clothing, the owners of the brands hold the power. The relationships range from arms-length market exchange, such as to drive down costs through outsourcing, through close relational governance such as for coordinating product-specific design, to fully internalized linkages (Gereffi et al., ; Bair, ; Gereffi, ). The digitalization of production networks and value chains enables greater coordination of activities across borders and shifts power to the firms who collate and analyse the data. The nature of governance over internationalized production is changing, with new strategic industries and sectors which are the locus of control over data and underpin dynamic capabilities (Petricevic and Teece, ).

. D  P, E,  I P

.................................................................................................................................. A rapid digitalization of production is taking place associated with key technologies at different stages of maturity, including advanced robotics and factory automation, data from mobile and ubiquitous Internet connectivity, cloud computing, big-data analytics,

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machine learning, and artificial intelligence. This is associated with the development of new ‘platform’ business models and modes of value creation (UNCTAD, ; Sturgeon, ). The technologies and business models emerging in the digital economy have already disrupted traditional industries and created entirely new ones.²

.. Digitalization of Production Advanced manufacturing and automation can be understood as fully integrated, collaborative manufacturing systems that respond in real time to changing demands and conditions in the factory and the supply network. Though this typically relates to ‘smart factories’, it is equally applicable in agriculture, commonly referred to as ‘precision farming’, or even mining or construction. Advanced manufacturing is made possible by a combination of technologies including robotics, sensors, machine learning, and the Internet of things (IoT). Industrial robots linked to advanced manufacturing are automatically controlled and operate on their own. They are multipurpose (reprogrammable) and capable of doing different kinds of tasks rather than simply repeating the same tasks. The technological changes have profound implications for the coordination of economic activity by firms and the division of returns (UNCTAD, ). Digital tools can improve design, prototyping and customization processes, reducing scale economies, and opening opportunities for businesses in developing countries; however, advanced economies have tended to retain control of higher value-added activities. While, in principle, digital platforms can lower costs for smaller businesses to market their products and services, most digital platforms are characterized by high levels of concentration. Many of the technological changes are also skills biased and may undermine the ability of developing countries to compete in traditionally labourintensive industries that have supported their industrialization (Rodrik, ). Transnational corporations in the form of digital platforms are shaping global economic activity and pose new challenges for industrial policy around the world. In addition, there are substantial emerging regulatory challenges associated with the ownership and control of the data that provide major platforms with their power and associated commercial value (UNCTAD, ; Polson and Scott, ; McAfee and Brynjolfsson, ). The nature of the changes can be incremental as well as disruptive. Incremental changes include improving supply chain integration across firms through digital tracking of product flow and quality at every stage, which can be combined with

² This section draws on discussions with Rashmi Banga, Justin Barnes, Anthony Black, Parminder Jeet Singh, Stefano Ponte, and Tim Sturgeon, for the Digital Industrial Policy Issues paper produced by the Industrial Development Think Tank at the University of Johannesburg.

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 

machine learning to improve processes and respond to changes in the environment. Disruptive changes mean fundamentally altering the way products and services are created and delivered, for example, through D printing of products on demand. Digitalization also enables a dynamic cycle of continuously improved efficiency that is increasingly being driven by the rapid advance of machine learning (artificial intelligence). Maintaining competitiveness means adopting the incremental changes to build the capabilities of clusters of firms and, as such, engaging with the international technology leaders. The generation of ‘big data’ is a characteristic feature of digitalization. Data can be collected through sensors in production, from users of the product or service, and from the online search and purchasing activities of buyers. It is possible for firms to track performance across multiple production sites and distribution channels and to provide new services such as real-time monitoring of product use and/or performance using big-data analytics, and increasingly, artificial intelligence (Sturgeon, ). This is often referred to as the industrial Internet of things. It heightens the potential for centralized control across dispersed production sites and along logistics chains, enabling a further transnationalization of production.

.. Digital Platforms The more members or users on a platform, the more data is collated and the greater its value to other users in respect of data aggregation and analysis. There are strong economies of scale and scope and the positive network externality effects within and across different user groups of the platforms imply they are likely to tip to the ‘winner-takes-all’ quasi-monopoly (see Furman et al., ; Cremer et al., ; Committee for Study of Digital Platforms, ). There are major barriers to smaller competitors attempting to enter the market and the dominant platforms can exert substantial market power, requiring a rethink of the appropriate regulatory and policy framework. Data itself is an asset and the ownership and control of data is an important determinant of power relations in value chains and over markets. The data are collected partly in order to provide the service in question and partly as a by-product of the service. Moreover, the combination of data from different sources enables additional value to be offered. This underpins the substantial network effects where the aggregator of data is able to offer better services by virtue of having more users across the different ‘sides’ of their platforms (for example, suppliers of goods and consumers). First movers are therefore able to lock in their advantages. The routes to customers are increasingly through one of a very few ‘technology giants’, whether in online search, social networks, or e-commerce. These online platforms bring together consumer data and analysis, logistics, and payments. Firms such as Amazon and Alibaba have immense scale, strong brand identity, supplier

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networks, and data capabilities. Multi-sided online platforms are able to aggregate and analyse data from groups of users. The technology giants have been able to grow so fast partly because they have been allowed to acquire small and innovative companies without much consideration given to the possible harmful long-run effects on competition. Between  and  Google acquired  companies, Facebook acquired seventy-one companies and Amazon acquired sixty companies (LEAR, ). The reviews carried out in  and  for various governments and competition authorities, including those in the EU, Australia, and the United Kingdom, find that merger evaluation needs to recognize the competitive value of data, the harm to potential competition, and the possible conglomerate effects of such mergers.³ In other words, the assessment needs to extend beyond static analysis of whether there will be a lessening of competition from the merger due to firms being in horizontal or vertical relationships. The convergence of platforms which operate in and across payments systems, retailing, logistics, customer information and marketing, and telecoms requires regulation through a flexible and responsive regime. In addition, an enabling environment for the digitalization of business, including more reliable and cheaper connectivity and an urgent upgrading of the skills pool in big-data analytics, is urgently required to open up markets to local entrepreneurs. The evolving nature of economic power that arises from the digitalization of economic activity and the importance of digital platforms has huge implications for industrial development and industrial policy. The governance of value chains and production networks, as well as the very determination of what constitutes the value (including for tax purposes) is controlled by the aggregator of the core data in the form of the online platforms. The growth and competitiveness of local businesses depends on the terms on which they can insert themselves into, and/or interface with, the dominant international platforms. Europe has led competition enforcement of digital platforms with three decisions against Google as of September . These cases highlight the mechanisms by which power is exerted to shape markets. The European Commission’s Google Shopping case addressed the ability to preference partners in search results, restricting consumer choices, and raising prices paid by consumers.⁴ Similar concerns relating to consumers’ online searching behaviour have been identified in UK competition and consumer

³ The UK and EU reviews are respectively Furman et al. () and Cremer et al. (). For Australia see Australia Competition and Consumer Commission Digital Platform Inquiry Final Report, . For Germany see Report by the Commission ‘Competition Law .’, ‘A New Competition Framework for the Digital Economy’, report for the Federal Ministry for Economic Affairs and Energy, available at https://www.bmwi.de/Redaktion/EN/Publikationen/Wirtschaft/a-new-competition-frameworkfor-the-digital-economy.html. ⁴ European Commission, Decision of  June , case AT.–Google Search (Shopping).

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 

protection matters related to digital comparison tools and online hotel booking.⁵ India has taken a decision regarding Google preferencing searches for flights. The EC’s Google Android case related to Google extending and protecting market power with regard to restrictive terms applied to the Google Playstore for apps on mobile phones, as well as to the development of alternative Android operating systems.⁶ The Google Adsense case relates to Google extending power over advertising space on thirdparty websites.⁷ These cases emphasize the evolving ways in which routes to market now depend increasingly on the online reach to consumers including online advertising. The competition policy recommendations that have been made in the various reviews include changing the standards in merger control to consider a ‘balance of harms’ test, and designating companies as having ‘strategic market status’ with greater obligations not to distort competition. To ensure that there is consistency of regulation and competition enforcement some reviews have proposed establishing a regulatory ‘data unit’ with powers to obtain information, and timeously make and enforce orders. This recognizes the central role that control over, and access to, data has for economic participation.

.. Industrial Policy Implications The rise of digital platform businesses as the largest global corporations, and the importance of data for the competitiveness of firms of all sizes, poses fundamental challenges for industrial policy. The major technological changes in the ‘new digital economy’ require business models that can integrate, coordinate, and control value creation across businesses. Industrial policy and economic regulation similarly need to be consistent and support public organizations that set the standards required to support the interconnection and integration of components and subsystems into larger systems. Three business models have been identified as key to these goals (Sturgeon, ): • Modularity describes a business model based on interchangeability, where subcomponents can be added or subtracted without redesigning entire systems. On the factory floor, different sub-assemblies with shared interfaces can be substituted in the assembly of larger products. In product design, off-the-shelf or lightly customized modular components can be designed in as elements of larger systems. In supply chains, standards and protocols allow for complex information about ⁵ UK Competition and Markets Authority: press release of  September , available at https:// www.gov.uk/government/news/major-overhaul-of-hotel-booking-sector-after-cma-action; report on Digital Comparison Tools Market Study, available at https://assets.publishing.service.gov.uk/media/ cead/digital-comparison-tools-market-study-final-report.pdf. ⁶ European Commission, Decision of  July , Case AT.–Google Android. ⁷ European Commission, Decision of  March , AT.–Google Search (AdSense).

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products, production, and logistics to be exchanged across organizational and geographic boundaries.⁸ • Open innovation refers to the pre-competitive pooling of R&D activities and design criteria, either through consortia, or through the voluntary ‘crowdsourcing’ efforts of engineers and technologists interested in creating free resources for their communities. For example, nearly all the world’s major computer programming languages, such as Python, are open source and free. Like modularity, open innovation helps companies ‘vertically specialize’, that is, develop a strategic focus on a specific bundle of competencies, while still providing customers with a rich set of fully functional products and solutions. • Platforms provide services for networks of users, bringing together those using the platform to sell goods and services with consumers looking to purchase, effectively shaping and creating the markets themselves. The platform owners benefit from aggregating user data (including from key components such as geo-location and mapping) and charging for advertising, and can vertically integrate into the suppliers of the goods and services. The platforms can then channel consumers to the platform’s preferred services. Digitalization means that a coordinated industrial policy which prioritizes key sectors and cross-cutting activities is even more important. The spillover effects mean that industry-specific and cross-cutting technology and skills support are both critical. This includes the key enablers of skills in software engineering, data science, and related ICT skills, along with intermediate industries such as electronic control systems, logistics, design, and additive manufacturing. Development finance for investments in productive capabilities, upgrading of capital equipment, and supply-chain integration remains essential. The significance of digital platforms which straddle communication, media, publishing, search, e-commerce, finance, and payments requires a rethink of competition and regulation to establish rules for platforms to ensure local businesses are not discriminated against. Legal provisions asserting ownership of data on behalf of citizens are a necessary step at the national level, while countries such as Rwanda and India have taken steps to ensure local businesses are not undermined by transnational e-commerce businesses. Effective regulation is an industrial policy imperative when control over data is a barrier to being able to compete. This needs to be coupled with vertical policies to support stronger local linkages. While policy design and the governance framework are critical, the effective implementation and enforcement of any industrial policy will depend on government capacity and laws to ensure access to data. The implementation of a digital industrial policy requires the establishment of high-level coordination capacity, institutionalized private-sector inputs, and appropriate monitoring and evaluation systems. New ⁸ The standards and protocols supporting value-chain modularity are often embedded in digital ICT systems such as CAD/CAM and ERP.

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

 

coalitions for change forged around better aligned productive interests are necessary for the successful implementation of industrial policy, enabling sector-specific and cross-sectoral interventions.

. C

.................................................................................................................................. Enterprises are at the centre of understanding the processes of industrialization, and the potential for, and constraints on, industrial policy. A dynamic private sector is critical for catch-up by developing countries (Ohno, ). The transaction-costs theories of the firm which have dominated economics are, however, effectively unable to come to terms with the most important questions of dynamic organizational capabilities—the strategic orientation of large internationalized businesses and the nature of power relations and the political settlement. The resource-based theory of the firm, developed through detailed empirical study within and across countries, provides a robust framework for analysing the development of capabilities. It has been extended in terms of the ways in which power is understood and the internationalization of businesses. The implications of digitalization are subject to intense current research pointing to major changes in the nature of firm-level governance of economic activity and the appropriate industrial policies. Substantial economic power on the part of firms is an intrinsic feature of industrial development given the dynamic economies involved. There is therefore a natural tension between the short-term objectives of firms in securing and exploiting rents, and the longer-term investments required to build dynamic productive capabilities taking into account the uncertainties involved. This tension is at the heart of an effective industrial policy which has analysis of firms located in a production-centric framework. A critical objective of industrial policy is therefore to shift the calculus on the part of large firms, to be able to set and enforce conditionalities for the support required. The effective engagement with large firms includes locating them in clusters, with long-term relationships with smaller firms as subcontractors, through policies supporting shared research and development, skills improvement, ongoing capabilities upgrading, and product development. The greater emphasis which is now being placed on concentration of ownership and control in many countries is welcome. It is part of a rethink of competition policy which recognizes competition as a dynamic process of rivalry underpinning ongoing improvements in productivity. An effective framework for competition and economic regulation, which sets the rules for markets, complements industrial policies. Assessing the debates about concentration and the appropriate policy responses requires attention to the influence of coalitions of large business interests over the policy agenda in indirect and diffuse ways, as well as alternative coalitions which can underpin progressive industrial policies.

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   



The internationalization of businesses in the context of the digitalization of economic activity raises important questions about the ability of regulations and industrial policies at a national level to discipline the conduct of businesses. Large developing countries have greater scope to take appropriate measures, including supporting alternative digital platforms, in which China is leading. Countries with smaller economies, such as those in Africa, are in relatively weak positions and depend on a broader international development coalition to underpin effective regulation of the global digital platforms. At the national level, countries need to ensure access to data for local businesses as part of a digital industrial policy platform to support local capabilities in targeted sectors and cross-cutting measures for the critical skills and investment required to adapt to the digitalization of economic activity.

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   



Sutton, John () ‘Market Structure: Theory and Evidence’, in Robert H. Porter and Mark Armstrong (eds) Handbook of Industrial Organization, Volume III. Amsterdam: Elsevier, pp. –. Sutton, John () Competing in Capabilities: the Globalisation Process. Oxford: Oxford University Press. Teece, David J. () Dynamic Capabilities and Strategic Management: Organizing for Innovation and Growth. Oxford: Oxford University Press. Teece, David J. () ‘Alfred Chandler and “Capabilities” Theories of Strategy and Management’, Industrial and Corporate Change (): –. Teece, David J. and Gary Pisano () ‘The Dynamic Capabilities of Firms: An Introduction’, in Giovanni Dosi, David J. Teece, and Josef Chytry (eds) Technology, Organization, and Competitiveness: Perspectives on Industrial and Corporate Change. Oxford: Oxford University Press, pp. –. Teece, David J., Gary Pisano, and Amy Shuen () ‘Dynamic Capabilities and Strategic Management’, Strategic Management Journal (): –. UNCTAD () Trade and Development Report. Geneva: UNCTAD. Van Reenen, John () ‘Increasing Difference between Firms: Market Power and the Macro-economy’, Proceedings of the  The Federal Reserve Bank of Kansas City Economic Policy Symposium: Changing Market Structures and Implications for Monetary Policy, Jackson Hole, WY, August. Vickers, John () ‘Abuse of Market Power’, The Economic Journal : –. Vilakazi, Thando and Simon Roberts () ‘Cartels as “Fraud”? Insights from Collusion in Southern and East Africa in the Fertilizer and Cement Industries’, Review of African Political Economy (): –. Wade, Robert () Governing the Market: Economic Theory and the Role of Government in East Asian Industrialization. Princeton, NJ: Princeton University Press. Whinston, Michael () Lectures on Antitrust Economics. Cambridge, MA: MIT Press. Williamson, Oliver () Economic Organisation: Firms, Markets, and Policy Control. New York: Harvester Wheatsheaf. Zingales, Luigi () ‘Towards a Political Theory of the Firm’, Journal of Economic Perspectives (): –.

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  ......................................................................................................................

     .............................................................................................................

 ,  ,   

. I

.................................................................................................................................. I restructuring has been taking place in the Global North since the s. Ongoing de-industrialization, downsizing, outsourcing, off-shoring, and just-in-time production have had a profound impact on the conditions of work and on workers, marked by worsening precarity and lower wages (Lazonick and O’Sullivan, ; Milberg and Winkler, ; Tregenna, , ). The last forty years has seen a dramatic rebalancing of power in favour of capital, exemplified by the increasing share of income distributed to capital and stagnant real wages for labour (Giovannoni, ; Stockhammer et al., ). This has been most pronounced in state responses to the financial crisis, which have amounted to bailouts for capital, austerity for workers, and anti-union legislation. This economic malaise, together with impending climate catastrophe, has generated greater calls for inclusive and sustainable economic growth and development. Can growth be made to be more equitable and socially and environmentally sustainable through industrial restructuring and industrial development? Are there viable alternative ways of organizing production so that it is more democratic? Can industrial policy contribute to shifting power relations—internationally in favour of peripheral countries, and domestically in favour of the working class as well as in favour of women and other oppressed groups. These are among the key concerns of radical industrial policy that go beyond just capturing a greater share of global manufacturing production, and/ or changing the identity of the owners of industrial capital (for example, from former colonialist to indigenous). Radical industrial policy, we argue, emphasizes class structures and relations, including the importance of exploitation, and the subjugation of labour to capital as

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    



central to capitalist accumulation. It should be noted that class structures and relations are also racialized and gendered, as expressed in the division of labour. Industrial development is thus not gender neutral and occurs historically in interaction with prevailing structures of oppression in a co-constitutive manner. For example, the gendered division of labour and low wages for ‘feminized’ work is premised upon, and reproduces, social structures that place the burden of unpaid social reproduction on women in the home. Industrial policy choices can contribute to deepening or displacing patriarchal social structures. Chapter  in this volume, by Seguino, focuses on a gendered approach to industrialization and industrial policy.¹ Analytically, radical industrial policy must necessarily take into account gendered social and economic relationships. Prescriptively, radical industrial policy would also actively seek to promote a trajectory of industrial development in which women are empowered and gender inequality is reduced. This chapter aims to survey, evaluate, and develop radical perspectives on industrial policy. Radical industrial policy is both analytic—understanding how capitalism works—and prescriptive—suggesting what should guide industrial policy. We consider radical industrial policy as also aiming at fundamentally changing productive structures and dynamics of accumulation in the direction of labour-centred economic and political restructuring. ‘Labour-centred’ refers not only to the distribution of gains from development in the interest of labour, but also to the central participatory and determining role of labour in the process. We begin the chapter by discussing radical approaches to the role of the manufacturing sector and to industrialization, reflecting on how these approaches differ from both other heterodox and mainstream approaches. We go on to analyse radical approaches to industrial policy, focusing on the conceptual and theoretical levels, with particular attention to the inherent contradictions of capital‒labour relations under capitalism, the contradictory role of the state, and radical industrial policy with respect to the case of the climate crisis. We next discuss historical experiences of radical industrial policies with specific reference to statist, local co-operative, and participatory planning models of industrial policy and industrial development. By way of conclusion, we consider what is distinctive about radical industrial policy and what value such an approach adds. We also reflect on the limitations of industrial policy, especially under globalized and financialized capitalism. The effects of industrial policy on the balance of power are likely to be contingent and conjuncturally specific, and we discuss the factors affecting these outcomes. Finally, we consider the possibilities for radical industrial policies in current global and national conditions.

¹ See also, for instance, Berik, Rodgers, and Seguino (), Braunstein (), Çağatay and Özler (), Elson and Pearson (), İzdeş and Tregenna (), Kucera and Tejani (), and Seguino and Braunstein ().

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

 ,  ,   

. R A   R  M  I

.................................................................................................................................. Here we discuss radical approaches to the role of manufacturing in growth and development at a theoretical level. Rather than attempting to survey all ‘radical’ approaches to these issues, we focus on the structuralist and Kaldorian traditions, and on a Marxist approach. The approach to sectors is one of the important dimensions along which mainstream and heterodox economics can be distinguished. Mainstream economic approaches are generally sector neutral in the sense that the marginal effects of an additional unit of value added or of labour on growth do not vary by sector. Sectors are seen primarily as a way of classifying economic activities. While there is recognition of common characteristics within sectors, the growth process itself is not seen as sector specific. In contrast, heterodox approaches tend to view growth as sector specific. This is in the sense of the composition of output and employment affecting the potentiality of growth, and marginal increases in value added or labour affecting growth differently depending on the sector in which these increases occur. More specifically, the manufacturing sector is deemed to have a special role to play as an engine of economic growth, as discussed in section .. below.

.. Kaldorian and Structuralist Approaches: Manufacturing as a Special Engine of Growth Among the various heterodox schools of thought, it is in Kaldorian and structuralist approaches that the sector specificity of growth and the special role of manufacturing come out most clearly.² The structuralist approach to development was first developed by economists associated with the Economic Commission for Latin America and the Caribbean (ECLAC). ECLAC identified the dual problems of foreign exchange constraints and the tendency towards deterioration in the terms of trade for commodity exports as holding back sustainable growth in developing countries. These problems derive both from the structure of production in developing countries, and from the nature of articulation between ‘periphery’ countries on the one hand, and ‘core’ or ‘centre’ economies on the other hand. In structuralist thought, manufacturing matters and growth is product specific both on the supply side and on the demand side. From this perspective, industrialization is the key—or in fact the only viable—path ² See Ocampo, Chapter , this volume for a discussion of the structuralist approach to industrial policy.

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    



through which developing countries can catch up with advanced economies (Blankenburg et al., ). The importance of manufacturing as an engine of growth was theorized and formalized through Kaldor’s three laws (Kaldor, , , ). In brief, the first of these laws states that faster output growth in manufacturing is associated with faster aggregate economic growth. The second law, also known as Verdoorn’s Law (see Verdoorn,  []), states that productivity growth in manufacturing is endogenous to the growth of manufacturing output. According to the third law, aggregate productivity growth is positively related to the growth of manufacturing output and employment. The Kaldorian school of thought thus emphasizes the special role of manufacturing in driving economic growth. Kaldor’s views of increasing returns build on the ideas of Young (), who emphasized the importance of dynamic increasing returns as distinct from firm-level static increasing returns. Cramer and Tregenna () argue that one of the ways in which mainstream and heterodox approaches differ is in the recognition and treatment of increasing returns. In neoclassical thought, increasing returns are typically either ignored or are dealt with in an extremely limited fashion (see Best, ).³ Superior scope for dynamic increasing returns in manufacturing, relative to other sectors, is one of the key premises for a special role for manufacturing and for the emphasis on industrialization. Schumpeter’s wide-ranging contributions to economics also have implications for understanding the dynamics of accumulation, including around business cycles and long waves, innovation, and entrepreneurship. While Schumpeter’s approach is fundamentally different from Marx’s, he does draw on insights from Marx, including around the instability of capitalism and the inevitability of crises (see Rosenberg, ). Schumpeter places less emphasis on class and exploitation, and more on the role of the entrepreneur. (See Cimoli, Dosi, and Yu, Chapter  in this volume, on evolutionary and neo-Schumpeterian perspectives on technological change and industrial policy.) Associated more or less directly with these traditions within heterodox economics have been various applied studies, especially over the past three decades or so, of country and regional industrialization experiences. Seminal contributions on East Asian industrialization include Amsden (, ), Chang (), and Wade (). Oqubay () is a recent study of the case of Ethiopia, from a similar theoretical standpoint. These studies bear out the ongoing relevance of industrialization.⁴ We return below to the implications of different theoretical perspectives for industrial policy and to an appraisal of experiences of radical industrial policy.

³ Also of interest here is Babbage’s view of the ‘law of multiples’ in industrial production, which relates to increasing returns and the division of labour and to the problem of indivisibility, and to the sector specificity of this. This has implications for the scaling up of industrial production, and hence for industrial policy (see Andreoni and Scazzieri, ). ⁴ See also the country and regional experiences of industrial policy discussed in Parts IV and V of this volume, which draw attention to the diverse experiences of industrial policy and industrialization internationally and over time.

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

 ,  ,   

.. A Marxist Approach to Manufacturing and Industrialization Marxist economics takes a fundamentally different starting point from these other heterodox approaches and uses different categories of analysis. While Kaldorian/ structuralist traditions differ from mainstream economics in their approach to the sector specificity or sector neutrality of growth, they share a view of economic activity as categorized in the first instance in sectors. In Marx, by contrast, the basic issue is whether or not an activity is productive of surplus value (Tregenna, , ). Surplus value is generated in the (capitalistic) production of commodities. The primary basis for classifying economic activities in a Marxist schema is thus according to their position in the circuit of capital, and this does not fully coincide with sectoral distinctions. While sectors are not the starting point in a Marxist approach, such an approach is also not sector neutral. Marx does discuss sectors at length in various works, and identifies a special role for manufacturing in the processes of accumulation and growth. In fact, Tregenna () argues that the special characteristics of manufacturing that are associated with the structuralist and Kaldorian traditions (see earlier discussion) can be traced to Marx’s own writings. What Marx terms ‘modern machine industry’ is central to what he sees as the progressivity and dynamism of the capitalist accumulation process. He regards mechanization and industrialization as closely linked with the overcoming of human limitations in the production process, with competition between firms, with the concentration of ownership and control and the associated emergence of large-scale enterprises, and with the internationalization of production (Marx,  [],  []; Marx and Engels,  [/]). Marx’s analysis was animated by the dramatic transformations rendered by the First Industrial Revolution; he observed both the exploitation and social misery occasioned by this, as well as the unprecedented pace of accumulation and of technological and economic progress. More specifically, Marx identifies the features of manufacturing that lend it dynamism and provide the basis for sustained growth in the rate of relative surplus value as including: scope for both the division of labour and the socialization of labour; technological advancement; mechanization; learning by doing; increasing returns to scale; and overall, stronger potential for cumulative productivity increases (Tregenna, , ; see also Ricoy, ). We can perceive here the commonalities between Marx’s view of manufacturing and the Kaldorian and structuralist traditions that emerged in the second half of the twentieth century. For Marx, cumulative causation in manufacturing provides the basis for sustained growth in the productivity of labour, and thence in the rate of relative surplus value. With the rate of relative surplus-value production being central to the rate of accumulation, we can then see the sector specificity of growth in a Marxist approach (see Tregenna, ).

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    



As with non-Marxist radical approaches, Marx sees industrialization not only as central to accumulation and growth, but as transformative of wider social relations (see, for example, Marx and Engels,  [/]). Of course, an important difference between Marxist and other radical approaches is that, in Marxism, the analytical framework is part of a broader political project for revolutionizing the way that production is organized and the very nature of society, as discussed elsewhere in this chapter. Furthermore, while Marx is concerned with accumulation and growth and with the dynamism of capitalism, it is exploitation and class relations that take centre stage rather than economic growth and catching up between countries. Both Marxist and structuralist/Kaldorian perspectives recognize the sector specificity of growth, but a Marxist analysis is arguably less ‘sector fundamentalist’ than in the structuralist and Kaldorian traditions. From a Marxist stance, there is a great deal of heterogeneity within sectors, as sectors comprise activities with totally different relationships to the production and distribution of surplus value (see Tregenna, , ). Manufacturing is seen as having a special role to play in accumulation and growth, yet not all manufacturing activities necessarily have greater scope for producing relative surplus value than all (capitalist commodity-producing) activities in other sectors. In this section, we have discussed different approaches to sector specificity and to the role of manufacturing and to industrialization. We have drawn out the commonalities between different radical approaches (in contradistinction to mainstream economics), as well as some pertinent differences between them. Different conceptualizations of manufacturing and industrialization discussed here are part of fundamentally different political projects, with different concerns and aspirations. Moreover, these conceptualizations lead to different policy perspectives, in particular around the role and nature of industrial policy. This is the focus of section ..

. M  I P: B S  D

.................................................................................................................................. Marx’s analysis of capital accumulation and of capitalism goes beyond what might be called a technical analysis of the role of manufacturing in industrialization or a sectorspecific conception of growth. Marx’s concern is with the overall dynamics of accumulation and how they are founded upon, and reproduce, class differences and entail processes of class exploitation. As such, Marx is concerned with issues of the creation, circulation, and distribution of value, the power relations involved in this and the struggles that ensue, as well as with crises, as central dynamics of accumulation. In this section we look, first, at how Marx goes beyond the technical in ways that are both similar to, and different from, structuralist analyses. Second, we argue that radical approaches to industrial policy can be understood at both analytical and prescriptive

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

 ,  ,   

levels. Third, we use the example of the climate crisis to argue the case for radical industrial policy today.

.. Value, Exploitation, and Power in Capitalism Through his critique of classical political economy, Marx developed an analysis of capital accumulation that demonstrates its dynamic and radical nature, particularly when compared to earlier modes of production, but also its exploitative and destructive character. Competition between rival units of capital drives capitalists to innovate and to restructure production ‘on pain of death’, producing a tendency to drive up productivity and for capital to expand across the globe. This makes technical change far more rapid and systematic than in previous modes of production. At the same time, capitalist accumulation is based upon the subjugation of labour to capital, as propertyless labour is forced to sell its labour power to capital in order to survive, and competition compels capitals to seek new ways to increase surplus-value extraction. Capitalist accumulation is therefore inherently unequal and contradictory, and it is not only the market and the sphere of exchange, but also the relations of production, that are critical for Marx (Brenner, ; Weeks, ). It follows that an equitable society requires a profound reorganization of society and the reorientation of work and production to meet human needs and not simply the goal of profit (Spencer, ).⁵ The problematic for Marx, then, is that of capitalist industrial development, not industrial development per se. The state, the subject of some debate within Marxism (see, for example, Clarke, ), is also viewed as part of capitalist social relations. Marx’s analysis is inherently concerned with power relations and dynamics in understanding any economy, and in understanding world economy. A concern with power relations is also true of structuralist approaches. Prebisch, for example, highlights several reasons for the declining terms of trade for developing-country exports that are political in nature and/or relate to industrial organization and industrial relations; he underscores the power of the centre to maintain control over the benefits of technology; he points to the need for ‘social legislation’ to ensure real wage increases (in tandem with industrial development); and posits the overall goal of industrialization to be to ‘increase the measurable well-being of the masses’ (Prebisch, : ). Hirschman, too, grasped such dynamics, was a committed Marxist in his youth (Adelman, ), and remained in critical dialogue with Marxism. Hirschman developed the idea that development would be accelerated through investment (either private or public) in projects and industries with strong forward or backward linkages because of the induced investment effect or the ‘push factors’ which come from the

⁵ For reasons of space we are unable to discuss current debates around post-work and connected policy measures, such as a universal basic income. For relevant suggestions, see Spencer ().

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    



product side, arguing that it is not simply incomes and demand that govern investment (Hirschman, , ). We noted in section .. the importance of growth pulling backward linkages: ‘backward linkages lead to new investment in input-supplying facilities and forward linkages to investment in output-using facilities’ (Hirschman, : ). To these production linkages he added consumption and fiscal linkages and what he called inside and outside linkages. Hirschman’s conception of linkages is worth discussing further as it demonstrates both strengths and weaknesses in structuralist analysis. Hirschman points to how different ‘constellations’ of linkages can profoundly shape a specific pattern of economic development, be it in terms of the balance between the different types of linkages, the speed and strength of linkage development, the sequencing of the development of linkages, or how ‘technological gaps’ can hinder the development of production linkages. For example, he argues that strong fiscal linkages in the context of a lack of productive investment (or weak production linkages) can lead to a growth in bureaucracy, wasteful spending, such as on armaments, and/or a surge in imported consumer goods with concomitant impact on the balance of payments. In another context, customs duties on imported manufactures used in staple exports may seem desirable, but this is self-defeating if funds are simply used for infrastructure that only further aids staple exports. Hirschman’s insights continue to be of contemporary relevance for industrial policy and development more broadly. Indeed, he argues that his approach could be seen as an instance of ‘micro-Marxism’ (: ), an attempt to show how ‘the shape of economic development, including its social and political components, can be traced to the specific economic activities a country undertakes’ (: ). Countries will have different experiences according to ‘different linkage constellations’ (: ). Industrialization can be viewed as a ‘changing structure of linkages’ (Fine and Rustomjee, : ) with attendant implications for industrial policy. Yet, from a radical perspective, there are important limits to Hirschman’s conceptualization, specifically a lack of emphasis on class relations and dynamics in understanding industrialization processes. Fine and Rustomjee (), in their account of the industrialization of South Africa, provide both an account of industrialization in a particular place, and a methodology grounded in Marxism for examining particular processes of industrialization. They argue that Hirschman tends, not without contradictions, largely to suggest that a potential linkage will call forth the corresponding agency necessary to bring it about, be it public or private. They argue instead that which classes forge linkages, and how particular class interests are brought to bear in these processes, is critical to understanding how industrialization develops (see also Sender and Smith, ). And so, in accounting for development in South Africa, Fine and Rustomjee emphasize linking class and economic structure together with the role played by the state and industrial policy. The result of this analysis is Fine and Rustomjee’s idea of South Africa being dominated by a (changing) ‘minerals‒energy complex’, which is an analysis of industrial development that empirically identifies input‒output linkages between sectors. This analysis ties these patterns of linkage to the

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

 ,  ,   

different dimensions of interdependencies between fractions of capital, industrial sectors, and the state. Their analysis involves economic and political scrutiny (including of the state) through an emphasis on evolving class relations and conflicts and how these are reflected in patterns of accumulation and economic and social reproduction over time.

.. Industrial Policy: The Analytic and the Prescriptive Marxist industrial policy can be seen to operate at two levels: the analytic and the prescriptive. We discuss each in turn. The analytic can be said to be the analysis of ‘actually existing’ capitalism, both the historic centres of accumulation and empire, and the late developers. This entails a critique of mainstream accounts of capitalism, with its emphasis on self-regulating, dynamic, market-based processes. There is, therefore, considerable overlap with the perspectives advanced by the ‘developmental state’ (DS) approach, which has focused on the reality of state intervention to bring about rapid rates of capital accumulation and structural change in East Asia (see, for instance, Amsden, ; Chang, ; Wade, ), with South Korean macroeconomic policy, for example, understood as ‘investment management’ (Chang, : ). This approach emerged out of a critique of neo-liberalism and, in contrast to the sector neutrality of neo-liberal theories of economic growth, the DS approach recognizes the specific role of manufacturing in economic dynamism and growth. This work, with its emphasis on state intervention in, and state guidance of, late industrial development, has provided rich insights from history (see, for example, Chang, ). Following Gerschenkron (), ‘late’ development (late in the context of an already developed world market), is seen as requiring more effort by the state, not less. This brings forth a variety of institutional innovations, not least in the financing of industrialization. This literature both critiques the mainstream and discusses important aspects of industrial development, such as strategic mixing of incentivizing and disciplining capital (Amsden, , ; Di Maio, ); ‘embedded autonomy’ (Evans, ); and the role played by political settlements and political economy more broadly in patterns of economic development, including, for example, corruption (Khan, ; Behuria, Buur, and Gray, ). There are also important Marxist criticisms of the DS approach (Ashman, Fine, and Newman, ; and see the essays collected in Fine, Saraswati, and Tavasci, ). Utilizing a Marxist approach to the state and accumulation, to the theorization of both state and market, and the relationship between the two, these perspectives place greater and more systematic emphasis on issues around labour exploitation and struggle and the frequent instances of labour repression within the processes of late industrialization. The major issues can be summarized as follows. First: the tendency towards a technical-industrial conception of broader capitalist development which downplays

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    



the social antagonisms inherent in capitalist development, and which tends to see the state in neutral terms (Chang, ; Selwyn, ). Second: a certain teleology, if at times only vestigial, about development and industrialization and what is necessary to bring it about, rather than a recognition of the possibilities for regression, marginalization, or of its skewed, partial, or ‘combined and uneven’ nature (Ashman, ). Third: lack of recognition of capitalism as a world system with distinctive phases of development that shape and condition the development of its constitutive parts. Specificities of conditions in a particular period may not apply at another time (Chibber, ) and today the financialization of the world economy and the internationalization of production networks pose new challenges. The interconnections of the world capitalist system mean that the development of one affects the prospects for the development of others, with acute competition limiting the prospects for all to succeed, and endemic crises pointing to the impermanence of gains. Manufacturing is not specially protected (despite knowledge gains) from crises, radical restructuring, or ‘spatial fixes’, pointing to the limitations of nation-centric views and of national(ist) strategies for development (Song, ). Fourth, as already noted: the labour repression of late development and the tendency to neglect or downplay labour exploitation. Fifth, and finally: the question of whose standpoint is adopted. Selwyn () argues that the DS approach generally takes the view of an elite strategy for catch-up, and advocates policies that may give rise to faster rates of accumulation, but may not necessarily benefit society as a whole. Burkett and Hart-Landsberg () argue that catch-up views tend to see labour as passive, merely an instrument of accumulation and growth, that mass movements are merely disruptive of accumulation, and that ‘popular forces’ cannot be conceivers of, and contributors to, development. We should note at this point that state intervention is not without contradictions. Analysts of welfare have argued rightly that the universal provision of welfare has the potential to reduce the inequality involved in market-based provision, and in socializing the costs of caring (for children, for the aged, for the sick and disabled), effectively decommodifies provision and promotes collective over individualized values, and collective over individual or market-based solutions to both social needs and social problems (Esping-Andersen, ). The nationalization of industries, similarly, while often forced by economic crisis and war, has also provided gains in terms of labour conditions and trade union representation and protection from the market. In a sense, radical industrial policy can be seen as exploiting the contradictions of the state, by, on behalf of, and (potentially) with the active involvement of, labour, women, and the poor. This is important, as the same policies can be very different in different contexts according to the social forces pursuing them, for example, capital controls in Chile (Soederberg, ) compared with South Africa (Alami, ). This leads us to the prescriptive dimensions of radical industrial policy. At the level of the prescriptive, or of advocacy, we suggest that industrial policy needs yardsticks to assess its efficacy. We suggest a broad conception of industrial policy designed to meet basic social needs (not to be confused with a basic-needs approach) and to generate

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

 ,  ,   

employment. A broad-based conception of industrial policy seeks out the connections between industrial and social policy with health provision, mass public transport, and housing, for example, simultaneously meeting basic social needs, generating employment, and stimulating backward and forward linkages (MERG, ). Public health provision requires skilled and unskilled labour as well as infrastructure and there are potential connections with pharmaceutical policies. Radical industrial policy would also contribute broadly to a more egalitarian distribution of income and wealth, and to transforming social relations along gender, class, racial, and other dimensions. Diversification to a more broad-based and therefore equitable economic structure can be connected with defending labour and socializing production to meet these basic social needs. In addition, strengthening the redistributive capacities of the state, not least through taxation, restriction on tax avoidance, and base erosion profit shifting in order to fund collective rather than private provision of essential services, can offer protections against the market and commodification, and potentially go beyond the market. But radical industrial policy can only assist progressive change to the extent that it strengthens labour, civil society, and social movements, and promotes democracy and has a view to moving towards socializing the economy under democratic control.

.. Climate Change: The Potential and Necessity of Radical Industrial Policy Today The United Nations warned in  that the world has twelve years to take the action necessary to keep global warming to a maximum of . C, beyond which intense heat, flooding, drought, and poverty will follow for many (Watts, ). Others suggest there is even less time to radically decarbonize the world economy in order to avoid a disastrous level of global warming. What has become clear is that climate change is moving faster than previously thought, and its effects will be more rapid and severe. We use a brief discussion of the climate emergency to illustrate some of the broader arguments of the chapter. The roots of the climate crisis lie precisely in the industrial development being discussed in this volume, and in capital’s dependence upon particular commodities. The CO₂ emissions that arise from coal, oil, and gas—what Malm () calls ‘fossil capital’—are not the only drivers of climate change, but they are by far the largest. Fossil fuels are critical for the production of surplus value across an enormous spectrum of commodities. Coal, in particular, has been the ‘the fuel transmitting motion to the labour process’ (Malm, : ). The climate crisis is an unintended consequence of industrial development and industrial policy in many parts of the world. Now, industrial policy, and more besides, is necessary to address it. But as a consequence of the very power relations we have discussed, fossil capital continues to grow (alongside the growing green economy), and continues to be funded by the big banks (Rainforest Action Network, ). Energy

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    



is increasingly financialized, with private equity, hedge funds, and the whole shadow banking sector involved in the speculative trading of fossil capital. This financialization exists now across every aspect of everyday life, but power and nature have become increasingly intertwined. While there is a certain irony in radical industrial policy to address climate change, the consequences of failure to do so will be severe. Non-linear processes set in train by the warming of the planet mean that once we reach a certain point, the impact will be beyond human control and we will face ‘runaway climate change’ (Bendell, : ). This means we must accept ‘collapse as inevitable, catastrophe as probable, and extinction as possible’ (Bendell, : ). Social collapse—by which Bendell means ‘starvation, destruction, migration, disease, and war’—is already with us.⁶ The scale of the problem can lead to despair, as encapsulated in the remark, attributed both to Jameson and to Žižek, that ‘it’s easier to imagine an end to the world than an end to capitalism’ (Fisher, ). But Bendell argues that recognizing the possibilities of collapse, catastrophe, and extinction can also produce something positive: ‘a shedding of concern for conforming to the status quo, and a new creativity about what to focus on going forward’ (Bendell, : ). The climate strikes by schoolchildren and the discussion of the need for a Green New Deal may support such a view. There is growing awareness of this within industrial policy circles (see Pollin, Chapter  in this volume, as well as Altenburg and Assmann, ; Altenburg and Rodrik, ; Rodrik, ). Yet it is tempting for developing-country governments to implement industrial policy that, in trying to break out of commodity export dependence, disregards the impact of policy on climate change. UNCTAD (: ) shows that some energy export-dependent countries have increased their non-commodity exports by adding value to downstream energy sectors—a ‘good news’ story. Yet this has been achieved by increasing the share of chemicals in these countries’ exports. Between  and , Trinidad and Tobago increased the share of (petrol-based) chemicals in its exports by nearly  per cent, from . per cent to . per cent. Oman increased the share of chemicals in its exports from  per cent to . per cent during the same period, mainly through fertilizer manufacture. The UAE, Qatar, and Saudi Arabia have increased production of petroleum and gasbased products, and Bahrain utilized their rich energy resources and began aluminium production which is highly energy intensive (UNCTAD, : ). Instead of

⁶ Neale () argues that the imagery of social collapse brought about by climate change tends to be that of wandering nomads in a post-apocalyptic world where society has fallen totally apart. Instead, he argues, it will be nothing of the sort: the elites presently with power will intensify their rule, and climate collapse is more likely to come ‘with tanks on the streets and the military or the fascists taking power. Those generals will talk in deep green language. They will speak of degrowth, and the boundaries of planetary ecology . . . and they will build a new kind of gross green inequality. And in a world of ecological freefall, it will take cruelty on an unprecedented scale to keep their inequality in place.’

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

 ,  ,   

diversifying out of fossil fuels, these policies reinforce both their centrality and their climate impact. There is insufficient space in the present chapter for a thorough discussion of the policy measures needed to address climate change beyond pointing to areas of potential. Tackling climate change requires nearly all the burning of coal, oil, and gas to be ended. This cannot be achieved through market-based solutions, innovative entrepreneurial efforts to drive ‘green growth’, or the kind of mainstream approaches that tend to emphasize incentivizing firm and individual consumer behaviour (Klein, ). It requires radical state intervention, the creation of millions of public-sector climate jobs, and the extension and deepening of economic democracy and planning. The Green New Deal under discussion in the United States and elsewhere, though not without its limitations, proposes to simultaneously tackle climate change and inequality. This is intended to be achieved through economic planning and industrial policy measures to bring about mobilization for the environment, in a way that resources were previously mobilized for war. For many advocates of a Green New Deal, planning and democracy need to go together, to encompass labour and trade union involvement, while others advocate increased ‘energy democracy’ to bring about the necessary democratization of energy policy. Meeting basic needs in a green way, reorienting priorities towards local production to meet local needs—including more local food production and so less packaging and transport—would result in a degree of ‘de-globalization’ of the world economy. ‘Climate jobs’, which seek to minimize greenhouse gas emissions and maximize employment, have been advocated to address simultaneously the crises of unemployment and climate change. Such climate jobs could contribute to meeting the basic needs of communities in an equitable and sustainable way, with linkages focusing on jobs created in renewable energy (especially wind and solar power), retrofitting of buildings, new construction methods, expanded public transport (run increasingly on renewable energy), and re-employment or support for those in coal and other sectors who would lose their jobs. Relating back to the earlier discussion, it could be argued (adding a Kaldorian twist) that we can contrast the extraction of energy under diminishing returns (coal, oil, gas) with the harvesting of energy under increasing returns (solar, wind power). In this section, we have emphasized the distinctiveness of a radical approach to industrial development. Marx’s holistic account of capitalist industrial development moves beyond issues revolving around the role of sectors and development, though overlaps exist. We have argued that radical industrial policy operates at both the analytic and prescriptive levels. Capitalism creates interconnected crises: economic crises such as the recent global financial crisis, crises of war and global competition, crises of food, of health, of resources, and sustainability (Tabb, ). The climate crisis, we argue, reveals the possibility and the necessity for radical industrial policy today (and radical action more generally), though there are limits to what can be achieved within the constraints of the current social relations of production, which we explore in section ..

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    



. E  ‘R’ I P

..................................................................................................................................

This section discusses the ‘radical’ content of industrial policies that, to different extents, have been informed by a desire to transform the organization of production and capital‒labour relations. While by no means comprehensive, examples have been selected to illustrate key features of, and challenges to, ‘radical’ industrial policy. In particular, we highlight the ways in which tensions between economic imperatives for rapid industrial development on the one hand, and the balance of social forces and the development of participatory democracy as they relate to the state on the other, have been dealt with. These historical experiences have been loosely categorized here as statist approaches that are centred on state planning and national development, labourcentred co-operative approaches that focus on workers’ democracy in the local organization of production, and examples of industrial policy under participatory planning systems. There are very broad categorizations to organize our discussion, with considerable diversity within each as well as some commonality among these loose categories. For example, we discuss the Soviet Union and East Asia together, despite not only the fundamental differences between their industrial policies but also the broader political and economic characteristics of these models, and we discuss Cuba and Yugoslavia as examples of industrial policy under participatory planning systems. There are some relevant commonalities between these approaches (Cuba’s in particular) and that of the Soviet Union that we discuss in a different category.

.. Statist Models of Industrialization Statist models of industrialization include the—very different—models of ‘top-down’ industrial development in the Soviet Union and the earlier developmental states of East Asia, as well as more recent examples from China and Vietnam. Many technical aspects of radical industrial policy discussed above were present in statist industrialization experiences. Economists such as Kritsman, who worked in the Soviet State Planning Commission during the s, were early pioneers of the ideas of iteration and linkage as a way of understanding sectoral interrelationships and the growth-pulling potential of building industries with significant backward linkages. Leontief, who later developed the input‒output production model, worked in the Soviet planning establishment in the early s. Stalin’s priority sectors, according to later assessment by Chenery and Watanabe (), appeared to be those with maximum linkage effects, and there was considerable success in developing domestic linkages (backward linkages in particular) and the minimization of bottlenecks through highly effective mobilization of resources and high rates of fixed capital investment.

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

 ,  ,   

Statist models prioritized the development of productive forces over the development of democratic participation by labour. In different ways in the Soviet Union and the East Asian developmental states, the focus was on state‒capital relations and the need for the state to dominate and/or command capital. In the Soviet Union, this took the form of direct state ownership over the means of production and the state’s ability to command and deploy surpluses in the economy. In East Asia, the state‒capital relation took the form of the role of the state in regulating, directing, and disciplining private business. In line with the radical ideas on the role of manufacturing in economic development we have already discussed, development under Stalin was, ‘identified with industrialization, industrialization would be impossible without capital-intensive techniques, which meant high savings/investment ratios’ (Dyker, : ). In the absence of foreign credit, Stalin saw it as necessary to ‘pump over’ surpluses from the peasantry to fuel accumulation in the modern sector. This reflected a crude version of Preobrazhensky’s theory of ‘primitive socialist accumulation’ and entailed a campaign of collectivization (Dyker, : ). Industrialization was directed, top down, according to heavy centralization and the command principle, via a series of five-year plans that prioritized the development of heavy industry and the de-prioritization of light labour-intensive industry that had been the focus of earlier Soviet industrialization strategy. While the East Asian model can also be characterized as statist, this was under capitalism with strong developmental states that pushed a strong industrialization agenda. The strength of these states, combined with a high degree of bureaucratic autonomy, were seen as key to the success of state-directed investment to promote the concentration of capital and rising productivity and competitiveness via incentive structures and disciplinary mechanisms. The state protected and supported domestic business, including through subsidies and through captive domestic markets, yet by disciplining capital ensured that the rents from this were reinvested in investment, upgrading, and expansion. The role of the state in pushing firms to compete in export markets was one of the disciplining mechanisms used to ensure that this reinvestment materialized, facilitating rapid growth in productivity and an extraordinary record of economic growth sustained over a long period of time. This transformed not only living standards but also social relations in East Asian countries. One condition for state domination that has been identified by DS theorists has been that of ‘weak labour’ (Amsden, : ). Authoritarianism and the repression of labour has been an enduring feature of statist approaches to industrial development. It has been argued that the success of catch-up industrialization in East Asia is associated in part with the isolation and suppression of workers and social movements and the political geography established by the Cold War and the US foreign aid inflows that this engendered (Chang, ). In the Soviet Union, workers had limited scope for democratic participation either politically or economically. Furthermore, mass collectivization and the shift in priority from light to heavy industry under Stalin destroyed the (unofficial and voluntary) co-operative organization of production, based upon principles of democratic

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    



participation that had been emerging under Lenin’s leadership. Lenin had a cautious attitude towards the establishment of communes and equalization and collective consumption in advance of developments in production and the creation of abundance. Rather than supporting development of the communes towards wider social provisioning and consumption, the prioritizing of rapid industrial development entailed the expansion of agricultural surplus by intensification of production and downward pressure on consumption. Successful industrial development did raise average living standards in the Soviet Union and East Asia, but this success was in the context of very limited scope for workers’ democratic participation. This raises difficult questions around the compatibility of statist models of industrialization with vibrant participatory democracies, especially in the twenty-first century.

.. Labour-centred Industrial Development: Worker Co-operatives The neo-liberal assault on labour organization and the subsequent decline in the structural power of labour vis-à-vis capital manifest in capital’s rising share in the functional distribution of income across both the Global North and South, has inspired greater attention to alternative economic organization conducive to more equitable and sustainable distribution in the context of austerity. Industrial policy at the local level, based upon citizen cooperation and shared wealth, has sprung up in the wake of austerity in, for example, Cleveland, United States and Preston, United Kingdom, where new models of municipal socialism have been developed that draw from the experiences of successful co-operatives—in particular the Mondragon cooperatives of Spain’s Basque region. These local approaches stress the role of development in meeting human needs as well as the scope this offers for green transitioning. Participatory models of industrial organization have a long history and have co-existed within a wider context of capitalist relations of production. Studies of participatory forms of economic organization have variously identified the economic and social benefits of workplace democracy, which include: improved productivity; greater contribution to social development than purely private enterprise; improved conditions of work; improved health outcomes associated with better work‒life balance and greater autonomy; a more equitable distribution between profit and wages/managers and workers; and greater resilience (Foley and Polanyi, ; Pencavel, ; NEF, ). Yet, co-operative ownership of businesses is marginal compared with capital ownership. Where co-operatives have endured, such as the Mondragon Group, they have undergone significant restructuring that has included a gradual degeneration from democratic forms to capitalist forms of organization in the face of globalization and capitalist competition. This suggests that, in the absence of supportive policies, in

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

 ,  ,   

particular those that redress the power imbalance between capital and labour in society, the expansion of workers’ participation in production will be limited. The Mondragon complex, which consists of a network of linked productive operations, was founded in  on three institutional bases. First, a system for technical education. Second, the League of Education and Culture, which played a central role in linking the education system to co-operative firms and in the management of any legal and political issues with local and national government. And third, the credit union the Caja Laboral Popular, which was founded to support the expansion of industrial co-operatives and thus operated on the principle of long-term productive investment and the reinvestment of profits (Errasti et al., ). Strong input‒output linkages, together with a multi-layered institutional structure that amassed workers’ pension savings and surpluses for long-term productive investment, and facilitated education, research, and design, ensured that the dynamics of cumulative causation were not hampered by limited access to capital or technical expertise. Since the s, rising pressures associated with globalization and the increasingly competitive environment that it engendered, have led to major changes in firms’ management structures. The complex was transformed into a uniform corporate identity, the Mondragon Co-operative Corporation, with a centralized management structure and more ‘rationalized’ organization of constitutive elements that involved several mergers as well as the opting out of several co-operatives (Clamp, ). Rationalization and corporatization of the co-operative complex had ensured its survival and growth in an increasingly intensive and internationally competitive environment, but at the expense of the degree of worker participation in management and decision-making. The growth of Fagor Electrodomésticos, a leading co-operative in Mondragon, for example, entailed a process of acquisition of capital-owned local and foreign firms, and the group ultimately collapsed in . These challenges raise questions around the viability of sustaining and expanding co-operative forms of production, and maintaining democratic forms of decision-making within them, within wider national and international economies that are market based. Examples of enduring workers’ co-operatives in industrial production can also be found in Kolkata, India, where such groups were formed in the s and s in shipbuilding, aluminium cables and conductors, hosiery, printing works, and textiles through workers’ takeover of industries in apparent decline (Bhowmik and Sarker, ). The enduring democratic participation of workers in these co-operatives can be attributed to the lead taken by a strong trade union movement in their formation. The union movement could both draw upon the support of wider membership for workers’ co-operatives and, to an extent, negotiate with government. The high level of internal democracy and collectivity has also been credited for their survival in light of constrained access to finance and markets (Bhowmik and Sarker, ). These co-operatives survived and maintained employment but did not flourish in the competitive sense. The existential tensions between market competition and the preservation of the egalitarian and participatory ethos of co-operative models of production under

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    



prevailing capitalist social relations are widely acknowledged (Gunn, ). At the local level, governments have begun to experiment with forms of ‘municipal socialism’ in a few localities in the United States and the United Kingdom, with policies that support local enterprise and workers’ co-operatives. The extent to which such programmes can contribute to the wider sustainable structural transformation of production will depend upon the technical and political content of policies, among other factors. Radical industrial policies require a political economy of labour that is generated by collective action. The promotion of co-operatives therefore needs to go hand in hand with policies that maximize workers’ ability to generate and deploy their agential power. Challenges are also posed by competitive and other pressures exerted by the wider market environments, beyond the local levels, within which these projects operate. Rather than the imperative to generate additional capital through the exploitation of workers, a labour-centred development approach sees the reproduction of labour as the main objective, rather than the subsumption of labour to the objectives of capital.

.. Models of Industrial Policy with Participatory Planning In this discussion, we present examples of industrial policy that have engaged with the contradictions and tensions between economic development of productive forces and social development in terms of the extension and deepening of democratic participation in economy and society. Some socialist states outside the Soviet Union, including Cuba from  and Yugoslavia after , pursued radical industrial policies that can be deemed ‘developmental’. While recognizing the imperative for industrial development, these states did not narrowly prioritize development of the forces of production. In , Yugoslavia split from Stalin and abandoned the Soviet centralized model of industrial development in favour of a form of central planning that aimed at greater reliance on the domestic and world market and workers’ control over enterprise (Estrin, ). Between  and , a series of reforms replaced vertical command planning with ‘direct horizontal relations between more autonomous enterprise through a regulated market’—a model that became known as market socialism (Estrin, : ). In contrast to industrial development in the Soviet Union, institutional structures were set up to promote the self-management of enterprise by workers with high levels of participation by workers in decision-making, particularly over questions of welfare, employment, and pay, while managers retained much of the decision-making power over investment (Estrin, ). Further reforms between  and  sought to extend democratic participation by workers beyond decision-making at the level of the enterprise. This involved the breaking up of enterprises into their constituent establishments or workshops, called Basic Organizations of Associate Labor (BOALs), each with its own apparatus of selfmanagement that replaced the enterprise in law. Individual BOALs then worked

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

 ,  ,   

collaboratively based upon mutual agreements with the effect of replacing competition (between enterprises) with wider cooperation in the system. Further, the devolution of state power to the level of the republics represented a shift to a federal political structure that promoted the involvement of all interested parties in the process of policymaking and implementation (Estrin, ). In the case of Cuba, the development process has been characterized by ‘the need to industrialize and the imperative of social participation in the development process’ (Cole, : ). Even though these objectives were at times in conflict, their resolution marked the evolution of socialist development in Cuba, which has entailed the deepening of participation in the organization of society. The ‘dialectic between the political and the economic has been the central dynamic of policy and change’ in Cuba (García Brigos quoted by Cole, : ). In this way, Cuban development strategies developed through various iterations reflecting these tensions. A period of ‘idealistic spontaneity’ (‒) was followed by ‘centralized pragmatism’ (‒) and Soviet-style central planning (‒), reflecting economic imperatives that were not met in the earlier phases. Central planning saw subsequent adaptations to promote popular participation that had been marginalized by Soviet-type planning focused on accelerated accumulation. The Rectification Campaign (‒) saw the culmination of political sentiments in the building of institutional structures for greater citizen participation. While industrial development has been linked to social provisioning by leveraging public procurement, notably in healthcare (Tancer, ), capital accumulation remained centred on the agro-industrial complex and commodity exports. With the collapse of the Soviet Union, Cuba opened a window to the world economy, allowing foreign investment as a source of capital, resources, expertise, and markets. Industrial strategy focused on biotechnology, pharmaceutical, and medical equipment industries that had developed to a level that could compete with developed countries. Development of the Cuban biotechnology industry, for example, reflects elements of radical industrial policy outlined above, in the linking of industrial development with public provisioning and also in the organization of production units strategically linked to a multi-institutional system that included universities and research institutions fostering collaboration in innovation (Cárdenas, ). In addition, there was a shift from large-scale monocrop industrial agriculture that had been heavily dependent on imported inputs to small-scale, organic, or semi-organic agriculture organized via co-operatives that boosted yields and food independence (Cole, ). The period after  also saw the deepening of forms of democratic participation and involvement in decision-making (Cole, ). In this way, economic liberalization of the early post-Soviet era and the institution of greater economic specialization provided the opportunity for further socialist development via deeper participation (Cole, ). The aim of this cursory discussion of radical industrial policies in Yugoslavia and Cuba is not to paint an unduly rosy or linear picture of economic and political development, or to downplay the external and internal challenges these nations have

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    



faced. Mistakes were made, and these development models have their own serious limitations and constraints. Successive policy stages reflect an iterative approach that sought to calibrate the dynamic relationship between economic and social imperatives and attempts at deepening democracy. Overall, the experiences of industrialization processes and the range of models discussed in this section help to illuminate the radical content of industrial policies. There are both economic and political dimensions to radical industrial policies. Radical policies are class-conscious and do not focus on the narrow interests of elites. Rather, they both stem from and are directed at a class project that places labour at its centre, not only in the distribution of gains from development, but through direct economic and political participation of workers. Radical industrial policy, then, entails both the development of democracy and technical innovations in the organization of production, the precise form of which itself evolves and is subject to ongoing contestation.

. C

.................................................................................................................................. In our survey, evaluation, and discussion of radical industrial policy, we have examined the differences between mainstream and heterodox approaches to economic and industrial development. The focus of the debate between the mainstream and the heterodox has been around the question of whether or not growth is sector neutral and, to a lesser extent, activity neutral. Heterodox approaches have argued that the sectoral basis of output and employment will affect the pattern of growth and development. We looked in particular at the similarities and the differences between Kaldorian/structuralist approaches and Marxist ones. It is possible to identify points of common ground, and indeed Marx can be seen to have provided analytical antecedents for later approaches in his analysis of nineteenth-century industrial capitalism. Structuralists have been primarily concerned with the balance-of-payments constraint on growth (reflecting the structure of production) and the deteriorating terms of trade for developing economies (the nature of the international system). Combined, these hold back development. A radical perspective recognizes both the value and limits of such arguments. We see important differences between Kaldorian/structuralist approaches and Marxist approaches. Marx’s concern is not with sectors but with value and the overall circuit of capital. This view of a circuit of capital, integrating the different forms which capital takes, is rooted at a more abstract level in a broader framework for understanding capitalism as a mode of production that sees accumulation as founded upon exploitative class relations between labour and capital, and where competition between rival units of capital forces capital both to innovate and to increase the production of surplus value. Marx’s problematic, for all his insights into modern machine production, is concerned with the capitalist basis of production, not primarily with industrial production. We have argued, therefore, that radical industrial policy foregrounds class

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

 ,  ,   

and capitalism, not sectors, and integrates a distinctive conception of the state: the state as central to accumulation but which can also, in particular circumstances, be leveraged to aid radical transformation if connected to broader social forces and movements. Connected to this, we have argued that radical industrial policy operates at two levels, the analytical and the prescriptive. The analytical level refers to the understanding of capitalist industrial development in particular contexts, integrating the role of the state and diverging class interests, including patterns of linkages and the nature of industrial policy interventions. Prescriptively, in radical industrial policy, the contradictions of the state are exploited and there is a concern with meeting basic social needs, maximizing employment-generating linkages, strengthening labour and democracy, and, urgently, mitigating climate change. These are among the yardsticks by which to assess industrial policy from a radical perspective. Finally, we surveyed briefly some experiences of industrial policy, loosely dividing them between statist and labour-centred. The economic imperatives for national strategies of development have frequently entailed labour subordination to capital, as the experience of the former Soviet Union attests: the construction of a centralized command economy prioritizing ‘modernization’ and rapid accumulation, an approach that was replicated in the five-year plans inspired by the Soviet Union in a number of developmental states. Discussing labour-centred industrial policy based on co-operative models of organization raises issues seemingly out of fashion in industrial policy circles and literature: the economic and social benefit of workplace democracy in terms of improved conditions of work; better work‒life balance; greater autonomy; a more equitable distribution between profit and wages; and hence a reduction in inequality. It is difficult for workers’ co-operatives to survive without supportive policies from the state. Yet if we are to avoid/reverse the ‘race to the bottom’ and competition between workers, there are models from which we could learn. What, then, is the ‘value added’ of radical industrial policy? First, we argued that it breaks out of the technical. It is not simply about economic growth and catch-up by developing economies, nor is it simply about ‘sector fundamentalism’; indeed there are profoundly different political projects embodied in Marxist vis-à-vis Kaldorian and structuralist approaches to economic development and industrial policy, which stem from their diverging assumptions. Second, radical industrial policy has a distinctive analysis rooted in understanding the dynamics of capitalism: accumulation, exploitation, and the state. Class-based processes determine the nature and form of industrial development. Class is made central, rather than sectors and activities, and both class and the state are critical to understanding specific ‘constellations’ of linkages. These factors are brought to bear in critiques of the developmental state approaches. Third, radical industrial puts emphasis upon both economic and political dimensions, and the avoidance of economic reductionism (a partner of technical conceptions). We stressed this particularly in the necessity of labour’s active participation, and the radical

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    



extension of democracy necessary for greater labour participation in defining the priorities and methods of production, and in meeting the basic needs of the majority. Finally, standpoint. Radical industrial policy does not take the standpoint of elites, but is a class-based project with labour at its centre. In our discussion of radical industrial policy and the climate crisis, we argued that only a radical extension of state involvement and democracy can bring about the scale and speed of intervention necessary to address this impending catastrophe. Given this analysis, there are necessarily limits to what can be achieved by industrial policy. Gains for labour are frequently temporary, ‘islands of socialism’ do not survive long in seas of capitalism and genuine participatory projects remain utterly marginal to global accumulation. The scale of the climate crisis can induce paralysis, yet it demands imagining and striving for a more habitable and just economy, including through public transport, democratic control over energy and water supplies, local production to meet local needs, and the opening of borders to migrants displaced by climate impacts (Klein, ). Finally, what are the prospects for radical industrial policy today? While there is growing mainstream acceptance of the need for industrial policy, there are widely differing conceptions of what the appropriate goals and tools of industrial policy should be. The financialization of the global economy has not been the major focus of this chapter, yet this conditions the prospects for industrial policy today, be it radical or otherwise. The present phase of capitalism has witnessed the unprecedented (albeit uneven) internationalization of productive capital, and its restructuring as driven by finance. ‘Downsize and distribute’ (Lazonick and O’Sullivan, ) has radically altered the structure of many economies (along with the rise of China) and radically shifted the balance of power towards capital. The neo-liberal state has been central to this restructuring, and ‘finance-induced’ policy orthodoxy has meant price stability, and high real interest rates continue to be given priority (Fine et al., ). Policies which ‘risk’ higher inflation or higher taxes are fiercely resisted, as are interventionist industrial policies to restructure capital, not least to ward off the possibility that similar state intervention may be extended to the financial sector. Radical industrial policy, as we have argued, places power at its centre, and addressing the power of the financial sector is an absolute necessity.

R Adelman, Jeremy () Worldly Philosopher: The Odyssey of Albert O. Hirschman. Princeton, NJ: Princeton University Press. Alami, Ilias () ‘Capital Accumulation and Capital Controls in South Africa: A Class Perspective’, Review of African Political Economy (): –. Altenburg, Tilman and Claudia Assmann (eds) () Green Industrial Policy: Concepts, Policies, Country Experiences. Geneva, Bonn: UN Environment, German Development

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

 ,  ,   

Institute. Available at https://www.un-page.org/files/public/green_industrial_policy_book_ aw_web.pdf. Altenburg, Tilman and Dani Rodrik () ‘Green Industrial Policy: Accelerating Structural Change towards Wealthy Green Economies’, in Tilman Altenburg and Claudia Assmann (eds) Green Industrial Policy: Concepts, Policies, Country Experiences. Geneva, Bonn: UN Environment, German Development Institute, pp. –. Amsden, Alice () Asia’s Next Giant: South Korea and Late Industrialization. New York: Oxford University Press. Amsden, Alice () The Rise of the Rest: Challenges to the West from Late-Industrializing Economies. Oxford: Oxford University Press. Andreoni, Antonio and Roberto Scazzieri () ‘Triggers of Change: Structural Trajectories and Production Dynamics’, Cambridge Journal of Economics (): –. Ashman, Sam () ‘Combined and Uneven Development’, in Ben Fine and Alfredo SaadFilho (eds) The Elgar Companion to Marxist Economics. Aldershot: Edward Elgar, pp. –. Ashman, Sam, Ben Fine, and Susan Newman () ‘The Developmental State and Post-Liberation South Africa’, in Neeta Misra-Dexter and Judith February (eds) Testing Democracy: Which Way Is South Africa Going? Cape Town: ABC Press for Institute for a Democratic South Africa, pp. –. Behuria, Pritish, Lars Buur, and Hazel Gray () ‘Studying Political Settlements in Africa’, African Affairs (): –. Bendell, Jem () ‘Deep Adaptation: A Map for Navigating Climate Tragedy’, IFLAS Occasional Paper No. . Available at http://www.lifeworth.com/deepadaptation.pdf. Berik, Günseli, Yana Rodgers, and Stephanie Seguino () ‘Feminist Economics of Inequality, Development, and Growth’, Feminist Economics (): –. Best, Michael () How Growth Really Happens: The Making of Economic Miracles through Production, Governance, and Skills. Princeton, NJ: Princeton University Press. Bhowmik, Sharit K. and Kanchan Sarker () ‘Worker Cooperatives as Alternative Production Systems: A Study of Kolkata, India’, Work and Occupations (): –. Blankenburg, Stephanie, Gabriel Palma, and Fiona Tregenna () ‘Structuralism’, in Lawrence Blume and Steven Durlauf (eds) The New Palgrave: A Dictionary of Economics. nd edition. Basingstoke: Palgrave Macmillan, pp. –. Braunstein, Elissa () ‘Engendering Foreign Direct Investment: Family Structure, Labor Markets, and International Capital Mobility’, World Development (): –. Brenner, Robert () ‘The Social Basis of Economic Growth’, in John Roemer (ed.) Analytical Marxism. Cambridge: Cambridge University Press, pp. –. Burkett, Paul and Martin Hart-Landsberg () ‘A Critique of “Catch-up” Theories of Development’, Journal of Contemporary Asia (): –. Çağatay, Nilüfer and Şule Özler () ‘Feminization of the Labor Force: The Effects of Longterm Development and Structural Adjustment’, World Development (): –. Cárdenas, Andrés () ‘The Cuban Biotechnology Industry: Innovation and Universal Health Care’. Cambridge, MA: The Academic-Industry Research Network (theAIRnet). Chang, Dae-oup () Capitalist Development in Korea: Labour, Capital and the Myth of the Developmental State. Abingdon: Routledge. Chang, Dae-oup () ‘Labour and the “Developmental State”: A Critique of the Developmental State Theory of Labour’, in Ben Fine, Daniela Tavasci, and Jyoti Saraswati (eds) Beyond the Developmental State: Industrial Policy into the Twenty-first Century. London: Pluto, pp. –.

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    



Chang, Ha-Joon () ‘The Political Economy of Industrial Policy in Korea’, Cambridge Journal of Economics : –. Chang, Ha-Joon () Kicking away the Ladder: Development Strategy in Historical Perspective. London: Anthem. Chang, Ha-Joon ()  Things They Don’t Tell You about Capitalism. London: Allen Lane/ Penguin. Chenery, Hollis and Tsunehiko Watanabe () ‘International Comparisons of the Structure of Production’, Econometrica (): –. Chibber, Vivek () ‘The Developmental State in Retrospect and Prospect: Lessons from India and South Korea’, in Michelle Williams (ed.) The End of the Developmental State? Pietermaritzburg: UKZN Press, pp. –. Clamp, Christina () ‘The Evolution of Management in the Mondragon Cooperatives’, Mapping Cooperative Studies in the New Millennium, University of Victoria. Clarke, Simon (ed.) () The State Debate. Conference of Socialist Economists. Basingstoke: Palgrave Macmillan. Cole, Ken () ‘Cuba: The Process of Socialist Development’, Latin American Perspectives (): –. Cramer, Christopher and Fiona Tregenna () ‘Heterodox Approaches to Industrial Policy, the Shifting Boundaries of the Industrial, and the Implications for Industrial Hubs’, in Justin Yifu Lin and Arkebe Oqubay (eds) The Oxford Handbook of Industrial Hubs and Economic Development. Oxford: Oxford University Press. Di Maio, Michele () ‘Industrial Policies in Developing Countries: History and Perspectives’, in Giovanni Dosi, Mario Cimoli, and Joseph E. Stiglitz (eds) The Political Economy of Capabilities Accumulation. Oxford: Oxford University Press, pp. –. Dyker, David () The Future of the Soviet Economic Planning System. London: Routledge. Elson, Diane and Ruth Pearson () ‘ “Nimble Fingers Make Cheap Workers”: An Analysis of Women’s Employment in Third World Export Manufacturing’, Feminist Review : – . Errasti, Anjel, Ignacio Bretos, and Aitziber Nunez () ‘The Viability of Cooperatives: The Fall of the Mondragon Cooperative Fagor’, Review of Radical Political Economics (): –. Esping-Andersen, Gøsta () The Three Worlds of Welfare Capitalism. Princeton, NJ: Princeton University Press. Estrin, Saul () ‘Yugoslavia: The Case of Self-Managing Market Socialism’, Journal of Economic Perspectives (): –. Evans, Peter () Embedded Autonomy: States and Industrial Transformation. Princeton, NJ: Princeton University Press. Fine, Ben and Zavareh Rustomjee () The Political Economy of South Africa: From Minerals–Energy Complex to Industrialization. London: Hurst. Fine, Ben, Costas Lapavitsas, and Dimitris Milonakis () ‘Addressing the World Economy: Two Steps Back’, Capital and Class (): –. Fine, Ben, Jyoti Saraswati, and Daniela Tavasci (eds) () Beyond the Developmental State: Industrial Policy into the st Century. London: Pluto. Fisher, Mark () Capitalist Realism: Is There No Alternative? Ropley: Zero Books. Foley, Janice and Michael Polanyi () ‘Workplace Democracy: Why Bother?’, Economic and Industrial Democracy (): –.

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

 ,  ,   

Gerschenkron, Alexander () Economic Backwardness in Historical Perspective. Cambridge, MA: Harvard University Press. Giovannoni, Olivier () ‘Functional Distribution of Income, Inequality, and the Incidence of Poverty: Stylized Facts and the Role of Macroeconomic Policy’. University of Texas Inequality Project Working Paper No. . Gunn, Christopher () ‘Cooperatives and Market Failure: Workers’ Cooperatives and System Mismatch’, Review of Radical Political Economics (): –. Hirschman, Albert () The Strategy of Economic Development. New Haven, CT: Yale University Press. Hirschman, Albert () ‘A Generalized Linkage Approach to Development, with Special Reference to Staples’, Economic Development and Cultural Change : –. İzdeş, Özge and Fiona Tregenna () ‘Gender, Industrialization, and Industrial Hubs’, in Justin Yifu Lin and Arkebe Oqubay (eds) The Oxford Handbook of Industrial Hubs and Economic Development. Oxford: Oxford University Press. Kaldor, Nicholas () Causes of the Slow Rate of Economic Growth of the United Kingdom: An Inaugural Lecture. Cambridge: Cambridge University Press. Kaldor, Nicholas () Further Essays on Economic Theory. London: Duckworth. Kaldor, Nicolas () Essays on Economic Stability and Growth. nd edition. London: Duckworth. Khan, Mushtaq () ‘Political Settlements and the Analysis of Institutions’, African Affairs (): –. Klein, Naomi () This Changes Everything: Capitalism vs. the Climate. London: Allen Lane. Kucera, David and Tejani, Sheba () ‘Feminization, Defeminization, and Structural Change in Manufacturing’, World Development (C): –. Lazonick, William and Mary O’Sullivan () ‘Maximizing Shareholder Value: A New Ideology for Corporate Governance’, Economy and Society (): –. Malm, Andreas () Fossil Capitalism: The Rise of Steam Power and the Roots of Global Warming. London: Verso. Marx, Karl ( []) Capital: A Critique of Political Economy, Vol. . London: Penguin. Marx, Karl ( []) Capital: A Critique of Political Economy, Vol. . London: Lawrence & Wishart. Marx, Karl and Friedrich Engels ( [/]) The German Ideology. London: Lawrence & Wishart. MERG () ‘Making Democracy Work: A Framework for Macroeconomic Policy in South Africa’, Centre for Development Studies, University of the Western Cape, South Africa. Milberg, William and Deborah Winkler () ‘Financialisation and the Dynamics of Offshoring in the USA’, Cambridge Journal of Economics (): –. Neale, Jonathan () ‘Social Collapse and Climate Breakdown’, Ecologist: The Journal for the Post-industrial Age,  May. Available at https://theecologist.org//may//socialcollapse-and-climate-breakdown. NEF () Co-operatives Unleashed: Doubling the Size of the UK’s Co-operative Sector. London: New Economics Foundation. Oqubay, Arkebe () Made in Africa: Industrial Policy in Ethiopia. Oxford: Oxford University Press. Pencavel, John () The Economics of Worker Cooperatives. Northampton, MA: Edward Elgar.

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    



Prebisch, Raúl () ‘The Economic Development of Latin America and its Principal Problems’, Economic Bulletin for Latin America, No. , United Nations Department of Economic Affairs, New York. Rainforest Action Network () ‘Banking on Climate Change: Fossil Fuel Finance Report Card ’. Available at https://www.ran.org/wp-content/uploads///Banking_on_ Climate_Change__vFINAL.pdf. Ricoy, Carlos () ‘Marx on Division of Labour, Mechanization and Technical Progress’, European Journal of the History of Economic Thought (): –. Rodrik, Dani () ‘Green Industrial Policy’, Oxford Review of Economic Policy (): – . Rosenberg, Nathan () ‘Was Schumpeter a Marxist?’, Industrial and Corporate Change (): –. Seguino, Stephanie and Elissa Braunstein () ‘The Costs of Exclusion: Gender Job Segregation, Structural Change and the Labour Share of Income’, Development and Change : –. Selwyn, Benjamin () ‘An Historical Materialist Appraisal of Friedrich List and his Modern Day Followers’, New Political Economy (): –. Selwyn, Benjamin () ‘Trotsky, Gerschenkron and the Political Economy of Late Capitalist Development’, Economy and Society (): –. Sender, John and Sheila Smith () The Development of Capitalism in Africa. London: Methuen. Soederberg, Susanne () ‘An Historical Materialist Account of the Chilean Capital Control: Prototype Policy for Whom?’, Review of International Political Economy (): –. Song, Hae-Yung () ‘Marxist Critiques of the Developmental State and the Fetishism of National Development’, Antipode (): –. Spencer, David () The Political Economy of Work. Abingdon: Routledge. Spencer, David () ‘Fear and Hope in an Age of Mass Automation: Debating the Future of Work’, New Technology, Work and Employment (): –. Stockhammer, Engelbert, Özlem Onaran, and Stefan Ederer () ‘Functional Income Distribution and Aggregate Demand in the Euro Area’, Cambridge Journal of Economics (): –. Tabb, William () ‘Four Crises of the Contemporary World Capitalist System’, Monthly Review,  October. Available at https://monthlyreview.org////four-crises-of-thecontemporary-world-capitalist-system/. Tancer, Robert () ‘The Pharmaceutical Industry in Cuba’, Clinical Therapeutics (): –. Tregenna, Fiona () ‘Characterising Deindustrialisation: An Analysis of Changes in Manufacturing Employment and Output Internationally’, Cambridge Journal of Economics (): –. Tregenna, Fiona () ‘What Does the Services Sector Mean in Marxian Terms?’, Review of Political Economy (): –. Tregenna, Fiona () ‘The Specificity of Manufacturing in Marx’s Economic Thought’, European Journal for the History of Economic Thought (): –. Tregenna, Fiona () ‘A New Theoretical Analysis of Deindustrialisation’, Cambridge Journal of Economics (): –.

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

 ,  ,   

Tregenna, Fiona () ‘Deindustrialization and Premature Deindustrialization’, in Jayati Ghosh, Erik S. Reinert, and Rainer Kattel (eds) Handbook of Alternative Theories of Economic Development. Cheltenham: Edward Elgar, pp. –. Tregenna, Fiona () ‘Sectoral Structure and Change: Insights from Marx’, Review of Political Economy (): –. UNCTAD () State of Commodity Dependence . Geneva: United Nations. Available at https://unctad.org/en/PublicationsLibrary/ditccomd_en.pdf. Verdoorn, Petrus Johannes ( []) ‘On the Factors Determining the Growth of Labour Productivity’, in Luigi Pasinetti (ed.) Italian Economic Papers, Vol. II. Oxford: Oxford University Press, pp. –. Wade, Robert () Governing the Market: Economic Theory and the Role of Government in East Asian Industrialization. Princeton, NJ: Princeton University Press. Watts, Jonathan () ‘We Have  Years to Limit Climate Change Catastrophe, Warns UN’. Available at https://www.theguardian.com/environment//oct//global-warmingmust-not-exceed-c-warns-landmark-un-report. Weeks, John () Capital, Exploitation and Economic Crisis. London: Routledge. Young, Allyn () ‘Increasing Returns and Economic Progress’, Economic Journal (): –.

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  .............................................................................................................

   .............................................................................................................

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  ......................................................................................................................

                                            The Case of ASEAN .............................................................................................................

 .    

. R E I, T C  ASEAN I P

.................................................................................................................................. A decades of efforts to transform Southeast Asia into a resilient regional economy, the Association of Southeast Asian Nations (ASEAN)—a regional intergovernmental organization comprising ten countries in Southeast Asia—has shifted its priorities towards deepening its regional participation into global value chains (GVCs).¹ For ASEAN, greater participation into the GVC network should help the region improve its trade and investment nexus critical for firm and industry competitiveness amidst twenty-first-century globalization. Moreover, greater integration into GVCs might expand production linkages and export destinations of local firms that may not have been accessible prior to regional and global integration. Above all, at least

¹ The ten countries of ASEAN are Singapore, Brunei Darussalam, Indonesia, Philippines, Malaysia, Thailand, Vietnam, Laos, Myanmar, and Cambodia. ASEAN member states have been in an ongoing dialogue regarding the accession of Timor-Leste, or East Timor, as the eleventh member. It has been more than a decade (March ) since Timor-Leste applied for formal membership to ASEAN.

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

 .    

among ASEAN policymakers, greater participation into GVCs may play a key role in realizing ASEAN’s grand vision for creating a single market and production base known as the ASEAN Economic Community (AEC) by . In this chapter, we argue that the recent policy shift towards deepening regional and global production networks may pose both an opportunity and a challenge for the region’s future economic and development trajectories. We highlight several key points regarding ASEAN’s industrial policy in the era of GVCs. First, increasing GVC participation may benefit some sectors more than others. We show that the automotive GVCs in ASEAN have been a success, especially with the expansion of domestic production and export growth performance in recent times. We note that the success of automotive GVCs depends on continued institutional support to implement a more integrative production process. ASEAN’s regionally coordinated policies, such as the ASEAN Brand-to-Brand Complementation (BBC) scheme, or when parts and components are traded without paying full import duties, have made South East Asia an attractive region for automotive manufacturing. ASEAN’s BBC scheme, first introduced in , was a breakthrough in advancing the integrative process of the automotive industry in the Southeast Asian region. Second, the success story of automotive GVCs in ASEAN hinges on regionally coordinated industrial policy and the active role of large multinational firms in creating regional and local production linkages. Toyota, a Japanese auto manufacturer, has been directly involved in making Southeast Asia its own backyard for production and assembling since the s. Toyota’s influence in the region’s automotive production and assembly continues as it maintains a positive relationship with ASEAN’s political and economic establishments. Third, we underline the importance of institutions in improving local firm capacities and their competitiveness, human capital, technological capabilities, and ‘industrial upgrading’, or moving up the value chain from lower value-added to higher value-added economic activities in the era of rising participation in GVCs. Thailand’s initiative to establish universities and research institutions related to the auto industry greatly contributed to its advancement in auto manufacturing. Thailand has been dubbed as the ‘Detroit of South Asia’ for rapidly transforming its automotive industry since recovering from the  Asian financial crisis. This chapter starts with an overview of ASEAN as a regional institution that collectively promotes economic growth policies among its member states. The chapter will then trace the historical evolution of ASEAN’s economic policies since the s. We discuss the region’s strategic shift from the conventional approach of reducing or eliminating trade barriers and creating a conducive environment for foreign investors to the deepening of regional and global production network participation.² For ASEAN policymakers, regional integration through GVCs ² For example, the ASEAN Free Trade Agreement (AFTA) and its primary mechanism ASEAN Trade in Goods Agreement (ATIGA) have ensured the realization of the free flow of goods within ASEAN, including tariff liberalization, removal of non-tariff barriers, trade facilitation, customs,

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     : 



expedites a country’s participation in global markets and production and eases the process of economic development. Regional geopolitics is also worth noting here; ASEAN industrial policy in recent years serves to ensure recognition that the region continues to be dynamic and competitive. With a growing number of free trade agreements (FTAs), including from those regional trade agreements to which some ASEAN member states are a party, like the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP), ASEAN has to sustain its competitiveness. Second, the spectacular rise of China, and to some extent India, has changed the political and economic relationships of ASEAN member states and their counterparts.³ Deepening ASEAN’s GVC participation also means that there is more space for local participation, particularly by small and medium-sized enterprises (SMEs). Improving local participation and the redistribution of economic gains from regional and global value chains emerged as a focal point in establishing the ASEAN Economic Community , as outlined in the ASEAN Blueprint . While this policy may be good for redistributing gains to local actors, it falls short in guaranteeing the industrial upgrading that often occurs in firms with large capital investments. To this extent, ASEAN has yet to produce lead firms with international presence. Technological advancements in production and logistics have made it easier to establish inter- and intra-industry cooperation. While participation in GVCs opens up greater access to markets and technology, there remains a doubt whether technological spillovers are immediate or if they occur at all. The gains, such as a transfer of knowledge, from participation in GVCs have been mixed. Moreover, the chapter argues that while ASEAN industrial policy in the era of GVCs centred on improving local participation in recent years, more needs to be done to address the competitiveness of large firms to capture higher economic returns (i.e. profits) and technological advancements. What we observed from ASEAN’s current policy initiative in the era of GVCs is the lack of a systematic programme and streamlining policy for industrial upgrading. ASEAN’s industrial policy in the era of GVC is skewed towards increasing participation of the bottom and middle tiers of the value chain. Thus, leaving large local firms to compete directly with multinational firms. We conclude that ASEAN industrial policy in the era of GVCs should go beyond the objectives of deepening regional and global integration. ASEAN must find new ways to create value-added, whether that involves a large number of

standards and conformance, and other measures such as sanitary and phytosanitary. The inception of AFTA provides a clear timeline for the tariff reduction schedule for each product by  and has since promoted the export performances of ASEAN member states. ³ ASEAN member states are divided in their support for China, especially with the ongoing dispute over the South China Seas between China and ASEAN claimant states (including Brunei Darussalam, Malaysia, the Philippines, Vietnam, and more recently Indonesia).

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

 .    

vertically linked activities or only just a few in the value chain, and establish centres for innovation. Learning from past experience, ASEAN should reconsider introducing a new form of regionally coordinated policies, such as the ASEAN Industrial Joint Venture (AIJV) in  and later the ASEAN Industrial Cooperation (AICO) in , which was successful in expanding the regional division of labour and scale economies of the auto industry. Finally, the chapter concludes by suggesting that the future success of ASEAN industrial policy hinges on the continued growth of Chinese demand (particularly in light of the US–China trade war) and the ability for ASEAN to build some globally competitive, lead firms in key industries.

. T D  GVC I: ASEAN,  N

.................................................................................................................................. Southeast Asia has arguably emerged as one of the most dynamic regions in the world in the last decades. Over the years, ASEAN economies recorded positive real GDP growth rates of . per cent in  to . per cent in  (IMF, ).⁴ The region’s share of world GDP almost doubled from . per cent in  to . per cent in . ASEAN’s value-added exports also show signs of improvement. ASEAN’s domestic value added improved from  per cent in  to  per cent in . Domestic value added can be interpreted as positive improvement in a country’s domestic capacity to produce goods and services. Therefore, the more a country creates domestic value added, the more income is generated. Meanwhile, ASEAN’s foreign value-added exports slowed from  per cent in  to  per cent in . Contrary to domestic value added, foreign value added is often used to show a country’s exposure to foreign inputs, including raw material resources, parts and components, and services. Foreign value added differs by industry and country. Lower foreign value added may be a positive indication of improvement in domestic production. While ASEAN has had an impressive economic record over the years, the pace of economic growth and export performance varies from country to country. In , for instance, the domestic value added of exports as a share of GDP for Malaysia and Singapore is roughly  per cent and  per cent, respectively; Brunei Darussalam and Thailand are both  per cent; and the rest of the ASEAN economies’ domestic value added of exports as a share of GDP are below the regional average of

⁴ Real GDP growth rates have slowed to . per cent in .

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     : 



 per cent.⁵ Within ASEAN, the share of the total foreign value-added exports is highest in manufacturing ( per cent) compared to primary ( per cent) and services sectors ( per cent) in .⁶ Foreign value-added in manufacturing is driven by motor vehicles and other transport equipment and electronics sectors with roughly  per cent and  per cent, respectively, of the share of the foreign value added in manufacturing. ASEAN’s GVC integration is deeper and potentially more rapid than other regions. Over  per cent of ASEAN member states’ gross exports are linked to GVCs, measured in terms of the sum of the foreign value added and the indirect domestic value added, or the domestic value added incorporated in other countries’ exports (Yamaguchi, ; ASEAN-Japan Center, ).⁷ In , about  per cent of ASEAN’s gross exports were tied to GVCs, compared to the North American Free Trade Agreement (NAFTA,  per cent), Trans-Pacific Partnership (TPP,  per cent), the South American trade bloc (MERCOSUR,  per cent). About  per cent of European Union’s gross exports were linked to GVCs in the same period.

. T E  ASEAN I P: F I- I  E- I  D GVC I

.................................................................................................................................. Despite impressive regional growth over the years, it is difficult to pin down what is the ASEAN’s process of industrialization.⁸ As mentioned, the pace of economic reforms and the institutional capabilities of each ASEAN member state vary in the early phases of the industrialization process. At the outset, ASEAN was born from the collective aspirations of its leaders to fast-track their economic independence and production

⁵ On average, ASEAN’s domestic value added as share of export was  per cent in . ⁶ The share of foreign value added of exports showed little to no change from previous years. ⁷ The domestic value-added is composed of three parts: the domestic value-added embodied in the final demand or intermediate goods consumed directly by the importing economy; domestic valueadded sent to third parties (forward GVC participation); and domestic value-added that are sent back to country of origin used to produce exports. ⁸ ASEAN inter governmental interventions exist to promote trade and changes to regional and global production structures (Arfani, : ).

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

 .    

diversification away from primary and commodity-based production to value-added manufacturing production as the basis for economic modernization (Bautista, ).⁹ However, variations in each country’s endowments, experiences, and priorities compounded the region’s ability to implement a broad-based industrial policy (Ariff and Hill, ). From a political economy point of view, the creation of ASEAN’s was driven by the urgency of regional governments to be economically self-sufficient or ‘independent’, with the gradual withdrawal of global powers in the Asian region. The end of the Cold War is a case in point; ASEAN member states that had previously leaned on US aid scrambled to establish a new regional order that would favour their national developments. Industrial policy is therefore motivated by the need to industrialize and to form a new regional dynamics that would enable growth and sustainable development for all member states (Chang, ). ASEAN economies are small, which makes it even more challenging for countries to achieve the minimum efficiency required for scale economies. It is therefore not surprising that the idea to form ASEAN was first conceived by the foreign ministers of Indonesia, Thailand, Malaysia, the Philippines, and Singapore, or also known as the ASEAN-. The ASEAN- countries signed the ASEAN Declaration in , which outlined the aims and purposes as a regional order that promotes economic growth, social progress, and cultural development. The ASEAN Declaration also mandates its member states to promote regional peace, engage in regional collaboration (i.e. training, research, etc.) and mutual assistance on matters of common interest, including agricultural and industrial cooperation. For ASEAN member states, these collaborations are necessary to raise the living standards of the people in the region. The establishment of such regional institutions had a greater purpose than economic and social goals. Some scholars argued that the common fear of communism from mainland China was the underlying factor in the creation of ASEAN (Jones, ; Narine, ; Broinowski, ; Anwar, ). The political motivation led to some speculation that the association should serve as the informal body to curb even if only indirectly, communism in the region. During this period, we can interpret several events to provide an anti-communist rationale for ASEAN: the US involvement in Vietnam escalated in the region; a joint remark or communique by the Asia and Pacific Council (ASPAC), of which Thailand, Malaysia, and Philippines are members, explicitly endorsed regional efforts ‘to safeguard their national independence and integrity against Communist aggression’; and the declaration by foreign ministers and prime ministers of member states to defend national interests against communism (Broinowski, : ).¹⁰ However, it is far from certain that the existence of ASEAN ⁹ The leaders of ASEAN are referred to as the original founding members or the ASEAN-. ¹⁰ A number of leaders made direct remarks to defend their national interests against the growing threat of communism. This includes statements made by Thanat Khoman of Thailand in  about the need to counter ‘revived germs of an old disease—imperialism—which are still being cultured in [a] large

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     : 



was motivated by the political aim of weakening the potential spread of ideology even though contemporary developments may suggest otherwise. There is no official statement of ASEAN explicitly condemning the potential spread of communism into the region. Member states were strictly espoused to the principles of consensus building, non-alignment, and self-reliance.¹¹ The goal of economic independence led to the adoption of import-substitution industrialization (ISI) policy in the late –s, albeit differing in extent and duration between countries, before shifting to an export-oriented industrialization (EOI) strategy in the –s. Although ISI strategy was short-lived, it marked the region’s first direct effort to transform its regional production to meet global standards. But it was during the EOI period that Southeast Asian economies began to make their mark as major global exporters on the world production stage. Exportoriented growth had a significant impact in transforming the region into an industrial player. ASEAN’s annual industrial growth rates of  to  per cent were recorded for over three decades after introducing EOI policies. For instance, the structural transformation from ISI to EOI more than doubled the share of manufacturing for Indonesia and Malaysia (Hill, , a). In the s, the manufacturing sector constituted less than  per cent of all merchandising exports for ASEAN economies.¹² By the mid-s, manufacturing had become the primary source of economic growth. Scholars have also argued that ASEAN’s rapid economic growth during the EOI phase was linked to FDI or Transnational Corporations (TNCs) (Hobday, ; Pradhan, ; Moudatsou and Kyrkilis ). Singapore was the first to adopt such a TNC-led industrialization strategy, prompting others to follow suit, however, with varying degrees of success.¹³ ASEAN’s outward-looking industrialization strategy of export growth and attracting more investment often overlooks the unevenness of economic development and value-added allocation among individual economies in the region (Oikawa, ). While EOI policy allowed for greater access to international

area of mainland Asia and are threatening the spread to neighbouring lands’ and the statement by Narciso Ramos of the Philippines, which declared that ‘the time has come for a truly concerted struggle against the forces which arrayed against our very survival in these uncertain and critical times’ (Broinowski, ). ¹¹ Indonesia, and to some extent Malaysia, was particularly vital in voicing the principle of nonalignment within ASEAN. Indonesia’s colonial past played a crucial role in shaping its views and approach to international affairs, which is an ‘independent and active’ foreign policy or posture that is not subservient to the interest of major powers (including the west and China). ¹² With the exception of Singapore, which had relatively higher manufacturing exports (less than  per cent) than its ASEAN neighbours. Indonesia did not record significant manufacturing exports prior to the s. ¹³ China and Taiwan are relatively successful in implementing this model of industrialization, particularly in creating special economic zones for electronic exports. Later, Southeast Asian economies followed this model of industrialization with Singapore taking the lead.

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

 .    

markets and capital inflows, the region became increasingly vulnerable to global economic fluctuations, like with the  Asian financial crisis. The  Asian financial crisis upended the region’s decades of EOI strategy and its overall development trajectories.¹⁴ The crisis led to another round of regional industrial policy ‘rethinking’. ASEAN countries that cemented their industrialization strategy based on export performance find it difficult to contain external shocks. As a result, the financial crisis led to deregulation and privatization of several key industries, such as the auto industry in Indonesia and Thailand. However, countries that continued with strong domestic protection of ‘infant industry’ were in a better position to contain the financial crisis. For instance, Malaysia’s unorthodox response to the financial crisis was to impose strict financial measures or capital controls—thus, restricting the flow of foreign capital in and out of the domestic economy.¹⁵ This partly explains why the Malaysian government, unlike its neighbouring counterparts, was more successful in containing the domestic economy from widespread financial panic.¹⁶ Capital controls produced faster economic recovery, including declines in unemployment and improvement in real wages (Kaplan and Rodrik, ).¹⁷ The severity of the financial crisis left some countries with limited policy tools to take the domestic economy back into pre-crisis levels. As a response to the financial crisis, ASEAN economies began implementing a more integrative process of regional production as a potential solution to reintegrate into global markets. Deepening regional economic integration was sought to bring back foreign investments and reinstate market confidence. ASEAN leaders later adopted a more formal language of cooperation in the subsequent ASEAN Summits.¹⁸ In , ASEAN adopted several key policy measures to expedite the process of economic regionalization and integration into GVCs. The free flow of goods and services was the cornerstone of ASEAN cooperation as outlined in the ASEAN Free Trade Agreement (AFTA) in , which was enacted to create a single market and

¹⁴ For some countries in the region, the financial crisis turned into a political crisis. President Suharto of Indonesia was forced to step down after thirty-two years of authoritarian rule due to domestic and political turmoil in many parts of the country. ¹⁵ Capital controls are established to regulate financial flows from capital markets into and out of a country’s capital account. These controls can be economy-wide or specific to a sector or industry. Government monetary policy can impose capital control. They may restrict the ability of domestic citizens to acquire foreign assets, referred to as capital outflow controls, or foreigners’ ability to buy domestic assets, known as capital inflow controls. Tight controls are often found in developing economies where the capital reserves are lower and more susceptible to volatility. ¹⁶ A great deal of scholarly work has been written about the  Asian financial crisis. Refer to Wade (), Radelet et al. (), and Goldstein () for a more detailed discussion. ¹⁷ Financial restrictions, like capital controls, are becoming a more accepted policy tool among policymakers and think tanks. For example, the IMF has been flexible in advocating capital controls as a policy alternative to contain excessive financial speculation. ¹⁸ The ASEAN Summit is held annually by the ten member states to discuss the progress and agreed commitments on political, security, and economic cooperation.

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     : 



international production base, attract foreign direct investments, and expand the intraASEAN trade and investment nexus. The primary mechanism to achieving the goals envisioned in AFTA is the Common Effective Preferential Tariff (CEPT) scheme that underscores a gradual reduction and/or elimination of intra-regional tariffs and import duties up to  per cent for  per cent of all product categories by .¹⁹ The CEPT includes a phased schedule of intra-regional tariff reduction that takes into consideration the level of sensitivity of the products (imports) to the respective ASEAN member states’ domestic industry. A decade later, at the Bali Summit in , ASEAN leaders announced that the ASEAN Economic Community (AEC) would be the new aim of regional economic integration by .²⁰ AEC transforms the region into ‘free movement of goods, services, investment, skilled labour and freer flow of capital’ (ASEAN Secretariat, ).²¹ The AEC replaced the previously agreed CEPT scheme with the ASEAN Trade in Goods Agreement (ATIGA), signed in  and which came into force in . The ATIGA renewed the CEPT agreement by including comprehensive coverage in trade in goods, full tariff reduction schedules and non-tariffs measures, and implementing the ASEAN Single Window (ASW) for rapid exchange of standardized data among member states’ customs agencies, mutual recognition agreements (MRAs), and e-ASEAN, among other new initiatives.²² The ATIGA minimizes the cost of doing business and logistics, deepens economic linkages, creates greater economies of scale for firms within ASEAN, and further maintains a competitive investment environment. AEC was a clear signal to reaffirm its intentions to keep abreast with the rest of the world. The adoption of AEC and its mechanisms laid down the groundwork for deeper regional and GVC participation. For ASEAN, increasing regional integration has several advantages. First, regional integration improves the overall performance of ASEAN; the more connected are regional firms with one another, the more likely

¹⁹ Tariff reduction of up to  per cent by  was a commitment made by the original five ASEAN member states—Indonesia, Thailand, Malaysia, Singapore, and the Philippines. The remaining CMLV countries, which includes Cambodia, Myanmar, Laos, and Vietnam, were given additional time to implement the tariff reduction rates. ²⁰ The ASEAN Economic Community (AEC) goal was initially targeted for  but was accelerated to  by ASEAN leaders during the th ASEAN Summit in January . ²¹ The ASEAN Economic Community (AEC) blueprint outlines the principles for greater connectivity between member states and ASEAN’s participation in regional and global supply chains (Pettman, ; Padilla, Sari, and Handoyo, ). Moreover, the Initiative on ASEAN Integration (IAI) provides guidelines to fast-track the building of infrastructure as well as the legal framework in areas such as broadband connections, e-commerce, technical skills, and many others. ²² The ASEAN Trade in Goods Agreement includes improvements in a number of technical areas such as disciplines on Technical Barriers to Trade (TBT), Sanitary and Phytosanitary (SPS) Measures, and the Temporary Modification and Suspension of Concessions, which outlines some technical guidelines to compensate losses that arise from any modification to changes from existing commitments. Refer to the ASEAN Guidelines on Standards, Technical Regulations, and Conformity Assessment Procedures (STRACAP) for a detailed assessment of technical cooperation.

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

 .    

they are to export to similar global markets. Cooperation among regional firms would result in more efficient production. Second, regional integration would improve the resilience of domestic markets to global fluctuations; during the  global financial crisis caused by the subprime mortgage crisis in the Western world, the ASEAN economies began looking into regional and domestic markets, creating an economic buffer from external shocks. Regionalization gave ASEAN the bargaining power it needs to balance geopolitics and anticipate the economic rise of regional powerhouses, like China and India.

. A C L  ASEAN I P   E  GVC

.................................................................................................................................. For years, traditional economics and leading global economic institutions questioned the effectiveness and the ambiguous contribution of industrial policy on a country’s economic growth. Economic miracles that a country may have experienced cannot be directly attributed to industrial policy or some kind of government- or state-led interventions, such as the promotion or targeting of several strategic industries. Therefore, the lack of a standardized definition of industrial policy among scholars and practitioners would often lead to a dubious, and often inconsistent, method of analysis. There is no consensus on the definition of industrial policy other than that it is some form of government intervention that selectively promotes certain industries (Stiglitz, ; Cimoli, Dosi, Nelson, and Stiglitz, ; Chang, ; Milberg et al., ; Naudé, ). Another interpretation of an industrial policy is the deliberate effort to ‘defy’ its comparative advantage (Chang, , ).²³ Some examples of these interventions include infant industry protection measures through tariff and non-tariff barriers and imposing local content requirements as the basis for ‘infant industries’ protection. Note that contrary to traditional views, countries such as the United States, Great Britain,

²³ Comparative advantage is a theoretical tool for determining a country’s production and trade specialization. However, a strict interpretation of comparative advantage may understates the analysis for industrialization and economic development, say from agriculture to manufacturing and consequently from manufacturing to services. The debate surrounding the importance for countries to rely on or defy its comparative advantage has shed light on the importance of industrial policy and the role of institutions in coordinating resource maintenance and production output (Lin and Chang, ).

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     : 



Japan, and, more recently, South Korea became the world’s industrialists precisely because of industrial policy that promoted the development of national industries and nurtured innovation (Cimoli et al., ; Chang, ). Amsden’s () seminal work on the political economy of South Korea’s industrialization shows the important role of the state in industrial development. According to Amsden, the South Korean government developed its economy not by turning to free-market prescription or by getting the prices right; South Korea succeeded in developing its industries because it got its ‘prices wrong’. Some scholars have also argued that industrial policy should have a more broadbased function that promotes the competitiveness of all productive sectors (Sanjaya, ; Naudé, ). This view suggests a more neutral approach to industrial policy in that it has a function to elevate the growth of the entire supply side of the economy and not only be specific to certain sectors (Rodrik, ). In this sense, industrial policy is an intervention where state and private sectors exchange information, or dialogue, to reduce or eliminate constraints in order to allow the creation of efficient market outcomes (Hausmann and Rodrik, ; Rodrik, , ). Thereby, the state can identify and overcome barriers that may be a hindrance to development. Putting it differently, industrial policy is a process where the state takes a proactive stance to change the structural characteristics of the economy to support selective sectors that yield better prospects of economic growth and development. Others, however, adopt a more pragmatic or practical point of view in their interpretation of industrial policy, implying that there is no single recipe for industrial policy (Chang, ). Industrial policy should reflect the conditions and specific needs of countries seeking economic growth and development. Contrary to the popular view that the Southeast Asia region grew rapidly by relying on market forces and limited, if not acceptable, interventions on human capital and technological innovations, the role of industrial policy in the development of ASEAN economies cannot be understated (Jomo, ). Over the past four decades, industrial policy has had a major role in the successful development of the agricultural and agro-processing sectors, such as palm oil, in Thailand, Malaysia, and Indonesia. Without the existence of such direct intervention by the state, Malaysia would not have emerged as a global exporter in electronics manufacturing. Likewise, Thailand would not have been known as the ‘Detroit of the East’ had it not used government investments to nurture the development of the automotive parts and components industry as early as the s. However, industrial policy in the era of GVCs is different in a sense that it focuses on firms rather than the role of the state (Milberg et al., ). Industrial policy in the era of GVCs would involve the shifting of intervention from the creation of domestic supply chains to increasing bargaining power and improving value creation within the value chains, which includes moving into higher value-added production tasks, or what is commonly called vertical specialization; facilitating access to competitively priced

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

 .    

intermediate inputs; negotiating and creating linkages with multinational lead firms; and moving into higher value-added production tasks (Kaplinsky and Morris, ; Taglioni and Winkler, ). ASEAN has had some relative success in promoting industrial competitiveness and trade facilitation in the region. ASEAN industrial policy began as early as the s. The ASEAN Industrial Project (AIP),  started ASEAN’s agenda to bring about better industry competitiveness, which encouraged joint projects among ASEAN firms (Bautista, ; Ravenhill, ; Yoshimatsu, ). The original plan was to assign one industrial project to each of the five (two out of five were implemented) founding members of ASEAN (Ravenhill, ). Under the AIP arrangement, ASEAN firms were encouraged to come into a joint-venture with regional partners as a way to share fixed costs of production. However, political squabbles among member states and the institutional limitations at the national level hindered the full scope of the original project (ASEAN Secretariat, ; Suriyamongkol, ). Regional industrial cooperation came to fruition with the subsequent implementation of the ASEAN Industrial Complementation Arrangement (AICA) in .²⁴ AICA allows for specialization in a narrower range of products by facilitating manufacturers to produce at a much lower price and achieve higher optimal output for the regional market. Toyota played an important role in implementing AICA as a solution to overcome various local content requirements in automotive production. For instance, in , under AICA, Toyota could purchase auto parts and components from other manufacturers in the region at a low and competitive price, which later became known as the Brand-to-Brand (BB) complementation scheme. Subsequent industrial cooperation was, however, less of a success. In , the ASEAN Industrial Joint Venture (AIJV) was implemented to grant regional firms (registered in ASEAN) with  per cent preferential margins.²⁵ But despite ASEAN’s success in improving auto industrial competitiveness through a centralized policy coordination, like the BB, other industries, particularly ASEAN’s nineteen priority sectors, have yet to follow suit. The future success of ASEAN’s industrial policy hinges on its ability to sustain foreign direct investments. The ASEAN Investment Guarantee Agreement (ASEAN IGA) and the Framework Agreement on the ASEAN Investment Area (AIA), first signed in  and later revised in , provide clear guidelines regarding investment liberalization and protecting foreign investors under a single roof. In ,

²⁴ AICA was formulated with the close cooperation of member state governments and the private sector. The proposal was put forward by the ASEAN Automotive Federation, which was originally made by the Ford Motor Company in . ²⁵ The preferential margins are the absolute difference in the preferential rate of duty between the most-favoured nation and the duty for like products. The preferential margins are extendable up to four years with a maximum extension of eight years extension.

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

     : 



ASEAN upgraded its provisions for investors’ protection through implementing ASEAN Comprehensive Investments Agreements (ACIA). As an economic instrument, the ACIA aims to create a liberal, facilitative, transparent, and competitive investment environment in ASEAN and further advance regional economic integration. Under the current investment framework, foreign investors are rewarded with greater protection and flexibility, including the prohibition of performance requirements (PPRs), which are simply demands by governments for technology transfers or for some preferential treatment of investment, and the freedom to appoint senior management positions, which often requires the inclusion of local managers in the upper hierarchy. The current ACIA framework also sets a clear timeline for member states to implement investment liberalization. Additionally, ACIA has included a more comprehensive investor–state dispute settlement (ISDS) procedure to protect investors from potential damages or losses that arise from changes in state policy. The controversy surrounding the ISDS mechanism in its current form is that it is skewed towards the foreign investor who can enter an arbitration tribunal when there is a breach of contract (of rights granted to investors) by the host state, causing a loss of revenue and profits to private firms. The ISDS is a legal private arbitration that bypasses national judicial systems, which implies a great disadvantage for governments that typically have fewer means to defend their national interests (including litigation expenses). ISDS is considered an integral part of several bilateral and multilateral trade treaties such as the North American Free Trade Agreement (NAFTA) and the Comprehensive and Progressive Trans-Pacific Partnership (CPTPP), which is the successor of the Trans-Pacific Partnership (TPP) after the US withdrawal (Sturgeon, Van Biesebroek, and Gereffi, ). The renewed terms on investor protection reflect a bold intention to better accommodate the interests of investors and the maintaining of foreign capital. ASEAN has traditionally been a strong proponent of intellectual property rights (IPR) protection, although industrializers of the past—including the United States, the United Kingdom, and Japan—industrialized without the existence and the enforcement of IPR protection (Chang, ).²⁶ The ASEAN Framework Agreement on Intellectual Property Rights in  and the ASEAN Intellectual Property Rights Action Plan – are the two primary documents that outline the general principles of intellectual rights protection in the region.²⁷ The framework on intellectual property rights puts in place effective protection measures for IPR, including a new provision to improve the administrative body for data collection and human resources

²⁶ China has been a member of the World Intellectual Property Organization since  and acceded to the Paris Convention for the Protection of Industrial Property in , however IPR infringements and copyright violations are commonly reported. ²⁷ The two provisions on intellectual property rights are formulated directly by the ASEAN Working Group on Intellectual Property Cooperation (AWGIPC) and coordinated by ASEAN Secretariat.

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi



 .    

development. The existing framework on intellectual property rights provides the groundwork to establish a new ASEAN patent system, such as the ASEAN Patent Office. Policymakers recognized the urgency of renewing intellectual property rights protection to promote and encourage more technology start-ups or ‘unicorns’ in the region.²⁸ Although ASEAN’s new intellectual property rights regime was put in place to protect the future of ASEAN’s e-commerce industry, it falls short in addressing the extent of intellectual property rights protection in its current production structures. In the world of GVCs, government protections of intellectual property have the effect of ‘locking in’ the monopoly power to the intangible asset creation (Pagano, ; Durand and Milberg, ). Intangible assets are increasingly monopolized by multinational firms (mostly in the West) who own intellectual property. However, this ‘intellectual monopoly’ in intangible assets would have great implications on the presence of economies of scale and network externalities associated with intangible asset creation. The current interpretation of IPR has yet to address the extent or the deepening of intellectual monopoly within ASEAN GVCs. The general evolution of ASEAN’s industrial policy suggests a greater facilitation for foreign investors, that is, access to regional markets and protection, as opposed to creating mutually beneficial outcomes for domestic producers and lead firms. While ASEAN accommodates member states’ levels of development and considers deeply the sensitivity of national products to imported goods, recent policy initiatives lacked the creative approaches necessary to improve regional production efficiencies and further encourage innovation in local economies. For instance, the provisions needed to create economies of scale and a more specialized division of labour in the auto industry (i.e. the AIP and AICA provisions) remains a unique case that existed during the pre-GVC era when industrial policy was centrally coordinated by the state at the national level.²⁹ ASEAN has yet to replicate similar region-wide policy initiatives in several of its targeted strategic industries. One must also consider the proliferation of regional trade arrangements that have become the preferred alternative to the slow-paced, and often convoluted, multilateral negotiations process. This might restrict the effectiveness of ASEAN industrial policy. For example, competing for regional trade arrangements such as the CPTPP, formerly known as TPP, might overshadow ASEAN’s very own CEPT arrangement as the cornerstone to promote regional trade competitiveness. Four out of ten ASEAN members (Brunei, Malaysia, Singapore, and Vietnam) are parties to the CPTPP. Indonesia—the largest country in ASEAN in terms of the size of the economy and

²⁸ Regional firms with ‘unicorn’ status include Grab (Singapore), Gojek (Indonesia), Lazada (Singapore), Traveloka (Indonesia), VNG (Vietnam), and Revolution Precrafted (Philippines). ²⁹ ASEAN’s undemocratic regimes and their close association with Japanese multinational firms, like Toyota, have been fostered since the s and s. This made it possible for the state to singlehandedly manage the process of industrialization.

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

     : 



population—has considered joining the CPTPP in the past but retracted its intention to join. The proliferation of regional trade arrangements pressured ASEAN to respond to the demands for better protection by global investors. This is clear when the number of measures, such as ISDS and the recent intellectual property rights framework, are considered. We cannot ignore the spectacular rise of China and its increasing demand for intermediate inputs from ASEAN suppliers. China’s economic influence in the region poses an economic opportunity to expand ASEAN’s export market, especially given the impasse present in the current state of international trade negotiations.

.. Reshaping ASEAN Industrial Policy in the Era of GVCs: Towards a more Inclusive Participation In the effort to expedite the process of regional economic integration in Southeast Asia, ASEAN has put forward several updates of its strategic action plans to complement the ASEAN Economic Community (AEC) Blueprint .³⁰ The aim of the AEC Blueprint  was to strengthen and reinforce the characteristics of the ASEAN Economic Community by , that is: (i) a highly integrated and cohesive economy; (ii) a competitive, innovative, and dynamic ASEAN; (iii) enhanced connectivity and sectoral cooperation; (iv) a resilient, inclusive, and people-oriented, people-centred ASEAN; and (v) a global ASEAN. A key feature in its consolidated strategic action plan (CSAP) is to allow for a more structured monitoring and reporting of the implantation progress of the AEC . The newly implemented CSAP makes it more transparent and open for stakeholders to provide feedback towards achieving ASEAN economic integration priorities. The newly adopted CSAP reinforces existing integration areas and a new focus, such as cross-sector complementarities and coordination among ASEAN. The new CSAP made clear efforts to strengthen the characteristics of regional economic integration and ‘ASEAN centrality’. While the language of regional cooperation and industrial policy within ASEAN has been consistent in endorsing the free movement of goods and services, people, and capital, the ASEAN  CSAP shifted towards the promotion of increased participation in regional and global value chains. For instance, in efforts to create a ‘highly integrated and cohesive economy’, ASEAN policymakers have focused on five key elements that include trade in goods; trade in services; investments; financial integration, financial inclusion, and financial stability;

³⁰ The newly updated action plans include Strategic Action Plan – for ASEAN Taxation Cooperation, the ASEAN Work Programme on Electronic Commerce –, and the AEC  Trade Facilitation Strategic Action Plan. These updated action plans serve as a single reference and key action lines towards achieving the ASEAN economic integration agenda –.

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi



 .    

facilitating movements of skilled labour; and finally enhancing participation in GVCs. In each of these elements, new provisions have been included to better facilitate the participation of SMEs—especially, in the least-developed ASEAN member states— within the GVC structures.³¹ Some distinct key action plans outlined in AEC  include increasing the engagement of the private sector with a particular emphasis on the development of SMEs. This policy area is in response to the need to improve the economic distribution and participation of local suppliers in regional supply chains. ASEAN has included new provisions to allow for better opportunities and resources for SMEs to increase their share of participation and reduce constraints such as high costs for exports (Bernard et al., ). SMEs face more resource constraints than domestic large firms, including access to competitive intermediate inputs. Moreover, they capture a low share of the foreign value added of exports and, in turn, contribute indirectly by supplying to domestic firms (Lopez-Gonzales, ). The structural contribution of SMEs to ASEAN economies is significant. SMEs represent a majority (above  per cent) of commercial enterprises in South East Asia and employ  to  per cent of the domestic workforce. SMEs contribute over  per cent of ASEAN’s GDP (OECD/ ERIA, ). SMEs’ employment in the production of intermediate goods traded within the value chains has grown at a much faster rate than overall employment growth (Lopez-Gonzales, : ). This illustrates the contribution that SMEs make in supplying intermediate inputs to regional supply chains (Kowalski et al., ). However, SMEs’ contribution to total exports is relatively insignificant, estimated at around  to  per cent. The recent change in policy shows that ASEAN policymakers have put a great deal of effort into reducing costs and improving access to physical and non-physical infrastructures for SMEs, including practical and/or vocational training. Although SME policies have traditionally been associated with creating social cohesion, it has evolved into stimulating innovation and entrepreneurship in ASEAN. Over the last thirty years, ASEAN’s industrial strategy focused on creating greater market access, through reducing or eliminating barriers to trade and investments, and maintaining high foreign investments. While such policies may be necessary to motivate the flow of goods and services between different production nodes in the value chain, they fall short of guaranteeing firms and industries from ‘industrial upgrading’, or moving up the value chains from relatively lower to higher value-added economic activities (Pietrobelli and Rabellotti, ). Industrial upgrading captures more of the value-added in the production process and increases profits for local firms. The recent policy priorities to increase

³¹ The ASEAN Roadmap for Integration codifies ASEAN policies on industrial competitiveness by way of providing mutual technical assistance, especially for the least-developed economies such as the CMLV (Cambodia, Myanmar, Laos, and Vietnam).

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

     : 



intra-ASEAN trade and investment flows consequently created a vacuum for structural change and the ability to foster innovation.

.. ASEAN Industrial Policy in GVCs: Success or Failure? Given the recent adoption of ASEAN’s GVC policies, it is too early to tell whether such a shift was a success. The AEC Blueprint outlined the agenda to strengthen and reinforce regional economic integration through trade facilitation and increasing the participation of SMEs within GVCs. In this section, we assess the shortcomings of ASEAN industrial policy in the era of GVCs and put forward potential solutions to ensure that the current policy focus is consistent to the objectives of ASEAN economic integration. First, ASEAN’s regional policy coordination has helped to deepen regional integration, however, it remains incoherent. The pace and quality of policy implementation at the domestic level vary across member states (Bautista, ; Yoshimatsu, ). For instance, while reducing and/or eliminating tariffs across the region has been relatively successful (i.e. zero tariffs for most products for ASEAN countries), other technical aspects, such as improving customs procedures, dispute settlement mechanisms, the rule of origin, and the removal of non-tariff barriers, have weak institutional enforcements (Kadarusman, ). The capacity for national ministries and agencies to coordinate the regionally agreed principles also matters a great deal (Chang, ; Kadarusman, ). The lack of policy enforcement is partly because ASEAN policy relies on a consensus-building process, which allows flexibility, such as additional time and assistance, to implement the agreed regional commitments. Second, while increasing SME participation is a positive attempt to redistribute gains (i.e. employment and income) from taking part in the global economy, more needs to be done in expanding regional cooperation on SME development. Firms that are more engaged in export markets tend to be more efficient and pay more in wages (Bernard and Jensen, ). However, SME limitations are well documented and policy dimensions to overcome them have been proposed (Lévy, ; Jinjarak et al., ; OECD, ; Taglioni and Winkler, ; Kowalski et al., ; Lopez-Gonzales, ). At the current stage, regional cooperation on SME development takes the form of information and experience sharing. More direct cooperation would be needed to better streamline the lessons learned from national to regional level. ASEAN SMEs could benefit from adopting a more standardized system of exchange, including the financial information of SMEs among ASEAN member states. Third, ASEAN’s trade and investment outlook has persistently fostered export performance but lacked the infrastructure and framework for industrial upgrading,

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi



 .    

primarily for the nineteen priority sectors. This partly explains why the regional production network in ASEAN continues to be concentrated in ‘buyer-led’ GVCs as opposed to ‘producer-led’ GVCs (Gereffi, ). The former refers to production chains whose lead firms outsource the entire production process and final product to suppliers.³² Conversely, in a producer-led production chain, the lead firm controls the means of production and technologies in the host country.³³ This field have argued that GVC participation in a buyer-led GVC is increasingly difficult and costly for local firms in developing economies. ASEAN’s industrial policies lack the reward (or penalty) system that East Asian industrialists received during their process of industrialization (Amsden, ; Chang, ; Naudé, ). A reward system, such as an export subsidy, encouraged South Korean chaebols, or large industrial conglomerates, to enter export markets. ASEAN may consider incorporating a reward system (such as an export subsidy) for local firms that successfully achieved some form of upgrading (i.e. functional) for certain product categories. Without such incentives, policies to eliminate tariffs and the removal of non-tariff barriers would, in the long run, only benefit large and foreign multinational firms. Finally, there is a great deal of uncertainty regarding ASEAN’s intellectual property rights regime. The new initiatives to create a new ASEAN patent system, which includes the ASEAN Patent Office to promote regional patent protection, respond directly to the growth of the non-productive and technology sectors. While we cannot undermine the importance of an ASEAN patent system, a more general approach that would allow for knowledge transfers would be more appropriate in GVCs.

. ASEAN’ R P C: T C   A I  I  T

.................................................................................................................................. This section reviews the progress of ASEAN industrial policy in the automotive industry that began as early as the s. There are historical and political economy ³² Buyer-led is when large retailers and global brands contract the entire process of production, including designs and production, to the supplier on a short-term contractual basis. ³³ Industries that value highly intellectual property, like the automotive industry, are good examples of producer-led GVCs. ASEAN’s buyer-led GVCs may extend the patterns of production towards a low value-added manufacturing export rather than shifting towards producer-led GVCs, which would require significant investments and access to financial resources. There is a big gap in the distribution of these resources among ASEAN member states (Chang, ; Kadarusman, ). With the current policy initiatives, ASEAN suppliers will probably face power asymmetries within the GVC governance.

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

     : 



elements that contributed to the rapid growth of the automotive parts and components and assembly sectors in Southeast Asia. Japanese automakers, particularly Toyota, and, to some extent, Kia of South Korea, played a key role in transforming the region as the hub in auto manufacturing. These conglomerates developed new business ‘relationships’ with regional authorities. The growth of the automotive industry in ASEAN is congruent with the internal political interests of the current regimes. The development of the automotive industry is arguably one of the recent success stories that emerge directly from ASEAN regionally coordinated industrial policy. Today, ASEAN is emerging as the hub of regional automotive manufacturing with the production of auto parts and components integrated across member states. The automotive industry is undoubtedly one of the most complex global industries, with production centres (or clusters) scattered across several continents. The auto industry relies on large capital investment and research and development, and institutional support for capacity building. Auto firms are increasingly becoming more dependent on each other for inputs and for delivering quality products to the end market. The auto industry is persistently transforming from geographical, organizational, and technological standpoints (Sturgeon and Van Biesebroeck, ; Sturgeon et al., ). Auto production is no longer concentrated in advanced countries, such as the United States, Germany, and Japan. There has been a gradual shift away from the global North and into the global South (Traub-Merz, ). In , for instance, China ( per cent of global production share,  million units) became the largest automotive manufacturer, followed by the United States ( per cent,  million units), Japan ( per cent,  million units), Germany ( per cent,  million units), and South Korea ( per cent, . million units). At the regional level, India, Mexico, Indonesia, and Thailand are also becoming prominent auto manufacturers. The trend in automotive production is likely to divide into automotive manufacturers in the global North producing a ‘core competence’ of skills-based production, such as engineering and design, while manufacturers in the global South take up most of the labour-intensive and assembling process (Sturgeon and Van Biesebroeck, ). As a whole, global auto production has been on the uptrend and Asia (including China) has been the major contributor. Global sales in automotive products (excluding motorcycles) rose from  million units in  to  million units in ; Asia is the largest automotive consumer market, with growing motor vehicle sales as high as  million units, followed by North America (. million units) and Europe ( million units). However, demand for motor vehicles in Latin America (. million units) and Africa (. million units) has not been as dynamic as in other regions in recent years. The rise of Asia’s middle-income group partly explains the demand surge for vehicles. From a regional perspective, Asia captures more than half of the global production. In , Asia produced about  million units of vehicles, up from  million in  (International Organization of Motor Vehicle Manufacturers. Global auto

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi



 .    

production absorbs roughly  million workers worldwide or about  per cent of the world’s total manufacturing employment (OICA, ).³⁴ At the regional level, there is a clear shift in investment into countries with relatively lower production costs, that is, Thailand, Indonesia, and Vietnam in Southeast Asia; China in East Asia; and Mexico and the American South in North America (Sturgeon et al., ).³⁵ Conversely, auto industry manufacturing in the less-industrialized economies remains in labour-intensive production, such as in parts and components and assembling (Milberg and Winkler, ). The development of the auto industry is consistent with the industry’s global transformation in production structures, distribution, and innovation. Indonesia and Thailand are the largest automotive manufacturers in Southeast Asia, with a combined production of over  billion units of vehicles, and export values of roughly US$ billion in  alone. Foreign direct investment (FDI) reached US$ billion for Indonesia in  and net FDI investments of US$ billion for Thailand from  to  (Phungtua, ). Indonesia and Thailand have made new commitments to place the auto industry at the centre of their national economic and development programmes. The government of Indonesia, for instance, has set a production target of  million vehicle units (from  million) and similarly the government of Thailand has increased its production target to  million vehicles (from  million) by .³⁶ Indonesia issued a presidential decree to restructure the country’s automotive industry away from traditional parts and components production to producing environmentally friendly and technologybased vehicles. The decree also outlined new initiatives for more R&D and investments in technology-based universities. The auto industry represents a small but growing sector. Recent figures show that the sector’s contribution to employment grew impressively from roughly , to , in Indonesia and similarly , to , in Thailand from  to  (UNIDO, ). The industry’s contribution to value-added per worker also showed a growth trend from US$, per worker to US$, per worker in Thailand and US$, per worker to US$, per worker in Indonesia.³⁷ ³⁴ This figure includes employment for the production of parts and components and assembling. The lack of disaggregated employment data makes it difficult to assess employment compositions. This raises an important question regarding local job improvements from increased participation in global production networks or global value chains. ³⁵ In North America, vehicle design, development, and specific parts and production are concentrated in the United States and Canada (as well as the southern part of the US border) in the business of assembling (Sturgeon et al., ). The North American automotive industry is shifting towards sub-assemblies of parts of components, supplying not only in its region but also to the rest of the world. Thailand and Indonesia assemble most of the vehicles for East and South East Asia. ³⁶ The automotive industry in Thailand has strategic importance of  per cent to the country’s economic development and accounts for  per cent of the GDP in  and is part of the country’s economic developmental agenda. ³⁷ The value-added per worker is computed by taking the total value added from the auto industry divided by the number of employees.

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

     : 



.. The GVC in the Automotive Industry Mainstream economics predict that increased openness to international trade, typically through various policies such as export promotions, deregulation, and, more recently, greater participation in the GVC network, leads to faster economic growth. The argument is that openness to the international market opens up new economic opportunities for host countries, including foreign investment inflows from capitalrich countries to emerging countries, providing better access to technology for production. The neo-liberal agenda³⁸ (i.e. the Washington Consensus policy) of the s also contributed significantly to global production fragmentation, which enabled developing economies to contribute to the global supply chains by producing the labour-intensive aspects of the production (Feenstra, ).³⁹ The new pattern of global trade led to production offshoring part of the production processes to factories in developing economies, which meant that multinational firms could lower their production unit costs and keep their core competence (i.e. design, engineering, etc.) and developing countries could specialize in certain production tasks without having to build an entire industry from the ground up (Gereffi and Kaplinsky,  Humphrey and Memedovic, ; Humphrey, ; Pietrobelli and Rabellotti, ; Cattaneo et al., ). Production fragmentation gave way to more sophisticated trade flows known as GVCs.⁴⁰ The GVC is an intricate web of modes of production; GVC production is not just a linear stream of a value-added creation that involves a multiple cross-border of production mode (i.e. export and re-export). Intermediate input goods cross and reenter the border more than once via other countries’ exports. What the GVC concept also proposes is the opportunity for local producers to learn from the global leaders of the chains, which may be buyers or producers, and capture the dynamics of the trade from trade in final goods to intermediate inputs trade, also known as ‘trade-in-tasks’. The GVC analysis includes not only production aspects but also the flow of information, clarifying that firm linkages within and between industries involve skills and knowledge-sharing, critical for increasing value added. ³⁸ Harvey () argues that the spread of neo-liberalism in the s played a central role in modern economic processes towards the creation of a free market economy. Harvey underscores how the role of the state was to facilitate that freedom and protect capital and private property. ³⁹ The Heckscher-Ohlin model of international trade stipulates that a country’s exports hinge on their comparative advantage and abundant factor endowments. For instance, developed countries are abundant in capital- and/or skilled-intensive production and developing countries are abundant in labour- and/or low-skilled production. Following the Heckscher-Ohlin model, the direction of trade would be that developed countries export capital-intensive goods/services and developing countries export labour-intensive goods/services. ⁴⁰ The GVC is a series of activities needed to turn raw materials into finished products and sell on the value-added at each node of the production processes (Gereffi and Kaplinsky, ; Kaplinsky and Readman, ). GVCs can be argued to be the practical application of World System Theory that predicted a global production dependency among core or advanced countries on the one hand and periphery countries on the other.

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

 .    

Greater participation in GVCs is also a way for developing economies’ suppliers to improve their prospects of earning economic profits (Gereffi, ; Humphrey, ). However, governance in GVCs and competitive pressure make it difficult for developing economies’ suppliers to earn higher profit margins (Humphrey and Schmitz, ). Suppliers are under pressure to provide quality products at a low unit price. In most cases, firms may earn profits outside production. It is necessary for suppliers to have the ability to upgrade and capture more value within the value chain. We can categorize automotive GVCs into six main stages: vehicle design and development; parts and components; modules and subsystems; system integration and final assembly; marketing and sales; and finally, replacement parts and recycling. Of these categories, the lead firms specialize in vehicle design and development and marketing and sales. It outsources other product categories to local firms in the supply chain. In ,  per cent (or about US$ billion) of the value of global trade was of parts and components and  per cent (or US$ billion) was of sub-assemblies (Sturgeon et al., ). The value of parts and components rose from previous years— per cent in . From this, Sturgeon et al. estimated that final products for passenger vehicles contributed to about  per cent of total exports in the automotive sector in  (a fall from  per cent in ). Parts and components also represent a large chunk of Indonesia’s and Thailand’s automotive exports. The source of auto demand mostly comes from emerging economies with a rising middleincome class. China, Indonesia, India, and Brazil are among the world’s largest economies, with strong market growth rates of ., ., ., and . per cent, respectively, in . However, advanced economies such as the United States, Japan, and Germany are experiencing a fall in demand with market growth rates of –., –., and –., respectively, in the same period. This trend in automotive demand is likely to continue.

.. A Path to Development and Industrial Upgrading Participation in GVCs presents emerging countries with an alternative channel or pathway for economic development. For local firms in developing economies, GVC participation is an opportunity to have greater access to technological advancements and potentially have a positive spillover effect for the domestic economy (Humphrey and Memedovic, ).⁴¹ GVC participation is closely associated with growing productivity and less concentration in a country’s export basket, including exports of more

⁴¹ This includes improvements in human resources and skills-upgrading, and increased investment in infrastructure and R&D.

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

     : 



sophisticated products (Kowalski et al., ). GVCs can also be the driving force in creating local network clusters, or a ‘collective efficiency’ or ‘clusters’, to the overall knowledge of the economy. Silicon Valley in California, United States, and Bangalore, India, are prime examples of clusters in the tech industry. These clusters create positive network externalities. But the important question is whether GVC participation leads to a ‘low-road’ (increasing profits via squeezing wages) or ‘high-road’ (sustainable income growth) process of development. So far, the channels for development in GVCs have not been direct (Milberg et al., ). Recent scholarly work has tried to connect (and measure) both the economic and social gains from increased GVC participation (Rossi, ; Barrientos et al., ; Bernhardt and Milberg, ; Milberg and Winkler, , ). We have expected to see economic upgrading from export expansion and social upgrading from improvements in the workers’ working conditions such as employment and real wages increases. However, evidence suggests that economic upgrading does not lead to social upgrading, and vice versa, and there are significant variations between countries and sectors (Taglioni and Winkler, ; Kaplinsky and Morris, ). From a development standpoint, there are potential shortcomings with GVC analysis. First, emerging countries face barriers (i.e. technology, access to capital, etc.) and asymmetrical power structures skewed towards lead firms (Gereffi and Kaplinsky, ). Thus, knowledge transmission for upgrading is not automatic and may depend on the relationships between local firms and lead firms (Humphrey and Schmitz, ). The literature on FDI mostly shows weak evidence linking FDI inflow and its spillover effects, although there is evidence showing a significant association with improvements in human capital (Slaughter, ). Second, industrial upgrading functions at the level of the individual firm in a particular value chain. The success stories of GVC upgrading have been sporadic for selected industries and countries, which makes it difficult for policymakers to replicate successes in other industries (Bair, ; Brewer, ). Thus, industrial upgrading in one particular sector does not result in overall development at the national level (Bair and Gereffi, ). Third, there is no such thing as a ‘one-size-fits-all’ policy prescription for countries to capture the gains from international trade and greater participation in a GVC network (Pietrobelli and Rabellotti, ). This would require countries to identify specific transmission channels, such as market entry (backward or forward linkages), market structure, and the labour market conditions within the value chain to capture the gains.

.. ASEAN’s Regional Policy Coordination in the Automotive Industry ASEAN has had a significant role in ensuring the region takes full advantage of global production in industries such as textiles and garments, electronics, and automotive.

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

 .    

The ASEAN Complementation schemes ‘allow parts manufacturers to supply final assemblers in all member states from a single ASEAN location at favourable terms of trade as long as inter-ASEAN trade among taking part companies remains balanced’ (Sturgeon and Florida, ). ASEAN’s complementation schemes include programmes such as the ASEAN Industrial Joint Venture (AIJV) in , Brand-toBrand Complementation (BBC) in , and ASEAN Industrial Cooperation (AICO) in . These programmes rely on resource-pooling and market-sharing among member states to generate economies of scale. One application of the complementation scheme is to allow countries to trade different aspects of the production process, including as parts and components, and engine transmissions, from different origins at lower costs than would have been possible if the scheme were not in place. More than that, complementation schemes (like the ASEAN AICO) allows for inter-firm cooperation, encouraging increased intra-ASEAN trade, FDI flows, and technological transfers. The ASEAN complementation scheme plays a unique role in ensuring that member states benefit from the global production network. As Traub-Merz () asserts in his study on the rise of automotive in emerging markets, ‘without membership of large economic zones in which duty-free internal market trade exists, no country has yet entered export markets for cars on a significant level’.

. T F M  ASEAN I P

.................................................................................................................................. This chapter looked more closely into ASEAN industrial policy in the era of the GVC. After periods of industrial policy evolution, from import-substitution industrialization in the s to export-oriented growth in the s and s to focusing on deepening GVC participation, ASEAN has emerged as one of the most dynamic economic regions in the world. ASEAN has made significant inroads into deepening its participation in regional and global value chains by eliminating tariffs, removing non-tariff barriers across member states, and improving general and conformance standards and providing greater protection and rights for foreign investors. However, ASEAN industrial policy in the era of the GVC has yet to bring significant outcomes in the automotive sector. ASEAN’s industrial policy in the automotive industry, like AIJV and AICO, provides a great example of how a regionally coordinated industrial policy creates scale economies and better distributes the gains to member states. ASEAN should look back to its past policies and rethink how it can introduce new forms of policy initiatives suited to address the intricacies of the global production network. We noticed that ASEAN’s industrial policy in the last few years shifted to addressing the participation and inclusivity of SMEs in regional value chains. ASEAN has been particularly active in SME policy in recent years, which includes facilitating SMEs with

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

     : 



greater access to financial resources and vocational training, to name just a few. While the redistribution of gains from increased GVC participation may be good for SMEs in the sense that it improves employment and income, it does not necessarily address the asymmetries of market power within the GVC network. While we cannot understate the value of their contribution in supplying intermediate input goods for large domestic firms and multinational firms, it leaves a large vacuum in policy for large domestic firms that are in a better position to compete with multinational lead firms within the existing GVC structure. The future success of ASEAN would hinge on its ability to build globally competitive lead firms. Our assessment of ASEAN industrial policy in the era of GVCs, as outlined in the ASEAN Economic Blueprint , showed that limited policies were available to ensure industrial upgrading, or moving up from relatively lower valueadded to higher value-added economic activities. ASEAN’s priority to improve local participation and the inclusivity of SMEs should not outweigh policy initiatives for innovation for large domestic firms that are directly competing with foreign multinational firms. Stakeholders need to rethink regional industrial policies within the existing intricate web of global production. Policymakers should reconsider the aim of regional integration based only on increasing the number actively participating in supply chains and look beyond and consider how local actors can take full advantage of the GVC network. ASEAN industrial policy in the era of GVCs could push countries into a ‘low valueadded trap’, or increased specialization in low value-added labour-intensive manufacturing. Policies that would increase SME participation fall short in encouraging innovation and the possibility of capturing profits for local firms. ASEAN policymakers should also consider new ways to build a regional hub for research and development that would be useful for identifying the possibility and the scope of functional upgrading in priority sectors.

R Amsden, Alice H. () Asia’s Next Giant: South Korea and Late Industrialization. Oxford: Oxford University Press. Anwar, Dewi Fortuna () ‘ASEAN and Indonesia: Some Reflections’, Asian Journal of Political Science (): –. Arfani, Riza Noer () ‘Political Economy of Regionalism in ASEAN and Its + Partners: Contemporary Changes in the Automotive and Electronics Production Networks’, Ritsumeikan International Affairs : –. Ariff, Mohammed and Hal Hill () Export-oriented Industrialisation: The ASEAN Experience. London: Routledge. ASEAN-Japan Center () ‘Global Value Chains in ASEAN: A Regional Perspective’, ASEAN Promotion Center on Trade, Investment, and Tourism. January.

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 .    

ASEAN Secretariat () ‘ASEAN Economic Cooperation for the s’. A Report Prepared for the ASEAN Standing Committee. Philippines: Philippine Institute for Development and ASEAN Secretariat. ASEAN Secretariat () ‘ASEAN Economic Community Blueprint’. Association of SouthEast Asian Nations. Bair, Jennifer, () ‘Global Capitalism and Commodity Chains: Looking Back, Going Forward’, Competition & Change (): –. Bair, Jennifer and Gary Gereffi () ‘Upgrading, Uneven Development, and Jobs in the North American Apparel Industry’, in William Milberg (ed.) Labor and the Globalization of Production. London: Palgrave Macmillan, pp. –. Barrientos, Stephanie, Gary Gereffi, and Arianna Rossi () ‘Economic and Social Upgrading in Global Production Networks: Developing a Framework for Analysis’, International Labor Review (–): –. Bautista, Romeo M. () Industrial Policy and Development in the ASEAN Countries. Manila: PIDS. Bernard, Andrew B., J. Bradford Jensen, Stephen J. Redding, and Peter K. Schott () ‘Firms in International Trade’, Journal of Economic Perspectives (): –. Bernhardt, Thomas and William Milberg () ‘Economic and Social Upgrading in Global Value Chains: Analysis of Horticulture, Apparel, Tourism and Mobile Telephones’. Global Development Institute Working Paper Series, University of Manchester. Brewer, Benjamin D. () ‘Global Commodity Chains and World Income Inequalities: The Missing Link of Inequality and the Upgrading Paradox’, Journal of World-Systems Research (): –. Broinowski, Alison (ed.) () Understanding ASEAN. Basingstoke: Macmillan International Higher Education. Cattaneo, Oliver, Gary Gereffi,and Cornelia Staritz (eds) () ‘Global Value Chains in a Post-crisis World: A Development Perspective’. Washington, DC: World Bank. Chang, Ha-Joon () ‘Trade and Industrial Policy Issues’, in Ha-Joon Chang (ed.) Rethinking Development Economics. London: Anthem Press, pp. –. Chang, Ha-Joon () The East Asian Development Experience: The Miracle, the Crisis and the Future. London: Zed Books. Chang, Ha-Joon () ‘Industrial Policy: Can We Go beyond an Unproductive Confrontation?’, Annual World Bank Conference on Development Economics, pp. –. Cimoli, Mario, Giovanni Dosi, Richard R. Nelson, and Joseph E. Stiglitz () ‘Institutions and Policies Shaping Industrial Development: An Introductory Note’, in Mario Cimoli, Giovanni Dosi, and Joseph E. Stiglitz (eds) Industrial Policy and Development: The Political Economy of Capabilities Accumulation. Oxford: Oxford University Press, pp. –. Durand, Cédric and William Milberg () ‘Intellectual Monopoly in Global Value Chains’, Review of International Political Economy (): –. Feenstra, Robert C. () ‘Integration of Trade and Disintegration of Production in the Global Economy’, Journal of Economic Perspectives (): –. Gereffi, Gary () ‘The Organization of Buyer-driven Global Commodity Chains: How US Retailers Shape Overseas Production Networks’, in Gary Gereffi and Miguel Korzeniewicz (eds) Commodity Chains and Global Capitalism. Greenwood, CA: Praeger Publishers, pp. –. Gereffi, Gary () ‘A Commodity Chains Framework for Analyzing Global Industries’, Institute of Development Studies (): –.

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     : 



Gereffi, Gary and Raphael Kaplinsky () ‘Introduction: Globalisation, Value Chains and Development’, IDS Bulletin (): –. Goldstein, Morris () The Asian Financial Crisis: Causes, Cures, and Systemic Implications. Washington, DC: Peterson Institute for International Economics. Harvey, David () A Brief History of Neoliberalism. New York: Oxford University Press. Hausmann, Ricardo and Dani Rodrik () ‘Economic Development as Self-discovery’, Journal of Development Economics (): –. Hill, Hal () ‘Rapid Industrialization in ASEAN: Some Analytical and Policy Lessons’, Agenda: A Journal of Policy Analysis and Reform (): –. Hill, Hal (a) ‘Towards a Political Economy Explanation of Rapid Growth in ASEAN: A Survey and Analysis’, ASEAN Economic Bulletin (): –. Hobday, Mike () ‘Learning from Asia’s Success Beyond Simplistic “Lesson-Making” ’. UNU-WIDER Working Paper No. -. Helsinki: UNU-WIDER. Humphrey, John () ‘Upgrading in Global Value Chains’. Working Paper No. . Geneva: ILO Policy Integration Department. Humphrey, John and Olga Memedovic () ‘The Global Automotive Industry Value Chain: What Prospects for Upgrading by Developing Countries?’. UNIDO Sectorial Studies Series Working Paper. Vienna: UNIDO. Humphrey, John and Hubert Schmitz () ‘How Does Insertion in Global Value Chains Affect Upgrading in Industrial Clusters?’, Regional Studies (): –. IMF (International Monetary Fund) () World Economic Outlook. Washington, DC: IMF. Jinjarak, Yothin, Paulo J. Mutuc, and Ganeshan Wignaraja () ‘Does Finance Really Matter for the Participation of SMEs in International Trade? Evidence from , East Asian Firms’. ADBI Working Paper No. . Asian Development Bank Institute. Jomo, Kwame S. () ‘Rethinking the Role of Government Policy in South East Asia’, in Joseph E. Stiglitz and Shahid Yusuf (eds) Rethinking the East Asian Miracle. Oxford: Oxford University Press, pp. –. Jones, Lee () ASEAN, Sovereignty and Intervention in Southeast Asia. Basingstoke: Palgrave Macmillan. Kadarusman, Yohanes B. () ‘AEC  and Beyond: Realizing ASEAN Value Chain’, Thailand and the World Economy (): –. Kaplan, Ethan and Dani Rodrik () ‘Did the Malaysian Capital Controls Work?’, in Sebastian Edwards and Jeffrey A. Frankel (eds) Preventing Currency Crises in Emerging Markets. Chicago, IL: University of Chicago Press, pp. –. Kaplinsky, Raphael and Mike Morris () ‘Thinning and Thickening: Productive Sector Policies in the Era of Global Value Chains’, European Journal of Development Research, (): –. Kaplinsky, Raphael and Jeff Readman () ‘Globalization and Upgrading: What Can (and Cannot) Be Learnt from International Trade Statistics in the Wood Furniture Sector?’, Industrial and Corporate Change (): –. Kowalski, Przemyslaw, Javier Lopez Gonzalez, Alexandros Ragoussis, and Cristian Ugarte () ‘Participation of Developing Countries in Global Value Chains: Implications for Trade and Trade-related Policies’. OECD Trade Policy Paper No. . Paris: OECD Publishing. Lévy, Benny () ‘Korean and Taiwanese Firms as International Competitors: The Challenges Ahead’. Center for Development Economics , Department of Economics, Williams College.

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

 .    

Lin, Justin and Ha-Joon Chang () ‘Should Industrial Policy in Developing Countries Conform to Comparative Advantage or Defy It? A Debate between Justin Lin and Ha-Joon Chang’, Development Policy Review (): –. Lopez-González, Javier () ‘Mapping the Participation of ASEAN Small- and Mediumsized Enterprises in Global Value Chains’. OECD Trade Policy Papers No. . Paris: OECD. Milberg, William and Deborah Winkler () ‘Economic and Social Upgrading in Global Production Networks: Problems of Theory and Measurement’, International Labour Review (–): –. Milberg, William and Deborak Winkler () ‘Trade Crisis and Recovery: Restructuring of Global Value Chains’. Washington, DC: World Bank. Milberg, William and Deborah Winkler () Outsourcing Economics: Global Value Chains in Capitalist Development. Cambridge: Cambridge University Press. Milberg, William, Xiao Jiang, and Gary Gereffi () ‘Industrial Policy in the Era of Specialized Industrialization’, in José Manuel Salazar-Xirinachs, Irmgard Nübler, and Richard Kozul-Wright (eds) Transforming Economies: Making Industrial Policy Work for Growth, Jobs and Development. Geneva: International Labour Organization, pp. –. Moudatsou, Argiro and Dimitrios Kyrkilis () ‘FDI and Economic Growth: Causality for the EU and ASEAN’, Journal of Economic Integration (): –. Narine, Shaun () Explaining ASEAN: Regionalism in Southeast Asia. Boulder, CO: Lynne Rienner Publishers. Naudé, Wim () ‘Industrial Policy: Old and New Issues’. Working Paper No. –, World Institute for Development Economics Research. OECD () ‘Small and Medium-sized Enterprises in Global Markets: A Differential Approach for Services?’. OECD Trade Policy Paper No. . Paris: OECD Publishing. OECD/ERIA () SME Policy Index: ASEAN : Boosting Competitiveness and Inclusive Growth. Paris, Jakarta: OECD Publishing, Economic Research Institute for ASEAN and East Asia. OICA (The International Organization of Motor Vehicle Manufacturers) () ‘Passenger Car Production Statistics’, available at http://www.oica.net/category/production-statistics/. Oikawa, Hiroshi () ‘To Be or Not to Be a Supplier to TNCs? An Entrepreneurial Approach to Linkage Formation in the Malaysian Electronics Industry’, in Momoko Kawakami and Timothy J. Sturgeon (eds) The Dynamics of Local Learning in Global Value Chains. London: Palgrave Macmillan, pp. –. Padilla, Miguel A. E., Dyah W. Sari, and Rossanto D. Handoyo () ‘Formation of Production Networks in ASEAN: Measuring the Real Value-added and Identifying the Role of ASEAN Countries in the World Supply Chains’, Business and Economic Horizons (): –. Pagano, Ugo () ‘The Crisis of Intellectual Monopoly Capitalism’, Cambridge Journal of Economics (): –. Pettman, Simon () ‘Standards Harmonisation in ASEAN: Progress, Challenges and Moving beyond ’. ERIA Discussion Paper Series . Jakarta: ERIA. Phungtua, Wilawan () ‘The Impacts of Japanese MNCs and Foreign Direct Investment on Thailand’s Automotive Industry’, EAU Heritage Journal Social Science and Humanities (): –.

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     : 



Pietrobelli, Carlo and Roberta Rabellotti (eds) () Upgrading to Compete: Global Value Chains, Clusters, and SMEs in Latin America. Washington, DC: Inter-American Development Bank. Pradhan, Rudra Prakash () ‘The FDI-led-growth Hypothesis in ASEAN- Countries: Evidence from Cointegrated Panel Analysis’, International Journal of Business and Management (): –. Radelet, Steve, Jeffrey D. Sachs, Richard N. Cooper, and Barry P. Bosworth () ‘The East Asian Financial Crisis: Diagnosis, Remedies, Prospects’. Brookings Papers on Economic Activity (): –. Ravenhill, John () ‘Economic Cooperation in Southeast Asia: Changing Incentives’, Asian Survey (): –. Rodrik, Dani () ‘Industrial Policy for the Twenty-first Century’, CEPR Discussion Papers No. . London: CEPR. Rodrik, Dani () ‘Normalizing Industrial Policy’. Working Paper No. . Washington, DC: Commission on Growth and Development. Rossi, Arianna () ‘Does Economic Upgrading Lead to Social Upgrading in Global Production Networks? Evidence from Morocco’, World Development : –. Sanjaya, Lall () ‘Reinventing Industrial Strategy: The Role of Government Policy in Building Industrial Competitiveness (No. )’. Geneva: United Nations Conference on Trade and Development. Slaughter, Matthew J. () ‘Does Inward Foreign Direct Investment Contribute to Skill Upgrading in Developing Countries?’. Working Paper -. New York: Schwartz Center for Economic Policy Analysis. Stiglitz, Joseph E. () ‘Some Lessons from the East Asian Miracle’, World Bank Research Observer : –. Sturgeon, Timothy and Richard Florida () ‘Globalization and Jobs in the Automotive Industry’, Final Report to the Alfred P. Sloan Foundation. International Motor Vehicle Program, Center for Technology, Policy, and Industrial Development, Massachusetts Institute of Technology. Sturgeon, Timothy, and Johannes Van Biesebroeck () ‘Global Value Chains in the Automotive Industry: An Enhanced Role for Developing Countries’, International Journal of Technological Learning, Innovation and Development (): –. Sturgeon, Timothy J., Jack Daly, Stacey Frederick, Penny Bamber, and Gary Gereffi () ‘The Philippines in the Automotive Global Value Chains’. Durham, NC: Duke University Center on Globalization, Governance and Competitiveness. Sturgeon, Timothy J., Johannes Van Biesebroeck, and Gary Gereffi () ‘Prospects for Canada in the NAFTA Automotive Industry: A Global Value Chain Analysis’. Report for Industry Canada, Ottawa. Suriyamongkol, Marjorie L. () Politics of ASEAN Economic Co-operation: The Case of ASEAN Industrial Projects. New York: Oxford University Press. Taglioni, Daria and Deborah Winkler () ‘Making Global Value Chains Work for Development’. Washington, DC: World Bank Group. Traub-Merz, Rudolf () The Automotive Sector in Emerging Economies: Industrial Policies, Market Dynamics and Trade Unions: Trends and & Perspectives in Brazil, China, India, Mexico, and Russia. Berlin: Friedrich-Ebert-Stiftung, Global Policy Development. UNIDO () INDSTAT  Industrial Statistics Database at - and -digit level of ISIC Revision  and . Vienna: UNIDO.

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 .    

Wade, Robert H. () The Asian Debt-and-development Crisis of –? Causes and Consequences’, World Development (): –. Yamaguchi, A. () ‘Global Value Chains in ASEAN’. Institute for International Monetary Affairs, Newsletter . Yoshimatsu, Hidetaka () ‘Preferences, Interests, and Regional Integration: The Development of the ASEAN Industrial Cooperation Arrangement’, Review of International Political Economy (): –.

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  ......................................................................................................................

                   Industrial Policy in an Interdependent World .............................................................................................................

 -   

. I

.................................................................................................................................. T links between trade and development have been a perennial feature of clashes over economic policy since the Industrial Revolution, if not before. A strict interpretation of the comparative advantage story tends to contrast a desirable policy of ‘free trade’ and unbridled competition with distortionary interventions in support of favoured industrial sectors (Becker, ), prone to ‘government failures’ (Krueger, ); looser interpretations of that story open up possibilities for a more engaged discussion (Krugman, ; Lin, ), albeit with much hand-wringing over ‘picking winners’ (Harrison and Rodriguez-Clare, ). However, there is more to trade and development dynamics than can be extracted from comparing factor endowments. Taking a macroeconomic focus changes the terms of the debate; exports can provide a ‘vent’ for domestic production surpluses and a source of external demand while imports can help correct supply-side shortfalls even as they leak domestic demand; the resulting examination of economic imbalances necessarily links trade to the balanceof-payments constraint and related financing issues, as well as focusing attention on the structure of global markets—through both the negotiation of trade rules and the power of large firms that dominate international trade—and raising the possibility of ‘unequal’ or at least ‘unequalizing’ exchange (Singer, ; Emmanuel, ). Moreover, the dependence on key imports at different stages of the development process— particularly technology, capital, and intermediate goods—highlights possible structural

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

 -   

obstacles to integrating successfully into the global economy, and in the process linking the discussion of trade to industrial policy. Introducing an historical and comparative dimension to the debates on trade and industry adds institutional and behavioural details missing from much of the conventional trade discussion. Exporting, for example, is seen by some as facilitating entrepreneurial and other firm-level capabilities through buyer–seller links and competitive pressures while at the same time giving rise to ‘first-mover advantages’ that can stymie competitive pressures (Gomory and Baumol, ). More generally, international trade can heighten distributional conflicts, both within and across countries (Harrison et al., ), and introduce geo political pressures into the workings of the global economy (Findlay and O’Rourke, ). These matters necessarily shift the attention on the critical role of the state in managing trade relations (Caporaso, ; Storm, ) and that role has received particularly close attention in the success stories of East Asia, reinforcing, according to some, the advantages of export-oriented industrialization over import-substitution industrialization in devising a national development strategy but, on other counts, broadening the policy challenges arising from efforts to create ‘dynamic advantage’, including through the rapid mobilization of resources for accelerated capital formation and the establishment of a strong nexus between profits, investment, and exports (UNCTAD, ; Krugman, ). Comparative studies have also revealed how differences at the firm level and in the organization of production can influence trade relations. With international trade traditionally dominated by large firms (Bernard et al., ), how these emerge, their links with smaller enterprises, and the wider impact of their economic power and influence provide a critical part of the trade and industrialization narrative. Conventional trade models, constructed around a bias for perfect competition, have been amended by introducing economies of scale and scope. However, other features of a trading system dominated by large firms, including, for example, the role of financial markets (themselves prone to scale effects) and the presence of rent-seeking behaviour, have been less adequately researched (Buckley, ). A more descriptive literature has examined some of these issues through the lens of global value chains (GVCs) which have become a more prominent feature of international trade over recent decades. Establishing links in these chains has, on some accounts, made it easier to begin an industrialization drive in poorer countries (Baldwin, ). However, on other accounts, stronger intellectual property rights and weakened labour laws have further shifted the balance of power towards the multinational firms leading these chains, not only further strengthening their dominant market positions and ability to generate high profits but also stalling the industrialization process in developing countries (Gereffi et al., ; Phillips and Henderson, ; Kozul-Wright and Fortunato, ). The chapter is organized as follows. Section . critically discusses the role played by trade integration in the process of economic development, insisting that trade is a means not an end and that the potential gains from the effective management of trade involves more than specialization. Section . focuses on productive integration,

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    



analysing the channels through which the slicing of the value chains across different economies affects the structure and composition of exports. In this context, the section discusses the emergence of global value chains (GVCs) and presents a simple mapping exercise designed to locate different developing economies in the ‘GVCs space’ along two critical dimensions, the extent and the typology of participation in production networks. Section . analyses some factors which are of critical importance when it comes to policy design in an interdependent world economy: the difference between active and passive policy stance, the challenges of product upgrading along GVCs, and the relevance of regional value chains (RVCs). Section . offers some concluding remarks.

. T M C B T I  D

..................................................................................................................................

.. Gains from Trade? Most successful economies, starting from a relatively specialized primary structure, have moved resources into higher productivity manufacturing activities which, along with access to low-cost inputs, has facilitated access to foreign markets; subsequently more sectors are added, along with more economic linkages within and across sectors, including with more sophisticated service activities which are initially located inside manufacturing firms but subsequently become the basis for more independent sectors. In the process, successful economies come to rely increasingly on intangible assets, scale economies, and learning to generate further increases in productivity and further gains from international trade. At higher levels of income, these economies begin to specialize once again, but now in service activities. Strong empirical support associates this pattern with technological progress, the rise of a large middle class, and the progressive development of financial markets. These components of successful development have persisted over the last fifty years even as the world economic landscape has changed considerably. During this period, growth in world trade has consistently exceeded growth in global output and today’s global economy is a much more open and interconnected space than it used to be (UNCTAD, ). Furthermore, the relative importance of developing countries in world trade has been rising—steadily from the early s, more sharply after the early s—reaching between  and  per cent of the total. The composition of world trade has also changed significantly, shifting away from primary products (particularly metals, minerals, and fuel) with a corresponding rise in the share of manufacturing and services, a shift that has also been pronounced in developing countries.

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

 -   

This evolving landscape is on some accounts the inevitable outcome of a rules-based liberal world economy in which countries have adhered to their comparative advantage and where economic gaps are destined to become smaller and smaller (Baldwin, ). For standard economic theory, specializing according to comparative advantage allows countries to reap efficiency gains from moving to a production and exporting profile that concentrates on exploiting their relatively abundant resources and importing goods that embody relatively scarce resources. Even countries lagging behind in all sectors would benefit by following this path (Clarida and Findlay, ) and, assuming markets remain competitive, more mobile capital, particularly in the form of direct investment, should ensure strong gains for developing countries. On this basis, the policy conclusion is, invariably, rapid trade liberalization along with complementary measures to deregulate domestic markets (particularly the labour market) and remove other government measures that ‘distort’ prices and stymie international competition. A vast academic industry has sprung up employing sophisticated models and statistical techniques which purport to prove a direct link from trade liberalization through increased trade flows to rapid economic growth, poverty reduction, and improved societal welfare. Trade simulation exercises, which seem to multiply whenever multilateral or regional trade negotiations are getting underway (or getting stuck), offer headline-grabbing multi-billion dollar gains from trade liberalization, often accompanied by finger wagging at those who are reportedly stalling or opposing the process. While the argument is much admired for its mathematical elegance, it rests on a set of severely restrictive assumptions whose distance from reality has troubled generations of economists beginning with Adam Smith, no less, who insisted that a universal system of free international trade was more a utopian ideal than a coherent blueprint for policy, and that the costs of adjusting to it required that it be done ‘only by slow gradations, and with a good deal of reserve and circumspection’ (cited in Panic, : ). Smith’s conclusion followed from his observation of a world of underutilized and misused resources in which lagging regions faced a set of unfavourable circumstances.¹ Smith also recognized, that in this world, and whatever the causes of the initial gaps among countries, the free movement of goods, technical know-how, and factors of production could give an advantage to those who opened up an early lead, allowing them to maintain or extend that lead at the expense of later developers.²

¹ Smith offered a number of reasons why some countries lagged behind, including unfavourable cost conditions (which led some countries to forsake manufacturing); a hostile policy environment (which included insecure property rights and misguided trade policy); weak infrastructure (which augmented geographical obstacles to market expansion); and small or scattered populations (which limited the division of labour). ² In his Lectures on Jurisprudence published before The Wealth of Nations, Smith noted that ‘it is easier for a nation, in the same manner as for an individual, to raise itself from a moderate degree of wealth to the highest opulence, than to acquire this moderate degree of wealth’ (cited in Vaggi and Groenewegen, : ).

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    



While Smith’s observations have been obscured by conventional trade models, development economists and economic historians have long recognized that policymakers do not operate in a world populated by small firms, with perfect information about consumer tastes and available production technologies, where learning or scale economies are absent, and immobile factors of production fully employed (Toner, ). This has cautioned against rapid trade liberalization, with economic divergence just as plausible an outcome from such moves as narrowing income and technology gaps, with even more conventional economists acknowledging that, under some circumstances, ‘the roulette wheel of evolving comparative advantage’ can lead to ‘genuine harm’ (Samuelson, : ). In reality, trade takes place among countries at very different levels of development and is shaped by a variety of forces other than factor endowments, including economic structure, firm size, technological learning, and power imbalances. This makes for a much more uncertain trading environment than allowed for in standard trade models and implies that trade policy will be poorly designed if it is focused on achieving some single best outcome rather than on making tangible gains from an evolving set of trading relations among partners of varying degrees of economic power and sophistication. In this world, trading possibilities are created rather than given and the adjustments to opening up can take time and have significant distributional effects, historical accidents have long-run economic consequences, and ‘market forces do not select a single, predetermined outcome, instead they tend to preserve the established pattern, whatever that pattern may be’ (Gomory and Baumol, ). Indeed, as Gomory and Baumol insist, given that the modern trading system is so different from the implicit eighteenth-century historical setting of the free-trade model, the analysis of how trade works needs to start from a very different set of stylized facts. Consequently, a ‘win– win’ outcome is just one among a range of possibilities in a more open trading system and highlight that international market forces, in conjunction with varying national capabilities, can produce results that are beneficial for some but detrimental to others. Not surprisingly, the idea of a simple positive association between trade and economic growth is still contested (Kim, ; Rodrik, ). The vague definition of openness, and the failure to separate episodes of export promotion from those of import liberalization, can easily lead to the misrepresentation of trade regimes, making it difficult to draw meaningful cross-country comparisons and correctly interpret the findings. Cross-sectional averages hide country-specific differences and breaks in the series. Furthermore, several studies have found that results reporting a strong link between openness and growth may be sensitive to the specific trade measures employed (Pritchett, ), the introduction of additional control variables (Levine and Renelt, ), cyclical factors, and periodization (Wacziarg and Welch, ). It also needs to be stressed that even when a close statistical association between trade and growth is found, this still leaves open the question of the direction of causation, with plenty of reasons to suppose that it runs from domestic success in raising productivity to increased trade, and not the reverse (Clerides et al., ).

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

 -   

From a policy perspective, rather than assuming a positive association between trade and growth, what is needed is a closer examination of the channels through which the two variables might be related. From an industrial policy perspective, it is of particular interest to explore how trade (both exporting and importing) can affect productivity growth via its impact on aggregate patterns of structural change and diversification.

.. Trade Composition, Structural Transformation, and Diversification While there is considerable disagreement over how to weigh up the potential losses from trade and even more on what to do about it, there is general agreement that what a country produces and exports matters, that is, whether it exports apples or iPhones is important for its development process and prospects. This was the lesson drawn by the first catch-up economy, the United States, under the guidance of Alexander Hamilton who, as its First Secretary of the Treasury, ruptured its agrarian destiny and actively pursued a pro-industrialization agenda through high tariff barriers, big infrastructure projects and support for technological learning (Cohen and de Long, )—a strategy reproduced, with local variation, in the European late industrializers of the late nineteenth and early twentieth centuries. As a new post-war international division of labour took shape, reinforcing the advantage of industrial as opposed to primary producers, development economists embraced the idea that trade could generate polarized outcomes between ‘centre and periphery’ (Prebisch, ) but also, by privileging certain activities, locations, and firms, could further fracture the international division of labour as large international firms with tight control over finance and knowledge were able to reinforce their dominant market positions at the expense of weaker players (Hymer, ; UNCTAD, ). Whether through polarization or fragmentation pressures, the resulting room for slippages between trade and development implied that even if countries were able to increase exports, and even achieve higher shares in global trade, they might still fail to diversify their economies and achieve broader development goals like poverty reduction, increased employment, improved welfare, etc. As a result, policymakers in many developing countries looked for new ways to reconnect trade to diversification and wider development challenges through more active measures to transform the underlying structure of their economies. Structural transformation refers to the movement of labour, capital, and other productive resources from low-productivity to higher-productivity economic activities within and across sectors. By expanding destination markets and realizing scale economies, international trade can favour the development of higher productivity sectors and the shift of labour and other resources in their direction. While the opportunities are not exclusive to manufacturing, the presence in that sector of various productivity-enhancing forces has given it a privileged place in the discussion on trade

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    



and development (Prebisch, ; Toner, ; Cherif and Hasanov, ). Moreover, exporting manufactures can not only foster a productivity spurt within that sector, it can also raise an economy’s aggregate productivity by redistributing existing resources across a broad range of economic sectors, bringing dynamic gains as the access to better technologies fosters skills-upgrading and other positive externalities. However, positive outcomes are not predetermined; when there is surplus labour, strong import competition, or the exit of less productive firms, trade liberalization can result in declines in aggregate (economy-wide) productivity even as it raises productivity in the industrial sector or among trading firms (McMillan and Rodrik, ). The net impact ultimately depends on wider employment dynamics and on whether the productivity growth in industry is outweighed by a larger shift of labour and resources into low productivity work outside the sector. Evidence of such shifts underlies concerns about weak industrialization (including premature de-industrialization) in the developing world in recent decades (UNCTAD, , ; Felipe et al., ; Rodrik, ; Tregenna, ). From this perspective, structural transformation is less a one-off adjustment and more a continuous process and the attendant policy challenges vary, inter alia, with a country’s level of income, the structure and sophistication of its productive base, the size of its firms and their technological capacities, and the fiscal space to manage the employment challenge (UNCTAD, , , , ). Each level of economic development is a point along the continuum from a low-income agrarian economy, where most of the output and labour are concentrated in agriculture, to a high-income economy, where the lion’s share of production and labour accrues to manufacturing and services. The structure of the economy continuously changes as technological change leads it to upgrade to more and more sophisticated goods and production methods. This involves both a progressive diversification of the production base and an upgrade of the goods produced within each industry. Diversification is therefore the key economic development challenge to which industrial and trade policy must adapt accordingly. The critical importance of diversification, or horizontal evolution of production, has been underscored by the findings of Imbs and Wacziarg (). Examining sectoral concentration in a large cross-section of countries, they document an important empirical regularity: as poor countries get richer, sectoral production and employment become less concentrated, that is, more diversified. Such a diversification process goes on until relatively late in the process of development. This highlights another potential channel of connection between trade liberalization and development; by favouring the access to international markets, openness can help to overcome domestic demand constraints and may therefore facilitate the horizontal evolution of production. On the other hand, an excessive or premature liberalization, taking place when the economy still lags very far behind the frontier in terms of productive capacities, might instead foster an overspecialization on natural resources or low-skilled intense manufacturing products according to the logic of the comparative advantage.

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

 -   

Structural transformation can also proceed through the gradual process of moving towards higher value-added and more productive activities and the increasing sophistication of the goods produced. Empirical evidence has demonstrated that countries that have managed to upgrade their productive structures and export more sophisticated goods have grown faster. Hausmann et al. () develop a quantitative index of countries’ export sophistication generally denoted as EXPY. Unsurprisingly, the authors show that this measure of export sophistication is highly correlated with per capita income. But what is important from our perspective is that they also show the existence of a positive correlation between the initial level of EXPY and the subsequent rate of economic growth. That is to say, if a country has a sophisticated export basket relative to its level of income, subsequent growth is much higher (see also Fortunato and Razo, ). It is telling that China and India, among the most successful economies in the recent past, had in  more sophisticated export profiles than their income levels might have suggested. Along with diversification and upgrading, the third component in the transformation narrative is linkages. The immense appeal of manufacturing lies in its potential to generate productivity and income growth (Kaldor, ), and because such gains can spread across the economy through production, investment, knowledge, and income linkages. Several linkages deserve mention here. To begin with, expanding production can help build ‘backward’ linkages (to source inputs for production), and ‘forward’ linkages in so far as the produced goods are used in other economic activities (Hirschman, ). Intersectoral linkages emerge as knowledge and efficiency gains spread beyond manufacturing to other sectors of the economy, including primary and service activities (Cornwall, ; Tregenna, ). Investment linkages are created when investments in productive capacity, new entrepreneurial ventures, and the related extensions of manufacturing activities in one enterprise or subsector trigger additional investments in other firms or sectors, which otherwise would not occur because the profitability of a specific investment project in a certain area of manufacturing activity often depends on prior or simultaneous investments in a related activity (Rodrik, ). Income linkages emerge from rising wage incomes generated from industrial expansion; these add to the virtuous cycle through ‘consumption linkages’. Income linkages also operate through supplementary government revenues (i.e. ‘fiscal linkages’), which may therefore expand public expenditure. The creation of such income linkages can strengthen the self-reinforcing aspect of industrialization through increasing domestic demand and therefore GDP growth. While diversification, upgrading, and linkages frame the structural transformation in general, what determines whether and in which direction a country transforms its production structure is country specific and often difficult to identify even ex post. But among the many variables that influence the outcome of this process, industrial and trade policy have received particular attention in academic and policy debates. Since countries cannot produce a good for which they have no knowledge or expertise, deploying policies to foster learning, accumulation of productive capabilities, and technological change becomes of crucial importance. Trade policy also matters in

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    



this context, not only because access to markets abroad can provide new growth opportunities but also because the commercial partners and the type of integration strategy pursued may significantly affect the characteristics of the exported products and the opportunities to further diversify the economy.

. P I: T E  G V C

.................................................................................................................................. For a good deal of the post-war period, policy debates on how best to establish a robust connection between trade and industry was pursued through the largely misleading dichotomy between import-substitution industrialization and export-oriented industrialization and a false comparison between free and managed trade. This, by draining the discussion of a specific structural, institutional, and historical context was an unfortunate turn, because the case for international trade and its implications for growth, employment, and distribution is a subtle one that has always depended heavily on context (Rodrik, ). Those debates have become, if anything, even less nuanced with the rise of hyperglobalization marked by large flows of footloose capital and the reorganization of production around global value chains (GVCs). Advances in information and communication technologies (ICTs) along with extensive market liberalization have made it easier and cheaper for large international firms to move capital around, including by illicit means, as well as to manage far-flung production networks, which nowadays account for a rising share of international trade, global output, and employment (UNCTAD,  and ). Participation in these chains by developing countries is expected to attract more foreign direct investment (FDI), provide easier access to export markets, advanced technology and know-how, and generate rapid efficiency gains from specializing in specific tasks, appropriately guided by the ‘lead firm’ in the chain. Such participation is seen as particularly important for developing countries with small domestic markets whose firms confront a range of technological and organizational constraints stemming from the fact that the minimum effective scale of production often far exceeds that required to meet their prevailing level of domestic demand. This has encouraged policymakers to focus on providing an attractive business climate (including adequate infrastructure and a sufficiently trained labour force) for the lead firms that manage these chains, avoiding any restrictions on the free flow of goods and finance that connect suppliers along the chain. With the spread of these chains, the foreign content of exports, or backward participation, which measures the value added generated outside the country that completes and exports a product, has increased significantly in a number of developing economies but also in Europe and North America. According to Timmer et al. (), foreign content shares increased

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

 -   

for  per cent of the product chains between  and . As a counterpart, forward participation of many economies, that is, how much domestic value added is embodied as intermediate inputs in third countries’ gross exports, has also been on the rise; in  it accounted for over  per cent in the United States, China, and the European Union. Such data indicate the pervasiveness of international fragmentation. No longer are products simply made in one country and shipped to another for sale. Indeed, products often go through many stages, traversing several geographic and organizational borders and adding components and value before they reach their final markets. This is also reflected in the significant increase in trade in intermediates, whose share of global trade increased from  per cent in  to a peak of over  per cent in  (explaining two-thirds of the total growth in trade over the period), and in the continuous rise of the global FDI stock, from just over  per cent of global GDP in  to over one-third in .³ In recent years, outsourcing and producer-driven value chains have tended to concentrate especially in capital- and technology-intensive industries such as automobiles, electronics, and machinery. The underlying rationale for this reorientation from the firms’ perspective is straightforward; first, their control of intangible assets (derived from investments in R&D, design, marketing, and branding) are less prone to competition, as they are based on unique resources and capabilities that other firms find difficult to acquire, and are therefore sources of superior returns or rents (Kaplinsky, ) and second, their dominant position as lead firm also gives them a monopsonistic position with respect to suppliers, squeezing their margins and adding to their own super profits. On the other hand, fragmentation has made integration into these chains attractive for many developing countries, who, by becoming niche suppliers of parts of the chain, present an attainable first step towards building industrial capacity, creating employment, and integrating into global trade. Accordingly, policymakers are increasingly turning to integration and upgrading in GVCs as a means of driving economic development but, more often than not, without the policy tools required to make this happen.

.. Mapping GVCs Production is nowadays fragmented across national boundaries much more than it used to be in the past, and it entails the sourcing of inputs and components from multiple suppliers based in several countries. Understanding how this is affecting trade patterns and wider development prospects relies on an accurate measurement of the intensity of participation in the GVCs of each individual economy but also on the identification of the extent to which countries are specializing in different stages of the global production processes. Since many developing countries have faced difficulties in achieving their development policy objectives, their place in GVCs has tended to be located on the lower ³ Of course, a significant proportion of the increased stock of FDI is linked to non-tradable tertiary sectors of the economy.

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    



Digital manufacturing value chain with corrective policies

Traditional manufacturing value chain

R&D

Digital manufacturing value chain without corrective policies Design Production Marketing Services

 . Stylized manufacturing value chain smile curve Source: Authors.

portions of what is sometimes referred to as the ‘smile curve’ (Figure .). The smile curve conceptualizes international production as a series of linked tasks and sees international trade organized within GVCs as involving trade in those tasks rather than trade in goods. The resulting fragmentation of production carries significant consequences for the spatial division of labour and the distribution of economic power and privilege. Most of the preproduction and post-production segments of the manufacturing process, with their higher return activities, are usually located in advanced economies, with developing countries often left with the lower value added activities of the production segment of the manufacturing process. To get a more granular measure of the nature of integration of any given country in international production networks, we employ a participation index calculated as the sum of forward linkages, that is, domestic value added embodied in foreign exports (as a share of total exports), and backward linkages that is, foreign value added (as a share of total exports). Our measure of upstreaming is taken from Fally () and Antràs et al. () and is meant to gauge the distance of each specific production sector in a country i from final demand. The index collects information on the extent to which the industry produces goods that are sold directly to final consumers or to sectors that themselves sell to final consumers. A country is specializing in upstream activities if it imports a low share of intermediates and exports a big share of intermediates to third countries. Upstream activities are, for instance, the production of raw materials, but also intangibles such as research and development or the design of industrial products. Formally, we calculate the total share of products sold for final use over the gross output of each sector and then aggregate across sectors to evaluate the upstreamness of country i. We take from Fally () also our index of downstreaming. The index is meant to capture the distance of a given sector in country i from the economy’s

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 -    GDP

2005 Distance from Final Demand

3.0

7500

2.5

Country

3.0

Bulgaria Brazil China Indonesia India Mexico Romania Russia Turkey

2.0

1.5

1.0 30

40

3000 6000 9000

2.5

Bulgaria Brazil China Indonesia India Mexico Romania Russia Turkey

2.0

1.5

1.0

50

30

Participation

40

50

Participation 2005–2011

Country

3.0

Distance from Final Demand

GDP

2011

2500 5000 Distance from Final Demand



Bulgaria Brazil China Indonesia India Mexico Romania Russia Turkey

2.5

2.0

1.5

Year 1.0 30

40

50

2005 2011

Participation

 . Evolution of GVC positioning in selected developing economies (participation and upstreamness), – Source: WIOD () and OECD TiVA.

primary factors of production. According to this measure an industry in country i is more downstream when its production process uses intensively intermediate inputs (rather than primary production factors) and thus when the value added associated with its production is relatively low. Typical downstream activities include the assembly of processed products and post-sales customer services. Formally, the measure is calculated as the complement to unity of the ratio between the value added generated by each sector and its gross output. Following Marel (), the data are subsequently aggregated across sectors to obtain the value of the index for a country i. We focus specifically on low- and middle-income countries within the set of forty countries covered by the World Input Output dataset (Timmer et al., )⁴ and look at the years  and , and to the changes that occurred during the period. We study first how changes in participation rates are associated to specialization in upstreaming activities (Figure .). On the horizontal axis we measure the intensity of participating in GVCs (participation index) while the vertical axis measures distance from final demand (upstreamness). ⁴ Bulgaria, Brazil, China, India, Indonesia, Mexico, Romania, Russia, and Turkey.

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     GDP

2005

Country

1.5

1.0 1.0

1.5

2.0

2.5

9000

2.5

Bulgaria Brazil China Indonesia India Mexico Romania Russia Turkey

2.0

6000

Distance from Final Demand

Distance from Final Demand

2.5

3000

3.0

5000 7500

GDP

2011

2500

3.0

Country

2.0

1.5

1.0 1.0

3.0

Distance from primary factors of production

1.5

2.0

2.5

3.0

Bulgaria Brazil China Indonesia India Mexico Romania Russia Turkey

Distance from primary factors of production

2005-2011

Country

3.0

Distance from Final Demand



Bulgaria Brazil China Indonesia India Mexico Romania Russia Turkey

2.5

2.0

1.5

Year 1.0 1.0

1.5

2.0

2.5

3.0

2005 2011

Distance from primary factors of production

 . Evolution of GVC positioning in selected developing economies (downstreamness and upstreamness), – Source: WIOD ().

All the economies under scrutiny, with the notable exception of China, experienced an increasing participation rate coupled with a shift of the production away from the final demand, that is, upstreaming in  is higher than in . This reflects both increased outsourcing in advanced economies and the relative distance from the market of those productive activities sourced by developing economies. China, on the contrary, increased its upstreaming but reduced its overall participation in GVCs. This reflects its increased specialization in intermediate inputs trade, which in turn increases the distance from final demand, and the reduction of foreign value addition in domestic production. Figure . introduces the distance from an economy’s primary factors of production (downstreamness). We measure downstreamness on the horizontal axis while, once again, the vertical axis measures distance from final demand (upstreamness). Figure . shows the existence of a strong and positive correlation between the two indicators. Countries characterized by more upstream production according to the production-staging distance from final demand are at the same time closer to primary factors of production. In other words, economies that sell higher shares of their output directly to final consumers tend also to display relatively high value added over gross output ratios, reflecting a limited amount of intermediate inputs embodied

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

 -   

Brazil—Sectoral Positioning (2005–2011) 4.0

Russia—Sectoral Positioning (2005–2011) 4.0

Year

Year

2007 2008

3.0

2009 2010 2011

2.5

Industry

2.0

Manufacturing Primary

1.5 2.0

2.5

3.0

2006

3.5

2007 2008

3.0

2009 2010 2011

2.5

Industry

2.0

Manufacturing Primary

1.5

Services 1.5

3.5

Services 1.5

2.0

2.5

3.0

3.5

Downstreamness

Downstreamness

India—Sectoral Positioning (2005–2011)

China—Sectoral Positioning (2005–2011)

4.0

Distance from Final Demand

2005

Distance from Final Demand

2006

3.5

4.0

Year

Year

2005 2006

3.5

2007 2008

3.0

2009 2010 2011

2.5

Industry

2.0

Manufacturing

2005

Distance from Final Demand

Distance from Final Demand

2005

2006

3.5

2007 2008

3.0

2009 2010 2011

2.5

Industry

2.0

Manufacturing

Primary

1.5

Services 1.5

2.0

2.5

3.0

Downstreamness

3.5

Primary

1.5

Services 1.5

2.0

2.5

3.0

3.5

Downstreamness

 . Sectoral positioning of BRIC economies, – Source: WIOD () and OECD TiVA.

in their production.⁵ This is the case since modern economies tend to specialize alternatively in ‘short’ or ‘long’ value chains. Services are provided through ‘short’ chains with both a high ratio of sales to final consumers and little use of intermediate inputs in production. Indeed, payments to labour comprise a larger share of the production costs in services industries. Conversely, manufacturing processing can be more easily fragmented into stages involving separate parts and components. Consequently, manufacturing is characterized by relatively ‘longer’ chains with a lower share of output going directly to final use and a more intense use of intermediate inputs compared to services. Figure . highlights the significance of these sectoral differences displaying the relative position of manufacturing, services, and the primary sector in the BRIC’S economies between  and . In all cases, the services sector falls in the lower left ⁵ Among the BRIC economies, Brazil and India have experienced a marginal decline in both measures while Russia and China experienced a rise, albeit for different reasons.

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    



quadrant, indicating both proximity to the final demand and to the production factors. The manufacturing sector displays higher variation across the four countries. In line with the idea of ‘long’ production chains, China’s manufacturing industries are more distant from the final demand, reflecting their increasing specialization in intermediate inputs. Manufacturing in India and Brazil, on the other hand, appears closer to final demand, thanks to their greater dependence on service activities and primary products respectively.

.. Assessing the Impact of GVCs The connection between participation in GVCs and development is not a straightforward one. When the low unit cost that attracts TNCs is largely dependent on low wages rather than rising productivity, the danger of a race to the bottom is ever present. Moreover, while the evidence presented in UNCTAD (), for example, shows that when increases in the foreign value added of exports occurs in a larger context of greater production and exports of manufactures (as in much of the Asian region, for instance), GVC participation can complement industrialization and structural when increasing participation in GVCs reflects a reduction of domestic sourcing in a context of weak export performance of manufactures, GVC participation may actually delay structural transformation, as in the case of many developing economies in Africa and Latin America. Kowalski et al. () analyse the impact of GVC participation on economic upgrading as measured by sophistication of the export structure. They find that while growing backward participation to GVCs, measured using the share of foreign value added in exports, is associated with product upgrading in high- and middleincome countries, wider fragmentation does not have the same effects in low-income economies. This heterogeneity across income groups suggests that the level of economic development must be taken seriously into consideration when evaluating integration strategies based on GVC participation. Kowalski et al. () also study the determinants of functional upgrading, defined as the capacity of acquiring new functions within a given value chain. Key determinants of functional upgrading turn out to be the import of sophisticated non-primary intermediates and the distance from economic poles of activity. Claims for how GVCs can strengthen productivity (and contribute to economic growth) are largely based on conventional trade models (OECD, ; WTO, ). But from a development perspective, the structure of most GVCs and the distribution of power along them require a more nuanced analysis. In particular, the conditions that ease access to GVCs can also act as barriers to upgrading since more accessible parts of the chain are associated with few forward and backward linkages, limited institutional development, and little possibility for knowledge externalities in the wider economy. A broad body of evidence indicates that only a small number of developing countries—

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

 -   

mostly in East Asia—have been able to build the needed linkages between domestic and foreign firms and achieve upgrading within GVCs (UNCTAD , ) and even with respect to job creation the impact, in most cases, has been limited (Ingram and Oosterkamp, ). Divergence between expectations and outcomes from participation in GVCs is, in part, a reflection of the fact that the private interests of international firms do not necessarily coincide with the developmental interests of the host countries. This disconnect is, of course, familiar to many developing countries from their participation in commoditybased value chains, reflecting, in part, the asymmetric structure of markets and the pricing power of firms from the North and South. It also highlights the importance of strategic policies, as countries look to shift towards a greater reliance on manufacturing (and service) activities and exports and is an important reminder that reductions in policy space can hamper industrialization and catching up in late developers (UNCTAD, ). As Stephen Hymer (: ) recognized over forty years ago, as international production fragments along task lines, ‘output is produced cooperatively to a greater degree than ever before, but control remains uneven’; in particular, the lead firm tends to concentrate its own tasks at the two ends of the smile curve where ‘information and money’ provide the main sources of control and where profit margins tend to be higher. These ‘headquarter’ economies are still located predominantly in the North (now including parts of East Asia) while ‘factory’ economies are, largely, in parts of the South. Indeed, as these chains have spread across more countries and sectors over the past three decades they have been accompanied by a more and more uneven distribution of those benefits. In developed countries, the concern is that low and mediumskilled production jobs in traditional manufacturing communities have been ‘outsourced’, first to lower-wage regions of the developed world and then ‘offshored’ to developing countries, and wages have stagnated while new jobs created at the ends of the chain have not only been insufficient in number to replace those being lost, but are often out of reach to those ‘left behind’, both geographically and in terms of the skills required. The result is socio-economic polarization and a vanishing middle class in advanced economies as well as some emerging economies. Developing economies with limited productive capacities can therefore remain trapped in, and competing for, the lowest value-adding activities at the bottom of value chains, which can ultimately result in ‘thin industrialization’, weak linkages and slow economic growth (Gereffi, ; UNCTAD, , ). Participation in GVCs also carries the additional risk of leading to specialization in only a very narrow strand of production with a concomitantly narrow technological base and overdependence on multinational enterprises (MNEs) for GVC access. Such shallow integration manifests itself in asymmetric power relations between lead firms and suppliers and in weak bargaining positions for developing countries. For example, the experiences of Mexico and Central American countries as assembly manufacturers have been likened to the creation of an enclave economy, with few domestic linkages (Gallagher and Zarsky, ). The same can be said about the electronics and automotive industries in Eastern and Central Europe (Plank and Staritz, ; Pavlínek, ; Pavlínek and Zenka,

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    



). In all these cases, there has been significant ‘internal upgrading’ within MNE affiliates, but this has involved very few spillovers to the local economies in the form of productivity improvements and imitation by domestic firms, partly due to limited linkages of MNEs with local firms and labour markets (Fons-Rosen et al., ; Paus, ). Moving up the chain into more capital-intensive or higher value-added production is particularly challenging in such an environment, because it necessitates relationships with lead firms at the top that are ultimately focused on maintaining their profitability and flexibility. Indeed, these firms sometimes intentionally use GVCs to induce and intensify competition among suppliers and countries for their own benefit (Levy, ; Phillips and Henderson, ). In a recent paper, Rigo () presents some interesting stylized facts on the extent to which firms operating in developing countries benefit from GVCs. The author compares groups of firms along several measures of technology adoption and knowledge creation (running training programmes, using foreign-licensed technology, possessing quality certifications, and communicating with customers and suppliers via the Internet). He finds that two-way traders, which are firms typically involved in GVCs, display on average a higher propensity to adopt new technologies than other groups of firms and that local suppliers to these firms, that is, non-trading domestic firms involved in upstream operations with them, strongly benefit from technological spillovers. However, he also shows that foreign-owned firms involved in GVCs are more likely to be dependent on the global sourcing policies of their parent companies and have generally a low propensity to engage in local sourcing. The opportunities for generating local spillovers in developing countries are therefore to a large extent still unexploited. South East Asia represents an interesting exception to this trend. Local enterprises in fact seem to be much more integrated with the MNEs operating in the region. A recent OECD-UNIDO () report shows that foreign manufacturers in ASEAN source considerably from local producers. In Thailand, Lao PDR, Indonesia, Malaysia, and the Philippines, foreign MNEs source over  per cent of intermediate inputs from firms that produce locally. The average share of local sourcing by foreign MNEs in Vietnam, though somewhat lower, is still significant. An emerging literature is trying to assess empirically the impact of the rise of GVCs on structural transformation by using input–output matrices recently made available by a number of new databases (e.g. the World Input Output Database and the Trade in Value Added Database). These studies show that despite the global label, production in value chains is concentrated in a small number of industries and countries. Lead firms are generally from advanced economies and production tends to be most fragmented in clothing and textiles, electronics, and automotive industries (De Backer and Miroudot, ; Timmer et al., ; UNCTAD, ). Another common finding in this literature is that while participation of developing countries in GVCs has increased tremendously over recent decades, firms headquartered in developed economies have been the big winners from the spread of GVCs (Milberg et al., ; UNCTAD, , ). Dedrick et al. () use the examples of the Apple iPod and notebook personal computers to illustrate how profits are distributed between the participants of these two

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

 -   

Table 9.1 Uneven returns in the iPod value chain Function

Supplier

Gross margin

Operating margin

Return on assets

Controller chip Les firm Video chip Primary memory Battery Retailer Display Hard drive Assembly Distribution Minor memory Minor memory

Portal Player Apple Broadcom Samsung TDK Best Buy Toshiba-Matsushita Toshiba Inventec Appl. Ingram Micro Elpida Spansion

44.8 29.0 52.5 31.5 26.3 25.0 28.2 26.5 8.5 5.5 17.6 9.6

20.4 11.8 10.9 9.4 7.6 5.3 3.9 3.8 3.1 1.3 0.1 –14.2

19.1 16.6 9.8 10.3 4.8 9.6 1.8 1.7 6.1 3.1 –1.0 –9.2

Note: Grey areas evidence the gaps in profit margins between different participants in the iPod global value chain. Source: Dedrick et al. (2010: 92).

