Alternative Approaches to Economic Theory: Complexity, Post Keynesian and Ecological Economics 2019011980, 2019012920, 9780429021510, 9780367076016

Table of contents :
Cover
Half Title
Series Page
Title
Copyright
Contents
Acknowledgements
List of illustrations
Foreword
Notes on contributors
Introduction
1 Complexity and economics
2 From complexity science to complexity economics
3 Categorical economic theory
4 Microeconomics: is there a Post Keynesian alternative?
5 Microeconomics in a complex social world
6 Teaching macroeconomics after the crisis
7 Asymmetric price adjustment and other issues in Keynesian macroeconomics
8 Understanding financialisation: standing on the shoulders of Minsky
9 Ecological economics: redefining economics for democracy and sustainability
Conclusions
Index

Citation preview

Alternative Approaches to Economic Theory

The 2007–2008 financial crisis exposed the shortcomings of mainstream economic theory with economists unprepared to deal with it. In the face of this, a major rethinking of economics seems necessary, and in presenting alternative approaches to economic theory, this book contributes to the rebuilding of the discipline. This volume brings together contributions from different perspectives and theoretical approaches that address the challenge of updating the economic theory corpus and seek to recover prestige for this discipline after the failure of neoclassical economics. It addresses a range of topics, including the complexity approach to economics, category theory, the Post Keynesian approach to micro and macroeconomics, financialisation, multidimensional analysis and ecological economics. The book is aimed at economics scholars, researchers, academics and practitioners, as well as upper undergraduates and graduates in this area of knowledge. It may also be of interest for people interested in methodological issues in economics and the relationship between economic theory and the real world. Victor A. Beker is Professor of Economics at the University of Belgrano and the University of Buenos Aires, Argentina. He has been Director of the Economics Department at the University of Belgrano and of the Economics Programme at the University of Buenos Aires and has received several prizes for his work in economics.

Routledge Frontiers of Political Economy

The Dark Places of Business Enterprise Reinstating Social Costs in Institutional Economics Pietro Frigato and Francisco J. Santos Arteaga Economic Woman Gendering Economic Inequality in the Age of Capital Frances Raday The Economics of Military Spending A Marxist Perspective Adem Yavuz Elveren Political Pluralism, Disagreement and Justice The Case for Polycentric Democracy Julian F. Müller Nonviolent Political Economy Theory and Applications Edited by Freddy Cante and Wanda Tatiana Torres Cognitive Capitalism, Welfare and Labour The Commonfare Hypothesis Andrea Fumagalli, Alfonso Giuliani, Stefano Lucarelli and Carlo Vercellone Political Economy for Human Rights Manuel Couret Branco Alternative Approaches to Economic Theory Complexity, Post Keynesian and Ecological Economics Edited by Victor A. Beker For more information about this series, please visit: www.routledge.com/books/ series/SE0345

Alternative Approaches to Economic Theory Complexity, Post Keynesian and Ecological Economics Edited by Victor A. Beker

First published 2020 by Routledge 2 Park Square, Milton Park, Abingdon, Oxon OX14 4RN and by Routledge 52 Vanderbilt Avenue, New York, NY 10017 Routledge is an imprint of the Taylor & Francis Group, an informa business © 2020 selection and editorial matter, Victor A. Beker; individual chapters, the contributors The right of Victor A. Beker to be identified as the author of the editorial material, and of the authors for their individual chapters, has been asserted in accordance with sections 77 and 78 of the Copyright, Designs and Patents Act 1988. All rights reserved. No part of this book may be reprinted or reproduced or utilised in any form or by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without permission in writing from the publishers. Trademark notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging-in-Publication Data Names: Beker, Victor A., editor. Title: Alternative approaches to economic theory : complexity, post Keynesian and ecological economics / edited by Victor A. Beker. Description: New York : Routledge, 2019. | Series: Routledge frontiers of political economy | Includes bibliographical references and index. Identifiers: LCCN 2019011980 (print) | LCCN 2019012920 (ebook) | ISBN 9780429021510 (Ebook) | ISBN 9780367076016 (hardback : alk. paper) Subjects: LCSH: Economics. | Keynesian economics. | Ecology— Economic aspects. Classification: LCC HB171 (ebook) | LCC HB171 .A468 2019 (print) | DDC 330.01—dc23 LC record available at https://lccn.loc.gov/2019011980 ISBN: 978-0-367-07601-6 (hbk) ISBN: 978-0-429-02151-0 (ebk) Typeset in Times New Roman by Apex CoVantage, LLC

Contents

Acknowledgements List of illustrations Foreword Notes on contributors Introduction

vii viii x xiii 1

V I C TO R A . B E K E R

1

Complexity and economics

9

V I C TO R A . B E K E R

2

From complexity science to complexity economics

19

PING CHEN

3

Categorical economic theory

56

F E R N A N D O TO HMÉ AND MARCE L O AUDAY

4

Microeconomics: is there a Post Keynesian alternative?

69

J O R D A N M E L MI È S

5

Microeconomics in a complex social world

89

M I C H E L S . Z O U BOUL AKI S

6

Teaching macroeconomics after the crisis

104

I R E N E VA N S TAVE RE N

7

Asymmetric price adjustment and other issues in Keynesian macroeconomics V I C TO R A . B E K E R

156

vi Contents 8

Understanding financialisation: standing on the shoulders of Minsky

185

C H A R L E S J . WHAL E N

9

Ecological economics: redefining economics for democracy and sustainability

207

P E T E R S Ö D ERBAUM

Conclusions

222

V I C TO R A . B E KE R

Index

227

Acknowledgements

I am very grateful to the authors of the chapters in this volume, who have been very responsive in the face of some strict guidelines. I am particularly indebted to Andy Humphries, who offered me the edition of this volume, as well as to Anna Cuthbert, who assisted me at the different stages involved in the creation of the book. I appreciate the efforts of everyone who took part in the production of this book and I hope its readers will, too. I want especially to thank my wife, Dora, whom I married 53 years ago, which nowadays seems to be quite an achievement. I am sure I would not have edited this volume and written some of its chapters without her patience and support. I am also grateful to my son, Pablo, and his wife, Luciana, who are both responsible for the greatest joy in my life, my grandson Tomas. Victor A. Beker

Illustrations

Figures 2.1 Linear and nonlinear demand–supply curves in microeconomics 2.2 Structural stability in parameter space 2.3 Transition probability for (a) calm (1950–1980) and (b) turbulent (1980–2010) market regimes 2.4 The steady state of probability distribution function in the Ising model of collective behaviour with h = 0 (without central propaganda field) 2.5 The steady state of probability distribution function in a socio-psychological model of collective choice 2.6 Metabolic growth characterised by technology competition with logistic resource constraint 3.1 Commutative diagram 3.2 Cone with limit a × b 4.1 Wood’s (1975) two-curve diagram 4.2 Effect of a rise in financial constraints on non-financial businesses (see Dallery, 2009) 4.3 Effect of a fall in the concentration ratio of the industry 7.1 Equilibrium in the goods market 7.2 The level of employment in the Keynesian model 9.1 Habitual behaviour and decision-making can be understood as the matching of an actor’s ideological orientation and expected impacts in multidimensional terms

20 30 32 34 34 42 59 59 76 79 80 161 166 216

Diagrams 6.1 6.2 6.3 6.4 6.5 6.6

Basic macroeconomic circular flow Embedded macroeconomic flow Institutional economic flow Effective demand Post Keynesian aggregate consumption function Post Keynesian economic flow

110 112 117 119 122 124

Illustrations  ix 6.7 Tax revenue as % of GDP, 2006–2010 6.8 Conditional cash transfers in Latin America: reductions in Gini-coefficient 6.9 Capital/income ratio in Germany, France and Britain, 1870–2010 6.10 The decline of the labour share of income between 1992 and 2008 in China 6.11 Land redistribution and efficiency

132 133 136 143 144

Tables 2.1 Relative deviation (RD) and effective number (N) for macro and finance indexes 2.2 Numbers of households and firms in US (1980) 6.1 Human Development Index and performance, South Asia, 2012 6.2 Multidimensional poverty indicators 6.3 Multidimensional Poverty Index and indicators, South Asia, 2012 6.4 Regional disparities in human development in Thailand, 2014 6.5 GEI and gendered institutions in the MENA region, 2010–2012 6.6 Country scores of the corruptions index (0–100), selected countries, 2012

36 36 126 127 128 134 135 147

Foreword

The economics of the next decade will be quite different from the economics of today, which is already quite different from the economics of ten years ago, and so on. As a useful classifier, the term neoclassical economics is long dead; the term should be condemned to the dustbin of history. What we will call the economics that has replaced it won’t be decided until decades in the future. The reason is that classifying schools of economics is inevitably done after the fact – generally decades after that classification actually described the views of a sufficient portion of the current field to warrant its classification as that school. And, by then, the field has almost inevitably already moved on, so that the cutting edge of the profession is exploring new avenues and approaches that won’t fit even the new classification. This wide-ranging volume gives the reader some insights into ideas that will shape the economics of the future. The volume covers a variety of areas, which are held together by some common themes. One theme is that there are many alternative ways that economic issues can be approached, and that a well-functioning economics profession should be considering many of them in ways that currently it is not doing. With that I am in fully agreement. But, as is also appropriate for a volume devoted to diversity of thought and alternative perspectives, I approach many issues slightly differently than do the authors of the chapters in the volume. One theme that comes through clearly is that complexity economics has become increasingly important and is likely to become more so. Here I am in total agreement, which is why, I suspect, that I was asked to write this foreword. For more than 20 years, I have been arguing that economics is moving into the complexity era. A number of chapters in the volume reinforce this argument and explore issues in complexity and their relationship to economics. As Ping Chen points out in his contribution, complexity has many different definitions and means different things to different people. I emphasise complexity methodology and complexity vision. Both involve a willingness to address the interconnectedness among all parts of the economy and society, rather than relying on the Walrasian model that assumes them away, or the Marshallian model that deals with them as afterthoughts – to be kept in the back of one’s mind as one does formal economic analysis. In reality, both approaches tend to result in important issues being left out of economic analysis, based on tractability arguments. The complexity approach adds them back in.

Foreword  xi The complexity approach deals with issues that educated common sense tells us are important – such as changing tastes, heterogeneous interconnected agents and non-linearities – as best one can, and not pay homage to Burbakian formality. There should not be only one fable guiding policy; there should be many, and cutting-edge economic theorists should be exploring them and developing new ones. Where analytic models aren’t up to the task, one doesn’t avoid the issue; one turns to alternative simulation and agent-based models. Where standard econometrics is not up to it, one uses educated common sense. The approach is: deal with the intractability; don’t let it limit one’s analysis. That “deal with it” approach opens the analysis up to a widening set of issues and suggests multiple models that could be used to capture aspects of reality. The belief that, given our current analytic technology, there are multiple models that can be used is a hallmark of the complexity methodological approach. By capturing some of these multiple alternative models, this book provides an introduction to complexity thinking. A second theme that runs through the chapters in the volume is the need for pluralism and diversity. Again, I find myself in overall agreement. Pluralism is good. But, as with most things, the specifics are much more ambiguous than the general statement. Since the volume is devoted to pluralist views, I will add my own idiosyncratic views related to pluralism. I just don’t deal with pluralism in economic science much – I see science as that part of economics that can be resolved by scientific methods, and I just don’t see a whole lot of questions in economics that have to do with science. Logically, the general equilibrium model is fine. The logic of the model is not something one agrees or disagrees with. Similarly with econometrics. The logic of econometrics is, in my view, unassailable, and thus not subject to pluralist views. Good economic scientists doing science share the same procedures. The problem is: that doesn’t take us of far. How one interprets the model and relates it to reality are not based on science but rather on sensibilities and values, in which science does not guide us. This involves conventions, heuristics and inertia that are open to debate. But the economic profession doesn’t provide anywhere near enough venues for vigorous, reasoned discussion of such issues, and instead circles the wagons around whatever new technique the latest young elites are focused on. That gets the rest of us hoi polloi economists riled and calling for pluralism, when what we mean is that the profession needs a bit more educated, reasoned common sense and humility, and a bit less hubris from the elites. As I’ve argued in the past, my sense is that the economics profession is suffering from inbreeding, with the result that the mainstream profession seems to be following the path of the Spanish Habsburgs, with likely similar results in the long run. That said, I don’t have much to say about pluralism in economic science, since, from what I’ve seen, the type of inbreeding that occurs in economics occurs in just about any science when the empirical tests aren’t conclusive. What’s wrong with economics is similar to what’s wrong with theoretical physics once it moves beyond what empirical work can reasonably answer. Where I do have something to say involves pluralism in economists’ policy discussions. All too often, economists jump from theory and science to policy as

xii Foreword if science were going to provide definitive guides about policy. It doesn’t. Policy analysis requires one to go far beyond science and often precedes science in dealing with problems. All too often, the adjective, scientific, is used as a synonym for objective and reasonable. “That’s non-scientific” is a putdown. What researcher wants to be unscientific? The problem is that policy, by nature, has an important non-scientific element, because it is (and must be) based on normative values and subjective judgments. As David Hume taught us long ago, you cannot derive a “should” from an “is.” Science is about “ises”; policy is about “should.” Of course, in a deep sense “ises” and “should” are entangled from the beginning, leading some philosophers, such as Hillary Putnam, to argue that the entanglement between the positive science of economics and the normative elements of economics cannot be undone. And in a purely logical fashion, he is correct. But, as a working convention one can differentiate entanglements. Deep entanglements – the way one looks at a problem reflects one’s history and values – can’t be eliminated. But they can be differentiated from surface entanglements which occur when you favour a policy because it fits your particular values, not because it is a policy that you believe would be generally beneficial to society. Economists’ positive/normative distinction was an attempt to deal with this surface entanglement. Positive economics deals with issues that are thought to be resolvable using scientific methodology. While it reflects some deep normative issues, since they can’t be escaped, that’s something we just have to live with. Normative economics deals with issues that scientific methodology can’t resolve. We have to deal with normative issues using philosophical methodology, which involves vigorous debate among people with fundamentally different values and views. Pluralism is a necessary and fundamental part of the philosophical method of arriving at what we will consider “philosophical truths” with a small t. Policy belongs in neither of the two categories; following John Stuart Mill, it belongs in a third category – the art of economics – and it requires a combination of both scientific and philosophical methodology. For that reason, applied economics necessarily involves pluralism in ways that positive economics doesn’t. Thus, my major complaint about standard economics is that it is attempting to be more scientific than it can be. Policy involves values; values influence interpretation of theory and of empirical evidence. Söderbaum’s contribution to the volume deals with these issues and comes to similar conclusions. The bottom line: there is a strong need for more alternative perspectives in economics and thus a strong need for books such as this one. I wish you a good read. David Colander Middlebury College, Middlebury

Contributors

Marcelo Auday holds an associate professor position at the Department of Humanities of the Universidad Nacional del Sur and is a member of the Institute of Economic and Social Research of the South (CONICET) in Bahía Blanca, Argentina. He holds degrees from the Universidad Nacional del Sur and the University of Pittsburgh. His research is on the philosophical and methodological foundations of the social sciences. Victor A. Beker is Professor of Economics at the University of Belgrano and the University of Buenos Aires, Argentina. He has been Director of the Economics Department at the University of Belgrano and of the Economics Program at the University of Buenos Aires. He has received several prizes for his work in economics. He is former Associate Editor of the Journal of Economic Behaviour and Organisation and author of several economics books and papers. His main research interest is in the methodology of economics. Ping Chen is a research fellow at the China Institute at Fudan University in Shanghai and a retired professor of the National School of Development at Peking University in Beijing, China. He received a PhD in Physics from the University of Texas at Austin in 1987. His research field is complex business cycles, metabolic growth theory, economic chaos, complexity economics and nonequilibrium physics. Jordan Melmiès is Assistant Professor at University of Lille, France, Clersé Research Department. His research interests lie in the theory of prices, Post Keynesian theory of the firm and profit margins, industrial economics and competition theory. He has published related articles in the Journal of Post Keynesian Economics, Review of Radical Political Economics and Revue de la régulation (The Regulation Review: Capitalism, Institutions, Power). Peter Söderbaum is Professor Emeritus in Ecological Economics at Mälardalen University, School of Business, Society and Engineering, Västerås, Sweden. He is part of the editorial advisory board of the international journals Ecological Economics and Pluralism and Economics Education. His books include Ecological Economics (Earthscan, 2000), Understanding Sustainability Economics (Earthscan, 2008) and Economics, Ideological Orientation and Democracy for

xiv Contributors Sustainable Development (World Economics Association Books, 2018). He has also contributed chapters to Positional Analysis for Sustainable Development (Routledge, 2017) with Judy Brown as first author. Fernando Tohmé is a principal researcher of CONICET (National Research Council of Argentina) and full professor at the Department of Economics of the Universidad Nacional del Sur, in Bahía Blanca, Argentina. He held visiting positions at UC Berkeley, Washington University in St. Louis and Endicott College. His research has focused on decision problems, game theory and optimisation in socio-economic settings. He is currently working on a categorytheoretical reformulation of game theory. Irene van Staveren is Professor of Pluralist Development Economics at the International Institute of Social Studies of Erasmus University Rotterdam. She is a board member of Rethinking Economics NL and of the think tank Sustainable Finance Lab. She also writes a bi-weekly column for the daily newspaper Trouw about the economy and sustainability. She is the author of the textbook Economics After the Crisis – An Introduction to Economics for a Pluralist and Global Perspective (Routledge, 2015). Charles J. Whalen is Visiting Scholar in the Baldy Center for Law and Social Policy at SUNY Buffalo School of Law, USA. In 2018, he served as President of the Association for Evolutionary Economics. He has worked as a macroeconomist at the US Congressional Budget Office, an economics editor at BusinessWeek, a faculty member at Cornell University and a resident scholar at the Levy Economics Institute of Bard College, where he collaborated with Hy Minsky. Michel S. Zouboulakis is Professor of Economics in the Department of Economics, University of Thessaly, Greece. He graduated from the Department of Economics, Aristotelian University of Thessaloniki (1982) and obtained a PhD in Economics from the University of Paris 1, Pantheon-Sorbonne (1988). His research interests are in the methodology and history of economics and various fields of institutional economics. He has published three books, in English (Routledge, 2014), French (PUF, 1993) and Greek (UoThP, 2007), as well as over 80 articles in international peer-reviewed journals and collective volumes.

Introduction Victor A. Beker

The economic crisis and the crisis of economics The 2007–2008 financial crisis exposed the shortcomings of mainstream economic theory. The crisis showed that mainstream economics was quite unprepared to deal with it. There was a widespread belief in the self-correcting power of markets. Most economists not only did not foresee the depth of the crisis but also did not even consider it possible; therefore, they did not know how to deal with it. The crisis has deeply damaged the reputation of economics. A major rethinking of economics seems to be absolutely necessary. In this volume, a collection of contributions offers alternative economic approaches to help improve both our understanding of real-life economic phenomena and the design of economic policy. In this way, the volume tries to take part in the debate, presenting contributions from different perspectives and theoretical approaches that address the challenge of updating the economic theory corpus and recover prestige for this discipline after the failure of neoclassical economics. It is true that economists face very serious difficulties for testing their theories because of the complexity of the subject matter and because of the presence of a lot of disturbances. As Hausman (1992) asserts, they usually trust more in the implications deduced from the theory’s axioms than in the negative results which may emerge from empirical testing. It is very strange to see a theory disregarded because of an apparent disconfirmation. In economics, there is nothing like a crucial experiment. For example, given a certain econometric result, in many cases it is enough to just include another variable or to slightly modify the model assumptions or the estimation method to get different, and even opposite, results. Moreover, contrasting with physics, no Nobel Prize in economics has been awarded for confirmed scientific predictions. Does this mean that economic theories are never refuted? Not necessarily, but refutation usually comes not through empirical tests learnt in statistics and econometrics courses but rather through what I have called “big social experiments” (Beker, 2005). These are the “big events” mentioned by Tobin (1996) which discredit ideas and replace them with new ones. The Great Recession was one of them. It followed the so-called Great Moderation years and refuted the then-predominant Panglossian view that all in the economy was for the best in this best of all possible worlds. As Blanchard (2014: 28) admits, mainstream economists “did think of the

2  Victor A. Beker economy as roughly linear, constantly subject to different shocks, constantly fluctuating, but naturally returning to its steady state over time.” The Big Recession came quite unexpectedly; for most of them, it was a black swan. The Big Recession put an abrupt end to the optimism of the Great Moderation years, when the study of economic and financial disruptions had been practically expelled from the economic theory arena and confined to the economic history field. Unfortunately, as I point out in Chapter 7, while in empirical sciences it is theory which is in trouble whenever there is a conflict between theory and empirical evidence, for mainstream economics it is the opposite, as if economics were a branch of applied mathematics and not an empirical science. That is why internal consistency, rather than external consistency – in the sense of conformability with empirical evidence – becomes the criteria for model admissibility, as rightly noted by Wren-Lewis (2009). The time has come for the reconstruction of economic theory. The main purpose of this book is to present alternative approaches to mainstream economic theory, without necessarily expressing compatible points of view between them. The purpose is not to replace the neoclassical monopoly of economic theory with another monolithic point of view. On the contrary, it is the editor’s point of view that pluralism should be called on to restore the lost academic principle of controversy within economics (see Beker, 2018). It recognises that both the effective development of theory and its valid application depend on debate between contrasting and opposed ideas (Freeman, 2009). Pluralism does not mean that “anything goes.” Pluralism does not mean relativism. It means that economics is not a religion where the economists’ main task is to compete with colleagues to show who is more faithful to the economic Bible. Pluralism implies “a field in which there is a fair competition of ideas and the ‘best ideas’ win out” (Colander, 2007: 1). To promote this competition, “the profession should de-emphasize crass careerism and promote creative activity” (Heckman and Moktan, 2018). In this respect, these authors criticise the centralised power in the hands of a small group of editors and reliance on the so-called Top Five journals of economics to certify quality. They add that this practice incentivises professional incest and raises entry costs for new ideas and persons outside the orbits of the journals and their editors. As Irene van Staveren points out in her chapter in this volume, “economists are just like people. They try to hold on to their worldview and put in much effort to protect their vested interests as academics, policy advisors, and teachers based on the skills they have acquired and invested in.” Pluralism is the key to creating a level playing field where the different economic theories and policies can fairly compete. In order to rebuild economic theory, it is necessary to have in mind that economics – and especially macroeconomics – is supposed to be a guide for economic policy as well as a tool to explain and predict real-world economic behaviour. For this reason, the departure point has to be the need of studying economic illnesses rather than trying to prove the non-existence of economic problems, as neoclassical economics mainly does. Studying real-world economic pathologies and how to cure them should be the main task of economic science.

