Contemporary Issues in Sustainable Finance: Financial Products and Financial Institutions (Palgrave Studies in Impact Finance) 3030651320, 9783030651329

Table of contents :
Contemporary Issues in Sustainable Finance
Contents
Notes on Contributors
List of Figures
List of Tables
List of Boxes
1 Sustainable Finance: Emerging Challenges and Opportunities
1.1 Sustainable Products
1.2 Financial Institutions and Sustainable Practice
1.3 Investee Organizations and Impact Measurement
1.4 Concluding Remarks Over a Global Pandemic
References
2 Who Likes SIBs? A Bibliometric Analysis of Academic Literature (Time Span 1990–2018)
2.1 Introduction
2.2 Methodology
2.2.1 Step One: Investigating Keywords
2.2.2 Step Two: Analysis of the Authors’ Sentiment
2.3 Findings
2.3.1 Finding 1: Distribution of Paper by Cluster and Trend
2.3.2 Finding 2: Country Collaboration Map
2.3.3 Finding 3: Authors Distribution by Cluster
2.3.4 Finding 4: Keywords, Clusters and Sources
2.3.5 Finding 5: Intra Cluster Streams
2.4 Conclusion, Limitations and Ideas for Future Research
Appendix A—List of Papers Per Cluster
Cluster 1—Financial Pessimistic Approach
Cluster 3—Financial Optimistic Approach
Cluster 3—Public Pessimistic Approach
Cluster 4—Public Optimistic Approach
Appendix B: Cluster Description of the Research Sample Compared with Fraser Sample
References
3 Fighting Poverty and Inequalities Through Social Impact Bonds: Learning from Case Studies to Support the Covid-19 Response
3.1 Introduction
3.2 Background
3.2.1 Social Impact Bonds: A Thematic Perspective
3.2.1.1 Key Narratives and Approaches Identified Through Literature Reviews on SIBs
3.2.1.2 Outcome Metrics and Evaluation Models
3.2.1.3 Social Uncertainty, Risks and Pricing of SIBs
3.2.1.4 Innovativeness of SIBs and New Frameworks
3.2.1.5 Collaborations, Contractual Schemes, and Business Models for Sustainability
3.2.1.6 Empirical Analysis and Case Studies About SIBs
3.2.1.7 Recent Special Issues About SIBs and Open Questions
3.2.2 Prospects for Impact Finance Development in the EU Scenario
3.2.3 A Focus on the Italian Legislative Context for SIB Development
3.3 Research Design, Methods and Data
3.3.1 Methodology Approach
3.3.2 Data Collection and Case Selection
3.4 Empirical Evidence of the SIB Market
3.4.1 The SIB Market: A Snapshot
3.5 The SIB Case Studies: A Description
3.5.1 The SIB “ADIE—Association Pour Le Droit à L’Initiative Economique (Association for the Right to the Economic Initiative)”—France
3.5.2 The SIB “Back on Track”—Belgium
3.5.3 The SIB “Workforce Development SIB: Empleando Futuro (Employing the Future)”—Colombia
3.5.4 The SIB “Chicago Child–Parent Center PFS Initiative”—United States
3.5.5 The SIB “Mother Teresa Middle School”—Canada
3.6 Fighting Poverty and Inequalities Through Social Impact Bonds: Insights from Case Studies
3.6.1 The Role of Banks and Foundations and of Their Reputation to Catalyse Financial Resources
3.6.2 Promoting Inclusion and Poverty Alleviation Through Social Enterprises: The Link for the Development of the SIB Market
3.6.3 Improving the SIB Deal Structure Through Specialized Advisors
3.7 Looking Ahead: Implications for Research and Practice
3.8 Moving Practice Forward: A Proposal for Italy and for Europe
3.8.1 Building National Social Innovation Policies
3.8.2 Unpacking the Role of Social Enterprises in the Implementation of SIB Projects
3.8.3 Exploiting the Role of Microfinance Institutions and Banks
3.9 Final Thoughts
References
4 Green Bonds Capital Returns: The Impact of Market and Macroeconomic Variables
4.1 Introduction
4.2 Review of Literature
4.2.1 Green Bonds: General Aspects
4.2.2 Green Bonds: Market Variables
4.3 Sample and Data
4.4 Methodology
4.5 Results and Discussion
4.6 Conclusions
Annex
References
5 Crowdfunding as a Support Tool for the Activity of Social Investors
5.1 Background and Object
5.2 Methodology and Data Analysis
5.2.1 Meridonare and FBO: A Brief Description
5.2.2 The Meridonare Operating Model and Its Evolution
5.2.3 Data Analysis
5.3 Findings
5.4 Discussion and Conclusion
References
6 Environmental, Social, and Governance Integration in Asset Management Strategy: The Case of Candriam
6.1 Introduction
6.2 Theoretical Background
6.2.1 ESG Integration into SRI Strategies
6.2.2 How to Communicate the Integration of ESG Criteria into Investment Strategies
6.3 Research Design
6.3.1 Research Strategy
6.3.2 The Case Company
6.3.3 Data Collection and Content Analysis
6.4 Results
6.5 Discussions
6.6 Final Remarks
Appendix—Word-Count Matrix
References
7 Family Firms as Prominent Investment Organizations of Social Finance: An Empirical Analysis of U.S. Family Foundations
7.1 Introduction
7.2 Family Firms as Key Social Finance Investment Organizations: Financial Characteristics
7.3 Family Firms as Key Social Finance Investment Organizations: Non-Financial Characteristics
7.4 Methods
7.4.1 Sample Selection
7.4.2 Data Collection
7.5 Results
7.6 Discussion
7.7 Conclusions
References
8 Norwegian Pension Fund’s Portfolio: What Happens to the Companies Divested for Environmental Concerns?
8.1 Introduction
8.2 The Norwegian Government Pension Fund-Global Investment Process
8.3 Review of the Literature
8.4 Data and Methodology
8.5 Results
8.6 Conclusions and Hints for Future Research
References
9 Women’s Empowerment Through Social Entrepreneurship and Impact Investing in Myanmar
9.1 Introduction
9.2 Women’s Empowerment Through Social Entrepreneurship and Impact Investment: Definitions and Literature Review
9.3 Women’s Empowerment in Myanmar: An Overview
9.4 Government’s Actions to Address Gender Inequality in Myanmar
9.5 The Role of Social Entrepreneurship on Women’s Empowerment in Myanmar
9.6 Barriers Faced by Female Social Entrepreneurs in Myanmar
9.7 Myanmar’s Financial Landscape
9.8 Women’s Financial Exclusion in Myanmar
9.9 The Importance of Impact Investments in Social Enterprises in Myanmar
9.10 Conclusions and Recommendations
References
10 Social Impact Assessment: Measurability and Data Management
10.1 Introduction
10.2 Literature Review
10.3 Theoretical Framework
10.4 Methods
10.5 Results
10.6 Conclusion
References
11 Social Impact Assessment: A Focus on Italian Innovative Startups with a Social Goal
11.1 Introduction
11.2 Literature Review
11.3 Italian Innovative Startups with a Social Goal
11.3.1 Regulatory Definition and Main Features
11.3.2 Impact Measurement
11.4 Research Design
11.4.1 Peculiarities and Main Demographics on Innovative Startups with a Social Goal in Italy
11.4.2 Method
11.5 Main Findings and Discussions
11.6 Conclusions
References
12 Sustainable Finance and COVID-19 Pandemic: Weathering the Storm and Preventing a New One
12.1 Introduction
12.2 Weather the COVID-19 Storm Through Sustainable Finance: The Role of Impact Investments
12.2.1 Social and Sustainable Bonds
12.2.2 Social Impact Investment Funds
12.2.3 Social Impact Bonds
12.3 Preventing New Storm Through The Large Spectrum of Sustainable Finance Products
12.4 From the COVID-19 Outbreak to the Post-Pandemic: Theorizing the Role of Sustainable Finance
12.5 Concluding Remarks
References
Index

Citation preview

PALGRAVE STUDIES IN IMPACT FINANCE

Contemporary Issues in Sustainable Finance Financial Products and Financial Institutions Edited by Mario La Torre · Helen Chiappini

Palgrave Studies in Impact Finance

Series Editor Mario La Torre, Department of Management, Sapienza University of Rome, Rome, Italy

The Palgrave Studies in Impact Finance series provides a valuable scientific ‘hub’ for researchers, professionals and policy makers involved in Impact finance and related topics. It includes studies in the social, political, environmental and ethical impact of finance, exploring all aspects of impact finance and socially responsible investment, including policy issues, financial instruments, markets and clients, standards, regulations and financial management, with a particular focus on impact investments and microfinance. Titles feature the most recent empirical analysis with a theoretical approach, including up to date and innovative studies that cover issues which impact finance and society globally.

More information about this series at http://www.palgrave.com/gp/series/14621

Mario La Torre · Helen Chiappini Editors

Contemporary Issues in Sustainable Finance Financial Products and Financial Institutions

Editors Mario La Torre Department of Management Sapienza University of Rome Rome, Italy

Helen Chiappini Department of Management and Business Administration G. d’Annunzio University of Chieti-Pescara Pescara, Italy

ISSN 2662-5105 ISSN 2662-5113 (electronic) Palgrave Studies in Impact Finance ISBN 978-3-030-65132-9 ISBN 978-3-030-65133-6 (eBook) https://doi.org/10.1007/978-3-030-65133-6 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Palgrave Macmillan imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Contents

1

2

3

4

5

6

Sustainable Finance: Emerging Challenges and Opportunities Mario La Torre and Helen Chiappini

1

Who Likes SIBs? A Bibliometric Analysis of Academic Literature (Time Span 1990–2018) Luigi Corvo, Lavinia Pastore, and Matteo Ghibelli

5

Fighting Poverty and Inequalities Through Social Impact Bonds: Learning from Case Studies to Support the Covid-19 Response Annarita Trotta, Rosella Carè, Rossana Caridà, and Maria Cristina Migliazza

37

Green Bonds Capital Returns: The Impact of Market and Macroeconomic Variables Alessandra Ortolano and Eliana Angelini

91

Crowdfunding as a Support Tool for the Activity of Social Investors Antonio Minguzzi and Michele Modina

117

Environmental, Social, and Governance Integration in Asset Management Strategy: The Case of Candriam Silvia Cosimato, Nicola Cucari, and Giovanni Landi

135

v

vi

7

8

9

10

11

12

CONTENTS

Family Firms as Prominent Investment Organizations of Social Finance: An Empirical Analysis of U.S. Family Foundations Carmen Gallucci, Rosalia Santulli, and Riccardo Tipaldi Norwegian Pension Fund’s Portfolio: What Happens to the Companies Divested for Environmental Concerns? Stefano Dell’Atti, Viviana Fanelli, and Federica Miglietta

167

191

Women’s Empowerment Through Social Entrepreneurship and Impact Investing in Myanmar Vlada Perekrestova

221

Social Impact Assessment: Measurability and Data Management Luigi Corvo and Lavinia Pastore

247

Social Impact Assessment: A Focus on Italian Innovative Startups with a Social Goal Manuela Gallo and Valeria Vannoni

263

Sustainable Finance and COVID-19 Pandemic: Weathering the Storm and Preventing a New One Helen Chiappini

285

Index

301

Notes on Contributors

Eliana Angelini is Full Professor in Financial Markets and Institutions and Securities Markets, at the Department of Economic Studies, “G. d’Annunzio” University of Chieti–Pescara (Italy). She obtained a Ph.D. in Economics, Politics and Legislation of International Institutions and Financial Markets from University “La Sapienza” of Rome, in 2001. After graduating “cum laude” in Economic Sciences & Banking at the University of Macerata, she attended the M.B.A. Loyola University of Chicago, at the School of Business Administration, Department of Finance, as Visiting Candidate in 1998. Her main research interests are: financial risk management, performance and business model, systemic risk and spill-over effects, ESG factors, CDS and credit spreads. Rosella Carè is Senior Assistant Professor of Banking and Finance at the University of Cagliari and Marie Curie Research Fellow at the School of Environment, Enterprise and Development (SEED) of the University of Waterloo (Canada). Her research interests include: social and sustainable finance, alternative finance, impact investing, sustainable banking, climate risks and financial stability. Rossana Caridà is Associate Professor of Italian Public Law at University Magna Græcia University (UMG) of Catanzaro (Italy). She holds a Ph.D. in Administrative Law from the University of Catania (Italy). She currently holds public law, regional law and public management courses; she is a teacher at the advanced training courses. She teaches also in many

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High Training Courses (Postgraduate Schools of Law, Masters, Refresher Trainings, etc.) and she was responsible for various research projects relating to Public and Administrative Law, with a structural link with Constitutional Principles. She has authored more than 40 scientific publications. Her main areas of research concern Fundamental Rights, Citizenship and Public Administrators’ Liability. Main research topics: fundamental rights, citizenship, public liability, political-administrative organization and the role of local authorities, social finance, the third sector and public services. Helen Chiappini is Senior Assistant Professor at G. d’Annunzio University of Chieti–Pescara, Italy, where she teaches Sustainable Finance and Corporate Finance. Helen is the subseries editor of Palgrave Studies in Green Finance and Guest Editor of Sustainability. Her areas of research include sustainable finance, bank nonperforming loans and corporate governance. As well as publishing in academic journals, she has written and coedited three books: Social Impact Funds (Palgrave, 2017), Socially Responsible Investments (Palgrave, 2019) and Contemporary Issues in Sustainable Finance (2020). Luigi Corvo is Researcher at the Department of Management and Law of the University of “Tor Vergata”, teaches social entrepreneurship and social innovation, member of the Government Civil Society research group. Ph.D. in Management, he has been working for over 7 years on projects for the modernization of Public Administration, collaborating with the Department of Public Function of the Presidency of the Council of Ministers. He is Social Innovation Expert for the Social Innovation Fund of the Prime Minister’s Office—Ministry of Public Administration. He is cofounder of the innovative start-up and research spin-off Open Impact (https://www.openimpact.it/). For more than 10 years he has been program manager of the Master in Economics Management and Social Innovation and coordinates the social and economic impact assessment team within the Department of Management and Law. He is on the editorial board of “Rivista Impresa Sociale” pf IRIS Network (the Italian network for social enterprise) and European Journal of Social Impact and Circular Economy. Silvia Cosimato, Ph.D. in Marketing, is an Assistant Professor in Management at the University of Naples “Federico II”, Department of

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Economics, Management, Institutions (DEMI), where holds a course in Business Creation and Start-up Management. Her main research interests deal with service and system management, healthcare management, sustainability and sustainable development, innovation and service innovation. She has participated in several national and international conferences and published her research in international journals, such as the TQM journal, Socioeconomic Planning, Sustainability. She also serves as reviewer for outstanding journals (e.g. Journal of Cleaner Production, Waste Management, the TQM journal). She participated in the management of projects for supporting innovation and entrepreneurship financed by EIT Health. Nicola Cucari gained his Ph.D. in Business Management at Sapienza University of Rome. He obtained the national scientific habilitation as Associate Professor. Currently, he is Assistant Professor at Sapienza University of Rome and Adjunct Professor at different Italian Universities. He has been Research Fellow at the University of Salerno and Visiting Researcher at the University of Huelva (Spain)—Department of Management and at the University of Hohenheim (Germany)—Institute of Marketing & Management. His research is related to corporate governance, shareholder engagement, innovation management and family business. Stefano Dell’Atti is Full Professor of Banking and Finance at the University of Foggia in Italy. He holds a Ph.D. in Business Administration and Governance from the University Parthenope of Naples (Italy). He is Director of the Interuniversity Research Center on the Guarantee Institutions (CeSAC) of the University of Foggia and University of Bari Aldo Moro. He is also a Member of Editorial Board of JournalRivista Bancaria, Member of Editorial Board of Journal of Internet Banking and Commerce, Member of Editorial Board of Journal Risk Governance and Control: Financial Markets and Institutions and Co-Editor in Chief of Journal of Governance and Regulation. In his 20-year academic career, he has authored (or coauthored) more than 50 scientific publications and 16 books. His major areas of research are: Value and Intangibles in Banks; Reputational Risk; Small Banks, Guarantee Institutions; Efficiency of Financial Intermediaries, Regulation and Disclosure. Viviana Fanelli is Associate Professor of Mathematical Methods of Economics, Actuarial Science and Finance at the University of Bari Aldo

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Moro in Italy. She has also been an advisor at Mantho Solutions Ltd., London, where she focused on mathematical modeling and quantitative analysis. She has been appointed as course leader on financial risk management at a GARP-ERP Certification Program and as lecturer in energy finance at MIP—Polytechnic of Milan. Her research interests cover commodity finance, asset pricing, arbitrage strategies, dynamic models, interest rate and credit risk modeling. She regularly publishes in academic journals, including Quantitative Finance, European Journal of Operational Research, Energy Economics, Applied Energy and Nonlinear Analysis RWA. Viviana holds a Ph.D. in mathematical methods for economic and financial decisions. Manuela Gallo is a researcher in Banking and Finance at the Department of Economics of the University of Perugia, where she teaches Bank Management and Corporate finance. Manuela Gallo earned her degree in Economics from the University of Perugia in 2002 and the Ph.D. in Banking and Finance from the University of Roma Tor Vergata in 2007. Her main research areas are firm–bank relationships, financial literacy, households’ indebtedness and financial fragility, corporate governance. Carmen Gallucci is Associate Professor of Corporate Finance at the Department of Management and Innovation Systems—University of Salerno (Italy), where she is the Scientific Director of Family Business Observatory. She is currently teaching “Corporate Finance”, “Financial Analysis and Business Evaluation” and “Family Business Governance”. She is also affiliated researcher at IPAG Business School—Paris (France). Her research activity focuses on corporate finance, social finance, bank–firm relationship and the interaction between corporate governance models and economic and financial performance, with particular attention to family firms. Matteo Ghibelli is a Ph.D. in Business Economics with specialization in Public Management and Governance at the Faculty of Economics of Rome Tor Vergata. Master of Science in Economics and Development at the University of Rome Tor Vergata, member of the Government Civil Society research group. Social impact assessor and project manager for projects to tackle child educational poverty. He follows training projects for the Department of

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Management and Law including the Master in Economics Management and Social Innovation (MEMIS). Mario La Torre is Professor of Banking and Finance and Sustainable Finance at Sapienza University of Rome, Italy, and author of the blog Good in Finance. His research revolves around banking, financial intermediaries and financial innovation. Also an expert in ethical finance, microfinance and finance for the audiovisual industry, Mario is series editor of Palgrave Studies in Impact Finance. He is a member of the Board of the Italian National Body for Microcredit, and was previously a member of the G8 Taskforce on Social Impact Investments. As well as publishing in academic journals, Mario is the co-editor of Socially Responsible Investments (Palgrave, 2019) and Contemporary Issues in Sustainable Finance (2020). Giovanni Landi is Assistant Professor in Management at Department of Economics, Management, Institutions of University of Naples Federico II, where he earned a Ph.D. in Business Science from the University of Naples Federico II, defending a thesis on sustainability and corporate finance. During his Doctoral program, he has been visiting scholar at Cass Business School—City University of London (UK). After the Ph.D., he spent a research period as visiting fellow at Judge Business School— University of Cambridge (UK) for a seminar event about Technology Transfer and Social Innovation. His research activity focuses on sustainability management, business ethics, corporate sustainability assessment, sustainable finance and innovation management. Maria Cristina Migliazza is a Temporary Professor in “Financial Models and Instruments for public and health services” at the Department of Law, Economics and Sociology at the University Magna Graecia of Catanzaro (UMG), Italy. She holds a Ph.D. in Healthcare Management and Economics from the University Magna Graecia of Catanzaro (UMG). Her research focuses on social and sustainable finance, social impact investing and social impact bonds. Federica Miglietta is Associate Professor of Banking and Finance at the University of Bari Aldo Moro in Italy. She holds a M.Sc. in Financial Institutions and Markets from Bocconi University, Milano and a Ph.D. in Business Administration and Management from the same university and has attended part of her Ph.D. program at Xfi Center for Finance and

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Investments, Exeter University, UK. She is member of the editorial advisory board of several international journals and acts as a referee for books and papers dealing with conventional and Islamic finance, SRI and alternative investments. Federica has extensively published books and papers on ESG themes, such as socially responsible and religious investments. She is also part of the Board of Directors of the Joint Italian Arab Chamber, Roma. Antonio Minguzzi is Associate Professor in Management at the University of Molise, Italy. He has been visiting professor at Haskayne School of Business, University of Calgary (Canada). Professor Minguzzi’s actual research interests include management of social enterprises and small business development and he has published national and international articles on entrepreneurship and management. He has been studying and working in the social sector for over twenty years, covering various roles. He collaborated with disability centers of several universities for projects aimed at the inclusion of disabled people in university study paths. He has been administrator of social enterprises and managing director of grant banking foundations, cultural foundations and microcredit companies. Michele Modina is Associate Professor in Business and Management at the University of Molise, Italy where he holds courses in Entrepreneurship and Corporate Finance. Recently he was visiting professor at the Koppelman School of Business at Brooklyn College of the City University of New York (CUNY). His research focuses on the value creation in current and new business initiatives, the management of financing techniques with particular attention to the new methods of provision of financial resources, and the bank–firm relationship on which he has published numerous papers in leading journals. Alessandra Ortolano is Postdoctoral Research Fellow and Subject Expert in Financial Markets and Institutions and in Securities Markets at “G.d’Annunzio” University of Chieti–Pescara (Italy), where she obtained a Ph.D. in Business, Institutions, Markets. She published several papers on credit risk and Credit Default Swaps and achieved, as coauthor, the international recognition Best Research Paper ICABER 2016, for the study CDS spreads and balance sheet ratios in the banking sector: an empirical analysis on Mediterranean Europe. She has gained experience in academic teaching and tutoring. Her current interests of research deal

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with sustainable finance and the analysis of the relative products and markets. Lavinia Pastore is a research fellow in Management, Ph.D. in Public Management and Governance at the Faculty of Economics of the University of Rome “Tor Vergata”, member of the Government Civil Society research group. She is cofounder of the innovative start-up and research spin-off Open Impact (https://www.openimpact.it/). Since 2016 she has been manager of MEMIS (Master in Economics Management and Social Innovation). Lecturer at Social entrepreneurship and Innovation course and different master programs (the University of Rome “Tor Vergata”, Lumsa, IED, Link Campus). With more than 5 years of experience in social impact assessment, she is the coordinator of the impact assessment team for the Department of Management and Law for projects to tackle child educational poverty. She has worked as a consultant for public bodies, foundations, private companies and Third Sector Organizations, gaining extensive experience as a manager and main researcher within both national and international social innovation and impact-life-cycle-management related projects. Vlada Perekrestova is a Ph.D. candidate in Asia-Pacific Studies at National Chengchi University, College of Social Science. Vlada has research interests in the areas of women’s empowerment, social entrepreneurship, financial inclusion, and social impact measurement. She is involved in community-serving projects, which promote education and language learning. Rosalia Santulli is Lecturer in Financial Analysis and has a Research Fellow in Corporate Finance at the Department of Management and Innovation Systems—University of Salerno (Italy). She is also affiliated researcher at IPAG Business School—Paris (France). She received her doctoral degree in 2014. In 2015, she spent a period as a visiting researcher at Witten Institute for Family Business—University of Witten/Herdecke (Germany). In 2018, she was a visiting researcher at International Family Business Observatory—IPAG Business School— Nice Campus. Her primary research interests are family business, corporate governance, corporate finance, social finance and entrepreneurial finance.

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Riccardo Tipaldi is a Ph.D. student in Banking and Finance at “Sapienza” University of Rome. He works as a group member at the Family Business Observatory active at the University of Salerno, Department of Management and Innovation Systems (DISA-MIS). He received a B.S. degree in Business Administration and an M.S. degree in Corporate Consulting and Management from the University of Salerno. His main research interests are in corporate finance in the areas of social finance and impact investing. Annarita Trotta is Professor of Banking and Finance at the University Magna Græcia (UMG) of Catanzaro, Italy, where she currently teaches “Economics of Financial Intermediaries and Markets” (a.y.: 2020/2021). She holds a Ph.D. in Business Administration from the University of Naples “Federico II” (Italy), where she was Assistant Professor of Banking and Finance (from 1995 to 2001). In 2001 she moved to the “Federico II” at UMG. She has taught several courses over the years, at both undergraduate and graduate levels, including Banking, Financial Markets, Financial Markets and Behavioral Finance, Corporate Finance and Corporate Finance (Advanced). At present, she is a member of the Evaluation Unit of the LUM University (Italy). She serves as a member of the editorial board and referee for many scientific journals. She has authored (or coauthored) more than 70 scientific publications and 5 books. Her primary areas of research are: Social and sustainable finance; Impact Investing; Alternative finance and sustainability; Reputational risk and reputational crisis in the banking sector. Valeria Vannoni carries out research activities at the Industrial Liason Office and Third Mission of the University of Perugia, where she is also a professor of Corporate finance at the Department of Economics. Ph.D. in Banking and Finance at the University of Rome Tor Vergata, she is the author of many publications on topics related to financial intermediation and firm financing, with particular attention to the problem of funding innovative and start-up companies.

List of Figures

Fig. 2.1 Fig. 2.2 Fig. 2.3 Fig. 2.4 Fig. 2.5 Fig. 2.6 Fig. 2.7 Fig. 3.1 Fig. 3.2 Fig. 3.3 Fig. 3.4 Fig. 3.5 Fig. 3.6 Fig. 4.1 Fig. 6.1

Annual scientific production of the research sample Matrix of clusters in the research sample Cluster dynamic over the timespan based on the research sample Country collaboration map Three fields plot of author’s keywords, clusters and journals Three fields plot of author’s keywords, clusters and countries Intra cluster streams Sibs market: a snapshot (Source Author’s elaboration from Go Lab database [2010–April 2020]) Impact Bonds launched worldwide from 2010 to April 2020 (Source Author’s elaboration from Go Lab database) SIBs Social issues (Source Author’s elaboration from Go Lab database) SIBs Capital raised (Source Author’s elaboration from Go Lab database) European Quality of Government Index (EQI) (Source Author’s elaboration from publicly available information) Ecosystem for the development of SIB projects Green Bonds capital returns (Source Authors’ elaborations of Borsa Italiana data) Most recurrent SRI strategies in KIIDs (Source Authors’ elaboration)

13 14 15 16 18 19 20 56 57 57 58 58 73 101 144

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LIST OF FIGURES

Fig. 6.2 Fig. 6.3 Fig. 6.4 Fig. Fig. Fig. Fig. Fig. Fig. Fig. Fig. Fig. Fig. Fig. Fig.

8.1 8.2 8.3 8.4 8.5 8.6 8.7 8.8 8.9 10.1 10.2 10.3

Fig. 10.4 Fig. Fig. Fig. Fig.

11.1 11.2 11.3 11.4

Fig. 12.1 Fig. 12.2

Most recurrent ESG thematics in KIIDs (Source Authors’ elaboration) Most recurrent keywords for each category (Source Authors’ elaboration) Total occurrences for each document (Source Authors’ elaboration) Cumulative abnormal returns in the United States Cumulative abnormal returns in Japan Cumulative abnormal returns in Chile Cumulative abnormal returns in Canada Cumulative abnormal returns in India Cumulative abnormal returns in China Cumulative abnormal returns in Australia Cumulative abnormal returns in Germany Cumulative abnormal returns in the United Kingdom Data representation dashboard through Power BI Geographical distribution of the analysed projects Usability of measurement data and assessment of social impact Preliminary result of connection between the social impact data and the SDGs Kind of innovation by ISUSGs Financing sources of ISUGSs Financing entities for ISUGs Difficulties in drafting the “Social Impact Assessment Document” Social bond principles by ICMA (Source Author’s elaboration based on ICMA [2020]) COVID-19 response and reconstruction framework (Source Author’s elaboration)

145 150 151 206 206 207 207 208 208 209 209 210 256 256 257 258 276 277 278 279 288 296

List of Tables

Table 2.1 Table 3.1 Table 3.2

Table 3.3 Table 3.4 Table 3.5 Table Table Table Table Table Table Table Table Table Table Table Table Table Table Table

3.6 4.1 4.2 4.3 4.4 4.5 4.6 4.7 4.8 4.9 4.10 5.1 6.1 6.2 6.3

Description of the research sample An overview of the selected SIBs The SIB “ADIE—Association pour le Droit à l’Initiative Economique (Association for the Right to the Economic Initiative)”—France The SIB “Back On Track”—Belgium The SIB “Workforce Development SIB: Empleando Futuro (Employing the Future)”—Colombia The SIB “Chicago Child–Parent Center PFS Initiative”—United States The SIB “Mother Teresa Middle School”—Canada Green Bonds sample Descriptive statistics Results 2016 Results 2017 Results 2018 Results 2019 Correlation matrix 2016 Correlation matrix 2017 Correlation matrix 2018 Correlation matrix 2019 The key variables of Meridonare’s crowdfunding activity Case company main characteristics Dictionary containing the keywords under investigation Coding categories and keywords

12 53

60 63 64 67 68 100 102 104 104 105 105 109 110 111 112 124 144 146 147

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LIST OF TABLES

Table 6.4 Table 6.5 Table 7.1

Table 7.2

Table 7.3

Table Table Table Table Table Table Table Table Table Table Table Table

8.1 8.2 8.3 8.4 8.5 8.6 8.7 8.8 8.9 8.10 8.11 11.1

Table 11.2 Table 12.1 Table 12.2

Items and indicators rising from the content analysis The most and the least recurrent keywords Funding type, funding stage, and capital type—The table shows the sub-categories used to classify each transaction based on funding type, funding stage, and capital type Descriptive statistics—The table shows the descriptive statistics for each sub-category of funding type, funding stage and capital type Number of partner investors per funding stage and funding type—The table shows the number of partners involved by family foundations in different funding stages and using different funding types Excluded companies Event window analysis in the United States Event window analysis in Japan Event window analysis in Chile Event window analysis in Canada Event window analysis in India Event window analysis in China Event window analysis in Australia Event window analysis in Germany Event window analysis in the United Kingdom Regression results on the reputational loss Main demographic and financial data of Innovative startups with a social goal, October 2019 Female, youth, and foreign prevalence COVID-19 pandemic: social and sustainable bonds Social impact funds and COVID-19 pandemic

149 150

177

180

181 204 211 211 211 212 212 212 213 213 213 215 274 275 289 292

List of Boxes

Box 9.1 Box 9.2

Case study: MBoutik Case study: Proximity Design

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CHAPTER 1

Sustainable Finance: Emerging Challenges and Opportunities Mario La Torre and Helen Chiappini

Sustainable finance, and all the related concepts under this umbrella term—such as ethical, socially responsible, and impact finance (Sandberg et al. 2009; Yen et al. 2019)—is emerging as a mainstream topic, gathering the interest of worldwide policymakers, practitioners, and academics. Climate change, but also the unmet social needs, encourage a fast transition towards a sustainable economy and, in turn, the identification of a clear regulatory framework, able to support the financing of the most virtuous sectors. Several jurisdictions are moving on in this direction (OECD 2020), however, investors remain still caution due to the

M. La Torre Department of Management, Sapienza University of Rome, Rome, Italy e-mail: [email protected] H. Chiappini (B) Department of Management and Business Administration, G. d’Annunzio University of Chieti-Pescara, Pescara, Italy e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. La Torre and H. Chiappini (eds.), Contemporary Issues in Sustainable Finance, Palgrave Studies in Impact Finance, https://doi.org/10.1007/978-3-030-65133-6_1

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risk of green-washing that the sustainable market currently faces (Parguel et al. 2011; Revelli 2017; Yu et al. 2020). Undefined (or not aligned) regulations and green-washing are only some of the most relevant challenges of sustainable finance. This book aims to shed lights on current issues in sustainable finance through a critical presentation and discussion of theoretical issues, case studies of innovative financial products and sustainable institutions; it also empirically investigates some challenges related to both financial and social performance. In more detail: the book explores challenges in the following main streams: (i) sustainable products, (ii) financial institutions and sustainable practices, (iii) investee organizations, and impact measurement. The conclusions offer an overview on the most recent challenges faced by sustainable market and, more in general, by the global economy and financial system, over the COVID-19 pandemic crisis.

1.1

Sustainable Products

Chapter 2 Who likes SIBs? A bibliometric analysis of academic literature by Luigi Corvo, Ludovica Pastore, and Matteo Ghibelli, investigates academic contributions on social impact bonds (SIBs) through a bibliometric analysis. The study reveals that existing literature has a positive and optimistic view of SIBs and that both governments and investee organizations consider outcome-based contracts as valuable schemes. Chapter 3 Fighting poverty and inequalities through social impact bonds: learning from case studies for supporting the COVID-19 response by Annarita Trotta, Rosella Carè, Rossana Caridà, and Maria Cristina Migliazza, discusses critical case studies of SIBs aimed at addressing poverty and socio-economic inequalities. The chapter contributes to the ongoing debate on SIBs, providing a framework of practices useful for SIBs development, also in the post COVID-19 pandemic scenario. Chapter 4 Green bonds capital returns: the impact of market and macroeconomic variables, by Alessandra Ortolano and Eliana Angelini studies the determinants of green bonds capital returns. Findings highlight peculiarities, like the negative autocorrelation or the lacking influence of stock market.

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1.2 Financial Institutions and Sustainable Practice Chapter 5 Crowdfunding as a support tool for the activity of social investors by Antonio Minguzzi and Michele Modina, discusses the case study of an Italian crowdfunding platform, demonstrating that social crowdfunding promotes a significant interaction between all players involved in the crowdfunding scheme—non-profit organizations, social investors and donors—and improves the philanthropic activity of the banking foundation. Chapter 6 Environmental, Social, and Governance Integration in Asset Management Strategy: The Case of Candriam, by Simona Cosimato, Nicola Cucari, and Giovanni Landi, examines how the asset manager integrates ESG factors into their investment strategies, and how they communicate such strategies. Chapter 7 Family Firms As Prominent Investment Organizations Of Social Finance: An Empirical Analysis Of U.S. Family Foundations, by Carmen Gallucci, Rosalia Santulli, and Riccardo Tipaldi examines U.S. family foundations and supports that they are playing a significant role in the social finance landscape by providing social entrepreneurs with equity and debt capital, as well as grants. Chapter 8 Norwegian Pension fund’s portfolio: What happens to the companies divested for environmental concerns?, by Stefano Dell’Atti, Viviana Fanelli, and Federica Miglietta, investigates how international investors reacted to the news of firm exclusion from the portfolio of the Norwegian Government Pension Fund-Global. Results highlight different reactions according to the investors’ behaviors.

1.3 Investee Organizations and Impact Measurement Chapter 9 Women’s empowerment through social entrepreneurship and impact investing in Myanmar, by Vlada Perekrestova, explores the role of social entrepreneurship and impact investing on women’s empowerment in Myanmar. The chapter supports that impact investments in Myanmar play a decisive role in disrupting the current way of financing development, as well as in creating a new generation of female social entrepreneurs.

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Chapter 10 Social impact assessment: measurability and data management, by Luigi Corvo and Lavinia Pastore, explores the great potential of technological innovation in favor of social and environmental impact objectives. The results give evidence that digital technologies may have a relevant role in making social processes more measurable, reliable and scalable. Chapter 11 Social impact assessment: a focus on Italian innovative startups with a social goal, by Manuela Gallo and Valeria Vannoni, investigates impact assessment of startups that seek to achieve a social aim. The findings confirm the urgency of removing cultural and practical barriers that start-ups are experiencing in the measurement of social impact.

1.4

Concluding Remarks Over a Global Pandemic

Chapter 12 Sustainable finance challenges and COVID-19 pandemic: weathering the storm and preventing a new one, by Helen Chiappini concludes the book with an overview of sustainable financial products implemented during the pandemic crisis and summarizes some reflections on how sustainable finance could represent a useful tool for reconstructing a resilient financial and economic system.

References Yen, M. F., Shiu, Y. M., & Wang, C. F. (2019). Socially responsible investment returns and news: Evidence from Asia. Corporate Social Responsibility and Environmental Management, 26(6), 1565–1578. Yu, E. P. Y., Van Luu, B., & Chen, C. H. (2020). Greenwashing in environmental, social and governance disclosures. Research in International Business and Finance, 52, 101192. OECD. (2020). Developing sustainable finance definitions and taxonomies. Paris: OECD Publishing, Green Finance and Investment. Parguel, B., Benoît-Moreau, F., & Larceneux, F. (2011). How sustainability ratings might deter ‘Greenwashing’: A closer look at ethical corporate communication. Journal of Business Ethics, 102, 15. Revelli, C. (2017). Socially responsible investing (SRI): From mainstream to margin? Research in International Business and Finance, 39, 711–717. Sandberg, J., Juravle, C., Hedesström, T. M., & Hamilton, I. (2009). The heterogeneity of socially responsible investment. Journal of Business Ethics, 87 (4), 519.

CHAPTER 2

Who Likes SIBs? A Bibliometric Analysis of Academic Literature (Time Span 1990–2018) Luigi Corvo, Lavinia Pastore, and Matteo Ghibelli

2.1

Introduction

This chapter aims to study the development in academic literature on SIBs focusing on the concept of this financial instrument. To some extent, our work can be considered as an evolution of Alec Fraser’s publication (Narratives of Promise, Narratives of Caution: A Review of the Literature on Social Impact Bonds, Fraser et al. 2016) who divided literature on SIBs existing in 2015 into three different narratives regarding SIBs (PSR, FSR and cautionary narrative). We aim to explore commonly held attitudes towards SIBs by better understanding the extent to which researchers hold a “cautionary narrative”, as identified by Fraser et al. (2016). If an

L. Corvo · L. Pastore · M. Ghibelli (B) Department of Management and Law, University of Rome “Tor Vergata”, Rome, Italy e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. La Torre and H. Chiappini (eds.), Contemporary Issues in Sustainable Finance, Palgrave Studies in Impact Finance, https://doi.org/10.1007/978-3-030-65133-6_2

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author has a cautionary view of the instrument, is this cautionary view related to its risk or to its potential? To properly conduct our analysis, we set up the following research questions: – RQ1 How has scientific literature regarding SIBs and Impact Finance been evolving? As part of RQ1, we also considered what the main focuses for research have been. – RQ2 Is there a predominant feeling (optimistic or pessimistic) in academia regarding this issue? To answer the questions, we started from a classic literature review methodology, that comprised searching databases using selected keywords and then setting up exclusion criteria to select a final sample. In our case, the databases investigated were mainly Web of Science and Google Scholar, and we found more than 500 academic papers from which we shortlisted 97, all of which were written between 2010 and 2018. Having obtained our final sample, we did a sentiment analysis on the papers we selected, then we analysed the sample using Bibliometrix. Bibliometrix is an R-package built to conduct bibliometric analysis following the standard workflow for science mapping. We are unique in our use of Bibliomatrix for our mapping, which means that our work is different from existing literature reviews on SIBs. We hope that this provides an inspiration for other scholars to run bibliometric analysis on their topic of interest in order to further advance literature reviews studies by using new technology. This process is explained in depth in our methodology chapter. SIBs present a new and innovative way to finance social programmes and can be seen as part of a much broader concept known as Social Finance. When talking about SIBs, impact investing, and social enterprises, there is a lot of diversity (Hochstadter and Scheck 2015). One commonality in the variety of aspects and actors is that all have the same objective of combining revenue generation with social impact. In the last decade, social finance has emerged as an alternative to the traditional way of thinking about financial resources and their use (OECD 2014; Social Investment Task Force 2010). Historically, social entrepreneurs have relied on grants and contracts from government agencies or foundations as a primary source of financial support, but in

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times of fiscal constraint, these sources may become more limited. Therefore, new forms of capital for investment in social innovation are needed (Moore et al. 2012). Social finance has an important role in stimulating social innovation because the investment typically challenges the institutional logics associated with conventional investor rationalities (Nicholls and Murdock 2012; Nicholls 2010). This emerging trend in thinking has had sporadic growth, with some countries developing their research before others. Each country independently developed a unique solution to meet the most significant social issues of our times. Although a large number of very diverse communities explored this issue in different ways, there is some heterogeneity in thinking, not only in the sectors of operation and instruments used, but also in creating a shared definition of social enterprise itself. The social dimension of each organisation sets value-creation as the ultimate goal, however, the ways in which this is achieved are wideranging. It was unclear to us initially what to include in the definition of SIBs as many scholars have a slightly different understanding. This is due to a drive to identify which metrics and sets of variables motivate individual actions that could be used on a wider scale internationally. SIBs are considered part of Social Impact Investing (henceforth, SII), a term coined in 2008 by JP Morgan and Rockefeller Foundation.1 SII is an investment culture that endeavours to make long-term social gains by addressing social problems rather than attempting to maximise financial returns (Leventhal 2012). Pension fund managers and other institutional investors are increasingly making investments that are socially responsible and which pursue more active roles in corporate governance (Apostolakis et al. 2018). According to Wood et al. (2013), impact investing can be defined as investing with the explicit purpose of creating measurable social or environmental benefits in addition to financial returns. The motivation for creating SIBs now is the payment-by-results schemes associated with target-based performance management that were popularised under the Blair government in the UK during the 2000s, which aimed to link contracts to specific outcomes (Warner 2013). In this section of the chapter, we outline the steps we used to answer our research questions, detailing the methodology and motivation for using Bibliometrix. We also interpret the results obtained after employing our bibliometric analysis. We found five factors that govern what academic research is produced, which are based on: what type of research is most popular for published papers, what areas of the world are partnering in

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research into SIBs, how many academic actors are researching into each cluster, how wide the range of metadata associated with existing literature is, what dynamics exist between different clusters, and what sources influence different authors. One universal finding we identified is that most academic literature considers SIBs as a useful financial tool for governments. This highlights an important consideration about the possible implication and use of our study: if we assume, based on available data, that attitudes towards SIBs are largely positive globally, then there is scope for governments to explore how SIBs may be applied to help solve local issues. Our research could thus be used as an exploratory map for governments and other actors setting out on this study. One of the main limitations of our study is that there is a lack of quantitative data in the literature of SIBs, and particularly into outcomes reached, impact and revenues generated. That is, while we hope that our research is replicable, we cannot yet say that our findings are supported by other literature research at this time as there is currently little current empirical evidence of the optimistic consideration that is given to SIBs by scholars.