GVCs. The intuition behind this exercise is relatively straightforward: an iPod and a computer are made up of lots of components produced by different firms in different countries. Each of these firms charges a price for its component or activity and in turn pays other firms for the intermediate goods needed to complete its stage of production. Table . presents different indicators of profit margins of the main participants in the iPod global value chain. The table clearly depicts the gap between the profits enjoyed by firms that specialize in product design (or the production of critical components, such as the controller chip or the video chip) and firms that specialize in assembly or production of low-tech standardized components like memory chips. In light of the multifaceted and highly contingent flow from trade to productive integration to economic development, we need to understand under which particular conditions integration can actually deliver development in a given country and what are the critical policy challenges to be faced in this respect. This could serve as a guide to better target industrial and trade policy. This is the objective of section ..

. M I, F  P C A

.................................................................................................................................. This section discusses several issues which are facing policymakers on linking productive development and trade integration: the long-standing debate on targeting, the challenges of product upgrading along the value chains, and the potential of regional value chains (RVCs).

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    



.. Active versus Passive Policies The internationalization of production and accompanying changes in the direction and composition of international trade has not made industrialization easier or lessened the need for public policy to help build a virtuous circle between productivity growth, increased investment, and strategic integration into the global economy. Indeed, in many economies, there is an even greater need for state involvement, precisely because private actors on their own face greater uncertainty and higher uninsurable risks in today’s increasingly interconnected but unstable global economy. For many developing countries these concerns are particularly pronounced because, in addition to having to reverse widening technology and productivity gaps, efforts to catch up also have to deal with issues relating to global production chains that are under the tighter control of large international firms, and as they have been subject to increasing restrictions on national policy autonomy arising from the proliferation of free trade agreements and bilateral investment treaties. In such a context, governments in developing countries must be ambitious without being unrealistic, striving for a high development road by creating new sources of growth and dynamism, rather than simply trying to do the best with what they currently have by relying on existing advantages. Small and incremental steps can be useful (Lin and Treichel, ); but more radical ‘comparative-advantage-defying’ measures will be needed to shift towards higher value-added and employment-generating activities with high-income elasticities and greater scope for boosting productivity through knowledge creation (Wade, ; UNCTAD, ). The flip side of aiming high is that failure must also be accepted, but managed, with mechanisms for monitoring performance and underperformance, leading to a rectification of the latter or to a removal of state assistance. Accordingly, the focus should be not on whether to design and implement industrial policy at all, but on how to do it properly (Naudé, ), or, as Cohen and DeLong (: ) have put it, ‘getting the political economy right’. In the debates around industrial policy, a good deal of attention has been paid to distinguishing between vertical policies targeted at particular firms, sectors, or activities, and horizontal industrial policies aiming at general improvements to the wider economic environment, such as providing transport infrastructure, reliable supplies of energy, and a sufficiently educated workforce. However, this distinction is somewhat artificial, because, in practice, even supposedly neutral horizontal policies may have vertical effects by benefiting some activities or sectors more than others, depending on the particular characteristics of those activities. Exports of cut flowers, for instance, are facilitated more by infrastructure projects related to air travel, whereas trade in cars and commodities benefits from the upgrading of sea ports. A policy decision to ease credit restrictions may have an impact on interest rates in general, but affects particular industries differently, depending on their reliance on such factors as bank credit and degrees of profitability.

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

 -   

No matter how much governments may seek to avoid explicit targeting, even seemingly universal and undifferentiated policies will have varying effects on different activities. Since policymakers are ‘doomed to target’, it is better to accept this fact and try to get the targeting right. In the recent case of China, for example, the state has played a prominent role in establishing a dynamic ‘profit–investment–export’ nexus through a mixture of more general measures, as well as selective and targeted interventions at different levels, with the mixture changing over time (Knight, ). As China shifted towards a more export-oriented growth strategy in the early s, targeting sectors such as automobiles, semiconductors, and high-speed trains, with public finance pouring into massive investments in infrastructure development. Meanwhile, both state-owned enterprises and MNEs (often through joint ventures) were encouraged and cajoled into undertaking industrial upgrading (Lo and Wu, ). While China has its own unique features, this is a familiar policy approach from previous success stories in East Asia (Poon and Kozul-Wright, ). The mixture of more general and selective measures in less developed countries, such as in sub-Saharan Africa, will need to be substantially different from more standard industrial policy packages, since these countries are still predominantly rural, with less developed markets, a smaller industrial base, and weak public institutions. Moreover, the bulk of non-farm employment is generated in small firms or microenterprises, inter-firm specialization and collaboration are often absent, and economic transactions are strongly influenced by informal institutions that are not necessarily well aligned with the prevailing norms of market economies. To overcome these constraints and nurture larger and more competitive enterprises in both industry and agriculture, the state will need to assume a particularly active role. This will involve raising productivity in the rural economy in parallel with developing manufacturing activities in urban agglomerates, strengthening integration, and creating linkages among those activities. The process will likely involve significant investment in boosting the institutional capacities of both the government and the private sector. In this context, it is useful to distinguish between ‘passive’ and ‘active’ industrial policies. A ‘passive’ industrial policy essentially accepts the existing endowments and institutional structures, and aims to reduce the costs of doing business, including coordination and transaction costs. By contrast, an ‘active’ industrial policy targets deeper changes in corporate structure and strategy, such as the links between investment, exporting, and upgrading. The institutional prerequisites for active and passive policies are likely to be different. In particular, effective targeting of active measures requires substantial state capacity and a degree of discipline, which is an area often neglected in discussions of industrial policy. In practice, while an active policy is almost always accompanied by a passive policy, the reverse is not the case. Clearly, it is not enough simply for governments and businesses to develop a vision and design targets together; governments must also have some means of ensuring that businesses make the subsequent investments and changes in performance as agreed. Variously described as ‘reciprocal control’ (Amsden, ) or the ‘support/performance’

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    



bargain (Evans, ), this disciplinary function is essential for industrial policy to succeed, but it has received insufficient attention in much of the renewed discussion on industrial policy (Schneider, ; Peiffer, ; Kozul-Wright and Poon, ). In the East Asian examples, governments were able to link the application of their policy tools (such as the provision of lower-cost capital, dealing with the threat of foreign competition, or privileged access to scarce foreign exchange) to measurable improvements in business performance in terms of production efficiency or exports. All certainly saw one of their principal tasks as that of increasing the supply of investible resources and assuming part of the long-term investments. State-sponsored accumulation involved variously the transfer of land and other assets, efforts to decrease competition in some areas while increasing it in others, strong regulation and control, and in some cases ownership, of the financial system and a pro-investment macroeconomic policy, including direct public investment in some lines of activity. Critically, these developmental states did not simply measure success in terms of increasing investment to fuel economic growth, but also in terms of guiding the investment into activities that could sustain a high-wage future for their citizens. This implied a coordinated effort to shift resources from traditional sectors by raising agricultural productivity and channelling the resulting surplus to emerging industrial activities (Grabowski, ; Studwell, ). It also meant deliberately reducing risks and augmenting profits in industries deemed important for future growth (Wade, ; Amsden, ). Like their late nineteenth- and twentieth-century precursors, this meant making full use of the creative impulses of global markets, even while protecting some domestic producers from excessive competition, through strategically guided integration into the international economy. Building similar relations has proved more difficult in other contexts. In Latin America, a form of ‘hierarchical capitalism’ (Schneider, ) has been associated with undermining government’s abilities to persuade businesses to transform. From the s onwards, the big national firms were encouraged to invest heavily in importsubstituting industries behind protective tariffs and trade restrictions, but policymakers did not impose adequate performance standards in return for the higher profits earned as a result of these measures (Schneider, ; Agosin, ). Similarly, during the market reforms of the s, explicit performance standards were rarely imposed, even where governments structured privatization programmes to favour particular business groups. Utilities were subject to the usual sectoral regulations (i.e. for essential services or monopolies) but, according to Rodrik (), overall policymakers in Latin America used too much carrot and too little stick.

.. Upgrading and Sophistication As discussed in section .., in order to sustain development a country must be able to progressively upgrade its production structure and raise internal value added by exporting

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

 -   

more sophisticated and complex manufactured products. But if ‘what you export matters’ for economic growth, the natural question to address becomes what matters for your exports? What type of integration (and value chains) favour the export of those sophisticated and complex products which foster economic development? Upgrading in GVCs is crucially affected by the governance structure of value chains (Gereffi, ; Gereffi et al., , ). Governance structures depend on firm characteristics such as size, crucial for achieving economies of scale and establishing linkages with global lead firms, and the existing level of capabilities, which determines the potential for productivity growth and upgrading towards higher-value-added activities and more sophisticated products. Governance structures influence the impact that GVCs can have on firms in developing countries by determining the power relations within the chain. When some players gain too much power in the chain, they might adopt strategies to capture higher shares of value added. For example, by creating trade-related constraints in the form of tariffs and other taxes, lead firms in downstream activities can reduce the profit margins of upstream firms. Alternatively, they might hamper technological upgrading and entry into downstream activities, for example by limiting knowledge and technology transfers or by imposing standards through trade and investment agreements (Milberg and Winkler, ; UNCTAD, ). These strategies are likely to cement the asymmetries in power and skills between developed and developing country firms. Governments in developing countries can help local firms negotiate contracts with foreign firms, for example, by encouraging long-term contracts between them, supporting collective bargaining through producer associations, or providing training in bargaining and model contracts (Milberg et al., ; UNCTAD, ). Finally, the potential for upgrading also depends on local suppliers and on their capacity to source intermediate inputs and to acquire, assimilate, and successively exploit the value of information and knowledge coming through the interaction with other firms (absorptive capacity). Participation in GVCs exposes domestic suppliers to multiple interactions with foreign firms, thereby offering them unique opportunities of absorption. However, MNEs do not always activate linkages with local firms by preferring international sourcing strategies. Government efforts to strengthen learning capabilities is likely to help companies, both for start-ups and older firms, better adapt to the challenges arising from participation in GVCs. Recent research shows that technology transfers are more effective when firms possess previously accumulated knowledge and innovative capabilities. OECD and UNIDO () document how the gap between foreign firms and local SMEs remains high in some ASEAN member states and how precisely in these countries the spillovers from local sourcing become less intense. From a policy perspective it is therefore of paramount importance to couple ‘push’ measures which might incentivize local sourcing of parts by MNEs (e.g. local content requirements) with ‘pull’ policies designed to improve productive capacity and the ability of local suppliers to match the quality of imported components and intermediate products (e.g. promotion of entrepreneurship through incubators, training, or support with venture capital and scaling up of domestic capabilities through technical vocational education and training programmes).

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    



.. Regional Value Chains Another pillar for the design of integration strategies able to foster productive capacity building and structural transformation is represented by productive regional integration. As mentioned above, East Asian countries, particularly South Korea, Taiwan, Singapore, but also China, have long recognized the importance of regional production networks with a vast literature spawned around the ‘flying geese’ pattern of development based on the work of Akamatsu (; UNCTAD, ). In response to the collapse in trade after the financial crisis of –, suppliers in other developing regions shifted their end markets from the North to the South in an effort to regionalize their supply chains. South African clothing manufacturers, for example, moved into other countries in sub-Saharan Africa such as Lesotho and Swaziland, leading to an expansion of the regional value chain led by South African retailers (Gereffi, ); and the same path is being followed by Mauritian textile producers who are expanding their operations in Madagascar. Such regional value chains (RVCs) are characterized by the end-product being exported by a country within the region, more often to a regional partner, and with many high value-adding activities also undertaken within the region. They can therefore significantly contribute to the creation of value at the local level and offer more opportunities to participate, gain experience, and build those local capacities needed to compete globally, thus potentially serving as a stepping stone into GVCs (UNCTAD, ). Regional markets might also exhibit better upgrading potentials, particularly in terms of functional upgrading, including design, marketing, branding, and distribution. Furthermore, given the size and the capacity constraints faced by many developing countries, a local industrial strategy might quickly reach its limits. This can be overcome through a regional perspective as different complementary advantages in the region could be leveraged and economies of scale, vertical integration, and horizontal specialization could be promoted. RVCs can be instrumental in increasing value added in the developing regions (Kozul-Wright and Fortunato, ). Recent evidence, however, suggests that despite their advantages they remain far less developed than GVCs (Los et al., ). Indeed, over the last couple of decades, outside of Europe and East Asia, the gap between the two has been widening rather than shrinking and the extra regional component of foreign value addition remains significantly higher than the intra-regional component. Expanding regional productive integration in developing regions beyond the current limits critically relies on the capacity of developing countries to provide an environment conducive to GVC participation and that would make domestic firms competitive along these chains. This, in turn, requires the adoption of a vast set of strategic policy measures such as, for example, enhanced cooperation among governments to identify and prioritize entry points into value chains and exploit regional complementarities, facilitating the connections between firms operating in different countries at different parts of the chain. Setting-up Rapid Development Zones or Free Industrial Areas in those regions where natural resources are concentrated to foster resource

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

 -   

exploitation and upstream participation to value chains could also help, but the record of these mechanisms should warn against treating them as panacea to a complex set of interrelated policy challenges.

. C

.................................................................................................................................. This chapter has reviewed the debates around trade and industrial policy and discussed how the composition of trade and investment flows, as well as the spread and form of participation in GVCs, affect structural transformation. It focused on three characteristics that have been identified in the literature as critical to assessing the export structure of an economy and its potential to accelerate industrialization: the diversification of production, the level of sophistication of the exported products, and upgrading of productive capacities/capabilities required to sustain the production and export of increasingly sophisticated goods and the establishment of linkages within and across sectors. The relative importance of each one of these features changes through time, and with them the structure of trade and the policies needed for linking trade and production in ways that maintain a virtuous economic circle of rising productivity, expanding exports, increased investment, rising wages, and deeper domestic markets, fuelling further productivity rises. The chapter also discussed the critical components of a national export strategy which could support the insertion of national firms in international markets, favour the strategic attraction of FDI, and enable constant upgrading along global (and regional) value chains. What seems to be the case is that to expand production capabilities and foster structural change, a focus on exporting manufactures is not enough. Moreover, success comes not simply from shifting resources from primary activities to labourintensive manufactures but also from anticipating future challenges in these industries (as costs rise and new competitors emerge) and nurturing new linkages and more sophisticated products. Accordingly, an effective national export strategy must still involve active industrial policies, targeted support for upgrading, and regional economic arrangements.

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    

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Studwell, Joe () How Asia Works: Success and Failure in the World’s Most Dynamic Region. London: Profile Books. Timmer, Marcel, Erik Dietzenbacher, Bart Los, Robert Stehrer, and Gaaitzen de Vries () ‘An Illustrated User Guide to the World Input–Output Database: The Case of Global Automotive Production’, Review of International Economics : –. Timmer, Marcel, Bart Los, Stephen Rand, and Gaaitzen de Vries () ‘Fragmentation, Incomes and Jobs: An Analysis of European Competitiveness’, Economic Policy (): –. Toner, Phillip () Main Currents in Cumulative Causation: The Dynamics of Growth and Development. London: Macmillan. Tregenna, Fiona () ‘Characterising Deindustrialisation: An Analysis of Changes in Manufacturing Employment and Output Internationally’, Cambridge Journal of Economics : –. Tregenna, Fiona () ‘How Significant is Intersectoral Outsourcing in South Africa’, Industrial and Corporate Change (): –. UNCTAD () Trade and Development Report . New York: United Nations. UNCTAD () Trade and Development Report . New York: United Nations. UNCTAD () Trade and Development Report . New York: United Nations. UNCTAD () Trade and Development Report . New York: United Nations. UNCTAD () Trade and Development Report . New York: United Nations. UNCTAD () World Investment Report —Global Value Chains: Investment and Trade for Development. New York: United Nations. UNCTAD () Trade and Development Report . New York: United Nations. UNCTAD () Global Value Chains and South-South Trade. New York: United Nations. UNCTAD () Trade and Development Report, : Structural Transformation for Inclusive and Sustained Growth. New York: United Nations. UNCTAD () Structural Transformation and Export Diversification in Southern Africa. New York: United Nations. Vaggi, Gianni and Peter Groenewegen () A Concise History of Economic Thought: From Mercantilism to Monetarism. Basingstoke: Palgrave. Wacziarg, Romain and Karen Welch () ‘Trade Liberalization and Growth: New Evidence’. NBER Working Paper No. . Cambridge, MA: National Bureau of Economic Research. Wade, Robert H. () ‘Resolving the State–Market Dilemma in East Asia’, in Ha-Joon Chang and Robert Rowthorn (eds) The Role of the State in Economic Change. Oxford: Clarendon Press, pp. –. Wade, Robert H. () ‘The Role of Industrial Policy in Developing Countries’, in Rethinking Development Strategies after the Financial Crisis, Vol. I: Making the Case for Policy Space. New York: United Nations, pp. –. World Trade Organization () ‘Measuring and Analyzing the Impact of GVCs on Economic Development: Global Value Chains Development Report ’. Geneva: WTO.

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  ......................................................................................................................

  

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 . 

. W G I P?

.................................................................................................................................. I is widely agreed that the West grew wealthy through its mastery of the novel processes of industrialization, when fossil fuels were harnessed to provide abundant energy in new factory settings that liberated production from age-old constraints. Industrial capitalism underpinned the prosperity of Europe and North America, before diffusing East to Japan in the twentieth century, and then in the second half of that century diffusing to the East Asian Tigers (Korea, Taiwan, Singapore, and Hong Kong), utilizing developmental states as means of catch-up. Now in the twenty-first century the process encompasses China, followed by India and many other industrializing giants looking to enjoy their time in the sun. But no sooner do these emergent industrializing giants begin the same process of burning fossil fuels and wasting resources as practised by their industrialized predecessors than they are confronted with an inconvenient truth: their business model for industrialization will not scale. These industrializing giants have to confront the reality that they cannot rely on the conventional fossil-fuelled pathway, nor on the traditional linear pathway of resource usage (extracting resources from nature, and then dumping the residues in nature at the end of the process), if they wish to see their industrialization through to completion. Consider these traditional or conventional pathways from the perspective of energy and resource security. The burning of fossil fuels (whether coal in power generation and industry or oil in transport) at the scale involved in China or India (with their total current population of . billion) creates so much urban particulate pollution that the air becomes unbreathable. China has already paid a terrible price in terms of this urban pollution, and India will do so as well as the scale of its fossil-fuel burning rises. Similarly, the linear exploitation of resources, extracting them from nature at one end of the industrial process and dumping them back in nature at the

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  



other, creates unmanageable waste issues and shortages of key resources like water. Even more significantly, the huge appetite for fossil fuels and virgin resources brings these industrializing giants up against political and economic limits (and ultimately military limits) of what can be allowed within a densely populated planet. The Western powers evaded these geopolitical limits through colonization and imperialism—but such a strategy is not open to China, India, and other industrializing giants. How then are they to secure the energy and resource inputs needed by their quest for industrialization at a scale never before attempted? What are the industrial policies that would bring them the fruits of modernization? The answer to this conundrum is provided by green growth, or the greening of the industrial growth process—balancing growth against sustainability. China stumbled on this solution in the early years of the twenty-first century, as it was engaging in tearaway growth. While continuing to burn a lot of coal, oil, and gas, it has found that its energy security is enhanced by relying more and more on renewables—to the point that it now has targets for renewables usage that dwarf those of other countries and have already turned China into a renewables superpower (Mathews and Tan, a, b, ; Mathews et al., ). And this for the very good reason that renewables are products of manufacturing, and as such are subject to cost reductions achieved through the learning curve. While fossil-fuel extraction is subject to arbitrary cost increases or decreases, the costs of manufacturing renewables devices (wind turbines, solar PV cells, batteries) are diminishing relentlessly, in accordance with the learning curve. As costs fall, markets expand—and so the process opens up and expands markets for renewables devices, in a process that can be expected to lead to fossil fuels being superseded as energy sources by the middle of the century, if not before. In most parts of the world electric power generated from renewables is already cheaper than thermal power generated from burning fossil fuels—and the costs of renewable power will only continue to fall. Figure . shows that costs of solar PV have been falling by . per cent for every doubling of production, which has occurred every two to three years. The chart takes the story up to  when solar PV power generation will approach  trillion watts, opening up the terawatt era in solar power. Why would any country wish to continue burning fossil fuels, given their rising and fluctuating costs, their heavy burden on the balance of payments, and their geopolitical unreliability? China has discovered a radical solution to the problem of resource security by introducing circular flows of materials in place of the linear flows of conventional industrialization. The recirculation of resources is based on manufacturing (or rather, ‘demanufacturing’ or disassembling) and is subject likewise to diminishing costs, so that the costs of recirculated materials can be expected to continue to fall, eventually falling below the cost of virgin materials (indeed they are already lower in cost in some activities such as ‘urban mining’ of electrical and electronic waste in Chinese cities). The recirculation of resources solves not only the problem of resource accessibility, but also the problem of waste accumulation. It provides a sustainable solution to the problem of dealing with geopolitical limits to resource extraction. As China expands its adoption of a circular economy to enhance its own resource security, so it creates

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

 . 

Per- W price in 2018 dollars 100

1976

1985 10 2003

2008

m = 28.5% 1 2015

0.1 1

10 historic prices (Maycock)

100

1,000

2019e 10,000 100,000 1,000,000 Cumulative capacity (MW)

Chines c-Si module prices (BNEF)

Experience curve at 28.5%

 . Learning curve associated with solar PV power Source: BNEF.

markets and technologies that can be adopted by other industrializing countries, starting with India, and encompassing late latecomers in Africa, Asia, and Latin America. This perspective on greening views the process as fundamentally driven by the quest for energy security and resource security necessitated by the unprecedented scale at which China and India are industrializing. It is a very different perspective from the one that informs almost all commentary on green industrial policy, which begins with a concern over global climate change and deduces from this the need for a low-carbon economy (and in more extreme versions, for a zero-growth economy as well). Such a perspective can only result in industrializing giants facing energy and resource choices that compel them to confront the ethical and moral challenges of decarbonization; little wonder that this perspective is resisted by late industrializers like India, given that it would condemn them to abandoning their search for industrialization before it has started, and with it the search for increased wealth and income to bring them closer to the levels enjoyed by Western industrialized countries. And they were not responsible for climate change in the first place. Consider the impact of switching to renewables to drive power generation, industry, and transport for reasons of energy security. Security is enhanced by such a move because renewables are products of manufacturing, and as such come under the control of the country implementing the policy. A green choice entails a process of decarbonization—the only known solution to the problem of rising carbon levels. As the industrializing giants like China and India switch over to renewables, leaving behind

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  



the fossil fuels of an earlier era, so they are led to achieve the very results anticipated by a ‘climate change’ perspective on greening. Likewise, choosing recirculating resources for reasons of resource security decouples industrial activity from natural processes, reduces the materials footprint of industrial activity, and allows the Earth to begin to reclaim its natural processes and cycles. The aspirational goal of zero-growth advocates is thus achieved through green growth rather than zero growth. It is considerations like these that have led international agencies like UNEP to argue that the greening of economies ‘is not generally a drag on growth but rather a new engine of growth’.¹ The discourse on developing countries and green industrial policy is thus moving away from ‘burden sharing’, where the costs of renewables or circular flows are viewed as higher than in conventional fossil-fuelled or linear flows. Countries are now discovering profitable opportunities associated with a green shift—notably the falling costs of solar PV (as shown in Figure .) and the complementary cost reductions found in wind turbines, batteries, electric vehicles, and other instances of the global green shift. Green growth is not so much a response to market failure (as in the standard account of neoclassical economics) as a response to market opportunities opened up by the Schumpeterian creative destruction of the incumbent fossil-fuelled energy systems and linear resource flows by renewables and recirculated resources, with the new industries driven by green finance. These are the real-world industrial dynamics of the greening of industrial policy.² This chapter develops the argument that in a wider technoeconomic setting, as compared to the narrower economic setting of traditional industrial policy, it is the energy and resource choices made by industrializing countries that will come to be central. Indeed, they will determine the success or failure of the industrialization aspirations of the emergent giants like China and India, and following them, the late latecomers in Africa, Asia, and Latin America. The material and energy foundations of these industrialization strategies constitute the core of green growth industrial policies.³

. G F   G  I P

.................................................................................................................................. The core of industrial policy concerns the strategies deployed to shift an economy from lower- to higher-productivity sectors, and within sectors, from lower value-added to ¹ See UNEP () for the Green Economy report. ² For accounts of green industrial policy, which generally start with the challenge of decarbonization to mitigate climate change, see such works as Shadikhodjaev (), Altenburg and Rodrik (), Ambec (), Padilla (), Fay et al. (), Schmitz et al. (), Luetkenhorst et al. (), Rodrik (), Cosbey (), Hallegatte et al. (), or Karp and Stevenson (). ³ For my own contributions to these topics, see Mathews () to Mathews () in reverse order.

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

 . 

higher value-added activities. These strategies inevitably focus on manufacturing, where such productivity improvements can be concentrated, while manufacturing itself can be concentrated in clusters, or industrial hubs, where an export orientation can be pursued. These strategic choices by successful industrializers (in particular those in East Asia) now characterize the choices made by smart late latecomers around the world.⁴ The greening of industrial policy broadens the canvas to encompass the energy and materials/resources aspects of manufacturing activities—widening the scope from economic to technoeconomic considerations. As soon as this wider perspective is taken, the material underpinnings of industrialization begin to exert powerful effects. Let us consider the fundamental aspects of these technoeconomic policy choices, spanning green energy, green resources, and the green finance that drives the choices being made in energy and resources.⁵

.. Energy Energy choices are a principal aspect of the greening of industrial policy. A worldwide green transition is underway, shaped initially by the choices made by China and India, and now diffusing to encompass the choices made by countries in Africa, Asia, and Latin America.⁶ In the energy domain, the move towards renewables like solar and wind has the great advantage that the resource is free, and marginal costs of generating power from these free resources are correspondingly low—lower than burning expensive fuel. The renewable resources are diffuse, meaning that they are available almost everywhere, and to everyone, countering the trends towards centralization and gigantism in the traditional fossil-fuelled industry. Renewables-based industries tend to be labourintensive (think of installing rooftop solar modules) and generate jobs in rural and regional areas. And of course renewable energy is clean, in the sense that it carries no pollution risks (in contrast to the filth associated with coal mining and burning, or the radiation risks associated with nuclear power), and poses no security dilemma, as in the ever-present risk that civil nuclear power industries could be converted to military use virtually overnight. The renewables industries favour small and medium-sized firms as protagonists, basing their competitive dynamics on innovation as much as on ⁴ For a sophisticated account of East Asian industrialization strategies and the reasons for their success, see Storm and Naastepad (). ⁵ The alternative approach is to discuss various contingent instances of green industrial policy, spanning such instruments as carbon taxes, cap and trade schemes and emission allowances, energy subsidies (and reduction of fossil-fuel subsidies), environmental labelling, and WTO-related instruments such as exemptions under GATT Article XX. For recent discussion of some of these instruments, see Shadikhodjaev (). ⁶ The rise in renewables is relentless. Total renewables capacity reached . trillion watts in , according to REN’s report ‘Renewables ’. We are now well into the ‘terawatt’ era of the renewables transition.

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  



imitation. By contrast, how much innovation has there been in the automotive industry over the past century (until the appearance of electric vehicles)?

.. Materials/Resources The circular economy emerges as an alternative to the traditional linear economy in the resources or materials domain. The fundamental attribute of circular resource flows is that they enhance resource security as more and more resources are extracted from circular flows rather than as virgin resources (think of water recycling and treatment). Resource extraction thus becomes a branch of manufacturing (or ‘demanufacturing’)— as in ‘urban mining’—and its pursuit becomes a goal of industrial policy. Recirculated resources have declining costs, as demanufacturing generates its own learning curve and the market for recirculated resources enlarges—to the point where costs of recovered resources dip below the costs of extracting virgin resources.⁷ Capturing circular flows by closing industrial loops generates rich linkages between industrial sectors and multiplies opportunities for capturing increasing returns. For an industrializing economy, the shift to circular flows saves on resources, saves on waste, generates abundant business opportunities, and creates jobs in rural and regional areas. What is there not to like?

.. Finance What drives these shifts in energy and resources/materials flows is finance, which, as Schumpeter correctly observed, is the ‘engine room’ of capitalism. Here we introduce another departure from the usual treatment of greening of industrial policy. In the way that the issues are typically framed by United Nations agencies, finance means creating funds from the resources of governments, meaning taxpayers’ funds.⁸ But this approach to finance ignores the central feature of capitalism, namely that it runs on credit—and credit is created in capital markets. The issue becomes: how to create instruments of credit that draw from the vast capital markets created by capitalism? One solution to this issue is to target the bonds markets, which globally are double the size of equity (stocks) markets. Banks and financial institutions have found that they can attract the interest of professional investors—managers of wealth funds, hedge funds, insurance funds, and pension funds—with bonds targeted at green investments, or green bonds. Ever since the Korean Export-Import Bank first floated a green bond ⁷ See the study of urban mining in Beijing conducted with my Chinese collaborators, Dr Zeng and Professor Li (Zeng et al., ). ⁸ Consider, for example, the UN-inspired Green Climate Fund, established following the  Paris Climate Agreement, at: https://www.greenclimate.fund/who-we-are/about-the-fund.

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

 . 

successfully on global bond markets in March , raising US$ million in funds to be invested in green projects by Korean firms around the world, the idea has caught on in a big way. China in particular has taken to green bonds, viewing them as a way of tapping global capital markets to fund its green operations both at home and abroad (under the Belt and Road Initiative). Green bonds are diffusing to late latecomers around the world. The Bank Windhoek in Namibia, for example, issued a green bond in  targeted at renewable energy projects as well as at reducing carbon emissions from fossilfuel activities (a controversial aspect).⁹ The scale of green bond issuances continues to grow, reaching US$ billion in , and US$. billion in the first half of .¹⁰ The other way that industrializing countries can channel finance towards green growth initiatives—both energy and resources/materials aspects—is through development banks. China is at the forefront, with its two principal development banks, the China Development Bank (CDB) and the China Exim Bank, both providing Chinese green shift companies with long credit lines in the billions of dollars to sustain them in international competition against less well-endowed competitors. Brazil, too, has been able to finance green projects throughout the country through the operations of the Brazilian Development Bank (BNDeS) which has grown to be larger than the World Bank. How then are the leading industrializing countries today putting these green initiatives to work in driving green growth, or greening industrial policy?

. E I P/G G I  I  C

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.. Green Industrial Policy in India and its Impact on Trade Let us start with India, which is not only about to become the world’s most populous country (expected to overtake China by the mid-s) but is actively pursuing green projects across the board.¹¹ The hallmarks of India’s newfound green growth zeal ⁹ See characterization of the Namibian green bond from the Climate Bonds Initiative, at: https:// www.climatebonds.net/files/files/-%NA%Bank%Windhoek.pdf. ¹⁰ See the reports from the Climate Bonds Initiative, at: https://www.climatebonds.net/resources/ reports/green-bonds-market-summary-h-. ¹¹ The literature on India’s development has recently been throwing off its ‘cultural cringe’ with respect to Western industrialization, and is now reclaiming India’s strong economic performance right up to the nineteenth century before colonial depredations dismantled its sources of competitiveness. See, for example, Bagchi () or Parthasarathi (). On India’s pursuit of green policies, see the description and analysis by Simran Talwar and myself as at November , ‘India’s green shift to renewables: How fast is it happening?’, Energy Post,  November , at: https://energypost.eu/indiasgreen-shift-to-renewables-how-fast-is-it-happening/.

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   Yearly Addition in GW



Total Solar Capacity in GW

30

25

20

15

10

5

0 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

 . India’s solar PV installed capacity, – Source: Author.

(emulating China’s strategies with a lag of perhaps a decade) can be found in the National Solar Mission, designed to achieve solar PV capacity in India of  GW by , and in the corresponding target for wind power of  GW, again to be achieved by . As shown in Figure ., the National Solar Mission was steadily driving the uptake of solar power—until it met the unexpected obstacle of trade barriers created by the advanced countries. The Indian case reveals the hypocrisy of the West in advancing the concept of decarbonization as a means of mitigating climate change, and yet opposing it as soon as a country like India starts to take practical steps to build its own green industries. Emulating China’s great success with building a wind-power industry in the early s, utilizing the instrument of local content requirements (LCRs) (see section ..), as part of the National Solar Mission India stipulated that there should be steadily rising proportions of domestic manufactures in the national solar PV output and in the solar PV installation sector.¹² These requirements, while universally recognized as necessary to build a new industry in an industrializing country, are technically in breach of WTO rules, and India was duly taken to the WTO for disciplinary action by the United States in a case that started in .¹³ India defended its policies on the grounds that they were needed to enable India to meet its clean-tech targets under its ¹² On India’s National Solar Mission, see recent treatments such as Akoijam and Krishna () or Kumar et al., (). ¹³ See the description of the case (as at  February ) by the WTO, at: https://www.wto.org/ english/tratop_e/dispu_e/cases_e/ds_e.htm.

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 . 

Paris commitments, but these arguments were rejected by the panel put in place to hear the case and upheld by the highest WTO authority, an Appellate Court, in . By  the expansion of India’s world-beating solar PV industry was moderating. This is the perverse result of a global system where the WTO and the UNFCCC are dangerously out of alignment. The data on India’s solar PV generation in Figure . tell the story: rapidly growing PV generation up to the year , when it started to decline under the impact of India having to dismantle the LCR aspects of the National Solar Mission, on pain of expulsion from the WTO.

.. Green Industrial Policy in China and its Impact on Trade While there is ample documentation on China’s vast consumption of coal and its growing involvement in oil and gas production and consumption (its black economy), much less attention is paid to the serious greening that has been under way in China over the course of the past decade.¹⁴ The green shift in the electric power sector, where the trends are concentrated, is clearly shown in Figure .. Figure . reveals in striking detail how China effected a switch to dependence on renewable sources (water, wind, and sun) around , and has since been pursuing this green shift as fast as is practicable (given the vast scale of the electric power system). In terms of capacity (upper line) the proportion of electric power capacity sourced from water, wind, and sun (WWS) reached  per cent by , rising from  per cent in —a  per cent green shift in just one decade. If this green shift is maintained through consistent green industrial policy for the next decade, China’s WWS capacity could reach more than  per cent before , meaning China’s electric power system (the largest in the world) would have reached the tipping point where it is more green than black, with a corresponding impact across wider industrial and transport sectors. The data in terms of actual electricity generated show the same trend, if not the same absolute values (because of varying capacity factors across different generating sources). China has judiciously utilized all the tools of green industrial policy to effect this green transition in its electric power sector. The new industries of wind power (encompassing a manufacturing value chain for wind turbines, and the operation of huge wind farms like the Gansu  GW farm) and solar PV power have been carefully ¹⁴ On China’s greening of its energy system, with emphasis on the way that green additions to the power system now outrank black additions, see the successive articles by myself and Hao Tan in AsiaPacific Journal, including the most recent update, ‘The Greening of China’s Energy System Outpaces its Further Blackening: A  Update’, by John Mathews and Carol X. Huang, with comments from Mark Selden and from Thomas Rawski,  May , at: https://apjjf.org///Mathews.html.

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  



40%

35%

30%

Proportion of the installed power capacity from WWS sources

25%

20%

15%

Proportion of electricity generation from WWS sources

10% 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018

 . China: Rising proportion of electric power sourced from water, wind, and sun, – Source: Author.

nurtured. China utilized LCRs and foreign direct investment (FDI) to build its windturbine industry in the first decade of the twenty-first century, artfully deploying graded increases in LCRs and (once they had achieved their objective) dismantling them before a protest could be lodged at the WTO in Geneva. The emerging windturbine giants like Goldwind were equipped with long credit lines by CDB, and leveraged latecomer technology to good effect to acquire new technologies like permanent magnet direct drive (PMDD), which facilitated the expansion of the windpower industry offshore. The solar PV industry also expanded, with new entrants like Suntech Power, founded in Wuxi by young entrepreneur Dr Shi Zhengrong in , scaling up production of PV modules to a degree never before attempted, and driving down costs as they did so. Of course it was not all plain sailing. Because China opened up the solar PV industry as an exemplary case of unrestricted growth, there was a rapid build-up of overcapacity, resulting in many bankruptcies. Rather than being seen as a failure of industrial policy, this should be viewed instead as a success, in that the PV industry was exhibiting ‘normal’ industrial dynamics of free entry and free exit via bankruptcy or corporate acquisition. Suntech Power itself was one of the casualties. China’s power grid proved incapable of accepting all the renewable power generated from the new

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

 . 

wind and solar PV sources, and much of the power was wasted in a process called ‘curtailment’. But this in itself stimulated rapid innovation, with the grid upgraded as a vehicle of transmission and distribution (T&D) and the State Grid Corporation of China leapfrogging world electrical engineering leaders with the introduction of new T&D technologies such as ultra-high voltage (UHV) transmission. The new UHV transmission lines built over the second decade of the twenty-first century have enabled China to generate vast amounts of power from renewable sources in inland provinces and then transport the electrical energy to the eastern seaboard with minimal losses and enhanced reliability. This was a major achievement, revealing China’s rapid passage from imitation to innovation in a critical sector.¹⁵ An unheralded aspect of China’s green energy shift over the course of the past decade is that as the scale of its wind and solar PV markets expanded, so efficiencies improved and costs were driven down spectacularly, as evidenced in Figure .. These cost reductions have not been confined to China, but through globalization they have diffused to the rest of the world. The result has been an unprecedented boom in building renewable energy industries in newly industrializing countries, particularly in those pursuing ‘late’ latecomer development strategies.

. O  L L  A G I P  D D

.................................................................................................................................. An excellent example of a green economy initiative in a ‘late’ latecomer that makes abundant economic and business sense may be found in Ethiopia, a country that is industrializing fast, as the ‘China of Africa’. The country has a clear industrial policy focused on manufacturing, which is concentrated on a series of industrial parks located around the country. There are clear strategies in place to have these parks linked to logistical infrastructure, such as the new (Chinese-financed) railway from the capital Addis Ababa to the port of Djibouti on the Red Sea, which serves as a conduit to the outside world for the landlocked country. These industrial parks offer investors many advantages, including shared capital infrastructure and common provision of energy and resources inputs. For textile and clothing firms (the majority of invested enterprises in the industrial parks) water is a critical resource—and some of the parks are offering an advanced zero liquid discharge facility, or otherwise advanced water treatment and recycling facilities that come with park admission. In one park, water is treated both physically and chemically to remove pollutants and impurities in the form of a sludge that is solar dried and then ¹⁵ See the account of China’s UHV innovation as a leapfrogging strategy in Xu ().

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  



transported off-site to a local cement plant, where it is absorbed as an input. This creates linkages across manufacturing centres as well as the closure of a loop linking the textiles and cement industries. And from the perspective of the firms involved in the industrial parks, it reduces the costs of water as input, since the water utilized in the park is  per cent recycled, providing ‘grey water’ for all enterprises at costs well below those that would apply to water drawn from underground supplies or from local lakes and rivers. And the country is saved the environmental damage that would flow from otherwise ‘free’ discharge of polluted water into local waterways.¹⁶ This is an example of an environmental initiative that enhances the water security of the country, utilizing a technologically advanced water treatment and recycling system that is as yet found in few advanced countries. It is thus a case of a government agency (in this case, the Industrial Parks Development Corporation) acting as a public entrepreneurial agent and introducing technoeconomic ‘leapfrogging’ as a matter of industrial policy in Ethiopia. And once installed and operational, the initiative can be replicated by other late late developers elsewhere in Africa, Asia, or Latin America. The more it is replicated, the more the costs can be expected to decline, through the enhanced efficiencies and specialization that flow from market expansion. Far from a cost that must be imposed on a developing country through an ethic of ‘zero growth’, it is in fact a business opportunity that offers profits in one country after another through saving water as a precious resource by recirculating and treating the waste water as it is generated. As a resource-saving initiative it recovers its public investment through the exports facilitated by firms locating their operations in the industrial park involved. This is the circular economy in action.

. W W  C W  C  F-F D?

.................................................................................................................................. Compare the gains to be won through the greening approaches discussed above with maintaining the status quo based on fossil fuels and the linear economy. To pursue a conventional fossil-fuel pathway, a country would have to jeopardize its energy security by maintaining dependence on oil, gas, or coal imports, at arbitrary prices and as an increasing burden on the balance of payments. As the world approaches peak oil or peak gas in individual oil and gas fields (as it has done repeatedly in successive fields) so the demands for more extreme, dangerous, and costly extraction and transport processes multiply. As everyone knows, oil and gas deposits are arbitrarily scattered around the world, and the discovery of deposits represents a windfall opportunity. ¹⁶ The author visited this industrial park, Bole Lemi Phase II, in Addis Ababa, in October , at the invitation of the IPDC.

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

 . 

By contrast, the absence of these fossil-fuel resources (as in the case of Japan) makes the country excessively dependent on imports from a few sensitive countries, thus reducing energy security. In the case of Japan in the s, America’s tightening grip on Japan’s oil supplies eventually led to the Pearl Harbor attacks and the bloodbath of the Pacific War. Oil wars were the curse of the twentieth century, and they promise to be an even worse curse in the twenty-first unless industrializing countries succeed in weaning themselves off fossil fuels and shifting decisively towards renewable energy sources. And then there is the huge environmental and pollution load associated with the oil and fossil-fuel industries themselves—the dirtiest industries on the planet. Oil leakages are the bane of oil production everywhere, quite apart from the shocking oil pollution episodes involved in tanker collisions and accidents, of which the Exxon Valdez oil spill may be taken as exemplary. One common refrain in the anti-renewables discourse is that it would cost too much, or require too many resources, to build a manufacturing-based energy system to match the reach and scale of the existing fossil fuel-based system. Given the costs and suicidal trends associated with continuing with fossil fuels, this is a strange argument. But let us meet it head on. Would the costs of building manufacturing industries to produce all the solar PV cells, all the wind turbines, and all the batteries needed for a  per cent transition to a renewables future exceed the costs involved in continuing to invest in refineries, mines, oil drilling platforms, tankers, pipelines, and distribution systems as at present? And don’t forget to add in the hospital and health care costs incurred in treating the victims of fossil fuel-related toxic poisoning and death—including lung cancer, bronchitis, and other debilitating conditions. Several research projects have been devoted to proving that the costs—both financial and resource-based—of building a  per cent renewables-based energy system are containable—and that the transition is therefore feasible and practicable.¹⁷ No further credibility can be attached to fears that we might run out of silicon, or that we would have to cover the world’s deserts with black silicon panels. No such estimates are available as yet of effecting a global transition from the linear economy to the circular economy—but they should be conducted as a matter of public urgency.¹⁸ Viewed from this perspective, one has to wonder why any country would wish to persevere with the fossil fuel and linear economy status quo. And then reason dawns: this is not a rational choice made by well-informed countries, but an outcome of the incumbents continuing with their ‘business as usual’ and their extraction of rents from their past investments. It is good to know that our future is in such safe hands.

¹⁷ A prominent project devoted to demonstrating the feasibility of a  per cent renewables transition is that conducted by Mark Jacobson and Mark Delucchi at the University of California, with a growing band of collaborators; see, for example, Delucchi and Jacobson () and Jacobson, Delucchi et al. (). ¹⁸ The Ellen Macarthur Foundation in the United Kingdom has come closest to conducting global cost-examination studies of the circular economy; see Webster ().

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

. G  E E  R S: W   D P ..................................................................................................................................

If both a ‘climate perspective’ and a ‘green growth perspective’ end up favouring the decarbonization of the economy and reducing its ecological footprint, what then is the difference between them? This is an important and legitimate question—to which there is an important and legitimate answer. The ‘climate perspective’ sets a standard of zero carbon emissions as the ultimate goal, so that any single step towards this goal has to be viewed as minor, until the goal is close. Or it sets a standard of ‘zero growth’ in order to reduce the economy’s ecological footprint—so that, again, any individual step towards reducing growth has to be viewed as a minor achievement. By contrast, the green growth strategy is all about the process of greening, not the end result. So even a small initiative to shift the energy system towards renewables can be counted as a positive move that, for example, improves energy security and generates local employment, which of course are positives in themselves and help to cement support for the overall green growth strategy. Likewise, a move towards recirculating resources, such as finding a way to turn an unwanted output into an input to another industrial process (closing an industrial loop) can be counted as a positive move that enhances resource security and reduces the waste generation problem, while also boosting manufacturing linkages, employment, and profitability. So, while China is continuing to burn a lot of coal—as numerous articles remind us—the fact is that China is moving its energy system in a profoundly green direction, one step at a time. It is the moving edge that is greening, with the energy system as a whole slowly moving to become greener until a tipping point can be expected to be reached where the entire system would be greener rather than blacker. China’s resource productivity is also low (meaning that it generates a lot of waste). But China is taking active steps to improve resource productivity, with moves to close industrial loops contributing to the construction of a circular economy. And a tipping point will be reached when the circular flows outnumber the linear flows, and the whole economy becomes more resource conserving (through circularity) than resource wasting. In my  book, Greening of Capitalism, I discussed this issue under the heading of the ‘differential principle’.¹⁹ In mathematical terms, complex systems are described by their differential equations, and the ‘point of change’ is captured by the differential. The most succinct way of capturing how the system is changing is to find an expression for the differential. If a change in the system dynamics is required, the simplest way to

¹⁹ See Mathews (:  n. ): ‘A more general version of this idea might be called the differential principle, in that it identifies the point of change of a system as the point at which it is most susceptible to effective intervention in moving the system to a new trajectory.’

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

 . 

effect it is via a change in the expression for the differential. So, translating these ideas into real-world examples of complex physical or technoeconomic systems involves focusing change efforts on the point where the system is already undergoing change— which in technoeconomic systems means focusing on the point where investment is occurring. One can try to change a large, complex system by means of an absolute change—one whole system replaced by another. Or one can try (with more likelihood of success) to change the system at the point of change, where the forces of change are already in evidence. Once business and technological systems have been built, they are highly resistant to change. But at the point where investment is being contemplated, change can occur by substituting one plan for another, with a stroke of the pen. So one approach to greening industrial strategy is to focus on a system-wide absolute, like carbon emissions, and uphold zero carbon emissions (the clean energy economy) as the goal. This might be a legitimate goal—but as such it is quite unachievable, because complex technoeconomic systems can change only in small steps. And this lack of achievability of the absolute goal undermines confidence and support—which is why we have seen so little overall progress in meeting global climate targets. Another system-wide absolute might be to aim for the steady state (zero growth)—which again is a non-achievable goal in any practical sense. But that does not prevent zero-growth advocates from protesting about a large country’s inability to conform to their absolutist expectations. By contrast, the green growth strategy has more modest goals which are in fact achievable. As the steps towards achieving them accumulate, so the system starts to change in discernible ways that attract more and more support. Investment in one small change, when viewed as a step in the right direction, attracts more such investment. This is indeed the huge advantage of the capitalist business system. It allows change to occur incrementally, one investment at a time. The big changes needed are the province of the state—as in the case of the developmental state. There is no harm in reminding ourselves why the capitalist system has achieved unrivalled supremacy in the modern world.

. C C

.................................................................................................................................. In this chapter, I have argued that by extending the scope of industrial policy from narrow economic to broader technoeconomic considerations, encompassing energy and resource flows, the restructuring of industrializing economies may be accelerated and at the same time brought closer to a state of balance between economy and ecology. Using examples from India, China, and late latecomers from around the world, the case has been made that at the scale of transformation now under way, traditional reliance on the fallback options of fossil fuels and linear resource flows is no longer feasible. These traditional options run into problems of severe environmental spoliation: in the

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  



energy domain, through particulate pollution as well as the pollution associated with continuing extraction of fossil fuels; and in the materials/resources domain through resource exhaustion and waste accumulation. Worse still, these traditional options run up against geopolitical limits when, for example, countries seek to extend their supply lines utilizing countries that are subject to social conflict or even civil war. These geopolitical limits to growth now outweigh the physical limits that were so much in vogue when the world was wrestling with ‘limits to growth’ in the s.²⁰ Green initiatives being taken in India, China, and late latecomers, far from being viewed as ‘special cases’, should be viewed as the general case that all countries industrializing in the twenty-first century must engage with. There is a common view that ‘advanced’ countries constitute the general case in economics, and ‘developing’ countries a special case. But as argued by Dudley Seers in the s, and by Storm in the s, the general case is in fact the one where structural shifts are under way, and where dynamics have greater salience than statics.²¹ In advanced countries, incumbents are concerned to protect rents—but in the developing countries, particularly very large countries like India and China, latecomer firms are seeking to create profits by emulating and replicating the patterns of activity observable in the advanced world— and to do so at lower cost. In the case of greening, there are countless examples of such imitation and emulation, with latecomers drawing on the huge pool of knowledge and technology available in the advanced world. Think of Chinese firms scaling up solar PV wafer production to a mass production industry for the first time, on their way to becoming world leaders in this sector. Or Chinese wind-turbine manufacturers like Goldwind adopting such innovations as PMDD and scaling them up for the first time, thus facilitating the global expansion of wind power from onshore to offshore. There are also cases of leapfrogging, where the industrializing countries see market opportunities and grasp them, even when this means going beyond imitation to innovation. The case of China going it alone to UHV grid operation as a means of transporting vast quantities of electric power from the interior of the country to the eastern seaboard comes to mind as an outstanding example. Indeed, there is a case for abandoning the term ‘greening’ altogether, once it is understood that the initiatives involved in enhancing energy security and resource security are in fact well-recognized cases of industrial strategy at work. The perspective adopted in this chapter is that greening initiatives are going to accumulate, driven by cost reductions and Schumpeterian creative destruction, until the point where almost all technoeconomic initiatives are, axiomatically, regarded as green. At that point, there will indeed be no need to discuss ‘green’ industrial policy as a special case—because by then it will have become the general case.

²⁰ The reference here is to the influential  report to the Club of Rome, ‘The Limits to Growth’ (Meadows et al., ). ²¹ See Seers () for the original argument, and Storm () for a more recent elaboration.

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 . 

R Akoijam, Amitkumar Singh and Venni V. Krishna () ‘Exploring the Jawaharlal Nehru National Solar Mission: Impact on Innovation Ecosystem in India’, African Journal of Science, Technology, Innovation and Development (): –. Altenburg, Tilman and Dani Rodrik () ‘Green Industrial Policy: Accelerating Structural Change towards Wealthy Green Economies’, in Tilman Altenburg and Claudia Assmann (eds) Green Industrial Policy: Concept, Policies, Country Experiences. Geneva/Bonn: UN Environment/German Development Institute (DIE), pp. –. Ambec, Stefan () ‘Gaining Competitive Advantage with Green Policy’, in Tilman Altenburg and Claudia Assmann (eds) Green Industrial Policy: Concept, Policies, Country Experiences. Geneva/Bonn: UN Environment/German Development Institute (DIE), pp. –. Bagchi, Amiya K. () Colonialism and the Indian Economy. New Delhi: Oxford University Press. Cosbey, Aaron () ‘Green Industrial Policy and the World Trading System’, Issue Brief No. . Stockholm: ENTWINED/Winnipeg, Canada: IISD (International Institute for Sustainable Development). Available at https://www.iisd.org/library/green-industrialpolicy-and-world-trading-system. Delucchi, Mark A. and Mark Z. Jacobson () ‘Providing All Global Energy with Wind, Water, and Solar Power, Part II: Reliability, System and Transmission Costs, and Policies’, Energy Policy (): –. Fay, Marianne, Stefane Hallegatte, Adrien Vogt-Schilb, Julie Rozenberg, Ulf Narloch, and Tom Kerr () Decarbonizing Development. Washington, DC: World Bank. Hallegatte, Stefane, Marianne Fay, and Adrien Vogt-Schilb () ‘Green Industrial Policies: When and How?’. Policy Research Working Paper No. . Washington, DC: World Bank. Jacobson, Mark Z., Mark A. Delucchi et al. () ‘% Clean and Renewable Wind, Water and Sunlight All-sector Energy Roadmaps for  Countries of the World’, Joule : –. Karp, Larry and Megan Stevenson () ‘Green Industrial Policy: Trade and Theory’. Policy Research Working Paper No. . Washington, DC: World Bank. Kumar, Charles R., Vinod Kumar, and M. A. Majid () ‘Wind Energy Programme in India: Emerging Energy Alternatives for Sustainable Growth’, Energy & Environment (): –. Luetkenhorst, Wilfried, Tilman Altenburg, Anna Pegels, and Georgeta Vidican () ‘Green Industrial Policy: Managing Transformation under Uncertainty’. Discussion Paper No. /. Bonn: German Development Institute (DIE: Deutsches Institut für Entwicklungspolitik). Mathews, John A. () Greening of Capitalism: How Asia is Driving the Next Great Transformation. Stanford, CA: Stanford University Press. Mathews, John A. (a) ‘Global Trade and Promotion of Cleantech Industry: A Post-Paris Agenda’, Climate Policy (): –. Mathews, John A. (b) ‘Competing Principles Driving Energy Futures: Fossil Fuel Decarbonization vs. Manufacturing Learning Curves’, Futures (A): –. Mathews, John A. (c) ‘Latecomer Industrialization’, in Erik S. Reinert, Jayati Ghosh, and Rainer Kattel (eds) Handbook of Alternative Theories of Economic Development. Cheltenham: Edward Elgar, pp. –. Mathews, John A. () Global Green Shift: When CERES Meets GAIA. London: Anthem Press.

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  



Mathews, John A. () ‘The Green Growth Economy as an Engine of Development: The Case of China’, in Roger Fouquet (ed.) Handbook on Green Growth. Cheltenham: Edward Elgar, pp. –. Mathews, John A. () ‘The Greening of Industrial Hubs’, in Arkebe Oqubay and Justin Yifu Lin (eds) The Oxford Handbook of Industrial Hubs and Economic Development. Oxford: Oxford University Press. Mathews, John A. and Hao Tan (a) ‘Manufacture Renewables to Build Energy Security’, Nature (): –. Mathews, John A. and Hao Tan (b) ‘A  Trillion Watt “Big Push” to Decarbonize the World’s Electric Power’, Journal of Sustainable Energy Engineering (): –. Mathews, John A. and Hao Tan () ‘Circular Economy: Lessons from China’, Nature (): –. Mathews, John A., Hao Tan, and Mei-Chi Hu () ‘Moving to a Circular Economy in China: Transforming Industrial Parks into Eco-industrial Parks’, California Management Review (): –. Meadows, Donella H., Dennis L. Meadows, Juergen Randers, and William W. Behrens () The Limits to Growth: A Report to the Club of Rome. Washington, DC: Potomac Associates/ Universe Books. Padilla, Emilio () ‘What can Developing Countries Gain from a Green Transformation?’, in Tilman Altenburg and Claudia Assmann (eds) Green Industrial Policy: Concept, Policies, Country Experiences. Geneva/Bonn: UN Environment/German Development Institute (DIE), pp. –. Parthasarathi, Prasannan () Why Europe Grew Rich and Asia Did Not: Global Economic Divergence. Cambridge: Cambridge University Press. Rodrik, Dani () ‘Green Industrial Policy’, Oxford Review of Economic Policy (): –. Schmitz, Hubert, Oliver Johnson, and Tilman Altenburg () ‘Rent Management: The Heart of Green Industrial Policy’, New Political Economy (): –. Seers, Dudley () ‘The Limitations of the Special Case’, Oxford Bulletin of Economics and Statistics (): –. Shadikhodjaev, Sherzod () ‘The Greening of Industrial Policy’, in Sherzod Shadikhodjaev (ed.) Industrial Policy and the World Trade Organization. Cambridge: Cambridge University Press, pp. –. Storm, Servaas () ‘Economics for the “General Case” ’, Development and Change (): –. Storm, Servaas and Naastepad, C. W. M. () ‘Strategic Factors in Economic Development: East Asian Industrialization –’, Development and Change (): –. UNEP () Towards a Green Economy: Pathways to Sustainable Development and Poverty Eradication. Nairobi, Kenya: United Nations Environment Programme. Webster, Ken () The Circular Economy: A Wealth of Flows. Cowes: Ellen Macarthur Foundation. Xu, Yi-chong () ‘The Search for High Power in China: State Grid Corporation of China’, in Loren Brandt and Thomas G. Rawski (eds) Policy, Regulation and Innovation in China’s Electricity and Telecom Industries. Cambridge: Cambridge University Press, pp. –. Zeng, Xianlai, John A. Mathews, and Jinhui Li () ‘Urban Mining of e-Waste is Becoming More Cost-effective than Virgin Mining’, Environmental Science and Technology (): –.

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  ......................................................................................................................

    

.............................................................................................................

 .    . 

I the contemporary era, industrial strategies are crafted amid competing narratives of globalization. These narratives represent the parameters that both constrain industrial policymaking and provide an opportunity to negotiate alternatives. Such representations are powerful precisely because they can become objectified as policy. They are also compelling because the literature on industrial policy, taken as an ensemble, largely leaves them out, interesting exceptions notwithstanding.¹ The aims of this chapter are to fill in this blind spot and enlarge the orbit of inquiry. Mindful of the fluidity of discourses, we will analyse how elite narratives of globalization, expressed in verbal and written texts, bear on industrial strategies. Our goal is to parse out what these stories reveal. We will highlight ways in which the dominant narrative of hyper-globalization frames analysis and action. Specifically, we will probe the manner in which narratives of globalization are both shaped by and manifest in globalization indices as well as in statements and speeches by senior political leaders of the five BRICS countries: Brazil, Russia, India, China, and South Africa. We will also show how the unifying discourse of hyper-globalization has been challenged by an opposing narrative, de-globalization, which, though less apparent in the data analysed here, is increasingly intertwined with the former. Over the years, these narratives have gradually been supplanted by three more specific storylines, to be traced in the pages ahead.

¹ Yet literature in cognate fields such as cultural theory and media studies gives ample attention to keywords and speech acts. The acclaimed social critic Raymond Williams (), for instance, argues that the uses and implications of keywords must be explicated historically. He demonstrates that the language in vogue is constituted as lived experience in diverse contexts, open to challenge, and subject to appropriation for gainful purposes.

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    



For the purposes of this study, the context is low- and middle-income countries in the global South from the s to the present. These years are punctuated by the transition to a post-Cold War order and adjustments to neo-liberalism, a set of ideas and a policy framework centred on deregulation, liberalization, and privatization.

. T A A   C

.................................................................................................................................. To investigate the elective affinities between globalization narratives and industrial strategies, this chapter adopts a critical political-economy perspective supported by original data. Our critical approach upsets certainties in extant knowledge sets. Two branches of political economy and social theory are especially pertinent for examining industrial strategies: our work bridges insights from materialist and poststructuralist traditions, with their respective emphases on material power and discursive power. The rationale for linking them has its roots in classical political economy and classical social theory. Both traditions emerged during the social upheavals accompanying the rise of industrial capitalism in Western Europe from the late eighteenth to the early twentieth centuries, as chronicled by Smith, Ricardo, and Marx to Durkheim, Weber, and others. Our framework also draws on feminist and postcolonial theorists’ writings on standpoint analysis, that is, seeing global problems from different positions in social and geographical hierarchies (Tickner, ). Spoken and written words are central to this endeavour. Words condense and frame information. They overestimate some aspects of socio-economic phenomena and underestimate others. While words can plant ideas and generate action, they may also be a masquerade, disguising meaning and intentions. Whether used as a form of deception or to induce action, they are instruments of political economy that produce real consequences. Moreover, words reflect what the French sociologist and public intellectual Pierre Bourdieu () famously called habitus: the deep-seated habits, skills, and dispositions that serve as cornerstones of institutionalized social hierarchies. Bourdieu’s notion of habitus is important to analyses of industrial policy because it can be read as drawing attention to narrative voices that animate international practices. Expanding Bourdieu’s conceptualization, we argue that how international actors talk about industrialization, name strategies for bolstering it, and attach labels to its variants, seep into mindsets. The language chosen is used to kindle or confound practice.² The

² The impact of the preponderant use of the English language on the formation of global narratives is discussed elsewhere (Mittelman, : especially  n.  and ) and falls outside the purview of this chapter.

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

 .    . 

vocabularies are terrain for contesting policy. They invite us to derive a sense of what mistakes to correct and where to go: in short, how to do better policymaking. In dwelling on the power of verbal and written acts, we will attempt to pick up on the subtlety of these ambiguities and anomalies. While empirical digging beneath public statements to investigate hidden transcripts is beyond the scope of this inquiry about Industrial Globalization Talk,³ this chapter takes but a modest, exploratory step in that direction. It is our hope that it can serve as a starting point for multipronged projects combining interviews, ethnographies of organizations, and other types of field research that would delve deeply into dominant‒subaltern relations and the institutions of civil society amid the changing global division of labour and power (GDLP). Conceptually, the narratives of hyper-globalization and de-globalization serve as nonbinary markers, poles on a spectrum, with many variants in between. Of course, other discourses are circulating. But we focus on the two widely shared narratives because of their frequency in both the literature and the empirical data examined for this research. It must also be stressed that they should not be construed as a dichotomy. In the coming pages, we acknowledge sub-narratives. In addition, we presuppose that world regions, multilateral agencies, and individual countries are saturated with their external environment: in particular, by globalizing forces, albeit accompanied by counterforces such as resurgent nationalism and authoritarian populism. Methodologically, we offer textual analysis of intersubjective framing on the basis of documentary research. Evidence is garnered from governmental and intergovernmental reports issued between  and , a period spanning the  global financial crisis and the Eurozone debt crisis, the early years of modest recovery, and the rise of counter-globalist forms of national populism in different world regions. Our research integrates qualitative and quantitative data from think tanks and private corporations with statements and reports by multilateral organizations and BRICS leaders. These are drawn from online media outlets and the World Economic Forum (WEF, a private, non-profit body that brings together global elites at annual gatherings usually held in Davos, Switzerland), keynote speeches and reports by the five members of the BRICS Business Council, and annual reports of the sole worldwide specialized agency devoted to industrial development, the United Nations Industrial Development Organization (UNIDO). All the documents were collected between January and June  through extensive Internet searches and by accessing publicly available online repositories. Our empirical analysis thus proceeds selectively. As Fernando Santiago (see Chapter , this volume) demonstrates, the BRICS are a heterogeneous grouping with regard to their productivity and integration in the global political economy. This variation notwithstanding, they are a visible expression of ongoing shifts in the GDLP. Admittedly, some of the data in our study are patchy—they are not as ³ As in James C. Scott’s book () on hidden and public transcripts. For an exemplar of how to discover and decode imaginaries, see Michael Burawoy et al. (). On ostensible representations of industrial globalization, Cho, Kim, and Lee’s collection of essays () offers ample evidence.

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    



prodigious as we would like.⁴ Nevertheless, we deem them representative of national and international elite narratives of globalization as they relate to industrial policy. Whereas additional documents generated by governments and multilateral organizations could broaden our work, we propose avenues for future inquiry in section . of this chapter. By grounding this research in empirical findings, we seek to gain conceptual clarity, throw light on contending narratives, and inform industrial policies in the global South. The chapter therefore proceeds as follows. After advancing our theoretical framework and tracking the rival narratives of hyper-globalization and de-globalization, we turn to a first level of generality. It is the more wide-ranging narrative and maps the ways in which globalization indices epitomize hyper-globalization. The second level evolved from the first and describes specific trends, particularly narrative framing of industrial policy by the leaders of multilateral organizations and the BRICS. Today’s narratives have their roots in the hyper-globalist and de-globalization paths that continue to be frequently travelled.⁵ The two levels of narrativity alike embody an epistemology: a theory of how to know the world. It creates a problematic about what is ‘askable’ and how to go about responding, thereby influencing what is to be said and done. Supposedly a means, it becomes the objective of policymaking. To pull together these themes, we conclude by offering reflections on the emphases and silences in the data, inferring opportunities on this basis for industrial policymaking, and suggesting a research itinerary.

. T P

.................................................................................................................................. To link ideas, symbols, and language with material forces, Antonio Gramsci () formulated the concept of ideological hegemony: a fit between consensus and coercion in which consensus is the dominant element. It would seem that neo-liberalism and developmentalism constitute ideological projects in a Gramscian sense (Mkandawire, ). In the postcolonial era, these ideologies formed the prevailing wisdom about the role of the state in much of Africa and elsewhere (Whitfield et al., ). Their implications for industrial policy have been unambiguous: a broad consensus, with economic and diplomatic coercion in the backdrop, is reflected in narratives about industrializing by forerunners and latecomers, catching up, climbing a ladder, realizing comparative advantages, and leapfrogging (Chang, ; Nayyar, ; Behuria and Goodfellow, ). Within this consensus, there are of course serious internal differences. Intervening in these debates, Akira Suehiro (: ) cautions about the pitfalls of ‘thinking in old-fashioned catch-up terms’ and notes that it is difficult to shed this ⁴ See n.  this chapter. ⁵ As, for example, in Dani Rodrik’s () use of this construct for examining dilemmas in the current conjuncture.

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

 .    . 

mindset. Suehiro traces the process of ‘technology formation’—that is, upgrading learning capabilities in industry and bolstering linkages between industrialization and trade. His conclusion dovetails with our argument in the previous paragraph: ‘The core of the matter is ideological, not technological’ (Suehiro, : ; emphasis in original). To be sure, industrialization requires even more than these frames suggest. The challenge is not to climb a ladder rung by rung to a pre-ordained destination decided by the organizers of a race, mostly based in affluent countries. The ground beneath the mythical track and hypothetical ladder can be unstable, even tremulous. The landscape is produced by historical structures. It cannot be gleaned from analogical reasoning, which may spread misconceptions and generate faulty narratives. To the extent that analogies depict structured hierarchies, they facilitate analysis; but history is more complex than collective metaphors could possibly capture. For example, the image of climbing a ladder is a linear view of capitalist development. In fact, the route is circuitous; the process, dysrhythmic. The imaginary of ascendance omits zigzagging and swerving. It is mistaken to neglect multidirectional tendencies that can be deeply contradictory. Nonetheless, the conventional wisdom is binary. It intimates verticality: upward or downward movement. This picture deflects attention from the importance of horizontal and lateral moves—spreading operations, building networks, and forming alliances. In short, it induces two-dimensional thinking when multidimensional analysis is needed to grasp the messiness of specific contexts. Falling into these narrative traps can come about through the mimetic repetition of keywords, a pivotal point to which we will return. In view of this relentless drumbeat, our attention centres on how stakeholders frame industrialization. The focus on the discursive moves by which industrial strategies are established, maintained, modified, or abandoned is crucial because a substantial corpus of literature on industrial policy privileges economic factors and understates the salience of intersubjectivity and social forces. In an attempt to countervail economistic propensities, one of us (Mittelman, : ‒) has sought to advance the Smithian/Ricardian international division of labour (IDL) theories, which emphasize the importance of the specialization of function and the comparative advantage of trading products for which costs are relatively low. Efforts to supplement them in a new international division of labour (NIDL) describe the devolution of certain manufacturing industries from advanced capitalist countries to the global South (Fröbel et al., ). This spatial reorganization of production, which began in the second half of the twentieth century, merits fresh analysis since global monopolization further concentrates industries geographically (see Chapter , this volume) argue. Beyond the NIDL, the concept of the GDLP incorporates structural power, constituted by a mix of objective and intersubjective factors that transcend economic spheres. It links big powerful institutions such as transnational corporations (TNCs) to social structure: the intersectionality of class, gender, generations, race and ethnicity, and sexual orientation. Building on this conceptualization, we maintain that imaginaries of globalization embodied in competing narratives render some strategies more promising than others.

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    



The menu of narratives provides options for industrial policy and begets societal impacts, shaping countries’ positions in the global economy and their sociopolitical development. To move beyond structuralism and economism in mainstream narratives (with important correctives, e.g. Hirschman, , , [] ; Amsden, , ), we want to explore alternative approaches. The pay-off should lie in explanatory power as well as suggestions for regulatory reform. Towards these ends, let’s now endeavour to disentangle global narratives.

. H-G  D-G

.................................................................................................................................. Widely deployed by governance agencies as well as by scholars and other policy intellectuals, the narrative of hyper-globalization embraces propellants in the global political economy. It is characterized by an acceleration in cross-border flows of capital, technology, population, and cultural products. Its purveyors call attention to the extent to which the speed and reach of contemporary economic globalization differ significantly from the pace and expanse of earlier phases. The hyper-globalization narrative emerged in the s and coincided with the inception of the concept of global governance. Simultaneously pioneered by scholars such as James Rosenau and Ernst-Otto Czempiel () and policy intellectuals in international organizations, the umbrella concept of global governance premises increasing complexity in the GDLP. In various formulations, hyper-globalization and global governance are kneaded together. Taking into account Asian experiences with industrialization during the Cold War, heterodox thinkers affirm that the developmental state must play a major role in animating economic development by nurturing domestic industries to the point that their insertion into global value chains produces profits outweighing the initial investment and the costs. In its early renderings, the notion of hyper-globalization depicted a borderless world, one with heightened denationalization and a proliferation of actors (e.g. Ohmae, ; cf. Dicken, ). Globalization was said to be an inexorable process that spurs capital accumulation. For some authors (e.g. Dollar and Kraay, ), deep integration in the global economy trends towards faster growth and poverty reduction and constitutes a win‒win scenario. Yet questions about inequality on a world scale and the ethics of the GDLP abound: whose rules and which discourses are inscribed in it? And who is responsible for global economic governance? Other authors have attempted to sharpen the hyper-globalist claim, positing that with growing deterritorialization, the old Westphalian state system is increasingly porous. As an organizing concept, the Westphalian principle has limited utility in accommodating nongovernmental activities and accounting for ways that the state itself and sovereignty are being reconstituted. New actors have come on the scene with

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

 .    . 

a backlash against globalizing forces, in particular from social movements that have mounted protests targeting multilateral agencies such as the World Trade Organization (WTO), the World Bank, and the International Monetary Fund. It has become apparent that the North‒South divide and centre/periphery distinction lack sufficient explanatory value for elucidating mobility in parts of the global South and persistent marginalization in some areas (see Held et al., : ‒; Scholte, ). In the second decade of the twenty-first century, analysts updated their data, but many observers cling to the construct of hyper-globalization. Researchers based in international institutions such as the United Nations Conference on Trade and Development (UNCTAD, : iv‒v, ix, xiii, ) and at think tanks, among them Arvind Subramanian and Martin Kessler () at the Peterson Institute for International Economics and Yuefen Li (: passim) at the South Centre, still regard rising global flows as indicators of the staying power of hyper-globalization. This is despite nuanced readings of features of globalization—for example, the changing meaning of sovereignty and citizenship (Sassen, , )—and trenchant critiques by certain trade economists. Dani Rodrik (), for instance, notes a groundswell against the hyper form of globalization, efforts to level the playing field, and the rise of populisms, partly as a reaction to the impact of neo-liberal capitalism. In the current capitalist era, the tides of globalization tack back and wash forward. It would be impossible to trace a neat sequential progression. Yet analysts can chart toggles between retreats and advances, tensions and challenges, that spawn reconstituted narratives. From the s, scholar-activists began to forge the counter-narrative of deglobalization. An avant-garde book titled Delinking () by Samir Amin, an Egyptian-French intellectual, laid the groundwork for careful research on this theme carried out in myriad contexts. Amin distinguishes delinking from autarky and withdrawal from the worldwide industrial, trade, and financial systems. Delinking is a strategy for capturing control of the national economy—an auto-centric programme for reconstructing the postcolonial economy. Meanwhile, the aim at the international level is to work with allies to shape a polycentric system of power. Amin and like-minded thinkers such as Walden Bello (), a Filipino professor and former member of the House of Representatives of the Philippines, have put forward ideas for transforming a political economy with due regard for the specificity of individual countries in the global South. In Karl Polanyi’s sense (), the goal is to re-embed the economy and institutions in society rather than to allow the economy to drive society. Accordingly, in Amin and Bello’s usage, the lodestar of de-globalization is disengaging from, and then selectively redialling into, the global political economy. Seemingly similar to these propositions, populists have formulated nationalist economic agendas. They argue in favour of restructuring terms of trade, levying tariffs, and protecting the domestic economy. In Indian Prime Minister Narendra Modi’s words: ‘As opposed to globalization, the forces of protectionism are emerging. Their intent is to not only safeguard themselves from globalization, but also to alter the natural flow of

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    



globalization’ (Government of India, ). This thrust mirrors similar developments in the global North where diverse economic nationalists, religious fundamentalists, and radical environmentalists would use the national state as a shield or barrier to constrict globalization. But major differences between the de-globalization narrative and populist stances on the right are palpable. For instance, while the former propagates the idea of decoupling to address economic inequalities associated with soft regulation of global capital flows, the latter considers it mainly to reinvigorate nationalist discourses and policies. Moreover, whereas the former stresses governments’ regulatory power visà-vis global financial capital as a critical component of a just GDLP, the latter calls for a reduction in human rather than financial flows even if reducing international mobility is detrimental to industrialization because it restricts the movement of labour and ideas. In light of these currents, we will next look at empirical evidence for how contemporary elite narratives have evolved and, one might claim, materialize as practices and policies. We begin with how globalization indices produced by different nongovernmental and corporate actors provide scaffolding for dominant narratives of globalization.

. N  A I: G I

.................................................................................................................................. Both narratives—hyper-globalization and de-globalization—offer interpretations of uneven development and subtle shifts in the global political economy. The most recent aggregate data for the period since the  financial crisis show neither a large rise nor a substantial decline in the overall level of globalization. Nor do the data suggest a pattern wherein countries are voluntarily delinking from globalizing forces. However, the indices rest on the taken-for-granted premise that countries can be ranked and compared by the same measures. In response, we find that the production of global indices itself incorporates the preponderance of but one narrative: hyper-globalization. To sustain this proposition, we juxtapose two global indices, the KOF Globalization Index issued by the KOF Swiss Economic Institute (a) and the DHL Global Connectedness Index DHL () compiled by New York University and the Barcelona-based IESE business schools.⁶

⁶ Secondary data accuracy could be a concern for our analysis since the KOF Globalization Index notes that ‘not all data are available for all countries and all years [and] missing values within a series are imputed using linear interpolation’ (KOF Swiss Economic Institute, c). Yet we are more focused on construct validity than data quality. The KOF Globalization Index, for instance, measures ‘de facto Cultural Globalization’ through trade in cultural goods and personal services, international trademark applications, and McDonald’s and IKEA stores relative to the size of countries’ populations. ‘De jure Cultural Globalization’ is proxied by the ratio of girls to boys enrolled in primary education in public and

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

 .    . 

According to the  KOF Globalization Index (KOF Swiss Economic Institute, b), worldwide globalization increased between  and  but slowed during the  financial crisis and in the recession that ensued. Disaggregating globalization by dimension, the index suggests that despite a slight upward tick in , aggregate economic globalization has flat-lined.⁷ Although financial globalization continued to mount, trade integration reportedly receded. Yet this overall deceleration has left the hyper-globalist narrative largely intact, as we will indicate in section . of this chapter. While the social dimensions of globalization increased slightly before evening out since , global information flows and political globalization vectored upward. The  KOF Globalization Index lists Switzerland as the most globalized country, followed by other small European countries such as the Netherlands and Belgium, whereas landlocked and island countries in the global South like the Central African Republic and the Comoros are ostensibly the least globalized. The BRICS rank considerably below small European countries. Brazil occupies the th spot in the  KOF Overall Globalization Index; Russia, th; India, th; China, th; and South Africa, th. As stated by the organizations producing the ranking (KOF Swiss Economic Institute, b; Bertelsmann Stiftung, ), one factor that explains these ratings is country size. The BRICS are relatively large in terms of population and land mass, and small countries and their neighbours tend to be more interdependent than many big ones. Second, not only is the BRICS’ level of intra-regional integration less than that of the most highly ranked small countries, but greater economic strictures (trade barriers, capital controls, etc.) in the BRICS are likely to be another element in this ordering (Weiß et al., ). As the relative ease of flows within the European Union illustrates, comparative regionalism may help account for these differences. In this vein, regionalism may be construed both as a component of globalization and a response and challenge to it, an issue that we will revisit. Third, the KOF Globalization Index demonstrates that advanced economies in general are more tied to global capital flows than are emerging economies. For China and the other BRICS, domestic flows still exceed cross-border transactions. The DHL Global Connectedness Index measures globalization in terms of the depth and breadth of cross-border flows of trade, capital, information, and people. The most recent DHL Index (Altman et al., ) indicates that for the world as a whole, the level of global connectedness crested at a record high in . Although not entirely sharing private schools, Feenstra et al.’s () human capital index (based on the average years of schooling per country and an assumed rate of return to education), and Freedom House () data. The latter comprise quantifications of aspects of freedom of expression and belief, associational and organizational rights, rule of law, and personal autonomy and individual rights (KOF Swiss Economic Institute, d). While creative, these proxies omit crucial dynamics of cultural globalization. For instance, they do not capture the international spread of ideas (e.g. political traction gained by de-globalization), meanings (e.g. rules and norms of global trade), and values (e.g. conditions under which national governments may choose to violate trade agreements in order to protect their citizens). ⁷ For definitions of the dimensions of globalization and explanations of the methodology employed, see Savina Gygli et al. (). We are also drawing on Kwon ().

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    



KOF’s determination that globalization is declining, the DHL Index attests that on actual levels of global connectedness, the world is, in fact, not as globalized as many observers believe. The DHL finds that a larger portion of flows of trade, capital, information, and people is domestic rather than international. Equally, in contrast to the KOF Globalization Index, the DHL Index reveals that this is apparent for not only countries on the low end of tallies of globalization indicators but also for those at the top. Notwithstanding the ways in which technological globalization compresses time and space, sovereignty and distance continue to constrain cross-border flows. The DHL Index ranks the Netherlands as leading all countries in global connectivity. It is followed in the top ten by mostly European countries in the following order: Singapore, Switzerland, Belgium, the United Arab Emirates, Ireland, Luxembourg, Denmark, the United Kingdom, and Germany. They hardly constitute a homogeneous grouping as the list comprises a city-state (Singapore), a quasi-city-state (Luxembourg), and relatively large national territories (UAE, Germany). The DHL Index also clusters knowledge-based industrial economies such as Singapore, Switzerland, and Denmark with service-based ones like the United Kingdom and Ireland, and the oil revenuedependent UAE. Moreover, it evinces substantial variation in flows over time, across locales, between countries, and within regions. And despite complaints in Washington about the scale and impact of globalization on the US domestic economy, the DHL Index reports that the United States lags behind many other advanced countries in this regard, ranking it th among  countries in overall global connectedness. Considering that, of the major global tech players, fourteen are based in the United States, three in the European Union, three in China, four elsewhere in Asia, and only one in Africa (Jomo and Chowdry, , drawing on UNCTAD, ), the index omits important dimensions of global aggregations of power. Global connectedness varies considerably by both country and region; it cannot be reduced to one universal pattern. But the deeper issue about these indices is not just that they offer nominally factual insights. Their use betrays a philosophical embrace of positivism that resonates with the tenets of neo-liberalism. The underlying assumption is that data may be objectively measured, are independent of subjective processes, and that the findings—rankings— can be replicated and are falsifiable. In objectifying the measures, complex social and political dynamics are reduced to numbers. The presupposition is that brute data are ‘given’, not, as critical theorists would have it, produced. The question of production begets questions not ordinarily asked in the field of industrial policy: Who authorizes the production of measures, who selects the producers, who pays them, and to whom are they accountable? If these searching questions are sidelined, are the measures— indicators—an ideological construct adopted by myriad policymakers? In this sense, dominant narratives may be understood as ideologies of power. And for this reason, they are theoretically and empirically intriguing. The empirical evidence adduced above shows that the levels of global connectedness lie somewhere between what the enthusiasts of hyper-globalization claim and what the proponents of de-globalization seek. In other words, even if globalization trends were really measurable, neither narrative would adequately depict the actualities. To pursue

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

 .    . 

these issues, let us now pivot to how these two narratives and their variants are reflected in other forms of policy texts and explore what this implies for industrialization strategies in the global South.

. N  A II: T S

.................................................................................................................................. In segueing from globalization trends to industrialization strategies amid competing narratives of globalization, it is important to be cognizant of narrative entrapment. Observers can be enthralled with imagery not of their own making. These images often take the form of language, mental pictures of social phenomena, and paradigms that filter ideas (Mittelman, : , citing Shotter, : ‒). Much like speeches and statements by heads of state and ministers at global conferences, multilateral organizations’ flagship reports are political documents that need to be read as such (Esser and Williams, ). They are variegated and do not necessarily present coherent policy positions, but rather exemplify the dynamics of global policymaking. They also reaffirm dominant global narratives, such as the Millennium Development Goals and their  successors, the Sustainable Development Goals, that project authority, purport mandates, and seek legitimacy. This is not to suggest that all stories are directly action inducing or option excluding (Rasche and Esser, ). But, to underscore a point made at the outset of this chapter, storylines have the potential to be converted into strategies and policies.

.. Globalization as Inexorable yet Malleable The first storyline scrutinized here frames globalization as unavoidable on the one hand, but susceptible to unilateral interventions by some national governments on the other. Thus, in a  speech, President Xi Jinping presented the Chinese perspective as recognizing economic globalization as ‘a double-edged sword’ (Xi, ) and alluded to ‘a time when China also had doubts about economic globalization’ (Xi, ). Xi nonetheless posited ‘that integration into the global economy is a historical trend’ since ‘the global economy is the big ocean that you cannot escape from’ (Xi, ). Weighing into ‘a heated debate on economic globalization [amid] a world of contradictions’, he concluded that for China, the best way forward is to ‘act pro-actively and manage economic globalization as appropriate so as to release its positive impact and rebalance the process of economic globalization’ (Xi, ). Xi also stressed that ‘this round of industrial revolution will produce extensive and far-reaching impacts such as growing inequality, particularly the possible widening gap between return on capital and return

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    



on labour . . . This is the biggest challenge facing the world today. It is also what is behind the social turmoil in some countries’ (Xi, ). In a similar vein, speaking at a  conference in Washington, DC, Brazilian Vice President Hamilton Mourão attributed an ‘international environment of greater instability and competition’ to the ‘triumph of neo-liberal ideas’ (Wilson Center, ). In his view: ‘Today all nations, even the most developed ones, are kept in a permanent state of alert’ (Wilson Center, ). So, too, Rob Davies, South Africa’s former minister of trade and industry, warned about ‘the extreme uncertainty of the current and immediately foreseeable global environment’ (Department of Trade and Industry [DTI], : ), specifically the ‘volatile mix of geopolitical uncertainties and risks and the emergence (and apparently growing traction) of populist backlashes in the United States and much of Europe, partly fuelled by the unchecked exclusion and inequality which the current model of globalisation has engendered’ (DTI, ).⁸ And during the  WEF meeting, India’s prime minister paraphrased Mahatma Gandhi: ‘I do not want that the walls and windows of my house are closed from all sides . . . But at the same time it will not be acceptable to me that this wind blows away my feet off the ground’ (Government of India, ). It thus appears that even though BRICS leaders embrace a wide range of political ideologies, they converge on a narrative of economic globalization as a pervasive force subject to a set of pressures on their societies. They largely agree that the rise of protectionist stances as outgrowths of chauvinistic populism risks squandering development opportunities from the flow of goods and human capital and achieves little in terms of mitigating the pernicious social effects of unfettered globalization. These impacts and options are recognized across the global South, from Latin America to East Asia, with important differences in the political implications. Meanwhile, a joint communiqué by the BRICS’ trade ministers ‘recognized the importance of preserving policy space to promote industrialization, industrial upgrading, and value addition as a core pillar for structural transformation and sustainable development and BRICS countries’ integration into the global economy’ (BRICS, a: ). This need to defend and reclaim national policy space was reiterated during the eighth BRICS Summit, which affirmed ‘measures that support greater participation, value addition, and upward mobility in Global Value Chains of [BRICS] firms including through the preservation of policy space to promote industrial development’ (BRICS, b: ). This narrative shift towards a more nuanced assessment of globalization’s enabling and deleterious effects that extend beyond the economic sphere, along with the appeal of selective protectionism by countries confident in its successful implementation,

⁸ One year later, South African Prime Minister Cyril Ramaphosa also highlighted the ‘rise of trade protectionism’ as one of the country’s main foreign policy challenges (Council on Foreign Relations [CFR], ).

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

 .    . 

becomes equally apparent in UNIDO’s annual reports since .⁹ While recognizing ‘marginalization in today’s globalized world’ (UNIDO, , , ), UNIDO nonetheless counselled that ‘[i]ncreased globalization and market liberalization provide great opportunities for developing countries and economies in transition to trade their way out of poverty’ (UNIDO, : ). The emphasis changed in the aftermath of the  global financial crisis. According to UNIDO (: ), ‘[a] number of existing and emerging megatrends— including . . . unequal globalization—converged and together wreaked havoc on the poorest countries that are home to the bottom billion’. Although the same report noted a ‘multitude of gains to be achieved from globalization’ (: ), this formulation soon switched to another frame: ‘rapid changes brought about by globalization’ (UNIDO, : ), which was cast as a ‘new hurdle’ (UNIDO, : ) for the least developed countries. Four years later, UNIDO (: ) averred, ‘While globalization and trade liberalization offer undeniable opportunities . . . they also expose markets to rapid changes in technologies, consumer preferences, and the pressures of competition.’ The first storyline shows how narratives of globalization evolve and expand. Initially schematic frames become more multifaceted. Narratives of globalization spread globally but are also localized and modified to fit specific national and regional conditions and concerns.¹⁰ This evolution across multiple scales of policymaking is central to comprehending the second storyline emerging from the data.

.. Regionalization as a Process that can Refract Global Neo-liberalism The second storyline spotlights the promises of globalization as a crucial element in regional integration. Let us again illustrate with a statement by Chinese President Xi: We need to achieve a coordinated development of Asian countries . . . This will help bring down the logistic costs, create demand and employment, give play to our comparative and latecomer advantages, secure favourable position [sic] in the global supply chain, industrial chain, and value chain, raise our comprehensive competitiveness, and usher in a new situation in Asian development. (People’s Republic of China [PRC], )

This regional focus on Asia by the region’s largest economic power parallels the South African minister of trade and industry’s reframing globalization as African ⁹ We have avoided terms such as ‘success’ and ‘failure’ that recur in the literature on industrial policy, for they are normative and reflect sociopolitical hierarchies. ¹⁰ Almost three years after the global financial meltdown, former Argentinean President Cristina Kirchner pointed to the economic potential inherent in national industrialization amid contemporary forces of globalization. In a speech to industrialists, she said: ‘Today I see globalization, which for years looked like a threat to me, as an immense opportunity for the Argentinean Republic’ (Casa Rosada, ). Despite her government’s persistent nationalistic policies at the time, Kirchner hence felt it opportune to reverse her previously protectionist rhetoric.

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    



regionalization. Arguing that South Africa had ‘been supporting the industrialization of the African continent’ (Chatham House, ) and reflecting his government’s pursuit of a ‘broader-based industrialization [to] enhance[e] the participation of historically disadvantaged people and marginalized regions in the mainstream of the industrial economy’ (Government of India, : ), he underlined that South Africa’s government ‘want[ed] to see the development of value chains on a regional basis’ (Chatham House, ; see also Africa Report, ). Brazilian Vice President Mourão made similar claims concerning the role of Brazil in Latin America when he stated: ‘Our region wants a better place on the great geopolitical chessboard of globalization and global value chains’ (Wilson Center, ). Another facet of this second storyline is BRICS members states’ persistent emphasis on inter-regional integration. An early example is the  Sanya Declaration issued at the third BRICS Summit, which pledged to ‘support infrastructure development in Africa and its industrialization within framework [sic] of the New Partnership for Africa’s Development (NEPAD)’ (BRICS, : ). Two years later, the fifth BRICS Summit ‘took place under the overarching theme, “BRICS and Africa: Partnership for Development, Integration and Industrialisation”’(BRICS, : ). In addition, both summits adopted resolutions ‘to increase . . . engagement and cooperation with nonBRICS countries’ (BRICS, : ). This commitment has been reiterated consistently (e.g. BRICS, b). Extending the storyline to the nongovernmental realm, a statement from the  BRICS Business Forum reinforced the regional focus on Africa ‘in order to contribute to its development and to expand trade links between Africa and BRICS’ (noted in DTI, : ). BRICS Business Council chairman Onkar Kanwar complemented the emphasis on African infrastructure development by demanding joint BRICS economic zones (Kanwar, ) and greater ‘intra-BRICS trade using local currencies’ (Kanwar, ). And in , a joint statement by the council reaffirmed this commitment by promoting the ‘development of inter-regional business ties’ (BRICS Business Council, : ). This practical emphasis on the modalities of regional as well as inter-regional integration stands in contrast to the final storyline emanating from the data: namely, the importance of digital technologies for industrial development in the global South amid a continuing dearth of actionable strategies.

.. Digital Industrialization: Distant Promise or Catalyst of Inequality? The articulation of the third storyline hinges on what some have termed the Fourth Industrial Revolution (IR) and its implications for the global South.¹¹ In this ¹¹ Introduced in  as ‘Industrie .’ to enhance competitiveness in manufacturing, the German federal government incorporated this parlance in its High-Tech Strategy for  and empanelled a working group to advise on specific policies to implement the plan.

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

 .    . 

connection, Klaus Schwab, the founder and executive chairman of the WEF, maintains that the evolution of globalization and the genesis of IR are interrelated. He holds that the first industrial revolution brought steam trains, steamships, and the industrialization of weaving and mining; the second, the modern assembly line, the automobile, and the airplane; and the third, the computer and early digitalization. The fourth is marked by artificial intelligence (AI), autonomous vehicles, and the Internet of things: the integration of multiple technologies into one whole system (Schwab, , ). BRICS leaders have embraced the IR narrative. For instance, the  Fortaleza Declaration capping the BRICS’ sixth Summit stated: ‘We believe that ICTs [information and communications technologies] should provide instruments to foster sustainable economic progress and social inclusion’ (BRICS, : ). At a  regional WEF meeting, Chinese Premier Li Keqiang argued: ‘The advent of a new round of technological and industrial revolution has provided a historical opportunity for . . . the upgrading of traditional industries’ (PRC, ). And one year later, President Xi () reiterated this narrative in his remarks at the annual meeting in Davos, urging world leaders to ‘seize opportunities presented by the new round of industrial revolution and digital economy’. Echoing the Fortaleza Declaration, Indian Prime Minister Modi expounded at the  WEF meeting: ‘Technology and digital revolution increases [sic] the likelihood of . . . new solutions, which could help us to tackle the old problems of poverty and unemployment in a new manner.’ So, too, the Russian Federation’s minister of trade and industry referred to the present era as ‘a time when manufacturing must adapt to the demands and the opportunities created by the Fourth Industrial Revolution’ (Roscongress Foundation, ). Along these lines, the WEF’s Centre for the Fourth Industrial Revolution Network pursues a mission to hone governance frameworks and protocols and has started to work on projects in various domains, such as in AI and machine learning (WEF, : ). However, in the data analysed in this chapter, assertions about the potential of digitalization for the global South remain largely hypothetical. True, mutual gains seem likely when, for instance, South Korea and Singapore join forces to facilitate product development and marketization for start-ups (Korea.net, ). Yet, how national governments lacking influence on the world stage and in countries with weak links to global value chains are to engage digitalization is an open question, one acknowledged in the global South. Addressing this issue at a BRICS Business Council meeting in , South Africa’s minister of international relations and cooperation recognized ‘the challenges arising from the Fourth Industrial Revolution’ (Sisulu, ). Remarkably, a  UNIDO report was the only document in our database that presented a discordant view: namely, that new technologies are no panacea for industrial development, for they have ‘often failed to translate into concrete growth opportunities’ (UNIDO, : ). But what can governments of industrializing countries do to level the IR playing field? A joint initiative by the Indian and South African delegations to the WTO is emblematic of future opportunities as well as current limitations. Acting on their shared position that ‘[t]ariffs are instruments of industrial policy and have implications

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    



for capital accumulation, technological change, productivity growth, and employment’ (Government of India, : ) and citing a UN study on the implications of growing global trade in e-commerce (UNCTAD, ), the two delegations advocated an end to the WTO’s  moratorium on imposing customs duties on electronic transmissions in order to render the latter a source of domestic revenues (WTO, ). Urging the global regulatory body ‘to understand the ruinous impact of digitization on SMEs [small and medium-sized enterprises] in developing countries and LDCs [least developed countries]’ (WTO, : n.p.), the two signatories argued: The moratorium will negatively impact the efforts of many developing countries, which are laggards as far as digital industrialization is concerned, to industrialize digitally. It could also undermine existing industries. Tariffs play an important role in protecting infant domestic industries from more established overseas competitors until they have attained competitiveness and economies of scale. (WTO, : n.p.)

The joint memo concludes that ‘for designing such policies [to protect infant digital industries], it is extremely important for developing countries to preserve policy and regulatory space in the WTO’ (WTO, : n.p.). Like statements in favour of selective protectionism that exemplify the first storyline’s ongoing evolution, such calls for industry-specific protectionism are at odds with the neo-liberal vision of IR as a global process unfolding preferably without significant regulatory constraints. On the one hand, they show that some governments in the global South value the potential of digitalized trade and of industries for building technological scaffolding. On the other hand, they clearly recognize that unregulated global digital industrialization is unlikely to foster economic growth and welfare in countries where entrepreneurial capital has often been restrained, requisite infrastructure is still nascent, and productivity, whether digital or analogue, is held back by limited knowledge transfers. Taken together, the three storylines provide a wide range of examples of how the narratives of hyper-globalization and de-globalization are adopted and used, but also supplanted and challenged. In this chapter’s final section, section ., we interpret the emphases and silences apparent in the data and, on this basis, sketch opportunities for industrial policymaking in the global South. We also offer suggestions for how to expand the evidentiary support for these openings and, in a preliminary manner, provide a multipronged research agenda.

. N S

.................................................................................................................................. One of the otiose stories is about the ‘flying geese’ model, introduced by Kaname Akamatsu () in the s in Japanese and first appearing in an English-language publication in . This catchphrase depicts followers in formation, pursuing the pattern set by lead countries, enabling the others to ascend the hierarchy of

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

 .    . 

industrialization. The metaphor is used to describe the IDL in the Pacific region, where the United States was a lead country; Japan is said to have played catch-up, and other Asian countries have fallen in line. But one must take cognizance of how structural constraints operate. The crux of the matter is that neo-liberal globalization typically reduces national policy space and detaches economic reforms from social policy.¹² In the changing GDLP, policymakers can ill afford to be swayed by the familiar story of boosting manufacturing by relying on externally driven growth and creating agglomeration economies. This agenda is derived from the Cold War era, with the clustering of production in East Asia during the first wave of late industrialization. The contemporary context is far different. Strategic thinking must come to grips with vast Chinese investment in manufacturing (see Oqubay and Lin, ). Rising costs of skilled labour in China are precipitating continuous restructuring in manufacturing and shifts in global commodity chains, resulting in the redistribution of industrial employment and redeployment to new export destinations. At present, transitions from industrial to digital economies, thus far limited in the global South, along with more advanced knowledge inputs, appear to be impelling a parametric transformation in the global economy. While a few middle-income countries are preparing to benefit from digitalization, many are not. For some of them—among others, Malaysia—preparation involves studies, even blueprints, with little actual implementation. But the implications in terms of training and bringing skills and capital from their diasporas are stark. Another central question is how low- and middle-income countries can take part in this global transformation without being relegated to the role of its clients: takers rather than makers in the GDLP. For these countries, foregoing the potential of recalibrating their positions in the global political economy, with reduced transaction costs, market expansion, and technological learning and upgrading, represents an opportunity loss. Yet, without extolling the virtues of digitalization, as do vogue iterations of the hyperglobalist narrative, it would be wrong to underestimate the skewed structures of participation. By now, policymakers should be crafting new strategies for more fully engaging the knowledge structure to meet the challenges of digital industrialization. Phenomena such as industrial robots in manufacturing and the concentration of control of digital data under the auspices of a handful of big tech firms, the world’s largest ones headquartered in the United States, are patent. With the exchange of scientific and technological information, big tech companies based in the global North withhold know-how, especially with digital industries that are developing algorithms and AI. Obfuscation employed by these firms to protect their trade secrets takes the ¹² Along these lines, Osvaldo Sunkel and Michael Mortimore () contend that the flying-geese model does not obtain in the manufacturing sector in Latin America, where no single country has taken the lead and where TNCs and foreign direct investment have not fulfilled a developmental role. Rather than flying geese, countries in this region have been, in Sunkel and Mortimore’s words, ‘sitting ducks’.

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    



form of abstruse language, euphemisms, corporate jargon, and esoteric acronyms. In the United States and some other countries, trade law, with its many loopholes and carve-outs (e.g. for intellectual property), buttresses the use of secrecy in many kinds of disputes and reinforces barriers to entry. And in the name of national security, governments seek to deny access to information about their technological operations so that actors with whom they have adversarial relations cannot acquire it. Faced with this challenge, certain countries are trying to secure a measure of control, Rwanda among them; they have designed national policies for building digital skills and exercising sovereign rights over the flow of their national data. A reason why some actors and not others are making strides lies in the particularity of their domestic political and transnational economic coalitions. The knowledge community could make an important contribution to achieving this objective. However, the narratives and the data scrutinized above say little about this community’s role in industrialization. The only exception in our dataset was the  Fortaleza Declaration, which affirms the BRICS’ commitment to ‘working together with the ICT industry, civil society, and academia in order to realize the ICT-related potential opportunities and benefits for all’ (BRICS, : ). Although universitybased research and training can be vital resources for industrialization strategies, the linkages between knowledge production in the global South and industry are generally weak. Rodrigo Arocena, a professor of mathematics and former vice-chancellor of the University of the Republic of Uruguay, and his co-authors drive this point home, calling for the relationship to be strengthened (Arocena and Sutz, ; Arocena, Göransson, and Sutz, ). These ties offer possible gains in advanced knowledge and, beyond copycat technologies, perhaps breakthrough technologies. As emphasized above, national variation is evident. In some cases, the quality of higher education, research institutes in particular, is such that cooperation with domestic industries can bear fruit only if it is highly selective and actively nurtured by governments’ strategic investments. Realizing the potential of industry‒university collaborations (IUCs) in the global South therefore requires clearing hurdles that add to a list of related challenges arising from IUCs in the global North (Rybnicek and Königsgruber, ). Moreover, spending on research and development as a proportion of gross domestic product in the global South is well below the levels of domestic resource mobilization in most developed countries. In keeping with the neo-liberal trend in the global North, basic research, which is the basis of applied work and can catalyse innovations, is typically assigned low priority (Arocena and Sutz, : , ; Mittelman, ). Practical results and immediate pay-off have taken precedence. Also, external transfers of technology from sellers or donors to receivers of imported knowledge often become more a one-way process than a two-way street. Surely fundamental and applied research can be rendered complementary rather than compartmentalized. The knowers and doers can work together or be one and the same. In this effort, the knowers would strive to better understand the mechanisms of translating narratives of industrialization into policy, and the doers’ job is to use this

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

 .    . 

understanding to improve practice. Their mutual goal is to enable local actors to be makers rather than takers of industrial policies so as to achieve societal well-being. On this route, attempts to align knowledge production and a high level of training to meet the challenges of industrial globalization are often hobbled by mistrust of the international experts whose agencies sponsor development projects and the local officials who try to steer them. This suspicion is not irrational fear. It is based on experience: a combination of pronounced inefficiencies, endemic corruption, and class antagonism reflecting changing power relations between capital and labour. In this sense, industrial policies can run aground on ‘technologies of power’ (Foucault, : ). In order to arrive at a sober assessment of the prospects for realignment, it is important to note that knowledge institutions themselves, universities in particular, are beset with a plethora of problems. Some of them are structural. These include demographic trends, with a growing population of the young in the global South seeking higher learning; reductions in state spending per student with few exceptions, mainly in Asia; and lack of qualified staff equipped with PhDs. Added to this are matters of political and economic governance: an increase in executive power and the decline of collegial decision-making within the academy; mounting costs of maintaining and operating higher education institutions; and pressure from the public and politicians for enhanced performance (Mittelman, ). From the vantage point of industry, universities are prone to scholasticism. Universities are seen as being preoccupied with broad philosophical debates, arcane subjects, abstract theorizing with little relevance to the down-to-earth needs of the industrial sector, and their own inbred protocols: the habitus of the academic trade. The application of Bourdieu’s concept of habitus to this dimension of industrial policy lends perspective to persistent reservations about closing the gap between industrialists and university-based scholars, and helps explain why many opportunities for realigning knowledge communities and industry are not pursued. That said, industry and the academy should be reminded to proceed by respecting one another’s distinctive missions. And if the goal is to serve mutual interests so as to meet the needs of the local population in an equitable manner, an antidote to the distance between industry and higher education is to introduce tangible incentives for collaboration between them. Government authorities could allocate funds to institutions partly on the basis of what in the Nordic countries is known as the ‘third mission’—knowledge transfer and societal service. True, increasing incentives comes with a cost and requires money. Yet mobilizing revenue to invest in this kind of innovation is likely to have a substantial pay-off. But to what end? It is not that a gap separates competitors in a race for an imagined finish line. The so-called laggards are not in a race of their own making. The challenge is to design home-grown industrialization strategies, not to import or download them from standard global scripts. The goal ought to be increasing autonomy. This calls for capturing a larger share of control over globalization and thereby repositioning in the GDLP (Mittelman and Norani Othman, ). Implementation hinges on not only resources but resourcefulness. It entails not only inventions but inventiveness.

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    



More specifically, the three evolved storylines outlined above point to narrative traps as well as opportunities for policymakers in the global South. Putting aside whether the representations of industrial strategies plotted in prior decades were apt when they were conceived, the operative consideration now is that customary forms of industrialization in the global South, along with the older narratives that portray them, are historically and theoretically interesting, yet outmoded. The current conjuncture in the world economy is marked by transformations in capitalism. Among them, the decline of manufacturing relative to service industries and a shift from industrial capitalism to digital capitalism are prominent.

. L S  P S

.................................................................................................................................. In our times, the first storyline suggests that national policymakers ought to continue eschewing protectionist language in the global arena. But this does not mean that selective industry protection is politically unfeasible. In fact, subtle narrative modifications in response to regional hegemons’ pivot towards protectionism provide an opportunity for national actors to derive lessons from historical cases of industrial policy. The task is to consider locally and regionally workable approaches to industrial midwifery by which domestic industries are selectively nurtured and shielded internationally during their initial stages of growth. Economic powers other than the United States and China have already adapted their industrial policies accordingly, albeit with a focus on the latter component of economic midwifery. For instance, India’s unfolding industrial policy enacts Prime Minister Modi’s stance on protecting the domestic economy from global pressures. And his government’s collaboration with South Africa to mobilize state revenues from digital commerce signifies that India is not alone in this protectionist push. Although policymakers in countries at the bottom of the GDLP may have less room for manoeuvre, the global tide for strategic protection is indeed rising. Another promising move is to reclaim policy space by leveraging the second storyline, that is, globalization-as-regionalization, both on the intra-regional and inter-regional levels. The idea is to replace the logic of catch-up with more flexible scenarios of regional and inter-regional integration. Conceivably, the fragmentation of the global economic system may lessen international pressure on industrializing countries to comply with global norms. The example of India and South Africa jointly arguing their case against the extension of the WTO’s e-commerce moratorium is emblematic of this power shift. In this case, new tactical alliances among industrializing countries appear more viable than heretofore. But one more word of caution: promoting regionalism carries different pay-offs for the BRICS than for small, landlocked states. An empirical focus on the BRICS member

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

 .    . 

states leaves out the latter. Future research could complement our country cases by integrating data-enabling analyses of how national governments forging industrial policy in the proximity of the BRICS have framed globalization and, on this basis, assess prospects for regionalism. Next, an extension of this research could home in on multilateral organizations whose missions are to promote regional development: among them, the InterAmerican, African, and Asian Development Banks and the UN Department of Economic and Social Affairs’ regional commissions. More granular tracing of the evolution of narratives within the compass of international institutions and national governments could yield deep insights into the incentives and disincentives shaping the formation of globalization narratives as they bear on industrial policy. Third, inquiry should extend beyond elite discourses so that it encompasses those of the most vulnerable subjects of narrative power. A bottom-up perspective would round out what we have attempted in this chapter. Narratives from below are complementary to our analysis, especially with changes in industrial relations. Studies at the micro level would be particularly useful in this regard. Fourth, while undertaking micro studies, there should be no mistaking the macro issue concerning the parameters in which industrial policy is being forged. In the interregnum in which we find ourselves, industrial capitalism is rapidly losing ground to a new form of capitalism, only hinted at but not elaborated above. Digitalization and knowledge work are gaining sway at the expense of prior generations of technology and wage labour. The implications for industrial policy in the context of development have yet to be drawn in any systematic manner. As intimated, in an attempt to adapt during this transitional period, discourse brokers in government and at the WEF are promoting IR and have disseminated a spate of reports, white papers, and articles on the implications of IR for corporations, technology, governance, and academia (Kagermann et al., ; Drath and Horch, ; Brettel et al., : ; Cotteleer and Sniderman, ). The extent to which the IR business model and its asymmetries (see Morgan, ; Andreoni, Chapter , this volume) create a false narrative about a global win‒win scenario while widening the divide between the world’s datarich and data-poor populations gives pause. The Davos  Manifesto clearly calls for a new social narrative in response to the now widespread recognition of economic globalization’s pernicious effects on inequality. It would seem that IR affords an opportunity to shape this narrative in order to influence policy. For policymakers in the global South as much as for nongovernmental activists globally, this is the time to challenge technological solutionism by subjecting the narrative to more critical scrutiny. If executed in a constructive, thoroughgoing way, this effort could help mitigate socio-economic polarization both within and among countries and world regions. Finally, the point that warrants emphasis is that for countries at the low end of the GDLP, achieving fruitful policies requires striving for homemade approaches to industrialization by strategically seizing shifts in globalization narratives and resulting policy openings. Contextualized combinations of the steps proposed above—industrial

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    



midwifery enlisting the knowledge community, prioritizing basic as well as applied research, mustering resources for incentivizing knowledge transfers and societal service, and orienting training programmes to foster capacities for resourcefulness and inventiveness—can optimize the prospects for industrialization. Each country must forge its own path. It is our hope that deliberations over country-specific permutations of this portfolio will spur development through sound industrial policies amid globalizing forces.

A For valuable research assistance, we are indebted to Ji Young Kwon and Luciana StorelliCastro. Thanks, too, to the reviewers, especially Peter Lawrence, of a preliminary version of this chapter.

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    



Feenstra, Robert C., Robert Inklaar, and Marcel P. Timmer () ‘The Next Generation of the Penn World Table’, American Economic Review (): –. Foucault, Michel () The Foucault Reader, edited by Paul Rabinow. New York, NY: Pantheon. Freedom House () Freedom in the World . Washington, DC: Freedom House. Available at https://freedomhouse.org/report/freedom-world/freedom-world-. Fröbel, Folker, Jürgen Heinrichs, and Otto Kreye () The New International Division of Labour: Structural Unemployment in Industrialised Countries and Industrialisation in Developing Countries. Cambridge: Cambridge University Press. Government of India () The BRICS Report: A Study of Brazil, Russia, India, China, and South Africa with Special Focus on Synergies and Complementarities. New Delhi: Oxford University Press. Government of India () ‘Prime Minister’s Statement on the Subject “Creating a Shared Future in a Fractured Word [sic]” in the World Economic Forum’. Delhi: Government of India,  January. Available at https://mea.gov.in/Speeches-Statements.htm?dtl%F %FPrime_Ministers_Statement_on_the_subject_Creating_a_Shared_Future_in_a_ Fractured_Word_in_the_World_Economic_Forum_January__. Gramsci, Antonio () Selections from the Prison Notebooks, translated and edited by Quintin Hoare and Geoffrey Nowell Smith. London: Lawrence and Wishart. Gygli, Savina, Florian Haelg, Niklas Potrafke, and Jan-Egbert Sturm () ‘The KOF Globalisation Index–Revisited’, Review of International Organizations (published online). Available at https://doi.org/./s---. Held, David, Anthony G. McGrew, David Golblatt, and Jonathan Perraton () Global Transformations: Politics, Economics, and Culture. Stanford, CA: Stanford University Press. Hirschman, Albert O. () The Strategy of Economic Development. New Haven, CT: Yale University Press. Hirschman, Albert O. () A Bias for Hope. New Haven, CT: Yale University Press. Hirschman, Albert O. ([] ) Essays in Trespassing: Economics to Politics and Beyond. Cambridge: Cambridge University Press. Jomo, Kwame Sundaram and Anis Chowdry () ‘Developing Countries Losing out to Digital Giants’. Inter Press Service,  October. Available at http://www.ipsnews.net// /developing-countries-losing-digital-giants/. Kagermann, Henning, Wolfgang Wahlster, and Johannes Helbig () ‘Recommendations for Implementing the Strategic Initiative INDUSTRIE .–Securing the Future of German Manufacturing Industry’. Final Report of the Industrie . Working Group. Forschungsunion. Munich: National Academy of Science and Engineering. Kanwar, Onkar S. () ‘Bridging Gaps with BRICS’, The Financial Express, Noida, Uttar Pradesh,  September. Kanwar, Onkar S. () ‘BRICS Must Score a Goal in Fortaleza’, Hindustan Times, New Delhi,  July. KOF Swiss Economic Institute (a) KOF Globalisation Index. Eidgenössische Technische Hochschule Zürich. Available at https://www.kof.ethz.ch/en/forecasts-and-indicators/ indicators/kof-globalisation-index.html. KOF Swiss Economic Institute (b) ‘KOF Globalisation Index: Globalisation Lull Continues’. Press release,  December. Available at https://www.kof.ethz.ch/en/news-andevents/media/press-releases///kof-globalisation-index-globalisation-lull-continues. html.

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 .    . 

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    



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 .    . 

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        ......................................................................................................................

              ,                ,   

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    

. I

.................................................................................................................................. T--century policymaking is increasingly defined by the need to respond to major social, environmental, and economic challenges. Sometimes referred to as ‘grand challenges’, these include threats like climate change, demographic, health, and wellbeing concerns, as well as the difficulties of generating sustainable and inclusive growth. Against this background, policymakers are increasingly embracing the idea of using industrial and innovation policy to tackle these ‘grand challenges’. Examples of challenge-led policy frameworks include the United Nation’s Sustainable Development Goals (SDGs; Borrás, ), the European Union’s Horizon Europe research and development programme (Mazzucato, a), and the UK’s  Industrial Strategy White Paper (HM Government, ). Challenge-driven policy frameworks are emerging in parallel to well-established modernization¹ and competitiveness² frameworks. While modernization, and in particular competitiveness frameworks, rely on the idea that government should first and foremost fix market failures,³ a challenge-driven agenda does not have such clearly defined theoretical origins and analytical lenses. As Richard Nelson argued in  in his seminal book The Moon and the Ghetto, getting man to the moon and back is not

¹ See, for instance, the Blair government’s ‘Modernising Government’ White Paper from , https://www.civilservant.org.uk/library/_modernising_government.pdf. ² The EU’s Lisbon Strategy from  is perhaps the best-known example of this, see https://portal. cor.europa.eu/europe/Profiles/Pages/TheLisbonStrategyinshort.aspx. ³ On competitiveness, see Reinert ().

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

    

the same as solving the problem of ghettos in American cities. Put differently, the nature of our knowledge about socio-economic challenges differs from our perception of strictly technical challenges. We can discover answers to technical puzzles; socioeconomic issues do not have a single correct discoverable solution. Such issues require continuous discussion, experimentation, and learning. We believe challenge-led growth requires a new conceptual and analytical framework that has at its core the idea of confronting the direction of growth with growth that is, for example, more inclusive and sustainable. Such a framework should focus on market shaping and market co-creating (Mazzucato, ). This is a question of both theory and policy practice. In theory, challenge-driven innovation policy questions both established neoclassical and evolutionary concepts (Schot and Steinmueller, ). In policy practice, directed policies require rethinking what is meant by ‘vertical policies’. Industrial policies have always been composed of both a horizontal and a vertical element. Horizontal policies have historically been focused on skills, infrastructure, and education, while vertical policies have focused on sectors like transport, health, energy, or technologies. These two traditional approaches roughly embody differing schools of economics: neoclassical economics-inspired horizontal policies focusing on supplyside factors and inputs; and evolutionary economics-inspired policies putting emphasis on demand-side factors and systemic interactions (Nelson and Winter, ; Hausmann and Rodrik,  for a synthesis). Although certain sectors might be more suited to sector-specific vertical strategies, the ‘grand challenges’ expressed in SDGs are cross-sectoral by nature and hence we cannot simply apply a vertical approach to them. Both neoclassical and evolutionary approaches to industrial policy have relied on the idea that the best policy outcome is economy-wide development, without specifying its nature. In policy this has led to managing economies according to GDP growth rates, competitiveness indices and rankings, or other macro indicators (e.g. exports, patents) (Drechsler, ). Yet, many SDGs are only indirectly related to the economy and hence many of the key issues around SDGs have not been theorized in the context of innovation and industrial policy (see, e.g. Zehavi and Breznitz, ). In this chapter we argue that through well-defined goals, or more specifically ‘missions’, that are focused on solving important societal challenges, policymakers have the opportunity to determine the direction of growth by making strategic investments, coordinating actions across many different sectors, and nurturing new industrial landscapes that the private sector can develop further (Mazzucato, ; Mazzucato and Penna, ). The result would be an increase in cross-sectoral learning and macroeconomic stability. This ‘mission-oriented’ approach to industrial policy is not about top-down planning by an overbearing state; it is about providing a direction for growth, increasing business expectations about future growth areas, and catalysing activity—self-discovery by firms (Hausmann and Rodrik, )—that otherwise would not happen (Mazzucato and Pérez, ). It is not about de-risking and levelling the playing field, nor about supporting more competitive sectors over less (Aghion et al., ), since the market does not always know best, but about tilting the playing field in

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 ,  ,   



the direction of the desired societal goals, such as the SDGs. However, we argue, to achieve this requires a new analytical framework based on the idea of public value and a policymaking framework aimed at shaping markets in addition to fixing various existing failures. Indeed, we argue that if we want to take grand challenges such as the SDGs seriously as policy goals, market shaping should become the overarching approach followed in various policy fields.

. F M F  M S

.................................................................................................................................. The dominant approach to public policy is derived from neoclassical economic theory, in particular microeconomic theory and welfare economics.⁴ This approach emphasizes the idea that, given certain assumptions, individuals pursuing their own selfinterest in competitive markets gives rise to the most efficient outcomes (Samuelson, ; Mas-Colell et al., : ‒). Efficiency is understood in a utilitarian sense, whereby an activity is efficient if it enhances someone’s welfare without making anyone else worse off (so-called Pareto efficiency). Under these conditions, the role of government intervention is in practice often limited to addressing instances where the market is unable to deliver Pareto-efficient outcomes. These ‘market failures’ arise when there are information asymmetries, transaction costs and frictions to smooth exchange, non-competitive markets (e.g. monopolies) or externalities whereby an activity harms another agent not directly connected with the market transaction (e.g. pollution), or coordination and information failures hamper investment (Rodrik, ). In the s, public-choice theory considered how the actions of agents (voters, bureaucrats, politicians) involved in policy could be considered from an economic efficiency perspective, as those agents, including government agents, were assumed to be self-interested (Buchanan and Tullock, ). While in markets the existence of competition and the profit motive tends to enforce efficient decision-making, in collective decision-making processes (i.e. politics and public administration) the same disciplining framework does not exist. Policymaking is thus subject to capture by certain interest groups, in particular those most able to influence policymakers for reasons of power or money. In public administration, the lack of competitive pressures leads to ‘bureau-maximizing’ behaviour, whereby departments and agencies look after their own survival rather than the ‘common good’. Public-choice theory argues that even where there are clear examples of market failure, it is not always the case that government intervention would result in a more efficient outcome. Rather, there could also be ‘government failure’, whereby decisions ⁴ This section builds on Mazzucato and Ryan-Collins ().

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

    

aimed at improving welfare make things even worse than they would have been under conditions of market failure (Le Grand, ). For policymaking processes such an approach creates a bias towards inaction. If the default assumption is that the market will find the best outcome, even if it doesn’t the overriding concern is that government intervention may worsen existing outcomes; the default prescription for government policy is to maintain the status quo. There is a danger that analytical frameworks become focused more on justifying and measuring the non-failure of public policies than on the attainment of wider policy goals. In development theory and practice, the market-failure-based approaches coalesced in the s around the so-called Washington Consensus policies focused on deregulation, opening up domestic markets, and relying on foreign direct investments and exports to drive economic transition and growth (Williamson, ). The Washington Consensus main assumption was that as all development problems are of the same nature, the solutions are bound to be the same as well. This removes the question of directionality of growth away from domestic policymaking and leaves global markets in charge (Kattel et al., ). The market failure perspective also creates a particular orientation towards innovation, industrial policy, and structural economic change.⁵ While certain elements of innovation policy, in particular early-stage R&D, can be considered to be public goods and thus a case for public policy provision can be justified, in the main it is assumed that the private sector is the more efficient innovator, possessing greater entrepreneurial capacity and better able to take risks given the pressure created by competition. In contrast, the state is viewed as risk averse and in danger of creating government failure if it becomes too involved in industrial policy by ‘picking winners’. Its role is to level the playing field for commercial actors—mostly through supply-side inputs such as better skills or the removal of market frictions—and then get out of the way. This has led to rather diverse debates and the development of policy practices aimed at finding ever more precise policy targets through better measurement of failures and of the impact of policies trying to fix those failures. Instead, policy discussions in particular should focus on ‘heterodox’ policy approaches that recognize both market and government imperfections and failures—as well as the fact that it is impossible or even undesirable to attempt to remove all of them at once—and the need for policies that support scale economies, dynamic learning effects, and cross-sectoral spillovers (Rodrik, ).

⁵ Some eminent economists have rejected the market failure justification for policy intervention since the concept that markets by themselves lead to efficient outcomes is dependent on conditions—perfect information, completeness, no transaction costs or frictions—that have never been empirically demonstrated (Coase, ; Stiglitz, ). Rather, markets are always incomplete and imperfect, and hence not ‘constrained Pareto-efficient’, that is, they are never in a situation where a government (a central planner) may not be able to improve upon a decentralized market outcome, even if that outcome is inefficient (Greenwald and Stiglitz, ).

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 ,  ,   



In order to expand such heterodox notions to grand challenges, we need a positive theory of public value that begins with a notion of the public good not as a correction to a failure, but as an objective in itself—an objective that can only come about if linked to a process through which value is created. In this sense a new building block is needed to guide and legitimize public policy. As indicated by Kenneth Arrow (), while a market failure approach can be utilized to understand why, for example, private firms underinvest in R&D, it is not so useful for guiding public investment in R&D, because of the inherent uncertainty involved in the outcomes of such investment. Indeed, Arrow called for alternative approaches to analysing public investment and policies for innovation. Critically, the market-failure justification implies that pure private markets/private goods can exist independently of public or collective action. While the role of institutions is admitted (North, ), the role of different voices coming together to form the notion of the public itself is left mainly to sociology, not economics. Nelson notes that ‘there is no satisfactory normative theory regarding the appropriate roles of government in a mixed economy’ (: ) and no theory that captures the complex variety of institutional arrangements that people have developed to solve collective problems. Just as pure public goods are rare, so too are pure private goods. Babysitters or sharing everyday appliances such as lawnmowers involves no government intervention or regulations, but does involve collective or ‘public’ negotiation. Hence the ‘market failure’ dichotomy is not particularly useful. We propose an alternative approach, which begins with the notion of public value as collectively generated by a range of stakeholders including the market, the state, and civil society. Key here is the emphasis on value creation at the core: not ‘public’ value but value itself—with a clear delineation of the role of the different actors that are central to its formation. While in economics value is, in essence, created inside businesses and only facilitated by the public sector, in this view value is co-created and requires a stakeholder understanding of capitalism itself. This view draws on the work of Elinor Ostrom (), who shows that a radical state/private division is, to use her word, barren. In developed economies there are many types of organizations. Nonpartisan government regulators, state-funded universities, and state-run research projects, for example, are quite different. Besides, the crude binary state/private division fails to capture the many ways in which all institutions create and destroy value. In addition, Ostrom’s () emphasis on pooled common resources and her interest in shaping systems so that they take into account collective behaviour, can help shape new policy tools. This more collective view also benefits from a different understanding of the market itself, with the market as an outcome of the interactions of individuals, firms, and the state, as discussed in the work of Karl Polanyi (), and ‘embedded economies’, as discussed by Granovetter (). If value is created collectively, a first question becomes: what capabilities, resources, and capacities are needed for this value to be created inside all the different organizations, including those in the public sector, private sector, and civil society? In the same way that a theory of private value creation

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

    

benefits from a resource-based theory of the firm (Penrose, ), so does a publicvalue notion. Indeed, it is by sidelining the notion of value as only created in business and facilitated or redistributed by the public sector that the question of capabilities is missed. The work by Teece () on the dynamic capabilities of the firm becomes equally necessary for the public sector, as we have argued elsewhere (Kattel and Mazzucato, ). A collective theory of value creation requires understanding by all actors of investment and production capacity. Indeed, as discussed by Mazzucato and Sekera (), a theory of public value needs to also understand the productive capacity and capabilities of the state. And if the state loses that capacity it will lose its absorptive capacity—and hence be unable to understand technological and market opportunities (Cohen and Levinthal, ). Similarly, instruments like taxation are no longer about correcting externalities, but about creation itself. Adam Smith’s notion of the free market was free from rent and this distinction between rent and profits requires tools to incentivize creation, not extraction, of value (Mazzucato, a). Thinkers such as Ricardo, Mill, and even Adam Smith recognized that unfettered markets were often inefficient and prone to capture by special interests, and could have negative distributional outcomes without ongoing intervention by the state. In particular, there was a recognition between productive profits and economic rents that represented unearned income deriving from arbitrary control over resources. These authors argued that the primary role of taxation, for example, rather than internalizing externalities caused by identified market failures, should be to tax away rents accruing from the monopolistic ownership of factors of production, in particular land (Mazzucato, b: ‒; Ryan-Collins, : ‒). In the classical view, rents did not accrue from market ‘imperfections’ as in market failure theory, but from the inherent imbalances in economic and political power that characterized dynamic capitalist economies. Thus, the focus is on the economic and political processes, institutions, and conditions that enable (public) value creation—and equally on how to counter (public) value extraction—across sectors and economies (Mazzucato, a). The role of the state is key here, since it is the only institution with the power to shape markets and direct economic activity in socially desirable directions—or ‘missions’— to achieve publicly accepted outcomes (Mazzucato, , ). Similarly, many government interventions enable markets to function, such as legal codes, public policies, antitrust policies, university scientists, and physical infrastructure (Nelson, : ). Public value should thus be as much concerned with the direction of growth (and the macroeconomic implications) as with the microeconomic structure of government agencies. The question should be how to shape and co-create markets, not just how to correct them. Industrial and innovation policy should be focused both on fixing existing market failures and, equally importantly, on shaping future markets to deliver public value.

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 ,  ,   



. L  H: T E  M- P ..................................................................................................................................

While economists have had difficulties with the normative theory of the role of government in the mixed economy, as noted by Nelson above, governments have at various points in history attempted to implement challenge-driven, mission-oriented policies. This section gives a brief overview of these policies and draws some key lessons for public value-based market-shaping theory and policies.⁶ The idea of mission-oriented policies has its root in the idea of modernization, which of course is not a ‘modern’ idea at all. Even if we are today accustomed to equating modernization with Westernization, what we call the modern state and bureaucracy have arguably Asian and specifically Chinese origins (Fukuyama, ). What matters for our context is the religious-cultural idea of the ‘mandate of heaven’ (particularly applicable in late Imperial China) under which rulers must govern well and provide for the people; non-fulfilment of this ‘mandate’ was a legitimate reason to overthrow the ruler. The counterpart to mandate of heaven in Western culture is the idea of ‘reason of state’, originating with Giovanni Botero’s eponymously titled book from , Della Ragion di Stato—number five on the bestseller list of economics books published before  (E. Reinert et al., ; E. Reinert, ; S. Reinert, )—and justifying policies (Botero explicitly includes economic policies) on the grounds of what today is called ‘national interests’. These two ideas coalesce around developmental states of the late eighteenth and early nineteenth centuries with (proto-)missions of catching up, finding their practical toolbox in Alexander Hamilton’s Report on the Subject of Manufactures in  and their theoretical embodiment in Friedrich List’s Das Nationale System der politischen Oekonomie (). Mandate of heaven and national interest offer ideational backdrops to what can be called a ‘duty to catch up’ as an overarching policy challenge that subsumed under it a variety of policy missions, from building up knowledge base (e.g. reforming universities) to creating trade relations and social policy (the latter is particularly crucial for Bismarck’s Germany, including for the evolution of economics as a science through the debates around the ‘social question’ of the s; see Drechsler, ). The German catching-up story is especially noteworthy, not only for the country’s significant investments in development resulting in impressive actual catching up and, in many instances, forging ahead of England and other industry leaders of the time, but also for a wealth of institutional innovations such as central banks as underwriters of private investment in industry and multiple welfare-state insurance schemes. The first generation of mission-oriented policies, the ‘developmental state’, relied on expert meritocracy in public organizations accompanied, however, by constant renewal ⁶ This section builds on Kattel and Mazzucato ().

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

    

and rejuvenation of organizational configurations (Karo and Kattel, ). As exemplar institutions we can look at what is called System Althoff in German higher education and research policy (named after Friedrich Althoff, a top civil servant in the Prussian Ministry of Culture responsible for hugely successful university reforms; vom Brocke, ), and at MITI (Ministry of International Trade and Industry) in Japan as quintessential development agencies with ‘embedded autonomy’ (Evans, ). While both institutions are often seen as representing Weberian bureaucracy at its finest (with merit-based recruitment and promotion systems and rule-based organization of work), both enjoyed high-level political support but also relied on what can be called wide-ranging charismatic networks, built and nurtured by top civil servants (Karo, ). These policies were wide-ranging, demanding endurance and sacrifice in the name of national catching up and pride, which served as the key sources for normative framing of public value and as the backdrop for mission/priority selection. A version of these policies is also to be found in the Soviet Union and other planning-based policies of the post-Second World War era (Freeman, ; Chandrashekar, ; Chibber, ). Indeed, the latter can be considered an intermediate form between the first and second generations of mission-oriented policies, particularly in their more successful forms such as Commissariat du Plan in France, with its origins in mixed enterprises of the s and its heyday in the s. Schonfield argues that the success of French planning was also pivotal for Kennedy’s ‘un-American’ fervour for setting targets for long-term economic growth (: ‒). The French planning culture, with its focus on achieving a ‘more complete view of man’ (quoted in Schonfield, : ), makes it clear that the point of ‘planning is thus in part an ethical one: it imposes choices about the use of resources other than those which the market would produce’ (Schonfield, : ). The planning exercises were thus driven by an idea of public value and socio-economic challenges. The second generation of mission-oriented policies are the well-known policies and public agencies of the s‒s concerning military and space technologies in the United States and major Western European economies (Ergas, ; Soete and Arundel, ). As Alvin Weinberg, for eighteen years the director at Oak Ridge National Laboratory, which was part of the Manhattan Project, argues, these mission-oriented policies were about ‘big science’ deployed in the ‘national interests’ (Weinberg, : ). Thus, on the one hand, the national interest of the first generation of mission-oriented policies became much more clearly defined through defence and military aims; on the other hand, as we shall see, the translation of these public-value framings into civilian policy areas failed. Organizationally, these policies were often implemented by single national/public laboratories with a concrete mission to solve particular technological problems, not to engage in basic science, which also meant that their facilities were built up more hierarchically than universities (Weinberg, ). Weinberg argues that partly due to accomplishing missions, partly due to pressure from researchers, many of these organizations lost focus on the original missions and moved towards basic research

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 ,  ,   



(Weinberg, : ; see also Nelson et al., : ). Similar problems emerged in the Western European countries where the basic policy assumption was that ‘research results constitute an undirected potential’ (Krupp, : ) and that it was up to the private sector to ‘find’ the direction of innovation. The basic research policies were in reality supplemented by multiple civilian mission-oriented policies in the form of large-scale funding for example, nuclear energy and transportation (magnetic trains, supersonic aviation) (see Gummett, ). This was perhaps the key challenge for the second generation of mission-oriented policies, and specifically, implementing agencies: how to redeploy former military resources around new, civilian missions (Weinberg, : ‒; Nelson et al., : ). While first-generation missionoriented policies—catching-up policies—relied on a wide range of constantly renewed organizations that hired expert civil servants and had strong political support, the second generation of mission-oriented policies had a much more heroic vision of dynamic change. Missions were built around single agencies with high-profile managers in charge of them (Weinberg : ; also Lambright et al., ). This ambition—in terms of both the problems these organizations took on and the scale of investment—brought both massive successes and spillovers (Block and Keller, ; Mazzucato, ), but also played a crucial role in the demise of this generation of mission-oriented policies. As suspected by Weinberg and later documented by Ergas (), many missiondriven research laboratories could not create sensitivity and flexibility around their purpose, particularly when it came to taking up new emerging, less technological and more social, challenges such as pollution and the decay of inner cities (Nelson, ). The seeming lack of success in translating the successes of military R&D and its procurement into the civilian realm also played a significant role in changing policy attitudes (Pavitt and Walker, ). Similarly, planning exercises, the siblings of mission-oriented policies, often did not lead to successful outcomes. As documented by Schonfield (), economic and industrial policy failures in the United Kingdom and elsewhere in the s, particularly in contrast to their successes in France, were due both to low political commitment to long-term planning (not just business-cycle management) and to lack of proper capabilities within planning organizations. The idea was to pick the willing: ‘deliberately selecting a few promising firms who seem willing and able to move ahead fast, and then giving them every encouragement in the form of large contracts, financial help, and other favours’ (Schonfield, : ) and with handpicked membership in modernization commissions (Schonfield, : ). Furthermore, one of the key factors in the demise of mission-oriented policies and industrial planning in Europe was the emergence of the European Economic Community, in which each country had rather different planning styles and capabilities (Schonfield, ). In the late s and s, instead of a common European style of industrial planning and mission-oriented policies emerging, rather a gridlock of plans and missions, and policy cultures remained in place (Schonfield, : ; also ). The results of this could be seen in the fate of the European electronics and semiconductor industries: they could not compete individually with the US companies

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

    

but neither could a European industry emerge as national policy cultures remained dominant (Schonfield, : ‒; Dosi, ). The end of this era saw the emergence of (general-purpose) technology foresight exercises and a search for visions which, particularly in East Asian economies, was accompanied by the idea of leapfrogging international competitors rather than just catching up with them. In essence, mission-oriented policies were slowly replaced by the search for future technologies and preparing economies for their diffusion (Rothwell and Zegveld, ). At the same time, however, the end of the era denotes the emergence of the market-failure-based approach to (innovation) policy that came to dominate the policy arena, along with New Public Management reforms, in the late s, resulting in privatization of public laboratories, the emergence of new armslength funding agencies (such as research councils), a focus on commercializing and marketizing research (for example, with competitive grant systems), and cost-efficiency practices in policy evaluation (Gummett, ; Boden et al., ). This contributed to the demise of the directionality of innovation as a policy agenda, and to the dominance of market-failure-based value framings in innovation and industrial policies. The third generation of mission-oriented policies and organizations, which today is in the ascendant, has multiple drivers and a somewhat heterogeneous set of actors: a) Multilateral organizations such as the European Union have been prominent in urging the development of ‘new’ missions around sustainability and other decidedly socio-economic (as opposed to solely technological) issues (Soete and Arundel, ). b) Large private philanthropies such as the Gates Foundation and others have sought out specific problems (e.g. diseases) to solve and have focused not only their funding but also important networks on those problems as missions. c) Bottom-up social movements have been able to focus the directionality of research, for example, ACT UP’s impact on HIV research and its increased funding (Leadbeater, ). Similarly, Germany’s Energiewende would have never happened without the green movement (Fagerberg, ). In contrast to previous generations of mission-oriented policies, the current manifestation does not have a ‘dominant design’ regarding its public-value framing or its governance system. There is, however, a distinct focus on increasing the social responsiveness of science and innovation. Rather than focusing on a specific sector (such as energy) or technology (such as nuclear), as was often the case in the previous generation, current attempts are characterized by cross-sectoral focus ‘by design’ (Mazzucato, a). Alongside social responsiveness, citizens and social engagement have moved into the arena of mission-oriented policies. Finally, experimentalism is seen as a key feature of mission-driven policies and organizations, which is reflected in randomized controlled trials being embraced by philanthropists and social enterprises at the one extreme, and by service design principles of prototyping within various public agencies at the other. To sum up, we can draw the following lessons from the history of mission-oriented policies. First, there is a taxonomy of missions, from the socio-economic missions of

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 ,  ,   



the first generation to the technological missions of the second, and socio-technological missions of the current (third) generation. Each type of mission-oriented policies implies different public-value framings and capabilities to design, implement, and evaluate missions. The directionality of the innovation systems is engendered by different ideational contexts: first-generation policies were driven by catching up as a national and often also nationalistic mission; second-generation policies were driven by national security needs and the technological arms race; and third-generation policies gain their urgency and purpose from ‘intractable’ socio-economic challenges and social movements connected to these challenges (e.g. various green movements). Second, among factors determining the success or failure of previous generations of mission-oriented innovation policies were investments both in R&D capabilities (e.g. research laboratories) and in market-shaping capabilities (e.g. procurement practices of military organizations). This complementarity within and between mission-oriented policies and other economic policies plays an important role in the success of missions. Third, missions are about setting concrete directions, which of course must be picked, that is, chosen strategically. The choice is not whether or not to pick but how to do so: picking directions is not the same thing as ‘picking winners’, in the sense of picking individual firms or sectors. It is about deciding that a transformation must occur in society—and making it happen. The direction will require different missions, which in itself provides a focus for the different actors and sectors to collaborate. Thus, missions require ‘picking the willing’: those organizations across the economy (in different sectors, including both the public and private sphere) that are willing to engage with a mission relevant to society. Fourth, with the focus on the market-making, rather than the market-fixing, role of missions, it also becomes clear why public investment by mission-oriented institutions has been required along the entire innovation chain, and not just upstream basic research. Better understanding of the distribution of public agencies, their positioning across the innovation chain, and the balance between directive and bottom-up interactions is a key area for future study.

. I M  I P

.................................................................................................................................. In order to instrumentalize public-value-based policy frameworks as industrial and innovation policy tackling grand challenges such as the SDGs, we need, first, to be able to justify the kind of market creation and mission-oriented directionality that was required for innovations such as the Internet and nanotechnology and is now required to address today’s societal challenges (Mazzucato, ). Second, without the state as a lead investor and market creator, failure-based approaches do not provide insights into the type and structure of public-sector organizations needed to provide the depth and breadth of high-risk investments. Third, as long as policy is seen merely as an

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

    

‘intervention’, rather than a key part of the market creation and shaping process, the criteria used to assess public investments will inevitably be problematic. Finally, by not describing the state as a lead risk-taker and investor in this process, failure-based approaches have avoided the key issue of the distribution of risks and rewards between the state and the private sector. Thus, a policy framework for market-shaping activities by the public sector should offer answers to the following questions, for which we have devised the acronym ROAR:⁷ () How can public policy be understood in terms of setting the direction and route of change; that is, shaping and creating markets rather than just fixing them (Routes of directionality)? () How should public organizations be structured so they accommodate the risktaking, explorative capacity, and capabilities needed to envision and manage contemporary challenges (Organizations)? () How can this alternative conceptualization be translated into new dynamic indicators and evaluation tools for public policies, beyond the static microeconomic cost–benefit analysis and macroeconomic appraisal of crowding in/crowding out that stem directly from the market failure perspective (Assessment)? () How can public investments along the innovation chain result in the socialization not only of risks, but also of rewards, enabling smart growth to also be inclusive growth (Risks and rewards)? While the questions may seem broad, it is their potential connections and internal coherence that can help build a market-creation policy framework—and a practical toolkit. Policies that aim to actively create and shape markets require indicators that assess and measure the performance of a policy along that particular transformational objective. The state’s ability and willingness to take risks, embodied in transformational changes, requires an organizational culture and dynamic capabilities that welcome the possibility of failure and experimentation and are rewarded for successes so that failures (which are learning opportunities) can be covered and the next round financed.

. R: R  D—A M- A

.................................................................................................................................. A key success of past market-shaping innovation policies, such as the mission-oriented policies of the Moonshot era, has been setting a clear direction for problems to be ⁷ This section builds on Mazzucato ().

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 ,  ,   



solved (e.g. going to the moon and back in one generation), which then required cross-sectoral investments and multiple bottom-up solutions, some of which inevitably fail. Too much top-down can stifle innovation and too much bottom-up can make it dispersive with little impact. A crucial difference between classical mission-oriented policies of the Cold War era and modern missions is that the latter are focusing on areas such as managing the impact of technological advance and artificial intelligence on the labour market; adapting to changing demographics and an ageing population; or making the transition to a low-carbon economy (European Commission, ; Kattel and Mazzucato, ). Taking up the challenge posed by Richard Nelson in his seminal Moon and the Ghetto (), modern-day mission-oriented policies focus not on technological challenges alone but rather on areas traditionally the responsibility of public services, such as education or the welfare state, and entail changes across various economic and policy sectors. Germany’s Energiewende policy, for instance, aims to combat climate change, phase out nuclear power, improve energy security by substituting renewable sources for imported fossil fuel, and increase energy efficiency. By providing a direction to technical change and growth across different sectors, Energiewende is tilting the playing field in the direction of a desired socio-economic goal. Importantly, it is not just about growing ‘green sectors’—it has required many sectors, including traditional ones such as steel, to transform themselves, and is leading to changes in patterns of production, services, and consumption of energy. In other words, its spillovers are as much technological as social and behavioural (see Fagerberg, , for a discussion). Policies tackling grand challenges should thus be broad enough to engage the public, enable concrete missions, and attract cross-sectoral investment, and remain focused enough to involve industry and achieve measurable success. By setting the direction for a solution, missions do not specify how to achieve success, but rather stimulate the development of a range of different solutions to achieve the objective. In other words, missions guide entrepreneurial self-discovery (Foray, ). As such, a mission can make a significant and concrete contribution to meeting a Sustainable Development Goal (SDG) or grand challenge. The criteria for selecting missions adopted by the European Commission, after widespread stakeholder consultation based on the ‘Missions Report’ (Mazzucato, a), are that they should: • • • • •

be bold and address societal value; have concrete targets: you know when you get there! involve research and innovation: technological readiness over limited time frame; be cross-sectoral, cross-actor, and cross-disciplinary; involve multiple competing solutions and bottom-up experimentation.

To illustrate, take SDG : ‘Conserve and sustainably use the oceans, seas and marine resources for sustainable development.’ This could be broken down into various missions, for example, ‘A plastic-free ocean’ (Figure .). This could stimulate

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

    

Political agenda setting and civic engagement

CLEAN OCEANS

A PLASTIC-FREE OCEAN Clear targeted missions

Reduction of 90% of plastics entering the marine environment and collection of more than half of plastics present in our oceans, seas, and coastal areas by 2025

Cross-sectoral innovation

Chemical industry

Marine life

Portfolio of projects and bottom-up experimentation

Social innovation

Al technology

Autonomous ocean stations to remove plastic pollution

Biotech

Design sector

Re-usable and biodegradable plastic substitutes

Re-use of packing items through personalised collection services

Waste

Plastic and micro plastic digestion mechanism

Image recognition waste separation system for domestic and marine waste

 . A mission-oriented approach to cleaning the oceans Source: Mazzucato (a: ).

research and innovation in methods of clearing plastic waste from oceans or in reducing the use of plastics, innovation in new materials, research on health impacts from micro-plastics, behavioural research and innovation to improve recycling, or drive public engagement in cleaning up beaches. Each of these areas can be broken down into particular ‘projects’.

. O: O C   P S

.................................................................................................................................. A key concern should be to establish skills/resources, capabilities, and structures that can increase the chances that a public organization will be effective, both at learning

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 ,  ,   



and at establishing symbiotic partnerships with the private sector, and will ultimately succeed in implementing mission-oriented and transformative policies. Public and private organizations must re-rethink their roles when working together. Public‒ private partnerships have often limited the public part to de-risking the private part. This ignores the capabilities and challenges involved in public-sector risk-taking. De-risking assumes a conservative strategy that minimizes the risks of picking losing projects, but does not necessarily maximize the probability of picking winners, which requires the adoption of a portfolio approach to public investments (Rodrik, ). In such an approach, the success of a few projects can cover the losses from many projects, and the public organization in question also learns from its loss-making investments (Mazzucato, ). Here, matching failures with fixes is less important than having an institutional structure that ensures that winning policies provide enough rewards to cover the losses, and that losses are used as lessons to improve and renew future policies. One can argue that the community of Schumpeterian scholars never followed up the call by Nelson and Winter () for public policy to be matched by bold new organizational structures in the public sector: ‘The design of a good policy is, to a considerable extent, the design of an organizational structure capable of learning and of adjusting behaviour in response to what is learned’ (: ). Indeed, there is no equivalent in the literature to ‘dynamic capabilities of the firm’ for the public sector. Developmental state research looking at the success of the East Asian Tigers argued that public-sector capacities and capabilities can be best developed by talent, recruited and motivated by Weberian meritocratic recruitment and career management that makes working for government either financially competitive and/or culturally even more rewarding/prestigious than working in the private sector. Evans and Rauch () cemented these ideas through a quantitative analysis that tested the importance of some of the ‘Weberian’ elements (merit-based recruitment and career systems) in a much broader sample of countries as a whole (see also Rauch and Evans, ; Evans, ). This is best captured by Chalmers Johnson and his concept of the developmental state: a country with a predominant policy orientation towards development, supported by a small and inexpensive elite bureaucracy centred around a pilot organization, such as the Ministry of International Trade and Industry (MITI) in Japan, and with sufficient autonomy (limited intervention by the legislature and judiciary) (Johnson, : ‒). What is missing, however, in the Weberian framework of capacities are the evolutionary dynamics: why do specific constellations of capacities become more successful than others? Teece and Pisano define dynamic capabilities of the firm by their evolutionary nature. The term ‘dynamic’ refers to the shifting character of the environment; certain strategic responses are required when time-to-market and timing is critical, the pace of innovation accelerating, and the nature of future competition and markets

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

    

difficult to determine. The term ‘capabilities’ emphasizes the key role of strategic management in appropriately adapting, integrating, and re-configuring internal and external organizational skills, resources, and functional competencies towards a changing environment. (Teece and Pisano, : )

We argue that challenge-driven public policies need to be based on a similarly evolutionary understanding of capabilities in the public sector. We propose that twenty-first-century missions require the following set of dynamic capabilities in the public sector in order to engender mission-oriented policies (Kattel and Mazzucato, ). First, key to our premise is that grand challenges can only be solved through dynamic public‒private partnerships, but these have been constrained by the notion of public actors as, at best, fixing markets. A market-co-creating role requires the state to have capabilities for leadership and engagement: missions can all too quickly become either just fashionable labels on ‘business-as-usual’ practices or too rigid top-down planning exercises. Thus, capabilities to engage with a wide set of social actors and to show leadership through bold vision are vital at a time of high ‘democratic deficit’ in many developed countries (see also ESIR, ). Some of the grand challenges contest ‘the way of life’ as we know it (e.g. suburbanization accompanied by congested transportation systems). Capabilities to encourage bottom-up engagement mean a capacity to set missions but also to leave enough space for contestation and adaptability. Second, on the level of policy, finding coherent policy mixes (instruments and funding) and coordination capabilities is fundamental to the success of today’s mission-oriented policies. As these missions are not just about technological solutions but also have strong socio-political aspects, experimentation capabilities matter perhaps more than before. Equally important are evaluation capabilities that do not simply rely on market-failure-based approaches (e.g. cost‒benefit analysis) but can also integrate user research, social experiments, and system-level reflection (Lindner et al., ; Rip, ). Third, administrative capabilities need to rely on a diversity of expertise and skills from engineering to human-centric design: organizational forms that mix unrelated knowledge areas (e.g. in urban mobility and planning, lifestyles are just as important as new energy storage systems; see Grillitsch et al., ) and organizational fluidity (e.g. cross-departmental teams) seem to be fundamental for managing new missions (OECD, ).

. A: A  E

.................................................................................................................................. One of the key challenges of applying a public value-based framework to policymaking is the relationship between policy assessment, appraisal, and evaluation. Influenced by the market failure framework, today’s dominant evaluation practices are usually based

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 ,  ,   



on allocative efficiency and some form of ex ante cost‒benefit analysis (CBA).⁸ Costs (including the costs of potential government failure) are usually defined by their opportunity cost, that is, the value that reflects the best alternative use a good or service could be put to (include a do-nothing/business-as-usual option), with all else (including all other prices) assumed equal, and with market prices usually the starting point for the analysis (see, e.g. HM Treasury, : ). Post-intervention policy evaluation then seeks to verify whether the estimates were correct and whether the market failure was addressed. To enable market-type price comparison of interventions whose return will vary in terms of time, CBAs typically make use of a ‘discount rate’ that reflects the time preference of users of the service for having money now rather than in the future. After adjusting for inflation and discounting, costs and benefits can be added together to calculate the net present value (NPV) of different policy options. In recognition of the problem of externalities, some attempt has been made in recent years to incorporate the wider costs to society of particular policy actions, for example through monetizing certain social or ecological externalities in a ‘social cost‒benefit analysis’ (SCBA) or ‘social cost-effectiveness analysis’ (SCEA). However, the overall framework remains rooted in the idea that creating a ‘market price’ for interventions will enable the most accurate decision to maximize welfare and public value. CBA and NPV are mostly aimed at preventing costly government failures; by their very nature, they cannot tell us very much at all about proactive market creating and shaping. This limitation is of crucial importance. Market-shaping policies, such as missions, aim to accelerate innovation, creating new technologies and radically changing the prices, availability, and existence of goods and services. Their central purpose is to transform underlying relationships, a wide range of prices and the broader environment (OECD, ). The ‘all else (including prices) being equal’ assumption underlying cost‒benefit analysis becomes problematic in such circumstances. By always comparing the policy intervention with the status quo and emphasizing short-term risks, CBA approaches encourage decision makers to prefer small-scale, marginal interventions (Allas, : ). Yet there is considerable evidence that innovation systems exhibit increasing returns or an S-curve-type effect, in which shifting incentives across multiple sectors may be more likely to achieve such increasing returns (Mazzucato, ). So, arguably, if there is to be any bias around innovation policy it should be in favour of large-scale interventions. Furthermore, the strong emphasis on risk assessment/optimism bias is likely to mitigate against the creation of a mission-oriented approach where failure is viewed as a learning process integral to the achievement of important technological breakthroughs (Mazzucato, ). CBA-type analyses derived from market failure theory are concerned with allocative or distributive efficiency, which involves making the best use of (fixed) resources at a fixed point in time. Dynamic efficiency involves making the best use of resources to

⁸ This section builds on Kattel et al. ().

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

    

achieve changes over time and so is concerned with innovation, investment, improvement, and growth—including, perhaps most importantly, the creation of new resources (technologies) and shifting technology frontiers (Kattel et al., ). Missions are, by definition, concerned with dynamic efficiency, since they aim to accelerate innovation and transformational change. When allocative efficiency frameworks are applied to dynamic efficiency problems, the analysis risks are either irrelevant or actively unhelpful. Aside from considerations of efficiency, given the importance of dynamics over time for market-shaping policies, it is important to define a concrete target and objectives. In other words, it must be possible to say definitively whether the policy has been achieved or not. Technological missions such as putting a man on the moon had obvious end points which made evaluation easier. However, modern grand challenges are more long term and their end points less easy to define.

. R: R  R

.................................................................................................................................. But this raises a more fundamental question: how to make sure that, like private venture capital funds, the state can reap some return from the successes (the upside), in order to cover the inevitable losses (the downside) and finance the next round of investments.⁹ This is especially important given the path-dependent and cumulative nature of innovation. Returns arise slowly; they are negative in the beginning and gradually build up, potentially generating huge rewards after decades of investment. Indeed, companies in areas like ICT, biotechnology, and nanotechnology had to accept many years of zero profits before any returns were in sight. If the collective process of innovation is not properly recognized, the result will be a narrow group of private corporations and investors reaping the full returns of projects which the state helped to initiate and finance. So who gets the reward for innovation? Some economists argue that returns accrue to the public sector through knowledge spillovers (new knowledge that can benefit various areas of the economy), and via the taxation system due to new jobs being generated and taxes being paid by companies benefiting from the investments. But the evolution of the patenting system has made it easier to take out patents on upstream research, meaning that knowledge dissemination can effectively be blocked and spillovers cannot be assumed. The cumulative nature of innovation and the dynamic returns to scale (Nelson and Winter, ) mean that countries stand to gain significantly from being first in the development of new technologies. At the same time the global movement of capital means that the particular country or region funding initial investments in innovation is by no means guaranteed to reap ⁹ This section builds on Mazzucato ().

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 ,  ,   



all the wider economic benefits, such as those relating to employment or taxation. Indeed, corporate taxation has been falling globally, and corporate tax avoidance and evasion rising. Some of the technology companies that have benefited the most from public support, such as Apple and Google, have also been among those accused of using their international operations to avoid paying tax (Johnston, ). Perhaps most importantly, while the spillovers that occur from upstream ‘basic’ investment, such as education and research, should not be thought of as needing to earn a direct return for the state, downstream investments targeted at specific companies and technologies are qualitatively different. Precisely because some investments in firms and technologies will fail, the state should treat these investments as a portfolio, and enable some of the upside success to cover the downside risk. In particular, there is a strong argument to be made that, where technological breakthroughs have occurred as a result of targeted state interventions benefiting specific companies, the state should reap some of the financial rewards over time by retaining ownership of a small proportion of the intellectual property it had a hand in creating. This is not to say that the state should ever have exclusive licence or hold a large enough proportion of the value of an innovation to deter its diffusion (and this is almost never the case). The role of government is not to run commercial enterprises; it is to spark innovation elsewhere. But by owning some of the value it has created, which over time has the potential for significant growth, government can generate funds for reinvestment into new potential innovations. With the adoption of a portfolio approach to public investment in innovation, success from some projects can help cover the losses from others. In this way, both risks and rewards are socialized (Mazzucato, ). There are many examples of public organizations that have strategically considered the distribution of risks and rewards. At times, they have granted licences to private firms willing to invest in upgrading publicly owned technologies, offering the opportunity for public and private sectors to share both risks and rewards. For example, NASA has sometimes captured the returns to its inventions, while private partners gained on the value added in case of successful commercialization (Kempf, ). There are other examples of state-owned venture capital activity generating royalties from public investments (in Israel, see Avnimelech, ) or equity (in Finland via Sitra), and the more pervasive use of equity by state development banks (e.g. in Brazil, China, and Germany; see Mazzucato and Penna, ). Policy instruments for tackling risk/reward issues combine supply- and demandside mechanisms geared to enabling public value creation through symbiotic public‒ private partnerships (‘active’) (Lazonick and Mazzucato, ) and mechanisms blocking value extraction (‘defensive’). Rewards can be distributed either directly through profit sharing (via equity, royalties) or indirectly through conditions attached that focus more on the market-shaping role. The latter may involve conditions on the reinvestment of profits, conditions on pricing, or conditions on the way that knowledge is governed. This list is not meant to be exhaustive, but rather, to illustrate that there are multiple experiences in handling policy instruments that, implicit or explicitly,

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

    

enable consideration of issues like value extraction and allowing government to capture a share of the value it helped to generate. The latter, in particular, have been adopted by different types of agencies, at different stages of the innovation chain but mainly downstream, involving different types of partners (e.g. firm size) and industries. However, they have not always been adjusted to the specificities of different economic, industrial, and legal settings. Absent a framework that more clearly informs these policies, decisions on these matters have sometimes been made unintentionally and haphazardly, inviting both government and systemic failures. The prospect of the state owning a stake in a private corporation may be anathema to many parts of the capitalist world, but given that governments are already investing in the private sector, they may as well earn a return on those investments (something even fiscal conservatives might find attractive). The state need not hold a controlling stake, but it could hold equity in the form of preferred stocks that get priority in receiving dividends. The returns could be used to fund future innovation (Rodrik, ). Politicians and the media have been too quick to criticize public investments when things go wrong, and too slow to reward them when things go right. Thus, more thought should be given, not so much to the problem of ‘picking winners’, as to how to reward the winning investments so they can both cover some of the eventual losses (inevitable in the innovation game) and raise funds for future investments. Going hand in hand with this consideration is the need to rethink how public investments are accounted for in national income accounting. Investments in innovation are different to current expenditure. The latter does not add to balancesheet assets; the former does, and is potentially productive investment in the sense that it creates new value (Mazzucato and Shipman, ). When setting limits to fiscal deficits, it is therefore necessary to distinguish public debt contracted for investment in R&D and infrastructure (value-creating investments) from public debt contracted for (public or private) consumption. In this sense, financial and accounting reforms should be regarded as a prerequisite for any successful smart and inclusive growth plan. Finally, regarding the government as lead risk-taker helps to debunk fundamental assumptions behind the theory of shareholder value that underpins the exorbitant rewards earned by senior executives in recent years. Share options as part of pay packages have been a key feature of modern capitalism, and especially, a key driver of the inequality between the top  per cent of income earners and the rest (Piketty, ). Share options are boosted when share prices rise, and prices often rise through ‘financialized’ practices such as share repurchase schemes by companies (Lazonick, ). Focusing on boosting share prices is justified on the grounds of the theory of shareholder value, which holds that shareholders are the biggest risk takers in a company because they have no guaranteed rate of return (while workers earn set salaries, banks earn set interest rates, etc.). That is, they are the residual claimants (Jensen, ).

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 ,  ,   



But this assumes that other agents do have a guaranteed rate of return. As we have argued throughout this chapter, it is precisely because what the state does is not just facilitate and de-risk the private sector, but also take major risks, that there is no guarantee of success in its investments, which have historically also played a crucial role in enabling wealth creation. The fact that a key driver of inequality has been linked with a problematic understanding of which actors are the greatest risk takers implies that combatting shorttermism and speculative forms of corporate governance requires not only reforming finance and corporate governance, but also rethinking the models of wealth creation upon which they are based (Mazzucato, b).

. C

.................................................................................................................................. Market-shaping, mission-oriented approaches to policy allow us to reconsider how to justify ambitious policies that aim to transform landscapes rather than fix problems in existing ones. This approach to policy raises challenges in terms of how to nurture organizational structures that can manage such policies, and how to appraise and evaluate the market-shaping effect of the policies. This approach would help capture the potential for policy to create spillover effects across many sectors of the economy and alter the level of investment and the broader trajectory of economic growth. What are some of the possible concerns with this type of approach? One concern is around the setting of missions and the direction of the market shaping in the first place. Clearly governments can and do become captured by particular interest groups which limit their ability to both establish missions and follow through on them. The challenges of climate change and inequality are obvious examples. Government subsidies continue to favour vested interests (for example fossil-fuel energy firms), while taxation policy favours labour saving (increasing unemployment or underemployment) over resource saving (supporting decarbonization), despite governments signing up to treaties committing themselves to different policy directions. And, of course, democracy is no guarantee that societal missions such as climate change will be adopted globally, as the current administrations in the United States and Brazil clearly demonstrate. However, arguably, these are the outcomes of governments not doing enough to shape markets to support social and environmental policy goals in the first place. Hopefully the ideas in this chapter can help meet that challenge.

A This chapter is based on our previous work: Mazzucato (a and b), Kattel and Mazzucato (), Mazzucato and Ryan-Collins (), and Mazzucato, Kattel, and RyanCollins (). The research for the article has been partially funded by the Horizon project GROWINPRO, http://www.growinpro.eu.

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        ......................................................................................................................

      .............................................................................................................

  

. I

.................................................................................................................................. N development banks (NDBs) have played a dominant role in the provision of long-run investment, ‘patient’ financing of catch-up in agriculture, industry, and infrastructure in the context of late development (Gerschenkron, ; Amsden, ; De Aghion, ; UNCTAD, ), and in the context of innovation in advanced and emerging economies (Mazzucato, ; Mazzucatto and Penna, , ).¹ For less developed economies, late industrialization entails substantial risks (because many projects are large scale and have long learning and maturation periods) that banks are often unwilling to undertake. Long-term finance requires maturity transformation, which involves a risk that banks usually prefer to avoid (UNCTAD, ). For these reasons, NDBs are designed and mandated to fulfil the role of facilitating risk-taking and learning through the provision of long-run development finance. As Alexander Hamilton noted, in the context of post-colonial United States: ‘capital is wayward and timid in lending itself to new undertakings . . . the State ought to excite the confidence of capitalists who are ever cautious and sagacious, and in doing so, overcome the obstacles that lie in the way of all experiments’ (Alexander Hamilton, ¹ A World Bank survey defines a development bank as ‘a bank or financial institution with at least  per cent state-owned equity that has been given an explicit legal mandate to reach socio-economic goals in a region, sector, or particular market segment’ (De Luna-Martinez and Vicente, : ). A definition that does not require state ownership to be a necessary condition defines ‘development finance institutions’ (DFIs) as ‘legally independent and government-supported financial institutions with explicit official missions to promote public policy objectives’ (Xu et al., : ‒). See also Xu et al. (: , table A) for competing definitions of NDBs.

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  

Report on Manufacturers, ). State-sponsored development banking providing lowcost, long-run credit is thus central to socializing risk and inducing risk-taking and learning (Amsden, ). Due to the lack of private-sector capacity and commitment to financing the inherently risky ventures of late development and innovation, it is thus not surprising to find that NDBs are often the only source of long-run credit in leastdeveloping countries (LDCs), and form one of the main instruments of both vertical and horizontal industrial policy. Surveys of the share of NDBs clearly indicate that they are not things of the past, nor relevant only to low-income contexts. A World Bank survey of NDBs found that  per cent were established during the import-substitution years between  and , nearly one-half ( per cent) came into existence between  and  and  per cent since , periods characterized by increasing globalization and the growing predominance of neo-liberal policy reforms (De Luna-Martinez et al., ). Their presence in the financial system thus remains significant, as they account for  per cent of total banking assets around the world (De Luna-Martinez et al., ).² This suggests that, irrespective of policy orientation or global technological production patterns, policymakers across a diverse set of economies at varying stages of development have found that private financial markets do not deliver adequate long-term finance to support catch-up, innovation, and structural transformation. These patterns contradict notions of a ‘life cycle’ of development banks: the idea that a more active role for stateowned banks may be necessary, given the lack of private capital markets and private entrepreneurship in less advanced stages of development, but may become less important as economies transform and their financial markets develop (Torres and Zeidan, ). Moreover, the three largest NDBs in the world (China Development Bank (CDB), KfW Group in Germany,³ and BNDES in Brazil) have substantially increased their asset and loan disbursement as a share of GDP since . As of , these three NDBs had assetsto-GDP ratios in the range of ‒ per cent of GDP (Ferraz and Coutinho, : ).⁴ While there are several roles that NDBs can play in an economy,⁵ this chapter primarily explores why and how they have played a dominant role in the provision of long-run investment finance to support industrial policy and production strategies more generally. The chapter’s main aim is to identify common technical and political economy factors that have contributed to the effectiveness of national development banking. Prominent among the factors that matter to such NDB effectiveness and their ² According to Gallagher and Sklar (), the level of total assets of national development reached approximately US$ trillion in , which is far larger than the level of loans of the multilateral development banks (around US$ trillion in the same year). ³ KfW is ‘Credit Institute for Reconstruction’. ⁴ By , the five largest development banks in terms of assets (in billions of US dollars) were: (i) China Development Bank ($,); (ii) European Investment Bank ($); (iii) German Development Bank (Kfw) ($); (iv) World Bank ($); (v) Brazilian Development Bank (BNDES) ($) (Ferraz and Coutinho, : , table ). ⁵ Griffith-Jones et al. () identify five crucial roles for NDBs: (i) counteracting the procyclical behaviour of private financing; (ii) promoting innovation and structural transformation; (iii) enhancing financial inclusion; (iv) supporting the financing of infrastructure investment; and (v) supporting the provision of public goods, including promoting ‘green growth’.

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     



role in promoting dynamic structural transformation include: developing sectoral technical expertise among staff to monitor projects and the capacity to crowd in financing (that is, to promote co-financing) for projects from other government agencies, private banks, and business groups. To assist policymakers to identify political economy challenges, the chapter also addresses why and when such factors fail to emerge. These political economy factors provide a different view of less successful NDB performance from that of neo-liberal critics. Section . considers the economic reasoning behind the argument that statesponsored development banking is central to socializing risk and inducing risk-taking and learning as well as more innovative ventures across a range of LDCs, and indeed in advanced capitalist countries. In doing so, it challenges the mainstream view that advocates financial deregulation. Next, we draw on the historical experience of successful national development banking across a range of countries (Germany, Japan, South Korea, China, and Brazil), to determine what effective development banking is and how it has contributed to industrial policy across a range of cases in advanced and less developed countries. An important message that emerges, and something that is neglected in the literature, is that national development banks, when successful, can provide a focal point not only for enhancing firm capacities to learn and innovate but also for enhancing the technical capacity of the state bureaucracy to design and monitor state support of such activities. We make an original contribution to the literature with a discussion of the implications of whether economies develop single or multiple sources of long-run finance. In particular, we discuss why and how economies that encourage or mobilize diversified sources of long-run finance (rather than relying on one or a small number of state-owned development banks, which is common practice) enhance the prospects of their industrial policies meeting the challenges of large-scale, long-gestating projects which entail risk and uncertainty. We next take a more extended look at one of the world’s largest national development banks, the Brazilian Development Bank (BNDES), the source of most of the Brazilian economy’s long-run financing. This case study is useful for examining issues in the broader political economy and macroeconomic context in which national development banking takes place. It also highlights some of the limitations of relying on a single source of long-run financing, even when that source is one of the largest and most well-run development banks in the world. Section . summarizes the general policy implications of the link between development banking and industrial policy.

. T E R  D B

.................................................................................................................................. The general logic of subsidization to promote industrial production in the context of late development is well known: investments (especially in high-productivity sectors where scale and gestation period are large) entail significant risks. There are several

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  

reasons for this. First, the existence of learning by doing (Arrow, ) implies that the now more advanced countries have a ‘first-mover advantage’ of accumulated knowledge compared with producers in late developers. Second, in advanced economies, frontier firms have an implicit advantage because of the generally lower transaction costs of doing business, which is the result of institutions being more predictable, and the quality of physical infrastructure and education systems being higher (Abramovitz, ; North, ). Third, the risk inherent in undertaking industrial development in a late developer in the context of relatively underdeveloped capital markets is generally too high to induce investment in the absence of subsidization and protection. The supply of state-sponsored, long-run credit in even advanced late developers is all the more necessary because firms in OECD countries have further significant advantages. First, there are indirect and direct mechanisms that support the technological advance of their own frontier firms (Mazzucato, ). While R&D spending as a share of GDP may be only slightly higher in advanced countries compared with late developers, the absolute amounts of such spending are vastly higher in most OECD countries because GDP levels are five to ten times higher. Second, the depth of financial markets makes the advanced economies better able to withstand banking, financial, and balance-of-payments crises. This reduces the level of business uncertainty over the long run. Third, the depth of financial markets in OECD countries allows them to provide a diversity of long-run financing sources, which increases the prospects of selecting winners in the uncertain and risky world of innovation-driven investments. Finally, the high level of retained earnings in established Fortune  companies provides a vast supply of investment resources for undertaking R&D. Gerschenkron (), who examined the late development process in Germany and Russia, argued that catching up occurs by undertaking more capital-intensive investment in individual plants, even though overall capital intensity of the backward economy is less. In his analysis, investment banks and national development banks served as a functional substitute for stock markets and commercial banking, both of which financed (along with retained earnings) industrial investment in the forerunner country, Britain. Germany (as a more advanced, but backward economy) relied on relation-based private investment banking as the key to successful catch-up. Investment banks owned substantial shares in industrial ventures. Russia (a much more backward economy) relied primarily on a state development bank to finance industrialization. The key insight is that the stage of development is relevant to the type of development finance required, challenging the idea that late developers should adopt ‘best practice’ of more advanced countries. There are sound economic reasons why NDBs have enhanced the prospects of late development. Standard models of financing suggest that the private banking system is unlikely to be able to provide long-run financing on its own for such risky ventures without state coordination and guarantees (Stiglitz and Weiss, ; Dewatripont and Maskin, ; De Aghion, ). The logic of the basic models is as follows. In a competitive banking system in a low-income economy, banks tend to underinvest in long-term projects. This is because long-term projects involve large sunk costs

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     



requiring co-financing by several banks. However, each bank will tend to provide a limited monitoring effort in the knowledge that part of the marginal return from this effort will accrue to the other banks. Insufficient monitoring jeopardizes project profitability, discouraging the co-financing of long-term projects. This suggests a role for a coordinating agency in order to overcome ‘free-rider’ problems and prevent short-termism. Given the inadequate private provision of long-term finance, coordinating agencies are often sponsored by national governments. The role of government-led and government-regulated state development banking goes beyond standard market failure arguments. Late development plans or missionoriented governments are not simply ‘fixing market failures’. Rather, development involves the processes of creating markets and firms that do not exist in the first place. Such ‘missing markets’ are the result of inherent risks and uncertainty both in late development and in innovation. In this sense, NDBs and their accompanying policies and organizations enable and shape the creation of firms and markets, whether this involves infant industry production or innovation (Burlamaqui, ; Mazzucato and Wray, ).⁶ However, neo-liberal critics claim that state-controlled subsidized credit leads to several problems: financial repression (negative interest rates reducing the incentives to save); the crowding out of private-sector investment; relation-based governance which can generate ‘insider privileges’; non-competitive markets; cronyism and corruption; and misallocation of resources towards over-ambitious capital-intensive projects in labour-surplus economies (McKinnon and Shaw, ; Acemoğlu et al., ; Musacchio and Lazzarini, a). Their policy advice is to liberalize the banking sector, attract foreign banking, let private competitive markets determine the interest rate, avoid capital controls, maintain fiscal and monetary discipline (balance budgets and target inflation), create independent central banks insulated from political pressures, and adopt a rules-based system of financing to promote private stock and bond markets. Neo-liberal policy advice has some important shortcomings. First, there is no historical evidence that effective catch-up strategies have been based on following neo-liberal policy advice (Gerschenkron, ; Rodrik, ; Amsden, ). Second, private financial markets are subject to ‘manias, panics, and crashes’ (Kindleberger and Aliber, ) such as the Great Depression and the  global financial crisis, among many others in advanced countries. Independent central banks, ‘light touch’ regulation, and monetarist policies reigned supreme leading up to the  financial crash. The private financial sector seems subject to a massive ‘soft budget constraint’⁷—since ⁶ Indeed, from advances such as the Internet and microchips to biotechnology and nanotechnology, many major technological breakthroughs—in both basic research and downstream commercialization— were only made possible by direct public investment willing and able to take risks before the private sector was willing to (Mazzucato, ). ⁷ The soft budget constraint () holds wherever a funding source (such as a bank or government) is unable to keep an enterprise to a fixed budget, that is, whenever the enterprise can extract ex post a bigger subsidy or loan than would have been considered efficient ex ante (Maskin, : ). Kornai () analysed how the centralized, socialist economies of Eastern Europe and the Soviet Union were

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

  

large banks are deemed ‘too big to fail’; in fact, taxpayers bail them out when they fail to the tune of trillions of dollars. Moreover, according to Stiglitz and Uy (), assessing the success or failure of a directed credit programme is difficult for three reasons. First, there is usually no way of knowing whether growth would have been higher or lower in the absence of the programme. Second, a good programme requires risk-taking, which means that failures are inevitable. A programme with nothing but successes would necessarily have been too conservative. Third, many of the returns may be long term, so current profitability may not provide an adequate measure of success. For example, the measure of Korea’s chemical and heavy industry programme, Japan’s car industry, or Brazil’s aerospace industry should not be how those industries fared in the first decade of their existence, but what eventually became of their technological development, world market share, and so on thirty years after they began. Similarly, low profits may reflect cyclical conditions rather than long-run prospects. Despite the shortcomings of the neo-liberal view, it is still important to examine the factors and conditions that have allowed a select set of NDBs to make positive contributions to industrial policy and structural transformation, and to identify why many other countries, even when they have well-run NDBs, fail to achieve similar outcomes.

. L  E D B

.................................................................................................................................. The aim of this section is not to recount the historical experiences of development banks. Indeed, there is a substantial literature that covers cases such as Japan, Korea, Taiwan, China, Germany, and Brazil, among others (see e.g. Griffith-Jones and Ocampo, ; UNCTAD, ; Naqvi et al., ; Ferraz and Coutinho, ). Rather, it is to draw out some of the general patterns and mechanisms underlying why and how development banking supports effective industrial policy. First, NDBs, unlike most commercial banks, have developed and mobilized the specialized sectoral and financial skills required to deal with higher-risk, long-term investments. As noted by Sayers (): The logically sound basis for the presumption against long-term commitments is that it is much more difficult to estimate a borrower’s creditworthiness twenty years ahead than six months ahead. The factors relevant to creditworthiness are substantially different over the longer period and the capacity and experience required in

plagued by soft-budget constraints. The term has been applied to explain problems of SOEs in capitalist economies and used as a justification for advocating privatization.

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     



the bank manager are of an altogether different order, an order it is not reasonable generally to expect unless he has specialized expert staff. (Sayers, )

There have been many forms of long-run investment financing that have served the function of socializing the risks inherent in late development. The French experience in the nineteenth century, where significant developments in long-term state-sponsored finance occurred, provides the pioneering example. The creation in – of institutions such as the Crédit Foncier, the Comptoir d’Escompte, and the Crédit Mobilier was particularly important. The involvement of the Crédit Mobilier in Continental European railway investment was notable. The bank acquired substantial expertise in long-term finance as a result of railway investments. This expertise was then disseminated to other Continental European banks in which the Crédit Mobilier held shares. Of even greater importance than the outcome of the operations of the Crédit Mobilier were intangible benefits such as the imitated skills of the engineers and technicians which it sent abroad, the efficiency of its administrators, and its organizational banking techniques, which were so widely copied (Cameron, ). Indeed, one of the main reasons why private banking in LDCs cannot easily assume the risks of long-run financing is precisely their lack of sectoral expertise in assessing and monitoring risk. There is substantial evidence that the subsequent success of development banks in Japan, South Korea, Germany, France, and Brazil owes much to the well-trained staff with engineering and sectoral skills able to monitor loans and form teams that contribute to and influence planning and coordinate government policies (Amsden, ; UNCTAD, ; Ferraz and Coutinho, ; Griffith-Jones and Ocampo, ; Naqvi et al., ). In explaining why and how the German state development bank staff expertise is relevant to enhancing the effectiveness of industrial policy, Moslener et al. () note: Apart from the financial expertise that KfW staff has, it additionally employs experts with specific—often engineering-type—sector knowledge in agriculture, energy, transport, water, natural resources, and civil engineering, to name but a few. This substantively distinguishes KfW from the commercial banking sector. This allows KfW to base its investment decisions on a broader set of criteria from internal employees rather than relying on the market generally or external actors, such as consulting firms. This deeper understanding of sectors and the related markets is also essential not only to identify market imperfections, but also to anticipate the consequences of the respective interventions and programmes . . . Such knowledge further increases the likelihood that a particular project will be more successful from a socio-economic as well as a commercial perspective. Technical expertise further allows KfW to serve as an important conduit between its investments in the private sector and government policy, adding to its information advantage. Finally, KfW’s stamp of approval can effectively signal to other private investors that the project is viable. (Moslener et al., : ; italics added)

Moreover, the financial expertise of KfW staff allowed them to monitor industrial loans effectively, especially during downturns in the business cycles or during financial crises.

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  

In particular, staff were better able than simple government agencies to separate insolvent companies from healthy ones that were merely suffering from the reduced lending capacity of the private sector due to fallouts from the financial crisis (Moslener et al., : ‒). Second, NDBs have increasingly taken on a macroeconomic role of countercyclical financing to combat increasingly unstable and volatile financial markets (Griffith-Jones and Ocampo, ). This is important to help maintain long-term investment, including in infrastructure, ensuring the continuity of existing projects and helping new ones start, valuable both for short-term growth and long-term development. The multilateral development banks (MDBs) collectively increased their lending commitments to emerging and developing economies by  per cent between  and , the year when private capital flows to these countries fell most sharply as a result of the crisis (Griffith-Jones and Gottschalk, ). This countercyclical lending by multilateral and regional development banks was complemented by that of NDBs in emerging and developed countries.⁸ Third, successful state development lending has complemented and ‘crowded in’ private-sector lending rather than displacing it. The high private savings and investment rates in East Asian countries in the s and s, for example, would not have been possible if this were not the case. Although directed credit amounts to as much as  per cent of the loans of financial institutions in some countries (such as Brazil), in the period  to , even in Korea (which used directed credit most aggressively), directed credit amounted to only about  per cent of total credit, and in Japan it never exceeded  per cent (Stiglitz and Uy, ). There are several reasons why development banks have been more influential than their small share in lending might suggest. Because of their close ties to the government, their lending provided information to entrepreneurs and other banks on the areas that the government was promoting. In addition, other financial institutions valued information on the development banks’ choice of clients (as distinct from sectors). This signalling effect only works, of course, if development banks have sound institutional reputations, which they did in Japan, Singapore, Taiwan (China), and, by and large, Korea (Stiglitz and Uy, ). A fourth factor that enhanced effectiveness was substantial amounts of directed credit to industry, based on broad functional criteria (such as whether the firm produced exports), typically using objective performance measures (Amsden, , ; Stiglitz and Uy, ). This was particularly important in the rapid growth cases of North East Asia (Amdsen, ) but has also been important in the export manufacturing drive in Germany (Naqvi et al., ). This dynamic export performance results from domestic processes of learning, effort, and contestation among competing firms (Woetzel et al., ). Of course, it is also necessary for state competition policy to prevent oligopolistic collusion and capture of state subsidies, since internal ⁸ De Luna-Martinez and Vicente () provide evidence that these banks increased their lending from US$. trillion to US$. trillion between  and .

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     



competition among the selected few subsidy recipients is central to inducing the maximum efforts of firms learning to become as efficient as possible (Studwell, ). Fifth, effective export performance has been the result of explicit NDB strategies to promote large firms and/or industrial conglomerates. The literature on ‘strategic trade’ (see Krugman, ) finds that state subsidization matters to export competitiveness in the context of increasing returns and imperfect competition. It is well known that development finance has been central to national firm formation and ‘national champions’ such as Toyota, POSCO steel, or Hyundai in East Asia (Amsden, ). In Germany, in the post- period, the KfW aimed much of its very selective export financing at promoting the export of industrial plant and machinery by a relatively small group of well-known firms such as Siemens, Krupp, Ferrostaal, Ihde, Fritz Werner, and AEG to the major newly independent developing economies, while specific export finance programmes targeted shipping and aircraft exports, including companies producing for Airbus (Naqvi et al., ). In Brazil, BNDES finance was central to the export success of national champions in agri-business, aerospace (Embraer, the world’s third-largest passenger jet company), mining, oil and gas, among others. Sixth, macroeconomic policies need to enable the generation of high levels of savings and investment, and public and private development banking. Indeed, there is considerable debate about what range of inflation and fiscal deficits is compatible with rapid growth (Rodrik, : ). However, especially in less developed countries that do not have well developed capital markets for government bonds, the greater the use of the inflation tax (by printing money), the greater the prospects that hyper-inflationary pressure will emerge. Hyper-inflationary pressures result in increasing uncertainty and an increase in transaction costs, both of which are likely to slow down private-sector investment. Second, they limit the credibility of government bonds which reduces the borrowing capacity of the state to fund investments. It also tends to restrict the development of private banking credit, which limits both the level and diversity of private credit expansion through the banking system, which, in turn, limits the financing of investment (Calomiris and Haber, ). Finally, strong inflationary pressure tends to generate cycles of overvalued exchange rates which reduces the competitiveness of infant industry exporters, reducing in turn the extent to which export markets can become an opportunity to either expand market share or provide a realistic focal point for domestic firms to compete abroad (see Rodrik, , on exchange rate policy and industrial policy). Avoiding balance-of-payments crises is a large part of maintaining a viable macro environment (Thirlwall, , ).⁹ Because ‘big push’ industrialization drives ⁹ Growth reversals or collapses in developing economies have frequently been preceded by foreign exchange shortage, marked by urgent pressure to seek increased aid flows to finance immediate imported input requirements and the rising level of external debt (Arizala et al., ; Bagnai et al., ).

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

  

generate widespread ‘investment hunger’, the macroeconomic challenges of industrial policy are formidable. The danger of overexpansion in a ‘big push’ strategy is typically the build-up of unsustainable and destabilizing external debt positions that will occur if the investment does not lead to productivity improvements, increasing competitiveness and net export earnings. The debt overhang that could result also leads to increases in the share of interest payments on the external debt, which in turn will reduce the state resource available for investment in infrastructure, which is a central input into growth in this strategy. As Amsden () notes: That conditions of ‘lateness’ are inherently conducive to overexpansion is suggested by the fact that when a debt crisis occurs, it almost always occurs in a latecomer country. This is because diversification in the presence of already well-established global industries involves moving from labour-intensive to capital-intensive sectors characterized by economies of scale. (Amsden, : )

The scale of ‘big push’ investments was, indeed, instrumental in the debt crises in Latin America in  and in East Asia in , as both were preceded by a surge in investment (Amsden, : ). Thus, mobilizing national savings, both public and private, becomes central to sustaining a high investment effort without incurring potentially destabilizing levels of external debt. The higher savings and investment level in East Asia is probably the main reason why its growth rates recovered after its macro crises, unlike Latin America, where savings and investment rates are considerably lower. It is well known that high levels of national public savings have supported robust investment rates (Stiglitz and Uy, ; Krieckhaus, ).¹⁰ Thus, it is not surprising that NDB disbursements tend to grow and crowd in private investment the most in East Asia and the OECD, economies where macroeconomic conditions generally allowed governments to develop deep capital markets, especially in the issuance of long-run bonds. An often neglected and paradoxical trend is that the asset size of the two largest NDBs in the world, CDB in China and KfW in Germany, have grown fastest since the late s, an era characterized by financial deregulation processes of ‘financialization’. The triple A credit ratings in Germany have allowed the KfW to become one of the first national development banks to follow in the footsteps of the supranational World Bank and European Investment Bank in tapping into international capital markets (Naqvi et al., ). The dramatic rise in assets of the CDB have all been driven by its ability to issue primarily domestic (but also international) bonds. Indeed, it has played a central role in creating the domestic bond market (Xu, ). On the other hand, BNDES in Brazil has grown substantially on the more ¹⁰ The East Asian economies largely achieved high savings rates through the coercive power of the state, which was deployed through various forms of ‘forced savings’. Among the coercive elements were restrictions on consumer credit, financial restraint, mandatory provident pension contributions (used in Singapore and Malaysia), and encouragement of postal savings (Stiglitz and Uy, ). Other factors that contributed to high levels of private savings were banking and industrial policies (including entry restrictions) that guaranteed high levels of profitability, capital accumulation, and income growth (Stiglitz and Uy, ; Storm, ).

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

precarious and politically fragile basis of relying on government transfers of earmarked taxes and treasury transfers (Musacchio et al., ). This is because the legacy of hyperinflation in the s and s generated macro stabilization policies anchored in high real interest rates to accommodate investors’ demand for short-term returns and liquidity (see section .).

. D  D F M  I P

.................................................................................................................................. While most national development banks are majority or wholly state owned, it is important to note that the vast majority of total investment, even where NDBs have been pivotal to effective industrial policy and structural transformation (East Asia, Germany, France, Brazil) is private, particularly for middle-income and high-income economies. This draws attention to why and how NDBs can crowd in private investment and thus leverage their benefits to the greatest possible extent. The early experiences of development banking marked the role of government in enabling the development of private development banking. In France and Germany from the nineteenth century until the Second World War, government support for private emerging development banks took the form of share capital provision, loans at lower than market interest rates, the provision of state guarantees underwriting these institutions’ bond issues, or a combination of the three. From the early s, the Japanese government bought a substantial share of the bonds issued by private longterm credit banks and was a catalyst ensuring that other private banks and financial institutions subscribed to these bonds. It allowed development banks to issue longterm bonds or debentures, whose market the government helped create. This privilege helped redress the mismatch between the maturity structure of the banks’ assets and their liabilities, a problem that had plagued commercial banks (Stiglitz and Uy, ). Limiting competition also enabled the long-term credit banks to obtain funds more cheaply than they otherwise could have (Stiglitz and Uy, ). Only in the postSecond World War period do we find that almost all national development banks are state-owned enterprises (SOEs), mostly financed through retained profits and domestic taxation (particularly a portion of personal income taxes [PAYE], but also through domestic government bonds, international capital markets, and concessional finance) (on the varied sources of NDB finances, ownership and lending patterns, see UNCTAD, ; and Griffith-Jones and Ocampo, ).¹¹ ¹¹ According to a World Bank survey (De Luna-Martinez and Vicente, : ), almost threequarters of NDBs surveyed are  per cent state owned,  per cent have between  and  per cent state ownership, and in only  per cent do governments have minority ownership.

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

  

The current association of national development banking as a state-led process distracts attention from the wide variation in the importance of private long-run financing across countries, particularly at low- and middle-income levels. Indeed, it is possible to identify two basic patterns of relation-based sources of late-development and innovation-oriented financing. The dominant pattern in most LDCs since the Second World War has been the single/limited long-run financing model. This generally involves reliance on one dominant national development bank financing public and private industrial firms. Perhaps the most well-known example is BNDES in Brazil (for a discussion of BNDES and how it has worked, see Amsden, ; Musacchio and Lazzarini, a, b; Colby, ; Tavares de Araujo, ). In single long-run financing situations, such economies lack depth but also diversity in long-run financing mechanisms. This may, as we shall see in the case of Brazil, be the result of macro instability and chronically high inflation and uncertainty due to balance-of-payments crises that inhibit long-run government and corporate bond markets, and/or explicit government policies limiting cross-shareholdings between banks and industrial firms. The latter would mean that while business conglomerates may develop, such groups grow outside manufacturing. The second basic model, and one more likely to sustain the investment and innovative capacity of the economy, is a diversified/multiple financing model. This would include a national development bank co-financing projects with state/regional development banks and bank-based industrial conglomerates, as in Japan, South Korea, Taiwan, and Germany. In China, the model is based around a national development bank, policy banks in agriculture and trade, and a decentralized system of state government (town and village enterprises [TVEs,] and later local government financing vehicles), which constitute multiple poles of long-run financing as well as competing with each other in the large internal market (Qian and Weingast, ; Ang, ). In the United States, it is based on the large retained earnings of corporations, public banks, and a vibrant investment and venture-capital sector. Indeed, national development banking has been effective in crowding in productive investment when it has been able to draw on and nurture the construction of bankbased industrial business groups. Historical evidence suggests that bank-based industrial business groups have been central to the catch-up processes in Germany, France, Italy, Sweden, Japan, South Korea, Taiwan, and Israel (Khanna and Yafeh, ). Such relation-based financiers are able to take a longer-run view of catch-up investments (and therefore become more ‘patient’ investors) than either stock markets or independent commercial banks, both of which operate under impersonal, rules-based systems. There is evidence that, when a dominant national development bank intervenes, co-financing arrangements and/or co-ownership with private financial institutions can enhance the returns to capital of state-led long-run financing (De Aghion, ). The multi-financing model has several advantages for crowding in private investment in productive ways. First, it reduces the extent to which rent-seeking in search of long-run funds becomes a political game centred on one or a small number of state

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

banks. While there may be considerable legal and illegal rent-seeking involved in trying to obtain access to selective long-run state finance, the existence of several bank-based industrial conglomerates will likely increase the competition and contestation over such funds. Such contestation, even in countries with substantial cronyism and corruption, may provide incentives to generate more viable and dynamic production empires, since economic prowess will improve the prospects of winning these rentseeking contests. Second, it enhances the prospects of exchange of information, expertise, and collaboration between the public and private development banks. Business conglomerates are able to pool scarce managerial talent and provide internal financing to undertake risky ventures that are difficult to otherwise finance in the context of underdeveloped capital markets (Leff, ; Amsden, ; Khanna and Yafeh, ). The so-called transaction banks in such conglomerates (particularly in Germany, Japan, Taiwan, and South Korea) complement the financial, engineering, and other technical expertise to monitor sectoral investments. Such conglomerates are important not only because in many catch-up processes, large and concentrated firm size is a key to competitiveness (where scale economies are relevant), but also because they provide an important complement to state planning and coordination (Mahmood and Rufin, : ‒). Third, it increases the incentives for private business groups to monitor the quality of investments, to increase their technology learning efforts, and to become more innovative, because they have a stake in long-gestating and complex ventures. Indeed, one of the reasons behind the successes of NDBs in East Asia in developing dynamic firms and sectors has been the requirement on the part of governments to demand substantial collateral in return for loans as a way to incentivize effort (Stiglitz and Uy, ; Xu, ). Finally, the diversity of long-run financing enhances innovation because it enables a greater variety of experimentation. Apart from the need to generate a high volume of long-run investment funds, the diversity of these funds becomes as important. This is because a greater diversity of venture capital ‘bets’ increases the likelihood of success. As Mokyr () notes: ‘Diversity is the root of creativity, and much of what we call technological creativity is the ability to absorb, assimilate and apply ideas borrowed from others’ (: ). Indeed, the diversity of experimentation is also central to why the process of market competition and rivalry produces discovery and innovation, a process neoclassical economics has been ill-equipped to explain (Hayek, ). It is not a coincidence that the highest rate of patent applications and approvals (an albeit imperfect proxy of innovation) come from OECD countries but also emerging economies with diverse sources of long-run financing (e.g. South Korea, China). Recent evidence from the McKinsey Global Institute on the characteristics of countries with the fastest long-run growth rates (so-called ‘outperformers’) suggests a greater presence and performance of large firms (defined as firms with at least US$ million in sales). Moreover, this success is accompanied by greater competition or ‘creative destruction’ among large firms within these economies:  per cent of the top quintile are replaced within a decade compared to less than  per cent among

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

  

slower-growing economies (Woetzel et al., ). The report further argues that, rather than just picking winning firms or sectors, the focus was on boosting productivity and enabling competition. Performance criteria and the limited time frame of subsidies, and exposure to export markets, all increased firm effort and disciplined lagging performance. Large firm development also received government support in the form of subsidies for infant industries, including low-cost loans, preferential exchange rates, low tax rates, and R&D subsidies. In sum, scale, and diversity of long-run financing are two central features of industrial policy that delivers dynamic growth and structural transformation. As Amsden () first observed, the structure and size of business organizations matters for achieving the scale and scope necessary to achieve dynamic infant industries and exporters in latecomers. The above discussion suggests it matters in other ways, such as providing a diversity of financing options to support learning and experimentation, as well as providing the prospect of internal competition among competing business groups. All the cases of long-run growth identified as ‘outperformers’ have been countries with access to multiple sources of long-run financing. For economies without this diversity in sources of long-run financing, an important policy issue is how to diversify these sources. Several options are being pursued today. First, setting up several, more specialized policy banks could diversify organizational effort. In fact, apart from the main development bank, CDB, China has large policy banks such as the Export– Import Bank of China and the Agricultural Development Bank of China. Second, attracting foreign direct investment (FDI) diversifies long-run finance since multinationals have retained earnings and access to global capital markets. Third, reaching out to a large diaspora is an option for some countries such as Israel, India, Bangladesh, and Ethiopia. The latter, for instance, raised substantial capital through diaspora bonds to fund the Renaissance Dam project. Finally, and most important for low-income countries, international development banks have enhanced the diversity of funding. The World Bank Group has done this in two ways. First, it has undertaken local currency bond issuance through their signalling and demonstration effects, which strengthens confidence in a country’s domestic bond markets attracting foreign issuers and investors. Second, investment funds, such as the International Finance Corporation (IFC), have invested in both established and emerging private-sector companies.