Introduction  3 It is time to recover the tradition of authors like John Maynard Keynes, John Kenneth Galbraith, Charles Kindleberger and Hyman Minsky, whose main efforts were devoted to the study and solution of economic failures. Even former US Secretary of the Treasury Larry Summers admitted, in a well-known interview by journalist Martin Wolf, that the understanding of financial crises is to be found “not in the academic mainstream of mathematical models festooned with Greek symbols and complex abstract relationships” but rather in the work of pioneering nineteenth-century financial journalist Walter Bagehot, twentieth-century bubble theorist Hyman Minsky, and MIT professor Charles P. Kindleberger. The neoclassical approach works smoothly in normal, stable times, when yesterday’s events are the best guide to what will happen tomorrow. However, it is incapable of dealing with unstable, turbulent, chaotic times. Heterodox contributions elucidate what happens during those periods in which a good part of the economy is reshaped and provide powerful insights towards what policies to follow then. Crises happen from time to time. But sooner or later the storm is over, waters calm down and the orthodoxy’s argument that crises are just exceptions convince the majority, at least until the following crisis bursts. The challenge to heterodox economics is to show its advantages not only in explaining, preventing and coping with complex economic turbulence but also in dealing with more stable environments. It has to show that it not only can explain, prevent and reduce unemployment but can also do the same with inflation. It is true that, by definition, every model implies a certain degree of lack of realism in assumptions – it is a simplification of the real world; the issue is not whether to use or not to use abstraction but rather what it is we abstract of. It is one thing to simplify reality and quite another to overtly distort it. In the orthodox approach, simplification is often done in order to make the model mathematically tractable, at the expense of its ability to capture relevant real-world phenomena. Therefore, in many cases, mainstream economists conclude with theoretical models which exclude most of the features which may be of interest for policy making. Even worse, many practitioners do not check if the model’s assumptions match with the real conditions they are analysing; they just check whether the predictions match with their own ideological prejudices. Or the desired conclusions are reached thanks to sloppy empirical estimations, as the well-known case of the 2010 Reinhart–Rogoff paper testifies.1 As Mäki (2005: 304) rightly states, the representative model must adequately resemble the target system under study. Contrary to Friedman’s well-known assertion, assumptions do matter. If you assume that lions are herbivorous, you will predict that they are harmless to the human being. If you assume that wages are perfectly flexible, you will predict that only voluntary unemployment can exist, as neoclassical economists in fact do. Fairy tales indisputably have their value for entertaining children, but it is not advisable to build economic science on such a foundation. It is usual to distinguish between positive and normative economics. Positive economics is supposed to study “what is,” while normative economics has to do with “what ought to be,” according to Hume’s original distinction. However,

4  Victor A. Beker positive economics starts with certain basic assumptions and generalisations, from which predictions are deduced. Therefore, positive economics does not deal with what the world is but with what the world would be, if and only if it behaved in accordance with economic theory assumptions. That is why the choice of assumptions is crucial in approaching as close as possible the representative model to the target system under study. In normative economics, assumptions are as much as or even more important than in positive economics. For instance, if you assume that prices are perfectly flexible, you may recommend fighting inflation with a tight monetary policy. But, if prices are downwardly sticky, you will end up with more or less the same level of inflation and a decline in the level of real activity. Stagflation will be the most likely result. Of course, you may complain that sticky prices conspire against what theory rightly predicts and recommend changing the real-world behaviour to make it resemble the theoretical one. However, it seems more sensible to make assumptions which take you as close as possible to the real world. The use and abuse of mathematical models by neoclassical economists has unleashed a discussion on the use of mathematics in economics. Mathematics is a language, as Samuelson reminded economists, popularising Gibbs’s sentence. It is no less but no more than a language. Mathematics is a tool to guarantee logical consistency. If logical consistency can be assured without mathematics, what is the point of using it? On the other hand, if it allows conclusions to be arrived at that are not reachable with only logical reasoning, why not use it? As a matter of fact, one can be dogmatic with blackboard diagrams and open-minded with reams of equations. There are some economic problems which require a mathematical approach to ensure rigorous treatment, while others can only be approached using a literary style. So, one should conclude that neither the use nor the non-use of mathematics in economics is a necessary condition for judging scientific standards.

Contents of this book The authors of this volume cover several topics of economic analysis, presenting alternative viewpoints to the neoclassical paradigm. Complexity, microeconomics, category theory, macroeconomics, financialisation and ecological economics are the main subjects the reader will find in this book. It is beyond any doubt that the economy constitutes a very complex system. Victor A. Beker’s and Ping Chen’s contributions argue in favour of the complexity approach to economics. In Chapter 1, Beker emphasises that the complexity approach’s point of departure is that the behaviour of the whole is much more complex than the behaviour of the parts. From the interaction of the parts, new behaviours or new phenomena emerge. These new emergent behaviours and phenomena constitute its object of study. The complexity approach focuses on processes, pointing out to the evolution of the economic system over time, including out-of-equilibrium dynamics. Beker underlines that the orthodox approach to economic phenomena has little to do with empirical reality. Economic data provide little – if any – evidence of

Introduction  5 linear, simple dynamics, or of lasting convergence to stationary states or regular cyclical behaviour. Irregular frequencies and amplitudes of economic fluctuations are persistent and do not show clear convergence or steady oscillations. After presenting some of the findings of this approach, the author discusses whether the complexity approach may be another twist of orthodoxy or may become a heterodox paradigm. Ping Chen argues, in Chapter 2, that there are three lines of thinking in studies of economic complexity. The first school is inspired by the studies started in 1984 at the Santa Fe Institute and those of econophysics since the 1990s. Their focus is computational uncertainty and economic disorder. The second one was developed by the Brussels–Austin school, led by Prigogine since the 1970s. Self-organisation and dissipative structure from physics, chemistry and biology are some of its subjects. The third school is rooted in history, social science and psychology. The author remarks on the need for a more general framework of economic theory based on physics, biology and history and suggests that any realistic theory in economics should be compatible with the laws of physics and biological evolution. In Chapter 3, Fernando Tohmé and Marcelo Auday argue that economics should be defined as the study of the interactions among intentional agents. This definition asks for the ability to represent more faithfully the notion of interaction. The mathematical approach able to accomplish this goal is category theory. Given the increasing influence of computer science on the representation of real-world phenomena, category theory has impacted on the expression of scientific theories in many fields of inquiry. The authors start by presenting the main tenets of category theory, trying to convey why it provides the right language to talk about interactions among intentional agents. Then, they argue that it offers the possibility of building a whole new economic framework founded on behavioural economics. The authors remind readers that behavioural economics assumes that factors other than preferences may also influence the decisions of the agents. Some of those factors relate to the way in which agents frame their decision problems and use heuristics to solve them. In particular, they demonstrate that in the case of behavioural economics, there is no way of developing a unified model incorporating all the possible particular models of non-perfectly rational decision-making. This implies that behavioural economics should not aim at the same type of representation as mainstream economics. Category theory also allows modelling the possible existence of infinite regress in the beliefs held by agents about the beliefs of others. This is a main issue in game theory. This circularity has been shown to be very hard to tame. Tohmé and Auday offer an approach to this issue based on the way theoretical computer science deals with concurrence problems. Finally, the last contribution deals with the composition of games, i.e. the integration of different games and the characterisation of the ensuing equilibria in terms of the equilibria obtained in each of the component games. Categorical economic theory changes the focus from objects to morphisms. This frees the economic models of the emphasis on equilibria, which become objects that may or may not exist in the appropriate category. Unlike traditional

6  Victor A. Beker mathematical frameworks that demand that every entity must be defined in terms of simpler entities, category theory favours a “synthetic” approach, in which objects are given without any consideration to their inner structure, just by its interactions with other objects. In Chapter 4, Jordan Melmiès presents microeconomic theory from a Post Keynesian perspective. He explains that although alternative microfoundations was not an issue in Keynes’s General Theory, it is an important one for Post Keynesian analysis – as well as for Keynesian economics in general, which historically faced the so-called microfoundations problem. Melmiès distinguishes between two branches of Post Keynesian theoretical analysis: a first strand of theory considers that firms seek to maximise their profits, while a second assumes firms seek to maximise growth under the constraint of financing part of investment expenditures on internal funds. The author concludes that the “investment financing” theory of prices and profit margins constitutes the real Post Keynesian alternative to mainstream microeconomics on the topic. He shows how the Post Keynesian theory of the firm can be applied to different areas of economic analysis. This descriptive alternative has consequences for normative positions about economic policy. In particular, price cuts cease to benefit consumers and workers. Michel S. Zouboulakis’s chapter has to do with the teaching of microeconomics. He starts by drawing the reader’s attention to the fact that mainstream microeconomic theory remains conceptually the same as at the beginning of the last century. If Walras and Marshall were alive, he asserts, they would perfectly be able to understand its main topics. The author recalls North’s asseveration that “economic history is a depressing tale of miscalculation leading to famine, starvation, defeat in warfare, death, economic stagnation and decline, and indeed the disappearance of entire civilizations” (North, 2005: 7). Zouboulakis maintains that young economists should learn that conceptions of how best to run the economy change dramatically with major economic and financial crises. In this respect, he suggests strengthening the place of both economic history and history of economic thought, because teaching the evolution of economics and of economic thought are excellent means to promote the idea of scientific controversy and theoretical pluralism within our discipline. A second thing he encourages is the enrichment of the subject of microeconomics with the findings of psychology and behavioural science in particular. The third thing to do is to adopt a socially broader view on economic agency. He argues that many significant elements of social structure that really shape the efficiency of economic outcomes – like initial endowments, property rights and the distribution of wealth in general, preferences, social norms and habits, culture and ideology – should not be taken for granted. They need to be exposed and revealed to the students, to give them an idea of the omnipresent social interaction in market exchanges. For the author, the goal should be teaching a more relevant theory that is both theoretically sound and policy relevant; this will provide a better understanding of the economic phenomena at the level of the firm and the household. In Chapter 6, Irene van Staveren singles out neoclassical theory as one of the causal factors behind the 2007 financial crisis in the developed world as well as the

Introduction  7 1997 financial crisis in Asia. She then reminds the reader that the key policy response to the crisis by governments was grabbed from the Post Keynesian toolkit: increased public expenditures to stimulate economic recovery. However, ten years after the Big Recession, the most popular economic textbooks almost exclusively present the neoclassical economics perspective as the default theory of economics. This motivated her to deliver a textbook of pluralist economics, which presents both heterodox and orthodox perspectives on the economy. In her chapter, the author presents social economics, institutional economics and Post Keynesian economics perspectives to show how heterodox theories can be presented in the teaching of macroeconomics at the introductory level. Macroeconomic flow, wellbeing and poverty and economic growth are the topics subject to analysis from these three different perspectives. The neoclassical perspective is deliberately left out because the purpose of the chapter is to show how the alternative theories can be taught. In the following chapter, Victor A. Beker argues that economic theory has to take into consideration the fact that, in the real world, prices do not behave symmetrically: nominal wages and prices are sticky downward but a lot more flexible upward. For this reason, he stresses that price downward rigidity should be a fundamental assumption in any macroeconomic model which tries to explain and predict real-world market behaviour. The author asserts that while positive demand shocks have a minor effect on output and basically pass to prices, negative shocks are, to a larger extent, passed to output. However, most mainstream economics is built upon the assumption that nominal prices are equally flexible in both directions. Flexible prices are the magic instrument that clear markets. But if nominal prices are downward rigid, they cannot clear markets in the presence of an excess supply, and there is no wealth effect that re-establishes the level of aggregate demand at its full-employment level, as mainstream economics maintains. According to Beker, “price downward rigidity fits perfectly well the Keynesian model, while this does not happen with either the New Keynesian or the Post Keynesian models.” The author then explains how markets can reach their equilibria without the intervention of a price mechanism and presents the real-world reasons why prices are downward rigid. In Chapter 8, Charles J. Whalen explores the issues that Hyman Minsky examined in the last decade of his life and considers their relationship to the financialisation literature. During this period of his life, Minsky focused on the emergence of what he labelled money manager capitalism (MMC). With MMC taking hold, the short view replaced the long view across the economy. The emergence of MMC was also accompanied by an array of institutional innovations in the financial world. Whalen recalls Minsky’s argument that money-fund managers do not see themselves as guardians of the economy’s capital development, adding that this made them fundamentally different from the earlier leaders of finance admired by Joseph Schumpeter. The purpose of money managers was no longer to make profits from production and trade. Rather, the purpose had become giving value to stockholders by assuring that the liabilities of corporations are fully priced in the financial market. Increased economic instability is another danger Minsky associated with MMC. In fact, he argued that it increased the possibility of a market panic; it fuelled

8  Victor A. Beker securitisation; and it threatened to trigger an economic crisis that only coordinated international action would resolve. Whalen understands that Minsky’s work represents a major contribution to the study of financialisation and gives several examples which show how he anticipated much of the work done on the subject in recent decades. Finally, Whalen analyses Minsky’s ability to see what so many others missed and to peer so far into the future. The author concludes that the task ahead is to use our improved understanding to chart a course towards a future in which the economy is not only more robust and stable but also more humane. Finally, in Chapter 9, Peter Söderbaum questions what he calls “monetary reductionism” and recommends a multidimensional analysis to deal constructively with climate change and other elements of the sustainability challenge. Söderbaum starts by questioning neoclassical assumptions. He asks: should we expect firms to maximise monetary profits while forgetting about other interests? Should we look upon individuals as self-interested consumers who disregard all other affected interests? Although he admits that monetary impacts are still important, he argues that, on the non-monetary side, many dimensions are potentially relevant in analysis and decision-making. The author then deals with the concept of democracy. He stresses that democracy is a multifaceted phenomenon that cannot be reduced to one single aspect. It can be understood in relation to its opposites, dictatorship or technocracy. The latter is a dictatorship of experts where the framing of problems and the values to be considered in a search for optimal solutions are dictated by experts and the ideas and values they have internalised. Söderbaum proposes to define economics as “management of multidimensional resources in a democratic society.” He underlines that economics is political economics in the sense that values and ideology are necessarily involved. He remarks that value-neutrality is an illusion: each actor or scholar refers to some viewpoint, vision, worldview or ideological orientation. The author criticises the Cost-Benefit Analysis approach and suggests positional analysis (PA) as an alternative. He notes that in PA, decision-making is regarded as a multiple-stage process where inertia, path dependence, irreversibility and lock-in effects are illuminated. Söderbaum concludes by remarking that there are alternatives to the kind of ecological economics advocated in his chapter. Each perspective has something to offer, and he underlines that a degree of competition and interactive pluralism is not necessarily a bad thing.

Note 1 Finally, there are those who blatantly force the data to get the results they are looking for. One of the most notorious cases has been the World Bank’s “Doing Business” report, which ranks countries around the world by the competitiveness of their business environment. The 2018 Nobel Prize Paul Romer, at the time he was Chief Economist and Senior Vice President of that institution, denounced methodology changes that had the effect of sharply penalising Chile’s ranking under the term of Chile’s former president, Michelle Bachelet.

1

Complexity and economics1 Victor A. Beker

Introduction This chapter provides an overview of the main ideas that comprise the complexity approach in economics. There is no doubt that the economy is a very complex system. The traditional approach to understanding it has been to reduce complexities to simple rules and behaviours, abstracting many features of the real economy. The key issue in this reductionist approach is what features of the real world are kept in the theoretical model and what features are disposed of. What one keeps in and what one gets rid of makes the main difference between orthodoxy and heterodoxy in economics. In the orthodox approach, simplification is often done in order to make it mathematically tractable, at the expense of the models’ ability to capture relevant phenomena. Therefore, in many cases, mainstream economists conclude with models which exclude most of the features which may be of interest for policy making. An alternative to reductionism consists of studying economic systems with a complexity approach. The complexity approach’s point of departure is that reductionism is not suitable for studying systems with many parts that interact to produce global behaviour. This behaviour goes far beyond what can be explained in terms of interactions between the individual constituent elements: the behaviour of the whole is much more complex than the behaviour of the parts. From the interaction of the parts, new behaviours or new phenomena emerge. The study of these newly emergent behaviours and phenomena is the object of study of the complexity approach. Is there any definition for “complexity”? The physicist Seth Miller has gathered at least 45 different definitions of “complexity.” However, many of these are not appropriate for economics. The economist Richard Day (1994) defined complexity in economics in terms of dynamic outcomes. An economic system is dynamically complex if its deterministic endogenous processes do not lead it asymptotically to a fixed point, a limit cycle or an explosion. Yoguel and Robert (2013) propose the following five dimensions to synthesise the 15 elements they find in the different definitions of complexity: (1) heterogeneity,

10  Victor A. Beker (2) disequilibrium and divergence, (3) interactions and partial information, (4) network architecture and (5) emergent properties. The complexity approach changes not only the answers but also the questions to which economics has to respond. For instance, the Arrow–Debreu general equilibrium model is concerned with the static, timeless allocation of resources. Its dynamics just have to do with the existence, stability and uniqueness of the equilibrium. On the contrary, the complexity approach focuses on processes, pointing out the evolution of the economic system over time, including out-of-equilibrium dynamics. The complexity perspective implies a rejection of mainstream conceptual categories and tools, including economic methodology. While the received theory is based on deductive formal proofs of theorems that seek to derive broadly applicable general solutions, the complexity perspective relies on computer simulations and experimental methods to inductively determine possible outcomes and ranges of solutions. According to Brian Arthur (2014), “complexity economics got its start in 1987 when a now-famous conference of scientists and economists convened by physicist Philip Anderson and economist Kenneth Arrow met to discuss the economy as an evolving complex system.” Complexity economics has focused on economic phenomena like business cycle, crises and other out-of-equilibrium behaviour. On the contrary, the main interest of mainstream economics has been to show that the economic system converges on a stable equilibrium. Economic fluctuations are modelled as stochastic shocks attached to low order linear difference equations. The fact that economic fluctuations appear as a sole product of exogenous shocks is in line with the mainstream equilibrium approach in economic thought. In the absence of such shocks, the system would tend to a steady state, as different versions of the neoclassical model of optimal growth predict. “Everything is for the best in the best of all possible worlds” is the Panglossian neoclassical conclusion. The orthodox approach to economic phenomena has little to do with empirical reality. Economic data provide little – if any – evidence of linear, simple dynamics or of lasting convergence to stationary states or regular cyclical behaviour. Irregular frequencies and amplitudes of economic fluctuations are persistent and do not show clear convergence or steady oscillations. Orthodoxy developed a theory which excluded the possibility that a catastrophic crisis could ever happen. It assumes not only that the economy tends towards equilibrium but also that that equilibrium is a stable one. Therefore, economists enrolled in this line of thought not only did not foresee the 2007–2008 financial crisis but also did not even consider it possible. Consequently, they were absolutely unable and unprepared to deal with it. Alternative approaches to the fairy tale that neoclassical economics tells us came back to the fore after the crisis. One of them is the complexity approach to economic phenomena. Its use of nonlinear models offers the advantage that the same model allows us to describe stable as well as unstable and even chaotic behaviours.

Complexity and economics  11

The non-linearity assumption and its implications Once non-linearity is admitted, we are in the presence of positive feedback or increasing returns. Mainstream economic theory removed the assumption of increasing returns from most of its areas because of its tendency to generate the existence of multiple equilibria. Convexity was a necessary assumption to warrant uniqueness of equilibrium. However, the existence of non-convexities and increasing returns are widely used assumptions in some areas of economic analysis. International trade theory, macroeconomics, economic growth, industrial organisation, regional economics and economics of technology are examples. Multiple equilibria are also a widespread result in game theory. The multiplicity of equilibria means that there are many possible worlds. Which of these worlds finally resulted is the product of history: it is history dependent. Another dynamic trajectory might have led to another result. If the equilibrium is unique, history does not matter: sooner or later, the system will arrive at that unique equilibrium. The process is ergodic: whatever the sequence of events, the outcome is always the same. On the other hand, if the process is non-ergodic, the path defines the result. From this perspective, the economy can be seen as a process of self-organisation: the system “chooses” between the different options that are presented to it.

Non-linearity, attractors and chaos The equilibrium approach in economics2 is interested in only one type of attractor: fixed-point attractors. Most efforts are devoted to finding out the conditions under which a unique and stable equilibrium exists. In fact, linear systems either converge on a fixed point or explode. Nonlinear dynamic systems may evolve towards other types of attractors, such as limit cycle or periodic attractors, quasiperiodic attractors and chaotic attractors. The equilibrium approach, as Samuelson (1983: 21) points out, has been taken from equilibrium thermodynamics, which is based on linear relationships. It was the introduction of nonlinear relationships which allowed the development of nonequilibrium thermodynamics. Since sensitive dependence on initial conditions is the main feature of chaotic dynamics, the measure of chaos is provided by the Lyapunov exponent, and more precisely by the largest positive Lyapunov exponent. Lyapunov exponents (L) measure how quickly nearby orbits diverge in phase space. Unpredictability is an intrinsic feature of chaotic systems. Chaos implies the existence of a temporal horizon – defined by the Lyapunov time3 – beyond which predictions lose any reliability. The paradox of chaos is that we are in the presence of unpredictable behaviour that is generated by a completely deterministic process. Economists’ interest in non-linearity emerges from its potential aptitude to model fluctuations in the economy and in financial markets. It offers more options beyond the linear model’s binary alternative between a stable and an explosive path.

12  Victor A. Beker

Non-linearities in the financial markets The traditional approach in the literature on finance has been based on the efficientmarket hypothesis, which argues that the price of financial assets reflects all available information. If so, there is no opportunity for persistent speculative profits, because any news is immediately reflected in prices. However, the view that emerges from this traditional approach contrasts with the widespread perception that financial markets offer opportunities for speculative profits. An alternative approach is based on the distinction between chartists – also called noise-traders – and fundamentalists. While the first extrapolate past trends, the latter are investors governed by the fundamentals of the market. The fact that these models are very successful in replicating the stylised facts of financial markets is seen as a kind of empirical validation. Altavilla and De Grauwe (2010) developed a simple theoretical model in which chartists and fundamentalists interact. The model predicts the existence of different regimes, and thus non-linearities in the link between the exchange rate and its fundamentals. The results suggest the presence of nonlinear mean reversion in the nominal exchange rate process. Traditional linear rational expectations models cannot account for this except by introducing exogenous changes in regimes – that is, by leaving these switches unexplained. The most striking finding is that there appear to be two regimes: one in which the exchange rate follows the fundamental exchange rate quite closely and another in which the fundamentals do not seem to play any role in determining the exchange rate. Both regimes alternate in unpredictable ways; there are frequent switches between fundamental and nonfundamental regimes. As a result, the relation between the exchange rate and the fundamentals is an unstable one. These results are in line with other empirical studies that have so frequently found a disconnection between macroeconomic fundamentals and the exchange rate. They corroborate the advantages of using a nonlinear approach which allows for the existence of more than one state to be detected. The switching nature of the exchange rate process is inconsistent with a linear representation of the relation between the exchange rate and its fundamentals. In a more recent paper, De Grauwe and Rovira Kaltwasser (2012) introduce a distinction between optimist and pessimist fundamentalist traders, respectively referring to traders that systematically overestimate or underestimate the fundamental rate. They show that, even in the absence of chartists, chaos can govern asset price dynamics. Furthermore, chaos can indeed be triggered by the presence of biased fundamentalist traders alone as well as by the interaction between biased and unbiased fundamentalist traders. The model is extended, introducing unbiased fundamentalists and chartists. The latter prove to have a destabilising influence: the larger the coefficient expressing the degree with which they extrapolate the past change in the exchange rate, the stronger their destabilisation power. The system exhibits a Neimark–Sacker bifurcation of the steady state that leads to a stable limit cycle of the market exchange rate. Increasing the value of the chartists’ extrapolation coefficient eventually leads to a break of the limit cycle; the exchange

Complexity and economics  13 rate is governed by a chaotic attractor. This feature of the model is a common result obtained in the literature of heterogeneous agent models in finance, where the interaction between fundamentalists and chartists is analysed and the chartists act as a destabilising force in the market. Finally, the authors perform a Monte Carlo simulation. The model replicates the widely observed phenomenon that exchange rate returns are not normally distributed but, on the contrary, exhibit fat tails. It is clear that once the Holy Trinity of the unbounded rational representative agent, efficient markets and linearity hypotheses is put aside, new illuminating results are obtained. Several models have been introduced where markets are viewed as evolutionary adaptive systems with heterogeneous boundedly rational interacting agents. They match important stylised facts in financial time series such as fat tails and long memory in the returns distribution and clustered volatility. They exhibit interesting dynamics characterised by temporary bubbles and crashes (see Hommes and Wagener, 2008).