2.2

Methodology

To address our research questions, we chose to conduct a bibliometric analysis since it seemed the most appropriate methodology available to investigate the development of literature and academic discourse about SIBs. As recommended by Zupic and Cater (2015), we followed the standard workflow for bibliometric analysis, that consists of five different stages: 1. Study design; 2. Data collection; 3. Data analysis; 4. Data visualisation; 5. Interpretation. To conduct our bibliometric analysis on mainly existing academic literature, we decided to use an innovative open-access software called “Bibliometrix” developed by Aria and Cuccurullo (2017) as this tool is

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designed to assist scholars to complete a recommended workflow. It is different from other science mapping tools (Aria and Cuccurullo 2017) available. This choice was made for several reasons, including the following: – Objectivity; – Replicability; – Flexibility. Objectivity is created by following an automated process. In this case, one that Bibliometrix embeds in its source code. As Aria and Cuccurullo (2017) state, “in this paper, we propose a unique tool, developed in the R language, which follows a classic logical bibliometric workflow that we reconstruct”. Replicability arises from objectivity in this case, as whoever uses the same procedures and similar source documents should find the same results. Flexibility, which is our biggest consideration, allowed us to create a dataset, divide it into different clusters, and analyse the dataset we made, maintaining the clusterisation we did. “As it is programmed in R, the proposed tool is flexible, can be rapidly upgraded, and can be integrated with other statistical R-packages ”. We also used Bibliometrix as it is programmed to take information from academic databases such as Scopus and Web of Science (henceforth, WOS), that match our source documents. The first step of our method is study design, developing Alec Frasers’s model that he sets out in his publication. With his approach, Fraser et al. (2016) identified different narratives based on the perspective of the authors studied. In the PSR Narrative, SIBs are considered a tool for the public actor. “From this perspective, the opportunity offered by SIBs to merge public and private values is seen as advantageous ” (Fraser et al. 2016, p. 6). In the FSR Narrative, SIBs are considered a tool by which profits can be gained through social purposes. “It [is proposed] that blending public and private values will offer private sector actors (particularly financial institutions) an opportunity to affect socially worthwhile change through social entrepreneurship whilst simultaneously pursuing commercial interests ” (Fraser et al. 2016, p. 6).

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In the Cautionary Narrative, Fraser classified all papers that discuss SIBs in a “prudent way” as being written in either a public or private perspective. He simultaneously highlighted problems regarding measurement of outcome, risk of financialization (Lake 2015) and possible distortion of social mission of social enterprises (Joy and Shields 2013). It is this last narrative that we consider the most interesting, because it gives us a starting point by which to conduct in-depth analysis into the feeling of cautionary authors. In our analysis, we identify if the caution shown by authors is linked to either an optimistic or pessimistic attitude, and if this attitude can be framed in one of the two previous narratives that Fraser identified, that is, either PSR or FSR. For the second stage of our workflow (2. Data collection), we followed the steps described below. 2.2.1

Step One: Investigating Keywords

1. We found the keywords identified by Fraser et al. in 2016, namely: (a) ‘Social impact bond’ (b) ‘Social AND impact AND bond’ (c) ‘Pay* for success bond*’ (d) ‘Pay* for success contract*’ (e) ‘Development impact bond*’ (f) ‘Outcome based contract’ (g) ‘Impact invest*’ (h) ‘Impact-first invest*’ (i) ‘Social innovation financ*’ (j) ‘Health impact bond*’ (k) ‘Social impact invest*’ (l) ‘Social benefit bond’ (m) ‘Social bond’ (n) “Social finance” (o) “Social impact finance”. 2. We largely used two different databases: Clarity WoS and Google Scholar, and found 547 references in total. We then searched independently through papers that were not included in these databases, but cited by Fraser, over the timespan 1990–2018; 3. We set the exclusion criteria:

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(a) All documents that were not academic papers were deleted from our list (including proceeding papers and book chapters); (b) All documents that were not written in English were deleted from the list; (c) All papers that refer to “Social Bond Theory” were deleted; (d) All papers that did not directly refer to SIBs or Social Finance in the abstract, list of keywords or introduction were excluded. 2.2.2

Step Two: Analysis of the Authors’ Sentiment

1. We created four clusters, based on a matrix of the PSR Narrative and FSR Narrative, as follows: (a) Financial Optimistic; (b) Financial Pessimistic; (c) Public Pessimistic and (d) Public Optimistic. We considered “optimistic” the papers in which SIBs are seen as tools that might have positive consequences both in FSR and PSR. For instance, if the adoption of a SIB scheme is considered a potential tool to fund a social enterprise, or if it is seen as a way to address social problems that create savings and create additional value for the public actor, the paper would be classified as being “optimistic”. Likewise, we classified papers as “pessimistic” if there was potential for a SIB to negatively affect public and private actors. For instance, when a paper highlights the agency problem that public and private actors might face in a SIB contract or distorts social mission. 2. We set up exclusion criteria: (a) All papers that refer to SIBs or social finance only once or twice in the body of the text without allowing a sentiment analysis of the tool were deleted. During the period February 2019–June 2019, we skim-read all the papers and selected the cluster to which it belonged. We then matched the results and found a set of 97 academic papers that met all conditions required to be necessary for our analysis. We then concluded the second step of the

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Table 2.1 Description of the research sample

Description

Results

Documents Sources (journals, books, etc.) Period Average citations per documents Authors Documents per author Authors per document Annual growth rate

97 75 2011–2018 6.253 170 0.570588 1.75 72.12%

workflow and proceeded to the third and fourth steps: data analysis and data visualisation. Bibliometrix data analysis tools enable an array of documents to be created, and with that, a matrix, based on the attributes selected. For example, if the authors of a document were selected, Bibliometrix would create a matrix “N x M ” setting “N = Documents and M = authors ”. Since Bibliometrix is open and customisable, we made a spreadsheet with our sentiment analysis and clusterisation, imported it into Bibliometrix, and used that to analyse the data included in our 97 records. Our dataset, consisting of the papers we identified, is summarised in the table below (Table 2.1) and a graph of the scientific production over one year is provided (Fig. 2.1).

2.3

Findings

Our research analysis allowed us to identify five main findings: 1. The first refers to what type of research is most popular for published papers (Public-Optimistic, Public-Pessimistic, Finance-Optimistic, or Finance-Pessimistic); 2. The second allows us to explore what areas of the world are partnering into research on SIBs; 3. The third investigates the number of academics that are researching into each cluster, and includes a qualitative analysis of coherency of writing in each cluster; 4. The fourth explores the range of metadata associated with the existing literature, namely, the relationship between the author’s

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Fig. 2.1 Annual scientific production of the research sample

keywords, clusters and journals of publication, and then the relationship between author’s keywords, clusters and national origins of research; 5. The fifth identifies the dynamics between different clusters, and sources of influence for different authors. Hereafter a description of each finding. 2.3.1

Finding 1: Distribution of Paper by Cluster and Trend

By analysing our created dataset, we noticed that almost half of the papers could be included in the Public Optimistic cluster. The share of papers per cluster is summarised in the matrix below (Fig. 2.2). A full list of papers in each cluster is included in Appendix A. The reason why the majority of the papers analysed are found in the Public-Optimistic cluster is explained in the rest of the data analysis, particularly, in the description of findings concerning intra-cluster streams. The optimistic consideration of SIBs, particularly, those in the public sector, form part of the public governance narrative that underlines

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Fig. 2.2 Matrix of clusters in the research sample

the role of government as a multi stakeholder body that enables greater collaboration between actors and encourages the use of public–private partnerships (henceforth, PPPs). Public governance combines the strengths of public administration (henceforth, PA) and new public management (henceforth, NPM), by recognising the legitimacy and interrelatedness of the policymaking, its implementation and the service delivery processes (Osborne 2009; Osborne and Gaebler 1992). In this thinking, the SIB structure can be interpreted as a powerful tool that can be used to implement public governance framework (Corvo and Pastore 2017). The use of SIBs is also supported in the collaborative approach through which public services are delivered. This is further explored in research on the Triple Helix model, as studied by Etzkowitz and Leydesdorff (1995), Leydesdorff (2015), Leydesdorff and Etzkowitz (2001) and multiple authors in the field of cocreation and co-production of public services, see Bovaird and Loeffler’s (2012) paper for more information. SIBs, as seen through the lens of observation and theoretical assumptions, seems to be the perfect tool for tackling social problems, and generating public value and savings by incorporating different approaches from different actors who are united by shared values. Appendix B includes our assessment of Fraser’s analysis and reclustering of his sample according to our four categories. Where possible,

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Fig. 2.3 Cluster dynamic over the timespan based on the research sample

an application of the sentiment analysis and clusterisation of Fraser’s database to his 2016 work reveals the same share of papers per cluster as ours. We have no significant changes to make to the share of papers per cluster for the pessimistic sentiment, neither for FSR nor for PSR Narratives. A comparison of Fraser’s work with ours shows that most pessimistic perspectives arise from the attitude to risk when using a SIB. Many consider SIBs to be the tools that “financialise” human life (Kish and Leroy 2015). We found an increasing trend of paper production per cluster (see Fig. 2.3) in the optimistic perspective category over the timespan. The highest average growth rate is in the financial optimistic perspective, a growth of 40%. This is important as it shows a growing narrative on private actors’ benefits. 2.3.2

Finding 2: Country Collaboration Map

Using Bibliometrix, we investigated the country collaboration map, by using the co-citation analysis that provides information on the country of origin of papers. This map (Fig. 2.4) details the spread of each sentiment.

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Fig. 2.4 Country collaboration map

By investigating the different clusters, we noticed that: – Cluster 1 (Financial Pessimistic) includes documents from Englishspeaking countries, Germany and the Netherlands. We found collaboration between Canada and the UK, and between Australia and Germany; – Cluster 2 (Financial Optimistic) includes documents from the USA, Australia, the UK, Italy, Greece, South Korea, Taiwan and Vietnam. We found collaboration between the USA and South Korea, and between Greece and the Netherlands; – Cluster 3 (Public Pessimistic) includes documents from the USA, Canada, the UK, Italy and Australia. We found collaboration between Canada and the UK; – Cluster 4 (Public Optimistic) includes documents from Austria, Australia, Sweden, Russia, China, India, the Netherlands, the USA, Canada, the UK and Italy. We found collaboration between the USA and the UK, between the USA and India, and between Italy and Austria.

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While the production of academic literature does not always match the progress of SIB development in the world, most of the debate occurs in countries that have SIBs. Research into the optimistic public cluster, which is the most documented cluster, is most widespread globally. This data might suggest that due to the spread of the optimistic narrative category of research, SIBs are more likely to be adopted or developed in these countries. Surprisingly, while there are active SIBs in both South America and Africa in the selected timespan, there are no papers written in these area in the timespan considered, according to the SIB database.2 Italy, however, shows the converse. Many papers on SIBs have been written in Italy, but there no SIBs were developed there in the selected time period. In 2016, Bengo and Calderini wrote about a possible roadmap for SIBs in Italy, considering SIBs a potential tool for the public sector, and wrote “[…] the SIB model could be a solution to welfare and public service funding in Italy”. Before September 2019, only one feasibility study on SIBs had been conducted nationally, and that was in the city of Turin. The reasoning for this may be contextual, influenced by legal and accounting issues, and related to a general mistrust in government–government relations (Corvo and Pastore 2019). 2.3.3

Finding 3: Authors Distribution by Cluster

We conducted an inter-cluster analysis to assess whether some authors publish papers which align with different clusters. We found 18 repetitions. When an author is found in the same “sentiment”, either pessimistic or optimistic, we assigned them the tag “coherence”. Where authors changed sentiment, there were tagged “incoherent”. In particular, we found 12 papers written by coherent authors and 6 written by noncoherent authors. The six non-coherent authors show two common characteristics: – They all started from an optimistic cluster and ended in a pessimistic one; – At first, they considered SIB to be a good tool for allocating risk. For instance, Gosling argues that it is “vital that politicians, practitioners, academics and service users come together to develop a clear, informed rationale that can explain why PbR is the right commissioning model [in] the transforming rehabilitation agenda” (Gosling

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2016). Usually, the pessimistic sentiment is linked to the doubt that SIBs are used to finance “neo-liberal” activities rather than addressing structural conditions that have led to specific social problems (Dowling 2017) or a doubt that SIBs, and payments-by-results (henceforth, PbR) in general, can transform social problems in a financial market (Gosling 2018). Coherent authors are all in the cluster public optimistic. Only two remained optimistic throughout their research, but they explored the impacts in both PSR and FSR. 2.3.4

Finding 4: Keywords, Clusters and Sources

Bibliometrix allowed us to conduct document mapping and to create a three fields plot of the characteristics of the documents that we wanted to examine. We created two different plots: the first one aimed to investigate the relations between author’s keywords, clusters and journals

Fig. 2.5 Three fields plot of author’s keywords, clusters and journals

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(Fig. 2.5); and the second connected author’s keywords, clusters and countries (Fig. 2.6). To create this plot, we cleared the database of keywords that were considered tautological like social impact bonds and SIBs. Closer examination of the first plot (Fig. 2.5) reveals that specific journals had a strong link to sentiments regarding SIBs. Voluntas, for instance, publishes papers from pessimistic narratives while China Nonprofit Review only includes papers with an optimistic narrative. Journals related to health issues, such as Health Affairs or Global Health Action, have an optimistic orientation. Certain words tend to appear more frequently in particular clusters. “Crisis” is used in optimistic clusters while “austerity” and “neoliberalism” are more commonly found in pessimistic clusters. Other words are strictly connected to the topic of the narrative, “welfare” and “service”, for example, are used in the public narrative, while “venture philanthropy” or “enterprise” are used by the finance narrative. In the second plot (Fig. 2.6), we find that many papers are written in Anglo-Saxon regions as we found earlier when analysing the countries collaboration map. These were the countries where SIBs started (UK 2010), therefore the debate is more detailed and is based on analysis from

Fig. 2.6 Three fields plot of author’s keywords, clusters and countries

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SIBs in practice. Quantitative data, however, is not yet available. Despite efforts, by the Oxford Government Outcome Lab (henceforth, GoLab) and others, a complete database of information on the functioning of SIBs in terms of outcome reached, savings generated, and return for the sponsor of the activity has not yet been acquired.3 Most of the countries are present in the public optimistic cluster, though Vietnam, Korea, Taiwan and Greece have only presented financial optimistic data. Both the financial and public pessimist narratives are present in countries where SIBs are already developed such as the USA, the UK, Canada, Australia, the Netherlands and Germany. 2.3.5

Finding 5: Intra Cluster Streams

In our data analysis, we decided to investigate intra-cluster dynamics and wanted to find any correlation between authors within each cluster. To run this analysis, we used the function of “Historiograph” on Bibliometrix that allowed us to identify whether an author is citing another author of the same cluster. Our findings are shown in Fig. 2.7. The only cluster that did not show any influences between authors with the same cluster was 2 (financial optimistic) which had no in-cluster citations.

Fig. 2.7 Intra cluster streams

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In the Financial Pessimistic cluster, there were two streams—“empirical” that connected Glänzel and Scheuerle (2016) with Schrötgens and Boenigk (2017), and “theory” which connects Dey and Gibbon (2018) with other authors. The “empirical stream” includes papers that focus on the financial market conducting interviews or online surveys focused on Germany’s financial sector. Most of these papers were published on Voluntas. The “theory stream” is characterised by the presence of a literature review (Dey and Gibbon 2018) that focused on different aspects of “financialization of welfare”. In the third cluster (Public Pessimistic) we can identify, as shown in the Fig. 2.7, two streams: 1. The first one connects Warner’s research (2013) with three different papers that further developed different themes around SIBs. The work of Giacomantonio (2017) is based on a decision tree regarding the use of SIBs and shows the “Paradox of SIBs”. The second paper shows the difficulties in reconciling accountability goals with the aim of an Environmental Impact Bond (Balboa 2016). The third paper shows the risk that outcome-based contracting in co-production can negatively affect equality, effectiveness and innovation within public services (Farr 2016). As we can see from these results, all the papers linked to Warner’s work highlights, the problems that can arise when using an outcome-based contract, like SIBs, in providing public services, and the different ways in which these problems occur. 2. The second stream, identifiable in the Public Pessimistic cluster, connects papers that focused on the UK government and corresponding challenges in the use of SIBs, considering whether the adoption of SIBs is a risk or an opportunity. Within the Public Optimistic cluster, we found four different streams, all of which are focused on different services that can be funded with SIBs or other Outcome-Based Contracts. The most relevant streams in our opinion are the first (Temple– Reynolds) and the third (Fitzgerald–Lantz–Sorensen). The first stream focuses on early childhood programmes that can be profitably funded by SIBs. The third stream focused on the application of SIBs in preventative health.

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The remaining two streams either discussed SIBs more generally and the role that innovation has in capitalism (Shiller 2013), or they provided strategies of de-paradoxification (Maier et al. 2017). De-paradoxification is defined as the set of possible pathways that may be used by SIBs in different contexts where there are no pre-existing SIBs (Bengo and Calderini 2016).

2.4 Conclusion, Limitations and Ideas for Future Research In this chapter, we present our suggestions for future research and summarise our analysis. Before we do this, we detail the limitation of our study, which are as follows. The first limitation arises from the manual setting of the cluster. There was no software support in selecting the category of cluster for each paper, this might lead to a possible misunderstanding of the sentiment of the paper, and thus allocate it to the wrong category. This limitation is in some way mitigated by the identification of intra-cluster streams at the start of our study, and our finding links between different authors in the same cluster. The second limitation of the present study is in the number of databases investigated. Unlike Fraser et al. (2016), we only largely investigated two databases. We did this to be able to use Bibliometrix for our analysis, but we understand that this may have introduced an additional bias into the study. A third limitation is related to the range of documents we studied. By excluding all documents that relate to grey literature, we limited the number of documents that could be analysed, though this also allowed us to focus our research to academic literature only. A possible extension of our study would be to replicate the bibliometric analysis using grey literature. Having outlined our three key limitations, we now come to the final step of our workflow (5. Interpretation), summarise our analysis and conclude with three patterns that we have identified through this study. Firstly, we notice that existing literature is more oriented towards an optimistic consideration of the SIBs, both in financial and in publicorientated studies. Governments are being motivated to find a range

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of outcome-based contract schemes to provide services even without the presence of an investor. At the same time, private actors (particularly social enterprises) are encouraged to increase their financial knowledge in order to be able to co-create and develop SIBs. The second pattern we notice is that there is growing interest in SIBs and the benefits they offer private actors. Finance is diversifying to have increasingly varied roles as their traditional functions are increasingly negatively impacted by the world financial crisis. Thirdly, we have seen that there is still a lack of data about outcomes reached and savings generated, which could reinforce a positive view of SIBs. GoLaB is building a comprehensive SIB database, but this will take time to compile. In the meantime, there is good quality data on SIBs available for individual study. Based on these patterns that we have found, we advise academics interested in researching social finance, accounting, public policy to follow our suggested future research agenda. Firstly, there is a need to add to the body of literature on SIBs internationally. There are limited quantitative studies, which means that it is difficult to assess whether the optimistic or pessimistic consideration of SIBs is more justified. Both the GoLab project database and the Portuguese platform One Value (https://onevalue.gov.pt/?) as well as other initiatives around the world are developing methods for collecting data on outcome-based schemes in order to better understand SIBs globally and with the public saving perspective. Secondly, research into procurement and the evolution of coproduction paradigms may be helpful as there are currently very few studies into either of these areas. We anticipate that the financial optimistic perspective will be further studied, and we expect that studies on financial convenience of SIBs will be supported by increasing empirical evidence, and that this will drive the creation of new tools used to measure the results.

Notes 1. https://thegiin.org/impact-investing/.

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2. https://sibdatabase.socialfinance.org.uk/. 3. https://golab.bsg.ox.ac.uk/knowledge-bank/project-database/.

Appendix A---List of Papers Per Cluster Cluster 1—Financial Pessimistic Approach 1. Dey, C., & Gibbon, J. (2018). New development: Private finance over public good? Questioning the value of impact bonds. Public Money & Management, 38(5), 375–378. 2. Castellas, E. I. P., Ormiston, J., & Findlay, S. (2018). Financing social entrepreneurship: The role of impact investment in shaping social enterprise in Australia. Social Enterprise Journal, 14(2), 130– 155. 3. Schrötgens, J., & Boenigk, S. (2017). Social impact investment behavior in the nonprofit sector: First insights from an online survey experiment. VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations, 28(6), 2658–2682. 4. Dowling, E. (2017). In the wake of austerity: Social impact bonds and the financialisation of the welfare state in Britain. New Political Economy, 22(3), 294–310. 5. Kish, Z., & Leroy, J. (2015). Bonded life: technologies of racial finance from slave insurance to philanthrocapital. Cultural Studies, 29(5–6), 630–651. 6. Dagher Jr, P. G. (2012). Social Impact Bonds and the Private Benefit Doctrine: Will Participation Jeopardize a Nonprofit’s TaxExempt Status. Fordham L. Rev., 81, 3479. 7. Cooper, C., Graham, C., & Himick, D. (2016). Social impact bonds: The securitization of the homeless. Accounting, Organizations and Society, 55, 63–82. 8. Glänzel, G., & Scheuerle, T. (2016). Social impact investing in Germany: Current impediments from investors’ and social entrepreneurs’ perspectives. VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations, 27 (4), 1638–1668. 9. Berry, J. M. (2016). Negative returns: The impact of impact investing on empowerment and advocacy. PS: Political Science & Politics, 49(3), 437–441.

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10. Joy, M., & Shields, J. (2013). Social impact bonds: The next phase of third sector marketization? Canadian journal of nonprofit and social economy research, 4(2). Cluster 3—Financial Optimistic Approach 1. Lieberman, D. L. (2018). Hedge Funds and Impact Investing: Considerations for Institutional Investors. The Journal of Investing, 27 (2), 47–55. 2. Neyland, D. (2018). On the transformation of children at-risk into an investment proposition: A study of Social Impact Bonds as an anti-market device. The Sociological Review, 66(3), 492–510. 3. Zheng, S. (2018). Investigation into Funding Strategies of Social Enterprises. The China Nonprofit Review, 10(1), 34–61. 4. Apostolakis, G., van Dijk, G., Kraanen, F., & Blomme, R. J. (2018). Examining socially responsible investment preferences: A discrete choice conjoint experiment. Journal of Behavioral and Experimental Finance, 17 , 83–96. 5. Rizzi, F., Pellegrini, C., & Battaglia, M. (2018). The structuring of social finance: Emerging approaches for supporting environmentally and socially impactful projects. Journal of cleaner production, 170, 805–817. 6. Arena, M., Bengo, I., Calderini, M., & Chiodo, V. (2018). Unlocking finance for social tech start-ups: Is there a new opportunity space? Technological Forecasting and Social Change, 127 , 154–165. 7. Fischer, R. L., & Richter, F. G. C. (2017). SROI in the pay for success context: Are they at odds? Evaluation and program planning, 64, 105–109. 8. Kim, J. (2018). Social Finance Funding Model for Animal Shelter Programs: Public–Private Partnerships Using Social Impact Bonds. Society & Animals, 26(3), 259–276. 9. Qu, H., & Osili, U. (2017). Beyond Grantmaking: An Investigation of Program-Related Investments by US Foundations. Nonprofit and Voluntary Sector Quarterly, 46(2), 305–329. 10. Bloom, B. E. (2015). Creating new economic incentives for repurposing generic drugs for unsolved diseases using social finance. Assay and drug development technologies, 13(10), 606–611.

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11. Schinckus, C. (2018). The valuation of social impact bonds: An introductory perspective with the Peterborough SIB. Research in International Business and Finance, 45, 1–6. 12. Aggarwala, R. T., & Frasch, C. A. (2017). The Philanthropy As One Big Impact Investment: A Framework For Evaluating A Foundation’s Blended Performance. The Foundation Review, 9(2), 13. 13. Smeets, D. J. A. (2017). Collaborative learning processes in social impact bonds: a case study from the Netherlands. Journal of Social Entrepreneurship, 8(1), 67–87. 14. Gripne, S. L., Kelley, J., & Merchant, K. (2016). Laying the Groundwork for a National Impact Investing Marketplace. The Foundation Review, 8(5), 8. 15. Peterson, G. (2016). Partnering for Impact: Developing The McKnight Foundation’s Carbon Efficiency Strategy. The Foundation Review, 8(3), 9. 16. Apostolakis, G., Kraanen, F., & van Dijk, G. (2016). Pension beneficiaries’ and fund managers’ perceptions of responsible investment: a focus group study. Corporate Governance: The international journal of business in society, 16(1), 1–20. 17. Höchstädter, A. K., & Scheck, B. (2015). What’s in a name: An analysis of impact investing understandings by academics and practitioners. Journal of Business Ethics, 132(2), 449–475. 18. Ormiston, J., Charlton, K., Donald, M. S., & Seymour, R. G. (2015). Overcoming the challenges of impact investing: Insights from leading investors. Journal of Social Entrepreneurship, 6(3), 352–378. 19. Lyons, T. S., & Kickul, J. R. (2013). The social enterprise financing landscape: The lay of the land and new research on the horizon. Entrepreneurship Research Journal, 3(2), 147–159. 20. Humphries, K. W. (2013). Not your older brother’s bonds: the use and regulation of social-impact bonds in the United States. Law & Contemp. Probs., 76, 433. 21. Langford, A. R. (2011). Social impact bonds in canada: From theory to implementation. 22. Liang, M., Mansberger, B., & Spieler, A. C. (2014). An overview of social impact bonds. J. Int’l Bus. & L., 13, 267. 23. Moore, M. L., Westley, F. R., & Nicholls, A. (2012). The social finance and social innovation nexus.

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Cluster 3—Public Pessimistic Approach 1. Joy, M., & Shields, J. (2018). Austerity in the making: reconfiguring social policy through social impact bonds. Policy & Politics, 46(4), 681–695. 2. Wiggan, J. (2018). Policy boostering the social impact investment market in the UK. Journal of Social Policy, 47 (4), 721–738. 3. Overholser, G. M. (2018). Pay for success is quietly undergoing a radical simplification. The ANNALS of the American Academy of Political and Social Science, 678(1), 103–110. 4. Gosling, H. (2018). A critical insight into practitioners’ lived experience of payment by results in the alcohol and drug treatment sector. Critical Social Policy, 38(2), 244–261. 5. Edmiston, D., & Nicholls, A. (2018). Social Impact Bonds: the role of private capital in outcome-based commissioning. Journal of Social Policy, 47 (1), 57–76. 6. Mitchell, K. (2017). Metrics millennium: Social impact investment and the measurement of value. Comparative European Politics, 15(5), 751–770. 7. Michelucci, F. V. (2017). Social impact investments: does an alternative to the Anglo-Saxon paradigm exist? Voluntas: International Journal of Voluntary and Nonprofit Organizations, 28(6), 2683–2706. 8. Pauly, M. V., & Swanson, A. (2017). Social impact bonds: New product or new package? The Journal of Law, Economics, and Organization, 33(4), 718–760. 9. Farr, M. (2016). Co-production and value co-creation in outcomebased contracting in public services. Public Management Review, 18(5), 654–672. 10. Kuklinski, M. R. (2015). Benefit-Cost Analysis of Prevention and Intervention Programs for Youth and Young Adults: Introduction to the Special Issue. Journal of Benefit-Cost Analysis, 6(3), 455– 470. 11. Alessandrini, D., & Jivraj, S. (2017). Conceptualising the Economy-Society Nexus in Well-Being and Happiness Initiatives: Gross National Happiness in Business in Bhutan and Social Impact Bonds in the United Kingdom. International Critical Thought, 7 (4), 526–546.

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12. Dadush, S. (2015). Regulating Social Finance: Can Social Stock Exchanges Meet the Challenge. U. Pa. J. Int’l L., 37 , 139. 13. Giacomantonio, C. (2017). Grant-maximizing but not moneymaking: A simple decision-tree analysis for social impact bonds. Journal of Social Entrepreneurship, 8(1), 47–66. 14. Warner, M. E. (2013). Private finance for public goods: social impact bonds. Journal of economic policy reform, 16(4), 303–319. 15. Rowe, R., & Stephenson, N. (2016). Speculating on health: public health meets finance in ‘health impact bonds’. Sociology of health & illness, 38(8), 1203–1216. 16. Balboa, C. M. (2016). Accountability of environmental impact bonds: the future of global environmental governance? Global Environmental Politics, 16(2), 33–41. 17. Deering, J. (2014). A future for probation? The Howard Journal of Criminal Justice, 53(1), 1–15. 18. Demel, A. (2012). Second thoughts on social impact bonds. NYUJL & Bus., 9, 503. 19. Lake, R. W. (2015). The financialization of urban policy in the age of Obama. Journal of Urban Affairs, 37 (1), 75–78. 20. Warner, M. (2012, September). Profiting from public value? The case of social impact bonds. In conference Creating Public Value in a Multi-Sector, Shared-Power World, University of Minnesota (pp. 20–22). Cluster 4—Public Optimistic Approach 1. Aschari-Lincoln, J., & Jacobs, C. D. (2018). Enabling Effective Social Impact: Towards a Model for Impact Scaling Agreements. Sustainability, 10(12), 4669. 2. Maier, F., Barbetta, G. P., & Godina, F. (2018). Paradoxes of social impact bonds. Social Policy & Administration, 52(7), 1332–1353. 3. Lehoux, P., Pacifico Silva, H., Pozelli Sabio, R., & Roncarolo, F. (2018). The Unexplored Contribution of Responsible Innovation in Health to Sustainable Development Goals. Sustainability, 10(11), 4015. 4. Todd Young, S. (2018). Generating and Using Evidence Will Help to Reduce Social Problems. The ANNALS of the American Academy of Political and Social Science, 678(1), 194–198.

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5. Lantz, P. M., Miller, G., Rhyan, C. N., Rosenbaum, S., Ku, L., & Iovan, S. (2018). “Pay for Success” Financing and Home-Based Multicomponent Childhood Asthma Interventions: Modeling Results From the Detroit Medicaid Population. The Milbank Quarterly, 96(2), 272–299. 6. Gladilin, A. A., Glotova, I. I., Tomilina, E. P., Klishina, Y. E., & Uglitskikh, O. N. (2018). Social Bonds As A Tool For Financing Higher Education. Research Journal of Pharmaceutical Biological and Chemical Sciences, 9(3), 724–727. 7. Berndt, C., & Wirth, M. (2018). Market, metrics, morals: The Social Impact Bond as an emerging social policy instrument. Geoforum, 90, 27–35. 8. Pandey, S., Cordes, J. J., Pandey, S. K., & Winfrey, W. F. (2018). Use of social impact bonds to address social problems: Understanding contractual risks and transaction costs. Nonprofit Management and Leadership, 28(4), 511–528. 9. Ramsay, I., & Tan, C. (2018). Social Impact Bonds in Australia. Journal of Banking and Finance Law and Practice, 29(3), 248– 257. 10. Myers, R. R., & Goddard, T. (2018). Virtuous profits: Pay for success arrangements and the future of recidivism reduction. Punishment & Society, 20(2), 155–173. 11. Mangram, M. E. (2018). “Just Married”—Clean Energy and Impact Investing: A New ‘Impact Class’ and Catalyst for Mutual Growth. The Journal of Alternative Investments, 20(4), 36–50. 12. Appel, T., Bezak, B., & Lisle, J. (2017). DC Water Green Infrastructure Financing: Pay for Success Can Help Water Utilities Pursue Innovative Solutions. Journal-American Water Works Association, 109(10), 26–31. 13. Steverman, S. M., & Shern, D. L. (2017). Financing mechanisms for reducing adversity and enhancing resilience through implementation of primary prevention. Academic pediatrics, 17 (7), S144–S149. 14. Reynolds, A. J., Hayakawa, M., Ou, S. R., Mondi, C. F., Englund, M. M., Candee, A. J., & Smerillo, N. E. (2017). Scaling and sustaining effective early childhood programs through school– family–university collaboration. Child development, 88(5), 1453– 1465.

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15. Sorensen, G., Nagler, E. M., Pawar, P., Gupta, P. C., Pednekar, M. S., & Wagner, G. R. (2017). Lost in translation: The challenge of adapting integrated approaches for worker health and safety for low-and middle-income countries. PloS one, 12(8), e0182607. 16. Choudhary, R., & Jain, V. (2017). Social Impact Bonds: An Innovative Way for Social Financing. Pacific Business Review International, 9(10), 120–126. 17. Schinckus, C. (2017). Financial innovation as a potential force for a positive social change: The challenging future of social impact bonds. Research in International Business and Finance, 39, 727– 736. 18. Lantz, P. M., Rosenbaum, S., Ku, L., & Iovan, S. (2016). Pay for success and population health: Early results from eleven projects reveal challenges and promise. Health Affairs, 35(11), 2053–2061. 19. Bengo, I., & Calderini, M. (2016). New development: Are social impact bonds (SIBs) viable in Italy? A new roadmap. Public Money & Management, 36(4), 303–306. 20. Gosling, H. (2016). ‘All this is about is money and making sure that heads are on beds’ Perceptions of payment by results in a therapeutic community. Probation Journal, 63(2), 144–152. 21. Allen, L. N. (2017). Financing national non-communicable disease responses. Global health action, 10(1), 1326687. 22. Bloom, B. E. (2016). The trials and tribulations of repurposing metformin and other generic drugs for tuberculosis. Pharmaceutical patent analyst, 5(2), 101–105. 23. Fölster, S. (2017). Viral mHealth. Global health action, 10(sup3), 1336006. 24. Wang, Y. (2015). Development of Social Finance in China. The China Nonprofit Review, 7 (2), 290–320. 25. Galloway, I. (2014). Using pay-for-success to increase investment in the nonmedical determinants of health. Health Affairs, 33(11), 1897–1904. 26. Dowling, E., & Harvie, D. (2014). Harnessing the social: State, crisis and (big) society. Sociology, 48(5), 869–886. 27. Crowley, D. M. (2014). The role of social impact bonds in pediatric health care. Pediatrics, 134(2), e331–e333. 28. Nies, H. (2014). Communities as co-producers in integrated care. International Journal of Integrated Care, 14.

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29. Baliga, S. (2013). Shaping the success of social impact bonds in the United States: Lessons learned from the privatization of US prisons. Duke Law Journal, 437–479. 30. Fitzgerald, J. L. (2013). Social impact bonds and their application to preventive health. Australian Health Review, 37 (2), 199–204. 31. Atun, R., Silva, S., Ncube, M., & Vassall, A. (2016). Innovative financing for HIV response in sub–Saharan Africa. Journal of global health, 6(1). 32. Romanova, O. G. A., Akberdina, V. V., & Bukhvalov, N. Y. E. (2016). Shared Values in the Formation of a Modern TechnoEconomic Paradigm. Economic and Social Changes: Facts, Trends, Forecast, (3), 173–190. 33. Bishop, M., & Green, M. (2015). Philanthrocapitalism rising. Society, 52(6), 541–548. 34. Temple, J. A., & Reynolds, A. J. (2015). Using benefit-cost analysis to scale up early childhood programs through pay-for-success financing. Journal of benefit-cost analysis, 6(3), 628–653. 35. Shiller, R. J. (2013). Capitalism and financial innovation. Financial Analysts Journal, 69(1), 21–25. 36. Fox, C., & Albertson, K. (2011). Payment by results and social impact bonds in the criminal justice sector: New challenges for the concept of evidence-based policy? Criminology & Criminal Justice, 11(5), 395–413. 37. Burand, D. (2012). Globalizing social finance: How social impact bonds and social impact performance guarantees can scale development. NYUJL & Bus., 9, 447. 38. Cox, B. R. (2011). Financing homelessness prevention programs with social impact bonds. Rev. Banking & Fin. L., 31, 959. 39. Dodd, J. A., & Moody, R. (2011). Outcomes, not process: Towards a new model for European funding in an age of austerity. Journal of Contemporary European Research, 7 (1), 120–128. 40. Fox, C., Albertson, K., & Warburton, F. (2011). Justice reinvestment: Can it deliver more for less? The Howard Journal of Criminal Justice, 50(2), 119–136. 41. Fox, C., & Albertson, K. (2012). Is payment by results the most efficient way to address the challenges faced by the criminal justice sector? Probation Journal, 59(4), 355–373.

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42. Jackson, E. T. (2013). Evaluating social impact bonds: questions, challenges, innovations, and possibilities in measuring outcomes in impact investing. Community Development, 44(5), 608–616. 43. Stoesz, D. (2014). Evidence-based policy: Reorganizing social services through accountable care organizations and social impact bonds. 44. Haffar, T. (2014). Communicating Value in Social Impact Bonds: The Role Of The Intermediary.

Appendix B: Cluster Description of the Research Sample Compared with Fraser Sample Cluster

Present work (N. Share per cluster Fraser et Al. of documents) (Present Work) (%) (N. of documents)

Share per cluster (Fraser et Al.) (%)

Financial Pessimistic Financial Optimistic Public Pessimistic Public Optimistic Total

7

10.14

2

7.14

18

26.09

6

21.43

15

21.74

5

17.86

29

42.03

15

53.57

69

100

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100

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Moore, M. L., Westley, F. R., & Nicholls, A. (2012). The social finance and social innovation nexus. Journal of Social Entrepreneurship, 3(2), 115–32. Nicholls, A. (2010). The functions of performance measurement in social entrepreneurship: Control. Planning and Accountability. https://doi.org/10. 1057/9780230298026_13. Nicholls, A., & Murdock, A. (2012). The nature of social innovation. In A. Nicholls & A. Murdock (Eds.), Social innovation: Blurring boundaries to reconfigure markets (pp. 1–32). London: Palgrave Macmillan. OECD. (2014). Social impact investment: Building the evidence base. Paris: OECD Publishing. OECD. (2016). Understanding social impact bonds (Working Paper). The OECD LEED Programme. OECD. (2017). Government at Glance. http://www.oecd.org/gov/govatagla nce.htm. OECD netFWD. (2014). Venture philanthropy in development: Dynamics, challenges and lessons in the search for greater impact. Paris: OECD Development Centre. OECD/European Union. (2015). Policy Brief on Social Impact Measurement for Social Enterprises: Office of the European Union, Policies for Social Entrepreneurship. Luxembourg: Publications Program, Brookings Institution, OECD/European Commission. Osborne, S. P. (2009). Debate: Delivering public services: Are we asking the right questions? Public Money & Management, 29(1), 5–7. https://doi.org/ 10.1080/09540960802617269. Osborne, D., & Gaebler, T. (1992). Reinventing government: How the entrepreneurial spirit is transforming government. Reading, MA: Adison Wesley Public Comp. Reynolds, A. J., Hayakawa, M., Ou, S. R., Mondi, C. F., Englund, M. M., Candee, A. J., et al. (2017). Scaling and sustaining effective early childhood programs through school–family–university collaboration. Child Development, 88(5), 1453–1465. Schrötgens, J., & Boenigk, S. (2017). Social impact investment behavior in the nonprofit sector: First insights from an online survey experiment. VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations, 28, 2658. https://doi.org/10.1007/s11266-017-9886-5. Shiller, R. J. (2013). Capitalism and financial innovation. Financial Analysts Journal, 69(1), 21–25. https://doi.org/10.2469/faj.v69.n1.4. Social Investment Task Force. (2010). Social investment ten years on. London: Social Investment Task Force. http://www.makehope.org/wp-content/upl oads/old/1292754218.pdf.