. C S: T P E  D B  B ..................................................................................................................................

The Brazilian case is useful for examining the broader political economy in which national development banking takes place. While Brazil’s main national development bank, BNDES, has been central to one of the most remarkable stories of growth and structural transformation since the s, its policies have been insufficient to prevent

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

a dramatic slowdown in manufacturing performance in the post- period. Even more intriguing is that the latter period is subject to enormous variations in manufacturing performance: a great industrial divide involving the rise of national champions and the fall of the rest.

.. The Positive Side of Development Banking in Brazil On the one hand, Brazil has had one of the best-performing and most successful national development banks in the world. The national development bank, founded in , initially focused on financing infrastructure as part of the country’s drive towards modernization and industrialization. Later in the decade, its focus broadened to support the country’s capital goods industry and then, in the s and s, other industrial sectors (Armijo, ). The state also introduced important ‘forced savings’ schemes which were used to fund significant growth of the national development bank, BNDES, and the spectacular growth of relatively well-run SOEs in heavy industry and mining, which contributed to public savings via their profitability and provided a focal point for technological development (Trebat, ).¹² BNDES was central to the longrun financing that enabled rapid growth and structural transformation in the period  to  during which Brazil developed one of the most diversified and sophisticated industrial and manufacturing sectors among middle-income countries.¹³ Since the s, BNDES has been the focal point of industrial restructuring and ‘strategic’ large-scale privatizations (maintaining corporate control through ‘golden share’ minority positions), and has supported exporting sectors (with a focus on capital goods and engineering services) and, more recently, the internationalization of large national corporations, the so-called national champions.¹⁴ The extensive privatization programme, in particular, transferred ownership on preferential terms to established and emerging domestic business groups (Almeida, ; Massi, ). This process resulted in the emergence of firms in agri-business, steel, aerospace, mining, oil and gas, paper and pulp, engineering and construction, and telecommunications, many of whom have become innovative frontier firms.

¹² On the growth of SOEs in this period, see Musacchio and Lazzarini (b). The expansion of SOEs meant that the SOE share of total gross fixed capital formation increased from  per cent in  to  per cent in  (Frieden, : ). ¹³ It is well documented that BNDES played a dominant role in deploying subsidized long-run credit in this period (see Barros de Castro, ; Tavares de Araujo, Jr., ; Colby, ). In the period  to , between  and  per cent of all lending went to the public sector. In  to , the private sector received an average of  per cent of all lending, rising to an average of approximately  per cent of all loans going to the private sector in the period  to  (Colby, : ), mostly in intermediate and capital goods. ¹⁴ In –, loan disbursements increased from R$ billion to R$ billion at constant prices, a growth of  per cent in real terms (UNCTAD, : ).

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

  

The restructuring of Brazilian capitalism, or what Musacchio and Lazzarini (a) refer to as the ‘re-invention of state capitalism’, involved the construction of multiple and diversified sources of long-run financing and a governance focal point around sectoral restructuring for these targeted firms. This process took two basic forms. First, under BNDES leadership, the government pursued a policy of purposefully constructing ‘national champions’, largely through what were called ‘strategic privatizations’. The equity of many of the viable, but financially strapped SOEs was transferred to private domestic business groups, but BNDES (through its investment banking arm, BNDESPar) and state pension funds also maintained strategic minority shares. In the case of oil and gas and some electricity firms, the state maintained a majority share but also received vast amounts of BNDES loans.¹⁵ In both cases, export credits also increased substantially. These state policies enhanced the value of rents by enhancing the profitability and technical capacity of these firms to compete in export markets. Second, the centrepiece of the construction of innovative ‘national champions’ was long-run subsidized credit financing, most of which came from BNDES.¹⁶ The outcome of the processes of privatization coordinated in the Cardoso administrations (‒) had created a change in ownership patterns that was effectively a ‘coordinated’ process of restructuring innovative firms close to the technological frontier. The basic pattern is described by Aldrighi and Postali () as follows: The complex arrays that have led BNDESPar, Banco do Brasil, Petrobras, and pension funds of companies currently or formerly controlled by the government to hold large equity stakes or even to take part in the controlling coalitions in some business groups stem primarily from their participation in the privatization process. Given its intent to maximize revenues from the privatization auctions, the Federal Government urged BNDES and pension funds to act as financiers for the bidders, notably Brazilian private groups. (Aldrighi and Postali, : )

The state created rents by assuming the socialization of risk in promoting innovative activity and increasing the scale of business groups and firms through a combination of loans and taking equity positions. With the rise in BNDES funding in the post- period (reaching a peak of . per cent of GDP in ), these loans tended to target the largest firms in the country: in the period  to , the ten largest loans made up  per cent of all BNDES disbursements (Hochstetler and Montero, : , table ). Other mechanisms through which the state increased the diversity of long-run financing and growth potential of emerging national champions were the increasing equity

¹⁵ In the latter case, and in particular the case of Petrobras, the state has anchored much of its industrial policy around developing linkages from large offshore oil finds into shipbuilding, construction, and deep-sea oil exploration equipment. During this period, Petrobras set in motion a US$ billion investment programme for these projects. ¹⁶ The value of loans disbursed by BNDES in  was more than three times the total amount provided by the World Bank in  (Musacchio and Lazzarini, b: ) and still twice that amount in  (Torres and Zeidan, : ). Between  and , subsidies from the treasury to BNDES loans totalled US$ billion (The Economist,  December ).

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

participation of state pension funds (Almeida, ), the provision of export subsidies and credits,¹⁷ and the promotion of local content laws, through public procurement policies, in sectors such as oil, shipbuilding, automobiles, and wind turbines (Almeida and Schneider, : ). The strategy of creating frontier, innovative firms was not just about financing, but also about increasing their scale, promoting their internationalization into emerging multinationals able to compete at the apex of global value chains, and promoting their innovative capacity. The result of this process is a series of world-class Brazilian multinationals at the cutting edge of frontier technologies¹⁸ in aerospace, high-tech agriculture, agri-business, steel, telecoms, mining, oil and gas, bio-fuels, automobiles, and bio-technology (Brainard and Martinez-Diaz, ; Musacchio and Lazzarini, a, b; Perez-Aleman and Chaves-Alves, ; Ferraz and Coutinho, ).¹⁹ Many of Brazil’s ‘national champions owe their existence to past capacities that were constructed and developed as state firms in this period’ (Aldrighi and Postali, ). By , BNDES was the third-largest national development bank in the world, after the China Development Bank and Germany’s KfW. In the context of a country where commercial banking has focused on short-term loans, BNDES, with its strong technical expertise and record of promoting structural transformation, has been held up as a role model for countries considering setting up development banks (UNCTAD, ).

¹⁷ Interview with João Carlos Ferraz, vice-president of BNDES (August ). ¹⁸ In historical perspective, there are several features that unite the stories behind the emergence of these innovative firms. First, all of them have their origins as domestic business enterprises. Second, most of these firms come from sectors that have built up substantial productive and managerial capabilities over long periods of time, going back in some cases to the early twentieth century, and have benefited from long periods of protectionism (whether as a result of explicit state strategies or as unintended consequences). Third, all these firms have benefited from state policies, whether in the form of access to long-run, subsidized financing, protectionist policies, state-financed research and development, or public procurement. Fourth, exposure to international markets, and particularly growing through exports, even during the protectionist era, allowed these firms to gather information on the demands of foreign consumers and compelled them to seek out productivity-enhancing innovations to compete in world markets. Fifth, the military played a key role from the Vargas era in the s through the s in creating a discourse around the development of ‘strategic’ sectors, beginning with the steel industry, but also in oil and gas, and aerospace. This discourse not only helped governance focal points emerge around such sectors but also provided continuity of funding even in times of macroeconomic crisis and distress as well as providing research clusters and long-run financing facilities and using SOEs as focal points to train and attract scientists and engineers. This is most evident in the case of Embraer (the world’s thirdlargest aerospace company). ¹⁹ By , agricultural production in Brazil ranked first in the world in coffee, orange juice, and beef; it ranked second in soybeans; third in chickens; fourth in corn and pork; and fifth in cotton (Nassar, ). By , the yields for Brazil’s main crops (sugarcane, corn, cotton, soybeans, and wheat) reached levels similar to those of developed economies (Elstrodt et al., : ‒;) agricultural productivity growth has been among the fastest in the world since  (Arias et al., : ‒). Brazil is also a world leader in mining (e.g. Vale is the world’s second-largest mining company and Petrobras is a leading oil company and a producer of sophisticated deep-sea oil exploration equipment) (Brainard and MartinezDiaz, ).

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.. The Limitations of BNDES and the Importance of Broad Political Economy Factors Since , despite the best efforts of BNDES to increase disbursements and fund world-class national champions, overall GDP and manufacturing output and productivity growth rates have collapsed and there was substantial de-industrialization from as early as .²⁰ The share of the manufacturing sector in total GDP fell from a peak of . per cent in  to less than  per cent in . While BNDES investment may have ‘crowded in’ private-sector investments, it has done so within a range that is far too low: the private investment rate maintained a rate in the ‒ per cent range throughout the period, which is well below East Asian counterparts. Whatever the particular design of industrial policy, this low level of investment ultimately generates fewer experiments, risks, and learning processes. The Brazilian experience suggests that macroeconomic policy and context as well as policy decisions on banking laws have contributed to reliance on a single/limited longrun financing model. As a result, both scale and diversity of long-run financing mechanisms have been limited, even during periods of rapid growth. The subsequent slowdown in growth after  suggests that the nature of development patterns matters more for avoiding growth collapses that are common features of LDCs. Let us examine the historical evolution of the processes behind this problem. First, a series of development banking laws and policies inhibited the development of private-bank-based industrial conglomerates, and therefore limited multiple sources of long-run finances. Many of these policies, either initiated or enforced by BNDES, were meant to promote internal competition. BNDES put conditions on its loans specifying low debt/equity ratio ceilings that constrained the size of national firms (Amsden, : ). This decision, along with a banking law in  which restricted banks and industrial firms from having cross-holdings (Armijo, ) was meant to both create internal competition and prevent further concentration of industrial assets which historically were linked to the ‘insider’ advantages that big businesses had with a banking system with limited access to credit (Calomiris and Haber, : –). In a country with historically very high levels of income and asset distribution, the rationale for this policy is understandable. However, the policy constrained the size of domestic manufacturing firms (Amsden, : ) which is one of the reasons why there were very few capital goods firms that exported. They simply did not have the scale and scope to compete. It was thus not surprising to find, among all less developed (that is, non-OECD) countries, there was no private Brazilian business group in

²⁰ Manufacturing growth in the period  to  averaged nearly  per cent per year but averaged around  per cent per year in the post- period. According to Aldrighi and Colistete (), while average annual manufacturing labour productivity grew at . per cent in the period  to , it declined to . per cent in the period  to  and then collapsed to minus . per cent in the period  to .

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manufacturing in the top  (ranked by sales) in the world in  (Amsden, : , table .). The second factor that limited the development of private investment banking in the twentieth century was the increasingly excessive use of the inflation tax (by printing money) through the mid-s. Inflation rates averaged over  per cent in the period  to , and were to reach ‒ per cent by ‒ (Calomiris and Haber, : ). This ultimately culminated in hyperinflation in the s and early s. Chronic and high inflation resulted in increasing uncertainty and an increase in transaction costs, both of which inhibited the emergence of a private investment banking sector and resulted in the state becoming the main source of long-run development financing. Second, it limited the credibility of government bonds, reducing the borrowing capacity of the state to fund investments, and also tended to restrict the development of private banking credit. This limited both the level and diversity of private credit expansion through the banking system, which, in turn, limited the financing of investment (Calomiris and Haber, ). Finally, strong inflationary pressure tended to generate cycles of overvalued exchange rates which reduced the competitiveness of domestic manufacturing firms and thus their ability to increase exports.²¹ Third, the growing reliance on external debt made the economy vulnerable to balance-of-payments crises. The main culprit behind the worsening economic performance of the late s to the mid-s was the reliance on a debt-led growth strategy, which resulted in a growing balance-of-payments crisis, increasing external debt and rising inflation (Fishlow, ; Bacha and Bonelli, ). Due to the unforeseen dramatic rise in world interest rates, the country was forced to declare a suspension of external debt payments at the end of .²² The inability of the central government to control and discipline state financing contributed to a spiralling and unsustainable debt. Throughout the s and into the s, governors used the state banks to finance expanding deficits, accumulating staggering debts. State bank debts had reached US$ billion by  and amounted to a massive US$ billion in  (Kingstone, : ). State and local governments were responsible for about twothirds of Brazil’s US$ billion foreign debt (Mainwaring, : ). The climate of hyperinflation and the debt restructuring imposed led to a series of policies that would both hamper state finances and negatively affect the investment climate (Aldrighi and Postali, : ‒). Fourth, the macro policies after  to handle the legacy of inflation also inhibited private investment banking. Macro stability, in particular sustaining low inflation, was a ²¹ Despite its rapid industrial catch-up, Brazil’s share in world market exports was to decline from . per cent in  to . per cent in , and would remain at that share through  (BulmerThomas, : ). ²² The ‘big push’ strategy of PNDII development plan did not generate the net foreign exchange to finance debt payments in the s, something East Asian economies were able to accomplish. The country’s foreign debt (in constant  dollars) grew from US$. billion in  to US$. billion in  and further increased to US$. billion in , which represented two and a half times the value of the country’s exports (Malan and Bonelli, : ).

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main priority of each of the administrations in this period. The history of inflation taxes and episodes of hyperinflation had eroded the political support of the poor (who mostly paid for this tax) and asset owners, particularly within industry, who were unable to undertake meaningful long-run strategic planning. This price stability was achieved, however, by maintaining real interest rates that were among the highest in the world, as well as an overvalued exchange rate, in the period  to  (Afonso et al., ).²³ The legacy of hyperinflation meant that Brazilian savers demanded two things: high interest rates and short-term returns to ensure liquidity (Orair and Gobetti, : ). Among the consequences of this macro policy environment is that it reduces the effectiveness of BNDES action on industrial policy. First, in the period  to , interest payments on debt absorbed more government spending than did infrastructure, education, and health (De Magalhães and Costa, : ‒). Second, high real interest rates reduced the extent to which BNDES policies could ‘crowd in’ private investors who were unwilling to undertake risks despite government efforts provide a substantial amount of loans at subsidized interest rates (Ferraz and Coutinho, ). As a result, the ‘national champions’ policies, while generally successful, appropriated a significant proportion of long-run financing. This occurred in the context of an economy that did not have alternative forms of long-run financing investment arrangements, such as bank-based industrial conglomerates, or well-financed regional development banks. While BNDES disbursements increased to . per cent of GDP after ,  per cent of that funding essentially went to fund the formation of ‘national champions’. That left only  per cent (or a little over . per cent of GDP) available for long-run subsidized funding for potentially innovative smaller and medium-sized firms—not enough to drive productive investment. Moreover, policies to reduce the role of state development banks, while understandable given their previous activities building up massive external debts in the s, undermined the extent to which a more decentralized and diversified set of long-run financing organizations would emerge across levels of government, as has occurred in China, South Korea, or Germany. In , fiscal governance was reformed by the adoption of hard-budget constraint legislation—the Fiscal Responsibility Law—which imposed transparency requirements on states, and municipalities’ accounts and imposed a ceiling on states’ spending.

.. Policy Debates: Assessing the Role and Effectiveness of BNDES in Brazil There are several specific criticisms of the ‘national champions’ model. The first set of arguments revolves around the criticism that BNDES was focusing too much of its ²³ In the new model, the guarantee of government credibility became a requirement of the international market, and the liberalization that saw the opening up of the economy commercially and financially served, together with privatization, to guarantee the Brazilian government a supply of liquidity (Afonso et al., ).

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lending on sectors that were already internationally competitive, such as Petrobras and the agri-business sector (Almeida, ; Almeida and Schneider, ; Tavares de Araujo, ; Musacchio and Lazzarini, b). According to this line of argument, lending should not have focused on firms that were at the frontier, since industrial policy should focus on providing incentives to stimulate novel learning instead of reinforced specialization in utilities and commodities such as mining, oil, steel, agribusiness, and aerospace (Almeida and Schneider, ; Musacchio and Lazzarini, b: ‒). It is true that BNDES followed a strategy of ‘going with winners’ or ‘betting on the strong’ rather than ‘picking winners’. This is revealed in the fact that the default rates on its loans in the period  to  are almost nil, at . per cent compared to the national financial system rate of . per cent (Colby, : ). This is hardly the profile of a venture capitalist investment fund. One can also make the case that because BNDES maintains these equity shares, they are not ‘letting go of winners’ by selling on these shares to private equity firms. The second, and related, criticism is that BNDES lending reinforced a pattern of socalled ‘low-technology-intensive’ sectors. Almeida and Schneider () argue that ‘if industrial policy is supposed to create new competitive advantages, then it has failed to do so: the most competitive industrial sectors in , measured by the trade surplus, are the same as in , despite the goals in successive industrial policies to promote technology-intensive sectors . . . Rather the bias towards conservatism has consolidated the specialization of Brazilian exports around resource-based industries and commodities’ (: ‒). Both criticisms add up to the diagnosis that there was a misplaced focus on competitive ‘insiders’ at the expense of potentially more innovative ‘outsiders’ who were not yet competitive and thus the share of medium- and high-tech production suffered as a result. A third criticism concerns the returns to capital investment that BNDES equity participations, through its investment banking arm, BNDESPar, have yielded. Bruschi et al. () compare the individual performance of the shares held by BNDESPar with returns on the Ibovespa index, the main stock market index in Brazil. For firms that BNDESPar acquired after , they find that  per cent of the shares performed worse than the stock market index in the same period,  to . Their conclusion is that BNDES will be unlikely to continue to generate the majority of their income from equity investments. The criticism that BNDES subsidized already competitive firms is misleading. These lending patterns need to be seen in historical and political context. First, the fragility of BNDES financing in the s has created an understandable conservative bias in its spending since . The legacy of macroeconomic instability can impair the ability of state development banks to finance risky new ventures in the high-tech and capital goods sectors, since the very legitimacy of the bank’s mission needs to be reconstructed. Second, it is not clear that many of these near-frontier technology firms would have been competitive in the context of the well-known custo Brazil (Brazil Cost)—the relatively high prices of many domestic goods and services, a reflection of the

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concentrated production structure, and the failure of government regulation to introduce competition laws (which implicitly meant that producers in several sectors are effectively earning large rents).²⁴ Third, it is not at all clear that without long-run subsidized financing and state equity injections many of them would have become the innovative firms they did. There are not many examples of foreign investment banks funding long-run R&D programmes of firms in LDCs and there is little evidence that the private domestic banking system would have done so either. Moreover, many of the export credits were essential to the export success of these firms: Embraer, for instance, depended on them to keep its products competitive (as KfW has done with Airbus). Fourth, since NDBs take risks, there will be inevitable failures. Equity positions will allow them to reap some of the financial rewards in order to offset the inevitable failures and ensure a stable funding source so it does not lose its appetite for risk (Mazzucato and Penna, ). Fifth, the idea that BNDES lending patterns have reinforced the pattern of ‘lowtechnology’ exports is misleading. The categories ‘low-tech’ and ‘high-tech’ direct attention away from the point made by Baldwin () that the integration of global value and supply chains means sectors are less relevant than the stages of production. And what matters is the capacity to innovate at the level of design and product development. In this respect, most of the ‘national champion’ firms are innovative or based on state-supported R&D investments. The fact that Brazil is competitive in agribusiness (supposedly ‘low-tech’) as well as in aerospace (supposedly ‘high-tech’) owes more to the capacity to design and develop new products than to the sector it is producing for. There are many countries in South Asia and sub-Saharan Africa, including South Africa, and even in South East Asia, that would more than welcome the innovative capacity of so many so-called ‘low-tech’ sectors in agri-business, steel, and oil and gas that Brazil has developed (see Chapter  of this volume for a discussion of the problems of outdated categorization of what is ‘industrial’ or ‘low-tech’, which obscures dynamic, technologically sophisticated activities taking place within resourcebased industries, agriculture, and services).

.. The Politics of Development Banking in Brazil This discussion of development banking in Brazil suggests that policy design and reform need to be understood in terms of broader political economy dynamics. The economy in the post- period maintained a limited diversity of long-run financing ²⁴ There are numerous examples (The Economist, : ). In , ‘cost of doing business’ surveys indicate that exporting costs US$, per container in Brazil compared with an average of US$, in the rest of Latin America, and US$, in the United States. To take another example, the cost of electricity for industrial users in Brazil is the third highest in the world—about twice those of China and Korea, and two and a half times that of the United States (The Economist, a).

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organizations, in large part because the dominant large business groups had their core businesses outside manufacturing, and also because commercial banks were deriving substantial profits from purchasing high-yielding government assets (as a result of anchoring inflation on high real interest rates and maintaining fiscal surpluses) and other financial assets (particularly equities and derivatives). This made the opportunity cost of investing in risky innovation-based start-ups and/or in experienced but financially strapped capital goods industries and start-up ventures very high. In this context, the amount of subsidized long-run financing that was left over for ‘outsider’ but potentially innovative firms was simply too small to provide the vast amount of long-run financing that innovation-based strategies require. What is more, the BNDES leadership was well aware of the need to promote innovation and there were indeed many smaller loans to a variety of innovative firms (see Hochstetler and Montero, ). The ‘insider/outsider’ problem was not due to a lack of technically competent, well-meaning, and informed technocrats; it is generally accepted that Brazil does not have a skills shortage in its main development and banking agencies. Rather, this problem, along with the insufficient savings and investment rates, has much more to do with the historical political economy dynamics, and in particular, the way economic and political order was maintained in this period. The political nature of development banking is evident in recent political crises in Brazil. The discovery of the disappearance of nearly US$ billion from the accounts of Petrobras in late  set off the largest corruption scandal in Latin American history. The Lava Jato probe, undertaken by an increasingly proactive and independent judiciary and federal police in , has uncovered a complex bribery and kickback scheme in which, among other things, the biggest construction companies and other private industrial groups, many of whom received massive BNDES financing, paid bribes to politicians’ personal accounts and to political party campaign funds in exchange for padded government contracts in construction, shipbuilding, and other Petrobras investments. Large-scale corruption scandals are not new to Brazil, nor is there evidence that BNDES knew of the corrupt practices of its clients, but the magnitude and political fallout reveal more profound tensions than the merely political. An important aspect of the discontent concerns the alienation, for a number of reasons, of much of the middle class. First, there was growing discontent around the poor quality of public services such as transport, education, and health, as well as increasingly expensive housing, fuelled by the boom in financial and commodity markets. Much of the frustration was compounded by the inability of the government to address the growing levels of crime and urban violence. Second, much of middle-class discontent stemmed from the fact that they have borne the brunt of the increased tax burden to fund pro-poor expansions in the welfare state and have not received proportionate benefits (Saad Filho and Morais, ). Third, middle-class groups were losing much of their economic privileges relative to lower income groups. This has occurred because of the stagnation of average real wages in the context of minimum wages rising, and because there was a

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decline in the creation of well-paid employment, most likely the result of the stagnation in manufacturing employment and the rise of lower-paid service employment.²⁵ A further source of discontent, not only among the middle class, but also among some big business groups, was the perceived ‘insider bias’ in the massive loan portfolio of BNDES, the main provider of long-run financing.²⁶ The most infamous case, and a focal point of protest, was the case of JBS, the meat-packing company, which borrowed over . billion reais from BNDES to purchase meat-packing companies in the United States, Europe, and Australia, and became the world’s largest meat packer. In the process, BNDES purchased a . per cent stake in JBS in  (Leahy and Schipani, ). While big business groups in oil, shipbuilding, and construction, along with some food groups, comprised an inner circle of support for the Workers Party (PT)-led administrations between  and , other groups, particularly the banking sector and media conglomerates, were committed opponents of these strategies, which they viewed as promoting crony capitalism and excessive state control over resources. The discontent over such ‘corporate welfare’ became a focal point for middle-class groups, finance, and the media in street protests against the government from  onwards and were a focal point of anti-corruption discourse against the PT and the broader political party system. The corruption scandal became an instrument of political contestation and protest (Leahy and Schipani, ). Given media and banking opposition to PT, it was not surprising that a focal point of the scandal was the link between Petrobras and big insider supporters of PT in oil, shipbuilding, construction, and food (despite the fact that all political parties were involved in Lava Jato; Leahy and Schipani, ). Within Congress, the opposition to the PT ultimately led to the impeachment of President Dilma Rousseff and the demise of the legitimacy of state-led development banking. Of course, the corruption scandal itself has had a profoundly negative effect on the economy because of increased political uncertainty. The companies involved in the scandals, some of the largest in the country, have faced profound financial consequences. Petrobras, which in  accounted for approximately  per cent of Brazil’s gross domestic product, was estimated to have lost at least US$ billion by mid-. Petrobras and Odebrecht have sold assets worth billions of dollars to pay their debts. Unemployment in Brazil hit a new high in April  at . per cent, more than

²⁵ The real wage (deflated by domestic prices), while rising slightly in the period  to , has generally stagnated in the period  to  (Aldrighi and Colistete, : , figure ). ²⁶ In the period  to , about US$ billion was channelled to the food industry, and US$billion to Petrobras (Tavares de Araujo, Jr., : ). By  Petrobras became by far the largest borrower, with almost  per cent of total loans held by listed corporations (Musacchio and Lazzarini, b: ‒). From  to , BNDES subsidized loans increased five-fold, reaching R$ billion (US$ billion) (Leahy and Schipani, ). The main beneficiaries included Odebrecht (the country’s largest engineering and construction firm); Petrobras (the state oil company which accounts for  per cent of GDP); Embraer (the world’s third-largest commercial jet builder); Ambev (the Brazilian arm of the world’s largest brewer, ABInBev); and JBS (the world’s largest meat packer) (Leahy and Schipani, ).

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double the rate it was in late , prior to the start of Lava Jato. Thus even a well-run organization like BNDES has not been immune to the tempests of political contests and controversies. The current administration under President Jair Bolsonaro has initiated a process of reducing its role in the economy.

. G P C

.................................................................................................................................. First, the effectiveness of a national development bank depends upon the same factors that make industrial policy effective more generally. It requires a clear set of ‘carrot and sticks’, and the ability to ‘let go of losers’ (Amsden, ). From this perspective, the focus on simple, objective performance criteria, such as export growth, has been helpful for implementing reciprocal control mechanisms. When successful, national development banks have been able to monitor projects and loans with sectoral experts, many of whom hold PhDs in a wide range of areas. Relying on financial experts alone is insufficient. Of course, the effective implementation of a reciprocal control mechanism implies that the state has the power and authority to mobilize resources and provide a ‘carrotand-stick’ mechanism. Implicit in this is the political power to remove subsidies from powerful economic elites when their infant industries perform poorly. Moreover, if a reciprocal control mechanism is to be financed, the state requires the political power not only to mobilize resources but to ensure that a high proportion of loanable funds in the financial sector are channelled towards long-gestating manufacturing or other high-value investments as well as securing sources of funding for development banking (Woo, ; Kapadia, ).²⁷ Second, NDBs do not necessarily need to finance all of the venture capital on projects. The experience of East Asian and other economies (such as Germany, and in some instances, Brazil) suggests that policymakers should consider diversified/multiple financing sources by getting endowment funds, donors, domestic banks, and conglomerate groups and foreign firms to co-finance targeted projects. Even when the state privatizes SOEs in strategic sectors, that does not mean it needs to lose control over industrial policy. Instead, the state can maintain ‘golden shares’ in priority projects to maintain state control over strategic decisions, as has been practised in the privatization process overseen by BNDES in Brazil. In fact, according to Musacchio and Lazzarini (a, ²⁷ As Woo-Cummings (: ), notes: ‘finance is the tie that binds the state to the industrialists in the developmental state.’ Theda Skocpol (as quoted in Woo-Cummings, : ) further adds that ‘[t] he answers [to questions about financial resources] provide the best possible general insight into the direct or indirect leverage a state is likely to have for realizing any sort of goal it may pursue. For a state’s means of raising and deploying financial resources tell us more than could any other single factor about its existing (and its immediately potential) capacities to create or strengthen state organizations, to employ personnel, to co-opt political support, to subsidize economic enterprises, and to fund social programs.’

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b), the ‘state as minority shareholder’ model has several advantages. First, it limits the use of SOEs as a conduit for clientelist practices and expensive social policies such as (uneconomic) employment creation. Second, majority private shareholding enhances the incentives for focusing on profitability, which should increase firm efficiency and growth. Third, the state is still in a position, as a significant shareholder, to influence corporate strategy and development policies in strategic sectors. Finally, state holdings provide access to long-run financing, which is underdeveloped and expensive in private Brazilian capital markets. Indeed, in a survey on the re-emergence of state capitalism, The Economist (b) refers to the ‘Leviathan as minority shareholder’ model as ‘one of the sharpest new tools in the state-capitalist toolbox’ (b: ). Third, and related to the previous point, NDBs need to secure stable sources of funds so that they can act like venture capitalists and ‘lenders of first resort’. That is, NDBs ‘must be able to strike the right balance between risks and rewards, ensuring that investments are structured across a risk-return spectrum so that lower risk investments help to cover higher risk ones’ (Mazzucato and Penna, ). The ability to secure long-run bond financing is one main option along with maintaining equity stakes. The latter allows the bank to benefit from the rare successes in order to offset the inevitable failures. Equity shares also help the state more easily monitor the frequent tax evasion strategies of firms who have benefited from NDB financing. There is evidence from mineral and fuel mining that governments retain a higher share of the proceeds from mineral and fuel rents when state equity shares in these sectors are higher (Lundstøl et al., , ). This is because state presence on boards of directors makes it harder for companies to evade tax. Fourth, in order to ensure macroeconomic sustainability in its balance of payments, NDBs should target sectors and projects that generate net foreign exchange earnings. This is particularly the case for growth strategies that rely on the increasing use of foreign savings to finance investment as in, say, contemporary Ethiopia. When plans for NDB financing do not consider the importance of generating net foreign exchange, balance-of-payments crises tend to follow, which can in turn precipitate a growth collapse, even in countries where the NDB is sound in terms of technical capacity (e.g. Brazil, ‒). Fifth, the historical evidence suggests that national development banks have contributed to effective industrial policy through the financing of ‘national champions’. This has been achieved through the financing of infrastructure and agricultural research in a range of sectors and heavy industrial projects, particularly in the steel, chemical, electronics, automotive, and mining sectors, aerospace, and capital goods. This financing has been oriented towards public enterprises, but also towards large-scale domestic private conglomerates. The emphasis on financing domestic firms stems from the evidence that the most dynamic and innovative firms in LDCs are not generally subsidiaries of multinationals (Amsden, ). This emphasis on vertical industrial policy, or national firm formation, is central to the development of sophisticated and complex production (Amsden, ), since firms form the focal point through which people with skills and ideas can collaborate and eventually migrate to form new

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ventures. It is no accident that major industrial clusters, such as Detroit in the s or Silicon Valley in the s, took off from the spin-offs of workers from one lead firm in each case (Hausmann, ). Sixth, effective NDB financing achieves sectoral and firm success when it involves ‘targeted ambition’. NDB have unwritten complex missions in aerospace, high-tech agriculture, capital goods, high-speed trains, wind and solar technology, bio-fuels and bio-technology, among others. These missions have worked when they involved funding hundreds or even thousands of PhDs to work in relevant research centres to help firms design and develop the technology for innovative capacity, and when the NDB has collaborated with relevant government agencies (e.g. see Perez-Aleman and Alves,  on Brazilian bio-technology efforts; Figueiredo,  on Brazilian agriculture; Moslener et al.,  on Airbus). Albert Hirschman long ago pointed out that ‘big push’ development projects can overwhelm government capacity. However, he also argued that development is about taking on ambitious projects and developing the capacity to solve problems as they arise in the process of learning and experimentation. NDBs provide a focal point to implement selective industrial policy by providing the patient capital and sectoral expertise to undertake these missions. Seventh, macroeconomic policy and conditions need to enable the development of private capital markets and long-run government bond markets. While financial deregulation poses many challenges to state intervention and industrial policy, the dramatic increases in the size of the Chinese and German development banks is the result of their credit ratings and ability to issue long-run bonds. In the case of China, the CDB has itself been instrumental in creating bond markets. It is ironic that some of the most orthodox central banks (e.g. Bundesbank in Germany) provide the context through which significant increases in state development banks (e.g. KfW) can grow.

R Abramovitz, Moses () ‘Catching up, Forging ahead and Falling behind’, Journal of Economic History (): –. Acemoğlu, Daron, Philippe Aghion, and Fabrizio Zilibotti () ‘Distance to Frontier, Selection, and Economic Growth’, Journal of the European Economic Association (): –. Afonso, José, Eliane Araújo, and Bernardo Guelber Fajardo () ‘The Role of Fiscal and Monetary Policies in the Brazilian Economy: Understanding Recent Institutional Reforms and Economic Changes’, The Quarterly Review of Economics and Finance : –. Aldrighi, Dante and Renato P. Colistete () ‘Industrial Growth and Structural Change: Brazil in a Long-run Perspective’. USP Working Paper No. . Department of Economics-FEA. Aldrighi, Dante and Fernando A. Postali () ‘Business Groups in Brazil’, in Asli M. Colpan, Takashi Hikino, and James R. Lincoln (eds) The Oxford Handbook of Business Groups. Oxford: Oxford University Press. Almeida, Mansueto () ‘Desafios da real política industrial brasileira do século XXI’. Discussion Paper No. , Instituto de Pesquisa Econômica Aplicada (IPEA).

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Almeida, Mansueto and Ben Ross Schneider () ‘Globalization, Democratization, and the Challenges of Industrial Policy in Brazil’. Korean Development Institute, July. Amsden, Alice () Asia’s Next Giant. Oxford: Oxford University Press. Amsden, Alice () The Rise of ‘the Rest’. Oxford: Oxford University Press. Amsden, Alice () ‘The Wild Ones: Industrial Policies in the Developing World’, in Narcís Serra and Joseph E. Stiglitz (eds) The Washington Consensus Reconsidered: Towards a New Global Governance. Oxford: Oxford University Press, pp. –. Ang, Yuen Yuen () How China Escaped the Poverty Trap. New York: Cornell University Press. Arias, Diego, Pedro A. Vieira, Elisio Contini, Barbara Farinelli, and Michael Morris () Agriculture Productivity Growth in Brazil: Recent Trends and Future Prospects. Washington, DC: World Bank. Arizala, Francisco, Jesus R. Gonzalez-Garcia, Charalambos G. Tsangarides, and Mustafa Yenice () Growth Breaks and Growth Spells in Sub-Saharan Africa. Washington, DC: International Monetary Fund. Armijo, Leslie () ‘Brazilian Politics and Patterns of Financial Regulation, –’, in Sylvia Maxfield, Chung H. Lee, and Stephan Haggard (eds) The Politics of Finance in Developing Countries. New York: Cornell University Press, pp. –. Armijo, Leslie () ‘The Public Bank Trilemma: Brazil’s New Developmentalism and the BNDES’, in Peter Kingstone and Timothy J. Power (eds) Democratic Brazil Ascendant. Pittsburgh, PA: University of Pittsburgh Press, pp. –. Arrow, Kenneth J. () ‘The Economic Implications of Learning by Doing’, Review of Economic Studies (): –. Bacha, Edmar L. and Regis Bonelli () ‘Padrões de desenvolvimento industrial no Brasil: passado e futuro’. Mimeo. Bagnai, Alberto, Arsène Rieber, and Thi Anh-Dao Tran () ‘Sub-Saharan Africa’s Growth, South–South Trade and the Generalised Balance-of-payments Constraint’, Cambridge Journal of Economics (): –. Baldwin, Richard () ‘Trade and Industrialization after Globalization’s Second Unbundling: How Building and Joining a Supply Chain are Different and Why it Matters’, in Robert C. Feenstra and Alan M. Taylor (eds) Globalization in an Age of Crisis: Multilateral Economic Cooperation in the Twenty-first Century. Chicago, IL: University of Chicago Press, pp. –. Barros de Castro, Lavínia () ‘Financiamento do desenvolvimento: experiência comparada Brasil-Coreia (–)’. Available at https://web.bndes.gov.br/bib/jspui/handle// . Brainard, Lael and Leonardo Martinez-Diaz (eds) () Brazil as an Economic Superpower? Understanding Brazil’s Changing Role in the Global Economy. Washington, DC: Brookings Institution Press. Bruschi, Claudia, Sergio G. Lazzarini, and Aldo Musacchio () ‘Análise do retorno dos investimentos do BNDESPAR por meio de variações nos preços das ações investidas’. INSPER Research Report, São Paolo. Bulmer-Thomas, Victor () The Economic History of Latin America since Independence. Cambridge: Cambridge University Press. Burlamaqui, Leonardo () ‘Global Finance and Chinese Financial Development: The Emergence of a State-led Financial Model of Globally Oriented Financial Governance’. IPEA Working Paper, Brasília.

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Calomiris, Charles W. and Stephen Haber () Fragile by Design: Banking Crises, Scarce Credit, and Political Bargains. Princeton, NJ: Princeton University Press. Cameron, Rondo E. () ‘The Credit Mobilier and the Economic Development of Europe’, Journal of Political Economy : . Colby, Seth () ‘Explaining the BNDES: What It Is, What It Does and How It Works’. CEBRI Working Paper Artigos Vol. , Ano VII, Rio de Janeiro. Colby, Seth () ‘Searching for Institutional Solutions to Industrial Policy Challenges: A Case Study of the Brazilian Development Bank’. PhD dissertation, Johns Hopkins University. De Aghion, Beatriz Armendariz () ‘Development Banking’, Journal of Development Economics (): –. De Luna-Martinez, José and Carlos C. Vicente () ‘Global Survey of Development Banks’. Policy Research Working Paper No. . Washington, DC: World Bank. De Luna-Martinez, José, Carlos C. Vicente, Ashraf bin Arshad, Radu Tatucu, and Jiyoung Song () Survey of National Development Banks. Washington, DC: World Bank. De Magalhães, Luis C. and Carla Rodrigues Costa () ‘Arranjos institucionais, custo da dívida pública e equilíbrio fiscal: a despesa “ausente” e os limites do ajuste estrutural’. IPEA Discussion Paper , Brasilia. Dewatripont, Mathias and Eric Maskin () ‘Credit and Efficiency in Centralized and Decentralized Economies’, The Review of Economic Studies (): –. Elstrodt, Heinz-Peter, James Manyika, Jaana Remes, Patricia Ellen, and César Martins () ‘Connecting Brazil to the World: A Path to Inclusive Growth’. McKinsey Global Institute, May. Ferraz, João C. and Luciano Coutinho () ‘Investment Policies, Development Finance and Economic Transformation: Lessons from BNDES’, Structural Change and Economic Dynamics : –. Figueiredo, Paulo N. () ‘Technological Catch-up and Indigenous Institutional Infrastructures in Latecomer Natural Resource-related Industries: An Exploration of the Role of EMBRAPA in Brazil’s Soybeans and Forestry-based Pulp and Paper Industries’. IRIBA Working Paper No. . London: Department for International Development (DFID). Fishlow, Albert () ‘Latin American Failure against the Backdrop of Asian Success’, The Annals of the American Academy of Political and Social Science (): –. Frieden, Jeffry A. () Debt, Development, and Democracy: Modern Political Economy and Latin America, –. Princeton, NJ: Princeton University Press. Gallagher, Kevin P. and Sarah Sklar () ‘Nationalizing Development Finance: Putting National Development Banks in Context’. Boston University Global Economic Governance Initiative Working Paper. (Cited in Rogerio Studart and Kevin P. Gallagher () ‘Infrastructure for Sustainable Development: The Role of National Development Banks’. GEGI Policy Brief No. . Global Economic Governance Initiative, Boston University.) Gerschenkron, Alexander () Economic Backwardness in Historical Perspective. Cambridge, MA: Harvard University Press. Griffith-Jones, Stephany and Ricardo Gottschalk () ‘Exogenous Shocks—Dealing with the Only Certainty: Uncertainty’. Paper presented at Commonwealth Secretariat Finance Ministers Meeting Tokyo,  October. Griffith-Jones, Stephany and José Antonio Ocampo () ‘A Counter-cyclical Framework for a Development-friendly IFA’, in José Maria Fanelli (ed.) Macroeconomic Volatility, Institutions, and Financial Architectures: The Developing World Experience. New York: Palgrave Macmillan, pp. –.

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

  

Griffith-Jones, Stephany and José Antonio Ocampo (eds) () The Future of National Development Banks. Oxford: Oxford University Press. Griffith-Jones, Stephany, José Antonio Ocampo, Felipe C. Rezende, Alfredo Schclarek, and Michael Brei () ‘The Future of National Development Banks’, in Stephany GriffithJones and José Antonio Ocampo (eds) The Future of National Development Banks. Oxford: Oxford University Press, pp. –. Hamilton, Alexander () Report on Manufactures. Hausmann, Ricardo () ‘Development Collective Know-how and Us’. Lecture at London School of Economics, January. Available at http://www.lse.ac.uk/Events/Events-Assets/ PDF//-LT/-Ricardo-Hausmann.pdf. Hayek, Frederick A. () ‘The Use of Knowledge in Society’, American Economic Review (): –. Hochstetler, Kathryn, and Alfred P. Montero () ‘The Renewed Developmental State: The National Development Bank and the Brazil model’, Journal of Development Studies (): –. Kapadia, Anush () ‘The Structure of State Borrowing: Towards a Political Theory of Control Mechanisms’, Cambridge Journal of Regions, Economy and Society (): –. Khanna, Tarun and Yishay Yafeh () ‘Business Groups in Emerging Markets: Paragons or Parasites?’, Journal of Economic Literature (): –. Kindleberger, Charles P. and Robert Z. Aliber () Manias, Panics and Crashes: A History of Financial Crises. Basingstoke: Palgrave Macmillan. Kingstone, Peter () Crafting Coalitions for Reform: Business Preferences, Political Institutions, and Neoliberal Reform in Brazil. University Park, PA: Pennsylvania State University Press. Kornai, Janos () Economics of Shortage. Amsterdam: North Holland. Krieckhaus, Jonathan () ‘Reconceptualizing the Developmental State: Public Savings and Economic Growth’, World Development (): –. Krugman, Paul () ‘Is Free Trade Passé?’, Journal of Economic Perspectives (): –. Leahy, Joe and Andres Schipani () ‘Culture of Corruption Engulfs Brazilian Elite’, Financial Times,  May. Leff, Nathaniel H. () ‘Industrial Organization and Entrepreneurship in the Developing Countries: The Economic Groups’, Economic Development and Cultural Change (): –. Lundstøl, Olav, Gaël Raballand, and Fuvya Nyirongo () ‘Low Government Revenue from the Mining Sector in Zambia and Tanzania: Fiscal Design, Technical Capacity or Political Will?’. ICTD Working Paper No. . Lundstøl, Olav, Gaël Raballand, and Fuvya Nyirongo () ‘Revenue Sharing in Mining in Africa: Empirical Proxies and Determinants of Government Take’. ICTD Working Paper No. . Mahmood, Ishtiaq P. and Carlos Rufin () ‘Government’s Dilemma: The Role of Government in Imitation and Innovation’, Academy of Management Review (): –. Mainwaring, Scott () Rethinking Party Systems in the Third Wave of Democratization: The Case of Brazil. Stanford, CA: Stanford University Press. Malan, Pedro and Regis Bonelli () ‘The Success of Growth Policies in Brazil’, in Simon Teitel (ed.) Towards a New Development Strategy for Latin America: Pathways from Hirschman’s Thought. Washington, DC: IDB/Johns Hopkins University Press, pp. –. Maskin, Eric S. () ‘Theories of the Soft Budget-constraint’, Japan and the World Economy (): –.

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     



Massi, Eliza () ‘The Political Economy of Development Finance: The BNDES and Brazilian Industrialisation’. PhD dissertation, SOAS, University of London. Mazzucato, Mariana () The Entrepreneurial State: Debunking Public vs. Private Sector Myths, Vol. . London: Anthem Press. Mazzucato, Mariana and L. Randall Wray () ‘Financing the Capital Development of the Economy: A Keynes–Schumpeter–Minsky Synthesis’. Levy Economics Institute of Bard College Working Paper No. . Mazzucato, Mariana and Caetano C. Penna () ‘Beyond Market Failures: The Market Creating and Shaping Roles of State Investment Banks’, Journal of Economic Policy Reform (): –. Mazzucato, Mariana and Caetano C. Penna () ‘National Development Banks and Mission-Oriented Finance for Innovation’, in Stephany Griffith-Jones and José Antonio Ocampo (eds) The Future of National Development Banks. Oxford: Oxford University Press, pp. –. McKinnon, Ronald and Edward Shaw () ‘Financial Deepening in Economic Development’. Washington, DC: Brookings Institution. Mokyr, Joel () ‘Technological Change, –’, in Roderick Floud and Deirdre McCloskey (eds) The Economic History of Britain since , Vol. : –. Cambridge: Cambridge University Press, pp. –. Moslener, Ulf, Matthias Thiemann, and Peter Volberding () ‘National Development Banks as Active Financiers: The Case of KfW’, in Stephany Griffith-Jones and José Antonio Ocampo (eds) The Future of National Development Banks. Oxford: Oxford University Press, pp. –. Musacchio, Aldo and Sergio Lazzarini (a) Reinventing State Capitalism. Cambridge, MA: Harvard University Press. Musacchio, Aldo and Sergio Lazzarini (b) Workshop on State-Owned Enterprises in the Development Process: The Case of Brazil. Paris: OECD. Musacchio, Aldo, Sergio Lazzarini, Pedro Makhoul, and Emily Simmons () ‘The Role and Impact of Development Banks’. Mimeo. Available at http://people.brandeis.edu/ ~aldom/papers/The%Role%and%Impact%of%Development%Banks%%--.pdf. Naqvi, Natalya, Anne Henow, and Ha-Joon Chang () ‘Kicking away the Financial Ladder? German Development Banking under Economic Globalisation’, Review of International Political Economy (): –. Nassar, André M. () ‘Brazil as an Agricultural and Agroenergy Superpower’, in Lael Brainard and Leonardo Martinez-Diaz (eds) Brazil as an Economic Superpower? Understanding Brazil’s Changing Role in the Global Economy. Washington, DC: Brookings Institution Press. North, Douglass () Institutions, Institutional Change and Economic Performance. Cambridge: Cambridge University Press. Orair, Rodrigo O. and Sergio W. Gobetti () ‘Brazilian Fiscal Policy in Perspective: From Expansion to Austerity’. Working Paper No. . International Policy Centre for Inclusive Growth, UNDP and Government of Brazil. Perez-Aleman, Paola and Flavia Chaves Alves () ‘Reinventing Industrial Policy at the Frontier: Catalysing Learning and Innovation in Brazil’, Cambridge Journal of Regions, Economy and Society (): –. Qian, Yingyi and Barry R. Weingast () ‘Federalism as a Commitment to Reserving Market Incentives’, Journal of Economic Perspectives (): –.

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

  

Rodrik, Dani () ‘Rethinking Growth Strategies’, WIDER Annual Lecture . Helsinki: UNWIDER. Rodrik, Dani () ‘The Real Exchange Rate and Economic Growth’, Brookings Papers on Economic Activity (): –. Rodrik, Dani () ‘An African Growth Miracle?’, Journal of African Economies (): –. Saad-Filho, Alfredo and Lecio Morais () ‘Mass Protests: Brazilian Spring or Brazilian Malaise?’, Socialist Register : –. Sayers, Richard S. () Central Banking after Bagehot. Oxford: Oxford University Press. Stiglitz, Joseph E. and Marilou Uy () ‘Financial Markets, Public Policy, and the East Asian Miracle’, The World Bank Research Observer (): –. Stiglitz, Joseph E. and Andrew Weiss () ‘Credit Rationing in Markets with Imperfect Information’, American Economic Review (): –. Storm, Servaas () ‘Structural Change’, Development and Change (): –. Studwell, Joe () How Asia Works: Success and Failure in the World’s Most Dynamic Region. London: Open Road+ Grove/Atlantic. Tavares de Araujo Jr, José () ‘The BNDES as an Instrument of Long-run Economic Policy in Brazil’. CINDES Working Paper, Rio de Janeiro. The Economist (a) ‘Economic Policy in Brazil: Sparking Recovery’,  September. The Economist (b) ‘A Special Report on State Capitalism’,  January. The Economist () ‘Grounded: Special Report on Brazil’,  September. Thirlwall, Anthony P. () ‘Balance-of-payments-constrained Growth Models: History and Overview’, PSL Quarterly Review (): –. Thirlwall, Anthony P. () ‘Thoughts on Balance-of-payments-constrained Growth after  Years’, Review of Keynesian Economics (): –. Torres, Ernani and Rodrigo Zeidan () ‘The Life-cycle of National Development Banks: The Experience of Brazil’s BNDES’, The Quarterly Review of Economics and Finance : –. Trebat, Thomas J. () Brazil’s State-owned Enterprises: A Case Study of the State as Entrepreneur. Cambridge: Cambridge University Press. United Nations Centre for Trade and Development (UNCTAD) () The Role of Development Banks in Promoting Growth and Sustainable Development in the South. Geneva: UNCTAD. Woetzel, Jonathan, Anu Madgavkar, Jeongmin Seong, James Manyika, Kevin Sneader, Oliver Tonby, Andrés Cadena, Rajat Gupta, Acha Leke, Hayoung Kim, and Shishir Gupta () ‘Outperformers: High-growth Emerging Economies and Companies that Propel Them’, McKinsey Global Institute (MGI). Woo, Jung-en () Race to the Swift: State and Finance in Korean Industrialization. New York: Columbia University Press. Woo-Cummings, Meredith (ed.) () The Developmental State. New York: Cornell University Press. Xu, Jiajun, Xiaomeng Ren, and Xinyue Wu () ‘Mapping Development Finance Institutions Worldwide: Definitions, Rationales, and Varieties’, Institute of New Structural Economics. Peking University. Xu, Qiyuan () ‘China Development Bank: Born Bankrupt, Born Shaper’, in Stephany Griffith-Jones and José Antonio Ocampo (eds) The Future of National Development Banks. Oxford: Oxford University Press, pp. –.

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        ......................................................................................................................

             ,           ‘          ’,                         .............................................................................................................

 

. I

.................................................................................................................................. I is a complex process involving interdependent changes across multiple domains and structures of the economy. Since the First Industrial Revolution, technical change has been increasingly recognized as one of the most fundamental drivers of these structural transformations and one of the most distinctive features of modern economic growth (Schumpeter, ; Kuznets, ; Rosenberg, ; Lazonick, ; Abramovitz, ). Technical change makes it possible to improve products, diversify them, and even introduce completely new ones. It is also responsible for increasing productivity within sectors and, in turn, for changes in the way in which enterprises organize production processes and engage with other producers along the value chain—that is, industry organization (Richardson, ). Technical change is thus intertwined with several innovation processes and can lead to the transformation of the ‘organizational economy’ (Simon, ) and the creation of new markets (Schumpeter, ). Over the long run, technical change and related innovation finally trigger broader changes in the fabric of society, its institutional and political configuration, and the distribution of power among organizations and even nations (Hirschman, ; Dosi, ; Amsden, ; Chang, ; Pérez, ; Reinert, ; Andreoni and Chang, , ).

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

 

In some cases, technical change can be so transformative—that is, it can change products and production so much—that the nature and boundary of traditionally defined economic sectors also change. For example, what used to be called an agricultural product or sector becomes more like a manufacturing product or industry, and a manufacturing industry can become more like a service one (and vice versa). These sectoral shifts make it difficult to draw the boundaries of the traditionally defined ‘sectoral terrains’ of agriculture, industry, and services (and sub-sectors within them). From a dynamic point of view, these sectoral shifts also challenge a simplistic ‘linear’ idea of structural change according to which countries develop by moving from the primary to the secondary sector and from the secondary to the tertiary sector. Pre-classical (Antonio Serra, Giovanni Botero, and Pietro Verri) and classical political economists (Adam Smith, Karl Marx, and David Ricardo) relied on the concept of division of labour and rents to account for technical change and scarce resources in economic development (Scazzieri, ; Andreoni and Scazzieri, ; Reinert, Chapter , this volume). Within the classical economic framework, these dynamics were linked to and framed within different sectors of the economy—that is, primary and secondary. The idea of sector was also critical among development economists of the twentieth century in the study of structural change (for a review including circular and cumulative causation theories, see Toner, ) and in accounting for the input‒ output relationships (and linkages) constituting the production matrix of an economy (Leontief, ; Hirschman, ). Several other scholars (Kaldor,  in particular; see also Andreoni and Chang, ) have used the same concept of sector to highlight the special properties of manufacturing, with respect to technical change and productivity dynamics. More recently, with the revival in structural economic analysis (Lin, ; Rodrik et al., ), there has been an increasing focus on sectoral productivity and countries’ normal patterns of structural change, and the ways in which these analyses can inform ‘new’ industrial policy thinking (see Andreoni and Chang,  for a critical review). The conventional way of defining a ‘sector’ is by reference to a class of goods to be consumed and traded in the market (see Weiss, Chapter , this volume, for a discussion on industrial policy from a neoclassical perspective). This standard concept of sector is useful in many respects: for example, it helps in capturing sectoral and sub-sectoral differences; linking a cluster of production activities to specific demand dynamics and markets; and finally, from a policy point of view, identifying and coordinating sets of organizations and institutions around specific sectoral industrial strategies. While widely used in empirical and policy work, the concept of sector has, however, become increasingly problematic in analysing technical change and informing industrial policymaking in both advanced economies and among late industrializers. This is particularly the case as technical change has been increasingly shifting the ‘terrain of the industrial’ and, in doing so, has made conventional approaches unable to capture important sectoral dynamics and ‘industrial mutations’ (Schumpeter, ). These dynamics and mutations include changes in the innovation mode and productivity scope of each sector, sectoral boundaries, and structural change dynamics.

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     



In this chapter we address these limitations in three main steps. First, we review different concepts of sector and assess their usefulness (and limitations) with respect to different analytical questions and policy objectives. We present five reasons why a standard concept of sector alone is problematic for understanding technical change and the shifting terrain of the industrial. Next, we move to the analysis of how technical change is driving the shifting terrain of the industrial. Drawing on Andreoni (), we advance an ‘industrial ecosystem framework’ made up of several sectoral value chains underpinned by different technology platforms. Within this framework, we highlight the role of digital technologies alongside other key enabling technologies and discuss technological change trajectories and patterns of sectoral diversification. Example cases representing several forms of ‘industrial mutations’ are introduced, that is, cases in which technical changes have redesigned the boundaries and technical content of traditionally defined sectors. We examine these developments, identifying both sector-specific and industrial ecosystem targets for industrial policies, and in particular focus on the new ‘digital terrain’ emerging from digital technical change. We conclude by arguing that digitalization makes the rethinking of sectors particularly critical and that industrial policies are becoming even more important in filling the digital capability gap across developing countries.

. T C   C  S: ‘T W’, ‘T H’,  ‘T W’

.................................................................................................................................. Over the last century, since the provocative work of Clapham () denouncing the use of the ‘empty economic boxes’ in the analysis of sectors, economists have widely debated different conceptualizations of sector, in particular, what accounts for the ‘terrain of the industrial’, that is, the industrial sector. The terms of this debate were set by classical political economists in the nineteenth century. Their definition of ‘primary’ and ‘secondary’ sectors stemmed from a set of holistic considerations, including different human needs (primary and secondary); different social classes; the materiality (vis-à-vis intangible nature) of produce; and specific technical properties of production, that is, its return dynamics. Specifically, division of labour as a form of technical change was associated with increasing returns, while rents and non-reproduceable scarce resources were associated with decreasing returns. Building on these classical analytical categories, several contributions have advanced different conceptualizations of sector, often in relation to technical properties of production or produce, and their changes. Indeed, in his seminal work, Piero Sraffa () challenged the foundations of supply curve economics by unpacking the unfolding of increasing and diminishing returns in different sectors of the economy

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

 

(for a development, see Andreoni and Scazzieri, ). In doing so, Sraffa had to confront the problem of defining a sector, its boundaries and its relationship with other sectors. Sraffa recognized two potentially alternative concepts of sector: one according to which sectors are defined by ‘all the undertakings which employ a given factor of production, as, for example, agriculture or the iron industry’; and another more restrictive concept of sector including ‘only those undertakings which produce a given type of consumable commodity as, for example, fruit or nail’ (Sraffa, : ). While the latter commodity/product-based concept of sector has acquired significant traction among economists since the s, as observed by Becattini (), it does shift the problem of defining the sector to one of defining the commodity/product. Commodities can be conceptualized as a pure ‘means of exchange’ or as a ‘means of satisfying specific human needs’. The first definition was adopted in the study of market competition and developed along the idea of different degrees of commodity/ product differentiation (Robinson, ). The second, commodity/product-based definition of sector sees it as a collection of goods that satisfy the same function or class of human needs (Lancaster, ). Following Lancaster’s idea that consumers do not consume goods but aggregates of characteristics, we could claim that a sector is not made up of enterprises producing a certain type of good, but rather of a group of enterprises which produce a certain ‘characteristic’, for example, mobility, communication. The challenges in such a conceptualization of sectors are thus shifted from the level of market exchange to the level of the structure of needs and means at a certain historical moment. Interestingly, the concept of ‘tertiary production’ was first advanced by Fisher () to capture those industries (beyond transport and commerce) directly satisfying consumer wants. By using the consumer’s perspective, Fisher identified and ranked sectors in a sort of descending order of consumption urgency—from primary to secondary and tertiary. From a more empirical perspective, by adopting a relatively simple and commonsensical commodity/product taxonomy and classes, economists have been able to link sectoral-commodity/product dynamics to specific properties of demand/markets, for example differences in price elasticity. Others have also attempted to develop taxonomies of products based on their technological qualities and content. For example, building on the classification proposed by the OECD () and other indicators of technological activity and rankings in manufacturing sectors, Lall () developed a technological classification of tradable products distinguishing ‘resource-based manufactures’, ‘low-technology manufactures’, ‘medium-technology manufactures’ and ‘high-technology manufactures’. Each of these product clusters were also associated with traditionally defined economic sectors in an empirical analysis of industrialization and structural change. However, while Lall’s widely used classification is aimed at distinguishing different products (and associated sectors), their ‘technological ranking’ is intuitively associated with both technical properties of commodities and the technical properties of the production processes underpinning them (e.g. the technology or R&D intensity of these products/sectors).

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     



The alternative conceptualization of sectors is indeed based on ‘factors of production’ more than commodities and their properties, as already pointed out by Sraffa (). This production-based conceptualization of sectors found some developments in the s and s, especially among applied economists. For example, Wolfe (: ) proposed to ‘define the primary sector as that group of industries in which an increase in productivity, in terms of goods and services per man-hour, is limited by natural growth factors, the secondary by mechanical factors, and the tertiary by relatively unaided human skills’. Scholars using input‒output analysis similarly recognized a sector as defined by firms using the same production function. Building on the Marshallian definition of a sector proposed in Industry and Trade (), other scholars defined a sector as the set of firms which are capable—at least potentially—of performing each other’s production processes within certain parameters of efficiency. This definition of sector recognizes how the boundaries of the sector are not necessarily set but can change depending on the number of firms that have the incentives and capabilities to engage in certain production activities. A company might be potentially in multiple sectors, even if it is operating in only one commodity/product-defined sector. Indeed, as we shall see, diversification and lateral migration across sectors are typical dynamics of the growth of the firm (Penrose, ; Lazonick, ; Best, ; Andreoni, ; Chapter , this volume). Within this family of production-based (more than commodity/product-based) definitions of sector, other scholars have advanced a conceptualization of sector based on their ‘technical progress’ and distinctive ‘patterns of innovation’. With respect to the first one, for example, Fourastie (: ) proposed calling ‘primary and secondary, activities that have enjoyed great technical progress, reserving the term primary for agricultural activities and the term secondary for nonagricultural activities’. According to him, tertiary activities are those which have enjoyed ‘only slight technical progress’. While this type of definition remains unsatisfactory, it introduces a further dynamic criterion to distinguish sectors, that is, their scope for technical change. More recently, Pavitt () introduced an innovative taxonomy to study sectoral patterns of technical change and innovation modes. Pavitt’s taxonomy consists of four categories of industrial firms: (a) Supplier-dominated, including firms mainly operating within traditional manufacturing sectors such as textiles and agriculture which tend to rely on technical innovations external to the firm; (b) Scale-intensive, including large firms producing basic materials like steel and plastics and consumer durables such as automotive. For firms operating in these industries, innovation may be both internal and external to the firm with a medium level of appropriability; (c) Specialized suppliers, including smaller firms and specialist contractors whose main activity is to produce high-tech machineries, tooling, and instruments.

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Given their specialization and customization capability, these firms have a high level of technology appropriability; (d) Science-based firms, including high-tech R&D-intensive enterprises relying on both internal and external sources of innovations (e.g. public laboratories, university research), typically operating in industries like pharmaceuticals and electronics. Given their continuous focus on product and process innovation, these are firms with a high degree of appropriability from tacit knowledge and formalized, though protected, knowledge, that is, patents. As pointed out by Castellacci (): ‘Pavitt’s model of the linkages between sciencebased, specialized suppliers, scale-intensive and supplier-dominated industries provides a stylized and powerful description of the core set of industrial sectors that sustained the growth of advanced economies during the Fordist age.’ Unlike the commodity/product-based definition of sectors, the Pavitt taxonomy enables sectors to be defined according to the ways in which technical change and innovation occur within different types of companies within these sectors and, thus, how organizations become competitive (Lazonick, ). Competitiveness conditions—and, in particular, profitability—are also determined by the degree of barriers to entry and concurrent imperfect competition. Reinert () uses these two parameters to establish a dynamic taxonomy of economic activities and measures the extent to which profitability results (or not) in the ability of firms to raise wages. In this framework, how fast technical change becomes subject to ‘perfect competition’—the ‘gravity’ in the system—will be a key determinant of the ability of an economic activity to raise living standards. The dynamic imperfect competition that leads to high barriers to entry—high profits and the possibility of high wages and high taxation—historically was mainly found in manufacturing industry, although new sectors have been witnessing similar patterns. Alongside the two main conceptualizations of sector—commodity/product-based or production/technology-based—briefly reviewed so far, there is one last definition which is associated with a more sociological and spatial way of clustering economic activities and firms. Building on Alfred Marshall, Giacomo Becattini (, ) resurrected the concept of ‘industrial district’ as a way of defining clusters of firms based on their social ties, geographical proximity, technological interdependencies, and mixed relationships of cooperation and competition. This neo-Marshallian idea of identifying firms according to their ‘sense of belonging’ points to the fact that the relationships with a certain location of production (and market) define the firm better than its produce or production technologies. The idea of industrial district points to the existence of a unit of production beyond the individual firm, that is, a cluster of ‘locally embedded firms’ whose characteristic features result from their embeddedness rather than referring to a simplistic product- or production-based classification of sector. Two firms in the same sector are going to be very different, despite producing the same product (or using the same factors of production) if one of them is embedded in a certain industrial district, while the other is not (see also Andreoni, ; Andreoni and Lazonick, ).

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This brief excursus into the history of economic analysis reveals how sectors (and firms as their components) can be defined according to the ‘what’ they produce— commodity/product-based classification—, the ‘how’ they produce—production/ technology-based classification, and the ‘where’ they produce—location-based classification. Each of these definitions tends to reveal certain issues, while concealing others. And according to our epistemological stance in the conceptualization of sector, we might end up having a more or less clear picture of the ‘sectoral terrain’ we are considering, its boundaries and its role in driving structural change. In this respect, and with a focus on goods, Oscar Lange writes: ‘the classification of goods cannot be made on a purely arbitrary basis, because the laws of economics would be then dependent on the particular classification adopted. This would restrict the significance of the propositions of economics to a degree that would make them valueless. Each proposition can be changed in its opposite by a mere reclassification of goods’ (Lange, : ). Let’s then consider issues that arise from different classifications of sectors and how they impact our understanding of technical change. To start with, a commodity/product-based classification of sectors tends to become quickly outdated because of changes in products and their differentiation. The fact that since the ICT revolution material products might become platforms for accessing intangible contents or services has accelerated this disconnect between traditionally defined sectors and their differentiated products (Andreoni, Chang and Labrunie, ). Thirty years ago, Becattini (: ) had already posed the following question: ‘What is the significance today—amid the growing differentiation and personalization of products, intense intra-sectoral fragmentation, and the proliferation of “cross-sectors”— of the traditional “industries” and the old, clearly-defined markets for substantially homogeneous items?’ Moreover, as we have seen, when we adopt a definition of sector simply based on ‘what’ is produced, there is a tendency to define primary sectors like agriculture or fishing as ‘low’-technology sectors. Their produce is perceived as relatively basic, with unfavourable terms of trade and targeting relatively inelastic demand. However, if we instead conceptualize a sector according to the ‘how’ and, potentially, ‘where’ of production, we realize a number of important factors associated with technical change which are also relevant for industrial policy. First, the issue of heterogeneity in the how of production. If we look at the ‘how’ of production we discover that products within the same product groups can be obtained from extremely different production processes involving different types, combinations, and levels of technology (Andreoni, ). This means that product-based definitions of sectors might obfuscate high degrees of structural heterogeneity within sectors and might induce the wrong type of comparative assessments across sectors (Andreoni and Chang, ; see also Andreoni and Tregenna,  on problems of structural heterogeneity in the analysis of premature de-industrialization). For example, let’s look at the food and beverage industry. Food can be (and, indeed, still is) produced using traditional techniques and relatively basic machinery (especially in developing countries);

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however, in other countries food production has reached extremely high levels of industrial sophistication. Food products are obtained from ‘industry-type’ controlled processes, involving complex and highly automated technologies to benefit from scale economies and meet quality standards. In these cases, food production also relies on just-in-time global supply chains—as in the automotive industry—and the distribution of the produce involves sophisticated cold and logistics chains for timely market delivery. All this suggests that food and beverages can be a medium/high-tech industry, depending on the ‘how’ of production. Second, as already noted, this heterogeneity in the ‘how’ of production is often associated with heterogeneity in the ‘where’ of production. Becattini () distinguishes firms within the same sectoral classification—for example, garments—according to the external economies they can benefit from. A garment firm might be ‘encamped’ in its location and receive very little help; thus, this firm might easily move from that location without a reduction in productivity or innovativeness. In contrast, another garment firm might be ‘rooted’ in its location and benefit from externalities arising from its productive surroundings and relationships with other firms or markets. These collective capabilities are major drivers of innovation, technical change, and diversification (Penrose, ; Freeman, ; Andreoni, ). Even if these two firms are both sectorally defined as garment firms, the encamped firm is distinctively different from the rooted firm when it comes to their production, technological, and organizational capabilities. In this case, the ‘where’ of production, that is, being rooted in a certain industrial district or not, becomes the main unit of analysis for understanding heterogeneity. Third, the issue of industrial mutations. In order to reach ever-rising product standards, even a sector traditionally perceived as low tech must transform itself into a higher-tech sector. This means it will have to adopt complex processes and technologies and rely on quite sophisticated supply chains. For example, producing and selling fresh fruit might require more sophisticated technologies than producing a Tshirt, if to retain freshness firms in the sector must engage with sophisticated coldchain and logistic solutions (Cramer and Sender, ). An agrobusiness firm involved in this sector and operating in markets that value freshness will undergo an innovative process of ‘industrial mutation’ making it more like what would be traditionally considered a manufacturing company. Fourth, the issue of the sources of technical change. By changing the ‘how’ of production, that is, changing the technologies and processes required to obtain a certain product or reach a certain market, even traditional sectors can become major drivers of technical change and innovation. Indeed, by responding to location specific challenges and opportunities in the production of agro-commodities, firms in the agricultural sector or mining have triggered and steered innovation in a number of machineries, tooling, and instrumentation industries. Again, if we simply limit our attention to the commodity/product itself without looking at the production process behind it, we might miss these important technical changes. For a long time, the agricultural sector has been associated with decreasing returns and other stylized

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features which undermine the scope for ‘manufacturing agrarian change’ (Andreoni,  and ). Fifth, understanding structural change as a non-linear process. Grading sectors from primary to secondary and tertiary according to a simple focus on the ‘what’ produced or a superficial understanding of the ‘how’ of production, has often resulted in a ‘linear’ view of structural change. According to this view and traditional sectoral categorizations, countries are naturally supposed to move from agriculture to manufacturing and finally to services. This linear view of structural change is, however, problematic with respect to the analysis of the relationships between agriculture and manufacturing, between manufacturing and services, and between services and agriculture. The reason is that in the process of structural change, traditionally defined sectors continuously cross their boundaries and thus shift their sectoral terrains. Technical change and technological interdependencies across sectors make for a large part of these sectoral crossings and shifts along the process of structural change. Kay () pointed out how the relationship between agriculture and manufacturing is symbiotic in economic development, as the development of each sector creates the conditions for the development and productivity increases of the other in a circular and cumulative fashion, more than in linear process. Increasing agricultural productivity results from industrializing agricultural processes through technical change stemming mainly from manufacturing (Andreoni, ). These intersectoral linkages are destined to change and ‘vary according to the particular phase of the development process and as structural conditions and international circumstances change’ (Kay, : ). For example, it has been observed that, with the increase of productivity in agriculture, linkages between agriculture and services have also been expanding in magnitude and quality. Examples include post-harvest facilities such as transport, communications, information services for production control in agriculture, market services. Some of these activities sit at the boundaries of traditionally defined agricultural and service sectors. Similarly, since the s, several scholars have pointed out how the boundaries between manufacturing and services have become blurred as a result of two parallel processes of change. These are, first, the outsourcing of several activities like R&D from manufacturing companies to service companies and second, the ‘servitization’ of manufacturing companies, the process whereby companies in manufacturing sectors increasingly add value to their products by adding post-sales services (for a review see Baines et al., ). Because of the outsourcing of business- and production-related activities from traditionally defined manufacturing companies, we have witnessed the expansion of the service sector (also from a national accounting point of view). If we look at product-based classifications of sector, companies engaging in R&D or technology scaling-up are in the ‘service sector’, as they provide business services. However, if we look at the ‘how’ they produce these services we realize that this happens by engaging in technology activities which were traditionally classified within the manufacturing sector. Similarly, many companies included in manufacturing sectors are increasingly offering a wide array of product‒services combinations. For

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example, traditional downstream services are built into the product—‘embedded services’, such as in-flight monitoring of aero engine systems. In other cases, such as the provision of network-infrastructure solutions in information and communication technology (ICT), a company can provide an ‘integrated product‒service solution’ satisfying several consumer needs. Beyond case study research, Park and Chan (: ) were among the first to show empirically how ‘the evolution of the intersectoral relationship between services and manufacturing in the course of development is symbiotic, in the sense that . . . structural change of the former is bound to affect that of the latter’. To summarize, going beyond the commonly used commodity/product-based classification of sectors, in this section we have shown how the ‘what’, the ‘how’, and the ‘where’ of production matter. Each conceptualization of sector offers different analytical lenses for navigating the traditionally defined sectoral terrains, and their heterogeneity and evolving boundaries in modern industrial economies. Technical change is the main driver of these heterogeneous and evolving structural transformations. We have pointed out how, with changing production technologies, technical change constantly reshapes the nature of traditionally defined sectors as it changes the production activities that firms are conducting within them. For example, firms in the traditionally defined agricultural sector might start using advanced technologies to guarantee quality standards of certain products for the international market. Similarly, manufacturing companies in mechanical industries might start using advanced digital technologies to perform activities which were traditionally associated with electronics industries. Finally, manufacturing companies might become service companies, and vice versa (for a detailed discussion on ‘technology fusion’, see Andreoni et al., ). In section . we will look at how technical change underpins changes across different and blurred sectoral terrains and how, in doing so, it opens space for diversification and innovation in the what, how and where of production. In some cases, even completely ‘new’ sectors can emerge at the interfaces of traditionally defined sectors. This more systemic/cross-sectoral focus does not mean abandoning traditional sectoral distinctions or undermining the existence of sectoral differences across economic activities. As we have seen in this section, different types of conceptualization of sectors serve different analytical purposes and can lead to different industrial policy considerations and different sectoral targeting decisions. However, we suggest looking at traditionally defined sectors from different perspectives and within a systemic framework that fully acknowledges interdependencies across sectors and cross-cutting technical change dynamics. This is particularly important in the study of technical change. As stressed by Nathan Rosenberg (): It is necessary to discard the familiar Marshallian approach, involving as it does the definition of an industry as a collection of firms producing a homogenous product—or at least products involving some sufficiently high cross-elasticity of demand. For many analytical purposes it is necessary to group firms together on the basis of some features of the commodity or final product; but we cannot properly appraise important aspects of technological developments in the nineteenth century

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until we give up the Marshallian concept of an industry as the focal point of our attention and analysis. These developments [rapid technical change in the American production of machine tools] may be understood more effectively in terms of certain functional processes which cut entirely across industrial lines in the Marshallian sense. (Rosenberg, : ; italics added)

. ‘S T’: T C  D  I E

.................................................................................................................................. Modern industrial economies consist of complex and dynamic interdependencies spanning along and across various traditionally defined ‘sectoral terrains’ and technology platforms. As eloquently documented by Tassey (: ): ‘Most modern technologies are systems, which means interdependencies exist among a set of industries that contribute advanced materials, various components, subsystems, manufacturing systems, and eventually service systems based on sets of manufactured hardware and software. The modern global economy is therefore constructed around supply chains, whose tiers (industries) interact in complex ways.’ In fact, while some technologies (including organizational techniques) are sector specific, several others are cross-cutting traditionally defined sectoral boundaries, that is, they are deployed (or deployable) transversally. These are not simply traditionally defined general purpose technologies (GPTs),¹ but also clusters of technological and organizational capabilities which firms deploy in producing different products, reaching certain product standards and functionalities (Penrose, ; Richardson, ; Andreoni, ). Because of these cross-sectoral technological and organizational interdependencies, technical change like the introduction of a new chemical process, industrial material, machine, tooling, sensor, or embedded software can stem from one sector and then ‘reverberate’ across many sectors and several companies constituting them. Sector-specific adaptations of these new technologies are always present, although in the applications of these technologies companies from different sectors rely on the same technology platforms (Andreoni, ). These interdependencies involve different types of business organizations and supply chains both competing and cooperating along sectoral chains of production tasks and activities. Back in the s, Luigi Pasinetti () stressed how the term ‘industrial sector’ fails to describe the structure of economic sectors. It was for this reason that Pasinetti introduced the concept of ‘vertically integrated sector’ to analyse the chain structure of tasks and activities of economic sectors. Along these lines, more recently, ¹ GPTs have been studied especially with reference to the emergence of new technology paradigms and their broader impact on the economy (for a review see Jovanovic and Rousseau, ; Brenahan, ).

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the literature on global value chains/global production networks has focused on the global governance and distribution of production functions, activities, and tasks among different networked production units located in different countries (a multi-tiered organizational structure). Within this framework, the dynamics of value creation and capture have been centre stage (Milberg and Winkler, ; Gereffi, ; Ponte et al., ). These studies tend to go beyond the sector as the main unit of analysis, replacing it with ‘task’ and ‘chain/network’. A production task is linked to a certain functional stage of the production process or the production of a finite intermediate product component. The network is multi-country (often more regionally confined than truly global) and composed of multiple productive organizations involved in different stages and potentially operating in multiple sectors (for a critical review see Andreoni, a). A number of ecosystem frameworks have been introduced with a view to capturing both these systemic dynamics of technical and organizational change, thus capturing the new terrain of the industrial. Among them, Andreoni () developed a model of industrial ecosystem consisting of a matrix of distinct sectoral value chains underpinned by different technology platforms (also called clusters of capability domains in specific industrial locations). The idea of sectoral value chain is based on a productbased conceptualization (and empirical operationalization) of sector, the ‘what’ of production. However, it also integrates other insights into sector-specific supplychain features, different degrees of ‘vertical integration’, and spatial distribution of production activities in different locations. Each sectoral value chain is underpinned by a sector-specific combination of technologies; thus, each sectoral value chain can also be identified according to the ‘how’ of production. These combinations of technologies draw from broader cross-sectoral technology platforms constituting several types of key enabling technologies, including modern digital ones. These enabling technologies can be potentially deployed across a range of different sectoral value chains, bypassing the traditional idea that certain sectors are doomed to be low tech or characterized by low scope for innovation and technical change. Figure . illustrates the industrial

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 . Industrial ecosystem framework Source: Author.

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ecosystem framework, with a focus on a number of digital technology platforms (and other key enabling technologies) and a list of representative sectoral value chains. Within this framework, technical change is a sector-specific process as it involves changing sector/product-specific combinations of technologies whereby products are designed, produced, commercialized, and serviced. However, technical change is also a cross-sectoral process of transformation constantly redefining the boundaries across sectors and the emergence of new ones. Emerging technologies tend to have a disruptive impact on existing technology platforms, and require organizations to develop new sectoral value chains capable of producing and/or deploying and/or commercializing them for the market. With the increasing transformation of the global manufacturing landscape and the digitalization of the economy, cross-sectoral technical change and innovation dynamics have acquired increasing importance. Traditionally, industrial ecosystems structured around vertically integrated sectors would mainly experience internal processes of ‘structural learning’ (Andreoni, ), whereby a new technical solution emerging in one sector would be increasingly adopted by firms in the same sector to transform their business. In modern industrial ecosystems characterized by the presence of multiple sectoral supply chains involving multiple actors (at different levels/tiers) located in various locations, the emergence of an innovative digitally networked solution can rapidly spread across sectoral value chains. These technical change dynamics are ultimately the result of innovative processes occurring within business enterprises (and other organizations and institutions) and their continuous attempt to strike a balance between their specialization and diversification, given certain market opportunities/incentives and their capabilities. While often presented as disruptive technological changes, many digital technologies have evolved and emerged from the same engineering and organizational principles as in previous industrial revolutions and have been incrementally diffused across sectoral value chains since the s (Andreoni and Anzolin, ; Andreoni et al., ). These innovative processes often involve firms crossing sectoral boundaries and venturing into different sectoral terrains. Interfaces between sectoral value chains become areas for the development of cross-sectoral ‘symbiotic relationships’. For example, advanced materials such as membranes and polymers for micro-tubing developed in the design and manufacture of medical devices can be adopted to increase the performance of components and technology systems in the automotive sector. The production of the same advanced materials might also require fundamental innovations in the production technology supply chains (e.g. co-injection technologies for micro-tubing), and a set of infra-technologies to test and validate the new products or production technologies. These new production technologies, in turn, can lead to advances and the removal of bottlenecks in the production technologies underpinning other sectoral supply chains (Andreoni, ). The industrial ecosystem framework points to the importance of tracking these trajectories of technical change, cutting across sectoral boundaries and constantly reshaping each sectoral terrain. For example, throughout the s and s,

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technical change and innovations in electronics and mechatronics have transformed the automotive and machine tool industries—today electronics is dominant even in traditional metal mechanical sectors. Similarly, the increasing reliance on digital technology platforms in modern production is altering the nature of agriculture and manufacturing production, while blurring the boundaries between physical and digital production technologies and service systems. Across all sectors we can see signs of these ‘industrial mutations’: from satellite systems controlling autonomous tractors or data-driven feeding systems in agriculture to advances in intelligent automated systems, robotization, and additive manufacturing, and related data analytics—IoT, digital platforms, and digital supply chains in industrial and service sectors (Sturgeon, ). Industrial mutations driven by technological change—in particular, the widespread diffusion of digital technologies—have started shifting the terrain of the industrial and led several scholars to claim that we are on the verge of a new industrial revolution. However, these shifts are not occurring in the same ways across all production locations, regions, and countries. The ‘where’ of production does matter when we move from a stylized discussion of technical change across sectoral value chains and technology platforms to a more specific analysis of technical change in context. Digital technical change opportunities are not equally distributed as companies, regions, and countries face different challenges. The effective adoption of these new technologies presupposes the existence of productive organizations and supply chains around them endowed with basic and intermediate production capabilities and supported by enabling infrastructures such as reliable electricity, standardization, and connectivity. If we look at a wide range of fast emerging and developing countries throughout the first two decades of the twenty-first century, these conditions are still largely missing for most developing countries, as well as in many regions across mature industrial economies (Andreoni and Anzolin, ). Among late industrializers like China and India, while the use of digital production technologies is speeding up, these technologies are still concentrated in a few sectoral value chains (and companies and supply chains within them) and the full automation of routinized tasks is far from being as diffused as many observers seem to suggest. There are multiple reasons for this, including the infrastructural preconditions and trade-offs posed by digital production technologies, with respect to both the hardware and software of these technologies and, even more critically, their production system integration. Having said that, several production locations have started connecting and cross-sectoral value chains using digital production technologies are gradually emerging, also thanks to industrial policies by governments such as those of China, Thailand, and Malaysia (Andreoni, b). In low- and middle-income countries, such as Brazil and South Africa, companies are facing more fundamental problems related to access to these digital production technologies, their integration and retrofitting into existing production systems, not to mention the availability of basic production capabilities and enabling infrastructure. In these countries, the lack of job creation is not so much the diffusion of digital technologies as, largely, the result of structural and political economy problems, including premature de-industrialization, lack of productive organizations in key

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GVC stages, and basic productive capabilities (Andreoni and Tregenna, ). In countries like Thailand and Vietnam where the political economy configuration— developmental state coalition—has led to high levels of investment and increasing numbers of export-led competitive companies, governments are pushing for digital technical change and diffusion, especially in sectors like automotive and electronics. In least developed countries, especially in the African continent, the lack of competitive productive organizations makes the deployment of these digital technologies in production even more rare. While there are suitable applications for some basic information and communication technologies (ICTs), such as for financial transactions on online finance platforms or sharing some basic agriculture price data, these are in fact more like applications of the Third Industrial Revolution than actual digital production technologies. A limited number of companies are experimenting with the use of digital production technologies, to the extent they are involved in production activities. So, for example, we see some experimental applications in high-value agricultural products, extractive processes, and trade logistics. Unfortunately, given the limited amount of manufacturing industries and competitive companies, these countries are still unable to capture the potential ‘digital dividend’ promised by the big new wave of technical change. To summarize, the diffusion and effective deployment of digital technologies across several sectoral value chains will be determined by several factors. In particular, the extent to which these new technologies are the most cost-effective way to produce a certain component or product (still not always the case), and the extent to which companies have a sufficient bundle of capabilities to make the absorption and effective deployment of these technologies possible. Without the development of basic and intermediate-level capabilities, that is, basic production capabilities, and technology absorption and retrofitting capabilities, digital technical change will remain a technological mirage. Industrial policy can, however, play an important role in shaping technical change and redesigning the sectoral boundaries and terrain of the industrial. The final section before the conclusions (section .) looks at the implications of technical change and the shifting terrain of the industrial for industrial policy design (what selectivity means), and implementation (what cross-sectoral institutions are required).

. I P: C  O   N D T

.................................................................................................................................. Since the First Industrial Revolution, industrial policies have always shaped and driven the transformation of the economy, particularly when engagement with new technologies was uncertain and required coordination and the commitment of resources

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(Chang, ; Andreoni and Chang, ). The theoretical perspectives advanced in this contribution have pointed to the fact that the opportunities associated with technical change are very heterogeneous, in some cases sector and process specific, in other cases relying on cross-sectoral technology platforms underpinning several sectoral value chains. With the emergence of a new ‘digital terrain’, several manufacturing industries remain the main target of industrial policy investment. However, while some of them—the machine tool industry, for example—might play a key ‘technology push role’, others—high-tech agriculture and production-related services in particular— will play a key ‘demand pull role’. For example, the application of manufacturing principles to agricultural production could deliver dramatic productivity gains and better international market access, while creating the demand for an increasingly advanced and data-driven agricultural equipment industry. The enormous potential of digitalization in mining could similarly be a demand pull factor towards the development of world-leading mining equipment industries in the African continent and several other countries in Latin America. By targeting investments at the intersection of these demand pull and technology push dynamics, developing countries can also manage to decrease their reliance on pre-made machinery from advanced industrial economies—and the associated trade burden. Investing in these intersections of emerging industrial ecosystems can be also a way of laterally entering sectoral value chains and engaging with technologies which would be otherwise difficult to access. The specific challenges faced by developing countries in engaging with the Fourth Industrial Revolution can be clustered in five main groups.

.. Technology Absorption, Deployment, and Technical Change: ‘Capability Threshold’ First, the basic and more advanced production capabilities required for the absorption and effective deployment of the new digital production technologies, and their diffusion along the supply chains, are scarce and unevenly distributed. Moreover, digital production technologies have also raised the ‘capability threshold’ that companies are required to achieve to make effective use of the new technologies. This is not because parts of these technologies are completely new—for example, automated machinery goes back at least as far as the Second Industrial Revolution (IR), but mainly because the Fourth Industrial Revolution (IR) is about the ‘fusion of existing and new technologies’ into complex integrated technology systems (Tassey, ; Andreoni, Chang, and Labrunie, ). Managing complex integrated technology systems like a fully automated production line, combining robots and IoT technologies, is an extremely demanding task for a productive organization in a developing country.

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.. Production System: Retrofitting and Integration Second, industrialization is about commitment of resources under conditions of uncertainty (Chang and Andreoni, ). Most of these commitments involve physical capital that embodies certain technologies and cannot be remoulded in any significant way to embody other technologies. Very often the commitments are organizational too, involving individuals specializing in specific skills. These commitments are critical because they raise productivity, for example by enabling economies of scale in production. However, depending on the degree of reversibility of the investments, these commitments make future changes more difficult. This introduces a very specific challenge in developing countries. Existing companies that can make technology investments have already committed resources and have to see how they can retrofit and integrate new digital production technologies into their existing production plants. Setting up brand-new plants is less common as it requires significant long-term investment and access to markets, and these new plants may be difficult to run given the lack of basic and digital infrastructure.

.. Infrastructure: Basic and Digital Third, digital production technologies are very demanding when it comes to the infrastructure required to enable their use in production. Developing countries face significant challenges providing affordable and reliable electricity, as well as good enough connectivity. In some cases, these infrastructural bottlenecks have been bypassed by off-grid energy technologies and wireless connectivity systems. While these solutions work in certain areas, they are not always able to provide the quality and reliable services needed to run digital production technologies effectively. As a result, the productivity and quality improvements that digital production technologies offer are offset by these infrastructural bottlenecks, which can make technology investments by individual companies too risky and ultimately uneconomical.

.. Technology Diffusion: IR Islands and the Digital Capability Gap Fourth, despite the fact that in almost all developing countries it is possible to find ‘IR islands’, that is, a company which is engaging with some digital production technologies, many of these technologies remain contained within the company and their production cells. Occasionally, a few close suppliers who have the basic production capabilities to make use of them might be linked to these IR islands. Moreover, the IR islands often rely on enabling infrastructural capabilities (connectivity, electricity,

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etc.) built by the same company at their own cost for their own plants. Without these infrastructures, companies would not even be able to switch on digital production technologies. Around these IR islands the large majority of companies and sectors are still operating fully within the Third Industrial Revolution technology paradigm and are unable to operate at the same standards as the island companies. In some other cases, especially among least developed countries, companies have not even engaged with the Second Industrial Revolution yet. This means that it is extremely difficult for the leading companies—such as an OEM—to link backward and nurture their supply chains. The ‘digital capability gap’ between company islands and suppliers is so extreme and so costly to address (given the existing endogenous asymmetries—see section ..) that the diffusion of IR technologies remains very limited.

.. Technology Access and Affordability: Endogenous Asymmetries Fifth, digital production technologies are complex and are controlled by a limited number of advanced countries and their leading companies. Developing countries rely enormously on the importation of these technologies from advanced economies, and in many cases even when they are able to mobilize significant resources to access them, they are tied to their buyers with respect to both hardware and software components. International buyers and OEMs control the source, type, and utilization of the digital production technologies by setting parameters of engagement for the suppliers. Those who cannot meet these parameters are cut out. The importance of using common protocols and software platforms for the deployment of digital production technologies carries the risk of a verticalization and concentration of power. Also, many of these technologies are not ‘plug and play’, that is, the acquisition of the hardware goes hand in hand with the need for expensive technology services and royalties for the use of the related software (Sturgeon, ). To capture these opportunities and address these new challenges, the most recent international industrial policy experiences point to the importance of adopting new industrial policy frameworks and principles (Andreoni, , a; Andreoni and Chang, ; Andreoni and Tregenna, ). These new frameworks should capture the changing reality of production systems and products, and their underlying technology platforms and organizational models, that is, the industrial ecosystem. New industrial policy principles should also reflect the need for more strategic coordination among (and within) public and private sectors; better targeting and policy alignment; and the introduction of feasible policies whose implementation goes hand in hand with a change in the country’s political economy and the emergence of new productive alliances, the following sentence refer to all five points above ..–... Against this background, the following five industrial policy design principles must be considered if the opportunities of the new digital terrain are to be captured:

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• Digital industrialization opportunities are about both incremental changes in production and disruptive technological innovations. Industrial policy must be appropriate, that is, it must address those foundational—basic and intermediate— technical and organizational capability requirements without which the digital innovation opportunities cannot be captured, effectively deployed, and diffused across the industrial ecosystem. • Digital industrialization is sustainable and inclusive only if it creates conditions for more domestic value creation, capture, distribution, and retention. Digital technologies provide new platforms for developing linkages in the ecosystem, including more and new productive organizations and customers. Governing the technological, competition, and regulatory processes through which these linkages are formed (or prevented) is critical for sustainable value addition and distribution in the economy. Digitalization introduces a new policy dimension in the strategic management and regulatory enforcement of ‘glo-cal’ relationships. • Systemic changes call for systemic policy frameworks. Digital industrialization is about a systemic transformation of the economy, that is, the emergence of a new industrial ecosystem. This is why the effectiveness of a digital industrial policy will depend on interventions able to reflect both the specificities of existing sectors and the new opportunities emerging within and across them. • Strategic targeting, coordination, and policy alignment are critical for effective implementation. Systemic transformation cannot be achieved with generic policy frameworks. Strategic choices have to be made to unleash the potential that digital technologies offer for the innovative industrial renewal of existing sectors, and the emergence of new competitive players in the industrial ecosystem. For successful policy implementation, these choices must be effectively coordinated and aligned, and budgetary inconsistencies and scarce public resource dispersion and capture avoided. • New coalitions for change forged around better aligned productive interests are necessary for the successful implementation of industrial policy. The design of industrial policy must take into account the different interests, capabilities, and distribution of power within and among different organizations and constituencies in the economy, and must find ways in which policies can lead to better alignment of productive interests. Without such alignment, policies tend to be fragmented, difficult to enforce, and vulnerable to unproductive rent capture. The digital industrial policy principle and targets highlighted above point to the need for both sector-specific digital industrial policy and cross-sectoral interventions, as well as new ways of factoring in an assessment of the political economy feasibility of industrial policy interventions. • Sector-specific measures will take into account the organization, needs and conditions of firms within a particular industry, in particular the specific types of: digital skills; digital technology infrastructures and services; challenges and barriers to

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linkages development; competition conditions and value capture; and sectoral regulatory frameworks and incentives, including procurement and market regulation. • Cross-sectoral interventions should focus on those opportunities and challenges that are faced by different firms across sectors, especially those related to broader foundational capabilities (e.g. basic and transversal digital skills, digital and manufacturing extension services), technology infrastructure (e.g. digital software licensing, connectivity, data quality, and affordability) and broader financing, investment, and regulatory conditions in the country. The effectiveness of sectoral and cross-sectoral interventions across key policy areas will depend on the extent to which the government is able to reach strategic alignment between sectoral measures and cross-sectoral interventions, and to develop a governance framework beyond policy silos. Breaking out of policy silos is thus both a matter of what/how policy interventions are designed as well as how resources are allocated and governed along different structural cycles (Andreoni et al., ; Andreoni and Chang, ). The industrial ecosystem (Andreoni, ) provides the framework to operationalize and foster cross-sectoral innovations around mission-oriented industrial policies (Mazzucato, ; Mazzucato and Kattel, Chapter , this volume). Mission-oriented industrial policy provides a vision for the creation of new productive sectors and markets around emerging human needs and social challenges. These missions are not simply visions; they are also focal points for coordination within an industrial ecosystem as they trigger transformations along and across technology platforms and sectoral value chains. For example, the environmental sustainability grand challenge requires a concerted transformation in the patterns of production and consumption of several sectoral value chains. It also requires the introduction and cost-effective diffusion of new sources of energy, new advanced materials, new industrial processes. All these technical changes trigger a reconfiguration of the technology platforms on which modern industrial ecosystems are built as well as a change in the industry organization. While industrial policy design and governance frameworks are critical, the effective implementation and enforcement of any industrial policy will critically depend on the extent to which the policy is able to promote the emergence of a new coalition of productive interests, or offer existing powerful groups alternative and more productive ways to operate in the economy. In other words, especially in developing and middleincome countries with a poorly developed capitalist class, industrial policies will have to be designed taking into account the political economy feasibility of interventions. This assessment should not discourage bold industrial policy measures; rather, it should help identify feasible and incremental pathways for transformation (Chang and Andreoni, ). There are a number of sectors in which productive interests predominate, while capabilities and power are relatively evenly distributed. In these sectors, the political settlement structure might allow for quick wins and the emergence or consolidation of

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new coalitions for change. In other sectors, where interests have been more entrenched and have even resulted in state capture, consolidated power structures are more difficult to change and open up to new actors and competition. Here, competition policy alongside other regulatory and incentive restructuring can force the emergence of new deals. These deals can open the way to transition paths towards more productive and technologically dynamic sectors. Overall, digital industrialization will also produce potential trade-offs and new conflicts in the economy, for example with respect to employment. Given the challenges faced by SMEs, digital technologies, if not suitably governed, can exacerbate the existing divide between big and small firms to the detriment of the much-needed re-industrialization of the country. Digital industrial policy must therefore govern these processes and make sure that the digital industrial dividend is incrementally distributed across different firms, their employees, and society more broadly.

. C

.................................................................................................................................. Economists have always struggled to grasp the complex structure and dynamics of productive transformation. Since the First Industrial Revolution, several concepts of sectors have been used as compositional heuristics to group and differentiate economic activities, markets, and firms. These heuristics and resulting taxonomies have been also used to capture the way in which technical change constantly shifts the sectoral terrains of traditionally defined agriculture, industry, and services. In this contribution we have provided an analytical discussion of the evolution of different concepts of sectors and demonstrated how different concepts can serve different purposes. With a focus on technical change in the digitalization era, we have relied on an industrial ecosystem framework to discuss several processes of innovation, industrial mutation, and shifting sectoral terrains. Indeed, traditional sectoral terrains have been increasingly shifting and blurring as a result of changes in the technological platforms underpinning sectoral value chains. Many of these platforms have been increasingly acquiring a data-driven and networked character. Since , digitalization has emerged as the dominant form of technical change. However, digital transformation in production and products is diffusing unevenly across the world. Industrial policies are central to boosting technical change, and their effectiveness depends critically on the adoption of appropriate sectoral and crosssectoral instruments. Industrial policy targeting requires a focus on key parts of modern industrial ecosystems. New heuristics are critical to reveal opportunities and challenges within sectoral value chains and those nested at the interstices of industrial ecosystems. Mission-oriented initiatives can play a key coordinating role and support countries in developing context-specific pathways to capture the new windows of digital opportunities.

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A Thanks to Ha-Joon Chang, Simon Roberts, and Timothy Sturgeon for discussions and Eric Reinert and Eva Paus for comments to an early version of this chapter. Also, thanks to all participants to the workshops held in preparation of the OUP Handbook, and in particular the editors of the volume.

R Abramovitz, Moses () Thinking about Growth. Cambridge: Cambridge University Press. Amsden, Alice () ‘Diffusion of Development’, American Economic Review : –. Andreoni, Antonio () ‘Manufacturing Agrarian Change: Agricultural Production, Intersectoral Learning and Technological Capabilities’. DRUID Working Paper Series No. / . Andreoni, Antonio () ‘Structural Learning: Embedding Discoveries and the Dynamics of Production’, Structural Change and Economic Dynamics : –. Andreoni, Antonio () ‘Varieties of Industrial Policy: Models, Packages and Transformation Cycles’, in Akbar Noman and Joseph E. Stiglitz (eds) Efficiency, Finance, and Varieties of Industrial Policy. New York: Columbia University Press, pp. –. Andreoni, Antonio () ‘The Architecture and Dynamics of Industrial Ecosystems: Diversification and Innovative Industrial Renewal in Emilia Romagna’, Cambridge Journal of Economics, : –. Andreoni, Antonio (a) ‘A Generalised Linkage Approach to Local Production Systems Development in the Era of Global Value Chains, with Special Reference to Africa’, forthcoming in Ravi Kanbur, Akbar Noman, and Joseph E. Stiglitz (eds) Quality of Growth in Africa. New York: Columbia University Press, pp. –. Andreoni, Antonio (b) ‘Robotising Regions: A Comparative Analysis of Industrial Policy for Robotisation across China, Malaysia and Thailand’. South African Research Chair in Industrial Development, SARChi Working Paper, University of Johannesburg. Andreoni, Antonio and Guendalina Anzolin () ‘A Revolution in the Making? Challenges and Opportunities of Digital Production Technologies for Developing Countries’. UNIDO Working Paper No. /. Vienna: UNIDO. Andreoni, Antonio and Ha-Joon Chang () ‘Bringing Production and Employment back into Development’, Cambridge Journal of Regions, Economy and Society (): –. Andreoni, Antonio and Ha-Joon Chang () ‘The Political Economy of Industrial Policy: Structural Interdependencies, Policy Alignment and Conflict Management’, Structural Change and Economic Dynamics : –. Andreoni, Antonio and William Lazonick () ‘Local Ecosystems and Social Conditions of Innovative Enterprise’, in Arkebe Oqubay and Justin Yifu Lin (eds) The Oxford Handbook of Industrial Hubs and Economic Development. Oxford: Oxford University Press. Andreoni, Antonio and Roberto Scazzieri () ‘Triggers of Change: Structural Trajectories and Production Dynamics’, Cambridge Journal of Economics : –. Andreoni, Antonio and Fiona Tregenna () ‘Beyond the Inverted U: The Changing Nature and Structural Heterogeneity of Premature Deindustrialisation’. International Workshop: The Future of Industrial Work: New Pathways and Policies of Structural Transformation? UNIDO, Vienna, – September.

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     

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Andreoni, Antonio and Fiona Tregenna () ‘Escaping the Middle-income Technology Trap: A Comparative Analysis of Industrial Policies in China, Brazil and South Africa’, Structural Change and Economic Dynamics, forthcoming. Andreoni, Antonio, Ha-Joon Chang, and Matheus Labrunie () ‘Natura non facit saltus: Challenges and Opportunities for Digital Industrialisation across Developing Countries’, European Journal of Development Research, forthcoming. Andreoni, Antonio, Frederico Frattini, and Giorgio Prodi () ‘Structural Cycles and Industrial Policy Alignment: The Private–Public Nexus in the Emilian Packaging Valley’, Cambridge Journal of Economics : –. Baines, Tim, Ali Ziaee Bigdeli, Oscar Bustinza, Victor Shi, James Baldwin, and Keith Ridgway () ‘Servitization: Revisiting the State-of-the-art and Research Priorities’, International Journal of Operations & Production Management (): –. Becattini, Giacomo () Il concetto d’industria e la teoria del valore. Torino: Bollati Boringhieri. Becattini, Giacomo () ‘Dal “settore” industriale al “distretto” industriale. Alcune considerazioni sull’unità di indagine dell’economia industriale’, Rivista di Economia e Politica Industriale (): –. (English translation: ‘Sectors and/or Districts: Some Remarks on the Conceptual Foundations of Industrial Economics’, in E. Goodman, J. Bamford, and P. Saynor (eds) Small Firms and Industrial Districts in Italy. London: Routledge, , pp. –.) Becattini, Giacomo () ‘Industrial Sectors and Industrial Districts: Tools for Industrial Analysis’, European Planning Studies (): –. Best, Michael H. () The New Competition: Institutions of Industrial Restructuring. Cambridge: Polity Press. Brenahan, Timothy () ‘General Purpose Technologies’, in Bronwyn H. Hall and Nathan Rosenberg (eds) Handbook of Economics of Innovation. Amsterdam: Elsevier, pp. –. Castellacci, Fulvio () ‘Technological Paradigms, Regimes and Trajectories: Manufacturing and Service Industries in a New Taxonomy of Sectoral Patterns of Innovation’, Research Policy (–): –. Chang, Ha-Joon () Kicking away the Ladder: Development Strategy in Historical Perspective. London: Anthem Press. Chang, Ha-Joon and Antonio Andreoni () ‘Industrial Policy in the st Century’, Development and Change (): –. Clapham, John Harold () ‘Of Empty Economic Boxes’, The Economic Journal (): –. Cramer, Christopher and John Sender () ‘Agro-processing, Wage Employment and Export Revenue: Opportunities for Strategic Intervention’. Working Paper for the Department of Trade and Industry, Trade & Industry Policy Strategies (TIPS), Pretoria. Dosi, Giovanni () ‘Technological Paradigms and Technological Trajectories: A Suggested Interpretation of the Determinants and Directions of Technical Change’, Research Policy (): –. Fisher, Allan () ‘Production in Primary, Secondary and Tertiary’, Economic Record (): –. Fourastie, Jean () Machinisme et bien-etre. Paris: Les Editions des Minuit. Freeman, Chris () The Economics of Industrial Innovation. London: Pinter. Gereffi, Gary () Global Value Chains and Development: Redefining the Contours of st Century Capitalism. Cambridge: Cambridge University Press.

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 

Hirschman, Albert Otto () The Strategy of Economic Development. New Haven, CT: Yale University Press. Hirschman, Albert Otto () ‘A Generalized Linkage Approach to Economic Development with Special Reference to Staples’, Economic Development and Cultural Change : –. Jovanovic, Boyan and Rousseau, Peter () ‘General Purpose Technologies’, in Philippe Aghion and Steven Durlauf (eds) Handbook of Economic Growth, Vol. B, Amsterdam: Elsevier, pp. –. Kaldor, Nicholas () Strategic Factors in Economic Development. Ithaca, NY: Cornell University Press. Kay, Cristobal () ‘Development Strategies and Rural Development: Exploring Synergies, Eradicating Poverty’, Journal of Peasant Studies (): –. Kuznets, Simon () ‘Modern Economic Growth’, American Economic Review : –. Lall, Sanjaya () ‘The Technological Structure and Performance of Developing Country Manufactured Exports, –’, Oxford Development Studies (): –. Lancaster, Kelvin John () ‘A New Approach to Consumer Theory’, Journal of Political Economy : –. Lange, Oscar () Price Flexibility and Employment. Chicago, IL: Cowles. Lazonick, William () Competitive Advantage on the Shop Floor. Cambridge, MA: Harvard University Press. Lazonick, William () Business Organisation and the Myth of the Market Economy. Cambridge: Cambridge University Press. Leontief, Wassily () The Structure of American Economy, –. Cambridge, MA: Harvard University Press. Lin, Justin Yifu () New Structural Economics: A Framework for Rethinking Development and Policy. Washington, DC: World Bank. Marshall, Alfred () Industry and Trade: A Study of Industrial Technique and Business Organization, and of their Influences on the Conditions of Various Classes and Nations. London: Macmillan. Mazzucato, Mariana () ‘Mission-oriented Innovation Policies: Challenges and Opportunities’, Industrial and Corporate Change (): –. Milberg, William and Deborah Winkler () Outsourcing Economics. Cambridge: Cambridge University Press. OECD () Globalisation and Competitiveness: Relevant Indicators. Paris: OECD Directorate for Science, Technology and Industry, DSTI/EAS/IND/WP(). Park, Se-Hark and Kenneth Chan () ‘A Cross-country Input–Output Analysis of Intersectoral Relationships between Manufacturing and Services and their Employment Implications’, World Development (): –. Pasinetti, Luigi Ludovico () Structural Change and Economic Growth. A Theoretical Essay on the Dynamics of the Wealth of Nations. Cambridge: Cambridge University Press. Pavitt, Keith () ‘Sectoral Patterns of Technical Change: Toward a Taxonomy and a Theory’, Research Policy : –. Penrose, Edith () The Theory of the Growth of the Firm. Oxford: Oxford University Press. Pérez, Carlota () Technological Revolutions and Financial Capital: The Dynamics of Bubbles and Golden Ages. Northampton, MA: Edward Elgar. Ponte, Stefano, Gary Gereffi, and Gale Raj-Rechert () Handbook of Global Value Chains. Cheltenham: Edward Elgar.

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Reinert, Erik S. () ‘Catching-up from Way Behind: A Third World Perspective on First World History’, in Jan Fagerberg, Bart Verspagen, and Nick von Tunzelmann (eds) The Dynamics of Technology, Trade, and Growth. Aldershot: Edward Elgar, pp. –. Reinert, Erik S. () How Rich Countries Got Rich and Why Poor Countries Stay Poor. New York: Public Affairs. Richardson, George () ‘The Organisation of Industry’, The Economic Journal (): –. Robinson, Joan () The Economics of Imperfect Competition. Basingstoke: Macmillan. Rodrik, Dani, Margaret McMillan, and Claudia Sepulveda (eds) () Structural Change, Fundamentals, and Growth: A Framework and Case Studies. Washington, DC: International Food Policy Research Institute. Rosenberg, Nathan () ‘Technological Change in the Machine Tool Industry, –’, Journal of Economic History (): –. Rosenberg, Nathan () Perspectives on Technology. Cambridge: Cambridge University Press. Scazzieri, Roberto () A Theory of Production: Tasks, Processes, and Technical Practices. Oxford: Clarendon Press. Schumpeter, Joseph () Business Cycles: A Theoretical, Historical, and Statistical Analysis of the Capitalist Process. New York: McGraw-Hill Book Company. Schumpeter, Joseph () Capitalism, Socialism, and Democracy. New York: Harper & Brothers. Simon, Herbert A. () ‘Organisations and Markets’, Journal of Economic Perspectives (): –. Sraffa, Piero () ‘The Laws of Returns under Competitive Conditions’, The Economic Journal (): –. Sturgeon, Timothy () ‘The “New” Digital Economy and Development’. UNCTAD Technical Note on ICT for Development. Geneva: UNCTAD. Tassey, Gregory () The Technology Imperative. Cheltenham: Edward Elgar. Tassey, Gregory () ‘Rationales and Mechanisms for Revitalising US Manufacturing R&D Strategies’, Journal of Technology Transfer : –. Toner, Phillip () Main Currents in Cumulative Causation. Basingstoke: Macmillan. Wolfe, Martin () ‘The Concept of Economic Sectors’, The Quarterly Journal of Economics (): –.

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  ......................................................................................................................

                   .............................................................................................................

 

. I

.................................................................................................................................. I October , the Intergovernmental Panel on Climate Change (IPCC), the most authoritative global organization advancing climate-change research, issued an alarming report titled Global Warming of . . This report emphasized the imperative of limiting the increase in global mean temperatures to . degrees above pre-industrial levels as opposed to the previous consensus target . degrees. The IPCC concluded that limiting the global mean temperature increase to . rather than . degrees by  will dramatically lower the likely negative consequences of climate change. These include the risks of heat extremes, heavy precipitation, droughts, sea level rise, biodiversity losses, and corresponding impacts on health, livelihoods, food security, water supply, and human security. The IPCC estimates that to achieve the . degrees maximum global mean temperature increase target as of , global net CO₂ emissions will have to fall by about  per cent as of  and reach net-zero emissions by . I focus in this chapter on what it will take for the global economy to reach net-zero CO₂ emissions by , and specifically, in terms of the industrial and financing policies that will be needed for this project to succeed. In the interests of space, I do not delve into the additional specific challenges around also hitting the IPCC’s intermediate target of a  per cent CO₂ emissions reduction by , though important additional challenges do emerge with achieving this  goal.

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      



In fact, purely as an analytic proposition and policy challenge—independent of the myriad of political and economic forces arrayed around these matters—it is entirely realistic to allow that global CO₂ emissions can be driven to net zero by . By my higher-end estimate, it will require an average level of investment spending throughout the global economy of about . per cent of global GDP per year, focused in two areas: ) dramatically improving energy-efficiency standards in the stock of buildings, automobiles and public transportation systems, and industrial production processes; and ) equally dramatically expanding the supply of clean renewable energy sources— primarily solar and wind power—available at competitive prices to all sectors and in all regions of the globe. This level of clean energy investment spending would amount to about $. trillion¹ in the first year of the programme, which I will set as  and rise to an average of about $. trillion per year between  and . This assumes that the project actually begins in , but that the full-scale expansion in clean energy investments requires a three-year lead time. Thus the start date for the full-scale programme becomes . Total clean energy investment spending for the full-scale twentyseven-year investment cycle – would amount to about $ trillion. These figures are for overall investment spending, including from both the public and private sectors. Establishing the right mix between public and private investment will be a major consideration within the industrial and financing policies framework. As an initial rough approximation, I assume that the breakdown should be divided equally—that is,  per cent public and private investment. For the first year of full-scale investment activity in , this would break down to $. trillion in both public and private investments. A major part of the policy challenge will be to determine how to leverage the public money most effectively to create strong incentives for private investors. It is important to emphasize at the outset that this clean energy investment project will pay for itself in full over time. More specifically, it will deliver lower energy costs for energy consumers in all regions of the world. This results because raising energyefficiency standards means that, by definition, consumers will spend less for a given amount of energy services, such as being able to travel  miles on a gallon of petrol with a high-efficiency hybrid plug-in vehicle as opposed to  miles per gallon with the average car on US roads today. Moreover, the costs of supplying energy through solar and wind power, as well as geothermal and hydro, are now, on average, roughly equal to or lower than those for fossil fuels and nuclear energy. As such, the initial upfront investment outlays can be repaid over time through the cost savings that will be forthcoming. For , global clean energy investments levels, including both energy efficiency and clean renewable investments, were at about $ billion, equal to about . per cent of global GDP. Thus, the increase in clean energy investments will need to be in the range of . per cent of global GDP—that is, about $. trillion at the current global GDP level of about $ trillion, then rising in step with global GDP growth thereafter

¹ All $ values are in US dollars.

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

 

until . The consumption of oil, coal, and natural gas will also need to fall to zero over this same thirty-year period. The rate of decline can begin at a relatively modest . per cent in the initial years of the transition programme, but will then increase every year in percentage terms, as the base level of fossil-fuel supply contracts to zero as of . Of course, both the privately owned fossil-fuel companies, such as Exxon-Mobil and Chevron, and equally, the publicly owned companies such as Saudi Aramco and Gazprom in Russia, have massive self-interests at stake in preventing reductions in fossil-fuel consumption as well as enormous political power. These powerful vested interests will simply have to be defeated. How exactly this is accomplished is beyond the scope of this chapter, other than to recognize that a critical foundation for advancing a successful global Green New Deal will be to establish a viable set of industrial and financing policies to support the project. The structure of this chapter is as follows. Section . asks the first critical question for designing a global clean energy investment project, which is: what is clean energy? I review evidence on natural gas, nuclear energy, and various forms of geoengineering as providing clean energy alternatives to fossil fuels. But I conclude that all these approaches present major problems. This conclusion then becomes the basis for recognizing that building a global clean energy economy should rely mostly on dramatically expanding investments in energy efficiency and clean renewable energy sources. In considering the prospects for achieving major gains in energy efficiency, I introduce the concept of ‘energy intensity ratios’ and review evidence on this ratio for the global economy as well as for seven representative national economies, that is, China, the United States, Brazil, Germany, Indonesia, South Africa, and South Korea. I will also focus on Brazil, Germany, Indonesia, South Africa, and South Korea later in this study. With respect to ‘clean renewable energy sources’, as I use the term, it excludes many forms of bioenergy, such as ethanol from corn or sugarcane using conventional refining methods. This is because, considered over a thirty-year life cycle, the emissions generated from these energy sources are comparable to those from fossil fuels.² The clean renewable sources on which I focus in section . and throughout the study are solar and wind power, as well as, to a more modest extent, geothermal and hydro power, as well as bioenergy generated through low-emissions technologies. Section . presents a simple model through which I calculate the investment requirements for creating a global net-zero-emissions economy as of . I show through this model that investments in energy efficiency and clean renewable energy at an average . per cent share of global GDP per year will be sufficient for achieving this end. The model builds from the assumption of the most recent global energy model of the International Energy Agency (IEA), which assumes that global GDP grows at an average annual rate of . per cent per year over –. Section . then considers the industrial and financial policy measures that will be needed to support this global clean energy investment project. I examine a range of

² See Pollin et al. (: –).

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      



policy approaches that have been implemented throughout the world to varying degrees. I also propose specific sources of funding that are capable of bringing total clean energy investments to $. trillion as of —that is, . per cent of global GDP in —along with the capacity to increase funding at a rate corresponding with global GDP through . In section ., I consider the domestic resource capacities in various countries to support its clean energy transformation, focusing, again, on Brazil, Germany, Indonesia, South Africa, and South Korea. To the extent that a country runs up against domestic productive capacity constraints while expanding its investments in energy efficiency and clean renewable energy, it then must either scale back the clean energy investment project or rely increasingly on imports to maintain the ambitious investment agenda. For the five representative economies, I show how this domestic resource constraint will be manageable. One factor that will be important in enabling the expansion of domestic production in clean energy will be the fact that the fossil-fuel sectors in all countries will be correspondingly contracting. Thus, in section ., I show how the freeing up of economic resources out of the activities tied to the fossil-fuel sector will be substantial in all cases, including countries such as Germany and South Korea, which are presently dependent on imports as their source of fossil-fuel energy. In the concluding section ., I briefly summarize the full set of findings in sections .–.. These findings demonstrate how a global clean energy project—that is, a Global Green New Deal, as I understand the term—does indeed provide a viable path for achieving a net-zero-emissions global economy as of . I also show that the industrial and financial policy tools needed to deliver on this project are well understood and have been well tested in various parts of the world, under a range of circumstances. These policy tools now need to be implemented on a scale appropriate to the magnitude of the challenge we now face with climate change. This chapter covers a large number of issues within a relatively brief amount of space. At the same time, due to space limitations, it does not cover several topics that are also critical for understanding the full scope of industrial policy requirements for implementing a successful global Green New Deal. One such critical set of issues covers the employment impacts of the global clean energy investment project, which, in turn, breaks down into two components. The first is assessing the large employment creation opportunities that will be generated through investing . per cent of GDP in clean energy projects in all regions of the world. The second is recognizing the job losses that will result through the contraction of the global fossil-fuel industry, and the imperative of establishing a set of just transition policies for both the workers and communities that will be negatively impacted as a result. I have addressed these issues at length elsewhere and will continue to do so in future research.³

³ See Pollin (), Pollin et al. (), Pollin and Callaci (), and Pollin et al. () for discussions and further references on employment effects and Just Transition policies.

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

 

Related to this is the large set of questions on the developmental impact of the clean energy transition on economies that are presently net fossil-fuel exporters. These questions are linked to the broader literature around the so-called ‘resource curse’. These issues, again, lie beyond the scope of this chapter, even while the relevant literature is quite extensive.⁴ Another set of critical issues that I have not been able to address here are the land use requirements for building a global clean energy infrastructure. The work of the physicist Mara Prentiss demonstrates that, in fact, through well-designed policies, these land-use requirements will be relatively modest. But the overall global Green New Deal project will benefit through developing with greater specificity the framework that Prentiss has developed.⁵

. W  C E?

..................................................................................................................................

.. Natural Gas There are large differences in the emissions levels resulting through burning oil, coal, and natural gas, with natural gas generating about  per cent fewer emissions for a given amount of energy produced than coal and  per cent less than oil. It is therefore widely argued that natural gas can be a ‘bridge fuel’ to a clean energy future, through switching from coal to natural gas to produce electricity.⁶ Such claims do not withstand scrutiny. At best, an implausibly large  per cent global fuel switch to natural gas would reduce CO₂ emissions by only  per cent. But even this calculation does not take account of the leakage of methane gas into the atmosphere that results through extracting natural gas through fracking. Recent research finds that when more than about  per cent of the gas extracted leaks into the atmosphere through fracking, the impact eliminates any environmental benefit from burning natural gas relative to coal. Various studies have reported a wide range of estimates as to what leakage rates have actually been in the United States, at fracking operations have grown rapidly. A recent survey paper puts that range at between . and . per cent for different specific sites in North Dakota, Utah, Colorado, Louisiana, Texas, Arkansas, and Pennsylvania. It would be reasonable to assume that if fracking expands on a large scale in regions outside the United States, it is likely that leakage rates will fall closer to the higher-end figures of  per cent, at least until serious controls could be established. This then

⁴ Two recent survey articles on the Resource Curse are Ross () and Venables (). ⁵ See Prentiss () for her calculations on land-use requirements and a brief application of her framework in Pollin (: –). ⁶ https://www.yaleclimateconnections.org///pros-and-cons-the-promise-and-pitfalls-ofnatural-gas/.

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would greatly diminish, if not eliminate altogether, any emission-reduction benefits from a coal-to-natural-gas fuel switch.⁷

.. Nuclear Energy As of , nuclear power provided  quadrillion British Thermal Units (Q-BTUs) of energy throughout the global economy, amounting to  per cent of total global supply. Nearly  per cent of global nuclear power supply is generated in North America, Europe, China, and India. In terms of the world reaching a net-zero CO₂ emissions target by , nuclear power provides the important benefit that it does not generate CO₂ emissions or air pollution of any kind while operating. At the same time, the processes for mining and refining uranium ore, making reactor fuel, and building nuclear power plants all require large amounts of energy. But even if we put aside the emissions that result from building and operating nuclear power plants, we still need to recognize the long-standing environment and public safety issues associated with nuclear energy. These include: • Radioactive wastes. These wastes include uranium mill tailings, spent reactor fuel, and other wastes, which according to the US Energy Information Agency (EIA) ‘can remain radioactive and dangerous to human health for thousands of years’ (EIA, : ). • Storage of spent reactor fuel and power plant decommissioning. Spent reactor fuel assemblies are highly radioactive and must be stored in specially designed pools or specially designed storage containers. When a nuclear power plant stops operating, the decommissioning process involves safely removing the plant from service and reducing radioactivity to a level that permits other uses of the property. • Political security. Nuclear energy can obviously be used to produce deadly weapons as well as electricity. Thus, the proliferation of nuclear energy production capacity creates dangers of this capacity being acquired by organizations—governments or otherwise—which would use that energy as instruments of war or terror. • Nuclear reactor meltdowns. An uncontrolled nuclear reaction at a nuclear plant can result in widespread contamination of air and water with radioactivity for hundreds of miles around a reactor. Even while recognizing these problems with nuclear energy, it is still the case, as noted above, that nuclear power presently supplies over  per cent of global energy supply. For decades, the prevalent view throughout the world was that these risks associated with nuclear power were relatively small and manageable, when balanced against its benefits. However, this view was upended in the aftermath of the March ⁷ See, for example, Alvarez et al. (), Romm (), Howarth (), and Peischl et al. ().

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 nuclear meltdown at the Fukushima Daiichi power plant in Japan, which resulted from the massive . Tohuku earthquake and tsunami. The full effects of the Fukushima meltdown cannot possibly be known for some time. Still, these safety considerations with nuclear energy must be accorded significant weight. This is especially the case, given the high probability that the necessary tight standards for regulating nuclear power plants will become compromised if the number of such plants were to expand significantly on a global scale. As such, nuclear energy cannot be seen as providing a major reliable long-term source of non-carbon-emitting energy supplies.

.. Geoengineering This includes a broad category of measures whose purpose is either to remove existing CO₂ or to inject cooling forces into the atmosphere to counteract the warming effects of CO₂ and other greenhouse gases. One broad category of removal technologies is carbon capture and sequestration (CCS). A category of cooling technologies is stratospheric aerosol injections (SAI). CCS technologies aim to capture emitted carbon and transport it, usually through pipelines, to subsurface geological formations, where it would be stored permanently. One straightforward and natural variation on CCS is afforestation. This involves increasing forest cover or density in previously non-forested or deforested areas, with ‘reforestation’—the more commonly used term—as one component. The general class of CCS technologies has not been proven at a commercial scale, despite decades of efforts to accomplish this. A major problem with most CCS technologies is the prospect for carbon leakages that would result under flawed transportation and storage systems. These dangers will only increase to the extent that CCS technologies are commercialized and operating under an incentive structure in which maintaining safety standards will reduce profits. By contrast, afforestation is, of course, a natural and proven carbon removal technology. At the same time, most deforestation projects throughout the globe were undertaken to make space for raising crops and livestock. Relying heavily on afforestation as a climate change strategy would therefore likely present serious land-use competition problems. The idea of stratospheric aerosol injections builds from the results that followed from the volcanic eruption of Mount Pinatobo in the Philippines in . The eruption led to a massive injection of ash and gas, which produced sulphate particles, or aerosols, which then rose into the stratosphere. The impact was to cool the earth’s average temperature by about . C for fifteen months.⁸ The technologies being researched now aim to artificially replicate the impact of the Mount Pinatubo eruption through deliberately injecting sulphate particles into the stratosphere. Some researchers

⁸ https://earthobservatory.nasa.gov/images//global-effects-of-mount-pinatubo.

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contend that to do so would be a cost-effective method of counteracting the warming effects of greenhouse gases. Lawrence et al. () published an extensive review on the range of climate geoengineering technologies, including  literature references. Their overall conclusion from this review is that none of these technologies are presently at a point at which they can make a significant difference in reversing global warming. They conclude: Proposed climate geoengineering techniques cannot be relied on to be able to make significant contributions . . . towards counteracting climate change in the context of the Paris Agreement. Even if climate geoengineering techniques were actively pursued, and eventually worked as envisioned on global scales, they would very unlikely be implementable prior to the second half of the century . . . This would very likely be too late to sufficiently counteract the warming due to increasing levels of CO₂ and other climate forcers to stay within the .⁰C temperature limit—and probably even the  C limit—especially if mitigation efforts after  do not substantially exceed the planned efforts of the next decade (: –).⁹

.. Energy Efficiency and Clean Renewable Energy Given these major problems with natural gas as a ‘bridge fuel’, nuclear energy, and geoengineering, it follows that we focus instead on the most cautious clean energy transition programme, that is, investing in technologies that are well understood, already operating at large scale, and, without question, safe. In short, we focus on investments that can dramatically raise energy-efficiency standards and equally dramatically expand the supply of clean renewable energy sources.

.. Energy Efficiency Energy efficiency entails using less energy to achieve the same, or even higher, levels of energy services from the adoption of improved technologies and practices. Examples include insulating buildings much more effectively to stabilize indoor temperatures; driving more fuel-efficient cars or, better yet, relying increasingly on well-functioning public transportation systems; and reducing the amount of energy that is wasted both through generating and transmitting electricity and through operating industrial machinery. Expanding energy-efficiency investments support rising living standards because raising energy-efficiency standards, by definition, saves money for energy consumers. ⁹ In his  paper, ‘There Is No Plan B for Dealing with the Climate Crisis’, the leading climate scientist and lead co-author of the Third Assessment Report of the IPCC Raymond Pierrehumbert is even more emphatic in arguing that geoengineering does not offer a viable solution to the climate crisis.

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A major  study by the US National Academy of Sciences (NAS) found, for the US economy, that ‘energy-efficient technologies . . . exist today, or are expected to be developed in the normal course of business, that could potentially save  per cent of the energy used in the US economy while also saving money’. Similarly, a  McKinsey & Company study, focused on developing countries, found that, using existing technologies only, energy-efficiency investments could generate savings in energy costs in the range of  per cent of total GDP for all low- and middle-income countries. In her  book, Energy Revolution: The Physics and Promise of Efficient Technology, Mara Prentiss argues, further, that such estimates understate the realistic savings potential of energy-efficiency investments. This is because, in generating energy by burning fossil fuels, about two-thirds of the total energy available is wasted while only one-third is available for powering machines. By switching to renewable energy sources, the share of wasted energy falls by  per cent. This is what Prentiss terms the ‘burning bonus’. After taking account of the burning bonus as well as the efficiency gains available in the operations of buildings, transportation systems, and industrial equipment, Prentiss concludes, with respect to the US economy specifically, that economic growth could proceed at a normal rate while total energy consumption could remain constant or even decline in absolute terms. Prentiss’s conclusions regarding the US economy are consistent with the most recent projections for global energy demand by the International Energy Agency (IEA, ). As I discuss further in section .., the IEA assumes that the global economy will grow at a . per cent average annual rate between  and . Nevertheless, under their most conservative Current Policies Scenario, the IEA assumes that global energy consumption will grow at a much slower . per cent per year. Under their more ambitious Sustainable Development Scenario, they assume that global energy consumption will actually fall at an average rate of –. per cent per year, while economic growth still proceeds at a . per cent average rate.¹⁰ A useful way to measure the relationship between the level of economic activity and the energy resources consumed to support that activity is the energy intensity ratio. The energy intensity ratio is, straightforwardly, the level of total energy resources consumed in any given economy divided by the economy’s GDP. I report in Table A. (in the Appendix) below the most recent energy intensity figures for the world economy as well as for seven representative large economies—China, the United States, Brazil, Germany, Indonesia, South Africa, and South Korea. In section .., I will focus on this ratio for the world economy as a key variable for estimating the costs of reaching a zero CO₂ emissions global economy by . For now, it will be useful to consider the patterns for the global economy and the respective national economies. The units in which I measure the ratio are Q-BTUs of energy consumed/trillion dollars of GDP. As the table shows, the intensity ratio, as of , was . Q-BTUs for every $ trillion of global GDP. With the individual country ¹⁰ The IEA summarizes its three scenarios—the Stated Policies Scenario, the Sustainable Development Scenario, and the Current Policies Scenario, on p.  of its  World Energy Outlook.

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figures, we see that the intensity ratios vary widely by country. Germany is the most efficienct economy, with the lowest . intensity ratio. The United States is next, at with a . intensity ratio, following by Brazil at .. South Korea and Indonesia are at similar efficiency levels, with . and . intensity ratios respectively. China is operating at a relatively low efficiency level, with a . intensity ratio. South Africa is the least energy efficient of the countries in our sample, with an intensity ratio of ..¹¹

.. Estimating Costs of Efficiency Gains This range of energy intensity figures notwithstanding, the aim of the clean energy investment project will be to achieve dramatic improvements in efficiency in all national economies across the global economy. The question we therefore need to address is: how much will it cost to achieve such large-scale efficiency gains? In fact, estimates as to the investment costs for achieving energy-efficiency gains vary widely. In Table A. in the Appendix, I show summary estimates from three sets of studies. As we see, the  World Bank study by Taylor et al. puts average costs at $. billion per Q-BTU of energy savings, based on a study of  projects in both industrial and developing economies. A  study by McKinsey estimates costs for a wide range of non-OECD economies at $ billion per Q-BTU of energy savings. Focusing just on the US economy, NAS estimated average costs for energy-efficiency savings in the buildings and industrial sectors at about $ billion per Q-BTU.¹² It is not surprising that average costs to raise energy-efficiency standards would be significantly higher in industrialized economies. A high proportion of overall energyefficiency investments are labour costs, especially projects to retrofit buildings and industrial equipment. However, these wide differences in cost estimates shown in Table A. do not simply result from variations in labour and other input costs by regions and levels of development. Thus, the World Bank estimate of $. billion per Q-BTU includes both industrialized and developing countries, while the McKinsey $ billion per Q-BTU estimate— nearly six times greater than the World Bank figure—is primarily coming from developing-country projects. These alternative studies do not provide sufficiently

¹¹ It is, however, important to note that the pattern with these ratios is highly sensitive to the method by which one measures national GDP figures. The figures reported here are based on nominal US dollars calculated according to each country’s exchange rate. If, alternatively, we measured national GDP figures based on purchasing power parity, the GDP figures would be significantly higher for the lower-income economies. This would in turn lower their energy intensity ratios. How best to deal with these methodological issues is an important question, but it is beyond the scope of this chapter. ¹² I am not aware of more recent studies that have attempted to provide comparable aggregated cost estimates. However, recent studies on the building sector in the US economy have generated results similar to those in the  NAS study. These more recent studies include Molina (), Ackerman et al. (), and Rosenow and Bayer ().

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detailed methodological discussions that would enable us to identify the main factors generating these major differences in cost estimates. But it is at least reasonable to conclude from these figures that, with on-the-ground real-world projects, there are likely to be large variations in costs down to the project-by-project level. Thus, the costs for energy-efficiency investments that will apply in any given situation will necessarily be specific to that situation, and must always be analysed on a case-by-case basis. At the same time, for our present purposes, we need to proceed with some general rules of thumb for estimating the level of savings that is attainable through a typical set of efficiency projects in various regions of the world, and more precisely an aggregated estimate for the global economy. A conservative approach will be to allow that, relative to the World Bank and US National Academy of Sciences figures, the mid-range cost estimate provided by McKinsey at $ billion per Q-BTU of savings, is appropriate for low- and middleincome economies, such as Brazil, Indonesia, and South Africa. Along the same lines, we could assume that the cost figure for Germany will be equivalent to what the NAS study estimated for the United States, at around $ billion per Q-BTU of savings. The South Korean economy would then be an approximate midpoint between those two other figures, at around $ billion per Q-BTU. As a working approximation for the global economy, this same midpoint figure of $ billion per Q-BTU of savings should be a credible high-end estimate, especially while recognizing that the World Bank estimate for  projects in both developing and advanced economies is ten times higher, at about $ billion per Q-BTU of savings.

.. Rebound Effects Raising energy-efficiency levels will generate ‘rebound effects’—i.e. energy consumption increases resulting from lower energy costs. But such rebound effects are likely to be modest within the current context of a global project focused on reducing CO₂ emissions and stabilizing the climate. Among other factors, energy consumption levels in advanced economies are close to saturation points in the use of home appliances and lighting—that is, we are not likely to clean dishes much more frequently because we have a more efficient dishwasher. The evidence shows that consumers in advanced economies are likely to heat and cool their homes as well as drive their cars more when they have access to more efficient equipment. But these increased consumption levels are usually modest. Average rebound effects are likely to be significantly larger in developing economies.¹³ But it is critical that all energy-efficiency gains will be accompanied by complimentary policies (as discussed in section ..), including setting a price on carbon emissions to discourage fossil-fuel consumption. Most significantly, expanding the ¹³ See the discussion and references in Pollin et al. (: –).

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supply of clean renewable energy will allow for higher levels of energy consumption without leading to increases in CO₂ emissions. It is important to recognize, finally, that different countries presently operate at widely varying levels of energy efficiency. For example, as we saw in Table A., Germany presently operates at an efficiency level roughly  per cent higher than that of the United States. Brazil is at an efficiency level that is nearly three times that of South Africa. There is no evidence that large rebound effects have emerged as a result of these high efficiency standards in Germany and Brazil relative to those of the United States and South Africa.

.. Renewable Energy A critical point for building a net-zero global economy by  is the fact that, on average, the costs of generating electricity with clean renewable energy sources are now at parity or lower than those for fossil-fuel-based electricity. Table A. in the Appendix shows the most recent figures reported by the International Renewable Energy Agency (IRENA), for  and , on the ‘levellized costs’ of supplying electricity through alternative energy sources. Levellized costs takes account of all costs of producing and delivering a kilowatt of electricity to a final consumer. The cost calculations begin with the upfront capital expenditures needed to build the generating capacity, continue through to the transmission and delivery of electricity, and include the costs of energy that is lost during the electricity-generation process. As we see in Table A., the levellized costs for fossil-fuel-generated electricity range between . and  cents per kilowatt hour as of . The average figures for the four clean renewable sources are all within this range for fossil fuels as of , with hydro at  cents, onshore wind at  cents, geothermal at  cents and solar PV at  cents. The costs of geothermal and hydro did not fall, and actually rose modestly, between  and . However, the costs of onshore wind fell by  per cent, from  to  cents. The most impressive result though is with solar PV, in which levellized costs fell by  per cent from  to , from  cents to  cents per kilowatt hour. These average cost figures for solar and wind should continue to decline by significant amounts as advances in technology and economies of scale proceed along with the rapid global expansion of these sectors. We emphasize that these cost figures from the IRENA are simple averages. They do not show differences in costs due to regional or seasonally specific factors.¹⁴ In particular, solar and wind energy costs will vary significantly by region and season. Moreover, both wind and solar energy are intermittent sources—that is, they only generate energy, respectively, when the sun is shining or the wind is blowing. Of course, the central role of energy storage systems to address these matters will need to be fully

¹⁴ Such detailed figures are also available in IRENA ().

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accounted for when clean renewable energy systems are designed to provide a major share of an economy’s overall energy load.¹⁵ Keeping all such considerations in mind, we can still roughly conclude from these figures that, for the most part, clean renewable energy sources are rapidly emerging into a position at which they can produce electricity at comparable or lower costs than non-renewable sources. As such, assuming that wind, solar, and geothermal energy production can be scaled up to meet virtually all global demand by , then the costs to consumers of purchasing this energy should not be significantly different from what these consumers would have paid for non-renewable energy. Indeed, overall, the costs to consumers of purchasing electricity from clean renewable sources, including hydro as well as wind, solar, and geothermal power, are likely to be lower than what they would be from fossil-fuel sources. It is critical to also emphasize that this is without factoring in the environmental costs of burning oil, coal, and natural gas.

.. Costs of Expanding Renewable Capacity By a substantial amount, the largest share of overall costs in generating electricity from renewable sources are capital costs—that is, the costs of producing new productive equipment, as opposed to the costs of operating that productive equipment once it has been built and is generating energy. These capital costs are at about  per cent of total costs for geothermal,  per cent for onshore wind, and  per cent for solar PV.¹⁶ From these figures on levellized costs, we can also estimate the capital costs of installing renewable energy capacity as a lump sum—that is, how much investors need to spend upfront to put this capital equipment into place and in running order. I produce estimates of these lump sum capital costs in Table A. in the Appendix. Specifically, these figures represent the present values of total lump-sum capital expenditures needed to produce one Q-BTU of electricity from onshore wind, solar PV, and geothermal energy.¹⁷ As we see, the average lump-sum costs range from $ billion per Q-BTU for geothermal, $ billion for onshore wind, and $ billion for solar. If we assume that, roughly speaking, the global expansion of clean renewable energy capacity will consist of  per cent from wind and solar PV technologies, and  per cent from geothermal energy, this would place the average costs of producing one Q-BTU of overall renewable energy equipment at about $ billion, which we can round up to $ billion per Q-BTU of clean renewable capacity. This $ billion figure can therefore serve as a benchmark for estimating the average costs of expanding the supply of clean renewable energy on a global scale. At the same time, ¹⁵ See IRENA () on electricity storage costs and markets through . ¹⁶ These figures are from the US Energy Information Agency (EIA, ). ¹⁷ The full methodology for generating these costs is presented in Pollin et al. (: –).

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as with our cost estimate for investments in energy efficiency, we will want to err, if anything, on the side of overestimating, rather than underestimating, the costs of expanding clean renewable energy. Moreover, with the expansion of the globe’s clean energy supply proceeding rapidly over –, the average costs are likely to rise as production bottlenecks emerge. We therefore will assume that the average costs of expanding the clean energy supply will be $ billion per Q-BTU, that is, about  per cent higher than the $ billion average figure we have derived from the levellized costs data. We can now work with our two rough high-end estimates of the overall costs of both raising energy-efficiency standards and building new clean renewable energy capacity—$ billion per Q-BTU for efficiency gains and $ billion per Q-BTU for expanding renewable capacity—to generate an estimate of the total costs of achieving a net-zero global economy by .

. E G  E R

.................................................................................................................................. In this section, I present a simple model to illustrate how the global economy can achieve net-zero CO₂ emissions by  through investing about . per cent of global GDP per year to raise energy-efficiency standards and to expand the supply of clean renewable energy sources. The model works from the following assumptions: . Average costs for increasing energy efficiency and expanding clean renewable production. As discussed, I assume that the average costs to increase energy efficiency by  Q-BTU will be $ billion. I also assume that the average costs to expand productive capacity of clean renewable energy by  Q-BTU will be $ billion. . Global GDP growth trend. The IEA’s forecast assumes an average global GDP growth rate of . per cent between  and  (: ). My model incorporates this figure. To date, the IEA has not published a global GDP growth forecast that extends beyond . For the purposes of the current exercise, I assume that the . per cent average global GDP growth rate will extend to . . Clean renewable energy sources supply  per cent of global energy demand. As discussed, there may be a case for relying to a limited extent on nuclear energy and some types of carbon capture technologies beyond afforestation as a supplement to clean renewable sources. But this model demonstrates how, as of , it will be cost effective as well as technically feasible to deliver  per cent of global energy supply through clean renewables. . Three-year delay in bringing the project to scale. This is a thirty-year investment project. But given that the current level of clean energy investments is in the range

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  of . per cent of global GDP,¹⁸ we must realistically allow for some incubation time to pass before we can expect investments to rise by . percentage points as a share of GDP, to a . per cent of annual GDP level. To reflect this consideration, I assume, as noted above, that it will require three years of major initiatives within the realms of industrial policy and financing to raise global clean energy investments by roughly . per cent of GDP relative to current investment levels. We therefore assume that the . per cent of GDP per year level of clean energy investments will occur over twenty-seven years within the full thirty-year investment cycle, that is, between  and . The initial three years of the model, –, will be needed to develop an adequate industrial policy and financing environment to sustain clean energy investments at this level.

The results of this model are presented in Tables .–..

.. Global Model Framework and Calculations In Table ., we start with the actual global GDP figure in  of $ trillion.¹⁹ We then work with the IEA’s assumption of average global GDP growth over the subsequent thirty years at . per cent per year. From our initial  GDP figure of $ trillion and our assumption of . per cent average annual growth, we can then estimate the level of GDP every year through . Under these assumptions, global GDP will be $ trillion in . The model projects global GDP in  at $ trillion. We can also then calculate the ‘midpoint’ GDP figure over the – thirtyyear investment cycle. I define this midpoint figure as being equal to the average of the estimates of GDP in  and , assuming average annual GDP growth at . per cent. This midpoint figure, as we see, is $ trillion. From this midpoint figure, we can then readily calculate a ratio for average annual clean renewable investments. In Table ., I estimate the level of clean energy investments necessary to bring the average global energy intensity ratio down from its current level of . (Q-BTUs/ ¹⁸ Renewable investments = $ billion in , https://about.bnef.com/blog/clean-energyinvestment-exceeded--billion-/; but $ billion in  according to IEA (p. ). But it doesn’t break out bioenergy from the others. Energy efficiency, from IEA in  is $ billion (p. ). Total is therefore $ billion. But if we take out ~  per cent for high-emissions bioenergy, that gets us to $ billion. $ billion/$ trillion = . per cent GDP. ¹⁹ This $ trillion global GDP figure comes from World Development Indicators. It is derived from the prevailing exchange rates between the United States and all other global currencies as of . The most widely utilized alternative measure of global GDP is derived through establishing purchasing power parities between countries. Measured according to the purchasing power parity methodology, global GDP in  was $ trillion (World Development Indicators). For the purposes of this exercise, it is important to, if anything, err by underestimating the prospects for a clean energy investment programme over the thirty-year investment cycle. Therefore, for this exercise, I utilize the lower $ trillion figure derived on the basis of exchange rates as of .

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Table 15.1 Thirty-year global GDP growth trajectory, 2021–50 2018 global GDP Projected average annual GDP growth rate through 2040 (from IEA, 2019: 753) Projected 2021 GDP (with 3.4% average annual GDP growth) Projected 2024 GDP (First year of 27-year investment cycle; with 3.4% average annual GDP growth) Projected 2050 GDP (with 3.4% average annual GDP growth) Midpoint GDP value for investment spending estimates (= (2021 GDP + 2050 GDP)/2)

$86 trillion 3.4% $95 trillion $104 trillion $260 trillion $178 trillion

Sources: World Development Indicators; International Energy Agency, World Energy Outlook, 2019.

trillion dollars of GDP) to ., a  per cent improvement in average global energy efficiency. The . energy intensity ratio is the figure projected by the IEA in its  Sustainable Development Scenario. This will be while, according to the IEA model, average global GDP is growing at . per cent per year. As section A of Table . shows, if the global economy continues to operate at its current . energy intensity ratio through , global energy consumption will be at , Q-BTUs in . By contrast, if the global economy does succeed in driving down the energy intensity ratio to . through efficiency investments, it follows that global energy consumption will be at  Q-BTUs as of . As we then see in section B of Table ., total energy savings achieved through operating the global economy at a . rather than a . average intensity ratio will be , Q-BTUs. Since, as our high-end figure, we assume that the average global cost of achieving efficiency gains is $ billion per Q-BTU, this means that achieving , Q-BTUs in global efficiency gains will cost a total of $. trillion. As Panel B of Table . shows, the average annual investment level of the twenty-seven-year investment period is therefore $ billion. In Table ., we work with the  global energy consumption figure of  Q-BTUs from Table . to calculate the investment requirements for meeting this level of total energy demand through clean renewable sources. As the table shows, as of the most recent IEA figures, global supply of clean renewables is  Q-BTUs. This means that the expansion of supply as of  will need to be  Q-BTUs. It also means that the average growth rate for expanding the global supply of clean renewable energy will need to be at around  per cent per year for the full – investment cycle. In terms of estimating the costs of this investment project, I then, again, assume a high-end average cost figure for expanding global clean energy capacity, at $ billion per Q-BTU. Working from this figure, it follows, as shown in Table ., that the total costs of expanding global clean energy supply by  Q-BTUs as of  will be $. trillion. The average annual costs over the twenty-seven-year investment cycle will therefore be $. trillion. In Table ., I then summarize the figures for total and annual average costs for achieving a net-zero global economy strictly on the basis of large-scale investments in

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Table 15.2 Global energy demand and energy-efficiency cost projections for 2050 A) Total energy demand through alternative scenarios 2050 Energy consumption 2050 energy demand, with constant energy intensity ratio 2050 energy demand through IEA Sustainable Development Scenario

Average annual energy demand growth rate

Average 2050 global energy intensity ratio

1,716 Q-BTUs

3.4%

6.6

512 Q-BTUs

–0.3%

2.0

B) Cost of achieving energy savings through the IEA sustainable development scenario 1. Total energy savings through the IEA Sustainable Development Scenario 2. Average cost of energy savings through efficiency investments 3. Total cost of energy savings through efficiency investments 4. Average annual cost of energy savings through efficiency investments

1,204 Q-BTUs (= 1,716 Q-BTUs – 512 Q-BTUs) $20 billion/Q-BTU $24.1 trillion (= rows 2 x 3) $891 billion ($24.1 trillion/27 years)

Notes: Actual 2018 global energy consumption = 568 Q-BTUs; global energy intensity ratio = 6.6. Source: IEA (2019: 678).

Table 15.3 Global clean renewable energy expansion and cost projection for 2050 1. Total 2050 energy consumption through the Sustainable Development Scenario 2. 2018 clean renewable energy supply (from IEA, 2019: 678) 3. Net expansion of clean renewables as of 2050 4. Average cost of expanding clean renewable supply 5. Total cost of expanding global clean renewable supply by 486 Q-BTUs as of 2050 Average annual cost of expanding global clean renewable supply by 286 Q-BTUs as of 2050

512 Q-BTUs 26 Q-BTUs 486 Q-BTUs (= row 1 – row 2) $200 billion/Q-BTU $97.2 trillion (= row 3 x row 4) $3.6 trillion (= row 5/27)

Source: IEA (2019).

energy efficiency and clean renewables. As we see, total costs come to $. trillion. Over the twenty-seven-year investment cycle, this amounts to an average of $. trillion per year. Working from the estimates presented in Table ., our figure for midpoint global GDP between  and  is $ trillion. This is how, finally, we are able to estimate that the overall investment requirement for reaching a net-zeroemissions global economy as of  will amount, on average, to . per cent of global GDP per year.

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Table 15.4 Costs of thirty-year clean energy investment project as share of average GDP, 2021–50 Total costs of clean energy investments 1. Energy efficiency 2. Clean renewable energy

$24.1 trillion $97.2 trillion

3. TOTAL (= rows 1 + 2)

$121.3 trillion

2024 costs of clean energy investments (year 1 of 27-year investment cycle) 4. Energy efficiency 5. Clean renewable energy

$500 billion $2.1 trillion

6. TOTAL (= rows 5 + 6)

$2.6 trillion

Average annual costs of clean energy investments (27-year cycle) 7. Energy efficiency 8. Clean renewable energy

$891 billion/year $3.6 trillion/year

9. TOTAL (= rows 7 + 8)

$4.5 trillion/year

Total costs of clean energy investments as share of midpoint GDP 10. Midpoint GDP (from Table 15.1) 11. Clean energy investments as share of midpoint GDP (= row 6/row 7)

$178 trillion 2.5%

Source: IEA (2019).

. I  F P

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.. Industrial Policies Depending on specific conditions within each country, industrial policies will be needed to promote technical innovations and, even more broadly, adaptations of existing clean energy technologies. Again depending on circumstances, governments will need to deploy a combination of industrial policy instruments, including research and development support, preferential tax treatment for clean energy investments, and government procurement policies. Clean energy industrial policies will also need to include regulations of both fossil-fuel and clean energy prices as well as emission standards. One major policy intervention that can facilitate the creation of a vibrant clean energy market will be for governments to themselves become both large-scale investors in energy efficiency and purchasers of clean renewable energy. An important comparable historical experience was the development of the Internet within the US military, beginning in the s. In the process of bringing the Internet to commercial scale, the US military provided a guaranteed market for thirty-five years, which enabled

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the technology to incubate while private investors gradually developed effective commercialization strategies.²⁰ But guaranteeing stable prices with the private-sector purchases of clean renewables is also critical here. Such policies are termed feed-in tariffs. Specifically, these are contracts that require utility companies to purchase electricity from private renewable energy generators at prices fixed by long-term contracts. Feed-in tariffs were first implemented in the United States in the s, and a number of state and local programmes are currently operational in the United States today. However, the impact of feed-in tariffs has been much more significant outside of the United States, especially in Germany, Italy, France, Spain, and Canada. A  study by the US Department of Energy found that these policies in Europe ‘resulted in quick and substantial renewable energy capacity expansion’.²¹ This basic result has been affirmed through more recent research, including that by Milanes-Montero et al. (), which showed how feed-in tariffs ‘have had a significant positive influence on the economic profitability’ on solar PV companies in Europe. The key factor in the success of these European programmes is straightforward: the guaranteed prices for renewable energy were set to adequately reflect the costs of producing the energy along with a profit for the energy provider. This then encouraged private renewable energy investors by providing a stable longterm market environment.²² Feed-in tariffs have also had some successes as a policy tool in Africa. The African Development Bank reports as follows: Public investment is critical in bridging the gap between public demonstration of new technologies and mature deployment. Feed-in tariffs are a prominent example of such subsidies. These tariffs are a policy mechanism that offers compensation to renewable energy producers, based on the difference between the cost of electricity generation of each technology and the market price of electricity generation that, in the case of RETs, is usually lower. In Kenya, for example, feed-in tariffs led to the high level of uptake of solar PV. As of ,  African countries used feed-in tariff policies. (African Development Bank Group, )

Another important set of policies are those that aim to directly reduce fossil-fuel consumption. These include carbon caps and carbon taxes. In principle at least, a carbon cap establishes a firm limit on the allowable level of emissions for major polluting entities, such as utilities. Such measures will also raise the prices of oil, coal, and natural gas by limiting their supply. A carbon tax, on the other hand, will directly raise fossil-fuel prices to consumers, and aim to reduce fossil-fuel consumption through the resulting price signals. Either approach can be effective as long as the cap is strict enough, or tax rate high enough, to significantly reduce fossil-fuel consumption and as long exemptions are minimal to none. Raising the prices for fossil fuels will also, of ²⁰ See Ruttan (). ²¹ Cory, Couture, and Kreycik (: ). ²² Cointe and Nadaï () emphasize this point and contrast it with the official EU aim of liberalizing renewable energy markets.

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course, create increased incentives for both energy-efficiency and clean renewable investments, as well as a source of revenue to help finance these investments. We return to this point in section .. However, significant problems are also associated with both approaches. Establishing a carbon cap or tax will have negative distributional consequences that will need to be addressed in the policy design. All else equal, increasing the price of fossil fuels would affect lower-income households more than affluent households, since petrol, home-heating fuels, and electricity absorb a higher share of lower-income households’ consumption. An effective solution to this problem is to rebate to lower-income households a significant share of the revenues generated either by the cap or tax to offset the increased costs of fossil-fuel energy.²³ Renewable energy portfolio standards for utilities, and energy-efficiency standards for buildings and transportation vehicles, are similar in their intent to a carbon cap. That is, renewable portfolio standards set a minimum standard that utilities must achieve in generating electricity from renewable energy sources. Energy-efficiency standards for automobiles set minimum miles-per-gallon levels (or comparable measures) that a given auto fleet must achieve to be in compliance with the law. Comparable efficiency standards can also be established for buildings in terms of allowable levels of energy consumption for a given building size. However, a major problem that has emerged with carbon caps as well as renewable and efficiency standards has been with enforcement. As a major case in point, when these cap programmes are combined with a carbon permit option—as in ‘cap-andtrade’ policies—the enforcement of a hard cap becomes difficult to sustain or even monitor, thereby weakening the impact of the policy.²⁴

.. Providing Cheap and Accessible Financing There are two separate, but interrelated policy considerations here. The first is: where will the funding come from to support approximately $. trillion in new clean energy investments in  and $. trillion as an annual average over –? The second issue is: how can these funds be most effectively channelled into the full range of specific projects that will need to advance every year in order to build a net-zero global economy? We consider these issues in turn.

²³ See Boyce () for an effective solution to the distributional problem, via what he terms ‘carbon dividends’. Azad and Chakraborty () expand on the idea of an egalitarian carbon dividend programme to the global economy. ²⁴ See, for example, Teeter and Sandberg (). There is also the problem of the caps, or renewable portfolio standards, being established in law but then ignored in policy implementation. This has been the experience, for example, in New York State. See Pollin et al. (: –).

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.. Sources of Aggregate Funding In principle, it should not be especially challenging to solve this problem. To begin with, as of , Credit Suisse estimates that the total value of global financial assets was $ trillion.²⁵ The $. trillion that I am proposing to channel into clean energy investments as of  amounts to . per cent of this total financial asset pool. Still, it is important to anchor the discussion in specific proposals. Therefore, for purposes of illustration, I propose four large-scale funding sources to support public investments in clean energy. Other approaches could also be viable. These four funding sources are: ) a carbon tax, in which  per cent of revenues are rebated back to the public but  per cent are channelled into clean energy investment projects; ) transferring funds out of military budgets from all countries, but primarily the United States; ) a Green Bond lending programme, initiated by both the US Federal Reserve and the European Central Bank; and ) eliminating all existing fossil-fuel subsidies and channelling  per cent of the funds into clean energy investments. Strong cases can be made for each of these funding measures. But each proposal does also have vulnerabilities, including around political feasibility. The most sensible approach is therefore to combine the measures into a single package that minimizes their respective weaknesses as standalone measures. Table A. in the Appendix presents this set of combined proposals in summary form. . Carbon tax with rebates. As noted above, carbon taxes have the merit of impacting climate policy through two channels—they raise fossil-fuel prices and thereby discourage consumption while also generating a new source of government revenue. At least part of the carbon tax revenue can then be channelled into supporting the clean energy investment project. But the carbon tax will hit low- and middle-income people disproportionately, since they spend a larger fraction of their income on electricity, transportation, and home-heating fuel. An equal-shares rebate, as proposed by Boyce (), is the simplest way to ensure that the full impact of the tax will be equalizing across all population cohorts. Consider, therefore, the following tax-and-rebate programme. Focusing, again, on , the first year of the full-scale investment programme, we begin with a tax at a low rate of $ per ton of carbon. Given current global CO₂ emissions levels, that would generate about $ billion in revenue. If we use only  per cent of this revenue to finance clean energy investments, that amounts to roughly $ billion for investment projects. The  per cent of the total revenue that is rebated to the public in equal shares would then amount to $ billion. This amounts to about $ for every person on the planet, or $ for a family of four.²⁶

²⁵ file:///C:/Users/RPollin/Downloads/global-wealth-report--en.pdf. ²⁶ Azad and Chakraborty () develop a more complex rebate structure, that rewards residents of countries according to the emissions levels of each country.

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. Transferring funds out of military budgets. Global military spending in  was at $. trillion.²⁷ The US military budget, at about $ billion, accounted for nearly  per cent of the global total. There are solid logical and ethical grounds for transferring substantial shares of each country’s total military budget to supporting climate stabilization, if we take at face value the idea that military spending is fundamentally aimed at achieving greater security for the citizens of each country. But to remain within the realm of political feasibility, let us assume that  per cent of global military spending will transfer into supporting climate security. That would amount to $ billion. . Green Bond funding by the Federal Reserve and European Central Bank. It was demonstrated during the – global financial crisis and subsequent Great Recession that the Federal Reserve is able to supply basically unlimited bailout funds to private financial markets during crises. The extensive  study, The Costs of the Crisis, by Better Markets concludes that the Federal Reserve committed approximately $. trillion to stop the crash of the financial system, stabilize the economy, and try to spur economic growth. I would propose $ billion in Green Bond financing supplied by the Fed. This would amount to a miniscule . per cent of the Fed’s – bailout operations during the crisis. The Fed’s funding support could be injected into the global economy through straightforward channels. That is, various public entities, such as the World Bank, could issue long-term zero interest rate Green Bonds. The Fed would purchase these bonds. The various public entities issuing these bonds would then have the funds to pursue the full range of projects that will fall under the rubric of the global clean energy project. This framework has not yet been introduced into policy discussions at the Federal Reserve. But they are becoming a central area of focus at the European Central Bank. Thus, the Financial Times reported on // that the recently installed ECB President Christine Lagarde is moving quickly on the matter. The Financial Times reports that: Christine Lagarde . . . is pushing to include climate change considerations in a review the central bank is due to hold into the way it conducts monetary policy. Until now, the expectation was for a review into purely monetary matters, such as whether the inflation target should be revised. An explicit focus on climate change policy would be a huge move. Because the central bank is by far the biggest influence on financial conditions in the market, it can make a significant difference to investment decisions that determine how Europe’s climate transition goes.²⁸

The Financial Times article makes clear that the specific channels through which the ECB would intervene to support clean energy financing will require substantial fleshing out. The type of approach I have sketched for a Federal Reserve intervention would seem like a relatively straightforward and modest form of intervention. I therefore propose that the ECB undertakes Green Bond purchases at the same level as the Federal

²⁷ https://www.sipri.org/media/press-release//world-military-expenditure-grows--trillion-. ²⁸ https://www.ft.com/content/ff-bc-ea-a-dbfcfeae.

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Reserve, that is, at $ billion as of , and growing over time to support clean energy investments continuing at an average rate of . per cent of global GDP per year. . Eliminating fossil fuel subsidies and channelling  per cent of funds to clean energy investments. One recent estimate of direct fossil-fuel subsidies to consumers— measured as the difference between supply and consumer prices to purchase fossilfuel energy—is about $ trillion globally as of , or about . per cent of global GDP.²⁹ Channelling these funds, in full, into supporting public clean energy investments would therefore more than pay for the $. trillion estimate for total clean energy investments as of . This $ trillion would also represent more than double the amount necessary to cover a global public investment level of $. trillion. However, such fossil-fuel subsidies are largely used as a form of general support for all energy consumers. Lower- and middle-income households are therefore major beneficiaries of these subsidies, along with, of course, the fossil fuel energy suppliers. Therefore, in terms of global income distribution, eliminating these subsidies altogether would likely have a significant regressive impact, comparable to establishing a carbon tax without an accompanying rebate programme. As such, to continue to provide support for lower-income households, most of the funds that are now being channelled to these households through fossil-fuel subsidies should be redirected into either supporting lower consumer prices for clean energy or to provide direct income transfers for lower-income households. Given that we will have raised $ billion from the carbon tax, military spending transfers and central bank Green Bond programmes, we could then assume that  per cent of the $ trillion received as fossil-fuel subsidies be transferred into the clean energy investment fund. That would amount to $ billion. With these funds, we will have reached the total $. trillion in public investment funds necessary to attain the total of public and private investment spending of $. trillion as of .

.. Channelling Financial Resources into Specific Investment Projects Both general purpose development banks as well as special-purpose green development banks are already significantly engaged in financing clean energy investments. It will be crucial to build from these efforts to achieve the necessary level of financing for clean energy investments.

²⁹ Coady et al. (). This study distinguishes direct fossil-fuel subsidies—what it terms ‘pre-tax’ subsidies—and ‘post-tax’ subsidies. They define post-tax subsidies as including global warming damages, air pollution damages, and vehicle externalities, including congestion, accidents, and road damage. They estimate post-tax subsidies as amounting to roughly  per cent of global GDP. These are valuable calculations. But for the purposes of this discussion on financing, the standard, and much more narrowly defined, measure of pre-tax subsidies are more directly relevant.

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Germany’s KfW Bank. The case of Germany is instructive, since it has been the most successful large advanced economy to date in developing its clean energy economy. The publicly owned development bank in Germany, KfW, has been critical to this success. Griffith-Jones () considers KfW’s impact on Germany’s overall green transformation, including renewable energy as well as energy-efficiency investments. She finds that KfW has underwritten roughly one-third of all financing for green investments in Germany. KfW has thus been instrumental in moving policy ideas into effective investment projects, with respect to both energy efficiency and clean renewables. KfW has also been highly active in financing green investment projects elsewhere in Europe and in developing countries. As Griffith-Jones writes: KfW plays a key role, domestically and internationally, in supporting energy revolution, through funding major investments in renewable energy and in energy efficiency. In the national German case, this was to a large extent implemented within a clear institutional and policy framework, namely the renewable energy law, through strong policy measures, such as feed in tariffs (FITs) and reverse competitive auctions, which made investment in renewables commercially attractive. A similar modus operandi existed for energy efficiency . . . The combination of clear government policies and associated development bank targets has produced very positive results in green infrastructure in Germany, which can be replicated in emerging and developing countries. (: )³⁰

Griffith-Jones also describes the financing terms offered by KfW in all of their areas of active lending. These include long-term loans and below-market interest rates,  per cent disbursement rates, up to three years holidays in making repayments, and repayment bonuses of up to . per cent. Green banks. Special purpose green development banks have also become increasingly active in recent years. A  OECD study defines a green investment bank as ‘a publicly capitalized entity established specifically to facilitate private investment into domestic low-carbon and climate-resistant infrastructure and other green sectors such as water and waste management’ (: ). These special purpose banks have been established at the national level in Australia, Japan, Malaysia, Switzerland, and the United Kingdom. Within the United States, the states of California, Connecticut, Hawaii, New Jersey, New York, and Rhode Island have created green banks. The OECD study describes the banks as having ‘diverse rationales and goals, including meeting ambitious emissions targets, mobilizing private capital, lowering the cost of capital, lowering energy costs, developing green technology markets, supporting local community development and creating jobs’ (: ). The OECD study does not provide systematic evidence as to the scale at which these institutions are currently

³⁰ Griffith-Jones’s conclusions are fully in line with those of other researchers. For example, the overview of the IEA’s  Energy Efficiency Market Report concluded that ‘Germany is a world leader in energy efficiency. Germany’s state-owned development bank, KfW, plays a crucial role by providing loans and subsidies for investment in energy-efficiency measures in buildings and industry, which have leveraged significant private funds’ (IEA, : ).

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

 

providing investment financing. But considering other references, it is reasonable to assume that, in general, their scale of operations is much smaller than KfW.³¹ This raises the question as to whether the necessary level of financing can be achieved without the full backing of large-scale national or regional entities, such as the equivalent of KfW. Emerging trends in developing countries. Within developing economies there has been a general movement in the aftermath of the – global financial crisis away from the predominant neo-liberal financial market policy framework that prevailed prior to the crisis. This trend has included the formation or expansion of development banks. For example, Grabel () describes the emergence of the Development Bank of Latin America and the New Development Bank as potentially significant new sources of subsidized long-term financing for developing economies, including in the area of green energy investments. Recent studies by the World Bank (Hussain, ) and African Development Bank (African Development Bank Group, ) examine specific financial models for advancing green investments in developing countries. Both studies consider financing arrangements through which concessionary public financing can be mobilized to encourage, as opposed to crowd out, private investments, thereby creating viable public–private partnerships with clean energy investment projects. The World Bank study in particular, which focuses on renewable energy investments, emphasizes that the long-term funding for these investments has been limited by the range of risks private investors face while working with still relatively unfamiliar technologies. These risks include uncertainty over the reliability of the technology within any given project and shifts in the relevant regulatory environment. The World Bank proposes a series of financing techniques for reducing these risks for private investors. Yet the overall point remains that the public financing interventions—whether they be implemented through formal development banks or otherwise—will need to absorb a disproportionate share of these risks in order for the financing levels to reach scale rapidly enough. With respect to financing clean energy investments in developing countries in particular, it is also critical that the benefits of these investments be shared fully by society’s least-advantaged groups. Spratt, Griffith-Jones, and Ocampo emphasize this consideration in their  study ‘Mobilizing Investment for Inclusive Green Growth in Low-income Countries’. This would mean, as important examples, expanding access to electricity and providing clean energy for electricity and other needs at affordable prices.³² To accomplish these ends, Spratt et al. emphasize that it is not

³¹ See, for example, Pollin et al. () for a discussion of the New York State green bank and related public financing initiatives within New York State. See also Pollin et al. () for a discussion of green banks within the US economy, and as one element within a broader framework of measures to support clean energy investments. ³² As one specific policy proposal, Azad and Chakraborty () develop a programme for rapidly advancing the expansion of renewable energy supply in India. The proposal includes a carbon tax, with

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realistic to expect clean energy investments to consistently generate profits for private businesses at rates comparable to mature investment areas, including fossil-fuel energy. The requirement that the financing terms for clean energy investments be affordable for borrowers—that is, not always yielding high returns for lenders—reinforces the centrality of public investment banks with clear social criteria guiding their financing strategies.

. D R C  C E I

.................................................................................................................................. One of the major questions that all countries will face in undertaking a clean energy transformation will be the extent to which the large-scale expansion in clean energy investment activity can be accomplished through utilizing domestic resources as opposed to having to rely increasingly on imports. To the extent that a country runs up against domestic productive capacity constraints while expanding its investments in energy efficiency and clean renewable energy, it then faces two alternatives: either scale back the clean energy investment project or rely increasingly on imports to maintain the ambitious investment agenda. Within this framework, it is critical to establish some measures of the range at which, in any given country, import dependency is likely to increase as it establishes a clean energy investment project at around . per cent of the country’s GDP. To generate a rough estimate of this, I examine here the relative domestic and import content for the set of industrial sectors that will be mobilized to expand a country’s energy-efficiency and renewable energy investments. I report these figures for five large economies in different regions of the world, that is, Brazil, Germany, Indonesia, South Africa, and South Korea. To be more specific, I undertake the following exercise. Working from the most recent country-specific input–output tables from the OECD, those from , I first calculate the current level of domestic content for all activities that will be mobilized to undertake clean energy investments in five major areas. These five areas are energyefficiency investments in building retrofits, industrial-efficiency and grid upgrades as well as renewable investments in solar and wind power. Two examples of the specific set of inputs within a given investment project, along with the relative contributions of each of these inputs, are as follows: • Solar industry investments in Brazil: ▪ Computer and electronic products— per cent weight ▪ Construction— per cent weight ▪ Business sector services— per cent weight the revenues from the tax being channelled into clean renewable energy investments that will then supply free electricity to low-income communities, many of which still have no access to electricity.

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  ▪ ▪

General machinery and equipment products— per cent weight Basic metals manufacturing— per cent weight

• Grid upgrades in South Africa: ▪ Construction— per cent weight ▪ Computer and electronic products— per cent weight ▪ Electrical equipment— per cent weight ▪ General machinery and equipment products— per cent weight Within these input–output frameworks, I then divide each of the specific activities associated with each of the five investment projects into non-tradable and tradable activities. Following from the literature, I define a ‘tradable’ activity as one in which less than  per cent of this activity’s inputs come from domestic sources.³³ Within these definitions of ‘tradable’ and ‘non-tradable’ activities, I then assume that the domestic content levels for non-tradable activities will remain constant as the country’s clean energy investment project proceeds. These non-tradable activities include construction, ground transportation, and administration. With tradable activities, I allow that domestic content will fall by up to  per cent. This enables us to then observe how much overall domestic content within any given investment project area will decline when the domestic content of specific tradable activities declines by  per cent. In Table A. in the Appendix, I show the results of this exercise for the five clean energy investment areas and five representative countries. As we see, overall, domestic content levels are generally high for all five countries with all five clean energy projects. In virtually all cases, domestic content levels are higher than  per cent. When we then allow domestic content for tradable activities to fall by  per cent, we still find that, in virtually all cases, overall domestic content remains above  per cent. Thus, after the  per cent decline in domestic content for tradable activities, we see that the largest declines in overall domestic content are with grid upgrades in South Africa, in which domestic content falls from  to  per cent; grid upgrades in South Korea, in which overall domestic content falls from  to  per cent; and wind energy in South Africa, in which overall domestic content declines from  to  per cent. These changes would all represent significant increases in the respective countries’ import requirements. But they should not entail major strains in the countries’ overall balance of payments. Thus, for the most part, most countries should be able to undertake clean energy transformations mostly through mobilizing the country’s existing supply of domestic resources.

³³ This discussion and set of calculations are an updated version of that presented in Pollin et al. (: –). Full references on methodology and related matters are presented in this  publication.

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.. Fossil Fuel Consumption and Imports/Exports One factor in enabling the expansion of domestic production in sectors of economies linked to clean energy will be the fact that the fossil-fuel sectors in all countries will be correspondingly contracting. The freeing up of economic resources out of the activities tied to the fossil-fuel sector will be substantial in all cases. These activities include extracting, transporting, refining, and the retail distribution of fossil-fuel energy, along with all the sectors that provide supplies to support these activities. The data in Table A. in the Appendix provide a sense of the magnitudes involved. The first column of the table shows, for , the extent to which each of our five representative economies relies on fossil fuels to meet its overall energy consumption levels.³⁴ As we see, fossil fuels supply more than half of each country’s total energy consumption. Brazil has the lowest proportion of fossil-fuel consumption, at  per cent of total energy consumption. This is because of its uniquely high levels of both hydro and biofuel production. Indonesia is next lowest, at  per cent reliance on fossil fuels. But this figure includes Indonesia’s still heavy reliance on burning peat as a highemissions renewable energy source. Exclusive of peat, coal, oil, and natural gas provide roughly  per cent of Indonesia’s remaining energy supply. Germany, South Africa, and South Korea all rely on fossil fuels for between about  and  per cent of their overall energy supply. These figures show that, as these economies undergo transitions to clean energy sources, major shares of their economies’ overall resources will be released from the current demands generated by their fossil-fuel sectors. We obtain additional perspective as to how such scenarios might play out through the figures shown in the second column of Table A.. Here I show the import shares as a proportion of total energy consumption for our five selected economies as of . As we see, Indonesia and South Africa were energy exporters, both through their coal exports. With Brazil, as the table shows, imports constituted a relatively modest  per cent of its overall energy supply as of , while Germany and South Korea were major energy importers, at  and  per cent of their overall energy supply. These figures are representative of longer-term energy consumption patterns for both countries. Of course, the energy-importing countries, Brazil, Germany, and South Korea, are presently utilizing a smaller share of their total domestic resources in the fossil-fuel sector. Their share of total economic resources devoted to energy-linked activities could rise as a result of increasing investments in energy efficiency and renewable energy. However, the share of total domestic resources devoted to supplying oil, coal, and natural gas in these importing countries is still substantial. In Germany, the shares are  per cent for the coal sector and  per cent for oil and gas. In South Korea, the proportions are  per cent for coal and  per cent for oil and gas. Thus, even with

³⁴ The  data reported in Table A. are the most recent complete set of figures for all five countries.

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 

Germany and South Korea, as major energy importers, the move out of fossil fuels and into clean energy will entail releasing domestic resources that can be repurposed for the clean energy transition.

. C

.................................................................................................................................. This chapter has demonstrated that achieving a net-zero-emissions global economy by —in line with the IPCC’s climate stabilization goals—is an entirely feasible project with respect to its technical and economic requirements. As its foundation, it will require investments in energy efficiency and clean renewable energy at an average of $. trillion per year globally between  and . This is a formidable level of spending in absolute terms, but still amounts to only . per cent of average global GDP per year over –. Put another way, it implies that . per cent of global economic activity can proceed largely independently of the clean energy investment project, as long as the . per cent of GDP goal is achieved each year. The success of the global clean energy investment project—and thereby, the Global Green New Deal—will depend on whether effective industrial and financial policies will be enacted. Fundamentally, the Green New Deal amounts to a unified, and globally coordinated set of industrial policies—policies, which, taken as a whole, are capable of creating an entirely new global energy industry infrastructure within thirty years. Accomplishing this goal will require a range of specific policy initiatives, working in conjunction with each other to undergird energy-efficiency and clean renewable energy investments on an unprecedented scale. The first specific requirement will be to mobilize a large enough pool of investment funds to finance the project at the needed scale. As an illustration, I have shown how this can be achieved through a combination of four major funding sources—a  per cent share of funds from carbon tax revenues; a transfer of  per cent of military spending into clean energy investments; Green Bond purchases by both the Federal Reserve and the European Central Bank, at an initial combined level of $ billion and rising with economic growth thereafter; and the elimination of all fossil-fuel subsidies and the transfer of  per cent of these funds into clean energy projects. Working with this pool of funds, public investments will need to play the leadership role in ramping up clean investment activities in most countries at the required pace. But private investments will be equally critical over time. Indeed, I have assumed that public and private investment levels will need to be roughly comparable in magnitude in order to maintain the overall project at scale. Both carrots and sticks will be needed to induce and sustain a sufficient level of private investments. These include, as carrots, generous financial subsidies, concessionary borrowing rates, and guaranteed markets. As sticks, they include an ambitious renewable portfolio and energy-efficiency standards whose requirements cannot be readily circumvented, in contrast with some existing cap-and-trade and renewable portfolio systems. Achieving the appropriate

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mix of these measures in any given country setting will represent a major challenge in industrial policy design. Operating at the ground level, to advance this clean energy investment project at scale will of course require the mobilization of productive resources in all countries. But as I have shown, this should not create major problems with respect to domestic capacity bottlenecks, at least not after an initial adjustment period. For one thing, the domestic content levels for most clean energy investment activities are already high in the relevant productive sectors in most countries. Domestic content ratios should also remain high even as the demands on these sectors grow with the scaling up of clean energy investment activities. This is because a high proportion of the productive activity that will be required are in non-tradable sectors, such as construction, ground transportation, and administration. In addition, the fossil-fuel sectors in all countries will be undergoing major contractions as the clean energy sectors grow, thereby freeing up resources that can be redeployed into clean energy activities. In summary: the challenge facing humanity today with climate change is without precedent. Within the context of this urgent historical moment, the design and implementation of an effective set of clean energy industrial policies will play a critical role towards achieving the target of net-zero emissions in the global economy by .

. A

.................................................................................................................................. Table A15.1 Energy intensity ratios, global average and selected countries World Average

6.6

China United States Brazil Germany Indonesia South Africa South Korea

12.7 5.3 7.2 3.5 9.8 20.3 9.3

Note: Energy Intensity = Q-BTUs of energy consumed/GDP (in trillions of US dollars) World average for 2018; Individual Country figures for 2016. GDP figures in current US dollars. Sources: Energy consumption figures from EIA, International Energy Statistics, http://www.eia.gov/cfapps/ipdbproject/IEDIndex3.cfm?tid= 44&pid=44&aid=2. GDP figures from World Development Indicators: https://data.worldbank.org/indicator.

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 

Table A15.2 Estimates of cost savings from energy-efficiency investments Source

Regions/Countries/Sectors estimated

Estimated savings in Q-BTUs

World Bank (Taylor et al., 2008: 29) McKinsey & Co. (2010: 27)

455 projects in eleven industrial and developing countries Africa, India, Middle East, South East Asia, Eastern Europe, China United States

$1.9 billion per Q-BTU

United States National Academy of Sciences (2010)

$11 billion per Q-BTU ~ $29 billion per Q-BTU for buildings, industry

Source: Pollin et al. (2015: 88).

Table A15.3 Average global levellized costs of electricity from utility-scale renewable energy sources vs. fossil-fuel sources, 2010–17

Solar PV Onshore wind Geothermal Hydro

2010

2017

36 cents 8 cents 5 cents 4 cents

10 cents 6 cents 7 cents 5 cents

Note: Average levellized costs for fossil-fuel generated electricity: 4.5–14 cents per kilowatt hour. Source: https://www.irena.org/Statistics/View-Data-by-Topic/Costs/LCOE-2010-2017.

Table A15.4 Capital expenditure costs for building renewable electricity productive equipment, present values of total lump-sum capital costs per Q-BTU of electricity Wind Solar PV Geothermal Average costs Assuming investments are 45 per cent wind, 45 per cent solar, and 10 per cent geothermal

$160 billion $190 billion $112 billion $169 billion

Source: EIA, https://www.eia.gov/outlooks/aeo/pdf/electricity_generation. pdf. See Pollin et al. (2014: 136–7) for methodology in converting levelized costs per Q-BTU into lump-sum capital costs.

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Table A15.5 Major funding sources for global clean energy investments Investment level for 2024—Year 1 of investment cycle: $2.6 trillion in public and private investments, at 2.5 per cent of GDP Clean energy investment areas: • Clean renewable energy: $2.1 trillion ◦ Wind, solar, geothermal, small-scale hydro, low-emissions bioenergy • Energy efficiency: $500 billion ◦ Buildings, transportation, industrial equipment, grid and battery storage upgrades Public sources of funds: $1.3 trillion: • Carbon tax revenues: $160 billion ◦ 25 per cent of revenues from tax; 75 per cent returned to consumers as rebate • Transfers from military budgets: $90 billion ◦ 5 per cent of global military spending • Green bond purchases by Federal Reserve and European Central Bank: $200 billion ◦ 1.6 per cent of Federal Reserve Wall Street bailout support during financial crisis • Transfers of 25 per cent of fossil-fuel subsidies: $750 billion ◦ Total fossil-fuel subsidies = $3 trillion ◦ 75 per cent of funds for lower clean energy prices or direct income transfers for lower-income households Private sources of funds: $1.3 trillion: • Policies for Incentivizing Private Investors ◦ Government procurement ◦ Regulations ▪ Carbon caps and taxes ▪ Renewable energy portfolio standards for utilities ▪ Energy efficiency standards for buildings and transportation vehicles ◦ Investment Subsidies ▪ Feed-in tariffs ▪ Low-cost financing through development banks and green banks

Table A15.6 Change in overall domestic content of clean energy investment activities after 20 per cent import increase with tradable activities Energy efficiency investments

Brazil Germany Indonesia South Africa South Korea

Renewable investments

Building retrofits

Industrial efficiency

Grid upgrades

Solar

Wind

95 per cent ! 95 per cent 91 per cent ! 91 per cent 91 per cent ! 91 per cent 86 per cent ! 69 per cent 89 per cent ! 71 per cent

93 per cent ! 84 per cent 88 per cent ! 80 per cent 87 per cent ! 79 per cent 84 per cent ! 73 per cent 89 per cent ! 77 per cent

87 per cent ! 75 per cent 85 per cent ! 72 per cent 82 per cent ! 70 per cent 79 per cent ! 63 per cent 84 per cent ! 67 per cent

90 per cent ! 81 per cent 88 per cent ! 79 per cent 86 per cent ! 78 per cent 84 per cent ! 70 per cent 86 per cent ! 72 per cent

92 per cent ! 85 per cent 87 per cent ! 75 per cent 83 per cent ! 73 per cent 83 per cent ! 68 per cent 87 per cent ! 71 per cent

Sources: 2015 OECD input–output country-specific tables. Methodological details in Pollin et al. (2015: chapter 5 and appendix 2).

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Table A15.7 Reliance on fossil fuels and imports as energy sources in selected countries, 2014

Brazil Germany Indonesia South Africa South Korea

Fossil fuels as a share of total energy consumption

Imports as a share of total energy consumption

59.1 per cent 79.7 per cent 66.1 per cent 86.8 per cent 82.4 per cent

11.9 per cent 60.9 per cent –103.1 per cent –14.5 per cent 81.7 per cent

Note: Negative figures indicate net export proportion. Source: World Development Indicators, World Bank.

R Ackerman, Frank, Pat Knight, and Bruce Biewald () ‘Estimating the Cost of Saved Energy’. Available at http://www.synapse-energy.com/sites/default/files/COSE-EIA-Database-–.pdf. African Development Bank Group () African Development Report : Towards Green Growth in Africa. Tunis: African Development Bank Group. Available at https://www.afdb. org/fileadmin/uploads/afdb/Documents/Publications/African_Development_Report_ .pdf. Alvarez, Ramón A., Stephen W. Pacala, James J. Winebrake, William L. Chameides, and Steven P. Hamburg () ‘Greater Focus Needed on Methane Leakage from Natural Gas Infrastructure’, Proceedings of the National Academy of Sciences of the United States of America (): –. Azad, Rohit and Shouvik Chakraborty () ‘Balancing the Climate Injustice: A Proposal for a Differential Global Carbon Tax’, in Sevil Acar and Erinc Yeldan (eds) Handbook of Green Economics. London: Elsevier, pp. –. Azad, Rohit and Shouvik Chakraborty () ‘Green Growth and the Right to Energy in India’, Energy Policy : . Better Markets () ‘The Cost of the Crisis: $ Trillion and Counting’. Available at https:// bettermarkets.com/newsroom/-trillion-cost-financial-crisis-. Boyce, James () The Case for Carbon Dividends. Cambridge: Polity Press. Coady, David, Ian Party, Louis Sears, and Baoping Shang () ‘How Large are Global Fossil Fuel Subsidies?’, World Development : –. Cointe, Beatrice and Alain Nadaï () Feed-In Tariffs in the European Union. Basingstoke: Palgrave Macmillan. Cory, Karlynn, Toby Couture, and Claire Kreycik () ‘Feed-in Tariff Policy: Design, Implementation, and RPS Policy Interactions’. Golden, CO: National Renewable Energy Laboratory. Available at http://www.nrel.gov/docs/fyosti/.pdf. EIA (US Energy Information Administration) () ‘Nuclear Explained: Nuclear Power and the Environment’. Available at https://www.eia.gov/energyexplained/index.cfm?page= nuclear_environment.

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      

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EIA (US Energy Information Administration) () ‘Levelized Costs and Levelized Avoided Cost of New Generation Resources in the Annual Energy Outlook ’. Available at https://www.eia.gov/outlooks/aeo/pdf/electricity_generation.pdf. Grabel, Ilene () When Things Don’t Fall Apart: Global Financial Governance and Developmental Finance in an Age of Productive Incoherence. Cambridge, MA: MIT Press. Griffith-Jones, Stephany () ‘National Development Banks and Sustainable Infrastructure: The Case of KfW’. GEGI Working Paper No. , Boston University, Global Economic Governance Initiative. Howarth, Robert () ‘Methane Emissions and Climatic Warming Risk from Hydraulic Fracturing and Shale Gas Development: Implications for Policy’, Energy and Emission Control Technologies : –. Available at https://www.dovepress.com/methane-emissionsand-climatic-warming-risk-from-hydraulic-fracturing–peer-reviewed-article-EECT. Hussain, Mustafa Zakir () Financing Renewable Energy: Options for Developing Financing Instruments Using Public Funds. Washington, DC: The World Bank and Climate Investment Funds. Available at http://documents.worldbank.org/curated/en/ /pdf/WPFinanBoxBPUBLIC.pdf. IEA (International Energy Agency) () Energy Efficiency Market Report : Market Trends and Medium-term Prospects. Paris: OECD/IEA. IEA (International Energy Agency) () World Energy Outlook . Paris: OECD/IEA. IRENA (International Renewable Energy Agency) () Electricity Storage and Renewables: Costs and Markets to . Abu Dhabi: International Renewable Energy Agency. IRENA (International Renewable Energy Agency) () Renewable Power Generation Costs in . Available at https://www.irena.org/publications//May/Renewable-powergeneration-costs-in-. Lawrence, Mark, Stefan Schafer, Helene Muri, Vivian Scott, Andreas Oschlies, Naomi E. Vaughan, Oliver Boucher, Hauke Schmidt, Jim Haywood, and Jurgen Scheffran () ‘Evaluating Climate Geoengineering Proposals in the Context of the Paris Agreement Temperature Goals’, Nature Communications. Available at https://www.nature.com/ articles/s---#citeas. McKinsey & Company () Energy Efficiency: A Compelling Global Resource. New York. Milanes-Montero, Patricia, Alberto Arroyo-Farrona, and Esteban Perez-Calderon () ‘Assessment of the Influence of Feed-in Tariffs on the Profitability of European Photovoltaic Companies’, Sustainability, September. Available at https://www.researchgate.net/ publication/_Assessment_of_the_Influence_of_Feed-In_Tariffs_on_the_Profit ability_of_European_Photovoltaic_Companies. Molina, Maggie () ‘The Best Value for America’s Energy Dollar: A National Review of the Cost of Utility Energy Efficiency Programs’. Washington, DC: American Council for an Energy-Efficient Economy. Available at http://assets.fiercemarkets.net/public/smartgridnews/ ACEEE-Energy-Efficiency-Costs.pdf. NAS (National Academy of Sciences), NAE (National Academy of Engineering), and NRC (National Research Council) () Real Prospects for Energy Efficiency in the United States. Washington, DC: National Academies Press. Peischl, Jeff, Anna Karion, Cora Sweeney et al. () ‘Quantifying Atmospheric Methane Emissions from Oil and Natural Gas Production in the Bakken Shale Region of North Dakota’, Journal of Geophysical Research: Atmospheres (): –. https://agupubs. onlinelibrary.wiley.com/doi/full/./JD.

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 

Pierrehumbert, Raymond () ‘There Is No Plan B for Dealing with the Climate Crisis’, Bulletin of the Atomic Scientists (): –. Pollin, Robert () Greening the Global Economy. Cambridge, MA: MIT Press. Pollin, Robert () ‘Degrowth vs. the Green New Deal’, New Left Review (July/August): –. Pollin, Robert and Brian Callaci () ‘The Economics of Just Transition: A Framework for Supporting Fossil-fuel-dependent Workers and Communities in the United States’, Labor Studies Journal (): –. Pollin, Robert, Heidi Garrett-Peltier, James Heintz, and Bracken Hendricks () Green Growth: A US Program for Controlling Climate Change and Expanding Job Opportunities. Washington, DC: Center for American Progress. Available at https://cdn.american progress.org/wp-content/uploads///PERI.pdf. Pollin, Robert, Heidi Garrett-Peltier, James Heintz, and Shouvik Chakraborty () ‘Global Green Growth: Clean Energy Industrial Investments and Expanding Job Opportunities’, United Nations Industrial Development Organization and Global Green Growth Institute. Available at http://gggi.org/wp-content/uploads///GGGI-VOL-I_WEB.pdf. Pollin, Robert, Heidi Garrett-Peltier, and Jeannette Wicks-Lim () ‘Clean Energy Investments for New York State: An Economic Framework for Promoting Climate Stabilizing and Expanding Good Job Opportunities’, Political Economy Research Institute, November. Available at https://www.peri.umass.edu/publication/item/-clean-energy-investmentsfor-new-york-state-an-economic-framework-for-promoting-climate-stabilization-andexpanding-good-job-opportunities. Pollin, Robert, Jeannette Wicks-Lim, Shouvik Chakraborty, and Tyler Hansen () ‘A Green Growth Program for Colorado’. Political Economy Research Institute, April. Available at https://www.peri.umass.edu/publication/item/-a-green-growth-programfor-colorado. Prentiss, Mara () Energy Revolution: The Physics and the Promise of Efficient Technology. Cambridge, MA: Harvard University Press. Romm, Joe () ‘Methane Leaks Wipe out any Climate Benefit of Fracking, Satellite Observations Confirm’, Think Progress. Available at https://thinkprogress.org/methaneleaks-wipe-out-any-climate-benefit-of-fracking-satellite-observations-confirm-acdd/. Rosenow, Jan and Edith Bayer () ‘Costs and Benefits of Energy Efficiency Obligation Schemes’. Available at http://www.raponline.org/wp-content/uploads///rap-rosenowbayer-costs-benefits-energy-efficiency-obligation-schemes-.pdf. Ross, Michael L. () ‘What Have We Learned about the Resource Curse?’, Annual Review of Political Science : –. Ruttan, Vernon W. () Is War Necessary for Economic Growth? Military Procurement and Technology Development. New York: Oxford University Press. Spratt, Stephen, Stephany Griffith-Jones, and José Antonio Ocampo () ‘Mobilising Investment for Inclusive Green Growth in Low-Income Countries’. Berlin: Deutsche Gesselllschaft für Internationale Zusammenarbeit. Available at http://www.stephanygj. net/papers/MobilisingInvestmentforInclusiveGreenGrowth.pdf. Teeter, Preston and Jorgen Sandberg () ‘Constraining or Enabling Green Capability Development? How Policy Uncertainty Affects Organizational Responses to Flexible Environmental Regulations’, British Journal of Management (): –. Venables, Anthony J. () ‘Using Natural Resources for Development: Why Has It Proven So Difficult?’, Journal of Economic Perspectives (): –.