Chaos and economics The detection of chaos in economic time series faces three difficulties: (1) the limited number of observations such series contain; (2) the high noise level in economic time series; and (3) the high dimension of economic systems. While in physics, chemistry or biology experiments involve working with tens of thousands to millions of observations, economics works with much smaller series. This prevents many of the nonlinear dynamics tools from detecting intrinsic irregularities even when they are present. The detection of chaos in meteorology has been achieved thanks to the huge number of observations collected through the network of meteorological stations and satellites devoted to that purpose. These instruments have made it possible to significantly improve the accuracy of weather forecasts in recent times. One should wonder what would happen if an equivalent investment were made for the collection of economic data. Economic and financial storms have proved to be at least as destructive as natural storms. Besides that, the presence of dynamic noise makes it extremely difficult to distinguish between (noisy) high-dimensional chaos4 and pure randomness. On the other hand, concerning low-dimensional chaos, small noise easily causes the system to diverge to infinity in the chaotic parameter range. Hommes and Manzan (2005) show how the introduction of increasing levels of noise to a chaotic asset pricing model makes the Lyapunov exponent of the underlying chaotic skeleton model become negative due to the presence of even a small amount of dynamic noise. This may explain why there is weak evidence so far of low-dimensional chaos in economic and financial time series. However, robust deconvolution techniques may be useful for noise reduction (see Beker, 2014: 215).

14  Victor A. Beker

An interactive complex system The economic system is a supremely interactive one. Economic agents influence one another directly. A rush to buy or sell a particular asset can prompt others to do the same. Crashes are an example of stampede phenomena in which individuals act simultaneously in a herd-like and sometimes panic-stricken manner. However, the basic assumption of the general equilibrium theory is that the only interaction among economic agents is through the price system. Assuming that the preferences and hence the choices of one individual are influenced by others introduces an important element of uncertainty which conspires against the possibility of arriving at a stable price equilibrium. Moreover, the strategy followed by neoclassical economists to get stable and unique equilibria has been to introduce a representative agent, thus assuming away any coordination problems that emerge from the interaction among agents. On the other hand, a basic tenet of traditional mainstream economics has been that aggregate behaviour must be derived from underlying rational microfoundations.5 So, agents’ interactions are discarded at the micro level and, at the same time, in order to be acceptable, macro models are supposed to be derived from micro models built under that assumption. Not surprisingly, the result is that most of the real economic problems are excluded from economic analysis. The feedback that one’s decisions have on others’ expectations and behaviour is usually ignored. However, already in the 1930s, Keynes likened asset markets to beauty contests, where people have to guess which of the participants will get the most votes. In the same way, investors in asset markets try to guess which asset will be favoured by other investors’ preferences, in order to invest in it independently of other factors. This sort of conduct may pave the way to herd-like behaviour. Episodes of collective mania are well known in economic history, from the tulip mania in seventeenth-century Holland – where tulip prices ballooned absurdly – to the recent subprime mortgage market crisis.6 Yet, as Ball (2005: 175) notes, “irrational does not mean unpredictable.” Since the end of the 1980s, multi-disciplinary research as done at the Santa Fe Institute has stimulated a lot of work on interacting agents in economics and finance. Models of interacting particle systems in physics have served as examples of how local interaction at the micro level may explain structure at the macro level.7 In order to take into account the difference in behaviour among economic agents in the financial markets, an increasing number of structural heterogeneous agent models have been introduced in the economics and finance literature. Financial markets are viewed as complex adaptive systems consisting of many boundedly rational, heterogeneous agents interacting through simple investment strategies, constantly learning from each other as new information becomes available and adapting their behaviour accordingly over time.8 Speculative bubbles have been observed in laboratory experiments by Nobel prize-winning Smith et al. (1988) and Hommes et al. (2005) using interacting agent models on actual financial data. Inspired by the econophysics literature,

Complexity and economics  15 Kouwenberg and Zwinkels (2015) have developed and estimated a simple multiagent model for the US housing market using housing market data covering the period 1960–2014. The main result is that the interaction between agents in the model can generate boom–bust cycles endogenously. In a companion article, they further show that the econometric model derived from this multi-agent system delivers better out-of-sample price forecasts for the US housing market than standard models. Another promising line of economic modelling is Agent-based Computational Economics (ACE), also called Agent-Based Models (ABMs), the computational study of economic processes modelled as dynamic systems of interacting agents.9 As Davis (2006: 2) points out, contrary to the neoclassical view in which agents are taken to be human individuals all of essentially the same kind of make-up, we have here heterogeneous agents with heterogeneous forms of interaction. Agentbased modelling is formulated in terms of non-Euclidian space; “this nonEuclidian view of the space of agent interactions when understood dynamically requires that the paths individuals take across a sequence of interactions be seen as heterogeneous as well. Thus individuals, it follows, must also be heterogeneous” (ibid.: 13). An ACE macroeconomic model might include structural agents (e.g. a spatial world), institutional agents (e.g. a legal system, corporations, markets) and cognitive agents (e.g. entrepreneurs, consumers, stock brokers and government policy makers); the system’s dynamics are driven by the successive interactions of their participants. ACE models implemented on modern computational platforms can include millions of heterogeneous interacting agents. ACE researchers seek possible causal explanations grounded in the successive interactions of agents operating in realistically rendered virtual worlds. Specifically, they try to understand whether particular types of observed regularities can be reliably generated within these worlds. Agent-based modelling faces a trade-off between descriptive accuracy and explanatory power of the model. The more one tries to inject into the model “realist” assumptions, the more complicated the system becomes to study and the less clear the causal relations going from assumptions to implications are. As Fagiolo and Roventini (2012: 73) point out, ACE researchers have to choose between the KISS strategy – Keep It Simple, Stupid; the KIDS strategy – Keep It Descriptive, Stupid; and the TAPAS strategy – Take A Previous model and Add Something. ACE models are becoming increasingly popular, particularly among policy makers in different fields like economic growth, industrial dynamics, market design, environmental regulation, traffic management, etc., thanks to the flexibility they provide in model building. A guide to different applications of ACE models can be found in Hamill and Gilbert (2016). In a nutshell, ACE models introduce heterogeneity, dynamics and agent interaction in economic modelling. The availability of high-speed processors and the possibility of handling large amounts of data have undoubtedly contributed to the success of ACE models.

16  Victor A. Beker

The complexity approach: orthodox or heterodox? Heise (2016) raises the question of whether the complexity approach is another twist of orthodoxy or if it instead constitutes a heterodox paradigm. I find this question absolutely premature. We don’t know yet what the final outcomes of the complexity approach may be. The issue is not what complexity economists think or feel. As Heise points out, Barkley Rosser Jr., Herbert Gintis and Alan Kirman openly display their esteem for heterodox economics, while authors such as Steven Durlauf, Lawrence Blume and Brian Arthur do not see their paradigm in opposition to neoclassical economics. But neither the former nor the latter have produced something related to complexity which can conclusively be labelled as heterodox or orthodox. For the time being, the complexity approach mainly remains as a methodological proposal. What is clear is that it focuses on different issues than mainstream economics – how an economy emerges, grows and changes structurally over time (Arthur, 2013: 17) – while also using different tools than the neoclassical school. The complexity approach can be seen in this line from Wade Hands: “neither neoclassical nor heterodox economics are the main focus of recent methodological inquiry” (2015: 72). It is too early to know whether the complexity approach will live up to its most ambitious promises, such as being able to take into account “some of the complexity, unpredictability and reflexivity of the economy to take us beyond a mechanistic view of policy” (Beinhockers, 2016: 7).

Conclusions The complexity approach offers an alternative to reductionism for the study of economic systems. Its point of departure is that reductionism is not suitable to study systems with many parts that interact to produce global behaviour. This behaviour goes far beyond what can be explained in terms of interactions between the individual constituent elements: the behaviour of the whole is much more complex than the behaviour of the parts. From the interaction of the parts, new behaviours or new phenomena emerge. The complexity approach changes not just the answers but also the questions to which economics has to respond. Its use of nonlinear models offers the advantage that the same model allows us to describe stable as well as unstable and even chaotic behaviours. Non-linearity offers more options beyond the linear model’s binary alternative between a stable and an explosive path. Is the complexity approach another twist of orthodoxy or constitutes a heterodox paradigm? I find this question too premature. We don’t know yet what the final outcomes of the complexity approach may be. For the time being, the complexity approach mainly remains as a methodological proposal. It is too early to know whether the complexity approach will live up to its most ambitious promises but is clear is that it focuses on different issues and uses different tools than mainstream economics.

Complexity and economics  17

Notes 1 This chapter has benefitted from comments to a previous version presented at the 2017 WEA Conference on Economic Philosophy: Complexities in Economics. 2 It would be better called the “price equilibrium approach.” See Chapter 8 in this volume. 3 Lyapunov time (τ) is measured by the inverse of the Lyapunov exponent:

τ=

1 L

4 Low-dimensional chaos is characterised by only one positive Lyapunov exponent highdimensional chaos by more than one such exponent. 5 This is something required in no other science. 6 Kabir (2017) examines the herding behaviour of investors in the US financial industry during the global financial crisis of 2008. 7 See, for instance, M. Batty (2005). 8 Although I believe that microfoundations should not be a necessary condition for macroeconomics, this does not exclude the possibility of building a macro theory based on the collective behaviour of interacting agents at the micro level. The aim should be to model the behaviour of broad aggregates; if a model of interacting agents helps describe their collective behaviour, it may be a useful tool to model the aggregates to which that behaviour gives rise. 9 See LeBaron and Tesfatsion (2008).

References Altavilla, C. and De Grauwe, P. (2010). Non-Linearities in the Relation between the Exchange Rate and Its Fundamentals. International Journal of Finance & Economics, vol. 15, issue 1, 1–21. Arthur, W. B. (2013). Complexity Economics: A different Framework for Economic Thought. In Arthur, W. B. Complexity and the Economy, Oxford: Oxford University Press. http://complexity.stanford.edu/wp-content/uploads/2015/12/Econ-Frame.A4.pdf Arthur, W. B. (2014). Economic complexity: A different way to look at the economy. https://medium.com/sfi-30-foundations-frontiers/economic-complexity-a-differentway-to-look-at-the-economy-eae5fa2341cd#.tj96yed9z Ball, P. (2005). Critical Mass: How One Thing Leads to Another, London: Arrow Books. Batty, M. (2005). Cities and Complexity, Cambridge, MA: MIT Press. Beinhocker, E. (2016). New Economic Thinking and the Potential to Transform Politics. In OECD, New Approaches to Economic Challenges, Paris. www.oecd.org/naec/ Insights%20into%20Complexity%20and%20Policy.pdf Beker, V. A. (2014). Why Should Economics Give Chaos Theory Another Chance? In Faggini, M. and Parziale, A. (eds.) Complexity in Economics: Cutting Edge Research, Switzerland: Springer. Davis, J. B. (2006). Complex Individuals: The individual in Non-Euclidian Space. (December) Available at SSNR: http://dx.doi.org/10.2139/ssrn.1135685 Day, R. (1994). Complex Economic Dynamics: A Introduction to Dynamical Systems and Market Mechanisms, vol. 1, Cambridge, MA: MIT Press. De Grauwe, P. and Rovira Kaltwasser, P. (2012). Animal Spirits in the Foreign Exchange Market. Journal of Economic Dynamics and Control, vol. 36, issue 8, 1176–1192. Fagiolo, G. and Roventini, A. (2012). Macroeconomic Policy in DSGE and Agent-Based Models. Revue de l’OFCE, issue 124, 67–116.

18  Victor A. Beker Hamill, L. and Gilbert, N. (2016). Agent-Based Modelling in Economics, Hoboken, NJ: John Wiley & Sons. Hands, D. W. (2015). Orthodox and Heterodox Economics in Recent Economic Methodology. Erasmus Journal for Philosophy and Economics, vol. 8, issue 1, Spring, 61–81. http://ejpe.org/pdf/8-1-art-4.pdf Heise, A. (2016). Whither economic complexity? A new heterodox economic paradigm or just another variation within the mainstream? Zentrum für Ökonomische und Soziologische Studien, Universität Hamburg. www.wiso.uni-hamburg.de/fachbereich-sozoek/ professuren/heise/zoess/publikationen/dp58.pdf Hommes, C. H. and Manzan, S. (2005). Testing for Nonlinear Structure and Chaos in Economic Time Series: A Comment. Journal of Macroeconomics, vol. 28, issue 1, 169–174. Hommes, C. H., Sonnemans, J., Tuinstra, J., and van de Velden, H. (2005). Coordination of Expectations in Asset Pricing Experiments. Review of Financial Studies, vol. 12, issue 18, 955–980. Hommes, C. H. and Wagener, F. (2008). No 08-05, CeNDEF Working Papers from Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance. Kabir, M. H. (2017). Did Investors Herd during the Financial Crisis? Evidence from the US Financial Industry. International Review of Finance, vol. 18, issue 1, March, 59–90. https://doi.org/10.1111/irfi.12140 Kouwenberg, R. and Zwinkels, R. C. J. (2015). Endogenous Price Bubbles in a Multi-Agent System of the Housing Market. PLoS One, vol. 10, issue 6, e0129070. https://doi. org/10.1371/journal.pone.0129070 LeBaron, B. and Tesfatsion, L. (2008). Modeling Macroeconomies as Open-Ended Dynamic Systems of Interacting Agents. AER Papers & Proceedings, vol. 98, issue 2, 246–250. Samuelson, P. A. (1983). Foundations of Economic Analysis, Cambridge, MA: Harvard University Press. Smith, V. L., Suchanek, G., and Williams, A. (1988). Bubbles, Crashes and Endogenous Expectations in Experimental Spot Asset Markets. Econometrica, September, vol. 56, issue 5, 1119–1151. Yoguel, G. and Robert, V. (2013). El enfoque de la complejidad y la economía evolucionista de la innovación. Filosofia de la economía, vol. 1, issue 1, 87–130.

2

From complexity science to complexity economics Ping Chen

Main features of simplicity and complexity in economic thinking There is no common definition of complexity in the emerging science of complexity (Waldrop, 1992). Mathematicians and computer scientists are mainly interested in computational complexity and algorithmic complexity. For studies of economic complexity, three disciplines have had an important impact on economic thinking, including systems theory in biology, chaos theory in physics and network theory in mathematics. It is easier to define what simplicity is in neoclassical economics and econometrics. We will compare simplicity and complexity in competing economic theories. A more philosophical term is equilibrium economics in the mainstream as opposed to non-equilibrium economics or so-called heterodox economics. We list seven pairs of simplicity vs. complexity concepts in economics. Methodological individualism vs. system and network thinking The typical example of a simplicity model in neoclassical economics is the representative agent model or Robinson Crusoe economy. Its philosophical doctrine is atomism or reductionism. Its main idea is that the whole is the sum of the parts. It abstracts away all social and economic differences, such as life cycle and income inequality. In contrast, other schools of thought consider that the whole is more than the sum of its parts. These economists would introduce a more complex structure and interactions into economics, such as system dynamics in management, with many parts and many players (Forrester, 1961); or evolutionary economics, with changing structure and history, etc. (Foster, 2006). In mathematical terms, methodological individualism only considers the onebody problem or two-body problem, the latter of which could be transferred into a one-body problem. One striking model in neoclassical economics is the Brownian motion model in the Black–Scholes model of option pricing. The model is a representative agent model with only one particle (Black and Scholes, 1973). Theoretically, modelling competition or cooperation requires at least two parties; studying social interaction should solve the many-body problem. A neoclassical model with one representative agent could only study an optimisation problem without competition and division of labour. Its economic picture is essentially a pre-modern society without industrialisation.

20  Ping Chen Modern examples of many-body problems include complex adaptive systems (CAS), with many interacting agents, and the statistical mechanics model, with a large number of identical particles. Their behaviour is more complex than the neoclassical model of representative agents. One simple implication is that homogeneous vs. non-homogeneous structure in economy. The policy issue of inequality implies a theoretical issue of origin of class structure in economics. This non-homogeneous issue cannot be addressed by homogeneous approach of methodological individualism and the representative agent model. Linear vs. nonlinear models, and single vs. multiple equilibria The basic model in neoclassical microeconomics is the linear demand and supply curve with only one stable equilibrium state. Its macroeconomic version is the IS– LM model. Its main feature is the single stable equilibrium state at the cross point of DD–SS curves. In contrast, nonlinear demand and supply curves may have multiple equilibrium states. Some equilibrium states may be unstable. See Figure 2.1. Linear demand–supply curve

Nonlinear demand curve (Becker)

P DD

P

SS

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Q Nonlinear supply curve (Stiglitz) W(P)

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Figure 2.1 Linear and nonlinear demand–supply curves in microeconomics. (a) Linear demand (DD) and supply (SS) curves with single stable equilibrium. This is a typical picture of a self-stabilised market by “invisible hand” that resulted from rational behaviour in neoclassical economics. (b) Nonlinear S-shaped demand with social interaction (Becker, 1991). There are three equilibrium states (two stable and one unstable) corresponding to the same price. This is a picture of collective behaviour often observed in fashion or the stock market where irrational behaviour is driven by social interactions. (c) Nonlinear Z-shaped labour supply curve in labour market. Surplus labour in subsistence regime (the bottom segment) and shortage labour in leisure regime (the top segment) coexist in an uneven society (Stiglitz, 1976; Dessing, 2002).

Complexity science to complexity economics  21 Equilibrium vs. non-equilibrium process, and convergence vs. diversity in economic evolution The central idea in neoclassical economics is stability, which implies an equilibrium process or a convergent trend. In contrast, the main idea in evolutionary biology and evolutionary economics is diversity or a divergent trend. To ensure market stability, neoclassical economics imposes many conditions for theoretical modelling, including stable single equilibrium, negative feedback in dynamics, convex set in microeconomics, decreasing returns or constant returns to scale in technology, finite mean and variance in econometrics, zero-transaction costs in institutional economics, random walk or Brownian motion model in finance, optimisation framework in micro and macroeconomics, continuity and smoothness in utility and production functions, ergodic theorem in econometrics and economic statistics, path independence in economic history and institutions, nothing new under the sun (no innovation, no new product, no network, no organisation, no structure, no conflicts, no culture, no history), etc. In contrast, non-equilibrium implies diversity and changes. Its mechanism includes multiple stable and unstable equilibrium states, positive feedback and instability, non-convex set, increasing returns to scale, Levy distribution, fat tail distribution, multi-humped distribution, fractal, power law, significant and varying transaction costs, birth–death process, nonlinear dynamics in open systems (without optimisation in closed system), catastrophe, bifurcation, phase transition, bubbles, crisis, slow and sudden changes, self-organisation, spontaneous order, emergence, path dependence in history and institution, origin and evolution of life, city, state and organisation, etc. (Mandelbrot, 1963). Among competing schools of economic thoughts, the neoclassical school is the only equilibrium school. All non-orthodox schools in economics belong to a non-equilibrium perspective to varying degrees, including evolutionary economics, Marxist economics, institutional economics, Austrian economics, Schumpeterian economics, Keynesian economics, behavioural economics and complexity economics, etc., even though their political orientations and mathematical formulations are quite different. From a philosophical perspective, the equilibrium school strongly believes in universal values and institutions, while evolutionary schools have a more inclusive view of human value and institutions. In this regard, neoclassical economics is a Newtonian paradigm, while economic anthropology is a Darwinian paradigm in economic thinking. Certainty vs. uncertainty in dynamics, and stationary vs. non-stationary time series analysis in econometrics In econometrics and time series analysis, neoclassical economics makes strong predictions with certainty. Positive economics, proposed by Friedman (1953a), claimed that econometric analysis could be verified by out-of-sample tests, which is only possible for stationary time series without structural changes in history. Dynamic models demand the stability condition of a deterministic trajectory. Statistical analysis requires a small residual in econometric modelling, etc.

22  Ping Chen There are similar concepts in physics and mathematics. In physics, terms are time symmetric (reversible) in isolated and closed systems with conservation of energy, as opposed to time asymmetric (irreversible) dynamics in open systems without energy conservation. Mathematic terms are integrable vs. non-integrable systems. Econometric forecast and market optimisation is limited with dynamic uncertainty for non-integrable systems. External shocks vs. endogenous cycle in business cycle theory One unique aspect of economic theory is that its philosophy excludes frequency domain in business cycle analysis that is strange in natural science. The neoclassical school prefers external shocks as the only source of business cycles because of its belief in white noise as the math image of invisible hands. Econometric analysis only uses white noise models, such as random walk and Brownian motion, as the driving force of business cycles. Econometrics journals do not publish time series analyses based on frequency analysis. In contrast, frequency analysis is widely used in science, engineering and the medical industry. Classical and quantum mechanics have made tremendous progress based on the harmonic oscillator model. In theory, noise representation and frequency representation are equivalent in spectral analysis, based on the uncertainty principle in quantum mechanics and information theory, since the pulse function is a delta function in time domain and the frequency function is a delta function in frequency domain. Economic math excludes Fourier analysis without any theoretical basis. Neoclassical economics in macro and finance theory simply denies the possibility of internal market instability and market crisis by ruling out theoretical models of deterministic cycles. This is a clear feature of economic theology or alchemy (Hendry, 1980, 2001) rather than economic science (Foley, 2008). Time-symmetric and time-asymmetric processes in economics Historian and social scientists know history is the most complex factor in human affairs, while neoclassical economics abstracts out all traces of history in economic theory. We refer to history as irreversible, or time’s arrow, in physics terms. In contrast, physics laws in a closed system can be characterised by symmetry in time and space. For example, the conservation law of energy is a result of time symmetry, while conservation of momentum is a result of space symmetry; light sets speed limits because of symmetry in four-dimensional space–time. The time-symmetric features in neoclassical economics include symmetry between demand and supply in microeconomics; Markov processes in economic statistics; random walk and Brownian motion in finance; AR (n) models with short correlations in time series analysis; unlimited growth in macroeconomics; zero-transaction costs in institutional economics; and universal values in economic philosophy. History and culture are the most visible time-asymmetric features that are widely discussed in heterodox economics and social science. It is known that

Complexity science to complexity economics  23 production (supply) cycle and consumption (demand) cycle are asymmetric in international division of labour. The idea of a biological clock (Schumpeter, 1939) and of spontaneous order (Hayek, 1991) are economic forms of self-organisation and economic complexity. Nonlinear development and divergent evolution have been studied in economics (Engels, 1884, 1902; Rostow, 1960, 1990), behaviour (Thaler, 2015), institution (Hodgson, 2007), sociology (Weber, 1930), anthropology (Harris, 1978) and psychology (Piaget, 1971; Buss, 2019). Homogeneous models vs. hierarchal structure Homogenous models are prevalent in both economics and physics. However, political economists and psychologists both realise that hierarchal structures exist in human society and human behaviour (Marx, 1978; Maslow, 1970). We discovered a three-level structure (micro–meso–macro) from an empirical analysis of the macro and finance indexes, based on the principle of large numbers (Chen, 2002). The two-level model of a micro–macro structure in neoclassical economics is not sufficient to understand economic complexity from empirical data.