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Schinckus, C. (2018). The valuation of Social Impact Bonds: An introductory perspective with the Peterborough Sib. Research in International Business and Finance, 45, 1–6. https://doi.org/10.1016/J.RIBAF.2017.07.126. Sorensen, G., Nagler, E. M., Pawar, P., Gupta, P. C., Pednekar, M. S., et al. (2017). Lost in translation: The challenge of adapting integrated approaches for worker health and safety for low- and middle-income countries. PLoS ONE, 12(8), e0182607. https://doi.org/10.1371/journal.pone.0182607. Temple, J. A., & Reynolds, A. J. (2015). Using benefit-cost analysis to scale up early childhood programs through pay-for-success financing. Journal of Benefit-Cost Analysis, 6(3), 628. Warner, M. E. (2013). Private finance for public goods: Social impact bonds. Journal of Economic Policy Reform, 16(4), 303–319. Wood, D., Thornley, B., & Grace, K. (2013). Institutional impact investing: Practice and policy. Journal of Sustainable Finance & Investment, 3(2), 75–94. https://doi.org/10.1080/20430795.2013.776256. Zupic, I., & Cater, T. (2015). Bibliometric methods in management and organization. Organizational Research Methods, 18(3), 429–472.

CHAPTER 3

Fighting Poverty and Inequalities Through Social Impact Bonds: Learning from Case Studies to Support the Covid-19 Response Annarita Trotta, Rosella Carè, Rossana Caridà, and Maria Cristina Migliazza

3.1

Introduction

In recent years, social impact bonds (SIBs) have been high on the agenda of researchers, practitioners and policymakers active in the sustainable finance sector. SIBs are a form of pay by results (PbR) model but “extend this by harnessing social investment from capital markets ” (Edmiston and Nicholls 2018: 57). Compared to a PbR scheme, SIBs have many

A. Trotta (B) · R. Caridà · M. C. Migliazza Department of Law, Economics and Sociology, University Magna Graecia of Catanzaro, Catanzaro, Italy e-mail: [email protected] R. Carè Department of Economics and Business, University of Cagliari, Viale S. Ignazio 17, 09125 Cagliari, Italy

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. La Torre and H. Chiappini (eds.), Contemporary Issues in Sustainable Finance, Palgrave Studies in Impact Finance, https://doi.org/10.1007/978-3-030-65133-6_3

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more strengths, including the following: (1) they are a financial model able to channel private capital (from the financial system) into effective social interventions regarding specific and important social issues that are needed for the economic and social development of territories; (2) they encourage the implementation (and not merely a replacement) of the overall resources (public and private) for the welfare areas; (3) they transfer (or reallocate) the risks from the public sector (or in any case from private/third sector subjects) to the operators/subjects (investors/financial intermediaries) of the financial system, who are better equipped to handle the evaluation and management of the same. Therefore, SIBs are one of the pillars of social impact investment approaches, and in the SIB model, the PPP is finalized to address complex social issues. In this vein, investors, intermediaries, social enterprises and policymakers should work together for the success of the project. As stated by Fox and Morris (2019: 2): “SIBs can be understood as a class of PbR commissioning associated with the broader ‘social investment’ movement ”. Among the wider spectrum of PbR models, in more recent years, SIBs represent a unicum and catalyse several interests of multiple actors. Nonetheless, it is necessary to specify that academics and practitioners present polarized positions regarding the usefulness of these tools (Maier and Meyer 2017; Fitzgerald et al. 2020). Several scholars highlight the importance of this financial model (Schinckus 2018), while others point out the practical difficulties faced by attempts to realize tangible benefits from SIB programmes and, above all, on a larger scale (McHugh et al. 2013; Sinclair et al. 2014; FitzGerald et al. 2020). In fact, narrowing the focus on the SIB market, a very small number of SIBs have been launched worldwide, and this empirical evidence clashes with the relevance that these models are assuming in the international debate (Rania et al. 2020). In line with the alternative finance perspectives, SIB programmes represent experimental practices for addressing very important and various social issues (Rania et al. 2020), but it becomes necessary to realize more ex ante considerations of the complex balance of risks, drawbacks and benefits of SIBs and more empirical studies ex post (Fraser et al. 2018: 16) to favour the enabling factors and remove the impeding causes. However, on the theoretical level, in our opinion, it is indisputable that these models

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would provide a significant innovative change in the community’s development and also in advanced economies if only they are able to develop to their potential. This is even more true than before, in view of the COVID-19 emergency that the world is currently facing. A recent work pointed out that the impact of COVID-19 on global poverty could be severe (Sumner et al. 2020) and pose a real challenge to the UN SDG 1 (ending poverty) of the 2030 Agenda. Narrowing the focus on the EU and Italy, Figari and Fiorio (2020: 1) underline that the “downturn due to the Covid-19 pandemic will overshadow European economies for years to come, through a legacy of unemployment, public debt and long-lasting impacts on household incomes as already experienced during the Great Recession”. Focusing on the estimates on the poverty rates in Italy, the authors (2020: 15) emphasize that the breakthrough impact of the pandemic on the poverty status is evident, with an increase (estimated) in the poverty rate of more than 8 percentage points. SIBs could be practical tools that are useful for fighting old and new poverty and inequality forms, even in advanced economies, such as the European Union (EU), and especially in regions (such as South Italy) characterized by persistently high unemployment rates and/or high absolute poverty rates. Considering the efforts that the EU is pursuing for implementing a framework to support sustainable finance practice development and taking into account the Italian socio-economic context (see Sect. 3.2.2), Italy could become a laboratory of good practices (of impact investing instruments, even those arranged to be connected) that are useful to support socio-economic responses to COVID-19 for other European countries (such as Spain, Portugal, Greece, etc.). Moving on from these considerations, this chapter proposes an exploratory analysis, focusing on the “critical” practices of SIBs that are launched for addressing issues of poverty (also in advanced economies) and socio-economic inequalities, with the aim of exploring the key elements for scaling up these practices. The contribution of our work is threefold. First, it contributes to the international debate, exploring the role of SIBs in addressing poverty and socio-economic inequalities and introducing interesting stimuli for a wider debate regarding the post COVID-19 era. Then, it sheds light on the use of SIBs as effective tools

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for reducing poverty and inequality, an important area that has the opportunity to replicate mutatis mutandis these innovative financial models on a larger scale, in the UE and especially in some countries highly impacted by the COVID-19 emergency, with a focus on Italy. Third, by using the main evidence emerging from the case study analysis, a series of insights and suggestions for the implementation of pilot projects of SIBs as a concrete response to the socio-economic effects of the pandemic are provided. The remainder of the work is organized as follows. Section 3.2 provides a literature review of SIBs (and, more generally, PbR schemes) to identify the main dimensions of the case study analysis and proposes a snapshot of the European scenario, with a focus on the Italian legislative context for SIB development. Section 3.3 depicts the research design, method, and data collection used in this study. Section 3.5 illustrates the selected case studies. Then, Sects. 3.6 and 3.7 examine the main findings, providing a framework for an ecosystem for SIB development. Finally, Sects. 3.8 and 3.9 conclude with some suggestions for a realistic agenda for developing SIB models in Italy, in the post COVID-19 era.

3.2 3.2.1

Background

Social Impact Bonds: A Thematic Perspective

In this section, we examine various thematic aspects related to SIBs (and more generally to PbRs) by reviewing the literature, providing guidelines from past studies and providing a basis for the theoretical framework for the present investigation. A descriptive thematic approach was adopted for synthesizing the research (and their results) from different perspectives. 3.2.1.1

Key Narratives and Approaches Identified Through Literature Reviews on SIBs In their review of academic and grey literature on SIBs, Fraser et al. (2018) identified both a narrative of promise (related to the public sector reform and to the financial sector reform) and a cautionary narrative. The authors analysed these different narratives with regard to the following three fundamental issues: public versus private values, risk allocation and outcome contracting. The studies related to “the narrative of promise” emphasize the potential benefits of SIBs. On the other hand, the works closest to the cautionary narrative shed light on a complex and

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yet underexplored panorama characterized by the potential risks, drawbacks, benefits and alternatives of SIBs. In their review, Broccardo et al. (2020) identify four groups of key benefits, as follows: SIBs are examples of “good finance”; SIB programmes enhance corporate governance in public and private partnerships (PPPs); and SIB models are useful in health care and offer a viable solution for improving prevention and for raising/gaining private funding. Finally, the fourth benefit relates to the contribution of SIBs to the development of evidence-based policies. The review realized by the authors identified the following three persistent issues in the literature: (1) a challenge related to the potential trade-offs inherent to SIBs (e.g.: flexibility/innovation and evidencebased approaches; cost-effectiveness and risk transfer, etc.); (2) a challenge related to the key role of the outcomes; (3) a challenge arises from the financialization of the welfare state. Finally, Fox and Morris (2019) provide an interesting review of the state of the empirical evaluations of both PbR and SIB programmes in the UK. 3.2.1.2 Outcome Metrics and Evaluation Models Fox and Morris (2019: 5) conclude that there is yet a paucity of evaluations of PbR and SIB programmes in the UK and a scarcity of data available. In addition, those that exist are not of a high standard. Often, payments have not been based on results from impact evaluations (but only on meeting performance targets). Although several tools related to evaluation models for social impact have been discussed (e.g. rate cards, randomized controlled trials, outcome metrics, quantitative impact measurement, cost–benefit analysis), the impact measurement of SIB programmes is still very confined in practice. Therefore, evaluation models and outcome metrics issues represent—whether referring to PbR or referring to SIB models—one of the most open questions. Jackson (2013: 608) underlined the need for independent evaluations of the outcomes and impacts. A simplification of the SIB model is centred on outcome-based performance management (Lowe and Wilson 2015). It is necessary to distinguish between the social outcome language and the contractual outcome metrics (which measure a limited evaluation of impact). A recent work by Tse and Warner (2020) focuses on early care and education SIBs across the OECD and concludes that the focus on clients and metrics at the micro-scale fails to achieve broad outcomes and may even narrow social rights, while SIBs that focus on meso and macro-level actors have more opportunity to effect systemic change and

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broaden social rights. On the theoretical level, excessive attention to metrics and measurement could induce opportunism phenomena (by choosing inaccurate measurement systems or metrics excessively aimed at considering the micro-scale), causing a focus on data that will better prove the outcomes. The most common evaluation metrics regarding SIBs can be grouped into different categories, such as randomized control trials, quasi-experimental, matched comparisons, and tariff models (GustafssonWright et al. 2015). Fox and Morris note that virtually all SIBs in the US have been accompanied by a randomized controlled trial, whereas in the UK none have. Regarding the evaluation models of SIBs, recent works have discussed the strengths and weaknesses of the ROIs of SIB programmes (Méndez-Suárez et al. 2020) and the cost–benefit analysis and SROI for evaluating SIBs (Cordes 2017). An interesting analysis by Fischer and García-Cobián Richter (2017) explores in-depth the use of SROI in the pay for success context, with illustrations from an SIB initiative underway that is focused on homeless families with children in foster care. 3.2.1.3 Social Uncertainty, Risks and Pricing of SIBs In more recent years, many studies have focused on SIBs as financial assets and on investor expectations/perspectives (Brandstetter and Lehner 2015). In this regard, Schinckus (2018) proposes the development of a pricing method for this type of financial asset in an uncertain environment. By using a statistical technique for converting objective probabilities into subjective estimates, the author investigates a specific way of integrating the uncertainty related to the valuation of SIBs. Starting from a model for measuring social uncertainty/risks in SIB models, a recent work (Rania et al. 2020) proposes an original model to evaluate the social uncertainty of SIB programmes. Regarding the rate of returns of SIBs, it is worth noting that data are very limited at the moment. As stated by Hajer (2020: 119), “what data are available suggests that projected rates of return are well above government borrowing rates and, for the most part, investors are being repaid”. In the article, the author noted that the work (Hajer 2018) explores 36 SIB projects in which repayment status had been identified. Among these, 32 had either repaid investors in full or were on track for repayment based on available public reports. In addition, Hajer (2020: 119) underlines that “for projects that self -reported expected and maximum annualized rates of return, the averages were 6.0 and 8.8 per cent respectively”. However,

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currently, very few analyses focus on these issues. In this regard, Fox and Morris (2019: 5) pointed out that “the impact is implicitly assumed”. These aspects represent the paradox of impact investing (O’Flynn and Barnett 2017) and the paradoxes of SIBs (Giacomantonio 2017; Maier et al. 2018). 3.2.1.4 Innovativeness of SIBs and New Frameworks Several scholars underlined the innovativeness of SIBs for (1) social enterprises, considering that the development of SIBs could represent an important new approach to funding (Bugg-Levine et al. 2012); (2) the public sector, in which SIB models also represent a novel development in the approach to the mixed economy of welfare (Edmiston 2016); (3) financial intermediaries, considering that SIBs represent several opportunities for realizing innovative business practices, asset diversification and financially sustainable practices (Black 2016; de Mariz and Savoia 2018). In this vein, a recent work by Albertson et al. (2020: 1) suggests an innovative supporting theory that focuses on the integration of the New Public Governance (NPG) perspective (Osborne 2018; Fox et al. 2019; Wooldridge et al. 2019) with elements of open innovation 2.0 and social innovation (Gustafsson-Wright et al. 2015). More specifically, open innovation 2.0—and its innovation processes, which place emphasis on mixed economy collaborations involving the quadruple helix (industry, government, universities and communities)—appears to be a very interesting lens to understand the potential of SIBs. The authors (2020: 7–8) outline some different methods for future SIB development, including the social investment partnerships à la Jupp (2017), that might provide a more inclusive framework within which to accommodate user and community voices in co-creative processes. Another method might include the possibility of crowdsourcing funds to democratize the investment side of the SIB or micro-financing interventions. 3.2.1.5

Collaborations, Contractual Schemes, and Business Models for Sustainability In SIB schemes, investors, intermediaries, social enterprises and policymakers should work together (overcoming the problems of the alignment of interests) for the success of the project. SIB models go beyond classic PPP, both in terms of the different objectives to be achieved (infrastructure versus social issues) and in terms of the wider variety of operators/counterparties involved. Currently, the SIB partnerships are

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beginning to be analysed from different perspectives (Eames et al. 2014; Loxley and Hajer 2019; Vecchi and Casalini 2019). More specifically, SIBs also represent an innovative formula for sustainable business models (La Torre et al. 2019) and blended business models (UN Global Compact 2019). Finally, Méndez-Suárez et al. (2020: 2) emphasize the key role of SIBs in reducing poverty and inequality and executing partnerships in light of Agenda 2030. 3.2.1.6 Empirical Analysis and Case Studies About SIBs A series (still limited) of studies dedicated to the empirical analysis of SIBs is beginning to form (see, among others: Tomkinson 2013; Trotta et al. 2015; Chiodo et al. 2015; Smeets 2017; Del Giudice and Migliavacca, 2019). Some works focus on the linkages between SIBs and poverty and inequality issues. Among these, there is a strand of research that focuses on the development impact bonds realized in low- and middle-income countries (see Burand 2013; Sinclair et al. 2014; Drew and Clist 2015; Gustafsson-Wright and Gardiner 2016; Canning 2017; Albertson and Fox 2018; Clarke et al. 2018; Alenda-Demoutiez 2019). Case studies, best practices and examples of SIB projects are analysed in several ways and from several perspectives, focusing on homelessness, child poverty and labour reintegration of disadvantaged people (Dagher 2013; Malcolmson 2014; Gillespie et al. 2017; Neyland 2018; Aldridge 2020; Tse and Warner 2020). Often, in these cases, the analysis of SIBs crosses with the strand of literature on SIBs as emerging social policy instruments (Berndt and Wirth, 2018). 3.2.1.7 Recent Special Issues About SIBs and Open Questions Especially after 2018, a growing number of works on SIBs have been realized. Among others, in 2020, a Public Money and Management Issue was published. In addition, a special issue of the Journal of Comparative Policy Analysis identified the following five big questions about SIBs that do not yet have satisfactory answers: (1) What are the administrative or political problems to which SIBs respond? (2) Where and why do SIBs emerge in particular contexts? (3) What is the role of SIBs in the evidence-based policy movement? (4) Is delivering an intervention through an SIB more effective than other means and are associated costs justifiable? (5) Do SIBs catalyse wider organizational, system, or institutional changes? (FitzGerald et al. 2020: 85)

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In summary, several themes emerge as relevant in the SIB literature. The research field is nascent and novel and needs both expansion and refinement. There exist challenging opportunities to keep developing this topic. According to the best doctrine, SIBs are good examples of how finance and financiers can contribute to attaining society’s goals (Shiller 2013), at least in theory. This belief leads us to emphasize that this financial tool’s potential motivates us to perform exploratory studies to understand how to encourage SIB development. 3.2.2

Prospects for Impact Finance Development in the EU Scenario

In more recent years, the European Commission (EC) has prioritized advances in sustainable finance, realizing a sustainable finance action plan and establishing principles regarding positive impact finance (UN Environment Finance initiative 2017; High-Level Expert Group 2018). In this vein, several EU countries (including Italy) are trying to create prerequisites and conditions for an ecosystem for the development of impact finance and social innovation. In April 2020, the EC launched a discussion regarding its renewed sustainable finance strategy. Several impact investing instruments (even arranged to be connected) could be useful to support the European economy in the current juncture and in future years. More specifically, there are many EU frameworks that support microcredit initiatives, crowdinvesting models and SIB schemes, with the aim of fostering the evolution of the impact investing landscape. Among others, it is worth mentioning the European Fund for Strategic Investments (EFSI), which is the central pillar of the European Commission’s Investment Plan for Europe (so-called “Juncker Plan”). Then, the European Investment Fund (EIF), which is part of the European Investment Bank Group, has the mission of supporting Europe’s micro, small and medium-sized businesses (SMEs) by helping them access finance. EIF designs and develops venture and growth capital and guarantees and provides microfinance instruments that specifically target this market segment. Finally, the Employment and Social Innovation (EaSI) programme is a financing instrument at the EU level to combat social exclusion and poverty and improve working conditions. The European context appears ready for the development of complex impact investing tools, such as social impact bonds. In this vein, even if there are no concrete SIB experiences to date in Italy, the Italian context has had experience with best practices for financial models of social finance (such as

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microfinance and microcredit initiatives) and, more recently, it has been experimenting with a formula that includes impact investing (such as impact funds and equity crowdfunding). Therefore, the context could be mature for experimenting with SIB models. In 2017, a feasibility study was proposed (Corvo and Pastore 2019) to reintegrate inmates into the labour market (the pilot phase involved a target population of 100 inmates in Turin, Piemonte), but it has not yet been launched. However, this experience is reported as a remarkable example of innovative financial instruments useful for making social impact (and to the potential of the EFSI) by Franke et al. (2018). It is important to underline the launch and the development of a project (started in 2016, with the Acronym: AlpSib), in which the lead partner organization is the Municipality of Pordenone (Italy). In 2014, Italy approved a law on international cooperation to allow for funding based on public–private partnerships, making it easier to implement impact investment (Social Impact Investment Taskforce 2014: 65). In 2016, the “Social Impact Agenda per l’Italia” (as a continuation of the Social Impact Investment Italian Taskforce) was born to represent the Italian network for impact investing and participating in the Global Steering Group for Impact Investing (in continuum with the experience of the Social Impact Investment Taskforce). In addition, many research centres were founded (e.g. Tiresia, Polytechnic of Milan), and more recently, in Piemonte (North Italy), the Turin Social Impact Project—a fast-growing ecosystem for social entrepreneurship and impact investors—was launched. Finally, in 2019, the Presidency of the Counter of the Ministers launched the Italian Fund for social innovation. A roadmap, including barriers and opportunities, to support the development of SIBs in Italy was proposed in Bengo and Calderini (2016: 303). Many comments regarding the Italian legislative framework (see Sect. 3.2.3) for the development of SIBs are provided both by Blasini (2015) and Rizzello et al. (2018). 3.2.3

A Focus on the Italian Legislative Context for SIB Development

In a regime of limited public resources, the innovative model of welfare and public policies is linked to systemic and organized collaboration with the world of innovative social enterprise and finance. Focusing on investments with social impact is also the best system in the direction of modernizing welfare mechanisms at any level.

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Social impact investments generate a measurable positive reaction in the communities in which they are placed; at the same time, they create a profit, a return on the capital employed. This investment choice, investigated especially in the field of economic and social sciences, reconciles a plurality of objectives and allows the public–private relationship to be developed in an innovative form. The latter becomes the subject that invests in the public sector, creates profit for the company that invests and represents value for the society that enjoys the positive effects of the investment. The mechanisms and the related instruments of social finance reconcile a plurality of objectives, as follows: the sharing of economic interests, the performance of value-added business activities in favour of the reference company (or the territorial community) and, for the benefit of the users, the synergistic cooperation among several subjects aimed to improve the expected results of a jointly developed project. The indefectible element that accompanies this innovative system is the social impact, of which there is no clear definition, which is being used differently according to the specific methodology of the measurement; however, by comparing these different definitions, it has been elaborated as “the set of resources, inputs and processes used in the activities of certain subjects, internal or external to the organization, that, in pursuing specific business and/or social objectives, change the living/working/relationship conditions of the people directly or indirectly involved in those activities; a change in the people, or more generally in a territory, generated by a company or organization, directly through its activities and indirectly through the investments made in the short or long term; the difference that an intervention provides on the life of a person and on a territory, taking into account what would have happened without that specific activity” (Maiolini et al. 2013; Perrini and Vurro 2013; Social Impact Investment Task Force 2013; Impronta Etica 2016). Finally, art. 7, paragraph 3, of Law no. n. 106/2016, with the Delegation to the Government for the reform of the Third sector, the social enterprise and the discipline of universal civil service, specifies the assessment of the social impact in terms of “qualitative and quantitative assessment, in the short, medium and long term, of the effects of the activities carried out on the reference community with respect to the target identified”. This approach is linked to the collaborative economy system that precisely views collaboration as an element of change in the economy

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and access to the market (for workers and consumers). The European Commission itself has placed attention on collaboration as a necessary element for the economy of the future (European Commission 2016a). Hence, the opportunity for the States to facilitate social enterprises’ access to finance (through the European Social Entrepreneurship Funds) encourages the use of new financial instruments to develop social impact bond forms that are capable of favouring “the participation of private capital in the financing of social programmes in exchange for financial benefits obtained by the public sector”, where the programme achieves positive social results (European Commission 2013a). With regard to the regulatory framework, there is no discipline that fully regulates the instruments of social impact finance and, in particular, SIBs; a first normative reference is ethical and socially responsible finance. Article. 117-ter of the Consolidated Finance Act1 (provisions on ethical finance) establishes that CONSOB, after consulting all interested parties and after consulting the competent supervisory authorities, determines, by its own regulation, the specific information and reporting obligations to which the parties that promote products and services qualified as ethical or socially responsible are bound (therefore, the codification of the ethical or socially responsible financial product is not envisaged, which could also apply in the case of banking and insurance products; the article establishes specific information and reporting obligations and, therefore, transparency of information and liability). In addition to the legislation on public contracts, other regulations, albeit in a context of adaptation, are the Legislative Decree n. 112/2017 (social enterprise regulations) and Legislative Decree no. 117/2017 (Third sector code), both implementing delegated law n. 106/2016. A summary of the essential discipline is as follows: Article 20 of Legislative Decree n. 50/2016, which provides, with regard to public works carried out at the expense of private, that the Code does not apply if a public authority concludes an agreement by which a public or a private entity is committed to achieve, in its total care and with all necessary permits, a public work or a part of this, as provided by urban planning tools or programmes (without prejudice to article 80). Before the agreement is signed, the public authority evaluates whether the feasibility project of works to be performed (with details about the deadline by which they must be completed and the scheme

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of procurement contracts proposed by the counterparty) is respondent to the implementation of public works. The agreement should also regulate the consequences in case of a breach of contract, including contractual penalties. Article. 143, provides for the possibility of entrusting reserved for third sector organizations. The procuring entities may reserve to certain organizations that have certain requirements the right to participate in competitions organized for the award of public procurement in health care, social, and cultural services, but these awards must meet all the following conditions: (a) The organizations have the statutory objective of pursuing a public service mission linked to the provision of the services covered by the award; (b) The organizations’ profits are reinvested to achieve the statutory objective (if profits are distributed or redistributed, this should be based on participative considerations); (c) The management or ownership structures of the organization performing the contract are based on employee ownership or participatory principles or require the active participation of employees, users or stakeholders; (d) The organization has not been awarded a contract for the services related to the contracting authority concerned pursuant to this article within the past three years. The contract shall not exceed three years. In addition to the procedures governed by the Code, the following additional methods may be useful: – authorization/accreditation (ANAC Decision n. 966/2016); – co-design (ANAC Decision n. 32/2016, law n. 328/2000; Prime Minister’s Decree dated 30 March 2001) as a functional form to solve “specific social issues” with “innovative and experimental” measures; – direct agreements with associations. Among the other types of financial instruments, which could ideally be connected in a legislative framework that favours the development of SIBs, solidarity and social lending activities can also be included (articles

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77 and 78 of the Third Sector Code, respectively). Solidarity securities are bonds, other debt securities, and certificates of deposit that credit institutions can issue for the purpose of raising money but with the obligation to use the capital to finance the institutional activities of the third sector entities registered in the national single register. Social lending is a type of financial loan between individuals (Banca d’Italia 2016) through which a plurality of subjects can request from a plurality of potential financiers the disbursement of repayable funds, through online platforms, to be invested in a project. The growing attention towards these types of instruments, imported from other models, and in the absence of specific regulations, will ensure that in the combination of innovations in the public policy area, collaborative and shared administration, financial instruments and social impact, it will be possible to think about a renewed role of local and not local administrations that will be able to respond to the social needs and services through policies and tools appropriate to the economic and structural peculiarities of the specific territorial and social environment. This system, although briefly described, could be systematically regulated, as it is potentially suitable to meet the growing demand for social benefits through the coordination between public authorities and private agencies to foster a deeper public–private synergy (Chiodo and Gerli 2017; Cisternino 2017; Agostinelli 2018; Baggio et al. 2018; Bernardoni and Marocchi 2018; Gori 2018; Rizzello et al. 2018; Mazzullo 2019). The strength of these tools is precisely to map those needs with a strong social impact, to elaborate projects and responses aimed at enhancing territorial skills and resources and to implement the role of the third sector in the service of the person.

3.3

Research Design, Methods and Data 3.3.1

Methodology Approach

This work is based on a qualitative research design (Denzin and Lincoln 2011) and employs a multi-case-study approach that we developed to investigate, in-depth, a particular phenomenon within its contexts (Yin 2009, 2017). The case study methodology appears to be an appropriate strategy for revealing the complex dynamics of an underexplored phenomenon (Eisenhardt 1989, 1991) and describing key variables and

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their relationships in a scenario characterized by large challenges (Eisenhardt et al. 2016). Case studies offer the researcher an opportunity to gain “a deep holistic view of the research problem, and may facilitate describing, understanding and explaining a research problem or situation” (Baškarada 2014: 1). The emphasis is placed on how and why selected SIB models have been launched and realized, and the focus is on the dynamics of these phenomena within their real-life contexts (Yin 2009). The main concepts of our analysis arise from an iterative procedure based on Strauss and Corbin’s approach (Strauss and Corbin 1990), borrowing from the literature review and aiming at identifying relevant dimensions for the multiple case study (within and cross-case) analysis. This method appears useful to contribute to generalizable knowledge by combining inductive and deductive techniques. In our case study analysis, the main dimensions explored are (1) the social dimension (information referring to social issues, target populations, etc.), (2) the financial dimension (information related to financial aspects), (3) the partnership dimension (information referring to several counterparties’ key elements and their networks/roles/responsibilities), and (4) the evaluation dimension (information referring to outcome metrics, type of measure used to evaluate the impact, with a focus on qualitative and quantitative elements). 3.3.2

Data Collection and Case Selection

As stated by Méndez-Suárez et al. (2020: 3), SIBs are “a new form of social –financial hybrid product that can deepen the collaboration of the private and public sectors to decrease poverty and inequality, strengthening the common good and enriching the new forms of investment while supporting SGDs, specifically SDGs 1, 10, and 17 ”. Using the SIB database of Government Outcomes Lab (created under the outcome-based Centre of Excellence at University of Oxford), we conducted a textual search related to the data of all extant SIBs, focusing on “social issues” and “target population”. More specifically, we searched for the following terms: (1) poverty; (2) inequality; (3) homelessness; (4) child poverty; (5) disadvantaged people; (6) labour reintegration and (7) NEET employment. Apart from a few cases of health impact bonds devoted to tackling inequalities, most of the health impact bonds (that pursue, first of all, prevention goals in the healthcare sector) remain at the margins of our analysis, such as the extant environmental impact bonds.

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All the other SIBs can be included in the group of SIBs that contrast poverty and inequalities. Among these, we chose five SIB models (Table 3.1) for our exploratory analysis. The SIBs were not selected randomly but followed an appropriate choice strategy and were in line with the main suggestions of scholars to guarantee rigour (Eisenhardt 2017). In this regard, we used the following criteria: (1) all selected SIBs are critical cases (which means, cases with strategic importance to our research), and (2) each selected SIB represents a case that is very different on one dimension (an extreme/unusual case) (Flyvbjerg 2001). In addition, all cases are selected according to the practical relevance of the outcome. More specifically, to confirm the quality of our study and the validity of the process, a research protocol has been defined regarding (1) the main sources of data, (2) the data analysis and (3) the reporting procedures and outlines (Yin 2017). We conducted a synthesized comparison of publicly available information about the five cases, based on multiple sources of data, in compliance with the main data quality characteristics, including accuracy, relevancy, objectivity, completeness, accessibility (Wang and Strong 1996), transparency and verifiability.

3.4

Empirical Evidence of the SIB Market 3.4.1

The SIB Market: A Snapshot

The social impact bonds (SIBs) market started with the launch of the first social impact bond in 2010 in the United Kingdom (Peterborough). Currently, in accordance with the Government Outcomes Lab (GO Lab) database, 184 impact bonds (IBs) have been launched worldwide (see Fig. 3.1).2 Most of these projects were conducted in the United Kingdom (77) and in the United States (27). At the end of April 2020, in accordance with the GO Lab database, there are 39 completed IBs and 144 implemented IBs. Go Lab classifies impact bonds into five types of contracts, as follows: social impact bonds (170), development impact bonds (11), environmental impact bonds (1), humanitarian impact bonds and collective impact bonds. Analysing our sample under this perspective, most of these projects are identified as social impact bonds (SIBs). In particular, 170 SIBs have been launched worldwide, mainly in the United Kingdom (76) and in the United States (26). In 2016, these two countries also launched two new types of contracts; in the United Kingdom, the first collective

Country 2016 (78 months)

“The intervention aims at promoting the professional insertion of populations living in isolated and economically precarious rural regions through the provision of microcredit ”

“The ‘Back on Track’ program is aimed at 2020 young people deprived of income and housing. (36 months) The non-profit organization Oranjehuis will intensively support young people according to the principle of ‘Housing First for Youth.’” This method focuses first of all on housing, then helping young people to recover, build a network and find a job or training. For young people who are coming out of detention, the non-profit organization wants to greatly reduce the risk of recidivism”

Launch date (duration)

Description

An overview of the selected SIBs

L’Association France pour le Droit à l’Initiative Economique (Association for the Right to the Economic Initiative) ADIE Back on Track Belgium

SIB name

Table 3.1

133

e1,700,000

(continued)

320

Target population

e1.2m

Capital raised

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(continued)

Country

Colombia

Chicago (USA)

Table 3.1

SIB name

Colombia Workforce Development SIB: Empleando Futuro [Employing the Future]

Chicago Child-Parent Center PFS Initiative

“The aim was to employ vulnerable individuals in formal jobs and support them in retaining those jobs (for at least three months). The SIB supported a range of employment measures, including skills training, psychosocial support, and intermediation services for job placement and retention, for 766 vulnerable individuals. The IDB-MIF /SECO provided a bonus payment of 10 percent of the overall price of the two metrics for 6-month job retention” “Chicago Public Schools (CPS) and the City of Chicago have launched a Pay-for-Success (PFS) contract that will allow the City to provide high quality pre-K services to more than 2,600 children in high-need communities through the successful Child–Parent Center (CPC) education program. The intervention is based on the Child–Parent Center (CPC) preschool model. The program provides high quality half and full day preschool education to three- and four-year olds as well as comprehensive family services. The model achieves its outcomes by working with students and parents to help foster better learning at home and helping families address the myriad of challenges they face”

Description

2014 (48 months)

2017 (21 months)

Launch date (duration)

$16,900,000 (committed)

COP 834,976,700

Capital raised

2618

899

Target population

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Canada

Mother Teresa Middle School

“The intervention supports young people who are at high risk of poor academic achievement to engage in education and remain in school. It focuses particularly on students from indigenous communities, who historically have had lower graduation rates than non-indigenous students”

Description 2016 (60 months)

Launch date (duration) CAN $1,000,000

Capital raised 88

Target population

Source Author’s elaboration on data from Go Lab database (see https://golab.bsg.ox.ac.uk/knowledge-bank/project-database/. Last accessed 30 April 2020)

Country

SIB name

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Fig. 3.1 Sibs market: a snapshot (Source Author’s elaboration from Go Lab database [2010–April 2020])

impact bond was launched in West London to support disadvantaged young people, and in the United States, the first environmental impact bond in Washington, DC was launched. Regarding the social issue areas, most of the IBs launched worldwide refer to “employment and training” (49) and “child and family welfare” (32). According to Figs. 3.2 and 3.3, 2017 was the most important year for the impact bond market. During this year, 43 impact bonds were implemented, especially in the “health and well-being” and “homelessness” social issue areas. Analysing the capital raised3 (as reported in Fig. 3.4), the United States has primacy, with a total capital amount of $193,269,989 raised, and the United Kingdom4 presents a total capital amount of $65,283,882 raised. Exploring the target population, three SIBs in India comprise approximately 907,300 people due to the high population density. These projects are identified as development impact bonds (DIBs), and they have been implemented in the social issue areas of education and early years and health and well-being.

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Fig. 3.2 Impact Bonds launched worldwide from 2010 to April 2020 (Source Author’s elaboration from Go Lab database)

Fig. 3.3 SIBs Social issues (Source Author’s elaboration from Go Lab database)

Analysing the European context, taking into consideration the European Quality of Government Index (EQI),5 we note (see Fig. 3.5) that all countries that have launched SIBs (Austria, Belgium, Germany, France, the Netherlands, Portugal, Sweden and the United Kingdom) rank in the top positions6 of the European Quality of Government Index (compared to Europe EQI = 50). A singular case is Denmark, which, although it presents an EQI of 80, has not launched any SIBs. This is due to the

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Fig. 3.4 SIBs Capital raised (Source Author’s elaboration from Go Lab database)

Fig. 3.5 European Quality of Government Index (EQI) (Source Author’s elaboration from publicly available information)

“virtuous financial circuits” (OECD 2016: 19) created in this country to resolve social problems with social investments. The Danish welfare

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system is based on a high level of social services delivered by local authorities to resolve education, health and employment social issues (Kvist 2015).