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        ......................................................................................................................

                    .............................................................................................................

 

. I

.................................................................................................................................. T economics of development and structural change highlight the importance of industrialization as a means for countries to move from poverty to higher living standards and well-being. Industrial policy—that is, an articulated policy path to industrialization and the production of higher valued-added goods and services—is a means to achieve that goal. Markets on their own, however, do not ensure that the benefits of industrialization are equitably shared. With the scope of industrial policy becoming far broader than had traditionally been conceived, integration of issues of equality and inclusion are both timely and needed.¹ While greater equality that ensures the benefits of structural change and industrial upgrading are broadly shared is a goal in its own right, a large body of research on feedback loops from intergroup equality to the macroeconomy² suggests that the degree of equality itself impacts the effectiveness of industrial policy. For example, correctly implemented, industrial policies that promote greater equality generate the aggregate demand required to absorb increased output, putting the economy on a path to equity-led structural change and growth. And at the same time, greater equality has positive supply-side effects on the quality of the labour force and knowledge assets, key components of successful industrial policies. Attention to the role of gender equality in the success of industrial policies is yet another, albeit relatively neglected, way in which the industrial policy frame can usefully be expanded. This chapter explores the two-way relationship between gender ¹ On the changing landscape and scope of industrial policy, see Oqubay (Chapter , this volume) and UNCTAD (). ² See, for example, UNDP () and Ostry et al. ().

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

 

and industrialization and the consequent implications for industrial policy design. In terms of the effect of industrialization on gender, the employment, consumption, social reproduction, and knowledge production channels are the most salient. Regarding employment, in the early stages of industrialization of developing countries, women’s share of manufacturing employment rose substantially, albeit under conditions of insecure employment and low wages, with little opportunity to move up the ladder to better paid jobs. That trend appears to reverse as countries industrially evolve, with evidence of women excluded from jobs in more knowledge- and capital-intensive industries. This has occurred despite the fact that gender educational disparities have narrowed and even closed in a number of countries. Women are also underrepresented in high-tech firms, and more generally, in job categories associated with innovation and technological change. Apart from the loss of women’s talent in such jobs, this limits the types of innovations generated, and omits the interests and needs of women as consumers in product design. It also leads to a lack of attention to technologies that could reduce unpaid care work, with which women are disproportionately burdened. As outlined in this chapter, substantial economic gains could be achieved by industrial policies that promote gender equality. This suggests that gender should figure prominently in industrial policy design from the start, expanding the scope of industrial policies related to sustainability and inclusion.

. T I  I P  S C  G E

.................................................................................................................................. At the broadest level, the aim of industrial policy is to stimulate productivity growth in order to raise living standards. The way to do this is to generate the conditions for the production of high value-added goods, in particular manufactured products but also services and agricultural goods (Oqubay, Chapter , this volume; Cramer and Tregenna, ). To achieve this goal, industrial policies target activities that promote gains in productivity and employment, foreign exchange earnings via export competitiveness, production arrangements that support backward and forward linkages, and perhaps most importantly, knowledge production, including learning by doing, in order to support dynamic comparative advantage. Governments face significant social, economic, and environmental challenges that, if left unaddressed, can undermine progress in achieving the objectives of industrial policy. For example, the negative environmental impacts of pursuing industrialization and development with current energy technologies are by now well understood. The ‘greening’ of industrial strategies has been advanced as a means to address environmental challenges while promoting growth of output and employment (Rodrik, ; Pollin,

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    



Chapter , this volume). The Green New Deal is an example of an industrial policy that addresses environmental goals as well as equity issues (Ocasio-Cortez, ). Gender inequality is also impacted by industrial policies, and thus requires targeted efforts to design gender-equalizing policies. There are several channels through which industrial policies affect the degree of gender inequality. Among them, the most important are the following: () structural change influences access to employment and wages, and may be gender equalizing or dis-equalizing due to the existence of gender job segregation, unrelated to human capital differences; () industrial policies influence innovation pathways that result in the diffusion of new varieties of industrial goods that may benefit some groups more than others; and () public investment in infrastructure may reduce or exacerbate gender inequalities, especially in the sphere of social reproduction.

.. Gender, Employment, and Industrialization The impact of industrial policy, industrialization, and structural change on women’s relative access to paid employment has long been a topic of feminist economics research. A gender division of labour continues to be pervasive globally and is one of the main sources of gender income inequality. Two salient aspects to this phenomenon are that: () women are socially assigned responsibility for unpaid labour that produces and reproduces the labour key to the industrialization process; and () even within the paid sector of the economy, jobs are ‘gendered’, with women slotted into lower-quality occupations and industrial sectors of the economy. I begin with a discussion of the relationship between industrial policy, industrialization, and gender job segregation. Industrial policies, whether in the United States in the s or in semi-industrialized countries since the s, began with the development and expansion of labour-intensive manufacturing industries, most notably garments and textiles. Due to their lower wages than similarly qualified men, women have been the target labour force in these and other labour-intensive industries. The pursuit of cheap labour sources is intensified in economies that rely on exports to stimulate growth, with export competitiveness enhanced by low unit labour costs and thus low-wage labour. The recent period of globalization that began in the s in response to the liberalization of trade and investment flows has exacerbated the pressure on early industrializers to rely on low-wage female labour as a means to attain competitiveness. Two descriptive terms have emerged for this trend—the ‘global feminization of labour’ (Standing, ) and the ‘feminization of foreign exchange earnings’ (Samarasinghe, ).³ ³ The feminization of foreign exchange earnings is particularly salient in developing countries. With few exceptions, countries cannot run persistent current account deficits. This implies that national income cannot grow faster than the rate at which export growth at least equals import growth (Thirlwall,

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

 

This is not to say that industrial policies have explicitly identified women as the preferred source of low-wage workers in labour-intensive jobs. Rather, export-led labour-intensive industrialization has been passively compatible with, and indeed, has relied on patriarchal norms. Those norms, which assign women the responsibility for unpaid labour, meant that women have often been barred from light manufacturing employment once married.⁴ This proved essential to the success of industrial policies in so far as women provided the unpaid labour that produced and reproduced the labour force. That labour includes the care, socialization, and training of children and activities to ensure the productivity of adult workers (e.g. cooking and other tasks that maintain the household, as well as provision of emotional labour). Young unmarried women, as a result, have been the target factory workers in a number of industrializing countries in the last four decades.⁵ This is due to their low wages, perceived docility,⁶ ideologically constructed stereotypes about women (such as their supposedly ‘nimble fingers’),⁷ and the flexibility of hiring and firing women to reduce labour costs in response to fluctuations in product demand. What are the channels through which gender wage inequality stimulates growth? Women’s low wages are less a function of their skills than of overt gender wage discrimination as well as job segregation that reduces women’s bargaining power, depressing their wages. There is evidence that women’s low wages have been a causal factor in the success of the industrial policies that have stimulated the growth of export manufacturing in a number of newly industrializing economies (Seguino, ; Busse and Spielmann, ). Women’s low wages have substituted for (or complemented) currency devaluation, making exports cheaper than they would otherwise be and thus stimulating demand as well as a country’s share of global supply. This serves to relax the balance-of-payments constraint. Women’s low wages in labour-intensive manufacturing therefore act as a subsidy that supports the acquisition of intermediate inputs and technology required in more capital- and skill-intensive manufacturing industries. Neoclassical theory posits that women’s subordinate position in the industrialization process will improve over time. This view is based on the assumption that the strong demand for female labour and increased educational opportunities for women would ). Developing countries, typically dependent on imported intermediate and capital goods (for which demand is price inelastic), therefore rely heavily on exports to relax the balance-of-payments constraint. ⁴ The ‘marriage bar’, once widely practised in Europe and the United States in the s, and more recently by some late industrializing economies such as South Korea and Taiwan, has resulted in employers terminating women workers upon marriage. ⁵ The Industrial Revolution was also characterized by its heavy reliance on women’s factory labour (Berg, ; Freeman, ). ⁶ Perceptions of docility were, however, challenged by women factory workers’ militancy, a notable case being that of South Korea in the s and s, to which the government retaliated with force (Nam, ). ⁷ This refers to the assumption of greater manual dexterity making women more productive than men in some types of factory work, like assembly production, and less suitable for jobs requiring ‘brawn’ such as mining and heavy manufacturing. For a ground-breaking article on this topic, see Elson and Pearson ().

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    



contribute to rising female wages and a narrowing of the gender wage gap over time. Scholarly work on trends in gender wage inequality indicates that such optimism is not warranted. There is evidence that the discriminatory portion of gender wage gaps has widened in a number of industrializing countries, such as China, India, Mexico, and Vietnam, despite a strong demand for women’s labour (Braunstein, ). Downward pressure on women’s manufacturing wages is due to several factors. Women workers’ concentration in labour-intensive export industries as compared to men’s in non-tradables or capital-intensive export goods production results in women’s weaker bargaining power. Labour-intensive firms that are more mobile than ‘male’ industries can more easily relocate to other countries, should wages rise, holding down women’s wages (Seguino, ). Further, many firms in developing countries are subcontractors in global buyer- or producer-driven commodity chains. The outsized bargaining power of the dominant firms in the chain allows them to obtain low-cost components and assembled goods from subcontracting firms in developing countries, squeezing the wages of (women) workers. Again, the gendered effect is a function of the forms that gender job segregation takes in industrializing countries that have promoted export-led growth. As semi-industrialized countries have moved up the industrial ladder, employing production technologies that are more capital and knowledge intensive, there is substantial evidence of de-feminization—that is, of women’s declining share of manufacturing employment (Tejani and Milberg, ; Kucera and Tejani, ; Saracoglu et al., ). Kucera and Tejani () conducted a decomposition analysis to more fully understand this trend, focusing on two causal mechanisms of de-feminization. The first is the reallocation effect—that is, the impact on women’s share of employment due to the shift in production to more capital- and knowledge-intensive goods. The second is the within-industry employment effect, whereby industrial upgrading within an industry contributes to the decline in women’s share of employment. While they find evidence of both effects, within-industry effects in the manufacturing sector dominate in explaining the declines in female shares of manufacturing employment. Kucera and Tejani (: ) explain: Though structural change in the process of economic development is indeed characterized by shifts toward less labour-intensive, higher value-added manufacturing industries, it is developments within industries that generally matter more in accounting for patterns of feminization and de-feminization for the manufacturing sector as a whole.

In addition to women’s declining share of manufacturing employment as capital intensity of production rises, there is evidence of increased gender job segregation, with a declining share of women employed in industry⁸ (a broader measure than

⁸ Industry comprises mining, manufacturing, construction, electricity, water, and gas.

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

 

manufacturing) relative to the share of men employed in industry.⁹ This is indicative of increased exclusion of women (relative to men) from jobs in the industrial sector as a whole, where employment tends to be of higher quality than in the agricultural and services sectors.¹⁰ Data in Figure . demonstrate that gender job segregation is increasing in countries at varying stages of development over the period  to , reflecting women’s declining access to industrial employment (and thus crowding into jobs in other sectors of the economy). Panel A shows these trends by region.¹¹ Gender job segregation is measured as the ratio of the share of women employed in industry relative to the share of men employed in industry—dubbed ‘women’s relative concentration in industrial-sector employment’. The largest decline in women’s relative concentration (– per cent) occurred in the most industrially dynamic region, East Asia and the Pacific, closely followed by the Middle East and North Africa (MENA), and Central Europe and the Baltics. Sub-Saharan Africa has experienced increased relative exclusion of women from industrial-sector jobs as well, but to a lesser extent than more industrialized regions. South Asia has not experienced an increase in gender job segregation and this may be due to the fact that this region is still engaged primarily in labour-intensive export production. Panel B displays trends in gender job segregation by stage of development. As would be expected, in low-income countries, industrialization is less likely to be characterized by a decline in women’s relative concentration in industrial-sector employment. The most substantial decline (  per cent) is in middle-income countries. The increase in job segregation in high-income countries is also strong. There, women’s relative share of industrial jobs declined by  per cent over this period. Finally, changes in women’s relative concentration in industrial-sector jobs in selected noteworthy industrializing countries are shown in Panel C. The largest increase in job segregation among these countries has taken place in Ethiopia, with women’s relative concentration falling  per cent (from  per cent to  per cent) over this time period. Note that this occurred in the context of expanding industrial output, such that the percentage of women employed in the industrial sector as well as the percentage of men so employed rose during the period, but men’s rose more than women’s (from . per cent to . per cent as compared to . per cent to . per cent

⁹ Though a related concept, de-feminization is measured differently from gender job segregation. The former is the percentage of manufacturing employees that are women. The latter represents how women (relative to men) are distributed across sectors of the economy, and in particular, in industry as compared to other sectors. ¹⁰ That agricultural employment tends to be of lower quality than industrial employment is not contested. It might be argued, however, that service-sector jobs can be of high quality. Although there is some validity to that argument, service-sector jobs are bifurcated in quality with low-wage service jobs typically held by women and racial/ethnic minorities and high-quality professional jobs in the financial sector, health services, and product design dominated by men. ¹¹ Regional categories are defined using World Bank categorizations in World Development Indicators.

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    



Panel A. Change in women’s relative concentration by region 0%

–22.8% –21.4% –18.2% –17.6% –14.1% –10.7%

–2.8%

–5% –10% –15% –20% –25% East Asia & Pacific

MENA Central Europe & Baltics

LAC

OECD

North SubAmerica Saharan Africa

South Asia

Panel B. Change in women’s relative concentration by country income level 0%

–2.6%

–7.3%

–20.7%

–15.8%

–5% –10% –15% –20% –25% Low Income

Lower middle income

Middle income

High income

Panel C. Change in women’s relative concentration, selected countries 10%

–20% –30%

a In di

–10%

85.4% 41.5% 33.2% 28.9% 18.6% 17.3% 15.8% –8.4% –5.3% 1.3%

Et hi op M ia a la ys ia Ko re a Ch in a M ex ico In do ne sia Br az So il ut h Af ric a Vi et na m

0%

–40% –50% –60% –70% –80% –90%

 . Change in women’s relative concentration in industrial-sector employment, – Note: LAC is Latin America and the Caribbean. MENA is the Middle East and North Africa. OECD is the Organisation for Economic Cooperation and Development. Women’s relative concentration in industrial-sector employment is defined as (share of employed women in industry)/(% of employed men in industry). Source: Author’s calculations from World Development Indicators (accessed November ).

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 

for women).¹² Similarly, in China, Indonesia, Vietnam, and India, the decline in women’s relative concentration in industrial employment is due to a more rapid increase in men’s concentration in industrial employment than women’s. In Malaysia, Republic of Korea, and South Africa, the share of women employed in industrial-sector jobs declined more than did the share of men so employed. And in Brazil and Malaysia, the share of women in industry fell while the share of men employed in industry rose. These trends do not bode well for the ability of structural change and industrial upgrading to contribute to gender equality. Why is de-feminization and increased gender job segregation occurring? The mainstream explanation for women’s exclusion (whether absolutely or relative to men) from high value-added jobs is that women’s lack of education renders them less qualified for skill-intensive jobs. That, however, ignores the fact that for many workers, skills are acquired on the job through training and learning by doing—and that educational gaps have in any case narrowed substantially over time.¹³ A number of other factors, including restrictive gender norms and stereotypes,¹⁴ contribute to women’s exclusion from good jobs as the economy upgrades. Moreover, as industries become less labour intensive, labour costs are not as much of a constraint on product demand or firm profits—and therefore, employing men at higher wages (than women’s) is not a significant hindrance to competitiveness or profits. In other words, gender discrimination in access to good jobs becomes less costly as economies evolve industrially. Those explanations, however, cannot fully explain the process of de-feminization and job segregation observed in industrializing countries. To understand gender employment dynamics occurring with structural change requires an analytical framework able to explain the determinants of intergroup inequality—and in this particular case, gender inequality as evidenced by women’s increased exclusion from higherequality jobs in the industrial sector. Stratification theory argues that intergroup inequality is created and reproduced by dominant groups in order to maintain their privileged access to, and control over, resources. Two mechanisms are used to maintain dominance: exploitation (paying people less than the value of what they produce), and opportunity hoarding (or exclusion) of prized economic assets such as high-quality jobs (Blumer, ; Tilly, ).

¹² Data are author’s calculations, based on modelled ILO employment data and reported in the World Development Indicators. A caveat in interpreting these results is that labour market statistics in a number of African countries have weaknesses so results should be interpreted with caution. ¹³ Moreover, Borrowman and Klasen (), using data on sixty-nine developing countries, find that rising education levels, either overall or of females relative to males, tend to increase rather than decrease segregation. ¹⁴ Norms are informal ‘rules’ about behaviour that solicit punishment if violated. Stereotypes are generalizations we make about groups of people that may or may not be accurate. More generally, they tend to reflect limiting and often negative assumptions about the characteristics of a particular group of people.

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    



Gender inequality persists and indeed is increasing in terms of job segregation as a result of these dual processes. Gender norms and stereotypes saddle women with the responsibility for unpaid labour that others benefit from (exploitation), and justify men’s right to the highest quality and status jobs, affirming a gender hierarchy. ‘Gender police’ are not required to enforce a system of stratification. Gender norms and stereotypes work to consolidate perceptions of group differences that justify exclusion. In the case of gender, for example, a widely held norm is that men are the primary breadwinners, and are thus most deserving of high-wage jobs. More recently, the stereotype has emerged that men are more suited to science and technology jobs than women. The gendering of newly created types of jobs in technologically upgrading industries demonstrates that even as old occupations associated with one gender or the other disappear in the process of structural change, gender stereotypes recreate gender inequality in new occupations and work environments (Ridgeway, ). The processes of de-feminization and increased gender job segregation are exacerbated in the context of increasingly scarce industrial-sector employment. In recent years, patterns of stalled industrialization or premature de-industrialization have been observed in a number of developing countries, limiting the growth of industrial-sector jobs (UNCTAD, ). The result is a relative downsizing of the core industrial sector. A falling share of industrial jobs in total employment can intensify competition for the fewer jobs available, triggering the forces of stratification that influence job access. Seguino and Braunstein () present empirical evidence that structural change, as evidenced by increases in capital/labour ratios, combined with declining industrial employment shares of total employment, have contributed to a worsening of gender job segregation since . As a result of stratification dynamics, structural change induced by industrial policies can, and has, led to increased exclusion of women from employment in upgrading sectors in countries, resulting in women being crowded into other sectors of the economy, and putting downward pressure on their wages. This discussion underscores two key points. First, industrial policies that promote structural change and the shift to higher valued-added production using more sophisticated technologies can contribute to and exacerbate already existing gender inequality. Women as workers may be the losers, absent attention to the dynamics that lead to their exclusion from newly created jobs. Second, macroeconomic conditions matter. Productivity growth is not sufficient for workers to obtain the benefits of industrial upgrading. An exclusive focus on a supplyside increase in output through industrial policy misses the fact that aggregate demand and other macro-level policies (such as exchange rate, trade, and investment policies) may not be sufficient to ratify the increases in potential output that comes with effective industrial policy. Without sufficient demand growth for industrial output, there will be negative effects on employment, that is, de-industrialization, and ultimately, more intense gender job competition that contributes to gender inequality. These problems are not fatal to industrial policies that intend to be inclusive. Below I discuss approaches to industrial policies that can alleviate the potential for upgrading

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 

to worsen gender inequality. Suffice it to say that just as industrial upgrading is unlikely to happen without government intervention in the form of industrial policy, so too industrial policy is unlikely to be gender equitable, absent specific policies to override gender dis-equalizing practices embedded in labour markets and other institutions.

. G E F L: I  S  I P

.................................................................................................................................. Just as industrial policies may affect women and men differently—and potentially unequally, via gendered employment effects—so too does gender (in)equality affect the potential success of industrial policies, and the desired structural change that accompanies those policies. The following discussion, while not exhaustive, highlights salient aspects of feedback loops with regard to labour productivity and knowledge production.

.. Gender and Labour Productivity Growth A key question identified in section . is how to make industrial policy inclusive, given that gender job segregation is prevalent, with women slotted into lower-wage jobs and unpaid labour, and men dominating in higher-wage industrial jobs. This question is all the more pertinent due to the complementarities between production methods and a country’s level of skills and capabilities. As a country moves up the industrial ladder to the production of more knowledge- and capital-intensive goods and services, governments must ensure that human capability improvements, the invisible foundation of a country’s successful economic development, keep pace. Conventional economics portrays labour productivity as merely a function of the level of formal education and on-the-job training of the individual. That narrow characterization misses the important fact that long before arriving at the factory or office door, people as a resource have been produced through significant amounts of material investment as well as time. Recognizing this, feminist economists have expanded the concept of human capital in a way that treats it as an asset that is coproduced by families and government, rather than simply a product of the formal education system (Folbre, ). To differentiate the use of this term from its traditional definition employed in economics, we use the term human capacities, which reflects the full breadth of learning and socialization that extends beyond formal education and is required for workers to be productive.

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    



Investments in human capacities raise future productive capacity (i.e. generate economic growth) in ways similar to building more factories and equipment, though investing in the future labour force is almost never treated as investment in macroeconomic models (Braunstein, van Staveren, and Tavani, ; Heintz, ). Although governments and men also participate in human capacities development, it is primarily women who carry out the work of social reproduction by doing both paid and unpaid caring labour.¹⁵ Macroeconomic and economic development theory err by assuming women’s unpaid care work is infinitely elastic. But women’s participation in the paid economy necessarily affects the quantity of investment in human capacities—that is, the more time spent in paid work, the less time and energy is available for investments in human capacities. Failing to track and ensure sufficient human capacities investments can cause industrial and other macroeconomic policies to inadvertently undermine social reproduction with negative effects on the current and future labour supply’s productivity and ability to provide the complementary skilled labour needed as countries industrially upgrade. How can industrial policy take account of and address this problem? Through public policies and infrastructure investment, governments can redistribute and reduce¹⁶ unpaid care work, creating the conditions for women to participate in the paid economy without sacrificing investments in the care labour required to ensure children become a productive future labour force. Public policy can influence the distribution of care work between women and men, and can also reduce the amount of necessary care work through public investment in physical infrastructure (roads, sanitation, and electricity that reduce the time necessary for care activities such as fetching water and fuel), as well as social infrastructure (spending on publicly funded care services). These expenditures, which can reduce women’s unpaid care burden and redistribute social reproduction to the state and to men, also support the goals of industrial policy. Attention to issues of social reproduction, then, is another way in which the scope of industrial policies can be expanded beyond its traditional frame. Braunstein, Bouhia, and Seguino () present a model and empirical analysis that links structures of class-driven growth of output, employment, and productivity with those of social reproduction and gender inequality. How social reproduction is organized (Who does it? Does it take place in the household, or in public or market sectors?) influences long-run productivity. The analysis covers the period ‒. Principal components analysis (PCA) scores, based on indicators of social reproduction and ¹⁵ Social reproduction is a concept with origins in Marx’s concept of the development of productive forces (Cohen, ). It includes activities directly involved in the maintenance of life on a daily basis and intergenerationally, including the development of children and the regeneration of workers and is thus a far broader concept than human capital. The latter is defined as capacities developed through formal and informal education at school and at home, and through training and experience. For a critique of human capital theory from a social reproduction perspective, see Folbre (). ¹⁶ Diane Elson () describes the government’s task with regard to work as the  Rs—recognize, redistribute, and reduce.

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

 

equality-led vs. profit-led growth, are used to categorize national economies into one of four regime types: mutual, time squeeze, wage squeeze, and exploitation. Applying PCA to this typology, the authors identify the conditions under which systems of growth on the one hand and social reproduction on the other reinforce or contradict one another, with a focus on the role of gender (in)equality. Mutual regimes are the ideal—production and social reproduction dynamics mutually reinforce each other. In this scenario, more gender equality (higher wages, more time spent in paid labour) raises growth of output, employment, and productivity because it raises aggregate demand¹⁷ and promotes human capacities development more than it cuts into profits. Strong public support for care, the availability of care commodities, and men stepping up to provide care all add to the beneficial impact of gender equality on growth and social reproduction. In time squeeze countries, more gender equality in the form of higher wages for women or for care workers supports investment and growth because it raises human capacities. However, as women’s labour-force participation increases, the time devoted to care work decreases (because men do not contribute enough to care work, market care services and commodities are inadequate,¹⁸ and/or due to infrastructure inadequacies). This inhibits structural change and the success of industrial policies more generally, owing to the negative effect on labour productivity growth. In wage squeeze countries, higher wages for women raise human capacities but not by enough to outweigh the negative effect of those higher wages on profits, investment, and thus growth. The more profit-led (or inequality-led) the structure of the macroeconomy, the more likely wage squeeze is likely to be obtained. The more open to the global economy, the greater the probability an economy is profit-led, exacerbating the contradictions between gender equality, social reproduction, and growth (Blecker, ). And finally, the exploitation regime is one in which higher wages for women reduce growth because they dampen profits and aggregate demand more than they raise human capacities investment. And women’s higher wages and increased market participation squeeze time spent on social reproduction, a problem that is accentuated in the event of lack of public or male support, and absence of adequate care commodities and infrastructure to replace women’s decreased care time. In this regime, growth is predicated on exploiting women’s (unpaid) reproductive labour. Gender/growth regimes vary widely among the countries that have adopted industrial policies in the last several decades (Table .). This variation is demonstrated by the BRICS, among which Brazil’s is the only regime to fall into the mutual category. The recent increases in social protection spending there are instructive, demonstrating the importance of public policy to promote gender equality. But Brazil’s poor

¹⁷ One channel through which this takes place is that improvements in women’s labour-market outcomes (both wages and employment) allow them to replace some of their unpaid labour with paid care services, thus stimulating demand. ¹⁸ This could be due to lack of quality market (paid) care services, as well as insufficient capital goods such as stoves or washing machines.

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    



Table 16.1 Gender regimes in BRICS and selected developing and developed countries Regime type BRICS Brazil Russia India China South Africa

Mutual Wage squeeze Exploitative Wage squeeze Wage squeeze

Developing Africa Ethiopia Nigeria Rwanda

Time squeeze Time squeeze Time squeeze

Developing Asia Bangladesh Hong Kong Indonesia Malaysia Singapore South Korea Thailand

Time squeeze Wage squeeze Wage squeeze Wage squeeze Wage squeeze Wage squeeze Wage squeeze

Developed economies Finland France Germany Ireland Norway Poland Sweden United States

Mutual Mutual Wage squeeze Wage squeeze Mutual Exploitation Mutual Time squeeze

Source: Braunstein, Bouhia, and Seguino (2020).

macroeconomic performance (relative to other successful industrializers) reminds us that a mutual regime does not automatically or inherently induce economic growth, absent supportive macroeconomic policies such as appropriate exchange-rate policy (Astorga, Cimoli, and Porcile, ).¹⁹ ¹⁹ Argentina, Colombia, and Ecuador also have mutual regimes. For a full list of regime types in countries by region and at varying levels of development, see Braunstein, Bouhia, and Seguino ().

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 

In contrast, China, Russia, and South Africa are characterized as wage squeeze regimes. In those cases, higher wages for women show slow growth (these are profitled economies, due to the structure of production and macro-level policies) because the benefits to human capacities production are outweighed by the negative effect of higher wages on profits, investment, and demand.²⁰ India is a case of an exploitative gender/growth regime. Improvements in gender equality in the paid economy negatively impact growth, while movement of women into the paid economy reduces human capacities due to government’s failure to take action to redistribute unpaid care work, lack of adequate infrastructure, and insufficient male participation in care work. Among developing African economies that have adopted industrial policies, Ethiopia, Nigeria, and Rwanda have time squeeze regimes (as do many other African economies). As more women enter the labour market in these countries, the consequent strain on women’s time limits human capacities development and the growth of labour productivity. The policy implication of this combination is clear: increasing women’s paid employment must be accompanied by more support for care and social reproduction to sustainably deliver growth—and absent attention to this, industrial policies may very well not succeed in the longer run due to insufficiently productive workers, whose labour is complementary to industrial upgrading.²¹ In developing Asia, most regimes can be characterized as wage squeeze. Those that have adopted extensive industrial policies fall into this category—South Korea, Malaysia, Indonesia, and Thailand. Finally, developed economies have a higher number of mutual regimes (Finland and Norway, for example), but here too we find wage squeeze (Germany and Ireland), time squeeze (United States), and exploitation (Poland). It is apparent from this analysis that industrial policies can succeed by exploiting women’s time, and/or excluding them from participating in the development process—although those that structurally constrain investments in care and social reproduction are likely to pay a cost in the longer run due to lower labour productivity growth. Ensuring a win‒win scenario—that is, structural change that induces an

²⁰ To be clear, this does not imply wages for women should be lowered in order to promote growth. Macro policies, such as exchange-rate policies to maintain export competitiveness, can attenuate negative demand-side effects of higher female wages. Moreover, managed trade policies and restrictions on financial and firm mobility can create conditions for equality-led growth (Seguino and Grown, ). And a shift in the structure of production to reduce reliance on labour-intensive homogeneous export goods and a shift to skill- and capital-intensive goods production—with women integrated into new industries—can contribute to the creation of a mutual regime. That is because the latter types of goods and services tend to be price inelastic, such that higher wages have a much smaller negative effect on demand than on labour-intensive goods. ²¹ Among economists noting the complementarity of labour’s skills with industrial upgrading, Nelson and Phelps () have argued that the rate at which the gap between the technology frontier and the current level of productivity is closed depends on the level of human capital. In a more detailed analysis, Nübler () offers a theory of knowledge-based capabilities (a broader concept than human capital) whereby capabilities and structural change co-evolve and are mutually causative, and applies this to an analysis of the divergent paths of South Korea and Costa Rica.

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    



economy’s movement to higher value-added production with women included in that process—requires attention to tendencies towards excluding women from higher-wage and more technically sophisticated jobs and necessitates appropriate public investment and policies that promote human capacities development by redistributing and reducing the care burden women differentially shoulder.

.. Gender and Knowledge Production Knowledge production, situated in formal education and research, as well as workplace teams, is vital to the success of industrial policies. Gender inequality and in particular gender exclusion from these sites, however, can hinder innovation and the acquisition of knowledge. STEM (science, technology, engineering, and mathematics) education and research are essential to industrial policy, and here women are underrepresented, even though they are now the majority of university students in most countries (UNESCO, ).²² The challenge is that exclusion of women results in a selection bias problem with significant costs in terms of knowledge production and economic growth (European Institute for Gender Equality, ). That is, gender-unequal participation in STEM programmes in universities and research institutes can result in overinvestment in less qualified males, and failure to capture the benefits of an excluded talent pool of women, which has costs in terms of knowledge production.²³ In part, the low representation of women in STEM fields and research entities is due to gender-unequal norms and stereotypes that shape attitudes of the gatekeepers— professors, and directors and managers of research institutes. STEM subjects are typically characterized as ‘male’ and that characterization is not too distant from the facts. The majority of professors of STEM are male, sending an often unconscious message about what scientists look like. This both discourages women from entering STEM, and also causes implicit biases that can lead to subtle and overt forms of discrimination on the part of male faculty and students that make STEM a hostile environment for women. To make clear the point advanced here, the loss of women’s talent in STEM, a critical set of fields for industrial upgrading, may appear to be a labour-supply problem attributed simply to women’s lack of interest in science and engineering. But a more accurate understanding is that while this is a labour-supply problem, it results from exclusionary practices in both universities and research institutes (and tech-related workplaces) that create a hostile environment for women. ²² It is often argued by way of explanation that women simply choose to study topics other than science. That view, however, is inconsistent with the fact that women are the majority of students in the natural sciences and mathematics and statistics, even as they lag men in engineering, manufacturing, and construction ( per cent of all students), and information and communication technologies ( per cent of all students) (UNESCO, : ). ²³ Several studies also show that gender inequality in education in general has negative effects on growth (Bandara, ; Klasen and Lamanna, ). See also İzdeş and Tregenna ().

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 

Learning and upgrading for late industrializers is also predicated on the ability of organizations to incentivize and coordinate learning (Amsden, ). The composition of organizations impacts their effectiveness in the problem solving so central to industrial upgrading. A by now large body of research underscores that diverse organizations function more effectively than homogeneous ones. Economist and complex systems theorist Scott Page () finds evidence, for example, that identity-diverse groups (e.g. based on gender, race/ethnicity) can outperform homogeneous groups due to their greater functional diversity—that is, differences in how people define problems and approach solving them. With regard to the industries that are critical to industrial upgrading, Vasilescu et al. () similarly find that team diversity in open software development projects correlates positively with team output. Male and female engineers who collaborate with both genders are roughly twice as productive—that is, they produce more citations in peer-reviewed articles—than those who only collaborate with one gender (Ghiasi et al., ). Group composition matters, in other words, and in particular, lack of gender diversity in STEM activities, industries, and organizations can limit knowledge generation. Given that gender inclusion contributes to success in high-tech organizations, what factors explain women’s low representation? Discrimination, due to implicit or explicit bias, is an important factor.²⁴ As an example, one study finds that women’s opensource software coding has a higher acceptance rate than men’s when a coder’s gender is unknown. But when the gender of the coder is known, acceptance rates of women coders’ proposed changes to a software project’s code or documentation fall (Terrell et al., ). Tech workplaces more generally are widely reported to be hostile towards women scientists, with undermining by male managers a key reason given by women for leaving tech jobs (Mundy, ). This state of affairs, predicated on gender hierarchical practices embedded in organizations, is a market failure to be addressed by industrial policy.

.. Gender, Diversity, and Technical Design Exclusion of groups of people (e.g. women) from technological domains and activities can lead to their absence as users or consumers of technology because products

²⁴ Explicit bias refers to conscious attitudes and beliefs we have about people or groups of people. In contrast, implicit bias is an unconscious association or belief towards a social group. Implicit bias is shaped by social conditioning in response to dominant norms and stereotypes, such as that women are less good at science, that men are more intelligent, and so on. Stratification theorists argue that hierarchical norms and stereotypes are intentionally cultivated as a means for dominant groups (men) to legitimize their privileged position in institutions and broader society (Darity et al., ).

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    



developed do not reflect women’s needs and preferences. According to Wajcman (: ): Empirical research on everything from the microwave oven . . . the telephone . . . and the contraceptive pill . . . to robotics and software agents . . . has clearly demonstrated that the marginalisation of women from the technological community has a profound influence on the design, technical content, and use of artefacts.

In contrast, drawing on women for design can lead to benefits for women consumers of technology, whose needs are more likely to be taken into account—and could have the added benefit of addressing and reducing time required for social reproduction.²⁵ Several examples of the failure of technological innovation to represent the needs of women are instructive. A wide variety of products marketed as gender neutral are in fact biased towards men’s bodies: virtual reality headsets too big for women’s heads, smart watches too big for women’s wrists, and calorie counts on treadmills calibrated to men’s bodies are just a few examples (Perez, ). The problem is particularly serious when it comes to testing and safety. Although women are more likely to contract HIV than their male counterparts, they represent just  per cent of antiretroviral drug subjects in clinical trials (Ovseiko et al., ). Crash-test dummies, used to test the safety of automobiles, are typically male, despite the fact that women are at higher risk of serious injury in automobile accidents (Holder, ). This discussion underscores that inclusion of women in technical design can generate a more equitable distribution of the benefits of industrialization. Inclusion of women in the design of products could also contribute to a reduction of the grind of domestic housework that women disproportionately bear. Addressing the time squeeze of social reproduction, as noted in section ., has a positive effect on the long-run success of industrial policies.

. C

.................................................................................................................................. As a number of chapters in this volume indicate, the conceptualization of industrial policies has broadened, and is beginning to encompass sustainability and greening ²⁵ The introduction of labour-saving consumer durables (such as washing machines and vacuum cleaners) reduced the time required for household work, contributing to the rise of women’s labourforce participation in the twentieth century (Greenwood et al., ). I do not know of any recent studies, however, that measure the pace of household labour-saving technological change that reduces the time needed for care work. Much of the current research on this topic focuses on estimating the genderequalizing benefits of public infrastructure investment. See, for example, de Henau and Himmelweit () and Fontana and Natali (). There is also some evidence that information and communication technologies (ICT) reduce women’s time burden although, to be clear, ICT development was not originally targeted to reduce unpaid care burdens (Grassi, Landberg, and Huyer, ). A concern is that technological innovation emerges from the global North and is ill suited to the needs of women from the global South, who have a greater need for clean water and electricity than digital technologies (Mitter, ).

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

 

policies in addition to the themes of technology, innovation, and knowledge production. The relationship between gender and industrial policies, however, has not yet been comprehensively explored or integrated into the industrial policy literature. To address that gap, this chapter highlights several key channels through which gender and industrial policy interact: employment, consumption, social reproduction, and knowledge production and innovation. Regarding the employment channel, research has identified women’s instrumental role in providing the labour linked to the success of early-stage late industrialization efforts via women’s segregation in labour-intensive export manufacturing industries. As countries move up the industrial ladder, however, women become increasingly excluded as workers in industry, and are crowded into low-wage employment. Gender exclusion from employment in the dynamic sector of the economy is an important challenge for industrial policy. With respect to social reproduction, industrializing countries have also relied on women’s unpaid labour to nurture the development of the human capacities required of a skilled, productive labour force. This has unduly burdened women, and contributed to the gender wage and income gap. Further, by failing to recognize and redistribute the burden of unpaid caring labour—or social reproduction—productivity growth is hampered. The research discussed in this chapter also identifies the economic costs of the absence of equitable gender inclusion in processes of innovation and technological upgrading. Exclusion of women from knowledge-intensive workplaces can negatively affect the efficiency of firms’ learning and innovation efforts. Women’s limited representation in high-tech firms and occupations is often attributed to their preference for fields of studies such as humanities and the arts, rather than sciences. But this ignores the exclusionary practices and distorted gender norms and stereotypes that contribute to women’s exclusion from high-tech workplaces. Further, failure to include women in technology design undermines the ability of technological innovation to produce benefits for women as consumers. A challenge, then, is for industrial policy advocates, whether academics or policymakers, to adopt a gender lens so as to improve the efficacy of industrial upgrading efforts and to make those efforts more inclusive (Fontana, ). The tools that governments use to nudge, cajole, and encourage the private sector and research institutions to cooperate with industrial upgrading plans can also be used to address gender disparities identified in employment. Reciprocal control mechanisms, such as making subsidies and other supports contingent on achieving performance targets, can be used to incentivize gender inclusion. For example, governments could require (and some already do) that research teams on government-funded grants be gender balanced as a means of promoting gender inclusion in research that influences product and technology design. Governments could also use innovative monetary policy tools to achieve gender inclusion. Asset-based reserve requirements (ABRRs) are one such mechanism, whereby central banks use non-interest-bearing reserve requirements to guide the

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    



allocation of credit towards areas deemed of strategic importance.²⁶ Women-owned tech firms, or firms with an equitable representation of women in high-level positions could be the targets. Of course, state-owned development banks could also target their lending to achieve strategic goals, including those that promote gender equality. Social reproduction policies are also legitimately part of an industrial strategy. Publicly funded physical infrastructure, targeted at reducing women’s care burden in developing countries, can reduce time poverty, enabling women to join the paid labour force. Moreover, other social policies such as publicly funded care of children, the sick, and elderly, as well as policies that promote male participation in care, are critical to redistributing and reducing care work, promoting gender inclusion in employment. It also reduces any potential negative trade-off between women’s increased paid employment and investment in children’s and workers’ human capacities and, ultimately, long-run productivity growth. The message, then, for both scholars and policymakers is that the distributional effects of industrial policy should be understood and interventions designed to ensure that the benefits are broadly shared. Doing so also contributes to the effectiveness of industrial policy.

A I am grateful to Christopher Cramer, Fiona Tregenna, Will Milberg, and James Heintz for providing valuable comments and suggestions on earlier versions of this chapter. Any omissions or errors are my own.

R Amsden, Alice () Asia’s Next Giant: South Korea and Late Industrialization. Oxford: Oxford University Press. Astorga, Rodrigo, Mario Cimoli, and Gabriel Porcile () ‘The Role of Industrial and Exchange Rate Policies in Promoting Structural Change, Productivity and Employment’, in José Manuel Salazar-Xirinachs, Irmgard Nübler, and Richard Kozul-Wright (eds) Transforming Economies: Making Industrial Policy Work for Growth. Geneva: International Labour Office, pp. –. Bandara, Amarakoon () ‘Economic Cost of Gender Gaps: Africa’s Missing Growth Reserve’, Feminist Economics (): –. Berg, Maxine () ‘Women’s Work and the Industrial Revolution’, in Anne Digby, Charles Feinstein, and David Jenkins (eds) New Directions in Economic and Social History, Vol. . Basingstoke: Macmillan International Higher Education, pp. –.

²⁶ For more on ABRRs and other innovative tools central banks can utilize to promote development, see Epstein ().

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

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Ghiasi, Gita, Vincent Lariviere, and Cassidy Sugimoto () ‘On the Compliance of Women Engineers with a Gendered Scientific System’, PLOS One. Available at https://journals.plos. org/plosone/article?id=./journal.pone.. Grassi, Flavia, Josephine Landberg, and Sophia Huyer () Running Out of Time: The Reduction of Women’s Work Burden in Agricultural Production. Rome: Food and Agriculture Organization. Greenwood, Jeremy, Ananth Seshadri, and Mehmet Yorukoglu () ‘Engines of Liberation’, Review of Economic Studies (): –. Heintz, James () The Economy’s Other Half: How Taking Gender Seriously Transforms Macroeconomics. Newcastle upon Tyne: Agenda Publishing. Holder, Sarah () ‘A Clue to the Reason for Women’s Pervasive Car-safety Problem’, CityLab. Available at https://www.citylab.com/transportation///car-accident-injurysafety-women-dummy-seatbelt//. İzdeş, Ozge and Fiona Tregenna () ‘Gender, Industrialization, and Industrial Hubs’, in Arkebe Oqubay and Justin Yifu Lin (eds) The Oxford Handbook of Industrial Hubs and Economic Development. Oxford: Oxford University Press. Klasen, Stephan and Francesca Lamanna () ‘The Impact of Gender Inequality in Education and Employment on Economic Growth: New Evidence for a Panel of Countries’, Feminist Economics (): –. Kucera, David and Sheba Tejani () ‘Feminization, Defeminization and Structural Change in Manufacturing’, World Development : –. Mitter, Swasti () ‘Globalization, ICTs, and Economic Empowerment: A Feminist Critique’, Gender, Technology and Development (): –. Mundy, Liza () ‘Why Is Silicon Valley So Awful to Women?’, The Atlantic Monthly, April. Nam, Jeong-Lim () ‘Labor Control of the State and Women’s Resistance in the Export Sector of South Korea’, Social Problems (): –. Nelson, Richard and Edward Phelps () ‘Investment in Humans, Technological Diffusion, and Economic Growth’, American Economic Review : –. Nübler, Irmgard () ‘A Theory of Capabilities for Productive Transformation: Learning to Catch Up’, in José Manuel Salazar-Xirinachs, Irmgard Nübler, and Richard Kozul-Wright (eds) Transforming Economies: Making Industrial Policy Work for Growth. Geneva: International Labour Office, pp. –. Ocasio-Cortez, Alexandra () ‘H.Res.: Recognizing the Duty of the Federal Government to Create a Green New Deal’. Available at https://www.congress.gov/bill/thcongress/house-resolution//text. Ostry, Jonathan, Andrew Berg, and Charalambos Tsangarides () ‘Redistribution, Inequality, and Growth’. Staff Discussion Note No. /. Washington, DC: IMF. Ovseiko, Pavel et al. () ‘A Global Call for Action to Include Gender in Research Impact Assessment’, Health Research and Policy Systems (). Available at https://www.ncbi.nlm. nih.gov/pmc/articles/PMC/. Page, Scott () The Diversity Bonus: How Great Teams Pay off in the Knowledge Economy. Princeton, NJ: Princeton University Press. Perez, Caroline Criado () Invisible Women: Data Bias in a World Designed for Men. New York: Abrams Press. Ridgeway, Cecelia () Framed by Gender: How Gender Inequality Persists in the Modern World. Oxford: Oxford University Press.

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Rodrik, Dani () ‘Green Industrial Policy’, Oxford Review of Economic Policy (): –. Samarasinghe, Vidyamali () ‘The Feminization of Foreign Currency Earnings: Women’s Labour in Sri Lanka’, Journal of Developing Areas (): –. Saracoglu, Dürdane, Emel Memis, Ebru Voyvoda, and Burça Kizilirmak () ‘Changes in Global Trade Patterns and Women’s Employment in Manufacturing, –’, Feminist Economics (): –. Seguino, Stephanie () ‘Gender Inequality and Economic Growth: A Cross-country Analysis’, World Development (): –. Seguino, Stephanie () ‘Is More Mobility Good? Firm Mobility and the Low Wage Low Productivity Trap’, Structural Change and Economic Dynamics (): –. Seguino, Stephanie and Elissa Braunstein () ‘The Costs of Exclusion: Gender Job Segregation, Structural Change and the Labour Share of Income’, Development and Change (): –. Seguino, Stephanie and Caren Grown () ‘Gender Equity and Globalization: Macroeconomic Policy for Developing Countries’, Journal of International Development (): –. Standing, Guy () ‘Global Feminization through Flexible Labour’, World Development (): –. Tejani, Sheba and William Milberg () ‘Global Defeminization? Industrial Upgrading and Manufacturing Employment in Developing Countries’, Feminist Economics (): –. Terrell Josh, Andrew Kofink, Justin Middleton, Clarissa Rainear, Emerson Murphy-Hill, Chris Parnin, and Jon Stallings () ‘Gender Differences and Bias in Open Source: Pull Request Acceptance of Women Versus Men’, PeerJ Computer Science : e. Available at https://doi.org/./peerj-cs.. Thirlwall, Anthony () ‘The Balance of Payments Constraint as an Explanation of International Growth Rate Differences’, Banca Nazionale del Lavoro Quarterly Review (): –. Tilly, Chris () Durable Inequality. Berkeley, CA: University of California Press. UNCTAD () Trade and Development Report: Structural Transformation for Inclusive and Sustained Growth. New York: United Nations. UNCTAD () World Investment Report . New York: United Nations. UNDP () Humanity Divided: Confronting Inequality in Developing Countries. New York: UNDP. UNESCO () Cracking the Code: Girls’ and Women’s Education in Science, Technology, Engineering, and Mathematics. Paris: UNESCO. Vasilescu Bogdan, Daryl Posnett, Baishakhi Ray, Mark Van den Brand, Alexander Serebrenik, Preemkumar Devanbu, and Vkadunur Filkov () ‘Gender and Tenure Diversity in GitHub Teams’, Proceedings of the rd Annual ACM Conference on Human Factors in Computing Systems, pp. –. Wajcman, Judy () ‘Feminist Theories of Technology’, Cambridge Journal of Economics : –.

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        ......................................................................................................................

    -      ,             ,                   .............................................................................................................

 

. I

.................................................................................................................................. A ‘competitive’ exchange rate became Beijing’s de facto industrial policy, by default or design, after China’s WTO membership (in ) blocked the country from utilizing more traditional instruments, such as export subsidies or measures to promote access to foreign technology (Rodrik, ; Guzman et al., ). Indeed, maintaining a stable, undervalued exchange rate helped the country increase its exports, and facilitated import substitution and economic diversification, helping China to turn an ‘infant’ manufacturing sector into a mature, internationally competitive industry that now employs tens of millions of people and serves as a factory for the world. What China’s successful experience using the exchange rate as a tool for economic development and transformation reveals is that the ‘right’ management of the macroeconomy can strengthen, supplement, or even replace the power of traditional industrial policy instruments. The ‘right’ macro policies ‘generate the essential enabling environment for industrial policies to be effective’, write Guzman, Ocampo, and Stiglitz (: ); in the example of China, macro and industrial policies have been complementary and mutually reinforcing.¹ However, China’s success contrasts with multiple failures by other late industrializing economies that have been unable to employ macroeconomic policy in sync with industrial policy. In many such cases, the opposite occurred: an unduly appreciated exchange rate limited the long-run diversification of production ¹ While a currency devaluation may initiate growth acceleration (as we argue later in this chapter), it is unlikely to sustain it indefinitely without supportive industrial and fiscal policies (Storm and Naastepad, ; Rodrik, ; Thirlwall, ).

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

 

and export structures, often even leading to ‘premature de-industrialization’ (Storm, ; Diao, McMillan, and Rodrik, ). Negative impacts of a ‘mistaken’ macroeconomic policy stance regularly outweigh any positive impacts of industrial policy decisions—which brings us to the central argument of this chapter: a failure to effectively manage the macroeconomy and aggregate demand in ways that support industrialization and economic development disables industrial policy, often fatally so. Macroeconomic mismanagement underlies many historical cases of failed industrialization pushes in South East Asia, Latin America, and Africa. This mismanagement is in no small measure due to clear supply-side biases of industrial policy, based on the belief that the impediments to late industrialization were to be found and resolved on the supply side of the economy. The aggregate-demand side of the economy, in contrast, was expected to more or less passively accommodate and even facilitate the structural changes brought about by the industrialization process (Storm, ). Macroeconomically speaking, domestic resource mobilization to finance investment was seen as the binding constraint on the industrialization programme; hence the key challenge was to raise domestic savings supply: The central problem in the theory of economic development is to understand the process by which a community which was previously saving, and investing,  or  per cent of its national income or less, converts itself into an economy where voluntary savings are running at about  or  per cent of national income or more. (Lewis, : )

Industrial policy scholars and policymakers have thus been led to focus on the building up of capital-goods (machine-tool) industries, the strengthening of inter-industry (supply) linkages, the rationing of scarce (often imported) inputs and foreign exchange, the mobilization of enough (domestic) savings to finance industrial development, and the accumulation of the technological, managerial and engineering knowledge necessary for efficient manufacturing. Unfortunately, for most late industrializers things did not work out as planned—industrialization processes ran into aggregate demand constraints, showing up in overvalued exchange rates, unsustainable trade deficits and external debts, profit squeezes, increased inequalities, and domestic demand collapses (Storm, ). This chapter analyses ways in which macroeconomic policy can support, or hurt, the industrialization process, using a simple (Kaldorian) open-economy growth model of a ‘typical’ late industrializing economy, which features ‘cumulative causation’ as well as an explicit balance-of-payments (BoP) constraint. The approach builds on the theoretical analyses by Storm and Naastepad (), Naastepad (), Blecker (), and the New Structuralist tradition which integrates Keynesian models of BoP-constrained growth (Thirlwall, , ; Cimoli et al., ) and Kaldorian-Schumpeterian insights into endogenous technical progress, innovation, and structural change in productive and export specialization (Kaldor, ; Taylor, ; Cimoli and Porcile, ; Porcile and Sartorello Spinola, ). The remainder of this chapter is organized as follows. We first present the export-led growth model, before introducing the

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-,  ,   



long-run BoP constraint in the model and considering the macro impacts of a traditional (supply-side) ‘big push’ industrialization drive. We next identify three (historically relevant) macro mechanisms through which an aggregate demand shortage can slow or even halt the industrialization process: (a) an ‘agrarian-cum-foreign exchange constraint’, which through higher food prices and higher industrial wages reduces manufacturing profits and investment (a Ricardian–Kaleckian story); (b) a drop in domestic (private and/or public) expenditure, which hurts growth, investment, and diversification (a Robinsonian story); and (c) restrictive fiscal and monetary policies, often intended to keep imports and inflation down, or to mop up additional domestic savings, and/or placate foreign financial investors, which has direct negative impacts on manufacturing investment and growth (a Keynesian story). Section . considers the ‘primary-commodity specialization trap’ and examines how macroeconomic policy can support economic diversification and upgrading (a KaldorianThirlwallian narrative). Finally we zoom in on the role of wages and labour regulation and argue that the widely held claim that strong labour laws are a ‘luxury’ developing countries cannot afford, is wrong from a Weberian-Marxian-Schumpeterian perspective. If anything, labour regulation and higher real wage growth do further industrialization, when given adequate macroeconomic and industrial policy support. Section . summarizes the lessons learned.

. S  S: A E- M  E G

.................................................................................................................................. To organize the discussion we use a model of export-led growth adapted with some modifications from Storm and Naastepad (, ), Naastepad (), and Blecker () and which captures both the central mechanisms of demand-led growth and the critical (supply-side) constraints on the process of late industrialization. The model has been specified in aggregate (one-sector) terms to highlight the macroeconomic mechanisms at work in a typical late industrializing, export-led economy which is open to trade and cross-border financial flows. Implicitly we assume that the economy has a Lewisian ‘labour surplus’ consisting of underemployed workers in agriculture and other primary industries; real wages in the model reflect the cost of subsistence and are socially determined. The model is expressed in growth rates and defines a stable medium-run growth path in which the late industrializing economy settles for a period of time, given a certain set of exogenous structural demand and productivity conditions (Blecker, ). For convenience, all variables are measured in instantaneous rate-of-change form (or differences in natural logarithms). Table . provides empirically grounded estimates of the model parameters, which can be read as ‘stylized facts’ describing the economic structure of our typical late industrializing economy.

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

 

Table 17.1 Late industrializing economies: stylized facts and parameter values Structural parameter

Meaning

Source

α ¼ 0:75 χ ¼ 0:25 η ¼ 0:28 ξ ¼ 0:10

Share in GDP of autonomous demand Shares in GDP of exports of goods and services (1990‒2018) Shares in GDP of imports of goods and services (1990‒2018) The impact of a one percentage point increase in real wage growth on domestic demand growth World income elasticity of export demand Income elasticity of import demand

* A A B

Relative price elasticity of export demand Relative price elasticity of import demand ’ ¼ F =ðPX þ F Þ = ratio of financial inflows to foreign exchange earnings Marshall‒Lerner condition: ð1  ’Þρ þ δ  1  0 Share of unit labour cost in output price Kaldor‒Verdoorn coefficient 1 Ω¼ ¼ 0:73 1 þ ημ þ ðξ  βγðχρ þ ηδÞÞ dyE dlE ¼ 0:04; ¼ 1 dw dz0 Growth rate of world income (1990‒2018) Growth rate of autonomous demand Exogenous (‘technology-push’) labour productivity growth yE ¼ yB ¼ 2:15; zE ¼ 1:85; lE ¼ 0:30; wB ¼ 0:30

C D *

ε ¼ 1:20 μ ¼ 1:40 ε μ ¼ 0:86 ρ ¼ 0:54 δ ¼ 0:52 ’ ¼ 0:10 γ ¼ 0:55 β ¼ 0:40 Ω ¼ 0:73

g ¼ 2:75 a ¼ 2:75 z0 ¼ 1:00 Equilibrium outcomes

C D

E F

A * *

Sources: (A) average for the period 1990‒2018 for low- and middle-income countries, World Development Indicators, World Bank; (B) Onaran and Galanis (2014); (C) Senhadji and Montenegro (1998): median of long-run estimates for sixty-six countries (1969‒93); see also Bussière et al. (2016: table 2); (D) Senhadji (1997): median of long-run estimates for sixty-six countries (using data for 1969‒93); see also Bussière et al., (2016: table 3); (E) γ is defined in fn. 2; we assume that ν ¼ 0:35; see Table 17.4 below; (F) McCombie, Pugno, and Soro (2002); Storm and Naastepad (2005: tables 6 and 12); and (*) assumed.

Starting on the demand side, real GDP or output growth (y) is determined by the growth of aggregate demand, as in equation (): y ¼ αa þ χx  ηm þ ξðw  zÞ

α; χ; η; ξ > 0

ð1Þ

where a is the growth rate of (real) autonomous demand, x is the growth rate of (real) exports, m is the growth rate of (real) imports, w is (exogenous) real wage growth and z is labour productivity growth. Coefficients α; χ and η are the shares in GDP of autonomous demand, exports, and imports, respectively (Table .). If real wage growth exceeds labour productivity growth (w – z) > , the country’s wage share in GDP is growing. We assume in eq. () that wage share growth contributes to faster growth of

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-,  ,   



domestic demand. This reflects the fact that, at low average levels of income, higher real wage growth raises consumption growth strongly—and even if it does depress investment growth, this negative effect is assumed to be more than offset by the faster growth of consumption demand (see Table .). Autonomous demand growth a is exogenous. Export growth (x) is endogenous: x ¼ εg þ ρ ðe þ pW  pÞ ε; ρ > 0 ;

ð2Þ

where ε is the world income elasticity of export demand, g is the growth of rest-of-theworld income, ρ is the price elasticity of export demand, e >  is the rate of nominal exchange rate depreciation (with the nominal exchange rate measured in home currency per unit of foreign currency), and pW and p are the rates of change in the foreign and home price levels, respectively. Note that the expression ðe þ pW  pÞ represents the rate of real depreciation of the home currency. Foreign price inflation is taken as being exogenous (here we are invoking the small-country assumption). Home price inflation p is a function of the growth in unit labour cost (w – z), the growth of unit intermediate input cost h and the growth of the profit mark-up factor π: p ¼ π þ γðw  zÞ þ h.² We refrain from explicitly incorporating changes in markups here and assume that π ¼ 0; and since the focus is on unit labour cost, we further simplify by assuming that h ¼ 0. Under these assumptions, eq. () can be rewritten as:   ð2#Þ x ¼ εg þ ρ e þ pW  γðw  zÞ Import growth m is determined by growth of output y and the rate of increase in the relative price of foreign goods ðe þ pW  pÞ :   ð3Þ μ; δ > 0 : m ¼ μy  δðe þ pW  pÞ ¼ μy  δ e þ pW  γðw  zÞ Coefficients μ and δ are the income elasticity and the price elasticity of import demand, respectively. Assuming that π ¼ 0 and h ¼ 0, substituting (#) and () into (), and rearranging, gives the following expression for demand-determined output growth y:   1 ð4Þ y¼  ½αa þ χεg þ ðχρ þ ηδÞðe þ pW Þ þ γ ξ  ðχρ þ ηδÞ ðw  zÞ 1 þ ημ Demand-driven growth increases when there is an increase in autonomous demand growth (a) and world income growth (g) and when the currency loses value in nominal terms. The sign of the impact of higher real wage growth and faster labour

² This equation can be derived as follows. First, assume that the price level P=W̿ Z + H, where Π= + the profit mark-up, W̿ = the nominal wage, Z = the level of labour productivity, and H = intermediate input cost per unit of output. Expressed in instantaneous rate-of-change form (differences in natural logarithms), we get this equation for home price inflation: p=π+ν w̿ -z+-ν h. ν = W̿ Z – P or the ratio of unit labour cost, the profit mark-up factor and the price level. Nominal wage growth w̿ is defined as w̿ = w+p; substituting this into the equation for home price inflation and rearranging, we obtain: p=π+γ w– z+h, where γ =  – ν.

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

 

productivity growth can be positive or negative. To see this, consider the derivative of y with respect to w: dy 1 ¼  ½ξ  γðχρ þ ηδÞ dw 1 þ ημ

ð5Þ

dy is negative or ξ < γðχρ þ ηδÞ, that is, the increase in I assume that the sign of dw domestic demand growth due to an increase in real wage growth is smaller than (the absolute value of) the decline in net export growth due to higher wage growth (see Table .). It is in this sense that the late industrializing economy is ‘export led’: lower wage growth does hurt the domestic market, but this damage is more than offset by its positive impact on net export growth. Given eq. (), the impact of higher productivity growth on output growth must be positive:

dy 1 ¼  ½ξ  γðχρ þ ηδÞ > 0 dz 1 þ ημ

ð6Þ

Given that equation () describes demand-determined output growth, what about the supply side of this economic system where productivity growth is being determined? The supply side is given by the Kaldor‒Verdoorn relationship, according to which labour productivity growth (z) is a positive function of output growth: z ¼ z0 þ βy

z0 > 0; 0 < β < 1 ;

ð7Þ

where z₀ is exogenous productivity growth due to technology policies (such as R&D subsidies and public investment in basic research) and β is the Kaldor‒Verdoorn coefficient (which reflects dynamic increasing returns to scale; see Storm and Naastepad, , ). We assume that 0 0, da ¼ βαΩ > 0, and da ¼ ð1  βÞαΩ > 0. The same is true for a rise in g and a nominal currency depreciation. In contrast, higher real wage growth is not good for ‘export-led’ growth: dyE ¼ Ω½ξ  γðχρ þ ηδÞ < 0: dw

ð11Þ

This drop in equilibrium output growth in turn depresses both labour productivity dyE dyE dlE E growth (since dz dw ¼ β dw < 0) and employment growth (because dw ¼ ð1  βÞ dw < 0). Let us finally consider the macro effects of industrial policy, which succeed in bringing about an increase in productivity growth (i.e. Δz0 > 0), and hence contribute to faster net export and output growth: dyE ¼ Ω½ξ  γðχρ þ ηδÞ > 0 dz0

ð12Þ

Clearly, productivity growth must go up as well: dz dyE ¼1þβ >0 dz0 dz0

ð13Þ

These growth impacts of industrial policy are illustrated in Figure .. The curve for demand growth shifts up (in line with eq. ()) and the curve for productivity growth shifts down (as per eq. ()). The new growth path features higher output growth as

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

  y.ι productivity growth yE1

demand growth

yE0

ι0 employment growth

ι1 0

zE0

zE1

z

 . Successful industrial policy raises equilibrium output growth and productivity growth but reduces employment growth Source: Constructed by author.

well as faster productivity growth. However, the sign of the industrial policy impact on employment growth is ambiguous, because: dlE dyE ¼ ð1  βÞ  1⋛0 dz0 dz0

ð14Þ

Equilibrium employment growth could, in principle, increase if output growth rises dlE more in response to industrial policy than productivity growth. Formally, dz > 0 if 0 dyE 1 > and this could happen only if (i) the price elasticities of exports (ρ) and 1β dz0 imports (η) are large; (ii) unit labour cost makes up a sizeable part of the price (i.e. γ is large); and (iii) the shares of exports (χ) and imports (η) in GDP are large. Late industrializing economies do not generally meet these conditions (see Table .), dlE < 0 (as in Figure .). Therefore, industrial policymakers face however, and hence, dz 0 an unpleasant trade-off: raising productivity growth increases output growth, but slows down job growth. Storm and Naastepad (), Pieper (), Roncolato and Kucera (), and Junankar () provide empirical evidence on the ‘productivity growth– employment growth’ for late industrializing countries.⁵ Figure . illustrates the tradeoff using historical evidence for a sample of twenty-four industrializing countries. Only a few East Asian countries managed to escape the trade-off, but in other Asian and Latin American developing economies a step up in z has meant a decline in lE. Macro-policy can be used to overcome this ‘nasty’ trade-off. For example, a nominal currency depreciation Δe > 0 will raise output growth (assuming it can be maintained for some time), as (from eq. ()) we know that dydeE ¼ Ωðχρ þ ηδÞ > 0. This means that ⁵ Long-run econometric estimates by Storm and Naastepad () and Junankar () for a panel of low- and middle-income countries indicate that dlE/dz₀  –. We obtain the same elasticity value here, using the stylized facts in Table ..

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-,  ,   



6 Taiwan Thailand

4

Turkey

Sri Lanka

2

China Vietnam Myan

Argentina

0

South Korea

Singapore

Malaysia Pakistan Indonesia Brazil I Mexico Ecuador Guatemala Colombia

Bangladesh

Philippines Venezuela

–2 1

2

3

4

5

Employment growth (average annual growth rate in %)

 . Trade-off between labour productivity growth and employment growth in twentyfour late industrializing countries, ‒ Notes: () Employment is defined as the number of persons in civilian employment; () labour productivity is GDP (at constant prices) per person employed; () labour productivity and employment growth rates for India, Indonesia, Malaysia, Myanmar, Pakistan, Singapore, Korea, Sri Lanka, Taiwan, Thailand, and Vietnam are for ‒; the figures for China are for ‒; and () the statistically significant regression line was estimated for eighteen countries, i.e. excluding China, Malaysia, Singapore, Korea, Taiwan, and Thailand. Source: Storm and Naastepad ().

the demand-growth curve in Figure . shifts up even further. Note that exchange rate depreciation will also shift the productivity-growth curve to the right. However, because 0 < β < 1, productivity growth rises less strongly than output growth—and employment growth must increase. This can be seen directly by taking the derivative of employment growth with respect to e: dlE ¼ ð1  βÞΩðχρ þ ηδÞ > 0 de

ð15Þ

It is in this context that capital account regulations (CARs), especially restraints on financial outflows, become a critical tool for economic development (Frenkel and Taylor, ; Guzman et al., ). First, CARs can block a currency appreciation in a country with a persistent current account surplus and help maintain a competitive exchange rate. Maintaining a competitive exchange rate allows developing countries to open up new lines of (technologically more sophisticated) exports (Freund and Pierola, ; Cimoli et al., ). Second, CARs can favour foreign direct investment and discriminate against volatile short-term (portfolio) flows. Finally, CARs increase monetary policy autonomy by partly curtailing the interest-rate and exchange-rate effects of (a reversal of) financial flows. Eq. () suggests that there are good grounds for combining an industrial policy push by the state with supportive measures by a development-oriented central bank which allow the currency to depreciate as part of its macro-management of the capital account of the BoP. With CARs in place, monetary authorities can lower the interest

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

 

rate, which would weaken the currency by encouraging a financial outflow out of the country. As an added benefit, the lowered interest rate will encourage an increase in business investment; in our model, this shows up as an increase in autonomous demand growth. Higher a increases output growth more than productivity growth, contributing to faster employment growth: dlE ¼ ð1  βÞΩα > 0 da

ð16Þ

Alternatively, to prop up employment growth the state could step up public investment—which again would imply an increase in a. This way, supportive macroeconomic policy helps to buttress and reinforce the industrial policy initiative. However, if this is true, the reverse can occur as well: the wrong kind of macro policies, including a sustained currency appreciation,⁶ an unsupportive increase in interest rates (Frenkel and Taylor, ), and/or wrongly timed fiscal austerity (Neto and Porcile, ), can (partly or completely) erode the potential cumulative growth impacts of industrial policymaking.

.. Enter the Balance-of-Payments Constraint Successful industrial policy, when combined with supportive macroeconomic policies, raises the equilibrium growth rates of output and productivity, while maintaining job growth. But such a growth acceleration could be inconsistent with the long-run requirements of BoP equilibrium, if the growth of necessary imports (of food, capital goods, and technology) exceeds the growth of exports and of financial inflows (Thirlwall, , ). The industrial policy-induced virtuous cycle of faster technological progress, rising investment and exports, and higher output growth may not last, because the country is unable to finance its growing imports through either export growth or higher financial inflows (McCombie and Thirlwall, ). Following Blecker (), the long-run BoP equilibrium condition can be written as follows: ð1  ’Þðx þ pÞ þ ’f ¼ e þ pW þ m

ð17Þ

where f is the growth rate of financial inflows F (measured in domestic currency) and F ’ ¼ PXþF is financial inflows as a ratio of total ‘receipts’ in the BoP. We assume that F > . Substituting equations (#), (), and () into () gives, after rearranging, the following general solution for the BoP-constrained growth rate: yB ¼

ð1  ’Þεg þ ’f þ ½ð1  ’Þρ þ δ  1ðe þ pW  γðw þ z0 ÞÞ μ  βγ½ð1  ’Þρ þ δ  1 þ ’

ð18Þ

⁶ Elbadawi et al. () provide evidence that currency overvaluations had a negative impact on export diversification for eighty-three sub-Saharan countries (‒).

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-,  ,   



We assume that the denominator of () is positive, which appears empirically plausible, because 0 < β < 1, 0 < γ < 1 (see Table . below) and the extended Marshall‒Lerner condition with financial flows ð1  ’Þρ þ δ  1 > 0 is unlikely to hold, because the price elasticities ρ and δ are in general low for late industrializing countries (Table .). The expression ðe þ pW  γðw þ z0 ÞÞ gives the effect on BoP-constrained growth of an improvement in the country’s terms of trade. Note that if relative purchasing power parity holds, then ðe þ pW  γðw þ z0 ÞÞ =  and the expression drops out of eq. ().⁷ While this may be the case in the long run, it is true that termsof-trade improvements can raise the BoP-constrained growth for some time, as illustrated by the commodity-price booms in Africa (Bagnai et al., ) and Latin America (Ocampo, ) in the s. But such terms-of-trade effects have always been transitory (e.g. Nureldin Hussain, ). Let us simplify () by accepting ‘price elasticity pessimism’ as a stylized fact of late industrializing nations (Blecker, ). That is, we assume that the extended Marshall‒Lerner condition is not satisfied⁸ and that changes in the international terms of trade have no impact on the trade balance: ð1  ’Þρ þ δ  1 ¼ 0. This simplifies eq. () to: yB ¼

ð1  ’Þεg þ ’f μ  β’

ð19Þ

The BoP-constrained growth rate yB increases if world income growth (g) increases and also following an increase in the growth rate of financial inflows f; in both cases, the BoP constraint is relaxed and the country can have higher imports which in turn allows for faster growth. Note that a permanent increase in f is implausible in the long run, particularly if the growing financial inflows come in the form of foreign debt and increase faster than nominal GDP. In this case, the late industrializing country runs the risk of an unmanageable rise in its foreign indebtedness. Hence if we set f =  and further assume that ’ ¼ 0 (which means trade must be balanced in the long run), then eq. () becomes: ε ð20Þ yB ¼  g μ Eq. () is known as Thirlwall’s Law and it highlights the structural (long-run) determinants of a nation’s BoP-constrained growth rate (Thirlwall, , ): the growth rate of world income (g) and the ratio of the world income elasticity of export demand (ε) and the country’s income elasticity of import demand (μ). This ratio of income elasticities depends on the degree of diversification of the production structure of this economy as well as on the technological and knowledge intensity of its pattern of (export) specialization. In general, as is shown by the data

⁷ The econometric evidence on long-run relative purchasing power parity is inconclusive, and is sensitive to the currencies, price indices, time periodization, and econometric methods used (Blecker, ). ⁸ For empirical evidence, see Rose () and Bahmani et al. ().

World income elasticity of export demand ε: Primary products Argentina 0.66 Brazil 0.62 Chile 1.05 Mexico 0.77 South 0.98 Korea Malaysia 0.77 Philippines 0.76 High-income OECD countries Low-income countries Lower middle-income countries —China —India Upper middle-income countries

Resource-based manufactures

Low-technology manufactures

Medium-technology manufactures

High-technology manufactures

Weighted aggregate ε

μ

0.69 0.87 1.10 1.12 1.25

0.79 1.74 1.51 2.26 2.61

0.82 2.23 2.26 2.83 1.94

0.93 4.14 3.85 6.91 8.07

0.84 1.10 0.81 1.67 1.83

1.24 1.18 1.23 1.28 1.17

0.76 0.74

8.47 2.85

12.22 4.81

4.54 10.07

1.38 1.32 1.61 1.00 1.20 1.55 1.42 1.28

1.22 1.21 1.22 1.21 1.20 1.15 1.14 1.21

Sources: The commodity-wise estimates for Argentina, Brazil, Chile, and Mexico (using data for 1962‒2014) are from Neto and Porcile (2017); the commodity-wise estimates for South Korea, Malaysia, and the Philippines (using data for 1962‒2006) are from Gouvêa and Lima (2010); all weighted averages for (ε) and (μ) are from Gouvêa and Lima (2013) and based on data for 1965‒99.

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Table 17.2 Income elasticity of exports (ε) and imports (μ): selected late industrializing countries, 1962‒2006/2014

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-,  ,   



collected in Table ., ε takes a low value for primary and resource-based products and much higher values for medium- and high-tech manufactures. The more technology intensive the export commodity, the higher is its world income elasticity of demand (Gouvêa and Lima, , ; Bottega and Romero, ). Accordingly, the more developed, differentiated, and sophisticated the technological capabilities of a country, the higher the income elasticity of export demand (ε) and hence the higher yB. ‘What you export matters’ is how Hausmann et al. () sum it all up. The policy message is plain: a country should reorient its exports as much as is possible to fastgrowing markets and plan for import substitution in those imports for which the income elasticity of demand is high (Thirlwall, ). For many late industrializing nations, the ratio ε=μ yB , the country is running a current account deficit in excess of what it can structurally finance in the long run; this outcome cannot be sustained and restoring (long-run) external balance requires that yE is forced down to yB. On the other hand, if yE < yB , the country’s current account deficit is below what long-run BoP equilibrium would permit and there is no need for a realignment of yE and yB. Figure . presents the export-led growth model (of Figure .) with the horizontal BoP constraint—assuming that long-run equilibrium implies: yE ¼ yB .

. ‘B P’ I

.................................................................................................................................. Below a critical minimum of investment, industrial production may fail to benefit from economies of scale and consequently private returns to individual manufacturing investment turn out to be low, even if the rates of return to coordinated industrial ⁹ The point is illustrated by comparing the world’s most successful industrializer China (ε/μ = . in Table .) and a less successful industrializer such as Brazil (ε/μ = .). For a given rate of growth of world income (of, say, . per cent), China’s yB will be . per cent compared to . per cent in Brazil.

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

 

investments would have been high. Industrialization therefore requires a ‘big push’: the coordination of complementary investments, in the presence of significant scale economies and capital market imperfections (Storm, ). ‘Big push’ models of (import-substitution) industrialization in BoP-constrained developing countries were proposed by Rosenstein-Rodan (), Mandelbaum (), Singer (), Nurkse (), and Prebisch (). What was assumed in these models is that the demand side of the economy would, more or less passively, support the industrialization process. Likewise, it was held that national growth projects could remain unperturbed by global capital markets. The failure of Latin American import-substitution industrialization (Bertola and Ocampo, ) and the running out of steam of India’s Nehru‒ Mahalanobis industrialization strategy in the s (Chakravarty, ) are proof that both assumptions were wrong. Let us assume that the late industrializing economy raises public investment as part of a ‘big push’ strategy. In the model, this is captured by an increase in a. Its consequences for the equilibrium growth path of the late industrializing nation are illustrated in Figure .. An increase in a raises output growth from yE₀ to yE1 > yB . Productivity growth accelerates as well (from zE₀ to zE₁), while employment growth declines from lE₀ to lE₁, but remains positive. The supply-driven ‘big push’ strategy appears to be working well. Let us further suppose that the industrialization programme is not export oriented; indeed, as Ocampo () argues, state-led industrialization in Latin America during ‒ was characterized by a significant anti-export bias. We also assume that the programme is not successful in reducing the nation’s dependency on (medium- and high-tech) imports. Taken together, this means that the BoP-constrained growth rate yB remains unaffected by the ‘big push’, because ε and μ remain unchanged. The industrialization process thus runs into the BoP constraint: the output growth ( y) employment growth (l) productivity growth demand growth yE = yB BoP-constrained growth

ιE employment growth 0

zE

labour productivity growth (z)

 . An export-led growth model with cumulative causation and a balance-ofpayments constraint Source: Constructed by author.

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-,  ,   



growth acceleration cannot be sustained, because the country’s current account deficit and external debt are continuously rising relative to GDP. How are demand-led growth and BoP-constrained growth reconciled? East Asian late industrializers succeeded in taking the high road, raising yB to yE₁. They achieved this by aggressively encouraging investment in the desired export-oriented and importsubstitution activities by every available means, including the offer of tax concessions, subsidies, temporary and conditional trade protection, cheap credit, and considerable informal pressure (Wade, ; Akyüz et al., ; Amsden, ; Storm and Naastepad, ). Scitovsky () appositely characterized East Asia’s investment regime as a ‘forced investment’ one. But East Asia’s late industrializers are the successful exceptions (Cherif and Hasanov, ). Most other late industrializing countries went down the ‘low road’, as yE₁ was ‘forced’ down to equal yB. This happened in three distinct ways.

.. The ‘Wage-Goods Inflation’ Barrier: A Ricardian–Kaleckian Mechanism ‘Everyone knows,’ wrote Ragnar Nurkse (: –), ‘that the spectacular industrial revolution [in England] would not have been possible without the agricultural revolution that preceded it.’ Arthur Lewis (: ) concurred: Now if the capitalist sector produces no food, its expansion increases the demand for food, raises the price of food in terms of capitalist products, and so reduces profits. This is one of the senses in which industrialisation is dependent upon agricultural improvement; it is not profitable to produce a growing volume of manufactures unless agricultural production is growing simultaneously. This is also why industrial and agrarian revolutions always go together and why economies in which agriculture is stagnant do not show industrial development.

As shown by the experiences of South Korea, Taiwan, and China, rapid industrialization requires parallel or prior increases in agricultural productivity and food production to avoid the danger of running into the Ricardian trap (Saith, ; Storm, ). In our BoP-constrained economy (Figure .), the ‘big push’-induced acceleration of output growth raises the demand of the industrial sectors for intermediate inputs and wage goods (food and other subsistence goods) produced by the domestic agricultural sector. Domestic agriculture may be unable to increase the growth rate of wage-goods supply, even in the presence of a Lewisian reserve of underemployed workers, because the growth of agricultural productivity and output is constrained by technical as well as institutional factors (notably a highly unequal distribution of land ownership, the small size of average land holdings, and exploitative and insecure tenancy systems)—and therefore the growth of wage-goods supply is relatively price inelastic even in the longer run (Karshenas, ; Kay, ; Storm, , ). Under these conditions, as argued by Kalecki (, ), faster (industrial) growth leads to a structural excess demand for wage goods and to wage-goods inflation—

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

  output growth (y) employment growth (l) productivity growth demand growth

yE1 yE0 = yB

BoP-constrained growth

lE0 lE1

employment growth

0

zE0

zE1

productivity growth (z)

 . Successful industrial policy raises equilibrium output growth above the BoPconstrained growth rate Source: Constructed by author.

which (in the presence of a BoP constraint) will drive up nominal and real wage growth (in manufacturing) and this, in turn, will raise the (industrial) wage share, lower the (industrial) profit share and thus erode private investment (Chakravarty, ). Attempts to finance industrial investment through a forced extraction of resources from a technologically stagnant and socially unequal agriculture would inevitably dissipate in inflationary spirals. Note that Kalecki’s diagnosis that wage-goods inflation arising from the (price) inelasticity of agricultural supply could lower aggregate demand and output growth is one of the earliest references in the literature to the phenomenon that came to be known as ‘stagflation’. In the model, the Ricardian– Kaleckian wage-goods inflation mechanism would work through an increase in real wage growth w, which lowers yE (per eq. ()) and shifts the demand-growth curve in Figure . down.¹⁰ It is possible, by combining the expression for yB given by eq. () and eq. () for yE, to determine the ‘BoP-constrained growth rate for real wages’: wB ¼

ð1  μΩχÞεg αa þ ðχρ þ ηδÞðe þ pW Þ  þ z0   μΩðξ  γðχρ þ ηδÞÞ ξ  γðχρ þ ηδÞ

ð21Þ

wB is the growth rate of real wages which ensures long-run balance between yE and yB. B Noting that ½ξ  γðχρ þ ηδÞ 0, which means that ̿ ¹⁰ This can be justified as follows. The real wage is w =W̿ /P; we can write: w = ðPWF Þ  ðPPF Þ, where W̿ PF = the price of wage goods (food). The term ðPF Þ ¼ wF is the ‘product wage’, or the nominal wage deflated by the price of wage goods (Chakravarty, ). If wF is socially determined and fixed and if food prices rise faster than the general price level P, then w must increase. This is the mechanism underlying eq. ().

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-,  ,   



BoP-constrained real wage growth is forced up by the wage-goods inflation, which in turn depresses domestic demand for manufactures and thus stifles industrial growth. This particular mechanism was at work in large, populous, and foreign-exchangeconstrained countries such as Brazil in the s and s (Taylor and Bacha, ; Kay, ) and India in the s and s (Chakravarty, ; Storm, , ), when domestic demand for manufactures was eroded by wage-goods inflation caused by the fact that under-prioritized agriculture was unable to produce enough food and raw materials for the growing industrial workforce and expanding manufacturing sector.¹¹

.. A Drop in Domestic Expenditure Growth: A Robinsonian Mechanism A second mechanism realigning yE with (unchanged) yB has been suggested by Porcile and Yajima (), who following Robinson () propose that the growth of privatesector (investment) demand will go down. Robinson argued that a growing external deficit is likely to depress the ‘animal spirits’ of the capitalist class, and therefore private investment, because it signals a growing risk of a BoP crisis, a depreciation of the currency, a rising foreign debt burden and/or a sudden stop in foreign credit: The most important benefit of a surplus on income account [of the BoP], which affects the whole economy, is that, provided there are energetic enterprises and thrifty capitalists to take advantage of it, it permits home investments to go full steam, while a deficit country is nervously pulling on the brake for fear of excessive imports. (Robinson, : ‒)

This fall in private investment, so Robinson adds, slows down technical progress and hurts the country’s competitive position, tightening the BoP constraint even further. If there is a currency depreciation, this could hurt firm profits (assuming that firms cannot completely protect their profit mark-ups and pass higher import costs on to prices)—and private investment would go down. In the present model, autonomous expenditure growth a would fall, which shifts the demand-growth curve down to where it was before the public investment drive. In this adjustment process, higher public investment ‘crowds out’ private investment, not through higher interest rates, but rather through depressed ‘animal spirits’ of private firms and/or through a manufacturing profit squeeze.

¹¹ Note that in Latin America, Africa, and India, the resulting more unequal distribution of rural incomes restricted the growth of the domestic market, contributed to a distorted industrial structure and (via imports of consumer goods) contributed to chronic BoP problems (Kay, ; Karshenas, ; Chakravarty, ).

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

 

.. Forced Savings, Restrictive Monetary Policy, and Destabilizing Austerity: Three Keynesian Mechanisms In terms of macroeconomic accounting, a structural current account deficit reflects the fact that the country is unable to increase domestic savings to the same level as the expanded domestic (public + private) investment—and hence the country has to rely on foreign savings (a net financial inflow) to finance its capital accumulation. For most late industrializing countries, access to global capital markets is restricted and it is in this context of a shortage of foreign exchange that early development models—including the Harrod‒Domar model, the Lewis model and the Mahalanobis model—emphasized the importance of mobilizing domestic savings to finance capital formation growth. A failure to do so can, in a foreign-exchange-starved economy, lead to a process of forced savings (Storm, ), as the excess of demand allows firms to raise the profit mark-up factor (π > ), which then leads to home price inflation and a redistribution of income in favour of profit recipients (who have a higher propensity to save than wage earners). The higher profit share contributes to rising inequality in household incomes and higher savings, which reduces domestic demand and, by limiting the size of the home market, puts a brake on industrial investment, output, and productivity growth, as argued by Kalecki (, ) and Taylor and Bacha (). Lack of domestic demand slows down industrialization, forcing yE down to yB. This drag on growth can be avoided for as long as the current account deficit can be financed by foreign funds—but foreign indebtedness will rise and the external imbalance will have to be rectified at some point. Exchange rate devaluations will generally not be effective at doing this (Bahmani et al., ). The only way to reduce the external imbalance is by import compression—but to achieve this, demand must be depressed. Fiscal austerity is one way to depress demand, and it was part and parcel of the World Bank/IMF structural adjustment programmes adopted by, and imposed on, debtridden industrializing countries in Latin America and sub-Saharan Africa in the s and s. In our model, fiscal austerity means a decline in variable a, which by depressing growth and imports restores BoP equilibrium. The demand-growth curve shifts down again to where it was before the public investment drive (Figure .). In Latin America, the cure of fiscal austerity and pro-market reforms proved to be worse than the disease. As large exchange-rate devaluations were not effective in reducing current account deficits, Latin American governments imposed drastic cuts in public expenditure (mostly in public investment) and raised taxes in order to continue servicing their high external debts (Bertola and Ocampo, ). Private investment predictably suffered—and economic growth stagnated, industrial diversification and upgrading got stalled, and Latin American economies became more strongly dependent on the export of a few (primary) commodities. As Neto and Porcile (: ) write, ‘a fall in public investment reinforces backwardness in technology, infrastructure and productivity, which heightens the external deficit and disequilibrium’. Austerity reinforced Latin America’s comparative advantage in natural resource- and labour-

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-,  ,   



abundant sectors, led to a re-commodification of their production and export structures (Ocampo, ), and resulted in considerable de-industrialization (Diao et al., ). Persistent current account deficits will also alarm monetary policy authorities, who will raise interest rates in an attempt to mop up additional domestic savings and/or attract (or keep attracting) foreign finance. If successful, the central bank’s restrictive monetary policy raises domestic savings (thereby lowering consumption) and depresses (or ‘crowds out’) private investment—and as a result, domestic demand and import demand are forced down; this will also realign yE with yB. These mechanisms are called ‘Keynesian’ because they all constitute a failure to manage aggregate demand in ways supportive of the big push industrialization process.

. V   L  E I S

..................................................................................................................................

The challenge for late industrializing countries is to escape from the primarycommodity specialization trap in which they find themselves (Ocampo, ; Cherif and Hasanov, ). The question is how to defy comparative advantage, and how far from comparative advantage the state should push. To illustrate, South Korea’s development path after  would have been radically different if it had followed the policy advice it was given at the time to continue focusing on what were then its main exports (rice, raw silk and wolfram), instead of embarking on developing shipbuilding, electronics and automotive industries (Cherif and Hasanov, ). In principle, a commodity-price boom could provide the launch pad for an industrialization drive and a structural transformation of the economy. Exactly such an opportunity for industrialization was created during ‒ as the windfall export gains (caused by a global commodity-price boom) and a (China-led) surge in natural resource-seeking foreign direct investment revived economic growth in Africa and Latin America (Ocampo, ). This commodity boom turned African economies into the fastest growing on the planet (Bagnai et al., ) and this, for some time, led to much optimism about prospects for accelerated industrialization based on commodities. But overall, sub-Saharan African and Latin American countries have been unable to fully capture the benefits from commodity booms. Industrialization based on commodities is not at all easy—mostly because macroeconomic imbalances can throw the growth process off the rails.¹²

¹² Cycles in commodity prices introduce (enhanced) cyclicality in fiscal revenues (because government revenue is heavily dependent on taxation of natural resource-intensive industries) and in business investment (which tends to increase as commodity prices go up). Short-run stabilization emergencies (for instance in response to a sudden collapse of commodity prices) may seriously conflict with a longrun policy focus on industrialization and structural change (Ocampo et al., ).

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

 

.. The ‘Dutch Disease’ Let us explore the macroeconomic consequences of a prolonged commodity-price boom in terms of the growth model of Figure ., by assuming that the growth rate of world prices pW increases. The higher export earnings constitute a windfall gain, and assuming (for the moment) that these are not invested in projects intended to diversify and upgrade the country’s production and export structures, yB stays the same. Note further that a higher pW does not affect the long-run BoP-constrained growth rate yB, because we assume ð1  ’Þρ þ δ  1 ¼ 0. However, the commodity-price boom drives up equilibrium output growth, since: dyE ¼ Ωðχρ þ ηδÞ > 0 dpW

ð22Þ

and as a result, the demand-growth curve shifts up as is illustrated in Figure .. The labour productivity growth does not shift, but through the Kaldor‒Verdoorn mechanism, productivity rises (along the curve) from zE₀ to zE₁. Employment growth increases as well (from lE₀ to lE₁), because output growth increases more than productivity growth (since 0 < β < 1). The commodity-price hike thus triggers a process of cumulative growth. Before proceeding, we should note that while the late industrializing nation is enjoying a surplus in its current account due to the increase in export earnings, the step-up in its economic growth has raised the growth rate of the country’s imports; the growth rate of real exports has remained unchanged. Accordingly, in real terms, the country is running a larger current account deficit than is allowed by the BoP constraint (eq. ()). Hence, notwithstanding the fact that the country is enjoying a temporary current account surplus (in nominal terms), it is running a trade deficit in output growth (y) employment growth (l) productivity growth demand growth

yE1 yE0 = yB

BoP-constrained growth

lE1 lE0 employment growth 0

zE0

zE1

productivity growth (z)

 . The macroeconomic impacts of a commodity-price boom Source: Constructed by author.

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-,  ,   



real terms—which it is able to finance using the higher export earnings only for as long as the commodity-price boom endures. But the new equilibrium growth path is unlikely to last, if the monetary authority fails to maintain a ‘competitive’ exchange rate. Global demand for the country’s currency increases as a consequence of the export commodity-price boom, and the nominal exchange rate will appreciate Δe < 0. A ‘non-competitive’ exchange rate may strangle the development of the tradable manufacturing industries. The currency appreciation realigns equilibrium growth yE with yB as in Figure .. The currency appreciation (a fall in e) shifts the demand-growth curve downward, as dyE de ¼ Ωðχρ þ ηδÞ > 0, and the resource-rich country remains locked into the commodity-specialization trap. The mechanism is known as the ‘Dutch disease’,¹³ and is one manifestation of a larger pathology summarized under the heading of ‘natural-resource curse’: countries with abundant natural resources tend to have lower and more unstable economic growth than countries with fewer natural resources (Venables, ; Ocampo, ). A big part of the reason for this is that coping with massive fluctuations in export earnings (or with huge inflows of foreign finance) is challenging for any government.¹⁴ An escape from this trap is possible only when the country succeeds in diversifying and upgrading its production and export structures. For Hans Singer () and Raúl Prebisch () it was clear that this required strict and careful management of the BoP in the context of a long-run strategy of importsubstitution industrialization.

.. Escaping the Primary-Commodity Specialization Trap Economic growth yE in our late industrializing economy can only be increased in a lasting way if the country succeeds in simultaneously raising its BoP-constrained growth rate yB. The BoP-constrained growth rate is a reflection of the developing economy’s (initial) position in the international division of labour, specializing in natural resources and agricultural exports and importing mostly medium- and hightech manufactured goods. But a country’s pattern of specialization is not given—to paraphrase the famous dictum of Joan Robinson—by God and factor endowments¹⁵ (Porcile and Sartorello Spinola, ), but can be changed and improved by deliberate, state-guided strategies to change the structure of production towards activities with ¹³ The term was coined in  by The Economist to describe the decline in manufacturing in the Netherlands after the country had become a big natural gas producer and exporter in the s. ¹⁴ Part may be due to weak governance, which has, in some cases, created space for patronage politics and domestic conflicts. See Venables (). ¹⁵ In , only three South Korean export industries within the ‘machinery and transport equipment’ category (at the SITC -digit level) had a revealed comparative advantage index greater than one, singling them out as promising sectors for future development. But by , all three had disappeared as export industries, while Korea’s top exporting industries in  did not even exist in  (Cherif and Hasanov, ).

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

 

higher productivity—which means productively absorbing existing new technologies, catching up with the technological leading countries (as described most clearly by Gerschenkron, ), mobilizing resources and guiding investment to more sophisticated industries (Wade, ), prioritizing credit to targeted industries (with the strongest linkages and spillovers), enforcing export orientation, maintaining a ‘competitive’ exchange rate (Guzman et al., ) and managing the BoP, and learning how to manufacture by just doing it and keeping on doing it (as described most powerfully by Amsden, ). To capture the power of a developmental state to (gradually but critically) improve the pattern of specialization of the economy, we modify our growth model following Cimoli and Porcile (), assuming that: ε 0 ð23Þ ¼ f ðaÞ; f > 0 μ Equation () defines progressive structural change in the economy, away from natural resources-based activities and towards manufacturing, as a function of missionoriented public investment in infrastructure and more risky, innovation-related activities (Mazzucato, ; Neto and Porcile, ) and state-guided private investment (Wade, ; Amsden, ), which are both elements of autonomous demand growth a. A successfully coordinated public and private investment drive will diversify the production system, reducing the country’s import dependence (which lowers μ), while raising the share in exports of more technology-intensive manufacturing goods (which raises ε). A higher ratio ε=μ raises the country’s yB in eq. (). The relaxation of the BoP constraint next allows the late industrializing country to step up its demanddetermined rate of growth. This is illustrated in Figure .. Initially, the economy grows at yE0 ¼ yB0 . The state then initiates a big public investment programme and imposes effective industrial policy guidance on business investment—both elements of this industrialization strategy lead output growth (y) employment growth (l) productivity growth

yE1= yB1

demand growth

yE0 = yB0 BoP-constrained growth

lE1 lE0 employment growth 0

zE0 zE1

z

 . Escaping the primary-commodity specialization trap Source: Constructed by author.

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-,  ,   



to successful diversification and upgrading of national production and export structures. In Figure ., higher public investment (higher a) pushes up the demand-growth curve. But this time (and after a while), the industrial policy thrust raises ε=μ and yB shifts up as well. The economy can now settle in a new, higher-growth equilibrium yE1 ¼ yB1 , which will be determined by how much industrial policy manages to raise ε=μ. Equilibrium productivity growth rises along the productivity-growth curve from zE₀ to zE₁ in line with Kaldor–Verdoorn relation (in eq. ()). Figure . further shows that employment growth is higher in the novel growth equilibrium. A final point to note is that the structural relaxation of the BoP constraint lowers the BoP-constrained growth rate of real wages wB. To see this, we differentiate wB in eq. () with respect to the ratio of income elasticities of demand ε=μ and get: dwB ð1  μΩχÞg ε ¼ Ωðξ  γðχρ þ ηδÞÞ < 0 dð Þ μ

ð24Þ

which is negative because ½ξ  γðχρ þ ηδÞ < 0(see Table .). What eq. () tells us is that the structural loosening of the BoP constraint has lowered the pressure of wagegood inflation in the economy—the spectre of stagflation has been exorcized by successful industrial diversification and the system has more space for demand-led development. However, actual real wage growth can be higher than before, because equilibrium productivity growth has increased. Workers gain because employment growth and real wage growth will rise.

. L L  I  I P

.................................................................................................................................. Successful late industrialization that steers clear of persistent external disequilibria and an unsustainable external debt, requires the pattern of specialization to be re-oriented towards more technology-intensive industries with higher income elasticities of demand for exports. The market mechanism is unlikely to bring about the growthenhancing structural change that is needed (Storm, ) and hence the ‘leading and guiding hand of the state’ (Amsden, ; Wade, ; Cherif and Hasanov, ) must design and use (selective) industrial policy instruments to target exports with growth potential and identify imports where there is potential for import substitution (Storm and Naastepad, ; Thirlwall, ). Crucially, late industrializing nations can complement their industrial policy by using labour regulation designed in such a way that it serves as a ‘beneficial constraint’, forcing firms to upgrade, diversify, and become more productive (Storm and Capaldo, ; Storm, ). This suggestion may appear outlandish: after all, how can the late industrializing economy benefit from labour laws and regulations, as these will just raise labour costs and prices, and therefore harm net exports, business profits, and firm investment?

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

 

It is true that not so long ago, it was received opinion that labour protections for ordinary workers were a ‘luxury developing countries cannot afford’, because ‘laws created to help workers often hurt them’, as the World Bank (: ) concluded. However, it is now clear that this ‘perversity thesis’, while remaining influential among ‘madmen in authority, hearing voices in the air’, is no longer empirically tenable. Metaanalyses of the empirical literature on labour regulation and economic performance by Nataraj et al. () and Broecke et al. () find that the effects of regulation on growth and employment are generally small or absent, and negligible compared to those on income distribution. The reason why the ‘perversity thesis’ is wrong is that it sees labour laws as exclusively driving up unit labour cost, while neglecting their considerable positive impacts on domestic demand, productivity growth, and diversification and upgrading (Storm and Capaldo, ; Storm, ).

.. Wages and Demand Higher real wage growth (in combination with stable and growing employment) raises consumption growth and expands the home market (Ocampo et al., ; Storm, ; UNIDO, ). However, if wage growth exceeds labour productivity growth, this raises unit labour cost and prices, which damages net exports and consequently business profits and investment. It follows that the macro impact of higher wage growth is the net outcome of faster domestic demand growth, captured in the model by the coefficient ξ in eq. (), and lower net export growth, reflected by the expression ½γðχρ þ ηδÞ in eq. () (Bhaduri and Marglin, ). So far we have assumed that ½ξ  γðχρ þ ηδÞ < 0, meaning that on balance, higher real wage growth does lower economic growth. While the negative sign is empirically plausible, we must recognize that the macro impact of higher real wage growth in most late industrializing nations is surprisingly small (in absolute terms) and should not be exaggerated. The point is illustrated by Table ., which presents internationally comparable econometric evidence on ξ and ½γ ðχρ þ ηδÞ for seven major late industrializing economies (Onaran and Galanis, ). First, it can be seen that a one percentage point increase in real wage growth raises domestic demand growth by . percentage points on average (ξ > ) for six countries (excluding South Africa). Second, a one percentage point increase in real wage growth reduces net export growth by ‒. percentage points on average (when we exclude the estimate for China).¹⁶ This limited sensitivity of net export growth to real wage growth is perhaps surprising but the reasons are not difficult to understand. To begin with, as illustrated by Table ., (nominal) unit labour costs (multiplied by the profit mark-up) make up only one-third of the price ¹⁶ China is the ‘outlier’ in Table .: its net export growth is found to decline by almost two percentage points in response to a one percentage point increase in real wage growth. But note that Onaran and Galanis () find much higher price elasticities of exports and imports for China than Bussière et al. () and Bottega and Romero ().

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-,  ,   



Table 17.3 Impact on economic growth of a one percentage point increase in real wage growth, selected late industrializing countries

Argentina China India Mexico South Africa South Korea Turkey

Change in domestic demand growth ξ

Change in net export growth γðχρ þ ηδÞ

Change in economic growth ½ξ  γðχρ þ ηδÞ

0.14 0.41 0.29 0.28 0.02 0.42 0.49

‒0.19 ‒1.99 ‒0.31 ‒0.38 ‒0.51 ‒0.36 ‒0.28

‒0.05 ‒1.57 ‒0.02 ‒0.10 ‒0.49 0.06 0.21

Source: Onaran and Galanis (2014). The estimation period is 1970‒2007 for all countries (but 1978‒2007 for China).

Table 17.4 Share of wages in the gross output price, selected regions and countries

Africa South Africa Latin America Brazil East Asia China South East Asia India

¼ 1

Labourincome share

Profit share

Share of intermediate inputs in gross output

ν ¼ ΠWP Z

ν γ ¼ 1ν

0.467 0.515

0.533 0.485

0.54* 0.54

0.28 0.30

0.39 0.44

0.495

0.505

0.51*

0.33

0.48

0.587 0.514 0.495 0.416

0.413 0.486 0.505 0.584

0.51 0.69* 0.69 0.51*

0.36 0.19 0.18 0.29

0.37 0.23 0.23 0.40

0.544

0.456

0.51

0.35

0.53

Note: *The regional estimate is assumed to be equal to the corresponding country estimate. Sources: Labour-income shares and profit shares are from ILOSTAT https://ilostat.ilo.org/topics/labourincome/. Data on the share of intermediate inputs in gross output are based on the input‒output tables of Brazil, China, India, and South Africa, OECDSTAT https://stats.oecd.org/Index.aspx?DataSetCode= IOTS. See footnote 2, this chapter, for an explanation of the symbols.

level—which in terms of our model means that ν, defined in footnote , takes a value of ⅓ and hence γ is ½ (Table .). This means that a one percentage point increase in real wage growth will increase home price inflation by around . percentage points, on the assumption that firms decide to pass on the full increase in wages. However, empirical evidence indicates that this is not what firms actually do: operating under

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

 

competitive conditions, firms are found to pass only around  per cent of the increase in wages on to final prices, absorbing the other half in lower profit mark-ups.¹⁷ This then means that a more realistic value for γ is around ¼—which explains why the impact of higher real wage growth on net export growth is relatively limited (in Table .). Taking Table .’s findings on ξ and ½γðχρ þ ηδÞ together, the net impact of higher real wage growth on economic growth ½ξ  γðχρ þ ηδÞ is about zero—as is indeed the case in Argentina, India, Mexico, and South Korea. In sum, aggregate economic growth is not very sensitive to variations in real wage growth, and consequently, the effects of labour regulation on employment must also be small. This corroborates the conclusions of World Bank researchers Kuddo et al. () that the effects of regulation on growth and employment are much smaller than the heat of the debates suggests, and of the IMF (: ) that ‘reforms that ease dismissal regulations with respect to regular workers do not have, on average, statistically significant effects on employment and other macroeconomic variables’. It follows that attempts to industrialize by a strategy of ‘beggaring one’s neighbour’ (suppressing national real wage growth below wage growth abroad) are just pointless.

.. ‘Technology-forcing’ Labour-Market Regulation Labour laws may constitute ‘beneficial constraints’ on firms’ decision-making (Streeck, ), which, far from undermining markets and capitalism, raises the static as well as the dynamic efficiency of economic activity in distinct ways. A first—Weberian—efficiencyenhancing mechanism operates by improving legitimacy. Since labour-market institutions inject fairness into the employment contract (by limiting inequality and facilitating risk sharing), they create goodwill and political legitimacy amongst workers and enhance productivity, perhaps as an unintended consequence (Lee and McCann, ). A second channel through which labour regulations enhance productivity is a Marxian one: higher real wage growth (made possible by regulation) raises the rate of labour-saving technical progress. Such ‘Marx-biased technical progress’ can be included in eq. (): z ¼ z0 þ βy þ #w z0 > 0; 0 < β < 1; 0 < # < 1 :

ð25Þ

where # represents the impact of higher real wage growth on labour productivity growth through labour-saving innovations. Empirical evidence on # for a sample of developing countries suggests that # takes a value of around ..¹⁸ Using eq. (), the derivative of equilibrium growth with respect to real wage growth becomes: dyE ¼ ð1  #ÞΩ½ξ  γðχρ þ ηδÞ < 0 dw

¹⁷ See Holz and Mehrotra () for evidence on China. ¹⁸ See Storm and Naastepad () and De Souza ().

ð26Þ

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-,  ,   



Higher real wage growth may still continue to depress export-led growth, but the negative effect dwindles (in absolute terms) the closer # is to unity. A third and final channel through which labour regulation may enhance labour productivity, competitiveness, and industrial upgrading is a Schumpeterian one, which operates by spurring innovation (Streeck, ). Tougher labour rules favour the stronger, more productive firms, as these will change work practices and upgrade production technology, and in the process these firms displace established, but less productive, competitors. This ‘cleansing’ or ‘technology-forcing’ effect of labour-market standards has been observed to have been at work in China (Huang et al., ) and India (Acharya et al., ). From a Weberian-Marxian-Schumpeterian perspective, it makes sense to use labour standards deliberately designed to ‘force’ firms to comply with technological norms that are not currently viewed as economically feasible. This way, labour regulation and resulting higher wages can be made to contribute to export diversification: ε 0 0 ð27Þ ¼ f ða; wÞ; fa > 0; fw > 0 μ Eq. () expresses the ‘technology-forcing’ potential of labour market regulation and higher real wage growth: higher wage growth forces firms that can no longer compete on low wages and low-tech (labour-intensive) products to diversify and move into higher-tech more capital-intensive goods, and as a result of this, ε=μ increases—raising the country’s BoP-constrained rate of growth in turn. If the ‘technology-forcing’ labour regulation is combined with a mission-oriented public investment programme (an increase in a) to diversify and upgrade exports, we are back to Figure ., as this will push up the BoP-constrained growth rate yB even more. Properly designed labour regulation thus reinforces the process of progressive structural change through which the late industrializing country can free itself from the shackles of primary-commodity specialization and climb up the industrial ladder.

.. The Wage and the Profit Rate To hammer home the point that labour regulation and higher wages are not automatically antithetical to business interests, let me define the rate of profit (ρ) as the real return on invested capital, as follows: ρ¼

Π Π Y ¼  YY  ¼ π  u  κ K K Y

ð28Þ

where π = (Π/Y) = the share of real profits (Π) in real income (Y), u ¼ ðY=Y Þ= capacity utilization, and κ ¼ ðY =KÞ = the ‘normal’ output‒capital ratio. K is the capital stock (at constant prices) and Y is ‘normal’ (trend) output. κ is assumed to be a longrun constant. Eq. () can be extended using this definition of the profit share π (Storm and Naastepad, ): π ¼ 1  θ ¼ 1  W  Z 1

ð29Þ

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

  The (+/–) impacts of a higher real wage on the profit rate (ρ) ρ goes down

decline in the profit share

impact on aggregate demand higher real wage

‘Marx-biased’ technical progress

‘technology-forcing’ upgrading ε leading to a higher ratio μ

dyE dw

≈ 0 (Table 17.3) higher z

+/– sign of net impact

ρ goes up

higher utilization u

 . The (+/–) impacts of a higher real wage on the profit rate (ρ) Source: Constructed by author.

where θ = the wage share, W = the real wage, and Z = the level of labour productivity. Substituting () into () gives this decomposition of ρ: ρ ¼ ð1  W  Z 1 Þ  u  κ

ð30Þ

The business profit rate thus has three determinants: W, Z and u. A higher real wage raises the wage share, reduces the profit share and therefore decreases ρ. Higher productivity, on the other hand, reduces the wage share, increases the profit share and therefore raises the profit rate. And if demand and capacity utilization go up, this must raise ρ. We use eq. () to assess the impacts of a higher real wage rate on firms’ profitability. First, a higher real wage rate directly and one-for-one reduces the profit share and hence the profit rate. Second, higher real wages have positive and negative E impacts on aggregate demand and growth—as in eq. (). We assume that dy dw  0 (Table .). Third, higher real wages spur labour-saving technical progress (via Weberian–Marxian–Schumpeterian channels, as in eq. ()), and thus raise z in eq. (). Finally, the ‘technology-forcing’ potential of higher wages and labour regulation raises ε=μ and hence yB. Demand-led growth yE will adjust (going up), pushing up capacity utilization u in eq. (). If the ‘technology-forcing’ labour regulation is combined with public investment to diversify and upgrade exports, this will further push up yB, yE, and u. Empirically, the sign of the net impact of a higher wage on the profit rate ρ is probably negative, but (as Figure . makes clear), the impact may be surprisingly small (in absolute terms), if the Marx-biased technical progress channel and the ‘technology-forcing’ mechanism are strong. Plus, with a little help from fiscal stimulus, which raises u and hence ρ, higher real wages can be made compatible with rising business profit rates. The ‘perversity thesis’ does not hold water.

. M-P L  L I

.................................................................................................................................. If developing countries are to improve their long-run growth performance, they must industrialize, building up a broad and technologically sophisticated domestic industrial

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-,  ,   



base with strong potential for high productivity, income, and export growth, in ways that improve the trade balance and raise BoP-constrained growth. The challenge is to develop industries with growth potential, in defiance of static comparative advantage, and to keep pushing innovation, structural change, and industrial diversification to the next level of sophistication. Fiscal, monetary, exchange-rate and labour-market policies must be designed in ways that support the industrialization strategy—otherwise, the industrial policy drive will be frustrated by growing external deficits and unsustainable debts, or alternatively, by processes of domestic stagflation or austerity-induced deflation. We can derive a few guiding principles for macroeconomic policymaking based on our model analysis, but with the qualification that successful macro-management requires pragmatism, and rule-based ‘one-size-fits-all’ approaches should be avoided. A first lesson is that it is critical for late industrializing nations to use CARs to maintain competitive exchange rates, because a competitive exchange rate can strengthen the effectiveness of industrial policy and reward export orientation. CARs also increase monetary policy autonomy, increasing the policy space for central banks to use interest rates and prioritized credit allocation in support of industrialization. But undervalued exchange rates cannot permanently sustain growth transitions. Furthermore, we must recognize that undervaluing one’s exchange rate is essentially a mercantilist, ‘beggar-thy-neighbour’ strategy, which will be counter-productive if adopted by many countries at the same time. Second, fiscal policy is of paramount importance as an enabler of industrial policy—public investment increases long-term (productivity) growth, helps diversification and raises employment, while stabilizing short-term demand. Progressive taxation, luxury consumption taxes, import tariffs (to protect infant industries), counter-cyclical export taxes and taxes on foreign financial inflows (of equity and portfolio finance) can be used to mobilize resources for financing public investment in physical and social infrastructure in non-inflationary ways, which helps to resolve the limited supply-responsiveness of critical wage goods-producing sectors such as agriculture.¹⁹ Wrongly timed fiscal austerity can be destabilizing and may undermine the industrialization process. Third, persistent trade deficits and the threat of a sudden financial outflow may force central banks to raise interest rates, but overly restrictive monetary policy will trigger a recession. The way for the monetary authorities to maintain a ‘development-oriented’ policy regime, consistent with a targeted exchange rate and accommodating to fiscal and industrial policy, is to impose exchange controls and restrictions on financial outflows. A ‘development-oriented’ monetary policy also implies that inflation targeting cannot be the only goal of central bank policy. Fourth, wage restraint is fundamentally ineffective and undesirable as a strategy for trying to improve external competitiveness and raise growth. Sustained growth of domestic demand requires sustained growth of real wages—which raises capacity utilization and profit rates. Labour regulations can be designed as being ‘technology forcing’ in nature, and thus

¹⁹ Agrarian modernization requires more than just public investment. East Asia’s dirigiste states relied on egalitarian technology policy (hybridization and chemical fertilizers), infrastructure and irrigation investment, rural credit, and radical institutional and land reforms (Storm, ).

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

 

support and amplify the impacts of industrial policy aimed at export diversification and upgrading. However, the biggest lesson to be learned from the analysis is that successful macro-management of late industrializing economies requires discretion, rather than rigid fiscal, monetary, or exchange rate policy rules. What is required are pragmatism, a flexibility to deal with country-specific conditions and historical context, and above all, as John Maynard Keynes wrote in a letter to Roy Harrod (dated  July ), ‘vigilant observation of the actual working of our system’ in order to be able to choose good models. Elaborating his point, Keynes wrote: Economics is a science of thinking in terms of models joined to the art of choosing models which are relevant to the contemporary world. It is compelled to be this, because, unlike the typical natural science, the material to which it is applied is, in too many respects, not homogeneous through time. The object of a model is to segregate the semi-permanent or relatively constant factors from those which are transitory or fluctuating so as to develop a logical way of thinking about the latter, and of understanding the time sequences to which they give rise in particular cases.

The open-economy, BoP-constrained growth model used here has been shown to be relevant to the contemporary world, not least because it has highlighted the critical importance of a development-oriented management of aggregate demand for successful late industrialization.

R Acharya, Viral V., Ramin P. Baghai, and Krishnamurthy V. Subramanian () ‘Labour Laws and Innovation’, Journal of Law and Economics (): ‒. Akyüz, Y., Ha-Joon Chang, and Richard Kozul-Wright () ‘New Perspectives on East Asian Development’, Journal of Development Studies (): ‒. Amsden, Alice H. () The Rise of ‘The Rest’: Challenges to the West from LateIndustrializing Economies. New York: Oxford University Press. Bagnai, Alberto, Arsène Reiber, and Thi Anh-Dao Tran () ‘Sub-Saharan Africa’s Growth, South–South Trade and the Generalised Balance-of-payments Constraint’, Cambridge Journal of Economics (): –. Bahmani, Mohsen, Hanafiah Harvey, and Scott W. Hegerty () ‘Empirical Tests of the Marshall–Lerner Condition: A Literature Review’, Journal of Economic Studies (): ‒. Bertola, Luis and José Antonio Ocampo () The Economic Development of Latin America since Independence. Oxford: Oxford University Press. Bhaduri, Amit and Stephen A. Marglin () ‘Unemployment and the Real Wage: The Economic Basis for Contesting Political Ideologies’, Cambridge Journal of Economics (): ‒. Blecker, Robert A. () ‘Long-run Growth in Open Economies: Export-led Cumulative Causation or a Balance-of-payments Constraint?’, in Geoffrey C. Harcourt and Peter Kriesler (eds) Oxford Handbook of Post-Keynesian Economics. Oxford: Oxford University Press, pp. ‒.

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-,  ,   



Bottega, Ana C. and João P. Romero () ‘Innovation, Export Performance and Trade Elasticities across Different Sectors and Countries’. CCEPP Working Paper –. Cambridge: University of Cambridge, Department of Land Economy. Broecke, Stijn, Alessia Forti, and Marieke Vandeweyer () ‘The Effect of Minimum Wages on Employment in Emerging Economies: A Survey and Meta-analysis’, Oxford Development Studies (): ‒. Bussière, Matthieu, Guillaume Gaulier, and Walter Steingress () ‘Global Trade Flows: Revisiting the Exchange Rate Elasticities’. Working Paper No. . Paris: Banque de France. Chakravarty, Sukhamoy () Development Planning: The Indian Experience. Oxford: Clarendon Press. Cherif, Reda and Fuad Hasanov () ‘The Return of the Policy That Shall Not Be Named: Principles of Industrial Policy’. Working Paper No. WP//. Washington, DC: IMF. Cimoli, Mario and Gabriel Porcile () ‘Technology, Structural Change and BoPconstrained Growth: A Structuralist Toolbox’, Cambridge Journal of Economics (): ‒. Cimoli, Mario, Sebastian Fleitas, and Gabriel Porcile () ‘Technological Intensity of the Export Structure and the Real Exchange Rate’, Economics of Innovation and New Technology (): ‒. Cimoli, Mario, Gabriel Porcile, and Sebastian Rovira () ‘Structural Change and the BoP Constraint: Why Did Latin America Fail to Converge?’, Cambridge Journal of Economics (): ‒. Diao, Xinshen, Margaret McMillan, and Dani Rodrik () ‘The Recent Growth Boom in Developing Economies: A Structural Change Perspective’, in Massiko Nissanke and José Antonio Ocampo (eds) The Palgrave Handbook of Development Economics. London: Palgrave Macmillan, pp. –. Elbadawi, Ibrahim A., Linda Kaltani, and Raimundo Soto () ‘Aid, Real Exchange Rate Misalignment, and Economic Growth in Sub-Saharan Africa’, World Development (): ‒. Felipe, Jesus, Matteo Lanzafame, and Gemma Estrada () ‘Is Indonesia’s Growth Rate Balance-of-payments Constrained? A Time-varying Estimation Approach’, Review of Keynesian Economics (): –. Frenkel, Roberto and Lance Taylor () ‘Real Exchange Rate, Monetary Policy and Employment’. UN-DESA Working Paper No. . New York: United Nations. Freund, Caroline and Martha Denisse Pierola () ‘Export Surges’, Journal of Development Economics (): ‒. Gerschenkron, Alexander () Economic Backwardness in Historical Perspective. Cambridge, MA: Harvard University Press. Gouvêa, Raphael Rocha and Gilberto Tadeu Lima () ‘Structural Change, Balance-ofpayments Constraint and Economic Growth: Evidence from the Multi-sectoral Thirlwall’s Law’, Journal of Post Keynesian Economics (): ‒. Gouvêa, Raphael Rocha and Gilberto Tadeu Lima () ‘Balance-of-payments-constrained Growth in a Multisectoral Framework: A Panel Data Investigation’, Journal of Economic Studies (): ‒. Guzman, Martin, José Antonio Ocampo, and Joseph E. Stiglitz () ‘Real Exchange Rate Policies for Economic Development’, World Development (): ‒. Hausmann, Ricardo, Dani Rodrik, and Jason Hwang () ‘What You Export Matters’, Journal of Economic Growth (): –.

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

 

Holz, Carsten and Aaron Mehrotra () ‘Wage and Price Dynamics in a Large Emerging Economy: The Case of China’. BIS Working Paper No. . Basel: Bank for International Settlements. Huang, Yi, Prakash Loungani, and Gewei Wang () ‘Minimum Wages and Firm Employment: Evidence from China’. IMF Working Paper No. WP//. Washington, DC: IMF. IMF () ‘Time for a Supply-side Boost? Macroeconomic Effects of Labor and Product Market Reforms in Advanced Economies’, World Economic Outlook . Washington, DC: IMF, pp. –. Junankar, Pramod N. () ‘Is There a Trade-off between Employment and Productivity?’. IZA Discussion Paper No. . Bonn: Institute for the Study of Labor. Kaldor, Nicholas () Strategic Factors in Economic Development. Ithaca, NY: Cornell University Press. Kalecki, Michal () ‘The Problem of Financing Indian Economic Development’, Indian Economic Review (): ‒. Kalecki, Michal () ‘Problems of Financing Economic Development in a Mixed Economy’, in Michal Kalecki, Selected Essays on the Economic Growth of the Socialist and Mixed Economy. Cambridge: Cambridge University Press, pp. ‒. Karshenas, Massoud () ‘Agriculture and Economic Development in Sub-Saharan Africa and Asia’, Cambridge Journal of Economics (): ‒. Kay, Cris () ‘Why East Asia Overtook Latin America: Agrarian Reform, Industrialization and Development’, Third World Quarterly (): ‒. Kuddo, Arvo, David A. Robalino, and Michael Weber () ‘Balancing Regulations to Promote Jobs: From Employment Contracts to Unemployment Benefits’. Working Paper No. . Washington, DC: World Bank. Lee, Sangheon and Deirdre McCann (eds) () Regulating for Decent Work: New Directions in Labour Market Regulation. London: Palgrave Macmillan. Lewis, W. Arthur () ‘Economic Development with Unlimited Supplies of Labour’, The Manchester School (): ‒. Mandelbaum, Kurt () The Industrialisation of Backward Areas. Oxford: Blackwell. Mazzucato, Mariana () The Entrepreneurial State: Debunking Public vs. Private Sector Myths. London: Anthem Press. McCombie, John S. L. and Nat Tharnpanich () ‘Balance-of-payments-constrained Growth, Structural Change, and the Thai Economy’, Journal of Post Keynesian Economics (): –. McCombie, John S. L. and Anthony P. Thirlwall (eds) () Essays on Balance of Payments Constrained Growth: Theory and Evidence. London: Routledge. McCombie, John S. L., Maurizio Pugno, and Bruno Soro () Productivity Growth and Economic Performance: Essays on Verdoorn’s Law. London: Palgrave Macmillan. Naastepad, C. W. M. () ‘Technology, Demand and Distribution: A Cumulative Growth Model with an Application to the Dutch Productivity Growth Slowdown’, Cambridge Journal of Economics (): ‒. Nataraj, Shanti, Francisco Perez-Arce, Sinduja V. Srinivasan, and Khrisna B. Kumar () ‘The Impact of Labor-market Regulation on Employment in Low-income Countries: A Meta-analysis’, Journal of Economic Surveys (): ‒. Neto, Antonio S. M. and Gabriel Porcile () ‘Destabilizing Austerity: Fiscal Policy in a BoP-dominated Macro-dynamics’, Structural Change and Economic Dynamics (): ‒.

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-,  ,   



Nureldin Hussain, Mohammed () ‘The Balance of Payments Constraint and Growth Rate Differences amongst African and East Asian Countries’, African Development Review (): –. Nurkse, Ragnar () Problems of Capital Formation in Underdeveloped Countries. New York: Oxford University Press. Ocampo, José Antonio () ‘Commodity-led Development in Latin America’, in Gilles Carbonnier, Humberto Campodónico, and Sergio Tezanos Vázquez (eds) Alternative Pathways to Sustainable Development: Lessons from Latin America. International Development Policy Series No. . Geneva: Brill-Nijhoff, pp. ‒. Ocampo, José Antonio, Codrina Rada, and Lance Taylor () Growth and Policy in Developing Countries: A Structuralist Approach. New York: Columbia University Press. Onaran, Özlem and Giorgos Galanis () ‘Income Distribution and Growth: A Global Model’, Environment and Planning A (): ‒. Pieper, Ute () ‘Deindustrialization and the Social and Economic Sustainability Nexus in Developing Countries: Cross-country Evidence on Productivity and Employment’, Journal of Development Studies (): ‒. Porcile, Gabriel and Danilo Sartorello Spinola () ‘Natural, Effective and BoP-constrained Rates of Growth: Adjustment Mechanisms and Closure Equations’, PSL Quarterly Review (): ‒. Porcile, Gabriel and Giuliano Toshiro Yajima () ‘New Structuralism and the Balance-ofpayments Constraint’, Review of Keynesian Economics (): –. Prebisch, Raúl () ‘Commercial Policy in Under-developed Countries’, American Economic Review, Papers and Proceedings : –. Robinson, Joan () The New Mercantilism: An Inaugural Lecture. Cambridge: Cambridge University Press. Rodrik, Dani () ‘Second-best Institutions’, American Economic Review (): ‒. Rodrik, Dani () ‘An African Growth Miracle’, Journal of African Economies (): –. Roncolato, Leanne and David Kucera () ‘Structural Drivers of Productivity and Employment Growth: A Decomposition Analysis for  Countries’, Cambridge Journal of Economics (): ‒. Rose, Andrew K. () ‘The Role of Exchange Rates in a Popular Model of International Trade: Does the “Marshall–Lerner” Condition Hold?’, Journal of International Economics (–): ‒. Rosenstein-Rodan, Paul N. () ‘Problems of Industrialisation of Eastern and South Eastern Europe’, The Economic Journal (/): ‒. Saith, Ashwani () ‘Development Strategies and the Rural Poor’, Journal of Peasant Studies (): ‒. Scitovsky, Tibor () ‘Economic Development in Taiwan and South Korea –’, Stanford Food Research Institute Studies (): –. Senhadji, Abdelhak () ‘Time-series Estimation of Structural Import Demand Equations: A Cross-country Analysis’. IMF Working Paper No. WP//. Washington, DC: IMF. Senhadji, Abdelhak and Claudio Montenegro () ‘Time-series Estimation of Export Demand Equations: A Cross-country Analysis’. IMF Working Paper No. WP//. Washington, DC: IMF. Singer, Hans W. () ‘The Distribution of Gains between Investing and Borrowing Countries’, American Economic Review, Papers and Proceedings (): ‒.

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

 

Souza, Joao Paulo de () ‘Real Wages and Labor-saving Technical Change: Evidence from a Panel of Manufacturing Industries in Mature and Labor-surplus Economies’, International Review of Applied Economics (): ‒. Storm, Servaas () ‘Domestic Constraints on Export-led Growth: A Case Study of India’, Journal of Development Economics (): ‒. Storm, Servaas () ‘Structural Change’, Development and Change (): ‒. Storm, Servaas () ‘Labor Laws and Manufacturing Performance in India: How Priors Trump Evidence and Progress Gets Stalled’. Working Paper No. . New York: Institute for New Economic Thinking. Storm, Servaas and Jeronim Capaldo () ‘Labour Institutions and Development under Globalization’, in Massiko Nissanke and José Antonio Ocampo (eds) The Palgrave Handbook of Development Economics. London: Palgrave Macmillan, pp. ‒. Storm, Servaas and C. W. M. Naastepad () ‘Strategic Factors in Economic Development: East Asian Industrialization –’, Development and Change (): ‒. Storm, Servaas and C. W. M. Naastepad () Macroeconomics beyond the NAIRU. Cambridge, MA: Harvard University Press. Streeck, Wolfgang () ‘Educating Capitalists: A Rejoinder to Wright and Tsakalotos’, Socio-Economic Review (): ‒. Taylor, Lance () Reconstructing Macroeconomics: Structuralist Proposals and Critiques of the Mainstream. Cambridge, MA: Harvard University Press. Taylor, Lance and Edmar Bacha () ‘The Unequalizing Spiral: A First Growth Model for Belindia’, Quarterly Journal of Economics (): –. Thirlwall, Anthony P. () ‘The Balance of Payments Constraint as an Explanation of International Growth Rate Differences’, Banca Nazionale del Lavoro Quarterly Review : ‒. Thirlwall, Anthony P. () ‘Thoughts on Balance-of-payments-constrained Growth after  Years’, Review of Keynesian Economics (): –. UNIDO () Industrial Development Report . Demand for Manufacturing: Driving Inclusive and Sustainable Industrial Development. Vienna: UNIDO. Venables, Anthony J. () ‘Using Natural Resources for Development: Why Has It Proven So Difficult?’, Journal of Economic Perspectives (): ‒. Wade, Robert H. () Governing the Market: Economic Theory and the Role of Government in East Asian Industrialization. Princeton, NJ: Princeton University Press. Wade, Robert H. () ‘What Room for the Developmental State in an Era of Financialization, Global Production Chains and Knowledge Monopoly?’, Development and Change (). World Bank () Doing Business: An Independent Evaluation Report. Washington, DC: World Bank.

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        ......................................................................................................................

  ,    ,                   .............................................................................................................

     

. I

.................................................................................................................................. T organization of production inside firms and along the supply chain change to respond to disruptions in the technology and in the nature and geography of demand. A wealth of literature going back to the s has dissected the drivers of firms’ production internationalization strategies (the ‘why’) and related operations (the ‘how’) (Hymer, ; Dunning, ; Mathews, ). Such internationalization strategies of multinational corporations (MNCs) have been driven by the contribution that different ‘places’ can make to MNCs’ overall division of value. The globalization of production activities that emerged from the combined offshoring of manufacturing activities created so-called global value chains (GVCs) (Gereffi and Fernandez-Stark, ). Consequently, the Smithsonian division of labour became a division of ‘value additive functions’, whereby each production stage contributes to a higher or lower extent to the value addition of the final output. This space-neutral approach has been criticized by Scholte () who argued that the globalization of production activities has ‘de-territorialized’ production choices. The global organization of production in GVCs started to be challenged with the global financial crisis in – when it became clear that two decades of mass offshoring had left a painful mark on some regions and places in advanced economies, which were de-industrialized or hollowed out. The socio-economic costs of offshoring were unveiled and this prompted a process of soul searching that has, belatedly, led to a more critical approach to globalization (Bailey and Tomlinson ). At the same time, the global economy found itself at the end of a technological cycle with incremental innovations increasingly exhausting technological opportunities

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

     

(Rifkin, ). A wave of new technologies is emerging associated with digital and green technologies and these are expected to disrupt firms, value chains, regions, markets, and ultimately the whole economy. Against this backdrop, this chapter explores the impact of technological change on GVCs and what initiatives and instruments governments in advanced economies can deploy to support firms and people during the transition. There are signs that the global economy is ‘de-globalizing’ with firms seeking to co-locate manufacturing and innovation activities; this offers an opportunity to regions and places to upgrade and transform their economies, leveraging industrial legacy with frontier technologies. However, this is not going to happen automatically, as has been discussed with—for example—so-called ‘reshoring’ in developed economies; rather, an active industrial policy is required (Bailey and De Propris, ; Bailey et al., a, b). In this chapter we discuss the implications for a transformative industrial policy that we see comprising three objectives: () to connect embedded industries to new technologies; () to repopulate embedded industries with new firms and start-ups; and () to use regulation and procurement to create new markets and allow exploration.

. T C   F I R

.................................................................................................................................. A wave of new technologies is driving a shift in our techno-socio-economic paradigm (Pérez, ). These new technologies are expected be pervasive and disruptive, changing not only the organization of production inside the firm and thereby the workplace by altering the balance between capital and labour, but also re-drawing the organization of production between firms and along the value chain whether local or global. These new technologies include a range of advances in biotech, nanotech, neuro-technologies, green and renewables, ICT and mobile tech, cloud technology, big data, D printing, artificial intelligence, Internet of things, robotics, sensoring, space technology, and drones. Some of the current debate on the impact of these technologies on the economy and society has drawn on the seminal work of Kondratiev () on technological waves to argue that they amount to a Fourth Industrial Revolution (FIR) (De Propris, ; OECD, a; Rifkin, ; Schwab, ). The First Industrial Revolution coincided with the British Industrial Revolution between the last decades of the eighteenth century and the first half of the nineteenth century with new technologies related to steam power, cotton, steel, and railways, coupled with mechanization and the surge of the factory system. The Second Industrial Revolution was triggered by the introduction in the post-war period of electricity, heavy and mechanical engineering (automotive and aviation) and synthetic chemistry (oilbased production). New business forms emerged as large firms started producing away from the domestic market, becoming multinational firms. The Third Industrial Revolution coincided with the introduction of electronics and computers, petrochemicals and

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 ,   ,   



aerospace in the last decades of the twentieth century. Volatile demand required more flexible organizational forms, such as firm clusters and industrial districts, which became global hubs due to their competitive advantage (De Propris, ). New technologies also enabled faster communications and transport, kicking off a process of globalization in production that led to multiplications of GVCs (Gereffi, ). The ‘digital revolution’ argument is captured by the debate on Industry . (Deloitte, ; European Commission, ; PWC, ) and on technologies enabling the emergence of smart and connected factories. Often referred to as cyber-physical spaces (GTAI, ), production places will see humans working side by side with digitally connected robots or other forms of automation with the novelty that the latter will communicate with each other rather than just being operated by humans. This will transform the flow and use of inputs in the factory, with capital investment in automation expecting to replace some human tasks. Therefore, in factories we expect automation to displace labour-intensive productions for increasingly complex and non-routine functions. While FIR technologies will bring about a disruptive change that has been wrongly reduced by some to simply a ‘digital revolution’ linked to artificial intelligence and the Internet of things (Deutsche Bank, ), we believe that as a technological revolution, its -degree transformative power will be felt not only in the world of production but also in the world of consumption and usage and in everybody’s ways of life. To fully appreciate the transformational shift that the deployment of new technologies will have on firms’ value creation, it has been argued that a broader understanding of the impact that new technologies will have must be acknowledged; on this De Propris and Bailey () propose a more holistic conceptualization of Industry . that takes into account five interlinked transformations brought about by new technologies (see Figure .). The concept of Industry .+ allows us to understand changes in the nature of business and markets (Bailey and De Propris, ). These transformations are: a. b. c. d. e.

the creation of new radical markets the design and manufacture of radically new products the adoption of new business models the experimentation of new product-service innovations the exploration of new customer-centred innovations.

These transformations will possibly trigger two major new trends: one is a recoupling of innovation and production; and two, the scaling-down of production for niche markets. In particular, radically new products can create radically new markets that either address new demand needs or push new technology-driven offers. Either way, radical innovations require exploration, experimentation, and testing that are likely to call for a recoupling of innovation with production. As new products are launched or tested in the market, a smoother, direct, closer, more frequent, and more meaningful interaction between innovation and production will be necessary. The experimental nature of these high-tech markets and products means that a co-location between innovation and production is likely to emerge. Other disruptive transformations arising

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

     

INCLUSIVE GROWTH

          

  

 

 . Industry .+ Source: Authors.

from the FIR include the servitization of manufacturing and changes in firms’ business models. The servitization of manufacturing introduces a product–service innovation (Bustinza et al., ; Dimache and Roche, ; Baines et al., ) that is linked to the choice of businesses and customers to move from a product-based business model to a service-based business, whereby buyers overcome the need to own products and rather prefer to hire or lease them. As the relationship between producer and user is woven around the specific characteristics of the servitized good, again such relationship intensifies with constant exchanges that in this latter case extend beyond the moment when user receives the ‘good’ because they are not buying ‘the good’ but the function; that is, the usefulness and the service attached to it (Vendrell-Herrero and Bustinza, ). As the servitized good is designed, produced and supplied around the specifications of the user, the relation between innovation, production, and consumption becomes closer. The need for an innovation–production–consumption continuum may result in firms strategically experimenting with new business models where coinnovation with consumers occurs in the design of products—with personalized offers—and in delivery with elements of servitization. The other major trend is the efficient scaling-down of production. Some new technologies such as cloud technology, big data, and data analytics will enable the design, manufacturing, and delivery of personalized products (goods and services) thanks to a two-way flow of information and data between the producers and its customers. The flourishing of a growing number of start-ups or entrepreneurial activities linked to digital technologies but with the ethos of producing something has been widely documented in the ‘makers movement’. These ‘digital artisans’ utilize new technologies

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 ,   ,   



to create new—emerging or existing—niche markets or to address the demand for small-scale, specific products. The key point here is that digitally enabled technologies can be efficiently scaled down to support small-scale productions whose markets are very thin and geographically dispersed. Makers tend to appear in places where there is already an ‘industrial commons’ (Anderson, ) with localized specialized competences because their attachment to the tacit and cumulated knowledge of the place provides a unique advantage that they couple with an ability to master digital technologies. Another example of an efficient scaling-down of production is the use of additive manufacturing or D-printing that has enabled production at the point-ofconsumption with the related benefits of reducing time lags, lower disruption, storage, stockpiling, and so on (De Propris and Bailey, ). Digital technology and automation are therefore expected to transform buyer– supplier relationships along the whole supply chain. Indeed, the Internet of things, sensoring, space technology, and mobile technology are, for instance, expected to enable remote machine-to-machine communications that can allow for the coordination of complex production operations via a smooth integration of functions geographically dispersed. The attribution of value creation along the value chain is likely to be completely redrawn by FIR technologies. We are used to visualizing value attribution along the value chain with the smile curve (Mudambi, ) and this framework has (arguably) explained three decades of production decoupling (Baldwin, ) as MNCs adopted strategies to shave costs from low-value-adding functions by relocating them in low-cost economies. However, we would argue that the five transformations abovementioned are likely underpinned by a re-distribution of value creation across production functions in ways that are not yet fully understood. The adoption and application of new technologies will disrupt the parameters and the processes of value creation for firms, leading to a radical rethink of value creation along the supply chain. This means that production is no longer a low-value-added function but it can embody equal, if not more, value addition than innovation (design and R&D) since the two go hand in hand. We can think therefore of a flat or even of a ‘sad curve’ (see Figure .).

High Value added

R&D–design

assembly

logistics

marketing-advertising

Value chain

 . The sad curve Source: Authors’ elaboration.

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

     

In summary, technological change is expected to bring about disruptive transformations that will encourage a re-coupling of innovation with production, while also easing a scaling-down of efficient production. Overall this will likely reshape value creation along the value chain by redistributing value addition differently from before. The big question is what impact this will have on the geographical dispersion of the value chain. We are proposing that there is some initial evidence suggesting an increasing interest in co-locating innovation and production leading to some deglobalizing trends.

. GVC  M H O

.................................................................................................................................. A wealth of literature going back to the s has dissected the drivers of MNCs’ production internationalization strategies (the ‘why’) and related operations (the ‘how’) (Hymer, ; Dunning, ; Mathews, ). The globalization of production activities that emerged from the combined offshoring of manufacturing activities created so-called GVCs (Gereffi and Fernandez-Stark, ). Consequently, the Smithian division of labour became a division of ‘value-added functions’, whereby each production stage contributes, to a higher or lower extent, to the value addition of the final output. The location choices of multinational enterprises (MNEs) were motivated by the contribution that different ‘places’ could make to their overall division of value, but in practice such choices were place-neutral in the sense that MNEs were indifferent across places given equal features. Production choices were fundamentally ‘de-territorialized’ (Scholte, ) and places were replaceable, especially for low-value functions. In particular, what was relocated were low-value-adding functions, namely labourintensive manufacturing functions, to low-labour-cost countries via the creation of GVCs. This framework sees the production process as a value chain, that is ‘the full range of activities which are required to bring a product or a service from conception, through the different phases of production . . . delivery to final consumers and the final disposal after use . . . Production per se is only one of a number of value added links’ (Kaplinsky and Morris, ). So each function is weighted in the firm’s strategy depending on its value creation contribution: what contributes the most to the value added of the final production is clearly what is likely to be seen by the firm as a ‘core activity’ or a ‘strategic activity’ and is therefore internalized, while what contributes the least, on the contrary, is seen as secondary and can be outsourced. GVCs comprise, therefore, components that embody different value-adding content and which contribute differently to the overall value added (Timmer et al., ). In this framework, manufacturing, production, and assembly are deemed to produce low levels of value added, because when the technology is mature, in imperfectly competitive markets (i.e.

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 ,   ,   



global markets), a reduced price elasticity can only be constructed by embodying in products a high content of intangible value through product development, advertising, and marketing. These are the functions that most contribute to firms’ extraction of market power and are therefore higher in value added. This trend has been extensively documented in the literature on GVCs (OECD, b). The GVC framework was introduced by Gereffi and Fernandez-Stark () to describe and analyse the impact that manufacturing offshoring had on developing and emerging economies, especially in terms of working conditions and labour standards (Barrientos et al., ), and trajectories of upgrading (Humphrey and Schmitz, ). One of the key tenets of the GVC framework is that inter-firm relationships are determined by their relative decision-making powers, namely their governance (Gereffi et al., ). Suppliers producing low-value-added and standardized components are constantly competing on price; they are likely to be in a captive relationship with their buyer who can easily replace them with a cheaper supplier. Lee and Gereffi () argue that to overcome this vulnerable position, suppliers attempt to upgrade their capabilities to extend the portion of the value chain they can cover. This allows them to extend their bargaining power by moving towards building more relational transactions based on the uniqueness and value of the suppliers’ competences. Governance and upgrading are therefore the ‘twin pillars of the GVC framework’ (Gereffi, : ) to the extent that they determine the dynamics of economic development in developing economies. Under the assumption of a value chain shaped like the ‘smile curve’ above-described, any aspiration to greater value capture does not rest only on individual firms, suppliers, but it requires ‘economic actors—nations, firms, and workers—to move from low-value to relatively high-value activities in global production networks’ (Gereffi, : ). In other words, economic upgrading takes on a systemic connotation that supports and strengthens any upgrading attempts of individual suppliers. For such systemic upgrading to occur, national or regional governments are required to proactively intervene in the macro- and microcomponents of the economy. Gereffi and Sturgeon () suggest moving away from import-substitution policies or export-oriented policies, to embrace value-chainoriented policies that strategically target specific industries where growth is favoured. Economic upgrading in such specific industries—using the GVC approach—would mean supporting suppliers to develop a global customer base, develop a competitive advantage in high-value niches, in specialized value chains, and finally moving towards the top end of the value chain (Gereffi and Sturgeon, ). There are two points worth making as we are building up to discuss how IP can leverage the reshaping of global production due to technological change. One is that GVCs describe models of organizing production based on decoupling and offshoring at a time when the technology was mature, innovations were incremental, and competition was on price or on market imperfections and segmentations (e.g. branding). Therefore, firms could only innovate incrementally and adopt cost-saving strategies. The second point is that in the global economy there was a convenient divide between countries holding technological capabilities and countries holding lower-costs

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

     

resources; such ‘complementarity’ in our view drove what some saw as a ‘turbocharged globalization’ (Friedman, ). Indeed, the need and policy will of emerging/transition/ developing economies to enter the global economy met with the strategic determination of MNEs to seek cost efficiencies. These dynamics played out until , when the global financial crisis occurred. The relocation of manufacturing to Asia introduced a novel international division of labour that turned out to have significant implications for the erosion of the manufacturing base of advanced economies with a dangerous concentration on untradable sectors. The manufacturing hollowing-out presented a number of costs for EU economies. Various streams of research contested the assumption that manufacturing processes and innovation might easily be decoupled and relocated independently of each other (Pisano and Shih, ; Ketokivi and Ali-Yrkkö, ). Indeed, the offshoring of labourintensive manufacturing functions started pulling along also more innovation-intensive ones, thereby destabilizing the EU innovation basis. This is already occurring in pharmaceutical, advanced engineering, and ICT. The GVC framework has very recently been applied to describe the internationalization of Italian industrial districts as a systemic strategy that had implications for the home economies (De Marchi et al., ) in terms of changing the reconfiguring and breaking up local value chains as well as losing crucial competences to offshored functions. It became clear that the demise of manufacturing activities resulted in an impoverished ‘industrial commons’ eroding advanced economies’ innovation capabilities (Pisano and Shih, ), while allowing suppliers in emerging economies to gradually climb up the value ladder, through so-called processes of learning by supplying (Alcacer and Oxley, ). The loss of skills, competences, and tacit knowledge across a sufficiently diversified suite of sectors has had a long-lasting effect on the ability of EU regions to maintain an industrial base able to secure long-term prosperity for its citizens. Indeed, critiques of novel forms of organization pointed to the larger societal drawbacks of the offshoring bandwagon, highlighting how the ‘hollowing-out’ of the large corporation and the relocation of manufacturing abroad contributed to the increasing levels of inequality recorded in advanced societies. Sectoral imbalances in some EU economies and the United States towards services and untradable sectors also reduced the ability of these economic systems to respond to the financial shocks, which led to a much more precarious and lengthy economic recovery (Aiginger, ), in some economies like the United States overcome only by significant and sustained fiscal expansionary policies. Those countries that had chosen to maintain a solid manufacturing base, such as Germany, Belgium, or France, were found to reset their economy more quickly and therefore to be more resilient. Other economies with an equally healthy manufacturing base lingered, however, in a long and painful recession due to stringent austerity policies, such as Italy (Aiginger, ). Post-financial crisis, a lively debate emerged on the importance of manufacturing for advanced economies to maintain a balanced economic and skills base: what was often referred to as a need for ‘rebalancing’ or a new manufacturing renaissance (Bailey and Tomlinson, ). This renewed interest in manufacturing had three aspects. First, it engaged policymakers who understood a call to defend and promote domestic jobs and factories by

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 ,   ,   



supporting domestic firms and sectors. Second, protectionist trade policies and more recently aggressive trade wars have been defended to protect, for example, ‘American jobs’ (Forbes, ); however, this fails to understand the interconnectedness of global production and the consequences of such actions. Finally, it coincided with the surfacing of the debate on technological change and a ‘new’, ‘smart’ manufacturing model; in other words, there was an opening for high-cost economies to develop and anchor new technological capabilities across EU manufacturing sectors to support jobs creation and a higher standard of living. This also meant a new competitive scenario for firms where low-value-adding labour-intensive functions had to be redefined. The adoption of new technologies by the manufacturing sector will transform the manufacturing model in ways discussed above, which we argue will also entail a new global organization of production.

. S  D-

.................................................................................................................................. The renewed interest in manufacturing of advanced economies translated into policymakers’ commitment to re-build their manufacturing base. This meant attempting to slow down offshoring, but also encouraging a new trend that saw firms which had previously offshored some production functions looking to bring those activities back home. Indeed, evidence emerged that some firms with operations abroad were considering or actively pursuing reshoring strategies. Reshoring has been used to capture the choice of a multinational firm to move back to their home economy a production operation previously offshored—either via a new investment or domestic outsourcing (Bailey and De Propris ). Reshoring has since become something of a buzzword with many country case studies emerging in relation to the United States, Spain, Italy, and Germany (Kinkel, ; Kinkel et al., ; Ernst & Young, ) over the last few years. Company case studies have also emerged, documenting individual firms’ strategic rationale for reshoring part of their operations back to the home economy, such as Walmart, Apple, Google, Caterpillar, and General Electrics (Reshoring Institute, ; Bals et al., ) or the case of the Finnish bicycle company which moved production from Taiwan back to Finland (Gylling et al., ). Many studies have discussed some of the push factors that have convinced firms to reconsider the actual cost and benefit of offshoring (Kinkel et al., ). Value chain frictions and disruptions due to natural disasters or geo political factors have shown that global operations have so far ignored important hidden costs (Gray et al., ; Kinkel and Maloca, ) linked to the increasing complexity of value-chain governance (Lavissiére et al., ), a lack of flexibility and responsiveness due to long lags, and overlooked quality and control limitations (Bailey and De Propris, ). On the other hand, the decision to move back to relatively high-cost locations in advanced economies has also been driven by some pull factors that have made them attractive, especially in relation to the emergent technological change: such as greater flexibility

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

     

and responsiveness; closer integration with design and product development; better control on quality and variety, shorter lead time, and the use of new technologies to make cost savings. These location decision strategies have been linked to changes in the distribution of value creation along the value chain, as discussed above, with a shift from a smiling curve to a flatter one (see Figure .). Some scepticism has been expressed on the small scale of the reshoring phenomenon, notwithstanding the visible and active commitment of policymakers to leverage it to repopulate their industrial base (see, for instance, the US tax change to encourage MNEs to repatriate their profits, New York Times, ). This has been in part due to difficulties in capturing empirically the changes in firms’ production decisions: data on firms’ decision to swap a foreign supplier for a domestic supplier is hard to find. Easier to trace have been changes in firms’ investment decisions; however, these have tended to be more rigid in the short term and in some countries very much constrained. However, reshoring trends have been an important signal of a change in the perception of business over whether choosing to have globalized operations is always superior to having national or locally bound operations. Indeed, we see reshoring representing firms’ longer-term strategy to better face a new competitive environment (Młody, ; Navarro, ), and must therefore be read as an early sign of a transformation that is being unleashed at the moment. Firms’ supply chains are shortening and the cost-saving attraction of production offshoring is receding. This opens two levels of questions: one is to what extent we can talk about de-globalizing forces shaping a new production order, and the other is whether regional economies in advanced economies are capable of picking up this challenge and become fertile ground for a flourishing of new dense and geographically short value chains. An emerging literature on de-globalization is starting to look into what this might mean (Livesey, , ; van Bergeijk, ; Martin et al., ). Some have drawn on data on long-term changes in FDI and import/export trends and have argued that there is evidence of a reduction in the global production activities (Pegoraro et al., ) with supply chains being geographically shorter.

. I P  B

.................................................................................................................................. The term ‘industrial policy’ has gone through many fashions and has meant different things at different times. Government intervention in the productive parts of the economy was justified by instances of market failure or any time the market was unable to allocate resources efficiently or equitably. This view justified national champions in industries deemed to be natural monopolies, for instance in the utilities. All this was of course turned on its head by a massive wave of privatizations in the s in Europe, where competition and liberalization allowed market forces in industries of strategic societal importance such as water, energy, and telecoms. At the same time,

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 ,   ,   



industrial policy has been associated with interventionist governments promoting national champions or picking winners, that is, sectors, in a global competitive environment characterized by inter-country competition and home-rooted large firms. This was the case when industrial policies were aimed at supporting the growth of domestic champions and turning a blind eye to their sometimes-anticompetitive dominant position domestically, in view of allowing them to become competitive in foreign markets (Bianchi and Labory, ; Bianchi et al., ). We would argue that the industrial policy of picking sectors of the s and s occurred at a time of technological change coinciding roughly with the Third Industrial Revolution, so government intervention to promote industry development was aimed at supporting domestic champions positioning themselves in new industries vis-à-vis foreign competitors in a competitive environment shaped by absolute advantage and trade. The emergence in the s of MNEs controlling more complex GVCs changed the balance of power between large firms and their home government as MNEs started dealing with foreign governments keen to host their operations and offering favourable terms to attract them. In some countries, such as Ireland, the attraction of FDI was part of a national industrial policy to promote the emergence and development of some industries (Bailey et al., ). In such a globalized context and a time when technology was mature and known, the term industrial policy fell from grace, replaced by a heightened attention to the contribution of places and regions with their industrial specializations to create national competitive advantages (Porter, ). Indeed government intervention was recast to promote, not national champions, but a favourable national business environment, a national innovation system (Chaminade et al., ), and to create systemic conditions for businesses to thrive from telecoms infrastructure and education/skills, to transport connectivity and regulatory framework. These fell under different labels though, such as regional policy, innovation policy, or competitiveness policy. The latter had in common in our view two elements; one is that their prescriptions assumed maximum impact with minimum government intervention, as their gestation and delivery occurred at times where the dominant thinking was free market and deregulation. The second common element is that they introduced, for the first time, an appreciation of the importance of places as local engines of growth contributing to a country’s competitiveness. Yet, industrial policy is now back on the agenda after years of neglect (Bailey et al., ), with this revived enthusiasm coming at a time of technological transformation. Over the last decade, ‘place-based’ approaches have increasingly been used to develop regional industrial policies, as dissatisfaction with spatially blind approaches has grown. Place-based approaches emphasize tailoring policy to develop place-specific specialisms and capabilities, on which a region can thrive. Barca (), for instance, defines a place-based approach as a long-term strategy aimed at tackling persistent underutilization of potential and persistent social exclusion in specific places through external interventions and multilevel governance. This place-based focus has begun to be applied to a wide range of policy settings including industrial policy (Bailey et al.,

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

     

a, b), research on place-based leadership (Beer et al., ), and in managing the impacts of economic shocks (RSA, ). The place-based approach chimes with modern perspectives on industrial policy more broadly, where industrial policy is seen as a process of discovery requiring strategic collaboration between the private sector and state in unlocking growth opportunities, where policy ideally has the quality of ‘embedded autonomy’ (see Rodrik, ). It is not captured by firms and sectors, but focuses on bringing together actors in a discovery process, where firms and the state learn about underlying costs and opportunities and engage in strategic coordination. To be successful, place-based approaches require strengthened local and regional institutions, a need for local stakeholders to be active in order to deliver success, the development of human capital, and the critical embrace of innovation (Tomaney, ). However, as the Regional Studies Association () notes, government initiatives badged as ‘place-based policy’ often fall well short, with governments simply relabelling long-established programmes as ‘place-based policy’, or only partially innovating. In the context of the EU’s regional policy, smart specialization strategies at the regional level were designed to empower regional actors to identify trajectories of industrial renewal drawing on their embedded specializations. Although smart specialization strategies are seen as having paved the way in place-based approaches, Gianelle et al. () suggests that regions and countries have, in reality, put in place mechanisms that may circumvent the very rationale of smart specialization. They note that this could arise from the result of lobbying activities, higher political return from widespread public support measures, a risk-averse attitude of policymakers, and a lack of adequate institutional and administrative capacity that can be observed at national and regional levels. Furthermore, Barzotto et al. (a and b) argue that specialization strategy projects are more likely to be identified in stronger regions, which boast a strong entrepreneurial talent pool and business networks; with the result that policy implementation may inadvertently be a-spatial and could exacerbate regional imbalances. The arrival of radical and disruptive FIR technologies associated with Industry ., poses challenges for policymaking and the role of governments. Technological change will fundamentally transform industries and markets, as this will inevitably impact on regions and places. The big question is whether the focus on regional policy and concerns about wider socio-economic cohesion and growth should still dominate, or whether industrial policy can regain centre stage as a strategic intervention to shape a country’s productive competitiveness. Recent work has stressed that the disruptions brought about by such technologies have the potential to introduce new layers of socioeconomic divides (De Propris and Bailey, ), with a concomitant call for a more holistic transformative industrial policy that brings together technology, sectors, and place. Against this backdrop, the policymakers risk underestimating the fundamental role that policy and public interventions need to play just as the economy and wider society are embarking on transformations that will shape work, industry, mobility, communications, and more for decades ahead.

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 ,   ,   



. T I P

..................................................................................................................................

As suggested in the definition of Industry .+, new technologies will not only fundamentally change the organization of production, but crucially the nature of industries and markets and with them society. The global organization of production that we have witnessed so far is responding to these changes with visible reconfigurations of value chains in more compact networks that stretch within continents as production spaces and final markets (Schwab, ). Such radical and disruptive change cannot occur without the pro active role of governments and policymaking. Industrial policies must move towards having a truly transformative power, by enabling new technologies to penetrate and redefine existing sectors, as well as create brand new markets and industries. Indeed, awareness and adoption are crucial steps to ensure that the existing manufacturing base shifts onto the new technological paradigm despite the inevitable resistance from incumbent actors. This can, however, only be successful if the technological transformation of industries is rendered against the place-based unique characteristics of such localized industries in regions. We therefore advocate for a transformative place-based industrial policy that acts at the intersection across three dimensions: the place (cluster and region), the industry with its value chain, and the new technologies. This requires three levels of intervention. First, industrial policy must connect the industries already embedded in regions to new technologies through a process of accessing, adopting, and adapting to the latter. This could, in the European context for example, embody smart specialization strategies with a heightened attention towards the creation and adoption of FIR technologies in different regions so as to bring together technology, sectors, and place. A transformative industrial policy needs to think beyond sectors alone and, rather, identify, nurture, and diffuse the key crosscutting technologies (such as digitalization, the Internet of things, robotics, and artificial intelligence) that have an enabling role across manufacturing and services. Industrial and regional policy needs to recognize and exploit such technologies by making them accessible to businesses in different regions. Furthermore, a transformative regional industrial policy needs to be developed in a holistic sense (for example, on skills, access to finance, clusters, supply chains, and innovation) so as to enable policy to be better suited to the distinctive characteristics and advantages of different scales. The latter requires regionally based industrial development strategies promoting ‘related diversification’ capitalizing on the FIR. Such strategies need to recognize (i) the need to bring together different but related activities in a region via cross cutting FIR technology platforms (such as via Living Labs or digital demonstration hubs) and (ii) the differing potentials of regions to diversify, due to different industrial, knowledge, and institutional structures linked to specific regional historical trajectories. This requires tailor-made policy actions embedded in and linked to the specific needs and available resources of regions, starting with the existing knowledge and institutional

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

     

base in that region. These need to capitalize on region-specific assets, rather than attempting to replicate and apply policies that may have worked in quite different places (Bailey et al., b). Other elements of a transformative regional industrial policy would need to involve, inter alia, the need for: new skills to be developed and constant re-skilling and upskilling processes as the FIR progresses. However, to transform the region’s potential based on ‘unrelated variety’, and to broaden and renew the region’s industrial structure by helping it branch into new related activities, policy must also encourage crossovers between manufacturing and service industries and between manufacturing and new technologies. This could come via knowledge-transfer mechanisms that connect related and unrelated industries. Second, a place-based industrial policy must favour the creation of new firms and start-ups in the embedded industries. This new generation of entrepreneurs is crucial to explore, create, and experiment with market niches often at the intersection between sectors. This will require SMEs to have access to funding and finance to embrace digital technologies; recognizing and exploiting possibilities to reposition firms, industries, and regions on new parts of the GVC as the value added of manufacturing changes over time; creating and seizing re-shoring opportunities as re-localization opportunities open up, namely involving policies to rebuild supply chains in Europe. The EU Industrial Policy  (European Commission, ) suggests that new technologies offer a great opportunity to strengthen European firms to export in ‘fast growing world markets’ (European Commission, : ) and to leverage firms’ competitive advantage in new technologies by gaining a ‘strategic independence from foreign suppliers’ (European Commission, : ). This confirms, in the case of the EU (likewise for Asian and US competitors; Schwab, ), the commitment to control the emerging new technologies and to be able to deploy them horizontally across sectors in tightly knit networks of buyers and suppliers. At the same time, new technologies open up endless possibilities for exploration and innovation and this should stimulate the entrepreneurial, risk-taking nature of new businesses and start-ups. Now more than ever, initiatives—like incubators, science parks, accelerators—that enable the realization of such ventures should be supported and expanded. Drawing on the triple helix model, the embeddedness of these facilities in regional spaces with a dynamic (albeit mature) manufacturing specialization, can offer true path renewal strategies for local firm clusters, as they connect systemically businesses with academia or research organizations. These new innovative businesses will provide an injection of technological novelty in the local industry with transformative powers: a holistic regional industrial policy (Harrison et al., ). An example of this is the Vinnväxt programme of Vinnova (the Innovation System Agency of the Swedish Government) which supports regions that have declining industries to identify new industrial trajectories thanks to a systemic effort that brings together universities, local institutions, and the local business community. The Vinnväxt programme provides prime funding to help regional stakeholders work together to graft one or more

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 ,   ,   



relevant new technologies onto the local industry with the promotion of new firms and new local value chains. Finally, the redefinition and use of regulation and procurement to create new markets for technological change also means technological uncertainty as the old paradigm is setting, but many new ones are still leaving space for doubt and hesitation. In this transition, a pro active and far-sighted government is necessary to share the risk of technology adoption with business. This means first of all, significant infrastructural investment to embrace new technologies (e.g. G) and enable firms and citizens to become aware of users of such technologies. More significantly, the transformative power of an industrial policy that is prioritizing technological transformation requires the use of ‘smart regulation’ to change behaviours and incentives and a risk-sharing procurement policy that creates new markets and allows the exploration of new products or services. This idea was introduced first by Porter and van der Linde () who controversially suggested that to overcome firms’ resistance to adopt new technologies (in their article linked to sustainability) ‘properly designed—government—regulations’ can support firms’ innovation via technological adoption and applications at times of technological change. In protected domestic markets, firms can achieve levels of innovation and performance that allow them to compete internationally and engage in GVCs at the highest levels of value creation. Advocates of a pro active role of government have become more vocal recently thanks to the work of Mazzucato () who argued for an entrepreneurial role for government by inspiring, risk-sharing, and supporting businesses’ mission to innovate. By designing missionoriented policies associated to innovation and technological change, government can use procurement to favour the creation of small-scale value-chain networks of firms with purposeful links with research organizations. The design and deployment of new products or processes for protected public markets allow firms to gain a competitive advantage that will redraw completely their position and value creation contributions in GVCs.

. C

.................................................................................................................................. This chapter has examined the impact of technological change on GVCs and what initiatives and instruments governments in advanced economies might deploy to support firms and people during the transition. There are signs that the global economy is ‘de-globalizing’, with firms seeking to co-locate manufacturing and innovation activities; this offers an opportunity for regions and places to upgrade and transform their economies, leveraging industrial legacy with frontier technologies. We have discussed the implications for a transformative industrial policy that we see comprising a number of dimensions. A transformative industrial policy needs to think beyond sectors alone and, rather, identify, nurture, and diffuse the key cross-cutting

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

     

technologies (such as digitalization, the Internet of things, robotics, and artificial intelligence) that have an enabling role across manufacturing and services. Policy also needs to recognize and exploit such technologies by making them accessible to businesses in different regions. Furthermore, a transformative regional industrial policy needs to be developed in a holistic sense (e.g. on skills, access to finance, clusters, supply chains, and innovation) so as to enable policy to be better suited to the distinctive characteristics and advantages of different scales.

A The writing of this chapter has been supported by the EU Horizon  project ‘MAKERS’, which is a Research and Innovation Staff Exchange under the Marie Sklodowska-Curie Actions, grant agreement number , and via the Economic and Social Research Council’s ‘UK in a Changing Europe’ programme, Grant Reference: ES/T/.

R Aiginger, Karl () ‘Industrial Policy for a Sustainable Growth Path’, in David Bailey, Keith Cowling, and Philip R. Tomlinson (eds) New Perspectives on Industrial Policy for a Modern Britain. Oxford: Oxford University Press, pp. –. Alcacer, Juan and Joanna Oxley () ‘Learning by Supplying’, Strategic Management Journal (): –. Anderson, Chris () Makers: The New Industrial Revolution. New York: Random House. Bailey, David and Lisa De Propris () ‘Manufacturing Reshoring and its Limits: The UK Automotive Case’, Cambridge Journal of Regions, Economy and Society (): –. Bailey, David and Lisa De Propris () ‘. Industry ., Regional Disparities and Transformative Industrial Policy’, Regional Studies Policy Impact Books (): –. Bailey, David and Philip R. Tomlinson () ‘Industrial Policy since the Crisis’, in Philip Arestis and Malcolm Sawyer (eds) Economic Policies since the Global Financial Crisis. International Papers in Political Economy Series. London: Palgrave Macmillan, pp. –. Bailey, David, Carlo Corradini, and Lisa De Propris (a) ‘ “Home-Sourcing” and Closer Value Chains in Mature Economies: The Case of Spanish Manufacturing’, Cambridge Journal of Economics (): –. Bailey, David, Ann Glasmeier, Philip R. Tomlinson, and Peter Tyler () ‘Industrial Policy: New Technologies and Transformative Innovation Policies?’, Cambridge Journal of Regions, Economy and Society (): –. Bailey, David, Helena Lenihan, and Alex de Ruyter () ‘A Cautionary Tale of Two Tigers: Industrial Policy “Lessons” from Ireland and Hungary’, Local Economy (): –. Bailey, David, Christos Pitelis, and Philip R. Tomlinson (b) ‘A Place-based Developmental Regional Industrial Strategy and/for Sustainable Capture of Co-created Value’, Cambridge Journal of Economics (): –. Baines, Tim, Ali Ziaee Bigdeli, Oscar F. Bustinza, Victor Ghuang Shi, James Baldwin, and Keith Ridgway () ‘Servitization: Revisiting the State-of-the-art and Research Priorities’, International Journal of Operations and Production Management (): –.

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 ,   ,   



Baldwin, Richard () The Great Convergence. Cambridge, MA: Harvard University Press. Bals, Lydia, Jon F. Kirchoff, and Kai Foerstl () ‘Exploring the Reshoring and Insourcing Decision-making Process: Toward an Agenda for Future Research’, Operations Management Research (–): –. Barca, Fabrizio () ‘An Agenda for a Reformed Cohesion Policy: A Place-based Approach to Meeting European Union Challenges and Expectations’. Available at http://www.interact-eu. net/downloads//An_Agenda_for_a_Reformed_Cohesion_Policy.pdf. Barrientos, Stefanie, Gary Gereffi, and Arianna Rossi () ‘Economic and Social Upgrading in Global Production Networks: A New Paradigm for a Changing World’, International Labour Review (–): –. Barzotto, Mariachiara, Carlo Corradini, Felicia Fai, Sandrine Labory, and Philip R. Tomlinson (a) Revitalising Lagging Regions: Smart Specialisation and Industry .. London: Routledge. Barzotto, Mariachiara, Carlo Corradini, Felicia Fai, Sandrine Labory, and Philip R. Tomlinson (b) ‘Enhancing Innovative Capabilities in Lagging Regions: An Extra-Regional Collaborative Approach to RIS’, Cambridge Journal of Regions, Economy and Society, (): –. Beer, Andrew, Sarah Ayres, Terry Clower, Fabian Faller, Alessandro Sancino, and Markku Sotarauta () ‘Place Leadership and Regional Economic Development: A Framework for Cross-regional Analysis’, Regional Studies (): –. doi:./.. Bianchi, Patrizio and Sandrine Labory () A Concrete Experiment of Industrial Policy for the Manufacturing Revolution. Cheltenham: Edward Elgar. Bianchi, Patrizio, Clemente Ruiz Durán, and Sandrine Labory (eds) () Transforming Industrial Policy for the Digital Age: Production, Territories and Structural Change. Cheltenham: Edward Elgar. Bustinza, Oscar F., Ferran Vendrell-Herrero, Emanuel Gomes, and Esteban Lafuente () ‘Product–Service Innovation and Performance: Unveiling the Complexities’, International Journal of Business Environment (): –. Chaminade, Cristina, Bent Åke Lundvall, and Shagufta Haneef () Advanced Introduction to National Innovation Systems. Cheltenham: Edward Elgar. Deloitte () Industry .. Challenges and Solutions for the Digital Transformation and Use of Exponential Technologies. Zurich: Deloitte. De Marchi Valenina, Elisa De Maria, and Gary Gereffi () Local Clusters in Global Value Chains. London: Routledge. De Propris, Lisa () ‘How the Fourth Industrial Revolution is Powering the Rise of Smart Manufacturing’, World Economic Forum. Available at https://www.weforum.org/ agenda///how-the-fourth-industrial-revolution-is-powering-the-rise-of-smartmanufacturing. De Propris, Lisa and David Bailey () ‘Disruptive Industry .+: Key Concepts’, in Lisa De Propris and David Bailey (eds) Industry . and Regional Transformations. London: Taylor and Francis. Deutsche Bank () ‘Industry .: Upgrading of Germany’s Industrial Capabilities on the Horizon’. Available at https://www.dbresearch.com/PROD/RPS_EN-PROD/ PROD/Industry__%A_Upgrading_of_Germany%E%%s_ industrial_ca.pdf. Dimache, Aurora and Thomas Roche () ‘A Decision Methodology to Support Servitisation of Manufacturing’, International Journal of Operations and Production Management (–): –.

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

     

Dunning, John H. () ‘The Eclectic Paradigm as an Envelope for Economic and Business Theories of MNE Activity’, International Business Review (): –. Ernst & Young () Reshoring Manufacturing—Time to Seize the Opportunity. London: Ernst & Young. European Commission () Industry .. Brussels: European Commission. European Commission () Industry  Report. Luxembourg: Publication Office of the European Union. Forbes () ‘The Trade War That Never Stops’. Available at https://www.forbes.com/sites/ stevehanke////the-trade-war-that-never-stops/#dcdd. Friedman, Thomas L. () The Lexus and the Olive Tree. New York: Farrar, Straus & Giroux. Gereffi, Gary () ‘International Trade and Industrial Upgrading in the Apparel Commodity Chain’, Journal of International Economics (): –. Gereffi, Gary () ‘Economic Upgrading in Global Value Chains’, in Stefano Ponte, Gary Gereffi, and Gale Raj-Reichert (eds) Handbook on Global Value Chains. Cheltenham: Edward Elgar, pp. –. Gereffi, Gary and Karina Fernandez-Stark () ‘Global Value Chain Analysis: A Primer’, Center on Globalization, Governance & Competitiveness (CGGC), Duke University, North Carolina, United States. Gereffi, Gary and Timothy Sturgeon () ‘Global-value-chain-oriented Industrial Policy: The Role of Emerging Economies’, in Deborah K. Elms and Patrick Lows (eds) Global Value Chains in a Changing World. Geneva: WTO, pp. –. Gereffi, Gary, John Humphrey, and Timothy Sturgeon () ‘The Governance of Global Value Chains’, Review of International Political Economy (): –. Gianelle, Carlo, Fabrizio Guzzo, and Krzysztof Mieszkowski () ‘Smart Specialisation: What Gets Lost in Translation from Concept to Practice? Regional Studies May: –. ./... Gray, John V., Gökçe Esenduran, Johnny M. Rungtusanatham, and Keith Skowronski () ‘Why in the World Did They Reshore? Examining Small to Medium-sized Manufacturer Decisions’, Journal of Operations Management : –. GTAI () ‘Industrie .. Smart Manufacturing for the Future’, German Trade and Investment. Available at https://www.deloitte.com/content/dam/Deloitte/ch/Documents/ manufacturing/ch-en-manufacturing-industry---.pdf. Gylling, Michael, Jussi Heikkilä, Kari Jussila, and Markku Saarinen () ‘Making Decisions on Offshore Outsourcing and Backshoring: A Case Study in the Bicycle Industry’, International Journal of Production Economics : . Harrison John, Mercedes Delgado, Ben Derudder, Isabelle Anguelovski, Sergio Montero, David Bailey, and Lisa De Propris () ‘Pushing Regional Studies beyond its Borders’, Regional Studies (): –. Humphrey, John and Hubert Schmitz, () ‘How Does Insertion in Global Value Chains Affect Upgrading in Industrial Clusters?’, Regional Studies (): –. Hymer, Stephen H. () The International Operations of National Firms: A Study of Direct Foreign Investment. Cambridge, MA: MIT Press. Kaplinsky, Rafael and Mike Morris () A Handbook for Value Chain Research. Brighton: Institute of Development Studies. Ketokivi, Mikko and Jyrki Ali-Yrkkö () ‘Unbundling R&D and Manufacturing: Postindustrial Myth or Economic Reality?’, Review of Policy Research (–): –.

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 ,   ,   



Kinkel, Steffen () ‘Industry . and Reshoring’, in Lisa De Propris and David Bailey (eds) Industry . and Regional Transformations. London: Taylor and Francis. Kinkel, Steffen and Spomenka Maloca () ‘Drivers and Antecedents of Manufacturing Offshoring and Backshoring: A German Perspective’, Journal of Purchasing & Supply Management (): –. Kinkel Steffen, Diletta Pegoraro, and Rosemary Coates () ‘Reshoring in the US and Europe’, in Lisa De Propris and David Bailey (eds) Industry . and Regional Transformations. London: Taylor and Francis. Kondratieff, Nikolai D. () ‘The Long Waves in Economic Life’, The Review of Economics and Statistics (): –. Lavissière, Alexandre, Tibor Mandják, and Laurent Fedi () ‘The Key Role of Infrastructure in Backshoring Operations: The Case of Free Zones’, Supply Chain Forum: An International Journal (): –. Lee, Joonkoo and Gary Gereffi () ‘Global Value Chains, Rising Power Firms and Economic and Social Upgrading’, Critical Perspectives on International Business (–): –. Livesey, Finbarr () From Global to Local. London: Profile Books. Livesey, Finbarr () ‘Unpacking the Possibilities of Deglobalisation’, Cambridge Journal of Regions, Economy and Society (): –. Martin Ron, Peter Tyler, Michael Storper, Emil Evenhuisd, and Ann Glasmeier () ‘Globalization at a Critical Conjuncture?’, Cambridge Journal of Regions, Economy and Society : –. Mathews, John A. () ‘Dragon Multinationals: New Players in st-century Globalization’, Asia Pacific Journal of Management : –. Mazzucato, Mariana () The Entrepreneurial State. London: Demos. Młody, Michal () ‘Backshoring in Light of the Concepts of Divestment and Deinternationalization: Similarities and Differences’, Entrepreneurial Business & Economics Review (): –. Mudambi, Ram () ‘Location, Control and Innovation in Knowledge-intensive Industries’, Journal of Economic Geography (): –. Navarro, Peter () ‘China : The Year of Reshoring to America?’, Financial Executive (): –. New York Times () ‘Trump’s Push to Bring Back Jobs to U.S. Shows Limited Results’,  August. OECD (a) The Next Production Revolution: Implications for Governments and Business. Paris: OECD. OECD (b) Global Value Chain Development Report : Measuring and Analyzing the Impact of GVCs on Economic Development. Paris: OECD. Pegoraro, Diletta, Lisa De Propris, and Agnieszka Chidlow () ‘De-globalisation, Value Chains and Reshoring’, in Lisa De Propris and David Bailey (eds) Industry . and Regional Transformations. London: Taylor and Francis. Pérez, Carlota () ‘Technological Revolutions and Techno-economic Paradigms’, Cambridge Journal of Economics (): –. Pisano, Gary P. and Willy C. Shih () ‘Restoring American Competitiveness’, Harvard Business Review (–): –. Porter, Michael E. () ‘The Competitive Advantage of Nations’, Harvard Business Review (): –.

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

     

Porter Michael E. and Claas Van der Linde () ‘Toward a New Conception of the Environment–Competitiveness Relationship’, Journal of Economic Perspective (): –. PWC () ‘Industry .: Building the Digital Enterprise’. Available at https://www.pwc. com/gx/en/industries/industries-./landing-page/industry-.-building-your-digitalenterprise-april-.pdf. Reshoring Institute () ‘Companies Case Studies’. Available at https://reshoringinstitute. org/reshoring-knowledge-library/reshoring-case-studies/. Rifkin, Jeremy () The Third Industrial Revolution: How Lateral Power is Transforming Energy, the Economy, and the World. New York: Palgrave Macmillan. Rodrik, Dani () One Economics, Many Recipes: Globalization, Institutions, and Economic Growth. Princeton, NJ: Princeton University Press. RSA (Regional Studies Association) () Place-based Leadership. Available at http://pla celeadershipnetwork.org/rsa-policy-expo-enabling-best-practice-in-place-based-policy. Scholte, Jan A. () Globalization: A Critical Introduction. New York: Macmillan. Schwab, Klaus () The Fourth Industrial Revolution. Geneva: World Economic Forum. Schwab, Klaus () Shaping the Future of the Fourth Industrial Revolution. London: Penguin Random House. Timmer Marcel P., Abdul A. Erumban, Bart Los, Robert Stehrer, and Gaaitzen J. de Vries () ‘Slicing up Global Value Chains’, Journal of Economic Perspectives (): –. Tomaney, John () Place-based Approaches to Regional Development: Global Trends and Australian Implications. Sydney: Australia Business Foundation. Van Bergeijk, Peter A. G. () ‘On the Brink of Deglobalisation . . . Again’, Cambridge Journal of Regions, Economy and Society : –. Vendrell-Herrero, Ferran and Oscar F. Bustinza () ‘Servitization in Europe’, in Lisa De Propris and David Bailey (eds) Industry . and Regional Transformations. London: Taylor and Francis.

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  .............................................................................................................

    .............................................................................................................

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        ......................................................................................................................

               A Long-term Perspective and Overview of Theoretical Arguments ......................................................................................................................

 . 

Wee felt it before in sense; but now wee know it by science. Edward Misselden, The Circle of Commerce or the Balance of Trade, London, Dawson for Nicholas Bourne (: )

. N P  C W E T: A S, D R,  P S R

.................................................................................................................................. I it is of some importance to gain a broader perspective of what has developed into ‘general truths’ of the neoclassical economics during the Cold War. The fact that David Ricardo’s theory of comparative advantage in international trade dates back to  conveys an impression that this principle has been ruling economic theory since then. It is also assumed that David Ricardo merely solidified the free-trade principles of Adam Smith. However, the following quote from the young Adam Smith shows how far away his principles were from the logic of comparative advantage and neo-liberalism: When the legislature establishes premiums and other encouragements to advance the linen or woollen manufactures, its conduct seldom proceeds from pure sympathy with the wearer of cheap or fine cloth, and much less from that with the manufacturer or merchant. The perfection of police (i.e. policy), the extension of

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

 . 

trade and manufactures, are noble and magnificent objects. The contemplation of them pleases us, and we are interested in whatever can tend to advance them. They make part of the great system of government, and the wheels of the political machine seem to move with more harmony and ease by means of them. (Smith,  [], vol. : ; my emphasis)¹

It is important to note that in his main work The Wealth of Nations (), Adam Smith refers to ‘the invisible hand’ only once: when private individuals prefer English goods to imported goods, which would happen around this time after about  years of England protecting its own manufacturing industry. But this is an argument for when to give up protectionism rather than against protectionism as a principle. It is also worth noticing that the term ‘free trade’ historically did not at all have the unequivocal meaning it is usually given today. In a  volume Edwin Seligman— Colombia University’s eminent economics professor and an avid collector of economics books—makes the following point as regards the meaning of ‘free trade’ in Edward Misselden’s work: Free trade . . . denoted in those days something very different from what it signifies today. It did not mean freedom to import goods without the payment of duty. On the contrary . . . freedom to export goods as over against the companies which possessed a monopoly of trade, like the East India Company . . . Almost all free traders were in fact what we should today call protectionists. (Seligman, : ix)

Cold War economics—the theories that stood victorious after the fall of the Berlin Wall—had its roots in David Ricardo in . However, recent n-gram technology has made it possible to illustrate how David Ricardo and his theory of ‘comparative advantage’ were virtually neglected until Paul Samuelson brought them into the core of economics at the start of the Cold War with two articles in The Economic Journal in  and . Communism advanced under the utopian slogan ‘from each according to his ability, to each according to his needs’. With his renewed interpretation of David Ricardo, Paul Samuelson produced a counter-utopia: under the standard assumptions of neoclassical economics free trade would produce a tendency towards factor price ¹ A more complete quote from Adam Smith (): The same principle, the same love of system, the same regard to the beauty of order . . . frequently serves to recommend those institutions which tend to promote the public welfare . . . When the legislature establishes premiums and other encouragements to advance the linen or woollen manufactures, its conduct seldom proceeds from pure sympathy with the wearer of cheap or fine cloth, and much less from that with the manufacturer or merchant. The perfection of police [i.e. policy], the extension of trade and manufactures, are noble and magnificent objects. The contemplation of them pleases us, and we are interested in whatever can tend to advance them. They make part of the great system of government, and the wheels of the political machine seem to move with more harmony and ease by means of them. We take pleasure in beholding the perfection of so beautiful and grand a system, and we are uneasy till we remove any obstruction that can in the least disturb or encumber the regularity of its motions. (Smith,  [], vol. : ; my emphasis)

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 -    



equalization: the prices of labour and capital would tend to equalize across the planet. This became the ‘noble lie’ of neoclassical economics and neo-liberalism and appeared to make industrial policy superfluous. The n-grams below show how Cold War economics brought David Ricardo out of the shadows. Compared to other English economists and economic philosophers—such as father and son James and John Stuart Mill—David Ricardo had indeed been much less important during the first  years after his  theory (Figures . and .). On the theoretical level, the Cold War (‒) was fought between two cosmopolitical theories. Neither in neoclassical/neo-liberal theory nor in communism was the nation state a unit of analysis. In both theories the nation state was not seen as having a place. Neoclassical economics is built on methodological individualism—no state needed—and also in Marxism the state was supposed to wither away as obsolete after a brief ‘dictatorship of the proletariat’. In practice, of course, it was not the state but the rights of individuals that withered away under communism. 0.000180% 0.000160% 0.000140% 0.000120% 0.000100%

John Stuart Mill

0.000080% 0.000060% 0.000040% James Mill

0.000020%

David Ricardo

0.000000% 1820

1830

1840

1850

1860

1870

1880

1890

1900

1910

 . The frequency of ‘David Ricardo’ (in English) during the first  years after the  publication of his main work, Principles of Economics, compared to that of two other, then much more famous, English economists Source: Author and Google N-Gram.

0.000240% 0.000220% 0.000200% 0.000180% 0.000160% 0.000140% 0.000120%

comparative advantage

0.000100% 0.000080% 0.000060% 0.000040% 0.000020% 0.000000% 1820

1840

1860

1880

1900

1920

1940

1960

1980

2000

 . Frequency of the term ‘comparative advantage’ (in English) from  until today Note: As is clearly shown, the term was very little used for the first 100 years of its existence, but its use started with the birth of the planned economy and exploded with the start of the Cold War in the late 1940s. Source: Author and Google N-Gram.

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

 . 

Both political extremes were far too abstract to be practical guides to human societies. The implicit conclusion in , however, was that because communism had been proven to be wrong, neo-liberalism—the other political extreme—had to be perfect. This belief has led to increasing poverty in many countries. A key economist in the historical tradition in which this chapter is written, Gustav Schmoller (‒), clearly saw that both political extremes were unfit for practical purposes. In his  inaugural speech as Rector of the University of Berlin, Schmoller expressed the hope that he had seen the end of the two ideological extremes, Manchester Liberalism (today’s neo-liberalism) and communism. His characterization of both these ideologies was harsh: ‘the naïve optimism of “laissez-faire” and the childish and frivolous appeal to revolution, the naïve hope that the tyranny of the proletariat would lead to world happiness, increasingly showed their real nature, they were twins of an ahistorical rationalism’ (Schmoller, , my translation and emphasis). In practice, the ideological extremes of ‘the irrational twins’ opened up a wide spectrum of possible economic policies. In Western Europe, Germany’s soziale Marktwirtschaft (social market economy) (Müller-Armack, )² and Sweden’s Middle Way (Childs, ) were successful models navigating the broad spectrum of opportunities between the ‘irrational twins’. After the  fall of the Berlin Wall and with the rule of the Washington Consensus, these ‘middle ways’ were in practice outlawed.

. T H R  I P T

.................................................................................................................................. From manufacturing you may expect the two greatest ills of humanity, superstition and slavery, to be healed. Ferdinando Galiani (–), Italian economist

More than two decades ago, when I was working on another paper on the history of economic policy, David Landes, the eminent Harvard economic historian, gave me a serious warning: be careful, if not you are likely to end up with Adam and Eve. The point is well taken: it is possible to argue that in his Poroi of   (also called Ways and Means), Xenophon, arguing that a city’s economic problems could be improved by increasing the size of the population, could be seen as understanding increasing returns or economies of scale. In order to avoid the Adam and Eve problem, the story told in this chapter starts in the s, with practical policies, and with a systemic theoretical understanding that essentially starts in  with Giovanni Botero’s bestselling On the Greatnesse of Cities (Botero, ; Figure .),³ relatively unknown today. ² Economist Alfred Müller-Armack used the term in a  book, also defining it as a Third Way, but it became popular later. ³ However, a modern version is found in Symcox ().

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 -    



One important note on earlier European history, though: if we allow US economic historian Richard Goldthwaite to be our guide, the history of the rise of European civilization was in fact a process of import substitution. From the twelfth century onwards manufactured goods which had previously been imported from the Levant started to be produced in Europe. At the core of what is generally referred to as ‘the commercial revolution’ was the growth of an industrial sector, Goldthwaite argues: Initially Europeans had an unfavourable balance of payment . . . and initially they made up the difference through piracy and plundering, but above all through the export of silver and gold . . . With the growth and development of the European economy, the Italians steadily improved their situation. They began to produce for themselves the manufactured goods they had been importing, and by the fifteenth century they had gone beyond import substitution and were exporting these very goods to the Muslim world. (Goldthwaite, : )

This was later the logic of all European countries that have succeeded in upgrading their industrial sector, starting with England in the s up until and including classical development economics and the Marshall Plan.⁴ Only during very brief periods—the last of them being from around  until about now—has this principle of creating wealth through structural upgrading of national productive sectors been abandoned. Just as industrial companies almost by definition initially go through several years of loss, and need ‘subsidies’ from the owners, so whole national systems also need years of subsidies and protection before they are profitable. This period of protection—which the great liberal John Stuart Mill () called infant industry protection—is still needed. Old economic policies were carried out with varying degrees of understanding of the underlying principles. These policies were, in our meaning of the word, not based on what we would normally call scientific analysis, but on ‘clues’, on a mode of inference called abduction—or phronesis, Aristotle’s third form of knowledge (Reinert and Daastøl, ).⁵ This tradition is continued by the Italian philosopher Giambattista Vico (‒), in the US philosophical tradition of C. S. Pierce and in economics in Nicholas Kaldor’s ‘stylized facts’. According to Pierce: ‘[Induction] can never originate any idea whatever. No more can deduction. All the ideas of science come to it by the way of abduction. Abduction consists of studying facts and devising a theory to explain them. Its only justification is that if we are ever to understand things at all, it must be in that way’ (Lawson, : –).⁶ Pierce here describes the role played by the formulation of hypotheses as the fundamental element in the creation of new knowledge. This reasoning is also in line with the philosophy that lies at the root of the German historical school of economics, in the eighteenth-century philosophers Gottfried von Leibniz and Christian Wolff.

⁴ The only exception to this appears to be the Dutch Republic. On this see Reinert (a). ⁵ For a more general discussion of these issues, see Reinert and Daastøl (). ⁶ Pierce (: ). Quoted in Lawson (: ).

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 . 

No doubt most historical arguments have their points, but history shows that it has also been possible ‘to be right for the wrong reason’. We shall try to illustrate how the creation of industrial policy was generated through abductive reasoning with a parallel from the history of medicine. From the twelfth century sailors in the Mediterranean used lemons to prevent scurvy (Villner, : –). This was a very effective policy. However, the explanation as to why this policy worked only appeared in the early twentieth century with the discovery of Vitamin C (Mervin, : –). In the meantime, acidity had been seen as the curative element, which led to disastrous experiments with vinegar instead of citrus fruits. Likewise, we would claim that it is entirely possible to establish good economic policies for a time, without fully understanding the factors involved. For example, identifying ‘progress’, or the ability to pay more taxes, with the use of machinery in an increasing number of industries would result in a beneficial public policy, even if the causal relationship between the use of machinery and wealth were not clearly established, or had been ‘unlearned’. The intuitive abduction often precedes what we would think of as a more ‘scientific’ type of knowledge. This view that abduction anticipates ‘science’ was expressed in the above quote from English economist Edward Misselden—an economist who was heavily influenced by Giovanni Botero—in : ‘Wee felt it before in sense, but now wee know it by science.’ England is an example of a country which appears to have created an industrial policy without much theory, other than a clear recognition of what at Harvard Business School used to be called ‘we are in the wrong business’. In the fifteenth century, England was a poor nation, heavily indebted to her Italian bankers. Her main export was wool. But over a relatively short period, England went from being a poor nation on the periphery of Europe to being the leading nation of the world—from being a poor farming country to possessing a global empire on which the sun never set. There are different versions of the story as to how this happened. Probably a policy originally intended to increase national revenues—a tax on the export of raw wool— ended up having the unintended by-product of creating a domestic industry of woollen cloth. The story is likely to have started earlier, but let us look at the version of Daniel Defoe—the polymath historian best known as the author of Robinson Crusoe—who described the English strategy retrospectively in his book Plan of English Commerce in  (Defoe, ). Henry VII, who came to power in , had grown up in exile in Burgundy, where English wool was being spun into cloth. The wealth he observed there contrasted sharply with the poverty he later found in England. But, the Prince observed, the wealth in Burgundy depended totally on the import of English raw materials: wool and the Fuller’s earth used to clean it. When he came to the throne of England, Henry employed the antiRicardian logic which during subsequent centuries dominated, not only in England, but also on the continent: don’t accept your comparative advantage, shape it. Manufacturers are rich, producers of raw materials are poor. Therefore, to get rich and develop the country, we must promote the production of manufactures. Selling manufactures is

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 -    



‘good’ trade—in today’s language, it makes us competitive—while selling raw materials is ‘bad’ trade (King, , vol. I: ). The Tudor strategy, which started with King Henry, was to bring England into the wealth-creating downstream activities in wool manufacturing that he had observed abroad. Practice preceded theory, which is not uncommon when historical circumstances conspire to make certain facts, if not the deeper economic mechanisms at work or the theory explaining them, palpably visible, along with obvious policy measures. England’s economic growth (her economy had been essentially static, like all premodern agriculture societies, for centuries before this) started by observing the economic structure of richer countries and emulating—copying and trying to improve upon—their economic structure (Reinert, b). This meant pushing into manufacturing, the quintessential (if today not the only) home of ‘advantageous’ economic activities, the key to sustained growth. The English strategy was gradual, and started with import substitution, which to this day is a common first move in development plans. In , tariffs on cloth were increased, and local cloth manufacturing was encouraged. The Crown paid for skilled foreign workers to be brought in, and businessmen were paid bounties (in modern terms, subsidies) for establishing textile manufacturing firms. And when sufficient manufacturing capacity had finally been achieved to process all domestic wool production, England prohibited the export of raw wool. During the next century, in the reign of Elizabeth I, the death penalty was introduced for the export of raw wool from England. See Figure . for an example of similar harsh punishments for sins against ‘the cult of added value’ in the Republic of Venice.