The origin of complexity science in physics and ecology Three disciplines play an important role in studying complexity: physics, mathematics and ecology. They are closely related by mathematical problems in nonlinear dynamical systems. Computational complexity began in mechanics as early as 1899 with the three-body problem, such as the dynamics among sun, earth and moon in celestial mechanics. Mathematics developed new tools in bifurcation theory and nonlinear dynamics. Systems theory began in the field of biology in the 1930s. Evolutionary thermodynamics and self-organisation shed new light on order and chaos. Complexity studies have been interdisciplinary studies since 1970s. Complexity findings have been criticised as being more like metaphor than science, especially for claims made by artificial life (Horgan, 1995). We must be careful about the numerical results of computer experiments and empirical dynamics in a real world. Interesting patterns in cellular automata may not explain simple mechanisms in cell biology. Computational uncertainty and deterministic chaos The first motivation for studying complexity began with computational uncertainty in classical mechanics. Newtonian mechanics establish a deterministic worldview, where the trajectory of a particle is predictable if its dynamical equations and initial conditions are known. This was the origin of scientific determinism, first proposed by Laplace in 1814 (Laplace, 1814, 1902). A dynamical system is defined as stable if a small deviation from the initial condition would rapidly decay so that its movement would converge to its deterministic trajectory. Mathematically speaking, the dynamical system is integrable only if its analytical solution can be expressed as

24  Ping Chen a series of analytical functions and integrals. This belief was shaken by the discovery of deterministic chaos (Hao, 1990). Studies of deterministic chaos began with the mathematical theory of nonlinear dynamics. Poincaré first showed that there was no analytical solution to the threebody problem in gravitation theory (1887). The butterfly effect was first observed in studying radar problem (Cartwright and Littlewood, 1945) and the term was later coined by Ed Lorenz, who discovered computational chaos from the numerical solutions to three-dimensional nonlinear differential equations in climate dynamics (Lorenz, 1963). The popular term “chaos” was coined by mathematicians (Li and York, 1975). Other models of computational chaos were found from one-dimensional nonlinear difference equations, i.e. logistic maps (May, 1976) and nonlinear delay-differential equations (Mackey and Glass, 1977). Deterministic chaos has several features that are “complex” in comparison to linear dynamics, such as bifurcation mechanisms with changing parameters, sensitivity to initial condition characterised by a positive Lyapunov exponent λ, dense periodic orbits, fractal dimensions and strange attractors. A chaotic trajectory only has limited predictability. Unfortunately, mathematicians over emphasised the negative image of deterministic chaos in mechanics. Later we found out the positive function of deterministic chaos in biology, which is more relevant to economy. Experimental evidence of deterministic chaos was widely discovered through physics, chemistry, biology and climate dynamics in the 1970s. Systems theory in ecology and biology The second motivation for studying complexity was rooted in an understanding of the physics foundation of biology. Many scholars realise the fundamental differences between mechanical and biological phenomena. The question is how to characterise living mechanisms. The starting point is finding the alternative to reductionism. Biologists developed the framework of systems theory (Bertalanffy, 1934, 1968). Cybernetics introduced the concept of negative feedback as the main mechanism for selfstabilisation behaviour (Wienner, 1948). Negative feedback became the central mechanism for market stability in neoclassical economics and system dynamics. Haken proposed the idea of Synergetics to characterise the holistic view of biology (1977). Complex systems theory is easily accepted by management economics (Beinhocker, 2006). Three physicists made fundamental contributions to understanding biological phenomena. Schrödinger pointed out that there were two opposing features in biology: stability and variability. He proposed four ideas for describing organisms: meta-stable state, non-periodic crystal, negative entropy and the principle of large numbers in molecular biology (Schrödinger, 1948). May studied the stability of nonlinear ecological systems. He discovered that large ecological systems may become less stable than simpler systems (May, 1974). Prigogine’s idea of selforganisation and dissipative structure constructs chemical reaction models out of living systems, such as BZ reaction and the division of labour in an ant’s behaviour (Nicolis and Prigogine, 1977).

Complexity science to complexity economics  25 Thermodynamics of evolution and self-organisation in physics Early study in bioeconomics and biophysical economics realised the important link between thermodynamics and economics (Georgescu-Roegen, 1971). Some basic concepts in neoclassical economics are at odds with thermodynamics and quantum physics. Prigogine pointed out a fundamental contradiction between thermodynamics and biological evolution (Prigogine et al., 1972). The second law of thermodynamics predicts an evolutionary trend from non-equilibrium structure to equilibrium disorder, characterised by entropy, while biological evolution shows an opposite trend from simple to complex living systems. How can the gap between physics and biology be bridged? Prigogine defined three systems in thermodynamics. Heat death without order results from thermal equilibrium in an isolated system. The equilibrium structure, like a static crystal, can appear in closed systems through energy exchange with the environment. The dissipative structure in open systems exists through constant energy, matter and information flow. Living and social systems can only emerge in an open system. Prigogine’s non-equilibrium thermodynamics paves the way for the physics foundation of the living world. The fatal mistake in neoclassical economics is building upon a closed system. That is why neoclassical economics is a static model in nature without evolutionary change in space and time. Time’s arrow is the essential feature in a living system because history is irreversible in a non-equilibrium process (Prigogine, 1980). The neoclassical model based on equilibrium and random walk simply denies the role of history and time asymmetry in economics. In non-equilibrium physics, “complexity science” or “complex systems” is an extension of evolutionary thinking in biology. Prigogine’s idea of “order out of chaos” has had strong influence among biologists and social scientists (Toffler, 1980; Prigogine, 1984).

A brief history of studies in economic complexity The study of economic complexities has experienced three stages. The first stage is started by mathematical complexity in economic models. The second stage is characterised by empirical studies in economic research. The third stage is developing new economic theory with economic complexity. We will give a brief outline here. Mathematical complexity in economic modelling Chaos has been known as a new science in public media since the 1980s (Gleick, 1987). However, the study of economic chaos met with heavy barriers because of its conflicts with the theoretical framework of neoclassical economics. The first wave of studies in economic complexity simply applied existed math models to economic theories. The known example was a 1D (one-dimensional) chaos model of a logistic map (May, 1976) transformed into an irregular growth

26  Ping Chen cycle in nonlinear difference equations (Day, 1982); and a 2D (two-dimensional) chaos model of a Henon map (1976) into monetary theory (Benhabib, 1980). The limit cycle model in nonlinear differential equations was first introduced by Goodwin (1951). The Lorenz chaos model with three-dimensional differential equations (Lorenz, 1963) was introduced by Goodwin (1990). New mathematical concepts of catastrophe, bifurcation and fractals were introduced into economic models (Rosser, 1991, 2009). Some images, like “butterfly effect” and “edge of chaos,” are mainly computer experiments without a control experiment. Its negative image of disorder and destruction is exaggerated in mass media. In real climate dynamics, hurricane speed is far below light speed. A butterfly flipping its wings could not generate a real tornado because of the law of energy conservation. Chaos theory sets some limits to weather forecasting but does not reject any possibility of weather forecasting in the range of several days to a longer trend of global warming. In mathematical model of dynamics, nonlinear dynamical model is structurally more stable than linear dynamical model. We will discuss this issue later. Empirical studies of economic chaos A fierce debate that began in economics was over the existence of economic chaos and its meanings for economic theory, since the implications of economic chaos would challenge basic beliefs in neoclassical economics and econometrics. In 1984, a numerical algorithm for estimating fractal dimension from empirical data was developed (Grassberger and Procaccia, 1984), and the first empirical evidence of a climate attractor was discovered (Nicolis and Nicolis, 1984). The present author began to search for economic chaos from empirical data in 1984. Empirical and theoretical evidence of economic chaos was first discovered from a monetary index in 1987, and wide evidence from macro and finance indexes in 1996 (Chen, 1987, 1988, 1996a, 1996b). There was a big controversy regarding the empirical research of economic chaos. There are several issues that are unsolved in economics and physics. High noise level from economic indexes and noise-cycle separation in 2D time-frequency space Most empirical evidence of deterministic chaos was discovered from lab experiments in fluid dynamics, chemistry and physiology. Evidence from nonexperimental data such as climate attractors and economic chaos was controversial since their results were hard to verify in controlled experiments. The first wave of empirical tests was based on numerical algorithms in physics, such as Lyapunov exponents and correlation dimensions, which were not effective in economic research (Day and Chen, 1993). The main difficulty is high noise level in economic data. The physics test of chaos requires a large amount of data with very low noise, but high frequency economic data with a low noise level hardly exists.

Complexity science to complexity economics  27 Physicists also use frequency spectra to detect sub-harmonic frequencies from continuous-time deterministic chaos. However, a Fourier analysis in physics and engineering can only analyse stationary time series that can be obtained from lab experiments, not non-stationary time series from non-controllable observations, such as radar signals from moving targets. We could separate noise with cycles from economic data by means of new algorithm of time-frequency analysis based on Wigner transform in Gabor two-dimensional time-frequency space. We could minimise computational uncertainty because our base function is Gabor wavelet with minimum uncertainty in quantum mechanics and information theory (Qian and Chen, 1996; Chen, 1996a). Unfortunately, the physics algorithm for timefrequency analysis is only available in Matlab, under patent protection by National Instrument, and is not freely available with econometric software packages. Few economists could afford to have these advanced tools to verify our results. This is why obsolete math still dominates in mainstream economics, where the budget constraint in economic research prevents economists to adopt new tools from physics and engineering. White chaos in discrete time vs. colour chaos in continuous time The second wave of empirical tests of chaotic models was a big failure, since econometric tests based on regression analysis as well as discrete time difference equations, had no empirical evidence. Empirical tests of logistic maps and Henon maps had no success. Mainstream economics quickly accepted the premature conclusion that economics had little evidence of economic chaos based on conflicting evidence from econometric tests and physics tests (Brock and Sayers, 1988). We found several sources that make economic chaos hard to observe through conventional methods. Economists are used to econometric models in discrete time; few economists had the mathematical knowledge to solve nonlinear differential equations and spectral analysis of time series. Economists do not know that there are two types of deterministic chaos in math models. “White chaos” is from nonlinear difference equations and has flat spectra that looks like white noise. White chaos could only observe from numerical solutions from simple theoretical models but no empirical evidence of white chaos, since human experience is based on continuous time. Only generation dynamics of insects could be described by discrete time model such as logistic map. All observed empirical chaos is “colour chaos” from continuous-time differential equations, which has a fat peak plus a noisy background in frequency spectra. The physics reason behind math is simple, since we do not have a theory of “quantum time” with an intrinsic fixed time unit. We found low-dimensional colour chaos in monetary and finance indexes that can be explained by delay-differential equations in continuous-time (Chen, 1988, 1996a), which was first discovered from biological chaos (Mackey and Glass, 1977). It implies that economic dynamics are more complex than climate dynamics; since a 1D delay-differential equation is a mixed difference-differential equation, its numerical solution needs to calculate infinite-dimensional of differential

28  Ping Chen equations. And the numerical solution of a 1D differential equation needs to calculate infinite-dimensional difference equations. Mathematical physics was familiar with delay-differential equations first from neuron dynamics and then later from biological chaos such as cell vibrations. Economic mathematics is far behind chaos study, since economic models are mainly confined by low-dimensional difference equations and regression analysis. The Copernicus problem in macro and finance analysis There is an unsolved Copernicus problem in macro-finance analysis that is caused by a growing trend in many economic time series. Three competing schools in business cycle theory used different types of filters to transform a non-stationary macro time series with a growth trend into stationary time series without trend. Keynesian economists follow Solow’s method of log-linear detrending that implies a constant growth rate in a macro economy, which is different within different time windows. Econometricians follow the monetarist Friedman’s method of FD (firstdifferencing) of logarithmic time series, which implies no visible growth trend within a time unit. The RBC school used the HP filter to separate a smooth trend and business cycles within a range of 2–10 years, according to the NBER business cycle chronology. We found wide evidence of colour chaos, mainly from the HP filtered cycle series, but only white noise from the FD series. The reason is very simple. HP cycles, on average, are about 4–5 years, from US data; that is the typical political cycle in US. Multiple frequencies were also observed that were consistent with Schumpeter’s theory of business cycles as a biological clock. The whitening filter in econometrics and white noise representationof efficient market There is a philosophical bias that prevents economists from accepting new evidence of economic chaos. Believers in efficient markets assume that white noise is the proper math representation for perfect competition (Friedman, 1953b). The FD filter is a whitening device, which amplifies high frequency noise and suppresses low frequency signals. Economists used to FD filter not only because of its mathematical simplicity but also based on their belief in the “invisible hand.” Econometricians analyse economic data with a white looking glass. They fail to see a colourful world simply because they are colour-blind. Computational economics with complex patterns Advancement of computer technology paved the way for computer simulation in computational physics. There are three approaches in economic simulation with large systems. The first approach is system dynamics in management, developed at the Sloan School of MIT (Forrester, 1961). The second is self-organisation based on ecological dynamics, developed by physicists in the Brussels school (Allen and Sanglier, 1981; Allen, 1997). The third approach is called a complex

Complexity science to complexity economics  29 adaptive system (CAS) or agent-based model, developed at Santa Fe Institute, and is a computer automata that originated in artificial life (Anderson et al., 1988; Arthur et al., 1997). Computer simulations could generate many interesting features, such as complex behaviour caused by simple interaction rules, emergence of communities and cities, diversifying patterns in geography and erratic fluctuations in the stock market, etc. (Arthur, 2015; Wilson and Kirman, 2016; Aruka and Kirman, 2017). Their challenge is how to match specific mechanisms from empirical observation to computer simulation. Persistence of biological clock and resilience in regime switch One fear created by chaos and complexity theory is its public image of disorder and destruction. On the contrary to their math language, we discovered that a new kind of order that can be characterised by Schumpeter’s idea of a biological clock in business cycle theory and resilience in regime switch through crisis. First, the linear model of the periodic solution in Samuelson’s model and the unit-root in econometrics are fragile or only marginally stable, since they are valid only on the border or edge between stable and unstable regime. Any disturbance in parameter space will drive the cycle or unit-root solution into a damped or explosive regime. But a chaos regime with multi-frequencies could exist in a stable regime with finite areas in the parameter space (see Figure 2.2). Clearly, the PO (periodic oscillation) state in Samuelson’s linear model is fragile since the PO regime is located on the edge between the BO and EO regimes. In contrast, CP and CH (chaos) states are resilient within finite zones in the parameter space. CP and CH modes are viable when parameter changes within their dynamical zones. Multi-regimes of market and phase transition during crisis How can the resilience of the financial market in enduring recurrent crisis be understood? We found multi-regimes in the financial market. The calm regime and the turbulent regime can be identified from the financial indexes where a phase transition occurred during the financial crisis (Tang and Chen, 2015). We determined that the master equation in statistical mechanics is capable of understanding both calm and turbulent markets in finance (Tang and Chen, 2015). In nonlinear stochastic dynamics, we found out that the population model of the birth–death process is persistent in time, while the representative model of random walk and Brownian motion is either damping or explosive in time. The transition probability in different periods can be seen in Figure 2.3. The horizontal axis is the price level of the S&P 500 daily index. The vertical axis is the transition probability at varying price level. The data source is the S&P 500 daily close prices. From Figure 2.3, the upper curve can be explained by the “strength” with positive trading strategy, and the lower curve the strength with negative trading strategy. Intuitively, net price movements result from the power balance between the

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0.15

Figure 2.2 (Continued).

“Bull camp” and the “Bear camp.” There is a remarkable difference between Period I (1950–1980) and Period II (1980–2010). Figure 2.3a is smoother than Figure 2.3b. The significant non-linearity in Figure 2.3b is a visible sign of a turbulent market that may produce financial crisis. Clearly, the liberalisation policy in Period II is closely related to the 2008 financial crisis in the sense that deregulation stimulated excess speculation in the financial market. We can solve the master equation of the birth–death process and determine the break point of the distribution probability. Our numerical solution indicates that the market break-down occurs on 25 September 2008, when the Office of Thrift Supervision (OTS) seized Washington Mutual. This event was the peak of chain events preceding the 2008 financial crisis. The stock market went to panic from 26 September 2008 on. Our result is compatible with the historical timeline. Empirical patterns and statistical mechanics in econophysics A new wave of applied physics in economics created a new field of econophysics (Mantegna and Stanley, 2000). An early case of economics studied by physicists was the St. Petersburg paradox in decision theory in economics (Bernoulli, 1738,

The transition probability of S&P500 index (1950−1980)

0.8

W+

0.6

−W−

Transition probability

0.4

0.2

0

−0.2

−0.4

−0.6

20

40

60 80 100 S&P500 index (daily close)

120

140

The transition probability of S&P500 index (1981−2010)

8

W

+

6

−W

−

Transition probability

4

2

0

−2

−4

−6

−8

250

500

750 1000 S&P500 index (daily close)

1250

1500

Figure 2.3 Transition probability for (a) calm (1950–1980) and (b) turbulent (1980–2010) market regimes.

Complexity science to complexity economics  33 1954). Another example is game theory (Morgenstern and Von Neumann, 1948). The main discovery in econophysics was the empirical evidence of power law in a wide range of economic data (West, 2017). New techniques in studying economics and finance are introduced, such as random matrix (Plerou et al., 2002), logperiodic power law singularity (Sornette, 2003) and economic complexity index (Hausmann and Hidalgo, 2012). Unsolved issues in statistical mechanics: social temperature vs. social interactions It is too early now to evaluate numerous findings from econophysics, since the fundamental differences between economics and physics have yet to be determined. For example, the Ising model of ferromagnetism has been applied in social psychology and social dynamics (Weidlich, 1972, 2006). The problem is that the social temperature was a concept for equilibrium systems with conservation of energy. The social system is a non-equilibrium open system without conservation of energy. There is an interesting case that difference in “income temperature” can be defined by exponential distribution of US and UK income distribution (Yakovenko, 2009). The author suggested that a thermal machine could operate between a high income-temperature country like the US and a low income-temperature country such as China. The perpetual trade deficit of the US could be generated by a thermodynamic machine in non-equilibrium economies. The problem is that international trade is more complex than physics. China had a persistent trade deficit with Japan but a big surplus with the US, while both US and Japan are developed countries. Income temperature alone may not explain opposite patterns in trade imbalance between high- and low-income countries. Technology gap, product chain and other factors may also play roles in trade imbalance. Perhaps physicists could define a vector temperature with several components to characterise disequilibrium not just in income, but also in resource, technology, finance and military power in global competition. We did try an alternative approach in studying non-equilibrium statistical mechanics. To apply the master equation approach in statistical mechanics in social systems, we adopted an alternative measure of temperature by intensity of social interaction. We found a U-shaped distribution that is similar to the polar distribution in the Ising model of social psychology (Chen, 1991). See Figures 2.4 and 2.5. Power law, fat-tail, black swan and edge of chaos? Another problem is the implication of fat-tail distribution and power law in finance, since it implies huge instability and uncertainty. In the history of science, quantum biology was a tremendous success due to the discovery of generic code from molecule biology. We need a similar theory to explain why power law observed in fluid dynamics can be allied to biology and

(a)

Fst (q) k–u h–0

(b)

Fst (q)

(c)

Fst (q)

k–2 h–0

k – 2.5 h–0

Figure 2.4 The steady state of probability distribution function in the Ising model of collective behaviour with h = 0 (without central propaganda field). (a) Uni-modular distribution with low social stress (k = 0). Moderate stable behaviour with weak interaction and high social temperature. (b) Marginal distribution at the phase transition with medium social stress (k = 2). Behavioural phase transition occurs between stable and unstable society induced by collective behaviour. (c) Bimodular distribution with high social stress (k = 2.5). The society splits into two opposing groups under low social temperature and strong social interactions in unstable society. Fst (q)

b>a b a (denoted by solid line). It occurs when social pressure through mutual communication is stronger than independent judgment.

Complexity science to complexity economics  35 economics. The universe seems to have a multi-level structure. Physicists should be careful, since economic complexity could be more complex than existing physics models. The principle of large numbers and meso foundation of macro fluctuations Structure analysis plays an important role in physics and biology. However, structure is missing in macroeconomics. The so-called microfoundations theory simply asserts that macro dynamics should follow the same behaviour in microeconomics without intermediate structure. We found a three-level structure (micro–meso– macro) in business cycle theory that is revealed by Schrödinger’s principle of large numbers (Schrödinger, 1948; Chen, 2002) One fundamental issue in macro and finance theory is the origin of business cycles and the cause of the Great Depression. Lucas claimed that business cycles or even the Great Depression could be explained by workers’ choices between work and leisure, which is called the microfoundations theory of (macro) business cycles. Schrödinger proposed a simple math equation that reveals the relation between the number of microelements and the degree of aggregate fluctuations. We define the relative deviation (RD) as the ratio of the standard deviation to its mean when the underlying variable has only positive value, such as price and volume. RD =

STD( S N )  N

(2.1)

Here, RD stands for relative deviation for positive variable; STD is standard deviation, which is the square root of the variance of a variable S with N elements: SN =X1 +X 2 + …. +X N The idea is quite simple. The more elements number N at the micro level, the less will be the aggregate fluctuation at the macro level, since independent fluctuations at the micro level would largely cancel each other out. We call this relation the principle of large numbers. We extend this relation from a static system to the population dynamics of the birth–death process. We first calculate RD from an economic index through the HP filter. Then, we estimate the effective micro number N. The result is given in Table 2.1, which can be used for diagnosing financial crisis. In comparison, the number of households, corporations and public companies and the potential RD generated by them are given in Table 2.2. From Tables 2.1 and 2.2, household fluctuations may contribute only about 5% of fluctuations in real gross domestic product (GDP) and less than 1% in real investment; and small firms can contribute 50% of fluctuations in real GDP or 8% in real investment. In contrast, public companies can generate about 60% of

36  Ping Chen Table 2.1  Relative deviation (RD) and effective number (N) for macro and finance indexes. Item

RD (%)

N

Real personal consumption Real GDP Real private investment Dow Jones Industrial (1928–2009) S&P 500 Index (1947–2009) NASDAQ (1971–2009) Japan–US exchange rate (1971–2009) US–Euro exchange rate (1999–2009) Texas crude oil price (1978–2008)

0.15 0.2 1.2 1.4 1.6 2.0 6.1 4.9 5.3

800,000 500,000 10,000 9,000 5,000 3,000 300 400 400

Table 2.2  Numbers of households and firms in US (1980). Micro-agents

Households

Corporations*

Public companies

N

80,700,000

2,900,000

20,000

RD (%)

0.01

0.1

0.7

* Here, we count only those corporations with more than $100,000 in assets.

aggregate fluctuations in real investment. Clearly, there are very weak “microfoundations” but strong evidence of a “meso foundation” in macroeconomic fluctuations. In other words, large macro fluctuations in macro and finance can only generated by fluctuations at the meso (finance) level, not at the micro level from households or small firms. Extremely large fluctuations in the commodity and currency market can only be caused by financial oligarchs. This is the root of the 2008 financial crisis. Our approach finds strong evidence of meso (finance and industrial organisation) structure from macro and finance indexes. Our three-level system of micro– meso–macro is better than the two-level system of micro and macro in Keynesian economics in studies of structural foundation of business cycles and crisis. Conflicting perceptions of economic information Economists and physicists have different understandings about the nature and sources of information. For physicists, any meaningful information is associated with deterministic signals such as waves and codes with clear patterns. Shannon’s information entropy, based on probability theory, is a measure of ignorance rather than knowledge (Shannon, 1948). That is why Schrödinger used the term “negative entropy” to characterise information as decreasing ignorance (Schrödinger, 1948).