3.5

The SIB Case Studies: A Description

In this section, we illustrate the case studies by using an appropriate set of qualitative and quantitative information, highlighting the main features, key elements and characteristics. Table 3.1 provides an overview of our selected sample. 3.5.1

The SIB “ADIE—Association Pour Le Droit à L’Initiative Economique (Association for the Right to the Economic Initiative)”—France

In November 2016, the French Ministry of Economy and Finance, with the assistance of the Association for the Right to the Economic Initiative (ADIE—Association pour le Droit à l’Initiative Economique)—an association with the aim of supporting economic initiatives with the provision of microcredit (Adie 2016)—launched the first SIB to promote and encourage the employment of vulnerable people who live in rural regions in socio-economic precariousness and who do not have access to a formal banking system. The SIB started in January 2017 and provided a professional microcredit to support entrepreneurship and a personal microcredit for a durable job reintegration of these unemployed vulnerable individuals (Ministère de l’Economie et des Finances 2016). The professional microcredit provides a maximum finance of e10,000 for the creation of enterprises with the support of the service provider for the implementation or the development of a business idea. The personal microcredit intends to finance, with a maximum amount of e5000, access the labour market with the implementation of workforce mobility to obtain driving licenses or to purchase or repair a vehicle. The partnership with BNP Paribas, the financial intermediary, allows the creation of a specific financial model with particular characteristics that is useful for investment reimbursement for all involved parties (see Table 3.2). The service provider, ADIE, uses remote support (online services) to aid individuals who live in rural regions at the time of the microcredit application and, furthermore, with the help of volunteers, provides legal,

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Table 3.2 The SIB “ADIE—Association pour le Droit à l’Initiative Economique (Association for the Right to the Economic Initiative)”—France SIB Name: L’Association pour le Droit à l’Initiative Economique (Association for the Right to the Economic Initiative) ADIE Contractual characteristics Country Launch date Social Issue Target population Type of contract Structure

Stage

Financial characteristics France

2016 Employment and training 320 Unemployed vulnerable individuals Social impact bond N/A

Duration

78 month

Capital raised e1,200,000,00 Max outcomes e1,500,000,00 payments Involved Subjects Intermediary Outcome payer(s)

Implementation

Service provider(s)

Outcome(s)

Number of beneficiaries funded Number of people reintegrated

Investor(s)

Outcome validation methodology

Validated administrative data

Evaluator

BNP Paribas Ministère de l’Economie et des Finances L’Association pour le Droit à l’Initiative Economique (ADIE) BNP Paribas, Caisse des Dépots, Renault Mobiliz Invest, AG2R La Mondiale, Fondation Avril KPMG

Source Author’s elaboration from publicly available information

commercial and financial guidance services for their projects. The services are provided for three years (2017–2020); after this period, the evaluation of the programme will be managed by KPMG (2020–2023). The implementation of the project in 2016 KPMG (KPMG 2016) released a report on the evaluation of the economic and social impact of the Adie microcredit projects with the use of the social return on investment (SROI) approach. In particular, this report analyses the role of the professional microcredit for the community; KMPG argues that during a 3-year investment, for each euro invested in a microcredit project by ADIE, it gains e2.38 for the community after two years (KPMG 2018). ADIE affirms

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that the average social value created by this SIB is e7,560 (Impact Invest Lab 2020). KPMG is the independent evaluator and is responsible for the definition and evaluation of the indicators to measure the effectiveness of the programme (Impact Invest Lab 2020) to reach the outcome envisaged by the model. To evaluate the programme, the following two evaluation criteria have been selected (Ministère de l’Economie et des Finances 2016): – The number of vulnerable individuals financed and supported (500): this criterion aims to measure the pervasiveness of the project and is linked to the reimbursement of half of the capital invested; the estimated minimum is 270 individuals; – The number of vulnerable individuals with stable employment (320): this criterion aims to measure the impact of the project on the beneficiaries; the estimated minimum is 172 individuals. Furthermore, these criteria will be compared to the results obtained by a similar sample with the same conditions of the target population of the project to explore in greater depth the direct effects of the project; the involved parties have not clearly defined this aspect in the contract. The economic model of this SIB was built so that the government will always make a profit. In accordance with ADIE, the gaining of 320 beneficiaries will achieve (i) a profit for Adie (estimated to be e65,000), (ii) a profit for the investors (estimated to be e130,000) and (iii) a profit for the government; if the project obtains 406 beneficiaries, the profits gained will only be for the government (Impact Invest Lab 2020). The evaluation will be made with the use of the validated administrative data methodology7 using data provided by ADIE (Ministère de l’Economie et des Finances 2016).The total cost of the SIB amounts to e1,301,500 (Impact Invest Lab 2020), and it will end in 2023. 3.5.2

The SIB “Back on Track”—Belgium

The Flemish Social Impact bond called “Back On Track” was launched in March 2020. This SIB supports 133 young adults—between 17 and 25 years of age—at risk of becoming homeless. The target population is made up of incarcerated young refugees, young homeless individuals

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and young adults on the reception waiting list at CAW (Centrum voor Algemeen Welzijnswerk—Centre for General Welfare). This project is based on the principle of “Housing First for Youth System”, an initiative that emphasizes the need to have sustainable accommodation for disadvantaged people; after giving stable and sustainable accommodation, the project’s aim is to offer an important support system for these young people to (re)integrate them into a community (EIF 2020a). The support consists of an interrelated set of services regarding homelessness, employment and education social issues; for this reason, the outcomes to be achieved by the SIB are threefold, as follows: so that the project will be paid, at the end of the intervention, 85% of young adults must obtain a renting agreement, 40% of young adults must have a legal income or start a training programme and a 25% reduction in recidivism must be achieved compared to a reference rate. The services are provided by Oranjehuis, which employs 8 supervisors who help the young people search for accommodation and employment and provide constant social supervision and psychological support to prevent recidivism (Besix Foundation 2020). The SIB will have a positive impact if approximately 113 young adults complete the 12-month programme. Furthermore, the outcomes provided by the SIB are threefold, as follows (see Table 3.3): – 85% of young adults obtain a renting agreement; – 40% of young adults have a legal income or start a training programme; and – 25% reduction in recidivism is achieved compared to a reference rate. The cost savings to society are calculated to be e3.8 million. If the project ends positively, the Flemish government may decide to implement this project regularly (BNP Paribas 2020a). The financial structuring is provided by BNP Paribas (arranger), which is also an investor of the SIB. This SIB is part of the BNP Paribas European Social Impact Bonds Fund (EIF 2020a), a co-investment fund with the participation of BNP Paribas and the European Investment Funds (EIF) under the umbrella of the European Fund for Strategic Investments (EFSI). The BNP Paribas European Social Impact Bonds Fund has the purpose of developing SIBs in European countries (European Commission 2020). The legal structuring is made in collaboration with Curia, a specialized law firm in Belgium (CURIA 2020). LUCAS, a research team of KU Leuven

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Table 3.3 The SIB “Back On Track”—Belgium SIB Name: Back on Track Contractual characteristics Country

Financial characteristics Belgium

Launch date Social Issue

2020 Homelessness

Target population Type of contract Structure Stage

133 young adults Social impact bond Direct Implementation

Outcome(s)

Outcome validation methodology

1. 85% of young adults obtain a renting agreement 2. 40% of young adults have a legal income or start a training 3. 25% reduction in recidivism compared to a reference rate N/A

Duration

36 month

Capital raised Max outcomes payments Involved Subjects Intermediary Outcome payer(s) Service provider(s) Investor(s)

e1,700,000,00 N/A

Evaluator

LUCAS, KU Leuven

BNP Paribas Opgroeien Oranjehuis BNP Paribas, European Investment Fund, BNP Paribas Fortis, Boss Paints, BESIX Foundation

Source Author’s elaboration from publicly available information

University, is the independent evaluator. The collaboration between the involved subjects is fundamental to meet the purpose of the SIB (BNP Paribas 2020b). The project will end in 2023. 3.5.3

The SIB “Workforce Development SIB: Empleando Futuro (Employing the Future)”—Colombia

This unique Colombian SIB was launched in 2017 in the cities of Bogotá, Cali and Pereira, with the aim of restoring the employment of 766 disadvantaged people—between ages 18 and 40—living in vulnerable groups to formal jobs (see Table 3.4). These individuals are not employed in a stable job, are registered in Red Unidos and present a high SISBEN

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Table 3.4 The SIB “Workforce Development SIB: Empleando Futuro (Employing the Future)”—Colombia SIB Name: Colombia Workforce Development SIB: Empleando Futuro [Employing the Future] Contractual characteristics Country

Financial characteristics Colombia

Duration

21 month

Capital raised

COP 834,976,700,00 COP 2,944,000,000,00

Launch date

2017

Social Issue

Employment and training 766 vulnerable individuals Social impact bond

Max outcomes payments Involved Subjects

N/A

Outcome payer(s)

Target population Type of contract

Structure

Stage

Outcome(s)

Outcome validation methodology

Completed

1. Job placement 2. 3-month job retention 3. 6-month job retention Validated administrative data

Intermediary /advisor

Service provider(s)

Investor(s)

Evaluator

Source Author’s elaboration from publicly available information

Instiglio, Fundación ProBono, Baker McKenzie, Duran & Osorio, Compartamos con Colombia Departamento de Prosperidad Social (Government of Colombia Department of Social Prosperity) (Central government) Swiss Secretariat of Economic Affairs (SECO) Kuepa, Fundación Colombia Incluyente, Corporación Volver à la gente, Fundación Carvajal Fundacion Bolivar Davivienda, Fundacion Mario Santodomingo, Fundacion Corona Deloitte

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poverty score, or are registered as displacement victims because of conflict (Gustafsson-Wright and Boggild-Jones 2017). It is the first social impact bond launched in a developing country such as Colombia (Gustafsson-Wright and Boggild-Jones 2017). The services provided consist of a set of skills training, psychological support and labour intermediation services (Government Outcomes Lab 2019). In this SIB, the outcome payers are the Colombian government and the Swiss Cooperation (SECO). This relationship between the two payers demonstrates a new model to combine development and financial support, with public financing to pay for the outcomes of the projects (Gustafsson-Wright and Boggild-Jones 2017). This SIB involves the three major Colombian foundations (Fundacion Bolivar Davivienda, Fundacion Mario Santodomingo and Fundacion Corona) as investors to catalyse the market (Gustafsson-Wright and Boggild-Jones 2017). To validate the data of the project, this SIB uses “validated administrative data” by the Colombian Ministry of Health and Social Protection to (i) improve the validity and availability of the data; (ii) verify the results gained; and (iii) prevent a distortion of the data because it does not utilize data from the subjects involved (Gustafsson-Wright and Boggild-Jones 2017). In July 2018, phase A was concluded, and due to the positive results obtained, the time and the number of participants was extended in phase B. The SIB was concluded in 2019, and at the end of the project, 899 disadvantaged people had found formal jobs, which is 133 more individuals than the population target of 766. The outcome metrics (and their payment) for this SIB are as follows (Gustafsson-Wright and Boggild-Jones 2017): – Job placement, which corresponds to 50% of outcome payment (per capita); – 3-month job retention, which corresponds to 50% of outcome payment (per capita); and – 6-month job retention, which corresponds to a 10% bonus of outcome payment. The maximum outcome payment, after the extension in phase B of the project, amounts to 2,944 billion COP, and it is refunded by the Departamento de Prosperidad Social (Government of Colombia Department of

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Social Prosperity) for an amount of 1,450 billion COP and by the Swiss Secretariat of Economic Affairs (SECO) for an amount of 1,494 billion COP (Government Outcomes Lab 2019). 3.5.4

The SIB “Chicago Child–Parent Center PFS Initiative”—United States

The Chicago Child–Parent Center PFS Initiative was the first pay for success (PFS)/SIB initiative launched in Chicago in 2014 (IFF 2018) and impacts more than 2600 at-risk children (and their families) living in low-income neighbourhoods (Corporation for National and Community Service 2015). In particular, the programme involves helping them improving their skills and abilities in the following six fields of development: “literacy, language, mathematics, cognitive development, socioemotional well-being and physical health” (IFF 2017); this SIB aims to actively involve the parents of these children in school activities, school trips and adult classes. The services are provided for 4 years, but the repayment term and the evaluation period are 17 years. The outcome metrics to achieve this include an increase in kindergarten readiness, the decrease in special education services and an increase in third grade literacy. Regarding the evaluation methodology, a quasi-experimental approach has been adopted that provides a comparison group; the results achieved by the first cohort in 2014–2015 will be the target for the evaluation, with a quasi-experimental approach, of the future educational outcomes of the project (Urban Institute 2014). Analysing the investors (see Table 3.5), there is a simultaneous presence of two different types of lenders, as follows: the primary lenders are Goldman Sachs ($7.5 million) and the Northern Trust ($5.5 million), which will receive their investment reimbursement first, i.e. by 2022; the secondary lenders (for a total amount of $3.9 million) are J. B. and M. K. Pritzker Family Foundation, and they will receive the reimbursement of their investment after 2022. Furthermore, The Finnegan Family Foundation and the City of Chicago provide funding for the evaluation of this SIB (Corporation for National and Community Service 2015). The risk of this SIB is transferred to the private sector (Pennsylvania Economy League 2015). Stanford Research Institute International (SRI International) is a nonprofit research institute and, for this SIB, it is the independent evaluator of the programme. The SIB will end in 2022.

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Table 3.5 The SIB “Chicago Child–Parent Center PFS Initiative”—United States SIB Name: Chicago Child–Parent Center PFS Initiative Contractual characteristics Country

Financial characteristics United States

Launch date Social Issue

Duration

48 month

2014 Education and early years 2618 Social impact bond

Target population Type of contract

Structure

Stage Outcome(s)

Outcome validation methodology

Capital raised $16,900,000,00 Max outcomes $34,500,000,00 payments Involved Subjects Intermediary Metropolitan Family Services (program intermediary) Intermediated Outcome payer(s) Chicago Board of Education City of Chicago Implementation Service Chicago public provider(s) elementary schools Increase in Investor(s) Goldman Sachs kindergarten readiness (Social Impact Fund); Northern Trust; J.B. and M.K. Pritzker Family Foundation Quasi-experimental Evaluator SRI International

Source Author’s elaboration from publicly available information

3.5.5

The SIB “Mother Teresa Middle School”—Canada

In 2016, 88 Canadian students from indigenous communities were involved in a social impact bond in Regina, Canada. These individuals presented a high risk of poor academic achievement due to their socioeconomic condition (Khovrenkov 2018). The Mother Teresa Middle School SIB aims to give these disadvantaged young people the possibility to enhance their academic future through teaching courses, skills courses and extracurricular activities (e.g. sport, music). The single investor, The Mosaic Company Foundation, is actively involved; its representatives visit the school and operate as mentors to the engaged students. The outcome validation methodology of the only outcome to be validated (increment in high school graduation rates) is the validated

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administrative data provided by the Saskatchewan Ministry of Education, which annually measured and tracked the graduation rate of the students involved (see Table 3.6). Regarding the financial terms of this project, the investor is repaid by the Government of Saskatchewan (Government of Saskatchewan 2016): (i) if the school achieves an 82% graduation rate, the principal and interest equal to 1.3% are repaid; (ii) if the school achieves a 75% graduation rate, three-quarters of the principal is repaid, without interest; and (iii) if the graduation rate is below 75%, no repayment is made. The SIB will end in 2022.

Table 3.6 The SIB “Mother Teresa Middle School”—Canada SIB Name: Mother Teresa Middle School Contractual characteristics Country Launch date Social Issue Target population

Type of contract Structure Stage Outcome(s)

Outcome validation methodology

Financial characteristics Canada

Duration

60 month

2016 Education and early years 88 students at risk of dropping out from high school Social impact bond N/A

Capital raised Max outcomes payments Involved Subjects

C$1,000,000,00 C$1,160,000,00

Intermediary Outcome payer(s)

Implementation

Service provider(s)

N/A Government of Sasketchewan Mother Teresa Middle School The Mosaic Company Foundation Saskatchewan Ministry of Education

Increase in high Investor(s) school graduation rates Validated administrative data

Evaluator

Source Author’s elaboration from publicly available information

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3.6 Fighting Poverty and Inequalities Through Social Impact Bonds: Insights from Case Studies In line with the predictions of Yin (2009), this work inductively tries to identify some relevant ingredients that characterize each case with the aim of drawing a series of suggestions useful for the application of these emerging instruments as support in fighting the social and economic consequences of COVID-19. As described in Sect. 3.5, our five case studies come from a wide range of social issues (employment and training, homelessness, education, and early years) and have different structures. Despite the variations in the cases, our insights may be relevant in other countries, and many implications for research and practice can be highlighted, as described in the sections below. 3.6.1

The Role of Banks and Foundations and of Their Reputation to Catalyse Financial Resources

Banks and traditional financial intermediaries are involved in different ways in the cases analysed. In the cases “ADIE—Association pour le Droit à l’Initiative Economique (Association for the Right to the Economic Initiative)” and “Back On Track”, the BNP Paribas Group structured the SIB projects by acting as both financial intermediary and investor. By working together with the European Investment Fund (EIF), BNP Paribas Asset Management on behalf of BNP Paribas launched the first co-investment fund set up expressly to invest in developing Social Impact Bonds (SIBs) across the EU and particularly in France. The fund, named BNP Paribas European Social Impact Bond Fund, has been launched as part of the EFSI (or “Juncker Plan”). The fund is based on the following three main pillars: (1) the BNP Paribas’ expertise and reputation in structuring SIBs and their subsidiary BNP Paribas Asset Management’s long-term experience in impact measurement and solidarity funds (EIF 2020b); (2) a co-investment agreement; and (3) a view to develop Social Impact Bonds (SIBs) across the EU. Since 2016, BNP Paribas co-structured and invested in an SIB worth more than $11 million in the United States to avoid placing children whose parents have addiction problems in foster care (Corporate Knights 2017). In 2018, the second SIB in the United States, named “Veterans CARE”, was launched to support 480 veterans of the US armed forces suffering from post-traumatic stress (BNP Paribas 2019a). Similarly, in

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March 2019, by working with the Ministry for Ecological and Inclusive Transition, the Bank launched three new French Social Impact Bonds, i.e. Wimoov, Article 1 and La Cravate Solidaire (BNP Paribas 2019a; Social Entrepreneurship Barometer 2019). Overall, since 2016, in France and the United States, BNP Paribas structured 7 SIBs for a total of e21.5 million by investing (or committed to invest) a total of e7.8 million (BNP Paribas 2019b) and becoming the leader of this sector in France, having provided their financial engineering support for more than 50% of the SIBs labelled by the French government and 100% of the SIBs actually signed and launched (BNP Paribas 2019a). Our cases reveal the presence of another traditional financial intermediary, i.e. Goldman Sachs. In 2012, Goldman Sachs worked with the City of New York and Bloomberg Philanthropies to structure a funding mechanism to reduce the re-incarceration rate among adolescents at New York’s Rikers Island prison (through an intervention programme named NYC Able Project for Incarcerated Youth). Goldman Sachs funded the project with a US$9.6 million loan through its Urban Investment Group, while Bloomberg Philanthropies provided a US$7.2 million grant to guarantee the loan by reducing the lending risk (Carè 2018; Goldman Sachs 2020). Overall, Goldman Sachs has been engaged in 5 SIB projects as investors or arrangers, as follows: NYC Adolescent Behavioral Learning Experience Project for Incarcerated Youth, Utah High Quality Preschool Program, Massachusetts Juvenile Justice PFS Initiative, Chicago Child– Parent Center PFS Initiative, and D.C. Water Environmental Bond. Finally, with regard to the case “Workforce Development SIB: Empleando Futuro (Employing the Future)”, the investors in the SIB are a coalition of foundations, including Fundación Corona (a family foundation), Fundación Bolivar Davivienda (part of the Bolívar Business Group and of Davivienda Bank), and Fundación Mario Santo Domingo (a non-profit foundation), who provided the upfront capital to finance the intervention. 3.6.2

Promoting Inclusion and Poverty Alleviation Through Social Enterprises: The Link for the Development of the SIB Market

Social enterprises play a key role in social needs identification and service provisions. Scholars and professionals agree that social enterprises (SEs)—vital engines of social innovations—are a very important sector located on the demand side of the social finance market (Nicholls et al.

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2015). SEs—defined as organizations with an explicit aim to benefit the community (Defourny and Nyssens 2010)—need financing for different purposes, depending on their field of activity, business model and maturity (European Commission 2016b). In the last few years, the European Commission (EC) has encouraged the development of the relationships between SF and SEs, which is considered as the main strategy for the development of local economies and especially of marginal territories. European countries are adopting programmes and SF schemes to support social enterprise development, in many cases through the financial support of the European Social Funds (ESF). Under the EU Programme for Employment and Social Innovation (EaSI), the EC supports microfinance and social entrepreneurship finance—forms of SF—with an overall envelope of EUR 193 million for the period of 2014–2020. As stated in the Opinion on Building a Financial Ecosystem for SEs provided by the European Economic and Social Committee (EESC) (2016/C013/23), “a new social landscape is emerging in Europe”. Therefore, the theme of social finance and its relationship with SEs is becoming critical, more central and a clear priority for the EC. Our cases reveal the active role of SEs in both promoting and implementing SIB projects. In particular, ADIE is a non-profit organization that helps people who have been excluded from the workplace and the conventional banking system to start a business and become self-employed through microcredit. Similarly, Oranjehuis is a not-for-profit organization with close to 50 years of experience working with young people, children, and families in vulnerable situations. In the same vein, the case of Colombia involves three non-profit organizations/foundations (Fundación Colombia Incluyente, Corporación Volver à la gente, Fundación Carvajal) aiming at improving the quality of life of the most needed local communities. 3.6.3

Improving the SIB Deal Structure Through Specialized Advisors

External advisors help to set up the necessary structures for the implementation of SIB projects. In particular, both legal and financial advisors can help commissioners bridge the knowledge gap with investors by explaining the terms and conditions and by advising on what rates of return will make an SIB affordable and appealing.

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The projects included in our sample reveal the presence of a series of different actors that collaborated in the different stages of SIB development (see Tables 3.2, 3.3, 3.4, 3.5, and 3.6). Consulting giants, such as KPMG and Deloitte, and a renowned research team from KU Leuven University offered their support in the evaluation stage, while specialized law firms, such as Curia, provided support during the legal structuring of the project.

3.7

Looking Ahead: Implications for Research and Practice

Our cases reveal that SIB projects differ in many aspects and that there are no one-size-fits-all solutions in terms of structure, contractual scheme and partnership characteristics. Each project is based on a different background (including social, cultural, and institutional features) and on various actors’ ecosystems. However, there are some aspects that could be usefully exported to promote the development of the SIB market. Under a theoretical perspective, our work confirms the central role of the actors involved in an SIB project. The “ecosystem” represents the key point for the development of relationships in social innovation and in SIB projects. In our view, the analysis of the “ecosystem” can be arguably integrated by the development of innovative policies, generating a new way of conceiving welfare services. In fact, the promoting and facilitating role that some actors may play in interactions with actors within the ecosystem and in other ecosystems is a fundamental component to promote social inclusion through the development of SIB projects. Hence, as indicated, the research implications mainly regard two levels of analysis. The first mainly refers to the possibility of stimulating actors that usually work alone to work in teams by sharing knowledge, experience and reputation with the aims of creating social value and social impact. The second refers to the possibility that stimulus could arise from a new approach to welfare and social innovation policies, such as in the case of the collaboration between BNP Paribas and the EIF. From a practical point of view, these two key aspects could facilitate the development of SIB projects in countries in which they are not actually used by betting on the development and enforcement of the ecosystem described in Fig. 3.6.

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Fig. 3.6 Ecosystem for the development of SIB projects

The ecosystem should be understood as a context where there is an ongoing interplay among actors taking a variety of roles, such as promoters and facilitators. As described in Fig. 3.6, social enterprises represent the starting point of the entire process by facilitating the connection between the people in need, on the left side, and investors, on the right side. The entire pathway, from the population in need to the investors, is characterized by the presence of barriers—represented by the dashed lines in grey. However, the presence of social innovation-based welfare policies could facilitate the creation of networks and collaborations between the different actors.

3.8 Moving Practice Forward: A Proposal for Italy and for Europe The spreading of COVID-19 across Europe and its social and economic consequences may increase inequality, exclusion, discrimination and global unemployment in the medium and long term. If not properly addressed through adequate policy, the social crisis created by the COVID-19 pandemic and the need for urgent action to protect workers

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and people at risk of poverty will pose severe consequences for the sustainability of welfare systems. At the same time, the different geographic spread and severity of COVID-19 in Europe will keep widening the gap between rich and poor regions. The COVID-19 pandemic is expected to increase the number of deprived people. Recent statics reveal that Romania, Bulgaria, Greece and Italy are the countries with the highest rate of children at risk of poverty or social exclusion (Eurostat 2019). Similarly, Portugal has struggled with the effects of the financial crisis for several years and already has more than 2 million people at risk of poverty or social exclusion. The challenges posed by COVID-19 should be considered as the starting point for the reconsideration of public policies and for the development of a new era of welfare services provision. In addressing poverty and inequalities, innovative welfare policies routed in the framework of social innovation may help to overcome budget constraints and to mobilize private resources to finance welfare provisions. As clarified by Sabato et al. (2015: 7), “the highly contextual and bottom-up character of social innovation as well as its capacity to promote the participation and the empowerment of socially excluded groups thus eventually leading to the transformation of social relations ”. Social innovation, which is generally considered as the capacity to respond to emerging needs through new forms of collaboration, represents one of the fields through which SEs may fill the chronic distance between social needs and welfare policies. Moving from these considerations and by using the main lessons from our case studies, the following sections try to outline a series of suggestions useful for the reconsideration of public policies in a time of severe budget constraints and of pandemic emergencies useful for Italy and for Europe. In doing so, we used Italy as a laboratory to understand if and how SIBs may be implemented considering the main issues and challenges that the Italian legal framework poses. Although we used Italy as a laboratory, our considerations may be useful for other European countries with high rates of poverty and social exclusion. 3.8.1

Building National Social Innovation Policies

Welfare systems play a unique role in improving citizens’ well-being, for example, through the provision of affordable and good-quality education, (preventive) health services, lifelong learning opportunities, job search assistance, and benefits in old age (European Commission 2015).

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However, in recent times, all European welfare systems have been facing dramatic challenges—mainly related to the effects of the 2007 financial crisis—and the COVID-19 economic downturn will exacerbate their dynamics. The EU has repeatedly cited social innovation as a solution to the persistence of socio-economic issues. Budgetary constraints, public deficit pressures, and increased demand on public services have fuelled the need to capitalise on social innovation so that public and private institutions can do more and achieve more with less by stressing both increased efficiency and effectiveness (TEPSIE 2014). In this vein, a series of initiatives have been developed, such as the EU Programme for Employment and Social Innovation (EaSI), which was jointly launched by the EU, the EIF and the European Investment Bank (EIB) to support lending to microenterprises and social enterprises. In line with the EU’s policy objectives, the fund will promote microfinance and social entrepreneurship by encouraging microfinance institutions and social enterprise lenders to increase funding for microenterprises as well as social enterprises as a means of supporting social and financial inclusion. At the national level, the development of social innovation policies could potentially catalyse the attention of several actors; local communities and social enterprises could collaborate together to develop intervention programmes targeted to local social needs, while banks and bank foundations could potentially provide their reputation and expertise for project development and funding. Hence, the implementation of national policies could foster the development of the ecosystem described in previous sections. 3.8.2

Unpacking the Role of Social Enterprises in the Implementation of SIB Projects

In the aftermath of the economic and financial crisis of 2007/2008, the appearance of new needs made the demands by citizens more wideranging and complex. At the same time, the difficulties generated by growing fiscal constraints have made it increasingly difficult for the public sector to meet this demand on its own, as it had traditionally done in the welfare models dominated by state intervention. The ongoing pandemic crisis has accelerated the need for rethinking the respective roles of the market, the state, the “social economy” and, thus, of social enterprises. The term social enterprise is increasingly used to identify a “different way” of doing business, which occurs when enterprises are created specifically to

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pursue social goals by placing more emphasis on the dimension of general interest rather than on purely mutualistic goals (European Commission 2013b). Social enterprises fully mix social and economic objectives and are, therefore, possibly better suited to respond to the multidimensional nature of poverty (Fotheringham and Saunders 2014), as they can respond to social exclusion (Cooney and Shanks 2010; Heeks and Arun 2010). A priority for the development of a national policy in the field of social enterprises is related to the development of appropriate legal, regulatory and fiscal frameworks that should not be too onerous in what they require of social enterprises but should be able to recognize the dual focus of social enterprises, i.e. the economic and social dimensions. Moreover, fiscal policies also need to recognize their positive social benefits, while indirect fiscal measures could also be useful to help support investment in social enterprise development. A classic example is represented by the UK, where social enterprises can access Community Investment Tax Relief (CITR), which, although not specifically designed for social enterprises, was created to encourage investment in disadvantaged areas. 3.8.3

Exploiting the Role of Microfinance Institutions and Banks

Microfinance institutions play an essential role in bridging the gap between the mainstream financial sector, which is often reluctant to serve those individuals/micro-entrepreneurs perceived as very risky and less attractive from an economic point of view, and the regional/national social policymakers, which are often biased towards supporting weaker groups and excluded people but without a clear idea on how to stimulate an active and inclusive role. Consequently, microfinance represents an activity that can have a positive impact on inclusive finance and serve as an essential policy tool for policymakers. Moreover, banks and bank foundations should be involved in developing SIB projects by stressing two main aspects, i.e. the potential reputational return they may obtain and the possible financial return they may have by investing in such projects.

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Final Thoughts

The current literature on SIBs overstates the contractual requirements of SIBs but overlooks the role of different actors underlying their implementation. The current study addresses this gap by exploring the roles of several actors deployed to initiate and implement SIB projects. By connecting insights from case studies and the literature, two main contributions are made. First, it is demonstrated that the development of an SIB project goes well beyond the mere role that is attributed to the involved partner by contract. Reputation and name have the power to make the project highly appealing, as in the case of bank and bank foundations, and transparent, as in the case of legal and evaluation consulting firms. Second, the study emphasizes the importance of social enterprises as the link between social needs and private investors by using social innovation to solve a social problem. Finally, the findings of this research extend the current theory concerned with the implementation of SIB projects by emphasizing the importance of new welfare policies based on social innovation by providing some suggestions for Italy that are useful as a response towards the COVID-19 economic damages and for poverty reduction. This chapter is the result of a collaboration between the Authors. In particular, Annarita Trotta contributed to the Sects. 3.1, 3.2, 3.2.1, 3.2.1.1, 3.2.1.2, 3.2.1.3, 3.2.1.4, 3.2.1.5, 3.2.1.6, 3.2.1.7, 3.2.2, 3.3, 3.3.1, 3.3.2; Rossana Caridà contributed to the Sect. 3.2.3; Maria Cristina Migliazza contributed to the Sects. 3.4, 3.4.1, 3.5, 3.5.1, 3.5.2, 3.5.3, 3.5.4, 3.5.5. Finally, Rosella Carè contributed to the Sects. 3.6, 3.6.1, 3.6.2, 3.6.3, 3.7, 3.8, 3.8.1, 3.8.2, 3.8.3, and 3.9. It is worth to underline that all the analysis in this work are based on data publicly available as of April 30, 2020. Acknowledgments The Authors express their gratitude to reviewers for their useful contributions and comments.

Notes 1. Testo unico delle disposizioni in materia di intermediazione finanziaria (tuf), d. lgs. n. 58/1998.

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2. Information about the 18 SIBs launched in the United Kingdom within the “Life Chance Fund” is not available. From the end of October 2019, Go Lab declared that: Information about the 18 SIBs launched in the United Kingdom within the “Life Chance Fund” is not available. From the end of October 2019, Go Lab declared that: “The GO Lab projects database has previously included more details on this project. However, since these details were published, new information has come to light suggesting that some of the submitted figures are different from those finally agreed between project stakeholders . As such, our partners at the Centre for SIBs in the Department for Digital, Culture, Media and Sport have asked us to remove all figures for these projects while the information is verified. As we explain here, we believe that publication of social impact bond data is important for three reasons: to support equal access to information between project stakeholders , as an aid to those exploring similar approaches, and to support research and policy recommendations. To achieve these aims, it is important that the information published is as accurate as possible and we will update this page with further details on this project as soon as these are available”. For further information see: https://golab.bsg.ox.ac.uk/. 3. To compare the amount of capital raised among the different SIIs all around the world expressed in home country currency, we have used the exchange rates of 30 April 2020 (https://tassidicambio.bancaditalia. it/converter) to report the amount of “capital raised” from home country currency to US dollar. 4. Information about the “capital raised” of the 18 SIBs launched in the United Kingdom within the “Life Chance Fund” is not available. For further information, see note 3. In addition, there are also some SIIs in the UK of which the data on “capital raised” is not available. 5. The European Quality of Government Index (EQI)—constructed by The Quality of Government (QoG) Institute- is an index that considers the trustworthiness, reliability, impartialness, corruption and competency of the “Good Governance” and “the quality” of 28 European governments and 2 accession countries (Serbia and Turkey). This index is based on citizen surveys at the regional level to analyse the perception and the experience with the public sector and permits the comparison of data across European countries. 6. In the latest EQI dataset (2017), European countries rank this position (and score): (I) Finland, Sweden and Denmark (80); (II) The Netherlands and Luxembourg (76); (III) Germany and United Kingdom (71); (IV) Ireland (68); (V) Austria (67); (VI) Belgium (63); (VII) France (58); (VIII) Estonia (54); (IX) Portugal (50); (X) Malta (48); (XI) Cyprus (47); (XII) Lithuania; (XIII) Slovenia (43); Czech Republic (43); (XIV) Spain (42); (XV) Poland (39); (XVI) Latvia (38); (XVII) Slovakia (32); (XVIII) Italy (25); (XIX) Hungary; (XX) Croatia (23); (XXI) Greece (19); (XXII) Romania (15); (XXIII) Bulgaria (12).

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7. The “validated administrative data” methodology assumes that the data have been validated by an internal subject of the project (e.g., government) or by an independent external evaluator. Funding This work was realized in the framework of the Project Social Impact Finance (SIF16_00055) «An Italian platform for impact finance: financial models for social inclusion and sustainable welfare» (in collaboration with: Sapienza, University of Rome, Project Leader), funded by the Italian Ministry of the Education, University and Research (MIUR), PNR (2015–2020), DD. 2153, 12.10.2016; DD. 1303, 30.05.2017.

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Dipartimento di Sociologia e Ricerca Sociale, Università degli Studi di Trento, Italy. Government of Saskatchewan. (2016). Social Impact Bond Will Improve Graduation Rates for Mother Teresa Middle School Student. Retrieved from https://www.saskatchewan.ca/government/news-and-media/2016/sep tember/15/social-impact-bond-for-mtms. Accessed on 30 April 2020. Government Outcomes Lab. (2019). Colombia Workforce Development Social Impact Bond—Empleando Futuro. Retrieved from https://golab.bsg.ox.ac. uk/knowledge-bank/case-studies/colombia-workforce-sib/. Accessed on 30 April 2020. Government Outcomes Lab. (2020). Projects database. https://golab.bsg.ox. ac.uk. Accessed on 30 April 2020. Gustafsson-Wright, E., & Boggild-Jones, I. (2017). Colombia leads the developing world in signing the first social impact bond contract. Retrieved from https:// www.brookings.edu/blog/education-plus-development/2017/03/31/col ombia-leads-the-developing-world-in-signing-the-first-social-impact-bond-con tracts/. Accessed on 30 April 2020. Gustafsson-Wright, E., & Gardiner, S. (2016). Using impact bonds to achieve early childhood development outcomes in low-and middle-income countries. Washington, DC: Brookings Institution. Gustafsson-Wright, E., Gardiner, S., & Putcha, V. (2015). The potential and limitations of impact bonds: lessons from the first five years of experience worldwide. Washington, DC: Brookings Institution. Hajer, J. (2018). The political economy of social impact bonds (Doctoral dissertation). Available from ProQuest Dissertations & Theses Global database (UMI No. 13424971). Retrieved from https://search.proquest.com/ope nview/9c83c5342a06962ca137ea69541dc089/1?pq-origsite=gscholar&cbl= 18750&diss=y. Accessed on 30 April 2020. Hajer, J. (2020). The national governance and policy context of social impact bond emergence: A comparative analysis of leaders and skeptics. Journal of Comparative Policy Analysis: Research and Practice, 22(2), 116–133. https:// doi.org/10.1080/13876988.2019.1695924. Heeks, R., & Arun, S. (2010). Social outsourcing as a development tool: the impact of outsourcing IT services to women’s social enterprises in Kerala. Journal of International Development, 22(4), 441–454. https://doi.org/10. 1002/jid.1580. High-Level Expert Group. (2018). Financing a Sustainable European Economy. Retrieved from https://www.eesc.europa.eu/en/our-work/opinions-inform ation-reports/opinions/action-plan-sustainable-finance/related-links-eco456. Accessed on 30 April 2020. IFF. (2017). Chicago Pay for Success Initiative. Retrieved from https://iff.org/ chicago-pay-success-initiative/. Accessed on 30 April 2020.

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IFF. (2018). Fact Sheet. Chicago Pay for Success/Social Impact Bond Program. Evaluation Year Three. Retrieved from https://iff.org/wp-content/uploads/ 2018/04/Fact-Sheet-Chicago-SIB-Year-3-FINAL-4.26.2018.pdf. Accessed on 30 April 2020. Impact Invest Lab. (2020). Le contrat à Impact social de étude de cas d’un contrat à impact social. Paris, France: Impact Invest Lab. Retrieved from https://iilab.fr/wp-content/uploads/2020/01/ETUDECAS-IMPACT-SOCIAL-ADIE.pdf. Accessed on 30 April 2020. Impronta Etica. (2016). Le linee guida per la misurazione dell’impatto sociale. Una guida pratica per le organizzazioni. Bologna, Italy: Impronta Etica. Jackson, E. T. (2013). Evaluating social impact bonds: Questions, challenges, innovations, and possibilities in measuring outcomes in impact investing. Community Development, 44(5), 608–616. Jupp, B. (2017). Next Step: Develop Social Investment Partnerships (PIRU Blog, 15). Retrieved from https://blogs.lshtm.ac.uk/piru/2017/03/15/ next-step-develop-social-investment-partnerships/. Accessed on 30 April 2020. Khovrenkov, I. (2018) Assessing Social Impact Bonds in Canada. Johnson Shoyama Graduate School of Public Policy (2018). Retrieved from https:// www.schoolofpublicpolicy.sk.ca/research/publications/policy-brief/Assess ing-social-impact-bonds-in-Canada.php. Accessed on 30 April 2020. KPMG. (2016). L’impact économique de l’action de l’Adie. Paris, France: KPMG. Retrieved from https://home.kpmg/fr/fr/home/insights/2016/ 07/impact-economique-action-adie.html. Accessed on 30 April 2020. KPMG. (2018). Social impact bonds: Foreign best practices. Retrieved from https://home.kpmg/be/en/home/insights/2018/06/social-impactbonds-foreign-best-practices.html. Accessed on 30 April 2020. Kvist, J. (2015). ESPN thematic report on social investment–Denmark. Brussels: European Commission. Retrieved from http://ec.europa.eu/social/keyDoc uments.Jsp. La Torre, M., Trotta, A., Chiappini, H., & Rizzello, A. (2019). Business models for sustainable finance: The case study of social impact bonds. Sustainability, 11(7), 1887:1–1887:23. https://doi.org/10.3390/su11071887. Lowe, T., & Wilson, R. (2015). Playing the game of out-comes-based performance management: Is gamesmanship inevitable? Evidence from theory and practice. Social Policy & Administration, 51(7), 981–1001. https://doi.org/ 10.1111/spol.12205. Loxley, J., & Hajer, J. (2019). Public–private partnerships, social impact bonds, and the erosion of the state in Canada. Studies in Political Economy, 100(1), 18–40. https://doi.org/10.1080/07078552.2019.1612167.

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Maier, F., & Meyer, M. (2017). Social Impact Bonds and the perils of aligned interests. Administrative Sciences, 7 (3), 24:1–24:10. https://doi.org/10. 3390/admsci7030024. Maier, F., Barbetta, G. P., & Godina, F. (2018). Paradoxes of social impact bonds. Social Policy & Administration, 52(7), 1332–1353. https://doi.org/ 10.1111/spol.12343. Maiolini, R., Rullani, F., & Versari, P. (2013). Rendere sociali le imprese. Impatto sociale, confini dell’impresa e rete di stakeholder. Impresa Sociale, 0–1, 1–20. Malcolmson, J. D. (2014). Social impact bonds: Cleared for landing in British Columbia. CUPE Research. Canada: BC Region. Mazzullo, A. (2019). Diritto dell’Imprenditoria Sociale. Dall’Impresa Sociale all’Impact Investing. Turin, Italy: Giappichelli Editore. McHugh, N., Sinclair, S., Roy, M., Huckfield, L., & Donaldson, C. (2013). Social impact bonds: A wolf in sheep’s clothing? Journal of Poverty and Social Justice, 21(3), 247–257. https://doi.org/10.1332/204674313X13812372 137921. Méndez-Suárez, M., Monfort, A., & Gallardo, F. (2020). Sustainable banking: New forms of investing under the Umbrella of the 2030 agenda. Sustainability, 12(5), 2096:1–2096:13. https://doi.org/10.3390/su12052096. Ministère de l’Economie et des Finances. (2016). Conférence sur l’investissement a impact social. Paris, France: Ministère de l’Economie et des Finances. Retrieved from https://www.economie.gouv.fr/files/files/PDF/24112016_ DPVF_conference_investissement_impactsocial.pdf. Accessed on 30 April 2020. Neyland, D. (2018). On the transformation of children at-risk into an investment proposition: A study of Social Impact Bonds as an anti-market device. The Sociological Review, 66(3), 492–510. Nicholls, A., Paton, R., & Emerson, J. (2015). Social finance. Oxford, UK: Oxford University Press. O’Flynn, P., & Barnett, C. (2017). Evaluation and Impact Investing: A Review of Methodologies to Assess Social Impact. Brighton, UK: Institute of Development Studies. OECD. (2016). Social impact bonds: State of play & lessons learnt. Paris, France: OECD Publishing. Osborne, S. P. (2018). From public service-dominant logic to public service logic: Are public service organizations capable of co-production and value cocreation? Public Management Review, 20(2), 225–231. https://doi.org/10. 1080/14719037.2017.1350461. Pennsylvania Economy League. (2015). Pay for Success in the U.S. Summaries of Financed Projects. Retrieved from https://pelcentral.org/wp-content/ uploads/2013/01/summary_of_pay_for_success_social_impact_bonds_july_2 015.pdf. Accessed on 30 April 2020.

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CHAPTER 4

Green Bonds Capital Returns: The Impact of Market and Macroeconomic Variables Alessandra Ortolano and Eliana Angelini

4.1

Introduction

The general attention on the environmental sustainability, boosted by the leading objectives of a low-carbon and a climate-resilient economy, stated by the 2030 Agenda and Sustainable Development Goals (United Nations 2015) and the Paris Climate Agreement (UNFCCC 2015), has also involved financial markets. In more detail, sustainable finance deals with two imperatives: funding and accelerating a more inclusive and resource-efficient growth; strengthening financial stability and pricing, by improving the assessment and management of long-term material risks and intangible drivers of value creation, including those related to environmental, social, and governance (ESG) factors (Thimann 2017).

A. Ortolano (B) · E. Angelini Department of Economic Studies, D’Annunzio University of Chieti-Pescara, Chieti-Pescara, Italy e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. La Torre and H. Chiappini (eds.), Contemporary Issues in Sustainable Finance, Palgrave Studies in Impact Finance, https://doi.org/10.1007/978-3-030-65133-6_4

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In this context, the European Investment Bank launched the first Green Bond in 2007. As stated by ICMA1 (2018), Green Bonds are financial instruments, whose proceeds will be exclusively used to finance or re-finance, in part or in full, new and/or existing eligible green projects. More specifically they can be better described by the four pillars of the ICMA Green Bond Principles, namely: 1. Use of Proceeds 2. Process for Project Evaluation and Selection 3. Management of Proceeds 4. Reporting. The innovative aspect of Green Bonds is that, labeling a specific bond as “green” under transparent and independent criteria, they allow efficient capital intermediation between investors and green projects (Kochetygova and Jauhar 2014).2 Our focus on Green Bonds is due to the key role they might have in the development of a low-carbon economy. In particular, they are deemed as instruments that can be adopted in order to implement the intertemporal burden sharing of climate mitigation (Sachs 2014). In this regard, also central banks have a key role in the promotion of these instruments (Sartzetakis 2020), among the involvement for the growth of an ESG (Environmental, Social, Governance) finance.3 Some researchers (e.g. Paranque and Revelli 2019) give them even an ethical purpose, embedding Green Bonds in a social project of the collective governance. In general, the attention of investors for sustainability is reflected by the impact on risk premia and their linkage with the creditworthiness of issuers (Höck et al. 2020). As demonstrated (Glavas 2020), the announcement of Green Bonds issuance is also welcome in the stock markets, especially under stronger climate-related regulation frameworks. In this context, for instance, literature has demonstrated that Green Bonds of companies which accumulate funds to finance infrastructure works which are involved in huge projects in the areas of energy efficiency, alternative energy or utility service, are less vulnerable to global shocks, with respect to bonds issued by firms not working to these kind of projects (Shaydurova et al. 2018).