. T K  W  U S C  A V  R M   L D  L: G B ()

.................................................................................................................................. I first met practical industrial policy as a young student and assistant to the professor of Spanish at the Latin American Institute at the University of St. Gallen in Switzerland. In , the Swiss Federal Technical Cooperation, in cooperation with UNCTAD in Geneva, organized an export-promotion training course for representatives of Spanishspeaking South American nations. I was recruited to travel to Latin America to select the candidates who had been presented by the local governments, and also to organize the part of the course that took place in St. Gallen in the summer of . The core idea of the course was to promote Latin American exports with higher value than the traditional raw materials. In cooperation with the local Swiss embassies,

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

 . 

my task was also to pick one product from each country on which the participants, in addition to theoretical courses, should do practical market research during their two months’ stay in St. Gallen and Geneva. Although the idea was completely in line with classical development economics, as it was still practised at the time, neither I—nor probably anyone else—had any idea that this idea of added value had been at the very core of theories explaining the differences in national incomes. Value added had been the key explanation for what created wealth in the few cities of wealth in Europe—like Amsterdam, Florence, and Venice—since Giovanni Botero’s work On the Greatness of Cities (Botero, ). By , Botero’s book had been published in around forty-two editions in all the important European languages,⁷ and his thoughts were also spread in German-speaking areas by Veit Ludwig von Seckendorff ’s  book on The German Principality (Seckendorff, )⁸—which remained continuously in print for  years—and in English through the works of Francis Bacon.⁹ Two apparently different economic traditions, cameralism and mercantilism, seem to have grown out of the extremely widely diffused works of Giovanni Botero (–)¹⁰ as a common platform and point of reference. Botero, in turn, built on two much older traditions: his work Ragion di Stato—of which On the Greatness of Cities is part—satisfied the oldest tradition in economic policy advice, the tradition of Fürstenspiegel, a kind of owner’s manual to the numerous small states of Europe.¹¹ Botero’s other main work, Relazioni Universali (Botero, ) satisfied another very old tradition: the need for surveys and the fact-finding missions’ quest for geographical, cultural, and anthropological knowledge.¹² All in all, at the time when the knowledge of the whole world and its cultures became codifiable, Giovanni Botero provided an unusually complete range of social sciences.¹³ It is worth noting that in contrast to the many utopias of the period, Botero’s reasoning was based on observations of history and facts. In his work he clearly distances himself from ‘bullionism’—the idea that a nation’s wealth consists in the amount of precious metals owned—of which mercantilism is sometimes accused. ⁷ Reinert et al. () and Reinert and Reinert (). ⁸ Reinert (). ⁹ Trace () documents Botero’s influence on Bacon and other English authors. ¹⁰ See Firpo (, ). ¹¹ The Fürstenspiegel (‘Kings’ Mirror’) literature, bringing advice to the rulers on how to govern, can be seen as part of this broader tradition. The Sachsenspiegel, from German Saxony, about , is the best known, but even in peripheral Norway, this tradition goes back to a text from around : Konungs skuggsjá (Old Norse for ‘King’s mirror’). ¹² The tradition of accurate country surveys and descriptions, dating back to De magnalibus urbis mediolani of Bonvesin de la Riva () and later works also on the Florentine state. Such descriptive surveys were the purpose of costly and extensive visitas in the Spanish provinces of the New World, some of which have been republished (Ortiz de Zúñiga, /). ¹³ Of course, Botero made mistakes, such as when his sources were not correct. The remarkable thing, however, is the acuteness of his analysis of generalized wealth and policy prescriptions that came to typify the centuries of economics that go under the name of cameralism and mercantilism. Botero was involved in the process of making the Vatican’s list of prohibited books, which in his day also comprised the works of Jean Bodin (–). This position clearly gave him access to much new material.

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 -    



 . The cover of the first edition of the book that laid the earliest foundations for a theory of industrial policy: Botero’s  volume Note: Botero (1589) was translated into all important European languages—the first translations in Germany were from Italian into Latin—and the book reached a record of forty-two editions between 1589 and 1671. Source: Reinert family library.

Giovanni Botero was born in the small town of Bene Vagienna in the province of Cuneo in the Italian Piedmont region. As a Jesuit, he was keenly interested in nonEuropean cultures. From the point of view of now long-standing Western Eurocentrism, the ability of the Jesuits to engage in two-way cultural communication reminds us

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

 . 

that Eurocentrism is not necessarily a ‘natural’ state of affairs. Jesuit Matteo Ricci (–), a contemporary of Botero, ventured with a small group to China, where he translated not only Christian and Western scientific texts into Chinese, but also Chinese texts into Latin. By entering foreign cultures—from the Chinese to the Guaraní in South America—Jesuit travellers also played the role of anthropologists. As one observer says, Botero ‘brought together an immense mass of geographical and anthropological information, which he tried to organize according to broad methodological categories (like “resources,” “government” and “religion”)’ (Rubies, : ). Little appears to unite Sir Walter Raleigh (–), Francis Bacon (–), utopian Tommaso Campanella (–), English economist Edward Misselden (–), Spanish economist Gerónimo de Uztáriz (–) and Swedish technologist and economist Christopher Polhem (–). But one thing does: they all convey key insights found originally in Giovanni Botero, but following the practice of the time they do not quote him or anyone else as to the origins of these insights. As mentioned, the work of the first German bestseller, Veit von Seckendorff (–) is clearly also very much influenced by Botero (Reinert, ). There are still thirty editions of Botero’s works (mainly uncatalogued) from the time of Seckendorff ’s librarianship in the Gotha Library, which he formed for Ernest the Pious (Ernst der Fromme) of Sachsen-Gotha-Altenburg, and Botero was on the reading list Seckendorff made for the education of princes. The large number of translations of Botero’s works testify to his strong influence on the European seventeenth-century zeitgeist (Reinert and Reinert, ). Botero argues that one of the reasons for the economic superiority of cities over the countryside is that the ability to invent new things is much greater there than in the countryside. Here we find an early trace of ‘Schumpeterian’ thinking, which was followed up by Francis Bacon’s  essay ‘Of Innovations’.¹⁴ Botero’s Ragion di Stato () was the first modern economics bestseller. In English, Ragion di Stato came to be called Reason of State and in German Staatsräson. In his  work on Staatsräson, Friedrich Meinecke mentions Botero’s many followers and the ‘true catacombs of forgotten literature’ which follow in Botero’s path.¹⁵ (A new translation of Botero’s The Cause of the Greatnesse of Cities has an excellent introduction by Geoffrey Symcox.)¹⁶ The understanding that grew out of Botero’s work was that only in barren areas lacking natural resources and with limited possibilities for food production—but in favourable geographical positions such as Venice and Amsterdam—would economic development tend to arise ‘naturally’. In virtually all countries, heavy-handed government

¹⁴ Bacon’s () Essays represent the transition from innovations being a threat to the status quo and therefore doubtful, as when Roger Bacon was arrested in Oxford around  for ‘suspicious innovations’, into something desirable. Before  Bacon’s Essays had been translated into Dutch, French, German, Spanish, and Swedish. ¹⁵ ‘Wahre Katakomben von vergessener Literatur’ (Meinecke, : n). ¹⁶ Symcox ().

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 -    



policies were required during the transition from diminishing-returns activities (agriculture) to increasing-returns activities (manufacturing), as they were identified by Antonio Serra in  (S. Reinert, ); or from ‘natural activities’ to ‘artificial activities’, to use the later terminology of Thomas Mun (Mun, ). This was the essence of the thinking that Botero’s influence turned into the economic mainstream at the time. What Venice and the Dutch Republic had achieved—rather than the policies of Venice and the Dutch Republic—was the object of attention of foreign economists and foreign rulers alike. Edward Misselden argued in  that it was necessary to understand the difference between heaps of stones and logs and a house. Between them was the added value of human knowledge and skills. This rings a bell when reading Botero, the first English translation of which was in :¹⁷ Some will aske me; whether Fertilitie of Land, or Industrie of Man, importeth more to make a place Great, or populous? Industrie, assuredly. First because Manufactures framed by the skilfull hand of Man, are more in number,¹⁸ and price,¹⁹ than things produced by Nature: For Nature giveth matter, and subject: but the Curiositie and Art of Man addeth unspeakable varietie of formes. Wool, from Nature, is a rude and simple Commoditie: What fair things, how various, and infinite, doth Art make out of it?²⁰ Compare the Marbles, with the Statues, Colossuses, Columns, Borders, and infinite other Labours, taken. Compare the Timber, with the Galleys, Galleons, Vessels of many sorts, both of Warre, Burthen, and Pleasure: Compare also the Timber, with the Statues, the Furnitures for Building, and other things innumerable, which are built with the Plane, Chesill, and Turners-Wheele. Compare the Colours with the Pictures.²¹

Botero’s basic ideas around the geographical clustering of economic activities leading to progress have had many modern followers. Although geography was obviously present in other economists, in relatively modern times it was not until the publication of Johann Heinrich von Thünen’s first volume of Der Isolirte (sic) Staat (The Isolated State) (von Thünen, )²² that location theory based around a core industrial city— as Botero had—was rediscovered. Von Thünen (‒) also places the industrial city at the geographical and economic core of the modern state (Figure .). Von Thünen drew a map of civilized society with four concentric circles around a core of increasing returns activities—the city. Moving outwards from the city core, the use of capital and advanced skills gradually decreases and the use of nature gradually ¹⁷ The second English translation is clearer on this and is used here (Botero, : ‒). ¹⁸ That is, greater diversity of products. ¹⁹ Presumably this indicates that these products command a higher price and therefore a higher profit for the producer. Today we could say that manufactured goods are produced under higher barriers to entry than most raw materials, and under increasing rather than diminishing returns. Both these factors would produce a higher profit margin for manufactured goods than for raw materials. ²⁰ The second English translation is clearer on this and is used here (Botero, : ‒). ²¹ Botero (: ‒). ²² von Thünen ().

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 . An example of the practical consequences of ‘the cult of value added’ Source: Contemporary Venetian broadside. Reinert family collection.

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 -    

Modified Conditions

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Isolated State



Central city Navigable river Market gardening and milk production Firewood and lumber production Crop farming without fallow Crop farming, fallow and pasture Three-field system Livestock farming

 . von Thünen’s map of a modern state, with the industrial city at its core Source: von Thünen (1826).

increases. Near the city the most perishable products are produced, such as dairy products, vegetables, and fruit; grain for bread is produced further out, and in the periphery there is hunting in the wilderness. Economists today have rediscovered von Thünen’s approach to economic geography, but many miss the crucial point he stresses, which stands on the lines of the first page of Der Isolirte Staat: ‘Man denke sich eine sehr große Stadt in der Mitte einer fruchtbaren Ebene gelegen’; a very big city in the middle of a fertile plain is at the core of society. As with Botero, here also the city is at the core of the system. It is worth noticing that already very early on economists distinguished between manufacturing cities (like Venice or Milan) from which wealth spread, and administrative cities (the typical example was Madrid) that played more of a parasitic role. Since von Thünen was a farmer and mainly interested in the improvement of agriculture, he does not pay too much attention to the factories in the city, even though they are also mentioned in his book. Von Thünen did not argue against the accepted knowledge of the time that a state needed manufacturing industry, and that this industry needed tariff protection. Underlying what happened in von Thünen’s outer circles was a development machine at the core of the concentric circles—the urban increasing-returns industries (manufacturing)—which, for a time at least, needed targeting, nurturing, and protecting. In other words, the presence and state of development

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

 . 

of the core city would also determine the standard of living in the rest of the country, in these outer circles. In von Thünen’s map the most ‘modern’ sector—manufacturing—formed the city core, and the most ‘backward’ sector—hunting and gathering—formed the periphery furthest from the city. Moving outwards away from the city, the use of nature as a factor of production increases and the use of capital decreases. Only the city will have authentic increasing returns, free from nature’s flimsy cyclicality and supply of resources (land, minerals) of different qualities. As one moves from the city towards the periphery, man-made comparative advantage (subject to increasing returns) gradually diminishes and nature-made comparative advantage (subject to diminishing returns) increases. As we move outwards in the circles, the carrying capacity of the land in terms of population also diminishes. The importance of the linkages and synergies for agricultural development, seeing the benefits accruing to agriculture from the proximity of manufacturing, was not uncommon in eighteenth-century economics: ‘Husbandry . . . is never more effectually encouraged than by the increase of manufactures,’ says David Hume in his History of England (). Von Thünen’s model pictures all the stages of development inside one nation state, one labour market, one school and university system, and one social security system. The synergies that David Hume points to are partly the result of an equal access to basic institutions and government services accruing to the ‘hunters’ in the outermost circle as well as to the city dwellers. The local city market does to national agriculture what an international market can never do. Proximity to a city in the same labour market, rather than abroad, assures employment for the second and third son on the farm. The wage pressure from the city activities makes labour more expensive in the countryside, allowing for technological change that would never be profitable with low wage rates. The proximity to the city gives access to advanced technology and expertise that a rural-only nation would never achieve. All in all, von Thünen’s model provides a useful picture for development as a synergy between town and countryside. Late in the nineteenth century, in his Principles of Economics (Marshall, ) and in an earlier work (Marshall and Marshall, ), Alfred Marshall introduces ‘industrial districts’. In , Alfred Weber publishes Über den Standort der Industrie (Theory of the Location of Industries). After the Second World War, Botero’s ideas of geographybased economic agglomerations appear in August Lösch’s The Economics of Location: A Pioneer Book in the Relations between Economic Goods and Geography (), with French economist François Perroux as ‘growth poles’ (Perroux, ) and with Harvard Business School’s Michael Porter as ‘clusters’ (Porter, ). In Italy, Giacomo Becattini re-introduced ‘Marshallian industrial districts’, and ‘The Third Italy’—the economic power of the many small and medium-sized enterprises in Central Italy— generated much attention. In the Third World, the importance Albert Hirschman gave to ‘linkages’ also reflects this way of thinking. It is worth noticing that some of these ideas had clear Schumpeterian influences. August Lösch was a student of Schumpeter in Bonn, and François Perroux wrote a

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 -    



-page introduction to the French translation of Schumpeter’s Theory of Economic Development ().

. I R: F A S ()  A M ()  P K ()

.................................................................................................................................. I apprehend (the elimination of Diminishing Returns) to be not only an error, but the most serious one, to be found in the whole field of political economy. The question is more important and fundamental than any other; it involves the whole subject of the causes of poverty; . . . and unless this matter be thoroughly understood, it is to no purpose proceeding any further in our inquiry. John Stuart Mill, Principles of Political Economy ()

Joseph Schumpeter gave Antonio Serra the honour of having been ‘the first to compose a scientific treatise . . . on economic principles and policy’ (Schumpeter, : ). Schumpeter’s succinct description of Serra’s work confirms the author’s anti-bullionist bias, the normal criticism against mercantilists: Its chief merit does not consist in his having explained the outflow of gold and silver from the Neapolitan Kingdom by the state of the balance of payments but in the fact that he did not stop there but went on to explain the latter by a general analysis of the conditions that determine the state of an economic organism. Essentially, the treatise is about the factors on which depend the abundance not of money but of commodities—natural resources, quality of the people, the development of industry and trade, the efficiency of government—the implication being that if the economic process as a whole functions properly, the monetary element will take care of itself and not require any specific therapy.²³

Regardless whether this long theoretical tradition which dominated Europe until the late eighteenth century be labelled mercantilist, Colbertist, or cameralist, Botero’s narratives and Serra’s theories in a sense laid the foundations for all three schools by establishing two crucial dichotomies in economics. The taxonomies Serra established are important for understanding the wealth and poverty of nations, and indeed provide a continuing key to what his contemporaries called buon governo, or good government (Patalano and S. Reinert, ).²⁴

²³ Schumpeter (: ). Note the term ‘economic organism’, which indicates a type of economic theory based on biological metaphors, rather than on metaphors from physics as is present-day theory. ²⁴ See Patalano and S. Reinert ().

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

 . 

Serra’s two dichotomies, I will argue, were in the recent past still part and parcel of all three dominant ideologies and their economic policies in the s,²⁵ but were subsequently lost with the formalization of modern neoclassical economics, and are conspicuously absent in the rather superficial discussion of good governance presented by the Washington Institutions today. The first is a dichotomy separating economic activities subject to increasing returns from those subject to diminishing returns. Putting ‘manufacturing’ in a different category from ‘raw materials’ from the point of view of policymaking had already been the core element of the English Tudor strategy from , promoting woollen manufactures at the expense of the export of raw wool by slowly building up the export duties on raw wool. (For a thorough discussion see Reinert, .) There had been scattered references to the wisdom of such practices,²⁶ but what Giovanni Botero did in his volume was to elaborate the vision of the role of manufacturing, the insight that civilization was based on adding knowledge and value to nature’s raw material, into a full-fledged theory of economic development. In Botero’s volume the degree of economic and societal development manifested itself as the ability of a city to hold the maximum number of inhabitants in satisfactory conditions. This again was the result of the number of different professions that were exercised in the city: in other words, the degree of division of labour—the degree of complexity—would determine the wealth of a city. This argument has recently been convincingly recreated and proven (Hausmann, Hidalgo et al., ). Botero explained the mechanisms, but Serra’s big contribution was to explain why. He did so by highlighting the key difference between the production of raw materials and manufactured goods, that is, what happens to the development of costs as production is increased. In manufacturing there were increasing returns, and the synergies of the multitude of artisanal and manufacturing activities, each of them subject to increasing returns, produced the synergies, linkages, and cumulative causations that Botero and Serra saw as the main factor attracting so many people to the city-states that had specialized in manufacturing. In the first edition of his Principles of Economics, Alfred Marshall, the founder of neoclassical economics, emphasizes the crucial importance of diminishing returns: ‘The tendency to a Diminishing Return was the cause of Abraham’s parting from Lot,²⁷ and of most of the migrations of which history tells’ (Marshall, : ). Today the migration experienced in Europe is from nations dominated by diminishingreturns activities (for example, Eritrea) to nations where increasing-returns activities dominate (for example, Holland). The second dichotomy is that separating the financial sector from the real economy. As already mentioned, this dichotomy is of course much older than Serra’s work. ²⁵ I am here referring to communism, fascism, and Roosevelt’s New Deal. ²⁶ Luis Ortiz’s  memorandum to King Philip II of Spain is a famous example. ²⁷ Marshall’s footnote here: ‘The land was not able to bear them that they might dwell together; for their substance was great so that they could not dwell together.’ Genesis xiii.

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 -    



An academic expression of the problems that may arise when the financial and monetary spheres decouple hails back at least to Nicolaus Oresme (c.–)²⁸ and to the Bible. This dichotomy is not there in Botero’s Greatness of Cities—which concentrates on the real economy—but it is very much there in Antonio Serra’s discussion with his contemporary MarcAntonio de Santis on how to deal with the outflow of money from the kingdom.²⁹ De Santis was of the opinion that the lack of money in the kingdom was due to the excessively high level of the exchange rate. On the basis of his theory, several measures had been introduced to manage the rate of exchange and limit the export of metallic money, without positive results. Serra, on the other hand, starts by noting that there are countries with no natural supplies of metals from domestic mines that nevertheless manage to have an abundance of money. In other words, Serra asks: why on earth do the gold and silver which flow into Spain from the New World end up accumulating in places like Venice, which have no mines and raw materials at all? Serra’s reply was based on Botero’s analysis of what attracted people and resources to some cities and not to others, above all the abundance of different manufacturing industries. In other words, the solution to the problems posed by dichotomy two—the conflict between the financial and the real economy—lies in observing the insights emanating from dichotomy one: money will leave the cities and countries with no increasing-returns activities, being attracted to cities with manufacturing and increasing returns. In Schumpeter’s quote above, he emphasizes Serra putting the real economy centre stage: ‘if the economic process as a whole functions properly, the monetary element will take care of itself and not require any specific therapy.’³⁰ In fact, digging deeper into Serra’s arguments, we can argue with him that de Santis’s fiddling with monetary variables—as long as these monetary variables did not positively affect the health of the real economy—were not only completely in vain, but potentially destructive to the real economy. The present tragedy of Greece inside the European Union carries with it the same type of discussion as that between Messrs de Santis and Serra more than  years ago. The jury is still out on whether the policies carried out from the start of the financial crisis until the present () by the Federal Reserve—and even more so those of Mario Draghi and the European Central Bank—again will justify Antonio Serra’s warning: fiddling around with financial variables, which in reality do not improve conditions in the real economy, will not help, but will probably worsen the situation. Schumpeter saw the need for economic ‘cold showers’ provided by financial crises, because unproductive capital lost its value and the system was reset with a clean slate. From that point of view, we can ask whether Draghi, by providing more liquidity and more debt, is currently preventing Europe from taking the necessary ‘shower’, liberating itself from ²⁸ Oresme (). For a recent discussion see Schefold (/). ²⁹ This was a problem of the whole of Spain, not only in the Spanish Viceroyalty of Naples where the discussions between Serra and de Santis took place. ³⁰ Schumpeter (: ).

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

 . 

a huge debt overhang and kick-starting the real economy. Increasing debt and demand contraction in vicious circles—as a result of austerity policies—seem to prevent the virtuous circles that originate in Serra’s increasing returns to scale (that is, falling unit costs as the volume of production increases).³¹ The key factor being put back into trade theory is, again, increasing returns, and the key person in the process of rediscovery is MIT’s Paul Krugman. Krugman correctly observes that economic theory ‘has followed the perceived line of least mathematical resistance’.³² His explanation is that the reason scale effects were excluded was that the profession was unable to express these mathematically. Starting in , Krugman published a series of articles introducing increasing returns in international trade theory. His  article (Krugman, ) models a world where an initial discrepancy in capital/labour ratio exists between two countries or groups of countries. A period of increasing international trade follows, where only the industrial sector works under increasing returns to scale. The result of this is a world divided into two groups, a rich industrialized centre and a poor underdeveloped periphery. In this article, one of the very few in which he includes both increasing and diminishing returns, Krugman, a later recipient of the Nobel Memorial Prize in Economic Sciences, picks up a model of the increasing/diminishing returns dichotomy from US economist Frank Graham () and also recognizes the result of this mechanism: ‘This might mean that in addition to exporting capital, the industrial region might, in the second stage of growth, begin importing labour—a point also noted both by John Hobson and by the same Vladimir Lenin.’ Krugman’s references here place the increasing-vs.-diminishing-returns dichotomy in the context of works on imperialism by Hobson () and Lenin (). In the same article, Krugman also refers to development economics and to Myrdal, Frank, Baran, and Wallerstein. This breakthrough in international trade theory was the result of using models originating in the study of imperfectly competitive markets in the field of industrial economics. Krugman inadvertently opened a Pandora’s box, where international markets are no longer fully competitive, and where countries may grow poorer in the presence of free trade than under autarky. Paradoxically, the wave of Reaganomics freemarket policies which hit the developing countries in the early s coincided with the first proof of neoclassical trade theorists that government intervention really could improve the free-trade situation of a poor country. After the early s, however, Krugman seems not to have used models with both increasing and diminishing returns. Schumpeter had referred to using overly abstract models with limited practical relevance such as Ricardian trade theory as ‘the Ricardian Vice’. To this I added the

³¹ It should be noted that empirically it may be difficult to distinguish the effects of increasing returns to scale from the effects of technological change, simply because advanced techniques only exist in largescale production (Henry Ford’s technology did not exist in small-scale production). Schumpeter therefore suggests using the term ‘historical increasing returns’ to cover the combined effects of scale and technological change (Schumpeter, : ). ³² Krugman (: ).

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 -    



concept of ‘the Krugmanian Vice’: having much more relevant theory but refusing to apply it in practical economic policy. The core of nineteenth-century protectionism is exactly what Krugman points out: by protecting the national market for national industries the market was extended, because the increasing returns which accrued to new industries more than outweighed the initial increase in price caused by the protection. A higher initial price for industrial goods was traded off for an even higher increase in real wages and profits in the protecting nation—a phenomenon which is inexplicable without the existence of imperfect competition and/or increasing returns. The worker as a wage earner would be more than compensated for the initially higher prices that the same person would have to pay as a consumer.

. H E A D, L C,   S  T C ..................................................................................................................................

Figure . ranks the development of fifty-one industrial sectors in the United States from  to  according to three factors: (a) the increase in production (output), (b) the number of employees (wage earners) in the industry, and (c) the increase in productivity (measured as the lowered use of manpower behind each unit of production). The sector with the highest increase in output, almost , per cent, was the automotive industry. In this industry, however, the number of wage earners only increased by just over , per cent. The number of wage earners per unit of product (the third column) was reduced by more than  per cent. Figure . is also an indication of Verdoorn’s Law: that industries with the largest increase in volume of production also tend to present the largest growth in productivity.³³ Assuming perfect competition, the differences in Figure . would not have had any impact on the rate of economic development in countries that had an automotive industry vs. countries that did not. In reality, however, the automotive industry became a wage leader, pulling up the general wage level in the United States. In March , Henry Ford doubled the wages of his workers, from US$. a day to $ a day. The Marshall Plan policy to distribute important high-growth/high-productivity-growth industries among all large nations dominated until the end of the s. Italy’s car industry was protected from foreign competition by an annual import ceiling of , engines for assembling the Italian version of the Morris Mini, the Innocenti. With the integration of Spain into the EEC during the s, tariffs were lowered gradually,

³³ Verdoorn ().

Percentage change

Industry

20,000

INDIVIDUAL MANUFACTURING INDUSTRIES Change in physical output, wage earners employed, and wage earners employed per unit of product, 1899–1937

10,000

Output

8,000

Wage earners

6,000

Wage earners per unit

4,000

2,000

1,000 800 600 400

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26

Automobiles, incl. bodies and parts Chemicals, industrial, incl. compressed gases and rayon Petroleum refining Beet sugar Fruits and vegetables, canned Ice Glass Paper and pulp Silk and rayon goods Knit goods Printing and publishing, total Butter, cheese, and canned milk Cigars Rice Paints and varnishes Coke-oven products Zinc Liquors, distilled Steel–mill products Tanning and dye materials Copper Explosives Wood–distillation products Fertilizers Blast–furnace products Jute goods

Industry 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51

Cotton goods Hats, wool–felt Shoes, leather Cane sugar Salt Meat packing Cottonseed products Leather Woolen and worsted goods Liquors, malt Shoes, rubber Carpets and rugs, wool Lead Cordage and twine Gloves, leather Hats, fur–felt Chewing and smoking tobacco Flour Ships and boats Cars, railroad Lumber-mill products Turpentine and rosin Linen goods Locomotives Carriages, wagons, and sleighs

200

200

100

100

0

0

–20

–20

–40

–40

–60

–60

–80

–80

–90

–90

Ratio scale

–95

–95 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 Industry

27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 Industry

 . How industries differ Source: Fabricant (1942).

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200,000

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 -    



while support was given to local industries, particularly to the important Spanish automotive industries with many subcontractors. The last  per cent duty on Japanese cars imported into the European Union was abolished in December . Although the theoretical reasons for these policies were gone from the Washington Institutions paradigm, in the rich countries the policies themselves lingered on in practice. During what we could call the nation-based development paradigm, most countries had the whole range of production represented in Figure .. There was of course much trade, but mostly symmetrical trade: France and Germany exporting cars to each other. Smaller countries also had car production: Holland had their DAF and Yugoslavia had a car called the Yugo, rudimentary and inexpensive. But with globalization came Daewoo and Hyundai from a military-dominated South Korea, where wages were lower than in Yugoslavia. Korea’s strategic significance for the United States— especially after the defeat in Vietnam—allowed Korea to use protectionist rules, contrary to what was prescribed by the Washington Consensus. An independent communist Yugoslavia could not, and the Yugo disappeared. This is but one very brief example of what happened when the global economy took over from the nation-based economy. Many countries lost the high value-added activities on the left side in Figure ., and world trade became much more of a winner-takes-all game (see Table .). Figure . shows a virtual ‘productivity explosion’ in the automotive industry to the left in the graph. Figure . shows the First Industrial Revolution as another such ‘productivity explosion’. All European countries attempted to get their share of this by attracting such activities to their own states: they would bring higher wages, higher profits, and higher tax incomes to the state treasury.

Table 19.1 How the game changed Nation-based capitalism

Global capitalism

High-tech, high-growth industries present in all countries of any size Move advanced economic activities to lagging countries Adjust exchange rates (Europe) Create jobs in order to solve crises (Keynes)

High-tech, high-growth industries disappear in peripheral countries (from Greece to Mexico) Move human beings from one country to the other.

Strong government and labour unions (balance of countervailing powers) Harmonization (harmony created through economic policy)

Freeze exchange rates (Europe) Create money in order to solve crises (EU Central Bank President Mario Draghi) Gradual power shift to the financial sector (the rule of the one per cent) Polarization (spontaneous chaos)*

Note: My book Spontaneous Chaos was published in Norwegian in 2009 and has been translated into Russian and Serbian. Source: Author.

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

 .  An early productivity explosion The mechanization of cotton spinning in the first paradigm Ave. annual 30.0 increase in productivity

25.0

20.0

15.0

10.0

5.0

0.0 1750

1800

1850

1900 Years

1950

2000

2050

 . Productivity explosion: cotton spinning Source: Carlota Pérez/Reinert (2008).

18 16

Man-hours required by best-practice methods of producing a pair of medium-grade men’s shoes at selected dates in the United States

14 12 10

Year

Man-hours per pair

1850

15.5

6

1900

1.7

4

1923

1.1

2

1936

0.9

8

0

1850

1900

1923

1936

 . US learning curve in men’s shoes, – Note: An important aim for industrial policy is to produce where the learning curves are steep. Source: Reinert (1980).

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 -    



Figure . shows similar dynamics in the form of a learning curve, plotting the number of man-hours per unit of production. A similar tool—the experience curve³⁴— plots the lowering of total costs. These are useful tools for any industrial policy research. The natural dynamics of global competition tends to farm out mature products with flat learning curves to poor countries: the lack of technical change means that such products appear ‘labour intensive’ and as such suitable for low-wage countries. The mechanism—that technological dead-ends tend to be farmed out to poor countries—is a key tool automatically reinforcing the vicious circles of national poverty.

. O  ‘Q’  E A: B  E, H  S,  D I C

.................................................................................................................................. Salomon Fabricant’s chart—reproduced as Figure .—shows the vast differences in volume of production, productivity growth and employment between various US industries in the early twentieth century. However, the chart does not distinguish between qualitatively different types of competition. By the time the third edition of his Principles of Political Economy and Taxation () appeared in , David Ricardo had probably heard that the extensive use of machinery might make his theory of comparative advantage invalid. In this edition Ricardo therefore explicitly assumed that the use of machinery would simply lower the price of the goods. In that case, Fabricant’s taxonomy of economic activities would not have any consequences. Especially so because David Ricardo’s trade theory—the essence of modern capitalist trade theory—does not at all consider capital as a factor of production. The assumption behind this theory—one which was later to be picked up by Karl Marx—is the labour theory of value. On the basis of this I distinguish between two types of competition. One is classical competition, based on the classical economist David Ricardo, where the only thing technological change does is to lower the prices of production. Its counterpoint, collusive competition, is collusive in the sense that, as a result of dynamic imperfect competition and high barriers to entry, capitalists (profits), workers (wages), and government (taxes) are able to ‘collude’ and prevent prices from falling at the same rate as the productivity increases (Reinert, ). This is a main reason why industrial policy is important. Table . sets out the mechanisms which create, respectively, collusive and classical modes of diffusion of productivity improvements. ³⁴ Boston Consulting Group ().

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 . 

Table 19.2 Characteristics of the collusive and classical modes of diffusion of productivity improvements Collusive

Classical Characteristics of mode

Divisibility of investments Degree of perfect information

Indivisible, comes in ‘chunks’ Imperfect (e.g. patents, internal R&D)

Divisible Perfect (competitive market for technology itself)

Source of technology from user company point of view

Internal, or external in big chunks = high degree of economies of scale

External

Barriers to entry Industry structure Economies of scale Market shares

Increase Increases concentration Increase Very important

No change Neutral No change Unimportant

How benefits spread GNP as measured

Highly visible (at producer level) Tends not to appear (Solowparadoxes)

Profits level

Increases stakes: possibilities for No change larger profits or losses

Monetary wages Real wages (nationally) Price level Terms of trade

Increase Increase No change No change

Examples of innovations in the two groups

Electricity, online sales of hotel New pharmaceuticals, bookings and used books, use of automotive paint production, PCs, dispersion paint Microsoft, Google, Facebook production, containers

Where found

Traditionally mainly in industry, in recent products and processes, in IT-related monopolies

No change Increase Decreases Turns against industries experiencing technological progress

In primary and tertiary industry, use of new basic technologies, mature industry

Source: Reinert (1994), modified.

In Fabricant’s graph (Figure .) we find that industry , beet sugar, appears to have a very high score in output and productivity increase. However, we can safely assume that a commodity like sugar will operate under near-perfect competition, so we cannot expect profits or wages to increase as they do in the automotive industry. In fact we find that in all developed countries beet sugar—which in productivity is inferior to tropical cane sugar—is, like so many agricultural products, subsidized by governments. The conceptual quality index of economic activities (Figure .) adds the dynamics of profits, wages, and taxes from oligopolistic competition and the lack of such

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innovations new technologies

Dynamic imperfect competition (high-quality activity)

Characteristics of high-quality activities • new knowledge with high market value • steep learning curves • high growth in output • rapid technological progress • high R&D content • necessitates and generates learning-bydoing • imperfect information

Shoes (1850–1900)

• investments come in large chunks/are indivisible (drugs) • imperfect, but dynamic, competition

Golf balls

• high wage level

Automotive paint

• high stakes: high barriers to entry and exit

• possibilities for important economies of scale and scope • high industry concentration • branded product • produce linkages and synergies • product innovations • standard neoclassical assumptions irrelevant

Characteristics of low-quality activities • old knowledge with low market value • flat learning curves • low growth in output • little technological progress • low R&D content • little personal or institutional learning required

House paint Shoes (2020)

• perfect information • divisible investment (tools for a baseball factory) • perfect competition • low wage level

Baseballs

Perfect competition (low-quality activity)

• little or no economies of scale/risk of diminishing returns • fragmented industry • low stakes: low barriers to entry and exit • commodity • produce few linkages and synergies • process innovations, if any • neoclassical assumptions are reasonsable proxy

 . The quality index of economic activities Source: Reinert (1994: 184).

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 . 

Table 19.3 ‘Good’ and ‘bad’ economic activities Characteristics of economic activities that are good/smart to specialize in

Characteristics of bad/unsmart economic activities

Increasing returns to scale (higher volume = lower costs) Rapid technological development (steep learning curves) Technical change leads to higher wages to the producers (Fordist wage regime) Dynamic imperfect competition Have stable prices Generally skilled labour Create a middle class Irreversible wages (‘stickiness’ of wages) Create large synergies (linkages, clusters)

Diminishing returns (higher volume = higher costs, after a point) Slow technological change (flat learning curves) Technical change tends to lower prices to the consumers Perfect competition (commodity competition) Show strong price fluctuations Generally unskilled labour Create ‘feudal’ class structure Reversible wages Create few synergies

Source: Reinert (2007).

Table 19.4 Average wage per cluster category in Europe, based on 255 European regions Cluster category

Average wage, €

Cluster category

Average wage, €

Aerospace Financial services Biotech Pharmaceuticals Analytical instruments Chemical products Information technology Oil and gas Telecommunication equipment Production technology Automotive Plastics Medical devices Power generation and transmission Lighting and electrical equipment Transportation and logistics Heavy machinery Metal manufacturing Business services Distribution Media and publishing

44,718 43,930 42,384 40,735 39,519 38,381 37,360 36,073 35,960 32,371 29,399 29,066 28,927 28,927 28,767 27,462 26,393 26,269 25,964 25,888 25,556

Paper products Sporting and children’s goods Building fixtures Stone quarries Processed food Construction Construction materials Textiles Jewellery and precious metals Furniture Leather products Maritime Tourism and hospitality Agricultural products Tobacco Education and knowledge creation Apparel Footwear Entertainment Farming and animal husbandry

24,995 23,498 22,827 21,183 20,993 20,894 20,063 17,902 16,303 16,131 15,594 14,274 13,961 13,852 13,567 13,132 11,885 11,238 11,034 3,859

Source: http://www.foreurope.eu/fileadmin/documents/pdf/Workingpapers/WWWforEurope_WPS_no014_ MS47.pdf. Accessed September 2019.

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 -    



dynamics from perfect competition (commodity competition) to Fabricant’s graph. New inventions and innovations enter at the top—initially under near-monopoly conditions—but fall, with very different gravity, towards perfect competition. Economic theory generally only defines well monopolies (black, at the top of the quality index) and perfect competition (white, at the bottom). Most economic activities are in between, and in the absence of new innovations tend to fall towards perfect competition. For example, when a patent expires on a medicine, this product would experience a sharp drop on the quality index (towards perfect competition). As a product matures and the learning curves flatten out (Figure .), the same thing will happen. The fact that only continuous innovations will secure continuous profits is the main source of dynamism in an economy. Rich countries produce goods with a high score on the quality index, poor countries tend to produce goods with a low score (see Reinert, , for more details). These dynamics make it possible to theorize about industrial policy around ‘good’ and bad’ economic activities, and around the recent EU concept of ‘smart specialization’ and its counterpart, ‘unsmart’ specialization (Reinert, ). Table . sets out their contrasting characteristics. Empirically the effect of these activities can be measured as in Table ..

. C  I P ..................................................................................................................................

Two recent works on early economics bestsellers—defined as economics books appearing in ten editions or more before  (Reinert et al., )³⁵—reveal that many works in economics, which were very influential in their time, are today virtually forgotten. And forgotten to the extent that there are not even entries on them in Wikipedia.³⁶ In this context we shall only mention one work, published by Joshua Gee in , which is typical of English industrial policy before Adam Smith. It is also typical of much of English colonial practice until long after Smith and Ricardo. The massive title, in the tradition of the day, reads: The trade and navigation of Great-Britain considered: shewing that the surest way for a nation to increase in riches, is to prevent the importation of such foreign commodities as may be rais’d at home. That this Kingdom is capable of raising within itself, and its colonies, materials for employing all our poor in those manufactures, which we now import from such of our neighbours who refuse the admission of ours. Some account of the commodities each country we trade with take from us, and what we take from them; with observations on the Balance. London: Printed by Sam. Buckley, in Amen-Corner. MDCCXXIX ³⁵ Reinert et al. () and Reinert and Reinert (). ³⁶ This has recently changed as my students at Tallinn University of Technology have been writing such entries as partial fulfilment of their course obligations.

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 . 

There were at least twenty editions of Gee’s work between  and , and the issues are unusually widely spread geographically. There are English editions published in London, Glasgow, and Dublin, French translations (the first in ), published in London, Amsterdam, and Geneva, Dutch (), Spanish (), and German (in Copenhagen, ). One factor leading both to the geographical spread of this book, and to its later oblivion is probably that Gee was not only very straightforward when he described England’s interest in protecting its manufacturing industry, he was also unusually honest about the intention of colonialism being the opposite, to hinder manufacturing in the colonies: That all Negroes shall be prohibited from weaving or spinning or combing of Wool, or manufacturing hats . . . Indeed, if they set up manufactures, and the Government afterwards shall be under a Necessity of stopping their progress, we must not expect that it will be done with the same ease that now it may.

At the time it must have occurred to those who published the  edition of Gee’s volume that not only were blacks subject to this policy, so was Ireland. In , John Hely-Hutchison—then Provost of Trinity College, Dublin—anonymously published The Commercial Restraints of Ireland considered in a series of letters addressed to a Noble Lord, containing an historical account of the affairs of that Kingdom, so far as they relate to this subject (Hely-Hutchinson, ).³⁷ The English authorities thought HelyHutchinson’s book protesting against the prohibition on exporting woollen manufactures from Ireland so insidious that it became the last book in the United Kingdom to be publicly burned by the hangman. Joshua Gee was a contributor to the journal The British Merchant which opposed a commercial treaty that would have established free trade with France. The polemical articles from this journal were published in  in three volumes as The British Merchant; or, Commerce preserv’d, with Charles King as the author/compiler, and became another bestseller (King, ). Together with Charles King and John Cary (Cary, : see also S. Reinert, ), Joshua Gee’s volume probably scores higher than any other book on this list on what we could call the ‘fame to oblivion axis’: compared to their popularity at the time these volumes seem to be the least remembered today. These were the three authors who probably were the most honest in explaining the policies that were actually carried out by the English. They show, without modesty, that the industrial policy of colonialism was preventing manufacturing from taking place in the colonies. This was, of course, an important reason for the United States to wish independence from England, an event which caused another economics bestseller—that of Alexander Hamilton ()—to clearly spell out the reasons why the United States would not be a wealthy country without a manufacturing industry.³⁸ ³⁷ Dublin, William Hallhead, . For the reproduction of a second edition (Dublin, M. H. Gill & Son, ), see http://www.gutenberg.org/files//-h/-h.htm. ³⁸ Hamilton ().

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 -    



. T M P   N  R  E  I, T,  P D

.................................................................................................................................. There is a phase of this matter which is both interesting and serious. The farmer has always produced the foodstuffs to exchange with the city dweller for the other necessities of life. This division of labor is the basis of modern civilization. At the present time it is threatened with breakdown. George Marshall, announcing the future Marshall Plan, Harvard University,  June  (emphasis added)

Curiously the immediate post-Second World War era saw two contradictory types of economic theory grow simultaneously. On the one hand, with the  Marshall Plan, we saw, at the practical level, a repeat of the principles that this chapter has traced back to England in the s: the only way to create widespread national wealth is through industrialization. Indeed, the Marshall Plan re-industrialized Europe, but also created a ‘sanitary belt’ of wealthy industrial countries around the communist block from Norway in the North-west via Italy, Greece, and Turkey to South Korea and Japan in the North-east. On the other hand, Paul Samuelson’s theoretical papers in The Economic Journal in  and  (cited in section .), based on Ricardian trade theory, argued almost the exact opposite: whatever you produced, international trade tended to create ‘factor price equalization’. The two opposite theories—that manufacturing was needed for wealth creation and that it was not—lived side by side, but slowly, as the Cold War developed, Samuelson’s theory got the upper hand over  years of experience. The Washington Consensus ideology triumphed over the Marshall Plan ideology, which had also been hatched in Washington. While the Marshall Plan ideology successfully stopped the spread of communism, the Washington Consensus—especially after the death of communism—in effect put back the old type of colonial policy: surprisingly, with the thinly veiled excuse of David Ricardo—which hardly anyone had listened to until the Cold War—as its main tool. The UN institutions, including UNCTAD and initially UNIDO, defended the old Marshall Plan order, while the Washington Institutions—the International Monetary Fund (IMF) and the World Bank (WB)—started basing their recommendations on the Ricardo/Samuelson theories. As the communist threat waned, a Washington-based type of neo-colonialism was initiated, often with disastrous economic results.³⁹

³⁹ There are several examples in Reinert (). On Mongolia as a particularly ugly example, see Reinert (: ‒).

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 . 

At the very core of the Marshall Plan was a profound understanding of the relationship between a nation’s economic structure and its carrying capacity in terms of population density. We argue that it is necessary to rediscover this theoretical understanding—which has profound implications for trade and industrial policy—in the mutual interest of poor and rich countries. In early , worries grew in Washington that an impoverished Germany, where manufacturing industry had been forbidden under the Morgenthau Plan, would fall an easy prey to the Soviet Union. US President Truman therefore sent former president Herbert Hoover on a fact-finding mission to Germany. One powerful sentence in Hoover’s report of  March zeroed in on the basic problem: There is the illusion that the New Germany left after the annexations can be reduced to a ‘pastoral state’ [i.e. a country without industry]. It cannot be done unless we exterminate or move ,, out of it.⁴⁰

Hoover understood that the population density of a country is determined by its economic structure. Industrialization makes it possible to dramatically increase the population-carrying capacity of a nation. ‘Exterminate’ was a very strong word to use after the horrors of the Second World War, and everyone understood that there was no place where  million Germans could be sent. Re-industrialization was the only option. The lesson from the Marshall Plan is that only extreme danger, in this case a communist takeover of Germany, will convince the West temporarily to give up what has been called ‘free-trade imperialism’. Temporarily, we argue, two events come together that may enable a rediscovery of the relationship between the economic structure and population densities of nations, and consequently benefit Africa. At the moment—facing a situation similar to that of England after the  crisis— the United States under Donald Trump is withdrawing from the ideology of free trade. ‘Donald Trump can embed a single visceral truth in a welter of falsehoods,’ wrote Rana Foroohar in The Financial Times in . The ‘visceral truth’ is that David Ricardo’s  trade theory is being marginalized. The last time that Ricardian trade theory collapsed—in the s—marked the start of a process of industrialization in Latin America that lasted for decades. We argue that the current situation similarly presents a major opportunity for Africa and other poor countries. A second event is migration. In , Herbert Hoover stated the facts regarding industrialization and population density. However, Alfred Marshall, the founder of neoclassical economics, in his  textbook Principles of Economics, had already provided a framework of understanding: activities subject to diminishing returns (agriculture, mining, fisheries) must after a point shed population, while activities subject to increasing returns attract population. As mentioned before, Marshall emphasized the huge impacts of diminishing returns: ‘This tendency to Diminishing Returns was the cause of Abraham’s parting from Lot, and of most of the migrations of which ⁴⁰ Quoted in Baade ().

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 -    



history tells.’ This includes the present migration from Africa, we argue. In an attempt to show us the age of this fundamental insight—as we have seen in the footnote in section .—Marshall refers to Genesis xiii: : ‘And the land was not able to bear them that they might dwell together; for their substance was great so they could not dwell together.’⁴¹ Alfred Marshall essentially rediscovered what was already old knowledge. All over Europe, development economics of the s and well into the s was dominated by the insights of Giovanni Botero’s On the Greatness of Cities (), a work that appeared in more than forty editions in all the main European languages. Botero explained why the only ‘islands’ of wealth in Europe were a few cities, such as Venice, Amsterdam, and Florence, where adding value to raw materials, producing manufactures, was the key to wealth. In , Antonio Serra⁴² added the basic theoretical foundation to this: the production of raw materials was subject to diminishing returns, while manufacturing was subject to increasing returns. Consequent productivity increases and barriers to entry made it possible for manufacturing cities simultaneously to raise wages and lower the cost of their goods. Centuries of trade policy followed the principles of Botero and Serra all over Europe and in the United States. Former World Bank Chief Economist Justin Yifu Lin put it very succinctly: ‘Except for a few oil-exporting countries, no countries have ever gotten rich without industrialization first.’⁴³ In line with this analysis, we suggest it is time for Africa and poor countries elsewhere to follow Alfred Marshall’s recommendation: ‘One simple plan would be the levying of a tax by the community on their own incomes, or on the production of those goods which obey the Law of Diminishing Returns, and devoting the tax to a bounty on the production of those goods with regard to which the Law of Increasing Returns acts sharply.’⁴⁴ Here Marshall describes what all presently wealthy countries have done, mostly through the protection of increasing returns activities through tariffs, ever since England in the s started to tax the export of raw wool, while at the same time subsidizing the local production of woollen cloth. This was the essence of import-substitution industrialization that took some non-Western countries out of economic colonialism. For centuries, colonies were essentially areas where the production of most industrial products was prohibited, as in the United States until . The United States under Donald Trump is now ideologically and indirectly paving the way for the industrialization of Africa. This must be an industrialization not primarily focused on the nation state, as Latin America’s industrialization was. Nor can it be based primarily on supplying global markets, as East Asia’s industrialization was. It must be focused on the African continent, producing industrial goods that rich countries take for granted, but whose production has not reached Africa to any extent. An unintended consequence of the apartheid boycott of Zimbabwe was the rapid growth of the country’s industrial sector, which reached more than  per cent of ⁴¹ Marshall (: ). ⁴⁴ Marshall (: ).

⁴² S. Reinert ().

⁴³ Lin (: ).

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GDP. Recently, de-industrialization there has rapidly increased outward migration, proving the principle Herbert Hoover explained in  still true. A consequence of Africa’s industrialization could very well be reduced migration because more Africans will be able to find jobs in Africa. In , a possible communist takeover of Germany was a sufficient threat for the West to temporarily abandon freetrade imperialism. The threat now is the  million people worldwide who were undernourished in , according to the FAO. Migration cannot solve their problems. Industrialization can. We can only hope the West sees the light after the  Coronavirus crisis as it did in .

. ‘I’: A F A  R  A  C  E D

.................................................................................................................................. Early economic theory saw strong arrows of causality between the modes of production of a society and its social and economic structures. Arab economist Ibn Khaldun (–) concluded that ‘the differences between different peoples arise out of the differences in their occupations’.⁴⁵ Francis Bacon, a scholar who was heavily influenced by Giovanni Botero,⁴⁶ wrote in his Novum Organum () that ‘there is a startling difference between the life of men in the most civilized province of Europe, and in the wildest and most barbarous districts of New India. This difference comes not from the soil, not from climate, not from race, but from the arts.’ The same point is strongly emphasized by German economist Karl Bücher (–) in his bestseller Die Entstehung der Volkswirtschaft () in the English translations rendered as Industrial Evolution. This way of thinking represents an attempt to systematize the understanding of different categories of human societies—much in the same way as Linnaeus did with plants—freeing economics from what Nobel Laureate James Buchanan called the equality assumption in economic theory. In  English economist Charles King made a classification of international trade in the same spirit as the quality index presented in this chapter. Importing manufactured goods and exporting raw material was ‘bad trade’ for a country, while importing raw materials and exporting manufactured goods was ‘good trade’. Interestingly, exchanging manufactures for other manufactures was considered ‘good trade’ for a nation. The principle expressed by King was based on the same observations as those of Giovanni Botero () and Antonio Serra (). UNCTAD’s idea of symmetrical trade as being good for all trading partners  years later recalls King’s ideas. ⁴⁵ Ibn Khaldun quoted in Issawi (: ).

⁴⁶ See Trace ().

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 -    



The craving for taxonomies also created the so-called stage theories,⁴⁷ to which Adam Smith also subscribed. In German these theories have recently been referred to as Wirtschaftsstile,⁴⁸ which implicitly emphasizes the fact that different economic styles—or stages—may coexist at the same time in different places. At the core of stage theories is that the mode of production—that is, whether you are in the Stone Age or the computer age—will determine your institutional structure. In this stage tradition, the structure of production tends to influence the institutional structure more than the other way around.⁴⁹ On a personal note, having worked with pastoralists in the high Andes and with Saami reindeer herders in Northern Fennoscandia, I can testify to the striking similarities in the social organization of pastoralists under extreme climatic conditions in such different areas and cultures. Here, as under other extreme climatic conditions, the market economy has not penetrated (other than in the extraction of minerals). These societies have sequential usufruct of land over the years, not private property. Clearly some institutional innovations are crucial to economic development. Primogeniture—the right of the firstborn legitimate son (or child) to inherit his parents’ entire estate—has created stability in European kingdoms compared, for example, to the Arab world. In agriculture, primogeniture prevented farm sizes from diminishing into or beyond self-sufficiency. Werner Sombart, the great historian of capitalism, sees the birth of two institutions—double-entry book-keeping and bankruptcy—as the two key institutional ingredients making the system possible. Historically these institutions bring us back to Venice in the twelfth and thirteenth centuries.⁵⁰ However, it is generally most useful to see institutions being born out of the mode of production itself, as in the quotes from Ibn Khaldun and Francis Bacon above. With their  book Why Nations Fail: The Origins of Power, Prosperity, and Poverty ⁵¹ Daron Acemoğlu and James Robinson in practice come to the defence and salvation of neoclassical trade theory by blaming former European colonies for not ‘getting the institutions right’. They seem to disregard the key point that the ‘extractive institutions’ they blame for the lack of development represent the very essence of Western colonialism. When explaining that ‘North America became more prosperous [than Peru and Mexico] precisely because it enthusiastically adopted the technologies and the advances of the Industrial Revolution’ (: ), Acemoğlu and Robinson leave out that Peru and Mexico for a long time were colonies, and that a key element in colonial policies was precisely to prohibit manufacturing there (see Gee, ). When Peru and Mexico later gained formal independence, they were still de facto colonies, as power just shifted from Spaniards in Spain to Spaniards residing locally,⁵² with the same vested interests

⁴⁷ Meek (). ⁴⁸ Schefold (/). ⁴⁹ Some anthropologists argue that the institution of cannibalism tends to appear in environments with limited sources of animal protein, for example in Central America and the Caribbean. The conditions create the institutions, not the other way around. ⁵⁰ Mueller and Lane (). ⁵¹ Acemoğlu and Robinson (). ⁵² Bollinger ().

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

 . 

in exporting raw materials.⁵³ In this way Acemoğlu and Robinson, far from attacking the colonial policies we have emphasized in this chapter, appear to be blaming the victims of colonialism for their own poverty. I would argue, in the Bücher tradition, that the Venetians did not invent an official property register (catasto), around , later to create capitalism, but rather because the capitalist growth of the city created a need for the property register. The problem appeared before the solution. Likewise, one could argue that the Venetians did not invent insurance, and then—based on this—start long-distance trading. Rather, one would argue that the previous system of spreading risk through ever smaller percentages of ownership of ships and cargo became impracticable because of the many owners, and that the impracticability of this fractionalized ownership is the origin of a system of insurance: instead of diluting ownership, risk was externalized. In practice, economic activities and their institutions co-evolve, and the first geographical area where this process of co-evolution created capitalism was in the twelfth-century Italian city-states.⁵⁴ In short, historical observations tend to reverse the arrows of causality in economic development compared to the formal theorizing of modern institutional economics (as opposed to the classical institutional economic of Thorstein Veblen and his contemporaries).

. W I P I C  R T T ..................................................................................................................................

Economists are unlikely to say to their children: ‘My son (or my daughter), I have observed your efficiency in washing the dishes. It is clear to me that you have a comparative advantage in this activity, and I would recommend a career washing dishes in restaurants.’ As a parent, the economist would react according to the preRicardian logic we have described in this chapter. As an economist—advising the children of Africa—their advice would be based on David Ricardo. This is a clear example of what US economist Thorsten Veblen warned against: that formal education might contaminate healthy human instincts (Reinert and Viano, ). Exoteric knowledge—practical and intuitive knowledge—could with higher education be lost to much more prestigious but of little practical use—esoteric ⁵³ There were examples of local industrial policies in Latin America, in Peru when the exports of silver had died out and before guano exports started, and in Brazil before gold was found in the province of Minas Gerais. But the local elites fell back on traditional raw material exports whenever a new commodity became available. In that way the industrial mentality hardly had a chance to be established. ⁵⁴ The massive work on Der Moderne Kapitalismus by Werner Sombart (–) argues for the origins of capitalism in the Italian city states. A first English translation of the four-volume  edition of this work is scheduled to be published as Modern Capitalism (Springer, ).

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 -    



knowledge, such as Ricardian trade theory. As already referred to, Schumpeter referred to this as ‘the Ricardian Vice’; bringing the theory to such a high level of abstraction that it became irrelevant. It is also intuitively obvious that, in spite of the theories of David Ricardo, free trade between a Stone Age society and a computer-age society will not tend to produce factor price equalization. A similar intuitive reasoning made presidential candidate Bill Clinton in  advocate high-tech industries. The reply from George H. W. Bush’s economic adviser Michael Boskin came straight out of the neoclassical economic textbook: ‘computer chips, potato chips, what’s the difference?’ With time, Boskin seems to be on the losing side when it comes to US industrial policy, but not when it comes to US trade policy towards Africa.⁵⁵

. N: A ‘I’ P S  A

.................................................................................................................................. The twentieth century was dominated by standardized mass production. Henry Ford’s statement in  that ‘any customer can have a car painted any color that he wants so long as it is black’ expresses the need to standardize in order to keep costs down. Gradually, and especially with the introduction of information technology, it was possible to produce smaller runs. The need for standardization diminished. In agricultural production, more so in Northern than in Southern Europe, standardization increased as a by-product of the economic crisis of the s. Some agricultural economists claim, probably correctly, that agriculture is the first economic activity to enter into an economic crisis and the last to leave it. Due both to market power and to strong unions, during the crisis of the s the industrial workers who kept their jobs tended to keep their wages. The crisis had a completely different effect on agriculture: farmers’ sales prices and their incomes fell precipitously. John Steinbeck’s  The Grapes of Wrath captures the drama of the situation. After the Second World War it was understood that farmers could not produce their way out of their problems; this would only cause overproduction and falling prices. Agriculture was seen as needing more market power, and in that sense agriculture ought to be more like industry. For this reason, national farmers’ cooperatives were given monopoly powers, and in the United States agriculture was (and still is) exempt from anti-trust and often heavily subsidized.

⁵⁵ As an early confrontation between neoclassical economics and common sense this quote is precious. But potato chips unfortunately are not a good example to use in international trade. This product is very intensive in transportation costs and is normally not carried over long distances.

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

 . 

This brought agricultural production, previously locally based, into the logic of Fordist mass production. While previously in Europe every farm, or every region or valley, had its own cheese, cheese production became more and more industrialized and more and more standardized. This coincided with the rise of big supermarket chains that came to dominate the retail food market. Farm products became bulk products, and when competition slowly opened up the farmers found themselves in the clearly inferior position of being specialized in bulk products, basically left to compete on price alone. A very ‘bad specialization’. In Southern Europe the local and regional pattern survived much longer, and big supermarkets also came to dominate later there than in Northern Europe. People wanted their local cheese and their local salame, so price competition between bulk producers was much less dominant. The local niche products, and with them decentralized production, survived. General de Gaulle once rhetorically asked: ‘How can you govern a country which has  varieties of cheese?’ According to a book on Italian cheeses, Italy beats that number by more than  varieties, registering  different varieties of cheese.⁵⁶ Having avoided the bulk- and mass-production paradigm, French and Italian cheese, as well as some cheeses from Spain and Switzerland, became a ‘smart specialization’. The organizational principle of Fordist mass production in bulk was economies of scale in hierarchies, while ‘smart specialization’ depended on economies of scope among small players in networks. Competition here is based on quality and product differentiation, not on price as in the mass-production paradigm. In agriculture and food production there is today ever-increasing diversity, more so in Southern Europe than in Northern Europe and the United States. Italy has of course hundreds of different types of pasta, and this diversity multiplies because regional differences between pasta types—often with the same names—are enormous. The casoncelli of Lombardy—a kind of ravioli—are very different in Cremona from those in Bergamo or Brescia. In many ways this Italian diversity is a remnant of pre-Fordism. More than most countries, France and Italy have managed to preserve variety in food and agriculture, while at the same time utilizing the industrial economies of scale. At the other extreme of the scale, Norway, with only about  million people, was probably the country where Fordist mass production—killing off previous niches—most came to dominate agricultural production, both meat and milk. The development and importance of diversity is illustrated by figures from modern biological research. Figure . is from Harvard biologist Stephen Jay Gould’s () Full House: The Spread of Excellence from Plato to Darwin. The illustration shows the evolution of the diversity of biological species from a common ‘ancestor’. In the case of horses, it would be a kind of Urpferd or Sifrhippus. Each end point further to the right represents a new biological variety descending from the same ‘ancestor’ (to the left in the drawing), like Shetland ponies, Peruvian paso horses,

⁵⁶ di Corato ().

Time

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Size

 . Increasing diversity and specialization over time (= ‘tid’)

Source: Gould (1996).

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

 . 

zebras, and donkeys. In Gould’s scheme a small number of varieties grow much larger than the rest as a result of random evolution. This is represented by the larger varieties at the bottom of the time axis (the varieties to the right, seen from the point of view of the ‘ancestor’). If we transfer this illustration to economic diversity, we create a graph that corresponds to Botero’s idea of increasing value added the further one moves away from the raw material. In this graph the end points represent a product. For example, let this common ‘ancestor’ be milk (the single starting point to the left). As the biological ‘ancestor’, the starting point is generic and non-specialized. Milk can come from a variety of animals, from cows to sheep, reindeer, and moose. The first more specialized branch could be the product cheese. The product cheese is again divided into new and ever more specialized products as we move towards the right of the time axis. Other products could be yoghurt, buttermilk, whole milk, cream, sour cream, and so on. Far out to the right on the diversity tree of cows’ milk, we find, for example, Appenzell cheese, which is only produced in two small cantons in Switzerland, or—as an extreme example— Parmesan cheeses coming from  different cheese factories which all produce technically slightly different cheeses. (On the biological axis far out to the right we find the koala, which is so specialized that it only eats the leaves from one specific kind of eucalyptus.) Wine is an example of extreme nichification. If we look at Gould’s starting point at the left (bottom) of Figure ., the single starting point would be that by fermenting grapes you can produce wine. If we add that there are green and red grapes, and that red grapes may be left with the skin for a while to create rosé wine, you have the next stage of diversification in Gould’s graph: white, red, and rosé wine. Then, further to the right, a huge variety of grapes and climates produce a never-ending variety of niche wines. These niches—from Barolo in Piedmont to Zinfandel in California—make it possible to compete along other aspects than price: more value is added as in Botero’s theory. The wine industry was the first to use terroir—clusters of environmental factors affecting quality—as a marketing tool. Reportedly, the first such geographical protection was established in  by Cosimo III de’Medici, the Grand Duke of Tuscany, for the Chianti wine. With the end of Fordist mass production and the introduction of information technology, the potential for decentralization increased: on Gould’s axis many production processes moved towards the right, towards a far greater diversity. The possibilities not only vary from industry to industry, but also from product to product. In the last instance it is also the human will—no invisible hand—deciding to what extent the decentralizing element in the present economic paradigm shift should be used to strengthen the economic periphery. Also, in the new organizational paradigm we have large industries—like Boeing and Microsoft in Seattle—representing the larger varieties at the bottom right of the time axis. When it comes to both large and small industries, it is the increasing amount of human knowledge that advances the process.

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 -    



One of Gould’s main points in the book is that over time the small units, in spite of the many visible large units (read ‘firms’), dominate ever more. We see the same development in the economy during the transition from the Fordist to the future technoeconomic paradigm. Gould’s second important point from this worldview is that to utilize average values becomes more and more meaningless as development advances. In the economic world there are different degrees of demand for the original generic product (the ‘ancestor’ and the basis for the illustration)—commodities, for example generic ‘milk’. It is only natural that different business strategies make some firms specialize in production of the generic product, where the demand is for low prices rather than high quality. Here the margins are very small, and this strategy needs an enormous turnover (and/or low wage rates) to survive (a result of economies of scale). Here we find giants like Cargill in the world grain markets. It is worth noting that the strategy in this volume market essentially implies a fight for market shares because high volume = low unit costs. Emilia-Romagna in Italy is an interesting area from the point of view of nichification. In Emilia-Romagna the high-volume/low-cost strategy was represented by the production of ultra-pasteurized milk by the giant firm Parmalat, which built on the importance of globalization and economies of scale in this market by, for example, buying up thirty-six dairies on the East Coast of South America. However, at the time operating in more than thirty countries, Parmalat came close to bankruptcy in the midst of a financial scandal. The high-volume/low-cost strategy bulk production failed Emilia-Romagna’s agriculture. What makes Emilia-Romagna agriculture so special is the fact that in many agricultural products—milk, ham, vinegar, olive oil—local raw materials are used. Producers in this region receive higher prices than the producers of the same raw materials do in the rest of Italy. The explanation is that Emilia-Romagna delivers very high-quality niche products that we find far to the right in Figure .. Industrial giant Parmalat mass-produced its standard-quality milk based on milk imported from Bavaria in Germany. When this author researched this issue in , the producers delivering milk for Parmesan cheese achieved  per cent higher prices than did the producers of normal consumer milk in nearby regions. When it comes to milk production this region has managed to get the best of all worlds: ) High prices for local raw materials for niche products, higher prices than for the same products in many parts of Europe. ) A decentralized production of niche products utilizes the partly rugged geographical territory in the Apennines very well (:  dairies producing milk for Parmesan cheese). ) To the extent this still lasts, economies of scale in high-tech mass production of bulk milk based on the import of cheap milk imported from Germany (Parmalat etc.).

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

 . 

. W’ N   P I P G?

.................................................................................................................................. As regards industrial policy, the US Republican Party platform in  sounded as if it had been based on the writings of Giovanni Botero almost  years earlier: The largest diversity of industry is most productive of general prosperity, and of the comfort and independence of the people. We, therefore, demand that the imposition of duties on foreign imports shall be made, not ‘for revenue only’, but that in raising the requisite revenues for the government, such duties shall be so levied as to afford security to our diversified industries and protection to the rights and wages of the laborer; to the end that active and intelligent labor, as well as capital, may have its just reward, and the laboring man his full share in the national prosperity. Against the so-called economic system of the Democratic party, which would degrade our labor to the foreign standard, we enter our earnest protest.⁵⁷

Policies to this effect could be achieved by allowing all raw materials free of duty into the country, and by increasing the customs duty in proportion to the added value to the raw materials. The principle of industrial policy was to apply the highest duty to the technologically most sophisticated product. Since then, many developments have complicated the issue. The minimum efficient size of industrial firms—and therefore also of nations—has increased considerably.⁵⁸ In the s a country like Estonia, at the time richer than Finland, with a population of only  million people, could have internal competition in many industries. This is no longer possible. The  Cecchini Report⁵⁹ arguing for a single market in Europe had a good point when predicting that most of the benefits from the single market would occur because of increasing returns to scale in manufacturing industry. What Cecchini did not calculate was that, particularly with the help of a frozen exchange rate in the form of the euro, manufacturing industry would tend to die out in the countries in the European periphery, thus creating a win‒lose situation where Germany in the end appears to be the biggest, or sole, winner. From a perceived hierarchy of increased value added based on raw materials, the appearance of global value chains has complicated the issue. Often global value chains can be analysed using the quality index in this chapter, but sometimes the categories, such as high-tech goods, contain a large diversity of products of different levels of sophistication. The trade tensions between the United States and China illustrate the issue. One thing is clear, though, that by putting high tariffs on important products that are already subsidized—like soy beans—China hit a weak point in US trade policy.

⁵⁷ Johnson and Porter (: ‒). ⁵⁸ Minimum efficient size is discussed in Reinert (: –). ⁵⁹ Cecchini ().

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 -    



. C: U U  B   C  E   W

.................................................................................................................................. The naive optimism of ‘laissez-faire’ and the childish and frivolous appeal to revolution, the naive hope that the tyranny of the proletariat would lead to world happiness, increasingly showed their real nature, they were twins of an ahistorical rationalism . . . The period – led to the theoretical and practical bankruptcy of both the old schools. Gustav Schmoller, German economist, Inaugural speech as Rector of the University of Berlin, 

Again we appear to stand at the intellectual bankruptcy of a school of economics, of a big vision of how the world was supposed to work. This time it is neo-liberalism, the modern version of Manchester liberalism, one of the two ahistorical twins Schmoller refers to above. Since one irrational twin, communism, died in , in the ideological triumphalism that followed we allowed the other twin, neo-liberalism, to rule the field virtually alone for thirty years. One curious aspect of this is that in the balance of countervailing power that had existed between capitalism and communism the industrial policy of Friedrich List had ruled on both sides: West Germany (Deutsche Bundesrepublik) and East Germany (Deutsche Demokratische Republik) both issued stamps with the same portrait of Friedrich List. List’s  textbook on industrialism had been ruling on both sides. The disappearance of this ideology was probably the most important defect when neo-liberalism went from theory to practical policy following the  fall of the Berlin Wall. Austrian-Swiss economist Felix Somary (–) made the perceptive observation that all big universalist projects of Europe have boomeranged, and caused the opposite of what was intended:⁶⁰ . The Crusades to the Holy Land should bring the infidels to Christianity and strengthen the union of the Catholic Church. Instead the Crusades led to the fall of Constantinople—of the Eastern Roman Empire and its Church—to the Muslims. . The basic rule of religious tolerance under the Reformation—cuius regio, eius religio (‘whose realm, his religion’)—meaning that the religion of the ruler was to dictate the religion of the country, suffered the indignity of centuries of devastating religious wars and more intolerance (including anti-Semitism). After the  Peace of Westphalia—which brought an end to this period—there were around  small states in Germany alone. ⁶⁰ Somary ( []).

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

 . 

. A little more than  years later the French bourgeoisie started its revolution for political and economic freedom, which led to a bloodbath, despotism, and four generations of dictatorship. Adam Smith had taught us that: ‘It is not from the benevolence of the . . . baker that we expect our dinner, but from [his] regard to [his] own self-interest.’ However, what Smith had not envisioned was that in the decades before the French Revolution much more money could be made from withholding flour and grain from the market—causing prices to rise—than by baking bread.⁶¹ To most economistes of the time—Physiocrats—it was inconceivable that money made from producing goods and services could have different effects in the economy than money made from increasing the prices of things already produced (i.e. from speculation).⁶² French minister of finance Jacques Necker (‒), born in the Republic of Geneva, was in ardent opposition to the Physiocratic laissez-faire doctrine which was mainly responsible for the shortage of bread in Paris. When the French Revolution broke out with the storming of the Bastille on  July , the fact that Necker had been dismissed as minister of finance three days earlier was a main reason for these disturbances. Necker’s popularity as an economist is proven by the fact that he is the only author—of more than eighty—represented with four different works on the list of economics bestsellers before .⁶³ Today we can observe—in the spirit of Somary—that the lofty ideals of the European Union project resulted in countries divided by a common currency with serious economic problems in the periphery; that the United States is faced with falling real wages, a dwindling middle class, and increased mortality of white males; and that the vision of globalization as an exercise in increasing harmony—propelled by the Ricardian Cold War visions of Paul Samuelson—often proves to be more an exercise in factor price polarization than in factor price equalization (with China as the great exception). During the French Revolution, the supposedly ‘natural’ forces of automatic harmony, from Franz Anton Mesmer’s quack science of Mesmerism,⁶⁴ and its supposed creation of a Society of Universal Harmony, to the Physiocrats’ idea of laissez-faire provided the opposite: famine and revolution. This shows that the nature of economic systems obeys Charles Darwin more than it obeys any unrealistically abstract theories creating illusions of automatic harmony: economic harmony is man-made. A point which has become very clear now, when decades of neo-liberal policies have created

⁶¹ Kaplan (). ⁶² In Florence, the practice—apparently dating from the s—of prohibiting the movement of food out of the city, shows that this problem had once been understood. It is worth noting that while the French economists at the time, the Physiocrats, argued that all economic activities other than agriculture were sterile, and therefore rendered much power to the feudal lords, the practice of Florence—one of our earliest democracies—was to exclude landowners from the political process. ⁶³ See Reinert et al. (). ⁶⁴ Darnton ().

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 -    



massive problems of inequality. We therefore need meso-level theories adapted to the specific contexts of each nation. From this point of view neoclassical economics and neo-liberal theory have functioned as snake oil, a cure-all for most ailments. Googling the term ‘austerity’ together with ‘snake oil’ in fact gives a surprisingly large number of hits. The wealth and poverty of a country are to such a degree a result of its economic structure, that industrial policy, in its widest sense, is necessary in order to create peace and economic justice. The present ecological crises only reinforce the need for the understanding of the mechanisms of diminishing returns (which created Malthus’ ‘dismal science’) and increasing returns under which it is possible to harvest a generous nature rather than to unrenewably extract the products of nature.⁶⁵ Utopian visions of automatic harmony resulting from free trade are main drivers of human migration away from un-industrialized or de-industrialized countries in Africa and Latin America to Europe and North America. In , the WTO director-general, Renato Ruggiero, declared—in the spirit of Paul Samuelson’s interpretation of David Ricardo—that we should unleash ‘the borderless economy’s potential to equalize relations among countries and regions’.⁶⁶ This is the foundation upon which the whole world economic order came to rest, and also the ideological marching order for the Washington Institutions—the International Monetary Fund and the World Bank—in their policies towards the poor countries of the world. It is again important to emphasize that, in terms of industrial policy, this theoretical understanding was exactly the opposite of the theory on which the extremely successful  Marshall Plan had been built. ‘The worse the situation, the less laissez-faire works,’ said Keynes. Historical developments proved this to be true: the negative effects of laissez-faire first showed up in the Third World, then in the Second (former communist) World, and in the end in the core of the First World, in the United States and the European Union (Reinert, ). One important side-effect of the policies of the Washington Institutions is that dictatorships obtain a considerable advantage over countries which try to be democratic. China and Singapore are doing extremely well under their system of wellmanaged free trade—opening up to free trade where it suits them as Europe used to do—while the policies of the Washington Institutions de-industrialize and impoverish many democratic countries (Figure .). The virtual ‘prohibition’ of industrial policy through the conditionalities of the Washington Institutions has, in many places, been very costly in terms of failed development and economic retrogression.⁶⁷ In , real wages in Ukraine were considerably higher than those in Belarus. The reason real wages in Belarus now are about double those in Ukraine is not because

⁶⁵ Mathews and Reinert (). ⁶⁶ Ruggiero (). ⁶⁷ Reinert () presents two particularly ugly case studies, Mongolia and Peru.

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

 . 

Percentile of income distribution

100 90 80 70 60 50 40 30 20 10 Egypt Jordan Morocco Tunisia Turkey

Ukraine Montenegro Serbia Tajikistan Georgia Hungary Kyrgyz Rep. Maldova Kazakhstan Bosnia and Herz FYR Macedonia Azerbaijan Croatia Russia Estonia Latvia Romania Lithuania Bulgaria Slovenia Uzbekistan Slovak Rep. Armenia Belarus Poland Turkmenistan

0

Income below 1989 levels Income growth below G7 average Income growth above G7 average --- Median

 . Economic growth since  (fall of the Berlin Wall), selected countries: percentiles of population with income growth above/below the  level/the G average level Source: European Bank for Construction and Development, Transition Report 2016–2017, London, 2016.

the statue of Lenin still stands on the main square in Minsk, it is probably not that Belarus is less corrupt than its neighbours, it is mainly because, as a dictatorship, the country does not have to follow the foreign dictates of the Washington Institutions and can actually pursue a national industrial policy. We are in a period when the attitude towards industrial policy is slowly changing, but in the reverse order of what should happen if we follow Keynes’ insight above. The clearest changes in favour of industrial policy are taking place in Germany and in the United States. The process is much slower in poor countries where there has been a prohibition of industrial policy and where it is most needed. In , asked to contribute to an annual report on the development of the OECD, I was able to observe how alternative ideas are only extremely slowly filtering into this powerful global institution. It is difficult for a whole generation of experts to admit that they were wrong, and the virtual monopoly of neoclassical economics at the university level makes it difficult to recruit professionals with alternative views. In a sense the world faces the same kind of intellectual monoculture that faced the universities in former East Germany at the  German unification: there were twenty-three professors of Marxist economics at the universities in former East Germany, and little else.

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 -    



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 -    



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        ......................................................................................................................

   -                           Market Myths and Production Realities .............................................................................................................

 . 

. I   E  P  S P F

.................................................................................................................................. T s marked a dramatic turning point in the performance of the American economy. Manufacturing employment’s share of total US employment declined steadily from near  per cent in  to  per cent in  (Baily and Bosworth, : figure ).¹ Real weekly wages in  were around  per cent below their  peak for private-sector production and non-supervisory workers (Blanchflower, : ). Described as the ‘great reversal’, wages that had risen year on year in the post-war era for those with no more than a high-school education began to fall in the s and continued to do so for three consecutive decades (Acemoğlu and Autor, ; Frey, : ). From  to , Piketty, Saez, and Zucman () find that none of the growth in per-adult national income went to the bottom  per cent, while  per cent went to the th to the th percentile,  per cent to the top  per cent, and

¹ After , the absolute level of US manufacturing employment fell by one-third to under  million in  (Atkinson et al., : figure ). In the s, US manufacturing suffered its worst performance in US history in terms of employment. Not only did the United States lose . million manufacturing jobs, but the decline as a share of total manufacturing employment ( per cent) exceeded the rate of loss in the Great Depression (Atkinson et al., ).

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 . 

 per cent to the top  per cent. Productivity growth and the nation’s trade balance both declined as well.² What has gone wrong? In this chapter, I examine the role of industrial policy not as an external fine-tuner to a self-organizing, autonomous economy but as integral to the productive structures and core processes that constitute an economy and how it operates. The industrial policy of a nation is more than a technical issue in economics: it is at the core of competing visions of a nation’s ideals. The two major approaches guiding national economic policymaking frameworks in the world today can be traced back to the economics of Adam Smith (Best, ). For simplicity one can be called market-centric and the other production-centric. Given the logic of market-centric economics, industrial policy can only fail as the market knows best.³ But real-world governments are known to craft productioncentric policy frameworks that foster rapid growth and industrial transformation. For example, arguably the most successful industrial policy experience in history was conducted by the US government during the Second World War. New industries were created, others transformed, and output nearly doubled in half a decade. Policymakers of late developers like Japan, Korea, and China learned about the primacy of productive structures to economic performance from successful growth experiences, crafted strategic production-centric policy frameworks, and galvanized business enterprises to drive them. These experiences open a broader context in which to consider the role of industrial policy and state agencies/activities in shaping how economies are organized and that address the defining questions of textbook economics: what gets produced, how it gets produced, and for whom. Industrial policy calls attention to the powers and responsibility of government to advance the manufacturing base of a region or nation, because the manufacturing sector has unique characteristics in determining prosperity. Its products are tradable, improvements in its processes are the source of productivity gains, and it is the last link in an innovation process chain that includes the translation of scientific and technological innovations into products. Industrial policy is not about correcting for market failure; it is about shaping a nation’s and region’s productive structures. The question that motivates this chapter is: why did post-war American manufacturing and the nation’s industrial heartland undergo severe de-industrialization so soon after its pivotal contribution to the victory of the Allies in the Second World

² Labour productivity grew at an average rate of . per cent over decades but fell to . per cent in the mid-s and . per cent since . In the mid-s, the US overall trade balance began a decline from a surplus of approximately  per cent gross domestic product to a deficit of – per cent in , followed by a recovery before plunging again to a deficit of between  and  per cent in the s (Pisano and Shih, : ). ³ The market failure approach offers policy guidelines in the form of taxes and subsidies to correct for deviations of the prices and outputs from an idealized perfectly competitive market system. For economic modelling the attraction is that the theory is context- and history-blind and assumes that production is subject to the same optimality rules and equilibrium conditions as the world of consumption. If only real-world production systems cooperated.

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-   



War? I apply an economic analysis of comparative policy frameworks and production systems to better understand what went wrong. It takes us inside a set of interconnected processes linking political power, policy frameworks, production capabilities, business organization, and skill formation. The argument is that the American mass-production system that won the war came under threat from two existential challenges: the emergence of more advanced production systems abroad, exemplified by Japan and Germany, but more importantly an abrupt and historical shift in the nation’s economic policy framework. With the s triumph of neo-liberalism, the regulations, progressive tax system, labour legislation, and manufacturing support infrastructures around which the nation’s industrial heartland had been built and the war had been won were eroded and dismantled. The neo-liberal policy perspective and its economic and social consequences are not new to the s; they are as old as the Republic. It is a policy framework and a political economy perspective with roots in the plantation economy of the American South. Ironically, the idea that free markets and democracy are interconnected has long been used to legitimize repressive labour regimes, beginning with defenders of slavery (Einhorn, a). What is new is that the s marked a historic shift in political power and direction of national economic policymaking undertaken by both major parties. Neo-liberalism resonates with, and is a triumph of, the economic philosophy, policy frameworks, extractive industries, and social hierarchy upon which the production system and autocratic business model of the South were built and have endured for four centuries. The power of wealth and corporate elites to influence politics and dictate policymaking is not the whole story, important as it is. It is also a story of the power of economic ideas to persist, whatever evidence to the contrary may be readily observable. The market-centric economics axiom that industrial policy cannot lead to improved economic performance has long outlived its contradiction by post-war Japan and Germany as well as the US Second World War economic experience. Nevertheless, since the s, US economic policymakers have continued to act on the myth and deny the reality. The policymaking regime ‘assumed’ that strategic Japanese industrial policy could not be a threat to America’s manufacturing leadership. The post-war economic theory and policy debates centred around monetarist versus Keynesian macroeconomic stabilization policies. Lacking an economics of production, the debates were blind to the success of governments abroad in crafting strategic policy frameworks based on advancing their nation’s business and production capabilities to target the vulnerabilities of post-war American industry. The goal of policymakers abroad was not to attack the American working class; it was a consequence of statecraft lessons drawn from the Second World War experience and elsewhere. American economic policymaking turned in a different direction. Neo-liberalism is an economic growth agenda that appeals to the ‘invisible hand’ parable to justify ‘market’ deregulation and tax reductions on corporations and the wealthy. Its corollaries include that deregulation improves business performance, as better managed firms win in free markets; that deregulated financial markets ensure that the resources

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

 . 

of poorly managed firms get reallocated to superior firms; and that increased productivity generates profits that trickle down to workers and reduce prices to consumers. As noted, neo-liberalism is not a new agenda to America. The South has always practised a version of neo-liberal policymaking, beginning with the plantation economy. What changed in the post-war era was the migration of neo-liberal policymaking from the South to the national level. A centuries-old civil war between policy frameworks was won by the South. The historic production-informed policymaking regime of the North succumbed in the s to the South’s low-tax, deregulation, anti-union, ‘rentier capitalism’ policy regime which for the first time became the federal government’s economic policymaking regime. Apart from the rentier elite, it never worked for the South and for the last four decades it has severely eroded the production capabilities and infrastructural foundations of the nation’s industrial heartland. The nation’s policymaking leadership, of both political parties, did not foresee the de-industrialization consequences of neo-liberalism. The economics they ‘knew’ assumed that the power of the profit motive, if liberated from taxes and regulations, would incentivize business managers to pursue activities that would maximize national prosperity. It left them blind to the potential for a neo-liberal policy agenda to shift the managerial incentive structure from value creation to wealth-extraction strategies with devastating consequences. The economics they ‘knew’ ignored the historic public-sector role in shaping the organizational and extra-firm infrastructural foundations of the nation’s manufacturing system and their dependence on public investment on the one hand and their vulnerability to competition from foreign production systems on the other. The production engineering expertise and managerial culture by which manufacturing enterprises had invested heavily in innovative production and technological capabilities and skills to the benefit of the nation gave way to shareholder pressures and innovations in financial engineering practices to the benefit of wealthy and shareholding elites. The reduction in taxes in the deregulated environment created a new incentive structure for corporate managers to join the shareholding elites and amass fortunes. It unleashed the drivers of a rapid increase in inequality. Even as the nation’s manufacturing belt became the ‘Rust Belt’, the financialization of America’s industrial enterprises created huge profit opportunities for hedge fund owners, asset management companies, and investment banking. The rentier landowning class of the South was joined by a rentier financial elite. Policymakers, too, fell victim to the power of free-market economics as a political weapon to shape popular economic discourse and influence economic policy. Economic policymakers did not reckon on the power of special interests, if unchecked by government regulation, to ‘financialize’ a nation’s manufacturing enterprises, toxify their workplace environments, and undermine their productive structures. Absent the strategic direction from political leadership and policymakers’ awareness of the cost in loss of production capabilities and manufacturing employment to America’s industrial heartland, the neo-liberal agenda became national policy with devastating consequences on the families and communities on which they depended.

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-   



The policy framework of the South has always been, in effect, anti-skill-intensive manufacturing. The South has, with rare exception, never developed learning firms, manufacturing clusters or innovative city dynamics and, except for foreign car companies, has always imported rather than produced manufactured products. This, tragically, is the anti-industrial policy framework that has become national policy over recent decades. It is the story of how Dixie won a centuries-old, North–South civil war of production systems. In defending and expanding on these claims, this chapter is organized as follows. First, we bring America’s Second World War production ‘miracle’ down to earth with an examination of the policy framework, implementation agencies, and organizational change methodologies through which policymakers organized a transformative advance in the nation’s industrial performance. It takes us deep into the internal productive structures of business enterprises and change programmes by which government and business joined forces to upgrade production methods, educate a workforce with the requisite skills, and advance productivity on such a scale as to make a step change in national economic performance. Successful implementation drew upon the active participation of management, production engineers, and skilled labour to make changes in organizational practices. While the US Second World War experience is a special case, it is consistent with historical accounts of the role of government leadership in crafting strategic policy frameworks and organizing enterprise change methods and infrastructural agencies to advance the productivity of a region’s or nation’s business enterprises (Best, ). Next we examine the post-war policy legacy. The Second World War experience permanently transformed the interconnectedness of government and the economy in major ways. The US transitioned from a virtually non-existent pre-war weapons industry to a defence budget larger than that of all other nations combined. A huge government-contractor system was created with an estimated , defence research contracts in  expanding to perhaps , in . Wartime organizational innovations in economic governance and industrial policy were selectively adapted and permanently institutionalized in the post-war era. For example, the wartime creation of administrative agencies to design and produce technologically advanced weapons systems became the world’s biggest and most advanced science and technology infrastructure. In contrast, wartime successes in designing management and manpower development methodologies to foster workforce participation in decision-making and continuous innovation were, unfortunately, not institutionalized. In other countries, such as Japan and West Germany, they became the manufacturing cells of rival production systems with superior new product development and technology management capabilities. Post-war macroeconomic policy was profoundly changed by the transition from the era of Pax Britannica to Pax America. Pax America offered the defeated nations of Japan and Germany open access to the vast American market. It involved a free-trade policy and an overvalued exchange-rate policy that created opportunities for the defeated nations to craft export-driven industry policy frameworks organized around

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 . 

innovation-led manufacturing systems and Schumpeterian business strategies. US macroeconomic policy, in contrast, focused on stabilization policy issues based on the belief that US technological leadership would ensure US manufacturing leadership. The strategic policy framework of Japan both built on the strengths of the American mass-production model and exposed its weaknesses. Japan’s manufacturing advantage was not based on building a bigger science and technology infrastructure than that of the United States. Instead, Japanese business leaders and policymakers focused on building competitive advantage by superior manufacturing capability. They began by applying lessons from the US Second World War experience about the policy interconnectedness of production capabilities, business organization, and skill formation. As they progressed rapidly up the production capability spectrum (Best, , ), American mass production became a victim of its past success. The war-winning advantage of American mass production was organized around economies of speed (throughput efficiency) and the principle of single product flow. It maximized throughput and productivity by hardwiring the factory to a single product and a single design (Best, ). The product’s design was frozen because design changes required the whole production line to be re-engineered. A single product was required because multiple products would mean changing machine set-ups and require specialist expertise to change over from one product to another, which could cause the production line to be shut down for hours or days, if not more. It was a highly productive system, but it was inflexible. As Henry Ford famously said, ‘Any customer can have a car painted any color that he wants so long as it is black.’ Japanese engineers created a flexible mass-production system based on the principle of multi-product flow. They built factories that were organized to produce multiple products on the same assembly line and to transition from one to another and back again in minutes. Participatory and multi-skilled labour practices enabled quick changeovers from product to product and continuous improvement (kaizen) in production methods to design quality into the production process. It was a labour system in which work teams, multi-skilled workers, and manufacturing cells replaced the single-task worker as the primary work unit. The result was revolutionary; it set a new global standard for throughput efficiency, cost, quality, and delivery time (Best, ). It was a challenge that demanded a transformation in national-production industrial policy at a time in which market-centric economics was hegemonic. However, an internal challenge to America’s industrial heartland was looming in the form of a rival production system with roots going back four centuries. Manufacturing as a system of production and industrial policy took root in the north-east roughly a century and a half after the plantation economy, coincided with the founding of the Republic, and evolved into a highly diversified manufacturing production system in the cities and states of what became the nation’s manufacturing belt. The Northern ‘social democratic’ policy framework involved collecting taxes for the public provision of material and organizational infrastructures, such as public education and the federal armouries, and a financial and regulatory environment to support the development of the nation’s nascent manufacturing enterprises. Concentrations of wealth were limited

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-   



by highly progressive income and wealth taxes; by anti-trust and regulatory policies; and by restricting the involvement of corporations in politics. The historic activist state that sought the advantages of corporate economic power while limiting the disadvantages of corporate political and market powers were leveraged by both New Deal and Second World War industrial policymaking. The Second World War industrial policy framework went beyond the New Deal in galvanizing the synergistic power of US business and labour working together to build a highly productive economy. Tragically, this constructive alliance was immediately attacked with the passage of the anti-union Taft Hartley Act in , which heralded the first major neo-liberal victory. The Cotton Belt of the South began as a plantation economy with a landholding aristocracy and slave labour. From its early days the policy framework of the South was crafted to protect the institution of slavery, based on fears that the North would use national policymaking powers, such as taxation, to suppress and destroy the forced labour regime (Einhorn, a). The Southern hierarchy defined itself in opposition to the emergent manufacturing development initiatives of the Northern colonies from their origins in the s, as it was clear that the latter would depend upon free labour. Fast forward to the massive New Deal federal transfers, physical infrastructure, and military spending that turned the ‘Cotton Belt’ into the post-war ‘Sun Belt’. The political elites, the policy framework, and the dominance of extractive industries did not change. The oil and gas industry along the southern coast extended westward, and with mining and forestry northward joined the historic mining industries in the Rocky Mountain states. The manufacturing strategy of southern states and towns was to compete with one another to attract Northern companies seeking government subsidies, low taxes, anti-union laws, and lax regulation. Indigenous manufacturing did not take hold. The South’s manufacturing strategy worked to the extent that many Northern firms, faced with a choice between restructuring to meet the new world-class production standards and relocating to the anti-union, low-cost environment of the South, chose the latter. However, by the s, the ‘smokestack-chasing’ manufacturing strategy failed, as the South’s major labour-intensive industries, led by textile and furniture firms, succumbed not only to low-wage competition but to enterprises with more advanced manufacturing capabilities from China and elsewhere. Consequently, gas and oil production and mining, combined with federal defence spending, have become the mainstays of the region’s economic livelihood. Given four centuries of failed economic progress it seems incomprehensible that the anti-labour policy framework of the South would be adopted as national policy. Critically, political leadership, mainstream economics, and economic policymakers failed to learn from the policy framework of the American South and all other plantation economies before dismantling progressive income and wealth taxes, industrial policies, and regulatory agencies. In academic economics, macroeconomic modelling absorbed Keynesian demand management as a special case of market failure, and stabilization policy dominated economics education and popular discourse. The stagflation era of the s eroded

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

 . 

public confidence in the efficacy of stabilization instruments to fine-tune the economy and created the opening for an anti-industrial policy and a neo-liberal economics agenda to shape public discourse. Even though the South benefited most from America’s de facto industrial policy of military contracts and subsidized corporate clients, its apparent antipathy to industrial policy was central to its political ideology. In the real world of industrial policymaking, the South fostered a new American version of ‘state capitalism’ in which political elites leverage their government insider power to become rentier capitalists (Lind, ).⁴ In the name of free enterprise, the neo-liberal policy framework campaigned for deregulation of financial markets, elimination of anti-trust legislation, the passage of anti-union organizing laws such as the Labor Management Relations Act of  (better known as the Taft Hartley Act), and relaxation of social controls and historic norms of corporate governance. Critically, the historic stakeholder model of business organization and management norms was overtaken by the ideology propounded by Milton Friedman and Michael Jensen that the only purpose of business was to make profits and enrich shareholders. The appointment of Lewis Powell to the Supreme Court by President Nixon in  signalled the elevation of a key player in the crafting of the Southern strategy. Powell, an attorney for the tobacco industry, authored the Powell Memorandum, a secretive campaign to mobilize billionaires to fund neo-liberal think tanks to influence public opinion about the ideals of free markets. The goal of the neo-liberal campaign was the passage of legislation to dismantle New Deal institutions but also to promote market fundamentalist leadership of the economic policymaking agencies at the national level, including the Treasury Department, the Federal Reserve Bank, and the Commerce Department. It was a campaign that did not depend upon who was elected but aimed to sway public opinion independent of political party. Thus began the age of dark money in American politics, funded by the wealthy beneficiaries of extractive and monopolized industries. The costs to the North of the neo-liberalism era have run deep not only in fiscal transfers to the South but more especially in the erosion of the nation’s material and extra-firm infrastructures (educational, banking, engineering support) that co-evolved with the nation’s manufacturing belt and upon which the nation’s industrial leadership had been built. The industrial heartland lost its voice in policymaking at great cost to the nation’s industrial performance in loss of production capabilities, skills, high-wage employment, and tax bases upon which the region’s once prosperous cities depended. In the final part of this chapter, an economics perspective and industrial policy framework is introduced to address the task of transforming the American economy to meet the challenges of climate change and four decades of eroding infrastructural foundations, both material and organizational. The term ‘capability triad’ is presented as an expository device that draws upon the common policy dimensions of a series of ⁴ Elizabeth Shermer’s Sunbelt Capitalism: Phoenix and the Transformation of American Politics offers a similar account of the civil war of policy frameworks ().

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-   



transformative experiences on the scale of economic ‘miracles’ led by Franklin Roosevelt (Second World War), Deng Xiaoping (China), Taiichi Ohno/Edwards Deming (Japan), Ludwig Erhard (West Germany), Ralph Flanders (Massachusetts), and Kenneth Whitaker (Ireland) (Best, ). The economic ideas that informed the New Deal are contrasted with those that informed the Second World War policy framework. President Roosevelt drew critically important lessons from the failure of the New Deal as a transformative policy agenda. The Tennessee Valley Authority (TVA) was the centrepiece of the New Deal policy framework. It was hugely successful in the electrification of the South as the Hoover Dam was in the South-west and Grand Coulee Dam was in the North-west. As material infrastructure, they were critical to building the Arsenal of Democracy, but not sufficient. The TVA experience is instructive from a capability triad perspective. It created a growing demand for electricity which did become a regional export industry, but as new sources of hydro power ran out the TVA turned to coal as a source of energy (Jacobs, ).⁵ It did not shift the South’s structural dependence on extractive industries or the interconnnected labour system and deeply anti-democratic skill formation system that applied in both public and business spheres. Dixie has always meant a steadfast commitment to not increasing the skills of the region’s workforce. It started with reconstruction-era fears that a numerate workforce would understand how to counter the debt-peonage system and instigate worker rebellion. But without advancing skills, business enterprises cannot successfully pursue Schumpeterian product-led competitive strategies and build new product development or technology management capabilities. This was a hard-earned lesson that distinguished the focus of President Roosevelt’s Second World War industrial policy on fostering business capability development and harnessing the production engineering and human capital expertise of America’s most successful manufacturing enterprises. It worked. It provided lessons that were taken up by the defeated nations but unfortunately ignored by the victorious.

. T US S W W P- P F

.................................................................................................................................. The most successful industrial policy experience in history is arguably that conducted by the US government during the Second World War, in which President Roosevelt’s vision of an ‘Arsenal of Democracy’ involved a near doubling of national output in a ⁵ The TVA became a World Bank development model around the world long after its flaws were well known (Jacobs, ).

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

 . 

half a decade. How was it done? The answer was to organize an interdependent innovation-process chain linking basic research, developmental research, and applied research, combined with the diffusion of world-class production capabilities. The US business system was transformed to harness the driving force of innovating enterprises. In the process, the US production system was, in effect, re-engineered to accomplish a step change in performance standards. An inter-organizational technology management capability was institutionalized as a consequence. The manufacturing process in virtually every enterprise in the United States was reengineered to achieve the output targets. It required a national translational research capability to be created that linked ‘top-down’ enabling agencies with ‘bottom-up’ operational drivers. Implementation involved the combined efforts of a set of unified extra-firm infrastructural agencies led by the Office of Scientific Research and Development (OSRD), the War Production Board (WPB), the Manpower Development Commission (MDC), and the Defense Plant Corporation (DPC). Each was dismantled at the end of the war. The key to implementation was inter-organizational connectedness. The OSRD, led by Vannevar Bush, was tasked with building a national science and technology ‘extrafirm’ infrastructure that could create an inter-organizational capability to design, develop, and produce technologically advanced weapons systems. Examples such as microwave or radar, penicillin, and synthetic rubber required basic, developmental, and applied research to be married with design for manufacturability by massproduction facilities. The latter required the production base of the country to be reengineered to meet the performance standards of cheaper, better, faster. When adopted and extended by Japan in the post-war era, the process innovations became widely known, imitated, and diffused as JIT, TQM, and SDWTs.⁶ With  million Americans transferred into the armed services, the production system had to be transformed. Designing the means to undertake the transformation across the economy to meet the production targets was the task of the WPB and the MDC. For example, meeting the production target of one B- bomber per hour required the supply chain to deliver . million parts to the factory gates per hour. The War Manpower Commission designed and operationalized the functional equivalent of a fast-track national training programme to equip both management and labour with the skills and organizational methods to meet the production targets. Economic statisticians played a key role. The engineering challenge through which the nation’s production system was restructured was critical to the implementation of the Victory Program itself written by Simon Kuznets, chief economist at the War Production Board. He and fellow economic statisticians diligently created statistical tables on the existing and planned output of the nation’s manufacturing enterprises. They identified sequential bottlenecks that required investments to remove them. Kuznets, as the father of US national income and production accounts, was the perfect

⁶ Just-in-time, total quality management, and self-directed work teams.

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-   



person and perhaps the only person who could have linked the nation’s production system requirements with the Allies’ war strategy. No doubt, the US Second World War policymaking experience was a special case. Nevertheless, it is informative with respect to an economics of production, innovation dynamics, and enterprise capability development. It also offers a powerful negative lesson, examined more fully in section .. US post-war policymaking has been dominated by debates over stabilization instruments and targets that, in effect, rendered the production side of the economy invisible. The focus of the Department of Commerce’s national account measurements of Keynesian expenditures and income reflects this invisibility, as does the failure to incorporate a production side into macroeconomic models. The dominance of macro stabilization economics and the omission of production knowledge has prevailed at the Federal Reserve Bank and the Treasury, the pinnacle of economic policymaking over recent decades. Kuznets and his team of statisticians did not have computers or today’s sophisticated data-generating survey techniques, but they did construct tables measuring the production capacity of the nation’s enterprises with estimates of the links between existing output and the output that could be achieved by undertaking macroeconomic bottleneck analysis and diffusing the best human resource change methodologies. These calculations were necessary inputs into the estimates of the nation’s supply capabilities that lay behind the strategic military decision to delay the Allied invasion of Europe until . Without them, the supply lines required for the D-Day landings would have been problematic, and the decision was made to not land in Europe until the supplies were in place to support the military drive across Europe of up to  million men and  million tanks, aircraft, and vehicles in the year-long effort. The wartime government did not depend upon or seek centralized authority to plan the economy as demanded by the military. It meant subordinating military authority over production planning to the economic statisticians at the WPB and subordinating the technology priorities of the military authorities to the OSRD. Within the WPB, the economic statisticians, partnering with production engineers, did not seek to supplant operational decision making at the enterprise level. Instead, they devised policies, including innovative planning accounting measures, to galvanize the energies of those with the requisite expertise, skills, and experience to design methods and practices to make advances in production performance happen. The government took over the banking system’s role described by Schumpeter as the ‘headquarters of the capitalist system’. During the war, two-thirds of expenditure on industrial facilities was directly financed by the government (White, : ; Jones and Angly, ). Economic policymakers went outside the market system to create a leasing mechanism to negotiate the industry–government divide. The Defense Plant Corporation (DPC) was created in  as a subsidiary of the Depression-era Reconstruction Finance Corporation (RFC), ‘with such powers as it may deem necessary to aid the Government of the United States in its national defense program’ (White, : ). The rules governing the RFC’s Depression-era financing of industry were

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

 . 

modified in May and June of  to enable subsidiaries of the RFC to finance and own defence plants, and to lease them to private industry (White, : ). Jessie Jones, the head of the DPC, was described by Time magazine in the following terms: ‘In all the U.S. today there is only one man whose power is greater: Franklin Roosevelt’ ( January ).

. P-W P L

.................................................................................................................................. The Second World War experience permanently transformed government and business institutional relationships in major ways. The neglect of economic analysis of these changes and consequences stems in part from the triumph of the free-market paradigm in post-war economic theory and policymaking. In this section, legacies of the Second World War transformational experience that permanently changed government and industry inter-relationships are sketched. First, while the Second World War mobilization agencies that implemented the transformation and galvanized growth were disbanded, many of their functions were incorporated into rapidly expanded departments of the federal government. The Department of Defense and the Department of Energy became the lead agencies in building a vast science/technology infrastructure which linked government agencies, industrial, university, and government laboratories, and business enterprises. The publicly stated purpose was national security. The Manhattan Project and the atom bomb seared into the body politic the role that science and scientists could play in defence and war. It was a de facto industrial policy administered by the Department of Defense. The United States does not have a department of industry, as industrial policy is ostensibly run by the Department of Commerce, but the title of the department is a giveaway: it is not about industry as the domain of production. Second, and closely related, the US government established an unrivalled management capability in inventing disruptive technologies that to date business enterprises have found difficult if not impossible to emulate. DARPA (Defense Advanced Research Projects Agency) has had a major influence on the invention of, for example, the Internet, UNIX, GPS, stealth fighters, the Windows operating system, the World Wide Web, videoconferencing, and Google Maps. Third, wartime planning, coordination, and accounting practices originally developed to manage multi-divisional enterprises were adapted to create a national industrial planning capability. Known as control materials planning (CMP), the performance accounting system involved the creation of a new tier of interorganizational management by which officers in government departments and prime contractors worked together, shared offices, and moved freely between government and contractor employment (Best, ). Today Boeing, for example, has a thousand employees working in the Federal Aviation Authority.

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-   



Fourth, the government institutionalized a vast procurement capacity, as it was and has remained the major customer of emergent technology-driven sectors. In fact, major export industries of America in the post-war period received substantial government R&D and purchasing support in their formative, low-productivity years (Markusen and Yudken, ). This included aircraft, computers, electronics, telecommunications, and instruments. It has been estimated that the federal government funded  per cent of the R&D for the emerging electronics industry in the s but as late as the mid-s the government purchased over two-thirds of the output of the aircraft industry. The wartime armaments industry morphed into a huge permanent governmentcontractor system and created what H. L. Nieburg () termed the ‘contract state’. In the words of Daniel Kevles (): ‘For almost a quarter century after , defense research expenditures rose virtually exponentially, even in constant dollars, accounting through  for  percent or more of the entire federal R&D budget. In , it was estimated that there were , defense research projects; in the early s, perhaps ,’ (: , cited in Hounshell, : ).⁷ Fifth, in macroeconomic policymaking the government combined Keynesian demand management with military expenditures which became a de facto long-term employment policy. While economics employment policy discourse focused on fiscal and monetary instruments, real-world high employment was dependent upon military spending. No other country had a science and technology infrastructure and government participation in the business world approaching the scale of the United States. In this respect, US defence policy is, in fact, its post-war industrial policy. Within the defence establishment it is celebrated as dual-use technology policy. Government-funded R&D for defence purposes generates new product and process ideas that can be put to commercial use as well as that of national security. As industrial policy its success record is mixed. On the plus side, it has fostered world-leading, high-tech regional innovation systems in Silicon Valley and Greater Boston. Both regions have enjoyed a rapidly expanding technology base, replenished by technological breakthroughs at an unprecedented rate by rapidly growing spin-off firms from world-leading universities. However, important as they have been in technology development, policy initiatives elsewhere to establish high-tech clusters have not proven tractable, particularly in localities suffering from the loss of manufacturing enterprises. This is understandable. The wartime government’s Office of Scientific Research and Development attracted many thousands of scientists and engineers to research, develop, and design advanced technology weapons systems in California and Massachusetts at huge expense. The result was a legacy post-war science, technology, and skill base which formed the ⁷ The extended global reach of the Pentagon was part of the process. In the s, the US armed forces were stationed in only three countries abroad. During the Second World War the number grew to thirty-nine. By the s the United States had over , military bases spread out over sixty-four countries (Best and Connolly,  []: –).

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

 . 

foundation for emergent industrial ecosystems in which early-stage technology development business systems could flourish. No single or even multiple state governments can invest more than a small fraction of what the federal government invested in Greater Boston and California from San Francisco south to San Diego (Wright, ). In any case, de-industrialization has persisted despite the combination of New Deal infrastructure investment in the South, the creation of the world-leading science and technology infrastructure, and a huge government procurement programme including for emergent sectors. Manufacturing employment declined by one-third between  and  and by a third again in the s. While service and temporary employment offset the lost manufacturing jobs, they did not provide the US$/hour-wage plus benefits for non-college educated workers. Macroeconomic policies did not come to the rescue. In fact, the wartime legacy turned what had been an inward-looking to an outward-looking orientation which, unintentionally, was a major force in driving American de-industrialization. The Second World War ended the long era of the British Empire and Pax Americana filled the vacuum. The United States and the Pentagon became the administrator of the nation’s , military bases around the world. In exchange for becoming allies in the Cold War the new US foreign industrial policy removed all barriers to imports and offered open access to the world’s biggest market. The defeated nations took full advantage of free entry into the massive US market to build manufacturing export industries. Moreover, these countries pursued exchange-rate and interest-rate policies in support of rebuilding their manufacturing bases. The exchange- and interest-rate policies pursued by the United States, meanwhile, decimated domestic manufacturing and supported the strategic export-driven policy frameworks of other nations. Most prominently, the long, costly, and unpopular war in Southeast Asia was largely funded by monetary creation rather than fiscal policy and the resultant inflation of the s (Best, ). Federal Reserve Chairman Paul Voelker, appointed from Goldman Sachs in  by President Carter, increased the interest rate to  per cent, seven points over the inflation rate, with devastating effects on the cost of credit upon which manufacturing investment is dependent. The high interest rates attracted huge capital inflows and the demand for US dollars led to a  per cent increase in the exchange rate over the next four years. The consequences were devastating for the profitability and global competitive advantage of US manufacturing. It marked the end of the Keynesian macroeconomic era and ushered in the Voelker-Greenspan-Reagan era of neoliberalism. Clinton acquiesced and agreed to Japan’s manipulation of the value of the yen in order to support Japanese manufacturing growth. In its simplest terms, the United States turned to a stabilization-informed macroeconomic policy framework at the same time other nations were subordinating stabilization policies to export-driven, capability-informed macroeconomic frameworks. The high interest rates attracted short-term capital inflows which drove up the demand for dollars and offset the growing trade imbalance in manufactured goods. Here America’s macro and trade policies contributed hugely to the conversion of the manufacturing belt into the Rust Belt.

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-   



. T J E M: R T M P

.................................................................................................................................. It is now conventional wisdom that, first in Japan and then in Germany, competitors emerged that built manufacturing export platforms based on more advanced production systems capable of achieving higher performance standards. In time they gained market share in the United States, which had been the world’s leading manufacturing nation. But less appreciated is that competition between the Japanese and American production systems was at the same time competition between two rival models of technology management at both the enterprise and industrial policy levels. In fact, foreign rivals pursued policy frameworks that turned America’s massive advantage in science and technology to their own manufacturing advantage. The competitive challenge to American industry began to appear in the s when the United States first began losing market share to Japan in the steel industry. It was attributed to a lack of investment in new continuous casting technologies by lethargic American steel companies, long-time members of a cosy cartel. But market share declines in complex production industries such as cameras, cars, and motorcycles soon followed. There was little cause for concern as various interpretations of the causes of decline in ‘traditional’ industries all agreed that America’s strength in hightech industries was unassailable. Heads finally turned in the early s as the pattern was repeating itself in semiconductors followed by semiconductor equipment makers and downstream industries such as advanced consumer electronics, computers, and telecommunications. In the late s, Japanese machine-tool companies mounted a vigorous and successful attack on America’s machine-tool industry with devastating effect. They did so by ramping up the production of CNC (computer-controlled) machine tools, a technology that had been invented in the United States but diffused rapidly into manufacturing in Japan. The Japanese production system evolved, in stages, into a superior technology management capability that exposed a weakness in the American production system. During the wartime production miracle, technological innovations were separated from manufacturing. Innovations in radar systems, for example, were not introduced to the aircraft production lines. The weakness of Germany and the reason it could not expand production of aircraft even close to the US scale is that they continuously changed aircraft design to improve its functioning. The United States did not; the design was frozen. The miracle advances in technologically advanced weapons systems were organized entirely separately. Japan’s manufacturing advantage was not based on building a bigger science and technology infrastructure than the United States. The Japanese business leaders and policymakers focused on building competitive advantage by superior manufacturing

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

 . 

performance. They began by applying lessons about the primacy of production capabilities, business organization, and skill formation from the US Second World War experience, and progressed rapidly up the production capability spectrum (Best, , ). Japanese enterprises advanced and institutionalized Second World War US production and management principles in the form of just-in-time, the quality movement, and kaizen. Unlike US post-war industrial policy, their policy framework was strategic. For example, they learned from W. Edwards Deming that US manufacturing enterprises did not embrace or even understand the fundamental organizational principle of system integration and systems thinking.⁸ America’s leadership in industry had been based on production engineering; but production engineering was never a concept in economic policymaking in the post-war era and without policies based on an accurate conception of production there could be no production economics. Second, Japanese enterprises moved beyond competitive advantage in production performance in cost, quality, and throughput efficiency to rapid new product development and technology management. Third, based on superior technology management capability, Japanese manufacturers converted access to America’s scientific and technology infrastructure into a strategic competitive advantage against US manufacturing. Unfortunately, in the post-war era, much of American business had turned to priceled, low-cost strategies which locked them into productive structures and work organizational practices and blinded them to the real competitive threat of enterprises elsewhere that emphasized increasing labour productivity rather than lowering wage costs. The emergent Japanese manufacturing advantage can also be described as a rival technology policy paradigm anchored not in leadership in science but in organizing an industrial ecosystem in which business enterprises could pursue a strategy based on building world-class manufacturing capabilities in production, new product development, and technology management. In the United States the presumption was that US technology policy would prevail, since Japan lacked a vast science and technology infrastructure that included an unrivalled research-intensive university system producing scientists and engineers. The result was a change in the dominant form of competition from price led to product led. The defining feature of the mass-production system when it emerged, and the reason that it put all other production systems on notice in its time was that it drove down the costs and prices of production. The defining feature of the New Competition emergent in Japan was rapid new product development created by the marriage of ⁸ Deming remarked that what he took to Japan was the ‘theory of the system’ (personal conversations, ). He meant, in part, that much of US business enterprise was functionally departmentalized into profit centres to achieve local optimization without regard to interdependencies, and that with Japanese management came managing interrelationship across business activities, hence the organizational principle of process integration, later adopted by management consultants as process re-engineering. Instead of optimizing business functions A, B, and C independently as in US business, the Japanese focused on AB, AC, and ABC, thereby filling in white spots in the organizational charts of US firms (Best, ).

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-   



productivity and innovation, and the redefinition of both. The result was a new interactive manufacturing and innovation dynamic. Japan did it, not by investing heavily in the creation of a science and technology infrastructure, but by building a production capability that could turn America’s technology knowledge base into a national competitive advantage for Japan at the expense of American manufacturing. The rival technology paradigm was about shifting the technological base from the science end of the spectrum to the production end. Technological innovation is driven as much by competitive dynamics as by ‘science push’.⁹ Research in fundamental science is less important than cultivating the already existing technology base which can be harvested for new technological combinations and permutations as part of the product development process. They all involve the creation of new technological knowledge. Knowledge is certainly crucial to new product development. But knowledge is not research; knowledge is the accumulated stock of wisdom that can be reinterpreted, combined and recombined in new ways. Technological knowledge, unlike scientific knowledge, is not always codified or even explicit. Polanyi, Penrose, and others have stressed the role of technological and experiential knowledge as tacit or informal knowledge often built into collective organizational practices, much as craft skills are inseparable from the muscle memory of machinists and technicians who have learned by doing. To summarize, product-led competition engendered new organizational capabilities which involve the redefinition and integration of three processes: . Manufacturing. The cell is the building block of the whole edifice; without cellular manufacturing the rest of the business system cannot drive product-led competition. . Design/manufacturing cycle. Companies need to compete on the basis of rapid new product development, or they will fall behind in technology adoption. . Technology diffusion. This is pulled by the first two processes as distinct from being pushed by autonomous R&D activities. The US technology leadership paradigm was based on three implicit assumptions. In this it was a failed industrial policy strategy. The first assumption was that technological innovation travels along a one-way sequence of activities proceeding from basic science to applied science to engineering science to engineering design and development to production. The presupposition was that scientific pre-eminence generated technological pre-eminence which, in turn, assures product pre-eminence. The second assumption was that technology diffusion follows a –-year cycle. By the time that Japan and other countries were able to capitalize on ⁹ Stephen Kline () presented a long list of industries that were formed without direct linkage to science, at least new science developed in R&D laboratories: the jet engine, sewing machines, weaving machinery, machine tools, most construction methods, space shuttles, turbomachinery, combined-cycle power plants, vertical and slant take-off and landing aircraft, and integrated circuits.

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

 . 

the commodity production stage of the product life cycle, US firms would have moved on to leadership in the development of new products. The third assumption was that organizational capabilities are not important in explaining competitive advantage. Therefore, the threat to US manufacturing competitiveness came as a surprise. It was witnessed first in an order-of-magnitude advance in both lower-cost and higher-quality performance previously assumed to be a trade-off. Anchored in a participatory model of work organization, the Japanese production system established new performance standards for cost, quality, and time to market. The latter was a consequence of superior new product development and technology management capabilities. The consequences of the loss of competitiveness of American manufacturing were evident with the unexpected fiscal crises of US manufacturing belt cities as early as the s. To understand these new dynamic forces, including the structural roots of deindustrialization, we must go inside the policy frameworks and core processes that drive modern economies both in the United States and other nations.

. P S L: T N   S

.................................................................................................................................. The United States has always been divided between a Northern and a Southern production system and social structures. While part of a single nation, the two regions evolved radically distinctive models of capitalism, modes of economic governance, business organization, and labour systems. From the early days of the plantation economy, the South has been organized around extractive industries. In contrast, from the early days of the manufacturing economy, the North underwent a historical trajectory of industrial transition and technological innovation. Economies are complex and terms arise in economics discourse to simplify and enable discussion. For example, the term ‘miracle’ is commonly used to describe rapid economic transformations that are outside conventional economic theory and policy frameworks. I suggest that in the United States a common taxonomy of geographical belts is another example. Miracles and belts are metaphors that facilitate communication about economic matters that are deemed important, but which are not anchored within the boundaries of market-centric economics. Efforts to better understand both require concepts that undermine the assumptions required by market fundamentalism. In this section I apply the metaphor of economic ‘belts’ to contrast regionally distinctive systems of production and economic governance that evolved in the United States. It has a second purpose. The major argument of the chapter is that the neo-liberal policy revolution in the s was not new to the nation but has always dominated economic governance in the South. Its extension to the national policy framework for the first time was a triumph of the South’s political elite and the production system it governs.

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-   



.. The Manufacturing Belt America’s economic governance practices going back to the founding of the Republic focused attention on infrastructural requirements, both physical and organizational, to advance the nation’s productive structures. Educational, technical, and financial infrastructures were organized within a strategic economic governance framework to promote manufacturing and national independence. Alexander Hamilton’s attention to manufacturing is well known, but I suggest that Thomas Jefferson was an equally important developer of the emerging and globally distinctive Northern production system (Best, ; Winchester, ).¹⁰ As President Washington’s ambassador to France, Jefferson, like Benjamin Franklin, was highly learned in the advances being made in French science and engineering. Jefferson brought to America the production principle of interchangeability, a French invention but not practice, and championed its introduction in the nation’s armouries. Under Colonel Roswell Lee, the Springfield Armory in Massachusetts was organized to operationalize the principle of interchangeability of parts which institutionalized product engineering as a defining characteristic of what the British termed the ‘American system of manufacturing’ or just the ‘American System’ (Marshall,  []: –). This became the strategic industrial policy that organized the creation of the first machine-tool industry based on interchangeability, a precondition for American mass production. It also unleashed the competitive drive for ever-smaller dimensions and precision engineering, perhaps the most important and enduring source of American technological leadership. The drive to ever-smaller critical-size dimensions is at the core of America’s unmatched advantage in opening new technological domains (see figure . in Best, ). Industrial policies that are informed by fundamental production principles are integral to advancing a nation’s productive structures and establishing industrial success and national competitive advantage. But implementation depends upon investment in engineering education. As president, Jefferson founded the nation’s first engineering college at West Point, birthing the Army Corps of Engineers. Thus began the institutionalization of the American civil engineering expertise which enabled physical infrastructural investments in transportation and energy and the creation of America’s ‘industrial heartland’. Presidents Abraham Lincoln, a railroad lawyer, and Franklin Roosevelt also undertook nationwide policies to advance engineering and science education to upgrade the production capabilities of the nation’s business enterprises and increase the skills and productivity of the nation’s labour force. It is but one form of extra-firm infrastructure that impacts on business system development, opportunities for innovation, and national productivity. ¹⁰ See Smith and Clancey (: ) for Jefferson’s letters on manufacturing, for example, ‘experience has taught me that manufactures are now as necessary to our independence as to our comfort’,  January ; and Marx (: ) for Jefferson’s views on machines and ‘technology’, before the term was coined in  by Jacob Bigelow.

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

 . 

In these ways the skill formation domain of the triangular relations linking government, education, and industry was shaped in sync with the emergence of a machinist community that was integral to the emergence and growth of many new sectors and the diffusion of the American practice of product engineering as the catalyst for tool design and the historical trajectory of driving down critical-size dimensions. Precision engineering opened new technological domains. Cities, including Springfield, MA, Providence, RI, and greater Boston, grew and extended to push the emergent manufacturing belt westward. Thus began the establishment of America’s industrial heartland, commonly described as the manufacturing belt. Early in the s, in the words of Paul Krugman, ‘geographers noted the great bulk of U.S. manufacturing was concentrated in a relatively small part of the Northeast and the eastern part of the Midwest . . . within the approximate parallelogram Green Bay—St. Louis—Baltimore—Portland’ (Krugman, : ). It proved remarkably persistent from its peak in  when it is estimated to have accounted for  per cent of America’s manufacturing employment up until  when it still contained  per cent of the nation’s manufacturing jobs. Equally remarkable, until well into the twentieth century, ‘most of the manufacturing activities outside [the manufacturing belt] were concentrated in processing of primary products or manufacturing for a very local area’ (Krugman, : –). This was the heartland of American manufacturing which propelled the nation’s industrial leadership and was a platform for realizing Roosevelt’s Arsenal of Democracy vision. It encompassed both the ‘American system of manufacturing’, driven by the world’s first machine-tool industry based on the principle of interchangeability in the nineteenth century, and the first mass-production enterprises organized by the principle of flow in the first half of the twentieth century.¹¹ Wages increased with productivity; the public school system was funded by business and local property taxes; research-intensive universities established by the Morrill Act of  flourished in every state throughout the region and established an educational pathway to an engineering curriculum in sync with the needs of emerging technologies, fast-growing enterprises, sectors, and clusters; the machine-tool industry acted as an extra-firm infrastructure working closely with technology-innovative firms but also provided the tooling, machines, instruments, and equipment for the mass producers required for continuous innovation; state-chartered banks provided due diligence and patient capital for growing enterprises, whole sectors, and cluster dynamic processes; and the federal government designed, engineered, often funded, and organized the building of transportation, energy, and communication material infrastructures that turned the wheels of a multi-state region, combining a regional production system with its productivity and wages with a matching demand side in the form of a large and accessible market.

¹¹ Flow lines had existed but none before were organized around the engineering principle of equalizing cycle times for all activities. This is a requirement for manufacturing without inventory.

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-   



The post-war mythology has been that free markets created America’s industrial heartland; but markets do not create, only people and organizations have the power to create. Groups of people working together build and organize companies and, with the support of government policies and infrastructures, mutually create industrial ecosystems that foster cluster dynamic processes. The bottom line is that firms, individually and collectively, are the drivers of innovation and production capability development; markets are the servants of successful economic policymaking, not the masters. Governments are organizers of the requisite regulatory systems and infrastructures that can turn markets into useful servants of policy frameworks. Regulation is a bulwark to prevent corporate political power from capturing government and fostering a business culture dependent upon subsidization as distinct from an entrepreneurial business culture that fosters innovation. No other part of the nation had cities populated by symbiotically networked groups of specialist innovative enterprises which collectively and cumulatively advanced a region’s production capabilities, skill formation processes, and distinctive technology bases. Manufacturing enterprises in the rest of the nation were largely concentrated in the processing of primary products or producing for a local market. While some were individually successful, none were embedded in innovative industrial ecosystems that advanced a region’s production capabilities and skill base. Krugman and others explain the geographical concentration of manufacturing in the manufacturing belt in terms of declining transportation costs and expanding access to an increasing national market, but these were the effect of successful industrial and infrastructural policies. Market fundamentalism ignores how important the ways in which the interrelations between government and the economy are organized is to development. Historians debate whether it was the states or the federal government that did more to lay the foundations of US industrial development. It was both together. Lamoreaux and Wallis (n.d.) conclude that in the mid-western states an ‘extraordinary penetration of the state and civil society . . . was often strongly regulatory in its impetus yet sustained by an unusual degree of legitimacy’. This is what distinguished the governance institutions upon which the industrial heartland of the United States was built. It was an extraordinary example of social democracy.

.. The Sun Belt In contrast to the Midwest, the South did not attach itself to the manufacturing system that began along the north-east coast. Emancipation ended the plantation system in  and freed  million slaves. The slaves were liberated, but the production system was not transformed. The land remained concentrated, and the social and political structure of the plantation economy persisted. New forms of labour coercion were created, and the industrial structure remained one of resource extraction rather than organizational capability development. What Eric Foner () calls the unfinished

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

 . 

revolution was entrenched along with race hierarchy. The th Amendment to the Constitution prohibited slavery and involuntary servitude but it had an escape clause. Anyone duly convicted of a crime was exempted from the prohibition. Rapidly, a vast number of ex-slaves became subject to newly passed local laws such as vagrancy, which included not being able to show current employment, to create a post-emancipation, peonage labour system composed of various forms of involuntary servitude such as penal labour, convict leasing, and debt bondage.¹² The debt-peonage system was dependent on sharecroppers’ lack of numeracy. President Lyndon B. Johnson abolished peonage in , which ‘rapidly decreased sharecropping in every plantation nationwide’.¹³ Manufacturing was limited to large processing factories in lumber, tobacco, and chemicals or to small craft enterprises serving local markets. The ubiquitous metalworking machine shops supplying parts, tooling, and machinery critical to the emergence of the manufacturing belt cities were non-existent in the South. Post-Civil War tenant farmers and sharecroppers, unlike landowning farmers of the North, did not create enough demand to foster local village or small-town markets and stimulate cityregion growth dynamics. David Meyer estimates that the South’s share of national value added in manufacturing remained about  per cent from  to  (: ). Textiles were the growth exception, increasing from  to  per cent over the period. During the period only textile firms relocated into or started in the South in pursuit of large supplies of low-wage labour. With this exception, the industrial ecosystems and the markets of the Northern manufacturing cities provided too many advantages for firms to move outside the manufacturing belt. Robin Einhorn’s (a) classic comparison of the tax systems of the North and the South has become highly relevant to the present period. From the beginning the Northern colonies collected taxes for the public provision of material and organizational infrastructures, such as education and the federal armouries, and legislated for a financial regulatory environment that would support the development of the nation’s nascent manufacturing capabilities. It evolved into a three-tier system of local, state, and national-level government, each with tax-raising power to fund public services and otherwise foster industry–government partnerships, and develop the businesses, employment opportunities, and communities that came to constitute the nation’s industrial heartland. The South had an entirely different agenda. In the words of Einhorn (b): Slaveholders had little need for transportation improvements (since their land was often already on good transportation links such as rivers) and hardly any interest in an educated workforce (it was illegal to teach slaves to read and write because slaveholders thought education would help African Americans seize their freedom). ¹² https://en.wikipedia.org/wiki/Peon; https://en.wikipedia.org/wiki/Slavery_in_the_United_States. ¹³ https://en.wikipedia.org/wiki/History_of_unfree_labor_in_the_United_States.

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-   



Slaveholders wanted the military, not least to promote the westward expansion of slavery, and they also wanted local police forces (‘slave patrols’) to protect them against rebellious slaves. They wanted all manner of government action to protect slavery, while they tended to dismiss everything else as wasteful government spending.

The Southern colonies feared that taxes on wealth (i.e. slaves) could be a Trojan horse threatening the institution of slavery. In the name of states’ rights and freedom from federal government interference and regulations, the South opposed all forms of public power and public decision-making. Manufacturing cities did not develop, even with huge subsidies from TVA, and other national infrastructure and low-cost energy supplied by the federal government. State and local government were not organized to learn from their rapidly growing Northern counterparts. By the early decades of the twentieth century, Southern political leaders began to pursue a strategy of modernizing state government, improving public facilities, and subsidizing business enterprises to encourage industrial growth (Cobb, : –). By the s and s states had sanctioned and supervised the sale of municipal bonds to finance industrial plant construction. While the granting of subsidies by towns to encourage access to railroad companies, for example, had long existed, it became the centrepiece of the region’s industrial policy. It began a new era of competitive subsidization by state and local governments attracting and adopting ‘footloose’ branches of enterprises from the manufacturing belt rather than investing in the infrastructures to grow indigenous manufacturing enterprises (Cobb, ). The labour strategy of the South did not include establishing skill-formation institutions, either within business enterprises or public education. It did not stem the Great Migration in which  million African Americans migrated out of the South between  and .¹⁴ The Depression of the s hit hard. In , President Franklin D. Roosevelt declared that America’s number one economic problem was the continued impoverishment in the South. The New Deal imposed the most extravagant regional-cumindustrial policy in the nation’s history and set the stage for the South’s growth during the Second World War and the post-war decades. In his account of the impact of the New Deal in South Carolina, Jack Irby Hayes, Jr writes that the Public Works Administration (PWA)—created under the National Industrial Recovery Act during the first wave of New Deal legislation—‘literally changed the face of the Palmetto State. Its visible legacy a half-century later included hundreds of low-cost housing units to replace urban slums, miles of modern highways, a host of schools, courthouses, hospitals, post offices, and administrative buildings, a thriving shipyard, a number of new sewage and water systems, and two huge hydroelectric projects’ (Hayes, : ). Gavin Wright (, ) confirms the size of the New Deal’s infrastructural investments in the South. In , one-third of the nation’s urban population drank untreated water; by , less than . per cent. Southern cities were disproportionate beneficiaries of this remarkable upgrade, but prior to the New Deal, many of them ¹⁴ (https://en.wikipedia.org/wiki/Great_Migration_(African_American).)

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

 . 

lacked the fiscal capacity or political will to improve basic public services. Altogether, the New Deal spent more than US$ billion in the South, much of which supported ‘the types of services that southern cities would not have provided even in good times’. Equally important for regional development was the electrification of farms, homes, and industries. By far the most visible and controversial New Deal electric power programme was the Tennessee Valley Authority (TVA), created during the first hundred days of legislation in . Between  and , the TVA completed seven major dams. Rapid diffusion of electricity usage was encouraged not just by lower rates but by subsidized loans for rural service, initially from the TVA but after  through the Rural Electrification Administration (REA), primarily to cooperatives. By ,  per cent of households in the valley were electrified, compared to just  per cent in .¹⁵ The South’s post-war industrial strategy was two-pronged: first, to build a regional competitive advantage in high-volume, low-cost, price-led production processes to become dominant in the national market. The business strategy was to attract enterprises and particularly branches of labour-intensive enterprises primarily from the manufacturing belt. The New Deal infrastructural investments in transportation, electric power, and communications were necessary for the success of the business strategy. The large textile and furniture factories set a pattern for much of subsequent Southern industrialization. In contrast to the product-led business strategies required to compete in the rapidly changing complex production industries, the sectors in which the South specialized did not entail investing in workforce skills, which precluded transitioning to world-class manufacturing practices or participatory forms of work organization and which ultimately made the South vulnerable to off-shoring for low-wage labour. The second part of the strategy was to build and exercise political muscle in Washington, DC to attract federal funding concentrating heavily on military installations and bases from the Department of Defense, the Atomic Energy Commission and its successor the Department of Energy, and NASA. During the Second World War the WPB gave special treatment to the South and invested heavily in military bases and production. The South’s share of military prime contract awards roughly doubled from under  per cent in  to roughly  per cent in the years – to nearly one-quarter in the s (Schulman, : , table .). In the words of Schulman, ‘Defense dollars permeated nearly every town in the region’ (: ), and by  more Southerners worked in defence-related industries than in textiles, synthetics, and apparel combined. The South was hugely successful in attracting defence contractors. ‘During the s, the New York Times reported that defence was the single largest employer in four southern states, outpacing agriculture, textiles, lumber and all the others. And of the top ten US defence contractors, seven, including Lockheed, McDonnell-Douglas, General Dynamics, and Rockwell operated large installations in the South’ (Schulman, : ). Marietta, Georgia, the home of Lockheed-Georgia, the single largest

¹⁵ See Robert Caro (: –) for a description of rural life without electricity.

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-   



business organization in the Southeast in the s and s, employed workers in fifty-five of Georgia’s  counties (Schulman, : ). But the strategy was not limited to military contracts. The South long played the role of commissary to the nation’s armed forces, providing textiles, tobacco, food, and coal. The South had become fortress Dixie and the Sun Belt became the southern periphery of the Gun Belt.

.. The Gun Belt The United States transitioned from a virtually non-existent pre-war weapons industry to a defence budget larger than the defence budgets of all other nations combined.¹⁵ Defence expenditures remained over  per cent of GDP into the s and over  per cent until the end of the Cold War.¹⁶ Harry Magdoff and Paul Sweezy () argued that the success of the New Economics of Keynesian demand-management theory rested heavily on military expenditures. Out of the total federal purchases of US$. trillion between  and , US$. trillion were defence-related spending (including debt payments for previous wars, veterans’ benefits, space exploration, and the Atomic Energy Commission). Without this spending, they argue, unemployment rates in the post-war period would have approximated those of the Great Depression. Geographically, the Gun Belt forms a periphery along the east and west coasts and across the South (Markusen et. al., ; Markusen and Yudken, ; Wright, ). The Gun Belt is a composite of two types of industrial policy. The first involves large R&D expenditures to design and develop technologically advanced weapons systems. It has fostered high-tech regional innovation systems consisting of research-intensive universities, open-system business models, and ‘manufactories of new sectors’ (Best, ), of which Silicon Valley and Greater Boston are the leading examples. Other cities or regions that have leveraged defence department R&D to build researchintensive universities and develop distinctive technology bases include the North Carolina Research Triangle, Los Angeles, San Diego, and Seattle.¹⁷ Federal funds are complemented by city and state government infrastructural support to

¹⁵ To quote Jessica Mathews (): ‘Today U.S. defense spending is exceptional in two ways. First, it spends more than the next eight largest spenders combined—China, Saudi Arabia, India, France, Russia, Britain, Germany, and Japan. Second, defense accounts for almost three-fifths of the federal government’s discretionary budget. This is a measure of all federal spending other than mandatory allotments to entitlements and interest on the national debt. Discretionary spending is everything else the government does.’ ¹⁶ In the Second World War defence spending peaked at  per cent of GDP, and then declined to about  per cent at the height of the Cold War. Thereafter it declined to – per cent of GDP, with surges during the s and the s (https://www.usgovernmentspending.com/defense_spending). ¹⁷ Northern Virginia is a special case; most of its research activity is classified. See Best ().

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

 . 

establish industrial ecosystems that foster localized technology and enterprise capability development.¹⁸ The second form of defence-driven industrial policy is purchasing contracts for supply of the myriad provisions required to support the various arms and activities of the defence department at home and abroad. The major labour-intensive industries of the South, such as textiles and furniture, have long-established supply relationships to the government to complement commercial sales. But the production system is that of the South, which specializes in commodity products for which design changes are rare and investment in skilled labour is not required. The South has attracted Gun-Belt federal funding for high-tech programmes, most notably NASA in Florida and Houston, and research universities in Atlanta, Austin, and San Antonio. But the region has not established cities that foster indigenous innovative enterprises and the cluster growth dynamics that historically populated the North and built the nation’s industrial heartland. In terms of employment, the Gun Belt became as important to the US economy and industrial policy in the post-war era as the manufacturing belt and industrial policy that fostered manufacturing infrastructures and nurtured city growth dynamics had been to the pre-war and wartime economy. Moreover, the high-tech regions have been hugely successful in advanced technology weapons systems and creating new spin-off information technology sectors. Nevertheless, despite the huge defence expenditures on R&D and high-tech business development, and other military spending, manufacturing’s share of total US employment dropped from close to  per cent in  to  per cent in  (Baily and Bosworth, ). What the Gun Belt has not done is to create high-paying manufacturing employment on the scale of the manufacturing belt in the United States’ industrial heartland.

.. The Rust Belt The s were a turning point in US industrial leadership and policymaking. The manufacturing belt became the Rust Belt.¹⁹ Factory employment in the nation’s manufacturing sector declined by one-third between  and . In an ironic twist with tragic consequences, the industrial heartland in the United States, where management and labour worked together to meet the production targets to win the Second World War, became the victim of the nation’s success. At exactly the time when industrial policy was most necessary to address the challenge of restructuring the nation’s manufacturing system, US political leadership and economic policymakers chose to look the other way. The fate of the US industrial heartland was ¹⁸ See Gavin Wright () for a history of the ‘handful of “knowledge economy” clusters that dot the country’s western coastline’. Wright maintains that ‘World War II was indeed the triggering shock that set in motion chains of events whose outcome was the Pacific coast economy as we know it’. ¹⁹ https://en.wikipedia.org/wiki/Rust_Belt.

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-   



subordinated to the pursuit of the United States’ new political role in the global economy. It was an opportunity seized upon by the South’s political leaders to pursue a campaign to dismantle tax, regulatory, and labour policies and the manufacturing infrastructures that had long been integral to the nation’s industrial heartland. The political and business leadership of the South has never accepted the production organization challenge of Henry Ford to make changes in the organization of production, engineering principles, and work practices to advance productivity and deliver the wages upon which the US middle class was built. The New Deal came up against the hierarchical social structure of the South and its dependence on maintaining the repressive labour systems and the political power of the beneficiaries of the extractive industries upon which vast fortunes had been built that had endured for centuries. History offers few if any examples of the landowning elites of plantation economies establishing transformative policy frameworks. New territories were developed and new types of extractive industries have been organized, but the autocratic, exploitative business model is a constant. The first signs of what became a long-term de-industrialization process were in the s when the fortunes of the cities that constituted the manufacturing belt began to suffer from declining tax bases, which came to a head in the fiscal crisis of big-city governments in the s (O’Connor, ; Best and Connolly,  []; Bluestone and Harrison, ). Historian Jon Teaford examined twelve large cities in the manufacturing belt, each of which had a population of over a half a million in . None of these cities had lost population before the decade of the s and most had enjoyed the reputation of a boomtown, doubling in population every ten years. All these cities, except for New York, declined in population during every decade from  to  (Teaford, : ). Only Boston was later to recover as the region became known as the Rust Belt. All other cities undertook industrial policies to revitalize, but to little effect. Larger forces were at play. Teaford states: It was a gradual slide from a position of economic supremacy, that slide beginning prior to World War II and persisting throughout the remainder of the century. Midwestern cities no longer were economic miracles as in bygone days . . . at the close of the s they all feared an emerging vision of the interior as void . . . Midwestern cities were on the defensive, and their economic and political leaders would embody every tactic, offer every lure, and unleash every power at their command to keep a corporate headquarters, revive an aging steel plant, or halt the slow death of downtown retailing. (Teaford, )

The de-industrialization dynamics have not been limited to the North. The United States lost one-third of its manufacturing employment in the decade of the s but this time it was disproportionately in small towns of the rural South. David Carlton and Peter Coclanis () cite the example of North Carolina, the leading manufacturing state of the South. In the first decade of this century, North Carolina’s manufacturing employment dropped by  per cent, from , to ,. Two of North

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

 . 

Carolina’s major industries suffered the most: textiles lost  per cent of its employment between  and , and furniture lost nearly  per cent.

. N-  D  ‘A S’

.................................................................................................................................. The s marked the beginning of the end of the tradition of the anti-trust and proregulation agenda based on the distrust of concentration of political and economic power going back to Thomas Jefferson and James Madison, the framers of the Constitution and the authors of Federalist Paper No. . They argued the nation could have democracy or concentrated wealth, but not both. While corporations barely existed at the time of the ratification of the United States Constitution and Bill of Rights, stark warnings about the risks to the survival of democratic institutions of corporations with unaccountable power engaging in political activities were articulated by Jefferson and Madison a quarter-century after their ratification. In , Jefferson, second president of the United States, urged that we ‘crush in its birth the aristocracy of our monied corporations which dare already to challenge our government to a trial of strength, and bid defiance to the laws of our country’. Madison, fourth president and also hailed as the ‘father of the Constitution’, was equally blunt: ‘There is an evil which ought to be guarded against in the indefinite accumulation of property from the capacity of holding it in perpetuity by ecclesiastical corporations . . . the growing wealth acquired by them never fails to be a source of abuses’ (Whitehouse and Stinnett, : –). In the time of Jefferson and Madison, the challenge of political dominance of government by ‘monied corporations’ had only begun. By the Gilded Age of the last decades of the s the power of corporations to foster economic prosperity and to capture government were both operating in high gear. But the power of the ‘robber barons’ to control government and subvert democracy did not last. The resulting increase in inequality and economic hardship provoked the progressive era in US politics. President Theodore Roosevelt engineered the passage of the Tillman Act in  which outlawed corporate contributions to politics.²⁰ In , President Woodrow Wilson passed into law the Federal Reserve Act which was to supervise banks and had the dual mandate of maximizing employment and keeping inflation low, in  the Clayton Antitrust Act was passed prohibiting anti-competitive mergers, predatory and discriminatory pricing, and other forms of unethical corporate behaviour, and the ²⁰ The Tillman Act did not require proof of corrupt intent by the corporation, mere contribution of corporate funds to politicians sufficed to establish ‘corruption’. Political spending was not potentially corrupting, it was corruption as the term was used in the Act (Whitehouse and Stinnett, : ).

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-   



Federal Trade Commission was created also in  to protect consumers. President Franklin Roosevelt signed the United States Banking Act (Glass–Steagall) in , which decentralized and restructured the banking industry, including the separation of commercial banks from investment banks and securities dealers; and the National Labor Relations Act (Wagner) in , which guarantees the right of private-sector employees to organize into trade unions, to engage in collective bargaining, and to take collective action such as strikes. His administration also launched anti-trust investigations into ‘housing, construction, tire, newsprint, steel, potash, sulphur, retail, fertilizer, tobacco, shoe, and various agricultural industries’ (Stoller, ).²¹ The Celler–Kefauver Act was passed in  to reform and strengthen the Clayton Antitrust Act of , which had amended the Sherman Antitrust Act of .The anti-trust tradition dating back to Thomas Jefferson lasted for the first three post-Second World War decades. Matt Stoller () dates the dismantling of the regulation tradition to the alliance of the post-Watergate generation of congressional Democrats with the traditional antiregulation Republicans which in  combined to overthrow Wright Patman, the chairman of the US House Committee on Banking and Currency. A former cotton tenant farmer, he had served in Congress since . In the words of Stoller: It was a revolution and signalled the end of an era in which banks and big business were largely kept under control. In  Patman authored the Robinson–Patman Act, followed by the Bank Secrecy Act, successfully defended Glass–Steagall . . . authored the Employment Act of  and initiated the first investigation into the Nixon administration over Watergate. With Supreme Court Justice Louis Brandeis . . . the New Dealers drafted legislation into legally actionable ideas to formalize the sentiment that big business and democracy were rivals. ‘We may have democracy, or we may have wealth concentrated in the hands of the few,’ Brandeis said, ‘but we can’t have both.’ (Stoller, )

President Jimmy Carter deregulated the trucking, banking, and airline industries with the appointment of Alfred Kahn as ‘anti-inflation czar’. President Reagan went further; the dismantling of regulation became his major legacy and heralded the end of regulatory policies to constrain economic and political power. President Clinton joined the deregulation crusade and oversaw rapid increases in monopoly and accompanying political power in banking, media, oil, and telecommunications. Not by coincidence, the s marked the beginning of a shift in economic discourse from the mixed economy of Paul Samuelson’s economics textbooks to the policymaking dominance of market fundamentalism. Alan Greenspan captured the essence ²¹ Franklin D. Roosevelt described the powerful forces of ‘organized money’ as ‘this resolute enemy within our gates’: ‘Never before in all our history have these forces been so united against one candidate as they stand against me—and I welcome their hatred. I should like to have it said of my first administration that in it the forces of selfishness and of lust for power met their match. I should like to have it said of my second administration that in it these forces met their master’ (Whitehouse and Stinnett, : ; see also Phillips-Fein, ).

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

 . 

of market fundamentalism: ‘The ultimate regulator of competition in a free economy is the capital market.’²² He became the nation’s single most powerful economic policymaker. From  to  Greenspan was chairman of the Council of Economic Advisors under President Gerald Ford before becoming chair of the Federal Reserve Bank of the United States from  to . As observed by Stoller: ‘The following year the financial crisis exploded the myth that the nation’s deregulated financial institutions were the guarantors of economic progress. The financial bailouts also illustrated their political power.’ Perhaps an even greater measure of the myth of de-regulation to foster economic prosperity has been the explosive growth in inequality and the hollowing out of the nation’s manufacturing capabilities in recent decades. In the s, a period of widespread prosperity, the ratio between executive pay and worker pay was :; it reached over : in . In , the Securities and Exchange Commission issued a new rule—b- of the Securities Exchange Act. Historically, stock buybacks by corporate managers were illegal. The new rule enabled corporate managers to purchase large quantities of their company’s stock without being accused of stock-price manipulation. Buybacks reward investors and CEOs only. The consequences for workers and their communities have been devastating. In a study of  companies listed continuously in the S&P  between  and , William Lazonick found stock buybacks consumed  per cent and dividends  per cent of net income. In his words: ‘Excluding the recession years  and , buybacks and dividends taken together have averaged  per cent of net earnings for all corporations since ’ (). This leaves little for R&D, investing in production capabilities, new product development, technology management, worker training, worker benefits, worker salaries. The corporate business model, by which the nation established global leadership in manufacturing, was swept away and the engineering culture and worker skills upon which it depended went with it. Put simply, the value-creating business system gave way to a value-extracting business system organized to drive up CEO salaries and shareholder returns. Business enterprises were financialized as activist investors, aka vulture capitalists, who buy a controlling stake in a corporation, cut jobs and other costs to drive up the share price, and get out leaving a weakened business behind. They ignore the long-term work of building a company and all too often destroy it instead. The destructive consequences of neo-liberalism for the common good have been obscured by billionaire-funded foundations and thinktanks to shape economic discourse.²³ The American Enterprise Institute, the Cato Foundation, the Heritage

²² From a paper presented at the Antitrust Seminar of the National Association of Business Economists in Cleveland,  September . Available at https://www.aei.org/carpe-diem/alan-greenspanon-monopoly-and-antitrust-policy-in-/. ²³ President Richard Nixon appointed Lewis Powell, a long-time attorney for the tobacco industry, to the Supreme Court in . He was the author of the Powell Memorandum, a secretive call to action for billionaires to overthrow the tyranny of regulation by spreading the doctrine of market fundamentalism (Mayer, ; Phillips-Fein, ).

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-   



Foundation, and the Olin Foundation are major benefactors and champions of billionaire-funded neo-liberal economic discourse. The economics they espouse did not alert the nation to the destructive consequences of the neo-liberalism. The reality is that the nation’s once powerful manufacturing enterprises were left ill equipped to compete against production systems organized around world-class manufacturing principles and self-directed work teams as in Japan, co-determination models for building innovative business enterprises as in Germany, or the latecomer advantage successfully implemented by Chinese policymakers starting at the bottom but undertaking a business development strategy organized to move up the production capability spectrum (Best, ). We turn next to an alternative economics perspective and policy framework that draws lessons from the building of the nation’s industrial heartland, the building of the Arsenal of Democracy, as well as successful post-war transformative experiences elsewhere.

. T C T  P F

.................................................................................................................................. The catastrophic consequences of four decades of neo-liberal policymaking are becoming increasingly apparent. The once world-leading productive structures of the US economy have undergone perhaps the sharpest organizational erosion in history. The challenge of overcoming deficits in production capabilities, worker skills, infrastructures, and industrial ecosystems to reclaim the American Dream are formidable, even without pandemics and climate change. The first requirement is an objective assessment of the state of the nation’s economy. The second requirement is to learn lessons from historical experiences of successful economic transformations. These are called economic miracles, and it will take a transformative vision and political leadership on the economic ‘miracle’ scale to address the combined challenges of pandemics, climate change, and nearly half a century of neo-liberalism. Besides Franklin Roosevelt and the Second World War, examples of such leadership include the work of Deng Xiaoping (China), Taiichi Ohno/ Edwards Deming (Japan), Ludwig Erhard (West Germany), Ralph Flanders (Massachusetts), and Kenneth Whitaker (Ireland) (Best, ). These are all architects of strategic policy frameworks that have transformed economies facing serious challenges. I use the capability triad as an expository device to characterize common policy framework lessons. It asserts the following proposition: Rapid growth can only be achieved through the careful pursuit of interconnected strategies in each of three domains: production capabilities, business organization, and skill formation. The three domains are not separable and additive components of growth, but mutually interdependent sub systems of a single developmental

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 . 

process. No one of the three elements of the capability triad can contribute to growth independently of mutual adjustment processes involving all three elements. (Best, : ; Best, )

Roosevelt’s Arsenal of Democracy policy framework is informative with respect to the failure of the New Deal. The latter was based on a Keynesian-like deficient demand economics in which increased spending and infrastructure investments would expand demand and incentivize business to increase production. Like all market-centric economics, the focus did not go inside the organization of production and business organization to focus on capability development; the focus instead was on taxes and subsidies without regard to the structures of production and business organization. President Roosevelt’s vision of creating an Arsenal of Democracy to win the war against fascism called for a policy framework to achieve an order of magnitude increase in output without an increase in the civilian labour force. Unlike the New Deal, it was anchored in a policy framework informed by the critical interdependence of mutual adjustment processes linking the three domains of production, business, and skills. The Arsenal of Democracy policy framework drew upon production engineers of the nation’s enterprises with the most advanced production capabilities. It required process engineering leaders in organizational innovation like Charles Sorensen of Ford Motor Company (production principle of flow), William Knudsen of General Motors, and the senior leaders of skill training programmes at leading companies, to develop and implement the organizational changes in management practices needed to transform the nation’s productive structures and double output in under five years. It also required the creation of the Defense Plant Corporation as a subsidiary of the New Deal’s Reconstruction Finance Corporation, ‘with the powers as it may deem necessary to aid the Government of the United States in its national defense program’ (White, : ). The capability triad extends New Deal policymaking in a second major way. It broadens the policy framework from material and social infrastructures such as transportation, energy, water supply, communication, social housing, and public health and sanitation to organizational infrastructures critical to business development, including access to human capital, long-term finance, science and technical expertise, and a machine tool/software engineering sector. I refer to the latter as extra-firm infrastructures or more narrowly manufacturing infrastructures. All have suffered as a consequence of neo-liberalism.²⁴ Roosevelt learned from the New Deal experience that material infrastructure investment is not enough to foster economic transformation. The TVA programme, the ²⁴ By one estimate, with a precipitous drop in water infrastructure spending per capita since the s, the United States has built up a debt of US$ trillion that must be paid over the next twenty-five years (Madrigal, ). The American Society of Civil Engineers estimates it will cost US$. trillion to get the United States back to an acceptable level of debt in the nation’s material infrastructures (Madrigal, ; Bipartisan Policy Center, ). To these must be added the erosion of public health infrastructural investments exposed by the Covid- pandemic.

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-   



biggest ever regional development policy in the United States, is an example. It succeeded as material infrastructure policy but even with massive investments in electrification, transportation, clean water, and communication it did not galvanize the emergence of a critical mass of capability-developing business enterprises and thereby industrial development. The whole region did not produce a single importreplacing and export-generating city (Jacobs, : ). The South continued to import virtually all the manufactured products it had historically imported. It failed as industrial development and innovation policy.²⁵ The United States’ Second World War experience provides examples of extra-firm infrastructures designed and coordinated to target productive structure changes within and across regional or national populations of enterprises. The experience is an exemplar of industrial policies that focus on enterprise change methodologies to advance production, new product development, and technology management capabilities at the macroeconomic level. The German post-war economic miracle is an exemplar of industrial policy in the form of local and state governments as organizers of industrial ecosystems in which small and medium-sized business enterprises are supported by a range of capabilityenabling infrastructures (Best, ). Local governments have the local knowledge to coordinate, focus, and galvanize participation in the historically specific range of infrastructural agencies required to drive holistic organizational change cutting across the three domains of production, business, and skill formation. At the same time, sustained growth depends upon national governments providing budget support for physical and organizational infrastructure, ideally by investing in and nurturing regional industrial ecosystems in which a whole host of innovation dynamics characterized by Babbage, Marshall, Young, Penrose, Schumpeter, Richardson, and Jacobs can be found (Best, ). The crafting of strategic policy frameworks has both a capability-informed microeconomic dimension with respect to industrial and regulatory policies and a capabilityinformed macroeconomic policy dimension including stabilization, exchange rate, and interest-rate policies. A common feature of rapid growth experiences is that government stabilization policy is subservient to capability development policy. Manufacturing performance is highly sensitive to the pursuit of stabilization policies that are subservient to capability development policies, and the failure to do so is a key feature differentiating post-war policymaking in the United States from that of her major manufacturing rivals. The tragedy is that while the industrial policy by which the US leadership in production was created has not been appreciated within the United States, it has provided lessons which latecomer nations have put to good use. When an economic system is trapped in a fragmented, low-level capability triad, government leadership is required to craft a strategic policy framework, outline a roadmap of the way ahead, invest in the requisite extra-firm infrastructures, and ²⁵ The South, with rare exceptions, did not promote industrial districts or cluster dynamic processes that are integral to industrial innovation. See Best ().

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 . 

galvanize the energies of all those required to progress the roadmap, transition to a more advanced capability triad, and thereby transform the production system. This is not what markets do. It is what government leadership has, in special cases, organized with outstanding success. It offers the only way to address the climate-change challenge in the time required to make it happen.

. A: M C   C  I P

.................................................................................................................................. Production as the sphere of technological innovation became a subject of political economy with the publication in  of Charles Babbage’s On the Economy of Machinery and Manufactures.²⁶ He went beyond Smith’s rhetorical pin factory to explore the interiors of the most technologically innovative enterprises of his day. Babbage introduced a research methodology of systematic observation of change to political economy.²⁷ He undertook, in his words, an ‘examination of the workshops . . . which contain within them a rich mine of knowledge’ (Babbage,  []: ) to understand the ‘processes of manufactures’ and to apprehend their ‘general principles and mutual relations’ (Babbage,  []: –). He distinguished ‘mechanical principles’ from the principles of political economy which ‘seemed to pervade many establishments’. But at the same time, he found that the ‘interior economy of factories’ and questions of political economy were ‘so interwoven . . . that it was deemed inadvisable to separate the two subjects’ (Babbage,  []: ). Unfortunately, as with his drawings of the first computer, Babbage’s contribution to political economy has long been neglected and only rediscovered in recent times.²⁸ Joseph Schumpeter paid tribute to Babbage’s book more than a century after its publication as follows: This work which was widely used (also by Marx), is a remarkable performance by a remarkable man. Babbage . . . was an economist of note. His chief merit was that he combined a command of simple but sound economic theory with a thorough first²⁶ For an extended treatment from which this is drawn, see Best (). ²⁷ Babbage’s pursuit of principles of change was an application of the systemic observation approach to scientific progress being advanced by his fellow natural philosophers at Cambridge University. The pursuit of systemic-observational principles of change united the emerging sciences of evolutionary biology, geology, and astronomy. In the case of political economy, scientific investigation started with observation of production in workshops and factories in which engineering practices were most innovative and change was most dramatic. ²⁸ The Babbage ‘new system of manufacturing’ did not, however, disappear in the real world; instead the integration of technology development within production and scientific research reappeared in the form of real-world, vertically integrated industrial enterprises that drove the Second Industrial Revolution in the United States (Chandler, ; Lazonick, ).

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-   



hand knowledge of industrial technology and of the business procedure relevant thereto. This almost unique combination of acquirements enabled him to provide not only a large quantity of well-known facts but also, unlike other writers who did the same thing, interpretations. He excelled, amongst other things, in conceptualization, his definitions of a machine and his conception of invention are deservedly famous. (Schumpeter, : , cited in Hyman, : )²⁹, ³⁰

Schumpeter made a distinction between price-led and product-led competition and stressed the necessary role of credit to invest in capability development. Babbage distinguished types of manufacturing systems and the role of principles of production, distinguished technology from science, and stressed the critical role of a policy framework in promoting innovation capabilities. Both insisted on the interconnectedness of production and business organization and together characterized the mediating role of extra-firm infrastructures in fostering the building of successful manufacturing enterprises: in Babbage’s case, government investment in science and technology, and in Schumpeter’s, banking institutions for investment for the creation of ‘future values’, innovation, and capability development. Failure to do so, as in the case of the United Kingdom in Babbage’s day, would cause the prosperity of the nation to suffer from a loss of competitive advantage and markets. The idea of a production system extends economics beyond the firm and the form of competition to the dynamics of industrial change. Alfred Marshall’s Principles of Economics, first published in , extended Babbage into an emergent theory of industrial organization.³¹ In a celebrated passage, Marshall described economies arising from an increase in the scale of production as falling into ‘two classes—those dependent on the general development of the industry, and those dependent upon the individual houses of business engaged in it and the efficiency of their management; that is into external and internal economies’ ( []:  and repeated on ). External economies ‘result from the growth of correlated branches of industry which mutually assist one another’ (Marshall,  []: ). With the inclusion of organization and inter-firm dynamics as a variable, Marshall’s ‘law of increasing

²⁹ For the modern reader, Babbage’s On the Economy of Machinery and Manufactures can be read as an early version of Vannevar Bush’s highly influential Science the Endless Frontier, published in . Both were pioneers in designing complex machines that preceded the computer. Both combined deep practical and scientific knowledge surrounding the leading-edge engineering innovations and ‘mechanical principles’ of their times. Both authored, although over a century apart, a visionary text in which productivity and national wealth could be continuously advanced by iterative co-adaptation of science and production engineering. ³⁰ Simon Kuznets and Babbage also shared a common theme. Kuznets’ empirical studies of long-run trends attributed gains in productivity to the marriage of science and production, and the creation of new industries. But while Vannevar Bush and Kuznets linked economic progress to scientific advance, Babbage articulated a political economy framework which brings technology out from the shadow of science. ³¹ In Marshall’s words, ‘The law of increasing return may be worded thus: An increase of labour and capital leads generally to improved organization, which increases the efficiency of the work of capital’ ( []: ).

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 . 

returns’ introduces a growth dynamic of cumulative increasing returns, later advanced by Thorstein Veblen, Allyn Young, and Gunnar Myrdal. Edith Penrose went inside the business enterprise to distinguish resources that are purchased in the market from productive resources that require experience and teamwork to develop (). The growing firm develops distinctive productive resources or capabilities to meet emergent market opportunities, but success not only produces new products but also releases resources that can be put to work identifying a new round of opportunities. This is the learning theory of the growth of the firm. Jane Jacobs asked the questions: Why do cities grow? Why did today’s major cities undergo a period of explosive growth? Why do some cities continue to grow over a long period while others go into decline? She examines cities historically, giving special attention to cases of rapid growth to discover patterns of complex interactions in their most pronounced forms. She sees cities as the engines of economic advance, providing markets, jobs, capital, and technology for themselves, the regions around them, and other cities as well. Jane Jacobs’ The Economy of Cities was published in . Rather than celebrating economic efficiency, Jacobs celebrates a city’s growth dynamics as expressed in the rate of addition of new goods and services. Sustained city growth is simultaneously a process of increasing differentiation of skills and an experimental process of new product development and sector evolution. In her words: ‘Existing divisions of labor multiply into more divisions of labor by grace of intervening added activities that yield up more sums of work to be divided’ (Jacobs, : ). The ‘intervening added activities’ are described in terms of new ‘work’ combined with multiple trials and errors linking the old to the new divisions of labour. The increasing differentiation in skills increases the opportunities for innovation and for sustained city growth.

A I wish to thank Eva Paus and Lindsay Whitfield for extensive comments on an early draft of this chapter. As always, I owe a debt to John Bradley for feedback and advice along the way. I am most grateful to Rick Best, Carol Heim, and Gavin Wright for sharing their accumulated experience, knowledge, and wisdom in conversations over these matters. They have offered insights, ideas, references, and corrections that I have incorporated throughout the chapter. We all share a passion for the issues, but I alone am responsible for the claims being made and the shortcomings that will inevitably have to be addressed.

R Acemoğlu, Daron and David Autor () ‘Skills, Tasks, and Technologies: Implications for Employment and Earnings’, in Orley Ashenfelter and David Card (eds) Handbook of Labor Economics, Vol. B. Amsterdam: Elsevier, pp. –.

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-   

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Atkinson, Robert D., Luke Stewart, Scott Andes, and Stephen Ezell () ‘Worse Than the Great Depression, What Experts Are Missing about American Manufacturing Decline’. Washington, DC: The Information Technology & Innovation Foundation. Babbage, Charles ( []) On the Economy of Machinery and Manufactures. Cirencester: Echo Library. Baily, Martin and Barry Bosworth () ‘US Manufacturing: Understanding its Past and its Potential Future’, Journal of Economic Perspectives (): –. Best, Michael H. () ‘Notes on Inflation’, The Review of Radical Political Economics IV(): –. Best, Michael H. () The New Competition: Institutions of Industrial Restructuring. Cambridge, MA: Harvard University Press. Best, Michael H. () The New Competitive Advantage: The Renewal of American Industry. Oxford: Oxford University Press. Best, Michael H. () ‘Review of Internet Alley: High Tech in Tysons Corner, –, Cambridge: MIT Press, by Paul Ceruzzi’, in Business History (): –. Best, Michael H. () ‘Greater Boston’s Industrial Ecosystem: A Manufactory of Sectors’, Technovation –: –. Best, Michael H. () How Growth Really Happens: The Making of Economic Miracles through Production, Governance, and Skills. Princeton, NJ: Princeton University Press. Best, Michael H. () ‘The Economics of Innovation behind Cluster Dynamic Processes’, in Justin Yifu Lin and Arkebe Oqubay (eds) Oxford Handbook of Industrial Hubs and Economic Development. Oxford: Oxford University Press. Best, Michael H. and William E. Connolly ( []) The Politicized Economy. nd edition. Lexington, MA: D. C. Heath. Bipartisan Policy Center () ‘America’s Aging Water Structure’. Washington, DC. Available at https://bipartisanpolicy.org/wp-content/uploads///BPC-AgingWater-Infrastructure.pdf. Blanchflower, David () Not Working: Where Have All the Good Jobs Gone? Princeton, NJ: Princeton University Press. Bluestone, Barry and Bennett Harrison () The Deindustrialization of America: Plant Closings, Community Abandonment, and the Dismantling of Basic Industry. New York: Basic Books. Carlton, David and Peter Coclanis () ‘The Roots of Southern Deindustrialization’, Challenge (–): –. Caro, Robert () The Path to Power: The Years of Lyndon Johnson. New York: Knopf. Chandler, Alfred () The Visible Hand. Cambridge, MA: Harvard University Press. Cobb, James () The Selling of the South: The Southern Crusade for Industrial Development –. nd edition. Urbana, IL: University of Illinois Press. Einhorn, Robin (a) American Taxation, American Slavery. Chicago, IL: University of Chicago Press. Einhorn, Robin (b) ‘Tax Aversion and the Legacy of Slavery’. Available at https://www. press.uchicago.edu/Misc/Chicago/.html p. Foner, Eric () The Fiery Trial: Abraham Lincoln and American Slavery. New York: W. W. Norton. Frey, Carl () The Technology Trap. Princeton, NJ: Princeton University Press. Hayes, Jack I. () South Carolina and the New Deal. Columbia, SC: University of South Carolina Press.

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

 . 

Hounshell, David A. () ‘The Evolution of Industrial Research in the United States’, in Richard S. Rosenbloom and William J. Spencer (eds) Engines of Innovation: U.S. Industrial Research at the End of an Era. Boston, MA: Harvard Business School Press, pp. –. Hyman, Anthony () Charles Babbage: Pioneer of the Computer. Oxford: Oxford University Press. Jacobs, Jane () The Economy of Cities. New York: Random House. Jacobs, Jane () Cities and the Wealth of Nations. New York: Vintage. Jones, Jesse H. and Edward Angly () Fifty Billion Dollars: My Thirteen Years with the RFC (–). New York: The Macmillan Company. Kevles, Daniel J. () The Physicists: The History of a Scientific Community in Modern America. New York: Knopf. Kline, Stephen () ‘Innovation is Not a Linear Process’, Research Management  (Jul–Aug): –. Krugman, Paul () Geography and Trade. Cambridge, MA: MIT Press. Lamoreaux, Nancy R. and John J. Wallis (n.d.) ‘General Laws and the Mid-nineteenthcentury Transformation of American Political Economy: Massachusetts, New York, Indiana, and Beyond’, National Bureau of Economic Research. Lazonick, William () Business Organization and the Myth of the Market Economy, Cambridge: Cambridge University Press. Lazonick, William () ‘Profits without Prosperity’, Harvard Business Review, September: –. Lind, Michael () Made in Texas: George W. Bush and the Southern Takeover of American Politics. New York: Basic Books. Madrigal, Alexis C. () ‘The Toxic Bubble of Technical Debt Threatening America’, Atlantic,  October. Magdoff, Harry and Paul Sweezy () ‘Capitalism and Unemployment’, Monthly Review June: –. Markusen, Ann and Joel Yudken () Dismantling the Cold War Economy. New York: Basic Books. Markusen, Ann, Peter Hall, Scott Campbell, and Sabina Deitrick () The Rise of the Gunbelt: The Military Remapping of Industrial America. New York: Oxford University Press. Marshall, Alfred ( []) Principles of Economics. th edition. London and New York: Macmillan. Marx, Leo () ‘The Machine’, in Merritt Roe Smith and Gregory Clancey (eds) Major Problems in the History of American Technology: Documents and Essays. Boston, MA: Houghton Mifflin, pp. –. Mathews, Jessica T. () ‘America’s Indefensible Defense Budget’, The New York Review of Books,  July. Mayer, Jane () Dark Money: How a Secretive Group of Billionaires is Trying to Buy Political Control in the US. London: Scribe Press. Meyer, David R. () The Roots of American Industrialization. Baltimore, MD: Johns Hopkins University Press. Nieburg, H. L. () In the Name of Science. Chicago, IL: Quadrangle Books. O’Connor, James () The Fiscal Crisis of the State. New York: St. Martin’s Press. Penrose, Edith () The Theory of the Growth of the Firm. Oxford: Basil Blackwell and New York: John Wiley and Sons. Revised edition . Oxford: Oxford University Press.

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-   



Phillips-Fein, Kim () Invisible Hands: The Businessmen’s Crusade against the New Deal. New York: W.W. Norton & Company. Piketty, Thomas, Emmanuel Saez, and Gabriel Zucman () ‘Distributional National Accounts: Methods and Estimates for the United States’, Quarterly Journal of Economics (): –. Pisano, Gary and Willy Shih () Producing Prosperity: Why America Needs a Manufacturing Renaissance. Boston, MA: Harvard Business Review Press. Schulman, Bruce () From Cotton Belt to Sunbelt. Durham, NC: Duke University Press. Schumpeter, Joseph () History of Economic Analysis. London: Allen and Unwin. Shermer, Elizabeth () Sunbelt Capitalism: Phoenix and the Transformation of American Politics. Philadelphia, PA: University of Pennsylvania Press. Smith, Merritt Roe and Gregory Clancey (eds) () Major Problems in the History of American Technology: Documents and Essays. Boston, MA: Houghton Mifflin. Stoller, Matt () ‘How Democrats Killed their Populist Soul’, The Atlantic,  October. Teaford, Jon C. () The Rough Road to Renaissance: Urban Revitalization in America, –. Baltimore, MD: Johns Hopkins University Press. Teaford, Jon C. () Cities of the Heartland: The Rise and Fall of the Industrial Midwest. Bloomington, IN: Indiana University Press. White, Gerald T. () ‘Financing Industrial Expansion for War: The Origin of the Defense Plant Corporation Leases’, The Journal of Economic History (): –. Whitehouse, Sheldon and Melanie Wachtell Stinnett () Captured: The Corporate Infiltration of American Democracy. New York: The New Press. Winchester, Simon () Exactly: How Precision Engineers Created the Modern World. London: William Collins. Wright, Gavin () Old South, New South: Revolutions in the Southern Economy since the Civil War. New York: Basic Books. Wright, Gavin () ‘The New Deal and the Modernization of the South’, Federal History, Jan. Issue . Wright, Gavin () ‘World War II, the Cold War, and the Knowledge Economies of the Pacific Coast’, in Mark Brilliant and David Kennedy (eds) World War II and the West It Wrought. Stanford, CA: Stanford University Press, pp. –.

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  ......................................................................................................................

   A Comparative Perspective .............................................................................................................

    

. I

.................................................................................................................................. T chapter examines industrial policy implemented in European countries across time, especially after the Second World War and in recent years. It briefly shows that industrialization never occurs without strong supporting industrial policy providing the enabling conditions for the deep structural changes involved, such as infrastructure, capabilities, and human capital, and often direct involvement in production, especially in strategic sectors. This is true for the pioneer of industrialization, Britain in the eighteenth century, as well as later industrializers in continental Europe in the nineteenth and twentieth centuries. Industrialization is associated with the creation and consolidation of nation states, and industrial policy has been carried out to strengthen the power of these states, not only because industrial development increased wealth, hence economic and political power, but also because industrialization contributed to military equipment and capacity. This led to national perspectives on industrial development and industrial policy, at the expense of regional imbalances. After the Second World War, industrial policy continued as an instrument of the power of nation states, especially in the first phase of reconstruction and development where it was massively, though selectively, implemented. Three phases of industrial policy since  can be distinguished (Bianchi and Labory, , a): strong and selective intervention in the first three decades of the period, market-led approaches in the s and s, and what has been called a pragmatic approach at the turn of the century. The first phase is that of interventionist and selective industrial policy, characterized by direct intervention in markets, with the government often being producer through

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  :   



state ownership. Such policies tended to favour ‘national champions’ or consisted of ‘picking winners’. In Europe, this was also accompanied by a lax implementation of competition policy and regulation of the ‘command-and-control’ type. This type of policy started to be questioned in the s, when state-owned firms began to display a number of inefficiencies and were unable to restructure after crises. The second period is the s and s, when competition policy was implemented more stringently, regulation became incentive based, and measures to favour structural changes were preferably horizontal—implemented across all sectors of the economy rather than sector or firm specific. Preferred measures included policies for SMEs, favouring their networking and supporting entrepreneurship by simplifying firm creation procedures, providing training, better access to finance, innovation policies favouring R&D collaborative programmes, financing research projects on important—generic—technologies, and then favouring the interaction between universities and industry for technological transfer. The aim of industrial policy in that period was to provide the conditions for the competitiveness of industry. The focus on providing the conditions for the competitiveness of firms and the development of sectors continues in the third period of industrial policy. This essentially starts at the turn of the new century, when industrial firms, concerned with the intensification of global competition induced by globalization, increasingly call for industrial policy. Globalization means the integration of the world market, thanks to new technologies and to political changes in a number of countries that have allowed them to enter world trade agreements (China entered the WTO in ). Competition policy is still stringently applied, regulation is rather incentive based, measures and actions are primarily horizontal and aim at providing the conditions for competitiveness and development; however, vertical measures in the sense of measures specific to sectors are also envisaged if they are necessary to reach the objectives. The term ‘industrial policy’ is also used again, not to mean the selective policies of the past, but to indicate the support necessary for industrial development, namely structural changes, requiring new infrastructure, adoption of new technologies, developing new capabilities and new institutions. Industrial policy strategies proposed at the turn of the new century emphasize the importance of knowledge creation, and hence innovation policy, as well as policies on education and training to raise the skills in the labour force. Bottom-up processes have increasingly been stressed, with industrial development starting in specific poles or territories where particular knowledge and competencies are concentrated. Hence, for instance, the policy of clusters, especially high-tech ones, implemented in many countries. The new century is characterized by significant and numerous technological changes, and innovations in many scientific and technological fields to which industries have to adapt by digitalizing, and changing products, production processes, and distribution channels as digital platforms become powerful new market intermediaries (Bianchi and Labory, ). These challenges, which most European countries are addressing in their industrial policies, are those of the Fourth Industrial Revolution.

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

    

This chapter examines the experiences of industrial policy implementation in some European countries. The aim is not an exhaustive review of all European countries’ policies, nor a systematic comparison of all instruments. Rather, broad policy lines are compared, and what emerges is that while all European countries have followed broadly similar policies, some divergence exists regarding particular focuses, such as attention to regional imbalances and the empowerment of regional or local government levels to contribute to industrial development, or the strength of support for particular firm size. For instance, Germany has paid attention to its SME base, the Mittlestand, while France and the United Kingdom have not effectively done so, or at least not at the appropriate time: offshoring by large firms in the latter two countries has caused major difficulties for their SMEs and perhaps contributed to more acute deindustrialization. This chapter is structured as follows. We first provide a definition and taxonomy of industrial policy, followed by a review of the role of industrial policy in the first three industrial revolutions. We then analyse countries’ experiences from  before looking at the current phase of industrial policy implementation, which is characterized by a number of challenges, such as globalization and the Fourth Industrial Revolution. In section . we reflect on the evidence provided in the chapter and draw conclusions. We largely use previous research (Bianchi and Labory, a, b, , a, b) to make the review in the first part of this chapter, while the analysis of current industrial policy essentially confronts official documents on the national strategies.

. I P: D  T

.................................................................................................................................. There are numerous definitions of industrial policy in the literature, making it an ‘elusive concept’ (Vanden Bosch, ). Some definitions are restrictive and selective and exclude horizontal measures that treat all firms and all sectors the same (R&D programmes, training, SME support, and so on). Thus, Brander (: ) defines industrial policy as a ‘coordinated selection’, namely firm or industry selection through government planning (coordination). This type of definition is closely linked to industrial policies implemented in the immediate aftermath of the Second World War, when ‘national champions’ were strongly supported, leading to a lack of structural adjustment when shocks arose or the competitive context changed. Other definitions are broader. For instance, Donges (: ) considers industrial policy as comprising all government measures that influence industry, such as national investment policy, regional and labour policy. For Curzon-Price (: ), industrial policy consists in sets of measures implemented with the objective of impeding or favouring structural change.

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  :   



Recent literature (Cimoli et al., ; O’Sullivan et al., ; Chang et al., ; Bailey and Tomlinson, ; Andreoni and Chang, ; Bianchi and Labory, a, ) can be synthesized to provide a definition that seems to be widely accepted today. First, industry does not mean exclusively manufacturing but includes all productive activities, including services. This makes sense because manufacturing activities are increasingly bundled with services (see Chang and Hauge, , for an interesting discussion on this). Industry, then, is the capacity to organize production by mobilizing both tangible and intangible resources. Second, industrial policy comprises a variety of instruments and actions that are combined in order to set competitive rules and accompany structural change. The competitive conditions in which firms operate frequently change for various reasons, such as variations in the extent of the market or technological innovations. Industrial policy must adjust the rules of the game as a result of these changes; it must also adopt a long-term perspective to favour the structural adjustment of enterprises. Industrial policy can be defensive—protecting existing firms in the face of structural changes, or proactive—anticipating changes and implementing measures that favour structural changes. The former type of industrial policy often impedes or delays inevitable changes, ultimately raising the costs of transformations. Many policy actions affect industries: fiscal, monetary, environmental, trade, innovation, and labour policy instruments have a direct or indirect impact on industries. It can therefore be argued that all countries and territories implement industrial policies in one way or another. However, what is important to stress is that industrial policy is a deliberate attempt by the government (at the local, regional, or national level) to orientate industrial development towards specific paths. Such orientation can take various forms, from building infrastructure to favour particular sectors to promoting the adoption of new technologies in existing sectors in order to induce their upgrading. It can be ‘interventionist’, or ‘picking the winner’, in the sense of choosing specific industries that are developed from scratch, with for instance high investments, creation of appropriate infrastructure and training of human capital, and sometimes state ownership. It can be more inclined to letting market forces play, for instance by providing the conditions for industrial development, and letting entrepreneurs make choices and implement strategies as a result of which new industries can emerge. A taxonomy of industrial policy actions can be created from this definition (Labory, : Pelkmans, ), dividing actions into two categories: measures not aimed at industry but which have an impact on it; and measures aimed at industry. The first group includes macroeconomic stabilization policies (monetary policies influence inflation and interest rates, affecting both consumer purchasing power and business investment opportunities), or social and labour policies. Education policies aim at the social development of the territory but also influence the availability of human capital for business. The second group includes all measures directly aimed at industry, which can be divided into three subgroups: (i) measures defining competitive conditions, such as antitrust policy and product regulation; and measures aimed at enhancing

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

    

business capabilities which can be (ii) horizontal, concerning all firms and industries, such as support to R&D, development of human capital, access to financing, and so on, or (iii) vertical, specific to particular industries, such as public procurement of specific products, investment in specific technologies or specific skills, for example, creation of engineering schools. A particular issue in the definition of industrial policy is coherence, given that the wide variety of possible measures may have conflicting objectives or unintended combined effects (Bianchi and Labory, a). Instruments are often used for various objectives: for instance, training policy is useful both for social purposes and for the provision of appropriately skilled human capital; energy policy often has both social (access to energy for all at reasonable cost) and industrial goals (ensuring energy costs do not negatively affect business competitiveness), and sometimes also geopolitical ones (relations with producing countries). The objectives can sometimes conflict, as when geopolitical interests lead to a preference for certain energy sources although their efficiency might not be optimal. Similarly, trade policy usually aims at eliminating trade barriers, which can conflict with industrial policy when the new industries need temporary protection to develop.

. I  I P

.................................................................................................................................. Industrial policies have been implemented in most countries since the First Industrial Revolution at the end of the eighteenth and beginning of the nineteenth century, although with varying degrees of deliberate planning and monitoring. The main reason is that industrial capacity becomes the main determinant of the wealth of nations, as stressed by Adam Smith (). Countries have to develop this capacity in order to affirm their strength, both directly because it determines wealth generated in the country, and indirectly because industries also produce military equipment. Industrialization requires complex sets of policy instruments even in the First Industrial Revolution. They are generally determined by a new technological system (Gille, ) or paradigm (Freeman and Lourça, ), but also new needs in society and a changing organizational model which adapts to the new context so that technological progress impacts on economic development. In the First Industrial Revolution, the factory system transforms the organization of production from craftsmanship to the division of labour. Its diffusion requires new resources and skills, and a new social structure. Entrepreneurs creating and managing factories constitute a new social class, which increasingly influences the political process. Cities transform with the creation of factories, since the latter attract a workforce previously hired in agriculture, hence a rural exodus and the growth of urban areas, which have to re-organize and offer new services, from transport to housing and progressively schooling.

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  :   



The state must therefore intervene at the local level to develop new services in cities (transport, housing, and schooling), but also at the national level since industrialization requires a new institutional framework, including contract law, protection of intellectual property rights, financial and insurance systems. Countries industrializing after the pioneers have to implement particularly strong industrial policy in terms of direct intervention in markets, since their industries are developing in a competitive context where they are immediately challenged by first-industrializer industries. They also have to absorb new knowledge and new technologies rapidly, since technological change proceeds continuously in the nineteenth and twentieth centuries: knowledge absorption has to be combined with the development of research competencies if it is to follow and take an active part in the innovation process. The first industrial revolutions (IRs) are based on the increasing use of coal as energy source; iron (First Industrial Revolution) and later steel (Second Industrial Revolution) as main raw material; and the diffusion of the steam engine in many activities. In the early nineteenth century, electricity becomes an integral part of continued innovations in the Second Industrial Revolution. Railways are a key element in nineteenth-century industrial development because they enlarge the market from regional to national and international. Steamships complement railways to facilitate international trade. The development of railways also stimulates further innovations, since they require infrastructure such as bridges, but also a specific organization and planning to avoid incidents and delays. The organizational innovations introduced in the management of railway companies are often argued to have been implemented in the large companies that progressively emerged in the second half of the nineteenth century (Bianchi and Labory, ).

.. The United Kingdom The United Kingdom was the pioneer of the First Industrial Revolution, in the sense that key inventions were made in that country and the first factories developed there. Industrialization then diffused to other European countries (Belgium, France, Germany), the United States, and later Japan. Policies to support this process were especially strong in countries which followed the United Kingdom. Even in the latter part of the twentieth century, catching-up countries such as Korea, Taiwan, and China did implement industrial policy (see Lall, ; Allen, ). Whether the United Kingdom also implemented industrial policy in the First Industrial Revolution is debated. Bairoch () claims that the British government implemented industrial policy well before the First Industrial Revolution, using instruments such as tariff protection, subsidies, and export taxes from as early as the fourteenth century to support development of the woollen textile industry. This support was later extended to all industrial sectors. Complementary measures included massive investment in infrastructure and development of the financial sector to support it. Measures were taken to protect the new industry and avoid imitation in other countries, such as a ban on exports of machines in the late eighteenth and early nineteenth century.

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

    

However, a number of scholars argue that the measures taken by the British government were not part of an intentional industrialization programme, but rather aimed at protecting particular lobbies (Mokyr, ; Allen, ). According to them, for instance, the aim of the Calico Act was to protect the lobbies in the cotton industry (Mokyr, ), although it had the secondary effect of promoting the development of that industry. Another example is the heavy taxation imposed by the central government, which was mainly used for military purposes and not industrial development; however, this spending allowed Britain to gain dominance over sea routes, which was favourable to trade. The development of education, science, and technology was left to private initiative rather than being defined in an industrialization programme (Van Neuss, ). Industrialization starts in Great Britain around , with a series of inventions (the spinning jenny, the water frame, and the mule) making it possible to use machines in production, especially in the cotton sector. The rapid pace of innovation contributes to the development of factories and industries, and especially of the steam engine, continuously improved throughout the nineteenth century. Industrialization accelerates thanks to the railways boom from the s. France starts industrializing between  and  with the diffusion of weaving looms and the building of the first railways. From , Germany, Canada, and the United States become rivals of France and the United Kingdom, while Japan and Russia join after . According to Allen (), industrial policy implemented by followers consisted of four main actions: unification of the internal market; external tariffs to protect domestic industry; development of infrastructure such as roads and later railways; and development of human capital, with better health thanks to improvements in agriculture and food security, as well as education and training. Sweden and Germany appear to have been pioneers in the latter, establishing universal basic education in  and  respectively.

.. Germany Germany was the most active in this forced industrialization (Landes, ). Until the unification of the Reich, King Frederick the Great (–) actively promoted new industry: factories were set up, particularly in the steel and linen industries, together with road and railway infrastructure. The financial system was developed with the creation of investment banks. The availability of human capital was also ensured with compulsory education, resulting in a schooling rate of  per cent (Landes, ). Academic research also substantially improved with a focus on industrial applications, both for the state (military equipment) and for business (for instance, chemistry). The market was unified with the Zollverein of  and protected, following the recommendations of List who had observed trade protection policy in the United States (Bianchi and Labory, ).

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  :   



.. France Industrialization was realized in a similar way in France, thanks to the creation of factories by entrepreneurs, state investment in public goods such as railways and other infrastructure, and the development of a financial system based on banks and shareholders’ associations (known as caisses). Industrial policy in France was based on the Colbertist doctrine, named after the seventeenth-century minister who created specific companies belonging to the monarchy that were granted monopoly (Levy-Leboyer, ). State intervention remained important in France especially after the Second World War.

.. Italy Italy started industrializing in the late nineteenth and early twentieth century, with strong intervention by the state, culminating in the creation of the Institute for Industrial Reconstruction at the beginning of the s, which took shares in numerous companies in strategic sectors (steel, energy, transport, and communications) after the financial crisis. Throughout the twentieth century, innovations continue at a sustained pace, based on scientific discoveries in all fields generating two new industrial revolutions. The Second Industrial Revolution is primarily based on electricity and steel, but also chemicals and the automobile industry, where mass production begins and is later diffused to all industries. The Third Industrial Revolution after the Second World War concerns oil as the main energy source, but also nuclear energy, aerospace, automobile, computer, and telecommunications industries (Freeman and Lourça, ).

. I P     T- C

.................................................................................................................................. European countries implemented industrial policies after the Second World War, initially reconstruction after the devastation of war. Many industries had been turned into war industries and had to re-organize. The United States provided financial support for this effort with the Marshall Plan (European Recovery Programme) of . The political economy of industrial policy at that time was to ensure that Western European countries would recover to become prosperous economies that could face the threat of communism during the Cold War, besides providing a market for American firms. Industrial policy was interventionist in the first phase, with the state often the producer through state-owned enterprises, especially in infrastructural (transport

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

    

and telecommunications) and strategic sectors, such as coal and steel. This strong intervention also translated into the promotion of national champions that could deal with international competition: the explicit aim of this policy in France was to have large firms able to compete against American ones.¹ Another aim was to develop the defence industry as a Cold War deterrent, and this led to important R&D programmes, for instance in the nuclear and telecommunications industries in France and the United Kingdom in particular; much less so in Germany and Italy, which were defeated countries. Other European countries that were more politically neutral or at a different stage of development made different strategic choices. All European countries benefited from the economic integration programme, starting with the ECSC (European Coal and Steel Community) in  and the EEC (European Economic Community) in . The Treaty of Rome set up a common market between the member states following different stages of integration, from trade union to the single market (see Landesmann and Stöllinger, Chapter  of this volume). The market therefore enlarged for the member states, allowing firms to exploit higher economies of scale and scope, since both volume and product variety could increase. The original six member countries— France, Germany, Italy, the Netherlands, Belgium, and Luxembourg—expanded to include Denmark, the United Kingdom, and Ireland in , Greece in , Spain and Portugal in , Austria, Finland, and Sweden in , and the countries of Eastern and Central Europe from  onwards.² The single market is thus often considered as the main industrial policy of the European Union (Pelkmans, ). Other aspects of industrial policy at the European level are competition policy and trade policy. Ensuring fair competition on the European market is therefore a key element, as well as ensuring open trade worldwide. While the European level has constantly stressed the importance of innovation policy, with a number of European R&D programmes, such as ESPRIT and EUREKA in the s (see Chapter  by Landesmann and Stöllinger in this volume), the main competence regarding industrial policy (of which innovation policy is a part) is at the national level. European treaties have included an article on industrial policy since the Maastricht Treaty of , but it invites member states to support the competitiveness of their industries with particular attention to SMEs and their collaboration, as well as R&D and innovation, privileging horizontal measures, that is, measures not specific to firms or sectors. Industrial policy (called enterprise or competitiveness policy) is mentioned at the European level only in the second phase of industrial policy implementation, starting with the new approach formulated by Commissioner Bangemann in . Earlier debates at the European level had included the Colonna Report of , which stressed that the creation of the single market and other exogenous factors would ¹ An influential reflection on this subject was published by Jean-Jacques Servan-Schreiber in : ‘Le défi américain’ (the American Challenge). ² Cyprus, Czech Republic, Poland, Estonia, Lithuania, Latvia, Slovakia, Slovenia, Malta, and Hungary in ; Bulgaria and Romania in ; Croatia in .

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  :   



make the structural adjustment of European firms necessary. However, after the difficulties for European industries generated by the oil crisis of the s, the reaction of the member states was to pursue a defensive policy. The best illustration is the Davignon Plan of , which intervened to support the steel industry in crisis: minimum prices and important firm subsidies were provided to reduce production capacity. This led to protection of the existing firms (avoidance of failures) but without encouragement to realize structural adjustment. The increasing trade in the European Community was, however, beneficial to businesses and economy in the member states, which supported their industries during this first period.

.. Italy In Italy, the literature agrees on the important role of the state in its industrial development (e.g. Bianchi, ). After the Second World War the country was still lagging behind the United Kingdom, Germany, and France. The government intervened to modernize and develop the country, mainly with subsidies to industry and large investment through the state-holding Institute for Industrial Reconstruction, with large stateowned companies acting as leader. Trade was progressively liberalized in the s, first in the ECSC and in the EEC from . Italy then chose a growth strategy based on exports. The government supported declining industries in the s, while the emphasis shifted in the s when it realized both the importance of SMEs in the industrial system, especially those grouped in industrial districts, and the need to promote research and innovation. Support to industrial districts started being provided at the regional level, using the European structural funds. IRI was closed at the end of the s, after a big wave of privatizations and the adoption of a national antitrust law in . Many authors, such as Federico and Foreman-Peck () and Bianco () criticize the incompleteness of the Italian industrial policy: some measures have been taken, but many elements are missing, such as an efficient capital market, simple bureaucratic procedures especially for firm creation, and support for new industries (Malerba, ; Rolfo and Calabrese, ). Nonetheless, Italy ranks second in manufacturing in the European Union today.

.. France In France, industrial policy was a national strategy defined by a specific entity, the Commissariat Général au Plan, created in . In the decades after  this planning office used state ownership, among other instruments, to support large firms that could compete against American ones. The country has experienced two waves of nationalization when the state acquired private enterprises: in –, various firms in the

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

    

financial, energy, utility, and transport sectors came under state ownership; in the s, the state acquired firms in declining industries, such as steel and shipbuilding, as well as strategic sectors such as chemicals, pharmaceuticals, and electronics. Privatizations started in the s, but many former state-owned companies remained under state control through ‘golden shares’. As well as state ownership, French industrial policy provided large subsidies to industry, as well as large R&D programmes (grands programmes) in strategic sectors. These programmes were characterized by state-owned companies and public procurement, with a strong research focus in science and technology that had important military applications (aerospace, nuclear, and telecommunications). Industrial policy was definitively relaunched at the beginning of the s.

.. The United Kingdom The United Kingdom also based industrial development on state ownership, subsidies, knowledge transfer, and fiscal policy in the period  to . Restrictions on international trade were implemented in the s. The government acquired private enterprises in difficulties, such as Rolls Royce in the s. Skills development was strong right up to the s, but perhaps not enough emphasis was put on intermediate skills: in ,  per cent of -year-olds passed their maths and mother-tongue test, against  per cent of German,  per cent of French and  per cent of Japanese people of the same age (Foreman-Peck and Hannah, ). Some specific sectors, for instance aerospace and information technology, and all activities with military applications, were supported. As early as  the United Kingdom was also the first European country to adopt antitrust law. From , with the advent of the Thatcher government, industrial policy was abandoned. There were privatizations and liberalization of utilities, old industries closed down with heavy social costs and the only remaining industrial policy measures were innovation policy (although this was not effective according to von Tunzelmann, ) and FDI attraction (as a result of which Japanese producers attracted by the European market set up factories in the United Kingdom in the s).