Complexity science to complexity economics  37 In contrast, economists used the term “information” in four different ways. In microeconomics, the concept of “complete information” in a “perfect market” implies a Laplace world of Newtonian determinism. It is only possible in a closed system like a chess game, where any innovation and uncertainty is ruled out. No entry or exit of new products, new technologies or new players, plus no rule of changes, could occur in the idealised market. In growth theory and macroeconomics, random variables are treated as driven force of business cycles in the form of “innovation” or monetary shocks in monetary theory. From the methodological perspective, the Solow residual in growth accounting is simply a black box with a magic name of “the total factor productivity.” No any theoretical model in physics and biology put random noise as the driving force of growth and development. According to thermodynamics, random movement is the form of heat or disorganised energy. If living order could emerge from heat, it would be a perpetual motion machine that is impossible in physics world. Brownian motion plays a central role in finance theory for purely descriptive convenience. There is no logical link between basic variables in financial market and the erratic movements of stock price. The financial market used to treat random shock as rumours rather than information behind price fluctuations. Only RBC economists tried to separate noise and cycles along a nonlinear trend (Hodrick and Prescott, 1997). Their approach reveals the Copernicus problem in selecting observation reference systems in macro and finance. If economists and econometricians had basic knowledge in information theory and signal processing technology, economic analysis and theory would be more pragmatic for the real world. We need to further discuss the philosophical background of conflicting information theories in economics. Information costs and bounded rationality It is known in quantum mechanics that any information collection and transmission is associated with finite energy. There is no chance in physics world that complete information can be obtained without energy costs. The idealised world of a perfect market with complete information and rational expectation in economics is impossible in the physics world, since dealing with complete information in a global market needs a super computer with infinite speed plus infinite memory, which will consume infinite energy. Any realistic human being or artificial intelligence could only have bounded rationality (Simon, 1984). This is a common sense among computer scientists and electrical engineers. Unfortunately, economic thought experiments like rational expectations and Friedman spirits simply assumed perfect rationality could operate without energy dissipation communication. The Friedman spirits in market arbitrage and the Maxwell demon fighting market uncertainty A thought experiment for basic belief in a stable and efficient market was created by Friedman in discussing the self-stability of a flexible exchange rate regime. The central idea could be characterised by Friedman spirits, which were rational

38  Ping Chen arbitrageurs capable of driving out irrational (de-stabilising) speculators (Friedman, 1953b). This is the main argument for the efficient-market hypothesis in macro and finance dynamical theory. Friedman spirits behave much like the Maxwell demon in equilibrium thermodynamics (Chen, 2008). The Maxwell demon is an imaginary gatekeeper trying to create a non-equilibrium order from an equilibrium state by operating a frictionless sliding door between two chambers that are filled with moving molecules (Maxwell, 1871). Maxwell assumed that his demon had perfect information about the speed and position of all molecules such that he could allow only a fast molecule into a designated chamber by opening or closing the mass-less valve in perfect timing. In economic language, under the condition of perfect dynamic information, the Maxwell demon could create a temperature difference without doing work, though that outcome is contrary to the second law of thermodynamics. The meaning of perfect information is also essential for a Coasian world with zero information costs (we will return to this issue in the next section). Friedman spirits face a similar problem to that of the Maxwell demon but with an opposite task. To eliminate any market instability, Friedman spirits had two problems in achieving their goal. First, resource limitation is a severe barrier in defending speculative winds with positive feedback strategy, i.e. the recurrent market fads by following the crowd (Shleifer and Summers, 1990). For example, foreign reserves in any central bank are limited compared to speculative capital in the global financial market. Second, the uncertainty principle and dynamic complexity set fundamental limits in duplicating disequilibrium portfolio in a competitive market. Friedman implicitly assumed that a winner’s imitator could quickly drive down profit margins to zero. This strategy could work only if the winning pattern was replicable. There are two fundamental difficulties in doing so. One problem is timing uncertainty in the frequency domain. The strategy of buying low and selling high works if the turning points of a speculative wave are predictable with small error. This possibility is limited by the uncertainty principle in terms of the trade-off between time resolution and frequency resolution (Qian and Chen, 1996). Another barrier is complexity in the time domain. The sources of complexity in time series analysis include imperfect information (finite data with noise and time delays), information ambivalence (conflicting news and distorted information), unpredictable events (financial crisis and changing structure) and limited predictability (caused by deterministic chaos or wavelets). Information ambiguity is not only associated with bounded rationality but also rooted in dynamic complexity (Simon, 1984; Chen, 2006). In short, the Friedman spirit cannot ensure an efficient market. Unpredictability and ignorance do not lead to market efficiency. Mixed economies and cooperative partnership in facing information uncertainty and changing society In this perspective of bounded rationality, any market decision is a learning process with trial and error. Neither entrepreneurs nor government officials could make

Complexity science to complexity economics  39 optimal solutions in resource allocation. Therefore, market failures with invisible hand and government failures with visible hand are inevitable in adapting to changing technology and environment. Private ownership and incentive mechanisms alone are not sufficient to deal with natural disaster, environmental crisis and social instability when market uncertainty and coordination costs are too large to be borne by individuals, firms and small communities. Institutional economics lacks theory in dealing with mixed economies, including public, private, non-profit organisations and international cooperation. Clearly, market forces alone are not capable of solving long-term problems, such as infrastructure investment, economic development and poverty. Economics should be more inclusive in addressing contemporary issues in the developing and developed world. Equilibrium approach cannot understand the failure of the Washington consensus in Latin America and the transition depression caused by the shock therapy in Eastern Europe and the Soviet Union (Williamson, 1990). Mainstream economists behave like a witch doctor who treats different diseases with a standard medicine called equilibrium policies, such as privatisation, liberalisation, and macro stabilisation, regardless of economic complexity and political risk in far from equilibrium social conditions (Stiglitz, 2010). In contrast, developed countries never apply the similar equilibrium policies in dealing with the 2008 Great Recession in their own countries. Perpetual motion machines in equilibrium economics There are three types of perpetual motion machine widely used in mainstream economics that violate basic laws in thermodynamics. General equilibrium mechanism without energy costs Both the Walrasian model and Arrow–Debreu model of general equilibrium are static models with many variables without time trajectory and interaction speed in economic dynamics. They imply an infinite speed in price adjustment. If the general equilibrium model worked in real economies, this would be the perpetual motion machine of the first type, since instantaneous interaction means infinite speed of communication without dissipation of energy. In historical experiment, the shock therapy in transition economies in Eastern Europe resulted with quite different situations. The time-period of reaching stabilisation in Eastern European countries varied greatly from seven years in Poland to more than 20 years in Ukraine. This diversity can be explained by different political and historical conditions in specific countries (Chen, 2006). Frisch model and perpetual motion machine in econometrics The Frisch model of noise-driven cycles is a perpetual motion machine of the second type, which is a thermal machine with only one heat source. We knew from the second law of thermodynamics that the Carnot heat engine can transfer heat from a high temperature into work at the cost of waste heat released at low temperature. But Frisch

40  Ping Chen imagined a heat engine could do work (keeping the pendulum oscillating) with only one heat source (Frisch, 1933). Noise or external shocks became the very foundation of econometrics, finance and the DSGE model in macro dynamics. Even macro growth is driven by noise with the magic name of innovations. We found that the Frisch model was a fake model discredited by physicists before and after him (Uhlenbeck and Ornstein, 1930; Wang and Uhlenbeck, 1945). In fact, Frisch never formerly published his promised paper in Econometrica and did not even mention his prize-winning model in his Nobel Lecture. The strange success of the Frisch model in economics is a historical puzzle in the history of Nobel economics in which an alchemy model was treated as a science (Chen, 1998, 2010, 2016). The Coasian world with zero-transaction costs, an equilibrium utopia with one-way evolution The Coase theory of transaction costs had an implicit assumption that market competition would drive down transaction costs to zero, a utopian market without conflicts and government regulations (Coase, 1988). Coase assumed that the bargaining mechanism could solve all conflicting issues in social exchange without the need for government regulation or violence. It sounds like a perpetual motion machine of the third kind. Darwin would be surprised to see a strange world in which wolf and lamb could peacefully coexist and social animals all disappear. The existing space in the living world could be divided and maintained without conflicts under free exchange without energy costs. The Coase world of zero-transaction cost is a utopian world without friction. The concept of transaction costs is equivalent to the physics concept of heat or entropy in thermodynamics, when organised energy is transferred into disorganised heat by overcoming friction. There is a visible trend of increasing energy dissipation in industrialisation that is the root cause of global warming. If Coase were right, then market forces alone would solve the problem of global warming. So far, we do not have any convincing evidence. First, the Coasian world of zero-transaction costs cannot exist in the real world since it violates several basic laws in physics. The frictionless world is realistic for planetary motion in space but is not possible in the living world, since living organisation is maintained by a dissipative structure with constant matter, energy and information flow (Prigogine, 1980; Chen, 2007). The analogy between a frictionless world in physics and the Coasian world with zero-transaction costs is wrong, since zero information cost is impossible for information collection in a living world according to the uncertainty principle in quantum mechanics (Brillouin, 1962). Any information collection or transmission requires some form of energy. Coase believed that a frictionless world could constantly move without energy input. He did not even understand Newton’s law: both acceleration and deceleration are driven by forces that consume energy. How could a train keep running without stopping and restarting? The Coasian world is another example of a perpetual motion machine in equilibrium economics (Chen, 2007).

Complexity science to complexity economics  41 Second, economists have observed a trend of increasing transaction costs in modern society. For example, transaction costs in US GDP increased from about 25% in 1870 to more than 50% in 1970 (Wallis and North, 1986). The core of transaction costs is marketing costs and information costs in division of labour. Coase made a hidden assumption that market competition would drive down transaction costs. He seems to ignore counter-business strategies, such as marketing strategy for creating value and expanding market share, at the cost of increasing transaction costs. Technological progress may reduce the unit transportation cost and communication cost, but aggregate transaction costs as a whole may increase when network complexity and innovation uncertainty grow with technology progress. Third, the most controversial assertion in the Coase Theorem is that any social conflicts could be resolved by bilateral bargaining without third party (law, government or civic society) mediation (Coase, 1960, 1988). His argument was based on the symmetry between polluter and victim and, more generally, between consumption and investment (Coase, 1960, 1988; Cheung, 1998). If the Coase Theorem were valid, there would be no power, no conflicts, no war, no government and no regulations. This may be true for a primitive society without private property and wealth accumulation but is not true for a competitive but unequal market economy. Coase made the claim of observing the real world. After careful examination, we found out that no single case studied by Coase could support his claim. Bilateral bargaining under a specific context could not converge to an (universal) optimal state when asymmetry exists in the form of non-convexity, such as scale economy in a cattle ranch, upward-demand for pollution compensation and social dissent for commercial bribery. Coase argued that price theory could be applied to the externality problem if the demand curve is always negatively sloped (Coase, 1988). Coase did not understand why the market breaks down. History told a much simpler story. If people fight for existence, there is no room left for Pareto optimum.

Complexity study and new economic thinking Until now, studies on economic complexity only made a limited impact on mainstream economic thinking, but a paradigm change is forthcoming. Increasing returns and path dependence in economy The most visible impact was the existence of path dependence and increasing returns to scale in economy, such as the notable example of Silicon Valley (David, 1985; Arthur, 1994). The question is whether rigid increasing returns in the AK model can be integrated into the optimisation approach in neoclassical economics (Krugman, 1980; Romer, 1986); or we need an alternative framework to address the larger picture of technology evolution. This issue can be solved with dynamic model with varying returns to scale.

42  Ping Chen Dynamic returns to scale and metabolic growth theory Conflicting predictions from neoclassical growth theories resulted from static returns to scale. The Solow model of exogenous growth predicted a convergence trend in economic growth based on the assumption of constant returns to scale (1957), while the Romer model of endogenous growth claimed a divergence trend based on increasing returns to scale in knowledge accumulation (Arrow, 1962; Romer, 1986). In history, observed patterns of the rise and fall of great nations in history are more complex than the predictions of neoclassical growth models. However, learning by doing and knowledge accumulation ignore the interruptive nature of technology advancement. We developed a theory of metabolic growth (Chen, 2014). We introduce dynamic returns to scale based on the logistic model in ecology. An emerging technology can be described by a S-shaped logistic curve with resource limits in ecology. A new technology competition with higher resource limits would drive old wavelets into decline or would die out. The rise and fall of technologies and industries can be seen in Figure 2.6. Creative destruction of new technology and life cycle of logistic wavelets Creative destruction can be understood with knowledge metabolism (Schumpeter, 1950). The wavelet representation can be applied in analysing the life cycle of products, firms, technologies and nations. The time scale of the logistic wavelet varies between product life cycles from several months to Kondratieff long waves Logistic competition

2.5

Population

2 1.5 1 0.5 0

0

100

200

300

400

500

Time

Figure 2.6 Metabolic growth characterised by technology competition with logistic resource constraint. The old technology declines when new technology emerges. The output envelope is the sum of the output of all technologies. The units here are arbitrary in computational simulation.

Complexity science to complexity economics  43 over several decades. The wavelet is a better model than noise and cycles in economic dynamics, since it provides a unified theory in micro, meso, macro and clio economics. We may divide the logistic wavelet into four stages: infant, young, adult and old stage. Government policy has to adapt to changing market in these stages, just like the relation between parents and growing kids. Similarly, institutional arrangements must adapt to different stages of technology life cycles. Both market and governments have to learn through trial and error in order to adapt to changing technology. The co-evolution of technology, environment and regulation in complex economic systems is more realistic than the utopian picture of Pareto efficiency, since we should consider the balance among long-term ecological sustainability, medium-term social stability and short-term economic efficiency. Rethinking Adam Smith and returning to political economy The contemporary issues of global warming and persistent poverty revived the original thoughts of classical economists from Smith and Malthus to Darwin and Marx (Piketty, 2014). People realised that important issues in political economy could not be marginalised by neoclassical economics. We find a fundamental contradiction existed in Adam Smith’s theory of the wealth of nations (Smith, 1776). Bifurcation between classical and neoclassical economics We realised that classical economics and neoclassical economics conflict in economic perspectives. First, classical economics is nonlinear in nature, since economics was constrained by resource limits. Smith’s theorem clearly stated that “the division of labour is limited by the extent of market” (Smith, 1776; Stigler, 1951). Malthus further emphasised the resource constraint on population growth (Malthus, 1798) that inspired evolution theory in biology (Darwin, 1859). In this regard, economic dynamics should build on theoretical ecology with the resource limits that are the very foundation of ecological economics. However, linear models in neoclassical economics assume unlimited resources, so that “economic man” could be “selfish” and “greedy” with unlimited want in material consumption. The basic assumptions of human nature are simply against basic knowledge of evolutionary biology and evolutionary psychology. That is why economic chaos could not exist in neoclassical economics, but is compatible with classical economics with nonlinear constraints in market extent and natural resources. Second, political economy is the essence of classical economics, as when Smith quoted Hobbs that “wealth is power” (Smith, 1776), since resource competition can be won by economic, political and military powers. In contrast, neoclassical economics abstracts away the political, cultural and social background of economic decisions and institutions by value-neutral assumptions of economic behaviour. A notable example is the trade war and colonial war that are inherited in market-share competition with increasing returns to scale, while the general

44  Ping Chen equilibrium framework in microeconomics (Arrow and Debreu, 1954) and transaction cost theory (Coase, 1988) simply rule out multi-equilibrium and conflicts in economic theory. Now we know the existence of increasing returns to scale will not have a unique stable equilibrium. Clearly, the problem with neoclassical economics is not using too much math but using improper math, since the linear and optimisation approach in neoclassical economics is not capable in dealing with economic evolution with resource constrains. We apply basic tools in complex systems and non-equilibrium physics to analyse basic theories in neoclassical economics. We made fundamental progress in developing a new paradigm for economic theory. We could reformulate economic theory based on more a general math framework in nonlinear dynamics and non-equilibrium physics (Chen, 2010, 2016). Complexity in division of labour and perplexity in trade imbalance Economic complexity sheds new light on understanding fundamental issues in Adam Smith’s theory of the “wealth of nations” (Smith, 1776), which was born with complexity and fantasy. There were three perplexities caused by economic complexity. First, the market-share competition in division of labour is the destabilising cause of market stability, since increasing efficiency in production implies increasing risk in product marketing when production capacity could not be fully utilised by the export market. This is the root of trade war and government subsidies for stabilising commodity price. For example, the US has had persistent trade deficits since the 1970s. Flexible exchange and interest rates could not balance international trade. The structural disequilibrium in international economies could not be explained by equilibrium theory. Second, Smith’s theory of the “invisible hand” was based on the symmetry assumption in international trade. Smith naively believed that the return ship would bring commodities back to the export country to balance the trade, but he had no reason to believe the two-way trade would have equal value. In history, Britain had a persistent trade deficit to China for 170 years. Britain used the visible hand to balance the tea-trade with China by launching the Opium War and tea plantations in India, plus the Indian railway subsidised by British colonial government (Pomeranz and Topik, 2006). The current US trade war under President Trump is a good lesson of the limit of the invisible hand in international trade. We need study the real cause of market instability in complex economic systems. Numerous asymmetries exist in economic complexity that break down general equilibrium in the market economy. For example, income and wealth disparity between import and export countries play important roles in trade imbalance. The US could maintain a persistent trade deficit because the dollar has monetary power as a reserve currency. Supply and demand forces are not symmetric because life cycle asymmetry is significant in business cycle, since production cycles are much longer than consumption cycles. Uneven technology creates more disparity in economic development. The general equilibrium theory is an economic utopia with

Complexity science to complexity economics  45 symmetric demand and supply within an equal society. It could not address contemporary issues of global warming, ecological crisis and financial crisis. The Smith theorem and the Smith dilemma in division of labour In this sense, the Smith theorem is compatible with Malthus and Darwin with resource limitation of the market, while the Smith doctrine of self-stabilised market by invisible hand is incompatible with scale economy that is nonlinear in nature with complexity and diversity. The nonlinear model of ecological system provides a better alternative than the AK model with unlimited growth. We discovered that the rigid AK model with constant returns to scale could not explain historical patterns of economic growth. The Solow model of exogenous growth predicted a convergent trend under constant returns to scale (1956), while the Romer model of endogenous growth implied a divergent trend under increasing returns of scale (1986). In order to explain observed patterns of rise and fall in technologies, a better model is dynamic returns of scale in metabolic growth with ecological constraints (Chen, 1987, 2014). We proposed the generalised Smith theorem in complex economic systems. The division of labour is limited by three factors, including market extent (or resource limit), resource diversity (number of resources) and environmental fluctuations. There is a trade-off between complexity and stability. There may be a two-way evolution (or co-evolution) process towards complexity or simplicity in division of labour under nonlinear evolutionary dynamics. When social stability is high and new resources keep coming, the system may develop into a complex system, like the Industrial Revolution in the past. However, when social turmoil is high or resources are used up due to overpopulation, a complex system may break down into a simple system, such as the collapse of the Roman Empire in the Middle Ages. This is the theoretical foundation for understanding diversity of civilisations and cultures in history. In this perspective, metabolic growth theory is closer to evolutionary economics, institutional economics and anthropology than to the equilibrium perspective in neoclassical economics. Return to political economy: from Smith’s question to Hobbs’s answer We realised that Smith raised the question about the “wealth of nations” but failed to provide an answer. Instead, Smith quoted Hobbs that “wealth is power.” This answer falls into the tradition of political economy that divides classical economics and neoclassical economics. The latter tries to define economics as a value-free science without background in history, culture and politics. The generalised Smith theorem and trade-off between stability and diversity For complex ecological systems with many species and technologies, increasing the number of technologies will reduce system stability (May, 1974). There is a

46  Ping Chen trade-off between diversity and stability. We propose a generalised Smith theorem (Chen, 2010, 2014). The division of labour is limited by three factors, including the market extent (resource limit), biodiversity (number of resources), and environmental fluctuations (social stability). Neoclassical growth models have a one-way evolution to convergence or divergence under linear stochastic dynamics. In complex ecological systems, there may be a two-way evolution (or co-evolution) process towards complexity or simplicity in division of labour under nonlinear evolutionary dynamics. When social stability is high and new resources keep coming, the system may develop into a complex system, such as the case of Industrial Revolution. When social turmoil is high or resources are used up due to over population, a complex system may break down into a simple system, such as the collapse of the Roman Empire in the Middle Ages. The interactions among population, environment and technology leads to diversified patterns in market mechanism and social evolution.