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In 2019 the market reached USD257.7bn with 51% growth on 2018. The European segment of Green Bonds is almost a half of the global one. In particular, in 2019 the total amount issued in Europe raised by 74% year-on-year, reaching a total of USD116.7bn (Climate Bonds Initiative 2020).4 The increasing role of these instruments has been also testified by the introduction of a segment of the Extra Mot PRO dedicated to them, in the Italian Stock Exchange Borsa Italiana. The focus on this market is due to the potential importance that financing sustainable projects has for the Italian economy and its interconnections with the international ones: in fact, there is a relevant percentage of supranational, national and corporate international Green Bonds listed in this stock exchange. Specifically, Borsa Italiana places itself on an international dimension, as it has become part of the Sustainable Stock Exchanges Initiative, supported by the UN, in order to boost the transition to a sustainable economy. Moreover, with reference to the period of our analysis, the Italian Stock Exchange belonged to the London Stock Exchange Group,5 that has signed the Paris Pledge for Action, has joined the Climate Bonds Initiative and follows ICMA Green Bonds Principles. Our study intends to analyze the impact of market and macroeconomic variables, on the daily capital returns of Green Bonds. Specifically, we inspire our research to the literature made on conventional bonds, in order to assess the peculiarities of the green ones. In particular, our sample deals with securities traded over the period January 2016–May 2019 in Borsa Italiana, but our observation units grow over time, as the bonds start to be listed. In more detail, literature has observed as impacting factors on conventional bonds, variables like stock market (e.g., Tolikas 2018; Chiang et al. 2015), government bond yields (e.g., Graham et al. 2014; Castagnetti and Rossi 2013), or macroeconomic variables (e.g., Zhou et al. 2019; Huang et al. 2019). Consistently, we intend to illustrate the influence of factors like FTSE MIB (a stock index), Euro/Dollar exchange (as macroeconomic factor), the slope of European government bonds yield curve (as a measure of liquidity), the oil price (as a traditional energy source), or the international volatility. Through the adoption of Arellano–Bond dynamic panel regressions, we observe a significant negative autocorrelation of the dependent variable for all the period of analysis, whereas the significance of other factors like government bond yield slope, or the foreign exchange rate is not the same over time. Peculiarities of the market emerge, like the lacking

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influence of stocks. We also state that these instruments, even though are valid alternative to conventional bonds in order to build safer portfolios, in times of unusual volatility are exposed as well. The added value of our paper is given by the analysis of the daily capital return of these securities, with reference to factors really connected to systemic risk, whose impact has been observed in the conventional bonds market. We also insert the one-day lagged dependent variable, in order to analyze the potential presence of a market trend. For this reason, we deem interesting proceeding our research by taking into account the peculiarities of the segment, in particular the negative autocorrelation and the weak relation with the stock market. Furthermore, we point out that these instruments, even though seem to be valid alternatives to conventional bonds, can be negatively affected in times of unusual market turbulence. We think that all these issues are important elements to be analyzed, during the construction of more “sustainable” portfolios. The chapter proceeds as follows: Sect. 4.2 shows the literature review divided into two sub-sections: Green bonds: general aspects (Sect. 4.2.1) and Market variables (Sect. 4.2.2). Next to Sect. 4.3, Sample and Data, there is the Sect. 4.4 where we describe the model adopted. In Sect. 4.5, we illustrate and comment the main findings of the analysis. The chapter ends with Sect. 4.6 where we present our final remarks and purposes for future research. Finally References and the Annex are shown.

4.2

Review of Literature

4.2.1

Green Bonds: General Aspects

Chiesa and Barua (2019), focusing on corporate Green Bonds issuance from 2010 to 2017, explore the factors affecting the size of borrowing. They employ a set of tridimensional elements, namely security, issuer and market characteristics and investigate the consistency of the effects across emerging and non-emerging markets. Their findings suggest that, in general, issue size is positively related to coupon rate, credit rating, collateral availability, issuer’s sector and financial health. The authors highlight that the determinants of Green Bond supply are significantly heterogeneous: this fact suggests the need of market specific policies instead on “one-size-fits-all”, in order to expand the size of the global market of Green Bonds.

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Tu et al. (2020) deem Green Bonds as useful tools of funding for lowcarbon projects in Vietnam. In this regard the analysis investigates various solutions for the development of the Vietnamese market of Green Bonds, adopting the analytic hierarchy process method that is a multi-criteria decision-making approach. Their main findings show that infrastructural and economic factors play the most important role in developing the market in Vietnam, along with the presence of an efficient monetary policy and high interest rates on Green Bonds. More negligible are political, social or cultural factors. Banga (2019) examines the potential of Green Bonds in mobilizing adaptation and mitigation finance, for developing countries. He identifies both key drivers of the Green Bond market and the barriers for the developing countries. The results suggest that the latter are due to the lack of appropriate institutional arrangements for Green Bond management, the issue of minimum size, and high transactions costs associated with the bonds’ issuance. The author proposes an efficient use of multilateral and national development banks, as intermediary institutions for local green bond management; he also recommends local governments to provide local Green Bond issuers with guarantees, aimed at covering the transaction costs associated with the issuance of these bonds. Bagnoli and Watts (2020) observe wholesalers’ decision of producing socially responsible activities and, above all, the choice of financing them by issuing Green Bonds or by charging a premium to the retailers who buy their products. They start from the idea that the retailer can profitably fund its socially responsible activities by charging more for its product, because end consumers are willing to pay more, to support those activities. They focus on the wholesalers, because it is more difficult to fund socially responsible activities indirectly, by selling to retailers rather than selling directly to socially aware end consumers. This added difficulty allows the authors to highlight incentives to issue Green Bonds that are not relevant to a retailer’s decision. They find that in less competitive retail markets, when retailers can “skim” more of the premium that end consumers pay for socially responsible products, Green Bonds provide additional funds to cover the cost of a wholesaler’s socially responsible activities. Similar incentives arise if the wholesaler’s input is a small component of the end consumers’ product, or if it is difficult for end consumers to identify the wholesaler’s socially responsible activities.

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4.2.2

Green Bonds: Market Variables

Below we present a literature review that focused on the analysis of Green Bonds and market variables by a side, and the comparison with conventional bonds on the other. In more detail, Tolliver et al. (2020) assess the impact that capital market growth drivers and Nationally Determined Contributions to the Paris Agreement have on Green Bond issuance volumes. They employ a structural equation model observing a panel dataset of over $300 billion in green bonds issued in 49 countries between 2007 and 2017 and combine unique drivers of Green Bond market growth, in addition to factors that similarly affect the conventional bond segment. They find that Nationally Determined Contributions scores exert the largest positive and statistically significant impacts among observed variables. These results suggest that Nationally Determined Contributions and other macroeconomic and institutional factors, are driving to the growth of Green Bond issuances that will finance climate and sustainability investments through the future. Pham and Luu Duc Huynh (2020) observe the link between investor attention and Green Bond market performance. The investor attention is measured by Google Search Volume Index (GSVI) of the main keyword “Green bond”. They find time-varying feedback effects of the independent variables on the Green Bond returns and volatility. This issue has important implications, like the fact that investors can rely on market attention as a useful tool to predict Green Bond performance and highlights the relevance of adequate information and attention for directing financial flows toward sustainable investments. Hyun et al. (2020) observe how greenness information is priced in the Green Bond market. They measure the Green Bond premium as the liquidity adjusted ask yield spread between a Green Bond and its synthetic conventional bond. On average, they find no significant green premium or discount that is robust to different estimation methods, but they do observe robust evidence that greenness information indicators significantly affect the level of the Green Bond premium. Therefore, the authors suggest that greenness information indicators could benefit the development of the Green Bond market. Febi et al. (2019) observe the impact of liquidity risk on the Green Bonds yields and compare it with conventional bond market. According to the authors, the attention to liquidity in Green Bond market is due to

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two reasons: its disproportional thinness, and its unclear solvency profile. Liquidity is measured both through LOT and bid-ask spread. Despite the greater demand over the supply, they find that Green Bonds are more liquid than conventional ones over the period 2014–2016. They moreover confirm a positive correlation between liquidity risk and Green Bonds yields, but evidence that this effect gets negligible over time. Zerbib (2019) studies the impact of non-pecuniary motivates, specifically pro-environmental preferences, on bond market prices, in a study among July 2013 and December 2017. More specifically, he compares each Green Bond with a counterfactual conventional bond, in order to isolate the pro-environmental component. He finds out a significant, but low, premium that highlights the opportunity for issuers to expand their bondholders, especially with reference to low-rated and financial bonds. Li et al. (2019) focus their attention on the Chinese Green Bond market, over the period January 2016–September 2018. They analyze the impact of credit ratings, corporate social responsibility (CSR) and of green certification on yield spread. The authors show the significance of all these variables and highlight the implications with reference to lower yields, because of better long-term perspectives. In particular they state the importance of a third-party verification, in order to have proof of transparent information disclosure in the use of proceeds, potential risks, and corporate governance. Nanayakkara and Colombage (2019) investigate the price difference of Green and conventional bonds, in a worldwide study for the period 2016–2017. In particular they adopt the Option-Adjusted Spread (OAS) and control for the influence of bond specific, macroeconomic and global factors. They find that Green Bonds are traded at a premium of at least 63 bps, showing the investors’ interest for these instruments as a source of portfolio diversification and important implications for stakeholders, in order to support the market growth. Gianfrate and Peri (2019) analyze the convenience to issue bonds labeled as “green”, versus conventional ones. Through a propensity score matching approach, made on European bonds over the period 2013– 2017, they assess that there’s a significance convenience to issue Green Bonds, expressed by lower interests paid annually to investors of 18 basis points. They also show that this advantage is achieved both by corporate and non-corporate entities and overcomes the extra costs, needed to obtain the “green” certification.

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Broadstock and Cheng (2019) study the determinants of the timevarying correlation between the Green and Black Bond markets over the period 28 November 2008–31 July 2018. They adopt a two-stage sequential methodology: in the first they extract dynamic conditional correlations in order to characterize underlying market dynamics, while in the second they apply dynamic model averaging to establish the determinants of market correlations. They find that the correlation changes over time and is sensitive to financial market volatility, economic policy uncertainty, daily economic activity and oil prices. In particular, the authors highlight three phases in the connection between markets: the first shows a shift from negative to positive correlation in mid-2013; across phases one and two there is no strong adjustment in the significance of the determinants; finally the third, that starts in the mid-2016, evidences that macroeconomic conditions increase their role in the connection between Green and conventional bond price benchmarks. Reboredo (2018) examines the co-movement between the Green Bond and financial markets (i.e., corporate and treasury fixed income, stock and energy commodity markets) over the period October 2014– August 2017, in order to verify the implications in terms of price spillovers and the diversification benefits of Green Bonds. The author analyzes the dependence structure between the Green Bond and financial markets using static and dynamic copula functions, given that they allow to discern between average dependence and dependence in times of great upward or downward market price movements. He finds analogies with corporate and treasury bond markets and weak relations with stocks and energy commodities. He also highlights that Green Bonds have a positive impact on diversification in stock and energy markets and a negligible one for treasury and corporate bonds. Hachenberg and Schiereck (2018) observe the risk-return profile of Green Bonds compared to conventional ones. To this purpose, they match daily i-spreads of green-labeled and similar non-green-labeled bonds and look at their pricing differentials. They find that rating classes AA–BBB of Green Bonds, trade marginally tighter for the respective period compared to non-green bonds of the same issuers. Furthermore, financial and corporate Green Bonds trade tighter than their comparable non-green bonds. The authors also observe that industry and ESG rating have a significant influence on the difference, contrary to issue size, maturity and currency.

4

4.3

GREEN BONDS CAPITAL RETURNS …

99

Sample and Data

Our sample is made by 50 Green Bonds (see Table 4.1) listed in Borsa Italiana. The observations deal to period 2016–2019. As the number of securities listed grow over time, we have: ● ● ● ●

12 22 48 50

bonds bonds bonds bonds

for for for for

2016 2017 2018 2019

(January–December) (January–December) (January–December) (January–May).

As concerns the independent variables, our sources of data are ECB, S&P and Investing.com databases. Table 4.1 shows the complete Green Bonds sample. Most of the securities are issued by supranational entities; a little percentage is constituted by corporate and national issuers. Figure 4.1 illustrates graphically the daily capital return of Green Bonds, for each year of observation and according with data availability. As shown, the market presents very low returns, close to zero and sometimes negative. The same findings are reported in Table 4.2 through descriptive statistics.

4.4

Methodology

We adopt the Arellano and Bold (1991) model in order to insert the lagged dependent variable among regressors. Moreover, this variable is used as instrumental for the estimation of all the covariates. The GMM method adopted by the model allows to obtain more efficiency in the estimations. This model lets us also control for the impact of the previous value of capital return on the current one, with the purpose to detect the potential presence of a market trend. We adopt a dynamic panel model for each year of observation, using daily data. The referring equation is the following: RETURNi,t = β0 + ϕRETURNi,t−1 + β1 FTSE MIBt + β2 EUR/USD FXt + β3 BRENT FUTURESt + β4 GOVSLOPEt + β5 VIXt + ei,t

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Table 4.1 Green Bonds sample

ISIN code

Issuer

XS1500338618 US298785HD17 XS1087815483 XS1442211923 XS1442212145 XS1488416592 XS1508503809 XS1488416329 XS1268337844 XS1586107101 IT0005314544 XS1551293019 XS1314336204 XS1572222526 XS1641457277 US298785HM16 XS1550149204 XS1704789590 US500769GF56 US500769GU24 US500769HD99 US500769HP20 FR0013234333 XS1536786939 XS1653777612 XS1315186921 XS1673620875 XS1639852505 XS1639838694 XS1550144668 XS1550135088 XS1593538694 XS1721365671 XS1609294308 BE0000346552 IT0005346579 XS1811852109 XS1878833695 XS1750986744 XS1792195908

SUPRANATIONAL SUPRANATIONAL CORPORATE SUPRANATIONAL SUPRANATIONAL SUPRANATIONAL SUPRANATIONAL SUPRANATIONAL CORPORATE CORPORATE NATIONAL SUPRANATIONAL SUPRANATIONAL SUPRANATIONAL SUPRANATIONAL SUPRANATIONAL CORPORATE CORPORATE CORPORATE CORPORATE CORPORATE CORPORATE NATIONAL NATIONAL CORPORATE SUPRANATIONAL SUPRANATIONAL SUPRANATIONAL SUPRANATIONAL SUPRANATIONAL SUPRANATIONAL SUPRANATIONAL SUPRANATIONAL SUPRANATIONAL NATIONAL NATIONAL SUPRANATIONAL SUPRANATIONAL CORPORATE CORPORATE

(continued)

4

Table 4.1 (continued)

101

GREEN BONDS CAPITAL RETURNS …

ISIN code

Issuer

XS1881533563 XS1766612672 IT0005333551 XS1813572663 XS1913451776 XS1830925886 XS1767083360 XS1767082800 US459058GL16 XS1917880285 XS1793242295

CORPORATE CORPORATE CORPORATE SUPRANATIONAL SUPRANATIONAL SUPRANATIONAL SUPRANATIONAL SUPRANATIONAL SUPRANATIONAL SUPRANATIONAL SUPRANATIONAL

2016

2017 0.06

0.2

0.05 0.15 0.04 0.03

0.1

0.02 0.05 0.01 0

0 JAN

FEB

MAR

APR

MAY

JUN

JUL

AUG

SEP

OCT

NOV

DEC

JAN

-0.01

FEB

MAR

APR

MAY

JUN

JUL

AUG

SEP

OCT

NOV

DEC

-0.05 -0.02 -0.1

-0.03

2018

2019

0.04

0.045

0.03

0.04

0.02

0.035 0.03

0.01

0.025

0 -0.01 -0.02 -0.03

JAN

FEB

MAR

APR

MAY

JUN

JUL

AUG

SEP

OCT

NOV

DEC

0.02 0.015 0.01 0.005

-0.04

0

-0.05

-0.005

-0.06

-0.01

JAN

FEB

MAR

APR

MAY

Fig. 4.1 Green Bonds capital returns (Source Authors’ elaborations of Borsa Italiana data)

The dependent variable is represented by the daily percent capital return of Green Bonds, calculated from daily prices. The covariates, shown below, are daily market and macroeconomic variables and are also expressed in percentage:

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Table 4.2 Descriptive statistics Table 4.2(a) Descriptive Statistics of Daily Green Bonds Capital Returns 2016 Min. 1st Qu. Median Mean 3rd Qu. Max. −14.63935 0.00000 0.00000 0.01966 0.00000 42.63758 Table 4.2(b) Descriptive Statistics of Daily Green Bonds Capital Returns 2017 Min. 1st Qu. Median Mean 3rd Qu. Max. −10.50345 −0.01351 0.00000 0.00928 0.02547 47.30258 Table 4.2(c) Descriptive Statistics of Daily Green Bonds Capital Returns 2018 Min. 1st Qu. Median Mean 3rd Qu. Max. −9.358263 0.000000 0.000000 −0.003672 0.000000 17.230598 Table 4.2(d) Descriptive Statistics of Daily Green Bonds Capital Returns 2019 Min. 1st Qu. Median Mean 3rd Qu. Max. −3.28064 0.00000 0.00000 0.01554 0.00000 4.99012

● ● ● ● ●

RETURNt −1 (one-day lagged Green Bond return) FTSE MIB (stock index) EUR/USD (Euro/USDollar exchange rate) BRENT FUTURES (futures on the Brent oil) GOVSLOPE (slope of the yield curve of EU AAA government bonds)6 ● VIX (CBOE Volatility index). Definitively, our study allows us to study the relation between Green Bonds and: ● their previous capital returns ● fundamental variables (i.e., foreign exchange rate and EU government bonds yields) ● stock markets ● traditional energy commodities ● the volatility of international markets. The specific variables chosen are closer to the European market, as we analyze the Green Bonds listed in Borsa Italiana. The only exception is given by VIX, inserted in order to verify the influence of the leading American market. As stated, the covariates adopted are inspired by literature on conventional bonds (both corporate and sovereign, consistently to our “green” sample’s composition). In particular, several studies observe the relation

4

GREEN BONDS CAPITAL RETURNS …

103

between bonds and both macroeconomic and market factors like interest rates, exchange rates, market volatility (e.g., Aboura and Chevallier 2013; Bansal et al. 2014; Viceira 2012; Driessen et al. 2003). Under an international point of view of investment, literature has shown the impact of currency movements (Francová, 2017) to bonds and also the spillovers between the two markets (Sahoo et al. 2019). A large strand of literature deals with the analysis of the co-movement between the stocks and bonds. Specifically, researchers have shed light on the relevance of macroeconomic factors affecting the correlation (Aslanidis and Martinez 2020; Park et al. 2019); in more detail, the co-movement between stock and bond market has changed over time (Chiang et al. 2015), showing an increase during times of distress, especially with reference to European peripheral countries and with a deeper impact of the global stock market rather than domestic one (Skintzi 2019). Researchers have also illustrated the relationship between bonds and commodity market (e.g. Henriksen et al. 2019), with particular attention to oil price: this variable has an important impact on sovereign returns (Balcilar et al. 2020; Kang et al. 2014), both for exporters and importers (Morrison 2019) and on corporate bond yields, both energy and nonenergy, although in different way (Apergis 2019).

4.5

Results and Discussion

Results of our regressions are shown in Tables 4.3, 4.4, 4.5, and 4.6. In particular, we note that the lagged variable is significant for all the four years of observation, with a negative sign. This autocorrelation of the yield is also confirmed by the negative sign of the Pearson correlation shown in Tables 4.7, 4.8, 4.9, and 4.10 in the Annex. This issue is particularly interesting in terms of discussion. In fact, according to this result, we deem that Green Bond market has opposite short-term expectations on the bonds returns, so the current behaviors are negatively influenced by previous performances. Another relevant result deals with the EU government yield slope variable that is a measure of the liquidity of the market. In more detail, a flatter slope indicates greater liquidity in the market as a whole. Specifically, our analysis shows significant negative relation between Green Bonds returns and the EU AAA-government bond curve slope each year, except for 2017 (see Tables 4.3, 4.4, and 4.6). As proved (Ericsson and

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Table 4.3 Results 2016

Variable

Estimate

INTERCEPT

1.622966*** (.6434928) −.1045692*** (.0282165) −.0115107 (.0098533) −.0120729 (.030741) 0.0078704 (.0062923) −2.899428** (1.154487) −.0036605 (.002609)

LAG(RETURN) FTSE MIB EUR/USD FX BRENT FUTURE GOVSLOPE VIX

z-value

Pr(> |z|)

2.52

0.012

−3.71

0.000

−1.17

0.243

−0.39

0.695

1.25

0.211

−2.51

0.012

−1.40

0.161

Observations: 3060 Wald chi2(6): 25.82 Prob > chi2: 0.0002 Note Standard Deviations are indicated in parentheses. Levels of significance: ***p < 0.01, **p < 0.05, *p < 0.1

Table 4.4 Results 2017

Variable

Estimate

z-value

Pr(> |z|)

INTERCEPT

−.0393221 (.9470745) −.1686359*** (.0218892) −.030378* (.0161492) −.0720831*** (.0239745) 0.0026281 (.0077166) 0.0484613 (1.258983) 0.0003726 (.0017673)

−0.04

0.967

−7.70

0.000

−1.88

0.060

−3.01

0.003

0.34

0.733

0.04

0.969

0.21

0.833

LAG(RETURN) FTSE MIB EUR/USD FX BRENT FUTURE GOVSLOPE VIX

Observations: 5455 Wald chi2(6): 73.72 Prob > chi2: 0.0000 Note Standard Deviations are indicated in parentheses. Levels of significance: ***p < 0.01, **p < 0.05, *p < 0.1

4

Table 4.5 Results 2018

GREEN BONDS CAPITAL RETURNS …

Variable

Estimate

INTERCEPT

1.260556* (.6516594) LAG(RETURN) −.1807273*** (.0148588) FTSE MIB −.0075676 (.0071073) EUR/USD FX −.036267** (.0152816) BRENT 0.0042675 FUTURE (.0045127) GOVSLOPE −1.972155* (1.014489) VIX −.0022942** (.0009207) Observations:11.999 Wald chi2(6): 166.93 Prob > chi2: 0.0000

z-value

105

Pr(> |z|)

1.93

0.053

−12.16

0.000

−1.06

0.287

−2.37

0.018

0.95

0.344

−1.94

0.052

−2.49

0.013

Note Standard Deviations are indicated in parentheses. Levels of significance: ***p < 0.01, **p < 0.05, *p < 0.1

Table 4.6 Results 2019

Variable

Estimate

z-value

Pr(> |z|)

INTERCEPT

1.542319** (.6798787) −.1005435*** (.0263678) 0.0223425 (.0166473) 0.0235911 (.0295381) 0.0029543 (.0100577) −3.090686** (1.380513) −.0003076 (.0018665)

2.27

0.023

−3.81

0.000

1.34

0.180

0.80

0.424

0.29

0.769

−2.24

0.025

−0.16

0.869

LAG(RETURN) FTSE MIB EUR/USD FX BRENT FUTURE GOVSLOPE VIX

Observations: 4500 Wald chi2(6): 21.24 Prob > chi2: 0.0017 Note Standard Deviations are indicated in parentheses. Levels of significance: ***p < 0.01, **p < 0.05, *p < 0.1

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Renault 2006), illiquidity is positive correlated with default risk and so with bond credit spread: this issue is negatively reflected in securities’ price. Our output testifies that the more the curve slope is low, the more the market is liquid, the higher are Green Bonds capital returns and vice versa. This relation is contextualized in our period of analysis, characterized by stationary value of interest rates around the zero level. The EUR/USD exchange rate is significant for 2017 and 2018 (see Tables 4.4 and 4.5) and has a negative sign: this result testifies the negative impact of an appreciation of the Euro currency against the Dollar on Green Bonds listed in a European market. There are no significant estimates for the stock index parameter, except for 2017, when we have a 10% value of significance (see Table 4.4), while Brent oil futures variable is never significant. The last three results are consistent with Reboredo and Ugolini (2019), who state the impact of currency on Green Bonds and, on the other side, the weak relation with stock market and the negligible impact of oil. As concerns the VIX variable, it is a proxy of the volatility of international markets and it shows a negative significant sign just in 2018 (see Table 4.5). This is an interesting result, because 2018 was characterized by the comeback of very high levels of volatility over financial markets.7 Our output suggests that, even though the green segment of bonds seems to be less exposed to the negative impact of the variability of markets (Martinez Farina 2019), it can be similarly affected in times of unusual turbulence.

4.6

Conclusions

Our study has observed the impact of market and macroeconomic variables on the Green Bonds listed in Borsa Italiana. In particular, we have calculated the daily capital returns of Green Bonds over the period 2016–2019 and adopted Arellano–Bond dynamic panel regressions, in order to analyze their determinants, including their previous values. Our main results show that variables affecting Green Bonds change over time and in some cases present analogies with conventional bonds: for instance, the negative significant impact of the EU government bonds yields slope, stated in 2016 and 2018, testifies that the level of liquidity of market influences the default credit spread of bonds and so their price.

4

GREEN BONDS CAPITAL RETURNS …

107

We highlight that, conversely to conventional bonds, green ones have a weak relation with stock market returns. Notwithstanding, in times of exceptional international volatility like 2018, they prove to be exposed as well. An interesting output is referred to the lagged dependent variable: the return shows a negative autocorrelation that could be a starting point of discussion about the short-term expectations of investors on Green Bonds prices. One limitation of the research is the focus on the Green Bonds listed in the Italian Stock Exchange: we deem that our study could be extended through the analysis of European and extra-European markets. In particular, it could be interesting to proceed the research carrying out comparison with the developing countries. More specifically, with reference to the latter, it could be fitting to focus on longer maturities: in fact, a macroeconomic environment characterized by low interest rates, low inflation rates, high short-term volatility, and strong value of the dollar, seems to contribute to phasing more long-term green securities into the market of these countries (Flaherty et al. 2017). As concerns the perspectives for future research we deem useful investigating the peculiarities of the segment, specifically the negative autocorrelation and the weak relation with the stock. Furthermore, the informative value of the study would be enhanced by adding a peculiar variable, like the environmental rating: in fact, as demonstrated, environmental scores show a significant impact on bond return, suggesting that high environmental scores lower the cost of debt financing for small firms; moreover ESG is complementary to credit ratings in assessing credit quality, since traditional credit ratings cannot explain the ESG effects in predicting future bond return (Jang et al. 2020). We deem that our research, highlighting market aspects of Green Bonds, contributes to the information investors need, in order to build portfolios that integrate ESG criteria, without sacrificing the financial performance (Pereira et al. 2019).

Notes 1. ICMA is the acronym for International Capital Market Association. 2. With refence to the criteria of labeling a bond as “green”, the framework is given by the voluntary guidelines of “ICMA Green Bonds Principles”. The European Union is working for a standardization of these instruments

108

3. 4. 5. 6.

7.

A. ORTOLANO AND E. ANGELINI

and June 2019 the TEG (Technical expert group) published its Report on EU Green Bond Standard. See Visco (2019). Climate Bonds Initiative is a no-profit international organization that mobilizes the global bond market for climate change solutions. In date 9 October 2020 the London Stock Exchange has sold Borsa Italiana to Euronext for 4.3 bn euros (Stafford and Dempsey 2020). The slope has been calculated as the difference between the 10 Years EU AAA government bonds yield curve and the 5 Years EU AAA government bonds yield curve. Many factors have caused the exceptional level of volatility over the markets, in particular the commercial duties issue between USA and China, or the rising interest rates in the US (Lops 2018; Renninson 2018; Ungarino 2018).

Annex See Tables 4.7, 4.8, 4.9, and 4.10.

Return

1.000000000 −0.030836483 −0.024247710 0.008670000 0.002198528 −0.005218352 −0.03230903

RETURN Lag(RETURN) FTSE MIB EUR/USD BRENT FT. GOVSLOPE VIX

0.00867000 0.02507116 −0.03366528 1.00000000 0.01678181 0.01311445 −0.003671722

−0.030836483 1.000000000 0.009045971 0.025071163 0.003604025 −0.005592924 0.009104106

−0.024247710 0.009045971 1.000000000 −0.033665276 0.421762448 0.018065084 −0.5197466

EUR/USD

Lag(RETURN) FTSE MIB

Correlation matrix 2016

Variable

Table 4.7

0.002198528 0.003604025 0.421762448 0.016781812 1.000000000 0.043068742 −0.3302764

BRENT FT.

−0.005218352 −0.005592924 0.018065084 0.013114453 0.043068742 1.000000000 −0.001929332

GOVSLOPE

−0.03230903 0.009104106 −0.5197466 −0.003671722 −0.3302764 −0.001929332 1.000000000

VIX 4 GREEN BONDS CAPITAL RETURNS …

109

Return

1.000000000 −0.086394167 −0.015967027 −0.024253973 0.009812668 −0.007468310 −0.009015071

RETURN Lag(RETURN) FTSE MIB EUR/USD BRENT FT. GOVSLOPE VIX

−0.024253973 0.025155012 −0.050708819 1.00000000 0.001749217 −0.063677994 0.02943717

−0.086394167 1.000000000 0.0145370171 0.0251550124 0.0005347253 −0.012294084 −0.007779352

−0.01596703 0.01453702 1.000000000 −0.05070882 0.02655750 0.02903147 −0.4069402

EUR/USD

Lag(RETURN) FTSE MIB

Correlation matrix 2017

Variable

Table 4.8

0.0098126681 0.0005347253 0.0265575028 0.0017492173 1.000000000 −0.054369956 −0.0409884

BRENT FT.

−0.00746831 −0.01229408 0.02903147 −0.06367799 −0.05436996 1.000000000 0.02305805

GOVSLOPE

−0.009015071 −0.007779352 −0.4069402 0.02943717 -0.0409884 0.02305805 1.00000000

VIX

110 A. ORTOLANO AND E. ANGELINI

Return

1.000000000 −0.290784214 −0.001204059 −0.035624839 0.005746846 −0.029370748 −0.03863444

RETURN Lag(RETURN) FTSE MIB EUR/USD BRENT FT. GOVSLOPE VIX

−0.035624839 0.004097033 0.073096776 1.00000000 0.076532936 −0.010598303 −0.149417

−0.290784214 1.000000000 0.010957203 0.004097033 −0.009145327 −0.031587007 −0.01971702

−0.001204059 0.010957203 1.000000000 0.073096776 0.319415355 0.035281722 −0.3508562

EUR/USD

Lag(RETURN) FTSE MIB

Correlation matrix 2018

Variable

Table 4.9

0.005746846 −0.009145327 0.319415355 0.076532936 1.000000000 0.135664487 −0.2367015

BRENT FT.

−0.02937075 −0.03158701 0.03528172 −0.01059830 0.13566449 1.000000000 0.02643373

GOVSLOPE

−0.03863444 −0.01971702 −0.3508562 −0.149417 −0.2367015 0.02643373 1.00000000

VIX 4 GREEN BONDS CAPITAL RETURNS …

111

YIELD Lag(YIELD) FTSE MIB EUR/USD BRENT FT. GOVSLOPE VIX

Variable

Table 4.10 Lag(RETURN)

FTSE MIB

EUR/USD

BRENT FT.

GOVSLOPE

VIX

1.000000000 −0.238768290 −0.008279618 0.007557494 −0.01312552 −0.013463291 −0.03863444 −0.238768290 1.000000000 0.020953996 0.006342336 0.01341696 −0.005203277 −0.01971702 −0.008279618 0.020953996 1.000000000 0.107786187 0.39817312 0.218284326 −0.3508562 0.0075574940 0.006342336 0.107786187 1.00000000 0.09286731 0.065556441 −0.149417 −0.013125524 0.013416965 0.398173115 0.092867311 1.000000000 0.140532010 −0.2367015 −0.013463291 −0.005203277 0.218284326 0.065556441 0.14053201 1.000000000 0.02643373 −0.03863444 −0.01971702 −0.3508562 −0.149417 −0.2367015 0.02643373 1.00000000

Return

Correlation matrix 2019

112 A. ORTOLANO AND E. ANGELINI

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GREEN BONDS CAPITAL RETURNS …

113

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CHAPTER 5

Crowdfunding as a Support Tool for the Activity of Social Investors Antonio Minguzzi and Michele Modina

5.1

Background and Object

Social enterprises play three roles in the promotion of community-friendly initiatives: the offering of innovative solutions to unsolved social problems, the centering of their corporate mission on the concept of shared social value, and their intention of contributing to the progress and sustainability of the global economy. The motivational, ethical, and social determinants that characterize their identity are known today (Nel and McQuaid 2002; Margolis and Walsh 2003; Dart 2004; Austin et al. 2006; Zahra et al. 2009; Bugg-Levine et al. 2012; Desa and Koch 2014; Doherty et al. 2014; Santos Barbosa et al. 2017) as well as the specificities of their management which differentiates the social enterprise from the

A. Minguzzi (B) Department of Biosciences and Territory, University of Molise, Campobasso, Italy e-mail: [email protected] M. Modina Department of Economics, University of Molise, Campobasso, Italy © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. La Torre and H. Chiappini (eds.), Contemporary Issues in Sustainable Finance, Palgrave Studies in Impact Finance, https://doi.org/10.1007/978-3-030-65133-6_5

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profit company (Spear 2006; Dorado 2006; Landes Foster et al. 2009; Sparviero 2019; Salavou and Cohen 2020). Their performance is mainly assessed on the basis of factors external to the company represented by the social impact (Roman et al. 1999; Moore et al. 2012a; Chiappini 2017; Calderini et al. 2018; Rizzi et al. 2018; Caroli et al. 2018) which can be measured with different techniques (Meadows and Pike 2010; Bagnoli and Megali 2011; Gibbon and Deu 2011; Ebrahim and Kasturi 2014; Bengo et al. 2016; Dey and Gibbon 2017; Nicholls 2018). An increasing topic of interest within this field concerns the financial aspects that affect social enterprises (Moore et al. 2012b; Geobey et al. 2012; Jackson 2013; Rizzi et al. 2018; Cash 2018; Lagoarde-Segot 2019) with particular reference to the nature of their activity and the relationship with the financial system (Emerson 2003; Ormiston et al. 2015; Viviani and Maurel 2019; Minguzzi et al. 2019; Agrawal and Hockerts 2019). Social enterprises suffer from limited funding opportunities as they experience problems in securing loans and raising equity: they are not profitable or growth-oriented enough to access traditional financial markets, which results in a financial-social return gap (Bugg-Levine et al. 2012). The difficulty in accessing credit and financial markets requires identifying innovative financing models capable of attracting private financial resources to support social initiatives (Azemati et al. 2013). In this context, crowdfunding has emerged as a promising new option to guarantee a large number of small donations from the socially aware crowd for the needs of projects managed by both established non-profit organizations and socially focused start-ups. (Clarkin 2014; Bruton et al. 2015; Clarkin and Cangioni 2016; Parhankangas and Renko 2017; Chan and Parhankangas 2017; Walthoff-Borma et al. 2018). The use of the web platform and online communities facilitates access to financial resources for both profit and Non-Profit Organizations (NPOs), which need to raise funds mainly through non-traditional channels (Belleflamme et al. 2014; Ordanini et al. 2011; Schwienbacher and Larralde 2010) using appropriately the techniques that promote the success of the campaigns (Okten and Weisbrod 2000; Howe 2006; Azemati et al. 2013; Colombo et al. 2015; Cholakova and Clarysse 2015; Ahlers et al. 2015; Short et al. 2017; Courtney et al. 2017; Skirnevskiy et al. 2017; McKenny et al. 2017; Josefy et al. 2017; Vismara 2018; Brema et al. 2019; Yang et al. 2019; Presenza et al. 2019). Social crowdfunding helps social initiatives to test the appeal of new feasible minimum services that they want to launch and can integrate

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other sources of financing in the initial phase that are generally difficult to find (Lehener 2013; Lehener and Nicholls 2014; MacLeod Hamingway 2017; Presenza et al. 2017; Gallucci et al. 2018; Renko et al. 2019; Rey-Martí et al. 2019). It is important to emphasize that for socially focused organizations, crowdfunding can be used to create momentum and excitement around a common cause, to build a community around the organization by activating current donors in addition to finding new ones. This work analyzes the role that a crowdfunding platform can play in making the activity of a social investor broader and more efficient, a topic that has not yet been conclusively explored in the literature. Our research focuses on the role played by an Italian social crowdfunding platform and on the screening process that this platform performs in enhancing and facilitating the interaction between not-for-profit organizations seeking to raise funds and private investors willing to participate in the financing of innovative social projects. Examining the first 140 projects hosted by the crowdfunding platform Meridonare between January 2016 and September 2018, our work analyzes how the platform was able to promote philanthropic activities and obtain a multiplier effect on the intervention of a specific social investor, i.e., the Foundation of the Bank of Naples (FBN). The various reports used by the platform over the years and the information received by Meridonare managers represent our main data sources in order to explore the context of social crowdfunding and to investigate the relationship between the crowdfunding platform and the banking foundation. In particular, we are interested in exploring the role the Foundation and Meridonare play in the social investing process. A key point is to study how institutional forces, such as the FBN, influence the functioning of social crowdfunding and increase the potential of this alternative funding channel. In this perspective, the research questions are defined as follows: RQ1: How does the relationship between a crowdfunding platform and a social investor influence social investment? RQ2: What are the benefits for the social investor, i.e., the Foundation, in using the crowdfunding platform as a tool to carry out its philanthropic activity?

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Our work highlights that the management of the crowdfunding platform by a social investor, i.e., the Foundation of the Bank of Naples, strongly influences the activity of the platform by differentiating it from the behavior of competitors both in the way of relating to the fundraiders and in the forms of internal organization. Besides playing an important role in connecting and matching fundraisers with investors, the Meridonare platform has been able promote the early interaction and participation of all the actors involved, thus confirming the findings of Presenza et al. (2019). As a result, the use of the platform as a tool in favor of the philanthropic mission of the Foundation has permitted to generate a social multiplicator of 300 percent in addition to the traditional philanthropic annual activities. Social investment has a real impact on the world of business practices, philanthropic foundations and investor behavior. This work helps to better understand the consequences of social investments made through a new channel identified in the crowdfunding platform. This study turns out to be useful to researchers, policymakers and practitioners to evaluate the effectiveness of the interaction in social investment over the platform and to evaluate under what conditions, such as support services and reward mechanism, social crowdfunding is best applied in enhancing philanthropic activity. The chapter is structured as follows. Section 5.2 describes the methodology and the data. Section 5.3 presents the results and Sect. 5.4 concludes by illustrating the theoretical and operational implications of this research.

5.2

Methodology and Data Analysis

Given the inductive nature of the research questions, the study adopts a qualitative, case-based approach that enables the exploration of a phenomenon within its context (Yin 2003). Data analysis is carried out by following a four-step procedure adapted from Easterby-Smith et al. (2012): (i) we carefully read the evaluation forms in order to familiarize with the data; (ii) we express judgments by evaluating the collected data in light of the extant literature on social crowdfunding and social investment; (iii) we identify a set of variables considered relevant to address our original research questions; and (iv) we then formulate an analytical framework where the principal implications of our work can be traced.