.. Germany According to Feldenkirchen (), industrial policy was continuously applied in Germany in the twentieth century. While the overall approach was to provide the conditions for industry to prosper, specific support was also given to industries or firms (Donges, ; Feldenkirchen, ) in declining or strategic sectors, with military applications in particular. Despite mergers and demergers experienced due to the political and economic upheavals before and after the Second World War, German

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  :   



big businesses remained stable. They were concentrated in the heavy industries (coal and steel), with, for instance, Hoesch, Krupp, and Mannesmann, chemicals (IG Farben), electrical engineering (Siemens, AEG) and automobiles. Germany regained a world-leading position in the chemical industry after the Second World War, with four main companies created from the dismantling of the IG Farben company: Bayer, Hoechst, Agfa, and BASF. Only large banks suffered after , when the Allies forced the dismantling of the three major banks, the Deutsche Bank, the Dresdner Bank, and the Commerzbank. However, they reunited in the s. In addition, German industrial policy has been export oriented, especially in the European economic integration process. Innovation has also been an element of this policy, with a strong focus on the industrial application of research: for instance, the Fraunhofer Institutes were created in  with a focus on industrial application research, while other institutions like the Max Planck Institute focused on basic research. Fraunhofer Institutes establish links with both large firms and especially SMEs (Mittlestand), the backbone of the German industrial system. Germany also has a specific banking system focused on long-term lending to industry. The German government created a number of public or quasi-public banks during the s to ease industry access to finance. Thus, the Kreditanstalt für Wiederaufbau (KfW) was created in  in order to manage the Marshall funds allocated to the country for reconstruction. It soon became focused on financing to SMEs. Other activities were progressively added, such as export financing in the s, financing of infrastructure on behalf of the municipalities and other local administrations in the s and s, and financing of the reconstruction of East Germany in the s. Mittlestand companies were supported with access to finance since they also benefited from the Bank for Settlements (AG) and a decentralized network of savings banks (Sparkassen) and credit cooperatives. There are about  savings banks³ and  cooperative banks⁴ in Germany, which together provide about two-thirds of all lending to Mittelstand companies. Industrial policy acquired a new impetus in the s with reunification. Alongside a decisive effort to modernize and reconvert industry in the former East Germany, measures for industry in West Germany continued, focused on providing the appropriate conditions for competitiveness and spurring innovation. Characteristic of German industrial policy is the coherence of its multilevel governance framework between the local, the regional (Länder), and national (federal) levels. It is also proactive, trying to anticipate changes so that industry can adapt to changing competitive and technological conditions, for example, in the recent policy supporting the structural transformations implied by Industry ..

³ Markgraf and Véron (), Bruegel Institute, https://bruegel.org///germanys-savingsbanks-uniquely-intertwined-with-local-politics/. ⁴ National Association of German Cooperative Banks (), https://www.bvr.de/Press/Press_ releases/Cooperative_Financial_Network_publishes_its__consolidated_financial_statements_Stable_ earnings_in_the_operational_customer_business_profit_before_taxes_of_Euro__billion.

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

    

This institutional coherence also prevails in Sweden and Finland. Both countries have implemented industrial policies with instruments similar to those of other European countries. Up to the s these policies tended to be selective, directed, for example, at forest industries which were important in these countries’ economy at the beginning of industrialization and remain so today (Blomström and Kokko, ). A new approach was adopted in the s, with a higher focus on innovation and technological transfer, as well as the local roots of industrial development, and important cluster policies (Blomström and Kokko, ; Ylä-Anttila and Palmberg, ). An important feature is the adoption of a systemic view in which great attention is paid to the relationships between actors in the innovation process. Policies have been defined in dialogue with stakeholders, establishing public–private partnerships especially at local and regional levels. Industrial application of research has thus been rooted locally but favouring the networking of local clusters and excellence centres at a national level (Ketels, ).

.. Finland The case of Finland deserves more analysis, because this country achieved very deep structural changes in only a few decades. More than half the population and  per cent of output were still in the primary sector in the s. However, the country had already become a mature industrial economy by the s. The evidence suggests that Finland’s industrialization was strongly backed by the state through industrial policy. From the s an important intervention was made, based on a strong consensus between the state at all levels of government, businesses, and other stakeholders, that defined a vision of industrial development as well as measures towards this aim. ‘The Finnish business elites colluded to distort the markets in a way that sustained high investment rates’ (Jäntti and Vartiainen, : ). Actions included large investments, particularly in forestry and metals, that were enabled by the high rate of savings available in the economy at that time. Interest rates were also controlled by credit rationing. Human capital was developed by investment in education and the development of the welfare state. Social cohesion was therefore high, partly for political reasons, since Finland had ‘recently’ become independent from the USSR () and the feeling in the population was that the country had to grow to justify its independence and workers had to be cared for to avoid increasing support for communist ideas and the possible influence of its neighbour country. Trade unions were encouraged to take part in the discussions on industrial policy and unionization was encouraged. The industrial system developed, favouring economic growth and maintaining social cohesion. Moderate wage increases were agreed in the negotiations between the state, businesses, and labour to maintain the international competitiveness of Finnish firms. Finland was a dynamic knowledge-based economy by the beginning of the s, thanks to a second industrial transformation in the s, characterized by the rise of

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  :   



the ICT sector with the dominant firm Nokia, promoted by an industrial policy aimed at developing new sectors defined at the beginning of the s, and comprising actions aimed at raising higher education, clusters, and R&D investments. The flagship company Nokia grew exponentially in the s and became the bestselling mobile phone brand in the world in . The company represented about  per cent of the country’s GDP,  per cent of its total exports and about half of total national R&D in  (Ali-Yrkkö, ). However, the company missed the shift to smartphones and went into deep and rapid trouble from  onwards. The firm represented only . per cent of GDP and  per cent of the country’s exports in . In just six years ( to ), the market value of Nokia declined by  per cent. Nokia was taken over in  by Microsoft, which started a drastic re-organization, laying off employees and closing some factories and research centres in Finland. The Finnish government made an agreement with Microsoft to avoid excessive lay-offs. More importantly, the government immediately started a strong policy to support firm creation: the budget of the Finnish agency for research and innovation, Tekes, was substantially increased to support new and innovative businesses; Vigo, a start-up accelerator, was launched in  by the Finnish Ministry of Employment and the Economy. Since then the country has remained an innovation leader in the European Union, as witnessed by the European Innovation scoreboards.⁵

.. Ireland Like Finland, Ireland developed rapidly from the s to . The effects of the  financial crisis were particularly severe in Ireland, seemingly due to structural weaknesses that were not addressed by industrial policy. Yet the country had experienced average annual GDP growth rates of more than  per cent, leading commentators to speak of the ‘Celtic Tiger’. This development was eased by industrial policy of a very different kind from that of Finland. While the latter country based its industrial policy on the development of autonomous capacity, Ireland tended to import industrial capacity from outside. Irish development in the s was spurred by the boom of the high-tech sector, especially in electronics and pharmaceuticals, but the bulk of the sector was and still is foreign owned. The latter represented about  per cent of output in , while employment was almost equally divided between the two types of firms (Kirby, : –). The Irish industrial policy model has been very open and based on the attraction of foreign companies with mainly low tax rates (Bailey et al., ). Different authors (Kirby, ; Cullen, ) have shown that this strategy came at a high social cost, in that the benefits of industrial development have not been shared among the population; the poverty rate rose during the s at a time of high growth. ⁵ https://ec.europa.eu/growth/industry/innovation/facts-figures/scoreboards_en.

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

    

The European integration process has deeply influenced the industrial policies of European countries. First, it has offered new opportunities for national industries, thanks to the enlargement of the market, allowing static and dynamic scale and scope economies. Second, it has induced member countries to coordinate their policies, some industrial elements of which (competition and trade policy) have become common policies. Other policies such as innovation policy, have included a progressively European dimension. However, the main competence on industrial policy remains at the national level in the EU. Third, the European Commission has played an important role in monitoring and benchmarking industries and economies, highlighting the economic challenges and helping to focus policy efforts on them. National industrial policies remained focused on declining industries up to the s, together with R&D programmes. The awareness that globalization accelerated at the end of the s led to the definition of a new approach to industrial policies by Commissioner Bangemann in . The term ‘industrial policy’ was no longer used, because of its association with the interventionist and selective policies of the past. Policies supporting structural changes in industries were called competitiveness or enterprise policies. The new approach consisted in providing the conditions for the competitiveness of industries, privileging horizontal measures and instruments as well as fair market competition. The role of the state was defined as a pioneer and catalyst of industrial development, identifying future technologies and industries and promoting their adoption and expansion. It was formalized in Article  of the Maastricht Treaty. The new horizontal approach, however, does not appear to have been successful in reducing the competitiveness gap between the European Union and its main rivals in the s, Japan and the United States. The problem was not lack of innovation, but a limited capacity to transform innovation into commercial success, which the European Commission called the ‘European paradox’ in  (European Commission, ; Dosi et al., ). This is particularly challenging as new rivals have emerged since , especially from Asia, and China and Korea in particular. As a consequence, the debate on industrial policy emerged again in the European Union at the beginning of the new century, especially in  when the heads of state of France and Germany (respectively Jacques Chirac and Gerhard Schroeder) openly expressed concern over de-industrialization and called for industrial policy. The European Commission has published numerous communications on industrial policy since then, proposing to increase R&D effort and industrial applications for research, as well as training and education, while maintaining a strong emphasis on competition policy and open trade. Some measures specific to sectors have also been suggested, for instance in the chemicals sector. The numerous communications of the European Commission on the subject in the last fifteen years (Bianchi and Labory, a; Landesmann and Stöllinger, Chapter  in this volume) are perhaps signs of a search for what industrial policy should look like. The competitiveness gap has persisted and somehow widened because it now also exists with respect to China. Another issue is that although member states are aware of the need to support industries, most have only been able to do so in a limited manner, especially during

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  :   



crises, because budget constraints in the eurozone impose limits on spending. In particular, the golden rule adopted after the financial crisis (the fiscal compact of ) has been criticized by macroeconomists as severely limiting the ability to use fiscal policies for stabilization purposes in a manner consistent with moderate long-run debt levels (Whelan, ). The ability of EMU countries to implement fiscal stimulus is extremely limited, and this has been a problem in the recession that followed the  financial crisis and that lasted several years (Eyraud et al., ; Darvas et al., ). While the horizontal approach has helped, it has the disadvantage of spreading financial efforts over a large number of actors, which can lead to results that are, at best, diluted. This is particularly problematic when resources are scarce, as in the case of strict constraints on public deficit, which is what happened in the first decade of the s, and led to a new approach, namely smart specialization. Section . reviews current industrial policies in European countries, starting from a review of the importance and evolution of the manufacturing sector in recent decades.

. N I P   T   C

.................................................................................................................................. Manufacturing value added as a percentage of GDP tended to fall in all countries over the period  to  (Figure .). Germany is the European country where the manufacturing sector remains most important in the national economy: manufacturing value added represents  per cent of GDP in , against about  per cent in Finland, Italy, and Sweden (respectively ., ., and . per cent). Countries with the lowest shares are France ( per cent) and the United Kingdom (. per cent). Figure . shows that all countries encountered a long phase of restructuring, whereby the importance of the manufacturing sector in GDP declined, followed by a stabilization phase. However, the timing and length of the restructuring process differs across countries: Germany saw a reduction of the share of the manufacturing sector in GDP in the first five years of the s, followed by a stabilization and slight growth after the financial crisis. In France, Italy, and the United Kingdom the decline carries on up to the financial crisis. In Finland and Sweden, the decline starts later, in , and lasts about ten years. For all countries except Germany, the decline becomes steeper after , corresponding to the entry of China to the WTO () and the period where globalization was most strongly felt, in the sense of intensification of world competition following the massive entry of new protagonists such as China and the BRICS countries. China has become the global manufacturing centre, with manufacturing value added representing about  per cent of GDP against  per cent in the United States in .

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

     30 25 France

20

United Kingdom 15

Germany Italy

10

Finland 5

Sweden

17

15

20

13

20

11

20

09

20

07

20

05

20

03

20

01

20

99

20

97

19

95

19

93

19

19

19

91

0

 . Manufacturing value added as a percentage of GDP, selected countries, – Source: World Bank data, https://data.worldbank.org/indicator/NV.IND.MANF.ZS?locations=CN.

Chinese production is no longer (or not only) of low quality, since the country has become a world leader in innovation. For instance, China’s share of world patent applications increased from . per cent to nearly a third of world patent applications (. per cent) in the period  to , mainly at the expense of Japan (. to . per cent), while the shares of the EU- and of the United States slightly reduced. Overall, European countries invest in R&D, but their size is too small to reach the level of expenditure (input) but also innovation (output, as shown by patenting activity) of China and the United States. The innovation capacity of the European Union as a whole is much higher and comparable to that of China and the United States, although it has slightly declined in the last decade: the share of world patent applications of the European Union as a whole (twenty-eight countries) was more than  per cent in  and was about  per cent in . OECD data on triadic patent families⁶ show that only a few advanced countries increased their share over the period  to ; the EU’s share reduced from . to . per cent, the United States experienced the same downward trend from  to . per cent, while China’s share increased from . to . per cent (OECD, ). Especially in a period of dramatic transformations, and the continuing Fourth Industrial Revolution, support for structural changes and upgrading/renewal in industries is fundamental. European countries are implementing industrial policy to adapt to the industrial revolution, but their effort is small in size relative to countries such as the United States and China, and European countries would gain from further integrating their efforts. ⁶ A triadic patent family is defined as a set of patents registered in the three major patent offices: the European Patent Office (EPO), the Japan Patent Office (JPO), and the United States Patent and Trademark Office (USPTO).

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  :   



The Fourth Industrial Revolution is characterized by the development of scientific breakthroughs and disruptive technologies such as the Internet of things (IoT), robotics, virtual reality (VR), and artificial intelligence (AI), but also nanotechnologies, genomics, and new materials, which are changing the economy and the society. The Third Industrial Revolution was characterized by the development of computers and IT (information technology) in the second half of the twentieth century. The Fourth Industrial Revolution builds on innovations of the third but is considered a new era because it generates technological development that is massive and disruptive (Bianchi and Labory, ; Schwab, ). The growing awareness of the deep transformations involved and the importance for industry to adapt and participate in the process have led governments to design and implement industrial policy aimed at supporting these structural changes. European countries have been among the first countries to do so.

.. Germany Germany in particular can be argued to be the first country to have adopted an industrial policy for the manufacturing revolution. The term ‘Industry .’ was first publicly introduced in  as Industrie . by a group of business, government, and academia representatives who gathered to reflect on how to enhance German competitiveness in the manufacturing industry. The German federal government adopted their proposal in its High-Tech Strategy for . A working group was created to further advise on the implementation of Industry ., which made recommendations in . They stressed the deep changes occurring in manufacturing, since ‘these cyber-physical systems comprise smart machines, storage systems, and production facilities capable of autonomously exchanging information, triggering actions, and controlling each other independently. This facilitates fundamental improvements to the industrial processes involved in manufacturing, engineering, material usage, and supply chain and life-cycle management.’ The term is now widely used to indicate the transformation of productive processes induced by the technological changes of the Fourth Industrial Revolution: a new organization of production is possible in the ‘smart’ or ‘digital’ factory, where machines and robots interact to adapt and manufacture customized products on a large scale, thanks to cyber-physical systems that also interact directly with the customer. Bianchi and Labory (a) argue that this implies a change in the manufacturing system, since the Fourth Industrial Revolution allows the setting up of largely automated manufacturing processes that enable products to be personalized (economies of scope) on a large scale (economies of scale). Mass production had high volumes (scale) but low differentiation (scope). Industry . (mass customization) allows both high scale and high scope. These changes allow business to develop new products, launch new markets, and change existing ones. Disruption in industry is even increased by the

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

    

emergence of new market intermediaries in the form of digital platforms (Bianchi and Labory, ). Germany’s industrial policy has therefore been focused on Industry . in recent years (together with the earlier focus on green technologies), and the prime importance of technological and innovation policy, since this revolution is primarily about scientific discoveries and technological breakthroughs in various fields. The governance process is participative, in the sense that it is based on a dialogue with stakeholders— industry, science, and social partners. The funding model is based on public sources, targeting research, partnership-building, competence centres, and test-beds, but industry also contributes, especially larger firms who contribute proportionately more. German industrial policy for the manufacturing revolution is particularly concerned about SMEs, which may lack access to finance and other resources for the transition and structural changes involved. The government strategy requires industry co-financing, but large firms provide proportionately more financing than SMEs. The German government has also been increasingly concerned over the protection of its industrial know-how, especially since Chinese organizations have started to acquire German firms. This led the German economics minister Peter Altmaier to announce the possibility of the German state buying stakes in German companies in order to maintain its industrial know-how.⁷

.. The United Kingdom After the period of policies characterized by privatization, deregulation, and the free market in the s and s, the United Kingdom economy had a weak performance at the turn of the twenty-first century: increasing trade deficit, decreased manufacturing capacity, and rising regional inequalities (Bailey and Tomlinson, ; O’Sullivan et al., ; Chang et al., ). The financial crisis made the situation even worse, and the government realized that countries with stronger manufacturing bases had better capacity to recover. Concern over de-industrialization increased and successive governments introduced different measures to support a revival of British industries. By the end of the second decade of the new century, however, the performance of the British economy had not substantially improved, productivity being particularly low relative to other advanced countries (Bailey and Tomlinson, ). The United Kingdom has good research capacity, with four universities in the top ten in the world. However, the manufacturing base is so weakened that it has been unable to transform this research capacity into upgraded commercial products. It is a question not only of strengthening the links between research institutions and industry, but also of increasing manufacturing capacity, particularly through the development of

⁷ Reuters,  February : https://www.reuters.com/article/us-germany-industry/german-stateready-to-buy-company-stakes-to-protect-core-industry-idUSKCNPUD.

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  :   



manufacturing skills. The United Kingdom particularly lacks the intermediate skills that are so important to industry. Catapult centres have been created, following the German model of Fraunhofer Institutes, in order to increase the capacity to transform innovation into industrial products and processes. They are based on specific technologies and scientific domains and aim at gathering stakeholders, particularly universities and industry, to promote the industrial application of research. They are funded by private businesses, the UK government, and other sources (such as EU funds). According to Bailey and Tomlinson (), the public funds allocated to catapult centres have been limited so far, at least compared to efforts made in other countries. Another problem is the lack of engagement with SMEs. As a result of both the fear of de-industrialization and lagging productivity, UK governments have regularly adopted industrial strategies. The measures announced have been promising, but the problem is that governments have changed and so have strategies, so the overall picture is confusing and amounts to myriad different measures, some remaining from the past and some new, but their coherence is largely uncertain. Businesses in the United Kingdom complain about the lack of support for SMEs and for training and education. SMEs do not have the resources to define and implement their own training and education programmes, so they rely on public programmes, which are lacking in the United Kingdom.⁸ A Green Paper on ‘Building our Industrial Strategy’ was adopted in January  to relaunch industrial policy. However, it largely reiterates existing measures (Bailey and Tomlinson, ). The government has also committed to a rise in R&D effort in the Green Paper, as well as raising skills with the creation of Institutes of Technology that could provide the lacking intermediary skills. Surprisingly, the Green Paper does not mention Industry ., on which industrial policy in other European countries, such as Germany and France, is focused. Given the evidence regarding this important industrial transformation, leading to a new manufacturing paradigm (Bailey and Tomlinson, ) or manufacturing regime (Bianchi and Labory, a), industrial policy should be centred on support to the important structural changes involved. Transition to the new manufacturing regime, moreover, could be an opportunity for the United Kingdom to rebuild British industry following new technologies. Another important point concerns regional imbalances. We argued above that German industrial policy is extremely coherent in its multilevel governance framework, with the regional governments (Länder) tailoring federal policy to regional characteristics, namely to the regional mix of industries. This is particularly true with respect to R&D and training efforts; for instance, intermediate skills are provided in apprenticeship programmes that are broadly defined at the federal level but specifically

⁸ For instance, in the Financial Times, ‘Is the UK’s New Industrial Strategy Starting to Work?’ ().

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

    

defined together with industrial actors at the regional level. This favours industrial development, but also balanced development across the country. From this perspective, the UK economy has strong regional inequalities, but recent industrial policy initiatives have not addressed this issue. The recent abolition of Regional Development Agencies (RDAs) and their replacement by Local Enterprise Partnerships (LEPs), which are development agencies operating at very small scale, namely that of local authorities, does not seem to help regional rebalancing. LEPs are too small and fragmented to be able to implement effective industrial policy.⁹

.. Italy Like the United Kingdom, Italy has strong regional inequalities, despite a relatively strong manufacturing sector. In fact, the latter sector is strong mainly because the north of the country reaches development levels and industry sophistication comparable to the most advanced regions in the European Union. In contrast, the southern part of the country (the Mezzogiorno) has continuously declined in recent decades. National policies have failed to address this problem (see Barzotto et al., ). Industrial policy at the national level has been missing, apart from a few initiatives that sometimes could not even start due to political instability. One initiative that has been effective is Industria ., launched in  in order to finance the adaptation of Italian industry to the Fourth Industrial Revolution. However, the populist coalition that took office in  did not relaunch that policy. It can be argued that the main industrial policy implemented in Italy is at the regional level, mainly due to a reform of the constitution providing regions with competence over development policy, particularly industrial development. For instance, Bianchi and Labory (b, b) have analysed the effective industrial policy carried out in the Emilia-Romagna region in recent decades. Not all regions, however, have the institutional capacity to define and implement appropriate industrial policies; southern regions are particularly disadvantaged in this respect, and decentralization has not helped them.

.. France The French government relaunched industrial policy in , with the main objective of promoting specialization in new, technology-intensive sectors. The two main measures were the creation of ‘competitiveness poles’ and an Agency for Industrial

⁹ This has been stressed to the UK Parliament by economists of the Regional Studies Association: https://publications.parliament.uk/pa/cm/cmselect/cmbis/writev/lep/m.htm.

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  :   



Innovation (AII) that coordinated actions for the new sectors and also intervened in some of the competitiveness poles. The policy thus constituted an attempt at decentralization, inviting territories to identify possible synergies between activities so as to create these poles around specific productions. Each pole gathered together businesses, training and research centres, and the local government to reach the necessary critical mass for international visibility. The mission of the AII was to promote and support big programmes of industrial innovation that would be led by large groups, hopefully leading to commercial success in new markets. The AII would help with technological foresight and project selection, financing, and monitoring. The initial budget amounted to € billion, mainly financed by privatizations. However, the agency only operated for twenty-seven months. Programmes initiated before  are now followed by OSEO, a state-controlled company that supports financial access to businesses, especially SMEs. In fact, the absorption of the AII into OSEO is associated with a shift of industrial policy towards major support for small and medium-sized firms ( to  employees), as well as enterprises of intermediate size (entreprises de taille intermédiaire, ETI,  to , employees), which are lacking in the country. OSEO is characterized by decentralization, in the sense that it has regional offices which allow it to be closer to territorial entrepreneurs. It favours collaborative projects between SMEs in strategic sectors that have concrete commercialization prospects at the world level. The objective is to help the emergence of European champions. A good part of the financing provided by OSEO goes to competitiveness poles. In , a state holding, BPI France, was created, bringing together OSEO, CDC Enterprises (public institutional investor), and the sovereign fund FSI (Fond Stratégique d’Investissement). In other words, all sovereign funds existing in France at the time were grouped into a single organization. BPI France supports enterprise growth and internationalization through innovation. It is controlled by the state and the Caisse des Dépôts, an institution that uses public funds to finance public projects. The French state has thus returned to stronger intervention in markets. The turning point was the intervention to save the enterprise Alstom, producer of railway equipment, from failure in , leading to a return of industrial policy in . The new industrial policy is pragmatic in that while horizontal measures are favoured, direct and selective interventions are considered when necessary. However, French industrial policy does not appear to have been consistent across the years since . While the general approach has continued to be innovation and support to SMEs and firms of ‘intermediate’ size, measures have been constantly either changed or re-dimensioned. For instance, in  the objective of the competitiveness poles was to bring together regional stakeholders to favour the launch of new products and process; in , the objective was to realize ‘fabrics of projects’, while in  it was again to realize new products. Each pole brings together a very large number of participants, apparently too many to focus projects and reach critical mass for each of them. In addition, the overall financing of the poles, provided by the Fond Unique d’Innovation (FUI, Single Innovation Fund), has decreased by about  per cent over

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

    

the period  to  (François, ).¹⁰ Evaluations of this policy do not appear to have assessed the performance of the poles in terms of product and firm creation, and business competitiveness, although Hassine and Mathieu () show that the participation of SMEs and ‘intermediate-sized’ firms has allowed them to invest more in R&D. The overall objective is to rebuild ‘industrial France’ or develop industries of the future, but the measures being taken are fragmented and inconsistent, lacking an industrial development vision for the country and a mobilization of efforts towards this vision. Industrial policy requires specific choices and substantial financial support, both of which are missing. The present government’s project to build a New Industrial France is based on the plan for industrial reconquest, comprising thirty-four plans, launched by the previous government in . As a result, French industrial policy has been essentially defensive. Large firms have been saved from failure, such as Areva (nuclear sector), STX France (shipbuilding), and Alstom. This contrasts with the German policy, which has been proactive. A number of fiscal reliefs for business have been adopted by President Macron since his election, but whether industries have used the money saved to invest in long-term growth plans remains to be seen. What is clear is that the policy defined under the previous government and pursued by the new one has not produced positive effects: the condition of the French industrial sector has not substantially changed, with two million jobs in industry lost since the s.

. C

.................................................................................................................................. All European countries have followed similar trends in industrial policy. From a historical perspective, industrial policy has been an instrument of the power of the state. Thus, continental European countries implemented strong policies to industrialize and reach the development level of the United Kingdom, pioneer of the First Industrial Revolution. This was important both to raise the economic performance of the country, and hence its wealth, but also to enhance its military capacity with new technologies and an increased power of deterrence in international relations. Especially among the first industrializers, economic and military, therefore political power, are intimately linked. This was also the case after the Second World War, when the United States, but also European countries, invested heavily in new technologies in a race to affirm their status as world powers. This race in turn fed industrial development, since many innovations made for defence purposes had numerous industrial applications in a variety of sectors. Strengthening industry has been an important strategy for China, which is now a world power. ¹⁰ Computation by the authors from data shown in François (: ).

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  :   



Industrial policy has also been stronger in times of market disruptions caused both by changes in the extent of the market, such as the opening of international trade and later globalization, and by technological progress, especially in industrial revolutions. Once markets and production systems are established and incumbent firms defined, the role of industrial policy reduces. However, when new technologies appear, or new businesses with improved or renewed products enter markets or create new ones, established firms have to change their structure, and hence whole industries might be threatened or in need of transformation, calling for government intervention. Today the focus of industrial policy in European countries is on the adoption of the new technologies of the Fourth Industrial Revolution to upgrade manufacturing processes, as well as introducing new products that can encourage new industries. One notable difference concerns regional imbalances: some countries have consistently addressed them (Germany, Finland), while others have not (France and the United Kingdom). Yet a regional (or local) focus is particularly required today for two reasons. First, globalization has made the locational footprint more important for companies today, not less. Firms develop or locate in centres of excellence, where institutions are coherently defined and infrastructure well developed, and where human capital with appropriate skills and learning/innovation capabilities is available. Territories not able to construct these strengths are left behind (Bianchi and Labory, b). Second, incumbent firms in established sectors can only be challenged by small, innovative actors that develop from the bottom up. Territories must therefore implement industrial policies in order to develop the capacity to favour the emergence of these smaller, game-changing actors. This is also important to maintain social cohesion in times of deep structural changes. Finland is an example, with the failure of Nokia spurring important government programmes to favour the creation of new, innovative firms at national and regional levels. Attention is also required at higher levels of the multilevel governance (MLG) process. Coherence and action are important between national and international levels of government, as well as between national and lower levels. In a globalized world, many issues introduced by the Fourth Industrial Revolution have to be addressed at an international level, such as regulation of digital platforms and standards for emerging new products and processes, such as robots and artificial intelligence. Environmental sustainability and climate change are also global issues. The discussion in this chapter adds another consideration regarding higher levels of the MLG process: European countries on their own do not have adequate size and scope to compete against the United States and China. Some truly joint and integrated efforts should be made in order to favour competitive European businesses such as Airbus. There are no European firms in a number of key sectors of the manufacturing revolution: there are no European Googles, Amazons, or Alibabas; the most powerful supercomputers produced in the world today are produced in Japan, the United States, and China; and there is only one European company (SAP, Germany) among the top ten big-data companies in the world in .

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

    

R Ali-Yrkkö, Jyrki (ed.) () ‘Nokia and Finland in a Sea of Change’. Helsinki: ETLA, Research Institute of the Economy of Finland, Taloustieto Oy. Allen, Robert C. () Global Economic History: A Very Short Introduction. Oxford: Oxford University Press. Andreoni, Antonio and Ha-Joon Chang () ‘The Political Economy of Industrial Policy: Structural Interdependencies, Policy Alignment and Conflict Management’, Structural Change and Economic Dynamics : –. Bailey, David and Philip R. Tomlinson () ‘Back to the Future? UK Industrial Policy after the Great Financial Crisis’, in Philip Arestis and Malcolm Sawyer (eds) Economic Policies since the Global Financial Crisis. Basingstoke: Palgrave Macmillan, pp. –. Bailey, David, Helena Lenihan, and Ajit Singh () ‘Tiger, Tiger, Burning Bright? Industrial Policy “Lessons” from Ireland for Small African Economies’, in Akbar Noman, Kwesi Botchwey, Howard Stein, and Joseph E. Stiglitz (eds) Good Growth and Governance in Africa: Rethinking Development Strategies. Oxford: Oxford University Press, pp. –. Bairoch, Paul () Economic and World History. Brighton: Wheatsheaf. Barzotto, Mariachiara, Carlo Corradini, Felicia M. Fai, Sandrine Labory, and Philip R. Tomlinson () ‘Enhancing Innovative Capabilities in Lagging Regions: An Extraregional Collaborative Approach to RIS’, Cambridge Journal of Regions, Economy and Society : –. Bianchi, Patrizio () La rincorsa frenata. L’industria italiana dall’unità nazionale all’unificazione Europea. Bologna: Il Mulino. Bianchi, Patrizio and Sandrine Labory (eds) () International Handbook of Industrial Policy. Cheltenham: Edward Elgar. Bianchi, Patrizio and Sandrine Labory (a) Industrial Policy after the Crisis: Seizing the Future. Cheltenham: Edward Elgar. Bianchi, Patrizio and Sandrine Labory (b) ‘Industrial Policy after the Crisis: The Case of the Emilia-Romagna Region in Italy’, Policy Studies (): –. Bianchi, Patrizio and Sandrine Labory () Industrial Policy for the Manufacturing Revolution. Perspectives on Digital Globalisation. Cheltenham: Edward Elgar. Bianchi, Patrizio and Sandrine Labory (a) ‘Manufacturing Regimes and Transitional Paths: Lessons for Industrial Policy’, Structural Change and Economic Dynamics : –. Bianchi, Patrizio and Sandrine Labory (b) ‘Regional Industrial Policy for the Manufacturing Revolution: Enabling Conditions for Complex Transformations’, Cambridge Journal of Regions, Economy and Society (): –. Bianco, Magda () L’industria italiana. Bologna: Il Mulino. Blomström, Magnus and Ari Kokko () ‘From Natural Resources to High-Tech Production: The Evolution of Industrial Competitiveness in Sweden and Finland’. EIJS Working Paper Series No. , Stockholm School of Economics, The European Institute of Japanese Studies. Brander, James A. () ‘Shaping Comparative Advantage: Trade Policy, Industrial Policy and Economic Performance’, in Richard G. Lipsey and Wendy Dobson, (eds) Shaping Comparative Advantages. Toronto: C. D. Howe Institute, pp. –. Chang, Ha-Joon and Jostein Hauge () ‘The Role of Manufacturing versus Services in Economic Development’, in Patrizio Bianchi, Sandrine Labory, and Clemente Ruiz Duran

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  :   



(eds) Transforming Industrial Policy for the Digital Age: Production, Territories and Structural Change. Cheltenham: Edward Elgar, pp. –. Chang, Ha-Joon, Antonio Andreoni, and Leon Kuan, M. () ‘International Industrial Policy Experiences and the Lessons for the UK’. Report for the UK Government’s Foresight Future of Manufacturing, London. Cimoli, Mario, Giovanni Dosi, and Joseph E. Stiglitz (eds) () Industrial Policy and Development: The Political Economy of Capabilities Accumulation. The Initiative for Policy Dialogue Series. Oxford: Oxford University Press. Cullen, Elizabeth () ‘Unprecedented Growth, But for Whose Benefits?’, FEASTA Review : –. Curzon-Price, Victoria () Industrial Policies in the European Community. London: Macmillan. Darvas, Zsolt, Philippe Martin, and Xavier Ragot () ‘European Fiscal Rules Require a Major Overhaul’. Policy Contribution Issue No. , Bruegel Institute. Available at https:// bruegel.org/wp-content/uploads///PC-_.pdf. Donges, Juergen () ‘Industrial Policy in West Germany’s Not So Market-oriented Economy’, World Economy (): –. Dosi, Giovanni, Patrick Llerena, and Mauro Sylos Labini () ‘The Relationships between Science, Technologies and their Industrial Exploitation: An Illustration through the Myths and Realities of the So-called “European Paradox” ’, Research Policy : –. European Commission () Green Paper on Innovation. Brussels: European Commission. Eyraud, Luc, Gaspar Vitor, and Tigran Poghosyan () ‘Fiscal Politics in the Euro Area’. IMF Working Paper No. /. Washington, DC: IMF. Federico, Giovanni and James Foreman-Peck (eds) () Industrial Policies in Europe. Oxford: Oxford University Press. Feldenkirchen, Wilfried () ‘Germany: The Intervention of Interventionism’, in Giovanni Federico and James Foreman-Peck (eds) Industrial Policies in Europe. Oxford: Oxford University Press, pp. –. Financial Times () ‘Is the UK’s New Industrial Strategy Starting to Work?’,  November. Available at https://www.ft.com/content/bb-efb-e-c-ddc. Foreman-Peck, James and Leslie Hannah () ‘Britain: From Economic Liberalism to Socialism—and Back?’, in Giovanni Federico and James Foreman-Peck (eds) Industrial Policies in Europe. Oxford: Oxford University Press, pp. –. François, Philippe () ‘Pôles de compétitivité: , Phase IV, le temps des résultats’. Available at https://ifrap.org/emploi-et-politiques-sociales/poles-de-competitivite-phase-iv-le-temps-des-resultats. Freeman, Chris and Francisco Lourça, () As Time Goes by: From the Industrial Revolutions to the Information Revolution. Oxford: Oxford University Press. Gille, B. () Histoire des techniques: technique et civilisations, technique et science. Paris: Gallimard, Collection La Pleiade. Hassine, Haithem-Ben and Claude Mathieu () ‘Évaluation de la politique des pôles de compétitivité: la fin d’une malédiction?’/France Stratégie, Document de Travail No. / . Available at https://www.strategie-gouv.fr. Jäntti, Markus and Juhana Vatiainen () ‘The Finnish Developmental State and its Growth Regime’. Research Paper No. /. Helsinki: UNU-WIDER. Ketels, Christian () ‘Clusters, Cluster Policy, and Swedish Competitiveness in the Global Economy’. Expert Report No.  to Sweden’s Globalisation Council, Stockholm. Available

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at https://www.hhs.se/contentassets/fbedefacdabde/clusterscluster policyswedishcompetitivenessde.pdf. Kirby, Peadar () Celtic Tiger in Collapse: Explaining the Weaknesses of the Irish Model. nd edition. Basingstoke: Palgrave Macmillan. Labory, Sandrine () ‘La politica industriale in un’economia aperta e basta sulla conoscenza’, L’Industria : –. Lall, Sanjaya () ‘Industrial Policy in Developing Countries: What Can We Learn from East Asia?’, in Patrizio Bianchi and Sandrine Labory (eds) International Handbook of Industrial Policy. Cheltenham: Edward Elgar, pp. –. Landes, David () The Unbound Prometheus. Cambridge: Cambridge University Press. Levy-Leboyer, M. (ed.) () Histoire de la France Industrielle. Paris: Larousse. Malerba, Franco () ‘Il sistema innovativo italiano’, in Franco Malerba (ed.) Economia dell’innovazione. Roma: Carocci, pp. –. Markgraf Jonas and Nicolas Véron () ‘Germany’s Savings Banks: Uniquely Intertwined with Local Politics’. Bruegel Institute. Available at https://bruegel.org///germanyssavings-banks-uniquely-intertwined-with-local-politics/. Mokyr, Joel () ‘Editor’s Introduction: The New Economic History and the Industrial Revolution’, in Joel Mokyr (ed.) The British Industrial Revolution: An Economic Perspective. nd edition. Boulder, CO: Westview Press, pp. –. OECD () Main Science and Technology Indicators. Available at https://read.oecd-ilibrary. org/science-and-technology/main-science-and-technology-indicators/volume-/issue_ggfbe-en#page. O’Sullivan, Eoin, Antonio Andreoni, Carlos Lopez-Gomez, and Mike Gregory () ‘What is New in the New Industrial Policy? A Manufacturing System Perspective’, Oxford Review of Economic Policy (): –. Pelkmans, Jacques () ‘European Industrial Policy’, in Patrizio Bianchi and Sandrine Labory (eds) International Handbook of Industrial Policy. Cheltenham: Edward Elgar, pp. –. Rolfo, Secondo and Giuseppe Calabrese () ‘Traditional SMEs and Innovation: The Role of the Industrial Policy in Italy’, Entrepreneurship and Regional Development : –. Schwab, Klaus () The Fourth Industrial Revolution. Geneva: World Economic Forum. Smith, Adam () An Enquiry into the Wealth of Nations, reprinted in  by J. M. Dent & Sons Ltd, London ( vols). Vanden Bosch, Xavier () ‘Industrial Policy in the EU: A Guide to an Elusive Concept’. Egmont Paper No. . Brussels: The Royal Institute for International Relations. Van Neuss, Leif () ‘Why Did the Industrial Revolution Start in Britain?’, Working Paper, University of Liège. von Tunzelmann, Nick () ‘Technology and Technology Policy in the Postwar UK: “Market Failure” or “Network Failure”?’, Revue d’économie industrielle –: –. Whelan, Karl () ‘Golden Rule or Golden Straightjacket?’, VOX, CEPR Policy Portal,  February. Available at https://voxeu.org/article/golden-rule-or-golden-straightjacketcritique-europe-s-fiscal-compact. Ylä-Anttila, Pekka and Christopher Palmberg () ‘Economic and Industrial Policy Transformations in Finland’, Journal of Industry, Competition and Trade : –.

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        ......................................................................................................................

               ’                .............................................................................................................

 .    ö

. I

.................................................................................................................................. I policy is back on the agenda around the globe. UNCTAD reports that since  no less than eighty-four countries have adopted formal industrial policy strategies (UNCTAD, ). The return of industrial policy (Wade, ) followed a period of industrial policy fatigue in the s and s. One of the reasons for the renewed interest in industrial policy is dissatisfaction with the growth and structural outcomes of the non-interventionist period of the s and early s. In the European Union (EU), concerns about de-industrialization in several member states, changing global context, as well as the experiences of persistent regional disparities and the uneven impact of the financial and economic crisis after , have played their part in altering the way industrial policies are perceived. Industrial policy in the EU has traditionally been a mixed approach, incorporating horizontal as well as sector-specific measures—with significant variation in focus throughout the decades. More recently, policy frameworks have multiplied with new approaches emerging from various fields ranging from Schumpeterian growth theories (Aghion et al., ) to empirically driven patterns of industrial development across product spaces (Hidalgo et al., ) to new conceptual frameworks that guide policy initiatives at the EU level, such as ‘mission-oriented’ policies (Mazzucato, ) or ‘smart specialization’ (Foray et al., ; Foray, ).¹ One unifying theme, though,

¹ For an overview see, for example, Radosevic ().

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

 .    ö

seems to be the rather general assertion that purely horizontal industrial policy is either inadequate or simply not possible.² Identifying the industrial policy stance of the EU is complicated by at least three factors. First, due to the high importance assigned to competition policy within the single market, subsidies are prohibited by default. More precisely, the European state aid rules prohibit subsidies that distort or threaten to distort competition between member states, unless they are justified by reasons of general economic development. While there are several exceptions to the general ban (e.g. projects of common European interest such as the Airbus endeavour), the assessment of the legitimacy of state aid is still governed by a market-failure approach. So the strict competition rules of the single market, itself part and parcel of the EU’s industrial policy (and arguably one of its greatest successes), has to be considered along with continued state aid support by EU member states, all of which must have been cleared by the European Commission and deemed compatible with the rules of the Single Market. Second, and related to the point above, industrial policy action takes place at both member-state and EU levels. Furthermore, member states, to varying degrees, delegate the formulation and implementation of industrial policy to the regional level. The same is true for the EU’s cohesion policy, realized via the numerous European Structural and Investment Funds (ESIF), a cornerstone of EU industrial policy. Third, at the EU level, making sense of industrial policy action is difficult, given the numerous strategies, programmes, actions, and initiatives that are announced, as it seems, at ever shorter intervals. Recently, the EU has developed the habit of publishing a new or adopted industrial policy strategy every second year or so (see European Commission, , a, , , a, ) with the latest one calling for investment in a smart, innovative, and sustainable industry. Triggered by the European Commission’s blocking of the planned Siemens-Alstom merger,³ intense negotiations about yet another reformed industrial policy (EPSC, ; European Commission, ) are taking place at this time. The rise of China with its geopolitically motivated One Belt, One Road (OBOR) Initiative and its comprehensive and ambitious industrial policy strategy, entitled ‘Made in China ’, is another major trigger for the new European industrial policy drive. China’s successful catching-up process and ambitious industrial strategy shows that EU industrial policy (be it at the supranational, the national or the regional level) is not conducted in a vacuum but is necessarily context specific. Changing global and

² This is because any form of industrial policy, even if designed as a horizontal measure such as R&D support or even a slightly undervalued exchange rate, will affect sectors differently or, as Rodrik puts it: ‘In practice most interventions, even those that are meant to be horizontal, necessarily favor some activities over others’ (Rodrik, : ). ³ The motivation behind the deal was to create a European player in the rail sector which has sufficient scale to compete with the rapidly expanding (state-owned) Chinese rivals. The European Commission’s decision has intensified the perception that the tough European competition rules in the areas of merger control, state aid, or also public procurement put European firms at a disadvantage vis-àvis foreign competitors who do not always play according to the same rules.

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   ’   



socio-economic circumstances are shaping policy efforts and priorities. The contextual nature implies that all discussions on European industrial policy are embedded in overarching economic challenges the EU is facing, namely, the objectives that it has set itself in the Lisbon Agenda and subsequent strategies. Interestingly, for the EU some of the challenges and associated objectives of industrial policy have remained surprisingly constant over decades. Others have been added following the EU’s growth in both size and diversity or with new global trends such as climate change and the deterioration of the environment more generally. The most pressing economic challenges may be summarized as follows: (i) Technological/innovation challenge: Keeping pace with the technologically most advanced economies in future-oriented technological areas, which includes the digital transformation. This has been one of the long-standing aspirations of EU industrial policy. In order to defend the European Union’s position at the technology frontier in many technology-driven industries, it is imperative to build on inherited strengths of industrial, technological, and human capital structures. (ii) Emerging markets challenge: Meeting the challenge of fast-catching-up emerging economies through both competition and collaboration. In this, China merits special attention due to its dynamic growth as well as both its geopolitical ambitions realized via OBOR and its technological ambitions as laid down in ‘Made in China ’, the country’s ambitious industrial policy strategy. (iii) Cohesion challenge: To foster progress in the field of convergence and cohesion policy within the European Union. A major issue in an industrial context here is the fact that peripheral regions and countries, in order to make progress in their initial industrialization or structural upgrading process, are confronted with strong agglomeration tendencies inherent in tradable activities in core areas of Europe’s economy. (iv) Environmental challenge: Dealing with the challenges of the Paris Agreement on climate change and sustainability issues more generally. Given the comparatively strong regulatory framework for environmental protection, European industry is bound to adjust and incorporate resource efficiency, emission reduction, and sustainability in a cost-efficient manner. The implications for the competitiveness of European industry of such a shift to the aspired circular economy are as yet unclear and differ across industries. On the one hand, regulations that force firms to increasingly rely on sustainable or re-usable goods (including packaging) may develop first-mover advantages in a series of new materials and technologies. On the other hand, initially several of these regulations will impose additional costs on firms producing within the EU. The structure of the remainder of this chapter is as follows. Section . briefly reviews the evolution of industrial policy in Europe and of the supranational (EC and then EU) layer in particular. Subsequent section . puts numbers on the relative importance of

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

 .    ö

EU industrial policy action. This quantitative exercise identifies the policy priorities based on member states’ (compulsory) notifications of state aid⁴ to enterprises and at the EU level based on budgetary expenditures on (broadly defined) industrial policy measures. This represents an important supplement to the conventional analysis of European industrial policy based on the study of policy documents. The quantitative approach seems appropriate as an effective industrial policy requires not only a sound policy formulation but also proper implementation⁵ including the appropriate funding.⁶ The penultimate section, section ., discusses the extent to which current industrial policies and the identified priorities can contribute to the key challenges ahead. The conclusion, section ., presents recommendations for EU industrial policy for the future.

. T E  EU I P   N

.................................................................................................................................. The history of industrial policy in the EU can be divided into three phases: an early interventionist phase (–), a liberal phase (–), and the current phase which Bianchi and Labory () have dubbed the ‘pragmatic’ phase.⁷ The three phases and some of their main features as well as selected key measures and initiatives are summarized in Table . and briefly reviewed in the following sub-sections (see also Bianchi and Labory, Chapter  this volume).

.. The Interventionist Phase (–) During the interventionist phase, European industrial policy was mainly conducted and shaped by national governments. As a consequence, industrial policies in most of the six founding members of the European Economic Community (EEC) were nationally oriented.⁸ The public policy grip on industry was much stronger back in the s and throughout the s than it is nowadays. Despite notable differences in type and intensity of industrial policy across member states, a common feature was the identification of, and particular support for, ‘strategic ⁴ ‘State aid’ is EU jargon for subsidies provided by national governments. ⁵ To policy formulation and implementation, one should also add evaluation. ⁶ This is true at least for active industrial policy measures. In contrast, framework policies might be budget-neutral. ⁷ Bianchi and Labory () use a slightly different temporal delimitation of the liberal and the pragmatic phase. ⁸ The founding members of the EEC (as well as the European Community for ECSC) were Belgium, France, Germany, Italy, Luxembourg, and the Netherlands.

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   ’   



Table 22.1 The three phases of industrial policy in the European Union Interventionist phase (1950–80)

Liberal phase (1980–2005)

Pragmatic phase (since 2005)

Member-state level Heyday of sector-specific industrial policies

Full shift of emphasis on framework Return of specific industrial and horizontal policies policies resulting in an industrial ‘policy mix’ Blend of interventions in Policies influenced by the Industrial policies constrained sunset industries, high-tech Washington Consensus; gradual by fiscal and competition industries, and public withdrawal of national subsidy rules utilities policies Nurturing of national Privatization of utilities Initiatives towards ecological champions transformation (some member states) Active FDI policies Experimentation with European Champions (Airbus, 1970) EU level Creation of the Common Market (1957) and the Customs Union (1960) Competition rules in place (1957) but largely ineffective Sectoral policies for coal, steel, and nuclear energy

Emergence of EU technology policy Europe 2020 Strategy (ESPRIT, 1980) Tightening of EU competition policy: Further focus on RTI policies modernization of state aid rules (2012); introduction of merger control (1989) European Economic Act ICT-sector programme Lisbon Strategy (2000) focused on knowledge-based competitiveness

Strategic Investment Plans Smart Specialisation Strategy (2012) institutionalized in regional policy Mission-oriented industrial innovation policies (planned) Global Europe Strategy (2006)

Source: Authors’ own representation using the periodization in Bianchi and Labory (2006).

industries’. There was a considerable overlap with respect to the targeted industries, defined on the basis of specific economic characteristics such as strong linkages with other parts of the economy and high-technology content (e.g. aircraft, computers, automotive industry) but also social considerations such as their importance for employment (e.g. coal and steel, shipbuilding) (Owen, ). Equally important, network industries with public goods characteristics (i.e. public infrastructure such as electricity generation, telecommunications, railway companies) were administered almost exclusively by state-owned companies.

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

 .    ö

In countries such as France and the United Kingdom,⁹ the selection of strategic industries was inextricably linked with the aim of creating national champions, that is, dominant domestic companies that should become successful in international markets.¹⁰ National champions are the most characteristic element in the European industrial policy set-up during the s. Taking place in an environment of comparatively protected domestic markets (by the standards of the s), the plan for creating a national champion typically consisted of a complex web of numerous support measures, including direct subsidies and preferential loans but also public procurement, the provision of technology by government-supported agencies, merger promotion, industrial diplomacy, export credits, and subsidies to domestic upstream suppliers to ensure access to strategic inputs (Owen, ). In France, such endeavours were often linked to a ‘grand project’, a prestigious technological undertaking, which constituted the primary mission of the future superstar firm.¹¹ Underlying these ambitious industrial policy projects was a belief in the need for technological (and in the case of France also military) independence, especially from the United States. This shows that even half a century ago, industrial policy in Europe was already driven by concern about an existing technology gap vis-à-vis the United States. Hence, one encounters here Europe’s enduring objective of matching (or catching-up with) the United States in strategic technologies or defending leadership positions already achieved, such as in car manufacturing. However, more often than not, such as in the highly subsidised computer industry, international competitiveness and export success did not materialize. In addition to the high number of failures and the high cost to taxpayers involved, the dirigiste policy approach in the industrial sector also lost appeal due to the creation of the EEC and the common market (the predecessor of the single market), followed by the completion of the customs union in . The European Common Market,¹² establishing the free movement of goods, services, capital, and people, was complemented with far-reaching competition rules, including a general prohibition of state aid,¹³ to ensure its proper functioning. The enforcement of the competition rules was

⁹ The United Kingdom joined the EEC in  (together with Ireland and Denmark). ¹⁰ Approaches to industrial policy, while highly selective and comprehensively employed during this era, were by no means uniform—neither throughout the three decades stretching from the s to the s, nor across member states. The German economic model differed in so far as it embraced ordoliberalism as its guiding economic principle. The specificity of the ordoliberal concept, often considered as the key to the German ‘economic miracle’ of the post-war period, was its strong emphasis on competition and market forces. Still, the state had a much greater role to play than in the AngloSaxon liberal conception in so far as it had to provide vital infrastructure, an inclusive training and educational system, and to ensure regional cohesion. ¹¹ A prime example dating from the s was the construction of a super-fast train, the Train à Grande Vitesse (TGV), developed by Alstom. ¹² The European Common Market came into being with the creation of the EEC in . ¹³ According to these rules, governments were not allowed to grant aid ‘which distorts or threatens to distort competition . . . in so far as it affects trade by member states’. See Article  of the Treaty on the Functioning of the European Union (TFEU).

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   ’   



entrusted to the European Commission. This was a remarkable arrangement in a period that was still characterized by massive government subsidization and protectionism at the national level, even if the general prohibition on trade-distorting aid was qualified by a number of exceptions (e.g. regional aid or aid to projects of common European interest). Nevertheless, control over state aid by sovereign governments was obviously a delicate issue and the European Commission had to show a high degree of pragmatism in this respect (Doleys, ). In the historical context of the time this meant that the state aid rules were only laxly enforced during the early phase of the common market. Hence, one could argue that it was dissatisfaction with the outcome of interventionist policies in a more open-economy environment, together with the fiscal strains imposed by them, rather than the introduction of stringent competition rules, which caused the industrial policy pendulum to swing towards the more market-oriented policies that were to dominate for the following quarter of a century.

.. The Liberal Phase (–) The s saw a remarkable shift in the industrial policy focus towards less interventionism and a more market-oriented policy stance. Pioneered by the United Kingdom, which joined the EEC in , sectoral planning and support for individual companies was severely reduced or abandoned altogether. While also in this case there was considerable heterogeneity with regard to the stringency and comprehensiveness of the policy shift, there can be no doubt that competition, ‘horizontal’ measures, and improving the framework conditions increasingly replaced the quest for national champions. Especially in the United Kingdom the emphasis on market principles and competition implied a wave of privatizations that included most public utilities, including British Telecom in  (Owen, ). A second novel element of the new industrial policies, which were increasingly referred to as ‘enterprise policy’, was the vanishing resistance against foreign takeovers, including by US and Japanese companies, though this was truer in the United Kingdom than, for example, in France, which continued to insist on domestic ownership of the country’s key industrial assets for much longer. An event of greater geopolitical significance during this phase was the collapse of the Soviet bloc and the dramatic transformation of the former communist regimes of Eastern Europe. Relevant for this discussion is that the radical system change discredited any form of state planning. This led to a dismantling of existing state capacities that were deemed to be compromised, and there was a general suspicion of anything that smacked of ‘industrial policy’. The substitute for industrial policy was the attractiveness of quite a few of the Central and Eastern European (CEE) economies to foreign direct investment. This led to a process of ‘re-industrialization’ in some of the CEE economies (those close to the German–Austrian borders) after an initial phase of

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

 .    ö

collapse of industrial production. This drive was led by Western European firms that found the existing skilled (and comparatively low-waged) labour force attractive. Various support measures by governments (such as export-processing zones) encouraged FDI before accession of the CEE countries to the EU, which then had to be withdrawn to comply with the Acquis Communautaire. Importantly, the geographic closeness to the high-wage industrial zones in Germany and Austria encouraged the build-up of vertical cross-border production networks (see Stehrer and Stöllinger, ; Stöllinger, ). These developments (both in Western and Central and Eastern Europe) suggest a certain degree of convergence in industrial policies across countries between the s and the middle of the s. This convergence was further nurtured by the changed economic environment characterized by more open economies, the appearance of new players in the global trade arena and, not least, the emergence of regional and global production networks which called for an adjustment and, as it turned out, a retreat of active industrial policies (Landesmann and Stöllinger, ). Less clear was the growing importance of the EU, which emerged as a more relevant player in the industrial policy sphere during the second half of the liberal phase. The heightened importance of the supranational level in the field of industrial policy was both a contributing factor to the convergence in national policies and a consequence of member states’ growing belief in ‘horizontal policies’ that were seen as compatible with free and fair competition in open markets. EU industrial policy took shape in three quite distinct directions. The first and most far-reaching of these was the Single Market Programme introduced in . Its purpose was the deepening and strengthening of the already existing common market by further harmonization of regulations and a stronger integration of services markets. As such, the Single Market Programme is the archetypical framework policy and constitutes the top layer of industrial policy defining the boundaries and possibilities of other EU industrial policy activities. Second, the existing competition rules were broadened and strengthened. Competition law,¹⁴ including state aid rules, merger control, and public procurement, can be seen either as a part of industrial policy or as its natural antagonist. In any case, it acts as a disciplining layer of industrial policy, monitoring and disciplining state interventions by national governments and uncompetitive behaviour by firms. The third layer, which emerged during this phase, comprises active horizontally designed industrial policy at the supranational level, mainly in the domain of technology R&D collaboration and innovation as well as regional policy (Figure .). Third, active, horizontally designed support policies targeting R&D collaborations were fostered, as were regional policies, due to the growing heterogeneity of an enlarged EU. Early attempts to spur R&D collaboration at the EU level in the s were largely

¹⁴ The EU competition rules form part of the single market programme but given its great importance and its distinct features and consequences, they are considered as a separate component.

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   ’   



Top layer: Single Market Disciplining layer: Competition rules Active layer: Industrial policy initiatives

Industrial Policy by Member States

Horizontal Programmes

VI

 . The industrial policy structure of the EU Note: VI = vertical initiatives, including projects of European interests. Dark grey areas indicate the EU level, light grey areas indicate the level of member states. Source: Authors’ own representation.

unsuccessful,¹⁵ at least, with a view to achieving the main objective of closing the technology gap with the United States (and increasingly with Japan) in advanced industries such as electronics or aircraft. Despite the limited successes of the early R&D cooperation programmes, technology and R&D policy remained the cornerstone of the EU’s support for industrial development. This is reflected in both the wording of the Article on Industrial Policy¹⁶ that was introduced with the Treaty of Maastricht in  and also in the Lisbon Agenda, the EU’s major growth strategy devised in .¹⁷ The new article on industrial policy, which anchored the competences of the European Commission in this area in the EU treaties,¹⁸ however, has never attained great practical relevance. With regard to regional policy, which dates back to  with the establishment of the European Fund for Regional Development (EFRD),¹⁹ it was the successive rounds of enlargement²⁰ that advanced ‘cohesion’ to become one of the main EU policy domains. This implies that the European Structural and Investment Funds (ESIF) are concerned with distributive impacts (Schwengler, ). As will be seen, the scale of spending is quite large, providing finance not only for investments in infrastructure but ¹⁵ The first collaboration programmes included the European Strategic Programme on Research in Information Technology (ESPRIT) and the European Research Coordination Programme (EUREKA). ¹⁶ Article () of the TFEU dealing with industrial policy stipulates that the EU ‘shall ensure that the conditions necessary for the competitiveness of the Community’s industry exist’. ¹⁷ The Lisbon Agenda aimed at making the EU ‘the most competitive and dynamic knowledge-based economy’. ¹⁸ Article () makes industrial policy a ‘shared competence’, which means that member states remain the main actors but with complementary activities and regulatory power at the EU level. ¹⁹ The ERDF was the first of the European Structural and Investment Funds (ESIF). Currently, the ESIF family comprises five distinct funds: the ERDF, the European Social Fund (ESF), the Cohesion Fund (CF), the European Agricultural Fund for Rural Development (EAFRD), and the European Maritime & Fisheries Fund (EMFF). ²⁰ Greece entered the EC in , followed by Portugal and Spain in .

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

 .    ö

for a wide array of activities including labour-market and qualification measures, technology and environmental policy measures. The allocation of funds from the ESIF changed fundamentally with the EU enlargement of  because of the much lower per capita income of the CEE countries entering compared to the ‘old’ member states. Payments from the ESIF became an essential source for the financing of infrastructure investments in the CEE countries, which also made extensive use of European funds to attract foreign direct investment (FDI). Despite the propping up of activities in the domain of innovation and technology policy and the heightened role of regional policy, the EU’s approach to industrial policy throughout the liberal phase is best described as horizontal in design, aiming at creating favourable framework conditions and correcting market failures, both with the ultimate objective of supporting the industrial competitiveness of EU firms. While it was to become more heterogeneous and multi faceted over time, this approach would also remain dominant during the subsequent pragmatic phase.

.. The Pragmatic Phase (Since ) Starting sometime between  and the global financial crisis, the current pragmatic phase of industrial policy is hard to characterize as it is still evolving. Some authors argue that the Commission’s blocking of the planned Siemens–Alstom merger in  has initiated a fourth phase of European industrial policy (see EPSC, ). In this view, member states, dissatisfied with the tough EU competition rules against the background of growing international competition (often deemed unfair), demand a loosening of the competition rules in order to (re-)establish a level playing field— especially vis-à-vis Chinese companies. However, it seems too early for such a conclusion, so for the purpose of this chapter the pragmatic phase is considered to be still ongoing.²¹ It was nevertheless true that a renewed interest in more active industrial policies developed, especially in member countries that experienced a crippling loss of competitiveness of their industries within the European Monetary Union (vs. Germany) but also those which had undergone waves of de-industrialization which generated not only macroeconomic problems but also deep structural regional imbalances. The straightjacket of EU competition policy and the interdependencies in an increasingly integrated world economy tightly linked by global value chains made it ²¹ Apparently, France and Germany pressed the European Commission to come up with a new Industrial Policy Communication which should facilitate the creation of European champions, ideally by amending EU competition law (EPSC, ). The new Industrial Policy Communication (European Commission, ) was finally issued in March  and only marginally reflects the Franco-German demands and focuses instead on technological leaders in digital markets and a transformation to a ‘green’ economy.

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   ’   



impossible to reactivate the industrial policy toolkit of the past. As a consequence, member states had to turn to new designs for their industrial strategies that were both compatible with the single market and in particular with its competition rule, on the one hand, and more effective (and therefore more specific) policies than the purely horizontal approach followed until the early s, on the other. The attempts by governments to square this circle have been diverse, ranging from barely noticeable changes in policy (e.g. in most CEE member states which essentially held onto their FDI attraction policies) to a quite explicit revitalization of industry, technology, or skill-specific policies. In all this it is important to note that the search for new industrial policy tools and concepts did not mean that the cherished preference for horizontal policy objectives was abandoned (Radosevic, ). Hence, the focus on R&D and innovation policy remained, though arguably with a slight twist as member states increasingly try to link their R&D and innovation efforts to societal challenges such as the digital transformation or mitigating climate change. Likewise, the EU’s main research support programme, the Horizon  programme, features ‘societal challenges’, one of which is Climate Action, Environment, Resource Efficiency and Raw Materials.²² This way, ‘Industry .’²³ and ‘green’ industrial policies aiming at a structural transformation towards renewable energies and circular (instead of linear) resource flows became integral parts of R&D and innovation policies. The Digital Agenda had already made an appearance in the European Commission’s industrial policy strategy of ²⁴ and has since then advanced to become one of the key themes in subsequent strategies.²⁵ The link between industrial policies and societal challenges further led to the incorporation of ‘mission-oriented innovation policies’ (Mazzucato, ) in the industrial policy frameworks of several member states. Such missions are less encompassing than the great societal challenges they should help solve and, above all, are defined in a way that clearly allows assessment of whether the mission has been accomplished.²⁶ At the EU level, missions will become part of the EU’s relabelled Horizon Europe (formerly Horizon ) programme in the next multi-annual financial framework period (–) (see European Commission, b).²⁷ ²² See: https://ec.europa.eu/programmes/horizon/en/h-sections. ²³ The term ‘Industry .’ originates from the German High-Tech Strategy and has since become a general term for either preparing for, and/or successfully embracing, the new production technologies associated with the Fourth Industrial Revolution (notably cyber-physical production systems). Industry . constituted the German government’s Project for the Future, initiated in  and developed into a platform in . See: https://www.bmbf.de/de/zukunftsprojekt-industrie---.html. ²⁴ See An Integrated Industrial Policy for the Globalisation Era (European Commission, ). ²⁵ See Investing in a Smart, Innovative and Sustainable Industry (European Commission, a). ²⁶ The prime example of a mission from the past is sending a man to (and returning him from) the moon. ²⁷ See: https://www.ucl.ac.uk/bartlett/public-purpose/partnerships/ucl-commission-mission-orientedinnovation-and-industrial-strategy-moiis#UK%IS’s%GC. For this purpose the European Commission also engaged Mariana Mazzucato as an adviser and commissioned a report on mission-oriented innovation and industrial strategy (Mazzucato, ).

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

 .    ö

Global value chains (GVCs) and the implied geographically dispersed production processes are another phenomenon that new industrial policy concepts try to take into account. The significant impact of GVCs on changing international trade and investment patterns in the EU and beyond implies a great potential for achieving industrial policy objectives. In general, however, in the context of industrial policy, GVCs seem so far to have become a buzzword that has entered the policy discourse but without any substantial effect on policy formulation, not to mention on actual implementation. For example, the European Commission’s industrial policy strategy calling for a European Industrial Renaissance (European Commission, ) urges member states to implement measures that facilitate the integration of EU firms in GVCs to boost their competitiveness. No guidance is provided though as to what kind of measures would be appropriate, nor are types of value chains or segments of value chains suggested that firms, regions, and countries should try to get involved in. This raises a question mark over the relevance of the participation in GVCs in the current EU industrial policy toolkit. This is regrettable as the analysis of functional specialization (i.e. specialization by value-chain functions such as R&D, production, or marketing) shows marked differences in functional profiles across member states (see Stöllinger, ). The general pattern is that the more advanced member states specialize in knowledgeintensive activities such as R&D or managing the production network (‘headquarters functions’) while especially the Central and Eastern European member states act as ‘factory economies’ (Baldwin and Lopez-Gonzalez, ) responsible for the actual production (including final assembly). Equally related to the global economy, an important change in EU trade policy, with consequences for industrial strategies, occurred in  with the adoption of the Global Europe strategy (European Commission, ). The strategy implies a marked shift away from a multilateral (WTO-based) approach to liberalization and towards a bilateral liberalization strategy. Since then, the EU has been concluding a series of deep and comprehensive free-trade agreements with several extra-European partners, including Korea, Japan, and Canada. Given the current disturbances in the global trade architecture emanating from the United States, the EU may be forced to change its very liberal stance towards international trade, too. Already a marked shift in the EU’s trade policy is noticeable. It seems that the EU is less convinced of the advantages of unilateral liberalization. And indeed, especially for the poorer member states, asymmetric liberalization efforts combined with tough EU competition rules and questionable practices by partner countries that follow a state capitalism model poses severe competitive challenges. The abandonment of the belief in the advantages of unilateral liberalization is also visible in the  reform of the EU’s public procurement rules.²⁸ A key aspect of this reform is the principle of reciprocity, which means that bidders from third countries that do not open their public procurement markets to EU companies can in turn be barred from EU tenders for public contracts. ²⁸ A summary of the reform is provided on the website of the European Commission at: https://ec. europa.eu/growth/single-market/public-procurement/rules-implementation_en.

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   ’   



In the realm of regional policy, a new variant of place-based innovation-oriented industrial policy, known as smart specialization strategies (see Foray et al., )—or S for short—is currently being propagated by the European Commission. It is seen as a tool to improve the technological capacities especially of lagging European regions, which could be one way to reduce the currently vast technological asymmetries (as evidenced by the complementary functional specialization patterns) within the EU. For this reason, the formulation of a smart specialization strategy has become a (formal) conditionality for regions to access funds from the EFRD for R&D and innovation purposes. Finally, there are calls for more projects of European interest, which so far have been rare, Airbus being one of the few examples. The new French industrial policy calls for the ‘Airbus of tomorrow’ in fields such as energy, multimedia networks, or emissionsfree vehicles (Cohen, ). Hence, for the time being the EU follows a ‘mixed’ industrial policy approach (which continues to be embedded in the single market and subject to the competition rules). According to the European Commission () this policy mix consists of a ‘horizontal basis’ which considers all sectors as important and tailor-made approaches to all these sectors. To what extent this view is compatible with the growing importance of mission-based thinking about industrial policy and the concept of smart specialization strategies remains to be seen. This issue will be taken up again in section ..

. EU I P P: T N

.................................................................................................................................. There is no lack of documents outlining the EU’s industrial policy strategies. Typically, these documents put forward a large number of objectives and initiatives. Since , the Commission has launched five industrial policy strategies, each supplementing and fine-tuning the previous ones. The  strategy (European Commission, ) is strongly influenced by the fall out from the global recession of – and the subsequent European debt crisis, and therefore focuses on investment in new technologies and innovation—a recurring topic throughout all strategies. The document defines six investment priorities (‘priority action lines’) plus ten further fields for key action (ranging from developing ‘raw materials diplomacy’ to matching skills with jobs, to the introduction of the concept of smart specialization with regard to the use of regional funds). The industrial policy strategies are complemented by countless communications, strategies, and initiatives which are in one way or another related to the EU’s industrial policy strategy. The updated industrial policy strategy of  (European Commission, a) lists no less than forty-eight such communications, strategies, and initiatives, including the Strategy on Digitising European Industry, the New Circular Economy

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

 .    ö

Package, the extension of the European Fund for Strategic Investment (EFSI), or the free-trade agreement with Japan. While the strategy documents are a valuable source for learning about the EU’s general approach to industrial policy and main objectives, to some extent the vast number of strategy documents and the varying priorities obscure, even if unintentionally, the true priorities of the EU’s industrial policy. This chapter therefore supplements the information on industrial policy priorities available in official documents with data on actual spending on policy objectives that are related to industrial policy. The two main sources of data used for this quantitative exercise are the Multi-Annual Financial Framework (MFF)—the EU’s budget plan—for the period – and the EU State Aid Scoreboard (SAS) which records the value of the aid elements involved in the subsidies granted by member states.²⁹ SAS data for the period – are used to align with the MFF data. The analysis reveals first of all the relative importance of spending on industrial policy at the EU level on the one hand and at the level of member states or regions within member states on the other (level dimension). At both levels the data are further dissected to identify the priorities of industrial policy (thematic dimension), and differences in these thematic priorities across member states or groups of states are discussed (country dimension).³⁰

.. The Level Dimension: Industrial Policy Spending at EU and Member-state Levels Against the background of the historical developments in EU industrial policymaking, it is not surprising that on the whole, expenditure on industrial policy by member states far exceeds the amounts spent at the supranational level (Figure .). The financial resources from the EU budget flowing to industrial-policy-related measures amounted to . per cent of the EU’s GDP annually during the period –.³¹ In contrast, industrial policy spending by member states was in the order of . per cent of GDP during the same period. The latter figure includes, apart from the state aid provided,

²⁹ For details see Appendix A... ³⁰ Note that this approach captures only policy actions that have budgetary implications and, therefore, other potentially important measures such as regulations or the conclusion of a free-trade agreement are left out. ³¹ Note that this share of industrial-policy-related spending is lower than that in Pellegrin et al. () who subsume  per cent of the EU MFF – to ‘Relevant programmes from an industrial policy perspective’ (see table , pp. –). This would result in EU industrial-policy spending of about . per cent of EU GDP. The main difference between the numbers in this chapter and those in Pellegrin et al. () is that these authors include all spending on the Common Agricultural Policy (CAP) and the Maritime and Fisheries Policies (amounting together to about  per cent of the EU budget) in their analysis.

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

   ’   

in % of GDP

0.75



0.10% (Co-financing)

0.50

0.67% 0.25 0.35%

0.00 EU

Member States

 . Spending on industrial policy in the European Union, average – Note: EU funding is the sum of expenditure items related to industrial policy in the MFF over the years –. Co-financing amounts by member states are estimations which are calculated as the ratio between planned allocation and actual spending by member states in the MFF –. All these expenditures are expressed as nominal values in per cent of GDP. National State Aid by member states is the subsidy element contained in national state aids, also expressed in per cent of GDP. Source: European Commission (state aid scoreboard) available at http://ec.europa.eu/competition/state_aid/ scoreboard/index_en.html; DG budget data (EU expenditure and revenue –) available at http://ec.europa.eu/budget/graphs/revenue_expediture.html; statistics on European Structural and Investment Funds (ESIF) available at https://ec.europa.eu/regional_policy/en/funding/available-budget/), authors’ calculations.

member states’ contributions to EU programmes financed by the ESIF, which are known as co-financing by member states. While the subsidy spending by member states obviously forms part of their national industrial policy activities, the co-financing part should, in principle, also reflect to some extent European industrial policy objectives, although specific projects financed by the ESIF are selected and designed by national or regional governments. The finding that member states’ funding of industrial policy exceeds that at the EU level by more than two to one³² also reflects the fact that industrial policy is a shared competence with only subsidiary powers of the supranational level, while member states assume the role of main actors in this domain (see also Wyns, ). The combined spending on industrial policy by member states and the EU amounts to about . per cent of EU GDP. This is certainly a non-negligible amount of public support but is low by historical standards, given that during the s subsidy spending in the EU is estimated to have amounted to  per cent of GDP and was still around

³² While not surprising, this is still a remarkable result given the rather generous allocation of funds from the EU budget to the realm of industrial policy in the calculations, which includes public infrastructure expenditure and parts of active labour-market policies.

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

 .    ö

 per cent during the s (European Commission, b). This can be interpreted in two different ways. Either the proclaimed ‘renaissance’ of industrial policy in Europe has not materialized, or the new industrial policies of the twenty-first century are not just old wine in new bottles but do indeed have some new features. In particular, these new policies are often described as being more subtle, less interventionist and better aligned with market forces, with governments or their agencies sometimes only acting as facilitators (‘honest brokers’).³³ In this narrative the comparatively low amounts spent at the aggregate level reflect the fact that the new industrial policies involve less of the old-fashioned ‘hard’ support policies and more ‘soft’ policies resulting in less government expenditure.

.. The Thematic Dimension: Priorities in Industrial Policy The categorization of industrial policy in this exercise is mandated by the structure of the MFF and reflects various drivers of competitiveness. More precisely, the following broad support categories are distinguished: (i) research, development, innovation, and technology (RDI&T); (ii) support for small and medium-sized enterprises (SMEs); (iii) employment, education, and training; (iv) ecological transformation (‘green’ industrial policy); and (v) investment in infrastructure. Two further categories, sectoral industrial policy and regional policy, are added, though the latter can be further allocated to the other thematic fields in the case of industrial policy spending at the EU level. Table . shows the absolute amounts spent on these industrial policy fields, along with their shares in GDP and their share in overall industrial policy spending. At the supranational level, the data reveal two main policy priorities: regional policy and support for RDI and technology. Taken by itself, the EU’s regional policy, that is, the activities of the ESIF,³⁴ accounts for the lion’s share of EU industrial policy spending. Forty billion euros or almost  per cent of the total industrial policyrelated expenditure at the EU level is disbursed via the ESIF. The fact that industrial policy spending at the EU level is dominated by regional policy has important implications for policy formulation. This is because in contrast to industrial policy measures financed via the central EU budget (e.g. the Trans-European Networks), the projects financed by the ESIF are designed and selected by the member states or their regions.³⁵ Hence, with regard to the design of policies it is useful to distinguish between EU industrial policy in a narrow sense, which is financed and predominantly designed by the EU institutions, and the EU’s regional industrial policy. ³³ See also Wade () describing US industrial policy. ³⁴ Note that this quantitative exercise does not include all spending under the ESIF but only that of the European Social Funds (ESF) and the European Funds for Regional Development (EFRD) as well as the Cohesion Fund (CF). ³⁵ EU institutions are monitoring the projects and the disbursement of funds though, which is also an important function.

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   ’   



Table 22.2 EU and member states’ spending on industrial policy by policy field, 2014–17 (annual averages) State aid by State aid by EU State aid by EU EU industrial member industrial member industrial member states policy states policy states policy Industrial Policy Field

Absolute amounts (in $ bn)

% in GDP

% of total IP spending/state aid

Ecological transformation 0.29 Employment, education, 0.44 training Infrastructure 1.44 RDI and technology 7.47 Regional policy 40.96 SME support 0.09 Sectoral industrial policy 1.32 Other 0.00

51.90 3.13

0.00 0.00

0.35 0.02

0.01 0.01

0.52 0.03

0.00 9.07 11.13 4.68 7.02 12.33

0.01 0.05 0.28 0.00 0.01 0.00

0.00 0.06 0.08 0.03 0.05 0.08

0.03 0.14 0.79 0.00 0.03 0.00

0.00 0.09 0.11 0.05 0.07 0.12

TOTAL

99.25

0.35

0.67

1.00

1.00

52.01

Note: See Figure 22.2. Co-financing amounts by member states are excluded in the table. Source: European Commission; authors’ calculations. For details see Appendix A.22.6.2.

The second key policy at the EU level, support for RDI and technology policy, accounts for another  per cent of the EU’s industrial policy budget. As will be discussed in detail, the main policy vehicle in this domain is Horizon , a grantbased programme for research institutions, enterprises, and universities which finances collaborative research activities of all kinds. Moving on to the state aid activities of the member states, Table . suggests that the industrial policy priorities at the national level are quite different from those at the supranational level. While member states also spend considerable amounts on RDI and technology policies (€ bn) and regional policy (€ bn), the most prominent state aid category is green industrial policy,³⁶ that is, state aid granted for ecological transformation. The importance assigned to ‘green’ industrial policy measures is attributable above all to Germany’s massive expenditure on the Energiewende (energy transition), parts of which constitute state aid. Also noteworthy is that during the period –, only marginal sums were spent on sector-specific industrial policy. This is true for the EU level where €. bn ( per cent) was spent on specific industries, essentially space, aircraft, and electronics, ³⁶ This result is influenced by the fact that we defined industrial-policy spending by member states rather narrowly, limiting it to state aid which therefore excludes most of the investment expenditure on public infrastructure.

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

 .    ö R&D and Technology

Ecological Transformation

Employment, Education, Training

SME Support

Infrastructure

Regional Policy

Sectoral Industrial Policy

Other

All sources of funding

0.14

0.40

0.09

State aid by MS

0.52

0.15

Co-financing by MS

0.11

EU Regional Funds

0.08 0.06 0.07

0.22

0.21

0.25

EU Industrial Policy ex ESIF

0.18

0.12 0.09

0.68 0%

20%

0.11 0.19 0.13

40%

60%

80%

100%

 . Funding of industrial policy in the European Union by themes, average – Note: EU Industrial Policy ex ESIF is the sum of expenditure items related to industrial policy in the MFF over the years –. For the EU Regional Funds, the total actual financing flows by the ESIF are assigned to individual funds using the shares of these funds in the planned budget allocations in the MFF –. Co-financing amounts by member states are calculated using the ratio between planned allocation and the actual spending by member states in the MFF –. National State Aid by member states is the subsidy element contained in national state aids, also expressed in per cent of GDP. Source: European Commission (state aid scoreboard) available at http://ec.europa.eu/competition/state_aid/ scoreboard/index_en.html; DG budget data (EU expenditure and revenue –) available at http://ec. europa.eu/budget/graphs/revenue_expediture.html; statistics on European Structural and Investment Funds (ESIF) available at https://ec.europa.eu/regional_policy/en/funding/available-budget/), authors’ calculations.

and € bn ( per cent) by member states. In the latter case, this includes restructuring and bail-out aid, for example, for airlines (former national carriers). Returning to the EU level and the ESIF, Figure . presents the same data but this time with the ESIF funds split into corresponding categories of industrial policy.³⁷ At the EU level, this presentation of the expenditure on industrial policy confirms the point made above that EU industrial policy predominantly coincides with R&D and innovation policy. Approximately  per cent of ‘central’ EU industrial policy spending is destined for RDI and technology. The other two categories of industrial policy that are of high relevance in financial terms are infrastructure investments and sectorspecific policies, which accounted for  per cent and  per cent of the industrial policy spending from the ‘central’ EU budget respectively. The EU’s infrastructure-related industrial policy is embedded in its Trans-European Network (TEN) policy. This policy comprises several instruments including the ³⁷ The disaggregation of ESIF funds into categories of industrial policies is possible because ESIF funds are structured into ‘thematic objectives’.

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   ’   



Connecting Europe Facility (CEF), which provides financial support for strategic investment in transport, energy, and increasingly digital infrastructure.³⁸ A key objective of the CEF is to create pan-European energy networks and European transport corridors in order to overcome Europe’s nationally fragmented energy and transport systems. While this objective is laudable, the effectiveness of the CEF is curtailed by persistent financing gaps in relation to member states’ declared needs (European Commission, c) and arguably also by their nationally oriented priorities. One particularly obvious aspect of the EU’s infrastructure-related industrial policy is that policy efforts are scattered across too many programmes. While the fact that infrastructure, including the TEN, is apart from the CEF also financed via the ESIF is understandable given the different policy objectives, the need for an additional infrastructure programme that was set up with the European Fund for Strategic Investments (EFSI)³⁹ is less clear. The EFSI, better known as the ‘Juncker Plan’ after its main promoter, former European Commission president Jean-Claude Juncker, was set up as a response to the financial crisis. The investment plan was initially intended as a temporary fiscal stimulus measure⁴⁰ but has been extended until . In the meantime, it is clear that the EFSI will become a permanent EU programme in the MFF – under the name EUInvest. Unfortunately, the design of the EFSI leaves much to be desired, constituting as it does an old-style industrial and investment approach. To start with, its actual budget is much too small to have a great impact. Contrary to the € billion announced, the actual funds provided by the EU amounted to only about €. billion for the original three-year period, with some additional funds coming from the European Investment Bank. The difference stems from the fact that official EU documents include the private investments that would supposedly be mobilized by the EFSI. While the figures for the investments actually triggered and published by the European Commission suggest that the target of € billion has even been exceeded, auditors have cast doubt on these figures, arguing that the claims by the European Investment Bank (EIB), which is managing the EFSI, have been overstated.⁴¹ Given the current experiences with the EFSI, it also remains unclear what is strategic about the fund. The areas eligible for financing by the EFSI are so broad and diverse that hardly any priorities are discernible. The fields of operation include energy and transport projects, but also support to SMEs, R&D, and the digital economy.⁴²

³⁸ See: https://ec.europa.eu/transport/themes/infrastructure_en. ³⁹ The European Fund for Strategic Investments (EFSI) is the central pillar of the Investment Plan for Europe. See EU regulation / on the European Fund for Strategic Investments, the European Investment Advisory Hub and the European Investment Project Portal. ⁴⁰ The initiative was initially scheduled for three years (–). ⁴¹ See: ‘EIB and Commission Defend Juncker Plan Following Auditors’ Criticism’, EuroActiv,  January . https://www.euractiv.com/section/economy-jobs/news/eib-and-commission-defend-junckerplan-following-auditors-criticism/. ⁴² For a distribution of the projects financed by the EFSI by country and topic, see: https://ec.europa. eu/commission/priorities/jobs-growth-and-investment/investment-plan-europe-juncker-plan/investmentplan-results_en.

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

 .    ö

Agriculture and social matters are also covered. Hence, to some extent the EFSI, and the future InvestEU programme, is likely to duplicate existing programmes. The EFSI is already linked to the Connecting Europe Facility (CEF), with part of its budget simply redirected from the CEF, the EU’s main infrastructure investment programme. The greatest problem of the EFSI, however, is that it does not seem to live up to its proclaimed principle of additionality. The EFSI was supposed to only support programmes that otherwise could not be realized (which, by the way, was one of the explanations given for the high leverage effects). A look at the project list, however, casts doubt on the additionality of projects and the dire need of the beneficiaries for public support from EU funds. A prime example is the purchase of new rolling stock (CityJets) for regional passenger transport by the Austrian Railways at a total cost of €. billion. The project is supported with a € million loan from the EIB backed by an EFSI guarantee. In all likelihood the Austrian railways would have bought this new rolling stock anyway as the new material was long overdue. This is just one example demonstrating that, in all likelihood, the support provided by EFSI is plagued by rent-seeking behaviour of firms who hope to benefit from improved financing conditions thanks to EFSI. In summary, the EFSI as well as the InvestEU programme are examples of a poorly targeted, old-style industrial policy programme and a rather unfortunate attempt to revive EU industrial policy. As will be shown, though, the EU is also following more promising industrial policy avenues. Staying in the domain of infrastructure-related industrial policy but moving to the European Structural Funds, an interesting finding regarding the ESIF’s spending profile is that infrastructure is no longer the primary thematic objective. Though it is still important, accounting for roughly a fifth of total ESIF spending, the number one priority within the ESIF according to the categorization employed is funding for ecological transformation, that is, regional green industrial policy. While it is reassuring to see that the EU is providing funds for the ecological transformation of industry and infrastructure, it should be borne in mind that the projects are selected by member states. From this perspective it is surprising that ‘green industrial’ policy enjoys much greater prominence (as measured by budgetary outlays) in national industrial policy budgets than at the EU level.⁴³ This is surprising in so far as the mitigation of climate change, and the protection of the environment more generally, constitute an archetypal global public good (see, e.g. Rodrik, ). As such one would expect that the design and funding of green industrial policies would be ideally placed at the supranational level. Given the quantitative importance of national governments’ state aid expenditure in EU industrial policy spending, the thematic priorities set by member states are strongly determining the major industrial policy spending patterns. Overall,  per cent of industrial policy spending in the EU is ‘green industrial policy’ of some sort, an issue to which we shall return.

⁴³ Certainly, the priorities of the central EU budget are also ultimately decided by member states.

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   ’    state aid & co-financing by MS ratio EU/MS (right axis)

IP spending in % of GDP

4.0

3.0

3.72

3.49

3.5 3.0

0.82

2.5

0.41

0.26

0.20

0.13

0.10

1.67

1.31

1.31

1.04

2.86

1.0

2.0 1.42

1.5

1.17

1.10

0.92

1.0

0.56

0.52

–1.0

0.62

0.5

s alk

ut

an

h

5

-B

ECE

So EU

sm O

th

er

EU

c

ly

lti Ba

EU all

Ita

-1

5

K U

an

c Fr

di or N

an m G

er

ce

–3.0 y

0.0

ratio EU / Member States

EU industrial policy funding Total (EU + MS)



 . Spending on industrial policy from the EU and from member states, by country groups, average – Note: EU-Balkans = HR, BG, RO; Other small EU- = AT, BE, NL, LU, IE; CEE- = HU, CZ, SK, PL, SI; EU South = CY, EL, ES, MT, PT. For the EU Regional Funds, the total actual financing flows by the ESIF are assigned to individual funds using the shares of these funds in the planned budget allocations in the MFF –. Co-financing amounts by member states are calculated using the ratio between planned allocation on EU spending and the actual spending by member states in the MFF –. National State Aid by member states is the subsidy element contained in national state aids equally expressed in per cent of GDP. Source: European Commission (state aid scoreboard) available at http://ec.europa.eu/competition/state_aid/ scoreboard/index_en.html; DG budget data (EU expenditure and revenue –) available at http://ec. europa.eu/budget/graphs/revenue_expediture.html; statistics on European Structural and Investment Funds (ESIF) available at https://ec.europa.eu/regional_policy/en/funding/available-budget/), authors’ calculations.

.. The Country Dimension: Substantial Differences in Industrial Policy Expenditure Going beyond EU averages across member states and zooming into the activities of individual member states (or groups of member states),⁴⁴ Figure . reveals a great deal of heterogeneity in spending priorities at both governance levels. A first key insight is that the dominance of industrial policy funding from member states’ own resources, which emerged in the aggregate, is not present across all country groups. In particular, for the CEE member states and the Southern cohesion countries, the industrial policy funding received from the EU budget exceeds national expenditures. The ratio between industrial policy funding received from the EU and the national sources is : in the case of the CEE- and even : for the EU Balkan countries (Croatia, Bulgaria, and Romania). ⁴⁴ For the groupings of member states see Appendix ...

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi



 .    ö

At the lower end of the spectrum is Germany which, due to its high expenditure on energy transition, has a funding ratio of only : (or : in favor of national industrial policy spending). For this reason, Germany is also the country with the highest aid expenditure among the EU-, not only in absolute terms but also in relation to GDP. Including the funding for industrial policy obtained from the EU budget, German expenditure on industrial policy amounted to . per cent of GDP, slightly higher than the EU average of . per cent. The reason for the patterns of industrial policy spending observed is that the CEE and the Southern cohesion countries are the main beneficiaries of the ESIF as they have more regions eligible for funding from the ERDF and the Cohesion Fund. Therefore, the pronounced differences in industrial policy spending across member states are, to a large extent, explained by the large differences in income levels within the bloc. The combination of comparatively high state aid levels and generous receipts from the ESIF resulted in expenditures for industrial policy amounting to . per cent of GDP for the CEE- (with  per cent of GDP coming from the EU budget); . per cent for the Baltic countries; and . per cent for the EU Balkan countries. These figures are high even by historical standards given that the amount of state aid was estimated to have been around  per cent of GDP during the s, the heyday of industrial policy. This has to be borne in mind when discussing possible industrial policy initiatives, especially because the effectiveness of various ESIF programmes has been shown to decline with the amount of funding received (e.g. Becker et al., ). Hence, in some regions there may be a risk of overspending. In these cases, new initiatives should not be added to existing support programmes but should be substituted for some of the less successful support mechanisms in place. Section .. shows that industrial policy spending across member states not only varies with regard to the amounts spent but also targets different thematic fields.

.. The Country Dimension: Different Countries, Different Priorities Differences in industrial policy priorities across member states are discernible in the funds received from the central budget (Figure ., panel a) and those channelled via the ESIF (Figure ., panel b). The most striking feature in the central EU budget is doubtless the dominance of industrial policy spending on RDI and technology. For the Nordic countries, the United Kingdom, and the other small EU- member states, RDI and technology accounts for more than three-quarters of the total funding of industrial policy. The shares are similarly high for Germany and Italy. The most notable exception here is the Central and Eastern European member states. For the CEE-, the Baltic countries, and the EU Balkan countries, the corresponding share is about  per cent or less. This comparatively smaller role of RDI and technology support is compensated by larger

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

(a) Funding of industrial policy from Central EU budget R&D and Technology

Ecological Transformation

Employment, Education, Training

SME Support

Infrastructure

Sectoral Industrial Policy

1.00 0.80 0.60 0.40 0.20

EU

So

ut

-1 EU all

O

th

er

sm

EU

h

5

c di or

CE

N

E-

5

c lti

-B

alk

Ba

an

s

K U

IT

FR

D

E

0.00

(b) Funding of industrial policy from European Regional and Investment Funds (ESIF) R&D and Technology

Ecological Transformation

SME Support

Infrastructure

Employment, Education, Training Sectoral Industrial Policy

Other 1.00 0.80 0.60 0.40 0.20

h

5 EU

So

ut

-1 EU

sm all

N or di c

5 ECE

c lti Ba

O th

er

EU

-B

alk

an s

K U

IT

FR

D

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0.00

 . Spending on industrial policy from the EU budget, by country groups and themes, average – Note: EU-Balkans = HR, BG, RO; Other small EU- = AT, BE, NL, LU, IE; CEE- = HU, CZ, SK, PL, SI; EU South = CY, EL, ES, MT, PT. The numbers are the share of the respective industrial policy theme in a country or country group’s total EU policy spending funded by either the central budget or the ESIF. Source: European Commission (state aid scoreboard) available at http://ec.europa.eu/competition/state_aid/ scoreboard/index_en.html; DG budget data (EU expenditure and revenue –) available at http://ec.europa. eu/budget/graphs/revenue_expediture.html; statistics on European Structural and Investment Funds (ESIF) available at https://ec.europa.eu/regional_policy/en/funding/available-budget/), authors’ calculations.

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

 .    ö

spending on infrastructure financed by the EU budget, mainly through the TransEuropean Network (TEN) projects. While the distribution of funds is more evenly split across the different industrial policy fields in the case of the ESIF, the pattern that infrastructure-related industrial policy is more important in the Central and Eastern European member states is also discernible in the ESIF budget. The same is true for the more limited role of RDI and technology policies in these countries compared to the EU-. It also seems that the share of funds destined for ecological transformation account for a relatively larger share of the overall industrial policy spending financed via the ESIF in the CEE-, the Baltic countries, and the EU Balkan countries than in the other member states. This might reflect the legacy in Central and Eastern European countries still dealing with the communist-era priority given to heavy and energyintensive industries. Given member states’ state aid spending profile, however, this seems to indicate a compensation for a lack of domestic spending rather than policy priorities. Finally, it should be mentioned that France’s high share of sector-specific industrial policies in the total funds it received from the EU budget does not reflect the country’s supposedly interventionist stance on industrial policy but is linked to France’s leading role in the European Earth Observation Programme, now called Copernicus, which the EU is operating jointly with the European Space Agency (ESA). Returning to the more general differences across countries in Figure ., it is worth mentioning that the stronger focus on infrastructure-related industrial policy detectable for the Central and Eastern European member states and the stronger emphasis on RDI and technology policies in the EU- signal different needs of member states. These different needs in turn are to a large extent again explained by the still prominent differences in development levels across member states. The key policy question in this respect is to what extent not only the EU’s industrial policy spending, but also the possibilities for member states in terms of state aid spending, should accommodate for these differences. This is a delicate issue as it touches directly upon the competition rules, that is, the disciplining layer of EU industrial policy and one of the building blocks of the single market. An alternative (or complementary) approach would be to ensure that the national innovation systems (NISs) in the Central and Eastern European member states are significantly strengthened in order to allow these countries to benefit to a greater extent from the EU’s R&D and innovation grants and programmes. In this context the Horizon  programme, the EU’s main R&D flagship programme, is of key importance, as is the thematic objective R&D and technology within the ERDF. Both are highly relevant, not only because of the significant amounts of support involved but also because they incorporate new industrial policy approaches. The Horizon  programme supports collaborative R&D and innovation projects to the tune of €. billion in the form of grants allocated via competitive funding. Its main objectives are to stimulate excellent science, build industrial leadership, and provide solutions to the grand societal challenges. The programme is structured into

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   ’   



three pillars: excellent science (targeting ‘frontier research’);⁴⁵ industrial leadership (targeting closer-to-the-market research focused on ‘key enabling technologies’);⁴⁶ and societal challenges (European Commission, b).⁴⁷ The most interesting pillar of the Horizon  programme and of its successor in the coming MFF, the Horizon Europe programme, is the grand societal challenges pillar. Here the European Commission has discovered the mission-oriented approach to industrial and innovation policy and seems determined to fully embrace it in the Horizon Europe programme.⁴⁸ The mission-oriented approach to industrial and innovation policy is rooted in a systemic perspective of innovation and is based on a number of assumptions and characteristics. The first assumption is that successful innovation necessarily involves a large number of actors, both private and public—hence the notion of an ‘entrepreneurial state’ (Mazzucato, ). Second, the impact of public funds is strongly enhanced if the money is not spent on narrowly defined and often isolated projects but channelled to related research endeavours that all serve a common purpose. Third, with regard to granularity,⁴⁹ research money should be linked to clearly defined missions. Ultimately, research projects will serve a grand societal challenge such as health, secure societies, and climate change. Missions are one level down in the granularity (compared to societal challenges) with the key features that they are clearly specified and, above all, measurable. Unfortunately, for the time being it is not quite clear how these missions will be defined in an EU context, although some concrete proposals exist (see Mazzucato, ). An implementation-related issue of the EU’s main research programmes continues to be the uneven distribution of funds. So naturally, the question of who defines these missions and who will participate in such missions will arise. Already now, the bias in favour of the most advanced EU member states is observable in the applications for Horizon  grants (Figure .). The EU’s regional funds have incorporated elements of new industrial policy thinking. In particular, since , support from the ERDF in the field of research, technological development, and innovation (thematic objective )⁵⁰ require that the region has a Research and Innovation Strategy for Smart Specialisation in place. This ⁴⁵ See ERC website at: https://erc.europa.eu/about-erc/mission. ⁴⁶ The key enabling technologies (KETs) include, but are not limited to: advanced materials, nanotechnology, micro- and nano-electronics, biotechnology, and photonics (European Commission, ). The KETs are regarded as the basis for innovation in a range of products across all industrial sectors. In particular, they should support the modernization of Europe’s industrial base and the shift to a greener economy. ⁴⁷ These numbers refer to the evaluation period –. ⁴⁸ See https://ec.europa.eu/info/horizon-europe-next-research-and-innovation-framework-programme_en. ⁴⁹ See also the discussion in section ... ⁵⁰ The same is true for thematic objective , information and communication technologies (ICT). In the quantitative exercise, these two objectives are subsumed under the themes ‘RDI and technology’ and ‘sector-specific industrial policies’, respectively. Note that the S conditionality also applies to TO of the EAFRD (Fostering knowledge transfer and innovation in agriculture, forestry, and rural areas). However, we have excluded the EAFRD from the analysis in this chapter.

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

 .    ö EU CEE-5 Balkans 2% Baltic 7% 1% Nordic 8%

UK 14%

IT 13% Small EU-15 15% DE 12% EU South 19%

FR 9%

 . Share of Horizon  applications per EU member state, average – Note: EU-Balkans = HR, BG, RO; Other small EU- = AT, BE, NL, LU, IE; CEE- = HU, CZ, SK, PL, SI; EU South = CY, EL, ES, MT, PT. Source: European Commission (). Authors’ own calculations.

‘ex ante conditionality’ for accessing funds from the ESIF confirms the view that smart specialization has gained a strategic and central function within the new Cohesion Policy of the EU (Foray et al., ). In quantitative terms, the actual expenditures during the period  to  amounted to approximately € billion annually, including co-financing by member states. The Strategy for Smart specialization is a regional and innovation-oriented form of industrial policy developed within Europe. The central idea underlying S is the ‘entrepreneurial discovery process’ (Hausmann and Rodrik, ). Entrepreneurial discovery is central because it is the process by which regions can find out about promising niches in which to specialize. The rationale for the government to get involved in entrepreneurial discovery processes (which in principle should be the responsibility of firms) is that first movers, that is, firms that invest in products that are new to the region or country, cannot, if successful, reap the full benefits from their ‘discovery’ (the well-known ‘externality’ impact of an innovating firm à la Schumpeter). This is the case because, once it has been revealed that a certain product or service can be successfully produced in the region, other firms from the region will enter production, driving down economic rents accruing to the first mover. Economic rents, however, would be necessary to cover the fixed costs associated with the investment in the discovery process. The likely scenario is, therefore, a too-low number of attempts to discover profitable new niches (Hausmann and Rodrik, ). Public support—that is, S—is therefore needed to encourage entrepreneurial discovery processes. Hence, it is assumed here that countries and regions possess latent comparative advantages which can be turned into effective comparative advantages with the appropriate policy interventions. While the economic model by Hausmann and Rodrik () would apply to both innovation and (physical) investment for the production of products new to the region,

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   ’   



the concept of smart specialization has been developed in the context of R&D and innovation policies (see Foray et al., ). S has been designed as a place-based (i.e. regional) innovation-oriented industrial policy. Despite the huge potential of the place-based S there is, however, also scepticism about the appropriateness of this policy for less-developed regions (e.g. Capello and Kroll, ). Based on case studies, Trippl et al. (), for example, found that while there is policy learning in less-developed regions, they are struggling with the issue of stakeholder involvement either due to a lack of capable stakeholders (e.g. universities) or the unfamiliarity of actors with this type of cooperation. Radosevic () argues that for less-developed regions the switch from an individual entrepreneurial discovery process to a collective one is difficult to achieve. Also, in order to avoid conflicts regarding alternative entrepreneurial opportunities of a region, stakeholders would agree on the lowest common denominator, which often leads to the selection of very broad technological areas. In such environments the value added of S can be expected to be rather limited.

. EU I P E  L   M C A

.................................................................................................................................. The wide spectrum of industrial policy and the large set of measures make the overall assessment of industrial policy an elusive task. This is all the more true as EU programmes and initiatives set different, potentially conflicting objectives and have different underlying intervention logics (see also Pellegrin et al., ). The potential conflict in objectives becomes evident when considering the four major challenges of industrial policy that were discussed in the introduction to this chapter. It is against these challenges that the strengths and achievements as well as the weaknesses and neglects of the current EU industrial policy are discussed in this section. The discussion pays due attention to the fact that industrial policy, to be effective, needs to be not only well formulated but also appropriately implemented and continuously evaluated.

.. The Technological/Innovation Challenge As regards the long-standing challenge of defending or attaining technological leadership, many excellent studies assess the record, scope, and current ambitions of EU innovation policy, evaluating the EU’s policy initiatives in the areas of electrical vehicles, digitization, the ‘battery alliance’, and others (Veugelers et al., ; Veugelers and Baltensperger, ). In fact, the initiatives and measures taken by the EU in the area of innovation policy can be considered one of the success stories of EU

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

 .    ö

cooperation. This is no small achievement given, as was confirmed by the quantitative exercise, that ‘innovation policy’ is at the core of what the EU sees as ‘industrial policy’. As described above, European R&D and innovation policy could be further sharpened by fully embracing the mission approach within the upcoming Horizon Europe framework programme.⁵¹ These missions will be defined within the realm of five clusters that have already been determined.⁵² Certainly, the effectiveness of the mission approach depends strongly on the type of missions that are going to be defined. Among the five clusters, climate, renewable energy and the environment figure prominently, which provides an excellent opportunity to link the technological challenge to the environmental challenges. At this stage it is noteworthy that the Horizon Europe programmes may also tackle the digital transformation which, for many, is the key technological challenge lying ahead of EU economies with potentially transformative power for the EU’s entire production system. While most EU countries seem to be well-positioned to master the digital challenge, given its innovation and industrial capabilities (see, e.g. World Economic Forum, ), concerns are nurtured by the fact that EU industry does not possess any major global player in the Internet business.⁵³ This may indeed turn out to be a disadvantage for the transition towards Industry ., in which cyber-physical systems combining the physical and virtual worlds are set up. While it is far too early to judge whether the EU will be falling behind, it is clear that the EU economy will need heavy investment in digital technologies and the required infrastructure. Efforts in this respect vary significantly across member states,⁵⁴ which is why a strong impetus originating at the EU level (as envisaged by the Digital Union) is required. As in the past with mechanization, and more recently with IT, encompassing technological changes go along with rapid changes in the composition and the demand for different types of skills, and changes in occupational structures with some occupations disappearing and others emerging. This requires strong adaptation processes from the labour force, and in education and training programmes. European industrial policy requires a two-pronged approach: on the one hand, to be at the forefront of technology developments and tapping into the full potential of such new technologies and production processes for productivity advances and improving ‘the comforts of life’; on the other hand, to make a major effort to also deal with the distributive and adjustment challenges of the impacts of rapid technological and structural change.

⁵¹ Horizon Europe is the R&D and innovation framework programme of the MFF –, which is to replace the current Horizon  programme. ⁵² These clusters are: Health; Culture, Creativity, and Inclusive Society; Civil Security for Society; Digital, Industry, and Space; Climate, Energy, and Mobility; and Food, Bioeconomy, Natural Resources, Agriculture, and Environment. ⁵³ See EPSC (). The German software company SAP may be an exception here. ⁵⁴ This is, for example, revealed by the Digital Economy and Society Index (DESI) available at https://ec.europa.eu/digital-single-market/en/desi.

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   ’   



Against this background, innovation support plays an ever-bigger role in EU industrial policy. And while European innovation policy has strongly improved since its shaky beginnings in the early s, there is one important shortcoming which needs to be dealt with. At the moment European innovation-oriented industrial policy is mostly oriented towards the most advanced economies, companies, and regions that are at the forefront of technological developments. Ideally, the EU’s industrial policy should be conceived in a way that gives equal prominence to the developmental needs of those regions, countries, and (industrial and company) segments that are not on (or close to) the global technology, in other words, Europe’s middle-ranked as well as peripheral regions, and countries that have to overcome massive structural challenges. Some of these countries are seriously lagging or falling behind in economic development. Again, this assessment is supported by the figures: even though the cohesion countries benefit disproportionately from industrial policy-related support programmes from the EU budget—especially when the ESIFs are included—the share of R&D and innovation support going to the CEE member states is comparatively small. This is related to the tendering process through which R&D grants are allocated. While the open tendering process is doubtless a strong point in the design of EU R&D and innovation support programmes, it is also clear that it favours countries with strong national innovation systems (NISs). Essentially, there are two ways to address this issue. One is to further adjust the tender rules to make sure research consortia that apply for Horizon/Europe  funds become more balanced geographically with regard to the participating institutions. The alternative approach is to refocus the ESIF towards creating and improving the NISs of CEE member states. This would entail the creation of tertiary teaching institutions like the European University Institute in Florence in a number of other member states. Another important avenue would be support for technical research agencies comparable to the Frauenhofer Institute in Germany.

.. The Emerging Markets Challenge The dominance of EU industrial policy in support of technological leadership globally to some extent deflects from the challenge posed by catching-up economies and also the cohesion process (discussed in sub-section ..). Both are crucial in the circumstances in which the EU (and closely connected neighbouring countries) currently finds itself. EU industrial policy needs to face vital structural development issues which the European economy confronts in today’s global environment. As recognized early on by authors such as Rosenstein-Rodan (), Hirschman (), and Gerschenkron (), such structural development issues were traditionally at the centre of industrial policy strategies (see also Rodrik, ; Wade, ; Cimoli et al., ) and the EU would be well advised to reconsider their importance in the formulation of its future industrial policy initiatives.

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

 .    ö

The structural development issue is closely connected to the emergence of new major players in the global trade arena,⁵⁵ first and above all China, because the greater overlap in economic structure between the CEE and Southern EU member states and emerging economies exposes them to fiercer competition. The key concern here is not the sectoral composition of economies which have strongly converged within the EU. Rather, it is the more recent functional and vertical dimension of specialization that was opened up with the emergence of GVCs.⁵⁶ Recent empirical evidence in this respect (Stöllinger, ; Timmer et al., ) suggests that the international division of labour with regard to value-chain functions (e.g. R&D, head office functions, production, back offices) within the EU continues to be very asymmetric, or in fact complementary,⁵⁷ with CEE member states specializing predominantly in production-related activities. In this respect they resemble countries such as Mexico and the economies in the third and fourth row of the Southeast Asian flying-geese formation (e.g. Vietnam, Laos, or Thailand). Baldwin and Gonzalez-Lopez () termed countries which specialize functionally in this manner ‘factory economies’, in contrast to ‘headquarter economies’ whose companies specialize predominantly in R&D and in organizing global value chains. For these reasons it is not surprising that the ‘China shock’ has affected the CEE and Southern European member states much more in terms of exports than the rest of the EU (Ciani and Mau, ; Celi et al., ).

.. The Cohesion Challenge Tightly linked to the stiff global competition presented by emerging economies, but still in itself a challenge, is the EU internal cohesion process. As has been emphasized throughout this chapter, a lot of funds are dedicated to cohesion objectives via the EU’s ESIF. Yet, despite the substantial amount of money spent on cohesion objectives, ‘peripherization’ has become a critical issue both at regional and country levels. This development has contributed to the issue of ‘North–South imbalances’ and severe tensions have arisen with respect to the formulation of a proper fiscal and structural policy framework at the EU level to deal with such imbalances (see Celi et al., ). The issue of external imbalances is closely related to the phenomenon of agglomeration of industrial activity (see Stehrer and Stöllinger, ), but also to that of other tradable activities (business services, financial centres; see also Landesmann,  and  on this). Apart from the macroeconomic implications, agglomeration phenomena have an inherent characteristic of giving rise to cumulative virtuous and vicious circles ⁵⁵ Arguably, the CEE member states are also new actors in the global economy but when referring to emerging economies we think of extra-EU partner countries. ⁵⁶ Functional specialization refers to the specializing in specific segments of the value chain within an industry-specific value chain. ⁵⁷ The same is true for other tightly integrated regional blocs such as (former) NAFTA and Southeast Asia.

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   ’   



that can deepen persistent disparities across European regions. Economic geography has pointed to such dynamic processes where concentration of economic clusters goes along—especially in the context of the single market with its four freedoms—with factor mobility and thus with disparate demographic developments and the concentration of skills (people with high levels of training, competence, and education) in some centres and the outflow of such skills and a deteriorating age profile in other regions (see, e.g. Martin, ; Iammarino et al., ). This cumulatively saps development potential from peripheral regions and countries, which has been shown to also have strong political implications (see Rodriguez-Pose, ). All these trends raise some questions about the effectiveness of the EU’s cohesion policy and the ESIF, an issue on which the empirical evidence is still inconclusive. As mentioned earlier, a very promising avenue for improving the effectiveness of the EU’s cohesion efforts is the concept of smart specialization, which has been incorporated in the ERDF, one of the major EU funds. The smart specialization strategies, as a territorial approach, are argued to favour the relatively poorer countries in the EU, that is, cohesion and CEE countries. Still, whether this is really the case in the context of the ERDF programmes remains doubtful as several cohesion countries are struggling with numerous implementation issues that are related to existing deficiencies in their (political) institutions. One way to tackle this issue is to change the support mechanism of the ESIF from a grant-based system to a support system that relies on financial instruments, essentially EU-backed guarantees administered by the EIB and involving commercial banks that would provide the actual finance for eligible projects. This would reduce the role of political institutions in the selection and implementation process, but it might also make the support less targeted, which must be seen as a major disadvantage in an era where industrial policy aspires to be linked to missions and societal challenges.

.. The Environmental Challenge The more recent but arguably the most pressing and fundamental challenge which extends far beyond industrial policy and in fact beyond the economic sphere, is climate change and environmental protection more generally. Doubtlessly, this challenge has received due attention more recently at EU and national levels through the formulation of both mission-oriented policies’ and ‘innovation policy’ (i.e. policies directed at the technological leadership challenges), as well as within the context of regional policy (and thus under the schemes supported by cohesion funds). As with S policies, it will be important to monitor how effective ‘mission-oriented’ policies (which take a systemic view of policy interventions) turn out to be once they have been implemented for some time and can be evaluated. Given the comparatively strong regulatory framework in environmental issues, European industry is bound to adjust and incorporate resource efficiency, emissions reduction, and sustainability. The implications for the competitiveness of European industry of such a shift towards the aspired circular economy are as yet unclear and are not the same across different

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

 .    ö

industries. On the one hand, regulations that force firms to increasingly rely on sustainable or re usable goods (including packaging) may develop first-mover advantages in a series of new materials and technologies. On the other hand, initially several of these regulations will impose additional costs on firms producing within the EU. In a longer-term perspective, however, the balance can be expected to be positive, especially if the mission approach is successful and leadership in environmentally sustainable technologies can be obtained. Acting quickly in order to secure first-mover advantages could be vital in this respect as Korea’s and China’s latest industrial policy strategies are also clearly targeting ‘green’ technologies and green industrial policies more generally. Unfortunately, acting fast is not exactly the EU’s greatest strength. Still, the integration of mission orientation and smart specialization into the EU’s industrial policy formulation is an important step in the right direction. Ideally, we would see the EU’s three layers of industrial policy interacting with each other to support the defined missions and the territorial approach demanded by the smart specialization concept. The coming years will show whether EU member states are capable of moulding the various interests and objectives into well-defined missions whose accomplishment will help meet the key challenges ahead.

. C

.................................................................................................................................. Starting with a brief recap of historical developments, this chapter went beyond the usual investigation of official documents and made a serious attempt to reveal the actual amounts spent on and priorities targeted by EU industrial policy. A first, rather unexpected, finding is that the supranational level, while on average still second to national governments’ state aid activities, has become substantial too. Especially for the CEE member states, the funding of industrial policy by EU programmes is of utmost importance and much larger than national expenditure. Given the substantial amounts disbursed via the EU’s regional and structural funds, the overall industrial policy budgets for this country group are large even by historical standards, and comparable to those seen in the s. If one adds to the EU industrial policy programmes the European Commission’s regulatory power in areas such as competition policy (including inter alia state aid, mergers and acquisitions, and public procurement) and trade policy, it is obvious that the EU level has become a central pillar, even if formerly member states remain the primary actors. The growing importance of the EU institutions in designing and also implementing industrial policy is welcome given that none of the key challenges, ranging from technological leadership to environmental transformation, can realistically be met by any of the member states individually. The flip side of this is that the EU’s industrial strategies as a whole, as well as individual programmes, need to be designed and implemented in a coherent and effective manner. With the incorporation of mission-

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   ’   



oriented thinking about industrial and innovation policies and at the regional level the concept of smart specialization, the EU has made formidable progress in the formulation of industrial policy. The effective implementation of the sophisticated strategies, however, in many instances remains curtailed by policy incoherence (with rival or even contradictory objectives) and a host of programmes and initiatives, many of which lack critical mass. If the official announcements are to be believed, the upcoming budget period (–) will see a noticeable reduction in the number of programmes and the elimination of duplications. With regard to policy priorities, the existing focus of industrial policy on R&D and innovation support is likely to remain and these areas will be strengthened, according to the European Commission’s current budget proposal for the period –. What seems important here is that efforts in the realm of R&D and innovation policy are not only aiming at the technological frontier and the leading edge vis-à-vis the United States (and increasingly China). Rather, it is imperative that, in line with the initial smart specialization concepts, R&D and innovation support is also a policy tool for the EU cohesion countries. While this is fully acknowledged by official rhetoric, the actions on the ground seem to be different, as regions from CEE economies (and laggards such as Bulgaria and Romania in particular) are underrepresented in the various pilot projects and R&D cooperation initiatives within the smart specialization strategy (e.g. when it comes to European Innovation Hubs). An additional aspect of the EU R&D and innovation strategies is that they too suffer from an overload of rival programmes. While this is understandable, given that such programmes are necessarily a compromise, reflecting the interests and priorities of all member states, it is necessary to have better-defined technological priorities which are derived from a vision of the technological trajectory European societies want to embark on. This is where a mission-oriented policy comes into play again. Guidance on how this trajectory may look can be taken from national governments’ industrial policy priorities, where the state aid figures clearly identify the ecological transformation as the number one target.⁵⁸ In other countries, concentration on avoiding a drift into a vicious circle of ‘peripherization’ and aiming towards a more balanced pattern of economic development across the European Union, will be the priority. Whatever member states decide the missions are going to be (which will be enshrined in the next R&D framework programme, the Horizon Europe programme), it should be clear that they need to be limited in numbers, ideally not more than three to four at any time. Otherwise, there is a risk that projects for the achievement of the ⁵⁸ Translating ‘green’ industrial policies into missions therefore seems the logical next step. If industrial policies aim at altering the economic structure, then the shift towards a sustainable, less resource-intensive and circular economy based on renewable energies is the obvious policy target given the pressing challenge of climate change but also the policy priorities revealed by member states. To this one should add that the prevalence of multiple market failures in the context of a greening of the economy, which include massive externalities, path dependencies favouring pollution-intensive technologies, and the public good characteristic of a clean environment, makes striving for an ecological transformation the number one objective for a credible industrial policy at the European level.

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

 .    ö

missions remain underfunded so that the fragmented policy efforts will not develop their full potential. Provided member states identify the missions and the underlying societal challenges, it is also likely the projects at the regional level funded by the structural funds are aligned with the defined missions. If the smart specialization strategies work out, each region should find its niches in the key enabling technological domains needed for completing the missions. Hence, what is needed first of all is a consensus on appropriate missions which, if achieved, would substantially support the EU’s competitive position in tomorrow’s industries.

. A

..................................................................................................................................

22.6.1 Member States and Country Groupings Table A22.1 List of member states, country codes, and country groups Country

Iso-3-code

EU code

Country group

Austria Belgium Bulgaria Cyprus Czechia Germany Denmark Estonia Greece Spain Finland France Croatia Hungary Ireland Italy Lithuania Luxembourg Latvia Malta Netherlands Poland Portugal Romania Sweden Slovenia Slovakia United Kingdom

AUT BEL BGR CYP CZE DEU DNK EST GRC ESP FIN FRA HRV HUN IRL ITA LTU LUX LVA MLT NLD POL PRT ROU SWE SVN SVK GBR

AT BE BG CY CZ DE DK EE EL ES FI FR HR HU IE IT LT LU LV MT NL PL PT RO SE SI SK UK

Other small EU-15 Other small EU-15 EU Balkan EU South Central Europe (CEE-5) Germany Nordic Baltics EU South EU South Nordic France EU Balkan Central Europe (CEE-5) Other small EU-15 Italy Baltics Other small EU-15 Baltics EU South Other small EU-15 Central Europe (CEE-5) EU South EU Balkan Nordic Central Europe (CEE-5) Central Europe (CEE-5) United Kingdom

Source: Authors’ own country groupings.

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

.. Selection of EU Budget Items and Assignment to Industrial Policy Themes ... Mapping of budget items in the MFF – to the industrial policy themes The discussion of the EU’s budgetary expenditure on industrial policy-related issues during the period – is based on a selection of items within the Multi-Annual Financial Framework (MFF) –, which are subsumed in the realm of industrial policy. Table A. lists all budget items that were selected to qualify as industrial policy related. The numbers used refer to actual disbursements.

Table A22.2 Industrial policy item within the MFF 2014–20 Section in Description MFF

Assigned industrial policy category

1.1.10 1.1.11

Infrastructure Sectoral policy

1.1.13 1.1.31 1.1.4 1.1.6 1.1.81 1.1.82 1.1.83 1.1.9 1.2.5 1.2.6 2.0.4 1.2.11 1.2.12 1.2.13 1.2.14 1.2.15

European Fund for Strategic Investments (EFSI) Implementation and exploitation of European satellite navigation systems (EGNOS and GALILEO) European Earth Observation Programme (Copernicus) The Framework Programme for Research and Innovation (Horizon 2020) Programme for the Competitiveness of Enterprises and Small and Medium-sized Enterprises (COSME) EU Programme for Employment and Social Innovation (EaSI) Energy Transport Information and Communications Technology (ICT) Energy projects to aid economic recovery (EERP) Youth Employment Initiative (specific top-up allocation)

Sectoral policy RDI SME

Employment, education, training Infrastructure Infrastructure Sectoral policy Infrastructure Employment, education, training Contribution to the Connecting Europe Facility (CEF) Infrastructure Programme for the Environment and Climate Action (Life) Ecological Less-developed regions (Regional convergence) Regional—for the thematic breakdown see Table A22.3 Transition regions Regional—for the thematic breakdown see Table A22.3 More-developed regions (Competitiveness) Regional—for the thematic breakdown see Table A22.3 Outermost and sparsely populated regions Regional—for the thematic breakdown see Table A22.3 Cohesion fund (incl. contribution to the CEF) Regional—for the thematic breakdown see Table A22.3

Source: European Commission at http://ec.europa.eu/budget/graphs/revenue_expediture.html.

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

 .    ö

... Mapping of thematic objectives in the ESIF to the industrial policy themes For the budget items representing expenditure of the European Structural and Investment Funds (ESIF) additional information on the ‘thematic objectives’ of the funds were used. However, for these targets, only the figures from the projected expenditure as allocated in the MFF – were available. This information was exploited to assign the regional policy expenditures to individual targets/objectives. The implicit assumption here was that the actual disbursements (both from the EU budget and national co-financing) have the same distribution across objectives as the projected amounts in the MFF –. Since the classification of the MFF – does not allow distinguishing between expenditure under the European Social Funds (ESF) and the European Funds for Regional Development (EFRD), these two funds are treated together, distinguished, however, by objectives. The data on regional fund allocations is found at: https://ec.europa.eu/regional_policy/EN/funding/available-budget/. Spending under the Cohesion Fund, which was not found in the budget allocations, is assigned to infrastructure as it must be assumed that this spending is made in respect of the Connecting Europe Facility (CEF) which is also included in this budget item.

... Assumption made for the co-financing by member states of ESIF projects For national co-financing no actual numbers are available. Therefore the ratio of budget allocation between EU financing and national co-financing was assumed to prevail also for the actual financing. Table A22.3 Categorization of the thematic objectives in the ESIF into industrial policies themes Code 1 2 3 4 5 6 7 8 9 10 11 12 TA DM

Target objective of structural funds

Assigned industrial policy category

Research and innovation Information and communication technologies Competitiveness of SMEs Low-carbon economy Climate change adaptation and risk prevention Environment protection and resource efficiency Network infrastructures in transport and energy Sustainable and quality employment Social inclusion Educational and vocational training Efficient public administration Outermost and sparsely populated Technical assistance Discontinued measures

RDI Sectoral policy SME Ecological Ecological Ecological Infrastructure Employment, education, training Social Employment, education, training Institutions Social Institutions Not assigned

Source: European Commission at https://ec.europa.eu/regional_policy/EN/funding/available-budget/.

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Mazzucato, Mariana () Mission-Oriented Research and Innovation in the European Union: A Problem-solving Approach to Fuel Innovation-led Growth. Luxembourg: Publications Office of the European Union. Available at https://ec.europa.eu/info/sites/info/files/ mazzucato_report_.pdf. Owen, Geoffrey () ‘Industrial Policy in Europe since the Second World War: What Has Been Learnt?’, ECIPE Occasional Paper No. , The European Centre for International Political Economy, Brussels. Available at http://eprints.lse.ac.uk///Industrial_pol icy_in_Europe_since_the__Second_World_War_what_has_been_learnt%lsero%.pdf. Pellegrin, Julie, Louis Colnot, Francesco Prota, Francesca Ardizzon, Laura Delponte, Michele Capriati, Agnieszka Olechnicka, and Chris Smith () ‘How to Tackle Challenges in a Future-oriented EU Industrial Strategy? Volume ’. Study commissioned by ITRI, June. Available at http://www.europarl.europa.eu/RegData/etudes/STUD///IPOL_ STU()_EN.pdf. Pellegrin, Julie, Maria Giorgetti, Camilla Jensen, and Alberto Bolognini () ‘EU Industrial Policy: Assessment of Recent Developments and Recommendations for Future Policies’. Study commissioned by the Directorate-General for Internal Policies, Policy Department A. Economic and Scientific Policy, February. Available at http://www.securepart.eu/down load/ipol_stu--_en.pdf. Radosevic, Slavo () ‘Assessing EU Smart Specialisation Policy in a Comparative Perspective’, in Slavo Radosevic, Adrian Curaj, Radu Gheorghiu, Liviu Andreescu, and Imogen Wade (eds) Advances in the Theory and Practice of Smart Specialisation. London: Academic Press, pp. –. Rodriguez-Pose, Andres () ‘The Revenge of the Places That Don’t Matter (and What to Do about It)’, Cambridge Journal of Regions, Economy and Society : –. Rodrik, Dani () ‘Industrial Policy: Don’t Ask Why, Ask How’, Middle East Development Journal (): –. Rodrik, Dani () ‘Green Industrial Policy’, Oxford Review of Economic Policy (): –. Rosenstein-Rodan, Paul () ‘Problems of Industrialisation of Eastern and South-Eastern Europe’, The Economic Journal : –. Schwengler, Barbara () ‘Einfluss der europäischen Regionalpolitik auf die deutsche Regionalförderung’. IAB Discussion Paper No. /. Available at http://doku.iab.de/ discussionpapers//dp.pdf. Stehrer, Robert and Roman Stöllinger () ‘The Central European Manufacturing Core: What is Driving Regional Production Sharing?’. FIW-Research Report No. /(). Stöllinger, Roman () ‘Structural Change and Global Value Chains in the EU’, Empirica : –. Stöllinger, Roman () ‘Testing the Smile Curve: Functional Specialisation in GVCs and Value Creation’. wiiw Working Paper No. , February. Timmer, Marcel, Sebastien Miroudot, and Gaaitzen J. de Vries () ‘Functional Specialisation in Trade’, Journal of Economic Geography (): –. Trippl, Michaela, Elena Zukauskaite, and Adrian Healy () ‘Shaping Smart Specialisation: The Role of Place-specific Factors in Advanced, Intermediate and Less-Developed European Regions’. Online. Regional Studies (). UNCTAD () World Investment Report . Investment and New Industrial Policies. Geneva: UNCTAD.

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 .    ö

Veugelers, Reinhilde and Michael Baltensperger () ‘Europe: The Global Centre for Excellent Research’. Study requested by the ITRE Committee of the European Parliament, Brussels. Veugelers, Reinhilde, Gustav Fredriksson, Alexander Roth, Simone Tagliapietra () ‘Is the European Automotive Industry Ready for the Global Electric Vehicle Revolution?’. Policy Contribution No. . Brussels: Breugel. Wade, Robert H. () ‘Return of Industrial Policy?’, International Review of Applied Economics (): –. World Economic Forum () Readiness for the Future of Production Report . Geneva: WEF. Wyns, Tomas () ‘A Mapping of the EU Industrial and Innovation Policy’. VUB IES Working Paper, November. Available at http://i-c.eu/wp-content/uploads// /Industrial-policy-mapping_ic_T.Wyns_.pdf.

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        ......................................................................................................................

                    A Schumpeterian and Capability-based View .............................................................................................................

 

. I

.................................................................................................................................. A notable result of the  global financial crisis has been the revival of industrial policy, initiated by the work of Stiglitz and Lin (). While classical work, such as Johnson (), defined industrial policy as policies that improve the structure of a domestic industry in order to enhance a country’s international competitiveness, the meaning has evolved to meet the context of the twenty-first century (Radosevic et al., ). This chapter presents a Schumpeterian and capability-based view of industrial policy (Lee and Malerba, ; Lee, b), reflecting upon its practices in Korea over the last several decades. It is critical for a developing country to enhance its capability to produce and sell products in the international market so that the country may earn foreign currency that it can then use to pay for imports of investment goods. However, the challenging part of this process is how to increase that capability. Thus, it is typical for many developing countries to suffer from capability failure (Lee, c; Lee and Malerba, ). Further, industrial policy should go beyond correcting market failure to aim at overcoming capability failure (Lee, c, ). The market-failure perspective focuses on providing optimal incentives to correct externalities associated with public goods like R&D, with a hidden assumption that firms are already equipped with capabilities. However, in the absence of capabilities, incentives alone are not sufficient to start innovation. It is not about picking winners, but more about picking good students and

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allowing them time to learn and build capabilities until they are able to compete with incumbent firms from developed countries (Lee and Malerba, ). Capability building was the focus of a World Bank study compiled by Chandra (). A World Bank () assessment of the reform decade of the s concluded that growth entails more than the efficient use of resources, and that growth-oriented action may be needed, for example, for technological catch-up or the encouragement of risk-taking for faster accumulation. Lee and Mathews () synthesize the capabilitybased view as the Beijing–Seoul–Tokyo (BeST) consensus, which is commensurate with their firm-level study (Lee and Mathews, ). Capability building, not the state–market dichotomy, is the essence of the Korean model of catch-up. This chapter argues that because Korea built and enhanced the capabilities of private firms, it was able to sustain growth for several decades until it joined the club of high-income economies (Lee, b). If we consider industrial development as a long-term process that takes over ten or twenty years, it is natural for the policy tools to change over the course of economic growth. Such a dynamic view of industrial policy is warranted, because the capability level of the beneficiaries of such intervention would change over time as well. This chapter discusses specific industrial policy tools practised in Korea at different stages of the country’s development: tariffs to protect infant industry (Shin and Lee, ); licensing of technology imports to promote building of absorptive capacity (Chung and Lee, ); entry control to guarantee rents to be paid for fixed and R&D investment (Jung and Lee, ); and public–private joint R&D to break into higher-end products and sectors (Lee et al., ; Lee, a). While these tools differ in their concrete contents, a common aspect is that they allow some rents (extra profits) for targeted sectors which can be used to pay for building variants of capabilities, such as production capabilities in the case of tariffs or technology licensing in the s, investment capabilities in entry control in the s, and technological (R&D) capabilities in the case of public–private joint R&D in the s. Sections ., ., and . discuss technology licensing, tariffs and entry control, and public–private joint R&D, and are followed by some conclusions.

. T L  A C

.................................................................................................................................. Absorptive capacity (AC) was first introduced by Cohen and Levinthal (, ) as the ability of a firm to identify, value, assimilate, and exploit knowledge from the environment. AC is also recognized as an important binding constraint in the development of latecomer economies. Borensztein, Gregorio and Lee () performed a country panel regression and found that foreign direct investment will produce a growth effect only if a country has a certain level of AC. Although several empirical

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      



studies emphasize the importance of absorptive capacity using in-house R&D or human capital as proxy (Keller, ; Mowery and Oxley, ), recent findings indicate that AC cannot be appropriately proxied by R&D or staff quality alone (Flatten et al., ; Lane et al., ). The earlier studies fail to discover other origins of AC aside from formal R&D or education. Relying heavily on Chung and Lee (), this section examines the origin of AC in Korea. How can we tell whether this capacity is established in a firm? This question is particularly relevant in the context of latecomer countries in which firms are usually uncertain about conducting their own R&D and continue to rely on imported technology by specializing in assembly-type production. Scholars studying Korea as an example of a successful latecomer economy have emphasized the importance of AC in enabling Korean firms to learn and assimilate external knowledge (Evenson and Westphal, ; Keller, ; Pack, ). As a latecomer economy, Korea has successfully transformed itself from a technology-importing to a technology-generating country. Korean firms only began to conduct in-house R&D in the mid-s after undergoing a period of learning, assimilating, and adapting foreign technologies (OECD, ; Lee, b). Chung and Lee () observed that the number of foreign technologies acquired by Korean firms increased from as early as the late s, followed by an increasing trend towards private R&D two decades later. In other words, a significant increase in foreign technology inflow preceded local R&D efforts and innovation outcomes in Korea. Many researchers assert that access to external knowledge is especially important in the development of latecomer firms (Bell and Pavitt, ; Kim, ; Laursen and Meliciani, ; Jaymin Lee, ; Park and Lee, ). Leading firms in Korea generally acquired various forms of know-how, such as operational skills and elementary process technology, before starting their own capital investment (Enos and Park, ; Kim, , ). These firms built their basic technology proficiency during the building and testing of their production facilities, enabling Korean engineers to assume responsibility for daily operations as early as possible. The Foreign Exchange Control Act of  addressed two objectives relating to foreign technology acquisition. The first was to ensure that foreign exchange, which became scarce after the Korean War, would only be used for critical technologies. Second, the government wanted to use acquired technology as a stepping stone on which Korean firms could build their own technological capabilities (Korea Development Bank, ). The scarcity of foreign exchange during the s compelled Korean firms to seek government approval prior to signing a contract with a foreign counterpart if they wanted to receive technical assistance for a year or more and if they paid their counterparts in foreign currencies. All applications were scrutinized by the Ministry of Commerce and Industry (Korea Development Bank, ). Korean industries attempted to build production and export capabilities in labourintensive or light industries, such as textiles, wigs, rubber footwear, and stuffed toys, from the s and into the s. However, during the s firms realized that these

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industries had low profit margins and insufficient cash inflow to produce the necessary foreign debt services. Therefore, both the government and the private sector wanted to integrate backwards into intermediate goods which, if secured within the country, would reduce the need for foreign exchange in the long run. Under the Economic Development Plan, a raft of legislation was enacted to promote the general machinery, electronics, oil refinery and petrochemicals, transport equipment, steel and shipbuilding industries (Byun and Park, ). The approval procedure for the acquisition of foreign technologies in these target sectors was also simplified. By the late s, many of the initial entrants into the ‘heavy’ industries were acquiring both physical capital and relevant technology from foreign sources. Westphal, Kim, and Dahlman (: –) reported that more than a quarter of gross domestic investment in Korea from  to  was spent on foreign capital goods. In , an automatic approval system for the acquisition of foreign technology was introduced in general and electrical machinery, shipbuilding, chemicals, textiles, and finance under the following conditions: () the duration of the contract must be three years or shorter; () the down payment must be US$, or less; () the running royalty rate must be  per cent or lower; and () the fixed fee must be US $, or less. From  onwards, most sectors, except weapons, explosives, and nuclear power, were granted automatic approval for their projects subject to satisfying the conditions. Deregulation continued in the s and s, with the filing requirement abolished in  and the approval process simplified to a filing-and-confirmation process from . From , foreign exchange banks were assigned to handle a certain level of foreign technology acquisition applications (Korea Development Bank, ; Korea Industrial Technology Association, : ). The Korea Industrial Technology Association, a semi-government agency, published a data book, KOITA (), covering foreign acquisition in the period –. The value of this unique data set lies in the fact that all contracts are reported and classified into three categories: know-how-only acquisition, know-how-and-patent-rights acquisition and patent-rights-only acquisition. Know-how-only acquisition typically consists of technical services and training that are bundled with relevant documents. Know-how-and-patent-rights transfer consists of technical services, training, and documentation protected by the patent system. Patent rights only consists of patentright licensing.¹ Chung and Lee () made a number of findings from analysis of this database. First, they found that contracts for know-how licensing dominated in the early years, whereas contracts that involve patents followed later. The shares of know-how-only, know-how-and-patent-rights, and patent-only contracts during the period – were  per cent,  per cent and  per cent, respectively. However, these shares amounted to  per cent,  per cent and  per cent between  and , reflecting

¹ We follow Kiyota and Okazaki () in using the term ‘foreign technology acquisition’.

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      



the subsequent increase in know-how-and-patent-rights licensing. This pattern may imply that those firms that successfully assimilated basic operational skills and elementary process technology through know-how acquisition advanced to the acquisition of technologies that involve patent rights at later stages. These contracts include not only printed information and blueprints, but also technical services and training information. Expatriate engineers usually come to Korea to ensure that the initial operation of new facilities goes according to plan. Selected Korean engineers are sometimes sent abroad for training, which emphasizes the importance of human capital investment in building AC, as demonstrated by leading firms in Korea, such as Hyundai Motors (Kim, ) and POSCO (Pohang Steel Co.) (Song, ). Various types of training, particularly overseas and on-site training, were arranged or provided by the firms’ foreign suppliers of facilities and equipment. For instance, after Hyundai entered into an agreement with Ford to assemble compact cars on a semi-knocked-down basis, Ford transferred ‘packaged’ technologies to Hyundai with an accompanying set of explicit knowledge, such as blueprints, technical specifications, and production manuals. Ford also provided tacit knowledge to Hyundai, sending ten Ford engineers to Hyundai and training Hyundai engineers at Ford sites in procurement planning, procurement coordination, production engineering, process engineering, production management, welding, painting, after-service, and marketing (Kim, ). In the case of POSCO, the company sent thirty-nine engineers to Japan in – and , staff members abroad from  to  during the construction of its first mill (Song, : ).² Second, they found that the acquisition of foreign technologies is dominated by four capital-intensive sectors—electricals and electronic equipment, chemicals, transport equipment, and general machinery—rather than by labour-intensive sectors. These findings reflect the industrial policy of the Korean government and the efforts of firms to enter these sectors from the early s. The contracts in these four industries made up more than  per cent of the total contracts filed in the sampling period and throughout each sub-period.³ This finding indicates that the state’s control over foreign technology acquisition was critical for the structural transformation of Korean industries from labour intensive to capital intensive, which has ultimately helped them achieve industrial upgrading. Korea’s ‘pillar’ companies, such as Samsung Electronics, Hyundai Motors, and POSCO, were all established around . The entry of Korean firms into these industries typically involved the manufacture of products that were new to Korea yet common in the developed world. According to a survey by the Korea Development Bank () on foreign technology acquisition in the s,  per cent of these acquisitions by Korean firms related to mature technologies

² These foreign-trained engineers played very substantial roles in the early days of POSCO, with their share in the workforce in charge of facility operation and maintenance reaching  per cent and  per cent, respectively (Song, : ). ³ However, this was not evident during the period from  to , when heavy investment in social overhead capital increased the demand for technology in cement and utility firms, such as electricity.

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in developed countries, whereas  per cent related to the expansion of product mix. With Korean firms finding the knowledge embedded in manufacturing facilities insufficient for their operations, they sought additional services and training (or know-how-and-patent licensing) from firms in developed countries at an appropriate price. From the suppliers’ point of view, concealing mature technologies was pointless because providing know-how was a way of exporting large manufacturing facilities. The Japanese government’s decision to move away from ‘pollution-prone’, ‘naturalresource-consuming’ heavy and chemical industries in  provided a favourable environment for Korean firms (Enos and Park, ). Selling unnecessary technologies proved profitable for Japan (Enos and Park, : ), and was consistent with the ‘flying-geese’ pattern of economic growth in East Asia, where Japanese companies serve as leaders for their follower firms from Korea or Taiwan by transferring their technologies or relocating their factories abroad (Akamatsu, ; Kojima, ). In this regard, as noted by several scholars, including Kiyota and Okazaki (), Korean industries followed a similar path to those of Japan, with foreign technology acquisition in the form of licensing rather than FDI nurturing their domestic absorptive capacity and improving their performance (Lee and Kim, ). According to the Korea Development Bank (), technologies that were bundled with patent rights were more expensive or had a higher value than those that were only bundled with know-how. This arrangement suggests that Korean firms may have demanded something more than the mere operation of manufacturing facilities after stabilizing their daily production. Patented technologies may have been adopted as a means of completing the assimilation and improvement processes that were initiated by investment and know-how acquisition. Imported capital goods have been regarded as among the most important forms of technology transfer in Korea (Lee and Kim, ; OECD, ). However, these goods become ineffective without the transfer of technology, and especially of tacit knowledge, through know-how-only contracts. Thanks to frequent on-site training by foreign expatriate engineers, Korean engineers quickly learnt to manage their daily operations efficiently. If the knowledge were deemed insufficient, the turnkey contractor and/or other sources, including R&D specialty companies or equipment providers, were contacted for additional information. Enos and Park () argue that even in the most successful cases, such as POSCO and Hanyang Chemicals, time and effort were necessary for Korean firms to become able to use foreign technologies effectively. Finally, the econometric analysis in Chung and Lee () shows that know-how licensing associated with imported capital led Korean firms to build AC and then to start in-house R&D, whereas patent-only licensing was not significantly related to being able to conduct R&D. Therefore, a substitution effect may be observed between the introduction of foreign patents and the initiation of own R&D activities at the early stages of development. A similar econometric exercise for the second step shows that conducting in-house R&D leads firms to generate innovations, in terms of either patent applications or increased productivity, during the later stages of their development.

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      



Moreover, there is a significant correlation between know-how licensing experience and firms’ first-time patent applications, whereas patent-only licensing helps stimulate the subsequent generation of patents. The study also finds that firms generally spend at least three to four years building their AC, from the first year of know-how licensing to the first year of patent applications. Chung and Lee’s study () was the first to verify the dynamic link between the learning of tacit knowledge and the formation of AC, as well as the first to measure the actual length of time firms take to build this capacity. This finding verifies the two-stepbased differentiation of ‘potential’ and ‘realized’ AC that is proposed by Zahra and George (), as well as the decomposition of AC into learning capacity and problemsolving capacity by Kim (). In contrast to Jaymin Lee (), our view is that the substituting or inducing effect of foreign technology acquisition on indigenous R&D depends on the specific licensing method. Patent-only licensing exhibits a substituting relationship, whereas know-how licensing tends to have an inducing effect on in-house R&D. Moreover, a learning process that involves foreign technology, especially tacit knowledge in the form of know-how, occurs before firms can conduct in-house R&D and innovation. However, this specific learning process may not be the only way to build AC, given the importance of worker education, on-the-job training, and overseas training. Lee (b), arguing that it may be difficult to derive generalizable lessons from the state-versus-market view of Korean economic development, proposed instead a ‘capability-based’ view and elaborated various modes of capability building that may be useful in other latecomer countries. Chung and Lee’s () econometric study provides a microeconomic foundation for a macro-level view of economic development, from which several generalizable implications may be derived. First, the building of AC is a dynamic process that may become more effective when combined with access to foreign knowledge, particularly tacit knowledge (know-how). This suggests, second, that know-how transfer should be an essential element in technology-licensing contracts for a latecomer firm. Moreover, third, the potential substituting effect of foreign patent licensing may interfere with formation of inhouse AC, especially if it is not linked to the start of in-house R&D activities or contracting for know-how transfer.

. I I P  T  E C

.................................................................................................................................. One of the most traditional industrial policy tools is infant industry protection through tariffs. However, empirical studies on the effectiveness of tariffs report conflicting results. According to Beason and Weinstein (), tariff protection, preferential tax rates, and subsidies did not affect the rate of capital accumulation or total factor productivity

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(TFP) in Japan from  to . Lee () found no impacts of tariffs on TFP in Korean industries from  to , such that nominal tariff was negative and significant to the growth rate of labour productivity and TFP at the sectoral level. Nevertheless, several studies verify the positive contribution of industrial policy, in particular tariffs. Shin and Lee (), using the same period and sectoral data as Lee (), find that tariff protection, especially when combined with export-market discipline, leads to the growth of export share and RCA (revealed comparative advantages). They also argue that in the early stages the goal of this type of industrial policy was not productivity—as in the s—but output or growth in market share. Aghion et al. () also find that subsidies widely distributed among Chinese firms have had a positive impact on both TFP and the innovation of new products in sectors with a high level of competition. Both of these recent studies identify competition or discipline as a common precondition for effective industrial policy. An example of success with tariffs is the case of Hyundai Motors, established in . Hyundai’s first own-brand car was the Pony, which had a  per cent market share in Korea in . However, it was protected by tariffs on imported cars, for example from Japan, as high as  per cent. While its domestic market price was about US$, dollars, it was exported to the US market for US$,. In other words, it was only this ‘dumping’ that enabled Hyundai to compete with other cars, and it was only possible owing to extra profits associated with the oligopoly market situation based on tariffs; at that time, Japanese or German cars in a similar segment were selling at US $, in US markets. In other words, domestic profit compensated for the loss of foreign markets, and it was these guaranteed profits that helped Hyundai to survive and pay for fixed and R&D investment for expansion. Thus, it can be argued that if Korea had been opened up from the beginning without tariffs, the Korean economy would not have been so successful in promoting indigenous firms and sustaining their catch-up in market share. A hidden assumption of trade liberalization is that local firms are sufficiently competitive to potentially compete against foreign companies or imported goods. This assumption is not true in many cases. In such circumstances, naïve trade liberalization may lead to monopoly by foreign goods or the destruction of local industrial bases. A smart or better opening strategy, as discussed in Shin and Lee (), is ‘asymmetric opening’, in which latecomer economies liberalize the import of capital goods for the production of final or consumer goods, while protecting their own consumer goods industries by charging high tariffs on imported goods. Korea implemented an asymmetric tariff policy for consumer and capital goods, with extremely high tariffs for consumer goods (e.g. around  per cent for household electrical appliances in the s) which were promoted as export industries, but considerably lower tariffs for capital goods, such as machinery which it needed to import for its assembly industries, mostly in the consumer goods sector. Another form of industrial policy in Korea was entry control. Put simply, the idea is that five profit-making firms is better than ten firms in the same sector with no profits.

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      

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This type of entry control has typically been practised in the past by Japan, and copied in Korea, where it has been regarded as an industrial policy copied from the Japanese (Johnson, ). The practice has two meanings: to sort the ‘good’ from the ‘bad’ producers; and to allow stable profits for the selected producers to encourage them to invest further in fixed capitals for business expansion. This practice also has the effect of return rates that are higher than interest rates. This is good for boosting private investment in manufacturing, which corresponds to low rates of return with longer time horizons. Manufacturing sectors can earn ‘rents’ associated with entry control, and the government’s industrial policy consisted in working out the optimum number of each sector, taking market size into account, so that the firms admitted are guaranteed a minimum level of profits (rents) which can provide the following period’s investment funds. Of course, the protection of local firms through tariffs and entry control leads to an oligopolistic domestic market. However, a study by Jung and Lee () demonstrates that monopoly rents can be used to fund R&D investment because firms are exposed to the discipline of world export markets, while their privileged protected status is not free but rather is linked to their export performance. In other words, the combination of rent-generating protection in the domestic market and discipline from world markets was one of the most important aspects of industrial policy in Korea during its catchingup stage (mid-s and s). Jung and Lee’s () study confirms that R&D financed in this way led to Korean firms developing enhanced innovation capabilities, which enabled their productivity catch-up with Japanese firms from  to . In other words, in-house R&D eventually became more important than foreign technology acquisition because () foreign firms became increasingly reluctant to provide core technology to their potential competitors in Korea, () labour costbased competitiveness gradually disappeared, and () government support for private R&D increased (OECD, : –).

. P–P J R&D

.................................................................................................................................. The final stage of industrial policy consists of public–private R&D consortia that can serve as important vehicles for breaking into higher-end segments or sectors which demand both more capital and more risk. An early example was the government-led R&D consortia in the telecommunications equipment industry, specifically the accompanying local development of telephone switches. This led to the successful localization of telephone switches in the s and s in several latecomer countries, including China, Korea, India, and Brazil (Lee, Mani, and Mu, ). In the s and s most developing countries experienced serious telephone service bottlenecks. With neither domestic telecommunications equipment manufacturing industry nor their own R&D programme, they imported expensive equipment and related technologies, and local technicians merely

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installed foreign switching systems into the country’s domestic telephone networks. With industrial and commercial bases developing rapidly—along with population growth—a number of countries decided to build their own manufacturing capabilities. First in Brazil in the s, followed by Korea and India in the mid-s, and finally by China towards the late s, a state-led system of innovation in the telecommunications equipment industry was developed with a government research institute at the core. The research institute developed more or less ‘indigenous’ digital telephone switches that were then licensed to public and private domestic enterprises. In all four countries, a common pattern in the indigenous development of digital switches was the tripartite R&D consortium between government research institutes in charge of R&D functions, state-owned enterprises or the ministry in charge of financing and coordination, and private companies in charge of manufacturing at the initial or later stages. However, subsequent waves of industry privatization and market liberalization in Brazil and India contrasted with consistent infant industry protection in Korea and China (Lee, Mani, and Mu, ). At one extreme, the indigenous manufacturers of China and Korea took over from the importers and MNCs. The enhanced capabilities in wired telecommunication they had been accumulating over the preceding decades led to the growth of indigenous capabilities in wireless telecommunications. At the other extreme, Brazil and India have increasingly become net importers of telecoms equipment, and their industries are now dominated by affiliates of the MNCs. As noted by Mathews (), examples from Taiwan include calculator and laptop computer production. The calculator is an example of the acquisition of more fundamental design capability (basic design platform) enabled with the help of a government entity such as the Industrial Technology Research Institute (ITRI). Another example is the – public–private R&D consortium to develop laptop computers (Mathews, ). This consortium developed a common mechanical architecture for a prototype that could easily translate into a series of mass-produced standardized components. The consortium represented an industry watershed, and even after several failed attempts, it succeeded in establishing new ‘fast-follower’ industries in Taiwan. While the telephone switch case localized somewhat mature technologies, the same public–private joint R&D model can be used to leapfrog into emerging technologies or products. A Korean example is digital TV development, the decisive final watershed that enabled Korea to begin overtaking Japan in the TV business. Examples from China include recent moves towards solar power and electric cars. In these areas, there are no products for latecomers to imitate: advanced and latecomer countries enter the market at the same time. If the former latecomers succeed first, there is a strong momentum for them surpassing the middle-income group and joining the rich-country club. The public–private R&D consortium plays a more vital role in this leapfrogging endeavour, given that the risk involved is huge and different. Furthermore, coordinated initiatives on exclusive standards and incentives for early adopters would be important in reducing the risk faced by the weak initial market. In these public–private R&D consortia in mature stage, private firms take the lead over the public labs in conducting R&D jointly whereas the opposite would work

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      

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during the early stage of public-private joint R&D. Thus, in the final stage of the R&D consortium, the public research arm would be in charge of monitoring the technology trends as well as providing information about technology standards and identifying suitable foreign partners (e.g. Qualcomm for mobile phone development and Zenith for digital TV development) for collaborative development. The foreign company’s role will also change. In the second stage, the foreign company is the direct teacher in the co-development contract, but in the final stage, it becomes the supplier of source technology to be commercialized by the latecomer firm or their consortium. The final stage features horizontal collaboration or an alliance based on complementary assets. Some Korean firms (e.g. Samsung) have reached this stage, and are now engaged with Intel, Sony, Toshiba, and Microsoft in diverse modes of alliances. The probability of leapfrogging success may therefore be higher when a new technoeconomic paradigm or a new generation of technologies begins to emerge. Pérez and Soete () and Freeman and Soete () observe that some latecomers may be able to leapfrog older versions of technology, bypass heavy investment in previous technology systems, and grasp new technologies to take over the market from the incumbent firms or countries. This leapfrogging strategy makes more sense at the time of a paradigm shift, because every country or firm is a beginner in using the new technoeconomic paradigm, and the entry barriers tend to be low. Furthermore, the ‘winner’s trap’ may operate in the sense that the incumbent tends to ignore new technologies and continue to use the existing dominant technologies until it exhausts its investment in the existing facility. The concept of leapfrogging is consistent with the idea of technological discontinuity proposed by Anderson and Tushman () and Tushman and Anderson (), that competence-destroying discontinuity may lead to the emergence of new entrants. Korea’s catch-up with Japan in the development of high-definition TVs (HDTVs) would not have been successful if Korean electronics companies, such as Samsung and LG, had not targeted the emerging digital technology-based products more aggressively than Japanese companies that opted to continue manufacturing the dominant analogue products.⁴ The Japanese firms developed analogue-based HDTV in the late s and suggested that Korean companies follow new technologies and products by learning from them—which was the strategy they used to pursue in the s and s. Instead, Korean companies tried a leapfrogging strategy of developing an alternative and emerging technology—producing digital technology-based HDTVs. They successfully formed the public–private R&D consortium that marked the beginning of Korean hegemony in the global display market previously dominated by Japan. If it had not been for this risk-taking leapfrogging strategy, Korean catch-up with Japan would have taken much longer or might have never happened. Leapfrogging is more likely to happen where there are sectors with more frequent changes in technologies or generation changes in products. This is closely linked with ⁴ The case of digital TV production is further explained by Lee et al. (). A direct comparison of Samsung and Sony can be found in the work of Joo and Lee ().

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the length of the technology cycle, as these features indicate the speed with which technologies change or become obsolete over time, paving the way for the continued emergence of new technologies. We can reason that it is advantageous for qualified latecomers to target and specialize in short-cycle technology-based sectors. Although this is risky, it is also logical because latecomers do not have to rely substantially on the existing technologies dominated by the incumbents; moreover, there are always more growth opportunities associated with constantly emerging technologies. Finally, we should note the importance of carefully handling the risks involved in choosing a leapfrogging strategy. As Lee et al. () explain, one of the biggest risks is choosing the right technology or standard in the ex post sense. In the competition for standard setting and market creation, the role of the government is to facilitate the adoption of specific standards, thereby influencing the formation of markets at the right time, especially when the target involved is in the area of information or other emerging technology. Isolated development without considering standards might cause the entire project to fail. Collaboration and partnership with rivals or suppliers of complementary products is essential for standard setting. Another key factor is determining who creates and reaches the market first, given the fact that market size determines the success or failure of one standard in relation to another. The above case for successful public and private joint R&D for leapfrogging in Korea can be contrasted with a mixed case in South Africa, which was also discussed in Lee (). Swart () explains that the South African government provided the initial funding to establish Optimal Energy in , which by December  had developed four roadworthy electric car prototypes. The Joule Electric Vehicle was a ‘born electric’ five-seater passenger car incorporating a locally developed battery, motor, and software technologies. However, the government decided to stop the funding required to start large-scale production because of uncertainties over marketing success, and the company closed in June . The failure of Joule cars was caused by the lack of private companies to take on volume production and sales. Existing foreign multinational companies and local auto companies did not want this new ‘disruptive innovator’, a state-owned company, to grow into another rival. A better outcome would have been for the government to form a public–private consortium so that volume production would be carried out by private actors after the consortium developed the prototype. Private firms need to be involved for two reasons: they know where market demand is, and they eventually run the show. However, public-sector agents are better placed to deal with technological and financial uncertainty. This South African case can therefore be considered one of ‘design failure’ rather than a ‘targeting failure’. The sources are often mixed together. While one might expect more cases of targeting failure, this is not always the case. Uncertainty diminishes if targeting is seen in terms of identifying potential or existing markets as long as the private sector, with its knowledge of markets, is involved. If not on the frontier, the targets may be obvious because there is often a clear benchmark case which enables niches between existing firms and projects to be identified. Numerous public initiatives fail because of design or capability (low execution capability) failure.

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      

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. C R

.................................................................................................................................. Reports on the effectiveness of industrial policy in the empirical literature provide conflicting or ambiguous results. This may be so because it is difficult to verify the average positive impact of industrial policy as the effects tend to appear only in certain conditions, depending upon specific contexts (countries or sectors). Moreover, the results change depending upon the criteria used to assess the effectiveness of industrial policy. As discussed in this chapter, while expansion of production volume and sales to increase market share had been the primary goal in the earlier stages of catch-up, productivity has become an important criterion only since the late s, when the Korean government shifted its policy from tariffs to R&D subsidies as well as joint R&D (Jung and Lee, ). Given that structural change in an economy is a long-term process, the idea of adopting different policy tools over time is consistent with the reasoning that industrial policy should deal with the various dimensions of capabilities of firms and industries in the latecomer countries. Different tools are necessary, depending on whether the target involves simple operational or production capabilities, investment capabilities, or advanced technological capabilities. In Korea, tariffs and other forms of protection led to export and output expansion through fixed investment during the early period (s and s), according to the study by Shin and Lee (), whereas Jung and Lee () find that for a later period (the mid-s to ), R&D investment stimulated by tax exemptions led to productivity growth. The two studies find that for both periods, the disciplinary impact of export orientation is significant, because it promoted the rents associated with tariffs (earlier period) and with an oligopolistic market structure (late period) used for fixed (earlier period) and R&D investments (later period), respectively. In sum, while the specific tools and contents of the industrial policies were different, they both allowed some rents for the targeted sectors or firms so that the extra profits could be used to build variants of capabilities, such as production capabilities in the case of tariffs or technology licensing in the s, investment capabilities in entry control in the s, and technological (R&D) capabilities in the case of public–private joint R&D in the s. Such a dynamic shift in policy tools is not simply imposed by the government but also reflects the available and/or desired level of firm capability, which changes over time. Although Korea had been growing fast with exports of labour-intensive low-end goods, this growth strategy reached a peak by the mid-s. Around that time, Korea saw an increase in its own wage rate, which coincided with the emergence of lowerwage countries able to compete in world markets. As Korean firms realized the need to upgrade to higher-end or value-added goods, they began, for the first time, to establish in-house R&D centres, after which the industrial policy tools switched towards tax exemption on R&D (Lee, b; Lee and Kim, ).

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The Korean experience indicates a dynamic shift in the form of government activism from traditional industrial policy (tariffs and undervaluation) in the early stages of development, to technology policy (R&D subsidies and public–private R&D consortia) in the later stages. This dynamic shift is required for a developing country to evolve from low-income to middle-income status, and eventually move on up to higherincome status. It can be argued that without such a shift, any country may be stuck in what is called the middle-income trap, struggling to remain competitive as a site for low-cost, high-volume production (World Bank, ; Lee, b).

A The author thanks the editors of this volume and the participants of the Review Workshop, held in Addis Ababa in September , in particular Arkebe Oqubay and John Weiss, for their useful comments and discussion.

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 

Lee, Keun (b) ‘How Can Korea Be a Role Model for Catch-up Development? A “Capability-based View”’, in Augustin K. Fosu (ed.) Achieving Development Success: Strategies and Lessons from the Developing World. Oxford: Oxford University Press, pp. –. Lee, Keun (c) ‘Capability Failure and Industrial Policy to Move beyond the Middleincome Trap: From Trade-based to Technology-based Specialization’, in Joseph E. Stiglitz and Justin Yifu Lin (eds) The Industrial Policy Revolution, Vol. I. Basingstoke: Palgrave Macmillan, pp. –. Lee, Keun () ‘Smart Specialization with Short-cycle Technologies and Implementation Strategies to Avoid Both Target and Design Failures’, in Slavo Radosevic, Adrian Curaj, Radu Gheorghiu, Liviu Andreescu, and Imogen Wade (eds) Theory and Practice of Smart Specialization. Amsterdam: Elsevier, pp. –. Lee, Keun () The Art of Economic Catch-up. Cambridge: Cambridge University Press. Lee, Keun and Yee Kyoung Kim () ‘IPR and Technological Catch-up in Korea’, in Hiroyuki Odagiri, Akira Goto, Atsushi Sunami, and Richard R. Nelson (eds) Intellectual Property Rights, Development, and Catch Up: An International Comparative Study. Oxford: Oxford University Press, pp. –. Lee, Keun and Franco Malerba () ‘Economic Catch-up as Evolutionary Process’, in Richard R. Nelson (ed.) Modern Evolutionary Economics: An Overview. Cambridge: Cambridge University Press, pp. –. Lee, Keun and John A. Mathews () ‘From the Washington Consensus to the BeST Consensus for World Development’, Asian-Pacific Economic Literature (): –. Lee, Keun and John A. Mathews () ‘Firms in Korea and Taiwan: Upgrading in the Same Industry and Entries into New Industries’, in Edmund Amann and John Cantwell (eds) The Innovative Firms in the Emerging Market Economies. Oxford: Oxford University Press, pp. –. Lee, Keun, Chaisung Lim, and Wichin Song () ‘Emerging Digital Technology as a Window of Opportunity and Technological Leapfrogging: Catch-up in Digital TV by the Korean Firms’, International Journal of Technology Management (–): –. Lee, Keun, Sunil Mani, and Qing Mu () ‘Divergent Stories of Catch-up in Telecom: China, India, Brazil, and Korea’, in Franco Malerba and Richard R. Nelson (eds) Economic Development as a Learning Process. Cheltenham: Edward Elgar, pp. –. Mathews, John A. () ‘The Origins and Dynamics of Taiwan’s R&D Consortia’, Research Policy : –. Mowery, David C. and Joanne E. Oxley () ‘Inward Technology Transfer and Competitiveness: The Role of National Innovation Systems’, Cambridge Journal of Economics : –. OECD () Reviews of National Science and Technology Policy: Republic of Korea. Paris: OECD. Pack, Howard () ‘Learning and Productivity Change in Developing Countries’, in Gerald K. Helleiner (ed.) Trade Policy, Industrialization, and Development: New Perspectives. Oxford: Clarendon Press, pp. –. Park, Kyoo-Ho and Keun Lee () ‘Linking the Technological Regime to the Technological Catch-up: Analyzing Korea and Taiwan Using the US Patent Data’, Industrial and Corporate Change (): –. Pérez, Carlota and Luc Soete () ‘Catching-up in Technology: Entry Barriers and Windows of Opportunity’, in Giovanni Dosi et al. (eds) Technical Change and Economic Theory. London: Pinter Publishers, pp –.

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      



Radosevic, Slavo, Adrian Curaj, Radu Gheorghiu, Liviu Andreescu, and Imogen Wade (eds) () Theory and Practice of Smart Specialization. Amsterdam: Elsevier. Shin, Hochul and Keun Lee () ‘Asymmetric Trade Protection Leading Not to Productivity But to Export Share Change: The Korean Case from  to ’, Economics of Transition (): –. Song, Sungsoo () ‘Historical Development of Technological Capabilities in Korean Steel Industry: Posco from the s to the s’, PhD thesis, Seoul National University (in Korean). Stiglitz, Joseph E. and Justin Yifu Lin (eds) () The Industrial Policy Revolution, Vol. I. Basingstoke: Palgrave Macmillan. Swart, Gerhard () ‘Innovation Lessons Learned from the JOULE EV Development’, The IAMOT  Conference Proceedings. Tushman, Michael and Philip Anderson () ‘Technological Discontinuities and Organizational Environments’, Administrative Science Quarterly : –. Westphal, Larry E., Linsu Kim, and Carl J. Dahlman () ‘Reflections on the Republic of Korea’s Acquisition of Technological Capability’, in Nathan Rosenberg and Claudio Frischtak (eds) International Technology Transfer: Concepts, Measures, and Comparisons. New York: Praeger, pp. –. World Bank () Economic Growth in the s: Learning from a Decade of Reform. Washington, DC: World Bank. World Bank () Exploring the Middle-income Trap. World Bank East Asia Pacific Economic Update: Robust Recovery, Rising Risks, Vol. . Washington, DC: World Bank. Zahra, Shaker and Gerard George () ‘Absorptive Capacity: A Review, Reconceptualization, and Extension’, Academy of Management Review (): –.

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  .............................................................................................................

      .............................................................................................................

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        ......................................................................................................................

                       .............................................................................................................

 

. I

.................................................................................................................................. T latecomer industrialization thesis has acted as a powerful policy instrument in the promotion of the industrialization, as well as the economic growth, of the United States, Germany, Japan, and the East Asian economies. However, there has been little explanation in the literature as to why several other economies that attempted to industrialize are facing premature deindustrialization. Thailand was never colonized; Indonesia, Malaysia, the Philippines, and Singapore gained independence in , , , and  respectively. Despite introducing industrial policies as a major instrument to stimulate economic development, only Singapore has managed to sustain sufficiently rapid growth to enjoy a per capita income of US$, in  (current US$), . times higher than that of Malaysia (US$,), and . times higher than that of Thailand. Malaysia and Thailand enjoyed the second- and third-highest per capita income in South East Asia in . On average in US$  prices, the GDP per capita incomes of Singapore, Thailand, Malaysia, Indonesia, and the Philippines grew by ., ., ., ., and . per cent per annum respectively between  and .¹ Thailand’s growth rate over the period – was higher than that of Malaysia, even though the per capita income in US$  prices of Malaysia (US$,.) was much higher than of Thailand (US$,.) in . This was because Thailand’s starting per capita income (US$.) base was much smaller than Malaysia’s (US$,.).

¹ Computed using data from World Bank ().

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

 

This chapter seeks to explain how industrial policy has driven sustained rapid economic growth and structural change in Indonesia, Malaysia, the Philippines, Singapore, and Thailand.² However, whereas Singapore has carefully managed upgrading to become a developed country, the rest are stuck in the middle-income trap. Going beyond the typical broad-brush framework used by latecomer exponents, the chapter examines the shortcomings associated with policies in these countries that failed to spur differentiation and division of labour, and technological upgrading—both across and within industries. Malaysia launched explicit industrial policies and developed the science, technology, and innovation infrastructure to stimulate upgrading, while Indonesia, the Philippines, and Thailand had ad hoc strategies in place to support technological upgrading. Unlike the experiences of Japan, South Korea, and Taiwan, where industrialization was propelled by national firms, foreign transnational corporations (TNCs) have played a major role in stimulating manufacturing expansion in the South East Asian market economies. However, all five countries have begun to experience deindustrialization. As a share of value added in GDP, Thailand and Malaysia enjoyed the highest expansion of manufacturing among these countries, but they have neither managed to stimulate upgrading to high value-added activities, nor succeeded in developing national firms to reach the technology frontier. Singapore has managed to specialize in the high-value-added segments in shipbuilding and petrochemicals, in which it enjoys relative comparative advantage, and in TNC-driven export-oriented manufacturing, by quickly shifting its industrial specialization to sustain industrial upgrading. This chapter seeks to explain the industrial policies introduced in Indonesia, Malaysia, the Philippines, Singapore, and Thailand, and their impact on industrialization. We begin with key theoretical arguments to locate the analysis, before discussing first, the import-substitution industrialization (ISI) policies, and second, the export-oriented industrialization (EOI) policies implemented in the South East Asian market economies. Section . assesses their industrialization and de-industrialization experiences, followed by an examination of the impact of technological upgrading initiatives in these countries. Section . presents the conclusions.

. T C

.................................................................................................................................. South East Asia’s industrialization did not follow the paths begun by latecomers, such as the United States, Germany, Japan, South Korea, and Taiwan. The early introduction of

² We have excluded the transition economies of Cambodia, Lao PDR, Myanmar, Vietnam, TimorLeste, and Brunei from South East Asia only because the first five economies were integrated into the capitalist world economy much later (starting with Vietnam since ) and Brunei has been an oil- and gas-driven economy that has not implemented any industrial policies.

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       



export-oriented industrialization in the South East Asian market economies of Indonesia, Malaysia, the Philippines, Singapore, and Thailand largely took the form of attempts to diversify exports to reduce dependence on a narrow range of commodities and avoid the occurrence of ‘fallacy of composition’ problems (see Prebisch, ; Singer, ). The initial focus was on the promotion of light labour-intensive manufactured goods to generate employment through the stimulation of foreign direct investment (FDI). Indonesia, Malaysia, the Philippines, and Thailand did introduce ISI but that strategy failed to contribute significantly to rapid economic growth as it was not accompanied by a rapid switch to export orientation. In addition, little attention was devoted to technological upgrading. In contrast, the massive growth and structural change enjoyed by Singapore was achieved by switching completely to export orientation in  and focusing on technological upgrading since . Smith () and Young () argued over the differentiation and division-oflabour potential of manufacturing to produce dynamic increasing returns. Industrial expansion through technological upgrading can be traced to latecomer strategies. The latecomer thesis on industrialization originally focused on broad-brush approaches that simply documented how Britain industrialized; the subsequent catch-up experiences of the United States, Germany, and other countries were documented by Gerschenkron () and Abramovitz (). This argument was later extended by Kaldor (), Chang (), and Reinert ().³ Amsden (, ) and Kim () offered empirical dynamics to the latecomer catch-up thesis by focusing on the diffusion of innovation from abroad using specific host-site firms in South Korea. They extended the developmental state arguments of Johnson () and Wade () on how industrial policy was used successfully to stimulate economic development. It is in this tradition that Mazzucato () was able to frame their mission-oriented and smart intervention industrial policy arguments. Ocampo (Chapter , this volume) connects policy with technological learning and upgrading through incremental innovations. Rasiah () went further by incorporating Schumpeter’s (, ) concepts of incremental and radical innovations using the experience of firms in South Korea (e.g. Samsung Semiconductors) and Taiwan (e.g. TSMC), showing how, despite their contrasting industrial policies, they successfully shaped catch-up and leapfrogging in the integrated circuits industry (Yap and Rasiah, ). South Korea and Taiwan did not integrate into the world economy in the same way as the South East Asian economies. Both countries focused on the latecomer catch-up model from the early s by prioritizing national ownership in strategic industries (Amsden, ; Wade, ). They also introduced monetary policies to ensure that volatile fluctuations in capital and trade flows did not destabilize their industrialization

³ Johnson () and Wade () addressed significant elements of industrial policy implemented in Japan and Taiwan respectively, but did not link it to manufacturing being a critical engine of growth.

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

 

initiatives. While prudent monetary policies ensured that the New Taiwan dollar’s exchange rate against the US$ did not fluctuate sharply, South Korea imposed foreign exchange controls from  till the s, including on borrowings from abroad by private entities, maintaining ownership of banks by the state until the s. South Korea also fixed the won against the US$ between  and  to stem the negative impact of growing balance-of-payment imbalances and debt service problems following the first oil crisis, when oil prices rose by a factor of  from  to . With targeted firms, especially chaebols, enjoying subsidized interest rates, the deliberate imposition of high arbitrage interest rate differentials between borrowing and lending assisted the government to gradually lower its external debt, as well as support targeted firms (Chang, ).⁴ The generation and adaptation of technologies, incentive systems, and appropriation of knowledge flows were critical for stimulating individuals, firms, and organizations to connect and coordinate with knowledge nodes that provide the synergy for catching up. Since the knowledge necessary to stimulate innovation can be regarded as a public good, its governance should prioritize technological upgrading. Embodied knowledge—both foreign and domestic—is continuously adapted to raise industrial productivity. The organizational set-up can vary between countries, as initial conditions and economic structures affect how they are shaped. Combining the key arguments on the manufacturing experiences of particularly South Korea and Taiwan (the most recent successful industrializers), we present a stylized model of industrial policy in Figure ., showing a framework of how incremental and radical innovations (including interactive learning) support technological upgrading in successful economies. Institutions must be structured to pursue macroeconomic policies that provide the financing (incentives and grants) essential to support innovative economic activity, as well as insulation from external shocks. Institutions need strengthening to meet stringent appraisal standards to check unproductive rent seeking. Amsden () and Kim () provide a lucid account of innovation appropriation and economic catch-up from foreign sources in South Korea and Taiwan. The public-good characteristics of knowledge creation and appropriation (innovation) were harnessed effectively in Taiwan and South Korea. The critical organizations relevant to institutionalizing knowledge creation and appropriation on a national scale, such as universities, public labs, standards organizations, and incubators at science parks, must play an active role in stimulating incremental and radical innovations with a focus on evolving experiential and tacit knowledge (see Penrose, ; Polanyi, ; Dosi, ; Rasiah, ; Best, ). While first movers initiate cycles of innovation, latecomers engage in incremental innovation (Schumpeter, ). As economies move from the ‘least-developed countries’ category to middle-income countries, governments should ensure that gross ⁴ We would argue that the abrupt liberalization since the s, but especially following the Plaza Accord of , denied the South Korean government the space to insulate the national economy from private borrowings from abroad and exchange rate volatility.

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       

Existing stocks of embodied knowledge (manuals, machinery, humans, methods, and organization, irrigation, drainage, species)—foreign and domestic

Organizations (universities, training centres, technical and vocational schools, R&D labs, and business advisory centres



Creative imitation (incremental innovation)

Science and technology parks

Realm of knowledge flows and adaptive innovations

Radical innovations

Individuals, parastatals/organizations, farms, and firms

 . Innovation-driven industrial policy Source: Adapted from Rasiah ().

expenditure on R&D (GERD) gradually rises, with a focus on R&D targeted at generating new stocks of knowledge. Instead of simply seeking to gradually replace government expenditure with business expenditure in GERD, non-business public expenditure should be included to address the public goods characteristics of science, technology, and innovation (STI) infrastructure.

. I- P

.................................................................................................................................. Influenced by advice from the World Bank and the United Nations Industrial Development Organization (UNIDO) to limit manufacturing to consumption goods, in the late s Indonesia, Malaysia, the Philippines, Singapore, and Thailand all began to promote ISI to replace imports (Chenery et al., ). Only in some extended backward-linkage industries, such as iron and steel, and cement, was there a focus on intermediate products. Corruption through smuggling was rampant, with rising tariffs encouraging clientelist relationships. Capital goods were not emphasized until the s in Indonesia and Philippines, and the s in Malaysia and Thailand. Singapore

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

 

introduced EOI immediately after its separation from Malaysia in ,⁵ so the ISI focus in this chapter will be confined to the other four countries.

.. Indonesia Suharto became president of Indonesia in , following a period of international isolation arising from Sukarno’s declaration of independence and nationalist policies. The New Order government had the support of the United States as it sought to promote import-replacement policies following the launching of the First Plan (–). Foreign ownership was discouraged but joint ventures were allowed (Anwar, ). Incentives and import credits cheapened the processing and assembly of consumption goods in the country. Incentives for existing projects included carryover losses over the first six years, accelerated depreciation allowance up to a maximum of  per cent, exemption from dividend tax, an investment allowance of  per cent over four years, and exemption from property tax (Poot, ). The Investment Coordinating Board offered new projects with additional fiscal incentives, which included exemptions from import duties and restrictions on imported machinery and raw materials, and exemption from corporate income tax, dividend tax, and company tax on reinvestments over five years. Booming oil revenues following the first oil crisis (–) supported the launching of the aircraft industry in  with special support from the state. Krakatau Steel was also launched by the state to support heavy industrialization (Prawiro, ). While diversification into manufacturing was viewed by policymakers as important for averting the ‘fallacy of composition’ syndrome, three major instruments undermined the growth of ISI industries in Indonesia. First, protection and incentives were given without clear performance standards, while there was no condition requiring import substitution industries to switch to EOI as in South Korea and Taiwan. Second, there was no institutional support for technological upgrading by firms. The combination of these two drawbacks saw a rise in production costs for downstream firms, and a lack of pressure to bring costs down. Third, the oil boom that began in  (which raised the share of oil to  per cent of Indonesian exports), resulted in the appreciation of the rupiah, which undermined manufacturing as cheap imports replaced domestic production over the period – (Tee, ). Although manufacturing grew by an annual average of . per cent over the period –, (almost double the growth over –), its ‘Dutch Disease’ effect stunted inward-oriented industries, such as food and beverages. The steep fall in oil prices after  forced Indonesia to consider a shift to EOI, and particularly to manufactured exports. However, until the late s serious balance-ofpayments problems forced the government to focus on monetary stabilization, ⁵ Singapore’s ISI lasted from  till  (Phang and Tan, ).

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       



financial deregulation to allow state banks to set deposit and lending rates, and a massive devaluation of the rupiah in March  (Hill, : ; Prawiro, ). Steel and aircraft manufacturing continued, as did state-led ISI, with the launching of large state-owned resource-processing heavy industries, which included the Timor–KIA joint venture deal to assemble cars (Rasiah, ).

.. Malaysia Malaysia raised tariffs on final consumption goods following the Pioneer Industry Ordinance of . A combination of a small domestic market and a lack of technological upgrading policies confined manufacturing to ‘screwdriver operations’ (Edwards, ). Not only had manufacturing growth become sluggish by the mids (Malaysia, ), the sector had also become a major source of imports as capital goods and a variety of consumption goods continued to be imported on a large scale (Alavi, ). The extension of ISI policies that took place from the s without due attention to their impact on downstream industries and technological upgrading merely sapped the domestic economy of resources. Protection levels remained high in the country (Edwards, ; Alavi, ), though estimations of effective rates of protection (ERP) did not take account of tax and tariff holidays of firms located in exportprocessing zones (EPZs), which were opened in Malaysia from . Free-trade zones (FTZs) and licensed manufacturing warehouses followed (Rasiah, ). The lack of export promotion as a condition for ISI undermined the competitiveness of firms. The lack of integration between the IS and the export-oriented sectors also discouraged linkages between the two (Jomo and Edwards, ). A second round of ISI began in  with the Fourth Malaysia Plan and the launch of the Look East Policy (Malaysia, ). Perwaja (steel), Proton (cars), and Kedah Cement were among the heavy industries promoted by the Heavy Industry Corporation of Malaysia (HICOM) in an attempt to imitate South Korea through subsidized credit and heavy protection (Malaysia, ). The construction of the North–South Highway in the s helped to stimulate these industries. While the focus of ISI was on national firms for the first time, the lack of effective selection and appraisal, technological upgrading, and exposure to export markets rendered the first two industries inefficient, though Proton did export using a questionable export subsidization strategy in the late s (Rasiah, ). Nevertheless, the massive expansion of construction and technology transfer made cement and construction firms competitive (Chang et al., ). Arguably the most catastrophic reason for the failure of IS strategies in Malaysia was the lack of policies to stimulate technological upgrading. With little emphasis on developing a science and technology infrastructure in the country, production costs began to rise, cheaper locations emerged from abroad (e.g. China and Vietnam

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

 

following economic reforms in  and  respectively), and Malaysian manufacturing could not upgrade to higher value-added activities. Meanwhile, while export diversification helped avert the ‘fallacy of composition’ syndrome, the appreciation in the ringgit in the face of chronic current account deficits between  and  caused by strong FDI and portfolio equity inflows undermined inward-oriented industries, including food and beverages (Rasiah, ).

.. The Philippines The Philippines gained independence from Spain in ; largely due to balance-ofpayment (BoP) problems, ISI policies were introduced in  (Bautista, ). Controls on both imports and foreign exchange became the prime instruments to curb imports, and the manufacturing sector lacked competitiveness due to lack of policies to stimulate technological upgrading. By the s it became obvious that ISI had become a drain on the Philippines’ economy, which drove the government to stimulate FDI inflows. Reconstruction assistance from the United States offset the negative balance of trade in the Philippines. However, while import restrictions stimulated manufacturing, import controls resulted in the substitution of domestic production by imports of textiles, paper and paper products, and non-metallic mineral products. Nevertheless, manufacturing grew at  per cent per annum on average between  and  (Bautista, ). However, the Philippines faced economic and political turmoil in the late s as the peoples’ car launched under ISI policies by the government failed to take off (Ofreneo, ) which, along with rising imports, caused a return of the BoP crisis in . Economic growth remained sluggish, particularly in the manufacturing sector which was heavily dependent on processing of primary commodities such as coconut products, sugarcane, forest products, copper, and gold. To combat its BoP difficulties, the government implemented the Republic Act  and the Export Incentives Act of  to encourage FDI through  per cent ownership of pioneering industries (textiles and garments, and electrical and electronics). Non-pioneering industries were allowed to be  per cent foreign owned and were offered accelerated depreciation allowance, tax exemptions on imported capital equipment, and tax holidays. However, in the s the bulk of the FDI was heavily import dependent (Ofreneo, ). Additionally, non-tariff barriers were implemented in the country to protect industries like vehicles and equipment, textiles, basic metals, and fabrics in the principal customs area. Instead of discouraging imports, the devaluation of the peso negatively affected the ISI industries that were dependent on imports of capital equipment, intermediate goods, and raw materials. While the proliferation of EPZs raised manufacturing growth to . per cent in the period –, driven largely by TNCs assembling and processing imported items from their own value chains, the Philippines’ economy suffered from rising external debt caused by the oil crises of

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       



– and –. The strong oligarchy supporting the government applied clientelist pressures to retain unproductive protection rents. Growing poverty and unemployment drove hundreds of thousands of Filipinos abroad, which eventually made overseas remittances a major source of revenue for the Philippines.

.. Thailand Following the First Development Plan (–), but especially after the enactment of the New Investment Promotion Act of , the Thai government raised tariffs and offered indirect subsidies to promote ISI. Three groups of industries were promoted by the Board of Investment (BoI). Category I industries were given full exemption from import duties on raw materials and intermediate inputs and business taxes, category II industries, one-half exemption, and category III industries, one-third exemption. Tariffs targeted at final goods for the domestic market continued to be promoted under the Second Five-Year Plan (–), but duties on imported inputs were reduced to a third. Manufacturing value added grew at  per cent on average per annum over the s with ISI policies the prime propellant (Bautista, : ). Food processing, beverages, and tobacco dominated manufacturing in the early s, but began to contract from the late s with the growth of import-replacing industries, such as petroleum products, transport equipment, non-durable consumer goods, and EOI industries, such as textiles, clothing, and electronic products (Bautista, : ). Although EOI began in the s, ISI remained potent with the government’s stimulation of domestic investment under the  Investment Promotion Law, through which the BoI reconstituted ISI strategies in Thailand (Akrasanee, ). The BoI’s promotion of minimum plant size also led to the establishment of large-scale manufacturing firms, which in general were found to be more capital intensive and import dependent than small firms (Tambunlertchai and Loohawenchit, ). While manufacturing value added still grew by an average of  per cent per annum during –, chronic BoP deficits and mounting external debt service (followed by a . times rise in oil prices in –) drove the government to seek assistance from the World Bank and the International Monetary Fund (IMF). Between  and , with massive inflows of FDI and portfolio equity investment and no trade surplus, the baht began to appreciate, leading to the ‘Dutch Disease’ effect of damage to inwardoriented industries (Akrasanee, ).

.. Summary In short, high domestic production costs and the absence of initiatives to gradually lower protection levels undermined export competitiveness, but the inability of ISI to support long-term growth in manufacturing was principally due to a lack of effective

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

 

technological upgrading policies to transform the economies of Indonesia, Malaysia, the Philippines, and Thailand from low to high value-added activities. To make matters worse, unproductive rentier operations through clientelism behind high tariffs and quotas aggravated the state’s capacity to sustain them over the long run.

. E- P

.................................................................................................................................. A combination of small domestic markets, the disastrous costs of poorly conceived IS policies, and TNCs relocating their labour-intensive production stages drove the South East Asian market economies to switch to EOI policies. Singapore and Thailand attracted foreign TNCs with tariff-free operations and tax holidays. Malaysia launched manufacturing as the engine of growth through its New Economic Policy (Malaysia, ). Indonesia allowed export-oriented TNCs to relocate in Batam from  with total ownership and tariff-free and tax holiday privileges (Prawiro, ).

.. Indonesia With the Plaza Accord of  and further falls in the oil price, Indonesia effectively began EOI in . The withdrawal of the generalized system of preferences (GSP) from South Korea, Taiwan, and Singapore in  drove massive FDI inflows into South East Asia. The surge in Indonesia’s manufactured exports since  is largely a consequence of the introduction of the duty exemption and drawback scheme. The Badan Koordinasi dan Penanaman Modal (Investment Coordination Board) promotes industrial investment in Indonesia (Prawiro, ). Indonesia also offered total equity ownership of export-oriented firms in selected locations, such as Bantam, leased to Temasik Holdings of Singapore to manage from the late s. As the EOI strategy began to proliferate in Indonesia, continued stagnation in the oil price and cumbersome integration of inward-oriented firms in heavy industries caused by dualistic policies restricted the capacity of EOI to synergize the whole economy. The rupiah appreciating against major currencies from the s undermined the IS industries owing to cheap imports, which aggravated the balance of payments and debt service. The unsustainable exchange rates affecting most East Asian economies caused Indonesia to succumb to the – Asian financial crisis, which brought down the rupiah and resulted in a massive capital flight from Indonesia (UNCTAD, ). The IMF-imposed structural adjustment package, as well as the low exchange rate, began to attract FDI inflows into Indonesia in , reviving manufacturing growth. The restructuring included the closure of the Timor–KIA aircraft manufacturing joint venture (Rasiah, ). Although Indonesian manufacturing was not seriously affected

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       



by the – global financial crisis, since its trade was decoupled from exports to the United States, a combination of cumbersome administrative procedures and a lack of technological upgrading undermined further growth.

.. Malaysia Although the Investment Incentives Act of  initiated the shift to EOI, it was only following the opening of FTZs (and their equivalent in licensed manufacturing warehouses) in  that export-oriented manufacturing expanded strongly (Malaysia, , ). Through aggressive promotion by the Malaysian Industrial Development Agency (an organ of the Ministry of International Trade and Industry (MITI)),⁶ EOI in the s focused on lowering unemployment with light industries and generating exports. Giant TNCs from the United States, Europe, and Japan relocated labourintensive operations to Malaysia. The electrical and electronics, and textile and clothing industries dominated EOI in the s (Rasiah, ). Without significant backward linkages, the fortunes of EOI fluctuated with the vicissitudes of volatile external demand swings. Hence, not only did manufacturing wages grow little in the s, but workers were also often exposed to retrenchments. Although a second round of ISI policies beginning in  changed the emphasis to heavy industrialization, rising external debt service and falling export commodity prices pressured the government to revive EOI policies, and new financial incentives were offered to TNCs to invest in Malaysia from the mid-s (Rasiah, ). As the EOI phase gained momentum with massive inflows of FDI from Japan, South Korea, Taiwan, Hong Kong, and Singapore in the late s, the government shifted its focus from simply creating jobs to promoting technological upgrading in the s. Plans were announced limiting financial incentives to capital- and technologyintensive TNCs, while R&D incentives were offered to stimulate technological upgrading. Parastatals were launched to create and strengthen the STI infrastructure in the country. The Human Resource Development Council, Malaysia Industry Government High Technology, the Multimedia Development Corporation, and the Multimedia Super Corridor were launched in the s for this purpose. The Malaysian Institute of Microelectronics Systems was corporatized, and science and technology parks were built over the Western Corridor to house incubators. While carrots were given to selected firms to undertake R&D, there was little monitoring and no sticks were applied to non-performers. The selection procedure for leadership of STI parastatals and designated technology firms excluded Malaysians with experiential and tacit knowledge in the respective industries. The preference was for extending the legacy of creating Bumiputera chief executive officers, which had become the government’s important goal since the promulgation of the Permodalan ⁶ ‘International’ was added to the Ministry of Trade and Industry in the s (Rasiah, ).

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

 

Nasional Berhad in , and had been actively pursued since . The ethnic coloration of industrial policy resulted in standards taking a back seat, rendering the STI parastatals ineffective, while the firms created for support failed to compete in export markets. Perwaja, Proton, and Silterra are three examples of national firms that have continued to sap the national economy. The control of Proton was finally taken over by China’s Geely in  (Zhang et al., ), while Silterra is languishing at the bottom of the world semiconductor ladder (Rasiah and Yap, ).

.. The Philippines Although EOI was launched in the Philippines in the s when the Board of Investment (BoI) started promoting export-oriented FDI, ISI continued to lead, as industries located outside EPZs remained protected. Indeed, there were virtually no links between the tariff-free operations in the EPZs that attracted primarily electrical and electronics, and textile and garment firms from abroad. However, chronic BoP deficits and debt service attracted structural adjustment packages from the IMF that, inter alia, required the liberalization of tariffs from the s as the Philippines’ integration into ASEAN intensified following the ASEAN Free Trade Area (AFTA) agreement in . The Foreign Investment Act of  increased foreign equity ownership to  per cent in non-EPZ industries. Tariffs were reduced on raw materials and finished products, which helped reduce external debt (Menardo, ). Although largely ineffective, these generous incentives attracted FDI into particularly electrical, electronics, and automotive components. However, the lack of a strong STI infrastructure, together with smuggling and the absence of proactive promotion of technological upgrading, restricted manufacturing expansion so that its share in overall exports only reached . per cent in  before falling again.

.. Singapore As one of the first to promote EOI in Asia, and located strategically as an entrepôt, Singapore was in a position to promote industries relevant to the country’s economic development. Given the high unemployment rates of the s, Singapore’s Economic Development Board (EDB) promoted labour-intensive export-oriented FDI from  until the saturation of the labour market and rising wages shifted the emphasis from  to attracting capital- and technology-intensive industries. Exports are promoted principally through financial incentives, withdrawal of which discourages incompatible industries. Strategic industries, such as shipbuilding, petrochemicals, information communication, and bio-technologies, have also been offered R&D grants and facilities (Singapore, a, b).

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       



Singapore fits the mission and smart industrial policy argument advocated by Mazzucato (). The EDB’s agile leveraging role takes account both of Singapore’s endowments and of changes in TNC strategies, to attract the adaptation required in a broad Schumpeterian sense to sustain technological upgrading and phase out incompatible industries (see also Wong, ; Rasiah and Yap, ). Three clear strategies can be observed in the conduct of the EDB. First, Singapore took advantage of its intermediate role in trade to launch oil refineries that expanded into petrochemicals and to develop shipbuilding. Second, incompatible industries were replaced with compatible industries. For example, Singapore phased out disk-drive firms in – once it became clear that the industry was labour intensive, and the semiconductor industry from  because of the lack of related research capability to support upgrading (Rasiah and Yap, ). Indeed, the notable semiconductor firms in Singapore, such as TSMC, Seagate, and Avago, were only fabricating low-end chips.⁷ Third, a science park was established to stimulate commercialization. Singapore’s leveraging strategy to transform the economy from low to high valueadded activities by offering R&D grants and facilities attracted regional operations from TNCs. Similarly, the government’s promotion of shipbuilding and downstream petrochemical industries allowed the country to become industry leaders. Both industries offered Singapore strategic positioning as the country gradually rose, through refining imported oil, and repairing and building ships, rigs, and platforms, to the status of the busiest in the world. The EDB’s quick approach to world-class firms, handling of registration, customs coordination, and developing institutional support by linking R&D labs and universities has gone a long way to wards evolving a world-class shipbuilding and petrochemical industry (Singapore, a, b; ASMI, ). In addition, Singapore’s entrepôt trade has continued to thrive, despite ASEAN economies gradually establishing their own trade routes. Around half of merchandise exports over the period – were re-exports, which in  benefited from a network of twenty-one regional and bilateral free-trade agreements with thirty-two trading countries. In fact, merchandise trade through preferential trading agreements accounted for about  per cent of Singapore’s imports and  per cent of exports in  (WTO, ).⁸ Through lucrative incentives and grants, and careful selection of foreign experts, Singapore has evolved a strong biotechnology industry.

.. Thailand Although the Export Promotion Act of  initiated Thailand’s export orientation, EOI only became the dominant industrial strategy of Thailand from the early s ⁷ See Rasiah and Yap () for a detailed study of Singapore’s inferior location in the semiconductor technology trajectory. ⁸ Singapore’s low corporate tax base of  per cent in , along with the FTAs, make it an attractive regional headquarters for TNCs.