Concluding remarks The 2008 financial crisis was a wake-up call to economists that mainstream economics had failed to understand the cause of business cycles and remedy for economic crisis. The World Economics Association was created to advance more pluralistic and inclusive economics (WEA, 2011). There are several issues in economic methodology and future directions that are related to complexity economics. The role of math in economic thinking There has been strong criticism that mainstream economics used too much math that was too far from reality. There are three lines of thinking about the role of math in economics. The first is that the degree of economic math justifies the image of economic science. Therefore, using more math is an implicit criteria in selecting submitted papers in the US. The second group took the opposite argument that human behaviour is too complex and math models are too simple. Therefore, economic ideas could not be described by math language. This is the position of Austrian school. There is a third line of reasoning. We think that math is a necessary tool for analysing large data from businesses, governments and researchers. This is especially true when big data open new opportunities in the information era. A useful graph or table with relevant economic data can tell a much clear picture than a thousand words. The real issue is how to find a proper math tool to address meaningful economic questions. If your question is based on short-term price movements, then a simple model of demand and supply may provide some clue. However, if your question is about medium-term investment and long-term development, or persistent problems of poverty and war, the linear model of general equilibrium has little answer except to avoid political substance. In addressing fundamental issues in

Complexity science to complexity economics  47 economics, nonlinear and non-equilibrium models are more powerful in diagnosing causes of instability and comparing different solutions. However, economists should be aware of the implications or limitations embedded in math assumptions. For example, the Brownian motion and the power law are stochastic models in nature. Their difference lies in the probability of large deviations in real economy. However, they have a common implication that governments could do nothing to stabilise the market. That is why liberalisation policy could be justified by math models like Levy distribution or power law, but be rejected by historical experiments like the Great Depression and the transition depression in Eastern Europe. In this regard, history is a better judge than math for testing competing economic schools. Physics and biology foundation of economic theory Another criticism of mainstream economics is that neoclassical economics looks more like physics rather than the humanities or social sciences. They argue that history, psychology and anthropology are more relevant to economic studies. This criticism has some merits since we do acknowledge that history, psychology and anthropology reveal important factors in economic behaviour and social changes. Future economic theory should integrate with other fields from history and the social sciences. However, many scholars do not realise there are two kinds of physics: equilibrium physics in a closed system and non-equilibrium physics in an open system. Their behaviour is fundamentally different. The optimisation approach in neoclassical economics did imitate Hamiltonian mechanics in a closed system, which requires conservation of energy without friction. Its scope is smaller than Newtonian mechanics, which permits nonlinear forces and friction. Therefore, deterministic chaos can be studied in classical mechanics, but not in equilibrium economics, which excludes nonlinear mechanisms and friction. In this regard, classical mechanics is a true science for the real world, because friction can be ignored in studying planet motion. In contrast, no realistic economy in modern society can be described by an equilibrium state without growth trend and market fluctuations. The so-called efficient market in equilibrium economics could not find any empirical evidence. Even the most developed countries such as the U.S. did have recurrent crisis. So many conflicts and wars occurred after World War II. The transaction costs in social organisation and geopolitics are so high; how can we believe that market exchange or invisible hands could solve the difficult coordination problem in international division of labour? Marshall realised that economics is closer to biology than mechanics (Marshall, 1920). However, the linear model of demand and supply is only a static metaphor rather than a dynamic model in biology or ecology. Nonlinear dynamics offer a better model of nonlinear oscillator and wavelets to characterise biological clock and life cycles, which were observed by economic historians like Schumpeter and NBER business cycle committee. Hayek’s idea of spontaneous order can be better described by self-organisation, emergence and phase transition in nonlinear and

48  Ping Chen non-equilibrium models in nonlinear physics and theoretical ecology. In this regard, mainstream economics needs more proper and advanced math tools. Econometrics is far behind in math development, since it is confined by difference equations in discrete time, which fell behind Newton by using differential equations in continuous-time! We should set a new standard to judge competing economic theories. Any realistic theory in economics should be compatible with physics laws and biological evolution. Neoclassical models are mainly utopian models of real economies when they assume unlimited resources, costless information and infinite speed in equilibrium mechanisms. Economists should abandon some misleading concepts, such as complete information, rational expectations, zero-transaction costs, unlimited resources and general equilibrium without diversity and change, since these concepts violate basic laws in physics and biology. Certainly, neoclassical models are useful in teaching methodology, since a nonlinear curve can be approximated by a broken line with many segments of straight lines, and a non-equilibrium situation can be approximated by an uneven picture with local equilibrium states changing in time and space. In this perspective, current models in mainstream economics could serve as special cases for a general economics with a nonlinear mechanism and a non-equilibrium framework. Dialogue and complementation between complexity science and history The real difficulty in complexity science is finding simple patterns from complex reality. This is the challenge to systems theory and computer simulation, since the more complex the model system being constructed, the more uncertainty predicted by complexity simulation models. If anything were possible in computer simulation, practitioners would also feel puzzling. We must develop new selection rule for complexity research. There are several directions for future complexity studies. First, construct some simple indicator for characterising complex phenomena. Notable examples are correlation dimension in chaos dynamics and information complexity with vector components. We need better economic indicators than current measures of per capita GDP that distort real pictures of income inequality. Second, we need to identify major mechanisms behind economic non-linearity and non-equilibrium. Resource constraint is essential in not only growth theory but also utility function and behavioural preference. Human nature is social because an infant could not survive without assistance from parents and community. The rational man with unlimited greed could not survive human evolution. Both competition and cooperation play critical roles in human behaviour. How to understand the cooperation mechanism is an unsolved issue in economics. We already know that the invisible hand of the price system is not capable of coordinating the division of labour and international trade. Third, economists and complexity scientists should learn more from political scientists and historians since they are more realistic in dealing with contemporary

Complexity science to complexity economics  49 issues. The contemporary issue is coordination of nations rather than wealth of nations, since the wealth of powers created numerous conflicts and wars that threaten the existence of earth’s ecology and human society. Both nuclear weapons and financial derivatives are double-edged swords. They could open new resources or stabilise markets, but they may also destroy the whole earth or create financial crisis. Blind faith in the free market among mainstream economists has had to face contemporary issues, like global warming, ecological crisis, poverty and mass destruction in recurrent wars. In this aspect, I had tremendous admiration for my mentor, Ilya Prigogine, who was a genius physicist with a strong sense in history. He was born in 1917 during the Russian Revolution and his family went through two world wars in Europe. He told me that the equilibrium paradigm in physics could not be squared with the history of war and revolution. His non-equilibrium physics was originated from his experience in world history. I had similar experience like Ilya Prigogine. I was foreign by teachings of general equilibrium economics in American universities when I moved from China to the States in the 1980s. I found that mainstream economists care little problems in the real world. In contrast, I learn more realworld economics from history and anthropology. Complexity science mainly provides math tools in studying financial data. Emerging paradigm of a unifying theory in physics, biology and economics Einstein’s special relativity and general relativity set a role model for Keynes in developing a general theory in economics. Methodologically speaking, a general theory is capable of including previous theories as its special cases. Notable example is Newtonian mechanics can be approximated as the special case of Einstein’s theory of special relativity. Keynes believed that economists could do the same, by developing a general framework of disequilibrium economics that treats classical economics as a special case. This was Keynes’s original goal of his “general theory” (Keynes, 1936). Unfortunately, neoclassical synthesis and Post Keynesian economics went in the opposite direction (Hicks, 1937). Classical equilibrium economics is treated as the general framework in textbook economics; while Keynesian disequilibrium is presented as special cases, such as liquidity trap and wage rigidity. Neoclassical economics failed to develop a unified theory that included normal business cycles as well as crisis and war. Keynesian economics was born in wartime economics, but neoclassical economics refuses to face reality. The basic demand–supply choice in Samuelson’s textbook was between butter and cannon in the 1950s (Samuelson, 1955), which became work and leisure in microeconomics and growth and debt in Reagan economics. We are developing a general theory, one compatible with fundamental laws in physics, ecology, biology, psychology and anthropology and applicable in economics and management science (Chen, 2010). Its main building block is the logistic wavelet, which can be widely observed from the life cycle in biology,

50  Ping Chen ecology and economy (Chen, 2014). Evolutionary perspective, as developed by evolutionary economics, economic historians and political economy, can be integrated into complexity economics (Dopfer, 2005). Studies in behavioural economics and psychology are useful guides in modelling economic complexity (Arthur, 2015). New tools in nonlinear dynamics, time-frequency spectra and collective models of the birth–death process can be applied in diagnosis of financial crises and as advance warning in market regulation (Tang and Chen, 2014). History will tell whether complexity economics can go further than equilibrium economics in dealing with contemporary economic issues in the modern world.

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3

Categorical economic theory Fernando Tohmé and Marcelo Auday

Introduction Economics has been famously defined as the discipline that studies “the science which studies human behaviour as a relationship between ends and scarce means which have alternative uses” (Robbins, 1932). While this is an accurate characterisation, it fails to capture aspects that are currently deemed relevant for the description of economic phenomena, such as the role of information and knowledge in exchanges among individuals. In that sense, an alternative definition could be that economics is the study of the interactions among intentional agents (Crespo and Tohmé, 2017). This extends the reach of the discipline to cover new fields, for instance multi-agent systems (Shoham and Leyton-Brown, 2009), the components of Industry 4.0 systems (Platzer, 2018) and perhaps even ecosystems (Dini, 2008). Be that as it may, the mathematical formalism required by this redefinition has to cover the same ground as the traditional mathematics of economics but also go beyond that. In particular, this definition asks for the ability of representing more faithfully the notion of interaction. We claim that the mathematical approach able to accomplish this goal is category theory, which has become a fundamental tool for the identification of commonalities among different and sometimes disparate areas of mathematics. In this sense, we can notice that the categorical approach has taken over mathematics in the last six decades. Starting with Grothendieck’s successful reconstruction of algebraic geometry and followed by the advances in Langland’s program, the trend towards the unification through abstraction of large swaths of mathematics has made the usefulness of this flexible yet rigorous language more evident than ever to mathematicians. Furthermore, given the increasing influence of computer science on the representation of real-world phenomena, category theory has impacted the expression of scientific theories in many fields of inquiry (Marquis, 2015). Economics has been surprisingly slow in adopting this new framework, even more considering the widespread influence of Paul Samuelson’s claim that mathematics is for economics just a language (Samuelson, 1952: 56). If so, at the very least for its pure notational value, category theory should have been more widely applied in the discipline. Unlike the traditional foundations, which are much more concerned with the nature of mathematical objects, category theory focuses on the

Categorical economic theory  57 relations among them. Intuitively, while set-theoretical foundations define functions in terms of their domain and range sets, category theory takes functions by themselves as the elements of interest. More precisely, any category can be described by the morphisms between its objects. While this could seem a mere re-writing of the traditional form of doing mathematics, its real strength arises when different categories are connected through functors that act over both the objects and the morphisms between them. Moreover, this way of relating mathematical constructions can be pursued further, establishing other kinds of relations. In this chapter, we will present the main tenets of category theory, trying to convey why we think it provides the right language to talk about the interactions among intentional agents. We will also review the scarce number of applications of category theory (and closely related fields) to economics. Finally, we will discuss some problems in economics amenable to representation in categorytheoretical terms.

Category theory in the literature on economic theory As noted, the relevance of category theory seems to have been lost to economic theorists, more favourable to adopt “Bourbakian” formalisms. Nevertheless, we have to point out that a subtle influence exerted by category theory can be found in the style of proofs, particularly of fixed-point theorems and other algebraic– topological results, which economists use in their existence and robustness results (Vassilakis, 1991; Mc Lennan, 2018). More specific applications include the treatment of decision-making under uncertainty (de Oliveira, 2018) and the characterisation of subgame perfect equilibria in infinite games (Abramsky and Winschel, 2017). An area in which mathematical methods derived after WWII (like homology theory) have been fruitful is social choice theory (Chichilnisky, 1980; Eckmann, 2004; Weinberger, 2004; Abramsky, 2014). Other, isolated applications of category theory in the field are to the analysis of risk (Adachi, 2014) and the characterisation of type spaces (Moss and Viglizzo, 2004). Another interesting application was to the derivation of preferences over strategies up from preferences over outcomes (Rozen and Zhitomirski, 2006). Categorical presentations of games have also been developed (Wiweger, 1982; Jimenez, 2014). Of particular interest is the series of work on compositionality of games, developed in Oxford by Jules Hedge (Ghani et al., 2018). We will present an alternative take on the subject. Category theory and its uses Category theory provides the framework without which most of the results of the last 60 years in algebraic geometry and algebraic topology would not have been found (Hatcher, 2002). The nuances in those fields seem hard to capture in more

58  Fernando Tohmé and Marcelo Auday classical mathematical settings (Marquis, 2015). The reason is the categorical approach allows for maximising both the scope of the results and the sensitivity to particular differences in the representation of mathematical structures. While this seems a natural choice of formal language, economics has been reluctant to adopt it, except for a few contributions to be mentioned below. In later parts of this chapter, we will draw heavily on the literature on category theory, although our discussion will remain elementary. In this section, we present a brief overview of the basic concepts of the field. For further details, see the excellent presentations in Goldblatt (1984); Barr and Wells (1999); Adámek et al. (2004); Lawvere and Schanuel (2009) or Spivak (2014). Category theory in brief A category C consists of a set of objects, Obj, and a class of morphisms between pairs of objects. Given two objects a,b ∈ Obj, a morphism f between them is f:a → b. Given another object c and a morphism g: b → c, we have that f and g can be composed, yielding g° f: a → c. On the other hand, for every a ∈ Obj, there exists an identity morphism, Ida: a → a. These morphisms obey two rules: (i) if f:a → b, ° Ida = f and Ida °f = f; (ii) given f:a → b, g: b → c and h: c → d, (h° g) °f = h° (g° f  ): a → d. Examples of categories are SET (the objects are sets, and the morphisms functions between sets), TOP (the objects are topological spaces and the morphisms continuous functions), Ord (the objects are pre-ordered sets and the morphisms are order-preserving functions) and Vec (the objects are vector spaces and the morphisms linear maps), etc. Categories facilitate diagrammatic reasoning. A diagram in which nodes represent objects and arrows represent morphisms allows establishing properties of a category. Diagrams that commute, i.e. with different direct paths from to same start and end nodes, indicate relations that can be established by means of equations. Some of the most interesting constructions that can be defined in categories are limits and colimits (duals of limits). Any limit (or colimit) captures a universal property on a family of diagrams with the same basic shape. This basic shape is b captured by a cone, that is, an object a and a family of arrows f a j : a → b j , for j ∈ J such that given a morphism between any pair j, l ∈ J, there exists gjl: bj → bl, b satisfying g jl ° f a j = f abl (see Figure 3.1). Then, given a class of cones of a given shape, a limit is an object L in this class such that for every other cone T in the class, there exists a single morphism T → L. For instance, consider a family of cones of the shape depicted in Figure 3.2. The limit is the product a × b together with arrows p1 and p2 representing the projections on the first (a) and second (b) components, respectively. For every other cone, with “apex” X there exists a unique morphism !: X → a × b. The dual notion of colimit can be illustrated by direct sums (in SET, disjoint unions). Besides capturing interesting constructions common to many fields of mathematics, category theory allows for relating different categories. This is achieved by means of mappings called functors. Given two categories C and D, a functor

Categorical economic theory  59

×

Figure 3.1  Commutative diagram.

Figure 3.2  Cone with limit a × b.

F: C → D maps objects from C into objects of D as well as arrows from the former to the latter category such that, if f: a → b ∈ C, then F (f  ): F(a) → F (b) in D. Furthermore, F(g ° f  ) = F(g) ° F (f  ) and F(Ida) = IdF(a) for every object a in C. These functors are called covariant. Another class, that of contravariant functors, is such that, if f:a → b in C, then F(  f  ): F(a) ← F(b) in D. Of particular interest are the contravariant functors f:C → SET (or a category of subsets of a given set), which are called presheaves. An intuitive interpretation is that, given a morphism a → b in C, the morphism F(b) → F(a) in SET is the projection of the “image” under F of b over the “image” of a. Given an object a in C, F(a) is called a section of F over a. This can be extended to any family B = {bj}j∈J of objects in C: F(B) is the section of B. In turn, given two families B ⊆ B′ and the section over B′, F(B′) we can find its projection over B, denoted F(B′)|B’, yielding F(B). Given a presheaf F: C → SET, consider a class of objects B in C and a cover {Kj}j∈J (i.e. B ⊆ U j∈J Kj). Let {kj}j∈J be a sequence such that kj ∈ F(Kj) for each j ∈ J. The presheaf F is said to be a sheaf if the following conditions are fulfilled: • •

Locality: for every pair i, j ∈ J, ki|K ∩K = k j|K ∩K i, j ∈ J, (i.e. the sections i j i j F ( K i ) , F ( K j ) coincide over K i ∩ K j ). Gluing: there exists a unique b ∈ F ( B ) such that b| K j = k j for each j ∈ J (i.e. there exists a single object in the “image” of B that when restricted to each set in the covering yields the section corresponding to that set).

Why category theory? Mathematical tools of representation and analysis have become increasingly necessary in all the scientific fields, at the very least as a language ensuring precision and clarity (Spivak, 2014). Category theory provides such tools, in particular for the representation of interactions in economic settings. The main point to note is that in interactions there exist some channels over which the agents can exchange information and resources. It is natural to focus on the structure of connections

60  Fernando Tohmé and Marcelo Auday among those channels, which has originated a large literature on networks (Baez, 2014). On the other hand, Nash equilibria and related solutions arising in those structures explain their functions. Such relationship between structure and function arises in multiple disciplines. In linguistics, in neuroscience and in computer science, among others, most of the functions of human languages, brains and computer systems result from the interaction of simple components, according to precise rules, such that global behaviour obtains up from that of those components. There exists a wide consensus that category theory is perfectly suited for describing structure and function of any kind. Numerous contributions attest this claim (Fong and Spivak, 2018). When the global behaviour arises monotonically from the interaction between the components, we speak of the compositionality of the system. On the other hand, interesting relations arise from the interaction among the two levels. That is, the structure gives rise to behaviour, while the latter influences the former, either reinforcing or debilitating links. An advantage of this approach is that the basic components can be chosen at any level of complexity and treated as black boxes without having to be concerned with their inner workings. It is interesting to note that this provides a platform for alternative treatments of the economy, allowing the pacific coexistence of different approaches: while behavioural economics can address the inner structure of decision makers’ minds, a more traditional economist can disregard it, both using the same mathematical framework. Understanding and being able to predict how a system of black boxes will behave can be facilitated by application of category theory, since its emphasis has always been placed on the interactions between objects rather than on individual objects in isolation. This is its main strength, derived from the appropriate linkage between structure and function that it provides. Since its inception in the 1940s, it has become an invaluable formal tool, first in mathematics and then in other disciplines. Particularly fruitful has been the interaction of category theory with computer science. In turn, the increasing influence of computer models in the representation of real-world phenomena has influenced many fields of inquiry, conveying category-theoretical ideas to them. Economics, nevertheless, has been slow to adopt these new ideas. But we are convinced that this will change in the near future, at the very least because of the increasing superposition of incumbencies between economics and computer science (Vazirani et al., 2007). The transition towards the adoption of categorical tools is relevant when we consider the slow drift from economic models based on linear algebra and functional analysis to the more abstract tools used in, for instance, the study of mechanism design and epistemic game theory. Some of the core aspects in these investigations can be better seen in the light of categorical representations: • •

The understanding of back and forth relation between individual and aggregate behaviour. The need for a priori models and real-world data, as well as the interaction between both of them.

Categorical economic theory  61 In the next section, we will review some categorically based contributions to the solution of specific instances of these problems. Afterwards we will present our own take on them.

Some new categorical models There are three problems of relevance in which a categorical treatment leads to novel insights and solutions. The first of them is the possibility of building a whole new economic framework (rivalling the one constructed on the basis of the concept of rational decision-making) founded on behavioural economics. Another problem is the highly relevant issue of how to model the possible existence of infinite regress in the beliefs held by agents about the beliefs of the others. Finally, the last contribution deals with the composition of games, i.e. the integration of different games and the characterisation of the ensuing equilibria in terms of the equilibria obtained in each of the component games. A behavioural integrated model? Economics (even micro-founded macroeconomics) is founded on a notion of agent that can be described in terms of a given preference over the space of alternatives. The agent is said to be rational if she chooses the most preferred alternatives among those that are feasible for her (see Mas-Colell et al., 1995, Chap. 1). Behavioural economists weaken this concept by extending the possibility of choosing what seems to the agent to be her most preferred alternative. In applications of the standard model, it is usual to reduce the analysis to a subspace of the space of alternatives, simplifying the problem of making a decision. This requires assuming the independence of the preferences over that subspace from preferences on the rest of the larger space of alternatives (see (Mas-Colell et al., 1995), Chap. 10). This does not prevent eventual inconsistencies in the combination of different solutions. The first question to ask is under what conditions do the solutions to partial decision-making problems allow the reconstruction of the preferences over the entire space of alternatives? This question is even more relevant for behavioural economics, since it assumes that factors other than the preferences may also influence the decisions of the agents. Some of those factors relate to the way in which agents frame their decision problems and use heuristics to solve them. But then solutions for different problems can be independent. Then we must ask whether there exists a set of alternatives such that each particular solution is a “projection” of one of those. Those two questions are closely associated. But this association cannot be clearly established in the traditional mathematical framework of economics, which clearly differentiates between preferences and choices, except under very specific conditions (Chambers and Echenique, 2016). Formally, we are conceiving a decision problem with a specific domain, D, and a problem-specific utility function u. Its optimising arguments yield the problemspecific solution. Given multiple decision problems sharing a common domain, a

62  Fernando Tohmé and Marcelo Auday global utility function U might be hard to state solely in terms of its local instances. We must be able to patch together the local restrictions in a consistent way. We have to find ways to identify the conditions for patching consistently the local pieces of information. To find those conditions let us define a category of local decision problems PR, where each of its objects is sk =( Lk , u k , X k ) , involving the maximisation of a continuous utility function uk over a compact set Lk ⊆ L , a closed linear subspace of a common space L, yielding a family of solutions X k . Defining appropriate morphisms of the type rjk : s j → sk , representing an appropriate “embedding” of sj into problem sk, we ensure that PR is a well-defined category. We can define a functor S: PR → ℘(L), where ℘(L) is the category consisting of subsets of L with morphisms being set inclusions. This functor is such that S(sk) is the class of solutions of sk. It can be proven that S is a presheaf. A consistent reconstruction of U over the entire L requires the satisfaction of the sheaf property, satisfied by a functor L: ℘(L) → PR. Furthermore, such reconstruction requires the property of triviality of L, meaning that there exists a problem s ∈ PR, such that L-1 (sk) is isomorphic to sk × S(s), which in turn means that every set of solutions of sk can be seen as a projection of the solutions to a global problem s. Then, we have: Theorem (Tohmé et al., 2017): If for every sk in PR, L(S (sk)) = sk, the sheaf condition is satisfied if there exists U such that for each sk, uk = U|L-k. Interestingly enough, by considering two local problems, s1, in which u1 satisfies the precepts of prospect theory (Kahneman and Tversky, 1979), and s2, where u2 obeys case-based decision theory (Gilboa and Schmeidler, 2001), it is not possible to define L satisfying triviality. This means that the conditions for the reconstruction of a global utility U are very demanding. Furthermore, in the case of behavioural economics, this means that there is no way of developing a unified model, incorporating all the possible particular models of non-perfectly rational decision-making. This by no means implies that these alternative models have to be discarded, just that behavioural economics should not aim at the same type of representation as mainstream economics. The problem of circularity Economics has always recognised the important role of beliefs, but since the development of game theory it has been clear that the main issue of analysis must be beliefs about others’ beliefs. That is, any agent analysing a situation has to figure what the other agents think, even about his own beliefs. This circularity has been shown to be hard to tame. Very involved arguments, mostly based on theorems on stochastic processes over different spaces, have ensured the existence of fixed points in the process (Mertens and Zamir, 1984; Brandenburger and Dekel, 1993). An analogous problem appears in the

Categorical economic theory  63 foundations of the mechanism design literature. If the choice of rules is what matters, then under which rules should this decision be made? This problem, again, was solved by means of fixed points in the processes of rule-changing rules of changing rules . . . (Lipman, 1991; Vassilakis, 1991). The pervasiveness of circularities poses a question that is indeed related to that of the existence of fixed points. Namely, the question of in which ways circularities can be “grounded.” This, of course, could be impossible if the process involved an infinite regress. Here the mathematical distinctions are crucial. Even if a fixed point exists, does it obtain at the first infinite ordinal (ω) or is the process transfinite? If no solutions can be ensured to obtain at the ω level, the only alternative is to accept that the world in the model is “open” and therefore prone to new and unexpected outside interventions. This is, of course, akin to concurrence problems studied in theoretical computer science, in which categorical tools allow them to be seen as coalgebraic constructs (studied as functors in categories) and its general properties to be assessed as colimits in the appropriate diagram (Adámek et al., 2004). In formal terms, all the circularity questions amount to finding a solution to the following equation: α = ( w, B (α)), where w involves the objective elements in the problem, including the outside contingencies (due to the open world assumption), while α is obtained by the iteration of a process represented by B(·). Notice that this implies two kinds of elements. On one hand, states of the world as α. On the other, we have hierarchies of belief (w, B(w), B2(w), B3(w), … Bn(w) …). The former defines a class Ω˘ while the latter belong to a class Ω∞ . The question is that, given that Ω∞ is “constructive,” is it the case that Ω∞ = Ω˘ ? To answer this question, consider the category D of simplices in which (Friedman, 2012) the objects are non-empty totally ordered sets, [0] = {0}, = [1] = {0,1} = [2] = {0,1,2}, etc. and morphisms are order-preserving functions. A simplicial set is a presheaf from D to the category of small sets, i.e. a contravariant functor D → SET. Suppose given X, a space of interest. A simplicial set is obtained by assigning a simplex to a family of subsets of X: to [k] ∈ D it assigns a family S[k] ⊆ ℘(X ), such that each of its elements is of cardinality k + 1. In more intuitive terms, a simplicial set yields, for every k, a covering of X by simplices of order k (i.e. elements of S[k]) with the property that the higher the k, the coarser the covering of X. By a slight abuse of language, we call Dk a generic simplex in S[k]. Then, Lkj is, for 0 ≤ j ≤ k, constituted by Dk-1 containing the j-th vertex of Dk. Lkj is called a horn. Consider now a simplicial set X on X. X is a Kan complex (Lurie, 2009) if for every k and every j with 0 ≤ j ≤ k, Lkj can be extended to a Dk. That is, each simplex in the covering “fills in” the skeleton made by its horns.