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5.2.1

121

Meridonare and FBO: A Brief Description

The Meridonare crowdfunding platform operates as a limited liability company (Meridonare Ltd.) having the legal form of the Startup Innovativa a Vocazione Sociale (SIAV). Meridonare was established in November 2015 and is led by the Foundation of the Bank of Naples, which considers it as an instrument for enhancing its social interventions. Meridonare’s mission is to plan and develop its activity through innovative financial instruments, such as crowdfunding, aimed at promoting social wellbeing and the development of local communities. Through the use of the crowdfunding platform, Meridonare aims to become the reference point for those who plan social, cultural, or civil interventions aimed at promoting a new way of understanding active citizenship in local urban areas. Meridonare intends to support the ideas and projects aimed at promoting the culture of philanthropic giving, at strengthening the sense of community and at facilitating the creation of strong and cohesive social ties, having as its main targets South Italy, its resources, its talents, and its unlimited potential. Italian Banking Foundations are defined by the Italian Constitutional Court (sentence No. 300/2003) as “private subjects, non-profit, participating in the construction of the common well-being” that use their assets to promote philanthropic activities in the territory to which they belong. Today, the Foundations of Banking Origin (FBO) system consists of 87 foundations originally made up of banks and savings banks with the objective to exercise direct philanthropy. In the 1999s, with the aim of separating the commercial activity of the banks from the philanthropic activity, the role of the FBO has been specifically structured by the Legislative Decree No. 153/1999. Today the Foundations of Banking Origin continue to be an important institutional investor in the Italian financial system and use their profits to pursue the socio-economic development of specific places through the supply of philanthropic resources to third sector operators and to public institutions. FBO are not allowed to make donations to commercial enterprises. Despite being private entities, the FBO are subject to the supervision of the Italian Ministry of Economy and Finance (MEF) with the aim to strengthen their role as institutional investors and regulate the purposes of social utility, collective interest, and economic development of their location region through the resources generated by the prudent investment of financial assets.

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5.2.2

The Meridonare Operating Model and Its Evolution

In 2015 the main crowdfunding operators in Italy were: DeRev, Produzioni Dal Basso, BuonaCausa, and PlanBee. None of these operators was, however, specialized in social activities but rather on innovative ideas. The Foundation of the Bank of Naples has entirely financed the launch of the Meridonare platform, including the hiring of its first three employees. They were selected both on the basis of their information technology skills and their past as founders of a former local social platform. To facilitate access to the platform for social project proposers, who often lack specific technological, marketing and social media skills, Meridonare has chosen to offer its users various support services free of charge: the video presenting the request, the strategic study of the campaign, the organization of events to present the crowdfunding campaign, banking assistance for the opening of a dedicated current account, and the use of a multimedia totem (donamat). Specifically, the latter is a tool that allows to illustrate the video of the campaign and, at the same time, to collect the donations in order to facilitate fundraising during special events (such as, for example, the one held in June 2016 at the San Carlo Theatre in Naples). To support the dissemination of knowledge of the campaigns present on the platform, Meridonare has developed an online journal called “Meridonare news” which contains various editorial activities including interviews with associations/organizations promoting social projects. The fundamental contribution to the development of the crowdfunding platform was the instrumental relationship with the Foundation of the Bank of Naples (FBN). In addition to financing the start-up phase of the social project, the FBN has been the main financier of the Meridonare since the beginning as part of a strategy that has considered the crowdfunding platform as the ideal channel to promote the social interventions of the Foundation. 5.2.3

Data Analysis

The database is composed of the information contained in the evaluation forms, i.e., Social Reports, filled up by the Meridonare operators at the end of each crowdfunding campaign. The evaluation and reporting activities encompass the various phases of the crowdfunding campaign and

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cover the entire spectrum of activities (online and offline), ranging from the project submission phase to the end of the crowdfunding campaign. In the pre-campaign phase, Meridonare analyzes the project in terms of completeness, potentiality, and social impact by assigning its own evaluation judgment. The preliminary assessment of the project aims to decide whether to place the request on the platform and precedes the assignment of a score to be communicated to the donors. At the end of the campaign, Meridonare assesses the social impact of the campaign on the community by compiling a final report. The evaluation process is not a black-box, but it is shared with the applicants already from the planning phase of the proposal. The sharing of the evaluation mechanisms helps to implement effective and efficient behaviors and actions for the following: the financial target of the crowdfunding campaign (funding); the implementation of the intervention (output) overseen by Meridonare, then publicized on the platform; the evaluation of the social impact (outcome) made by the Foundation, published annually in the social balance sheet of the Foundation itself. Table 5.1 describes the variables that have been identified following the initial phases of our analysis process (Easterby-Smith et al. 2012).

5.3

Findings

As described in detail below, the quantity and quality of information in the report has changed over time. Initially the report consisted of a simple form which, starting in 2017, was transformed into an evaluation sheet of the social impact of the campaign. In particular, Meridonare transmits to the board of the Foundation a report which identifies the capacity of the association to develop relationships—both personal and through social media—with new donors sensitive to the theme of charity and philanthropy. The analysis of the results obtained from the campaigns published on the crowdfunding platform stimulated, at the end of the first year of activity, the revision of the Meridonare operating model. The observation of the data contained in the evaluation forms has contributed to grasp the two main changes on Meridonare’s operating methods and, therefore, to give an answer to our first research question (RQ1). The first important change concerned the verification of the social purposes pursued by the applicant association to the platform for

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Table 5.1 The key variables of Meridonare’s crowdfunding activity General values

#

Financial values

e

Values on the campaign

Months of monitored activities Projects on platform Evaluation sheets carried out Impact assessment carried out Total Meridonare employees Variables to monitor for each project

33

Total budget required

2,650,819

Total months on the platform

Budget collected

1,190,124

Average value required Preventive contributions provided by FBN Premiums provided by FBN Total contribution provided by FBN

18,934

Months duration average campaign Total donors

140 98 42

6 51

318,000

Average donors per campaign

92,800

Donors natural persons Donor bodies

410,800

Average donation per event Communication tools

#

Videos made by Meridonare

112

Total coordination meetings held Events organized by Meridonare Events carried out independently Total events Views on Meridonare website Total Facebook contacts Total Twitter contacts Total Linkedin contacts Total Instagram contacts Total social contacts Press articles Articles on Meridonare news Other articles online Total articles

435

Source Our elaboration

106 216 338 90,760 119,712 8,047 2,370 32,005 159,526 111 171 206 488

Social impact results Budget collected on requested budget FBN contributions on total funding FBN premiums on total funding Budget collected on total FBN payments

# 601

4.29 8,684 62.03

5,289 305

264

% 44.9 26.7 7.8 289.70

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fundraising. The identification of a set of key variables ennobles the role of the crowdfunding platform which, acting as a hub that raises the sharing of knowledge, lays the foundations for the creation of an ecosystem of high-impact social initiatives. In this context, the Meridonare operators carry out an evaluation of the congruity of the requested amount in relation to the social objective pursued (e.g., the money necessary to purchase a minibus to accompany children to school) to obviate a detected tendency to make requests too high. The lack of congruence between the request for funds and the funds actually necessary for the realization of the project is one of the main causes of failure of the crowdfunding campaign. The second change was the introduction of a reward mechanism in order to raise the success rate of the campaigns and align the collection of funds with the social objectives pursued. The reward mechanism works in the following way (Gallucci et al. 2018): ● if the crowdfunding project collects less than 15% of the funds, the NPO will not receive the funds, and the funds will be devolved to another project on the platform indicated by the NPO itself; ● if the crowdfunding project collects between 15 and 50% of the funds, the applicant organization ought to modify its proposal to persuade both Meridonare and the Foundation that the additional funds provided by the Foundation will contribute significantly to the finalization of the project; ● if the crowdfunding project collects more than 50% of the funds, then resources are made available for the NPO; ● if the crowdfunding project collects 100% of the funds (funding target achieved), it receives an incentive from the Foundation, which determines an additional amount of resources (which range from 7% up to 15%) in accordance with the score obtained. The reward mechanism actually makes it possible to establish specific priorities with reference to those projects that can be proposed for additional funds. In this regard, the incentive program provides eventual financial intervention by the Foundation only for projects that have exceeded the financial target established by the crowdfunding campaign. This circumstance has produced two benefits (RQ2): the better allocation of financial resources and the greater control over the social impact

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of the financed projects. The combined effect of these two benefits has produced a multiplier effect. In quantitative terms, Meridonare’s activity has determined an important social leverage effect. For each euro of contribution to the projects paid by the Foundation, more than three euros were mobilized by non-institutional donors. Faced with 410,800 euros of financing from the FBN, the crowdfunding platform has collected and supported about 140 projects with over 1 million and 190 thousand euros. In this perspective, Meridonare’s role is not only to merely to act as a standard crowdfunding platform, but also to facilitate interaction and relationship-building between the various stakeholders in order to raise the chances of success of fundraising. The platform operates in order to broaden the charitable activities in the area by involving the support of donators who otherwise would not have participated. At the same time, the FBN plays a key role in allocating resources in a rational and strategic manner on projects that have the greatest social impact. In this perspective, the Foundation has identified in Meridonare not only a tool to attract donations, but also a means to monitor, evaluate, and leverage the efficacy of its own social intervention.

5.4

Discussion and Conclusion

The philanthropy sector in Italy is characterized by the presence of the banking foundations (FBO) which largely satisfy the NPO charity demand. Faced with the significant volumes of annual payments (over e 1 billion), the assessment and reporting system for the activities carried out is still not adequate. Attention to the transparency of the processes, which is met through the mandatory publication of the payments made, prevails over the assessment of the social impacts of the disbursements themselves (not required by any legislation). The understanding of social investment activities carried out by a crowdfunding platform such as Meridonare can only take place if the role and methods of intervention of the Italian foundations of banking origin are analyzed. The FBO are bound to very structured and regulated procedures for defining the budget and choosing the recipients of the charitable interventions. This often determines the impossibility to effectively support worthy projects of social utility as they are too small in size or excessively fragmented.

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The creation of a social crowdfunding platform allowed the Foundation of the Bank of Naples (FBN) to expand its sphere of intervention in favor of a large number of small-scale social projects. Meridonare’s initiative and its instrumentality in the mission of FBN represents an innovative modality in the operating model of banking foundations. The multiplier effect that has been created has increased the intensity of their philanthropic activity, contributing, among other things, to spread the culture of investment with a social impact. Thanks to the feedbacks coming from the evaluation forms and the continuous interrelationship between Meridonare and the Foundation, the platform’s operating methods have evolved over time. The development of specific internal skills aimed at optimizing the use of social media and a better understanding of fundraising techniques have not only encouraged greater coherence between the funding requests and the actual investment needs, but also introduced an effective reward mechanism. These interventions have produced a dual output. First, the selection of projects and their accompaniment during all phases of the crowdfunding campaign have increased the propensity to donate by thousands of people interested in supporting social initiatives. Second, it consolidated Meridonare’s role as a functional tool for the Foundation’s philanthropic activity. Meridonare strengthens the effectiveness of FBO interventions in the third sector by favoring the allocation of resources in a rational and strategic manner on efficient projects in compliance with the vision and the mission of the Foundation. Social crowdfunding makes it possible to establish specific priorities with reference to those projects which, due to their size or fragmentation, may not be part of the ideal objective of the Foundation’s charitable activity. Given the wider social, political, and economic impacts of social investment, the development of an analytical framework is of enduring concern to regulators, practitioners, and academics. The drivers that increase the return of social investment are expected to be different from those that lead to financial choices. The examination of the relationship between the crowdfunding platform and the bank-originated Foundation is functional in order to survive in a long-term challenge of sustainability (Cornée 2017). More generally, the results of our analysis highlight the importance for social investors such as banking Foundations to maximize the impact of philanthropic activity. In particular, from this work it emerges that crowdfunding platforms encourage collaboration between the various

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parties involved and attract the interest of small investors pursuing social projects, selected with transparent and shared criteria. The case under analysis allows to derive some useful guidelines for the philanthropic sector and for those interested in this field. In particular, the drivers of success are likely to be the innovative use of the crowdfunding tool within this sector, the wide offer of online and offline services, and the intense relationship between the Foundation and the platform that led to periodic improvements in the operating process including the introduction of the reward mechanism. The major benefits of this approach are represented by the growth of social interventions in the territory, the multiplier effect on the philanthropic activity of the Foundation and the diffusion of solidarity values among a wide audience of private subjects.

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CHAPTER 6

Environmental, Social, and Governance Integration in Asset Management Strategy: The Case of Candriam Silvia Cosimato, Nicola Cucari, and Giovanni Landi

6.1

Introduction

Over time, the practice of Socially Responsible Investing (SRI) has increased its relevance in the financial sector due to the constant growth of SRI (De Colle & York, 2009; La Torre et al., 2019; Nath, 2019). SRI has been defined as a financial investment process that takes into account social, environmental, and governance (ESG) impacts and/or investment in the community (Social Investment Forum, 2003). Drawing on the UN Principles for Responsible Investments, a large number of Asset Management Companies (AMCs) endorsed ESG criteria in their SRI strategies. Some scholars approached this integration as based

S. Cosimato · G. Landi University of Naples Federico II, Naples, Italy N. Cucari (B) Sapienza University of Rome, Rome, Italy e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. La Torre and H. Chiappini (eds.), Contemporary Issues in Sustainable Finance, Palgrave Studies in Impact Finance, https://doi.org/10.1007/978-3-030-65133-6_6

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on a derivative logic of ethics, attempting to make finance, and all SRI practices, open to address social, ecological, and even political issues (Avetisyan & Hockerts, 2017; Przychodzen et al., 2016). This led to the SRI gaining momentum which resulted in the integration of ESG criteria into asset allocation decisions, one of the areas that investors struggle with and are pressured for more sustainable products and solutions (Sherwood & Pollard, 2018). The incorporation of ESG issues into financial analysis represents an ever more common way to approach SRI and to engage investors with them, especially in Europe and North American countries (Renneboog et al., 2008; Van Duuren et al., 2016). This integration has been generally considered as a “strategy on how to embed environmental, social and governance considerations into wider business strategies, operations and product and service offers ” (Eccles & Stroehle, 2018, p. 527). In more detail, integration represents a way to negotiate, through financial markets, a broad range of social and political issues (Parfitt, 2019). However, it worth noting that ESG integration can be considered, to some extent, a responsible investment strategy, which incorporates ESG risks into investment analysis (Scholtens, 2014). In this sense, Eurosif, the European institution active in advancing and promoting SRI, annually measures AMCs portfolios in terms of ESG criteria implementation into their analysis and assessment. Thus, this institution defined ESG integration as “the explicit inclusion by asset managers of ESG risks and opportunities into traditional financial analysis and investment decisions based on a systematic process and appropriate research sources ” (Eurosif, 2014). Currently, several AMCs are used to approach the incorporation of ESG criteria into investment strategies as specific service, intended to provide information about the nonfinancial dimensions of a portfolio’s performance (Van Duuren et al., 2016). Thus, ESG incorporation remains an intricate and controversial topic, especially when dealing with the disclosure of ESG efforts concerned with the way some actors hold a disintermediated governance, taking on responsibility for managing specific risks (Kempf & Osthoff, 2008). This is mainly due to the narrow regulatory requirements dedicated to ESG disclosure; consequently, managerial preference still serves as a primary determinant of transparency (McBrayer, 2018). It follows that the disclosure of ESG integration represents a critical topic, which also borne out by the fact that, in some cases, AMCs can lose their mandates from private investors if they

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do not punctually communicate and explain the way they have incorporated ESG criteria into the investment process (Wagemans et al., 2018). Therefore, ESG integration into investment strategies, its communication, and the actions pointing to add rigor to the related methods and standards remain among the major challenges for scholars and practitioners (Gómez-Bezares et al., 2016; Van Duuren et al., 2016). Thus, this analysis is aimed at contributing to bridge this gap and investigating if, what, and how AMCs communicate the incorporation of ESG criteria into their investment strategy. Therefore, a case study analysis was performed to investigate the way an asset management company, Candriam, approached the disclosure of ESG integration. The case company was chosen because it is one of the oldest and a pioneer of AMC in SRI, whose mission is fully centered on a proactive and comprehensive approach to social responsibility. This proactivity led the case company to actively stimulate the financial community and, therefore, investors, as well as all the other stakeholders, to act responsibly, boosting their transition toward a more sustainable society. For the sake of the research, a content analysis of some Key Investors Information Documents (KIID)1 that the case company published in 2020 was performed to address the two research questions that inspired this work: RQ1: Do AMCs consider ESG themes critical for investment strategies? If so, to which extent do they disclose their ESG efforts ? RQ2: Which are the ESG themes that AMCs consider more attractive for investors? It follows that this analysis contributes to both the theory and practice on SRI, adding some more insights to challenge the enduring information asymmetries existing between investors and investees, mainly related to what, where, and how often to report (Sciarelli et al., 2020). In terms of practical implications, this study contributes to better understand how AMCs could engage investors with asset allocation process, in order to make them able to monitor their investments. Moreover, this contribution also pointed out the importance of developing a “common language” through which reducing the aforementioned information asymmetries. The remainder of the paper is organized as follows. Section 6.2 presents the theoretical background which has inspired this work. Section 6.3

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describes the research strategy and the implemented methods, while Sects. 6.4 and 6.5 present and discuss the achieved results. Finally, Sect. 6.6 provides some concluding remarks.

6.2 6.2.1

Theoretical Background ESG Integration into SRI Strategies

Over the last decades, SRI has gained momentum among private investors, practitioner analysts, and scholars (La Torre & Chiappini, 2016; Revelli & Viviani, 2015). Even though this concept has become “a familiar part of the vocabulary of institutional and retail investors. Just what these terms mean in practice, however, and how their practitioners’ claims can be impartially assessed, has been less clear” (Caplan et al., 2013, p. 1). Therefore, SRI as well as the related issue of ESG integration needs further investigation. SRIs have been defined not only as “a result of increasing social awareness by institutions ” but “primarily as a result of the increasing public (beneficiary) interest in social responsibility” (Cumming & Johan, 2007, p. 397). It follows that SRIs enclose ethical values, environmental protection, improved social conditions, and a good governance into investment decision-making (Matallín-Sáez et al., 2019; Revelli, 2017; Von Wallis & Klein, 2015). However, even though these investments currently cover a significant part of funds, some unaddressed questions arise. The first is related to the fiduciary duty and the way responsible investing practices correspond to that duty (Desmartin, 2015). In this vein, Kempf and Osthoff (2008) directed their research effort to further investigate investors’ expectations in terms of SRI funds’ performance and their compliance to social and environmental standards. The second is related to SRI influence on corporate behavior and CSR standards compliance (Birindelli et al., 2019). In this sense, it is worth noting that the core belief of SRI lies in the idea that investors, society, and the environment can benefit from the integration of ESG criteria into investment strategies, boosting more conscious decisions (Sultana et al., 2018). This requires the implementation of a set of investment screenings to choose or exclude assets based on ecological, social, or corporate governance or ethical criteria. This often leads to the phenomenon of local communities and shareholder activism, which drives corporate strategies toward the

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abovementioned aims (Renneboog et al., 2008). However, recent financial scandals have led AMCs to be much more focused on ESG issues, incorporating the related criteria into their SRI strategies (Lulewicz-Sas & Kilon, 2014; Zhang, 2006), which can assume a screening, monitoring, and engagement orientation (Scholtens, 2006). For the purpose of the analysis, the screening strategies are briefly introduced; thus, using social screenings these strategies enable fund managers to identify and select companies with better management skills and, in so doing, improving portfolio performance (Bollen, 2007; Leite & Cortez, 2015). Of the screening strategies that can be enacted, the most common are known as negative and positive screening strategies. The former is the oldest and the simplest one based on the analysis of “the practice that specific stocks or industries are excluded from SRI portfolios based on social, environmental and ethical criteria” (Radu & Funaru, 2011). More recently, SRI portfolios are often defined according to positive screening strategies, mainly based on the selection of those positive actions and performances that meet superior CSR standards (Renneboog et al., 2016). These strategies are intended to analyze corporate governance, labor relations, cultural diversity, and the environmental impact, among others, of investments. In doing so, positive screening strategies make it possible to select virtuous and well-ranked companies, often being combined with a best-in-class approach (Zhang, 2006). Both negative and positive screening strategies are defined as first and second generations of SRI screenings, followed by the so-called third- and fourth-generation screenings (Renneboog et al., 2016). Third-generation strategies are based on an integrated approach to company selection, which lies upon those economic, environmental, and social criteria implemented by both negative and positive screenings and which refer to the principles at the core of sustainable development (Brundtland, 1987) and of the so-called triple bottom line approach (focused on People, Planet and Profit; Elkington, 1997, 2013). Finally, the fourth-generation screenings merge sustainable investing approaches (third-generation strategies) with shareholder activism or “the use of ownership position to actively influence company policy and practice” (Sjöström, 2008, p. 145). This implies that asset managers try to influence companies conduct through an active dialogue with their management or the voting rights at Annual General Meetings (Renneboog et al., 2008). In this sense, it is worth noting that ESG criteria are one of the major drivers of direct investor engagement; shareholders are concerned about

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negative ESG exposures, because it implies substantial legal, reputational, operational, and financial risks (Esposito De Falco et al., 2018; Hoepner et al., 2018). Focusing on ESG integration into the aforementioned strategies, it is worth noting that this process implies the incorporation and evaluation of ESG information at all the stages of the investment process (Hoepner et al., 2018). However, some scholars shed light on the need for a better approach to ESG integration; thus, “very few asset managers actually do this (…), there are several ways to fail at ESG integration” (Schramade, 2016, p. 98), because “the overwhelming majority of investment managers have not implemented a strategy of full ESG integration” (Cappucci, 2018, p. 24). This seems to be mainly due to the fact that ESG integration is usually approached as something isolated, which specialists tend to consider as not material to their investment cases (Schramade, 2016). More recently, some scholars (Gary, 2019; Tamini & Sebastianelli, 2017) shed light on the relationship existing between ESG criteria integration into SRI strategies and the need for disclosing ESG efforts. In a nutshell, ESG and nonfinancial disclosures can put further emphasis on AMCs socially and environmentally responsible policies and practices (Chiappini & Vento, 2018) and supporting asset managers to demonstrate ESG integration and increase investors demand. 6.2.2

How to Communicate the Integration of ESG Criteria into Investment Strategies

SRIs were globally on the rise together with the demand for a more transparent approach to ESG issues. Therefore, even though some international and national laws and regulations have called for better communication of ESG efforts, the related disclosure remains a challenging issue for both scholars and practitioners (Al-Tuwaijri et al., 2004; Buallay, 2019; Fatemi et al., 2018; Simnett et al., 2009). In fact, even if ESG disclosure lacks specific, shared, and comparable metrics, it is currently used to define or assess the deepness of AMCs reporting (Eccles et al., 2011). In this sense, some studies (Holland, 2011; Velte & Stawinoga, 2017) highlighted the growing importance that companies, investors, and governments are attaching to ESG issues. Thus, an improved disclosure is considered essential to get the transparency of ESG efforts improved, but significant problems still limit AMCs disclosure and, consequently, the related communication strategies (Cho et al., 2010). In particular,

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the voluntary nature of ESG disclosure led investors to assume not completely aware investment decisions. In fact, they have to direct still too much effort in understanding the possible detrimental impact for environment, society, and even economy of some funds (Cetindamar & Ozkazanc-Pan, 2017). To counteract this situation, scholars and practitioners have proposed some possible enhancing actions pointing to make the investment process as clear as possible and, consequently, investment chooses more informed (Chiappini, 2017). Even though ESG disclosure remains mainly voluntary, nonprofit organizations such as the United Nations (UN), with its Principles of Responsible Investment (UNPRI), are pressuring institutional investors to integrate ESG factors into their investment decision-making and to disclose them. In particular, the UN attention to ESG sheds a new light on the importance of its incorporation into traditional analysis and financial reporting for offering a more exhaustive picture of a company’s risk profile and long-term sustainability (Ki-moon, 2010). In fact, when ESG initiatives are fully integrated into an investment strategy, they tend to be able to anticipate and manage future risks and in doing so increase long-term value for shareholders (Verheyden et al., 2016). In this sense, investors are changing their behavior, “considering ESG information as important factors that can offer insight into a company’s future performance, and help them price investments with more accuracy” (Bizoumi et al., 2019, p. 75). It is worth reporting that over the last several years the number of companies that measure, disclose, and communicate nonfinancial information is exponentially grown, with 85% of S&P 500 companies disclosing ESG information in 2017 (G&A Institute, 2018). However, research focused on analyzing the real impact of such disclosure and the use that institutional owners currently do of ESG information remains scarce. Due to the fact that SRIs still cover a small part of investments (Juravle & Lewis, 2008), AMCs often underestimate their potential and that of a better and clear information in terms of awarness and propensity to invest. This led to focus on the persisting information asymmetries between AMCs and investors, of which reduction is at the core of some scholars’ research as well as of some institutional actions (Cho et al., 2013; Landi & Sciarelli, 2019). Together with the information asymmetries, some scholars shed light on the emerging phenomenon of mission drift (Bruneel et al., 2017), which consists, on one hand, in assessing the realization of missions in favor of financial sustainability and, on the other, can be detrimental social objectives (Cetindamar & Ozkazanc-Pan, 2017; Chiappini, 2017).

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Drawing on Eccles et al. (2011), some scholars further advanced research on information asymmetries affecting financial markets, focusing on the way AMCs can inform investors about their ESG disclosures efforts as well as on if and how this information can affect investors’ asset allocation process (Higgins & Coffey, 2016; Lehner & Harrer, 2019; Brakman & Tucker, 2019). In a similar vein, Sciarelli et al. (2020) underlined that a high corporate social performance disclosure, also when performed through a web channel and social media, tends to be positively associated with a company’s asset management economic performance. Moreover, they showed that a high perceived coherence between AMCs’ self-presentation and ethical financial product communication can enhance AMCs’ financial success. In this sense, to reduce the aforementioned asymmetries a growing number of companies is much more focused on finding the best ways to communicate their ESG disclosure efforts through several different reporting tools, developed according to national and international frameworks, standards, ratings, and indices (Cucari et al., 2018). However, these frameworks and standards are not mandatory; therefore, ESG disclosure and the subsequent communication still lacks a punctual methodology or well-established and widely accepted criteria (Brakman & Tucker, 2019; Cappucci, 2018). Among the number of communicative tools that AMCs are implementing for providing information about their ESG efforts, one of the most used is the KIID, an informative document that offers information about investment funds in a standardized format with plain language for helping investors in comparing different funds. Drawing on KIIDs, Walther (2015) suggested that even though they are considered more informative, comprehensible, and helpful than Prospectuses, for a large portion of investors they remain difficult to understand.

6.3 6.3.1

Research Design Research Strategy

A qualitative exploratory study has been conducted to better understand a phenomenon which remains underinvestigated—AMCs integration of ESG into investment strategies and the related communication. Thus, qualitative methods are mostly fit for understanding emerging phenomena (Patton, 1990; Swanborn, 2010) and to examine within their “real-life

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context, especially when the boundaries between phenomenon and context are not clearly evident ” (Yin, 2009, p. 13). In this sense, a case study analysis has been conducted (Stake, 2013) and for research purpose, the 2019 KIIDs documents written in a standardized format and plain language for making investors able to take informed investment decisions of a European AMC active in SRI have been investigated performing a content analysis (Kohlbacher, 2006; Krippendorff, 2004). Moreover, the reliability of the results was ensured using multiple sources of data, which were subsequently triangulated comparing them with further corporate information resources (e.g., corporate website, ESG reports, ESG online news, etc.). 6.3.2

The Case Company

The analysis has been focused on a single case study (Eisenhardt, 1989; Yin, 2009), the selection of which was driven by a non-probabilistic technique (Neuman, 2000), being: (1) one of the most long-standing AMC (active since 1996); (2) pioneer in SRI; (3) regularly involved into KIIDs publication since 2012; and (4) able to publish a great number of KIIDs per year (76). The selected company, Candriam, is one of the oldest and a pioneer in SRI, whose mission is fully centered on a proactive and holistic approach to social responsibility that led it to go beyond the mere compliance to laws, standards, and regulations dedicated to responsible investments. Over time, the case company has actively stimulated financial community, investors, and other stakeholders to act responsibly, boosting their commitment to the transition toward a more inclusive and sustainable society. In this direction, the company started several initiatives together with other investors to call on stakeholders’ engagement with a responsible conduct supported by sustainability-oriented activities. This was possible because of its long-standing attention to ESG; thus, in 2006 it developed the so-called Principles for Responsible Investment, which represents the first step that it took toward the disclosure and the introduction of ESG criteria into the traditional investment evaluation financial measures. Table 6.1 briefly summarizes the main characteristics of the case company.

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Table 6.1 Case company main characteristics Age of foundation Location SRI orientation ESG initiatives

Asset under management

1996 Main investment management centers located in Europe and North America (New York) In 2017, the 26% of total assets were managed taking into account SRI criteria – Principles for Responsible Investment in 2006 – UK Stewardship Code 2016 – Investor Statement on ESG ratings 2017 108 Billion e as of 2017 FY

Source Authors’ elaboration

6.3.3

Data Collection and Content Analysis

A content analysis of the KIIDs, that the case company published for the first semester of 2020, was conducted to identify the main ESG themes or criteria that it used for disclosure purpose. Some specific KIIDs published in 2020 were selected as follows. The KIIDs sample of the ESG funds was organized in two asset classes, the first defined according to the ESG strategies implemented in asset management, and the second applied a thematic filter, which underscored the AMC inspiring ESG issues.

Fig. 6.1 Most recurrent SRI strategies in KIIDs (Source Authors’ elaboration)

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As shown in Fig. 6.1, the most recurrent strategies applied to SRIs are (1) the best-in-class strategy in stock-picking and (2) the shareholder activism as a result of engagement strategy. Candriam selected securities combining rigorous analysis’ criteria to identify those companies which are more open and willing to dialogue with institutional investors. ESG investments are also characterized by specific thematic trends, which underline the asset allocation activity corresponding to the emergence of social and environmental needs such as healthcare, climate change, or public global agreement. Figure 6.2 points out that the most common thematic standards used to build up ESG financial products are based on the Sustainable Development concept and on the United Nations Global Compact. The implementation of a content analysis enabled data coding and the interpretation of quantitative counts of the coded text in a descriptive way. Thus, some content units were defined and analyzed. Each sentence was set as a content unit, which is defined as “the limits on the information to be considered in the description” (Krippendorff, 2004, p. 101), while the word was set as the unit of analysis. Two researchers worked independently and checked the selected texts to eventually correct coding errors. Then, the gathered data were triangulated (Houghton et al., 2013) to make them as credible, conformable, and transferable as possible (Stake, 2013). To minimize the subjective influence of the researchers on the data

Fig. 6.2 Most recurrent ESG thematics in KIIDs (Source Authors’ elaboration)

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analysis, a set of rules was defined and organized in a dictionary where the units of analysis (words) were reported and organized. The exhaustiveness of the dictionary (the word list used for the analysis) was ensured using an English dictionary of synonyms and antonyms. After having eliminated articles, auxiliaries, and prepositions, and after having grouped singulars and plurals, a list of 150 words was identified. To analyze the selected KIIDs, a specific operative protocol was defined. Each content unit (sentence) was individually investigated, in order to grasp and count the occurrences of the most significant keywords. The researchers used the dictionary to check the occurrences of each word and their relevant synonyms, antonyms, and negative forms. Then, recorded and presented into a coding table (with no articles, auxiliaries, and prepositions) (Table 6.2) the detected occurrences were organized according to the coding categories defined based on previous research (Székely & Knirsch, 2005; Willis et al., 2005): (1) Environment, (2) Society, (3) Governance, (4) Labor, (5) Compliance, and (6) Performance (Table 6.3). The retrieved occurrences supported the researchers in understanding which of the selected coding categories and related keywords mostly fit the analysis. Finally, the results were organized and input into a word-count matrix, which supported the definition of the interconnections existing between Table 6.2 Dictionary containing the keywords under investigation Words’ list Acquisit*, age, approach, association*, award*, biodegradable*, biodiversity*, board*, collect*, commit*, communication, communit*, compensation*, competit*, complian*, condition*, culture, customer*, disclosure, diversit*, educat*, effective*, efficien*, emission*, employ*, energy*, engagement, environment*, entrepreneur*, equit*, ESG, ethics, expectation*, famil*, freedom, fuel*, future, gas, gain*, gender*, govern*, green*, group*, goal*, happ*, health*, incentive*, indicator*, institution*, integration, involv*, knowledge, law*, learn*, long-term, manag*, material*, monitoring, natur*, need*, non-discriminat*, objective*, occupation, oil*, opportun*, optimization, orientation, pension*, people, polic*, pollution, positive, public, pressure, price, priorit*, progress, quality, regulation*, renew*, report*, responsib*, result*, retirement, right*, risk*, safety, security, skill*, social, society, source*, SRI, stakeholder*, standard*, strategy*, sustainab*, target, train*, transport*, use, value, values, wast*, water, welfare, wellbeing*, wellness, wind, work Source Authors’ elaboration

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Table 6.3 Coding categories and keywords Coding categories

Keywords

#1 Environment

Biodegradable*, biodiversity*, emission*, energy*, environment*, ESG, fuel*, future, gas, green*, incentive*, material*, monitoring, natur*, need*, oil*, pressure, pollution, progress, quality, regulation*, renew*, responsib*, risk*, safety, source*, sustainab*, target, transport*, wast*, water, wellbeing, wind Acquisit*, age, association*, board, collect*, communication, communit*, compensation*, competit*, complian*, condition*, culture, customer*,disclosure, diversity, educat*, effective*, efficien*, employ*, ESG, famil*, freedom, future, gain, group*, happ*, health*, incentive*, institution*, integration, need*, non-discriminat*, objective*, occupation, opportune*, orientation, pension*, people, polic*, right*, positive, public, pressure, price, priorit*, progress, quality, regulation*, report*, responsib*, retirement, right*, risk*, safety, security, skill*, social, society, source*, SRI, standard*, strateg*, sustain*, target, use, value*, wellbeing*, wellness, work Acquisit*, approach, association*, awar*, board*, commit*, communication, communit*, competit*, complian*, condition*, culture, customer*, disclosure, diversit*, effective*, efficienc*, entrepreneur*, equit*, expectation*, ESG, ethics, future, gain*, govern*, group*, goal*, incentive*, indicator*, institution*, integration, involv*, knowledge, law*, learn*, manag*, monitoring, need*, objective*, opportun*, optimization, orientation, people, ploic*, public, pressure, price, priorit*, progress, quality, regulation*, renew*, report*, responsib*, result*, risk*, skill*, social, society, SRI, stakeholder*, standard*, strategy*, sustainab*, target, use, value, values, welfare Age, approach, association, award*, board, commit*, communication, communit*, compensation*, complian*, condition*, culture, customer*, diversit*, educat*, effective*, efficien*, employ*, engagement, entrepreneur*, equit*, ethics, expectation*, famil*, freedom, future, gain, gender*, govern*, group*, goal*, happ*, incentive*, indicator*, institution*, involve*, knowledge, law*, learn*, long-term, manag*, monitoring, need*, non-discriminat*, objective*, occupation, opportun*, pension*, people, polic*, positive, public, pressure, price, priorit*, progress, quality, regulation*, renew*, report*, responsib*, result*, retirement, right*, risk*, safety, security, skill*, social, society, standard*, transort*, use, value, vakues, welfare, wellbeing, wellness, work Approach, association*, commit*, communication, communit*, complian*, condition*, disclosure, ESG, future, gain*, govern*, group*, goal*, incentive*, institution*, integration, involve*, indicator*, institution*, law*, manag*, material*, monitoring*, need*, opport*, orientation, people, polic*, pressure, public*, regulation*, report*, result*, risk*, social, society, SRI, stakeholder*, standard*, sustainab*, target*, value, values, work

#2 Society

#3 Governance

#4 Labour

#5 Compliance

(continued)

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Table 6.3 (continued) Coding categories

Keywords

#6 Performance

Approach, association*, award*, communication, compensation, communit*, competit*, complian*, condition*, culture, customer*, disclosure, effecti*, efficien*, engagement, entrepreneur*, equit*, ESG, ethics, expectation*, future, gain*, govern*, group*, goal*, health, incentive*, indicator*, institution*, integration, involv*, knowledge, law*, learn*, long-term, manag*, material*, monitoring, objective*, opportun*, optimization, orientation, people, polic*, positive, public, pressure, price, priorit*, progress, quality, regulation*, renew*, report*, responsib*, result*, risk*, safety, social, society, source*, SRI, stakeholder*, standard*, strategy*, sustainab*, target, use, value, values, work

Source Authors’ elaboration

the coding categories and the importance that the case company attached to them (see Appendix). The main selection criterion was at least 10 occurrences for each coding category and for the related keywords. This led researchers to select the most fitting ones, which will be used for further and wider research.

6.4

Results

The results achieved from performing a quantitative content analysis have been synthetized and presented in a specific word-count matrix (see Appendix). Following is a brief presentation of some of the most interesting evidences coming from the analysis of the sample KIIDs. In particular, the indicators or keywords recurring at least 10 times in no less than five documents are presented in Table 6.4. Starting from the original 150 keywords (indicators), just 96 are reported in Table 6.4 because of their adherence to the aforementioned selection criterion. The categories and the related keywords which occurred most often in the analyzed documents were Performance (1367), Environment (1272), and Labor (1270) while the category with the least occurrences was Compliance (1056). Moreover, the most recurrent keywords for each category were: Risk* (129), Future (114), Sustainab* (115), Result * (105) (see Fig. 6.3). In more detail, the keyword with the highest number of occurrences is Risk* (129) which recurred into 4 different categories (Environment,

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Table 6.4 Items and indicators rising from the content analysis Categories

Occurrences’ per category

Keywords

Environment

1272

Society

1187

Governance

1066

Labour

1270

Compliance

1056

Performance

1367

Biodegradable*, Biodiversity*, Emission*, Energy*, Fuel*, Future, Gas, Green*, Material*, Natur*, Pollution, Progress, Renew*, Risk*, Source, Sustainab* Association*, Collect*, Complian*, Famil*, Future, Incentive*, Group*, Health*, People, Polic*, Quality, Regulation, Risk*, Wellbeing, Wellness Board*, Commit*, Customer*, Effective*, Future, Goal*, Integration, Involv*, Manag*, Result*, Stakeholder*, Strateg*, Sustainab* Age, Association*, Compensation*, Condition*, Customer*, Efficiency, Employ*, Equit*, Famil*, Goal*, Future, Occupation*, Opportunit*, Pension*, Risk*, Value, Welfare Communicat*, Disclosure, ESG, Goal*, Indicator*, Monitor*, Law*, Opportunt*, Regulation*, Report*, SRI, Stakeholder*, Standard*, Sustainab*, Target* Compensation, Condition*, Effecti*, Fficienc*, Energy*, Health, Incentive*, Future, Gain*, Indicator*, Manag*, Optimization, Positive, Public, Result*, Risk*, Social, Society, Value, Use

Source Authors’ elaboration

Society, Labor, and Performance) together with Future (114), which recurred in the Environment, Society, Governance, and Performance categories. Table 6.5 briefly depicts the most and least frequent keywords for each category. The results depicted in Table 6.5 show that even though the most recurring keywords demonstrated a certain homogeneity among categories, with evident differences just for the categories Labor and Compliance, the least recurring ones did not demonstrate the same homogeneity; thus, they were different for each of the reported categories. Among these, just two of them recurred into two categories Indicator* (in Compliance and Performance) and Health* (in Society and Performance).

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Fig. 6.3 Most recurrent keywords for each category (Source Authors’ elaboration)

Table 6.5 The most and the least recurrent keywords Category

The most recurrent keywords

The least recurrent keywords

Environment

Risk* (129), Sustainab* (115), Future (114) Risk* (129), Future (114), Complia* (91) Risk* (129), Future (114); Result* (105) Risk* (129), Custumer* (101), Value* (89) Sustainab* (115), Stakeholder (98), Goal* (84) Risk* (129), Future (114), Result* (105)

Biodiversity (40), Gas (53)

Society Governance Labour Compliance Performance

Health* (52), Relation* (57) Manag* (56) Pension (40), Employ (58) Indicator* (51), Monitor* (55), Communication (55) Gain* (45), Indicator* (51), Health* (52)

Source Authors’ elaboration

Finally, for each of the analyzed KIIDs, the total number of keyword occurrences were calculated; thus, Document 1 (1027) demonstrated to have the highest number of occurrences, while Document 9 had the lowest (483) (Fig. 6.4).