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

 

when mounting debt and BoP problems forced the government to accept an IMF structural adjustment package amounting to US$ million. The promotion of exports became a key instrument to clear the BoP deficit, which on average amounted to around US$ billion since the second half of the s (Akrasanee, ). Through increased production and productivity, EOI was expected to lead manufacturing valueadded growth to an average annual rate of . per cent during the plan period –. The government began to reduce tariffs, promote regional dispersal of industry, and offer tax incentives to exporting firms. Five industrial estates with excellent infrastructure were added to the four that had existed earlier. Thailand faced a contraction in manufacturing value added owing to falling commodity prices and a cyclical downturn in the electronics industry in the mid-s. However, serious unemployment problems were largely avoided as factory workers returned to rural farms to support themselves (Phongpaichit and Baker, ). The country also experienced a massive inflow of export-oriented manufacturing investment from the late s, which helped fuel rapid growth again. The appreciation of the yen, won, NT dollar, and Singapore dollar from  following the Plaza Accord, and the withdrawal of the GSP from South Korea, Taiwan, and Singapore in February  resulted in substantial capital flight from these countries to South East Asia. Thailand also depreciated the baht to attract further FDI inflows. Further deregulation in the s resulted in giant foreign automobile firms relocating their operations to Thailand. While manufacturing value added expanded over the period –, the lack of technology policies undermined the capacity of manufacturing to sustain wage increases and technological upgrading from low to high value-added activities. Minor ad hoc incentives and high-tech facilities were offered to large firms in the automobile (including an automobile university) and electronics industries (Intarakumnerd and Chaoroenporn, ), but the lack of development of a comprehensive STI infrastructure to support incremental and radical innovations resulted in manufacturing value added’s contribution to GDP plateauing in  and subsequently declining.

.. Summary Overall, EOI offered the appropriate scale to stimulate expansion in exports and employment creation. With foreign frontier TNCs spearheading EOI, the difficulties associated with competition from abroad were reduced. While Singapore enjoyed firstmover advantages in Asia, the creation of EPZs allowed the other four market economies to offer the excellent basic infrastructure essential for attracting labourintensive operations. However, the lack of a focused industrial policy to stimulate upgrading and the lack of stringent appraisal mechanisms for firms enjoying incentives and grants stifled their upgrading in global value chains. Lack of connectivity between

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

       



ISI and EOI firms also discouraged the development of linkages. Singapore did not face these problems; its EDB managed to stimulate industrial upgrading by promoting compatible industries while dis-incentivizing incompatible industries using a strong appraisal mechanism.

. I  D

.................................................................................................................................. While industrial expansion began with the launch of ISI in the s and s, the growth was fastest during EOI owing to a combination of bigger export markets enjoyed by TNCs relocating operations from abroad compared to small domestic markets and the use of labour-intensive technologies. Indonesia, Malaysia, the Philippines, and Thailand’s experience with ISI drained the economies of foreign exchange from imports of intermediate inputs and capital machinery equipment, while undermining performance owing to a lack of strong technological upgrading policies. While the powerful liberalizing initiatives through Asia-Pacific Economic Cooperation (APEC) and the World Trade Organization (WTO) reduced the significance of IS policies, (particularly after the formation of the AFTA in ), it is also the lack of effort to pressure ISI industries to shift to EOI that resulted in manufacturing either stagnating or declining in importance in Indonesia, Malaysia, the Philippines, and Thailand (Figure .).⁹ Although manufacturing has also started to fall in Singapore, 35

Per cent (%)

30

28.2

25 20

19.6

15 10.6

10 5

4.5 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016

0

Year Indonesia

Malaysia

Philippines

Singapore

Thailand

 . Manufacturing value added share in GDP, selected economies, – Source: World Bank ().

⁹ All uncited statistics on manufacturing composition and growth rates were computed from World Bank ().

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

 

its almost  per cent share in GDP for a city-state and being characterized by highvalue-added activities is positive. Although EOI became the dominant industrial strategy, all five South East Asian market economies examined in this chapter have begun undergoing deindustrialization. At its peak, manufacturing contributed over  per cent of GDP in Indonesia, Malaysia (–), and Thailand (–). The steady expansion of manufacturing in these countries began to slow down and contract once FDI-led light manufacturing firms could not upgrade to compete with cheaper sites in China, Bangladesh, and Indo-China. Heavy industries, such as iron and steel, cement, and automobiles have remained owing to the preferential tariffs and incentives enjoyed under the ASEAN Economic Community (AEC), which stipulates a rule-of-origin condition of  per cent value to be added cumulatively for firms to enjoy liberal access to domestic markets. As liberalization and incentives propelled exports, the trade structure of the five South East Asian market economies quickly shifted towards manufactured goods (Figure .), particularly electricals and electronics, automotive components, and textiles and garments. Except for declines caused by external crises, manufactured export shares in the total exports of Indonesia, Malaysia, the Philippines, and Singapore reached their peaks in –. Thailand enjoyed its highest export share in . The rapid expansion of manufacturing, including diversification within the sector, helped the South East Asian economies avert problems caused by the ‘fallacy of composition’. 100.0 90.0 80.0

Per cent (%)

70.0 60.0 50.0 40.0 30.0 20.0

0.0

1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016

10.0

Year Indonesia

Malaysia

Philippines

Singapore

Thailand

 . Manufactured exports share in total merchandise exports, selected economies, – Source: Computed from data collected from World Bank ().

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

       



Owing to problems of data availability and reliability, in evaluating the performance of manufacturing among the five economies we focus on the most common industries: machinery; electricals and electronics; transport vehicles and equipment; food, beverages and tobacco; and chemical industries. We have used the trade balance with South Korea and Taiwan of the key export-oriented industry of electricals/electronics (HS) and the key import-substituting industry of motor vehicles (HS) over the period  to  as the benchmark to examine the competitiveness of these industries. Using trade balance (TB) as the indicator of competitiveness is not without its problems.¹⁰ Although export volume and TB are used to measure the competitiveness of critical high-technology electric/electronics, and motor vehicles and components industries in the four countries,¹¹ as value added in gross output, the figures are often distorted by both tariff and non-tariff barriers. Non-tariff barriers are still important in the motor vehicles industry, although Thailand has largely phased them out since the late s in its efforts to turn the country into a regional platform for motor vehicle manufacturing. Singapore led initially on electrical and electronics (EE) exports, a massive proportion of which were re-exports. In fact, Singapore exported more EE goods than South Korea until  (Figure .). South Korea and Taiwan overtook Singapore in  and  respectively. The three countries enjoyed their highest exports of US$ billion, US$ billion, and US$ billion, respectively, in . Exports from Malaysia followed, peaking at US$ billion in . Exports from Thailand and the Philippines amounted to US$ billion and  billion respectively in , while Indonesia exported US$ billion in . Most South Korean and Taiwanese exports are generated by their domestic firms, while those of the South East Asian market economies are generated by foreign firms, which often has negative BoP implications once profits are repatriated away from the host countries. Consequently, firms from these countries have better control over global value chains. South Korea enjoyed a clear lead in the export of motor vehicles and parts, reaching a peak of US$ billion in  before falling to US$ billion in  (Figure .). Except for – when external demand fell owing to the global financial crisis, motor vehicle and parts exports have risen steadily from the countries illustrated. Thailand overtook Taiwan in  to become the second-largest exporter of motor vehicles, with exports reaching US$ billion in . Exports from Taiwan, Indonesia, Singapore, Malaysia, and the Philippines followed, reaching US$ billion, US$ billion, US$ billion, US$ billion, and US$ billion respectively in . Again, most South Korean and Taiwanese exports are generated by domestic firms, and

¹⁰ We have avoided using total factor productivity and labour productivity measures to examine performance owing to serious problems associated with them. ¹¹ We avoided using revealed comparative advantage (RCA) owing to the lack of reliable information on value-added share in gross output, which is seriously compromised because of varying degrees of protection in these countries. Also, it does not distinguish specific industries within the categories based on their technological sophistication.

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi



 

200 180 160

US$ Billions

140 120 100 80 60 40 20 0

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 Year Chinese Taipei

South Korea

Indonesia

Philippines

Singapore

Thailand

Malaysia

 . Electric and electronics exports, selected economies, – Source: Computed from data gathered from WTO ().

80 70 60

US$ Billions

50 40 30 20 10 0

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 Year Chinese Taipei

South Korea

Indonesia

Philippines

Singapore

Thailand

Malaysia

 . Motor vehicle exports, selected economies, – Source: Computed from data gathered from WTO ().

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

       



0.800 0.600

(X-M)/(X+M)

0.400 0.200 0.000

–0.200 –0.400

20 01 20 02 20 03 20 04 20 05 20 06 20 07 20 08 20 09 20 10 20 11 20 12 20 13 20 14 20 15 20 16 20 17 20 18

–0.600 Year Chinese Taipei

South Korea

Indonesia

Philippines

Singapore

Thailand

Malaysia

 . Trade balance, electric and electronics, selected economies, – Note: X – exports; M – imports. Source: Computed from data collected from WTO ().

those of the South East Asian market economies are generated by foreign firms, with negative BoP implications. A significant proportion of motor vehicle and parts exports from South Korea originate from lead national firms, including from their subsidiaries abroad, while there are only two national car assemblers in Malaysia (both heavily reliant on foreign technology) and none in the remaining South East Asian market economies. It therefore appears that firms from South Korea have better control over their global value chains. The least export-oriented economy among the five countries until the turn of the millennium, Indonesia, enjoyed the highest TB in the EE industry during –. However, following liberalization, Indonesia’s TB fell to –. in  (Figure .). In the same year Thailand had the second-lowest TB, and Taiwan and South Korea the highest (at . and .). Malaysia, Singapore, and the Philippines also enjoyed a positive TB, but owing to the dominance of foreign capital in the ownership of the EE industry much of the profits are likely to have been repatriated abroad. Thailand was the only country to enjoy a positive TB in the motor vehicles and parts industry in – (Figure .). Indonesia and South Korea had a positive TB in this sector in some years, but Taiwan, Malaysia, and the Philippines consistently faced negative TB over the period. Although the automotive industry cluster generated , jobs and  per cent of GDP in , the foreign-dominated industry still specialized in low-margin vehicles that paid low salaries and generated little savings for the national economy owing to repatriation of profits abroad (Intarakumnerd and Chaoroenporn, ; Maikaew, ).

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi



  0.800 0.600

(X-M)/(X+M)

0.400 0.200 0.000 –0.200 –0.400 –0.600 –0.800

20 0 20 4 05 20 0 20 6 0 20 7 08 20 09 20 10 20 11 20 12 20 13 20 1 20 4 15 20 16 20 17 20 18

02 03 20

20

20

01

–1.000 Year Chinese Taipei

South Korea

Indonesia

Philippines

Singapore

Thailand

Malaysia

 . Trade balance, motor vehicles, selected economies, – Notes: X – exports; M – imports. Source: Computed from data collected from WTO ().

We next discuss the key industries by country to assess how they have fared, including additionally the outward-oriented industry of textiles and garments, and the inward-oriented industries of food, beverages and tobacco, and chemicals. All real growth rates were computed using local currencies and national base years.

.. Indonesia In , as Indonesia was emerging from a political crisis, manufacturing accounted for only . per cent of GDP. By  it had risen to . per cent (Figure .). The – and – oil crises resulted in booming exports and with that an appreciation of the rupiah as oil prices soared. A flood of cheap imports saw the food, beverages, and tobacco industry contracting, with growth of –. per cent. Textiles and garments, and the chemical industry grew on average by . and . per cent, respectively, per annum. Nevertheless, government-protected heavy industries grew rapidly to record the highest annual average growth rate of . per cent during –. Thus, the low base and the expansion in heavy industries caused manufacturing value added to grow by . per cent on average per annum over this period. Despite falling oil prices in the s, protected IS industries (including downstream wood-based industries) drove manufacturing value added to grow by . per cent per annum on average between  and . The annual average growth rate of machinery, electrical and electronics, transport vehicles and equipment (. per

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

       



cent), food, beverage, and tobacco (. per cent), and chemicals (. per cent) was the highest in –. The share of manufacturing in GDP continued to expand in trend terms to reach a peak of . per cent of GDP in , despite a fall in – following the – Asian financial crisis. Manufacturing value added grew by . per cent on average per annum in –. Machinery, electrical and electronics, and transport vehicles and equipment recorded the highest growth rate of . per cent on average per annum in the same period. Electronics exports soared as the liberal environment in Batam and Bintan attracted massive inflows of low-end manufacturing. Indonesia began to de-industrialize in , with the share of manufacturing in GDP falling in trend terms from . per cent in  to . per cent in  (Figure .). Manufacturing value added grew on average by . per cent per annum in –. The restructuring of incentives and deregulation of tariffs from  slowed down the growth of machinery, electricals and electronics, and transport vehicles and equipment to an average of . per cent per annum, while food, beverages and tobacco, and the chemical industry grew on average by . and . per cent per annum in –. The end of the Multi-Fibre Arrangement (MFA) in  negatively affected the textile and garment industry, which recorded an average annual growth rate of –. per cent. The advent of liberal policies shifted the focus to the food, beverages, and tobacco industry, which grew on average by . per cent per annum in –. The rapid scaling down of protection has resulted in machinery, electrical and electronics, and transport vehicles and equipment industries growing by –., and the chemical industry by . per cent on average per annum in –. The textile and garment industry recorded an annual average growth rate of . per cent in – as new locations outside Java Island became attractive for low-wage operations.

.. Malaysia The manufacturing sector increased its share in GDP in trend terms from  till  (Figure .). The early increase, from  till , was largely due to a decline in other sectors, as the Malaysian economy was facing a deflationary environment caused by a fall in tin and rubber prices and ethnic riots in  (Rasiah and Salih, ). The low starting base, as well as massive relocation of labour-intensive export-oriented TNCs, expanded the manufacturing sector, which grew by . per cent on average per annum in –. The highest average annual growth of . per cent was recorded in the textile and garment industry, followed at . per cent by machinery and transport vehicles and equipment (which also comprises electrical and electronics equipment). It was in the s that the giant polyglot company Toray relocated its massive textile manufacturing operations to Penang. Intel, Advanced Micro Devices, National Semiconductor, Texas Instruments, Hewlett Packard, and Hitachi also relocated their assembly operations in Malaysia in the s (Rasiah, ).

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi



 

The manufacturing sector grew little in the period – owing to a shift in incentives to ISI heavy industries and a cyclical downturn in the electronics industry. However, it grew again from the late s with the renewal of incentives for EOI firms and massive inflows of FDI into the sector (Rasiah, ). Consequently, manufacturing grew by . per cent on average per annum in –. The highest growth rate of . per cent was recorded by the chemical industry, followed by the machinery, and transport vehicles and equipment industry (. per cent). The manufacturing sector grew by . per cent on average per annum in –. While food, beverages and tobacco (. per cent), chemicals (. per cent), and textiles and garments (. per cent) began to slow down, machinery, and transport vehicles and equipment recorded its highest annual average growth rate of . per cent in –. The export-oriented electrical and electronics industry was the biggest contributor to this growth, which resulted in machinery, EE, and transport vehicles and equipment accounting for a . per cent share of manufacturing in , before falling to . per cent in . Deindustrialization began to creep into Malaysia from  as the share of manufacturing value added in GDP began to contract from . per cent in  to . per cent in  (Figure .). The manufacturing sector recorded an annual average growth rate of . per cent in –. Labour shortages, rising wages, and the emergence of cheaper sites abroad saw textiles and garments contract with a growth rate of –. per cent. Food, beverages and tobacco (. per cent), and chemicals (. per cent) recorded the highest average annual growth rates. Machinery, electrical and electronics, and transport vehicles and equipment (. per cent) experienced their lowest growth. Deindustrialization continued in – as manufacturing recorded its slowest growth of . per cent on average per annum. Machinery, electrical, electronics, and transport vehicles and equipment grew by . per cent per annum on average, food, beverages, and tobacco by . per cent, textiles and garments by . per cent, and chemicals by . per cent.

.. The Philippines The Philippines was the earliest to industrialize rapidly in South East Asia. Its manufacturing share in GDP rose from . per cent in  to its peak of . per cent in  (Figure .). However, manufacturing’s share of GDP has largely stagnated through the period –. Between  and , manufacturing value added grew on average by . per cent per annum as textiles and garments, machinery, electricals, electronics, transport vehicles and equipment, and the chemical industries grew by ., ., and . per cent respectively. De-industrialization began to grip the Philippines from the s, with average annual manufacturing value added growing by only . per cent per annum in –. Machinery, electricals and electronics, and

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

       



transport vehicles and equipment (–. per cent), the chemical industry (–. per cent), and textiles and garments (–. per cent) contracted. Deregulation of tariffs and the provision of export-oriented financial incentives stimulated rapid FDI-driven growth in the machinery, electricals and electronics, and transport vehicle and equipment industry, which grew by . per cent on average per annum from  to . However, a contraction in textiles and garments (–. per cent), and food, beverages, and tobacco (–. per cent), and a slowdown (. per cent) in the chemical industry slowed manufacturing value-added growth to an annual average of . per cent. Manufacturing growth began to pick up in – and –, growing on average by . per cent and . per cent respectively. The deregulation process began in  with the introduction of AFTA, and the subsequent formation of the ASEAN Economic Community (AEC) in  saw the rationalization of tariff measures in South East Asia, resulting in food, beverages, and tobacco, and textiles and garments growing on average by . per cent and . per cent per annum in –. However, the trend towards de-industrialization continued, with manufacturing’s share in GDP falling to . per cent in  (Figure .).

.. Singapore After launching EOI in , Singapore enjoyed first-mover advantages in Asia, with manufacturing’s share of GDP reaching . per cent in  (Figure .). The peak of . per cent was reached in . While labour-market saturation offered the government the opportunity to promote skills development and higher value-added activities, rising wages and labour shortages discouraged further FDI inflows. Manufacturing value added grew by . per cent per annum in –. Machinery, electricals and electronics, and transport vehicles and equipment, textiles and garments, and chemicals grew by . per cent; textiles and garments by ., and chemicals by . per cent on average per annum. The saturation in the labour market, the floating of the Singapore dollar in , and the withdrawal of the GSP in  did not seriously affect the manufacturing sector, which grew by . per cent on average per annum in – following restructuring of incentives and a focus on the STI infrastructure. Further upgrading initiatives and careful macroeconomic management sustained manufacturing value-added growth of . per cent on average per annum in –. The machinery, electricals, electronics, and transport vehicle and equipment (especially electronics and ships), and chemical (especially petrochemicals), industries grew on average by . and . per cent respectively. Although de-industrialization began to take root after manufacturing’s share in GDP peaked at . per cent in , with the  share at . per cent, Singapore’s manufacturing sector has remained strong despite the country’s small size. The country’s competitive advantage regionally within ASEAN has ensured that the

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi



 

chemical, food, beverages, and tobacco industries, machinery, electricals, and electronics industries, and transport vehicles and equipment industries enjoyed annual average growth rates of ., ., and . per cent respectively in –. The textile and garment industry contracted (–. per cent) in this period. Consequently, manufacturing value added grew on average by . per cent per annum. The food, beverage, and tobacco, and chemical industries grew further by . and . per cent respectively while the textiles and garments industry, and the machinery, electricals, electronics, and transport vehicles and equipment sector slowed down to grow by only . and . per cent respectively in –. Annual average manufacturing value added grew by . per cent in –.

.. Thailand Burgeoning BoP deficits following the – and – oil crises drove the government to promote exports. The share of manufacturing in GDP rose from . per cent in  to . per cent in – before falling in trend terms to . per cent in  (Figure .). Manufacturing value added grew on average by . per cent per annum in –. The shift to EOI raised manufacturing value-added growth as the machinery, electrical and electronics, transport vehicles and equipment, textile and garment industries grew on average by . per cent and . per cent respectively per annum following the relocation of TNCs from abroad in –. Consequently, manufacturing value added grew by . per cent per annum despite the food, beverages and tobacco industry contracting (–. per cent) in this period. The food, beverages, and tobacco industry grew by . per cent, chemicals by . per cent, and machinery, electrical and electronics, and transport vehicles and equipment by . per cent on average per annum in –. However, manufacturing value added only grew by . per cent per annum on average in – because of a decline in inward-oriented industries, such as iron and steel and metals in the first half of the s as a strong baht attracted massive imports. The machinery, electricals and electronics, and transport vehicles and equipment industry grew by . per cent on average per annum in – following Thailand’s emergence as South East Asia’s regional production base for cars. Food, beverages, and tobacco, and chemicals grew on average by . and . per cent respectively. However, manufacturing value-added growth slowed to . per cent on average in – owing to a contraction (–. per cent) in the textile and garment industries.

.. Summary In short, after a long period of expansion since particularly the s, the South East Asian market economies has all faced de-industrialization. Export-orientation through TNC operations have been the prime propellant of industrialization in these countries.

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

       



However, only Singapore has so far avoided premature de-industrialization through strong industrial upgrading. Malaysia, Indonesia, the Philippines, and Thailand are experiencing premature deindustrialization as these countries have not managed to achieve significant industrial upgrading.

. T U I

.................................................................................................................................. With the exception of Singapore, the South East Asian market economies have underperformed compared to South Korea and Taiwan, especially in the two critical hightechnology industries of electrical/electronics, and motor vehicles and parts. Although all the South East Asian market economies eventually switched to EOI, not only has institutional support to stimulate technological upgrading varied, but Indonesia, Malaysia, the Philippines, and Thailand have not managed to transform their manufacturing industries to become global leaders. While South Korea and Taiwan expertly used export quotas to quickly expose IS industries to external competition (a glaring omission in Indonesia, Malaysia, the Philippines, and Thailand), the underfunded STI infrastructure and its weak governance in the latter four countries undermined the capacity of their governments to finance industrial upgrading. Whereas Singapore and Malaysia began to stimulate industrial upgrading on a national scale in  and  respectively, Indonesia, the Philippines, and Thailand only launched broad-based STI development policies in . Also, whereas Singapore’s mission-oriented and strategic industrial policy drove rapid technological upgrading, a lack of appraisal mechanisms and connectivity and coordination between STI infrastructure organizations, and institutions and firms restricted technological upgrading in the other countries. Ad hoc incremental innovation from knowledge inflows from abroad has been critical to supporting infrastructure and maintenance, mining, and agriculture in all these countries. This section explains the link between STI infrastructure and industrial upgrading in the five economies.

.. Indonesia Strategic policies targeted heavy industries in Indonesia, for example, for the aircraft industry from  until it was discontinued following the – Asian financial crisis. The first formal STI policy in Indonesia can be traced to the  launch of the Vision and Mission of Indonesian Science and Technology Statement which incorporated four-year plans to be rolled out until  by the National Research Council of Indonesia (Aminullah, ; UNESCO, ; OECD, ). The first two plans (– and –) addressed the need to support business R&D in strategic

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

  4.5 4

Per cent (%)

3.5 3 2.5 2 1.5 1

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

0

1996

0.5

Year Indonesia

South Korea

Malaysia

Philippines

Singapore

Thailand

 . GERD in GDP, South East Asian market economies, – (%) Source: UNESCO ().

sectors. However, R&D expenditure did not increase significantly, and hence much of Indonesia’s STI capacity has remained in public organizations, with only  per cent of the budget allocated to the Institute of Sciences by the National Research Council of Indonesia to spearhead R&D activities (Oey-Gardiner, ; see also Figure .). The focus has been on resource-based industries with steel, shipbuilding, palm oil, and coal identified for Sumatra; food and beverages, textiles, transport equipment, shipping, information communication technology (ICT), and defence identified for Java; steel, bauxite, palm oil, coal, oil, gas, and timber strategized for Kalimatan; nickel, food and agriculture (including cocoa), oil, gas, and fisheries specified for Sulawesi; tourism, animal husbandry, and fisheries classified for Bali and Nussa Tengarra (Lesser Sunda Islands); and nickel, copper, agriculture, oil and gas, and fisheries targeted for Papua and Maluku Islands (UNESCO, ). By , the government had only committed  per cent of the US$ million for infrastructure development (Rasiah, : ). In addition, the role played by the private sector is modest, and the ratio of GERD to GDP (. per cent) was negligible in  (Aminullah, ), reaching about . per cent in .¹²

.. Malaysia In the s, with increased demand for proximate sourcing, technology diffusion through TNCs appeared promising (Rasiah, ). Indeed, significant supplies of ¹² Communication with Erman Aminullah on  October  in Bandung.

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       



precision tools, semi-automated machinery, and fabrication opportunities were established between multinational and national firms in Penang in the s and s. The Action Plan for Industrial Technology Development was launched in  to stimulate industrial upgrading. Several organizations were introduced to solve collective action problems and to promote the innovation essential to make Malaysia a developed country by  (Malaysia, ). The government then launched the second STI policy (NSTP) (–) and the third NSTP (–) to stimulate technological upgrading. In the s the government launched the Human Resources Development Council (HRDC), the Malaysian Technology Development Corporation, the Multimedia Development Corporation, the Malaysia Industry–Government Group for High Technology, and the Multimedia Super Corridor (MSC) to support structural transformation of industry from low to high value-added activities. The HRDC collects  per cent of the payroll from firms with  or more employees, which the firms can only reclaim through approved training expenditure. Collaborative Research in Engineering, Science and Technology (CREST) was formed in  to strengthen R&D collaboration between universities, government, and industry.¹³ R&D expenditure in GDP also increased from  (Figure .). Several R&D funds have been introduced since the s: Commercialization of R&D (); Technology Acquisition (); Biotechnology Acquisition (); Biotechnology Commercialization (); Industrial Technical Assistance (); the Techno (); the E-Content (); the Demonstrator Application Grant Scheme (); the MSC Malaysia R&D Grant Scheme (); the Science Fund (); the AgroBiotechnology R&D Initiative (); the Genome and Molecular Biology R&D Initiative (); the Pharmaceutical and Nutraceutical R&D Initiative (); the Fundamental Research Grant Scheme (); the Long-Run Research Grant Scheme (); and High Impact Research (). However, despite the long-standing role of Malaysia’s government in funding R&D programmes, there is no systematic appraisal and monitoring mechanism (Rasiah, ).

.. The Philippines The Philippines’ low GDP growth rates are largely a consequence of the country’s specialization in low-value-added activities. The Philippine Development Plan – launched strategies for using STI to boost productivity and competitiveness in agriculture and small businesses (including in manufacturing), especially in geographical areas dominated by poor, vulnerable, and marginalized residents. The Harmonized Agenda for Science and Technology – sought to promote the establishment of five government-funded centres of excellence by  in ¹³ Interview conducted by the author on  December  in Georgetown.

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

 

biotechnology, nanotechnology, genomics, semiconductors, and electronics design. The Philippines Genome Centre, which operates two core facilities for DNA sequencing and bioinformatics, was built at the University of the Philippines Diliman. The Advanced Device and Materials Testing Laboratory, located at the Department of Science and Technology’s compound in Bicutan in Taguig City, started operations in  with three laboratories in surface, thermal, chemical, and metallurgical analysis. The Electronics Product Development Centre is due to be built at the Department of Science and Technology in Bicutan, and will provide cutting-edge design, prototyping, and testing facilities for printed circuit boards. The government supported an expansion in the number of graduates, including doctoral graduates, between  and . Hence, while the Philippines only invested . per cent of GDP in higher education in , tertiary enrolment experienced a rise from . million in  to . million in . The number of doctoral graduates more than doubled from , in  to , in  (UNESCO, ). However, not only has GERD in GDP remained low (Figure .), but neither the research undertaken in universities nor the human capital produced by them have participated actively in the commercialization of manufactured products in the Philippines.

.. Singapore Through the EDB, Singapore has systematically stimulated technological upgrading in the country, leveraging its world-class infrastructure, efficient civil service, and provision of incentives and grants in return for continuous technological upgrading by foreign TNCs. Science parks and R&D have been supported through the development of STI infrastructure to finance strategic technologies in knowledge-based industries. By , the two science parks that acted as R&D hubs for companies housed more than  organizations and companies. Singapore’s  GERD-to-GDP ratio of . per cent was far below the . per cent and . per cent enjoyed by Israel and Korea respectively (UNESCO, ; Figure .). The government has invested heavily in the development of science and technology at Singapore’s leading universities—the National University of Singapore (NUS) and Nanyang Technical University—with cutting-edge research facilities, including R&D labs, machinery, and equipment, and has opened employment in the country to world-class scientists and engineers. Biopolis opened in  to promote biomedical research, while Fusionopolis was established in  to promote ICT research. The National Framework for Innovation and Enterprise enjoyed a total allocation of SG$. billion during –. Singapore has emerged as a leader of incremental innovation activity in South East Asia owing to its world-class basic infrastructure, integration in global markets, and connectivity and coordination between firms and organizations. Laboratories at NUS have been a major platform for petrochemical innovations, which support over a hundred firms in Singapore (Singapore, a; ASMI, ). Similar support is also enjoyed by the shipbuilding

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

       



industry, which includes strong research linkages between firms, and labs in NUS and Nanyang University (Singapore, b).

.. Thailand Since the s, the Thai government has promoted technology diffusion and innovation, starting with the National Science and Technology Development Agency, which established the Industrial Consultancy Services in  to promote alliances between local and foreign technical consultants. The agency launched a Software Park to stimulate innovation in start-up firms. The BOI also developed the Unit for Industrial Linkage Development programme to strengthen linkages among small and mediumsized manufacturers (UNCTAD, ). However, the lack of human capital, the absence of R&D grants to stimulate design and R&D, and the lack of electronicsbased research in universities and other laboratories drove American chip manufacturing out of Thailand from the s (Rasiah, ). Nevertheless, designing of ICs related to automotive systems has emerged with collaborative links with the universities of Chulalongkorn, Mongkut, and Chiang Mai (Intarakumnerd et al., ). The founding of the Hard Disk Drive (HDD) Institute helped provide scientific infrastructure for the HDD industry by establishing a central laboratory and networks of government laboratories. National firms, such as Hana Microelectronics, Stars Microelectronics Thailand, and Silicon Craft Technology, began designing customized integrated circuit packaging (Intarakumnerd et al., ). While Thailand is South East Asia’s leading producer of disk drives and automobiles, a transition to higher value-added activities would require strong R&D funding, which, however, fell from . per cent of GDP in  to . per cent in  (Figure .). Nevertheless, the National Science and Technology Development Agency has become an anchor for stimulating R&D, which in  employed over  per cent of the country’s full-time researchers in four organizations: the National Centre for Genetic Engineering and Biotechnology; the National Electronics and Computer Technology Centre; the National Metal and Materials Technology Centre; and the National Nanotechnology Centre. However, although it is part of the ten-year National Science and Technology Action Policy (NSTAP), –, targeted at developing the STI infrastructure, it has made little progress. The – NSTAP attempted to focus on infrastructure development, capacity building, regional science parks, industrial technology assistance, and tax incentives for R&D. While it set a target of  per cent GERD of GDP by , it still only offered tax exemptions for R&D without any grants up front. Except for the Asian financial crisis period of –, all the South East Asian market economies showed an intellectual property right (IPR) TB inferior to that of South Korea from  to . Singapore has managed to close the gap with South Korea since , while Malaysia has improved since  (Figure .). Although there were improvements in some years, Indonesia, the Philippines, and Thailand have remained strongly dependent on foreign intellectual property. The IPR TB figures for

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi



  0

[X-M]/[X+M]

–0.2 –0.4 –0.6 –0.729 –0.8 –1

19 8 19 1 8 19 3 8 19 5 8 19 7 8 19 9 9 19 1 9 19 3 9 19 5 9 19 7 9 20 9 0 20 1 0 20 3 0 20 5 0 20 7 0 20 9 1 20 1 1 20 3 1 20 5 17

–1.2

Year Indonesia Philippines

South Korea Singapore

Malaysia Thailand

 . Intellectual property trade balance, selected economies, – Source: World Bank ().

Malaysia, Indonesia, Thailand, and the Philippines in  were ., ., ., and ., respectively. This hugely negative coefficient partly explains why firms in these countries have not been able to upgrade into higher value-added activities to enjoy positive de-industrialization.

.. Summary Overall, except for Singapore, the STI infrastructure of the South East Asian market economies have serious shortcomings. A combination of low R&D funding, especially in Indonesia, the Philippines, and Thailand, and poor governance instruments in Malaysia, has undermined catching up and leapfrogging in these countries. Consequently, Malaysia, the Philippines, Indonesia, and Thailand have no cutting-edge manufacturing operations. This stark reality is reflected in heavy reliance on foreign technology as the IPRs of these countries are well below those of South Korea and Singapore (Figure .). Despite not having national manufacturing firms at the technology frontier, Singapore has managed to continuously renew its manufacturing structure through ingeniously leveraging on its endowments, and attracting TNCs and foreign researchers to support high value-added manufacturing activities. Singapore has also managed to close the IPR trade gap with South Korea since , following grants offered to biotechnology labs and firms.

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

       



. C

.................................................................................................................................. Manufacturing has played a major economic role in raising GDP growth, reducing unemployment, and alleviating poverty in the South East Asian market economies, especially since the s. Although ISI began in Indonesia, Malaysia, the Philippines, Singapore, and Thailand in the s, the lack of performance standards and initiatives to pressure relevant firms to export undermined the competitiveness of importreplacing industries. Ambitious heavy industry promotion in Indonesia, Malaysia, and the Philippines also largely failed. As IS industries drained the economies, BoP, debt service, and rising unemployment problems drove the South East Asian market economies to introduce EOI. Foreign direct investment arrived in the form of giant TNCs from developed countries relocating low-end stages of production to stimulate exports from all these economies. Indeed, FDI has been the main engine of export manufacturing growth in all the South East Asian market economies. Indonesia, Malaysia, Thailand, and the Philippines have all experienced premature deindustrialization, with the value added in manufacturing gross output falling before reaching developed status. Singapore has managed to become developed, focusing on incremental innovation by continuously renewing its composition of cutting-edge industries using a leveraging strategy that offers incentives to attract leading foreign firms. In addition to shipbuilding and petrochemical industries, Singapore has also evolved a strong bio-pharma industry. Malaysia began to develop its STI infrastructure in  but a lack of stringent appraisal mechanisms in the selection and monitoring of firms for support caused a massive dissipation of rents. Ethnically coloured policies also prevented industries from attracting world-class diaspora members to return and lead both national firms and the organizations created to solve collective action problems (Rasiah, ). Whereas the South East Asian market economies largely prevented the twin troubles of ‘fallacy of composition’ and ‘Dutch Disease’ from dragging them to the debt precipice, the lack of effective policy coordination to avert such problems cost Indonesia, Malaysia, the Philippines, and Thailand considerable resources. Singapore not only managed to prevent these problems from becoming chronic, but its sophisticated petrochemical, biotechnology, and shipbuilding industries have evolved to become world leaders. The lack of scale, and related research in its universities, have contributed to Singapore reaching its critical limits in electronics manufacturing. However, the remaining four market economies have populations and land space exceeding that of South Korea and Taiwan, and therefore the contraction of the manufacturing sector since the turn of the millennium suggests that they are facing premature deindustrialization. While Singapore’s textile and clothing, and electricals and electronics, and vehicle manufacturing sectors have declined, the ‘mission-oriented state’ (Mazzucato, ) has successfully removed incentives from them, rapidly moving them away from the country and gradually replacing them with new compatible

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi



 

industries, such as biotechnology, while retaining the shipbuilding and petrochemical industries. Indonesia, Malaysia, the Philippines, and Thailand have not managed to create an integrated STI infrastructure that can stimulate transformation of the manufacturing sector to the technology frontier as South Korea and Taiwan have done. Singapore, however, has managed to stay ahead of these countries with a sophisticated STI infrastructure, and using a flexible strategy that has continuously renewed the industries required to support a rise in value added.

R Abramovitz, Moses () ‘Resource and Output Trends in the United States since ’, American Economic Review (): –. Akrasanee, Narongchai () Economic Development of Thailand and ASEAN Economic Cooperation. Canberra: Australian University Press. Alavi, Rokiah () Industrialization in Malaysia: Import Substitution and Infant Industry Performance. London: Routledge. Aminullah, Erman () ‘Learning, R&D Intensity and Economic Prosperity in Low R&D Countries (LRDCs): Envisioning the Indonesian Future’. Keynote speech presented at the th International ASIALICS conference, Jogjakarta, – September. Amsden, Alice () Asia’s Next Giant: South Korea and Late Industrialization. New York: Oxford University Press. Amsden, Alice () ‘Diffusion of Development: The Late-Industrializing Model and Greater East Asia’, American Economic Review (): –. Anwar, Arsjad () Trade Strategies and Industrial Development in Indonesia. Canberra: Australian National University Press. ASMI () ‘Singapore Marine Industry Milestones’, Association of Singapore Marine Industries (ASMI). Available at http://www.asmi.com/index.cfm?GPID=. Bautista, Romeo () ‘Industrial Policy and Development in the ASEAN Countries’, Philippines Institute for Development Studies, Monograph No. , Manila. Best, Michael () The New Competitive Advantage. Oxford: Oxford University Press. Chang, Ha-Joon () The Political Economy of Industrial Policy. Basingstoke: Palgrave Macmillan. Chang, Shan-Fang, Rajah Rasiah, and Wei-Meng Chan () ‘Understanding Innovations in Malaysia’s Construction Industry: A Study of Four Large National Firms, Asian Journal of Technology Innovation (): –. Chenery, Hollis, Sherman Robinson, and Moshe Syrquin () Industrialization and Growth: A Comparative Study. Washington, DC: World Bank. Dosi, Giovanni () ‘The Nature of the Innovative Process’, in Giovanni Dosi, Christopher Freeman, Richard R. Nelson, Gerald Silverberg, and Luc Soete (eds) Technical Change and Economic Theory. London: Pinter Publishers, pp. –. Edwards, Christopher () ‘Protection, Profits and Policy: An Analysis of Industrialization in Malaysia’, PhD thesis, University of East Anglia. Gerschenkron, Alexander () ‘Economic Backwardness in Historical Perspective’, in Bert F. Hoselitz (ed.) The Progress of Underdeveloped Areas. Chicago, IL: University of Chicago Press, pp. –.

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       



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

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       



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  ......................................................................................................................

               , ,     

......................................................................................................................

    

. I

.................................................................................................................................. I the s and s, massive and rapid privatization-cum-liberalization was the core strategy of industrial reform prescribed by the mainstream transition economics for socialist countries. It was argued that ‘the government is in a race against time’ and the achievement of reforms cannot be maintained unless privatization occurs ‘quickly and on a vast scale’ (Sachs, : ‒). The existing industrial system inherited from the communist past was seen as an inefficient fossil to be phased out, and the challenge of restructuring was primarily ‘to efficiently close much of the old structure and allow for a rapid expansion of a new one’ (Blanchard et al., : ). Many argued that transition economies should not imitate the industrial policies of Japan and South Korea, and instead should shift their state‒business relations towards an ‘arm’s-length’ type under competitive market structures and private ownership. China’s reforms since the s, however, have been characterized by a combination of market-oriented transition and the persistent practice of industrial policies. A key dimension of China’s industrial policy has been to transform and consolidate the core of its large state-owned enterprises sector into a batch of state-controlled big businesses with international competitiveness. The rise of China’s ‘national champions’, defined here as the giant central state-controlled corporations, business groups, and financial institutions in the ‘commanding heights’ sectors, has reshaped the landscape of China’s business system. Now China has the second-largest number of Fortune Global  companies in the world. In , there were a total of  large firms from Mainland China in the Fortune Global  by revenue, among which fifty-eight are central

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 , ,     



state-controlled national champions (apart from seven large financial institutions; the rest are under the supervision of China’s State-owned Assets Supervision and Administration Commission, hereafter SASAC). Orchestrated by state-led restructuring, each of these national champions occupies a leading position in China’s domestic markets in their respective business areas and many of them, such as CNOOC, Sinopec, China State Construction Engineering Corporation, COSCO, CITIC Group, Bank of China and Industrial & Commercial Bank of China, have started to build significant operations outside China, going increasingly global. This chapter examines the origin and evolution of China’s national champions industrial policy in the context of economic reforms. It reviews three key analytical perspectives on this issue: () the mainstream transition economics view; () the state capitalism view; and () the late industrialization and developmental state view. It then examines how state industrial policy has shaped the rise of China’s national champions in both the industrial and financial sectors. It shows that the central plank of China’s national champions industrial policy is to restructure the core assets and enterprise units of the socialist command economy into a batch of state-controlled corporations, business groups, and financial institutions viable in a predominantly market-oriented environment. China has chosen to reinvent the core of its ‘old structure’ by innovatively combining the existing bureaucratic institutions and resources with new governance forms and practices learnt from the advanced economies’ capital markets and big businesses. This process has involved continuous organizational learning and capability building at both government and enterprise levels and has led to some unique features of state‒business relations in China. The current governance regime of China’s national champions can be characterized as a networked hierarchy that interweaves multiple mechanisms of institutional bridging and reciprocal control. This chapter concludes by evaluating the position of China’s national champions in the global business system. It shows that despite their remarkable size and growth, China’s national champions are still at a relatively early stage of developing their international competitiveness.

. I P, B B,  C’ E R

.................................................................................................................................. The period since the early s has witnessed China’s persistent national champions industrial policy consolidating the core of China’s existing industrial ministries and financial system into a batch of large central state-controlled corporations, business groups, and financial institutions (Nolan, a, b; Sutherland, ; Li, ). However, until recently, this aspect of China’s industrial policy had been relatively overlooked by the mainstream literature on China’s economic reforms and industrial development. This section reviews three key analytical perspectives which provide

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

    

different frameworks to understand China’s national champions industrial policy and reforms: () the mainstream transition economics view; () the state capitalism view; () the late industrialization and developmental state view. They reflect different perspectives on the roles of industrial policy and big business in economic development and transition.

.. The Mainstream Transition Economics View Mainstream transition economics pays limited attention to the roles of oligopolistic big business in the economic and technical progress of advanced capitalist countries, tending to assume that countries grow prosperous through free markets and perfect competition. It interprets the ‘East Asian miracle’ primarily through the lens of market forces, getting the prices right and following comparative advantage (World Bank, ; Stiglitz, ; Nolan, a; Lin et al., ). Under Communist planning, China and the former USSR each had a small number of relatively large plants in many industrial sectors such as iron and steel, power equipment, aerospace, and defence industries, but neither had real modern multi-plant corporations with substantial vertical integration and diversification like Exxon Mobil, General Electric, and Siemens (Nolan, a; Shmelev and Popov, ; Popov, ; Popov, Chapter  in this volume). In advising on the industrial reforms of transition economies, mainstream economics focuses primarily on the privatization of individual plants and disregards the feasibility and desirability of merging and developing these plants to produce large, globally competitive multi-plant firms (Nolan, a, b). Consistent with the Washington Consensus, the ‘transition orthodoxy’ dismisses industrial policy as government-induced distortions that undermine market efficiency and fairness. National champions are typically viewed as either powerful interest groups influencing the government’s policymaking for their own benefit or the state’s instruments for achieving political goals, such as maintaining control and social stability. In the mainstream transition economics literature, China’s reforms are often characterized as ‘the retreat of the state, and the advance of the market’, their dominant logic described as the gradual establishment of a free and competitive private enterprise system by changing the government‒business relationship to one of an arm’s-length type (Tian and Liang, ; Qian, , ; Qian and Wu, ; Lin et al., ; Wu, ; Steinfeld, ). The key to understanding China’s rapid economic growth and industrial development during the reforms is, it is argued, China’s shift towards an industrial structure that reflects its comparative advantage. Small and medium-sized enterprises (SMEs) are regarded as the most dynamic part of China’s industrial economy (World Bank, ; Lin et al., ). In assessing China’s industrial policies of targeting the perceived ‘pillar industries’ and supporting selected large state-owned enterprises (SOEs) in the s, World Bank (: ) argues that ‘it is difficult to say what this policy really means’ and concludes that ‘it is quite likely they work at cross purposes and in unintended ways that distort development’. When China

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 , ,     



implemented the strategy of ‘grasping the large and letting go of the small’ in the late s and early s, the central government’s policy focus was on ‘grasping the large’, that is, concentrating resources and policy support on targeted large SOEs through the privatization of local small and medium-sized SOEs (Wang, ; Huang, ). However, neo-liberal analyses of China’s industrial reforms tend to focus exclusively on the ‘letting go of the small’ (Li, ). Around China’s WTO entry in , it was widely predicted that state‒business relations in the country would converge towards an arm’s-length type compatible with the norms of Western modern market economies and ‘unless privatized, the SOEs have no chance of surviving’ in market competition (Tian and Liang, : ; Qian and Wu, ). With regard to China’s state control over large SOEs, Qian () interpreted it as a second-best transitional arrangement which would soon be phased out as the market reforms deepen. It was argued that in the early stage of its development, China’s industrial economy should be based on small-scale, labour-intensive industries rather than using industrial policy to support the growth of big businesses in capital-intensive and technology-intensive industries (Lin et al., ; Lin and Chang, ). China’s industrial policymaking to support national champions is criticized as a departure from economic rationality and a symptom of the ‘partial reform traps’ that lead to capital misallocation and rent seeking (Steinfeld, ; Huang, ).

.. The State Capitalism View Recent studies on the rise of China’s ‘state capitalism’ or ‘state-led capitalism’, however, suggest that there have been fundamental changes in the nature of China’s industrial reforms since the early s. Some even argue there was a ‘great reversal’ of reforms as the state-controlled system regained the policy upper hand over the entrepreneurial private sector (Bremmer, ; Huang, , ). While earlier studies along these lines tend to label China as a unitary and yet only vaguely defined model of ‘state capitalism’, the recent political-economy literature has produced more nuanced perspectives and many important insights into the common features and sectoral variation in state control and regulation, corporate governance, ownership patterns, and managerial practices of China’s national champions (Lin and Milhaupt, ; Liebman and Milhaupt, ; Milhaupt, ; Milhaupt and Zheng, ; Naughton and Tsai, ). The focus of this ‘state capitalism’ literature is not on the aggregate ownership structure of China’s industrial system, but on the significance of China’s industrial policy, the development of a robust state sector in combination with a predominantly market-oriented economy and emerging capital markets, and in particular, the rise of China’s national champions during recent decades (Lin, ; Szamosszegi and Kyle, ; Naughton and Tsai, ; Lardy, ). The ‘state capitalism’ narratives emphasize that a crucial part of China’s industrial system has been evolving along a heterodox path defying the mainstream model of neo-liberal transition and institutional

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

    

convergence (Li, ). In particular, Pearson () argues that China’s economy has developed a hierarchical, three-tiered structure, with large state-controlled enterprises in strategic ‘commanding heights’ industries in the top tier. As China’s party-state becomes disengaged from direct management and ownership of enterprises in nonstrategic economic sectors, it has upgraded its interests and capability in developing national champions in strategic industries. Emphasizing the role of China’s central government, Lin () argues that China has been evolving towards ‘centrally managed capitalism’. There is now also a growing literature that analyses the central role of the Chinese Communist Party (CCP) in governing China’s national champions (Brødsgaard, ; Lin and Milhaupt, ; Liebman and Milhaupt, ; Li, , ; Leutert, a, b).

.. The Late Industrialization and Developmental State View The literature of late industrialization and the developmental state associates the degree of state intervention in industrialization with the level of backwardness as well as the timing and international environment for latecomers seeking to catch up with advanced industrial economies. Gerschenkron’s () backwardness thesis contends that the more backward a country is (vis-à-vis early developers), the more state-led its process of industrialization tends to be. The rise of the communist party-state and command economy in the USSR and China can be seen as extreme forms of state intervention to promote late industrialization. In the s, emulating the organizational structures of modern capitalist big businesses, the Soviet communist party had grouped major industrial enterprise units into a number of ‘trusts’. Then as the USSR pushed forward rapid industrialization through the First Five-Year Plan under Stalin, these ‘trusts’ were reorganized as various ministerial departments, absorbed by the party and state’s administrative hierarchies as the foundation of the Stalinist system of industrial ministries (Nove, ; Harrison and Markevich, ). Pursuing heavy industries-oriented catch-up, China developed similar institutional arrangements in the s and s (Lin et al., ; Wu, ; Li, ). The rapid industrialization of Japan and South Korea, with their extensive use of industrial policy, has provided a different paradigm from both the neo-liberal Washington Consensus and socialist central planning. Japan and South Korea have been considered quintessential examples of late development, in which the developmental state coordinated economic development through rational industrial policies designed and implemented by an elite bureaucracy (Johnson, ; Amsden, , ; Amsden and Singh, ; Chang, ; Kasza, ; Lee, Chapter  in this volume). The late industrialization and developmental state literature has emphasized the complex relations and crucial roles of the state and big business in modern economic development and technological innovation (Gerschenkron, ; Chandler, , ; Chandler et al., ; Nolan, a, b; Colpan et al., ). With economies

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 , ,     



of scale and scope, big businesses are ‘the fertile learning ground for technological, managerial, and organizational knowledge for an entire economy’ (Chandler et al., : ; Penrose, ). Lee et al. () have shown that big businesses have a significant and positive effect on economic growth and are positively associated with stability in economic growth. Many developing countries have fewer big businesses than predicted by their size and thus failed to escape the middle-income trap (Lee, ). Apart from responding to market failures (or institutional void), large business groups in developing countries can serve as the organizational device for economic catch-up under state activism (Lee, , ; Hahn and Lee, ; Khanna and Yafeh, ; Lee and Jin, ). In particular, large business groups in both Japan (kereitsus) and South Korea (chaebols) featured prominently in their economic miracles. Both Japanese and South Korean governments used various industrial policies to support their domestic big businesses to gain international competitiveness, including actively encouraging mergers between their leading indigenous firms in strategic industries, but they also encouraged oligopolistic rivalry to avoid monopoly, using exports and international market shares as the performance goals to evaluate big businesses supported by government policy (Amsden and Singh, ; Chang, ; Amsden, ; Nolan, a, b; Lee, Chapter  in this volume). China’s national champions industrial policy has drawn inspiration from nonmainstream economic theory and the policy practices of other late industrializing countries as well as from political considerations of nationalism and power (Nolan, a). In particular, it has been heavily influenced by selective policy learning from Japan and South Korea (Heilmann and Shih, ). As Nolan () pointed out in the s, it is conceivable that the communist party bureaucracy in China could adapt and be effectively transformed into a new type of developmental state. Rather than to ‘efficiently close much of the old structure’, an alternative approach for enterprise reform could be to learn from the industrial policies used by Japan and South Korea during their catch-up phase of growth, so the enterprise system built up under the command economy could be upgraded instead of demolished. Although it was largely overlooked in the World Bank’s policy prescriptions for transition economies, China has in effect adopted this heterodox approach over the past three decades (Nolan and Wang, ; Nolan, a, b; Sutherland, ; Li, ). There is now a growing literature of firm-level empirical studies examining China’s industrial policies and the performances of China’s national champions since the early s, such as the pioneering contributions of Nolan (a, b, , ) on the development of China’s national champions in multiple sectors; as well as a number of single-sector studies, including, for example, the petroleum and petrochemical industry (Zhang, , , ), the aerospace and aviation industry (Liu, ), the automobile industry (Sutherland, ; Lu and Feng, ; Thun, ), the shipbuilding industry (Moore, ), the coal mining industry (Nolan and Rui, ; Rui, ), the steel industry (Sun, , ; Nolan and Rui, ), and banking (Nolan, ). China’s industrial policy is broadly similar to those of Japan and South Korea in terms of performing the functions of stimulating investment and structural changes

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

    

with the development of large indigenous business groups under the guidance of an elite economic bureaucracy. However, China’s model also fundamentally differs from Japan and South Korea in several key aspects, especially in terms of direct state ownership and control, the institutional configuration of state bureaucracy, and the openness to foreign direct investment (FDI) (Naughton and Tsai, ). Moreover, China’s national champions are typically not as diversified across a range of industrial sectors as Japanese and South Korean business groups. They tend to be more vertically integrated, each focusing on a core sector, such as CNPC and Sinopec in oil and gas, ICBC in commercial banking, China Mobile in telecom, and CRRC Group in railway rolling-stock manufacturing (Nolan, a, b; Steinfeld, ; Lin and Milhaupt, ). Fierce competition in China’s domestic markets with high penetration by foreign multinational corporations tend to restrict excessive diversification of domestic firms (Lee and Woo, ). China’s central government has also directed that its national champions should focus on their core business areas rather than pursuing unrelated diversification (Li, ). Being less diversified, China’s national champions might be more vulnerable to firm-specific or sector-specific risks than Japanese kereitsus and Korean chaebols (Lee and Woo, ), but this is mitigated by common strategic state ownership in these national champions. From this perspective, China’s industrial policy has generated innovative features that adapt to its own specific political and economic conditions as well as a different international policy environment from that which Japan and South Korea encountered in their catch-up (Nolan and Wang, ).

. I P   R  C’ N C

.................................................................................................................................. China’s national champions industrial policy practices reflect its unorthodox approach of reforming its former central planning system and promoting industrial catch-up. The historical origin of China’s national champions can be traced back to the mids, when all large-scale industrial production and finance in Mainland China were consolidated into a handful of vertical administrative hierarchies led by the Chinese Communist Party bureaucracy. With decades of reform experiments, China has selectively imitated the governance forms, corporate structures, and practices of advanced industrial countries, and combined them with the existing institutional arrangements and resources in its bureaucratic structures. In particular, since the early s, a key goal of China’s industrial policy has been to nurture and consolidate selected large enterprise units into a number of modern large corporations and business groups as China’s ‘main force’ to catch up and compete with Western multinational big businesses. With continuous organizational learning and capability building at the levels of both government bureaucracy and enterprises, the core productive assets of China’s system of industrial ministries were transformed into a

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 , ,     



group of national champions under SASAC. Parallel restructuring has occurred in the state-controlled financial system which has given rise to a group of increasingly modernized, giant financial institutions as China’s national champions in finance.

.. The Rise of China’s National Champions in Industrial Sectors China’s policy experiment of restructuring the Stalinist system of central industrial ministries into certain forms of large multi-plant business organizations under the state’s control has a long history. It can be traced back to the early s when President Liu Shaoqi proposed that China should establish a number of giant national ‘corporate trusts’ (tuolasi) as socialist China’s counterparts of Western big businesses. In the s, the State Economic Commission (SEC) in China was tasked with studying how modern big businesses were organized in advanced industrial countries such as the United States, the United Kingdom, France, and Japan, notably including some relatively detailed analyses of General Electric and Westinghouse Electric, as well as earlier Soviet practices under Lenin. While this policy approach was halted by political campaigns launched by Chairman Mao, the long-term impact of this essential idea recurred in different forms. In the s, China had two competing industrial policy approaches. On the one hand, China established a set of large central state-controlled zonggongsi (literally translated as ‘general corporation’), such as Sinopec, as national administrative corporations to emulate Western big businesses. On the other hand, the dominant approach of industrial reforms promoted decentralization and enhancing ‘enterprise autonomy’ for individual plants. Many large industrial plants or enterprise units previously controlled by central industrial ministries were transferred to local governments (primarily at the levels of provinces and cities). Challenged by decentralization reforms, some industry-wide zonggongsi were dissolved, while others devolved managerial authority to their subordinate plants, with varied outcomes across sectors (Li, , ). Since the early s, however, industry policy of nurturing national champions has been a high priority endorsed with strong political commitments by China’s leadership. Building a number of central state-controlled oligopolistic big businesses in the form of large corporations and large business groups has been at the core of China’s industrial policymaking over the past three decades. These national champions are supposed not only to dominate the ‘commanding heights’ of China’s national economy, but also to gradually develop international competitiveness. Indeed, as China deepens its integration with the global economy, domestic industrial consolidation is regarded as imperative for national champions to survive and compete in international markets (Nolan, a, b; Sutherland, ; Li, ; Naughton, ). This policy logic is illustrated by the following quote from Wu Bangguo, former vice premier of China’s State Council in charge of industrial reforms in the late s and early s:

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

    

In our world today, economic competition among nations is in fact among each nation’s large enterprises and business groups. A nation’s economic might is concentrated and manifested in the economic power and international competitiveness of its large enterprises and business groups . . . the United States, for example, relies on General Motors, Boeing, Du Pont and a batch of other multinational corporations. Japan relies on its six large business groups and Korea relies on its ten large commercial conglomerates. In the same way now and in the next century our nation’s position in the international economic order will be to a large extent determined by the position of our nation’s large enterprises and business groups . . . If we let our strong large-scale enterprises and business groups all fight alone, everyone will still find it difficult in the ever-intensifying domestic and international competition to compete on equal terms with large international companies. We must therefore unite and rise together, develop economies of scale and scope and nurture a ‘national team’ capable of entering the world’s top . (Jingji Ribao,  January , quoted from IIECASS, : )

During this period, instead of creating industry-wide monopolies or pursuing comprehensive decentralization, China’s central government selected the core productive assets and enterprise units in sectors perceived as strategic, carved them out from their respective ministries, consolidated them into large central state-controlled corporate groups, and promoted oligopolistic rivalries between them. Those assets and enterprise units deemed outside this category were decentralized and privatized as the reforms proceeded. For example, the Ministry of Electricity Industry in China was first reorganized into the State Electricity Industry Corporation as an industry-wide zonggongsi, then split up into separate corporate groups; the ministries of coal, chemicals, machinery, and metallurgy industries were downgraded to state bureaus and later reorganized as industrial associations; the Ministry of Post & Telecommunications and Ministry of Electronics Industry were merged. All of them had their selected core assets carved out and reorganized as large corporate groups (Li, ). By , most of the key large designated ‘backbone’ state enterprise units in China’s system of central industrial ministries had been carved out and consolidated into  large central state-controlled business groups. They constitute China’s ‘national team’ in industrial sectors. SASAC was established to exercise state ownership and supervise these business groups on behalf of the party and state. Far from being a passive shareholder, SASAC has actively shaped the strategies and structures of its subordinate big businesses. As stated by Li Rongrong, head of SASAC between  and , the goal of SASAC is that ‘China must nurture its own multinationals to challenge the dominance of foreign corporations’ and SASAC was to ‘vigorously pursue a strategy of creating major corporate conglomerates’ and ‘accelerate the strategic adjustment of China’s economic structure’ (Buckley, ). Without taking the boundaries of its subordinate firms as given, SASAC directed that the business groups under its supervision should be consolidated into eighty to one hundred competitive big businesses in targeted strategic industries, among which thirty to fifty were supposed to become large corporate groups with strong international competitiveness (SASAC, ).

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 , ,     



As Naughton () commented, ‘increasingly, the SASAC formulates its agenda in terms that a Wall Street investment bank would understand’; under SASAC’s supervision, each of these large business groups were supposed to become No. , , or  in the markets of its core business areas, or it would be discarded through state-directed mergers, acquisitions, or even outright bankruptcy. Guided by this overarching policy goal, SASAC has initiated comprehensive reform programmes to restructure and strengthen the national team. At the industry level, it has clarified the definition of strategic industries targeted by the state to maintain control. According to SASAC’s designation, central state-controlled business groups should operate in three categories of sectors: () key industries concerning national security and the lifeline of the national economy; () basic and pillar industries; and () other targeted industries. The first category of key industries comprises seven sectors: defence, power generation and distribution, oil and gas and petrochemicals, telecommunications, coal, aviation, and shipping. The state maintains absolute control over these sectors, promoting a number of large ‘backbone’ firms within them as first-class global companies (Li, ). At the firm level, transforming traditional state-owned enterprises into corporations is at the core of SASAC’s policy agenda. Corporatization clarifies the relations between owners and managers, the scope of managerial authority and responsibility, and incentive mechanisms (Naughton, ). Establishing modern corporate governance structures and listing their minority stakes in stock markets is critical for the rise of China’s national champions, with the government filtering potential candidates for public listing on domestic and international stock markets and prioritizing the needs of targeted large ‘key’ enterprises. In particular, the late s saw the rise of international stock market listings for China’s central state-controlled corporate groups carved out from various industrial ministries or the State Council. The pioneering deals included the initial public offerings (IPOs) of China Mobile, PetroChina (the listing company of CNPC), and Sinopec. Each of these companies took over a large chunk of industrial assets and enterprise units previously managed under their old industrial ministries. It was these international listings that started to bring China’s emerging ‘national team’ onto the global stage. Since its establishment, SASAC has been a major force shaping the use of stock markets to support national champions. The listing strategy preferred by SASAC is the holistic IPO, which corporatizes each entire business group as a whole and lists its minority stakes, rather than separately listing the subsidiary enterprise units of the larger business group. For example, China Railway Group as a whole listed a minority stake of  per cent in Shanghai and Hong Kong stock markets for RMB. billion in ; China State Construction Engineering Corporation as a whole listed a minority stake of  per cent in Shanghai for around RMB. billion in . After their IPOs, national champions can raise further capital through various secondary offerings and refinancing without diluting the central government’s corporate control (Walter and Howie, , ; Li, ). Under its industrial targeting framework, SASAC has led several rounds of industrial restructuring and consolidation. Most of China’s national champions started as relatively loosely amalgamated groupings. With a core ‘parent company’ serving as the

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

    

group’s headquarters, each group incorporated many ‘son companies’, ‘grandson companies’, and even ‘great-grandson companies’ engaged in a wide spectrum of disparate business activities, many of which have nothing to do with the group’s designated core business areas. While diversification might be profitable from the perspective of the individual group, from the central government’s point of view it was considered detrimental to the overall goal of strengthening China’s ‘national team’. To rein in ‘undisciplined’ diversification, SASAC has designated ‘core businesses’ for each of the national champions. The approach of SASAC is to consolidate national champions’ designated core businesses, gradually spinning off their existing non-core businesses and discouraging new investments in non-core business areas. To achieve this goal, SASAC strengthened its supervision of national champions’ investment management process and required them to obtain its approval before making substantial investments in non-core business areas. It also pushed national champions to streamline their internal management hierarchies and improve their core competences in the designated key business areas. To strengthen the international competitiveness of China’s ‘national team’ as a whole, SASAC has conducted a series of mergers and consolidation programmes among China’s national champions. For instance, SASAC consolidated China’s aviation industry in  with the merger of the Aviation Industry Corporation of China I and II. Over the past decade, SASAC has consolidated a variety of sectors including transportation infrastructure, machinery building, energy, steel and non-ferrous metallurgy industries, with the rate of state-led mergers accelerating in recent years. For example, in , SASAC merged CNR Group and CSR Group into CRRC, which has overtaken Alstom and Siemens to become the world’s largest manufacturer of railway equipment. In , SASAC merged Baosteel Group and Wuhan Iron & Steel Group to create the second-largest steel producer in the world. In , it further merged China Guodian Corporation and Shenhua Group into China Energy Investment Corporation (China Energy), forming the world’s largest producer of coal, thermal power, wind power, coal-to-liquid fuels and coal chemicals. The guiding principle of SASAC-led restructuring is to transform the national team into a small number of large corporations and business groups capable of dominating their core business areas in the domestic markets and competing against top incumbent multinationals in their respective industries. By the end of , the original  business groups under SASAC had been restructured and consolidated into ninety-six groups. Between  and , the total assets of these business groups under SASAC increased from RMB. trillion to . trillion, growing around  per cent per annum on average. Their combined revenues and profits increased from RMB. trillion and . trillion in  to RMB. trillion and . trillion respectively in . The total taxes they paid to the state also grew from RMB. trillion to over  trillion during this period (SASAC, , ). Occupying the ‘commanding heights’ of China’s strategic sectors such as oil and gas, power generation, telecommunications, aerospace, aviation, automobile, mining, airlines, and nuclear, these business groups are a key pillar of China’s industrial economy.

OUP CORRECTED PROOF – FINAL, 21/9/2020, SPi

 , ,     



.. The Rise of China’s National Champions in Finance Between the s and the s, China’s financial system was organized as a ‘monobank’ that amounted to no more than a bureaucratic appendage of China’s Ministry of Finance. Driven by a combination of market-oriented reforms and industrial policies since the s, China has now developed a complex network of financial institutions, with a handful of large state-controlled commercial and policy banks, asset management companies, and insurance companies, and two stock exchanges at the apex of the system. China’s financial reforms have given rise to its national champions in finance, which also sustain critical support for the reforms and growth of the industrial-sector national champions as they channel financial resources to support the targeted firms. The focus of China’s financial reforms in the s was to deal with the soft-budget constraints and moral hazard inherent in China’s enterprise system. The reforms aimed at carving out financial institutions from the government bureaucracy and providing them with more operational autonomy. In particular, China established three new state-owned policy banks: China Development Bank, the Export-Import Bank of China, and Agriculture Development Bank of China. The idea was to reduce the policy burdens facing China’s large commercial banks by spinning off their policy loan responsibilities to the three new policy banks. However, this separation of policy banks and commercial banks did not reduce the importance of large commercial banks in China’s industrial policy. While China Development Bank and the Export-Import Bank of China have played increasingly important roles in financing targeted large enterprises, large commercial banks have consistently been the chief source of funding for China’s industrial restructuring and large state-owned enterprises reform. In particular, between  and , the five largest commercial banks generated well over RMB billion of non-performing loans to their SOE clients. The accumulation of these non-performing loans was partly due to inefficiency and lax internal control within these banks, as well as interference by various levels of local government, but also due to absorbing the costs of implementing the central government’s industrial policy (Li, ). In the context of the Asian financial crisis and China’s entry into the WTO, it became increasingly clear that China’s commercial banks had profound weaknesses. With massive non-performing loans, weak risk management, backward technologies and operational mechanisms, together with deeply problematic corporate governance, their prospects of competing with the giant global banks on the ‘global level playing field’ of the WTO were bleak (Nolan, ). In the late s, China’s central government implemented major banking reforms to mitigate financial-sector fragility and improve the competitiveness of its large commercial banks. The state arranged a massive capital injection of RMB billion into the four largest state-owned commercial banks (Yi, ). By spinning off staff from the commercial banks, China Orient, Cinda, Great Wall, and Huarong were established in  as the ‘Big Four’ asset management companies (AMCs) under the Ministry of Finance. Funded by the

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

    

Ministry of Finance (MoF) and the People’s Bank of China, they took on around RMB. trillion of problematic assets at face value from the China Construction Bank (CCB), Bank of China (BOC), Industrial and Commercial Bank of China (ICBC), Agriculture Bank of China (ABC), and China Development Bank (CDB) in –. While these asset acquisitions cleaned up the big banks’ balance sheets, they fell short of significantly strengthening their risk-management capabilities. Indeed, as their lending grew in subsequent years, non-performing loans rapidly accumulated again to reach a staggering level of around RMB. trillion by the end of . This made the big banks vulnerable against the backdrop of China’s WTO entry, as China was expected to open its financial services sector to foreign financial institutions after . Following intense policy debates in ‒, China announced the goal of developing ‘internationally competitive modern financial enterprises’ and decided to continue to restrict the roles of foreign financial institutions in China, limiting their permitted ownership shares in China’s indigenous financial institutions. China’s central government also decided not to split up the large state-owned commercial banks, but to reform them as ‘complete corporate entities’. This entailed further removals of non-performing loans; creating a strategic partnership with leading global banks to facilitate learning; investing heavily in advanced information technology; upgrading their risk management, human resources, and operational mechanisms; and eventually floating their minority shares on international and domestic stock markets. To implement this strategy, China’s central government established the Central Huijin Investment Corporation in  as the key organizational vehicle to facilitate the reform of targeted financial institutions. The Big Four AMCs were directed to acquire a second batch of non-performing loans between  and  from big commercial banks, totalling around RMB. trillion (Walter and Howie, ). The MoF also stepped in directly and made an innovative arrangement establishing ‘co-managed funds’ with ICBC and ABC respectively in  and . Funded by the issue of MoF debts, the central government further offloaded around RMB billon of non-performing loans from ICBC and ABC into the comanaged funds. By , China’s five largest commercial banks had all completed their public listings in Shanghai and Hong Kong Stock Exchanges. All but ABC had introduced leading global financial institutions as foreign ‘strategic investors’ to acquire some portions of their minority stakes. Public listings on stock markets exposed these banks to the scrutiny of global investors and provided them with market-based capital-raising channels and discipline (Pan, ; Nolan, ). While these public listings amount to partial privatization, China’s central government has maintained absolute majority ownership after their IPOs; it remains the single largest shareholder in all of the five largest commercial banks and still fully owns the three policy banks. During the restructuring process, China’s central government prohibited foreign financial institutions from acquiring control of any major domestic financial institutions in China. Global banks such as Citigroup and HSBC had to build up their own branch networks step by step in China. By , when all the five largest state-controlled commercial banks had completed their public listings, foreign banks only accounted for around  per cent of China’s total financial assets (Walter and Howie, ; Nolan, ;

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 , ,     



Li, ). Over the past decade, China’s national champion banks have ranked among the global top banks in terms of revenue, profits, market capitalization, and capital adequacy ratios, while the market shares of foreign banks remain negligible in China despite the fact that China’s government has removed many of its policy restrictions. Guided by the state’s industrial policy, there has been close strategic cooperation between China’s national champions in industrial sectors and in finance. Large statecontrolled banks were crucial in channelling credit to support corporate restructuring in the industrial sectors. For example, in the s, inspired by the Japanese experience, China’s central government designated ‘main banks’ to guarantee credit supply to  (later expanded to ) key enterprises. In the early s, the central government approved extensive debt/equity swaps for central state-owned business groups, with a total of around RMB billion in debts owed to big banks converted into equities held by the Big Four AMCs and China Development Bank, which profoundly relieved the financial burdens facing those enterprises (SASAC, : ). Guided by the industrial policy to upgrade China’s aircraft industry, Aviation Industry Corporation of China (AVIC) established various strategic partnership agreements with China’s banking champions, gaining RMB billion in credit lines from them in . Commercial Aircraft Corporation of China (COMAC) received over RMB billion in credit-line support from these banks by  (Li, ). Both state-controlled commercial banks and policy banks have played crucial roles in financing the overseas business growth of China’s industrial national champions. For example, China Development Bank and the Export-Import Bank of China are the most important strategic partners of China’s oil national champions (Sinopec, CNPC, and CNOOC) in their efforts to secure long-term supplies of oil and gas overseas, with various ‘loan for oil’ and ‘loan for gas’ deals with countries such as Turkmenistan, Kazakhstan, Ghana, Venezuela, Brazil, and Russia totalling around US$ billion (Jiang and Sinton, ; Downs, ; Jiang and Ding, ; Zhang, ).

. S‒B R   G  C’ N C

.................................................................................................................................. As shown earlier in the chapter, the central plank of China’s national champions industrial policy is to transform the core assets and enterprise units of the former command economy into large state-controlled corporations and business groups that are competitive in a predominantly market-oriented environment. Rather than ‘efficiently closing much of the old structure’, China has chosen to reinvent the core of its old industrial structure. This process has taken advantage of the existing institutions and resources of the party-state, and has innovatively combined them with new

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

    

institutional elements, governance forms and practices learnt from advanced economies. It involves continuous capability building, learning, and organizational changes at both the government and enterprise levels, which have also led to some special features of state‒business relations in China.

.. Government Capability and Learning In the s and s, the ‘transition orthodoxy’ focused on excluding communist bureaucrats from participating in the reforms of transition economies. It was argued that ‘the collapse of communist one-party rule was the sine qua non for an effective transition to a market economy’; ‘it is naïve to think of existing bureaucracy as equipped, professionally and temperamentally, to implement sophisticated policies based on Western-style theories of the “second best”’; and ‘the bureaucracy cannot be relied upon for efficiency in regulating monopoly prices, promoting infant industries, or implementing industrial policy’ (Lipton and Sachs, : –). In China, however, industrial reforms have been consistently led by the existing communist party bureaucracy with emphases on organizational learning and capability building to implement industrial policy. Following Deng Xiaoping’s cadre modernization scheme, the educational level and technical competence of China’s communist party cadres and economic bureaucrats has improved dramatically since the s (Lee, ; Li, ; Zheng, , ). Large state-owned enterprises and central industrial ministries also served as a major reservoir from which the Party could draw its top leadership talent. China’s industrial policymaking primarily reflects the training, work experience, and ideological outlook of these elite cadre-bureaucrats. From industrial ministries to modern big businesses, the transformation of organizational forms, coordination mechanisms, and personnel roles undoubtedly requires the acquisition of new knowledge, skills, capabilities, and behaviours. As China’s State Council put it, ‘to restructure government administrative ministries into firm-like economic organizations is a vital experiment for the economic system reform, and we need a process of exploration and learning’ (The State Council, ). Over the past four decades, China’s central government has undertaken multiple rounds of administrative reforms to streamline and upgrade the bureaucracy’s capabilities and mitigate coordination failures, creating new pivotal agencies such as SASAC and MIIT (Ministry of Industry and Information Technology) to strengthen its industrial policy practices with increasingly professionalized, efficient, and focused modes of intervention (Pearson, ; Jung, ; Naughton and Tsai, ). Using SASAC and Central Huijin as its key vehicles, China’s central government has also learnt to increasingly use financialized means of managing assets and governing its national champions (Wang, ). In particular, the stock markets have been used as key industrial policy instruments to nurture national champions (Walter and Howie,

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 , ,     



, ). The Chinese Communist Party also upgraded its cadre training and personnel management system as national champions became corporatized and listed in stock markets (Brødsgaard, ; Li, ).

.. Enterprise Capability and Learning Developing countries typically suffer from firm-level capability failure and size failure (Lee, ). It is difficult for them to generate indigenous firms with sufficient research and development (R&D) or technological capabilities and of sufficient size to achieve economies of scale. Under the traditional industrial ministries system, the very definition of ‘firm’ or ‘enterprise’ was ambiguous in China. Between the s and s, most of the ‘large state enterprises’ were merely large-sized individual plants (or projects, factories, mines, and research institutes, etc.) which had no distinct organizational boundaries from their governing industrial ministries and corresponded only to the lowest levels of production entity in a typical modern big business in an advanced industrial economy (Komiya, a, b; Nolan, , a, b). The coordination of these state enterprises’ activities was fragmented among various government bureaucratic agencies. They hardly qualify as autonomous organizations of production, let alone fully fledged business firms. China’s corporatization reforms and state-led restructuring to create national champions have involved a crucial learning process about how to define the boundaries of firms and to develop organizational capabilities at the level of large multi-plant firms and business groups. In particular, the corporatization and initial public offerings of China Mobile, Sinopec, and CNPC on the eve of China’s WTO entry demonstrated the feasibility of China consolidating core assets and enterprise units of traditional industrial ministries into giant corporate groups in a relatively short period of time (Zhang, , ). Guided by this approach, the state-controlled corporate groups and listed companies became the new units and organizational devices of firm-level catch-up. Similarly, China’s banking sector restructuring was also designed to promote organizational learning and capability building at the level of large nationwide banks. Overall, listing the minority stakes of China’s national champions in stock markets is not just about raising capital, but more about absorbing modern corporate governance practices, management structures and market-based disciplinary mechanisms, and creating partnership with international banks, law firms, auditors, accountants, regulators, and institutional investors to facilitate such learning. The strategies employed by China’s industrial policymakers and national champions thus involve building linkages with incumbent multinational corporations and global capital markets, targeting resources for leverage which are imitable and transferable, and enhancing organizational learning to catch up (Matthews, ). Starting from relatively loose amalgamations of enterprise units carved out from former bureaucratic hierarchies, these business groups and financial institutions have gradually become fully fledged modern

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

    

firms, with coherent corporate structures coordinating and performing various business functions including strategic planning, operations, financing, procurement, marketing and sales, human resources, and inhouse R&D.

.. Networked Hierarchy, Institutional Bridging, and Reciprocal Control The governance of China’s national champions in industrial sectors is embedded in a complex organizational architecture, which can be seen as a gigantic pyramid. With the Party centre and the State Council at the apex, tiers of national champions are organized under the central government and strategically linked to each other (Naughton, ). Lin and Milhaupt () proposed the notions of networked hierarchy and institutional bridging to characterize China’s unique model of industrial organization: a hierarchical system in terms of state ownership and control, the formulation and implementation of industrial policy, and the internal structures of these firms. China’s industrial national champions are typically vertically integrated groups with multiple layers of member enterprise units linked by ownership arrangements (typically including a parent holding company, one or a few core publicly listed subsidiaries, some internal research institutes and finance companies and several tiers of operational enterprise units). SASAC exercises shareholder’s rights on behalf of the state, but its control rights are incomplete as the Party maintains ultimate control of key corporate appointments (such as chairman and CEO) in these firms (Brødsgaard, ; Li, ). A dense structure of inter-organizational networks connects firms with the Party and various government agencies as well as other firms. These institutional bridging networks facilitate the flow of information, collaboration, and relationship building in the system (Lin and Milhaupt, ; Li, ). The governance regime of China’s national champions in finance shares similar features, with the Ministry of Finance and Central Huijin as the most important shareholders, and the Party retains control over key personnel appointments in major state-owned commercial banks, policy banks, insurance companies, asset management companies, and stock exchanges (Heilmann, ; Pistor, ; Pistor et al., ). The Chinese Communist Party’s nomenklatura control and personnel management system are crucial in the governance of China’s national champions. The Party controls the appointments and career prospects of top-level corporate leaders in national champions as well as key officials in SASAC, MoF, and all financial regulators. It aims to establish a meritocratic system to identify and promote cadres with both strong political loyalty and professional competence. It often rotates and transfers cadres among different national champions, regulatory agencies, and even local government leadership positions. Candidates for key leadership positions in the few dozen most important national champions are groomed and monitored directly by the Party’s Central Organization Department (COD) (Lin, ; Brødsgaard, ; Pistor, ;

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 , ,     



Li, , ; Leutert, a, b). These appointments concern not only each specific national champion, but also the needs of the system as a whole. It is often the case that a key change of personnel will call for, and be accompanied by, a series of top personnel reshuffles, involving multiple institutional units apparently independent of each other. Like the former central industrial ministries, China’s national champions have served as a talent pool for the Party to recruit its top political elites and a pathway for ambitious cadres to advance their political careers (Li, ; Lin, ). These linkages tend to generate what Lin (: ) calls ‘synchronized incentives and mobility’: top personnel are motivated by both political and professional achievement, and can be moved back and forth across political hierarchy and state-controlled corporate hierarchy under the Party’s personnel management system. Lin and Milhaupt () argue that this structure amounts to an ‘encompassing organization’ and policy coalition whose members have an incentive to promote the prosperity of the overall system (Olson, ). A core policy challenge of late industrialization is how to exert discipline over the interactions between the state and firms. The market paradigm relies on competitive market structures and creative destruction induced by technological changes serving as disciplinary forces, while the command economy paradigm relies on direct state planning and monitoring, which is typically characterized by soft budget constraints. Successful industrial policies typically have mechanisms to establish certain forms of reciprocal control in state‒business relations, with performance standards and disciplinary conditions attached to the state support that firms receive (Amsden, ). The rise of China’s national champions has relied on extensive state supports such as subsidies, domestic market protection, preferential access to finance, state-orchestrated mergers, and bailouts. How to strengthen financial discipline and harden budget constraints has been a critical policy challenge. Over the past three decades, China has gradually developed its own approach to reciprocal control in governing its national champions. First, it builds on the Party’s personnel management and disciplinary system to shape competition for promotion among cadres (Lin, ; Brødsgaard, ; Pistor, ; Li, , ). Second, while erecting high entry barriers and nurturing the rise of giant business groups in strategic sectors, China’s central government has promoted oligopolistic rivalries among national champions and encouraged them to compete in international markets, although export competitiveness is not a key performance criterion. Moreover, China has developed and increasingly resorted to various financialized policy tools and channels to impose discipline, creating the unique structure of a ‘shareholding state’ (Wang, ). On the one hand, the corporatization and public listings of national champions have rendered these firms increasingly sensitive to shareholder value. As a controlling shareholder, SASAC has developed a sophisticated performance evaluation system for national champions, setting various benchmarks and targets with an array of indicators such as profits, economic value added, technical progress, return on equity, return on asset, leverage ratios, and corporate social responsibility, and factoring in the different industrial environments within which different national champions operate. In

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

    

some respects, the relations between SASAC and national champions now resemble the ways private equity funds manage their portfolio companies. On the other hand, the restructuring of China’s banking sector has also made its large state-controlled commercial banks more effective disciplinarians. These banks now face strong pressure from the central government (as the controlling shareholder) to create shareholder value, strict capital adequacy regulatory requirements consistent with global standards and more robust internal risk management systems. Between  and , China’s central government had offloaded a total of around RMB trillion non-performing loans from the big banks through various vehicles of the People’s Bank of China, MoF, and the Big Four AMCs. While the big banks were recapitalized by the state with the MoF issuing new government bonds to fund the restructuring, they were required to pay out sufficient dividends from their profits in the subsequent years for the MoF to pay off the bonds. This imposes additional discipline on banks’ operational performance. Overall, China’s Ministry of Finance has been a fairly prudent ‘gatekeeper’ and disciplinarian during the industrial and banking reforms of the past two decades (Walter and Howie, ; Pan, ; Jiang, ). However, it remains too early for China to declare success in developing an effective system of governing China’s national champions. The Party’s personnel management and cadre disciplinary system is prone to complex principal‒agent problems, often intertwined with cronyism and factionalism. Given the informational constraints, it is difficult for the Party to rely on personnel control to effectively monitor and discipline politically well-connected business leaders who possess substantial managerial autonomy in daily business operations. As the recent anti-corruption campaigns reveal, corruption in China’s national champions often involves hidden political networks stretching across the Party and government hierarchy (Brødsgaard, ; Li, ). SASAC’s ownership control rights are also incomplete and it faces strong resistance from the national champions (Naughton, ). To what extent and how China’s big banks and capital markets can impose effective discipline remains an open question as the Chinese economy shifts to a ‘new normal’ of slower growth and China’s financial system further liberalizes. Above all, industrial policy is a highly politicized process of resource allocation, creating winners and losers with different interests and political voices. Now China’s national champions industrial policy is facing increasing criticisms and external pressure from international organizations and Western advanced countries (World Bank, ; Wu, ).

. I C  C’ N C

.................................................................................................................................. Over the past four decades, as China has deepened its reform and opening up, the business systems of the advanced countries have also experienced profound

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 , ,     



restructuring which was arguably no less revolutionary than the rise of modern big businesses during the late nineteenth and early twentieth century (Nolan, a, b; Steinfeld, ; Nolan, ). The rise of giant global firms, the emergence of big-business-centred production networks and the explosion of mergers and acquisitions dramatically reshaped the landscape of global business competition. The commanding heights of the global business system were almost entirely occupied by firms from high-income countries with superior technologies and powerful brands. These constituted the ‘system integrators’ at the apex of global value chains. As they consolidated their leading positions, the system integrator firms, with enormous procurement expenditures, exerted intense pressures on their supply chains to minimize costs and stimulate technical progress. This established the global context within which China’s central government designed and practised its national champions industrial policy (Nolan, a, b; Zhang, ; Nolan, et al., ; Nolan, , ). While giant multinational companies headquartered in advanced economies have increasingly penetrated the Chinese economy since China’s WTO entry, China’s national champions still occupy the apex of China’s strategic sectors. They have built up corporate structures that increasingly resemble the global leading big businesses of their respective industries. They have developed significant technological capabilities and well-trained, sophisticated managerial leadership, floated their minority shares on domestic and international stock markets, established joint ventures or strategic partnerships with global leading big businesses, and achieved a scale unprecedented in China’s business history (Nolan, ; Li, ). In , there were only a total of forty-three Mainland Chinese firms in the Fortune Global , among which thirtyeight were central state-controlled national champions. By , however, the number had increased to . Among them, fifty-eight were national champions which generated a total of US$. trillion combined revenue and US$ billion combined profit in / (Table .). Among the best performing were ICBC whose profits alone reached US$. billion, roughly equivalent to the combined profits of JP Morgan Chase and Bank of America; China Mobile’s profits reached over US$. billion, compared with US$. billion for Softbank and US$. billion for Deutsche Telekom. China’s State Grid, Sinopec, and CNPC all ranked among the world’s five largest energy companies by revenue. Among the world’s ten largest aerospace and defence companies, five are China’s national champions: China North Industries Group, AVIC, China South Industries Group, China Aerospace Science and Technology Corporation, and China Aerospace Science and Industry Corporation. Among the world’s ten largest engineering and construction companies, there are also five Chinese national champions: China State Construction Engineering, China Railway Engineering Group, China Railway Construction, China Communications Construction, and PowerChina. However, China’s national champions overall are still far from catching up with the global leading big businesses in terms of international competitiveness. Most of China’s national champions’ sales and profits come from China’s domestic markets where they still enjoy varying degrees of protection by the state’s industrial policies against competitive pressures from both foreign multinational companies and domestic

OUP CORRECTED PROOF – FINAL, 21/9/2020, SPi



    

Table 25.1 China’s National Champions in Fortune Global 500, 2018 Ranking Company Name

2 3 4 23

26 31 40 42 46 53 56 58 65 86 87 91

98 101 109 110 113 117 122 125 140 141 149 161 162 167

State Grid Corporation of China (SGCC) Sinopec Group China National Petroleum Corporation (CNPC) China State Construction Engineering Corporation (CSCES) Industrial & Commercial Bank of China China Construction Bank Agricultural Bank of China China Life Insurance Bank of China China Mobile China Railway Group (CRECG) China Railway Construction Corporation (CRCC) Dongfeng Motor Corporation China Resources Group China National Offshore Oil Corporation (CNOOC) China Communications Construction Company (CCCC) Sinochem Group China Energy Investment Corporation (CHN Energy) China Minmetals Corporation China Southern Power Grid (CSG) China Post Group The People’s Insurance Company of China (PICC) COFCO Group China FAW Group China North Industries (Norinco Group) China Telecommunications CITIC Group Aviation Industry Corporation of China (AVIC) China Bauwu Steel Group China National Chemicals Corporation (ChemChina)

Revenue (million US$)

Profit (million US$)

Core business

3,48,903

9,533

Power grid

3,26,953 3,26,008

1,538 691

Petroleum and petrochemicals Petroleum and natural gas

1,56,071

2,675

Construction engineering

1,53,021

42,324

Banking

1,38,594 1,22,366 1,20,224 1,15,423 1,10,159 1,02,767

35,845 28,550 267 25,509 10,932 1,170

1,00,855

1,309

93,294 82,184 81,482

1,400 3,152 3,019

Banking Banking Insurance Banking Telecom Infrastructure construction & equipment manufacturing Infrastructure construction & equipment manufacturing Automobile Diversified Petroleum and natural gas

79,417

1,545

Infrastructure construction & equipment manufacturing

76,765 75,522

753 2,495

Energy and chemicals Energy and chemicals

72,997 72,787

211 1,938

Metallic minerals Power Grid

72,197 71,579

4,961 2,382

Postal service and logistics Insurance

69,669 69,524 64,646

394 2,856 858

Diversified Automobile Defence

63,974 61,316 59,263

1,820 3,225 363

Telecom Diversified Aviation and defence

59,255 57,989

22 739

Steel Chemicals

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 , ,     

168 182 194 222 242 243 245 256 273 280 289 312 322 333 335 343 346 369 371 381 385 388 393 395 397 428 465 468

Bank of Communications Power Construction Corporation of China (PowerChina) China National Pharmaceutical Group (Sinopharm) Aluminum Corporation of China (Chalco) China South Industries Group China National Building Material Group (CNBM) China Shipbuilding Industry Corporation (CSIC) Sinomach Group China United Network Communications China Merchants Group China Huaneng Group China Poly Group China Everbright Group China Energy Engineering Group (Energy China) China Cosco Shipping Corporation China Aerospace Science & Technology Corporation China Aerospace Science & Industry Corporation China Electronics Group China National Aviation Fuel Group (CNAF) Xinxing Cathay International (XXCIG) CRRC Corporation China Electronic Technology Group Corporation (CETC) China State Shipbuilding Corporation Limited (CSSC) State Power Investment Corporation (SPIC) China Huadian Corporation Ansteel Group China Taiping Insurance Group China Datang Corporation

Source: Fortune Global 500 (2018).

57,711 53,870

10,390 947

Banking Energy and infrastructure

51,844

690

Healthcare

46,684

429

Aluminium

44,785 44,701

740 15

Defence and automobile Building materials

44,431

716

Shipbuilding

42,638 40,664

472 63

Machinery Manufacturing Telecom

39,971 38,872 37,002 35,840 35,048

4,039 216 1,153 1,895 372

Diversified Power generation Diversified Diversified Energy engineering

34,668

1,404

Shipping and logistics

34,254

2,225

Aerospace

34,073

1,607

Aerospace

31,990 31,942

167 402

Electronics Aviation fuel

31,078

440

Diversified

30,634 30,176

1,598 1,774

29,797

371

Shipbuilding

29,727

199

Power Generation

29,612 27,792 25,598 25,299

333 61 449 342

Power Generation Steel Insurance Power Generation

Rail Transit Equipment Electronics



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

    

challengers. In particular, they benefit from government procurements and buying products from each other. The profitability of China’s national team is highly concentrated and sensitive to government regulatory and price policies (Nolan, ; Naughton, ; Li, ). Apart from their remarkable success in building infrastructure in developing countries, the export competitiveness of China’s national champions remains limited. In terms of foreign investment, despite being supported by the ‘going out’ strategy of China’s central government, China’s national champions are still at an early stage of international expansion. In , there were only two Mainland Chinese firms (both are national champions under SASAC) in the world’s top  non-financial multinational enterprises ranked by foreign assets: CNOOC and COSCO. CNOOC had a total of US$. billion foreign assets, less than  per cent of Royal Dutch Shell’s foreign assets. In , China’s total outward FDI stock was less than the combined foreign assets of five top multinational companies from the advanced countries (Royal Dutch Shell, Toyota, BP, Total, and Anheuser-Busch InBev) (UNCTAD, ). Moreover, China’s national champions face tremendous barriers in conducting major crossborder mergers and acquisitions. Their attempts to gain control over established firms in high-income countries have often ended in failure. Even their efforts to acquire substantial minority stakes have encountered formidable political and regulatory resistance from high-income countries (Nolan, ; Naughton, ; Wu, ; Gordon and Milhaupt, ). While China’s five largest commercial banks have expanded their international operations through a combination of organic growth and acquisitions, none of them entered the world’s top fifteen transnational financial corporations ranked by the extent of their geographical spread in  (UNCTAD, ). As successors of former central industrial ministries, China’s national champions have long concentrated most of China’s indigenous technological capabilities in their respective strategic sectors. They have achieved remarkable technological progress in industries such as aerospace and defence, oil and gas, high-speed railway, telecoms, and electronics as well as power generation and related equipment. However, the gap in R&D capabilities between most of China’s national champions and the global leading big businesses in their respective sectors remains huge. According to the EU’s  Industrial R&D Scoreboard, the world’s top , companies ranked by R&D expenditure together invested around €. billion, approximately  per cent of the world’s business-funded R&D in /. They include  US companies for  per cent of the total investment,  EU companies for  per cent,  Japanese companies for around  per cent,  Chinese companies for  per cent and  from the rest of the world for  per cent (European Commission, ). Among the  largest Chinese companies ranked by R&D expenditure, twenty are China’s central state-controlled national champions (or their member firms), which together invested a total of around €. billion in R&D, compared with €. billion by Samsung alone and €. billion by Volkswagen. Nonetheless, these twenty national champions contributed around  per cent of the total R&D invested by the  Chinese companies ranked among the global top ,. As shown in Table ., the R&D intensity of China’s national champions is generally low and the investment is heavily concentrated in oil and gas,

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 , ,     



construction and materials, and industrial engineering (primarily infrastructure building and related equipment). Following China’s entry to the WTO, the Chinese government has actively maintained its industrial policies to secure technology transfers from global leading big businesses to its national champions. The results of this strategy have been mixed. In some sectors, notable success has been achieved: for example, in the high-speed railway and metro sector, China’s national champions have rapidly absorbed technologies from leading multinationals such as Alstom, Siemens, and Kawasaki Heavy Industries, and have produced substantial indigenous innovation. In other sectors such as automobiles, the strategy has been far less successful, if not a failure. For example, China’s national champions in the automobile sector are now heavily dependent upon the technologies and brands of global leading automobile companies that they have partnered with in joint ventures: FAW relies heavily upon Volkswagen and Toyota, and Dongfeng relies heavily upon Nissan and Peugeot SA (Lu and Feng, ; Nolan, ; Li, ). Overall, despite their dominant sizes in China’s domestic markets, China’s national champions are still at an early stage of developing their international competitiveness in terms of building up the necessary capabilities, technologies, brands, and global production networks to compete globally, especially in the markets of high-income countries.

. C R

.................................................................................................................................. China’s national champions industrial policy practices reflect its unorthodox approach to reforming the former socialist command economy. It also represents China’s adaptive responses to the challenges of late industrialization in a new global business environment. The ‘commanding heights’ sectors are typically characterized by high capital intensity, technology complexity, asset specificity, and substantial economies of scale. Developing countries face tremendous barriers to build viable indigenous firms with sufficient capabilities and sizes to compete with incumbents from advanced countries in the same sectors. The institutional limitations of the socialist command economy were not only about the absence of properly functioning markets, but also the absence of viable modern big-business firms. It should not be assumed that the deficiencies of firm-level organizational capabilities in transition economies and developing countries can be spontaneously resolved by marketization. Moreover, the industrial governance of transition economies comprises complex inter-organizational linkages which, in the old socialist command economy structure, connected various government agencies, enterprise units, and financial organizations that were a reservoir of talent, knowledge, and experience. There are substantial complementarities and valuable resources in these organizations. Instead of wasting existing resources and capabilities, the rise of China’s national champions suggests that it is possible to integrate and restructure the core assets and enterprise units inherited

World rank 86 88 99 102 105 126 144 166 200 219 237 251

Company

China State Construction Engineering Corporation PetroChina China Railway

Industry

Construction & Materials Oil & Gas Producers Construction & Materials CRRC Industrial Engineering China Railway Construction Construction & Corporation Materials Construction & China Communications Construction Company Materials Power Construction Corporation Construction & of China Materials Sinopec Oil & Gas Producers Metallurgical Corporation of General Industrials China China Merchants Bank Banks Dongfeng Motor Automobiles & Parts Baoshan Iron & Steel Industrial Metals & Mining

R&D 2017/ 18 (€mn)

Net sales (€mn)

R&D intensity (%)

Capex (€mn)

Capex intensity (%)

Operating profits (€mn)

Employees

1,585.9

1,32,857.8 1.2

2,230.4

1.7

9,053.5

2,70,467

1,578.0 1,421.8

2,58,137.7 0.6 88,198.4 1.6

29,354.4 1,677.5

11.4 1.9

9,304.3 3,945.1

4,94,297 2,83,637

1,343.5

26,512.3 5.1

1,009.4

3.8

1,984.4

1,76,754

1,331.4

86,183.2 1.5

3,871.1

4.5

3,508.7

2,61,333

1,104.9

61,538.5 1.8

1,692.8

2.8

3,871.6

1,16,893

972.7

33,518.1 2.9

9,365.5

27.9

2,259.1

1,31,091

822.5 683.3

3,02,226.2 0.3 30,848.6 2.2

8,136.5 522.4

2.7 1.7

12,198.6 1,887.5

4,46,225 97,771

607.1 546.7

28,274.4 2.1 16,008.5 3.4

1,575.7 418.6

5.6 2.6

11,611.7 4.0

72,530 1,46,843

506.4

36,619.6 1.4

1,700.1

4.6

3,320.5

57,154

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Table 25.2 National Champions in the top 100 companies ranked by R&D in mainland China

271 290 303 465 475

537

Construction & Materials Automobiles & Parts China Shipbuilding Industrial Engineering AviChina Industry & Technology Industrial Transportation China National Chemical Construction & Engineering Group Materials CNOOC Oil & Gas Producers China Gezhouba Group Construction & Materials NARI Technology Development Software & Computer Services

447.6

30,011.4 1.5

538.4

1.8

1,776.7

1,30,295

413.6

9,658.6 4.3

423.7

4.4

29.8

39,138

392.2

4,835.8 8.1

186.3

3.9

145.7

36,315

237.8

4,174.1 5.7

245.8

5.9

353.9

49,672

231.4

7,419.0 3.1

195.6

2.6

505.1

41,588

222.7 221.0

23,867.5 0.9 13,409.3 1.6

6,112.4 1,095.7

25.6 8.2

5,928.3 1,032.5

19,030 41,241

205.7

3,048.3 6.7

153.1

5.0

556.3

5,865

Source: The EU Industrial R&D Investment Scoreboard (2018) and company reports.

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496 501

China Energy Engineering Group Chongqing Changan

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

    

from the command economy into viable big-business firms as organizational devices to coordinate indigenous industrial development in a predominantly market-oriented economic environment. Effective industrial reform should recognize and take advantage of such institutional legacies. Under appropriate industrial policies, the danger of ‘ossification’ can be turned into a spur to new adaptation and growth. The key is, first, to promote continuous organizational learning and capability building at both the government and enterprise levels, strategically coordinating complementary reforms. Second, it is important to establish workable governance arrangements that adapt to a country’s own institutional conditions to facilitate learning and to discipline the recipients of state policy support. In particular, the state can innovatively use corporatization, commercial and policy banks, capital markets, and other financial means as industrial policy tools. The rise of China’s national champions is the result of its adaptive policy responses to its own specific political and economic conditions as well as the changing global business environment. Taking advantage of its large and continuously growing domestic markets, China’s industrial policy has created strategic space and opportunities for its national champions to acquire new capabilities and achieve remarkable growth. However, they are still at an early stage of developing international competitiveness in terms of building their global footprints and capabilities.

R Amsden, Alice H. () Asia’s Next Giant: South Korea and Late Industrialization. Oxford: Oxford University Press. Amsden, Alice H. () The Rise of ‘The Rest’: Challenges to the West from LateIndustrializing Economies. Oxford: Oxford University Press. Amsden, Alice H. and Ajit Singh () ‘The Optimal Degree of Competition and Dynamic Efficiency in Japan and Korea’, MPRA Paper (–): –. Blanchard, Olivier, Rudiger Dornbusch, Paul Krugman, Richard Layard, and Lawrence Summers () Reform in Eastern Europe. Cambridge, MA: MIT Press. Bremmer, Ian () ‘State Capitalism Comes of Age—the End of the Free Market’, Foreign Affairs : . Brødsgaard, Kjeld Erik () ‘Politics and Business Group Formation in China: The Party in Control?’, The China Quarterly : –. Buckley, Chris () ‘China’s “Nanny” Overhauls State Enterprises’, The New York Times,  June. Chandler, Alfred D. () The Visible Hand: Managerial Revolution in American Business. Cambridge, MA: Belknap Press of Harvard University Press. Chandler, Alfred D. () Scale and Scope: The Dynamics of Industrial Capitalism. Cambridge, MA: Harvard University Press. Chandler, Alfred D., Franco Amatori, and Takashi Hikino () Big Business and the Wealth of Nations. Cambridge, MA: Cambridge University Press. Chang, Ha-Joon () The Political Economy of Industrial Policy. New York St. Martin’s Press.

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 , ,     



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

    

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 , ,     



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    

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OUP CORRECTED PROOF – FINAL, 21/9/2020, SPi

 , ,     

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    

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OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

        ......................................................................................................................

                   

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 

. I

.................................................................................................................................. T chapter discusses industrial policies in the BRICS (Brazil, Russia, India, China, and South Africa). The discussion corroborates that the emergence of systems of innovation and the dynamics of industrial development and structural change in BRICS cannot be explained without considering the active role of national governments, which have supported specific sectors, industries, and even firms to grow from national champions to major global manufacturing and technological players (Vértesy, ; Scerri and Lastres, ; Kahn, Martins de Melo, and Pessoa de Matos, ). This active industrial policy approach is likely to continue at both the individual and the collective level. The chapter moves on from previous contributions to the literature, where the notion of BRICS is used as a reference to analyse individual country experiences, and to draw common elements and the main differences in policy models followed by BRICS (Di Maio, ; Brigante Deorsola et al., ). Instead, the chapter interrogates how the BRICS notion has been endorsed by the countries involved, to the extent that they are undertaking efforts to strengthen integration and collaboration. Industrial development in general, and industrial policy in particular, are relatively recent, yet already integral topics in the BRICS integration process. The analysis also sheds light on the extent to which the recent industrial performance of each BRICS country influences their participation in group dynamics. Differences in industrial development paths within BRICS suggest widening industrialization gaps, with China increasingly differentiated from the rest. This is likely to raise tensions in the integration process. Looking to the future, the chapter explores how the BRICS are responding to the opportunities and challenges associated with the Fourth

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 

Industrial Revolution (IR) (Schwab, ; Hallward-Driemeier and Nayyar, ). This new wave of technological change has the potential to alter industrial leadership, affecting prospects and conditions for catching up and forging ahead (Liu et al., ; Lee et al., ). Finally, we briefly introduce an international dimension, looking into BRICS interaction with third-party countries and regions. While each BRICS is a recognized economic and political powerhouse in their respective geographical regions, Africa seems to constitute a place of convergence for all of them.

. T T  I P   BRICS

.................................................................................................................................. Common among the BRICS is that recent industrial performance has accompanied processes of sustained capability accumulation and continuous policy reform to underpin substantive economic and institutional transformations. These experiences lend support to those who advocate active public interventions as the basis for industrialization, including conditions for resources mobilization, and more generally, for social and economic agents to thrive. Cimoli, Dosi, and Stiglitz (: ) argue that as ‘intrinsic fundamental ingredients of all development processes’, industrial policies encompass interventions across multiple policy domains (Di Maio, ; Stiglitz, ): • Science and technology and innovation—including intellectual property rights (IPRs); • Trade policies; • Policies to foster demand for manufacturing, including public procurement; • Policies to attract foreign direct investments (FDI) and other financial resources; • Policies to foster development of specific industries—including but not limited to the promotion of infant industries; • Competition policies and regulation, among others. From the end of the Second World War onwards, several of these policy domains have been integral components of each of the BRICS’ industrial policy programmes. In addition to direct contributions to the building of domestic systems of innovation (Scerri and Lastres, ), BRICS governments have fostered the articulation of industrial policies together with innovation, education, and other policies to underpin technological and productive capability building. Hence, interlinkages across distinct policy domains have been instrumental for the industrial development trajectories of BRICS (Di Maio, ; Liu et al., ; Dominguez Lacasa et al., ). Such interplay characterizes co-evolutionary processes whereby investments in science, technology,

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    



and innovation (STI) capabilities on the one hand, and industrialization and structural change on the other hand, have fed—or failed to feed—on each other historically (Nelson, ; Scerri and Lastres, ). The scope of industrial policies has varied over time and across countries according to changes in the prevailing needs and conditions of sectors, industries, or firms. External influences on the role of government generally, and industrial policy in particular, are important in fostering development. Periods of strong government intervention—import substitution, for example—alternate with more liberal stances—inspired largely by the Washington Consensus—towards the rule of markets in the economy. BRICS have actively used trade policies in the early stages of industrialization. Regarding FDI policies, Andreff () documents that unlike Brazil and India, where outward FDI mainly responds to economic purposes, China and Russia also target foreign policy, diplomacy, and even state ideology goals. Similarly, the author comments that the larger share of state-owned companies (SOCs) among Chinese and Russian multinationals means tighter state controls over corporate strategic decisions. A constant across the board is support to national champion firms, including through direct investment or through the creation of SOCs who then lead the development of specific industrial sectors, encouraging them to become major global manufacturing and technological players (Rodriguez-Arango and Gonzalez-Perez, ; Santiago, ; Liu et al., ; Di Maio, ). Interventions to assist domestic champions to weather the effects of global economic crises or shocks in relevant markets for their products or services (Simachev et al., ; Vértesy, ), or mobilization of national banks and SOCs to leverage private investment in strategic sectors or activities are also common (Di Maio, ; Simachev et al., ). BRICS support for champion firms remains debatable. Cui, Jiao, and Jiao () argue that in BRICS where government ownership is comparatively high, firms tend to show a lower probability of engaging in innovation; they have strong incentives to capitalize on monopoly positions and protection, and willingness to tackle emerging market opportunities through entrepreneurship and innovation is low. Liu et al. () illustrate this through the case of innovations in the growing online payments business, which is often associated with booming e-commerce in China. While none of the four largest state-owned banks was willing to develop such systems, the Alibaba Group took the initiative to develop Alipay, which has become a world-renowned model since its launch in . Turning attention to individual country experiences, in the case of Brazil, Di Maio () asserts that, setting aside controversies over the results of the period of import substitution (s to the s), during those years the Brazilian government undertook great commitments to enhance domestic technological capabilities and economic diversification. It actively guided the direction and pace of industrialization, often as a direct investor and owner/manager of firms (Di Maio, ). However, after the collapse of the import-substitution model (see Ocampo and Porcile, Chapter  in this volume) during the s, disappointment with active industrial policies led the Brazilian government,

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 

like those of other Latin American countries, to endorse a programme of economic reforms inspired by the Washington Consensus (Di Maio, ). The dismantling of trade barriers, the widespread privatization of publicly owned assets, efforts to restructure the economy, and a generalized opening of domestic markets to multinationals characterized this period. More recently, although the emphasis on structural change has faded, the government’s involvement in industrial development and capability building continues, with an emphasis on STI, support to small and medium-size enterprises (SMEs), and the promotion of clusters and investment in specific sectors, for example, automobiles (Di Maio, ). Russia has experienced difficulties managing the transition towards a market-driven economy, inspired mainly by the Washington Consensus and the corresponding hiatus in the government’s ability to implement active industrial policy during the s (Di Maio, ). One structural characteristic is the severe lack of transparency in state‒ business interactions and the capture of industrial policymaking by lobbyist and interest groups with differing views on how to govern industrial policy implementation (Simachev et al., ). In recent years, Di Maio () notes a ‘slide to the past’, with a growing participation of the Russian government in economic activities. State control of a large share of productive assets is characteristic of the current economic model, heavily influenced by an industrial policy oriented towards fostering import substitution, employment, and a selective and tightly controlled FDI policy. At the same time, Simachev et al. () assert that over the last decade or so, Russia has sought to harmonize industrial policy with STI policy as the basis for economic diversification, development of technology-driven sectors, and continued growth; this is occurring amidst a somewhat adverse international environment and a heavy burden imposed by political affairs at home and abroad. In , the Russian government introduced an ambitious digital economy programme, which intends to foster the institutional structure and infrastructure necessary for digitalization and the use of data at a large scale to increase competitiveness, economic growth, and sovereignty (Government of the Russian Federation, ). Similar to the other BRICS, India’s rapid industrialization starts with an importsubstitution model adopted by the newly independent country in the early s. Industrial development has been guided by five-year plans that give the Indian government great leverage to intervene in economic matters, including by identifying areas suitable for state monopoly and others where private investors could participate (Di Maio, ). The breakdown of the import-substitution model and the ensuing reforms of the early s granted greater freedom to private investors and expanded the scope of partnerships with external economic agents by reducing controls on FDI, allowing foreign majority ownership, and facilitating technology transfer. Liberalization and privatization of manufacturing are tangible in the structure of Indian manufacturing today. The country’s specialization in information and communication technologies (ICTs) benefited from accumulated investments in education and research institutions, including several private-sector-run initiatives, which also contribute to

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    



explaining the rapid expansion of services (Di Maio, ). Lee (a) argues that such expansion has been mostly at the expense of agriculture, while the share of manufacturing in total GDP remains constant. According to the author, this process, led by three giants, Infosys, Tata Consultancy Services (TCS), and Wipro, suggests that India has bypassed the stage of manufacturing-led growth, leapfrogged into service-led growth, and then back to promote manufacturing (Lee, a). China’s outstanding industrial and economic performance coincides with an ambitious period of economic reforms that started during the s. The country’s leadership committed to giving greater weight to the markets, without renouncing active government influence and the steering of the economic system. This pragmatic approach to industrial policy has been dominant since the s. China has supported structural transformation towards a market-driven economy, combined with heavily selective support, including through FDI and compulsory—including coercive— technology transfer, to strategic activities and sectors (Di Maio, ; Santiago, ). Investment in large infrastructure projects is noticeable; the provision of physical and digital infrastructure has been a priority, particularly over the last twenty to twenty-five years (Liu et al., ); and preferential credit and fiscal treatment has been given particularly to manufacturing and non-agricultural raw materials. China is getting close to or is already at the end of a rapid catching-up phase (Liu et al., ; Tourk and Marsh, ). She searches for the next policy cycle, away from top-down approaches to industrial development, and increasingly under the rule of markets, private entrepreneurship, and distinct institutional conditions for economic agents to operate (Liu et al., ; OECD, ). In South Africa, the democratic transition that started in  immediately led to efforts to reinsert the country into the international scene. The new leadership committed to dismantling industrial initiatives characteristic of the apartheid regime, including a large privatization programme. In parallel, the government adopted the Black Empowerment Programme to redress profound inequalities in access to skills, employment, and economic opportunities for black South Africans. Accession to the WTO and the signing of free-trade agreements with the EU and the Southern African Development Community (SADC) signalled the government’s intention to promote internationalization of large domestic firms, particularly in mining (Di Maio, ). The evidence suggests that the positive income effects associated with this modernization programme may have started to wear off, as industrial competitiveness seems stagnant. Industrial policy measures also face difficulties boosting exports and diversifying manufacturing (Di Maio, ). In recent years, a relevant change in the postapartheid orientation of industrial policy has been the shift towards an emphasis on skills and innovation, and from a sectoral focus to functional approaches (Di Maio, ). Considering this heterogeneous past engagement with industrial policy, how do we explain the recent emergence of BRICS as a novel political and economic entity in the global landscape?

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

 

. T BRICS    BRICS

.................................................................................................................................. The literature, particularly from a political science perspective, documents debates on the epistemological, methodological, and geopolitical underpinnings of BRICS, and the implications of the term for the rest of the world, particularly least-developed regions such as Africa. Considering the great heterogeneity characteristic of BRICS, is the term a valid geopolitical configuration? What are the strengths and limitations of the study of BRICS as an academic enterprise? Are BRICS a legitimate alternative to contemporary global, West-dominated economic and political governance, or are they merely an extension of it (Gray and Murphy, ; Gray and Gills, ; Mittelman, )? While addressing these debates is beyond the scope of this chapter, in what follows we offer food for thought from an industrial policy perspective. Notwithstanding efforts at the highest possible political level towards a common BRICS development agenda, differences in recent individual industrial performances have introduced tensions into the BRICS integration process.

.. From BRIC to BRICS From , Jim O’Neill and colleagues at Goldman Sachs released several papers proposing the acronym BRIC to acknowledge the growing power and influence of the large and dynamic economies of Brazil, Russia, India, and China over global political and economic dynamics (O’Neill, , ; O’Neill, Wilson, and Purushothaman, ). Wilson and Purushothaman () argued that given the pace of their GDP growth, income per capita, and currency movements, the BRIC could become a major driver of the world economy by . They could overtake several of the G economies—G minus Canada—in US dollar terms by  (Wilson and Purushothaman, ). The changed geography of the ten largest economies in the world, in GDP terms, would result in a more complex and more diversified scenario (Wilson and Purushothaman, ). O’Neill () advocated an ‘upgraded’¹ G—the United States, Japan, the United Kingdom, Germany, France, Italy, and Canada—to include the BRIC, or at least some of them, granting them a stronger say in global policymaking. While China appeared a natural candidate, the potential influence of the other three was undeniable, on a par with Canada or Italy. At the same time, O’Neill cautiously wondered whether the BRIC would want to integrate and embrace their potential counterbalancing role in global economic and political affairs (O’Neill, , ). After several informal meetings, at Russia’s initiative the first formal meeting of the BRIC foreign ministers took place in Yekaterinburg, Russia on  May . The first summit of the BRIC heads of state ¹ Emphasis in the original by the author.

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    



followed in June , also in Yekaterinburg. The induction of South Africa in  expanded the group to form BRICS as we know it today (BRICS, ). Ever since, BRICS has sought to tighten collaboration in mutually beneficial ways. Today, BRICS cooperation mechanisms include the annual summits, which convene the heads of state of each member country, the most recent of which took place in Brasilia in November . A diversity of meetings on specific topics involve representatives from all sorts of public, private, and academic organizations and hierarchies. Meetings regularly sideline those of multilateral organizations such as the United Nations, the G, or the Bretton Woods Institutions. Several expert working groups contribute to a broader collaboration agenda (BRICS, ).

.. BRICS to Build an Economic Block? Economic collaboration among BRICS evolves gradually. Framed against the global financial and economic crises, negotiations at the early leaders’ summits centred on financial, trade, and sustainable growth issues (BRIC, , ). As interactions intensified and diversified, largely influenced by individual approaches to industrial and other related policies, the agenda began to incorporate broader STI issues— including IPRs—employment creation, connectivity and ICT, and a Framework for BRICS e-commerce Cooperation. At the end of the Fortaleza Meeting in , the BRICS leaders agreed to develop a BRICS Economic Cooperation Strategy and a Framework of BRICS Closer Economic Partnership (BRICS, ). The former was adopted at the Ufa Summit (BRICS, a) and, together with the BRICS Action Plan on Economic and Trade Cooperation (BRICS, b, a), guides actions intended to strengthen economic collaboration. Progress in the implementation of the Strategy for the BRICS Economic Partnership is reviewed every five years, or earlier as necessary (BRICS b, a). The BRICS Economic Cooperation Strategy sets out guidelines to increase, expand, and promote intra-trade and investment, manufacturing and minerals processing, energy, STI, connectivity, and ICT among other areas (BRICS, b). The Action Plan calls for joint economic- and trade-related initiatives, including on industrial and technical upgrading, to foster economic complementarity and diversification (BRICS, a). It also targets a reduction in the digital divide and the associated economic and social implications both within and beyond BRICS. Collaboration on e-commerce should contribute to industrial development and inclusive growth in the BRICS and elsewhere (BRICS, a). A similarly incremental approach characterizes the BRICS’ search for collaboration on industrial development and industrial policy. These topics were absent from the joint statements at the first two BRIC leaders’ summits. The term ‘industrialization’ appeared for the first time in the Sanya Declaration of , in reference to the BRICS’ interest in supporting industrialization in Africa (BRICS, ). The associated

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 

action plan proposed cooperation in pharmaceuticals as part of STI collaboration (BRICS, ). The term ‘manufacturing’ appeared in the Strategy for the BRICS Economic Partnership at the th BRICS leaders’ meeting in . The Strategy acknowledges the significant contribution of manufacturing to structural change, the creation of quality jobs, and economic growth (BRICS, b). The joint agenda proposes to expand manufacturing and minerals processing (BRICS, a) and to foster such industries as mining and metals, chemicals and petrochemicals. BRICS committed to intensifying industrial production capabilities and promoting industrial parks and clusters, technology parks, and engineering centres; similarly, they intend to support specialized training for engineering and technical personnel and managers, while encouraging innovation and the development of high-tech industries (BRICS, a, b). Investment in railways, roads, ports, and airports is also envisaged. At the  BRICS leaders’ summit in Johannesburg, they recognized energy efficiency as a factor conditioning the achievement of economic targets such as industrial competitiveness, economic growth and job creation, and environmental sustainability (BRICS, ). Advancing collaboration in the ocean economy, including through coastal industrial zone development, is also on the agenda (BRICS, ).

.. Industrial Policy Coordination The launch of the BRICS Industry Ministers Meetings institutionalized collaboration on industrial development and industrial policy matters. The first meeting took place in  in Moscow, under the Russian presidency (BRICS Industry Ministers, ). Intra-BRICS cooperation expects to boost trade and sustainable economic growth, strengthening comprehensive industrial ties, promoting technology transfer and innovation, and improving investment climates and job creation (BRICS Industry Ministers, ). Joint training and skill development programmes are proposed, as are common research and business opportunities in several broadly defined industrial areas (BRICS Industry Ministers, ). The scope of collaboration was subsequently refined with the adoption of a sevenpoint Action Plan at the end of the second ministerial meeting in Hangzhou, China (BRICS Industry Ministers, ). The Action Plan acknowledges the emergence of IR and two other major transformations in global manufacturing: the increasing interdependence of manufacturing and manufacturing-related services, with the latter increasingly driving economic development; and the transformational power of concepts such as digitalization, networking, and ‘intellectualization’ and their significance for production and business models with the potential to create new industries (BRICS Industry Ministers, ). The Action Plan reaffirms the BRICS commitment to enhance collaboration in industrial capacity building, SME development, industrial policy coordination, standards, development of new industrial infrastructure, and technology- and innovation-related projects.

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    



Collaboration in industrial policy matters reaches out to the UN system, for example, to the United Nations Industrial Development Organisation (UNIDO) in establishing the BRICS Consolidated Technology Platform, with a mandate to boost cooperation in the upgrading and/or development of new high-tech engineering industries and innovation, and in the development of capital goods and machinery related to manufacturing and minerals processing (BRICS, c; BRICS Industry Ministers, ). Consonant with the BRICS long-standing tradition of supporting large firms, the eThekwini Declaration encourages existing SOCs to explore cooperation, exchange of information, and best practices (BRICS, ). Simultaneously, each country’s ministries and agency responsible for local SMEs is exploring opportunities to collaborate, particularly in international trade, innovation, and joint R&D (BRICS, ). The BRICS approach to collaboration is consistent with individual traditions of creating interdependence and complementarity between industrial policies and other policy areas. This recurs in several of the declarations and action plans across different policy areas. Common interests include technology transfer, support for joint research agendas, intention to leverage on initiatives around training, skilling, and upskilling, firm registration, and other crosscutting or horizontal policy interventions. Successful integration of different policy areas into a single BRICS industrial development programme should have major implications for manufacturing development in each individual BRICS.

. T C  H I P

.................................................................................................................................. The ability of the BRICS to overcome their distinct individual economic, political, and social conditions and traditions, and to collectively contribute to global economic and political checks and balances is the subject of debate. Degaut and Meachan (), Di Maio (), and Dominguez Lacasa et al. () perceive BRICS as a heterogeneous collection of industrial upgrading models, each of them with distinct perspectives and approaches to the accumulation of technological, productive, and other capabilities. However, as we discuss later, China’s dominance in the group dynamic poses major challenges to the BRICS integration. Kejin () argues that with Chinese choices and capabilities continuing to frame the scope of cooperation, attempts to enhance economic cooperation and build consensus are encountering difficulties.

.. Contribution to Global Economic Activity The BRICS’ growing global economic importance is evident (Figure .). In , they represented . per cent of global GDP, a three-fold increase on  (. per cent).

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

  Share in world's GDP

100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0%

1990

1995

2000 WLD

CHN

2005 IND

BRA

2010 RUS

2017

ZAF

 . BRICS’ growing but heterogeneous contribution to global economic dynamics Source: Author, based on World Bank Development Indicators.

Similarly, they contributed about a third of total global manufacturing value added in . Despite this enhanced collective presence, the individual shares are heterogeneous. China largely drives the dynamics in terms of both total GDP and manufacturing value added, although the rate of expansion has receded slightly in recent years. The most dramatic gains appear in manufacturing value added. In around a decade, China’s contribution rose from about  per cent () to about a quarter of the world total in . The shares of the rest of the BRICS are either growing less rapidly (India), are stagnant (Russia and Brazil), or are shrinking (South Africa). India’s share in both GDP and manufacturing value added has overtaken that of Brazil and Russia. Differences in individual contributions to both group and global economic dynamics should continue to deepen in the short run (Mbele, ). The BRICS’ export performance over the period ‒ further illustrates the heterogeneity within the group. China reports the largest and fastest-growing share of manufacturing in total exports. Brazil records a steady increase in the share of exports of agricultural and mining products and, to a lesser extent, services. In Russia and South Africa, manufacturing exports are giving way to mining and services, while services account for  per cent of Indian exports. The short-term dynamics should conform to Mbele (), who qualifies BRICS growth trajectories as singling out distinct subgroups. China will continue to upgrade her position in global supply chains, consolidating as a major global manufacturing centre and boosting her share in manufacturing exports within the BRICS and from the BRICS to the world. Brazil, Russia, and South Africa, in turn, should consolidate as exporters of natural resources-based products, while India continues to bounce between a manufacturing- and a predominantly services-based economy (Amirapu and Subramanian, ).

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    



.. Structural Change and Capability Accumulation Industrial development implies structural change, or the transformation from traditional agriculture or natural resource-based economies into economies led by increasingly complex manufacturing activities (Haraguchi, Cheng, and Smeets, ). There are three dimensions to structural change: technological, industrial, and organizational. It involves deliberate and decisive efforts to learn and accumulate different capabilities (UNIDO, , ). Liu et al. () argue that building innovation capabilities is a precondition to overcoming middle-income traps; they assert that the lack of capabilities, more than political institutions, may be the most significant binding constraint for middle-income countries. Countries achieve productive and technological upgrading by balancing different framework conditions to support capabilities to absorb and use different kinds of knowledge, to mobilize investments, and to accumulate the necessary capital to undertake structural change, sustain catch-up, and eventually, leapfrog (Abramovitz, ). At least two kinds of capability accumulation processes are possible (Lee, b). First, production capabilities, which refers to the accumulation of advanced physical capital and the associated human capital required to run productive facilities at given levels of efficiency. Second, innovation capabilities assist economic agents to master and change the technology they already use, eventually allowing them to create new technology. They also help latecomers to close the gap relative to the technological frontier and, under certain conditions, seek to overtake incumbents and assume leadership in furthering the technological frontier (Lee and Malerba, ). By tapping into emerging market opportunities, through exports for example, latecomers may reduce dependence on global value chains, steadily capturing market shares, and increasing domestic value addition (Lee, b). However, because capability building is path dependent, it may constrain the ability to identify and capture emerging windows of opportunity to further upgrading (Lee and Malerba, ) and limit the flexibility to accommodate changes in technological and productive trajectories (Abramovitz, ). Globalization and international conventions around IPRs also restrict the scope of technology transfer, and limit the possibilities of imitating and reproducing technologies through R&D (Dominguez Lacasa et al., ; Lee, a). Latecomers should focus on developing small but incremental innovations while avoiding confrontation with incumbents and their IPRs (Hobday, Rush, and Bessant, ).

... Productive Capabilities Compared to other developing countries, and thanks to a process broadly described as economic modernization, BRICS productive competencies tend to feature greater technological content and complexity relative to peer countries. Moreover, each of the BRICS hosts several of the largest and most important multinational firms in the developing world (Rodriguez-Arango and Gonzalez-Perez, ; Andreff, ).

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

 

Several of those firms are challenging, or have attained, global leadership in areas traditionally reserved for firms from highly industrialized countries, including aerospace, transport, pharmaceuticals, and advanced ICT applications (Daudt and Willcox, ; Santiago, ). However, modernization is insufficient to ensure long-term sustainability and growth (Cimoli, Dosi, and Stiglitz, ). Notwithstanding progress in specific sectors or individual firms, the BRICS’ economic structures are yet to achieve sustainable catch-up. They face overexposure to external shocks and risk dependence on external technology suppliers; moreover, differences in their endowments, technological progress, and integration into global flows of trade and investment remain significant (Di Maio, ). Figure . illustrates these points. It plots industrial and economic performance of each of the BRICS over the last twenty to twenty-five years along two dimensions. First, the x-axis plots long-term industrial performance, as measured by each individual country’s score on UNIDO’s Competitive Industrial Performance Index (CIPIndex), which benchmarks a country’s ability to produce and export manufactured goods competitively (UNIDO, ). The index helps to identify the occurrence of structural change towards high value-added technology-intensive industrial sectors, and assess the impact of a country’s industrial production on the world market. Second, the y-axis plots the value of gross national income (GNI) per capita measured in constant US dollars of . Heterogeneous performance within BRICS is evident. China stands out, as it has managed to combine and sustain structural change with a rapid expansion in GNI per capita. According to CIPIndex scores, China’s increased industrial competitiveness was fuelled mainly by a rapid expansion in her ability to generate manufacturing value

GNI per capita (000 US$ 2010=100)

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6000 1990 4000 2015

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Industrial competitiveness - CIP Index Brazil

China

India

South Africa

Russia

 . BRICS: structural change and catching up, ‒ Notes: Constant thousand US$ (=). CIP Index: the earliest date available for CIP Index for China is . Source: Author’s based on UNIDO CIP database and World Bank Development Indicators.

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    



added and a strong export-led growth model that seems to have reached a tipping point (Tourk and Marsh, ). Positive industrial performance has accompanied a five-fold increase in GNI per capita in about two decades. By contrast, the CIP Index scores of Russia, Brazil, and South Africa suggest processes of gradual industrial recession; in the best-case scenario, these countries are stuck in a period of industrial stagnation. Russia, in particular, is slowly recovering from the negative effects on industrial competitiveness that represented the end of the Soviet era. While GNI per capita continues to grow, albeit at a slower pace relative to China’s, the country’s CIP Index score remained constant for most of the ‒ period. Similar conclusions can apply to Brazil, although the descent in CIP Index rankings seems to have accelerated during the s. By contrast, South Africa’s gains in income per capita have seldom accompanied improvements in its industrial competitiveness. This loss results from weak production skills and digital infrastructure, poor access to finance and high energy costs, while firms that have addressed such challenges have continuously upgraded their capabilities and invested in innovative technologies (UNIDO, ). Finally, India records much steadier growth in terms of both industrial competitiveness and GNI per capita, but from a much lower base relative to South Africa, Brazil, or Russia. Overall, the data show that relative to the other BRICS, China is rapidly closing the gap in terms of GNI per capita while her relative distance in terms of industrial competitiveness is forging fast ahead.

... Innovation Capabilities Dominguez Lacasa et al. () argue that innovation, broadly defined as a process that includes but is not limited to R&D, is at the core of technological upgrading. While improvements in infrastructure and the institutional environment have generally enhanced innovation in the BRICS, particularly in China, performance remains modest relative to developed-country standards (Franco and Oliveira, ). Innovation performance corroborates the very distinct development paths followed by individual BRICS. Building on patent data to study technological upgrading in the BRICS over the period ‒, Dominguez Lacasa et al. () propose a statistical framework, which distinguishes between three interrelated dimensions: intensity of technology upgrading, structural change, and global interaction. The authors find multiple unique paths of technology upgrading in the BRICS, with differences across the three dimensions. Generally, the BRICS have increased their innovation capabilities, while reducing dependence on foreign actors and external knowledge transfer in order to catch up. They have progressively developed the ability to carry out technological frontierpushing activities—with the sole exception of Russia. As a result, the structure of technological knowledge—measured through the share of high-tech and knowledgeintensive patent applications—has increased across countries (Dominguez Lacasa et al., ). China and Russia are the only ones to have augmented, or at least kept constant, the intensity of behind-the-frontier technological activities. China is unique in this regard, as she has rapidly enhanced innovation capabilities, diversified technology knowledge bases and entered into dynamic frontier-pushing areas.

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

 

The country is fostering structural change and global interactions towards technological frontier-expanding activities—a process that, according to Dominguez Lacasa et al. (), emulates Korea or Taiwan during earlier periods of technological upgrading and catching up (see Rasiah, Chapter  in this volume). In contrast, foreign knowledge still tends to crowd out domestic behind-the-frontier technological efforts in Brazil, India, and South Africa. Massive R&D investments evidence China’s stronger commitment to the building of productive and particularly technological capabilities relative to other BRICS. In , China became the world’s second-largest investor in R&D in volume terms, second only to the United States (UIS, ). While in GDP terms China still ranks behind most developed countries, it tends to outperform the other BRICS. The R&D funding and execution structure shows that business enterprises account for about threequarters of the total, a structure similar to advanced countries and in stark contrast with the general situation of government-driven R&D in most other BRICS and other developing countries.

.. Integration through Trade and Investment Integration through value addition incorporated in manufacturing exports within BRICS has grown steadily over the past decade, but bilateral relationships are rather mixed (Table .). With the exception of China, and to a lesser extent Russia, the BRICS have enhanced their backward integration with others in the group. For instance, the share of value addition of Brazilian manufacturing exports coming from the BRICS grew from . per cent in  to . per cent in . The figures for India and South Africa are more significant, from . per cent to . per cent and from . per cent to . per cent, respectively. These two countries show the strongest level of backward linkage with other BRICS. At less than . per cent, Chinese exports maintain the lowest level of backward integration. The situation is less straightforward if one considers the industry of origin of value added in each of the BRICS’ manufacturing exports. Generally, Chinese manufacturing value added contributes  per cent or more of the manufacturing exports of other BRICS. In contrast, with the exception of India, which contributes about . per cent of Chinese manufacturing exports, the rest of the BRICS have seen declining shares of local manufacturing value addition incorporated into Chinese manufacturing exports. In , the figures were . per cent for Brazil, . per cent for Russia and . per cent for South Africa. Long-term trends show a decline in the intra-BRICS value-added content of Chinese manufacturing exports, while supplies of mining and quarrying products are the main input to Chinese manufacturing exports. While South African exports tend to incorporate a more significant share of manufacturing supplies from other BRICS, mining and quarrying products are the main source of South African value added incorporated into other BRICS manufacturing exports. This intra-BRICS

Table 26.1 Composition of gross manufacturing exports by country of origin of value added, 2005–15 2005

2010

2015

Brazil — 0.6 0.2 0.3 0.1 86.3 1.2 12.5

2010

2015

China — 1.1 0.3 0.3 0.1 86.9 1.8 11.4

— 2.0 0.3 0.3 0.1 83.8 2.7 13.4

0.3 — 0.4 0.8 0.2 71.6 1.7 26.7

2005

2010

2015

India 0.6 — 0.4 0.6 0.3 77.4 1.9 20.9

0.4 — 0.3 0.5 0.2 81.3 1.4 17.4

Notes: BRICS minus the specific member country reporting exports. Source: Author’s based on OECD’s Trade in Value Added (TiVA) database. http://oe.cd/tiva.

0.2 1.5 — 0.8 0.7 74.8 3.2 21.9

2005

2010

2015

Russia 0.4 2.7 — 0.9 0.8 66.5 4.8 28.7

0.4 3.7 — 0.6 0.5 72.7 5.2 22.0

0.2 0.7 0.1 — 0.1 85.9 1.1 13.1

2005

2010

2015

South Africa 0.2 1.8 0.2 — 0.2 86.3 2.4 11.4

0.1 2.0 0.2 — 0.1 85.9 2.4 11.7

0.3 1.2 0.4 0.2 — 77.8 2.1 20.0

0.4 2.2 0.7 0.3 — 76.1 3.6 20.3

0.7 4.7 1.1 0.4 — 70.1 6.9 23.0

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Brazil China India Russia South Africa Domestic value added BRICS Rest of the world

2005

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 

pattern of trade should continue to influence the bargaining power of individual group members, particularly vis-à-vis China. The BRICS have emerged as major destinations and sources of FDI. In  they represented  per cent of the FDI inflows and around  per cent of the inward FDI stock in the world (UNCTAD, ). Despite this growing importance at the global level, and notwithstanding positive growth trends in intra-BRICS FDI in the early s (UNCTAD, ), the level of integration within the group remains low (Table .). The strongest linkages appear in inward FDI stock from China in South Africa (. per cent), followed by Russia (. per cent), while the share of South Africa and Russia in Chinese inward FDI stock is considerably lower. South African investments in India (. per cent) stand out among the rest of the BRICS, which generally show very limited integration; individual shares hardly exceed . per cent of total inward FDI stocks in each individual BRICS. Overall, South Africa is the country with the largest share of inward FDI stocks from BRICS (. per cent), followed by India (. per cent) and Russia (. per cent). The data also corroborate the greatest importance of circular FDI flows (round-tripping) for China and Russia. Andreff () attributes this to the tradition of BRICS multinationals targeting tax havens or, in the case of China, benefiting from the favourable tax conditions offered to foreign investors in mainland China. The low level of integration through FDI can largely be explained by BRICS multinationals’ predominantly market-seeking strategy, which shows a preference for investing within regional value chains—including through trans-border mergers and acquisitions—and in tax havens or markets in (tax-friendly) developed countries (UNCTAD, ; Andreff, ). China, and to a lesser extent Russia, show a stronger inclination to diversify geographically, including to developing regions—notably Africa and in the case of China, also Latin America (Andreff, ).

Table 26.2 UNCTAD FDI estimates by ultimate investor, share in inward FDI stock, 2017 Recipient Investor

Brazil

China

India

Russia

South Africa

Brazil China India Russia South Africa BRICS

0.0 0.7 0.1 0.2 0.1 1.1

0.1 7.8 0.2 0.3 0.5 1.1

0.0 0.8 1.6 0.3 1.2 2.3

0.0 1.6 0.3 6.5 0.1 2.0

0.0 5.0 0.4 0.2 0.1 5.7

Notes: UNCTAD estimates for 108 recipient countries, corresponding to 93 per cent of the value of global inward FDI stock. Details in Casella (2019). Source: UNCTAD (2019).

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    



According to Andreff (), BRICS investment in developed countries mainly takes the form of mergers and acquisitions rather than greenfield investments. Regarding sectoral composition, the evidence suggests a resource-seeking behaviour with relevant shares in primary-sector activities, followed by services in overall outward FDI.

. BRICS   IR

.................................................................................................................................. An analysis of patent and trade data conducted by (UNIDO, ), and involving the advanced digital technologies usually associated with the IR—industrial Internet of things, big-data analytics, advanced robotics, artificial intelligence, cloud computing, and additive manufacturing—characterized the global landscape of production and the use of those new technologies. About  economies were divided into four distinct groups according to their level of engagement with the new technologies. Looking at the BRICS, only China made it to the frontrunners’ group, which includes the top ten countries—mostly developed—in terms of innovation in advanced digital production technologies. These economies account for more than  per cent of all patent applications and about  per cent of the exports of goods associated with these technologies (UNIDO, ). The other four BRICS appear in the follower group, economies that actively engage with the new technologies, producing and selling in international markets, but to a much lesser extent than the frontrunners. Some differences persist within this group. While Brazil, Russia, and India appear as producers and exporters of IR technologies, South Africa remains mainly a user— importer—of them (UNIDO, ).² Lee et al. () question how much the IR represents a window of opportunity for upgrading or whether, on the contrary, this is a process likely to reinforce the risk of becoming stuck in middle-income traps. Similar questions influence strategic thinking and policymaking within BRICS, and efforts are already ongoing towards a BRICS joint IR development agenda. The emerging evidence suggests that each country is positioning itself differently depending on individual industrial development trajectories and individual approaches to industrial policy. Generally, the BRICS are among the few developing countries where a dedicated strategy, or at the very least, some explicit policy efforts, are geared to addressing the IR (UNIDO, ; Santiago, ). BRICS aspire to foster innovation-driven economies, away from commodities and traditional industrial products and moving increasingly into higher value-added sectors. China, in particular, is steadily moving towards industrial

² The classification further includes a group of latecomers, economies with marginal patent or trade activity in this field, but that have already engaged with IR technologies. Finally, a larger group of laggards includes economies with no or very low engagement with these technologies (UNIDO, ).

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 

development strategies that seek to capitalize on her increasing ability to reproduce and produce new technologies; the search for value addition and enhanced technological content is superseding traditional cost advantage strategies (Li, ). Similar to the case of advanced countries, the BRICS national strategies around the IR are a blend of policy realms and approaches, including industrial policies (China and South Africa) or STI plans (Brazil and South Africa), digitalization strategies (Russia) or national digital agendas (China), or standalone documents using such terms as ‘Industry .’ and ‘advanced manufacturing’, or referring to specific technologies (UNIDO, ). South Africa exemplifies the latter approach, as it has recently introduced a strategy around additive manufacturing (CSIR and DST, ). Alternatively, India is leveraging on existing industrial development plans, such as Make in India, strengthening linkages to the digitalization of industry. An interesting feature of IR is its ability to underscore the need for novel approaches to strategy setting. In his study of industrial policy in the BRICS countries, Di Maio () asserts that a recent trend in industrial policy design is the adoption of principles of the so-called new industrial policy, stressing multi-stakeholder participatory processes and the contribution of public‒private dialogues to policy design and implementation. UNIDO () supports this finding, as several BRICS have followed participatory processes in the preparation of national IR strategies. Country responses are often built around a ‘multiple helix’ involving government, academia, private entities, and civil society; the challenging nature of these consultative approaches cannot be underestimated. Future research on the BRICS should consider how to organize, govern, and sustain such participatory processes and, more importantly, how BRICS are moving forward in the implementation of those strategies at the individual and, as we discuss in section .., the collective level.

.. Collective Responses At the end of their most recent meeting, the BRICS industry ministers acknowledged that tightening collaboration in industrial development matters should assist them in addressing what they termed the ‘Digital Industrial Revolution’ (BRICS Industry Ministers, ). They committed to boosting industrialization through new hightech-driven innovative policy and regulatory frameworks (BRICS, b) and the adoption of joint initiatives around the IR (Business Report, ). While at this early stage it is difficult to document BRICS initiatives in the field, few proposals have been tabled. Based on a somewhat common approach to industrial policy design ideas, such proposals can be characterized along three core areas: building basic framework conditions, fostering the demand for and adoption of IR technologies, and strengthening skills and research capabilities at different levels (López-Gómez et al., ; UNIDO, ).

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    



... Building Basic Framework Conditions Framework conditions refers to regulations and digital infrastructure. They also include the institutional framework for strategy setting, policy formulation, and governance, which is increasingly perceived as multi-stakeholder and involving close private‒public collaboration. BRICS have started the dialogue. At the  summit in Johannesburg, the BRICS leaders endorsed the creation of a BRICS Partnership on New Industrial Revolution (PartNIR) (BRICS, ), as previously agreed by the respective ministers of industry at their third ministerial meeting (BRICS Industry Ministers, ). An Advisory Group to include representatives from BRICS ministries of industry and experts from all BRICS members will be responsible for operationalizing the PartNIR. The terms of reference and work plan will focus on digitalization, industrialization, innovation, inclusiveness, and investment (BRICS Industry Ministers, ). Close collaboration with the private sector is prescribed through working groups on a wide variety of industrial and manufacturing sectors. The ultimate intended outcomes of the PartNIR include boosting economic growth, strengthening sustainable industrial production capacity, and creating networks of science parks and technology business incubators; of particular importance is the inclusion of SMEs in technology-intensive areas (BRICS, : item ). Concrete initiatives include the establishment of the BRICS Networks of Science Parks, Technology Business Incubators and Small and Medium-sized Enterprises (BRICS, ). Regarding infrastructure, UNIDO () documents that digitalization remains a binding constraint for the development of advanced manufacturing. South Africa, a laggard among BRICS, needs to address high-cost and limited bandwidth, skill shortages in ICT and data analysis, not to mention innovation system weaknesses such as poor interaction between firms, universities, and research centres (UNIDO, ). More generally, upgrading of ICT infrastructure and connectivity are among BRICS priorities; they are committed to promoting internationally accepted and applicable rules for security of ICT infrastructure, data protection, and the Internet (BRICS, b). All these initiatives are consequential on the BRICS’ intention to foster the digital economy through the BRICS ICT Development Agenda and Action Plan (BRICS, b). Global debates around the developmental implications of big data cannot be overlooked as capabilities to generate, process, and extract value from rapidly expanding pools of datasets are prone to high concentration both geographically and in terms of monopolistic power (Cable, ; Marr, ). The BRICS can potentially play major roles in advancing a global agenda around the development of big data and its associated implications for security, privacy, and the capabilities required for handling growing and increasingly complex volumes of varied forms of data (Mahrenbach, Mayer, and Pfeffer, ). China is among the most advanced developing countries in the use of data as an economic driver; development strategies prescribe data analytics and big-data platforms to support new industries and foster upgrading of traditional ones (Mahrenbach,

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

 

Mayer, and Pfeffer, ). The Chinese government encourages innovation and funds big-data research, while scientists are compelled to link and share research findings with industry, and companies are expected to increase productivity and growth via incorporation of big data and associated technologies in high-tech manufacturing and in new business models (Mahrenbach, Mayer, and Pfeffer, ). All private-sector activities have to remain within specified regulatory and incentive frameworks. While this performance potentially locates China among the forerunners in the development of big data at the global level, any counterbalancing or supplementary role for the other BRICS in the consolidation of generally agreed guidelines for governing development of markets for big data is yet to emerge. Sing () proposes three possible emerging models. At the one end is a model led mostly by the United States, centred on a global laissez-faire approach and dominated largely by domestic digital firms and free and unregulated data flows. At the opposite end is the Chinese approach to state-led capitalism, where the government enjoys strong surveillance rights and control of digital transactions. In between these two, Sing () places mixed-economy approaches to digitalization, as emerging in India or the European Union, where governments play major roles in fostering infrastructure and regulation to support competitive and efficient open data market operations, without renouncing control of monopolies and concentration, or the oversight of areas of social and economic importance. Similarly, as part of the BRICS Action Agenda on Economic and Trade Cooperation, the group adopted an Intellectual Property Rights Cooperation Mechanism (BRICS IPRCM) which should enhance cooperation and coordination in this area, particularly through the BRICS IPR Cooperation Guidelines and an Action Plan on BRICS IPR Cooperation (BRICS, a). Concrete activities include fostering information exchange among the IPR offices of BRICS countries and capacity building on IPR issues.

... Fostering Demand and Adoption of IR Technologies UNIDO () argues that even if suitable framework conditions are put in place, countries need to encourage adoption and adaptation of advanced digital production technologies. Given the novelty of many of the products and services that can be derived from the IR technologies, economic agents find it difficult to appraise their value propositions relative to competing existing technologies, while challenges to assessing the expected return on investment contrast with perceived high upfront investment requirements (Steinmueller, ). Addressing this situation requires concentrated policy efforts to raise awareness of firms about the potential benefits of the new technologies. It also requires funding of their adoption to be facilitated. Countries may adopt and jointly implement dedicated programmes and incentives to raise awareness and rally the interest of domestic agents, or to foster emerging behaviours and initiatives related to the IR. The BRICS expect to enhance collaboration on STI through joint proposals to mobilize their accumulated technological and R&D capabilities (BRICS, ).

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    



BRICS exploration of collaboration is already motivating joint research activities and innovation agendas on big data, ICT, and other advanced manufacturing technologies and their applications, and on ICT infrastructure and connectivity (BRICS, b). Concrete proposals include establishing the BRICS Institute of Future Networks, which will support joint BRICS research and innovation in ICT—including Internet of things, cloud computing, big data, data analytics, nanotechnology, artificial intelligence, and G—and their applications (BRICS, b). The suggested approach is to encourage partnerships between multiple stakeholders to devise and implement proofs-of-concept and pilot projects in these areas.

... Strengthening Skills and Research Capabilities UNIDO () documents that governments can play a major role in the creation of the capabilities required to adopt IR technologies, for example, through dedicated learning centres and new approaches to technical and vocational education and training. Expanding the scope and number of research institutions specifically to deal with these technologies is key for their absorption and adaptation to local circumstances. López-Gómez et al. () advocate the building of human capabilities, particularly to enable adjustments in labour markets and systems of education, training, and retraining. Concrete activities along these lines are yet to emerge but, as agreed in the most recent ministers of industry meeting, the BRICS intend to enhance policy coordination around advanced technical skills and training, exchange of information, and best practices with respect to digitization. Securing inclusive and equitable growth, while developing synergies in the use of financial and human resources, is likewise important (Business Report, ). Interesting initiatives implemented recently at the individual country level may serve as examples for larger, BRICS-level interventions. For instance, in Russia, the Agency for Strategic Initiatives (ASI) and Skolkovo (Moscow School of Management) have developed the Atlas of New Professions, an online platform intended to help understand what the twenty-five most promising sectors will be for the next fifteen to twenty years, together with relevant occupations and their respective skill requirements and associated organizational practices; likewise important is the stocktaking of more than fifty occupations that are bound to become outdated—including both routine and high-skilled ones (ASI and Skolkovo, ). In parallel, ASI initiatives such as Skill Development for Industrial Growth are working to improve matching between industry’s skill demands and the supply from educational establishments (Roland Berger GMBH, ). According to Tourk and Marsh (), China is fostering programmes to attract foreign talent to supplement its limited domestic innovation capabilities. For example, in , the Fozhou Bureau of Foreign Experts Affairs was established in Fozhou, capital city of Fujian province, providing free work spaces and funding for start-up companies and arranges matching them with potential investors (Tourk and Marsh, ). By the end of , ten start-ups had settled in the city, and it recorded a

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 

significant flow of returning students; moreover, the model had attracted the attention of other provincial governments in China (Tourk and Marsh, ).

. T I D

.................................................................................................................................. The BRICS cooperation agenda is broad, with an ever-growing number of items. From an initial focus on global governance and diplomacy—including UN reform and enlargement of the UN Security Council to include some BRICS as permanent members—or the reform of current international financial architecture, the agenda has evolved to include STI topics and economic development. BRICS expect to influence global peace and security, energy and climate change, and social and economic issues in a non-confrontational spirit together with other global governance arrangements (BRICS, ). The creation of a New Development Bank (NDB) is a major initiative articulating the BRICS’ collective presence and global influence. The NDB mobilizes resources for infrastructure and sustainable development projects in BRICS and other emerging and developing economies (New Development Bank, a).³ In addition to strengthening intra-BRICS cooperation, the NDB expects to supplement the funding of multilateral and regional financial institutions (BRICS, ). The bank became operational with the signing of the Headquarters Agreement with the government of China and the Memorandum of Understanding with the Shanghai Municipal People’s Government on  February  (BRICS, ). The first loans, approved in ‒, support projects in green and renewable energy, transportation, water sanitation, and irrigation (BRICS, ). By the end of , the total loan portfolio should amount to US$ billion (New Development Bank, c), double the US$. billion at the end of  (New Development Bank, b). Creation of the NDB has not been without tensions. Its operational structure prescribes an initial authorized capital of US$ billion, with a first subscription of US$ billion equally shared among founding members. Governance and leadership are split among the BRICS, with headquarters in Shanghai and an Africa Regional Centre in South Africa (BRICS, ). Kejin () and Degaut and Meachan () assert that although the BRICS contribute equally to the first tranche of capitalization of the NDB, China seems the only member standing ready and able to expand and fulfil future commitments. China could take the lion’s share of the decision-making power, particularly as the conditions for non-BRICS membership of the NDB remain uncertain (Kejin, ).

³ The BRICS have also enacted a Contingency Reserve Arrangement to support one another in situations of balance-of-payments instability (BRICS, ).

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

.. Africa in Focus It is no surprise that Africa occupies a prominent place in the BRICS agenda. Even before their integration, each had established close social, political, and economic ties with the continent. The steady increase in BRIC FDI in Africa suggests attempts at breaking customary regional specialization regarding destination countries. At the same time, the growing presence of BRIC among Africa’s major trade and investment partners is perceived as a counterbalance to traditional partners, the United States, Europe, or Japan (Kimenyi and Lewis, ). Similarly, the BRIC were already important donors in the region through concessionary and soft loans, credit lines and grants; China in particular actively supports infrastructure projects (Kimenyi and Lewis, ). Coincident with South Africa’s accession to BRICS, the Sanya Declaration made explicit the BRICS’ intention to collaborate with Africa, with the New Partnership for Africa’s Development (NEPAD) identified as the relevant interlocutor (BRICS, ). Engagement with South African Union countries followed at the fifth BRICS leaders’ summit in Durban, under the overarching theme of ‘BRICS and Africa: Partnership for Development, Integration and Industrialization’ (BRICS, ). BRICS support to Africa’s industrialization seeks to potentiate the continent’s development efforts through FDI, knowledge exchanges, capacity building, and trade diversification. A priority is to assist the continent in redressing its infrastructure deficits, required to boost regional integration and industrialization (BRICS, ). This is consistent with the long-standing BRIC presence in the African infrastructure market (Kimenyi and Lewis, ) and the potential gains offered by a continent where investments in infrastructure to provide basic services to the population compete heavily against resources to improve or expand on transport and other economic infrastructure (Oxford Economics and Global Infrastructure Hub, ). The establishment of a Multilateral Agreement on Infrastructure Co-Financing for Africa with support from the BRICS’ export‒import and development banks is proposed to move collaboration forward (BRICS, ). The BRICS presence in Africa provokes some criticisms. Kimenyi and Lewis () decry the perceived appetite for Africa’s natural resources, notably oil—with principally China’s and Brazil’s expanding presence in Angola, Nigeria, and Sudan—mining in Liberia and Mozambique, and gas in Nigeria. Similarly, India’s presence has expanded in textiles, social services—health and education—ICT, and automobiles. Mbele () stresses the asymmetrical patterns of trade and investment between the BRICS and Africa. South Africa’s accession to BRIC provoked strong criticism; in addition to the huge economic asymmetries, South Africa is perceived as supporting the BRIC and particularly Chinese interest in the continent. Kimenyi and Lewis () note ties between Chinese investments and Chinese-sponsored infrastructure development projects over the last two decades, while South African firms provide the platform for a cooperation model based on African exports of raw materials and manufacturing imports (Carmody, ).

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 

Africa is likely to continue to play a major role in the context of China’s Belt and Road Initiative (BRI), launched in , which endeavours to transform six trade and investment corridors across Asia, Europe, and Africa, with an emphasis on infrastructure and connectivity. Underscoring the benefits of BRICS’ closer collaboration will be the possibilities of channelling funding through the NDB and other funding mechanisms—for example the Asian Infrastructure Investment Bank—in which BRICS participate. However, geopolitical tensions associated with BRI should not be ignored, particularly as India and Russia maintain close ties and interests in regions directly located along several BRI main economic corridors.

. C

.................................................................................................................................. The conformation of the BRICS block is a work in progress, at very early stages of development. The process faces significant constraints rooted in the history, structure, and recent economic and industrial performance of the countries involved. Several significant shortcomings could deepen in the near future. In particular, this chapter has corroborated the widening gap in performance between China and the other BRICS. This is potentially a major hindrance, as it exacerbates differences in interests and capabilities within the group (Degaut and Meachan, ). While BRICS integration would benefit from closing productive and technological capability gaps, recognition of this challenge remains largely absent from policy documents governing the integration process. BRICS seem to understand the value of conforming a strong block. Those who dismiss the possibility of their achieving closer collaboration should remember that BRICS is mostly an informal collaboration mechanism; each participant plays according to its own rules and interests (Kejin, ). BRICS integration is and will continue to be gradual but systematic, through dedicated strategies or action plans to govern collaboration in several areas. Other, more mature international governance mechanisms—the G or even the G—have been built progressively; there is no reason to expect the BRICS to move any faster or any deeper. As areas for collaboration expand at every leaders’ or ministerial or expert meeting, systematic and empirically driven evaluation of commitments and their tangible outcomes is necessary to draw conclusions. This chapter proposes that industrial development offers great potential for further follow-up in the future. Despite its novelty within the BRICS collaboration agenda, industrial development is an area that could integrate and expand individual BRICS approaches to STI, IPRs, e-commerce, infrastructure, and other related areas. BRICS, and particularly China, attract significant attention regarding strategic policy responses to the IR. Unlike many other developing countries, they have generally undergone significant structural change with strong reliance on manufacturing. They are, and will remain, role models for other developing countries where

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

industrial development is yet to take root. As the ongoing technological and productive transformations continue to unfold in uncertain directions, BRICS are continuing to foster structural change and the development of innovation-driven economies, moving away from commodities and traditional industrial products and increasingly into higher-value-added sectors and products. At the same time, BRICS’ strides up the ranks of global industrial leadership increase the risks of widening gaps relative to leastdeveloped economies (Liu et al., ; Mayer, ). Among the BRICS, China seems ready to tap into the current juncture to explore new development paths, steadily shifting from a catching-up mindset centred on labour-cost advantages to one of capitalizing on its growing role as a leading global technology and manufacturing centre (Li, ; The Economist, ). Implications for the future of industrial dynamics in both developed and developing countries may be significant. Finally, yet importantly, from a historical perspective the experience of BRICS reminds us that catching up entails active industrial policies to underpin the creation of absorptive technological and productive capabilities. This characteristic should continue to assist the BRICS in their individual and collective development efforts.

A Earlier versions of this manuscript benefited from comments and suggestions from Nobuya Haraguchi, Professor Fantu Cheru, Professor Li Chen, the editors of this volume, and participants at two review workshops held in Addis Ababa in April and September .

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BRICS () ‘Sanya Declaration’. Sanya, Hainan, China,  April. BRICS Information Centre—University of Toronto. Available at http://www.brics.utoronto.ca/docs/leaders.html. BRICS () ‘BRICS and Africa: Partnership for Development, Integration and Industrialisation. EThekwini Declaration’. Durban, South Africa,  March. BRICS Information Centre—University of Toronto. Available at http://www.brics.utoronto.ca/docs/statement.html. BRICS () ‘Fortaleza Declaration’. th BRICS Summit,  July, Fortaleza, Brazil. BRICS Information Centre—University of Toronto. Available at http://www.brics.utoronto.ca/ docs/-leaders.html. BRICS (a) ‘ Ufa Declaration’. th BRICS Summit, Ufa, Russia,  July. BRICS Information Centre—University of Toronto. Available at http://www.brics.utoronto.ca/ docs/-ufa-declaration_en.html. BRICS (b) ‘Strategy for the BRICS Economic Partnership’. BRICS. Available at file:///C:/ Users/santiagf/Downloads/partnershipstrategy_eng.pdf. BRICS (a) ‘BRICS Action Agenda on Economic and Trade Cooperation’. BRICS. Available at http://economy.gov.ru/wps/wcm/connect/dc-ece--ae-cdfada/ .pdf?MOD=AJPERES&CACHEID=dc-ece--ae-cdfada. BRICS (b) ‘BRICS Leaders Xiamen Declaration’. BRICS. Available at http://www.brics. utoronto.ca/docs/-xiamen.html. BRICS (c) ‘Progress Report on the Implementation of the Strategy for BRICS Economic Partnership’. BRICS. Available at https://www.ranepa.ru/images/media/brics//BRICS %Strategy%Progress%Report_...pdf. BRICS () ‘BRICS in Africa: Collaboration for Inclusive Growth and Shared Prosperity in the th Industrial Revolution. Johannesburg Declaration’. th BRICS Summit, Johannesburg, South Africa,  July. BRICS Information Centre—University of Toronto. Available at http://www.brics.utoronto.ca/docs/-johannesburg.html. BRICS () ‘BRICS Information Portal’. Available at http://infobrics.org/. BRICS Industry Ministers () ‘Declaration of the BRICS Industry Ministers. Industrial Cooperation of the BRICS Countries: New Opportunities for Growth’. Moscow, Russia,  October. BRICS. Available at http://www.brics.utoronto.ca/docs/-indus try.pdf. BRICS Industry Ministers () ‘BRICS Heads Decide on a -Point Action Plan’. BRICS Information Portal. Available at http://infobrics.org/post/. BRICS Industry Ministers () ‘Declaration of the Third BRICS Industry Ministers’ Meeting’. TRALAC. Available at https://www.tralac.org/news/article/-declarationof-the-third-brics-industry-ministers-meeting.html. Brigante Deorsola, Adriana, Marcia Cristiane Martins Ribeiro Leal, Milene Dantas Cavalcante, Ingrid Jensen Schmidt, and Edimilson Junqueira Braga () ‘Intellectual Property and Trademark Legal Framework in BRICS Countries: A Comparative Study’, World Patent Information : –. Business Report () ‘Declaration of the BRICS Industry Ministers’. IOL Business Report. Available at https://www.iol.co.za/business-report/economy/declaration-of-the-bricsindustry-ministers-. Cable, Vince () ‘The Tech Titans Must Have Their Monopoly Broken—and This Is How We Do It’, The Guardian,  April.

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    



Carmody, Pádraig () ‘The Geopolitics and Economics of BRICS’ Resource and Market Access in Southern Africa: Aiding Development or Creating Dependency?’, Journal of Southern African Studies (): –. Cassella, Bruno () ‘Looking through Conduit FDI in Search of Ultimate Investors—a Probabilistic Approach’, Transnational Corporations: Investment and Development (): –. Available at https://unctad.org/en/PublicationsLibrary/diaeiad_en.pdf. Cimoli, Mario, Giovanni Dosi, and Joseph E. Stiglitz () The Political Economy of Capabilities Accumulation: The Past and Future of Policies for Industrial Development. Oxford: Oxford University Press. CSIR and DST () ‘A South African Additive Manufacturing Strategy’. Council for Scientific and Industrial Research and Department of Science and Technology. Available at https://site.rapdasa.org/wp-content/uploads///South-African-AdditiveManufacturing-Strategy.pdf. Cui, Yu, Jie Jiao, and Hao Jiao () ‘Technological Innovation in Brazil, Russia, India, China, and South Africa (BRICS): An Organizational Ecology Perspective’, Technological Forecasting and Social Change : –. Daudt, Gabriel and Luiz Daniel Willcox () ‘Reflexões Críticas a Partir Das Experiências Dos Estados Unidos e Da Alemanha Em Manufatura Avançada’, BNDES Setorial : –. Degaut, Marcos and Carl Meachan () ‘Do the BRICS Still Matter?’. Center for International and Strategic Studies. Available at http://enotus.com/wp-content/uploads// /Do-the-Brics-Still-Matter_.pdf. Di Maio, Michele () ‘Industrial Policy in the BRICS: Similarities, Differences, and Future Challenges’, in Wim Naudé and Nobuya Haraguchi (eds) Structural Change and Industrial Development in the BRICS. Oxford: Oxford University Press, pp. –. Dominguez Lacasa, Iciar, Björn Jindra, Slavo Radosevic, and Mahmood Shubbak () ‘Paths of Technology Upgrading in the BRICS Economies’, Research Policy (): –. Franco, Camila and Renan Henrique de Oliveira () ‘Inputs and Outputs of Innovation: Analysis of the BRICS: Theme —Innovation Technology and Competitiveness’, RAI Revista de Administração e Inovação (): –. Government of the Russian Federation () ‘Digital Economy Program of the Russian Federation’. Moscow: Government of the Russian Federation. Gray, Kevin and Barry K. Gills () Rising Powers and South–South Cooperation. London: Routledge. Gray, Kevin and Craig N. Murphy () ‘Introduction: Rising Powers and the Future of Global Governance’, Third World Quarterly (): –. Hallward-Driemeier, Mary and Gaurav Nayyar () Trouble in the Making? The Future of Manufacturing-led Development. Conference edition. Washington, DC: World Bank. Haraguchi, Nobuya, Charles Fang Chin Cheng, and Eveline Smeets () ‘The Importance of Manufacturing in Economic Development: Has This Changed?’, World Development : –. Hobday, Michael, Howard Rush, and John Bessant () ‘Approaching the Innovation Frontier in Korea: The Transition Phase to Leadership’, Research Policy (): –. Kahn, Michael, Luiz Martins de Melo, and Marcelo Pessoa de Matos () Financing Innovation: BRICS National Systems of Innovation. New Delhi: Routledge and IDRC. Kejin, Zhao () ‘The Limits of Cooperation among BRICS Countries’. Carnegie-Tsinghua Center (blog). Available at https://carnegietsinghua.org////limits-of-cooperationamong-brics-countries-pub-.

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

 

Kimenyi, Mwangi and Zenia Lewis () ‘The BRICs and the New Scramble for Africa’, in Foresight Africa: The Continent’s Greatest Challenges and Opportunities for . Washington, DC: Brookings Institution Press, pp. –. Available at https://www.brookings.edu/multichapter-report/foresight-africa-the-continents-greatest-challenges-and-opportunities-for-/. Lee, Keun (a) ‘Economics of Technological Leapfrogging’. Background paper for the UNIDO Industrial Development Report . Inclusive and Sustainable Development Working Paper Series. Vienna: United Nations Industrial Development Organization. Lee, Keun (b) The Art of Economic Catch-up: Barriers, Detours and Leapfrogging in Innovation Systems. Cambridge: Cambridge University Press. Lee, Keun and Franco Malerba () ‘Theory and Empirical Evidence of Catch-up Cycles and Changes in Industrial Leadership’, Research Policy (): . Lee, Keun, Chan-Yuan Wong, Patarapong Intarakumnerd, and Chaiyatorn Limapornvanich () ‘Is the Fourth Industrial Revolution a Window of Opportunity for Upgrading or Reinforcing the Middle-income Trap? Asian Model of Development in Southeast Asia’, Journal of Economic Policy Reform. Available at https://doi.org/./.. . Li, Ling () ‘China’s Manufacturing Locus in : With a Comparison of “Made-inChina ” and “Industry .” ’, Technological Forecasting and Social Change ©: –. Liu, Xielin, Sylvia Schwaag Serger, Ulrike Tagscherer, and Amber Y. Chang () ‘Beyond Catch-up—Can a New Innovation Policy Help China Overcome the Middle-income Trap?’, Science and Public Policy (): –. López-Gómez, Carlos, David Leal-Ayala, Michele Palladino, and Eoin O’Sullivan () ‘Emerging Trends in Global Advanced Manufacturing: Challenges, Opportunities and Policy Responses’. United Nations Industrial Development Organization and University of Cambridge’s Institute for Manufacturing. Mahrenbach, Laura, Katja Mayer, and Jürgen Pfeffer () ‘Policy Visions of Big Data: Views from the Global South’, Third World Quarterly (): –. Marr, Bernard () ‘Here’s Why Data is Not the New Oil’, Forbes (blog). Available at https://www.forbes.com/sites/bernardmarr////heres-why-data-is-not-the-new-oil/. Mayer, Jörg () ‘Digitalization and Industrialization: Friends or Foes?’. Research Paper No. . Geneva: UNCTAD. Available at https://unctad.org/en/pages/PublicationWebflyer. aspx?publicationid=. Mbele, Sizwe () ‘Opportunity Africa: Will the BRICS Countries Manage Mutual Cooperation?’. BRICS. Available at http://infobrics.org. Mittelman, James H. () ‘Repositioning in Global Governance: Horizontal and Vertical Shifts amid Pliable Neoliberalism’, Third World Quarterly (): –. Nelson, Richard R. () ‘The Co-Evolution of Technology, Industrial Structure, and Supporting Institutions’, Industrial and Corporate Change (): –. New Development Bank (a) ‘History’. New Development Bank (blog). Available at https://www.ndb.int/about-us/essence/history/. New Development Bank (b) ‘NDB Board of Governors and Board of Directors Meetings Held in Cape Town, South Africa’. New Development Bank (blog). Available at https:// www.ndb.int/press_release/ndb-board-governors-board-directors-meetings-held-cape-townsouth-africa/. New Development Bank (c) ‘New Development Bank (NDB) Outlines Ambitious Plans to Boost Loans, Increase Impact of Investment’. New Development Bank (blog). Available

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    

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at https://www.ndb.int/press_release/new-development-bank-ndb-outlines-ambitious-plansboost-loans-increase-impact-investment/. OECD () ‘China and the Next Production Revolution’, in The Next Production Revolution: Implications for Governments and Business. Paris: Organisation for Economic Cooperation and Development, pp. –. O’Neill, Jim () ‘Building Better Global Economic BRICs’. Global Economics Paper, Goldman Sachs. O’Neill, Jim () ‘Jim O’Neill: Revisiting the Next BRIC Economies’. Available at https:// www.fnlondon.com/articles/jim-oneill-revisiting-the-next-bric-economies-. O’Neill, Jim, Dominic Wilson, and Roopa Purushothaman () ‘How Solid are the BRICs?’. Global Economics Paper, Goldman Sachs. Oxford Economics and Global Infrastructure Hub () ‘Global Infrastructure Outlook: Infrastructure Investment Needs  Countries,  Sectors to ’. Oxford Economics. Available at https://outlook.gihub.org/. Rodriguez-Arango, Liliana, and Maria Alejandra Gonzalez-Perez () ‘Giants from Emerging Markets: The Internationalization of BRIC Multinationals’, in Rob Van Tulder, Alain Verbeke, Jorge Carneiro, and Maria Alejandra Gonzalez-Perez (eds) The Challenge of BRIC Multinationals. Progress in International Business Research . Bingley: Emerald Group Publishing, pp. –. Roland Berger GMBH () ‘Skill Development for Industry .: White Paper Summary’. BRICS Business Council, India Section. Available at http://www.ficci.in/spdocument/ /Whitepaper-brics-skill.pdf. Santiago, Fernando () ‘Innovation Policy and Industrial Policy at the Crossroads: A Review of Recent Experiences in Advanced Developing Countries’. Inclusive and Sustainable Development Working Paper No. /. Vienna: UNIDO, Research, Statistics and Industrial Policy Branch. Santiago, Fernando () ‘You Say You Want A Revolution: Strategic Approaches to Industry . in Middle-income Countries’. Inclusive and Sustainable Development Working Paper No. . Vienna: UNIDO, Research, Statistics and Industrial Policy Branch. Scerri, Mario and Helena Maria Martins Lastres (eds) () The Role of the State: BRICS National Systems of Innovation. New Delhi and Abingdon: IDRC and Routledge. Schwab, Klaus () The Fourth Industrial Revolution. New York: Crown Business. Simachev, Yuri, Mikhail Kuzyk, Boris Kuznetsov, and Evgeniy Pogrebnyak () ‘Russia on the Path towards a New Technology Industrial Policy: Exciting Prospects and Fatal Traps’, Foresight-Russia (): –. Sing, Parminder Jeet () ‘Digital Industrialisation in Developing Countries—A Review of the Business and Policy Landscape’. Bangalore: IT for Change. Available at http:// itforchange.net/sites/default/files//Digital-industrialisation-May-.pdf. Steinmueller, Edward () ‘ICTs and the Possibilities for Leapfrogging by Developing Countries’, International Labour Review (): –. Stiglitz, Joseph E. () ‘Industrial Policy, Learning, and Development’, in John Page and Finn Tarp (eds) The Practice of Industrial Policy: Government–Business Coordination in Africa and East Asia. WIDER Studies in Development Economics. Oxford: Oxford University Press, pp. –. The Economist () ‘Made in China?’, The Economist,  May. Available at http://stage. economist.com/news/leaders/-asias-dominance-manufacturing-will-endure-willmake-development-harder-others-made.

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 

Tourk, Khairy and Peter Marsh () ‘The New Industrial Revolution and Industrial Upgrading in China: Achievements and Challenges’, Economic and Political Studies (): –. UIS () ‘How Much does your Country Invest in R&D?’. Available at http://www.uis. unesco.org/_LAYOUTS/UNESCO/research-and-development-spending/index-en.html. UNCTAD () ‘Global Investment Trends Monitor’. Global Investment Trends Monitor No. . Geneva: United Nations Conference on Trade and Development. Available at https://unctad.org/en/PublicationsLibrary/webdiaeiad_en.pdf. UNCTAD () ‘World Investment Report ’. Geneva: United Nations Conference on Trade and Development. Available at https://unctad.org/en/pages/PublicationWebflyer. aspx?publicationid=. UNIDO () ‘Industrial Development Report /: Competing through Innovation and Learning’. Vienna: United Nations Industrial Development Organization. UNIDO () ‘Industrial Development Report : Capability Building for Catching-up. Historical, Empirical and Policy Dimensions’. Vienna: United Nations Industrial Development Organization. UNIDO () ‘Competitive Industrial Performance Report ’. Biennial CIP Report. Vienna, Austria: United Nations Industrial Development Organization. Available at https://www.unido.org/sites/default/files/files/–/CIP.pdf. UNIDO () ‘Industrial Development Report . Industrializing in the Digital Age’. Vienna: United Nations Industrial Development Organization. Vértesy, Dániel () ‘Interrupted Innovation: Emerging Economies in the Structure of the Global Aerospace Industry’, PhD thesis, Maastricht University. Wilson, Dominic and Roopa Purushothaman () ‘Dreaming with BRICs: The Path to ’. Global Economics Paper, Goldman Sachs.

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        ......................................................................................................................

            

......................................................................................................................

 

. I: I P  E D

.................................................................................................................................. T increase in the share of the service sector, especially of trade and finance, at the expense of industry (de-industrialization) occurred in all post-communist economies. Previously in the centrally planned economies, the service sector, in particular trade and finance, was underdeveloped. In Russia, for instance, the share of industry in GDP fell from about half in  to about one-third by the mid-s, whereas in industry itself the share of the primary sector (fuel, energy, steel, and non-ferrous metals) in total industrial output increased from  per cent to over  per cent, and the share of secondary manufacturing declined accordingly (Popov, ). Part of the decline was due to the change in relative prices (domestic prices for resources and services increased more than for manufactured and agricultural goods), but relative changes in physical output also played a role—real decline in secondary manufacturing and agriculture was more pronounced than in services and resource industries. The structure of exports in most post-communist states has also become more primitive in the past two decades—the share of manufactured goods in total exports either declined or did not show any clear tendency towards increase. This was partly

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

 

due to the increase in resource prices and the resource boom—the expansion of fuel production and exports in Azerbaijan, Kazakhstan, Russia, Turkmenistan, and Uzbekistan. In Russia, the share of fuel, minerals, metals, and diamonds in total exports grew from  per cent in  (USSR) to  per cent in  and to  per cent in , whereas the share of machinery and equipment fell from  per cent in  (USSR) to  per cent in  and to . per cent in . But the real shifts (in constant prices) were also in favour of resources at the expense of ready-made goods. International comparison of the structure of the economy at different stages of development may provide some insights into what kind of structural shifts occur during the transition from the agricultural to the industrial stage and to the postindustrial stage. The Chenery hypothesis (Chenery, ) predicts changes in the relative shares of three major sectors of the economy (agriculture, industry, services) in the process of economic development. The data suggest that the share of agriculture constantly decreases, the share of services constantly increases, whereas the share of manufacturing increases before countries reach a level of per capita income of about , international dollars of  (ln  = .), that is, about , in today’s prices, and then declines. To put it differently, at a stage of development of below $, GDP per capita in today’s prices, resources were transferred from agriculture to industry and services, whereas after the level of $, per capita GDP, resources were transferred from both agriculture and industry to services (i.e. the service sector was growing at the expense of not only agriculture, but also industry) (Herrendorf et al., : figure ). The level of development, of course, is not the only determinant of the structure of the economy. The other determinants are the size of the economy and its resource endowment, as was pointed out in the early literature on the issue. Syrquin and Chenery () concluded that higher income growth and more marked transformation are found among countries with large populations, a predominance of manufactures in exports, and a larger role of exports. Changes in industrial structure are not the result of the ‘invisible hand of the market’ alone. As Greenwald and Stiglitz (, ) state, market failures are pervasive; private rewards and social rewards virtually always differ, so governments are inevitably involved in shaping the industrial structure of the economy, both by what they do and by what they do not do. As many authors point out, the secret of ‘good’ industrial policy in East Asia, as opposed to ‘bad’ industrial policy in the former Soviet Union, Latin America, and Africa may be associated with the ability to reap the benefits of export externalities (Khan, ; Gibbs, ). Exporting to world markets, especially to developed countries, enables the upgrading of quality and technology standards and yields social returns in excess of returns to particular exporters. The greatest increases in productivity are registered at companies that export to advanced (Western) markets and that export high-tech goods (Harris and Li, ; Shevtsova, ). It has been also shown that the gap between the actual level of development (per capita income) and the hypothetical level that corresponds to the degree of sophistication of a country’s exports is strongly correlated with productivity growth rates (Hausmann et al., ).

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        



To put it differently, it pays to promote exports of sophisticated and high-tech goods. Not all the countries that try to promote such exports succeed, but those that do not try, virtually never engineer growth miracles.¹ It should be noted though that there is an opposite view—for instance, the recent World Bank paper (Gill et al., ). It concludes that it is not clear whether diversifying exports and production is necessary for development and that governments need to worry less about the composition of exports and the profile of production and more about national asset portfolios—the blend of natural resources, built capital, and economic institutions.

. O  C   S  E  P- C

.................................................................................................................................. After the fall of the Berlin Wall (), the collapse of the Union of Soviet Socialist Republics (USSR, ), and market-oriented reforms in successor states, the performance in the post-Soviet space varied greatly (Figure .). In retrospect, it is obvious that rapid economic liberalization did not pay off: many gradual reformers from the former Soviet Union in this region performed better than the champions of ‘big bang’ liberalization—the Baltic states and Central Europe. In Turkmenistan and Uzbekistan, for instance, privatization was rather slow—over  per cent of their GDP is still produced at state enterprises, but their performance is superior to that of more liberalized economies. Resource abundance has definitely helped resource exporters, such as Azerbaijan, Kazakhstan, and Turkmenistan, to maintain higher incomes recently, when resource prices were high, but was not a sine qua non for growth— resource-poor Tajikistan, as well as Uzbekistan, self-sufficient in fuel and energy, did much better than resource-rich Russia (Figure .). As past research shows, the crucial factor in economic performance was the ability to preserve the institutional capacity of the state (Popov, , ,  for a survey). The story of transition was very much a government failure, not a market failure story.

¹ One exception could be Botswana, which had one of the highest rates of per capita GDP growth in the last fifty years ( per cent during ‒), primarily driven by exports of primary commodities (namely, diamonds) and not of high-tech goods. The other exception may be Oman: out of twenty economies with average growth rates of GDP per capita in ‒ of  per cent and more a year, Oman was the only oil-rich state (nearly  per cent growth a year) (Popov and Jomo, ). True, many other oil and gas exporters in the Persian Gulf and elsewhere quickly became rich in recent decades, but not due to higher growth rates of output (it was moderate), but due to the improvement of the terms of trade—their income from resource exports grew much faster than their output and exports.

OUP CORRECTED PROOF – FINAL, 21/9/2020, SPi



 

370

320

270

Turkmenistan Uzbekistan Azerbaijan Kazakhstan Tajikistan Central Europe Belarus Estonia Kyrgyzstan Armenia Lithuania Latvia Russia Georgia

220

170

120

Moldova Ukraine

70

99

97

95

01 20 03 20 05 20 07 20 09 20 11 20 13 20 15 20 17

20

19

19

19

91

93 19

19

19

89

20

 . GDP change in economies of the former Soviet Union,  = % Note: Central Europe is the unweighted average for Czech Republic, Hungary, Poland, Slovakia, and Slovenia. Source: EBRD Transition Reports for various years.

In all former Soviet republics and in Eastern European countries, government spending fell during transition and the provision of traditional public goods, from law and order to health care and infrastructure, worsened. This led to an increase in crime, the shadow economy, income inequalities, corruption, and mortality. But in countries with the smallest decline in government spending (countries very different in other respects—from Central European states to China and Vietnam and to Uzbekistan), these effects were less pronounced, and the dynamics of output was better (Popov, ). China carried out gradual reforms from , Vietnam, gradual reforms in ‒ and radical reforms in , but both countries managed to avoid the

OUP CORRECTED PROOF – FINAL, 21/9/2020, SPi

        



transformational recession² due to their ability to preserve state institutional capacity (Popov, ). All former communist countries had centrally planned economies and all of them inherited distortions in industrial structure and interregional trade patterns created by central planning. Central planners gave high priority to industry, especially heavy and high-tech industries (at the expense of resources industries and agriculture) and to selfsufficiency achieved through import-substitution policy. As a result, secondary manufacturing industries took a high share of the national economy (as compared to other countries with similar per capita incomes), but they were less efficient and competitive. After the deregulation of prices and the opening of the economy, market forces were allowed to influence the allocation of resources and most secondary manufacturing and high-tech industries proved to be uncompetitive, so their output shrank. All former communist countries (with the exception of China and Vietnam) experienced transformational recession, de-industrialization and a decline in R&D potential in the s after the transition to the market economy. There was also rapid ‘resource-ialization’ after the transition to the market in . An increase in the share of the service sector, especially trade and finance, at the expense of industry (de-industrialization) occurred in all post-communist economies. It seems, however, that in many of these economies de-industrialization went too far. In Eastern European countries, especially in the countries of Central Europe (Czech Republic, Hungary, Poland, Slovenia, Slovakia) the decline was less pronounced than in many former Soviet Union (FSU) countries. In Tajikistan, for example, the share of services in GDP nearly doubled, increasing from about  per cent in the early s to  per cent in , whereas the share of manufacturing in GDP fell from  per cent in  to  per cent in  (Figures ., ., and .). In Armenia, the share of industry fell from  per cent in  to  per cent in  and the share of manufacturing, from about  per cent to  per cent, whereas the share of services increased from about  to  per cent in the late s/early s, and to over  per cent in . In resource-rich FSU countries, the decline of the share of manufacturing was most dramatic—it was driven not only by the expansion of the service sector, but also by the expansion of the resource industries that became most competitive with the new price ratios. The contrast with China and Vietnam—two countries with active industrial policies to support export-oriented manufacturing—was extremely pronounced. In Azerbaijan, Kazakhstan, and Russia the share of manufacturing fell below the level of much poorer Vietnam ( per cent), not to mention China ( per cent). A comparison of Figures . and . is quite instructive. The share of manufacturing in total value added (GDP) has declined in almost all post-communist countries

² While Vietnamese industry, excluding constantly and rapidly growing oil production, experienced some downturn in ‒ (– per cent in  and  per cent in ) agricultural growth remained strong, so that GDP growth rates remained virtually stable at ‒ per cent a year.

OUP CORRECTED PROOF – FINAL, 21/9/2020, SPi



  Non-resource-rich FSU and Mongolia

Eastern European countries 44 29

39 Czech Republic Slovenia Slovak Republic Romania Hungary Poland Lithuania Serbia Bulgaria Estonia Croatia Latvia

24

19

14

Belarus Kyrgyz Republic Ukraine Moldova Georgia Armenia Tajikistan Mongolia

34 29 24 19 14 9

1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 2017

4 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 2017

9

China, Vietnam and resource-rich FSU 39

34

29

China

24

Turkmenistan Vietnam Russian Federation Kazakhstan

19

Azerbaijan

14

4

1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 2017

9

 . Share of manufacturing value added in GDP in post-communist transition countries between  and , % Source: World Development Indicators (there is no data for Uzbekistan in WDI).

and is now at a very low level of  to  per cent (Figure .), whereas in the late s it was at a level of about  to  per cent. And of course this share is way lower than in China, where it has remained at a level of about  per cent in recent years, considerably higher than in other developing countries.

OUP CORRECTED PROOF – FINAL, 21/9/2020, SPi

        



Eastern European countries 65

Non-resource-rich FSU and Mongolia 55

60 Bulgaria

55

50

Czech Republic Estonia

50

45

Croatia Hungary Bosnia and Herzegovina Lithuania

45

40

Mongolia

40

Belarus Tajikistan

35

Kyrgyz Republic

Latvia Slovak Republic

Armenia 30

Ukraine

Slovenia

35

Poland Serbia

30

Georgia Moldova

25

Romania 20 25 15 20 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 2017

2017

2015

2013

2011

2009

2007

2005

2003

2001

1999

1997

1995

1993

1991

1989

1987

1985

10 15

China, Vietnam and resource-rich FSU 70

60

Turkmenistan 50

Azerbaijan China Vietnam

40

Kazakhstan Russian Federation Uzbekistan

30

20

1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 2017

10

 . Share of industry value added in GDP of post-communist countries, –, % Source: World Development Indicators.

The share of industry as a whole (which includes not only manufacturing, but also mining and utilities—electricity and gas distribution; Figure .),³ as a rule of thumb, despite sharp fluctuations, did not decline much in resource-rich countries (Azerbaijan, Kazakhstan, Russia, Turkmenistan), but declined in non-resource-rich countries. The only exception is Uzbekistan, which has a medium resource abundance (self-sufficient in energy), but managed to increase the share of industry to over  per cent after it fell from  to below  per cent in ‒ (Figure .). The structure of exports in most post-Soviet states has also become more primitive in the last two decades; the share of manufactured goods in total exports either declined ³ Unfortunately, there are no comparable statistics on the shares of mining and utilities separately.

OUP CORRECTED PROOF – FINAL, 21/9/2020, SPi



 

90

80

70 Kazakhstan

60

China Armenia

50

Kyrgyz Republic Uzbekistan

40

Azerbaijan Afghanistan

30

Tajikistan Turkmenistan

20

10

19

8 19 5 87 19 89 19 91 19 93 19 95 19 97 19 99 20 01 20 03 20 05 20 07 20 09 20 11 20 13 20 15 20 17

0

 . Share of service value added in GDP in selected post-communist countries, –, % Source: World Development Indicators.

or did not show any clear tendency towards increase. Perhaps surprisingly, Kyrgyzstan was the only country where the share of manufacturing exports in total exports increased (Figure .).

. S E T  I P

.................................................................................................................................. The crucial question, of course, is whether the government should participate in the process of structural shifts (and if yes, then how), or whether the structure of the economy should be totally determined by market forces. Government preferences (tax, trade, credit, other) for particular industries are called industrial policy and the huge literature on industrial policy (see Popov, , for a summary) focuses on three key issues:

OUP CORRECTED PROOF – FINAL, 21/9/2020, SPi

        



100 90 80

China Kyrgyz Republic Georgia Armenia Russian Federation Kazakhstan Afghanistan Azerbaijan Tajikistan Turkmenistan

70 60 50 40 30 20 10

07

05

20

03

20

01

20

99

20

97

19

95

19

93

19

91

19

19

19

89

0

09 011 013 015 017 2 2 2 2

20

 . Manufacturing exports, % of merchandise export, in some post-communist countries Source: World Development Indicators.

. Is industrial policy necessary for successful development or does the market know better how to allocate resources? . If industrial policy is needed, how should industries that need to be supported be selected? . What are the appropriate tools/instruments to support particular industries? To give one example of what industrial policy can do, consider a resource-rich country that previously (under central planning) favoured secondary manufacturing and now (after transition to the market and the change in relative prices of resources and ready-made goods) is experiencing, under the pressure of market forces, the reallocation of capital and labour from manufacturing to mining and primary manufacturing (oil, gas, electric energy, diamonds, steel, non-ferrous metals). Available calculations of total factor productivity show that in resource-rich countries, such as Azerbaijan, Kazakhstan, Russia, Turkmenistan, Uzbekistan, it is much higher in mining than in other industries, with the possible exception of trade and finance (Popov, , ; Gharleghi and Popov, b). No wonder that capital and labour are being reallocated from non-resource to resource industries. Should the government just observe the process without interfering, should it oppose the market forces, or should it try to promote structural shifts already under way to ensure that they happen faster? And what tools should be used to promote desirable shifts: subsidies, cheap credits, tax concessions, import tariffs, or exchange rate management?

OUP CORRECTED PROOF – FINAL, 21/9/2020, SPi



 

Page () argues that Africa should industrialize because without structural change it cannot sustain recent growth. Economies with more diverse and sophisticated industrial sectors tend to grow faster. But since  Africa has de-industrialized. Page’s paper shows that between  and  the size, diversity, and sophistication of industry in Africa have all declined. He argues that an industrialization strategy containing two elements is needed: ▪ The first is straightforward: refocusing current investment climate reforms on infrastructure, skills, and regional integration. These actions alone will not be sufficient, however. ▪ Africa must also learn to compete through strategies to create an export push, develop industrial clusters, and attract task-based production. A recent IMF paper (Cherif and Hasanov, ) highlights the key role of industrial policy in the Asian miracles, for the United States after the Civil War, for Germany under Bismarck, and for Japan after the Meiji Restoration. Jomo () argues that East Asian industrial policies contributed to the economic miracle stories and, despite the current conventional wisdom, can be successfully emulated by other developing countries. Stiglitz (), however, states that export-led growth was the model behind the twentieth-century growth miracles. There was unprecedented growth in East Asia— closing the gap in income per capita and standards of living with the advanced countries. That model, he claims, will not work in the future in the way and to the extent that it did in the past. He suggests a multi-pronged strategy for developing countries, entailing a combination of manufacturing, agriculture, services, and natural resources. It is always difficult, of course, to predict the efficiency of the growth model. The famous example is that of Gunnar Myrdal () who in his Asian Drama was extremely pessimistic about the prospects of Asian future growth exactly at a time when Asian dragons and tigers were taking off to propel themselves out of poverty and become economic miracles.

. I P: W I  S?

.................................................................................................................................. As the UN ESCAP () report on diversification states: Implementing strategic diversification requires an industrial policy—the selective promotion of particular economic activities over others. Here, new economic activities should be promoted that would encourage greater levels of product

OUP CORRECTED PROOF – FINAL, 21/9/2020, SPi

        



complexity and allow for further diversification in the future. Active public intervention is required that is aimed at supporting infant industries and creating the necessary complementary productive infrastructure, including industrial estates and economic zones. Intervention would also be aimed at encouraging marketing and export market development, together with other promotional measures under industrial policy. (UN ESCAP, : viii)

Not only is industrial structure shaped by the development process; it also has important implications for economic development. The Chenery hypothesis (Chenery, ) states that countries at similar levels of economic development should have similar patterns of resource allocation between sectors. But in theoretical models it is often assumed that there are externalities from industrialization and industrial export (Murphy et al., ; Polterovich and Popov, , ). There is growing evidence that countries which are more industrialized and countries with more technologically sophisticated industrial exports are growing faster than others (Hausmann et al., ; Rodrik, ). The important stylized fact is that no economic miracle in the developing world was based either on agricultural or service industries. A Canadian economist, Harrold Innis, was the author of the staple theory of economic development (Innis, ). He claimed that Canadian economic (and not only economic, but also social and cultural) development was determined by exports of staple goods, in chronological order since the seventeenth century: furs, fish, lumber, wheat, mined metals, and coal. It could be also claimed that some countries that are now members of the ‘rich-country club’ made their fortunes on resource and agricultural exports; examples would be (in addition to Canada) Australia, New Zealand, and the United States. But by the twentieth century, after the income gap between developed and developing countries widened, cases of successful catch-up development (Popov and Jomo, ) were associated with manufacturing exports, not with exports of agricultural or resource commodities. Oil-rich countries, like Persian Gulf states or Equatorial Guinea, which have now achieved developed-country levels of per capita income, did so due to terms-of-trade improvement (increase in fuel prices), not due to exceptionally high rates of growth of output (Oman is the exception, see footnote ). The reduction in the share of industry and manufacturing in GDP and the increase in the share of services is an objective process; but in fast-growing countries (e.g. China), this decline was slower than in others with a similar level of development (Figures ., ., and .). The increase in the share of machinery and equipment in manufacturing output, as in China, usually accompanies rapid growth or even becomes the engine of growth. We are not aware of cases of rapid growth (‘economic miracles’) that are based on accelerated growth of the service sector. The question ‘What are the particular manufacturing industries which could become the engine of growth?’ is a difficult one (Popov and Chowdhury, ). Unfortunately, economic theory does not suggest any definite clues, with the exception of the idea that these industries should have the highest externalities, that is, their social returns should

OUP CORRECTED PROOF – FINAL, 21/9/2020, SPi



 

be higher than private returns. Yet, it is not easy to measure these externalities. Nevertheless, upon examination of the literature and the experience of countries with industrial policy, it is possible to isolate methods which can aid in identification of industries that should be supported. For example, one can support several industries which seem promising on condition that assistance ends if the increase in exports is not achieved within, say, five years. This is called ‘EPconEP’—effective protection conditional on export promotion (Jomo, ). Economic policymakers in this case are similar to the military commander who begins an offensive on several fronts, but throws reserves at where there has been a breakthrough. Alternatively, one can attempt to determine specific industries where limited investment can produce the greatest effect, leading to the creation of globally competitive production. These are most likely to be industries that lag behind the most advanced countries in total factor productivity, but not so much as other industries. It is also possible to choose at random. In this case, it is important to be consistent by embarking on the path of support for a particular industry and not withdrawing even if there is no immediate success or breakthrough in world markets. After all, the modern theory of international trade explains country specialization not by comparative advantages, but rather by ‘learning by doing’. If a country does not have any comparative advantage, like post-war Japan for example, it is necessary to create them (‘dynamic comparative advantages’) by mastering the production of goods that have not been produced before. Supporting such production and consistently encouraging exports for some time without giving up is likely to have the learning-by-doing effect, allowing the country to gradually become competitive. There are two opposing views on how technologically advanced industries supported in the framework of industrial policy ought to be. Justin Lin, former chief economist of the World Bank, developed the idea of comparative-advantages-following (CAF) and comparative-advantages-defying (CAD) industrial strategy. The best result, according to his argument, can be achieved if countries develop industries that are consistent with their comparative advantages, as determined by their endowment structure, and do not try to bypass necessary stages aiming at exporting the goods which are exported by very advanced countries (Lin, ). Middle-income oil-rich countries, like Kazakhstan and Azerbaijan, for instance, according to this logic, should aim at developing heavy chemical, not computer industries. This view is consistent with the ‘flying geese’ paradigm: as more competitive countries move to more advanced types of exported products, the vacated niches are occupied by less developed countries. It is known that relatively poor countries began to export textiles and shoes, then moved on to the export of steel products and heavy chemicals, then to the export of cars and electrical consumer products such as washing machines and refrigerators, then to consumer electronics and computers. Newcomers can benefit from the experience of other countries by trying to replicate their success.