64  Fernando Tohmé and Marcelo Auday We can show (Tohmé et al., 2018) that there can be defined two Kan complexes, D ∞ = D , D ∞ and D, up from Ω∞ and Ω, respectively. Then we have that these two Kan complexes are identical, and thus: Theorem: each state of the world α is identical to a hierarchy of beliefs (w, B(w), B2(w), B3(w), …, Bn(w) …). This means that every state of the world, i.e. a state of affairs that can be seen as a fixed-point in a belief formation process, can be in principle constructed by iteration. Compositionality in games An interesting problem in game theory involves the possibility of changing the scale of analysis, seeing particular games as instances of larger games. There is not yet an established formalism for that, particularly because allowing a player to participate in different games requires identifying the way in which she evaluates the corresponding payoffs. We will present here a way of modelling this, following the main ideas in (Fong and Spivak, 2018). Let us consider a category G of games. Each object G in the category corresponds to a game G = (IG, SG, OG, φG; pG), where (IG, SG, OG φG) is a game form. That is, IG is the class of players, SG ⊆ Pi∈IG Si is the class of strategy profiles of the game, where Si is the set of strategies of player i, OG is the class of outcomes of the game and φG: SG → OG is a one-to-one function that associates each profile of strategies in the game with one of its outcomes. On the other hand, pG = ∏ piG i ∈I G

is a profile of payoff functions, where each piG : OG →  is the payoff function of player i in game G. Given two games G = (IG, SG, OG φG; pG) and G′ = (IG′, SG′, OG′, φG′; pG′), a morphism of games G → G′ is such that: • • •

IG ⊆ IG′ SG ⊆ SG ′ OG′ There exist two functions, an inclusion pOG from OG’ into OG and a projecSG′ S ˘ G ( s ) = pOOGG′ (˘ G ( s ′)) tion pSG from SG’ into SG such that for every s = pSGG′ ( s ′) , φ SG ′ OG ′ = pSG ( s ′) , ˘ G ( s ) = pOG (φ ˘ G ( s ′)) . Thus, if morphism G → G′ exists, G can be conceived as a subgame form of G′.

It is easy to prove that G is a category with colimits, which allows conceiving each game G ∈ G as a box. That is, G = inG | out G , where inG and outG are, respectively, input and output ports. Inputs belong to OG while outputs to SG. Up to this point, our definition of morphisms in G does not involve the payoffs. They can be incorporated by redefining the games as modal boxes, in which an additional component is the internal sets of the game. More precisely, given any G and the class of its internal states, SG, we can identify G as a triple G = inG | out G | ΣG , plus two correspondences such that rG1 (o, d ) yields a

Categorical economic theory  65 corresponding payoff (for an outcome o ∈ OG and a state d ∈ SG) and rG2 (d ) yields a profile of strategies in SG. We can thus define a new category WG with the same objects as G and where a morphism G → G′ indicates that there exists a game of which G and G′ are subgame forms. Besides the usual composition of morphisms ° we can endow WG with a monoidal structure defined by a unit (the initial object of G) and an operation defined on pairs of games, denoted G + G′ (+ is the coproduct in G ). Notice that the monoidal structure is well defined since G has colimits. We define a functor Eq: WG → Pi∈IG Si, such that, for every object G in WG , Eq assigns a class of strategy profiles in G, representing equilibria in G, for some notion of equilibrium (as for instance, dominant strategies equilibrium, admissible strategies, or Nash equilibrium). For an illustration, consider two games, G between players 1 and 2 with S1 = S2 {Bx, Bll} (known as the Battle of the Sexes): 1↓/2→

Bx

Bll

Bx Bll

(2,1) (0,0)

(0,0) (1,2)

And G′ between players 2 and 3, known as the Prisoner’s Dilemma, where S2 = S3 {C, D}: 2↓/3→

C

D

C D

(2,2) (3,0)

(0,3) (1,1)

In light gray, we have highlighted Eq(G) = {(Bx,Bx),(Bll,Bll)} and Eq(G′) = {(D,D′)}, where Eq yields Nash equilibria. Let us represent now G + G′. We obtain the following game, in which if 3 chooses C we have: 1↓/2→

Bx ‒ C

Bx ‒ D

Bll ‒ C

Bll ‒ D

Bx Bll

(2,1 × 2,2) (0,0 × 2,2)

(2,1 × 3,0) (0,0 × 3,0)

(0,0 × 2,2) (1,2 × 2,2)

(0,0 × 3,0) (2,1 × 3,0)

While if 3 chooses D we have: 1↓/2→

Bx ‒ C

Bx ‒ D

Bll ‒ C

Bll ‒ D

Bx Bll

(2,1 × 3,0) (0,0 × 3,0)

(2,1 × 1,1) (0,0 × 1,1)

(0,0 × 3,0) (1,2 × 0,3)

(0,0 × 1,1) (1,2 × 1,1)

66  Fernando Tohmé and Marcelo Auday In other words, players 1 and 3 keep the payoffs they get in the subgames, while 2 takes the product of the payoffs in G and G′. In light gray we have highlighted the equilibria of G + G′ under this specification. The formalism that justifies this procedure is based on the definition of an operation ■ such that given two equilibria s ∈ Eq(G) and s′ ∈ Eq(G′), yields a new profile s ‒ s′ ∈ Eq(G) ■ Eq(G′) verifying that for each player i ∈ I G ∩ I G ′ a new strategy obtains combining si and si′ , while in on all other cases the individual strategies are the same as in G and G′. Furthermore, if we assume a simple internal  state d i such that rG1 (o − o ′, d ) = rG1 (o, d )× rG1 (o ′, d ) , we have that ′ piG +G ( s − s ′) = piG ( s )× piG ( s ′) for i ∈ I G ∩ I G ′ In our example, since Eq(G+G′) = {(Bx,Bx – D,D′), (Bll, ‒ D,D′)} and Eq(G′) = {(D,D′)}, it follows that Eq(G) ■ Eq (G′) Eq (G+G′). Then, if we denote + the monoidal operation in WG, if we take ■ as monoidal operation in Pi∈IG ∪IG′ Si , we have an isomorphism between Eq(G + G′) and Eq(G) ■ Eq (G′). Thus, Eq associates the composition of games with the equilibria of the components, allowing the creation of large networks of games, preserving in the global result the properties of the components.

Discussion General categorical concepts have enjoyed wide use across many different mathematical fields. We have tried to convey here the idea that they also hold conceptual advantages for economics. On one hand, category theory changes the focus from objects to morphisms. This, in particular, frees the economic models of the emphasis on equilibria, which become objects that may or may not exist in the appropriate category. Instead, the relational aspect of morphisms allows for capturing a variety of approaches in a single framework. Unlike traditional mathematical frameworks that demand that every entity must be defined in terms of simpler entities, category theory favours a “synthetic” approach, in which objects are given without any consideration to their inner structure, only by their interactions with other objects. This is true both for the axiomatisation approach à la Debreu and to the more contemporary approach of “model-building” in game theory, implementation theory, macroeconomics, etc. In the former case, category theory allows the relations among the mathematical universes corresponding to different axiom systems to be captured. On the other hand, the model-building approach, grounded in practices more common among computer scientists and physicists, can be clarified by means of categorical tools: A major tool is the structure of information itself: how data is made meaningful by its connections both internal and outreaching to other data [. . .] Giant databases are currently being mined for unknown patterns [. . .] Similarly, in science there exists substantial expertise making brilliant connections between concepts. (Spivak, 2014: 6)

Categorical economic theory  67 This is, indeed, the reason why category theory seems to have a bright future in Economics.

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68  Fernando Tohmé and Marcelo Auday Lipman, B. (1991). How to Decide How to Decide How to . . .: Modeling Limited Rationality, Econometrica 59: 1105–1125. Lurie, J. (2009). Higher Topos Theory, Princeton University Press, Princeton, NJ. Marquis, J.-P. (2015). Category Theory, in E. Zalta (ed.), The Stanford Encyclopedia of Philosophy (Winter edition) (http://plato.stanford.edu/archives/win2015/entries/ category-theory/). Mas-Colell, A., Whinston, M. and Green, J. (1995). Microeconomic Theory, Oxford University Press, New York. Mc Lennan, A. (2018). Advanced Fixed Point Theory for Economics, Springer, Berlin. Mertens, J.-F. and Zamir, S. (1984). Formulation of Bayesian Analysis for Games with Incomplete Information, International Journal of Game Theory 14: 1–29. Moss, L. and Viglizzo, I. (2004). Harsanyi Type Spaces and Final Coalgebras Constructed form Satisfied Theories, Electronic Notes in Theoretical Computer Science 107: 279–295. Oliveira da, H. (2018). Blackwell’s Informativeness Theorem Using Diagrams, Games and Economic Behavior 109: 126–131. Platzer, A. (2018). Logical Foundations of Cyber-Physical Systems, Springer, Berlin. Robbins, L. (1932). An Essay on the Nature and Significance of Economic Science, Macmillan, London. Rozen, V. and Zhitomirski, G. (2006). A Category Theory Approach to Derived Preference Relations in some Decision Making Problems, Mathematical Social Sciences 51: 257–273. Samuelson, P. (1952). Economic Theory and Mathematics: An Appraisal, American Economic Review (Papers and Proceedings of the Sixty-Fourth Annual Meeting of the American Economic Association) 42: 56–66. Shoham, Y. and Leyton-Brown, K. (2009). Multiagent Systems: Algorithmic, GameTheoretic, and Logical Foundations, Cambridge University Press, New York. Spivak, D. I. (2014). Category Theory for the Sciences, MIT Press, Cambridge, MA. Tohmé, F., Caterina, G. and Gangle, R. (2017). Local and Global Optima in DecisionMaking: A Sheaf-Theoretical Analysis of the Difference between Classical and Behavioral Approaches, International Journal of General Systems 46: 879–897. Tohmé, F., Caterina, G. and Gangle, R. (2018). The Class of States of the World as a ∞-Groupoid: Identifying States of the World and Hierarchies of Belief, International Journal of General System 47: 632–645. Vassilakis, S. (1991). Rules for Changing the Rules, Technical Report 32, Stanford Institute for Theoretical Economics, Stanford University. Vazirani, V., Nisan, N., Roughgarden, T. and Tardos, É. (2007). Algorithmic Game Theory, Cambridge University Press, Cambridge, UK. Weinberger, S. (2004). On the Topological Social Choice Model, Journal of Economic Theory 115: 377–384. Wiweger, A. (1982). Categories of Kits, Coloured Graphs and Games, Lecture Notes in Mathematics 962: 312–322.

4

Microeconomics Is there a Post Keynesian alternative? Jordan Melmiès

Introduction Most of the time, microeconomics doesn’t constitute a core issue in Post Keynesian theory, and it still remains quite underdeveloped compared to mainstream microeconomics. The reason microeconomics has not retained much attention among Post Keynesian economists is that, initially, developing an alternative microeconomic theory was not necessary to make the Keynesian revolution operative, since Keynes’s goal was to substitute Say’s law by the effective demand principle within the neoclassical citadel and its assumptions. Post Keynesian economists have, however, developed meaningful elements on the theory of the firm, pricing, competition and consumer behaviour, sometimes even before Keynes’s publication of the General Theory (for example, on imperfect competition with Joan Robinson). Two paths of divergence from mainstream economics can be identified in Post Keynesian microeconomics: a descriptive rupture (PK micro theory thinks that agents do not behave like mainstream economics assumes) and a normative rupture (Post Keynesian microeconomics doesn’t lead to the same political recommendations). In the first section, we examine why alternative microfoundations was not an issue in Keynes’s General Theory, and why it is an important one for Post Keynesian analysis – as well as for Keynesian economics in general, which historically faced the so-called microfoundations problem. In the second section, we present the elements of a Post Keynesian “producer theory.” We show that the essential contribution of Post Keynesian economists is an inclusion of self-financing into the economic theory of the firm. In the third, we discuss Post Keynesian consumer theory. In the last section, we discuss the implications of adopting Post Keynesian microeconomic tools in terms of economic policy.

Keynesian economics and micro theory Keynesian economics are often described as being mainly focused on macroeconomics. It was only with the emergence of the so-called New Keynesian school that Keynesian economics, as will be shown, seriously took the question of microfoundations into account.

70  Jordan Melmiès Keynes’s micro theory In Keynes’s (1936) General Theory, microeconomic behaviour is essentially similar to that described by neoclassical economics, more precisely Marshallian theory of the firm. The question of a Keynesian alternative to standard microeconomics was not an issue in Keynes’s book. The reason is not that Keynes was persuaded that neoclassical/Marshallian microeconomics was an adequate tool to describe the behaviour of individuals, but more that it was not necessary to him to develop such an alternative to make the Keynesian revolution operative, to put the principle of effective demand forward and to refute Say’s law. That is why Keynes, throughout the General Theory, always accepts as many neoclassical assumptions as possible. This relative neglect of microeconomics by Keynes has a further consequence: by insisting on macro, he left out the theory of the consumer. Thus, microeconomics in the sense of Keynes often results in a discussion about firms, which are assumed to behave in a neoclassical/Marshallian way. Firms are thus assumed to maximise profits, to face an upward sloping marginal cost and to be price takers. Keynes’s producer theory thus has nothing different than mainstream economics, even if Robinson and Wilkinson (1983) assert that there was a Keynesian revolution in price theory just as important as the revolution in employment theory, though Keynes himself did not take much interest in it. (89) They further recall that Keynes did not bother much about “micro theory” – the prices of particular commodities (though he started my career by recommending enthusiastically to Macmillans my Imperfect Competition). (89) Microeconomics is thus not a fundamental issue in Keynes’s work and left open the door to several interpretations for the development of microfoundations for a Keynesian thinking. The neoclassical synthesis and its collapse The neglect of microeconomics by Keynesian economics went further with the so-called and dominant neoclassical synthesis, which relied on a rigid nominal wage/price assumption. In the IS/LM model, wages are often considered to be given, as are prices, since this model is a (very) short-term one. Modigliani’s 1944 Econometrica article is often considered to be a key effort to reconcile Keynes’s theory with classical economics, and this reconciliation is done through the “wage rigidity assumption.” As recalled by Rancan (2016), this article suggested that the only difference between Keynes and the Classics was that money wages don’t fall

Microeconomics  71 as unemployment rises, as would be the case in classical economics (Rancan, 2016). To use Modigliani’s (1944) own words: It isusually considered as one of the most important achievements of the Keynesian theory that it explains the consistency of economic equilibrium with the presence of involuntary unemployment. It is, however, not sufficiently recognized that, except in a limiting case to be considered later, this result is due entirely to the assumption of “rigid wages” and not to the Keynesian liquidity preference. (Modigliani, 1944: 65) This assumption of wage/price rigidity is clearly undertaken by Samuelson in an interview he gave to Colander: I was content to assume there was enough rigidity in relative prices and wages to make the Keynesian alternative to Walras operative. (Samuelson, in Colander and Landreth, 1996: 160) In the neoclassical synthesis, rigid wages and prices were thus, most of the time, assumed without explaining the reasons underlying it. This short-run price fixity was fundamental to the neoclassical synthesis and provoked its collapse in the 1970s in the face of “New Classical” economists, for whom there existed no rational or theoretical support for such an assumption. For New Classical economists, assuming that wages and prices do not adjust to demand and supply disequilibria is the same as assuming agents would not achieve trade gains or, as Robert Lucas often said, that they leave $500 bills on the sidewalk. It was clearly with this attack on not providing microeconomic justification for price rigidity that Keynesian economics came to be confronted with the question of microfoundations. Ball and Mankiw (1994) explain that this critique was devastating for Keynesian models, because it exposed their incompatibility with microeconomics. The revival of Keynesian economics Some authors, still believing in the rigidity of prices, considered this critique as a challenge to take up. Instead of rejecting Keynesian models due to the weakness of their microeconomic foundations, they started to derive price rigidity from agents’ rational behaviour. This resurgence of economists labelling themselves Keynesians gave birth to the so-called New Keynesian paradigm. This revival of “Keynesian” economics is thus linked to the answer given to New Classical macroeconomists. As often stated by Mankiw, it was an answer to Lucas. The aim of new Keynesian economics was thus to ground price rigidity in microeconomic terms so as to explain the existence of involuntary unemployment and the absence of money neutrality (in the short run). It was on that basis that standard Keynesian economists started to build rigorous and solid microfoundations into their models. For that purpose, they developed several theories of

72  Jordan Melmiès price/wage stickiness: menu costs, implicit or explicit contracts, coordination failure, efficiency wage, etc. The best review of these theories, as well as their implications and a detailed empirical investigation, can be found in Blinder et al. (1998).1 New Keynesians can now assert that Keynesian theory is built upon rigorous micro-behaviour of firms and households. These microfoundations take into account the New Classical objections and tools. In standard DSGE (for Dynamic Stochastic General Equilibrium) models, for example, households are assumed to have rational expectations and to maximise intertemporal utility, and firms are assumed to maximise profits, with prices being sticky due to rational behaviour (menu costs, coordination failures, implicit contracts and so on). The place for a Post Keynesian alternative In other words, New Keynesian economics is the art of finding Keynesian results in a New Classical framework. Whether with the New Keynesians or with Keynes’s General Theory, one remains with very orthodox micro-tools to describe firms and households. Dullien (2011) describes the content of such DSGE models and shows their clear incompatibility with Post Keynesian theory. This New Keynesian story is, however, not the only one that can be told (and taught), as a Post Keynesian alternative to mainstream economics exists in the field of micro as well as in macro, even if it receives less attention. Post Keynesian economists have indeed developed meaningful elements in the theory of the firm, theory of prices, competition and even consumers’ behaviour which radically differ from usual tools. The question is whether such an alternative is needed, and why. The answer is that this alternative is needed since New Keynesian economics and Post Keynesian economics don’t share the same overall project. As emphasised for example, by Davidson (1992), Keynes’s original goal was to demonstrate that a free capitalist economy is not self-adjusting (i.e. it does not converge by itself to full employment) and that Say’s law does not prevail even if competition is perfect and even if prices and wages are perfectly flexible. In that sense, New Keynesians, while explaining the role of demand and the existence of involuntary unemployment by price and wage rigidity, be it rational and theoretically grounded, is contrary to the Keynesian project. To put it differently, Post Keynesian economics is the art of developing Keynes’s theory in the same direction as the initial project, while New Keynesian economics tends to develop Keynes’s project as well, but in a direction usually in the opposite sense as the original project. In Davidson’s words, there are several reasons why Keynes would not have accepted being called a New Keynesian. The differences between Post Keynesian and mainstream microeconomics are twofold. The first difference is a descriptive one: Post Keynesian economists think individuals (firms or households) don’t behave as standard microeconomics says. As will be emphasised, in Post Keynesian microeconomics, firms can seek to achieve other goals than profit maximisation (for example, growth of sales), households don’t follow the pure rational behaviour described by mainstream economics, etc. The second difference is normative: the way Post Keynesian economists

Microeconomics  73 describe micro-behaviour does not lead to the same political conclusions as mainstream economists (this difference is also true, at a lower level, with New Keynesian economics). This is especially true, as will be shown, for competition policy. These two differences (descriptive and normative) explain why a Post Keynesian alternative is needed, and why one cannot rely on New Keynesian microeconomics, which essentially relies on mainstream tools, to analyse the economy.