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Fig. 6.4 Total occurrences for each document (Source Authors’ elaboration)

6.5

Discussions

The content analysis was implemented to investigate a sample of KIIDs that the case company published for 2020 to understand if and to which extent it has integrated ESG criteria into its asset management strategy as well as to understand if and to which extent it was performing and promoting a transition toward more sustainable investments. Prior literature (Capelle-Blancard & Petit, 2019; Mervelskemper & Streit, 2017) showed limited empirical evidence about the relationship between asset management companies’ ESG commitment and corporate strategy, with a focus on communication and investment behaviors. Currently, AMCs are receiving growing pressure to integrate ESG criteria into their strategies, because investors, market participants, and individuals perceive the related different issues or themes as critical (Gerard, 2019). The achieved results demonstrated that the case company has deeply integrated ESG criteria into its investment strategies. The results also showed interesting insights in line with the current call for a more reliable and transparent information and communication about the incorporation of ESG criteria into SRI strategies (Berthelot et al., 2012; Dhaliwal et al., 2014; Diouf & Boiral, 2017). This finding emerged from the KIIDs analysis, which currently represents one of the most

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used tools to communicate the AMCs’ transition toward more sustainable investments. In fact, to better respond to investors’ information need in terms of sustainability efforts, AMCs are approaching KIIDs in a rigorous way. Therefore, even though their publication remains voluntary, companies are paying growing attention to their communicative aims, form, and contents, making them somewhat similar to a bottom-up communicative standard. In fact, even though the enduring lack of standards for communicating ESG commitment, Candriam adopted a self-regulated approach to offer reliable information about their SRI strategies to their real and potential investors (Berthelot et al., 2012; Diouf & Boiral, 2017). These considerations led to address the first research question at the core of this analysis. (Do AMCs consider ESG themes critical for informing investors as well as other stakeholders? If so, to which extend they disclose their ESG efforts ?) The case company demonstrated great attention to the communication of their ESG efforts, even though it differently focused on each of the ESG-related themes. In fact, findings revealed that most of Candriam’s attention was paid to a peculiar theme such as Performance, followed by Environment and Labor. For Labor, the case company attached greater attention to two of the well-established issues of sustainability, environment, and economy (Scholtens, 2014), where economy is represented by the theme named Performance that was used here for approaching and defining financial and social performances of the sampled AMC. This finding is in line with the current literature which highlights that a growing number of listed companies have incorporated ESG criteria into their agenda, communicating the related activities to both investors and stakeholders in order to better and more comprehensively depict their corporate (economic and social) performances (Aybars et al., 2019; Fatemi et al., 2018). This implies that performance evaluations are now based more both on financial and nonfinancial results, which are essential for assessing also the overall sustainability of a company and its survival potential (Achim & Borlea, 2015). This also justifies the attention that the case company paid to environmental and labor issues into its KIIDs; thus the current society labor represents one of the most challenging issues. This result is in line with the extant literature, which widely argued labor inherent relation with human resource management and ESG, for example in terms of work protection and unemployment reduction (Baldini et al., 2018; Taylor et al., 2012).

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Focusing on human resource management, research underlined its potential in pushing companies toward a more proactive approach to sustainability strategies, especially when related to environmental protection (Vidal-Salazar et al., 2012). In this vein, some scholars shed light on the positive influence that the involvement of human resources has with their work practice which can have on the implementation of proactive environmental strategies (Deegan & Blomquist, 2006; Martínez-del-Río et al., 2012). It also follows that the importance that the case company attached to the third most recurrent theme, Environment, is in line with the mainstream literature. Focusing on the last two analyzed themes (Governance and Compliance), the achieved results pointed out that the case company in its KIIDs put less emphasis on them. This finding somewhat contradicts some research, according to which disclosing about governance issue is fundamental for companies and in particular for AMCs (Baldini et al., 2018; Benlemlih et al., 2018). However, assuming an institutional perspective on nonfinancial disclosure, other scholars highlighted that companies do not decide about ESG issues just “on the basis of instrumental decision making, but that such decisions are framed vis a vis a broader social context ” (Jackson & Apostolakou, 2010, p. 374). Finally, the less attention that the case company dedicated to compliance issues can be due to the growing maturity level of ESG disclosure as well as to the proactive approach that several companies are assuming toward the related issues. In fact, a growing number of AMCs are voluntary reporting about ESG, often going beyond what international and national laws and regulations call for (Talbot & Boiral, 2015). In mature financial markets, AMCs’ proactivity in responding to investors demands has led them to build their asset management strategies upon ESG criteria. Thus, apart from the obligations normatively framed, these companies are starting to proactively approach societal and environmental needs, assuming ESG as an instrumental worth that can lead themselves to create and capture in a more responsible way a long-term economic value (Barman, 2018; Eccles & Stroehle, 2018). It follows that the integration of the ESG criteria into asset management strategies contributes to better inform investors and stakeholders about socially responsible and sustainable investment policies (Escrig-Olmedo et al., 2017; RuizLozano et al., 2019). This also emerges from the achieved results; thus, the KIIDs analysis and the number of recurrent keywords related to the

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main ESG themes (see Fig. 6.3) is in line with what the mainstream literature maintains in terms of companies disposition toward their integration, disclosure, and strict relation with corporate commitment toward sustainability issues and goals (Chauvey et al., 2015; Gamerschlag et al., 2011; Mura et al., 2018). Assuming an institutional perspective, Candriam’s investment behavior complies with European policymakers’ expectations, which are pushing investors to actively participate in the so-called Green New Deal (European Commission, 2019), which is a concrete expression of the development of a new financial environment, where people are even more aware about the importance to push finance toward sustainability. Indeed, the AMC applies the ESG factors in asset management strategies mainly through “best-in-class” and “investor engagement” approaches to align private investors’ expectations with investees’ practices (see Fig. 6.1). In so doing, Candriam considers the Sustainable Development Goals as well as the Global Compact topics critical in KIIDs to increase its assets under management (see Fig. 6.2), being aware to meet ESG concerns and— at the same time—gaining the attention of socially responsible investors. These considerations led to address the second research question (Which are the ESG themes that AMCs consider more attractive for investors?).

6.6

Final Remarks

Over the last decades, AMCs were pressured to disclose their ESG effort. This was due to the criticality that investors were growingly attaching to the related ESG issues and their disclosure and the way companies try to address them. Consequently, AMCs are starting to approach them as a core component of their business and investment strategies (Baldini et al., 2018). This sparked a lively debate among investors and scholars (Escrig-Olmedo et al., 2017; Ruiz-Lozano et al., 2019), who discussed the opportunity and/or the need for integrating ESG criteria into investment strategies. Therefore, this study was intended to contribute to this debate, offering some insights on if and what and in which way AMCs are open to integrate the different ESG criteria into their SRI strategies. Even though over the last decade some national and international institutional bodies (e.g., OECD, European Commission, United Nations) have encouraged ESG integration into SRI strategies, the way investors and/or AMCs approached it remains different (Baldini et al., 2018). This is mainly due to the divergent investors’ interests and expectations, which

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often led them to prioritize specific ESG criteria rather than others for optimizing their return more than for aligning their portfolio to corporate values (Gerard, 2019). In this vein, findings confirmed the variability of criteria integration (Aybars et al., 2019), mainly due to the persistence of an incomplete alignment or of the so-called information asymmetries between institutional investors and investees related to what, where, and how often to report (Sciarelli et al., 2020). This could lead to a paradox disclosure that requires a different exploitation of the disclosing information and ESG themes. Therefore, it can be also assumed that companies and investors approach ESG criteria speaking different languages, which also emerges from the competing standards and/or frameworks they apply, and which make information not easily and always comparable (Schramade, 2016). Given these limitations for AMCs in ESG disclosure, both in private fundraising and trading phases, the KIID documents represent a widely accepted financial tool that AMCs currently use also to disclose their ESG commitment. Due to the lack of institution interventions in terms of ESG disclosure, the current use of KIIDs can be considered an approach triggered by a bottom-up effort to institutionalize the aforementioned disclosure in asset management (Gómez-Bezares et al., 2016). However, it worth noting that since private investors still lack a reliable and comparable ESG tool, the KIIDs could also be used for a good investment, fishing leverage for socially responsible investors. Due to the enduring difficulties related to the quality, reliability, and credibility of SRI strategies communication (Boiral et al., 2019; Fortanier et al., 2011; Hahn & Kühnen, 2013), AMCs tend to approach the related tools (e.g., KIIDs) as marketing tools: consequently, they use these instruments for gaining or increasing corporate social legitimation (Deegan & Blomquist, 2006), rather than as a source of reliable information for stakeholders. Thus, to avoid a mission drift behavior and negative perceptions about eventual social and green-washing phenomena (Cetindamar & Ozkazanc-Pan, 2017), AMCs should engage investors with asset allocation processes, making them able to self-monitor their investments. Even though the recent progress and the influence that KIIDs are playing in communicating ESG disclosure, some issues remain unaddressed, such as those related to the reliability of ESG data, the communication of disclosure communication, and the very quantitative approaches which somewhat limit ESG criteria integration into investment strategies. Therefore, to address this gap the literature still calls for a better assessment of ESG

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integration’s strengths and weaknesses, which might support the development of a common language, pointing to contribute to further reduce the aforementioned information asymmetries existing among companies, AMCs, private investors, and other stakeholders (Higgins & Coffey, 2016; Lehner & Harrer, 2019). In fact, a new financial environment is rising, where people are even more demanding for information about the impact and the sustainability of their investments; thus, an AMC should forward a more responsible investment approach in order to bridge these two categories. This study offers some insights for AMCs’ managers in terms of communication of EGS disclosure and the way to engage investors with asset allocation process. The inherently explorative nature limits this study; therefore, further research will be dedicated to the investigation of ESG integration in terms of transparency, comprehensibility, and shareability through the implementation of qualitative research approaches.

Note 1. The KIIDs are documents that provide key information about investment funds to help investors in comparing different investment funds and assess as requested by Directive 2009/65/EC on UCITS IV and Commission Regulation 583/2010.

Appendix---Word-Count Matrix Occurrences Environment Biodegradable* Biodiversity* Emission* Energy* Fuel* Future Gas Green* Material* Natur* Pollution

KIID KIID KIID KIID KIID KIID KIID KIID KIID KIID 1 2 3 4 5 6 7 8 9 10

10 0 11 13 2 17 2 15 14 10 10

13 10 5 10 10 20 10 11 9 11 13

10 11 6 11 8 16 10 19 10 9 10

15 10 11 3 10 2 0 10 5 10 11

10 0 0 11 0 5 0 13 0 17 5

10 10 10 2 1 15 0 11 14 10 0

0 0 1 0 10 13 11 17 0 11 15

10 1 10 1 11 2 10 1 11 1 17

3 1 11 10 10 14 0 2 0 0 0

2 1 0 0 0 10 10 0 14 3 0

(continued)

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(continued) Occurrences

KIID KIID KIID KIID KIID KIID KIID KIID KIID KIID 1 2 3 4 5 6 7 8 9 10

Progress Renew* Risk* Source* Sustainab* Society Association* Collect* Complian* Famil* Future Group* Health* Incentive* People Polic* Quality Relation Risk* Wellbeing Wellness Governance Board* Commit* Customer* Effective* Future Goal* Integration Involv* Manag* Result* Stakeholder* Strateg* Sustainab* Labour Age Association* Compensation* Condition* Customer*

18 2 12 3 21

15 10 11 10 10

10 3 12 15 11

9 0 23 10 0

11 10 19 2 1

12 11 2 0 13

10 13 12 0 22

0 11 11 10 24

0 0 16 1 1

0 0 11 11 12

1 10 11 13 17 0 1 11 12 10 19 0 12 15 10

17 11 13 10 20 11 1 16 0 18 10 0 11 2 15

4 10 16 12 16 13 0 14 11 10 13 10 12 14 12

11 0 1 10 2 10 10 13 0 2 10 11 23 10 11

18 10 15 2 5 17 10 1 10 9 10 12 19 0 0

13 1 2 10 15 2 10 10 12 10 0 1 2 0 5

0 12 5 12 13 10 0 1 15 3 10 2 12 11 14

5 0 18 1 2 9 0 0 16 10 11 10 11 10 2

10 1 10 0 14 2 10 0 10 0 0 1 16 2 10

0 1 0 0 10 0 10 1 0 11 1 10 11 2 0

11 10 14 10 17 10 10 14 12 21 14 12 21

13 10 0 11 20 10 10 18 10 19 12 0 10

10 0 21 11 16 12 11 0 13 20 12 0 11

10 2 10 3 2 10 10 1 0 12 11 12 0

10 11 16 11 5 11 1 15 10 10 13 10 1

0 1 15 9 15 10 0 11 10 1 13 11 13

1 0 10 0 13 0 10 2 0 0 0 14 22

1 11 11 0 2 1 1 10 1 11 12 10 24

1 10 3 10 14 0 0 1 0 0 0 0 1

10 10 1 0 10 0 10 12 0 11 11 0 12

1 10 11 11 14

10 0 11 0 0

11 12 0 10 21

10 10 11 0 10

10 0 10 1 16

1 0 1 0 15

1 1 1 0 10

10 1 10 11 11

10 10 0 10 3

1 11 10 10 1

(continued)

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(continued) Occurrences

KIID KIID KIID KIID KIID KIID KIID KIID KIID KIID 1 2 3 4 5 6 7 8 9 10

Efficien* Employ* Equit* Famil* Future Goal* Occupation Opportun* Pension* Risk* Value* Welfare Compliance Communicat* Disclosure ESG Goal* Indicator* Monitor* Law* Opportnit* Regulation* Report* SRI Stakeholder* Standard* Sustainab* Target Performance Compensation Condition* Effecti* Efficien* Energy* Future Health Gain* Indicator* Incentive* Manag* Optimization

12 13 15 13 17 10 11 15 0 12 12 15

13 1 18 10 20 10 15 12 0 11 15 0

10 0 0 12 16 12 10 11 10 12 15 1

12 1 10 10 2 10 11 0 10 23 10 11

0 10 21 2 5 11 1 0 0 19 1 12

1 1 13 10 15 10 0 1 10 2 0 13

10 0 10 12 13 0 1 12 0 12 10 16

1 10 0 1 2 1 0 1 10 11 1 0

0 11 0 0 14 10 1 10 0 16 12 10

0 11 1 0 10 10 10 0 0 11 13 0

10 0 10 10 0 10 12 13 16 12 10 14 0 21 10

10 1 11 10 0 11 10 16 11 10 10 12 1 10 11

1 10 0 12 10 0 10 11 12 0 10 12 10 11 10

11 10 0 10 11 13 1 10 0 10 12 11 12 0 1

12 11 2 11 10 10 1 0 10 9 0 13 11 1 1

13 0 11 10 11 0 10 11 12 0 0 13 10 13 12

1 0 12 0 1 0 11 1 1 10 1 0 12 22 0

0 1 0 1 10 10 0 0 10 0 10 12 10 24 2

10 11 1 10 0 1 0 0 0 10 10 0 1 1 1

11 11 11 10 0 1 0 0 1 0 11 11 10 12 10

11 11 10 12 13 17 1 0 10 11 12 10

11 0 11 13 10 20 1 10 10 16 10 0

0 10 11 10 11 16 0 10 10 14 13 0

11 0 3 12 3 2 10 10 11 13 0 0

10 1 11 0 11 5 10 11 0 1 10 11

1 0 9 1 2 15 10 1 0 10 10 11

1 0 0 10 0 13 0 2 10 1 0 10

10 11 0 1 1 2 0 0 0 0 1 0

0 10 10 0 10 14 10 1 0 0 0 10

10 10 0 0 0 10 10 0 0 1 0 10

(continued)

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(continued) Occurrences

KIID KIID KIID KIID KIID KIID KIID KIID KIID KIID 1 2 3 4 5 6 7 8 9 10

Positive Public Result* Risk* Social Society Value Use

0 10 21 12 14 12 12 0

0 12 19 11 12 13 15 0

10 11 20 12 11 10 15 11

11 10 12 23 0 0 10 10

10 1 10 19 0 10 1 10

0 1 1 2 10 0 0 12

0 10 0 12 11 0 10 0

11 0 11 11 1 1 1 1

1 10 0 16 0 10 12 1

12 1 11 11 2 1 13 10

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CHAPTER 7

Family Firms as Prominent Investment Organizations of Social Finance: An Empirical Analysis of U.S. Family Foundations Carmen Gallucci, Rosalia Santulli, and Riccardo Tipaldi

7.1

Introduction

Social finance aims to generate social, environmental, and financial returns using investment schemes combining financial instruments with different risk–return profiles (La Torre et al. 2017a; Moore et al. 2012a). Social finance represents a disrupting innovation in a “bifurcated world” still separating profit-making from social and environmental

C. Gallucci (B) · R. Santulli Department of Management & Innovation Systems, University of Salerno, Fisciano, Italy e-mail: [email protected] IPAG Business School, Paris, France R. Tipaldi Department of Management, Faculty of Economics, “Sapienza” University of Rome, Rome, Italy © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. La Torre and H. Chiappini (eds.), Contemporary Issues in Sustainable Finance, Palgrave Studies in Impact Finance, https://doi.org/10.1007/978-3-030-65133-6_7

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problem-solving (Bugg-Levine and Emerson 2011). As a financial practice, social finance surged after the global financial crisis, when it became clear that mainstream finance marginalized those individuals and communities who could benefit the most from social innovation (Langley 2020; Moore et al. 2012b). Traditional investors deemed social innovation too risky in terms of return on investment, and governments could no longer subsidize social entrepreneurs due to shrinking budgets. In such a scenario, the actors constituting the bulk of social finance emerged: investment organizations, investor supporters, and innovative grantmakers. Investor supporters comprised capital aggregators, secondary markets, social stock exchanges, foundations, and quasi-public investment funds. Investor supporters included enterprise brokers and capacity builders. Modern grantmakers encompassed online portals, corporate-originated charitable funds, conversion foundations, and funding collaboratives (Salamon 2014). Scholars acknowledged the pivotal role that fund managers and impact funds played in the early days of social finance (Chiappini 2017), when they pooled around USD 15.5 billion toward far-reaching social and environmental projects (Alijani and Karyotis 2019). Likewise, academic literature underlined how high-net-worth individuals and development finance institutions contributed to scale up innovative social projects thanks to their higher risk tolerance and their ability to provide funding at early stages (Bose et al. 2019). Social finance literature also examined the role of private foundations (Moore et al. 2012b), microfinance investment institutions (Carè et al. 2018; La Torre et al. 2017b), social investment networks and advisors (Spiess-Knafl and Scheck 2017), and social finance intermediaries (Moore et al. 2012b). In terms of practices, academics discussed the implementation of public–private partnerships like social impact bonds (La Torre et al. 2019; Del Giudice and Migliavacca 2019; Lehner and Nicholls 2014), the development of alternative finance approaches like microcredit, social lending, equity-based crowdfunding, debt-based crowdfunding, peer-to-peer lending, and web-based funding schemes (Carè et al. 2018), and the structure and role of social stock exchanges (Spiess-Knafl and Scheck 2017). However, research to date neglected large family firms. This gap is noteworthy given that large family firms, when maintaining a healthy balance between family and business priorities (Calabrò et al. 2018), already demonstrated their effectiveness in providing patient capital to social organization (Phillips and Johnson 2019), thus easing local and

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global societal ills (Astrachan 1988; Bhatnagar et al. 2019). We argue that family firms possess the needed financial and non-financial characteristics to play a key role in the social finance arena (Salamon 2014). In terms of financial characteristics, family firms possess the profitability (Anderson and Reeb 2003; Andres 2008; Maury 2006; Miller et al. 2007; Miller and Le Breton-Miller 2006; Minichilli et al. 2016; Villalonga and Amit 2006), capital structure (Koropp et al. 2014; Prencipe et al. 2008), liquidity (Caprio et al. 2020), and control (Gómez-Mejía et al. 2007; LópezGracia and Sánchez-Andújar 2007) necessary to subsidize the demand side of the social finance market (Moore et al., 2012a). Moreover, family firms may find in social finance practices an opportunity to diversify their portfolio risk in terms of geography and financial instruments (GomezMejia et al. 2010). Moreover, due to their sensitivity to societal issues (McKenny et al. 2012; Van Gils et al. 2014) and non-financial characteristics, family firms have further incentives to fund social innovation (Miller and Le Breton-Miller 2005). This chapter suggests including family firms among the leading investors of the social finance market. Given the embryonic stage of the research, we conducted an exploratory study using an inductive approach to data analysis (Yin 2014) in an attempt to discover a model (Eisenhardt 1989) that could “fit and work” (Glaser and Strauss 1967). The sample includes 46 U.S. family foundations and 478 social finance transactions taking place from 2002 to 2019. We focused on family foundations because they are the vehicle family firms use to tackle societal causes (Gautier and Pache 2015). We concentrated on U.S. family foundations for two reasons. First, given that data were, at least partially, publicly available. (Rey-Garcia and Puig-Raposo 2013). Second, because U.S. family businesses express a higher frequency of ethical values than their nonfamily corporate and international counterparts (Blodgett et al. 2011). From 2002 to 2015, U.S. family foundations increased from USD 64.845 to USD 86.203 and expanded their total assets from USD 431 billion to USD 867 billion. In terms of gifts, U.S. family foundations attracted USD 22 billion in 2002 and USD 53 billion in 2015. Their giving also increased from USD 30 billion in 2002 to USD 62 billion in 2015 (Foundation Center 2015). This pilot study indicates that family firms, through their family foundations, are already playing a significant role in the social finance arena by providing social entrepreneurs with equity and debt capital as well as grants. Based on that, we assert that the societal impact of large family

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firms and family foundations is more significant than at first recognized (Litz and Stewart 2000). The present chapter is relevant in light of the social finance market’s current state. The insights emerging from the subsequent empirical analysis may benefit large family firms still not engaged in social finance practices. Given the actual configuration of the social finance market, there are several ways in which large family firms could profit from social finance practices. First, as mentioned previously, a significant gap between public funds and welfare necessities persists. This gap emphasizes the need to reinvent the social intervention paradigm, thus harnessing the potential of capital markets (SIIT 2014) to create social entrepreneurship models subsidized by private finance. Large family firms, given their financial and non-financial characteristics, could help bridge this gap, profit from such investments (SIIT 2016), and be among the leading capital suppliers of social finance. Second, from a traditional finance standpoint, large family firms could find in social investments a way to channel excess liquidity and retained earnings toward endeavors other than the traditional business, thus favoring diversification and risk mitigation (Caprio et al. 2020; Gómez-Mejía et al. 2007; López-Gracia and Sánchez-Andújar 2007). Last, from a strategic standpoint, large family firms can seize the opportunity to differentiate themselves in the growing social investments arena, a market worth USD 502 billion as of April 2019 (Abhilash and Dithrich 2019), by adopting investment approaches different from those of banks, traditional foundations, and asset managers. The study contributes to the growing field of social finance by proposing a quantitative, yet exploratory study in a research field still mostly organized around qualitative studies (Agrawal and Hockerts 2019), and revealing that large family firms possess the financial and nonfinancial characteristics needed to be among the prominent investment organizations of social finance (Moore et al. 2012a; Salamon 2014). To the best of our knowledge, this is the first study in the social finance literature documenting the impact of U.S. family foundations on societal well-being. This chapter has been divided into six sections. Section 2 argues that family firms, given their profitability, financial policies, and diversification strategies, can play a significant role in the social finance market. Section 3 discusses that family firms also possess the social sensitivity and the non-financial characteristics allowing them to be at the forefront of the social finance arena. Section 4 details the research methodology and

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the sample selection and data collection processes. Section 5 presents the results. Section 6 discusses the results and suggests that large family firms, through their family foundations, are already providing social entrepreneurs needing funds with equity and debt capital and grants. Section 7 concludes and outlines several future research avenues.

7.2

Family Firms as Key Social Finance Investment Organizations: Financial Characteristics

Family firms, given their peculiar financial logic driven by growth, risk, and ownership control (Gallo et al. 2004), can play a crucial role in the social finance market. This is because of three main reasons. First, family firms are profitable enough to subsidize social innovation. Second, their financial policies leverage internally generated resources to retain business control. Third, family firms are more willing to diversify as the business risk increases. Regarding profitability, there is evidence that publicly traded familycontrolled businesses, and especially lone founder businesses (Miller et al. 2007), outperform other types of companies in terms of financial performance and market valuations (Maury 2006; Miller and Le Breton-Miller 2006). When the founding family is still active on the executive or the supervisory board, family firms perform better in terms of return on assets (ROA) and of Tobin’s q compared to companies with a dispersed ownership structure and firms with a controlling shareholder (Anderson and Reeb 2003; Andres 2008; Maury 2006; Villalonga and Amit 2006). Even though the issue is still debated (Carney et al. 2015; Mazzi 2011) and the need to consider methodological and conceptual moderators is still relevant (Gallucci and Santulli 2016), recent metaanalyses have confirmed the superior performance of family businesses in terms of ROA (Wagner et al. 2015). Compared to non-family publicly listed companies, listed family-controlled firms performed significantly and consistently better during crises (Minichilli et al. 2016). This is why we argue that family firms are profitable enough to subsidize social innovation (Chu 2009). Their superior performance in terms of ROA suggests that family firms use their assets efficiently. This may also be because they approach their optimal debt level faster than non-family businesses, reducing agency costs and making obtaining resources easier (López-Gracia and Sánchez-Andújar 2007).

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In terms of financial policies, family firms primarily leverage internally generated resources, given that their primary goal is not to lose control of the business (Gómez-Mejía et al. 2007; López-Gracia and SánchezAndújar 2007). When internally generated funds are insufficient, family firms will deter growth opportunities rather than use external financing (Koropp et al. 2014). Moreover, when deciding how to manage their earnings, they are likely to alleviate debt-covenant concerns (Prencipe et al. 2008). In other words, large family firms’ sound financial structure arises from having less leverage and high-quality risk capital. Concerning liquidity, family firms hold more cash than other firms, with an average difference of 2.3% of total assets (Caprio et al. 2020). This aspect is particularly relevant, given that cash-rich companies invest more in the medium-term (Bigelli and Sánchez-Vidal 2012). This leads family firms to be insulated from capital markets pressures and owner-managers to have greater latitude in setting strategic goals, resulting in varying strategic choices and performance outcomes (Carney et al. 2015). We therefore argue that family firms’ leverage and liquidity policies allow them to be among the prominent investment organizations of social finance. This is because of two reasons. First, family firms encounter fewer obstacles when allocating their resources to societal causes through their foundations. This stems from the fact that family firms mainly use internally generated resources to sustain their growth (López-Gracia and SánchezAndújar 2007) and that family owners want to keep the control of their business (Gómez-Mejía et al. 2007). By avoiding external financing when unnecessary (Koropp et al. 2014) and using their earnings to ease debtcovenant concerns (Prencipe et al. 2008), family firms are not subject to significant external or market pressures when deciding for the liberal use of their resources. Second, family firms have enough excess liquidity and high-quality capital to bring into the social finance market. This is because family firms’ capital structure seems to work well together with cash holdings and lower dividend distributions (Croci et al. 2011). Therefore, family firms are profitable enough and possess the proper financial resources to subsidize the demand side of the social finance market, both in the short-term and medium-term through liquidity, and in the long-term through retained profits. As concerns diversification, family firms are more willing to diversify as the business risk increases (Gomez-Mejia et al. 2010). Diversification provides greater financial security to the family, reduces earnings volatility,

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and allows family firms to minimize the business risk due to the undiversified nature of their holdings (Anderson and Reeb 2003; Demsetz and Lehn 1985; Faccio et al. 2001; Shleifer and Vishny 1986, 1997, as cited in Gomez-Mejia et al. 2010). We argue that social finance provides family businesses with an opportunity to ease societal ills while reaping diversification benefits. Investments in social innovation, significantly those “closer to the action” (Bugg-Levine and Emerson 2011), may improve the chances of firm survival, a crucial concern for family members whose welfare is inextricably tied to the future of a single organization (Casson 1999). Summing up, given their profitability, capital structure, liquidity, and control, family firms can subsidize the social finance market’s demand side. Moreover, since family firms are also more willing to diversify as the business risk increases, social finance practices may provide them with an opportunity to diversify their portfolio risk in terms of geographic areas and financial instruments.

7.3 Family Firms as Key Social Finance Investment Organizations: Non-Financial Characteristics Family firms are more attuned to society’s problems than non-family firms (Van Gils et al. 2014). Despite their importance for the economy (Astrachan and Shanker 2003), and even though family firms show higher community involvement levels than non-family enterprises, their social significance is often overlooked. However, their collective impact on societal well-being may be more significant than at first recognized (Litz and Stewart 2000). Family businesses’ relevance to community donations and involvement is evident in their press releases and on their websites, where family firms discuss normative goals next to utilitarian purposes (McKenny et al. 2012). Recently, scholars suggested that familycontrolled businesses’ sensitivity toward ethical behaviors stems from three characteristics: the involvement of the owning family, the inclination to socioemotional wealth, and the typical social interactions (Vazquez 2018). Overall, these studies suggest that there are ethical-related differences between family and non-family firms. In non-family firms the main aim of financial choices is to maximize stocks’ market value. In family businesses the need to ensure firm’s continuity may lead to considerations encompassing also essential emotional components (Gallucci et al. 2017).

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Building on Miller and Le Breton-Miller (2005), we argue that family firms possess the social sensitivity and other non-financial attributes that qualify them as prominent social finance investment organizations. Specifically, we refer to the “4 Cs”: continuity, community, connections, and command (Miller and Le Breton-Miller 2005). Regarding continuity, family-controlled businesses concentrate on a substantive mission attached to a specific social or economic purpose and do not stray from that purpose. The ultimate objective of family firms is to keep doing something important better than anyone else and make the investments that would allow that to happen (Miller and Le BretonMiller 2005). Family business leaders are preoccupied with assuring the family enterprise’s continuity and longevity, so they grow the business for the long-term benefit of family members (Miller et al. 2008). Continuity may be a driving force for family firms in social endeavors, where family members can directly contribute, through their family foundation, to a specific social purpose. By so doing, family firms can harness the financial rewards attached to social finance practices (Moore et al. 2012a) and pursue a favorable reputation allowing family members to feel good about themselves, thus contributing to their socioemotional wealth (Deephouse and Jaskiewicz 2013). Concerning community, family firms build cohesive internal communities based on values and principles. This ensures that family values and ethics are embedded in the company and reflected in all its behaviors (Miller and Le Breton-Miller 2005). Having a strong sense of community may help family-controlled businesses wanting to enter the social finance market in several ways. First, by selecting investees based on the same values and principles used to hire employees, family firms can build an extended community of socially responsible business partners, reflecting family values and ethics. Second, when considering investment decisions, social finance practices raise questions about the purpose of family wealth and carry family values forward over subsequent generations (Bugg-Levine and Emerson 2011). On the question of connections, family firms strive to build enduring relationships based on generosity, trustworthiness, and high ethical standards with a host of stakeholders. Interestingly, some relationships do not relate directly to the business but to serving the community. Such contributions accrue social capital for the company and its later generations and promote its image and brands (Miller and Le Breton-Miller 2005). Since community connections are vital for family firms, we argue that

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social finance, because of its range of instruments and hybrid funding models (Moore et al. 2012a), allows family firms to impact communities significantly. In the case of command, family-controlled businesses are often run by unusually independent and influential family managers acting courageously in the interest of the company (Miller and Le Breton-Miller 2005). Investing in social innovation may carry a higher risk than an investment in more established products, processes, or organizations (Moore et al. 2012a). Summing up, we argue that family firms, because of their sensitivity to societal issues and their non-financial characteristics, namely continuity, community, connections, and command, may be appointed a primary role in social finance.

7.4

Methods

Given the research’s embryonic stage, we conducted an exploratory study and opted for an inductive approach to data analysis (Yin 2014). A significant advantage of the “ground-up” analysis of the data (Yin 2014) is that it may lead to discover a model (Eisenhardt 1989) that could “fit and work” (Glaser and Strauss 1967). 7.4.1

Sample Selection

To begin the sample selection process, we used the Foundation Center (2015) Foundation Stats to identify the top 50 U.S. family foundations by total giving for the years 2002 to 2015. We focused on family foundations because they are the vehicle family firms use to tackle societal causes (Gautier and Pache 2015). We concentrated on U.S. family foundations for two reasons. First, given that data were, at least partially, publicly available (Rey-Garcia and Puig-Raposo 2013). Second, because U.S. family businesses express a higher frequency of ethical values than their non-family corporate and international counterparts (Blodgett et al. 2011). Our initial sample included 700 U.S. family foundations. After removing duplicates, 147 units remained. We then verified if each of these foundations had a CrunchBase (n.d.) profile. Scholars have widely used CrunchBase (n.d.) to get information on venture capital investments in the U.S. (Signori and Vismara 2018; Wal et al. 2016). Having done that,

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we restricted our sample to 60 U.S. family foundations. For each one, we verified if there was at least one deal on CrunchBase (n.d.). We then restricted our sample to 35 U.S. family foundations. Last, we sought other U.S. family foundations having a CrunchBase (n.d.) profile and at least one deal. This resulted in a final sample of 46 U.S. family foundations. Since we aimed at understanding their philanthropic behavior, we retrieved information on the deals that each of the 46 U.S. family foundations performed from 2002 to 2019, with one deal in 1998. We then obtained 531 transactions and, after removing those without information on the amounts raised, we kept 478 of them. Our final sample therefore included 478 deals for the years 2002–2019. 7.4.2

Data Collection

To begin the data collection process, we visited the CrunchBase (n.d.) profile of each of the 46 family foundations. We then looked for the “Investments” section to get information on a family foundation’s deals. For each transaction, we collected the following qualitative and quantitative data: funding year, funding type, funding stage, capital type, money raised (in USD), and the number of partner investors. The sub-categories used to classify each transaction for funding type, funding stage, and capital type are shown and explained in Table 7.1. For each funding stage and capital type, family foundations can use one or more funding models.

7.5

Results

Table 7.2 shows the descriptive statistics for each funding type, funding stage, and capital type. What stands out in Table 7.2 is that in over 70% of transactions, family foundations use funding instruments implying the use of equity capital, namely: angel, funding round, post-IPO equity, pre-seed, private equity, seed, series A, series B, series C, series D, series E, series F, series G, and venture (series unknown). Family firms primarily invest in series B, series C, and series D equity capital, accounting for over USD 5 billion. Further analysis of the data reveals that, although early-stage venture equity capital and grant capital make up over 60% of total transactions, the sum of the money raised in these two funding stages only slightly

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Table 7.1 Funding type, funding stage, and capital type—The table shows the sub-categories used to classify each transaction based on funding type, funding stage, and capital type Sub-categories Funding type Angel Debt financing

Funding round

Grant Post-IPO equity

Pre-seed Private equity Seed Series A

Series B

Series C

Series D

Meaning

In angel rounds, the family foundation provides equity capital to a start-up In debt rounds, the family foundation provides debt capital to an investee with the expectation of a financial return When using the label “funding round” we refer to equity capital, but a more detailed definition of the funding type is unavailable In grants, the family foundation provides grant capital to an investee without holding an equity stake In post-IPO equity, the family foundation provides equity capital to an investee after the investee launched an Initial Public Offering (IPO) In pre-seed rounds, the family foundation provides equity capital to an investee for early-stage product development In private equity rounds, the family foundation provides equity capital to an investee that is already established In seed rounds, the family foundation provides equity capital to an unlisted investee In series A rounds, the family foundation provides equity capital to an investee that already made it through the seed stage In series B rounds, the family foundation provides equity capital to an investee that already made it through the start-up stage In series C rounds, the family foundation provides equity capital to an investee ready to expand into new markets, acquire other businesses, or develop new products In series D rounds, the family foundation provides equity capital to an investee that failed to raise enough money during the series C round or needs additional capital for expansion

(continued)

surpasses the funds raised via late-stage venture equity capital, accounting for only 12% of total transactions. Finally, in Table 7.3, the empirical evidence on the number of partner investors shows that family foundations have the most significant number

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Table 7.1 (continued) Sub-categories

Meaning

Series E

In series E rounds, the family foundation provides equity capital to an investee that failed in raising money during the series D round or needs additional capital for expansion In series F rounds, the family foundation provides equity capital to an investee that failed to raise enough money during the series E round or needs additional capital for expansion In series G rounds, the family foundation provides equity capital to an investee that failed to raise enough money during the series F round or needs additional capital for expansion When using the label “venture (series unknown)” we refer to the equity capital that a venture capitalist provides, but a more detailed definition of the funding type is unavailable

Series F

Series G

Venture (series unknown)

Funding stage Debt Early-stage venture Grant Late-stage venture Post-IPO Private equity Seed Unknown Capital type Debt capital Equity capital

In debt funding stages, the funding type used is debt financing In early venture funding stages, the types of funding used are series A and B equity capital In grant funding stages, the funding type used is grant capital In late-stage venture funding stages, the types of funding used are series C, D, E, F, and G equity capital In post-IPO funding stages, the funding type used is post-IPO equity capital In private equity funding stages, the funding type used is private equity capital In seed funding stages, the types of funding used are angel, pre-seed, and seed equity capital In unknown funding stages, the types of funding used are “funding round” and “venture (series unknown)” When investing in debt capital, family foundations use the “debt financing” funding type When investing equity capital, family foundations use the following funding types: angel, funding round, post-IPO equity, pre-seed, private equity, seed, series A, B, C, D, E, F, G, and venture (series unknown)

(continued)

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Table 7.1 (continued) Sub-categories

Meaning

Grant capital

When investing grant capital, family foundations use the “grant” funding type

Source Our elaboration

of partner investors in early-stage venture funding, when using series A equity capital as funding type.

7.6

Discussion

Social finance research to date neglected large family firms. This gap is noteworthy given that large family firms, when maintaining a healthy balance between family and business priorities (Calabrò et al. 2018), already proved effective in providing patient capital to social organizations (Phillips and Johnson 2019), thus easing local and global societal ills (Astrachan 1988; Bhatnagar et al. 2019). This chapter suggests including family firms among the prominent investment organizations of social finance. To support this view, we examined 46 U.S. family foundations and 478 social finance transactions taking place from 2002 to 2019. We focused on family foundations because they are the leading vehicle family firms use to tackle societal causes (Gautier and Pache 2015). We concentrated on U.S. family foundations for two reasons. First, given that data were, at least partially, publicly available (Rey-Garcia and Puig-Raposo 2013). Second, because U.S. family businesses express a higher frequency of ethical values than their non-family corporate and international counterparts (Blodgett et al. 2011). We argued that large family firms possess both the financial and nonfinancial characteristics necessary to be included among the prominent investment organizations of social finance. In terms of financial features, family firms have the profitability, capital structure, liquidity, and control necessary to subsidize, through their family foundations, the demand side of social finance. Moreover, family firms may find in social finance an opportunity to diversify their portfolio risk in terms of geography and financial instruments. Also, because of their sensitivity to societal

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Table 7.2 Descriptive statistics—The table shows the descriptive statistics for each sub-category of funding type, funding stage and capital type Money raised (in USD)

Nr. of Mean investments

Funding type Angel 10.100.000 3 Debt 49.500.000 3 financing Funding 151.400.000 2 round Grant 1.491.374.859 138 Post-IPO 45.000.000 1 equity Pre-seed 200.000 1 Private 74.430.647 4 equity Seed 123.395.122 56 753.369.263 101 Series A Series B 1.002.623.069 59 Series C 1.088.811.937 35 Series D 1.201.733.415 14 Series E 466.653.938 6 Series F 197.974.787 2 Series G 85.000.000 2 Venture 565.555.874 51 (series unknown) Funding stage Debt 49.500.000 3 1.755.992.332 160 EarlyStage Venture Grant 1.491.374.859 138 Late3.040.174.077 59 Stage Venture Post-IPO 45.000.000 1 Private 74.430.647 4 Equity Seed 133.695.122 60 Unknown 716.955.874 53

Max

Min

S.D.