OUP CORRECTED PROOF – FINAL, 21/9/2020, SPi

        



The transition from one exported good to another could be dictated by the cycle of innovations. As Lee () suggests, the cycle is short for electronics and long for pharmaceuticals and chemicals. This may explain why East Asian countries which focused mostly on industries with short cycles managed to avoid growth slowdowns while moving from one export niche to another. The debate between Justin Lin and Ha-Joon Chang (Lin and Chang, ) is telling in this respect. The latter was defending the idea of CAD industrial policy which favours industries that defy the country’s comparative advantages. Such industries take time to develop, yet they can be worthwhile. For example, ‘Japan had to protect its car industry with high tariffs for nearly four decades, provide a lot of direct and indirect subsidies, and virtually ban foreign direct investment in the industry before it could become competitive in the world market. It is for the same reason that the electronics subsidiary of the Nokia group had to be cross subsidized by its sister companies for  years before it made any profit. History is full of examples of this kind, from eighteenth-century Britain to late twentieth-century Korea’ (Lin and Chang, ). Hausman, Hwang, and Rodrik’s position (Hausmann et al., ; Rodrik, ) may be rather different from Chang’s CAD strategy and the policy of promoting high-tech industries and R&D in relatively poor countries. The CAD strategy does not necessarily imply a transition to more technologically sophisticated industries, but rather, to industries that are not linked to the comparative advantages of a particular country. Theoretically, it could be a transition from chemicals to machine building with the same, or even a lower, level of R&D intensity and technological sophistication. Hausman, Hwang, and Rodrik’s idea is that externality benefits from the production and export of new products are proportional to the degree of their technological sophistication, which is measured by the comparison of the export structures of rich versus poor countries. High-income countries export on average more high-tech products. Developing high-tech production in poor countries may be costly, yet the returns from such a policy can be greater. It may well pay a relatively poor country to make ‘a big leap forward’ by investing heavily in the education of the labour force and high-tech industries, bypassing the intermediate stages of producing goods with medium research intensity. Uzbekistan, for instance (a low-income country, not even a middle-income country), started to invest massively in the development of the auto and heavy chemical industries at the stage of development at which other countries export mostly resource goods, textiles, and leather products. It remains to be seen whether these investments will be justified (see Box .). Rodrik et al. () consider two sources of productivity growth: within the industry; and due to structural shifts, that is, reallocation of resources to more productive industries. Which is more efficient: relying on productivity growth within existing industries or promoting structural shifts from less productive to more productive industries? In a similar vein, Rodrik () describes two approaches to development: bottom up and top down. The former focuses directly on the poor, and on delivering services, such as education, health care, and microcredit, to their communities. As Reddy ()

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

 

Box 27.1 What Uzbekistan knows about industrial policy that other countries do not know In the last two decades the economy of Uzbekistan has been extremely successful—high growth ( per cent), low unemployment and reasonable macroeconomic stability, low domestic and international debt, relatively low inequality. Even more impressive are the structural shifts that have happened in less than thirty years since Uzbekistan became an independent country: () decrease in production and export of cotton (which was previously a mono culture), increase in food production and achievement of self-sufficiency in food; () achievement of self-sufficiency in energy and becoming a net fuel exporter; () increase in the share of industry in GDP and the share of machinery and equipment in industrial output and export (a competitive export-oriented auto industry was created from scratch) (Popov, , ). In recent years Uzbekistan has promoted heavy chemical industries (production of synthetic fuel and polypropylene goods from natural gas). This is the next stage of industrial policy after reaching food and energy self-sufficiency and successful autoindustry development. In  it became the fifteenth country in the world to launch a high-speed train line, between Tashkent and Samarkand (it was continued to Bukhara and Karshi in  and ). The train is made by Spanish company Talgo and travels the  km between Tashkent and Bukhara in  hours  minutes. Uzbekistan’s development achievements, even though not as spectacular as those of China, have been due to deliberate government policies. True, Uzbekistan enjoyed a favourable external environment, but its rapid growth is due to reasonable macroeconomic stability and industrial policies rather than simply to market reforms that triggered growth conforming to its factor endowment and/or natural comparative advantages. What makes Uzbekistan different and even unique is its low exchange rate policy. It promotes export-oriented development, similar to Japan in the s to s, South Korea in the s to s and China and the ASEAN countries since the s (Dollar, ; Easterly, ; Polterovich and Popov, ; Rodrik, ; Bhalla, ). Undervaluation of the exchange rate via accumulation of foreign exchange reserves becomes a powerful tool of industrial policy creating stimuli for tradable goods at the expense of nontradables (Greenwald and Stiglitz, ). Other former communist countries of Eastern Europe and the USSR did not implement such a policy; on the contrary, their exchange rates were and often are overvalued, especially in countries that export resources (they suffer from the ‘Dutch disease’). Since  Uzbekistan has probably been the only country in the post-Soviet space that has carried out gradual, predictable nominal devaluation of the currency to a slightly greater extent than is needed to counter the differences in inflation rates between Uzbekistan and its major trading partners, so that the real effective exchange rate is depreciating slowly. The real exchange rate of the som versus the US dollar has appreciated a bit, though not as much as currencies of other countries. However, the real effective exchange rate (i.e. with respect to currencies of all major trading partners) decreased by over  per cent in ‒—a sharp contrast with other countries of the region on which data are available. The relatively successful economic performance of the country is even more impressive given that Uzbekistan is not a major oil and gas exporter and is one of two doubly landlocked countries in the world—that is, a country completely surrounded by other landlocked countries (the other being Liechtenstein).

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        



Uzbekistan remains a poor country, with PPP GDP per capita of below US$, in  against over $, in Russia and Kazakhstan, $, in Azerbaijan, and over $, in Turkmenistan; and many Uzbeks are migrating to find work in Russia, not vice versa. It is important, however, to distinguish between growth rates and the level of per capita income. It is necessary to separate the effects associated with the dynamics of output from the effects of the terms of trade and financial flows. At the end of the Soviet era, in the s, real incomes in Uzbekistan were about half those in Russia. After the collapse of the USSR real incomes in non-resource republics fell dramatically due to the change in relative prices—oil, gas, and other resources became several times more expensive relative to ready-made goods (Uzbekistan was a large importer of oil and its trade with all countries, including other Soviet republics, if recalculated in world prices, yielded a deficit of  per cent of GDP; IMF, ). To add insult to injury, with the collapse of the Soviet Union financial flows from Moscow dried up (in  inter-budgetary transfers—from the Union budget—amounted to  per cent of the revenues of the republican budget; IMF, ). Diversification in industry and expansion of manufacturing exports was mostly the result of protectionism and the government/central bank’s low exchange rate policy. Like China, Uzbekistan maintained a low (undervalued) exchange rate due to rapid accumulation of foreign exchange reserves. In addition, there were non-negligible tax measures to stimulate exports of processed goods ( per cent lower tax rate for manufacturing companies that export  per cent or more of their output). Although comparable statistics from WDI for Uzbekistan are lacking, national statistics suggest that the share of nonresource goods in exports increased to over  per cent against less than  per cent in  before independence (Popov, , ).

explains, this tradition’s motto could be: ‘Development is accomplished one project at a time.’ The other approach takes an economy-wide perspective. It emphasizes broad reforms that affect the overall economic environment, and thus focuses on areas such as international trade, finance, macroeconomics, and governance. The first approach uses widely randomized controlled trials as an instrument that could allow good policies to be formulated: vaccinations and microcredit, additional teachers in schools, and mosquito nets dipped in insecticide being examples of small projects that are leading to big breakthroughs. But without reforms at the macro level it is often impossible to ensure the efficiency of micro projects (Reddy, ). If assistance provided for particular investment projects merely crowds out government or private investment in other areas, the macro impact of the assistance will be zero. As Rodrik () writes, ‘poverty is often best addressed not by helping the poor be better at what they already do, but by getting them to do something different’. This latter approach is exactly the one defended here: the global South can gain much more from economy-wide reforms aimed at promoting export-oriented growth based on domestic savings than from meagre official foreign assistance or even from all foreign financing. A benevolent Western attitude to macro-structural reforms and industrial

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

 

policy would be more beneficial to catch-up development than a thousand minor specific development projects with noble goals. A UN ESCAP study () suggests that there is a strong link between the share of manufacturing in GDP and the share of the poor in total population. It predicts that industry-oriented structural transformation that enhances agricultural productivity through sustainable agriculture and overall efficiency improvements through innovations has the potential to lift an additional  million people out of poverty, create  million additional jobs in South Asia and boost GDP by  to  per cent by  over and above the business-as-usual scenario.

. I P: W T  U?

.................................................................................................................................. Industrial policy tools can be divided into two broad categories: selective and nonselective. Selective tools are those that apply to specific industries, regions, and companies. Examples are import duties, subsidies, tax concessions. Non-selective tools are government investment in infrastructure, education, health care, law and order, and so on, that helps to create a better business climate for all businesses. Management of the exchange rate is another important tool of non-selective industrial policy—the maintenance of the undervalued real exchange rate via accumulation of foreign exchange reserves (above the normal amount needed to ensure smooth trade and capital account transactions) is an important instrument for promoting economic growth based on export of tradable goods, although at the expense of non-tradables (Polterovich and Popov, ). There are important differences between import duties and devaluation of the exchange rate. As Larry Summers once observed: ‘A ten percent decline in the dollar exchange rate is equivalent to a ten percent tariff on all imported goods and a ten percent subsidy for all exported goods’ (The New Republic,  January, , p. ). Import duties raise the real exchange rate (level of prices in the country as compared to the world), whereas real devaluation lowers the real exchange rate. Besides, ‘exchange rate protectionism’ is a more efficient policy to stimulate growth because decisions on import duties and government taxes/spending are affected by poor quality of institutions (corruption and inefficiency of implementation), whereas low exchange rate policy is indiscriminate and non-selective by nature: it cannot be captured and ‘privatized’ by particular interest groups, which makes it an especially efficient growth-promoting instrument in poor and middle-income countries that generally suffer from corruption (Polterovich and Popov, ). As the UN flagship report states (UN WESP, ), ‘reserve accumulation can have positive externalities on the production and export of tradables and industrial development and can thus be a feature of the country’s development model. Undervaluation

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        



of the exchange rate can increase the competitiveness of exports, without the need for sector- or firm-specific subsidies or interventions.’ As Griffith-Jones and Ocampo () observe, the rationale for the accumulation of foreign exchange reserves ‘is usually found in either one of two explanations: the “competitiveness” (or, in more pejorative terms, “mercantilist”) and the “selfinsurance” motives’. This mercantilist view that undervaluation of the exchange rate via accumulation of foreign exchange reserves is in fact an industrial policy, aimed at promoting export-oriented growth by benefiting the producers of tradables and exporters at the expense of the producers of non-tradables and importers, which is gaining support in the literature (Dollar, ; Easterly, ; Rodrik, ; Bhalla, ; Greenwald and Stiglitz, ). If there are externalities from the export and production of tradables (industrialization, development of high-tech sectors), undervaluation of the exchange rate resulting from the accumulation of reserves is an efficient way to provide a subsidy for these activities and this subsidy is automatic, that is, it does not require a bureaucrat to select possible beneficiaries. In short, this is a non-selective industrial policy promoting export and production of tradables that seems to be quite efficient, especially in countries with high corruption and poor-quality institutions. Thus, accumulation of reserves and undervaluation of the exchange rate may be good for long-term growth. The formal model demonstrating how the accumulation of reserves can spur growth, together with empirical evidence, is presented in Polterovich and Popov (), where it is also shown that, in practice, accumulation of reserves leads to a disequilibrium exchange rate, which in turn causes an increase in export/GDP and trade/GDP ratios, which stimulates growth. There is strong evidence that accumulation of reserves can spur long-term growth in developing countries, although not in rich countries (Polterovich and Popov, ). In practical terms, there are no formal limits to the accumulation of reserves by developing countries, but ‘exchange rate protectionism’ can result in ‘beggar-thyneighbour policies’: obviously all countries cannot exercise these policies at the same time to achieve undervaluation of their exchange rates. If all countries use these policies, they will all lose, and moreover, it does not work for developed countries. But for developing countries it does work, and there are good reasons why these countries should have sufficient policy space to use this tool to promote catch-up development. Trade surpluses resulting from undervaluation of the exchange rate due to reserve accumulation may lead to what are now called ‘global imbalances’, driving the other countries into debt. However, there is some room for such a trend, which will reverse the opposite trend of the nineteenth and twentieth centuries (the United States enjoyed a trade surplus for nearly a hundred years after the Civil War of the s, driving many developing countries into debt; see Popov, a, b, , for details). The policy of reserve accumulation is often considered to be self-defeating because in order to avoid inflation (which would eat up the impact of devaluation on the real exchange rate) it is necessary for the monetary authorities to carry out a sterilization

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

 

policy, that is, to sell government bonds in order to neutralize the impact on the money supply of the purchase of foreign currency. But sales of government bonds lead to higher interest rates, which in turn attract capital from abroad that contributes to an increase in foreign exchange reserves, which should be sterilized again, creating a vicious circle. That is why economists talk about an ‘impossible trinity’: a country cannot maintain at one and the same time an open capital account, a managed exchange rate, and an independent monetary policy. But many developing countries exercise control over capital flows (China and India are prime examples) and even without such control, capital mobility—especially for large economies—cannot be considered perfect. In practice, as the statistics show, the accumulation of foreign exchange is financed through government budget surplus and debt accumulation, but not through printing money. That is to say, most countries that have accumulated reserves rapidly exhibit low inflation and low budget deficit (or budget surplus), but increased holdings of government bonds by the public (see Polterovich and Popov, ).

. I P  R- C

.................................................................................................................................. Resource abundance should, logically, be a plus for economic development, but very often it becomes a constraint—a ‘resource curse’ rather than a ‘resource blessing’ (Sachs and Warner, ; Sala-i-Martin and Subramanian, ; Stiglitz, ; Polterovich et al., , , ). Whereas resource-rich countries have generally overvalued their exchange rate (‘Dutch disease’), they also maintain a relatively low level of domestic fuel prices (Polterovich et al., , , ). This is another important industrial policy instrument that has at least two implications: first, like the undervaluation of the RER, low domestic prices for fuel provide competitive advantages to domestic producers and stimulate exports and production (especially of energy-intensive products); second, low fuel prices lead to energy waste due to higher energy intensity, and hence imply higher costs. Today in all resource-rich post-communist countries, Russia being the prime example, domestic prices for fuel are kept below the world market level through taxes on exports of fuel and direct restrictions on exports (such as access to the pipeline). As a result, domestic prices for oil and gas are considerably lower than in the rest of the world, and this allows energy-intensive industries to flourish. In Russia, for instance, the production of energy-intensive aluminium is very competitive due to low energy prices—aluminium is one of Russia’s top export commodities, even though half of it is produced from imported bauxite. The argument developed in Polterovich et al. (, , ) is that the undervaluation of the exchange rate is a preferred industrial policy tool for resource-rich

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        



countries, compared to keeping domestic fuel and energy prices below the world market level. It allows export-oriented development to be stimulated without high energy intensity. In order to make a transition to a new policy, a delicate policy manoeuvre is needed. Theoretically it is possible, but it requires bureaucratic competence to achieve the following: • Gradual increase in domestic fuel and energy prices (by phasing out export tax and lifting restrictions on access to pipelines) up to world levels; • Higher taxes on fuel companies to capture windfall profits from increasing domestic fuel prices; • Spending of increased budget revenues on infrastructure and non-tradables; • Lower real exchange rate (via accumulation of foreign exchange reserves and import subsidies) to compensate losses of non-fuel industries from higher domestic fuel prices.

. I, R,  D

.................................................................................................................................. Should countries which are behind the technological frontier invest in the adoption of existing technologies or should they aim to develop completely new technologies and products? The notion of the ‘advantages of backwardness’ introduced by Alexander Gerschenkron () implies, among other things, that relatively backward economies can grow rapidly by investing in and adopting already existing technologies. Justin Lin believes that countries should not leapfrog over the consecutive stages by going from processing agricultural goods directly to high-tech industries (see section .). He suggests, for instance, that Uzbekistan could gain greater benefits by developing less sophisticated industries such as food, textiles, and leather goods.⁴ The arguments against, however, are supported by the examples of Israel and South Korea, which at the end of the twentieth century had mastered the production of high-tech goods (electronics) and are now leading the world in R&D expenditure as a share of GDP (Figure .). Ricardo Hausmann, Jason Hwang, and Dani Rodrik (Hausmann and Rodrik, ; Hausmann et al., ; Rodrik, ) hypothesize that the more technologically sophisticated the export structure of a country is, the greater the stimuli for economic growth. China in  and , for example, had the greatest gap between hypothetical per capita income (computed based on the technological sophistication of its export structure) and the actual per capita income. That is to say, the structure of

⁴ Personal communication with Justin Lin. In general form the theory is presented in Lin ().

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

  5 4.5 4 Israel 3.5

Korea, Rep. of Japan

3

Finland Germany

2.5

United States 2

China United Kingdom

1.5

Russian Federation 1

India

0.5 0

1996 1998 2000 2002 2004 2006 2008 2010 2012 2014

 . R&D (research and development) Expenditure in selected countries, % of GDP Source: World Development Indicators.

Chinese exports was similar to that of countries with several-fold higher levels of economic development, and this gap stimulated economic growth. In another article (Hausmann and Rodrik, ), the process of transition from the production and export of one group of goods to another is compared to the movement of monkeys in a forest from closer to more distant trees in search of food. The trees rich with fruits are far away, whereas closer trees do not have as much. Thus, the monkeys must compare the costs of movement with the benefits of reaching the more fruitabundant trees. Like the monkeys, firms and society as a whole must compare the cost of mastering the new output and export (low for ‘nearby’ industries which are close to existing technologies and high for ‘far-away’ industries with totally new technological processes) with the benefits (externalities) associated with developing particular industries (theoretically, the more sophisticated these industries are, the higher the benefits). Today the share of R&D expenditure in GDP in most post-communist economies is lower than  per cent (except for several Eastern European countries, Russia and China; Table .), no higher than in countries with a similar level of economic development, whereas in the communist past the opposite was normally true. Determining the optimal level of R&D spending at different stages of development is an important research question. The answer is probably specific to every country: it depends on the size of the country, the structure of the national economy and the share of industries that are close to the technological frontier.

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        



Table 27.1 R&D expenditure in post-communist countries as a percentage of GDP, 2015 Country

R&D as a % of GDP

Slovenia China Czech Republic Estonia Hungary Slovak Republic Russian Federation Lithuania Poland Bulgaria Serbia Croatia Latvia Ukraine Belarus Romania Macedonia, FYR Vietnam Moldova Georgia Armenia Azerbaijan Bosnia and Herzegovina Uzbekistan Albania Kazakhstan Mongolia Kyrgyz Republic Tajikistan

2.2 2.1 1.9 1.5 1.4 1.2 1.1 1.0 1.0 1.0 0.9 0.9 0.6 0.6 0.5 0.5 0.4 0.4 0.4 0.3 0.3 0.2 0.2 0.2 0.2 0.2 0.2 0.1 0.1

Source: World Development Indicators, World Bank.

. S  P S, G, P,  F I

.................................................................................................................................. There is a debate as to what is the crucial factor behind economic fiascos: market failure or state failure? The dominant story in the profession is that economic breakthroughs are achieved only due to a vital and vivid private sector that is dynamic and entrepreneurial, oriented towards innovation and not afraid of risk-taking, whereas the state is clumsy, inefficient, and even reactionary, and restricts private initiatives. It is said that the private

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

 

sector contributes to economic growth and poverty eradication through the building of productive capacity, creation of decent jobs, promotion of innovation, economic diversification, and competition. In landlocked developing countries, the private sector is actively involved in activities related to transit and trade facilitation, including as traders, freight forwarders, insurance providers, and transporters, and the sector is a source of tax revenue and domestic investment and is a partner for foreign direct investment. Public‒private partnerships can play an important role in infrastructure development (Almaty Programme of Action for Landlocked Developing Countries, ). Another story, however, is that of the entrepreneurial state: Mazzucato () provides ample evidence that technological breakthroughs are due to public and state-funded investments in innovation and technology, and that the private sector only finds the courage to invest after an entrepreneurial state has made the high-risk investments. Rodrik and Subramanian () describe the attitudinal shift on the part of national governments towards a pro-business (as opposed to pro-liberalization) approach, and attribute the acceleration of Indian economic growth to this factor: they show that the acceleration of growth has actually occurred since  and not since , when liberalization reforms were carried out. The problem in many developing countries in general and in post-communist countries in particular is that the private sector often fails to take the initiative in promoting development due to an actual or alleged ‘poor investment climate’. As can be seen from Figure . (and comparing it to Figure .), there is no correlation between the share of the private sector in the economy and the GDP dynamics. Or, if there is a correlation, it is rather negative than positive: more privatized economies are doing worse than less privatized ones. Some studies suggest that government investments do not crowd private investment, but have a ‘crowding in’ effect. As can be seen from Figure ., it is not only private but also public investments that contribute to the increase of the share of investment in GDP. If for some reason private investments are in limbo, the state can achieve an increase in total investments through the expansion of its own public investment projects financed through taxation and/or borrowing. Government savings (financing public investment through the government budget and/or budget surplus), as studies show, do not crowd out private savings in a proportion of :, but only in a proportion of ‒ cents for every dollar (Schmidt-Hebbel et al., ). In low-income countries, as recent research shows, one extra dollar of government investment does not crowd out, but crowds in private investment, raising it by roughly two dollars and output by . dollars (Eden and Kraay, ). If the private sector is not doing the job, the solution may be that government investment and government entrepreneurship helps to resolve the bottlenecks. It should be also noted that the impact of foreign direct investment (FDI) on development is not always positive. Some countries created growth miracles without relying on FDI (Japan, South Korea, China in ‒), others relied on FDI extensively (Taiwan, Singapore, Hong Kong, China after ) (Polterovich and Popov, ). It may be hypothesized that FDI inflows into countries with a poor investment climate actually do actually more harm than good. First, investors are self-selecting: if the investment climate is bad, foreign investors come mostly for short-term profit and/or resource projects, where the transfer of technology, the main benefit of FDI, is at best

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        



80

70 EST ARM

60

AZ GEORG KYRG

50

LITH LAT 40

KAZ MOLD RUS

30

UKR TADJ 20

UZB BEL TURKM

10

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

1995

1994

1993

1992

1991

1990

1989

0

 . The share of private sector in GDP in some former Soviet republics, –, % Source: Transition Report, EBRD (data for years after 2010 unavailable).

limited. Second, foreign investors do not reinvest profits in countries with a poor investment climate, so the outflow of profits with time outweighs the inflow of FDI. Third, purchases of companies in countries with bad investment conditions do not necessarily lead to an increase in total investment because the inflow of FDI is often completely absorbed by an outflow of short-term capital.⁵ ⁵ Regression analysis (Polterovich and Popov, ) supports these conclusions. It implies that FDI positively influences growth in countries with a good investment climate and negatively in countries with a poor investment climate: GR ¼ CONSTANT þ CONTROL VARIABLES þ 0:02*FDI ðICI  80:5Þ; where GR—annual average growth rates of GDP per capita, ICI—investment climate index, FDI—average foreign direct investment inflow as a % of GDP in ‒. Coefficients are significant at the  per cent level or less. This equation establishes a very high threshold of investment climate index—about  per cent, which is basically the level of developed countries. Only a few developing countries (Botswana, Kuwait) have such a good investment climate. The worse the investment climate of a country, the larger may be losses from FDI, hence stronger foreign investments should be regulated by the state.

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

  Gross investment and public investment in 2012, % of GDP Gross fixed capital formation, % of GDP

60 Mongolia

50

R2 = 0.3239

China

Mozambique

Turkmenistan

40 30 20 10

Gross fixed capital formation, % of GDP

0

Guinea-Bissau 0

5

10

15 20 25 Public investment, % of GDP

30

35

40

Gross investment and private investment in 2012, % of GDP 70

R2 = 0.6537

60 50

China

Turkmenistan

40

Mozambique

Mongolia

30 20 10 0

Guinea-Bissau 0

10

20 30 40 Private investment, % of GDP

50

60

Public investment and private investment in 2012, % of GDP Public investment % of GDP

40

Turkmenistan

35 30 25

China

20 15 10

R2 = 0.0006

5 0

0

10

20 30 40 Private investment, % of GDP

50

60

 . Public, private, and gross investment in developing countries as a % of GDP,  Source: World Development Indicators.

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        



. I T  T P

.................................................................................................................................. Trade specialization (the predominance of particular goods in exports and imports) is the other side of the coin of the structure of a national economy: if the country exports manufactured goods and imports food products, the share of manufacturing in its total output and employment would be high and the share of agriculture low. That is why the structure of the national economy depends to a large extent on trade developments— openness to trade in particular sectors and industrial policies to promote exports of some goods and to provide (or not to provide) protection to particular industries.

.. Trade Liberalization What kind of trade policy is best for promoting sustainable development? The debates on whether free trade or protectionism are more conducive to growth are as old as economic research itself. The advocacy of free trade became commonplace in economics research and a number of studies demonstrate its benefits (Sachs and Warner, ; IMF, WB, and WTO, ; OECD,  to name a few). However, it was noticed that free trade does not always lead to an increase in the share of exports and imports in GDP (Rodriguez and Rodrik, ; Polterovich and Popov, ). The best example is China after the Opium Wars that forced the country to open up: for a hundred years afterwards, there was no increase in the external trade-to-GDP ratio and China continued to fall behind Western countries in per capita income. Other more recent examples are Japan, South Korea, and Taiwan in the s‒s and China in the s‒s. In the s Chinese import duties were at the - per cent level and it was only in the s and s they were gradually reduced to  per cent (Prasad, ). China became a member of the WTO only in , so GDP growth rates of about  per cent a year in the previous two decades (and of the export-to-GDP ratio from  per cent in  to  per cent in ) cannot be explained by the benefits of trade liberalization. Studies also show that the benefits of free trade depend on domestic adjustment policies, without which it is impossible to reap the potential benefits of trade liberalization (IMF, WB, and WTO, ; OECD, ). Stiglitz and Charlton () question the conclusion that broad trade liberalization always makes countries better off. They claim that this conclusion is based on invalid assumptions about full employment and perfect competition that are lacking in most developing countries. It is well documented that fast-growing countries are usually more involved in international trade, and have higher and faster-growing trade/GDP ratios. In addition, there is a correlation between the share of investment in GDP and the share of export in GDP—countries which export more invest more as well (Polterovich and Popov,

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

 

). However, fast-growing and more intensively trading nations are not always and were not always more open to trade (low tariff and non-tariff barriers) than their less globalized competitors. Empirical studies (Rodriguez and Rodrik, ; O’Rourke and Williamson, ; see, for a survey, Williamson, ) have found that there is no conclusive evidence that free trade is always good for growth: whereas protectionist countries grew more rapidly before the First World War, they exhibited lower than average growth after the Second World War. Rose () estimated the effect on international trade of multilateral trade agreements such as the WTO, its predecessor the General Agreement on Tariffs and Trade (GATT), and the Generalized System of Preferences (GSP) extended from rich countries to developing countries, using the standard ‘gravity’ model of bilateral merchandise trade. He found little evidence that countries joining or belonging to the GATT/WTO have different trade patterns than outsiders, whereas the GSP, which gives poor countries better access to markets in developed countries, had a very strong effect on the trade of developing countries (an approximate doubling of trade).

.. Import Substitution versus Export Orientation Import substitution is usually associated with protectionism: the idea is to protect domestic non-competitive industries with trade barriers, so that they can withstand competition from imported goods and eventually increase their competitiveness and efficiency. The problem with this kind of policy is that the efficiency of protected industries does not increase automatically, and protection that is usually designed as a temporary measure very often becomes a permanent shield preserving industrial ‘dinosaurs’, as inefficient and non-competitive enterprises are often called. Export orientation is usually understood as a policy of support for exporters (via subsidies, credits, tax concessions, and other stimuli), but it is important to realize that export promotion can in fact go hand in hand with protectionist measures. In fact, there is no contradiction in imposing high import duties on a particular product and providing export subsidies for it—higher prices in the domestic than the world market provide finances for restructuring, whereas export orientation in this case is supported by export subsidies. This was exactly the policy of Japan, South Korea, and Taiwan (even though not that of Singapore and Hong Kong) in the s‒s. The difference between import substitution and export orientation is that the first policy only protects domestic industries (without promoting export orientation), whereas the second policy not only protects domestic industries, but also stimulates them to export their output. The criteria for distinguishing between the two types of policy are the dynamics of the share of export in GDP. If it grows fast, this should be classified as export-oriented development, if it stagnates it is import substitution.

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        



The authors of The East Asian Miracle (World Bank, ) found that government efforts to promote specific industries (without promoting exports) generally did not increase economy-wide productivity. But government support for exports was a highly effective way of enhancing the absorption of international best-practice technologies, thus boosting productivity and output growth. In the former Soviet Union region, much trade liberalization occurred in the s and beyond as former Soviet republics made the transition to the market and deregulated their export/import operations. Kyrgyzstan was the first post-Soviet country to become a member of the WTO in , followed by the Baltic states (‒), Georgia (), Moldova (), Armenia (), Ukraine (), Russia (), Tajikistan (), and Kazakhstan (). But their development looked anything but export oriented. The share of export in GDP in Central Asian countries, for instance, fell dramatically after the dissolution of the Soviet Union, and has not increased in the s‒s. A yardstick for comparison can be Turkey, a country at a similar level of development: it managed to increase the share of exports in GDP from  to . per cent in ‒, whereas in Central Asian countries this indicator either increased only marginally (Kyrgyzstan, Turkmenistan) or decreased (Kazakhstan, Tajikistan, Uzbekistan) (Gharleghi and Popov, a). It is noteworthy that four former Soviet republics that are still not members of the WTO as of  (Azerbaijan, Belarus, Turkmenistan, Uzbekistan) had higher growth rates over the last thirty years than the others (Figure .).

. C

.................................................................................................................................. In the s, Eastern European and former Soviet Union countries carried out market reforms and experienced regressive developments in their industrial structure—deindustrialization, ‘resource-ialization’ and ‘primitivization’ of the structure of their exports. Extensive liberalization in the s in the former Soviet Union countries led to premature de-industrialization in the region, which inhibited economic growth. In contrast, China and Vietnam also carried out market-type reforms (China, gradual reforms since ; Vietnam, gradual reforms in ‒ and radical reforms in ) and achieved an acceleration of their economic growth and an impressive increase in manufacturing output and exports. The varying performance of post-communist countries can be attributed to a large extent to different models of industrial policy: whereas China and Vietnam relied on active promotion of exports (mostly via an undervalued exchange rate), Eastern European countries did not introduce any sizeable stimulus to particular industries, and former Soviet republics for a long time assisted domestic producers in a very inefficient way—by maintaining low prices for energy and fuel in the domestic market. This is one of the most important lessons of the post-communist transition: marketoriented reforms alone are not enough, the state needs to maintain strong institutional capacity and to stimulate progressive structural shifts. A successful industrial policy is

OUP CORRECTED PROOF – FINAL, 21/9/2020, SPi



 

needed for structural economic transformation to achieve inclusive and sustainable development. Industrial policy could use protectionist instruments, but should stimulate exports. Protectionism alone is not enough for upgrading the industrial structure and speeding up economic and social development. There are many ways to promote manufacturing exports, but the most promising tool is the undervaluation of the exchange rate and public investment, especially in infrastructure and education. These policies were widely used by virtually all ‘economic miracle’ countries and contributed to rapid growth and successful catch-up development in East Asia and elsewhere. Undervaluation of the exchange rate is a non-selective industrial policy that creates stimuli for the tradable goods sector and exports of tradables, whereas public investments contribute to the acceleration of economic growth, not only because they lead to the rise of the share of investment in GDP (no crowding-out effect), but also because they provide public goods (education, infrastructure) with strong externalities and can eliminate bottlenecks (if private investors ignore particular areas). For resource-rich countries, the need for a special policy to lower the real exchange rate is especially pressing (to avoid ‘Dutch disease’). Today in all resource-rich postcommunist countries, domestic prices for fuel are kept below world market level through taxes on exports of fuel and direct restrictions on exports (export quotas, access to the pipeline). This provides subsidies to all producers using fuel and energy, stimulating economic growth, but at the same time leads to high energy intensity. A more efficient way to stimulate export-oriented growth is to gradually eliminate export taxes for fuel and energy, to tax the extra profits of fuel companies and use the revenues for infrastructure investment, and to stimulate producers of tradables, not via price subsidies for fuel, but via an underpriced exchange rate. Since the mid-s and especially in the s and s, many FSU countries have made substantial economic advances. Six countries in the region (Turkmenistan, Uzbekistan, Azerbaijan, Kazakhstan, Tajikistan, and Belarus) increased their output no less than Central Europe (. times and more as compared to ; Figure .). Uzbekistan’s and Tajikistan’s achievements are especially impressive because they are only partly based on resource exports. Such positive dynamics are due, to a large extent, to the efficient industrial policy that resisted de-industrialization and supported manufacturing exports through undervalued exchange rates and tax policies.

R Almaty Programme of Action for Landlocked Developing Countries () ‘ITT for LLDCs. Priority : Structural economic transformation ()’. Available at http://land-locked.org/ priority--structural-economic-transformation/. Bhalla, Surjit S. () Devaluing to Prosperity: Misaligned Currencies and their Growth Consequences. Washington, DC: Peterson Institute for International Economics. Chenery, Hollis B. () ‘Patterns of Industrial Growth’, The American Economic Review (): –.

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        



Cherif, Reda and Fuad Hasanov () ‘The Return of the Policy That Shall Not Be Named: Principles of Industrial Policy’. IMF Working Paper No. /. Washington, DC: IMF. Dollar, David () ‘Outward-oriented Developing Economies Really Do Grow More Rapidly: Evidence from  LDCs, –’, Economic Development and Cultural Change (): –. Easterly, William () The Lost Decades: Explaining Developing Countries Stagnation –. Washington, DC: The World Bank Eden, Maya and Aart Kraay () ‘ “Crowding in” and the Returns to Government Investment in Low-income Countries’. Policy Research Working Paper No. . Washington, DC: World Bank. Gerschenkron, Alexander () Economic Backwardness in Historical Perspective: A Book of Essays. Cambridge, MA: Belknap Press of Harvard University Press. Gharleghi, Behrooz and Vladimir Popov (a) Changes in the Geographical Structure of Trade in Central Asia: Real Flows in – versus Gravity Model Predictions. Berlin: Dialogue of Civilizations Research Institute. Gharleghi, Behrooz and Vladimir Popov (b) Farewell to Agriculture? Productivity Trends in and Competitiveness of Agriculture in Central Asia. Berlin: Dialogue of Civilizations Research Institute. Gibbs, Murray () ‘Trade Policy’. UN DESA. Available at https://esa.un.org/techcoop/ documents/PN_TradePolicyNote.pdf. Gill, Indermit S., et al. () Diversified Development: Making the Most of Natural Resources of Eurasia. Washington, DC: World Bank. Greenwald, Bruce and Joseph E. Stiglitz () ‘Externalities in Economies with Imperfect Information and Incomplete Markets’, The Quarterly Journal of Economics (): –. Greenwald, Bruce and Joseph E. Stiglitz () ‘Learning and Industrial Policy: Implications for Africa’, in Joseph E. Stiglitz, Justin Yifu Lin, and Ebrahim Patel (eds) The Industrial Policy Revolution II: Africa in the XXI Century. International Economic Association Series. London: Palgrave MacMillan, pp. –. Griffith-Jones, Stephany and José Antonio Ocampo () ‘Sovereign Wealth Funds: A Developing Country Perspective’. Paper prepared for the workshop on Sovereign Wealth Funds organized by the Andean Development Corporation. London,  February . Available at http://www.stephanygj.net/papers/SovereignWealthFundsDevelopingCountry Perspective.pdf. Harris, Richard I. and Qian Cher Li () ‘Learning-by-Exporting? Firm-level Evidence for UK Manufacturing and Services Sectors’. Glasgow Business School—Economics, University of Glasgow. Available at http://www.gla.ac.uk/media/media__en.pdf. Hausmann Ricardo and Dani Rodrik () ‘Doomed to Choose: Industrial Policy as Predicament’. First Draft. Paper prepared for the first Blue Sky seminar organized by the Center for International Development at Harvard University,  September . Cambridge, MA: Harvard University Press. Hausmann, Ricardo, Jason Hwang, and Dani Rodrik () ‘What You Export Matters’. NBER Working Paper No. . Cambridge, MA: National Bureau of Economic Research. Available at http://www.nber.org/papers/w.pdf. Herrendorf, Berthold, Richard Rogerson, and Ákos Valentinyi () ‘Growth and Structural Transformation’. Paper prepared for the Handbook of Economic Growth. Washington, DC: IMF. Available at https://www.imf.org/external/np/seminars/eng//SPR/pdf/rrog.pdf. IMF () Soviet Economy: A Study of the Soviet Economy.  vols. Washington, DC: IMF.

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

 

IMF, WB, and WTO () Making Trade an Engine of Growth for All: The Case for Trade and for Policies to Facilitate Adjustment. Washington, DC, Geneva: International Monetary Fund, World Bank, and World Trade Organization. Available at https://www.wto.org/ english/news_e/news_e/wto_imf_report_.pdf. Innis, Harold Adams () Essays in Canadian Economic History, edited by Mary Q. Innis. Toronto: University of Toronto Press. Jomo, Kwame Sundaram () ‘The Best Approach to Economic Development is Pragmatism’, in Piotr Dutkiewicz and Richard Sakwa (eds)  Ideas to Fix the World: Conversations with the World’s Foremost Thinkers. New York: New York University Press, pp. –. Jomo, Kwame Sundaram () ‘Industrial Policy Finally Legitimate?’, Inter Press Service, July. Available at http://www.ipsnews.net///industrial-policy-finally-legitimate/. Khan, Mushtaq H. () ‘Governance, Economic Growth and Development since the s’. DESA Working Paper No. , August. Available at http://www.un.org/esa/desa/papers/ /wp_.pdf. Lee, Keun () Schumpeterian Analysis of Economic Catch-up Knowledge, Path-Creation, and the Middle-income Trap. Cambridge: Cambridge University Press. Lin, Justin Yifu () ‘From Flying Geese to Leading Dragons: New Opportunities and Strategies for Structural Transformation in Developing Countries’. Policy Research Working Paper No. . Washington, DC: World Bank. Available at https://elibrary.worldbank. org/doi/abs/./--. Lin, Justin Yifu and Ha-Joon Chang () ‘Should Industrial Policy in Developing Countries Conform to Comparative Advantage or Defy it? A Debate between Justin Lin and Ha-Joon Chang’, Development Policy Review (): –. Mazzucato, Mariana () The Entrepreneurial State: Debunking Public vs. Private Sector Myths. London: Anthem Press. Murphy, Kevin M., Andrei Shleifer, and Robert W. Vishny () ‘Industrialization and the Big Push’, The Journal of Political Economy (): –. Myrdal, Gunnar () Asian Drama: An Inquiry into the Poverty of Nations.  vols. New York: Pantheon Books. OECD () Making Trade Work For All. Paris: OECD. Available at https://www.oecd.org/ trade/making-trade-work-for-all.pdf. O’Rourke, Kevin H. and Jeffrey G. Williamson () ‘From Malthus to Ohlin: Trade, Growth and Distribution since ’. NBER Working Paper No. . Available at http://www.nber.org/papers/w.pdf. Page, John () ‘Should Africa Industrialize?’. WIDER Working Paper No. /, August. Helsinki: UNU-WIDER. Polterovich, Victor and Vladimir Popov () ‘Accumulation of Foreign Exchange Reserves and Long-term Economic Growth’, in Shinichiro Tabata and Akihiro Iwashita (eds) Slavic Eurasia’s Integration into the World Economy. Sapporo: Slavic Research Center, Hokkaido University. Available at http://www.nes.ru/%Evpopov/documents/EXCHANGE%RATEGrowthDECwithcharts.pdf. Polterovich, Victor and Vladimir Popov () ‘Appropriate Economic Policies at Different Stages of Development’. NES. Available at https://papers.ssrn.com/sol/papers.cfm? abstract_id=. Polterovich, Victor and Vladimir Popov () ‘Stages of Development, Economic Policies and New World Economic Order’. Paper presented at the Seventh Annual Global Development Conference in St. Petersburg, Russia, January. Available at http://http-server. carleton.ca/~vpopov/documents/NewWorldEconomicOrder.pdf.

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        



Polterovich, Victor, Vladimir Popov, and Alexander Tonis () ‘Экономическая политика, качество институтов и механизмы”ресурсного проклятия” ’. Moscow: The Higher School of Economics Publishing House. Available at http://pages.nes.ru/vpopov/ documents/Resources--HSE-Polterovich-Popov-Tonis.pdf. Polterovich, Victor, Vladimir Popov, and Alexander Tonis () ‘Mechanisms of Resource Curse, Economic Policy and Growth’. NES Working Paper No. WP//. Moscow: New Economic School. Available at https://pages.nes.ru/vpopov/documents/Resource_ Curse_and_Economic_Policy-English-NESFin-Febr.pdf. Polterovich, Victor, Vladimir Popov, and Alexander Tonis () ‘Resource Abundance: A Curse or Blessing?’. DESA Working Paper No. . New York: United Nations Department of Economic and Social Affairs. Available at http://www.un.org/esa/desa/papers/ /wp_.pdf. Popov, Vladimir () ‘Shock Therapy versus Gradualism: The End of the Debate (Explaining the Magnitude of the Transformational Recession)’, Comparative Economic Studies (): –. Popov, Vladimir () ‘Shock Therapy versus Gradualism Reconsidered: Lessons from Transition Economies after  Years of Reforms’, Comparative Economic Studies (): –. Popov, Vladimir (a) ‘Development Theories and Development Experience’. CEFIR and NES Working Paper No. . Moscow: Centre for Economic and Financial Research at New Economic School. Popov, Vladimir (b) ‘Global Imbalances: An Unconventional View’, IDEAs,  October. Popov, Vladimir () ‘Стратегии экономического развития’ (‘Strategies of Economic Development’). Moscow: The Higher School of Economics Publishing House. Popov, Vladimir () ‘An Economic Miracle in the Post-Soviet Space: How Uzbekistan Managed to Achieve What No Other Post-Soviet State Has’. MPRA Paper No. . Available at https://mpra.ub.uni-muenchen.de///MPRA_paper_.pdf. Popov, Vladimir () ‘Can Uzbekistan Economy Retain its High Growth Rate? Scenarios of Economic Development in –’. PONARS Eurasia Working Paper. Washington, DC: PONARS Eurasia. Popov, Vladimir and Anis Chowdhury () ‘What can Uzbekistan Tell Us about Industrial Policy That We Did Not Already Know?’. DESA Working Paper No. . New York: United Nations Department of Economic and Social Affairs. Available at http://www.un. org/esa/desa/papers//wp_.pdf. Popov, Vladimir and Kwame Sundaram Jomo () ‘Are Developing Countries Catching Up?’, Cambridge Journal of Economics (): –. Prasad, E. () ‘China’s Growth and Integration into the World Economy: Prospects and Challenges’. IMF Occasional Paper No. . Washington, DC: IMF. Reddy, Sandjay G. () ‘Randomise This! On Poor Economics’, Review of Agrarian Studies (). Available at http://www.ras.org.in/randomise_this_on_poor_economics. Rodriguez, Francisco and Dani Rodrik () ‘Trade Policy and Economic Growth: A Skeptic’s Guide to the Cross-National Evidence’, in Ben S. Bernanke and Kenneth Rogoff (eds) NBER Book Series NBER Macroeconomics Annual, Vol. . Cambridge, MA: MIT Press, pp. –. Rodrik, Dani () What’s So Special about China’s Exports? Cambridge, MA: Harvard University Press. Rodrik, Dani () ‘The Real Exchange Rate and Economic Growth’, Brookings Papers on Economic Activity Fall: –.

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

 

Rodrik, Dani () ‘Doing Development Better: Project Syndicate’,  May. Available at https:// www.project-syndicate.org/commentary/doing-development-better?barrier=accesspaylog. Rodrik, Dani and Arvind Subramanian () ‘From Hindu Growth to Productivity Surge: The Mystery of the Indian Growth Transition’. IMF Working Paper No. WP//. Washington, DC: International Monetary Fund, May. Available at: https://www.imf.org/ External/Pubs/FT/staffp//–/rodrik.pdf. Rodrik, Dani et al. () ‘Structural Change, Fundamentals, and Growth: Overview’, in Margaret McMillan, Dani Rodrik, and Claudia Sepúlveda (eds) Structural Change, Fundamentals, and Growth: A Framework and Case Studies. Washington, DC: International Food Policy Research Institute Washington, pp. –. Rose, Andrew K. () ‘Do We Really Know that the WTO Increases Trade?’. NBER Working Paper No. . Cambridge, MA: NBER. Available at http://www.nber.org/papers/w.pdf. Sachs, Jeffrey D. and Andrew M. Warner () ‘Economic Reform and the Process of Global Integration’. Brookings Papers on Economic Activity. Washington, DC: Brookings Institution Press. Sachs, Jeffrey D. and Andrew M. Warner () ‘Natural Resources and Economic Development: The Curse of Natural Resources’, European Economic Review : –. Sala-i-Martin, Xavier and Arvind Subramanian () ‘Addressing the Natural Resource Curse: An Illustration from Nigeria’. NBER Working Paper No. . Available at http:// www.nber.org/papers/w.pdf. Schmidt-Hebbel, Klaus, Luis Serven, and Andres Solimano () ‘Saving and Investment: Paradigms, Puzzles, Policies’, The World Bank Research Observer (l): –. Shevtsova, Yevgeniya () ‘International Trade and Productivity: Does Destination Matter?’. Discussion Papers in Economics /. York: University of York. Stiglitz, Joseph E. () ‘Making Natural Resources into a Blessing rather than a Curse’, in Svetlana Tsalik and Anya Schiffrin (eds) Covering Oil: A Reporter’s Guide to Energy and Development. New York: Open Society Institute, pp. –. Stiglitz, Joseph E. () ‘From Manufacturing Led Export Growth to a st Century Inclusive Growth Strategy: Explaining the Demise of a Successful Growth Model and What to Do About It’. WIDER Development Conference, September. Stiglitz, Joseph E. and Andrew Charlton () Fair Trade for All: How Trade Can Promote Development. Oxford: Oxford University Press. Syrquin, Moshe and Hollis Chenery () ‘Three Decades of Industrialization’, The World Bank Economic Review (): –. UN ESCAP () ‘Economic Diversification in Asian Landlocked Developing Countries: Prospects and Challenges’. Bangkok: United Nations Economic and Social Commission for Asia and the Pacific, United Nations. Available at https://www.unescap.org/sites/default/ files/Economic%Diversification_low%resolution.pdf. UN WESP () World Economic Situation and Prospects : Global Economic Outlook. Available at https://www.un.org/development/desa/dpad/publication/world-economicsituation-and-prospects-/. Williamson, Jeffrey G. () ‘Winners and Losers over Two Centuries of Globalization’. NBER Working Paper No. . Cambridge, MA: NBER. Available at http://www.nber. org/papers/w.pdf. World Bank () The East Asian Miracle: Economic Growth and Public Policy. Oxford: Oxford University Press.

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        ......................................................................................................................

                   A Comparative Perspective ......................................................................................................................

ˊ     

. I

.................................................................................................................................. I policy is a policy that reshapes incentives to foster technological and structural change. Since, as the Schumpeterian tradition argues, economic development is driven by technological innovation and learning, and associated structural change, industrial policy is at the core of development policies. In an international system marked by asymmetries in technological capabilities, development requires technological catching up and diversification towards a more sophisticated (technology-intensive) pattern of specialization. This defines a desirable path of structural change for development, as opposed to ‘regressive’ structural change—a path leading to the loss of knowledge-intensive sectors and growing dependence on primary exports. The question to be addressed in a comparative study of industrial policy in a developing economy is in which cases such policy—or its absence—has been effective in reducing the technology gap and changing the pattern of specialization, and in which cases it has failed to do so, and why. What constitutes the best industrial policy for development is far from consensual among economists—perhaps even less consensual than in other economic policy areas. There is a strong current in neoclassical economics that argues the best industrial policy is to have none at all, or at best that only a ‘horizontal’ policy is admissible, that is, one that provides across-the-board incentives to help all industries without targeting anyone in particular—such as a general subsidy for research and development (R&D). This approach considers that ‘vertical’ industrial policies—in which the selection of sectors to be favoured is explicit—distort incentives, produce allocative inefficiencies, and encourage rent-seeking activities that compromise productivity growth and capital

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

ˊ     

accumulation in the long run. Vertical industrial policy is described by this view as ‘picking winners’. However, there is an implicit selection of sectors (non-neutrality) in horizontal industrial policies as well: for instance, an across-the-board subsidy to R&D will favour mostly industries that are intensive in R&D. The strong version of the neoclassical view was dominant in the formulation of industrial policy after the market reforms that took place in the Southern Cone countries (notably Chile) in the late s, and on a broader basis in Latin America since the mids. Inversely, the quest for structural change was paramount in the policies adopted by several Latin American countries during the period of ‘state-led industrialization’¹ and by the successful cases of catching up, mostly in East Asia. This chapter compares industrial policy in different countries and how they shaped different trajectories of productivity growth and structural change. Although we present the broader Latin American trends, we focus our analysis on the four largest Latin American economies— Argentina, Brazil, Colombia, and Mexico—comparing these countries with the Republic of Korea (henceforth just Korea). We argue that the persistence of industrial policy in Korea, combined with a macroeconomic policy that avoided the appreciation and instability of the real exchange rate, were critical for its success, while the abandonment of industrial policy in the s and the use of the real exchange rate mainly as an antiinflationary tool and a policy instrument to adjust to commodity boom–bust cycles, explain why the Latin American countries failed to catch up. The chapter is organized into five sections. Following this introduction, we describe our theoretical framework for the analysis of technical and structural change, combining micro and macroeconomic variables in what we broadly call the structuralist tradition. There follows a discussion of industrial and macroeconomic policies in Latin American countries, taking Korea as a benchmark. Next we use different indicators of technological catching up and economic transformation to show that Latin America has been lagging behind East Asia and the world economy since the s. A final section presents some brief conclusions.

. T, L T C,  S I

..................................................................................................................................

.. The Dynamics of Learning and Industrial Policy Although there are many different neoclassical models of technical change (see Aghion and Howitt, ), the orthodox views that are prevalent in the policy debate assume ¹ Following Bértola and Ocampo (), we use this concept rather than the more traditional one of ‘import-substituting industrialization’, because the latter captures only one element of the policy package of that period, and not necessarily the most relevant one.

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   



that all sectors are equally capable of promoting technical change and that there are no significant barriers to the diffusion of technology. This perspective, however, is at odds with the growing evidence that the velocity of innovation and technological opportunities varies significantly across sectors (Bogliacino and Pianta, ). It is also at odds with the large international technological gaps that characterize the global economy, and with the fact that countries that have succeeded in catching up have applied comprehensive industrial policies ‘distorting’ market incentives. In contrast with the orthodox view, the structuralist tradition argues that the international diffusion of technology is slow and irregular. The empirical evidence coming from firm-level studies of technological innovation and diffusion shows much less flexibility in the pace and direction of learning than what is implicit in neoclassical growth models (Dosi et al., ). One major factor is the importance of production experience as a source of productivity growth, a significant factor underscored by Arrow’s concept of learning by doing and by the Kaldor–Verdoorn Law (Arrow, ; Kaldor, : chs. , , and ). The key insight in both cases is that technical change cannot be separated from experience in production and the existing set of capabilities firms and countries deploy at a certain point in time. The evolutionary theory of technical change has offered new insights, in particular the concept that technological capabilities are tacit, in the sense that they cannot be transmitted in a codified way (i.e. through manuals or printed instructions), and must be incorporated into the routines of the firm and the skills of shop-floor workers and engineers. A similar idea was suggested in a pioneering article by Atkinson and Stiglitz (), who argued that technical change is localized around techniques that firms are using.² The production function takes the form of disconnected sets (clusters of technologies) instead of a smooth, continuous isoquant along which the firm chooses the optimal combination of factors of production. In other words: what firms learn, the possibility of catching up, and the direction of innovation depend on current capabilities and experience. This also means that technological capabilities are embedded in the production structure. The interconnection between learning and production implies that production structures and technology co-evolve. There is a strong element of inertia in specialization and in technological capabilities that may lead to slow growth and learning traps. In the absence of an exogenous shock that redefines the prevailing incentives, asymmetries in technology will endogenously reproduce the ‘old’ structure. The role of industrial policy is to provide such an exogenous shock to reshape incentives and overcome learning traps. Changes in relative prices (albeit necessary) may not suffice to bring about technical change when learning is localized. Upgrading technological capabilities

² ‘It is sometimes argued that the problem of the allocation of resources to research is not relevant for a present-day underdeveloped country, since it will benefit from technical progress in the advanced countries, and any independent research would simply be a duplication of effort. But if, as we have suggested, technical knowledge is highly specific to particular production processes, this will not be the case’ (Atkinson and Stiglitz, : ).

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

ˊ     

requires more than adequate price signals. It demands an institutional framework for the coordination of the various actors (in the private and public sectors, such as R&D agencies, universities, and centres for technological training and extension) engaged in learning and innovation, redirecting investments towards new capabilities over a longterm horizon, and away from the most obvious short-term incentives (Katz and Stumpo, ; Cimoli and Katz, ; Anderson and Ejermo, ; Bell, ). A systemic approach is at the core of the evolutionary literature, especially in the concept of national systems of innovation (Fagerberg and Verspagen, ; Lundvall, ) and their institutional variations across countries. These variations may take the form of ‘mission-oriented’ and ‘diffusion-oriented’ paradigms in industrial and technological policies (Chiang, ). Mission-oriented innovation policies are based on large projects with public and private funding that seek to produce a technological breakthrough and shift the international technological frontier, leading to global leadership in strategic sectors. Diffusion-oriented strategies are those focused on the absorption and improvement of existing technology, especially in adapting and improving foreign technology through cumulative minor innovations. Countries that adopt diffusionoriented strategies (mostly, but not exclusively, developing economies) seek to create competitive advantages acting as smart followers rather than as innovators, moving up (‘trickle-up’) in the technological ladder. An important issue is to what extent the firms’ nationality matters in the effort to build a national system of innovation. Amsden () has argued that counting on national firms was an important ingredient in Korea’s success story, which is at variance with Latin America. This could have been a factor in the ability of the governments in Asia and Latin America to effectively implement industrial policies. While we acknowledge the importance of this point, it will not be discussed in this chapter.

.. The Links between Macroeconomic and Industrial Policies Fiscal, monetary, and exchange rate policies are essential to stabilize inflation and smooth business cycles. However, macroeconomic policy also has substantial effects on structural change. As GDP growth volatility increases investment risks, avoiding sharp cyclical fluctuations may be particularly important to promote growth and associated structural change. This especially compromises innovative sectors, which are in themselves subject to larger risks. Macroeconomic policies, and especially the real exchange rate policy, may also change the composition of output. Changes in the real exchange rate (RER)³ redefine the structure of relative prices in favour of, or against, the production of tradable goods. To the extent that tradable and non-tradable goods ³ The RER is defined as q=PfE/P, where Pf are foreign prices and P domestic prices, and E the nominal exchange rate, expressed as the value of the foreign currency in terms of the domestic currency.

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   



have different potential for learning and productivity growth, the exchange rate policy generates long-run effects. There is substantial evidence suggesting that a stable and slightly undervalued RER favours structural change and economic growth in the long run (Rodrik, ; Razmi et al., ; Guzman et al., ). Two mechanisms explain this association. The first is that growth in developing economies tends to be constrained by the external sector, as the literature on balance-of-payments-constrained growth suggests. There is also a strong dependence of short-term economic activity on external shocks, positive and negative—an effect that one of us has called ‘balance-of-payments dominance’ (Ocampo, ). A country that overvalues its currency will grow at a lower rate than a country that keeps it in equilibrium or slightly undervalued. This would be associated with short-term growth risks (the probability of a balance-of-payments crisis), but also long-term effects, particularly reduced opportunities for investment and learning by doing in tradable sectors. The second mechanism is that tradable sectors are at the heart of industrial policy because high-tech sectors are usually tradable and are exposed to more intense competition in international markets. Therefore, to be effective, industrial policy should work in line with macroeconomic policy, especially with the exchange rate policy. If the RER is overvalued, attempts to promote tradable sectors—for instance, by improving the coordination of R&D agencies and firms, improving technical training, or granting subsidies to innovation—are doomed to fail. In other words, industrial policy cannot surmount the disincentive for the production of tradables associated with an appreciated RER. On the other hand, relying too much on an undervalued currency for competitiveness entails the risk of dependence on cheap labour. Arrow’s learning by doing and the Kaldor–Verdoorn Law are not automatic forces: the speed of learning out of growth depends on the industrial and technological policies. In short, the macroeconomic policy cannot replace industrial policy; and an industrial policy without a competitive RER will be ineffective in providing incentives for structural change.

. P   C P: I P   D P  L A D

..................................................................................................................................

.. Industrial Policy: From State-led Industrialization to the Washington Consensus Why did Latin America fall behind, while several Asian countries succeeded in converging with the advanced economies? We will argue that the specific combination

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

ˊ     

of industrial and macroeconomic policies these countries pursued explain the different outcomes. First, we briefly summarize some general trends for the region and subsequently focus on Argentina, Brazil, Colombia, and Mexico in Latin America, and Korea in Asia—the latter as a successful benchmark. At least three phases in the evolution of industrial policy can be identified in the post-Second World War period in Latin America (simply post-war hereafter). First, from the early post-war period⁴ to the late s/early s, state-led industrialization was the dominant strategy, especially in the largest economies of the region (Bértola and Ocampo, ). The Latin American governments actively sought to encourage industrialization and diversification, initially through import substitution, which was increasingly complemented by export diversification and regional integration. There were significant improvements in several fields, including the building up of technological capabilities in new sectors—frequently with a key role for publicly funded universities or R&D departments in large public-sector firms. State-led industrialization, however, was challenged by the debt crisis of the s, which subsequently turned into a major fiscal crisis. There was no room for industrial policy in the s, as investment collapsed, inflation rocketed, major macroeconomic adjustments were in place (usually under severe restrictions imposed by the creditor countries) and resources were transferred to foreign creditors. Second, in the s, foreign capital inflows returned to Latin America, and the external constraint was eased. With a less restrictive external environment, there should have been more space to move beyond the stabilization agenda. However, the predominance of orthodox views in policymaking, and the trauma left by the high inflation levels of the s, led to a retreat of the state, keeping industrial policies at bay. At best, across-the-board policies to enhance competitiveness were admitted (sometimes focusing on small and medium-sized enterprises; see Peres and Primi, ). Real exchange rate appreciation, facilitated by high liquidity in global financial markets, reinforced negative signals towards manufacturing and export diversification. Third, after a series of external crises in the late s and early s, there was a revival of industrial policies. Disappointment with the results of the pro-market reforms of the s had led to reform fatigue by the late s, as new generations of orthodox reforms were called for but were not adopted or had no significant success. However, the revival of industrial policies was timid and faced powerful countervailing forces. The – commodity boom (temporarily interrupted by the – North Atlantic financial crisis) boosted exports intensive in natural resources—a reprimarization of the export structure—particularly in South America, and generated a new wave of exchange rate appreciation. Some of the industrial policy instruments were mostly defensive and ill articulated with technological policy. The emergence of China as a prominent global trader not only contributed to the reprimarization of Latin America’s export structure through its demand pattern ⁴ In some cases, the strategies went back to the s or even to the late nineteenth and early twentieth centuries. See Bértola and Ocampo ().

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   



(concentrated in natural resources) but also by competing with the Latin American manufactures in Europe, the United States, and in the region itself. It became more difficult for Latin American countries to remain competitive in industries with low or medium technological intensity. As stated by Jenkins and Freitas Barbosa (): ‘it is clear that the concerns of manufacturers over Chinese competition are found throughout the region from Mexico to Argentina. They are also prevalent in a wide range of industries from traditional labour-intensive activities such as clothing, footwear, and furniture to more technologically advanced and capital-intensive sectors such as steel and electrical and electronic products.’⁵ During the three periods, a common feature was the weakness of the state when it came to penalizing firms that received public support without delivering in terms of technical change and competitiveness. Even during the years of state-led industrialization, the state’s failure to remove rents when they did not encourage innovation contrasts with the assertive policies adopted in Asia, where incentives were granted on the basis of performance, generating ‘reciprocal control mechanisms’, to borrow Amsden’s () term.

.. From State-led Industrialization to the Debt Crisis The period of state-led industrialization was a period of convergence (or less intense divergence) in relative productivity and improvements in the indices of structural change in Argentina, Brazil, and Mexico, and to a lesser extent Colombia. The RER remained overvalued for long periods, due to the prevalence of fixed exchange rates in an inflationary context (Mexico being an exception in this regard, as it showed low inflation). This problem was partially corrected by the adoption of the crawling peg in Brazil and Colombia in the mid-s. It was also counterbalanced, in terms of its effects on tradable sectors, by high levels of protection and export subsidies on nontraditional exports. Brazil and Mexico were more successful in convergence. The trend began earlier in Mexico, as a result of the policy known as stabilizing development, whereas in Brazil convergence gained momentum in the second half of the s, leading to the ‘Brazilian miracle’. Unlike Argentina and Colombia, Brazil and Mexico continued to converge in the second half of the s as a result of ambitious plans for building capital and intermediate goods industries—the Second National Development Plan in Brazil (Aldrighi and Colistete, ) and the National Plan for Industrial Development in Mexico (Moreno-Brid and Ros, ). Both plans sought to deepen

⁵ The authors point out that the high share of intermediate Chinese inputs in manufacturing production in Brazil and Mexico implies the risk of a process of ‘hollowing out’ of the manufacturing sector if domestic policies are not changed.

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

ˊ     

import-substituting industrialization and export diversification, using tariff and non-tariff barriers, and export subsidies. While Brazil was heavily dependent on oil imports, partly moderated by a booming sugar-based ethanol industry that was part of its industrial policy, Mexico had become a significant oil exporter in the mid-s, a fact that also boosted economic growth. Brazil and Mexico were seen as rising industrial powers belonging to the group of Newly Industrializing Countries (NICs). Economic growth could rely in the second half of the s on high liquidity and low interest rates in the international financial markets. Still, trade liberalization and the opening up of the capital account in Argentina, and rapid growth in Mexico and Brazil (including the rising costs of imported oil in the case of Brazil), gave rise to an unsustainable increase in external debt (Cardoso and Fishlow, ; Dornbusch and de Pablo, ). Colombia remained immune to that trend thanks to its decision to save part of the coffee boom that it experienced in –. In turn, domestic financial liberalization generated a domestic financial boom in all of these economies. It is important to note that the rise in external debt occurred both in countries that were still pursuing state-led industrialization (Brazil and Mexico) and in countries that had already abandoned this development strategy (Argentina, as well as Chile, not analysed here). The debt crisis came, therefore, from the excessive reliance on foreign capital rather than on the specific type of industrial policies that were in place. The debt crisis that sparked in  reversed the industrialization drive in Brazil and Mexico and accelerated de-industrialization in Argentina. It was accompanied by major macroeconomic adjustments in Argentina, Brazil, and Mexico in the early s to manage their massive fiscal and balance-of-payments crises, the latter leading to large exchange rate adjustments that heightened inflationary pressures. Short-run concerns over stabilization (how to pay the debt and tame inflation) prevailed over long-run objectives of economic growth. The economic crisis, together with the political crises in Argentina and Brazil, made the Latin American governments particularly vulnerable to pressure from banks and international organizations, which acted in a coordinated way. They demanded austerity measures and a reduction in public investment to pay for the debt. The region implemented a drastic overhaul of trade and industrial policies along the lines of the structural-reform agenda being pushed by the World Bank and embedded in a sequence of stand-by agreements signed with the IMF. Although Colombia avoided an external debt crisis, it also experienced fiscal and balance-of-payments problems and slower growth, but not massive exchange rate adjustments and associated inflationary pressures; hence, it was able to renew growth in the second half of the s, earlier than the other countries. Debt and austerity imposed a crucial burden on the development prospects of the region, one that would persist for many years. Until the late s/early s, the Latin American countries grew at very low rates while investment rates collapsed, generating a ‘lost decade’—the term that the Economic Commission for Latin America and the Caribbean (ECLAC) coined to refer to the s, and that has been widely used for other parts of the world since then. The strong impact of the debt crisis on investment seems to have produced a hysteresis phenomenon: the investment rate never

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   



returned to the levels it had attained in the three decades before the crisis. Again, due to its lower debt ratios, Colombia was a partial exception.

.. The Washington Consensus Years The second phase began in the late s/early s and continued until the early s, a period that marked the heyday of the Washington Consensus.⁶ It was characterized by reforms aimed at liberalizing foreign trade, privatizing state-owned enterprises, and deregulating markets. Many countries abandoned industrial policy (‘the best industrial policy is no industrial policy’) or at most implemented horizontal policies to encourage competitiveness and innovation across the board. These policies were, in theory, aimed at making industrial development and technological change more efficient—driven by the needs of firms rather than by the decisions of government agencies. In practice, they dismantled most of the old policies and put in place a poorly articulated set of incentives to encourage productivity and innovation. Argentina created the National Agency for Scientific and Technological Promotion. Brazil launched the Brazilian Programme for Quality and Productivity, and the Programmes for Technological Development in the industrial and agricultural sectors. Brazil’s National Development Bank (BNDES), which had been very active in the s supporting the creation of new industries, played a new role financing the privatization of public-sector firms. In Mexico, the Economic Solidarity Plan of  began to dismantle trade barriers, a process that accelerated in the following years. By the s non-tariff barriers had been almost completely removed, with a few exceptions in the oil, automobile, and agricultural sectors (Moreno-Brid and Dutrénit, ). In the transition towards more liberal policies and the abandonment of industrial policy, trade agreements became an essential element of the new strategy, particularly the  North American Free Trade Agreement (NAFTA). This agreement implied a commitment to eliminate barriers to trade over a period of ten years. It was expected to allow Mexico to start a phase of export-led growth based on its privileged access to the US market. Colombia massively liberalized foreign trade in the early s (with some agricultural goods and car assembling as partial exceptions). It also redesigned its system of development banks (creating a bank for foreign trade, BANCOLDEX, out of a central bank rediscount facility for non-traditional exports, and keeping a development bank

⁶ See Stalling and Peres (). The liberalization drive started earlier in Mexico, with the De la Madrid administration (–). In , Mexico adopted a Programme for Modernizing Industry and Trade (Programa Nacional de Modernización Industrial y de Comercio Exterior, PRONAMICE, –), which would subsequently be complemented by further liberalization, as pointed out in the main text.

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

ˊ     

for industrial development, IFI)⁷ and an export promotion agency (PROEXPORT). The country also launched a series of national and regional competitiveness councils to support the private sector (Ocampo and Arias, ). However, the effects of trade liberalization and the exchange rate appreciation—generated in the latter case at least partly by the foreign exchange and capital account liberalizations that accompanied the new trade policy—prevailed throughout the manufacturing sector over those of the moderate competitiveness policies. The latter also lacked continuity across government administrations. The s also witnessed a change in the prevailing outlook on economic integration in Latin America. While integration agreements since the s had been mostly partial and had been reached in a context of high barriers to international trade, the ‘open regionalism’ of the s sought to reduce overall trade barriers while keeping a margin of preference for regional trading partners. The Andean Community (previously Andean Group) and the Central American Common Market were relaunched in the early s, and the Southern Common Market (Mercosur, according to its Spanish acronym) was created in . They served as a framework for the significant growth of intra-regional trade (particularly of manufactures) in the s until the crisis that struck the region at the end of the decade. Overall, trade liberalization and the removal of barriers to competition and regulations failed to enhance competitiveness and speed up economic growth to the levels that had been typical during the period of state-led industrialization. This decade was also one of sluggish investment and strong RER appreciation. Figure . shows how the opening up of the capital account (as measured by the Chinn–Ito Index of capital account openness (Chinn and Ito, ), plotted on the left vertical axis) and the investment rate (plotted on the right vertical axis) moved in opposite directions in Latin America (see Cherkasky and Abeles, ). There were partial exceptions to the horizontal approach to industrial policy. In all four countries analysed, the automobile industry enjoyed a special regime, which also sought to foster the production of auto parts. In Brazil, sixteen Sectoral Funds (Fundos Setoriais) were created in , which represented a new mechanism for funding investments in science and technology, based on contributions from many different sources, including royalties from oil exploration. In Argentina, a regional policy provided incentives for the installation of assembling industries in Tierra del Fuego—though with very little incentive for developing local capabilities; it was created in the s and renewed over the years. In Colombia, as indicated, weak competitiveness policies were put in place. Global financial conditions in this period were favourable for capital inflows towards the region, which took place, as we have seen, amid capital account liberalization processes (Ffrench-Davis and Ocampo, ; Ffrench-Davis, ; Freund and ⁷ There were three additional development banks, not relevant for the analysis here: one for rural development, another for regional and local government projects, and a third one for energy investment, which was later given the responsibility to promote public–private infrastructure projects.

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2014

2012

2008

2010

2006

2004

2002



Investment ratio (% of GDP)

18%

2000

0.0

1998

19% 1996

0.1 1994

20%

1992

0.2

1990

21%

1988

0.3

1986

22%

1984

0.4

1982

23%

1980

0.5

1978

24%

1976

0.6

1974

25%

1972

0.7

1970

Chinn–Ito Index

   

Chinn–Ito index of capital account openness Investment ratio (% of GDP), 3-year moving average

 . Investment ratio and capital account openness in Latin America Source: ECLAC based on the Chinn–Ito Index and Penn World Tables.

Pierola, ; Frenkel and Rapetti, ; Frieden, ). Capital account liberalization was moderated by taxes on capital inflows in Brazil and by reserve requirements on such inflows in Colombia (as well as Chile, not analysed here). Global liquidity led to an appreciation of the RER in Argentina, Brazil, and Colombia (Figure .). While this was helpful to curb inflationary pressures in Argentina and Brazil, it depressed the competitiveness of industrial production. In both countries, the exchange rate became, therefore, a nominal anchor to stabilize inflation expectations. Mexico also faced appreciation pressures, which were interrupted, however, by a balance-of-payments crisis in late . Deregulation of capital accounts, the loss of competitiveness, and current account deficits foreshadowed the next external crises. They occurred in  (Tequila crisis) in Mexico, and in – in the other economies, as a contagion of the crises in East Asia and Russia. Brazil experienced a crisis at the end of the Real Plan in , Colombia experienced in that year its worst recession of the post-war period, and Argentina saw the collapse of its Convertibility Plan in  after several years of difficulties.⁸ In all cases, these processes were accompanied by strong exchange rate depreciations (see Figure .).

⁸ Brazil’s Real Plan was less rigid that Argentina’s Convertibility Plan and was abandoned earlier than the latter (see Salvia, ). In addition, Brazil imposed a tax on capital inflows as a response to their surge in – (Goldfajn and Minella, ; Carvalho and Garcia, ), which failed, in any case, to prevent the appreciation of the real, given the attractiveness of the Brazilian market due to high domestic interest rates. Brazil fell into what has been called a ‘low RER x high interest rates trap’ (Oreiro et al., ; see also Prates et al., ). After the – turbulences, capital account regulations were lifted (see Baltar, ). In any case, these regulations made the Brazilian crisis of January  (which marked the end of the Real Plan) milder and shorter than the Argentine crisis of . On the crisis of the late twentieth century in Colombia, in contrast to its performance during the Latin American debt crisis, see Ocampo and Romero (: –).

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

ˊ     

160.0 140.0 120.0 100.0 80.0 60.0 40.0

0.0

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

20.0

Argentina

Brazil

Colombia

Mexico

 . Real exchange rate ( = ) Source: ECLAC; an increase means a real exchange rate depreciation.

.. The Timid Return of Industrial Policy in the s The external crises of –, and the sense that pro-market reforms had failed to bring about the expected recovery in growth, led to a gradual return of industrial policy, mixed in part with new R&D policies and the spread of intellectual property rights regimes adopted by WTO and free-trade agreements (Peres, ; Primi, ). The timid return of industrial policies faced, however, a new wave of RER appreciation in South America, the strong effects of the – North Atlantic financial crisis on Mexico, and a significant slowdown in South America after the – commodity boom came to an end. Also, in contrast to the revitalization of the regional integration agreements in the s, which had been a significant source of intra-regional trade in manufactures, they weakened and became embedded in political rivalries with strong ideological content. Notably, Venezuela left the Andean Community in  and joined Mercosur, from which it was in turn expelled in  due to its lack of commitment to democracy. The split in the Andean Community, together with the political confrontations and the economic and political crisis of Venezuela, led to the collapse of the second major bilateral intra-regional trade flow, that between Colombia and Venezuela. A new integration agreement, the Pacific Alliance, has been the most dynamic regional agreement since it was launched by four Pacific nations (Chile, Colombia, Peru, and Mexico) in . In Brazil, during the first presidency of Lula da Silva in , the Industrial, Technological and Trade Policy (PITCE by its Portuguese acronym) was approved,

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   



focusing on encouraging innovation and high-tech sectors. The PITCE included horizontal instruments along with fiscal and financial incentives for strategic sectors, such as capital goods, pharmaceuticals, software, nanotechnology, and biotechnology. An interesting dimension was the development of technologies and capital goods for deep oil exploration to allow Brazil to fully exploit discoveries that were taking place at the time, enabling the country to become an international leader in this field. Brazil also set out a new institutional framework with a key coordinating role for the Agency of Industrial Development (Portuguese acronym ABDI). PITCE was subsequently replaced by the Policy of Productive Development (PPD, –), in which the development bank (BNDES) played a major role in encouraging the internationalization of large Brazilian firms. There was also a focus on coordination with the private sector and with other public-sector programmes, notably the PAG (Programme for the Acceleration of Growth), primarily focused on investments in infrastructure. While the crisis of  compromised the advance of the PDP, this program was instrumental in sustaining investments and aggregate demand in the context of an international recession of industrial countries. Finally, the PDP was replaced by the Plano Brasil Maior (PBM) in the period –, under President Dilma Rouseff. The PBM showed a more protectionist stance and was concerned with lowering production costs, as the appreciation of the RER (boosted by the commodity boom) harmed growth and employment (see ECLAC, ; Bresser-Pereira, ; Bresser-Pereira et al., ; Nassif et al., ; Bekerman and Dalmasso, ). In spite of its ambitious objectives for competitiveness and technical change, PBM mostly played an anti-cyclical role (Laplane and Laplane, ). It remains to be seen whether the trade liberalization policy announced by the Bolsonaro administration that started in  will end up reversing the industrial policies of previous administrations, which is a very likely outcome. The Brazilian industrial policy of the s had an impact on industry and R&D. Significant resources were devoted to these programmes, including, as we will see, relatively large levels of investment in R&D relative to other Latin American countries, though much lower than those of Korea. Notwithstanding these advances, industrial policy was fragmented, driven by short-term political pressures, targeting in many cases sectors not related to advanced technologies. There was no progress in terms of structural change or reversing the de-industrialization process. Indeed, the – commodity boom reinforced the Brazilian specialization in natural resourceintensive exports. The growing role of China as a trade partner of Brazil reproduced the traditional North–South (centre–periphery) specialization patterns with which structuralist economists were so concerned: Latin American countries exporting commodities in exchange for manufactures. Incentives for investment thus remained concentrated in traditional comparative advantages. The lack of synchrony with the macroeconomic policy was indeed an important factor leading to the reinforcement of the specialization pattern in natural resources (see Nassif et al., , ). The strong appreciation of the real was a persistent challenge for industrial competitiveness, except for a short interregnum in late 

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi



ˊ     

and . Since October , Brazil has deployed a vast array of capital account regulations to prevent the real from continuing appreciating. A tax on the notional amount of derivatives was applied, which complemented other measures to close loopholes that had allowed investors to bypass the regulations. However, differences in interest rates between foreign and domestic markets remained very high in the s (Kaltenbrunner and Paincieira, ).⁹ Capital account regulations began to be dismantled from , as the real showed increasing weakness, and monetary policy became less restrictive. In Argentina, the Convertibility Plan collapsed in , when the peso was devalued, and GDP contracted by  per cent ( per cent with respect to ).¹⁰ The response of the new government that took office amidst political and economic turmoil was to advance in both macroeconomic and industrial policies. Concerning the latter, it reinvigorated the science and technology policy, and (especially since ) recovered instruments that had become redundant in the s, including investments in technology by state-owned enterprises, using government purchases as an industrial policy instrument and some elements of trade management. Policymakers sought to articulate large public projects with investments in R&D and technological development. Sectoral technology funds and sectoral innovation funds (FTS and FITS, according to their Spanish acronyms) were created to encourage technological learning in biotechnology, nanotechnology, and agro-industries. There were also public research programmes in satellites and nuclear energy, and a rise in technology investments by large public firms, such as the (re)nationalized REPSOL in the oil sector (Stumpo and Rivas, ). On the macroeconomic front, and for a short time, RER management encouraged industrial growth. In , the government adopted a system of differential taxes on exports (retenciones) that amounted to a multiple exchange rate system, penalizing agricultural exports and favouring manufacturing. Taxes on exports of primary goods increased from  per cent to  per cent between – and –. Inversely, these taxes remained at  per cent for manufactures processing industrial inputs during the whole period – (Lavarello and Mancini, : ). However, RER appreciation eroded competitiveness over time. This made the government turn to protectionism (as happened in Brazil), particularly after the  crisis, in the form of quotas, nonautomatic import licensing (since ), and managed trade and export requirements. The differential taxes were dismantled by the incoming Macri administration in late  (apart from for soybeans), but were re-established as a fiscal adjustment device in September . The launch of the Strategic Industrial Plan  and Argentine Innovation  in  represented important steps in the quest for a coherent industrial plan for Argentina. However, industrial and technological efforts remained dispersed and ⁹ Kaltenbrunner and Paincieira (: ) observed that the composition of financial investments was heavily concentrated in short-term maturity assets. ¹⁰ See IMF () for an analysis of this crisis.

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   



ill-articulated. Most of the resources for industrial policy went to the automobile sector and to special regimes like in electronics in Tierra del Fuego, in which assembling activities are dominant. The main pro-manufacturing incentives came, as we have indicated, from the system of differential export taxes. But, as in the case of Brazil (and, as we will see, Colombia), the – commodity boom redefined incentives in a way that penalized the industrial sector. Neither Brazil nor Argentina were able to prevent the RER from neutralizing the potential gains in productivity that arose from the return of industrial policy instruments. The return of industrial policy has been much less assertive in Mexico than in Argentina and Brazil. President Fox recognized the importance of sector-specific policies in his National Development Plan (–) but did not put resources behind the plan to make a difference compared to the previous administrations (Moreno-Brid, ). The idea of recovering the role of industrial policy was resuscitated by the Peña Nieto administration in the National Development Plan – and the quest for ‘democratizing productivity’.¹¹ According to this plan, industrial policy should be directed at raising productivity and increasing value added in manufacturing production. The need for a renewed industrial policy was put in the following terms by economic minister Videgaray in March : ‘We should have a country in which every year productivity grows; but for that we need an industrial policy . . . This concept was practically forbidden in Mexico during many years . . . But we have to come back and dare to pursue an industrial policy . . . for a more competitive industry and for raising the country’s productivity’ (quoted in Moreno-Brid and Dutrénit, : ). In practice, however, there was little progress in this direction, and few resources were effectively allocated to industrial policy programmes. The emphasis was on policies that should boost the existing comparative advantages rather than defying them. A Programme for Innovative Development (PRODEINN, –) was adopted to enhance productivity. But it had only a slight impact, as reflected in the stagnation of R&D expenditures at low levels. In the same vein, the government approved new legislation in  to create special economic zones, which would receive fiscal and financial incentives, and investments in infrastructure aimed at reducing regional inequalities and attracting higher-productivity activities to depressed territories, especially in the south of Mexico. As happened with other policy initiatives, implementation was sluggish and few resources were allocated. They failed to alter the scenario of slow productivity growth and slow structural change of the Mexican economy. All in all, industrial policy continues to be relegated to a secondary position in Mexico, a problem aggravated by low rates of public investment, which dwarfs the capacity of the government to effectively implement its development plans. By expecting that NAFTA and trade liberalization would provide enough incentives for export-led growth, Mexico remained locked in its static comparative advantages (notably the maquila system in which low wages are still a key driver of ¹¹ The concept was ill-defined, but probably made reference to the need to spread productivity gains from a small group of exporters to the rest of the economy.

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

ˊ     

competitiveness), missing the key link between trade and industrial policy as a tool for structural change in the Asian economies. A comparison with other major manufacturing exporters, China and the Republic of Korea, indicates that Mexico has been able to extract less value added from its exports and is showing a negative rather than a positive trend in this regard.¹² The absence of a national development bank as powerful as BNDES has also been a significant difference between the experiences of industrial policy in Mexico and Argentina compared to Brazil (Santarcángelo et al., ). For its part, and following the pattern set in the s, Colombia continued with the trade liberalization processes, now enhanced by free-trade agreements with developed countries, starting with the United States in . Proexport continued to play the role of export-promoting agency and was transformed into Procolombia in , with the additional tasks of promoting tourism and foreign direct investment. The foreign trade development bank (Bancóldex) absorbed the industrial bank (IFI) in . Bancóldex also emphasized a programme of entrepreneurial modernization, has been active in promoting financing of firms in their early stages of development, notably through the angel investor network (Red Nacional de Ángeles Inversionistas), and has promoted private-equity venture funds to support business growth in a diverse set of sectors (Ocampo and Arias, ). These policies were accompanied by a sequence of national and regional competitiveness strategies, which operated mainly as horizontal industrial policies. It also included sectoral initiatives, largely aimed at breaking bottlenecks to development, supporting regional clusters and strengthening regional agents promoting innovation and entrepreneurial development. The sectoral growth covenants (Pactos por el crecimiento y la generación de empleo), launched in , belong to this family. There are also specific programmes that provide technological, administrative, and financial support to firms—particularly innovative firms—at the microeconomic level through Colombia Productiva (formerly Programa de Transformación Productiva) and iNNpulsa (managed by Bancóldex), adopted in  and . These initiatives have been formulated in the context of the Production Development Policy, which had its roots in  and was improved in  when it was approved by the National Council of Economic and Social Policy (CONPES), the top national economic authority (CONPES, ). Additional support at the firm level and for regional clusters is implemented by chambers of commerce. A private-sector council (Consejo Privado de Competitividad), created in , provides regular analysis of competitiveness and productivity issues. However, the effect of these policies has been restricted due to scale and discontinuity across administrations. There has been a remarkable lack of coordination between national and regional programmes and limited resources have been allocated to them. Indeed, some of the local programmes run by the most dynamic chambers of commerce, which also support individual firms and regional clusters, have had greater ¹² See the recent OECD-WTO data in this regard (https://www.oecd.org/sti/ind/measuring-trade-invalue-added.htm#access).

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   



continuity and impact.¹³ Also, investment in R&D remained very low, at the lowest level of the four countries analysed here (see Figure .). Furthermore, as in the case of Argentina and Brazil, macroeconomic policy overwhelmed the effects of industrial policy—particularly, again, the exchange rate effects of the – commodity boom. Manufacturing did experience a revival in the mids, when the balance-of-payments crisis that hit the country in  was over: the exchange rate was still competitive (see Figure .), and a temporary boom in manufacturing exports to Venezuela also helped. But the exchange rate effects of the commodity boom soon led to the renewal of the de-industrialization trend. In contrast to  and –, when reserve requirements were imposed on foreign borrowing to limit short-term capital flows and the exchange rate appreciation they generated, similar policies were not put in place during the second phase of the commodity boom, –. The paths identified for the four Latin American countries confirm the observation of Peres and Primi (: ), who argue that: ‘Latin America’s development trajectory is linked to the fact that these policies have never been among the top priorities for governments—at least since the s. Macroeconomic stability and a certain compliance with what was considered to be a respectable and conventional economic policy have been the main shapers of national development strategies.’ The efforts of the s to revive industrial policy in the region were too weak to reverse the loss of the institutional and political capabilities it suffered in the s. What, on paper, was a quest for industrial efficiency in the shape of a move from a vertical to a horizontal industrial policy, was in practice a feeble and fragmented policy.

. K   B

.................................................................................................................................. In contrast to the Latin American experience in recent decades, the role of industrial policy in targeting more sophisticated industries through time has been the hallmark of the Korean development process in the post-war period.¹⁴ Korea is a paradigmatic example of the development pattern that characterized several economies in East Asia (traditionally called the ‘flying geese’, though China has already changed that pattern),¹⁵ which combined widespread government intervention with a strong presence in international markets (Khan, ).

¹³ For an evaluation of existing programmes, see Acosta () and OECD (). The latter proposes an interesting set of initiatives for the country in this field. ¹⁴ The classic work is Amsden (). See also Kim (, ), Lee (), Rodrik (), and Wade (). ¹⁵ China may be seen as the last (and more dramatic) example of the flying-geese strategy of industrialization, but it has changed the pattern, and now dominates Asian manufacturing. See Lo and Wu ().

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

ˊ     

A watershed in the evolution of industrial policy in Korea occurred with the military government in the s, which focused on establishing an industrial base that would allow the country to counterbalance the military power of North Korea and reduce its dependence on foreign finance and aid. The Economic Planning Board, created in July , was in charge of designing and implementing five-year development plans. Firms’ export performance was a key criterion for resource allocation based on the leverage provided by the government’s control over the financial sector (Lim, : ). In parallel, Korea invested heavily in education, expanding the supply of highly qualified labour to an increasingly complex industrial sector. Comprehensive policy support, structured in successive five-year plans, helped transform the production structure from consumer goods to heavy industries in the s, and since the s towards electronics, ICT, optics, and aerospace. In the s, the quest for new engines of growth led to the promotion of green industries, high-tech convergence, and high value-added services (Koh, ). The broad transformation of the industrial structure was accompanied by a rise in R&D spending, led at first by the public sector and subsequently, from the s, by the private sector, whose share in total R&D increased from  per cent in the late s to  per cent in  (Koh, ). The liberalization of imports was gradual and followed the path set by industrial upgrading (Koh, : –). Indeed, as pointed out by Nassif et al. (), the gradual, step-by-step approach to industrial policy in Asia (and its consistency with macroeconomic policy) is in sharp contrast with the shock therapy observed in Latin America (see also Suzigan and Furtado, ). Differences between Korea and Latin America were not confined to industrial policy, but can also be found in their financial and macroeconomic policies. Korea combined import substitution and export promotion to varying degrees throughout its development process, but emphasized export promotion from the early s. In this transition, the won went through a major depreciation in February and October  and in May  (when the price of the dollar jumped from  to  won per dollar). The system of multiple exchange rates was then replaced by a single fluctuating exchange rate (Koh, : ). Financial market and credit allocation and interest rates remained tightly controlled in the s and s. Several specialized public banks directed – per cent of domestic loans to selected industries, particularly in the capital and intermediate goods sectors (Yoon and Kim, ).¹⁶ Such a policy, combined with export promotion (the ‘acid test’ of learning), gave Korea the opportunity to redefine its comparative advantages. For a long time, Korea had capital account regulations in place (Noland, ). As set out by the former minister of trade, industry, and energy in Korea, Joong-Kyung Choi, strict regulations of foreign exchange flows were crucial in the early stages of ¹⁶ Noland (: ) points out that ‘modest financial-sector liberalizations that had been undertaken in the late s were reversed in , when interest rates were lowered and direct government control of the banking system was increased in order to channel capital to preferred sectors, projects, or firms’.

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   



development, and probably necessary even in the mature stages (Choi, : –). In the light of the impact of the  crisis, he observed that ‘a financial crisis is much more painful than inflation . . . Thus, controlling the cross-border flow of capital is more important than containing inflationary pressures’ (Choi, : ). As part of the process of joining the OECD in , Korea eased its financial and capital account regulations (Noland, ). This was not matched by the setting up of a domestic macro-prudential framework to contain short-term debt and RER appreciation.¹⁷ The rapid increase in the current account deficit, along with the short-term maturity of debts contracted in the external market, led to the  economic crisis. The intensity of the crisis was aggravated by a contractionary fiscal and monetary policy adopted in December  and implemented in the first half of —which was part of the agreement signed with the IMF that provided a US$ billion rescue package. Although the trend continued to be towards opening the capital account, Korea has, in some cases, resorted to safeguards to protect the country against financial instability and crises similar to those of  and .¹⁸ In addition, the country sought to build up its stock of foreign reserves to reduce its vulnerability to capital flight. All in all, although the transition to democracy in the s and the decision to join the OECD led to some changes in economic policy, industrial and technology policies remained highly developmentalist, as reflected more recently in very high levels of R&D. The  crisis also led to the return of more interventionist macroeconomic policies aimed at avoiding new financial crises.

. S F: A C V  P  S  L A

..................................................................................................................................

.. Phases of Convergence and Divergence The impact of industrial policy on productivity and structural change should be seen from a long-term perspective. Between  and , labour productivity in Latin America was between  and  per cent of that in the United States, with a slight upward trend (Figure .A). In contrast, there is a great divergence in productivity trends since : it dropped to about one-fifth of US productivity between  and , experienced a moderate recovery during the years of the commodity boom (‘the super-cycle’) of –, to stabilize at approximately one-fourth of the comparative ¹⁷ A Financial Supervisory Commission responsible for setting regulations and standards in the financial market was established in . ¹⁸ For instance, in  Korea placed some restrictions on derivative markets, but setting limits on the foreign-exchange derivatives relative to the capital base of the financial institutions.

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

ˊ      A. Total Latin America

0.45

0.40

0.35

0.30

0.20

1950 1952 1954 1956 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018

0.25

B. Individual Latin American countries vs. Korea 0.80 0.70 0.60 0.50 0.40 0.30 0.20

0.00

1950 1952 1954 1956 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018

0.10

Argentina

Brazil

Colombia

Mexico

Korea

 . Relative productivity vs. United States Source: Economic Commission for Latin America and the Caribbean (ECLAC), based on Total Economy.

benchmark. The stylized fact that emerges is quite clear: a phase of convergence with the developed world between  and , followed by a phase of divergence since around , with a mild spurt of convergence in the commodity-boom years (see Correa and Stumpo, ). The relative productivity in the four largest Latin American countries—particularly those of Brazil and Mexico—also tended to converge with that of the United States until the late s/early s and to diverge thereafter (Figure .B). In Argentina,

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   



divergence began in the mid-s, a few years before Brazil and Colombia, whereas it came a bit later in Mexico, in the very early s. In turn, the short period of convergence—or interruption of divergence—in the s benefited the South American economies, which are important commodity exporters, but not Mexico. The relative productivity of Latin American countries vis-à-vis the United States remained, in any case, at a dismal level. Inversely, Korea began at a much lower level of labour productivity in the s but went through a persistent process of convergence with the United States and Latin America, surpassing Brazil and Colombia in the mid-s, and Argentina and Mexico in the late s. These productivity patterns were also reflected in GDP trends. Overall, Latin American GDP growth fell by half between – and – (leaving aside the lost decade): from . per cent to . per cent a year. Growth also became more volatile, as reflected in two prolonged crises, in – and –. Among the four countries analysed here, the long-term slowdown was particularly strong in Brazil and Mexico (which grew by . and . per cent, respectively, in –, versus . and . per cent in the period of state-led industrialization), followed by Colombia (. versus . per cent); Argentina had been a poor performer during stateled industrialization but delivered an equally poor performance in the recent period (. per cent growth in both cases). An interesting comparison in terms of productivity performance is that of Brazil and Korea. In , labour productivity in Brazil was about . times higher than in Korea, while in  it was less than half. Convergence (in favour of Korea) was not uniform and was much faster after Brazil entered into an era of divergence vis-à-vis the United States. Brazil/Korea relative labour productivity declined by about  per cent in the four decades between  and , and by about  per cent in the four decades between  and . A similar pattern is obtained comparing the Latin American countries with developed economies. For instance, labour productivity in Brazil was, on average, about – per cent of that of Denmark in the s and s, and  per cent in the s, attaining a peak of  per cent in , but relative productivity in Brazil fell afterwards. Since  it has stabilized at about one-third of Danish productivity. Even during the commodity-boom years, Brazilian/Danish relative productivity increased just one percentage point (from  to  per cent, as estimated from data of the Total Economy Database of the Conference Board).

.. Structural Change and Convergence How does the evolution of relative productivity relate to structural change? A first aspect to highlight is the evolution of the share of manufacturing in GDP. For Latin America as a whole, Figure . shows the relevant trend, according to the three series of national accounts estimated by ECLAC. The period of stable productivity vis-à-vis the United States coincided with a significant increase in the share of manufacturing in

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

ˊ      21.0%

29.0%

20.0% 19.0%

1970 prices 1990 prices

18.0%

2010 prices

25.0%

17.0% 16.0%

2010 prices

1970 and 1990 prices

27.0%

15.0%

23.0%

14.0% 13.0%

21.0%

12.0% 11.0% 2015

2010

2005

2000

1995

1990

1985

1980

1975

1970

1965

1960

1955

1950

19.0%

 . Latin America: Share of manufacturing in GDP, – Source: ECLAC.

GDP, which, as shown by Bértola and Ocampo (: ch. ), depended on the size of the economies, in terms of both strength and diversification. In contrast, the period of divergence since the s has been accompanied by a strong de-industrialization, which in this case, was not interrupted, but rather speeded up by the – commodity boom. If we make a broad abstraction from changes in the base years of the national accounts, Latin America is essentially back to the levels of industrialization it had in the early s. As underscored by Palma (, ), the process can be characterized as one of premature de-industrialization, as manufacturing lost ground in GDP at a lower level of GDP per capita than when this process had started to take place in the developed countries. The share of manufacturing in GDP declined in all the larger Latin American countries (Figure .). The decline started earlier, in the mid-s, in Argentina and Colombia, and in the s in Brazil and Mexico. The sharp decline of manufacturing in Argentina was remarkable: it went from representing  per cent of GDP in  (more than  percentage points above Mexico) to  per cent in  ( percentage points below Mexico). The collapse of Brazilian manufacturing after  was also impressive, as was to a lesser extent that of Colombia. Thanks to its strong manufacturing export sector, the reduction was much more moderate in Mexico. In contrast, manufacturing’s share in Korean GDP increased by about  percentage points during the same period. The composition of manufacturing production also changed. The share of engineering industries (deemed to be the main drivers of technical change) in total manufacturing value added declined, while the share of less technology-intensive sectors

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   



45.0 40.0 35.0 30.0 25.0 20.0 15.0 10.0

0.0

1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 2017

5.0

Argentina

Brazil

Colombia

Mexico

Korea

 . Share of manufacturing in GDP: Largest Latin American countries vs. Korea Source: World Bank national accounts data, https://data.worldbank.org/indicator/nv.ind.manf.cpod.

increased. To keep a comparative approach, we computed the ratio between the share of the engineering industries in total manufacturing value added in Argentina, Brazil, Colombia, Mexico, and Korea relative to the same share in the United States (Figure .). This ratio is the Index of Relative Participation of engineering industries in total manufacturing value added (IRP;¹⁹ see ECLAC, ). It increased until around  in Brazil and Mexico and remained more or less stable thereafter—with a fall in the s and a strong recovery in the s in the case of Mexico, and smaller fluctuations in Brazil. In Argentina, this index stagnated in the s at lower levels than Brazil and Mexico by the later part of that decade and began to fall in the s, in such a way that it had lost about half of the value it had in the early s. Colombia had a less developed engineering sector compared to the other Latin American countries analysed, and also experienced a decline in the s. In contrast, Korea experienced a steady increase of this indicator, starting from levels slightly higher than

¹⁹ The IRP is defined as IRP=(ei/mi)/(eUSA/mUSA), where e is engineering value added and m total manufacturing value added; the superscript i denotes the country and the superscript USA denotes the reference country, in this case, the United States. The engineering industries are: metal products, nonelectrical machinery, electrical machinery, transport equipment, and scientific and professional instruments (categories  to  of the Standard Industrial Classification, SIC).

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

ˊ     

1.4 1.2 1.0 0.8 0.6 0.4 0.2

19

70 19 72 19 74 19 76 19 78 19 80 19 82 19 84 19 86 19 88 19 90 19 92 19 94 19 96 19 98 20 00 20 04 20 06 20 08 20 10 20 12 20 14 20 16

0.0

Brazil

Argentina

Mexico

Colombia

Korea

 . Index of the share of engineering industries in manufacturing value added vs. United States Source: Authors’ estimates based on ECLAC data.

4.5 4.0 3.5

2007

3.0

2016/17

2.5 2.0 1.5 1.0 0.5 0.0

Korea, Rep. of

OECD

Latin Brazil Argentina Mexico Colombia America

 . Research and development as % of GDP Source: UNESCO.

those of Colombia in the early s, surpassing Brazil and Mexico by the late s and even surpassing the United States in the s. Poor economic diversification was associated with very limited investment in R&D. Latin America’s investment in R&D is only a fraction of the average for the OECD, with only Brazil having attained levels higher than  per cent of GDP (Figure .). The levels of investment in R&D of Argentina and Brazil are less than half of those of Brazil and remained minimal in Colombia. The contrast with Korea is remarkable, as Korea

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   



2.6 2.4 2.2 2.0 1.8

1.4

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

1.6

Argentina

Brazil

Mexico

Korea

 . Strength of the National Systems of Innovation (NIS) Source: Lee and Lee (2019).

invests more than  per cent of GDP, indeed one of the highest levels in the world, and in recent years almost twice the average for the OECD. Another direct indicator of technological capabilities is the NIS computed by Lee and Lee () (see Figure .). Using US patent data, this index aims at providing a comprehensive picture of the innovative output of different countries, based on a set of standardized indicators of the patenting activity. The NIS is only available since , but does not include Colombia. Econometric exercises by Lee and Lee show that this index is a more robust predictor of economic growth than other indicators used in the literature. The evolution of the NIS points in the same direction as the previous indices when the economic performance of the Latin American countries is compared with that of Korea. First, Korea attained higher levels of NIS than in Latin American countries. Second, the trend in Korea was mostly positive, while in the case of the Latin American countries, the trend was more irregular, and there was no positive evolution over the long run. Brazil shows an almost flat NIS for the whole period. Mexico shows some fluctuation, but its most recent level is similar to that which it achieved in the early s. This captures the lack of backward linkages that the maquila-type export specialization, followed by Mexico within the NAFTA agreement (being replaced by the United States–Mexico–Canada Agreement, USMCA), contributing to technological learning in a laggard economy. In Argentina, there was a fall with the crisis of , a recovery after that, and finally a flat trend with some fluctuations.²⁰ Summing up, the pattern that emerges from relative productivity is confirmed by the evolution of various indices of structural change and technological capabilities.

²⁰ Lee and Lee () reach a similar conclusion running growth regressions using the NIS in the set of explanatory variables: ‘economies with successful growth experiences, such as South Korea, China, and Taiwan . . . mostly show upward sloping lines over time.’ These authors also note that in economies with less successful growth experiences, such as Brazil, Mexico, Thailand, and South Africa, ‘the NIS index does not increase much in certain periods or even declines’.

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

ˊ     

The decline in relative productivity in Latin America, particularly after , and the more dynamic performance of Korea, are associated with continuous structural change in the Korean case and stagnation or even reversion of industrial transformation in Latin America. Although these outcomes are the result of many different factors, the specific combination of industrial and macroeconomic policies adopted in the Latin American countries vis-à-vis Korea, as well as the low levels of investment in R&D, are crucial to explaining why they fell behind.

. C R

.................................................................................................................................. The dismantling of the state-led industrialization policies that many Latin American countries pursued in the post-war period—and in most cases since the s—led to a divergence of productivity levels and technological capabilities vis-à-vis the developed countries. This was the path followed by Argentina and Colombia since the mid-s, and by Brazil and Mexico since the early s. The return of industrial policies in the early twenty-first century has been hesitant, failing to prevent the loss of knowledgeintensive sectors in the production structure or to stimulate investments in R&D, except partially in Brazil. Structural change and specialization are stagnant, and there has been a reprimarization of export structure in recent decades in South America. Mexico relies on a specialization pattern based on exports of manufactures with low levels of domestic value added relative to the more successful insertion in global value chains of countries like China and Korea. In turn, Argentina, Brazil, and Colombia have reinforced their specialization in natural resources as a result of the – commodity boom and their growing trade with China. These paths are in sharp contrast with the experience of Korea, where active industrial policies aimed at deepening technological development and high levels of R&D spending have been the rule. The political economy of industrial policy was critical for the success of Korea. ‘Reciprocal control mechanisms’ helped discipline the large Korean firms and monitor the effectiveness of public policy in supporting the emergence of new industries and capabilities. On the other hand, these mechanisms were fragile in Latin America before the debt crisis and became still more fragile after it struck the region. The debt crisis first, the uncritical adoption of the Washington Consensus later, and a political economy which favours the capture of rents from natural resources over the creation of rents from technical change, have compromised the effectiveness and the willingness of economic actors to implement industrial policies. Macroeconomic policy, and particularly its effects on RER, has also been crucial. Recurrent RER appreciations have also contributed to the de-industrialization process and recurrent external crises. Periods of high financial liquidity in international markets have led to massive capital inflows, particularly when associated with capital account liberalization. The use of the exchange rate as an inflation anchor in many

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   



periods has contributed to that result. RER appreciation also resulted from the – commodity boom in the South American economies. This boom had adverse effects on manufacturing and counteracted the positive impact of the moderate return of industrial policies. Although Korea was not immune to the adverse effects of financial liberalization and capital account booms in the s, it returned to a macroeconomic and financial policy that aimed at avoiding these effects after the  crisis it faced. The tasks to be accomplished by the Latin American economies to catch up are still more daunting now than in the past. The technological revolution is shifting the international technological frontier very quickly, which makes it urgent for the region to finance and carry out massive investments in education, R&D, and institutional capabilities to respond to this more demanding competitive challenge. In addition, the socio-political context is in flux (at the international and domestic levels): demands for equality and sustainability need to be made compatible with the quest for technological change. As long as industrial policies continue to be a topic of secondary importance in the policy agenda, it will be increasingly difficult for Latin America not to fall behind.

A We are very grateful to Arkebe Oqubay, Eva Paus, Dirk Willem, Juan Carlos Moreno-Brid, and Andre Nassif for comments on a previous version of this chapter.

R Acosta, Jaime () ‘Economía de la innovación, territorios y equidad para Colombia’, Análisis, No. , Friedrich Ebert Stiftung, Bogotá. Available at http://library.fes.de/pdffiles/bueros/kolumbien/.pdf. Aghion, Philippe and Peter Howitt () Endogenous Growth Theory. Cambridge, MA: MIT Press. Aldrighi, Dante and Renato Colistete () ‘Industrial Growth and Structural Change: Brazil in a Long-run Perspective’. Working Paper Series No. –, Department of Economics, University of Sao Paulo. Amsden, Alice () Asia’s Next Giant: South Korea and Late Industrialization. New York: Oxford University Press. Amsden, Alice () The Rise of the Rest: Non-Western Economies’ Ascent in World Markets. Oxford: Oxford University Press. Anderson, Martin and Olof Ejermo () ‘Technology and Trade: An Analysis of Technology Specialization and Export Flows’. Working Paper No. /, CIRCLE, Lund University. Arrow, Kenneth () ‘Path Dependence and Competitive Equilibrium’, in William A. Sundstrom and Timothy Guinnane (eds) History Matters: Essays on Economic Growth, Technology and Demographic Change. Stanford, CA: Stanford University Press, pp. –. Atkinson, Anthony and Joseph E. Stiglitz () ‘A New View of Technological Change’, Economic Journal (): –.

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   



Fagerberg, Jan and Bart Verspagen () ‘Technology Gap, Innovation-Diffusion and Transformation: An Evolutionary Interpretation’, Research Policy : –. Ffrench-Davis, Ricardo () ‘Employment and Real Macroeconomic Stability: The Regressive Role of Financial Flows in Latin America’, International Labour Review (–): –. Ffrench-Davis, Ricardo and José Antonio Ocampo () ‘The Globalization of Financial Volatility’, in Ricardo Ffrench-Davis (ed.) Financial Crises in ‘Successful’ Emerging Economies. Washington, DC: Brookings Institution Press/ECLAC, pp. –. Frenkel, Roberto and Martin Rapetti () ‘A Concise History of Exchange Rate Regimes in Latin America’, in José Antonio Ocampo and Jaime Ros (), The Oxford Handbook of Latin American Economics. Oxford: Oxford University Press, pp. –. Freund, Caroline and Martha Pierola () ‘Export Surges: The Power of a Competitive Currency’, Journal of Development Economics (): –. Frieden, Jeffry () Currency Politics: The Political Economy of Exchange Rate Policy. Princeton, NJ: Princeton University Press. Goldfajn, Illan and Andre Minella () ‘Capital Flows and Controls in Brazil: What Have We Learned?’, NBER Working Paper No. . Cambridge, MA: NBER. Guzmán, Martin, José Antonio Ocampo, and Joseph E. Stiglitz () ‘Real Exchange Rate Policies for Economic Development’, World Development : –. IMF (International Monetary Fund) () ‘Lessons from the Crisis in Argentina’. Prepared by the Policy Development and Review Department in consultation with the other Departments,  October, p. . Jenkins, Rhys and Alexandre de Freitas Barbosa () ‘Fear for Manufacturing? China and the Future of Industry in Brazil and Latin America’, The China Quarterly : –. Kaldor, Nicholas () Further Essays on Economic Theory. London: Duckworth. Kaltenbrunner, Annina and Juan Pablo Paincieira () ‘Developing Countries’ Changing Nature of Financial Integration and New Forms of External Vulnerability: The Brazilian Experience’, Cambridge Journal of Economics (): –. Katz, Jorge and Giovanni Stumpo () ‘Sectoral Regimes, Productivity and International Competitiveness’, CEPAL Review : –. Khan, Mushtaq () ‘Rent-seeking as Process’, in Mushtaq Khan and Jomo Kwame Sundaram (eds) Rents, Rent-Seeking and Economic Development: Theory and Evidence in Asia. Cambridge: Cambridge University Press, pp. –. Kim, Eun Mee () ‘The Korean Development Alliance between Business, Labour and Government’. Paper presented to the seminar organized by UNRISD and KOICA, Seoul, South Korea,  September. Kim, Linsu () ‘Korea’s National Innovation System in Transition’. Science and Technology Policy Institute, Korea. Koh, Youngsun () ‘The Growth of Korean Economy and the Role of Government’, in Il SaKong and Youngsun Koh (eds) The Korean Economy: Six Decades of Growth and Development. Seoul: Korean Development Institute, pp. –. Laplane, Mariano and Andrea Laplane () ‘Planes industriales y los desafíos del desarrollo sostenible en Brasil’, in Mario Cimoli, Mario Castillo, Gabriel Porcile, and Giovanni Stumpo (eds) Políticas Industriales y Tecnológicas en América Latina. Santiago: ECLAC, pp. –. Lavarello, Pablo and Matías Mancini () ‘Política industrial y recuperación manufacturera en Argentina’, in Mario Cimoli, Mario Castillo, Gabriel Porcile, and Giovanni Stumpo (eds) Políticas Industriales y Tecnológicas en América Latina. Santiago: ECLAC, pp. – .

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ˊ     

Lee, Keun () Schumpeterian Analysis of Economic Catch-Up. Cambridge: Cambridge University Press. Lee, Keun and Jongho Lee () ‘National Innovation Systems, Economic Complexity, and Economic Growth: Country Panel Analysis Using the US Patent Data’, Journal of Evolutionary Economics. Available at https://doi.org/./s---. Lim, Phillip Wonhyuk () ‘Path Dependence in Action: The Adoption and Persistence of the Korean Model of Economic Development’, in Timothy Guinnane, William Andre Sundstrom, and Warren Whatley (eds) History Matters: Essays on Economic Growth, Technology and Demographic Change. Stanford, CA: Stanford University Press, pp. –. Lo, Dic and Mei Wu () ‘The State and Industrial Policy in Chinese Economic Development’, in José M. Salazar-Xirinachs, Irmgard Nübler, and Richard Kozul-Wright (eds) Transforming Economies: Making Industrial Policy Work for Growth, Jobs and Development. Geneva: UNCTAD-ILO, pp. –. Lundvall, Bengt-Åke () ‘From the Economics of Knowledge to the Learning Economy’, in Bengt-Åke Lundvall (ed.) The Learning Economy and the Economics of Hope. London: Anthem Press, pp. –. Moreno-Brid, Juan Carlos () ‘Industrial Policy: A Missing Link in Mexico’s Quest for Export-led Growth’, Latin American Policy (): –. Moreno-Brid, Juan Carlos and Jaime Ros () Development and Growth in the Mexican Economy. A Historical Perspective. Oxford: Oxford University Press. Moreno-Brid, Juan Carlos and Gabriela Dutrénit (eds) () ‘Políticas de Desarrollo Productivo en México’, OIT Américas, Informes Técnicos, /, October. Nassif, Andre, Luiz Carlos Bresser-Pereira, and Carmen Feijó () ‘The Case for Reindustrialisation in Developing Countries: Towards the Connection between the Macroeconomic Regime and the Industrial Policy in Brazil’, Cambridge Journal of Economics : –. Nassif, Andre, Carmen Feijo, and Eliane Araujo () ‘Structural Change and Economic Development: Is Brazil Catching up or Falling behind?’, Cambridge Journal of Economics (): –. Nassif, Andre, Carmen Feijo, and Eliane Araujo () ‘Structural Change, Catching up and Falling behind in the BRICS: A Comparative Analysis Based on Trade Patterns and Thirlwall’s Law’, PSL Quarterly Review (): –. Noland, Marcus () ‘South Korea’s Experience with International Capital Flows’, in Sebastian Edwards (ed.) Capital Controls and Capital Flows in Emerging Economies: Policies, Practices and Consequences. Chicago, IL: University of Chicago Press, pp. –. Ocampo, José Antonio () ‘Balance-of-Payments Dominance: Implications for Macroeconomic Policy’, in Mario Damill, Marín Rapetti, and Guillermo Rozenwurcel (eds) Macroeconomics and Development: Roberto Frenkel and the Economies of Latin America. New York: Columbia University Press, pp. –. Ocampo, José Antonio and Paola Arias () ‘Colombia’s System of National Development Banks’, in Stephany Griffith-Jones and José Antonio Ocampo (eds) The Future of National Development Banks. Oxford: Oxford University Press, pp. –. Ocampo, José Antonio and Carmen Astrid Romero () ‘La búsqueda, larga e inconclusa de un nuevo modelo (–)’, in José Antonio Ocampo (ed.) Historia económica de Colombia. Bogotá: Fondo de Cultura Económica and Fedesarrollo, pp. –. OECD (Organisation for Economic Co-operation and Development) () Production Transformation Policy Review of Colombia: Unleashing Productivity. Paris: OECD Development Pathways.

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

Oreiro, José Luiz, Lionello Punzo, and Eliane Araujo () ‘Macroeconomic Constraints to Growth of the Brazilian Economy: Diagnosis and Some Policy Proposals’, Cambridge Journal of Economics (): –. Palma, José Gabriel (), ‘Four Sources of “De-industrialization” and a New Concept of the “Dutch Disease” ’, in José Antonio Ocampo (ed.) Beyond Reforms: Structural Dynamics and Macroeconomic Vulnerability. Palo Alto, CA: Stanford University Press, ECLAC and World Bank, pp. –. Palma, José Gabriel () ‘How the full opening of the capital account to highly liquid financial markets led Latin America to two and a half cycles of “mania, panic and crash” ’. Cambridge Working Papers in Economics No. , January. Peres, Wilson () ‘The (Slow) Return of Industrial Policies in Latin America and the Caribbean’, in Mario Cimoli, Giovanni Dosi, and Joseph E. Stiglitz (eds) The Political Economy of Capabilities Accumulation: The Past and Future of Policies for Industrial Development. Oxford: Oxford University Press, pp. –. Peres, Wilson and Annalisa Primi () ‘Industrial Policy and Learning: Lessons from Latin America’, in Arkebe Oqubay and Kenichi Ohno (eds) How Nations Learn: Technological Learning, Industrial Policy, and Catch-up. Oxford: Oxford University Press, pp. –. Prates, Daniela, Andre Cunha, and Marcus Lelis () ‘La Gestión del Régimen Cambiario en Brasil’, Revista de la CEPAL : –. Primi, Annalisa () Promoting Innovation in Latin America. Maastricht: Maastricht University Press. Razmi, Arslam, Martin Rapetti, and Peter Skott () ‘The Real Exchange Rate and Economic Development’, Structural Change and Economic Dynamics (): –. Rodrik, Dani () ‘Getting Interventions Right: How South Korea and Taiwan Grew Rich’. NBER Working Paper No. . Cambridge, MA: NBER. Rodrik, Dani () ‘The Real Exchange Rate and Economic Growth’, Brookings Economic Studies Program (): –. Salvia, Sebastian Pedro () ‘The Boom and Crisis of the Convertibility Plan in Argentina’, Revista de Economia Política (): –. Santarcángelo, Juan E., Daniel Schteingart, and Fernando Porta () ‘Industrial Policy in Argentina, Brazil, Chile and Mexico: A Comparative Approach’, Revue Interventions économiques, Papers in Political Economy : –. Stalling, Barbara and Wilson Peres () Growth, Employment and Equity: The Impact of Economic Reforms in Latin America and the Caribbean. Washington, DC: Brookings Institution Press. Stumpo, Giovanni and Diego Rivas () ‘La industria manufacturera argentina –. Reconstruyendo capacidades para enfrentar los desafíos del siglo XXÏ’, in Giovanni Stumpo and Diego Rivas (eds) La industria argentina frente a los nuevos desafíos y oportunidades del siglo XXI. Santiago: ECLAC, pp. –. Suzigan, Wilson and João Furtado () ‘Política Industrial e Desenvolvimento’, Journal of Political Economy (): –. Wade, Robert H. () ‘East Asia’s Economic Success: Conflicting Perspectives, Partial Sights, Shaky Evidence’, World Politics (): –. Yoon, Je Cho and Joon-Kyung Kim () ‘Credit Policies and the Industrialization of Korea’. World Bank Discussion Paper No. . Washington, DC: World Bank.

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  ......................................................................................................................

                                

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    

. I

.................................................................................................................................. S-S A (SSA) countries experienced a growth spurt from the mids to the mid-s, after decades of economic stagnation and even contraction. However, despite over two decades of growth, very few African countries created manufacturing industries that were internationally competitive and diversified their exports away from dependence on a few primary commodities, and most countries were still importing the majority of their manufactured goods (UNECA, ). The ‒ global financial crisis and the associated collapse of the global commodity ‘supercycle’ by the mid-s highlighted the pitfalls of a narrow reliance on commodities and revived interest in structural transformation as key to providing jobs, increasing incomes, and raising the standard of living. There has been a slew of publications and processes exploring the prospects for a revival of industrial policy in SSA. Structural transformation is not just about attracting human and physical capital out of low-productivity and subsistence economic activities and into more productive enterprises. This definition does not capture the multiple, complex, and interacting processes that drive and sustain productivity growth. Rather, transformation involves moving the economy away from being a set of assets based on primary products exploited by unskilled labour towards an economy built on knowledge-based assets exploited by skilled labour (Amsden, : ). The term ‘technological capabilities’ refers to these knowledge-based assets: technical, managerial, and organizational skills that firms need in addition to formal education and scientific knowledge in order to achieve the level of

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       



productivity that established firms have achieved, which set the (international) market standard. The more technological capabilities that firms have, the greater their ability to sustain national income growth by moving into higher-value economic activities and innovating as well as responding flexibly to changing competitive conditions. The technological capability approach to understanding structural transformation and its concomitant focus on industrial policy as promoting local firm learning and capability building stems from an evolutionary economics perspective (see Cimoli et al., Chapter  in this volume). In examining industrial policies aimed at transforming African economies in the twenty-first century, this chapter focuses on how these industrial policies help locally owned firms become internationally competitive through building these capabilities. The chapter also examines the challenges that late-late industrializing countries in SSA face in the context of a global economy defined by international trade in intermediate goods through global value chains (Gereffi, ). Historically, the manufacturing sector is where technological capabilities were nurtured and wealth was produced as a result of imperfect competition, barriers to entry, and increasing returns, and this is why industrialization was key to generating wealth in Northern European countries and the United States (Reinert, ). When other countries tried to emulate this process, they used a combination of import-substitution and export-oriented industrial policies to build similar manufacturing industries (Schwartz, ). However, the expansion of manufacturing capabilities to more countries in the post-Second World War period and the concomitant outsourcing of manufacturing by Western and Japanese corporations led to the rise of global value chains. This took place in the context of extensive liberalization of trade, a dramatic expansion of the global workforce engaged in global trade, and rising pressure on corporations to raise returns to shareholders. Western and Japanese corporations now focus on economic activities in the pre- and post-manufacturing stages, such as research and development, branding, marketing, and retail, where they can still create high barriers to entry through proximity to markets, first-mover advantages, and intellectual property rights. Manufacturing activities are fragmented and dispersed globally in a spatial hierarchy of production sites depending on countries’ wage costs and their firms’ capabilities (Schwartz, ; Coe and Yeung, ). Production activities and functions in global value chains are characterized by different levels of competition, generating different levels of wealth and income, hence the hierarchy. The lowest function in buyer-driven global value chains, the assembly of imported inputs, is characterized by near perfect competition (including perfect substitutability). As a result, firms producing this type of manufactured export are price takers, and it is global buyers generally located in developed countries that capture productivity increases rather than the developingcountry producers, as was the case with agricultural exports from developing countries in the twentieth century (Kaplinsky, ). At the same time, agribusiness industries and knowledge-based service industries now have characteristics that manufacturing historically did, such as sophisticated organization and production processes that require technological capabilities to be built (and thus increasing returns through

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

    

learning) and the ability to create wealth through barriers to entry through research and development, specialization, economies of scale, and so on.¹ As a result, industrial policies can target agribusiness, manufacturing, and knowledge-based services for international, regional, and domestic markets as a way to build the technological capabilities of local firms, generate wealth, tap into high demand through export markets, and create deeper linkages within the domestic economy. However, SSA countries may not be able to use the same industrial policy strategies as previously industrializing countries. The import-substitution industrialization (ISI) and export-oriented industrialization (EOI) policies of past decades were never mutually exclusive alternatives; rather, they were used in combination to access foreign knowledge but also to protect local firms while they were learning. However, it has become difficult for SSA late-late industrializers to implement them in the same way. Entry into a new industry and its export markets generally requires entry into global value chains, often through assembly of imported parts. Thus, industrialization begins with vertically specialized industrialization and generally low-value-added exports, then local firms upgrade within the global value chain by producing more of the imported inputs locally (Milberg et al., ). In other words, firms start with a new form of EOI, acquiring foreign tacit knowledge and social connections to global buyers and input suppliers, and then move to a new form of ISI that works backwards from assembly to intermediate inputs to raw materials. Thus, successful industrialization through global value chains corresponds with declining vertical specialization. It also increasingly involves a move from export markets to regional and domestic markets, so that local firms can move into branding, marketing, and retailing (where more wealth can be captured), and then sometimes a re-coupling with global value chains where local firms enter at higher-value functions (Coe and Yeung, ). However, many SSA countries are still at the early stages of diversifying their economies away from natural resources, building knowledge-based assets, and creating deeper linkages within the domestic economy, especially in the context of the colonial trading economies that they inherited at independence (see Whitfield, ). Thus, they need industrial policies focusing on domestic industries and non-tradable sectors that face different challenges from entering global value chains, such as the need to stimulate domestic demand through government expenditure, linkages between agriculture and industrialization, and promoting several industries at the same time that can concurrently generate sustained domestic demand. These are old challenges discussed by structural development economists, but still very real for SSA countries. The aim of this chapter is to discuss these issues through an examination of the recent experiences of selected SSA countries implementing industrial policies. Notably, many SSA governments have not pursued industrial policies, reflecting policy continuity from the period of structural adjustment (see Chitonge and Lawrence, Chapter  in this volume). The cases of industrial policy examined in this chapter focus on types of ¹ For further details, see the review in Whitfield et al. (), and the discussion on agribusiness and services in Newfarmer, Page, and Tarp ().

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       



industries, markets, and industrial policies, and not on the entirety of country experiences. The first case involves industrial policies to promote the cement industry, a nontradable heavy industry, in Nigeria, contrasted with Ethiopia. We focus not only on how local firms emerged in an industry dominated by multinational corporations in most SSA countries, but also on how domestic market demand was created and sustained. The second case considers industrial policies in Ethiopia to create an apparel export industry. It examines the challenges for local firms entering labour-intensive manufacturing global value chains, and the challenges for SSA governments in implementing industrial policies that compel local firms to build the required capabilities as well as to create more of the value chain within the country. The third case explores industrial policies to promote knowledge-based service sectors in Rwanda and Kenya. In particular, it examines their governments’ attempts to promote local firm participation in export-oriented knowledge services such as business-process outsourcing. The fourth and final case assesses industrial policies in South Africa aimed at diversifying manufacturing beyond heavy industries, focusing on the automobile and apparel sectors. In doing so, it illustrates some of the challenges of using industrial policy to promote apparel production for export when local firms are domestically oriented, and to promote greater production of inputs locally for the export-oriented automobile sector and thus move beyond the early stage of vertical specialization industrialization through global value chains. Following the evolutionary economics approach, the chapter takes a firm-level perspective on industrial policy theoretically and empirically. While capabilitybuilding processes are embedded within broader industry-level, national, and international processes, they take place at the firm level. Section . provides an overview of the limited progress in SSA of developing manufacturing sectors. We consider why this has been the case by exploring the role of industrial policy in supporting and compelling local firms to build their technological capabilities. Industrial policy in the targeted sectors in Nigeria, Ethiopia, Rwanda, Kenya, and South Africa is then presented. In concluding, we draw out some of the implications of these sector experiences.

. L P  S T  S-S A

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SSA countries struggle with industrialization more than other developing-country regions as a result of historical factors that have been compounded, creating path dependencies that are hard to escape. At independence these countries found themselves far behind the world technological frontier and lacked skill endowments, especially in terms of experience in manufacturing compared to other developing countries (Amsden, ). This limited manufacturing experience in most SSA countries at the

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

    

start of decolonization was an important factor shaping the poor performance of import-substitution industrialization strategies of the s and s, as firms started with very low capabilities (Kennedy, ). In addition, import-substitution industrialization strategies in SSA countries generally focused on capital investments and often failed to build the technological capabilities of local firms, regardless of the ownership structure: public, private, or public‒private joint ventures (Stewart et al., ). Despite these weaknesses, some African countries were beginning to gain international competitiveness in areas of labour-intensive manufacturing by the s (Sundaram and Von Arnim, ). However, external debt crises and fiscal deficits led SSA countries to adopt structural adjustment policies in the s and s that undermined those gains (for a review, see Whitfield, ). The limited stock of technological capabilities explains why manufacturing and agro-processing industries in SSA countries were hit so hard by structural adjustment, especially compared to other developing-country regions (Whitfield et al., ). Structural adjustment reforms removed types of state intervention that in some cases turned out to be more harmful than helpful, but the ideological position embedded in these policies of complete reliance on the market also meant that these reforms had important negative economic effects. Trade liberalization under structural adjustment programmes, which was more rapid in SSA countries than their Asian counterparts, largely wiped out low-productivity African firms because they were given no buffer or support to become competitive (Lall, ; Sundaram and Von Arnim, ). SSA countries that had more competitive industries before structural adjustment did better in certain sectors. The growth revival starting in the mid-s was driven largely by increases in international commodity prices; economic liberalization, which led to the allocation of resources to sectors in which SSA countries already had comparative advantages; new discoveries of natural resources, using foreign direct investments to extract them; and government spending fuelled by foreign aid (Arbache and Page, ; Whitfield et al., : ‒). From the mid-s, SSA growth was increasingly driven by China’s rapid industrialization, which fuelled demand for the region’s natural resources, as well as Chinese direct investments in infrastructure, primary sectors, and manufacturing sectors in SSA economies (Farooki and Kaplinsky, ). However, when growth in China slowed so did growth in SSA countries, as the international prices of the commodities they exported began to fall significantly from . The subsequent moderation of SSA growth brought into sharp focus the limited sustainability of growth and welfare improvements without underlying structural transformation. Since the s, SSA has undergone consistent declines in the share of manufacturing in GDP; output and employment have fallen, and the diversity and complexity of manufacturing sectors have declined (Page, ). Thus, the quality of growth was characterized by ‘static gains’ but ‘dynamic losses’ with respect to structural transformation (de Vries et al., ). Projected medium-term growth on the continent is insufficient to make a dent in unemployment due to population growth and economic structures that continue to depend heavily on primary commodities and the extractive sector (ADB, ).

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

       



. T P: U I P  E  L T

.................................................................................................................................. In all developing countries, locally owned firms in industries new to the country are initially often unprofitable due to their low productivity, which stems from constraints external and internal to firms. Internal constraints have to do with low technological capabilities. Technological capabilities can only be acquired through experience and purposive investment in learning (Lall, ). Firms have to undergo a period of learning in which they may well operate at a loss, and it is uncertain how long they will do so. The risk is highest for the first investors when the knowledge and infrastructure required to become competitive in new economic activities do not yet exist and have to be acquired and adapted to local conditions. For local investors, the cost and uncertainty involved in learning is too high to be worth the risk, leading to what Khan () calls a learning trap: local firms do not invest in building their capabilities because the gap between their initial capabilities and what is required to be internationally competitive is too large, leaving them stuck in low-productivity activities. This learning trap is particularly acute in SSA countries, where local firms have very low initial capabilities and limited capital, knowledge, and networks on which to draw, leading to a large capability gap. In addition, all firms (local and foreign) in new industries in SSA countries initially face constraints external to the firm that result in high market costs: high-cost and limited access to capital, land, and skilled labour; high cost and poor quality of infrastructure and transport logistics; limited access to foreign exchange or banking instruments tailored to exporting; and so on. These constraints drive up the cost of production for firms, but they are costly or impossible for individual firms to address on their own. Furthermore, they make it even harder for locally owned firms to bridge the capability gap, as it increases the costs and risk. Whether local entrepreneurs decide to invest in a new industry depends on their perception of the risk, which in turn is shaped by the size of their capability gap plus the market costs that all firms face, but also the normal profit rate in the domestic market or the global value chain in a particular function and end market when global productivity norms are achieved. Khan () refers to the normal profit rate as the size of the prize, and it is determined largely by the degree of competition (or substitutability). Local investors compare the ‘prize’ in new industries to the risk/profit ratio of other economic opportunities in the national economy. The issue in SSA countries is often not the lack of capital, but the capability gap, which leads local investors to put their capital into economic opportunities that require lower capabilities and thus have lower risks, such as the import trade, real estate, and hotels. Escaping from the learning trap requires industrial policies that reduce the risk for local firms of investing in new manufacturing activities by subsidizing the initial costs

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

    

of investment, reducing market costs, and facilitating and subsidizing the learning process. But these industrial policies are difficult to implement because they involve government agencies creating rents and ensuring that local firms use the rents to invest in learning (Whitfield et al., ; Khan, ). The norm is for local firms to engage in ‘satisficing behaviour’, and the larger the capability gap, the more likely they are to do so (Khan, ). Thus, industrial policies that are essentially learning rents have to be tied to performance targets: what Amsden () called reciprocal control mechanisms. In this context, ex post rents (conditional on the achievement of competitive success) are often more successful in developing countries than ex ante rents (those provided before performance targets are met) because they do not depend on government agencies having the technical capacity and political power to enforce them (Di Maio, ; Khan, ). However, the process of creating and managing rents as part of industrial policy can easily become entangled with the processes of rent creation and distribution linked to political stability and the survival of the ruling political elites (Khan, ). Furthermore, the capacity of a state to monitor and enforce learning rents is derived from the ruling elites who govern the state and the ruling coalition that keeps them in power. What matters is how coalitional pressures shape the political costs of certain policies and the ability to implement them, given the resistance or support from powerful groups within and outside the ruling coalition (Whitfield et al., ). Thus, domestic politics is just as important as economics in determining the success of industrial policies.

. I- I P: T C S  N  E

.................................................................................................................................. Cement is an intermediate or heavy industry with large economies of scale and capital intensity and is a core input in the construction industry. Several Asian countries used the cement industry as a springboard for industrialization and to develop technological capabilities within local firms, including professional management skills (on Korea, see Amsden, ). Cement is characterized as a low-value, high-volume product, so it is generally not traded internationally. Cement is a classic oligopoly due to high entry and exit barriers, and requires certainty of market demand. Thus, government industrial policies are necessary to help create the market demand, but also to turn an oligopolistic market to more efficient means (Oqubay : ‒). Cement production in SSA countries tends to be dominated by a small number of multinational corporations. South Africa, Nigeria, and Ethiopia are the three largest cement-producing countries in SSA, in that order, and notably their sectors contain local firms. This section compares

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       



experiences of industrial policy to promote the cement industry in Nigeria and Ethiopia.² In both countries local cement production increased in the s and domestic demand was met entirely by domestic production by  in Ethiopia and  in Nigeria (Akinyoade and Uche, ; Oqubay, ). In both cases, government interventions played a key role: directly through industrial policy and indirectly through increasing domestic demand. Local cement firms, which dominate the cement sectors in these countries, were developed through a combination of learning rents and oligopolistic rents. Cement production in both countries uses almost entirely locally sourced inputs such as minerals from quarries and packaging. Yet, domestic demand remained too small to sustain more than a handful of firms, leaving them with excess production capacity. Both Nigeria and Ethiopia had state-owned cement firms as a result of state-directed import-substitution industrial policies between the s and the s, and they had regulations on imported cement ranging from outright bans to import licensing schemes in order to conserve foreign exchange. The expansion of the cement industry in both countries was driven by just one or two local firms as ‘first movers’. However, the role of the state differed significantly, as a result of the political settlement, which had important implications for some aspects of cement industry development in each country.³ In Nigeria, the key government policies included the privatization of state-owned cement factories, which were bought by local and foreign investors, and the backward integration policy of  (Akinyoade and Uche, ). Together, they effected a shift from importing cement to domestic production. The backward integration policy banned imported bagged cement and involved a scheme for phasing out bulk cement imports by allowing investors in local cement production to continue importing bulk cement as a means to finance their investments in cement factories. New import licences linked the volume that could be imported in proportion to the demonstrated investment in local plant production capacity. Dangote, a private firm, was the only local firm initially to take advantage of this incentive, and became the first mover. In contrast, in Ethiopia the first movers were a state-owned firm and a greenfield investment by a firm linked to the TPLF, the dominant party within the EPRDF ruling coalition at the time (Oqubay, ). The backward integration policy in Nigeria also included several fiscal incentives. Firms investing in cement factories were given ‘pioneer’ status, which meant a five-year tax holiday, and paid smaller duties on equipment for mining quarries and making cement, as well as no VAT on equipment and reduced VAT on factory construction

² This section draws primarily on research by Richard Itaman and Christina Wolf () on the cement industry in Nigeria, and the research of Arkebe Oqubay () on the cement industry in Ethiopia. ³ On the concept of political settlement and its application to sub-Saharan Africa, see Whitfield et al. ().

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

    

materials not available in Nigeria. The industrial policies did not include financial incentives such as access to cheap long-term loans for investing in expensive cement factories where the return on investment is only realized over the medium to long term. Dangote was the first mover among local firms because they already held a licence to import cement through political connections and thus could use capital accumulated from oligopoly rents in the regulated import trade to purchase a state-owned cement factory in . They could also use their political connections to reduce the risk by ensuring policies necessary to the expansion of the domestic market would be put in place and enforced (Itaman and Wolf, ). As a result of these industrial policies, there were four cement-producing firms in Nigeria by , including two local and two foreign firms. Dangote controlled  per cent of the domestic cement market, its closest competitor being Lafarge (a French multinational) with  per cent. In Ethiopia, the government started promoting the cement industry in  when it opened the sector to foreign direct investment and offered a standard package of fiscal incentives including a three-year tax holiday, duty-free equipment imports, and income-tax exemption for expatriates for two years. It also facilitated access to factory land and quarries for minerals at low prices, and provided low-cost electricity (Oqubay, ). The state-owned development bank offered investment loans covering  per cent of the investment over a fifteen-year period at  per cent interest, and cement factories had preferential access to foreign currency (in the context of government capital controls). Between  and , there were only two firms manufacturing cement in Ethiopia, the state-owned firm and the party-owned firm mentioned above. However, between  and , several additional local investments were made. The larger investments included a local business group that acquired a state-owned factory and invested in upgrading and expanding it; a greenfield investment by former managers of the state-owned cement factory that became the first mover; and several factories that emerged from joint ventures between Ethiopian and Chinese firms. By , there were sixteen firms, including mini cement plants as well as medium and large ones. The mini cement plants began operating in , but they had insignificant influence in the industry due to their small market shares. The state-owned and partyowned cement factories had a de facto monopoly until , when three large cement factories became operational, shifting it to an oligopolistic market structure. Notably, local firms accounted for half of total installed capacity in Ethiopia. These industrial policies targeting the cement sector were necessary, but not sufficient, for local investments; expanding domestic market demand was key. In both countries, government spending on infrastructure projects accounted for over  per cent of the demand and up to two-thirds in Ethiopia. Thus, the government was the main buyer. In turn, government infrastructure projects depended significantly on Chinese financing and Chinese contractors. Itaman and Wolf () note that the average annual value of construction projects completed by Chinese firms in subSaharan Africa between  and  was the highest in Angola, followed by Ethiopia and then Nigeria. In Ethiopia, the government had an explicit strategy of using investments in public housing, roads, and universities as an industrial policy tool to

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

       



increase domestic construction and thus stimulate demand for the manufacturing of cement as well as other building materials such as glass and steel (Oqubay, ). The cement industries in both countries ran into domestic demand constraints as the governments reduced public investments, in the context of lower global oil prices in Nigeria and unsustainable external debt from Chinese financing in Ethiopia. In Nigeria, Dangote began exporting to the region in  as well as opening cement factories in other African countries in response to saturated domestic demand. Itaman and Wolf () calculate that Dangote Cement had profit margins of ‒ per cent during  to , due to the continued import tariffs and low tax rates, as the company continued to benefit from its pioneer status with a tax exemption on export sales. Dangote also made investments in economies of scale and scope through an explicit strategy to become the market leader and sustain high profit margins. Due to the political connections of Dangote’s owner with subsequent ruling coalitions in Nigeria, Dangote continues to pay very little tax, and as Itaman and Wolf () show, the firm has not significantly raised the wages of its workers despite productivity gains. Thus, little of the value captured in the cement industry has been redistributed to workers or to other parts of the population through government expenditure based on taxes, which would have had multiplier effects in terms of increasing domestic demand for cement. In Ethiopia, in response to the excess supply of cement, the government banned new FDI in the sector and reduced incentives for local firms. However, it has not pursued industrial policies to encourage cement exports or to stimulate domestic market demand. Oqubay () notes that local firms need to increase quality and productivity in order to be competitive in regional exports. The price of cement is lower in Ethiopia than in Nigeria and expected to fall further as more investments come on stream. There are more large firms in Ethiopia and no single firm wields as much influence over the market, and thus pricing, as Dangote does in Nigeria.

. I P  L E M: A E  E

.................................................................................................................................. The apparel export sector has been a first step for most countries in the early stages of industrialization. The globalized apparel industry became a buyer-driven GVC characterized by decentralized, globally dispersed production networks coordinated by lead firms who control higher-value activities such as design, branding, and marketing (due to higher entry barriers), but often outsource all or most of the manufacturing process to a global network of suppliers. Buyers have tended to increase the manufacturing and non-manufacturing functions they require from their suppliers. Furthermore, the asymmetric power between global buyers and an increasing number of apparel

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

    

suppliers has led to a ‘squeeze’ on supplier firms, which are facing low prices and stringent buyer requirements (Gibbon and Ponte, ). Madagascar is the number one apparel exporter in SSA, overtaking Mauritius in , followed by Lesotho, Kenya, Swaziland, and then Ethiopia, but Ethiopia is the new rising star with impressive growth rates. Apparel exports rose in Ethiopia from less than US$ million in  to US$ million in  and US$ million in . In contrast to the other SSA apparel exporters, only the Ethiopian government has pursued industrial policy targeting the apparel sector. The Ethiopian government’s apparel sector-specific industrial policies have evolved, importantly, through trial and error and can be grouped into three largely chronological waves of industrial policy (Staritz and Whitfield, ).⁴ Ethiopia had a basic national supply chain from cotton to textiles to apparel for the domestic market dominated by state-owned firms (Staritz and Whitfield, ). In the early to mid-s, the government privatized the state-owned firms and offered incentives for local firms to invest in the apparel export sector, as part of the first wave of industrial policy. These incentives included concessional credit from the stateowned Development Bank of Ethiopia, income-tax exemptions, access to land or industry sheds at concessional rates, as well as general export incentives such as duty-free imported inputs, export credit guarantees, and partial retention of foreign exchange (in a context of capital controls) as incentives for local and foreign investors in apparel exports. However, there were no performance targets attached to these incentives, and the government created general incentives to encourage investment in manufacturing whether for export or the domestic market. Thus, the incentives to export were only marginal additions to the general benefits offered to manufacturers (Gebreyesus and Demile, ). Only fifteen local investors established new apparel factories between  and . These pioneer firms struggled to export and only a few other local investors had entered the apparel export sector by . As part of a second wave of industrial policy, the government created the Textile Industry Development Institute (TIDI) to support local firms. TIDI offered free benchmarking studies that came with foreign experts providing advice on how to improve production processes and training for newly hired sewing-machine operators, and it helped to direct global buyers to local firms. Again, these industrial policy rents had very weak or no performance standards attached to them, which was also the case with the donor agency programmes that provided local firms with foreign experts, attendance at trade fairs, and grants for buying equipment through matching grant schemes.

⁴ This section draws on research carried out by Lindsay Whitfield in collaboration with Cornelia Staritz, as part of the African-owned Firms Building Capabilities in Global Value Chains (Africap) project funded by the Danish Council for Independent Research, Grant number DFF––. The research included a survey on technological capabilities carried out with all locally owned apparelexporting firms, and interviews with staff in relevant government agencies and industry associations as well as global buyers and buying agents.

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       



The local firms struggled to learn, and by , many local firms had exited the apparel sector or shifted to producing only for the domestic market, while those that continued with apparel exports were operating at a loss or just breaking even. Local firms that survived in apparel exports were part of diversified business groups, which meant that their other businesses subsidized the cost of learning and made up for low profit margins, while the export industry provided the foreign exchange required for the other businesses. In general, the local apparel firms put limited effort into building their capabilities in order to become competitive in the export market, but their decisions on how much effort to put in and the result of that effort were shaped by external factors linked to the structural country context and GVC dynamics that created disincentives for investing in learning. Local investors had limited knowledge about the apparel global value chain and what was required to be competitive. Furthermore, there was a large gap between their initial capabilities and the capabilities required to enter and remain competitive in apparel assembly: ‘cut-make-trim’ (CMT), the lowest node in the apparel GVC. Thus, the local firm owners underestimated the time, resources, and effort they would have to put into this sector. At the same time, apparel exports on a CMT basis had very low profit margins, due to the high level of global competition, which created a limited ‘prize’ for investors willing to take the risk, especially compared to production for the domestic market or other economic opportunities. Furthermore, the bargaining power of supplier firms in terms of meeting cost, quality, time, and flexibility requirements of buyers was very limited, which created a narrow ‘margin for error’ and led to loss of orders when the buyers’ terms were not fulfilled, further driving up the risk and costs. Production based on full package, where suppliers are responsible for sourcing all inputs and delivery of the product, brings higher unit prices but also requires higher merchandizing, financing, and logistics capabilities and comes with additional risks. Moreover, local firms faced challenges outside the firm that made it difficult for them to develop capabilities, which reduced their incentives to invest in learning given that these external factors would undermine the results. The external factors included costly and slow transport of imported and exported goods through the Djibouti port, limited inputs available locally, scarcity of foreign exchange in the country and high labour turnover. A high level of sticks and carrots would be required to incentivize local investments and compel local firms to invest in learning. However, the industrial policy rents for apparel exporters were not significant compared to broad investment incentives for manufacturing, which did not distinguish between exporters and non-exporters (Gebreyesus and Demile, ). The limited additional export-related rents contained in the industrial policy measures were ex ante and came with weak compulsions to invest in learning as no clear performance targets were attached to them. TIDI required that all exporting firms submit annual export plans, but staff had no authority to take action against firms that failed to meet their targets. Furthermore, TIDI staff initially had limited knowledge of the apparel export sector and thus lacked the ability to monitor local firms’ performance and understand their challenges. Research on

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi



    

industrial policy and local firms in Ethiopia’s floriculture sector comes up with similar findings (Melese, , ). Furthermore, the government’s other industrial policy measures to protect domestic apparel production had contradictory effects on promoting exports.⁵ The new apparel firms used profits from the domestic market to subsidize learning in the export sector, but the protected domestic market also undermined incentives to invest in learning. Firms that originally only exported started diversifying into the domestic market, while other firms always straddled domestic and export markets or moved from the domestic market into exports to get access to foreign exchange but remained focused on their domestic market business. Most of the local firms that were producing for the domestic market decided not to even try exporting given the higher profits and lower requirements of the domestic market. There were forty-nine local textile and apparel firms in , and only fourteen exported part or all of their production. The third wave of industrial policy involved the creation of apparel-specific industrial parks and a more targeted promotion of foreign direct investment involving linkages with global buyers who in turn encouraged their first-tier suppliers to invest in Ethiopia. The industrial parks were crucial for attracting these first-tier foreign apparel firms, as they made investing in a ‘greenfield’ apparel supplier country easier. Attracting big foreign apparel firms was pursued as a way to quickly increase exports and employment, but also as a means for local firms to leverage access to global markets, technology, and skills. Thus, the government reserved some units in the industrial parks for local firms, which were to receive access to investment loans from state-owned banks, subsidies for worker training and hiring expatriate managers, and support linking to buyers. However, by mid-, there were only three local investors with premises in Hawassa Industrial Park, the first park to be completed— two apparel firms and one input supplier—but they had not yet started exporting apparel by mid-. This industrial policy approach to developing an apparel export sector and supporting local firms may turn out differently, because the industrial parks provide internationally compliant factory premises and close proximity to internationally competitive foreign firms. Furthermore, industrial policy around the parks was implemented by the Ethiopian Investment Commission, where government officials have a greater understanding of the apparel export sector and greater enforcement capabilities. Local firms that invest in the parks also face more compulsion to invest in learning than was the case under the previous waves of industrial policy, as they must export  per cent of their production. However, the outcome depends on how many local firms invest in the parks as well as the implementation of policy measures intended to provide more direct support to local firms, not only by subsidizing the cost of foreign experts and training workers, but also supporting linkages with global buyers and foreign firms. ⁵ The domestic market for textiles and apparel was still protected with a tariff rate of  per cent and an additional  per cent surcharge and  per cent excise taxes, as well as a ban on second-hand clothing imports.

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

       



The Ethiopia apparel export case shows that a core focus of industrial policy to support local firms in new export sectors has to be supporting and compelling them to invest in learning. This must include measures that subsidize the learning costs, especially given the ‘small’ prize but high level of efficiency and capabilities required to enter the lowest node of global value chains (where competition is highest). This kind of industrial policy to support learning is also very difficult, because it requires technical knowledge to support learning, coupled with the political ability to compel it with reciprocal control mechanisms. TIDI had neither the technical knowledge nor the political authority, and it remains to be seen how the Ethiopia Investment Commission will support more local firms in the industrial parks and their learning process. Nevertheless, the Ethiopian government has demonstrated learning in the evolution of its industrial policy targeting the apparel export sector, and it is the only SSA government to pursue industrial policies to support manufactured exports that go beyond creating general export-processing zones with their standard package of fiscal and financial incentives (see Whitfield and Staritz, ).

. L M? K- S  K  R

.................................................................................................................................. The governments of Kenya and Rwanda pursued development strategies in the s that emphasized ‘knowledge-based services’ as the key economic driver, with a relative de-emphasis on manufacturing. In Rwanda, this included its Vision , adopted in , which highlighted finance, ICT, and tourism as priority sectors to drive growth (Government of Rwanda, ). In Kenya, the government’s efforts have been more targeted, singling out the business-process outsourcing (BPO) sector in its Vision  as the key service sector targeted to drive growth. This sector was expected to be export oriented, generating jobs for young professionals, and driven by investments from Kenyan firms (Mann and Graham, ). This section assesses the experiences of Kenya and Rwanda with promoting services, especially export-oriented services and services like tourism that generate foreign exchange, rather than manufacturing. Rwanda staged a substantial economic recovery after the  genocide with GDP growth averaging . per cent between  and , driven chiefly by a combination of public investment, agricultural productivity upgrading, and promotion of tourism (Ggombe and Newfarmer, ). Rwanda made substantial gains through its industrial policy for the tourism sector, which involved public investment in the national airline and airport infrastructure, international marketing, skills development, and investment incentives (UNECA, ). Tourism became the largest contributor to foreign exchange earnings ( per cent) in  (Ggombe and Newfarmer, ). It is also a

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

    

significant employer, accounting for . per cent of total employment in  (UNECA, ). However, the tourism sector remains heavily dependent on a specific segment of the market which can only be expanded to a limited extent: visits to view its rare mountain gorillas (Government of Rwanda, ). Thus, the government also promoted the meetings, incentives, conferences, and events (MICE) sector as part of its tourism strategy, aiming to attract business tourism to conferences and events. The centrepiece of state support was the construction of the Kigali Convention Centre and concurrent investments in hotels in and outside the capital, complemented by the expansion of state-owned Rwandair’s fleet of aircraft (Behuria and Goodfellow, ). As part of efforts to foster knowledge-based services, the government also targeted the finance, insurance, and real estate (FIRE) sector. The main policy measures to promote investments in this sector included financial liberalization aimed at fostering the entry of foreign banks and selling shares in struggling state-owned commercial banks. The number of commercial banks increased significantly, directing a large proportion of investment finance towards the construction sector. While this partly reflects the building of hotels linked to the tradable tourism and MICE sectors, it also includes construction of high-end real estate for relatively affluent domestic purchasers. The government also invested directly, with other groups, in large real-estate projects. Private and public investments in the MICE and FIRE sectors have focused on high-end, luxury international markets, but there was evidence of an oversupply in the high-end market and a chronic housing shortage for the mass market (Behuria and Goodfellow, ). Lastly, the Rwandan government also promoted the information communication and technology (ICT) sector through investment in G fibre-optic and mobile broadband infrastructure and the extension of ‘e-government’ services (Government of Rwanda, ). Substantial increases in Internet penetration were recorded, with mobile broadband access at  per cent by , as well as the digitization of a number of government services and other innovative ways to render public services, such as the Zipline programme using drones to deliver medical supplies (World Bank, ). In particular, the government attempted to promote the BPO sector with two broad policies (Mann et al., : ‒). The first was to encourage local investors in the sector through public investment in training. The government established the Kigali Institute of Science and Technology, sent students abroad for training in advanced engineering, and convinced Carnegie Mellon University to open a graduate degree programme in Kigali. It also financed a technology innovation hub with the goal of encouraging tech start-ups. The second policy was to attract large multinational firms to set up regional headquarters in the country and help upgrade the country’s infrastructure, and it was hoped that Rwandan workers and businesses would benefit through knowledge transfer. However, Mann and colleagues found Rwanda’s BPO sector to be at an incipient stage in . There was a limited amount of business-process outsourcing for international markets; rather, firms focused on domestic and regional markets, and local firms were usually part of a regional network of companies with headquarters in Nairobi. In fact, many Rwandan-based financial companies and call-centre and

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

       



customer-service firms were headed by Kenyan nationals. The only firms that were able to attract international BPO work had personal and family connections abroad that allowed them to compete for foreign clients (Mann et al., : ). In short, socioeconomic connections were necessary for local firms to access international BPO markets. This point is taken up below when discussing Kenya’s experience with promoting the BPO sector. Notwithstanding significant progress, a number of limitations are apparent in Rwanda’s attempt to leapfrog the industrialization stage straight into modern services. The finance, insurance, and real-estate as well as ICT service sectors are largely skill intensive and have not been able to generate large-scale employment (Behuria, ; Behuria and Goodfellow, ). The BPO sector has more potential to generate semiskilled jobs, but it has not expanded as rapidly as envisioned. Thus, claims by Ggombe and Newfarmer (: ) that this services-led strategy has ‘inverted the normal sequence of structural change’ appear exaggerated and ignore fundamental weaknesses. For instance, these scholars include government services, accounting for  per cent of exports in , in their calculations to bolster the claim that Rwanda ‘is rapidly becoming a services-exporting economy’. However, the growth in government services predominantly reflects the government’s peace-keeping activities in the East Africa region. Financial and ICT services each only contributed  per cent to export revenues in  (Ggombe and Newfarmer, : ). Furthermore, promoting non-tradable real-estate construction is likely to exacerbate the balance-of-payments constraint to growth, rather than reduce it. Indeed, balance-of-payments constraints and the need to generate broader sources of employment prompted the government to change course by the late s and place greater policy emphasis on manufacturing (Behuria, ). As Mann and colleagues (: ) note, ‘Kenya is widely considered to be an East African success story in the realm of ICTs because of its status as a Pan-African “ICT Hub”.’ However, as these researchers show, the government’s efforts to promote international inflows of BPO work—equivalent to service exports—have been less successful, with most firms focusing on the domestic and regional markets. The government’s main policy measures included public investment in fibre-optic Internet cables alongside private investments, which were completed in , together with the creation of a government agency to promote the sector and a proactive marketing campaign highlighting Kenya as a place for BPO work and encouraging foreign firms to invest in Kenya’s BPO sector. While the cables were under construction, the government also subsidized the cost of satellite bandwidth for BPO firms, as the cost was much higher than in existing BPO countries such as India and the Philippines. However, both the government and locally owned BPO firms, which set up in response to the government’s policies, underestimated the difficulty of entering and becoming competitive in the BPO global value chain (Mann and Graham, ). In contrast to international discourses about ICT as a flat or ‘disintermediated’ economy that made it easier for developing-country firms to enter, Kenyan-owned BPO firms discovered that the BPO global value chain was an ‘extremely personal, socially connected economy’ (Mann and Graham, : ). Kenyan firms did not have the tacit knowledge, social

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

    

networks, or trust to secure direct connections to foreign clients, nor did they have the economies of scale and ability to correctly value and price BPO work. A few large firms hired foreign experts to advise them on how to structure their operations and to train their workers, but smaller firms could not do this and thus failed to meet deadlines and to make profits. In general, the latter had to depend on sub-contracted work from BPO firms in India or elsewhere that secured large contracts directly from foreign clients in the United States and then gave Kenyan firms small parts of it, but usually the least valuable parts. Research on small local firms in South Africa comes to the same conclusions, showing that these local firms were dependent on sub-contracting as they did not have the reputation to find work directly from international clients, and thus the BPO sector was largely oriented towards the domestic market (Anwar and Graham, ).

. C E-  I- P: A  A  S A

.................................................................................................................................. Apartheid industrial policies bequeathed South Africa an industrial structure built around a mineral-energy-complex (MEC) dependent on mining and heavy industry exports, within a highly concentrated conglomerate structure that failed to develop a more diversified manufacturing base (Fine and Rustomjee, ; Freund ). In the post-apartheid period, trade liberalization and other orthodox economic policies facilitated corporate restructuring that prompted rapid de-industrialization, with the share of manufacturing in GDP falling from  per cent in  to  per cent in  (World Bank, n.d.). Over this period there were only limited pockets of industrial policy interventions. This section evaluates the record of industrial policy in the only two sectors outside heavy industry that have benefited from sector-specific industrial policies: automobiles and clothing/textiles. It also briefly assesses government efforts since  to mobilize a more coherent overarching industrial policy, as well as constraints on its implementation. Emerging from the apartheid period, the automobile sector was focused on the domestic market and was characterized by a proliferation of the range of vehicles produced, with limited economies of scale. In , the Motor Industry Development Programme aimed to consolidate the industry to produce a narrower range of vehicles at considerably greater scale and focused on supplying the export market, led by foreign firms that were already transnational producers in the automobile global value chain as original equipment manufacturers (OEMs). OEMs are the global system integrators that control the design, assembly, and marketing channels of relatively

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

       



sophisticated multi-component manufactures such as vehicles. Within a framework of declining tariffs, the Programme allowed OEMs and component suppliers to earn import rebate credit certificates when they exported vehicles and components. OEMs could use these import rebate credit certificates to import vehicles that they did not produce in South Africa or components for their own production, or to sell on the certificates. As tariffs on both vehicles and components were lowered, more exports were required to secure a given value of import rebate credit certificates. This system acted as an effective reciprocal control mechanism to compel assemblers to double production to around , vehicles per year and to raise the share of vehicles exported from under  per cent in  to over  per cent since  (Barnes and Black, ). Through the Programme, automobiles became the leading manufacturing export outside heavy industry, contributing  per cent of total exports in  (Bell et al., ). However, the benefits of the programme relative to its costs have been contested (e.g. Flatters, ), and some weaknesses are apparent. Chief among the weaknesses are the relatively low local content at  per cent, large-scale imports of components and a correspondingly large trade deficit in vehicles and components, little employment growth, and limited participation by black-owned component suppliers, even at the second- and third-tier levels (Barnes et al., ). In , the Automotive Production and Development Programme (APDP) replaced the Motor Industry Development Programme, with the objective of addressing these weaknesses, particularly by raising volumes and local content. Rather than being entirely reliant on import credits (which fuelled the trade deficit), the new programme supported fixed investment by OEMs and component suppliers through an on-budget grant, while import rebate credit certificates were earned for production rather than exports. While production volumes have increased since the introduction of the APDP, local content has remained at approximately  per cent, with limited development of second- and third-tier component suppliers, particularly black-owned component suppliers. The limited gains under the APDP reflect in large part the dominance of transnational OEMs in securing a programme design even more financially favourable to them, relative to component suppliers. OEM bargaining power was bolstered by the fact that the APDP was concluded just as the shockwaves of the global financial crisis caused a slump in automobile demand, with US OEMs in particular financial distress. Limited employment growth and perceived lack of progress by the automobile industry in promoting black economic empowerment since the introduction of the APDP has also tempered political support for the industry. The government’s Automotive Masterplan  seeks to address these weaknesses, inter alia by increasing local content to  per cent, doubling employment, and developing black-owned tier-two and tier-three component suppliers. This involves amendments to the APDP that raise direct levels of support for domestic component manufacturing and shift support for assembly from sales to local value addition (Barnes et al., ; NAACAM, ). The clothing and textile sector provides an example of the switch from an inappropriately designed industrial policy to a considerably more effective one. Thus, this

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

    

sector reflects a case of industrial policy learning, where a programme that was unable to stem a large-scale flood of clothing imports and associated job losses was replaced by a more effective one, albeit after a long time lag. The South African clothing and textile industry in the early s was characterized by production almost exclusively for the domestic market behind significant tariffs. The thinking behind the immediate postapartheid economic strategy was that rapid trade liberalization was all that was required to compel manufacturers producing for the domestic market to raise their competitiveness to compete internationally. The  Duty Credit Certificate Scheme was meant to provide a boost to exporting firms, along similar lines to the MIDP. Exporting apparel firms could earn Duty Credit Certificates (DCCs) that they could then sell, typically to retailers who used them to lower the costs of their clothing imports. However, the scheme led to about  per cent of apparel firms exporting, which also fuelled imports as domestic retailers used DCCs to realize even lower effective tariffs than the applied rate. Furthermore, the applied tariff of  per cent on clothing was dramatically undercut by widespread under-invoicing and customs misdeclaration (NEDLAC, ). An additional weakness was that the industrial policy for the clothing and textile sector, which consisted almost entirely of the DCC policy instrument, did not take into consideration the looming expiry in  of the WTO Agreement on Textiles and Clothing which imposed quotas on developing-country exports to industrialized economies. Upon its expiry and China’s entry into the World Trade Organization, Chinese exports of clothing and textile products surged to  per cent of world trade and rapidly became the largest source of imported clothing in South Africa. Thus, the Duty Credit Certificate Scheme ultimately failed. It contributed to the flood of imports and associated job losses, while doing little to support sustainable exports. It effectively operated as a substantial subsidy to the small group of exporters that were largely unable to compete without it. When the Duty Credit Certificate Scheme expired in , it was replaced with an on-budget support programme called the Clothing Textiles Competitiveness Programme (CTCP), similar to the automobile sector. This programme allowed manufacturers to earn a value-added-based production incentive in the form of credits that could be redeemed only through investments in specific competitiveness and upgrading activities. A number of retailers supported the programme and sought to help revive their domestic supply base, motivated both by more competitive and responsive domestic manufacturers and rising Chinese wages. The Programme has broadly stabilized employment in the sector, while supporting the highest levels of labourproductivity growth within the overall manufacturing sector in South Africa. The government’s clothing and textile industrial policies have been contested by academics. A major theme is that tariff reductions should have been accompanied by labour-market deregulation to allow wages to fall (Kaplan, ; Nattrass, ). However, these arguments fail to engage with important empirical realities as well as political economy impediments to a labour-deregulation path. First, as measured by the World Bank, South Africa has an intermediate level of labour-market flexibility

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi

       



relative to peer middle-income economies, which cannot fully account for massive job losses in clothing and South Africa’s overall extreme unemployment levels (DTI, ; Zalk, ). Second, these arguments do not engage with the political feasibility of labour-market deregulation in the context of the strong alliance between the ANC government and COSATU, the largest trade union federation. It was only after South Africa had experienced profound de-industrialization that the National Industrial Policy Framework (NIPF) was adopted in , followed by associated annual Industrial Policy Action Plans (IPAPs) setting out strategies for other sectors as well as overhauling the automobile and clothing and textile strategies, as described above. However, notwithstanding formal adoption of the NIPF, industrial policy has been undermined in practice by a number of factors (DTI, ; Zalk, , ). Large private business groups have focused on sectors in which they have been able to achieve high levels of profitability, predominantly in non-tradable service sectors and capital-intensive tradable sectors over which market dominance could be asserted, but with limited economy-wide linkages and scope for structural transformation. With high financial returns available in these sectors, capital has not flowed to diversified manufacturing industries that are subject to higher levels of competition from imports due to trade liberalization. The misalignment of macroeconomic policy with structural transformation, including pervasive currency overvaluation and falling real budget allocations for industrial financing, undermines efforts to promote manufactured exports and creates further disincentives for firms to invest in manufacturing. Increasing patronage and corruption since , itself arguably a consequence of the failure to develop a more productive and employment-generating economy, has further undermined conditions for investment in diversified manufacturing. Large-scale corruption at strategic state-owned enterprises Eskom and Transnet has fundamentally undermined their formal mandate to provide reliable and cost-effective electricity, and rail and ports services.

. C

.................................................................................................................................. While we agree to some extent with Milberg and colleagues () on the need for vertical specialization and industrial policies tailored towards global value chains, they underestimate the challenges for local firms in SSA countries to enter even the lowest function in global value chains, as the cases of apparel exports in Ethiopia and business-process outsourcing in Kenya and Rwanda show. SSA countries need industrial policies targeting local firms to help them build their capabilities even at the lower end of value chain activities. Such industrial policies involve not only creating and monitoring learning rents, but also bringing foreign knowledge into the country through various means such as foreign direct investment, joint ventures between foreign and local firms, or other schemes through which local firms can access foreign tacit knowledge.

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

    

The case of the cement industry in Nigeria and Ethiopia illustrates that the constraint of domestic demand is real, and as a result, domestic markets tend towards oligopolistic structures, even more so in capital-intensive sectors where there are higher barriers to entry and large first-mover advantages. Yet Nigeria and Ethiopia are some of the most populous and thus largest economies in sub-Saharan Africa. Without expanding purchasing power through manufactured exports (which are minimal in Nigeria) or redistribution of wealth, domestic markets cannot support competitive intermediate and heavy industries that do not export. Thus, domestic market and export-oriented manufacturing that depends on sources of demand external to national economies have to go hand in hand. The cases of business-process outsourcing in Kenya and Rwanda show that global value chains in knowledge-based services operate just as manufacturing global value chains do. Entering requires much more than just low wages to become profitable. In particular, it requires tacit knowledge that can only be acquired outside the country from people who have experience working in the global industry, and it requires contact and trust to be established with clients across distance, which is not easy. Sub-contracting can be an easier way to enter export markets, but it comes with very low prices and thus firms cannot stay in that node of the global value chain for very long. Furthermore, as Kenyan firms and the government came to realize, the poor performance of some local firms can affect the overall image and reputation of the country as a supplier country. As a result, local BPO firms in Kenya realized that they needed to build up knowledge and experience by supplying the domestic and regional markets first, before trying again in the global value chain (Mann and Graham, ). The government then shifted its policy to focus on promoting higher-value IT-enabled services for the domestic market, and on attracting big multinational firms in order to build Kenya’s reputation in the eyes of foreign clients. Mann and Graham (: ) conclude that the synergy between the BPO sector and local software developers could allow Kenya to develop a longer-term potential for higher-value BPO. This strategy resembles what Coe and Yeung () discuss as coupling, de-coupling, and recoupling with global value chains in order to build capabilities but also eventually capture great value from participation in global value chains. Thus, export-oriented and domestic market strategies have to be combined. Industrial policies in the South African automotive and apparel sectors have achieved some successes in raising firm capabilities, albeit with limitations. However, a confluence of economy-wide factors has prevented the reversal of de-industrialization. Macroeconomic and financial-sector policies have hindered rather than supported structural transformation and industrial policy. Large private business groups have restructured and shifted capital to sectors over which they can exert market dominance, particularly non-tradable service sectors, allowing for high profitability with limited commitment of fixed investment, particularly in diversified manufacturing sectors. Low fixed investment coupled with high unemployment and inequality has contributed to conditions for patronage networks and corruption to flourish, further impeding the accumulation of productive capabilities.

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       



This analysis implies that SSA countries need to draw upon a wide range of industrial policy instruments. These include mobilizing investment in traditional and modern infrastructure; deepening intermediate inputs including cement, metals, and chemicals; exploring ways to stimulate domestic demand through government expenditure; forging stronger linkages between agriculture and manufacturing; promoting a range of industries that can concurrently generate sustained domestic demand and relieve the balance-of-payments constraint through exports.

R African Development Bank Group (ADB) () African Economic Outlook . Abidjan. Akinyoade, Akinyinka and Chibuike Uche () ‘Development Built on Crony Capitalism? The Case of Dangote Cement’, Business History (): –. Amsden, Alice () Asia’s Next Giant: South Korea and Late Industrialization. Oxford: Oxford University Press. Amsden, Alice () The Rise of ‘the Rest’: Challenges to the West from Late Industrializing Economies. Oxford: Oxford University Press. Amsden, Alice () ‘The Wild Ones: Industrial Policies in the Developing World’, in Narcis Serra and Joseph E. Stiglitz (eds) The Washington Consensus Reconsidered: Towards a New Global Governance. Oxford: Oxford University Press, pp. –. Anwar, Mohammad Amir and Mark Graham () ‘Does Economic Upgrading Lead to Social Upgrading in Contact Centers? Evidence from South Africa’, African Geographical Review (): –. Arbache, Jorge Saba and John Page () ‘How Fragile is Africa’s Recent Growth?’, Journal of African Economies (): –. Barnes, Justin and Anthony Black () ‘The Motor Industry Development Programme –: What Have We Learned?’, in International Conference on Manufacturing-led Growth for Employment and Equality, pp. –. Barnes, Justin, Anthony Black, Douglas Comrie, and Tamryn Hartogh () ‘Geared for Growth: South Africa’s Automotive Industry Masterplan to ’. Available at https:// www.thedti.gov.za/news/SA_Auto_Masterplan.pdf. Behuria, Pritish () ‘The Domestic Political Economy of Upgrading in Global Value Chains: How Politics Shapes Pathways for Upgrading in Rwanda’s Coffee Sector’, Review of International Political Economy (): –. Behuria, Pritish and Tom Goodfellow () ‘Leapfrogging Manufacturing? Rwanda’s Attempt to Build a Services-led “Developmental State”’, The European Journal of Development Research (): –. Bell, Jason, Sumayya Goga, Pamela Mondliwa, and Simon Roberts () ‘Structural Transformation in South Africa: Moving towards a Smart, Open Economy for All’. Available at https://static.squarespace.com/static/ebaefbce/t/bed ffff//CCRED+Working+Paper+__Structural+Transform ation_BellGogaMondliwaRoberts.pdf. Coe, Neil and Henry Wai-chung Yeung () Global Production Networks: Theorizing Economic Development in an Interconnected World. Oxford: Oxford University Press.

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

    

Di Maio, Michele () ‘Industrial Policies in Developing Countries: History and Perspectives’, in Mario Cimoli, Giovanni Dosi, and Joseph E. Stiglitz (eds) Industrial Policy and Development: The Political Economy of Capabilities Accumulation. Oxford: Oxford University Press, pp. –. DTI () ‘Concept Note: Placing Structural Transformation at the Centre of Economic Revival under the New Dawn’, Department of Trade and Industry. Available at https:// gallery.mailchimp.com/dedabac/files/faead-be-b-d-fcb ded/Concept_Note_Structural_Transformation_under_the_New_Dawn_DraftV.pdf. Farooki, Masuma and Raphael Kaplinsky () The Impact of China on Global Commodity Prices: The Global Reshaping of the Resource Sector. London: Routledge. Fine, Ben and Zavareh Rustomjee () The Political Economy of South Africa: From Minerals-energy Complex to Industrialisation. London: C. Hurst & Co. Flatters, Frank () ‘The Economics of MIDP and the South African Motor Industry’. Presented at the TIPS/NEDLAC South Africa Trade and Poverty Programme (SATPP) Policy Dialogue Workshop, November . Johannesburg: Queens University, Canada. Freund, Bill () Twentieth-century South Africa: A Developmental History. Cambridge: Cambridge University Press. Gebreyesus, Mulu and Ashagrie Demile () ‘Why Export Promotion Efforts Failed to Deliver? Assessment of the Export Incentives and their Implementation in Ethiopia’. EDRI Working Paper No. . Addis Ababa: Ethiopian Development Research Institute. Gereffi, Gary () ‘Global Value Chains in a Post-Washington Consensus World’, Review of International Political Economy (): –. Ggombe, Kasim Munyegera and Richard S. Newfarmer () ‘Rwanda: From Devastation to Services-first Transformation’, in Richard S. Newfarmer, John Page, and Finn Tarp (eds) Industries without Smokestacks: Industrialization in Africa Reconsidered. Oxford: Oxford University Press, pp. –. Gibbon, Peter and Stefano Ponte () Trading Down: Africa, Value Chains and the Global Economy. Philadelphia, PA: Temple Press University. Government of Rwanda () Rwanda: Vision . Kigali: Ministry of Finance and Economic Planning. Government of Rwanda () Rwanda National Export Strategy. Kigali: Ministry of Trade and Industry. Itaman, Richard and Christina Wolf () ‘Industrial Policy and Monopoly Capitalism in Nigeria: Lessons from the Dangote Business Conglomerate’. CAE Working Paper No. :. Roskilde University, Denmark: CAE. Available at http://www.ruc.dk/cae. Kaplan, David () ‘The Structure and Performance of Manufacturing in South Africa’, in Wim Naudé, Adam Szirmai, and Nobuya Haraguchi (eds) Structural Change and Industrial Development in the BRICS. Oxford: Oxford University Press, pp. –. Kaplinsky, Raphael () Globalization, Poverty and Inequality: Between a Rock and a Hard Place. Cambridge: Polity Press. Kennedy, Paul () African Capitalism: The Struggle for Ascendency. Cambridge: Cambridge University Press. Khan, Mushtaq () ‘Learning, Technology Acquisition and Governance Challenges in Developing Countries’. Available at mercury.soas.ac.uk/users/mk. Khan, Mushtaq () ‘Political Settlements and the Design of Technology Policy’, in Joseph E. Stiglitz, Justin Yifu Lin, and Ebrahim Patel (eds) The Industrial Policy Revolution II: Africa in the Twenty-first Century. Basingstoke: Palgrave Macmillan, pp. –.

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       



Khan, Mushtaq () ‘Knowledge, Skills and Organizational Capabilities for Structural Transformation’, Structural Change and Economic Dynamics : –. Lall, Sanjaya () ‘Technological Capabilities and Industrialization’, World Development (): –. Lall, Sanjaya () ‘Structural Adjustment and African Industry’, World Development (): –. Mann, Laura and Mark Graham () ‘The Domestic Turn: Business-process Outsourcing and the Growing Automation of Kenyan Organisations’, Journal of Development Studies (): –. Mann, Laura, Mark Graham, and Nicolas Friederici () ‘The Internet and Businessprocess Outsourcing in East Africa: Value Chains and Networks of Connectivity-based Enterprises in Kenya and Rwanda’. Report of the Oxford Internet Institute. Available at http://www.oii.ox.ac.uk. Melese, Ayelech Tiruwha () ‘Ethiopian-owned Firms in the Floriculture Global Value Chain: With What Capabilities?’, CAE Working Paper No. : . Roskilde University, Denmark: Center of African Economies. Melese, Ayelech Tiruwha () ‘African-owned Firms and Investment in Learning: Local Firms in the Ethiopian Floriculture Export Sector’. PhD thesis, Department of Social Sciences and Business, Roskilde University, Denmark. Milberg, William, Xiao Jiang, and Gary Gereffi () ‘Industrial Policy in the Era of Vertically Specialized Industrialization’, in Irmgard Nubler, José Manuel SalazarXirinachs, and Richard Kozul-Wright (eds) Transforming Economies: Making Industrial Policy Work for Growth, Jobs and Development. Geneva: International Labour Office, pp. –. NAACAM () ‘Business Guide’. National Association of Automotive Component & Allied Manufacturers. Available at https://www.naacam.co.za/assets/content/page.pdf. Nattrass, Nicoli () ‘A South African Variety of Capitalism?’, New Political Economy (): –. NEDLAC () ‘Report on Customs Fraud in Respect of Textile, Clothing and Footwear’. Trade and Industry Chamber. Available at http://nedlac.org.za/wp-content/uploads/// NEDLAC-REPORT-ON-CUSTOMS-FRAUD-IN-RESPECT-OF-TEXTILE-CLOTHINGAND-FOOTWEAR.pdf. Newfarmer, Richard S., John Page, and Finn Tarp (eds) () Industries without Smokestacks: Industrialization in Africa Reconsidered. Oxford: Oxford University Press. Oqubay, Arkebe () Made in Africa: Industrial Policy in Ethiopia. Oxford: Oxford University Press. Page, John () ‘Can Africa Industrialize?’, Journal of African Economies (Supplement ): ii–. Reinert, Erik S. () How Rich Countries Got Rich . . . and Why Poor Countries Stay Poor. London: Constable. Schwartz, Herman Mark () States versus Markets: Understanding the Global Economy. rd edition. London: Palgrave Macmillan. Startiz, Cornelia and Lindsay Whitfield () ‘Made in Ethiopia: The Emergence and Evolution of the Ethiopian Apparel Export Sector’. CAE Working Paper No. :. Centre of African Economies, Roskilde University, Denmark. Available at http://www.ruc.dk/cae. Staritz, Cornelia and Lindsay Whitfield () ‘Light Manufacturing in Ethiopia: The Case of the Apparel Export Industry’, in Fantu Cheru, Christopher Cramer, and Arkebe Oqubay

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    

(eds) The Oxford Handbook of the Ethiopian Economy. Oxford: Oxford University Press, pp. –. Stewart, Francis, Sanjaya Lall, and Samuel Wangwe (eds) () Alternative Development Strategies in Sub-Saharan Africa. London: Macmillan. Sundaram, Jomo and Rudiger Von Arnim () ‘Economic Liberalization and Constraints to Development in Sub-Saharan Africa’. Working Paper No. . UN, Department of Economics and Social Affairs. UNECA (United Nations Economic Commission for Africa) () Transformative Industrial Policy for Africa. Addis Ababa: Economic Commission for Africa. de Vries, Gaaitzen, Marcel Timmer, and Klaas de Vries () ‘Structural Transformation in Africa: Static Gains, Dynamic Losses’, The Journal of Development Studies (): –. Whitfield, Lindsay () ‘An Introduction to the Political Economy of Development’, in Nic Cheeseman, Lindsay Whitfield, and Carl Death (eds) The African Affairs Reader: Key Texts in Politics, Development, and International Relations. Oxford: Oxford University Press, pp. –. Whitfield, Lindsay () Economies after Colonialism: Ghana and the Struggle for Power. Cambridge: Cambridge University Press. Whitfield, Lindsay and Cornelia Staritz () ‘Industrial Hubs and Technology Transfer in Africa’s Apparel Export Sector’, in Arkebe Oqubay and Justin Yifu Lin (eds) The Oxford Handbook of Industrial Hubs and Economic Development. Oxford: Oxford University Press. Whitfield, Lindsay, Ole Therkildsen, Lars Buur, and Anne Mette Kjær () The Politics of African Industrial Policy: A Comparative Perspective. Cambridge: Cambridge University Press. World Bank () Future Drivers of Growth in Rwanda: Innovation, Integration, Agglomeration, and Competition. Washington, DC: World Bank Group. World Bank (n.d.) World Development Indicators. Washington, DC: World Bank. Zalk, Nimrod () ‘Industrial Policy in a Harsh Climate: The Case of South Africa’, in José M. Salazar-Xirinachs, Irmgard Nübler, and Richard Kozul-Wright (eds) Transforming Economies: Making Industrial Policy Work for Growth, Jobs and Development. Geneva: ILO, pp. –. Zalk, Nimrod () ‘The Things We Lost in the Fire: The Political Economy of Postapartheid Restructuring of the South African Steel and Engineering Sectors’, PhD thesis, University of London, School of Oriental and African Studies.

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        ......................................................................................................................

                        ,     ‒    

......................................................................................................................

    

. I

.................................................................................................................................. A countries have enjoyed relatively high rates of GDP growth over the last two decades, largely as a result of the commodity booms that have been driven by the rapid industrial growth of China and other Asian countries. However, this has not resulted in the structural transformation of African economies, that is, a transition from low- to high-productivity activities, most rapidly achieved by the growth of manufacturing industry, but rather the opposite (McMillan and Rodrik, ; Weiss and Jalilian, ). In Africa, industrial policy (IP), a deliberate attempt by governments to promote manufacturing industries through specific economic and financial policies, began to a limited extent under colonial rule, continued through the early years of independence, and was effectively abandoned under structural adjustment. It is now back in favour as the central role of the state in past industrializations has been increasingly acknowledged (Chang, ; Rodrik, ; UNECA, ; Weiss, ) and seen for Africa as ‘a necessary economic tool . . . to correct major sectoral and other misallocations’ (Stiglitz et al., ). This chapter examines IP in post-independence Africa through the lens of power relations and the state, traditionally the focus of political economy. We find the origins of IP in Africa lying in the colonial period and analyse policy before and after independence, focusing on changes in the strategies adopted and the reasons why.

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

    

We examine the main IP of import substitution, a strategy begun under colonial rule and intensified after independence and explain why it did not result in deeper industrialization. We then discuss IP, or its absence, during the phase of economic liberalization, following that with a discussion of current ideas together with some case examples of the return of IP in practice as a consequence of the failure of liberalization to deliver the transformation that it promised. Although we acknowledge the various organizational and technical explanations usually given for the failure of industrial transformation in Africa, our focus, unlike much of the literature in this area, is on issues of the character of state power, class relations, and the role of global capital and international financial institutions in determining the trajectory of African industrial policy and industrialization.

. C I P: T B  I- I

.................................................................................................................................. Colonial economic policy was geared to ensuring that supplies of agricultural and mineral primary products were secured for processing and consumption in the imperial countries while the colonies provided markets for the metropolis’s manufactures (Rodney, ; Chitonge, ). The protection of the imperial powers’ manufacturing industry by not engaging in such production in the colonies was the accompanying arm of economic policy—‘the metropolitan and colonial economies were complementary not competitive’ (Havinden and Meredeth, : ). There is, however, some debate about the degree to which manufacturing in Africa was already established at independence. Although it is usual to think of colonial regimes not having an IP, the literature on the subject suggests that by the s they began to turn attention to diversifying economic activity through industrialization (Butler, ). Whether this change of direction was the result of realizing that the colonies would eventually become independent, or whether it was to use such diversification to keep the populations content with colonial rule is debatable. Yet in spite of this apparent change in policy, the main strategy, even by the latter part of the decade, remained to restore colonial infrastructure neglected during the Second World War by securing imports of such critical products as cement and steel, such infrastructure being the result of initial colonial investment policy to facilitate the exports of primary products (Butler, ). In the case of the French colonies, however, the shortages they endured during the Second World War stimulated African manufacturing activity which by the end of the war was sufficiently well established to withstand competition from French-based companies and was also helped by French government policy of supporting industrialization in the colonies (Thompson and Adloff, ).

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       



The British vehicle for developing industrial activity was the UK government’s Colonial Development Corporation (CDC), deemed to be more locally acceptable than private companies such as the United Africa Company (UAC). However, by this time (around ) the government view had changed from one supporting diversification through industrialization to one arguing for specialization in agricultural exports. As a result, the investment by the CDC was directed to increasing colonial exports to US-dollar-earning destinations and producing primary products that could go to the United Kingdom; both measures aimed to ease the United Kingdom’s chronic balance-of-payments deficits (Butler, ). The settler regimes of South Africa and Southern Rhodesia were exceptions and established significant manufacturing capabilities. There was a strong European constituency in favour of industrialization, especially in South Africa whose main IP was to protect domestic manufacturing through tariffs and to subsidize electricity and steel production. The strength of the mining industry meant that export revenues enabled the import of goods not produced domestically while also building up the necessary infrastructure for manufacturing to flourish (Fine and Rustomjee, ). In Southern Rhodesia, the government started intervening in the economy in , nationalizing iron and steel production, and taking steps to establish a textile industry. IP was based less on protective tariffs and more on subsidizing losses, partly the result of poor management skills and a greater interest among white Rhodesians in trade and property (Kilby, ). Other parts of Africa where there were significant but not large settler populations also developed some manufacturing: Senegal, the Belgian Congo, and Kenya, aided to some extent by subsidies in the case of Senegal. Angola and Mozambique, Portuguese colonies until the early s, developed some manufacturing capacity, especially in the later years, although in the case of Mozambique, this was hampered by the proximity of an industrialized South Africa (Abshire, ). Much of manufacturing across the continent was in the hands of European and Asian settlers (Kilby, ) and colonial administrations assisted such enterprises, as, for example, with the formation of the Uganda Development Corporation in . There were also policies to develop technical education, for example, in Nigeria, and also to encourage import-substitution industries with some investment support in collaboration with private companies such as the UAC (Pedler, ; Kilby, ). Transfers of funds, a precursor of development aid, became much more significant after the Second World War (Munro, ). However, the absence of an industrial labour force in the peasant economies and the shortage of skilled labour in the settler economies of South Africa, especially because of its colour bar and job reservation policy, ensured that investments in manufacturing were capital intensive (Austin, ). By the end of the s and the early s imperial development policy saw the colonies as a source of primary-product export revenue used to import capital goods and develop infrastructure to attract private investment. As Havinden and Meredeth () note, this approach was problematic. Fluctuating export income from unstable commodity prices, import expenditure on ‘luxury’ consumer goods for the

OUP CORRECTED PROOF – FINAL, 18/9/2020, SPi



    

high-income settler population, poor linkages between the export sector and the rest of the economy, and profit outflows from the activities of foreign trading enterprises and foreign banks all made the prospect of export-led growth and development unlikely and anticipated the problems that would be faced by the newly independent African countries in the following decade. Nonetheless in some colonies, development funds were made available which allowed the beginnings of import-substitution industrialization (ISI), anticipating the industrial policy and strategy of the post-colonial governments (Kilby, ). Leaving South Africa aside, by the end of the colonial period the Belgian Congo and Southern Rhodesia had the largest manufacturing sectors in terms of their contribution to GDP, followed by Kenya and Senegal (Kilby, ). Production was centred on such products as cement, soap, textiles, baked foods, breweries, and food processing (Austin et al., ). The policy of promoting import-substituting manufacturing by largely private metropolitan companies was supplemented variously by tariff protection, subsidies, industrial training and development funds (Munro, ). These policies formed the basis of post-colonial industrial strategies in Africa.

. I- I  A: T E P- E

.................................................................................................................................. In spite of the low level of industrial development, its overall neglect during colonial rule in Africa was confirmed at independence. Typically, African economies were dominated by the export of agricultural and mineral primary products (GATT, ). The agricultural sector itself, including both cash crops for export and food crops for domestic consumption, accounted for ‒ per cent of GDP. Manufacturing value added as a share of GDP in  ranged from  per cent to  per cent but for most countries it was below  per cent (see Table .). Capital and consumer goods, even non-durables, were mostly imported (Ackah et al., : ). Generally, ISI during the first decade of independence was implemented as part of the broad development strategy elaborated in the national development plans (NDPs) which almost every independent African country formulated. Countries did not develop a separate IP in which they outlined the ISI strategy; ISI was embedded in the NDPs (Chitonge, ). For most post-colonial African governments, the establishment of domestic industrial capabilities was not only seen as a means of lessening dependence on former colonial powers but as a way of achieving economic and social development. ISI as a long-term strategy has been understood as a two- or three-stage process. The first ‘easy’ phase (Hirschman, ) was the local production of previously imported

Table 30.1 Manufacturing performance during early ISI, 1960–80

Country

Manufacturing share of GDP

Average annual growth rates of MVA

1963

1960–70

1980/81

1971–80

Countries with high MVA share in 1963 10.0 11.3 12.1 11.6 18.2 10.6 10.4 13.5 15.7 12.8 20.6 14.4 16.0

6.2 7.4 5.0 9.3 9.9 5.5 6.2 6.8 8.0 5.2

1963

1960–70

1980/81

1971–80

Countries with medium MVA share in 1963 (cont’d) 17.0 14.7 7.2 8.1 18.0 11.2 12.3 13.0 18.0 13.5 20.5 6.8 20.7

7.7 18.3 5.4 11.6 18.1 9 14.9 2.3 8.0 4.2 8.7 5.6 11.8

11.6 4.6 –4.3 5.8 6.7 –0.4 6.7 9.5 5.6 –4.5 4.5 1.5 2.8

Countries with medium MVA share in 1963 Angola Benin Botswana Burundi Cameroon Cape Verde Chad Congo Congo DR Equatorial Guinea

Average annual growth rates of MVA

Ethiopia Gabon Gambia Ghana Kenya Mali Mozambique Namibia Sierra Leone Tanzania Togo Tunisia Uganda Zambia

9.6 7.2 3.0 9.7 8.7 5.1 8.5 5.8 5.7 9.7 9.7 8.0 8.2 5.5

4.4 4.6 4.9 7.8 10.9 6.5 7.4 8.5 4.9 9.1 7.8 11.8 4.3 16.9

8.2 10.9 6.1 6.9 5.6 4.0 4.8 6.6 4.5 10.2 14 7.6 5.3 11.5

2.8 14.9 4.2 1 12.2 2.0 3.8 -6.1 3.7 2.9 –10.4 11.7 –9.3 0.3

3.3 8.4 3.4 12.8 8.4 9.2 9.6 7.6 2.2

2.6 3.4 7.2 5.6 18.4 4.6 4.7 13.4 6.3

Countries with low MVA share in 1963 9.7 8.0 4.4 6.9 8.8 — 11.1 7.5 7.6 5.5

7.2 6 6.2 13.8 7.4 9 5.4 7.4 12.5 5.1

–12.8 –0.6 17.3 5.9 7.3 3.2 5.7 –1.8 0.6 –16.1

Guinea Guinea Bissau Lesotho Liberia Libya Mauritania Niger Nigeria Rwanda

4.2 1.3 0.8 4.3 2.5 4.8 3.1 4.4 2.1

4.4 1.4 7.7 9.4 2.5 4.8 3.7 4.7 15.3

Notes: ISI: import-substitution industrialization; SAPs: structural adjustment programmes; MVA share: manufacturing value added as a share of GDP. High = 10 per cent+; medium= >5