3.366.667 9.000.000 300.000 4.885.011 16.500.000 45.000.000 1.500.000 24.693.116 75.700.000 150.000.000 1.400.000 105.076.068 10.807.064 180.000.000 6.500 25.353.350 45.000.000 45.000.000 45.000.000 − 200.000 200.000 200.000 − 18.607.662 37.580.000 7.760.130 13.048.692 2.203.484 9.655.354 100.000 1.657.670 7.459.102 56.000.000 1.000.000 7.540.625 16.993.611 100.000.000 1.642.860 17.174.934 31.108.912 100.000.000 2.203.464 23.849.021 85.838.101 300.000.000 4.500.000 110.396.776 77.775.656 206.000.000 3.453.938 71.681.871 98.987.394 107.974.787 90.000.000 12.710.094 42.500.000 60.000.000 25.000.000 24.748.737 11.089.331 150.000.000 600.000 24.119.243

16.500.000 45.000.000 1.500.000 24.693.116 10.974.952 100.000.000 1.000.000 12.831.898

25.353.350 10.807.064 180.000.000 6.500 51.528.374 300.000.000 2.203.464 64.875.952 45.000.000 45.000.000 45.000.000 − 18.607.662 37.580.000 7.760.130 13.048.692 2.228.252 9.655.354 100.000 13.527.469 150.000.000 600.000

1.872.620 30.433.374

(continued)

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Table 7.2 (continued) Money raised (in USD)

Nr. of Mean investments

Capital type Debt 49.500.000 3 Capital Equity 5.766.248.052 337 Capital Grant 1.491.374.859 138 Capital

Max

Min

S.D.

16.500.000 45.000.000 1.500.000 24.693.116 17.110.528 300.000.000 100.000

34.925.338

10.807.064 180.000.000 6.500

25.353.350

Source Our elaboration

Table 7.3 Number of partner investors per funding stage and funding type—The table shows the number of partners involved by family foundations in different funding stages and using different funding types

Funding stage & type

Nr. of partner investors

Debt Debt Financing Early-Stage Venture Series A Series B Grant Grant Late-Stage Venture Series C Series D Series E Series F Series G Post-IPO Post-IPO Equity Private Equity Private Equity Seed Angel Pre-Seed Seed Unknown Funding Round Venture-Series Unknown

− − 87 52 35 6 6 30 16 8 3 2 1 – – 2 2 23 1 1 21 13 1 12

Source Our elaboration

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issues and their non-financial characteristics, namely continuity, community, connections, and command, family firms may have further incentives to subsidize social innovation. This pilot study indicates that family foundations are already playing a significant role in the social finance landscape by providing social entrepreneurs with equity and debt capital as well as grants. Based on that, we can assert that family firms’ impact on societal well-being is much more significant than at first recognized (Litz and Stewart 2000). This study found that in over 70% of transactions, family foundations use funding instruments implying the use of equity capital, namely: angel, funding round, post-IPO equity, pre-seed, private equity, seed, series A, series B, series C, series D, series E, series F, series G, and venture (series unknown). Family firms mainly invest in series B, series C, and series D equity capital, accounting for over USD 5 billion. From a financial standpoint, not being subject to significant external or market pressures when deciding for the liberal use of their resources and having enough extra liquidity, retained profits, and high-quality capital to bring into the social finance arena (Caprio et al. 2020; Carney et al. 2015; Croci et al. 2011; Koropp et al. 2014; Prencipe et al. 2008), family firms can subsidize social innovation by investing in the medium-term (Bigelli and Sánchez-Vidal, 2012). Since they primarily leverage internally generated resources (López-Gracia and Sánchez-Andújar 2007), family firms are free to invest equity capital in companies tackling relevant societal causes, not only keeping control of the family businesses (Gómez-Mejía et al. 2007), but also acquiring control on the investee’s business. The same degree of decision-making freedom is unlikely to be found in highly leveraged companies, where external stakeholders’ demands are higher, and retained profits are lower because interest repayment. From a non-financial standpoint, family firms confirmed their sensitivity to societal issues (Van Gils et al. 2014). This pilot study’s preliminary evidence suggests some interesting implications regarding the concepts of continuity, community, connections, and command (Miller and Le Breton-Miller 2005). Data indicate that family firms put their wealth at stake when subsidizing a specific social purpose. This may seem counterintuitive, since family business leaders invest in building the business for the long-term benefit of family members (Miller et al. 2008). However, we should consider that the family foundation’s financial resources are only a fraction of family wealth. It is more likely that family firms, through their foundations, jeopardize a part of their wealth to

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harness the financial rewards of social finance (Moore et al. 2012a), while pursuing a favorable reputation and contributing to their socioemotional wealth (Deephouse and Jaskiewicz 2013). Regarding community, the use of equity capital, a form of longterm investments also implying a particular involvement in the investee’s decision-making processes and operations, suggests that family firms are not merely selecting investment targets when operating in societal endeavors. Instead, family firms seem to use their wealth purposefully (Bugg-Levine and Emerson 2011). They choose their investees based on values and principles, thus giving family wealth a meaning going beyond mere financial considerations (Gallucci et al. 2017). In the case of connections, social finance offers family firms an unprecedented opportunity to garner social capital for the company and its later generations while improving the image of the firm and its brands (Miller and Le Breton-Miller 2005). Last, regarding command, the willingness to act courageously in the interest of the family firm (Miller and Le Breton-Miller 2005) is reflected in the massive use of equity capital and specifically in the high share of early-stage venture investments made. However, with a small sample size, caution must be applied, as the findings might not represent the full spectrum of family firms’ social finance practices. We are also aware that several other non-financial characteristics of family firms have been overlooked in the present contribution. Likewise, our choice of building on the “4Cs” of Miller and Le BretonMiller (2005) is arbitrary. Nonetheless, we can argue that family firms’ contribution to societal well-being should not be underestimated (Litz and Stewart 2000). With over USD 5 billion of equity capital invested in societal endeavors, family firms have the right to be included among the major players in the social finance arena.

7.7

Conclusions

This chapter suggests including family firms among the leading investors of the social finance market. Results show that family firms, through their family foundations, are already playing a significant role by providing social entrepreneurs with equity and debt capital as well as grants. Family firms’ contribution to societal well-being should not be underestimated (Litz and Stewart 2000). To the best of our knowledge, this is the first study in social finance that has documented the impact of U.S. family foundations on societal well-being. Although the findings

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should be interpreted with caution, this pilot study is also relevant because U.S. family businesses express a higher frequency of ethical values than their non-family corporate and international counterparts (Blodgett et al. 2011). Several questions remain to be answered. This work’s natural progression is to identify other financial and non-financial characteristics of family firms conducive to social finance practices. More broadly, research is also needed to develop a theoretical framework capable of capturing the nuances of family firms’ behavior in the field of social finance. A further study could assess how social finance practices affect the transmission of family values from one generation to another (Bugg-Levine and Emerson 2011). Last, further studies need to be carried out to examine how different family foundations’ models affect impact investing choices (Rey-Garcia and Puig-Raposo 2013).

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CHAPTER 8

Norwegian Pension Fund’s Portfolio: What Happens to the Companies Divested for Environmental Concerns? Stefano Dell’Atti, Viviana Fanelli, and Federica Miglietta

8.1

Introduction

In recent years, institutional investors around the world have begun to attribute an increasing importance to their role as responsible investors. Some of them have been applying environmental, social and corporate governance criteria in order to measure the sustainability and ethical impact of their investment policies. Sustainable investing (also known as Socially responsible investment—SRI) has been defined by the US Social Investment Forum as “an investment approach that considers environmental, social and governance (ESG) factors in portfolio selection and management”. SR investments totaled, as of the end of 2016, $ 22.89

S. Dell’Atti University of Foggia, Foggia, Italy V. Fanelli · F. Miglietta (B) University of Bari Aldo Moro, Bari, Italy e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. La Torre and H. Chiappini (eds.), Contemporary Issues in Sustainable Finance, Palgrave Studies in Impact Finance, https://doi.org/10.1007/978-3-030-65133-6_8

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trillion of assets under management (GSIA 2017); in comparative terms, SRI accounts for 26% of all assets under management at a global level. They can be shared among retail and institutional investors. Institutional assets under management are those of large asset owners such as pension funds and insurers and dominate the market with a share of 74.3% of the total (GSIA 2017). Among all concerned SR institutional investors, Sovereign Wealth Funds represent active actors of primary standing. They are often of governmental origin and, despite the fact that the Fund shows a completely separate organizational structure, they pursue scopes which are closely related to the social and economic goals of the Country that established them. Some SWFs pursue SRI under a legal mandate: among them, the Norwegian Government Pension Fund-Global (GPF-G), the French Pension Reserve Funds and the New Zealand Superannuation Fund. Also the Canada Pension Fund practice SRI, but under a voluntary investment activity code (Richardson 2015). Some Asian and Middle Eastern SWFs have recently begun to pay attention to the so-called principles of climate finance and have financed green investments projects and large-scale implementation of renewable energies, also in order to pursue the economic-strategic objectives set by their countries of origin in terms of energy sources. On the other hand, Western countries have preferred to emphasize the importance of providing ethical and sustainable investment criteria within the asset management industry (Bernstein et al 2013). In particular, those funds involved in the accumulation of intergenerational wealth (as the pension funds) usually take into consideration investment screens related to a general criterion of sustainability, not only to the green finance. What pushes them to manage resources in a sustainable way is the respect of one’s duties towards future generations. Among all sovereign concerned investors, we have chosen to focus our study on the most renown socially responsible pension fund, namely the Norwegian Government Pension Fund-Global (GPF-G). It represents a SWF of primary standing and invests according to very transparent and severe codes of conduct. According to Bengtsson (2008), it reflects the great importance that, over the last decades, Scandinavian countries have devoted to the sustainable investments. Since 2010, the Norwegian Ministry of Finance has established that the Sovereign Fund should have sustained socially responsible investments

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permanently for an amount of NOK 20–30 billion. It has both an investment policy aimed at holding a percentage of holdings in eco-sustainable companies and an Ethical Council capable of assessing the convenience of excluding the less virtuous companies. The recommendations published by the Ethical Council between 2004 and 2014 allowed the GPF-G to disinvest in companies according to ethical concerns and risk based criteria. The GPF-G’s investment/divestment process is well defined and public: these circumstances allow researchers to study both the performance of its portfolio and how the financial markets evaluate the behaviours of those companies that have been excluded by the portfolio. We have chosen to concentrate on the second aspect quoted, wondering whether the companies are punished by concerned investors after being divested by the Fund for their unethical conduct. Divestment is part of the social activism, that is recognized to be an integrating part of SR activities (Ward 1991). Divestment, together with the use of engagement, is able to drive the ethical and environmental behaviours of companies (EUROSIF 2004). As we will detail in the section devoted to the GPF-G activities, several causes of exclusion are considered in the Investment Guidelines. Among them, we circumscribe our analyses on the criterion related to the product-based exclusion for production of thermal coal of coal energy. Basing our data on the recommendations issued by the Ethical Council and accepted by the Ministry of Finance (that have been regularly and transparently disclosed to financial markets since 2004), we have performed a standard event study methodology to assess if and at what extent the stock prices react to the public announcement of exclusion due to polluting environmental production. Once estimated the abnormal share price reaction around the event, we measure the negative effects resulting from reputational damage. We concentrate on one date of exclusion in April 2016, which is very close to the 2016 United Nations Paris Climate Agreement signing ceremony and look at the 37 stocks excluded in that date. The Paris Agreement has signed a milestone for the concerned public and, after a long path, it has represented a paradigm shift towards a better environment; consequently, we expect a coherent behaviour on the side of the financial investors, aimed at punishing (with a divestment) those companies that have been stigmatized by the GPF-G, due to bad environmental activities.

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In our analysis on the stocks excluded from the portfolio, we find that concerned investors care about the serious concerns that have led to the exclusion of the companies and this finding is an important assessment about the increasing importance of the socially responsible behaviours. However, we detect different behaviours on the nine different financial markets involved. Our article is outlined as follows: at first we illustrated the GPF-G investment process to highlight how the divestment decisions are released to financial markets. Second, we present and analyse the various strands of literature related to our research questions in order to show the novelty of our approach. Third, data and methodology are detailed; thereafter, we present our results and discuss the future research we mean to perform enriching the database, both in geographical and time spanning terms.

8.2 The Norwegian Government Pension Fund-Global Investment Process GPF-G, set up in 1990, is a fundamental part of the Norwegian Central Bank duties (called Norge’s Bank). Its website clearly states that “The central bank of Norway’s aim is price stability and financial stability, and to generate added value through investment management ”. The investment management activity is referred to the portfolio of the GPF-G, that is considered to be an oil fund, since it has the “to ensure responsible and long-term management of revenue from Norway’s oil and gas resources in the North Sea so that this wealth benefits both current and future generations ”. With a market value of approximately 9.779 billion of krones (983 billion euros) as of the first quarter of 2019, GPF-G represents a SWF of primary standing, investing according to very transparent and severe codes. Its owner is the Ministry of Finance, on behalf of Norwegian people, that appoints Norges Bank Investment Management as asset manager for the Fund, within a very tight investment mandate. According to a study by Sievänen et al. (2013), there is a curvilinear relationship among the SWF fund size and the decision to engage in SR investments. In particular, especially the smallest and largest pension funds concentrate on sustainability; this seems to be the case of the GPF-G that, with a huge market value is tied to pursue SR investments by a legal mandate. Since 2010, in fact, the Norwegian Ministry of Finance has established that the Sovereign Fund should have sustained socially responsible

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investments permanently for an amount of NOK 20–30 billion a year. It is a typical example of an institutional investor who envisages a policy focused on environmental, social, and correct governance factors (ESG), considering them essential to increase long-term returns. Investments are meant to produce long-term return “with an acceptable level of risk, as a responsible investor and trough an efficient organization”. The management mandate, in Sects. 1–3. Management objective, states that “A good long-term return is considered dependent on sustainable development in economic, environmental and social terms ”. It has both an investment policy aimed at holding a percentage of holdings in eco-sustainable companies and an Ethical Council capable of assessing the convenience of excluding the less virtuous companies. Those companies who are considered not pursuant to the mandate are placed on an observation list and can, after the observation, be excluded from the portfolio. The recommendations published by the Ethical Council between 2004 and 2014 allowed the Ministry of Finance, which was in charge for the decision, to disinvest from companies not compliant with ethical concerns and risk based criteria. After the 1st of January 2015 the board of Norge’s bank was entrusted with the exclusion decision, whilst before that date the exclusion was a duty of the Ministry of Finance. To finalize the decision, the board takes into account the recommendations released by the Council of ethics and imposes on invested portfolios (i) product-based observation and exclusion and (ii) conduct-based observation and exclusion; furthermore, environmental, social and governance issues are integrated into the risk management activities. In the first case (product-based criteria), according to the Sect. 2. Criteria for product-based observation and exclusion of companies set in the official Guidelines for observation and exclusion from the Government Pension Fund Global, the fund cannot invest in companies that, directly, or through controlled legal entities: a. produce weapons that violate fundamental humanitarian principles through their normal use b. produce tobacco c. sell weapons or military materiel to states that are subject to investment restrictions on government bonds.

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In addition, observation or exclusion may be decided for mining companies and power producers which themselves or through entities they control derive 30% or more of their income from thermal coal or base 30% or more of their operations on thermal coal. In the second case (conduct-based criteria), according to the Sect. 3. Criteria for conduct-based observation and exclusion of companies of the official Guidelines for observation and exclusion from the Government Pension Fund Global, companies may be put under observation or be excluded if there is an unacceptable risk that the company contributes to or is responsible for: a. serious or systematic human rights violations, such as murder, torture, deprivation of liberty, forced labour and the worst forms of child labour b. serious violations of the rights of individuals in situations of war or conflict c. severe environmental damage d. acts or omissions that on an aggregate company level lead to unacceptable greenhouse gas emissions e. gross corruption f. other particularly serious violations of fundamental ethical norms. To study these aspects analytically, we have focused our analyses on those companies excluded because of production of coal or coal-based energy according to product-based criteria in the observation date chosen. Dawkins (2016) argues that the divestment activity of the GPF-G is particularly worthy and it is considered as a best practice to look at. This consideration derives from the high transparency of all actions performed since all the decisions are public and immediately released to the market. The Bank maintains a public list of companies excluded from the Fund or placed under observation. From the Norge’s bank website, circumscribing our analysis to the exclusion date of April 2016, we have composed a database of 37 stocks listed on nine financial markets, namely US, Canada, Chile, India, China, Japan, Germany, Australia, UK. Once composed the dataset we have wondered whether and at what extent concerned investors punish the “sinful” companies that have been excluded by the portfolio. This allows us to highlight the behaviour of the

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investors on different markets and to measure the reputational damage of the excluded companies.

8.3

Review of the Literature

Our study is deeply rooted in the area of the socially responsible investments; they have been attracting considerable attention on the financial markets during the last decades and many studies have devoted their attention to those financial vehicles focusing on the environmental and social side of their portfolio. The movement was originally born during the ‘20s of the last century in the UK, when the Methodist Church established an investment policy aimed at avoiding sinful stocks (Sparkes 2002). The research has generally considered at least three aspects of the socially responsible investments; first, many authors have devoted their attention to the performance, wondering whether it is possible to do well by doing good. In other words, they have discussed and analysed the “ethical” portfolio in comparison with the conventional ones, to detect differences in performance attributable to the socially responsible choice. The analyses have been conducted taking into account mutual funds and market indices together with institutional vehicles like SWFs. The second strand of literature, that is less populated in terms of studies, is focused on the performance of the companies that have been chosen by the SR portfolios. The third approach highlights the consideration that concerned investors devote to the environmental side of the companies’ behaviours: this strand is very broad since spans from the national pathways to low carbon emission economies linked to the climate change to the evaluation of how polluting companies’ activities are judged and priced by banks. The first area (SRI performance vs conventional one) is the most ancient and these studies date back to the ‘80s of the last century. The performance of ethically screened portfolios and the link between financial investments and ethical concerns was first analysed by Grossman and Sharpe (1986) when, in response to apartheid, US social movements tried to persuade churches and charities to divest from South African stocks. In the following decades, many studies focused their analyses on ethical funds, comparing their performance with that of conventional vehicles. In some cases, the studies demonstrated that SR funds overperform

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the conventional ones (Mallin et al. 1995; Luther et al. 1992; DuranSantomil et al. 2019), whilst most of the researchers’ evidence suggested that SRI and conventional funds performed similarly in terms of financial returns (Kreander et al. 2002, 2005; Hamilton et al. 1993; Gregory et al. 1997; Gregory and Whittaker 2007; Bauer et al. 2005, 2007; Orlitzky et al. 2003; Humprey et al. 2016; Syed 2017). According to these studies, the results indicate that the hypothesis of SRI fund underperformance due to a lack of diversification can be rejected. Two recent studies of the same year (2015) performed a meta-analysis on the related literature, so to offer a final answer to the research question about the SRI performance. Friede et al. (2015) analysed in detail more than two thousand empirical studies, with a wide geographical scope and on different time spans. According to their analyses, most of the studies testify a positive correlation between the adoption of ESG criteria and the financial performance. The second review, though, finds that SRI funds do not add value in terms of performance; to sum up, according to the authors, the over/underperformance is a matter related to variables like the model specification, time period and benchmark used (Junkus and Berry 2015). In this line of explanation, Nofsinger and Varma (2014) have suggested that the over/underperformance can depend from the period that the market is facing; in their analysis, the SR funds underperform the conventional ones in non-crisis period, whilst during financial crisis the SR performance outperform the conventional funds. The debate, up to now, is still open; to be noticed, however, that all these studies concentrated on mutual funds and stock indices performance. When coming to the specific analysis of SWFs’ portfolios, Sethi (2005) discusses the reasons underlying the SWF and pension funds’ decisions to devote their attention to sustainability. Far from being a “moral” decision, he argues, socially responsible investing practices are a necessary imperative to avoid long-term risk deriving from bad practices in terms of environment and corporate governance. Since most of the SWF continuously monitor their portfolios and exclude some stocks, some authors wonder whether the exclusion of those stocks is able to penalize the performance of the funds. Hoepner and Schopol (2016) study the performance of two Nordic SWFs, namely the GPF-G and the Swedish AP Fund after the exclusion of the “bad” stocks. Their findings suggest that the exclusion of the companies generally does not harm funds’ performance.

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As for the second strand of literature, it mainly focuses on stocks in which SWFs invest under a “positive” point of view: authors have studied what happens to target companies’ value when the SWF decides to invest in their stocks and have investigated whether the SWF investment can exert a favourable effect on the target company. In this line of research Dewenter et al (2010) analyse the impact of investments by SWFs on the values of the companies in which they invest. The average abnormal stock return for those firms that attract SWF investments is positive and statistically significant and these results are consistent with the hypothesis that SWF stock acquisitions have generally benign effects on target firms. A positive effect on the invested company is also found by Bertoni and Lugo (2014) that concentrate on the credit risk of the portfolio companies. Their results are consistent with a decrease of the CDS, suggesting that creditors of the invested company expect SWFs to protect them from bankruptcy. The “negative” side of stocks has been studied by Hong and Kacperczyk (2009) that concentrated their analysis on a portfolio of “sin stocks”, the ones excluded by institutional SR investors and SR mutual fund. According to them, on a period spanning from 1965 to 2006, a portfolio long sin stocks and short their comparable has a return of 26 basis points per month after adjusting for a four-factor model comprising the three Fama-French factors and the momentum (returns) factor. The outperformance is explained by the neglect-effect; being neglected, in fact, these stocks are cheaper than their comparables and show a higher expected return. The authors, though, compose a portfolio of stocks that are not of interest to the SWF: we want to devote our attention, instead, to those stocks that at first entered the portfolio of the SWF and then were divested. In practice, we want to test to what extent the divestment is able to influence the divested stocks market value to understand if the concerned investors punish those stocks in term of reputational loss. Literature has investigated “divestment” in the case of the South Africa boycott due to apartheid (the same situation analysed by Grossman and Sharpe in 1986). Posnikoff (1997) analyse the effect of announcing disinvestment or withdrawal of U.S. firms from South Africa during the 1980s on those firms’ returns. The use of a standards event study methodology allows the author to show a consistent and significant positive announcement effect. On the same issue, Wright and Ferris (1997) report a significant and negative excess returns accrued to shares of those companies that

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announced divestments of South African operations. Their results suggest that noneconomic pressures may influence managerial strategies rather than value-enhancement goals. A similar methodology is used by Breuer et al. (2017) that examine how the stock market reacts when a firm decides to withdraw from countries designated as “State Sponsors of Terrorism” by the U.S. They find a positive stock price reaction; these results suggest an increase in demand for stocks of withdrawing firms as a plausible cause of the positive stock price reaction. In the last studies analysed, the event study methodology has been used to assess a positive or negative price reaction to announcement around the announcement date and this methodology seems to be the most appropriate one to assess the announcement effect. Our aim, however, is not related to the performance of the SR funds or of the SWFs that favour socially responsible investing practices; we mean to study, instead, the market performance of those companies that have been excluded for environmental polluting production (productbased criterion in the GPF-G terms). The approach we use relies in the third strands of literature, where authors consider the reputation of the polluting companies and how the economic actors evaluate them. This approach is strictly linked to the debate arising from the climate change and the necessary transition to a lower emission economy. Studies in this area are countless and span from CSR reporting for chemicals industry (Lock and Seele 2015) to the scoring methods for assessing and disclosing climate change risk in the banking sector (Ambachtsheer et al. 2018; Khalil and O’ Sullivan 2017; Prorokowski 2016; Dobler et al. 2014; Weber 2012; Aintablian et al. 2007). Most of these researches concentrate on banks and have a wide geographical scope. McKenzie and Wolfe (2004) focuses on UK together with two studies by the Bank of England (2017, 2018), whilst Mengze and Wei (2015) study the environment credit risk management in the Asia-Pacific region. In particular, Taiwanese and Chinese banking sector are analysed by McDonald and Hung Lai (2011) and Cui et al. (2018) respectively, whilst Khan et al. (2009) study Bangladesh markets. Weber (2012) analyses the attitude of Canadian banks towards credit risk management and Dobler et al. (2014) look at environmental risk management by US banks. Some researchers have devoted their attention to the European market, focusing on Latvia (Erina and Lace 2012) and, more in general, on the European banks (Weber et al. 2008). All these studies look at companies under a banking

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point of view; in other words, banking sector is increasingly starting to use different assessment methods for environmental risk measurements. The insight of our interest relies in the consideration that financial systems show a different account of maturity whilst dealing with sustainability variables related to environmental behaviours. Canadian and US markets, for instance, account for a better dealing and understanding of environmental risk measurement when compared to the Asian countries. In this sense, our study takes into account this geographical difference and means to analyse the behaviours of investors under this point of view. At first we wonder whether investors “care” about the companies’ exclusion due to environmental polluting production, then, we wonder whether there are differences on financial markets under a geographical point of view. The study concentrates on divested companies, in particular on those companies that have been excluded by the GPF-G for environmental violations. The methodology used is the one illustrated in Armour et al. (2015) to measure the reputational loss suffered by stocks in the UK following a regulatory enforcement by the UK authorities and in Brady et al. (2019) that suggest, in the last two decades of the twentieth century, a negative abnormal returns and insignificant reputational penalties that follow the announcement of environmental violations.

8.4

Data and Methodology

The Event Study methodology is commonly used to assess the announcement effect generated by a particular economic event in a certain period around the event itself. In our study the main phases of the methodology are: i. Defining exactly the event of exclusion from the Fund; ii. Collecting and analysing the historical prices of the considered stocks and benchmarks; iii. Using mathematical-statistical models to measure serious environmental damage consequences on the performance of the stock of the involved company and of the GPF-G; iv. Statistical and empirical analysis of results.

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The event study we analyse is the likely negative effect that the disinvestment of the Norwegian sovereign fund causes on the excluded company securities’ arithmetic returns, calculated on a daily basis, three days before and three days after the publication of the official declaration by the Ministry of Finance. The negative return series could be caused by a reputational loss, which we refer to as: – a damage to the security resulting from high sales volumes concentrated in a limited time window (although the GPF-G rarely holds a share higher than the 0.5-1\% in a single company); – a damage to the image and consequential reduction of the asset price for companies that apparently show to adopt policies aimed at preserving; – a damage to the security resulting from the disinvestment in the company due to the exclusion from the GPF-G because of the violation of environment and protect human rights; – a damage resulting from the imposition of penalties at the national level or even international for companies that are accused by the government of having caused serious environmental damage; their license is withdrawn and the share price decreases. For the data selection and analysis, we refer to the website of the Norwegian Ministry of Finance (www.regjeringen.no) in order to obtain information about the exclusion from the Fund and identify the companies to analyse. Although the currencies in which the securities of these companies are traded are different, in order to allow a homogeneous comparison of the results of the study, the closing prices of each day are converted to USD. All data are downloaded from Thomson Reuters Datastream. We focus on the first criteria of exclusion, namely the product-based criteria and select 37 companies for our analysis. All these companies belong to the Utilities sector. The day of exclusion is the same for all the chosen companies: 14/04/2016. The exclusion decision has been taken after a period of almost three months from the publication of the new product related criterion by the Ministry of Finance. The criterion follows the Guidelines for observation and exclusion from the Government Pension Fund effective on 1st

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February 2016. Where thermal coal is a significant part of a company’s business activities, the company may be excluded from the fund. The new criterion states that coal power companies and mining companies who themselves, or through other operations they control, base 30% or more of their activities on coal, and/or derive 30% of their revenues from coal, may be excluded from the GPFG. They refer to thermal coal. The thresholds are decided by considering the forward looking product/fuel mix transition as well as the degree to which the company utilizes renewable energy in its activities. We aim at investigating if the decision of exclusion from the Government Pension Fund causes an anomalous behaviour of the excluded company share price around the event day. Furthermore, we try to quantify the company reputational loss after the exclusion date. We employ the standard event study methodology (Fama et al. 1969) to evaluate the stock price reaction to the public exclusion announcement. We analyse the reaction to the exclusion announcement of 37 stocks listed on nine financial markets. In Table 8.1, for each market we list the excluded companies. According to the literature (see Fama et al. 1969; Brown and Warner 1985; Mackinlay 1997), we consider 252 trading days before the exclusion event in order to obtain the estimation window or observation period. Therefore, our dataset consists of daily share prices spanning from 30/03/2015 to 19/04/2016. The observation period is the time window from 30/03/2015 to 10/04/2016 and the event days are the working days from 11/04/2016 to 19/04/2016. In the event window, we calculate the abnormal stock price in order to understand the market reaction around the event. The abnormal return of the firm i at time t is defined as A Rti = Rti − α i − β i Rtm

(8.1)

where Rti is the logarithm return of the firm i stock on day t, Rtm is the logarithm return of the market on day t, α i and β i are parameters that vary from security to security. We use a market index as proxy of the market return. In particular, we use the S&P 500 Energy for the United States, the FTSE 100 for the United Kingdom, the Dax Index for Germany, the S&P ASX 200 for Australia, the Nikkei 225 for Japan, the SSE Composite Index for China, the IPSA for Chile, the S$P TSX for Canada and the Nifty for India.

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Table 8.1 Excluded companies

Market/Country

Companies

United States

AES Corporation ALLETTE Inc Ameren Corporation American Electric Power Co Inc First Energy Corporation DTE Energy IDACORP Inc MGE Energy Inc PNM Resource Inc WEC Energy Group Inc Xcel Energy Inc Huaneng Power International Inc Drax Group PLC Lubelski Wegiel Bogdanka SA Whitehaven Coal Ltd New Hope Corp Ltd Hokkaido Electric Power Co Inc Okinawa Electric Power Co Inc/The Shikoku Electric Power Co Inc China Coal Energy Co Ltd China Power International Development Ltd China Resources Power Holdings Co Ltd China Shenhua Energy Co Ltd Datang International Power Generation Co Ltd Yanzhou Coal Mining Co Ltd CLP Holdings Ltd Huadian Power International Corp Ltd AES Gener SA E.CL SA Capital Power Corp TransAlta Corp CESC Ltd Coal India Ltd Gujarat Mineral Development Corp Ltd NTPC Ltd Reliance Power Ltd Tata Power Co Ltd

United Kingdom Germany Australia Japan

China

Chile Canada India

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In the estimation window, the coefficients α i and β i are estimated from an ordinary least squares regression of Rti on Rtm , through the following equation: Rti = α i − β i Rtm + εti

(8.2)

It is assumed that εti satisfies the usual assumptions of linear regression model. That is, εti has zero expectation and variance independent on t; furthermore, all the εti are serially independent and the distribution of εti is independent of Rtm . It follows that A Rti = εti , so that the abnormal return according to a normal performance keeps the characteristics of εti . The average abnormal return (AR) for each day t in the event window is computed as A Rt =

N ∑

A Rti /N ,

(8.3)

i=1

where N is the number of companies over which abnormal returns are averaged on day t. The cumulative average abnormal return (CAR) for the window [t 1 ,t 2 ] is defined as C A Rt =

t2 ∑

A Rt .

(8.4)

t=t1

8.5

Results

The abnormal returns for each Country are estimated through Eq. (1) by using the parameters estimated in the observation period. We find that in the most cases the linear model is suitable for describing the abnormal return event. The exceptions are due to some extreme return values caused by anomalous market behaviour. The regression results improve if we winsorize the dataset before performing the regression. Figures 8.1, 8.2, 8.3, 8.4, 8.5, 8.6, 8.7, 8.8 and 8.9 show the cumulative abnormal returns (CAR) in the days surrounding the exclusion day for each considered country. CAR are calculated according to Eq. (4). It can be interpreted as the cumulative deviation of the returns and they

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0 -0.001 -0.002 -0.003 -0.004 -0.005 -0.006 -0.007

Fig. 8.1 Cumulative abnormal returns in the United States 0.05

0

-0.05

-0.1

-0.15

-0.2

-0.25

Fig. 8.2 Cumulative abnormal returns in Japan

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0.01

0.005

0

-0.005

-0.01

-0.015

-0.02

Fig. 8.3 Cumulative abnormal returns in Chile 0.03 0.025 0.02 0.015 0.01 0.005 0 -0.005 -0.01 -0.015 -0.02

Fig. 8.4 Cumulative abnormal returns in Canada

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0.015

0.01

0.005

0

-0.005

-0.01

-0.015

Fig. 8.5 Cumulative abnormal returns in India 0.04 0.03 0.02 0.01 0 -0.01 -0.02 -0.03

Fig. 8.6 Cumulative abnormal returns in China

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0.14 0.12 0.1 0.08 0.06 0.04 0.02 0

Fig. 8.7 Cumulative abnormal returns in Australia 0.2 0.18 0.16 0.14 0.12 0.1 0.08 0.06 0.04 0.02 0

Fig. 8.8 Cumulative abnormal returns in Germany

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0.09 0.08 0.07 0.06 0.05 0.04 0.03 0.02 0.01 0 -0.01

Fig. 8.9 Cumulative abnormal returns in the United Kingdom

show the cumulative effects of the wanderings of the excluded company stock returns from their normal relationships to the market movements. We focus our attention on the time windows before the exclusion event in order to capture the full impact on the share price and to account for potential information leakage in the days before the press statement by the regulators. In Fig. 8.1 we show the CAR of the United States. We find that it decreases sharply just the days before the announcement and then it becomes negative. In addition, the investors of Japan, Chile, Canada and India react to the exclusion announcement by divesting in the excluded companies, so that CAR becomes negative around the event day. See Figs. 8.2, 8.3, 8.4 and 8.5. For Chile, Canada and India a market equilibrium seems to be soon restored because the CAR increases and becomes positive again in the event window. In Tables 8.2, 8.3, 8.4, 8.5 and 8.6, we show the abnormal returns and CARs for each Country and the result of the t-test performed in order to verify the significant level at 5% of the abnormal returns. Investors of China, Germany, Australia and United Kingdom have an opposite behaviour. In these markets, the CAR sharply increases and

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Table 8.2 Event window analysis in the United States Date

AR

CAR

AR t-test

Significant AR?

11/04/2016 12/04/2016 13/04/2016 14/04/2016 15/04/2016 18/04/2016 19/04/2016

−0,0012 −0,00039 −0,00159 −0,00159 −0,00159 0,002612 −0,00245

−0,0012 −0,00159 −0,00318 −0,00477 −0,00636 −0,00374 −0,00619

−0,800606 −3,2877 −3,2877 −3,2877 5,4075613 −5,065724 −45,66687

no yes yes yes yes yes yes

Table 8.3 Event window analysis in Japan Date

AR

CAR

AR t Test

Significant AR?

11/04/2016 12/04/2016 13/04/2016 14/04/2016 15/04/2016 18/04/2016 19/04/2016

0,000599 −0,05236 −0,05236 −0,05236 −0,05236 −0,01152 0,005784

0,000599 −0,05176 −0,10412 −0,15648 −0,20884 −0,22036 −0,21458

−41,0209 −41,0209 −41,0209 −41,0209 −9,02173 4,53129 −5,96853

yes yes yes yes yes yes yes

Table 8.4 Event window analysis in Chile Date

AR

CAR

AR t Test

Significant AR?

11/04/2016 12/04/2016 13/04/2016 14/04/2016 15/04/2016 18/04/2016 19/04/2016

−0,00224 0,007343 −0,00676 −0,00676 −0,00676 0,007137 0,01584

−0,00224 0,005103 −0,00165 −0,00841 −0,01517 −0,00803 0,007809

13,94812 −12,8343 −12,8343 −12,8343 13,55579 30,08702 1,031578

yes yes yes yes yes yes no

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Table 8.5 Event window analysis in Canada Date 11/04/2016 12/04/2016 13/04/2016 14/04/2016 15/04/2016 18/04/2016 19/04/2016

AR

CAR

AR t Test

0,006899 −0,00214 −0,00676 −0,00676 −0,00676 0,039524 −9,5E-05

0,006899 0,004757 −0,002 −0,00876 −0,01551 0,024011 0,023916

−1,99615 −6,29675 −6,29675 −6,29675 36,8321 −0,08841 19,52668

Significant AR? yes yes yes yes yes no yes

Table 8.6 Event window analysis in India Date

AR

CAR

AR t Test

Significant AR?

11/04/2016 12/04/2016 13/04/2016 18/04/2016 20/04/2016 21/04/2016

0,004795 −0,00551 −0,00431 −0,00515 0,018225 0,004022

0,004795 −0,000709 −0,005024 −0,010174 0,008050 0,012072

5,558719 −6,38162 −5,0011 −5,97033 21,12705 4,661929

yes yes yes yes yes yes

Table 8.7 Event window analysis in China Date 11/04/2016 12/04/2016 13/04/2016 14/04/2016 15/04/2016 18/04/2016 19/04/2016

AR

CAR

AR t Test

0,01816 0,012132 0,012104 0,012104 0,012104 −0,00795 0,003825

−0,01204 0,012132 0,024236 0,03634 0,048444 0,040496 0,044321

12,91179 12,8821 12,8821 12,8821 −8,45864 4,070533 −11,6791

Significant AR? yes yes yes yes yes yes yes

becomes positive, as we show in Figs. 8.6, 8.7, 8.8 and 8.9 and Tables 8.7, 8.8, 8.9 and 8.10.

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Table 8.8 Event window analysis in Australia Date 11/04/2016 12/04/2016 13/04/2016 14/04/2016 15/04/2016 18/04/2016 19/04/2016

AR

CAR

AR t Test

0,039562 0,06414 −0,00676 −0,00676 −0,00676 0,04656 −0,01904

0,039562 0,103703 0,096946 0,090189 0,083432 0,129991 0,110947

39,39161 −4,1498 −4,1498 −4,1498 28,59441 −11,6957 23,3433

Significant AR? yes yes yes yes yes yes yes

Table 8.9 Event window analysis in Germany Date

AR

CAR

AR t Test

Significant AR?

11/04/2016 12/04/2016 13/04/2016 14/04/2016 15/04/2016 18/04/2016 19/04/2016

0,015993 0,034016 0,034016 0,034016 0,034016 0,032076 −0,01569

0,015993 0,050009 0,084025 0,118041 0,152057 0,184133 0,168441

12,09495 12,09495 12,09495 12,09495 11,40497 −5,57951 0,22716

yes yes yes yes yes yes no

Table 8.10 Event window analysis in the United Kingdom Date

AR

CAR

AR t Test

Significant AR?

11/04/2016 12/04/2016 13/04/2016 14/04/2016 15/04/2016 18/04/2016 19/04/2016

−0,00449 0,022931 −0,00437 0,022931 0,022931 0,022931 0,000553

−0,00449 0,018442 0,014077 0,037008 0,05994 0,082871 0,083424

10,1279 −1,92802 10,1279 10,1279 10,1279 0,24427 −0,42932

yes no yes yes yes no no

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Finally, we try to measure the company reputational loss due to the announcement of the observation procedure and the final exclusion of it from the Fund. We define the reputational loss as follows: Rlosst = ΔPt − penalt y,

(8.5)

where ΔPt = Pt − Pt−1 is the change in the stock price and the penalty is assumed to be 0.01% of the company market share. The penalty is a proxy of the fines or expenses that the company could support by the exclusion procedure. We show only the results for the United States, highlighting that similar comment can be made for other countries. We study the reputational loss in function of the following variables, which are also reported in Table 8.1: • Market size, given by the logarithm of market value or capitalization; • Earning for share (EPS), indicating the potential gain obtained by holding the share; • Beta calculated over 3 years given the monthly prices, according to a common procedure of the stock Exchange. We employ a cross-sectional multivariate analysis to examine the above determinants of the reputational loss. First, we exclude the outliers in the sample of stock price change. In particular, we eliminate the price change that are out of the range [μ-σ, μ+σ], where μ and σ are, respectively the change average and standard deviation on the considered time period. Then, we regress the reputational loss over two weeks before the exclusion communication and across the seven selected companies. We use market size, the logarithm of the EPS and beta as independent variables and we obtain the results shown in Table 8.11. We find that all the coefficients are statistically significant. We highlight that the reputational loss of equation (6) represents a real loss for the company only if the sign is negative, that is when Pt < Pt−1 , namely today price is lower than the price of yesterday. The correlation between the reputational loss and the market size is negative, meaning that the bigger the company, the larger the negative effect on the share price. Actually, it confirms what we expected. The EPS has an expansive effect on the size of the loss, given the greater coefficient. The smaller the EPS, the greater the loss. The coefficient of beta is positive, meaning that the higher the

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Table 8.11 Regression results on the reputational loss

const beta MKTSize lnEPS

Coefficient

Std. Error

t-ratio

p-value

−0.856156 2.73902 −0.231802 0.465284

0.322745 0.418175 0.0238954 0.116282

−2.653 6.550 −9.701 4.001

0.0088