Post Keynesian theory of the firm The question of the objectives of the firm The first essential question one has to ask in the theory of the firm is the following one: what is the objective of the firm (or what are the objectives of the firm)? Mainstream economics always considers that firms seek to maximise profits. The story is different but a bit more ambiguous in Post Keynesian economics, since two branches of theoretical analysis can be identified (see for example Melmiès, 2015): historically, a first stream of Post Keynesian theory considers that firms seek to maximise their profits (under technical constraint), as well as in mainstream economics. This analytical branch can be found in the writings of Joan Robinson and Michal Kalecki (and thus falls in line with Keynes himself), both of whose work relies on a common basis: firms are assumed to maximise their profits. In his 1936 reading note of the General Theory (initially published in Polish, Kalecki, 1936), Kalecki clearly endorses profit maximisation (marginal revenue and marginal cost equalisation). In his subsequent 1939, 1940 and 1941 articles, he refers to the price elasticity of demand as a determinant of prices, leaving no doubt of firms’ behaviour (Kalecki, 1939, 1940, 1941).2 The same applies to Joan Robinson’s Economics of Imperfect Competition, which explicitly assumes profit maximisation as a standard behaviour and then reviews all possible market structures on that basis: The single assumption which it is necessary to make in order to set that piece of apparatus at work is the assumption that the individual firm will always arrange its affairs in such a way as to make the largest profits that can be made in the particular situation in which it finds itself. [. . .] It is the assumption that any individual, in his economic life, will never undertake an action that adds more to his losses than to his gains, and will always undertake an action which adds more to his gains than to his losses, which makes the analysis of value possible. (Robinson, 1933: 6) And further: He is assumed always to choose the output which will maximize his net receipts. (Robinson, 1933: 16)

74  Jordan Melmiès The second branch of Post Keynesian firm theory assumes firms seek to maximise growth under the constraint of financing part of investment expenditures on internal funds. Linking profit margins to sales growth and the need for internal finance goes back to Gardiner Means (see Lee and Samuels, 1992 and Lee, 1998), who suggested that managers choose a profit margin that takes into account market competition as well as the need to finance the growth of the firm. In the literature, however, this theory is often dated back to Alfred Eichner (1973, 1976). Outside the Post Keynesian field, the closest contribution is the one by Baumol (1958). This assumption of sales growth maximisation is explicitly stated in several major contributions. For example, Eichner (1976) says in the introduction: Put another way, prices in the oligopolistic sector are set not to maximize short-run profits but rather to enable the firms in that sector to finance the level of investment necessary to maximize – or at least move further toward maximizing – their own long-run growth. (Eichner, 1976: 2–3) Eichner’s theory considers demand management for a firm’s product as a long-run activity; managers thus focus on the long-term growth rate rather than on shortterm profit maximisation. Therefore, the primary aim of a firm is to maximise growth (and to finance investment). In the same vein, Adrian Wood’s Theory of Profits (1975) asserts: The basic goal of those in charge of the firm is to cause its sales revenue to grow as rapidly as possible. (Wood, 1975: 62–63) The determination of profit margins Both branches of Post Keynesian price theory have a particular implication in the theory of profits – the theory of profit margins – they contain. The first branch (the “imperfectionist” approach) directly links profit margins to the degree of competition. Robinson’s Economics of Imperfect Competition reviews several market structures that depart from perfect competition. The representative case is the example of a monopolist, equating marginal cost to marginal revenue. In this case, firms earn a profit margin because prices exceed marginal and average costs. Compared with a perfectly competitive market structure, monopolists charge higher prices and hence extract positive profit margins from the market, because of competition imperfections. Robinson’s theory thus states that the weaker the competition, the higher the profit margins. Kalecki’s theory of the degree of monopoly relies on similar reasoning. In his writings, Kalecki assumes that firms act in an oligopoly, duopoly or monopoly world. His theory integrates a precise determination of profit based on the “degree of monopoly.” For him, the degree of monopoly determines the level of individual profit margins

Microeconomics  75 (and, at the aggregate level, the share of profit in national income). Although Kalecki’s view has evolved over time (see Basile and Salvadori, 1984–1985), his concept of the degree of monopoly establishes a direct link between competition and profit margins. Kalecki’s pricing equations are formulated as mark-up pricing over costs, in which the level of mark-up depends on factors like the price elasticity of demand and the price of competitors, what Kalecki called the “state of imperfection of the market” (Kalecki, 1939). His theory is thus in line with Joan Robinson’s imperfect competition theory and the first branch of Post Keynesian approach of profit margins. The second branch links, as was said, profit margins to the needs for internal funds to finance investment expenses and the growth of the firm. This theory was undertaken by several authors, among which number Kregel (1971), Harcourt and Kenyon (1976), Eichner (1973, 1976) and Wood (1975). We will here underline two of these contributions: Eichner and Wood. Alfred Eichner developed this theory in a 1973 article and a 1976 book, The Megacorp and Oligopoly. He notes the importance of internal finance in modern capitalism: Between the fourth quarter, 1948, and the third quarter, 1960, only a little more than 10 percent of all investment in the manufacturing sector was financed through long-term external debt, with slightly more than half of that being accounted for by new fixed interest obligations and the rest by equity issues. (Eichner, 1976: 289) Eichner thus stresses the importance of self-financing in the pricing policy of a firm. He sees profit margins (what he calls the “average corporate levy”) as dependent on a trade-off between the costs of internal and external financing. Managers seek to increase sales and to maintain a sufficient level of profit to be able to finance investment expenses, which are necessary to increase sales. Eichner formalised his theory in a four-part diagram (see Eichner, 1976: ch. 3). The reasoning is quite similar in Adrian Wood’s 1975 book A Theory of Profits. In contrast to Eichner’s diagram, which is quite complex and difficult to “use,” Wood’s theory benefits from incorporating the main features of this theoretical tradition in a relatively simple and manageable two-curve diagram. This two-curve diagram makes it possible to analyse various situations (and challenge mainstream views, as will be shown below). In spite of its simplicity, Wood’s model provides a very comprehensible model of investment financing. His diagram is based on twocurves symbolising frontiers. The first curve represents what Wood calls the “opportunity frontier” and links profit margins to the growth of sales proceeds – a trade-off between profits and demand in the medium to long run. This trade-off is easily understood: managers have to choose between a high profit margin and a high sales growth rate. The underlying idea is that to stimulate the growth of sales, managers must reduce prices and hence profit margins. This trade-off occurs because Wood assumes that although demand for products increases over time, it remains limited for any individual firm (due to competition between firms). Firms

76  Jordan Melmiès

π

Optimal point of the firm FF

OF

g Figure 4.1  Wood’s (1975) two-curve diagram.

thus have to compete to gain a greater share of this limited demand. This opportunity frontier is represented by a concave, downward sloping curve (see Figure 4.1). The opportunity frontier (OF) is to be read as follows: in order for a firm to achieve a higher rate of sales growth (g) for a given type of product traded in the market, managers must charge a lower price and thus accept a lower profit margin (π). The opportunity frontier curve is concave because it assumes that higher growth rates when the initial rate is low can be attained through minimal reductions in mark-up, whereas significant reductions in mark-up are required to increase sales growth rates when the initial rate was already high. The second curve represents a relationship between sales growth and profit margins that is based on the reverse causality – the influence of growth rates on required profit margins. Wood calls this the “finance frontier” (FF), assuming that, in the long run, firms either seek or are forced to internally finance part of their investment expenses for various reasons – for example, because of insufficient lines of bank credit, or a reluctance of managers to increase leverage ratios, such as in Kalecki’s increasing risk principle (Kalecki, 1937). Profit margins are thus necessary to ensure a firm’s continued existence. When a firm expects a higher sales growth rate, profit margins must also, all things being equal, be increased. The finance frontier is thus an upward sloping curve, based on the idea that managers must acquire new plants and/or equipment to attain a certain level of sales growth. For a given capital-output ratio, they must choose a profit margin in accordance with this level of growth (see Figure 4.1). Managers will choose to operate at the intersection of these two curves because it is the point that permits the maximum financially viable sales growth rate under prevailing financial conditions. Firms will not operate below the opportunity frontier or above the finance frontier because they seek to achieve higher sales growth rates without financial risk. In Wood’s model, firms do not maximise profits under technological constraints; they maximise growth under financing constraints. This

Microeconomics  77 analysis is still based on an optimising behaviour, but stresses the importance of “required” internal financing. Thus, profit margins are not a result of market imperfections; they are a necessity for all businesses, independent of the market situation. This position is a clear departure from neoclassical theory. The convergence of Post Keynesians Post Keynesian economics thus relies on two distinct views of the goals and behaviours of firms: a first one very close to mainstream theory, and a second one pretty much different. The question is thus to delineate whether one of these theories is to be preferred, and if so, which one. On that point, it can be shown that the socalled investment financing theory is designed to replace the “imperfect competition” theory, and that the “imperfectionists” have progressively endorsed the “investment financing” theory. For example, Joan Robinson postulated a link between profit margins and the financing of investment as early as 1952. She did not, however, clearly link profit margins to investment and continued to rely on her theory of normal prices (Lee, 1998). But she later admitted that her theory of imperfect competition was just a means to finding a way out of mainstream theory, and not really a “culmination”: [The notion of imperfect competition was a necessary step in liberation from orthodoxy but to say that the ratio of prices to prime costs is determined by the degree of monopoly is not enlightening]. (Robinson and Wilkinson, 1983: 90) In 1970 she went further in her thinking and, considering a possible link between profits and investment, argued that firms are, so to say, taxing the consumers to pay for their investment. (Robinson, 1970: 736) Kaldor, for his part, started at the same time to assume that profit margins depend on investment requirements and propensities to save (i.e. retained earnings) (Kaldor, 1957; see also Lee, 1998: 175). Ball (1964), Kregel (1971) and Harcourt and Kenyon (1976) further contributed to this theory. The contributions of Eichner and Wood we detailed above can be viewed as the culminating contributions. More explicit is the correspondence between Robinson and Eichner. Their exchanges in 1971 make it clear that Eichner tried, and managed, to convince Joan Robinson of the relevance of his theory as compared to her own theory. In a letter, he describes his theory the following way: Periodically (say, once every six months), a megacorp will pause to reassess its pricing policy. The past, which has given the megacorp a certain percentage of the market, is unalterable. The future, portending a certain rate of growth

78  Jordan Melmiès of industry sales and thus of demand for the megacorp’s product, is uncertain. Nonetheless, the future must be predicted. The megacorp has probably already decided upon a certain capital expansion program for the next five years or so, based on what seems like the best estimate of future demand. Now the megacorp must deal with the present, which means it must decide what change, if any it should make in the industry price level (assuming the megacorp is the industry price leader). If costs have risen since the last time the price level was reassessed (this would most likely be due to a rise in wage rates or the cost of raw materials), the price level will most certainly be increased to cover those higher costs. If, in addition, a more rapid rate of capital expansion has been decided upon, then the price level may be increased still further to supply the necessary additional funds from retained earnings. Whether the price level will in fact be increased for this reason will depend on the relative cost of obtaining additional funds from the corporate levy and from the capital funds market. (Eichner, letter to Joan Robinson, 26/12/1971, in Lee, 2000) After several exchanges, Robinson admits: This theory is perfectly straightforward and convincing. (1/11/1972 in Lee, 2000) The conclusion is thus that the “investment financing” theory of prices and profit margins (i.e. the “investment financing theory” of the firm) constitutes the real Post Keynesian alternative to mainstream microeconomics on the topic, since it progressively rallied the “imperfectionist” proponents, especially Joan Robinson (whereas one could not find the opposite movement in the history of Post Keynesian thought). Some applications of the theory of the firm The Post Keynesian theory of the firm, beyond its difference from neoclassical theory, can be applied to and is very useful for examining specific features of modern economies. We will here select three examples. Financialisation The first field to which the Post Keynesian theory of the firm can be applied is what is called financialisation, i.e. the rise of financial constraints and financial rationales for non-financial businesses. Stockhammer (2004) has offered one of the first analyses of financialisation while using the Post Keynesian two-curves diagram, in order to show the consequences of the so-called shareholder revolution on the pace of accumulation in developed countries. The simplest way to represent it is in an upwards shift of the finance constraint (due to the rise in dividends payments) which makes profit margins rise and accumulation decrease

Microeconomics  79 π FF2 FF1 π2 π1

OF g2

g1

g

Figure 4.2 Effect of a rise in financial constraints on non-financial businesses (see Dallery, 2009).

(see Figure 4.2). In that case, accumulation rates decrease (from g1 to g2), as long as profit rates increase (from π1 to π2). This gives an illustration of what Lazonick and O’Sullivan (2000) called the “downsize and distribute” narrative of financialisation. Several developments have been achieved on that question using this Post Keynesian theory of the firm. Dallery (2009) reviews the different cases of firms’ behaviour under financialisation. These analyses help to understand the recent evolutions of what is called “shareholder capitalism.” Subcontracting The second field that one can mention is the field of inter-firm relationships. As well as industrial economics in general, inter-firm relationships are not a widespread field of analysis among Post Keynesian economists. However, it constitutes a very stimulating and promising research field. Dallery and Melmiès (2014) have applied the Post Keynesian micro theory of the firm at a disaggregated level, examining the consequences of inter-firm relationships, for example subcontracting, on macro variables. Examining the case where subcontractors face the constraint of order givers imposing price cuts on them, they show that the need to secure and restore profit margins (so as to finance investment plans) leads to a “constraint transfer” which reduces the beneficial consequences of a price cut for the economy. The need to finance investment exerts strategic constraints on firms and impacts the way lenders (especially banks) can ration external finance. Credit

80  Jordan Melmiès rationing will be toughest when firms fail to generate enough internal funds. In the end, firms are forced to cut costs such as wages to maintain their position (Dallery and Melmiès, 2014), reinforcing the negative macroeconomic consequences of the initial shock. Competition To a larger extent, this Post Keynesian theory of the firm can be used to give a different reading of the way firms compete each other. In mainstream economics, competition is seen as beneficial for the economy as a whole, leading firms to cut prices and improve quality, finally reducing subnormal profits. Some Post Keynesians have questioned this story, however, pointing out for example the damaging macroeconomic consequences it can have for aggregate demand. Shapiro (2005) and Milberg (2009), or even Crotty (2002, 2003) from a more Marxist perspective, have underlined the macroeconomic consequences of competition. Lee (2013a) is also of a sceptical view about the benefits of competition from a Post Keynesian perspective. Melmiès (2015) uses Wood’s diagram to show that competition enhancement does not lead, in itself, to any shift in the opportunity frontier, thus leaving the industry equilibrium unaffected by the degree of competition. In Figure 4.3, a rise in the degree of competition (for example, a fall in the concentration ratio) can shift the individual opportunity frontier downwards, but mechanically moves the opportunity frontier of other firms in the industry upwards, having thus no effect on the average/sectoral profit (all other things and firms’ characteristics being equal).

π

FF

OF

Figure 4.3  Effect of a fall in the concentration ratio of the industry.

g

Microeconomics  81

Post Keynesian consumer theory Core elements of the Post Keynesian consumer theory As has been explained to this point in this chapter, Post Keynesian economists often don’t pay much attention to microeconomics. This is quite true concerning producer theory, but there are some meaningful developments on that topic. This neglect is, however, more blatant concerning consumer theory, which attracts very few contributions from Post Keynesians. One of the best and most developed syntheses on Post Keynesian consumer theory is perhaps to be found in Lavoie (1992, 1994, 2014), who proposed a general view of a heterodox/Post Keynesian theory of consumer choice and identifies six fundamental non-mainstream principles. We will present these principles identified by Lavoie and then offer some applications of this consumer theory: ecological economics; the link between competition and the quality of goods and services; and the connection with Galbraith’s theory of the revised sequence. The question of rationality The first feature one needs to examine when speaking of Post Keynesian consumer theory is the question of rationality, and its position relative to neoclassical economics. Until recently, mainstream economics relied on a very strong conception of rationality to describe agents. This view culminated with the so-called rational expectations revolution, leading to representations of the agents often called “RARE”: Representative Agents with Rational Expectations (see for example King, 2012). This conception of rationality has, however, been challenged with the emergence of behavioural economics, which emphasises cognitive bias in the behaviour of agents, thus questioning the pure rationality theory. The position of behavioural economics is intermediate between mainstream economics and pure Post Keynesian theory. First, behavioural economics seems to challenge the mainstream, underlining multiple violations to maximising agents. Behavioural economists may thus appear as “mainstream dissenters” (Lavoie, 2014). At the same time, behavioural economics may, for some part, have some features in common with the Post Keynesian way of thinking, as explained by Fontana and Gerrard (2004): for the group of developments in economic psychology which try to move beyond risk-based approaches and expected utility theory (ibid.), the convergence with Keynesian views of uncertainty, non-ergodicity and ambiguity is quite evident. In fact, behavioural experiments show that the behaviour of agents are much more like the procedural rationality described by Herbert Simon than the “sovereign consumer” found in neoclassical textbooks. This “bounded” or “limited” or “procedural” rationality theory is the other branch of economics that had already questioned the concept of rationality and on which Post Keynesians often relied when theorising consumers. It is the first principle of the theory of choice that Lavoie (1992, 2014) considers to be fundamental to describing consumers. Procedural or

82  Jordan Melmiès bounded rationality (Lavoie’s first principle) simply states that agents lack the ability to clearly evaluate all possibilities and distinguish all possible outcomes of a choice. In other words, people usually make decisions that are perceived as reasonable and acceptable choices based on established rules of behaviour, convention or habit. Post Keynesian economics thus borrows both behavioural economics and limited rationality theory to describe the basic behaviour of individuals. Other principles Lavoie (ibid.) identifies five other principles in his synthesis: • • • • •

Principle of satiable needs (second principle): people’s choices are thresholdsensitive. The utility derived from the consumption of a good tends to zero (for a positive price and for a finite income). Separability/irreducibility of needs (third principle): people usually divide and sub-divide their needs into several categories and subcategories with limited degrees of substitutability. Subordination of needs (fourth principle): categories and subcategories of needs are not ordered at random in people’s minds, but are ranked hierarchically (basic needs followed by less vital and nonessential needs). Growth of needs (fifth principle): people’s hierarchies of needs grow as their income increases (a phenomenon explained by Georgescu-Roegen (1954)). Nonindependence (and heredity) (sixth principle): the principle of dependence (or nonindependence) refers to the dependence of people’s choices on the choices made by other members of society. This “dependence effect” was described by Galbraith (1958). Accordingly, a person’s individual choices are made in part based on choices made by other people (imitation). This differs somewhat from the principle of heredity, which stipulates that individual choices depend on the order in which these choices are made. As Lavoie (1992, 2014) recalled, this principle had previously been highlighted by Georgescu-Roegen (1954).

Consequences and applications Ecological economics Lavoie (1992, 2014) uses these principles to analyse the behaviour of consumers regarding ecological economics. He goes back to the work of a French economist (however unrelated to heterodox economics), Rene Roy, who first put forward the concept of lexicographic choice to describe consumer behaviour. The lexicographic nature of individual choices derives from the principles described above, especially growth, subordination and separability of needs. In that sense, one can conclude that all goods can’t be treated equally. Lavoie takes the example of environmental protection, which may be subject to minimum threshold in private revenues to be incorporated in individuals’ preferences, and may thus disappear when revenues fall below

Microeconomics  83 this threshold. This conception of individual choice leads, in our view, to specific political implications: one can conclude, for example, that it is necessary, in order to provide the society with an ecological transition, that inequalities be maintained at a low level, with a certain level of revenues for low-income categories. The quality of goods and services Another example of application of Post Keynesian consumer theory concerns the evaluation households make of the quality of goods and services. The conclusion of the principles described earlier is that consumers may not be able to evaluate the quality of the goods and services they consume. A development of these concerns can be found in Melmiès (2017), exploring how competition between firms can lead to a reduction in the quality of goods and services without households perceiving it. Lacking both the awareness to clearly evaluate all possible outcomes of a choice and sometimes (but not always) access to relevant information, consumers may indeed experience difficulties in evaluating the quality of goods and services. This is, however, not new to economic theory. Three kinds of goods are generally found in mainstream economics: (1) goods whose quality can be  judged before use (“search goods”), (2) goods that people have to consume before being able to judge the quality (“experience goods”) and (3) goods whose real quality people are unable to discern even after consumption (called “confidence goods” or “credence goods”). Despite the exclusive focus of mainstream economic analysis on the first two kinds of goods, the third category is arguably, from the viewpoint of a heterodox/Post Keynesian theory of consumer choice, the most widespread. Even for common staple foods, consumers have thus a limited ability to objectively judge the quality of their purchase, resulting in certain difficulties in evaluating the quality of the product even after its consumption. Even when given the possibility of comparing between alternatives, the order in which people sample (taste or try) goods and services affects how they judge relative quality. This phenomenon relates to the (sixth) principle of nonindependence: the order in which people make choices influences the choices they make. In conclusion, choices influence preferences just as preferences influence choices. Melmiès (2017) explains how this behaviour can explain the reduction in quality that can be observed on some markets, be it fraudulent practices (adulteration) or non-fraudulent practices (product debasement, hidden price increase/product decrease, etc.). With non-fully rational consumers, competition between firms can take place at the expense of the quality of goods and services (contrary to the mainstream view that asserts competition improves the quality of goods and services) and thus at the expense of consumers themselves. Galbraith, the revised sequence and the sovereignty of consumers As a consequence, these principles can be linked to the theory developed by John Kenneth Galbraith. In The Affluent Society, Galbraith asserted that firms, through advertisement and marketing, have a huge degree of power upon

84  Jordan Melmiès consumers in their decision to make consumption expenses. Whereas in mainstream economics consumers are seen as sovereign decision makers, in Post Keynesian economics consumers are partially “passive” regarding their consumption choices. In other words, they are not as sovereign as neoclassical economics would state. This is a clear departure from the orthodox theory of choice, in which consumer sovereignty is of very high importance. At this stage, some economists would state that whether an alternative (Post Keynesian) theory of choice is needed may thus not appear as crucial as it is concerning the theory of the firm. As explained by Bunting (2003), the Keynesian theory of consumption is above all a theory of aggregate consumption, and the individual choice has no consequence. We will, however, make a softer claim, arguing that a way of describing the Post Keynesian spirit on the question is to say that firms’ behaviours are as determinant of household choices as households’ own preferences.

Post Keynesian microeconomics and economic policy Post Keynesian microeconomics provide an original understanding of the relationship between firms, prices, profit margins and competition (it also helps explain why empirical studies on the topic are often unable to empirically validate the basic mainstream linkage between competition and profit margins; see Melmiès, 2015). This theory offers a different descriptive view of the behaviour of agents (firms and households) in the economy. This descriptive alternative has a consequence on normative positions about economic policy. This is especially true of competition policy, when one endorses the “investment financing” theory we presented as the culmination of the Post Keynesian theory of the firm. If Post Keynesian micro theory were the “imperfectionist” one, there would then be no difference from mainstream political conclusions. This was regularly pointed out by Fred Lee: On the other hand, if the degree of monopoly declines, hence the profit markup and prices decline, the wage share will increase and so will income and employment. [. . .] From either mainstream or heterodox perspectives, monopoly or collective-cartel price fixing leads to market and system failure that can only be alleviated by introducing more competition. (Lee 2013a: 4) In the investment financing theory, however, profit margins are not a residual variable inherited from the firm’s market power, but are a strategic variable that has to be secured in the long run, regardless of the degree of competition. This point had already been noticed by Eichner (1976): The cash flow is not simply a residue or balance figure but is in fact a quantity deliberately chosen to enable the megacorp to achieve its investment goals. (Eichner, 1976: 13)

Microeconomics  85 Henceforth, orthodox political recommendations that promote competition enhancement in order to reduce prices, profit margins and hence improve wellbeing fade when faced with Post Keynesian microeconomics. Price cuts cease to benefit consumers and workers, since these price cuts (due to competition enhancement) will be obtained via cost reductions that affect the aggregate path of the economy without reducing profit margins. In that sense, an inverse relationship between competition and profit margins (which would thus be in line with mainstream economics) could only occur when increased competition changes the finance frontier (i.e. shifts it downward). For example, it would be necessary for increased competition to induce more external financing or to decrease profit distribution in the long run. In any case, this remains an exception. In fact, it is precisely for these reasons that Adrian Wood himself doubted that competition policies could effectively reduce profit margins: It is an implication of the present theory that measures which attack monopolistic and collusive practices by companies will have little or no effect on the distribution of income . . . the size of the share of profits depends primarily on the growth rate of national income, the investment coefficient, the external finance ratio, the financial asset ratio, and the gross retention ratio, none of which is affected by anti-monopoly policies in any systematic way. (Wood, 1975: 162–163) It is even conceivable that competition policies could lead to a rise in profit margins (as reported in some studies; see Melmiès, 2015), because a less secured market position (higher risk of losing sales) strengthened the importance of defending profit margins. In the Post Keynesian view, this argument can explain why several empirical studies struggle with a negative coefficient for the “concentration” variables (Melmiès, 2015).

Conclusion We have reviewed the key features to answer the question in the title of this chapter: is there a Post Keynesian alternative to the mainstream concerning microeconomics? As we recalled, the answer lies in two stages: is there a viable alternative, and is this alternative needed and why? The answer we gave is the following: this alternative does exist and is viable; this alternative is also needed, as it leads to descriptive and normative features that fundamentally depart from neoclassical economics. In short, the key features of Post Keynesian microeconomic theory are the following: • •

The basic goal of businesses is not profit maximisation but rather growth maximisation, constrained to a certain level of self-financing. Profit margins are not determined by the short-run degree of competition in the market, but are instead the outcome of two opposite forces: a

86  Jordan Melmiès

•

•

competitive constraint (the opportunity frontier), which results from long-run competition among firms in the market and competition among firms to conquer market shares of a growing but limited demand. This force drives prices and profit margins downward; and a financial constraint (the finance frontier), which links profit margins to the need to internally finance investment expenses that are necessary to meet growing demands. This force drives profit margins upward, given that firms want to maintain their ability to finance their development on the market. Consumers are not as rational and as sovereign as in the historical mainstream school. They are subject to limited/bounded/procedural rationality, and rely on simple rules of behaviour that lead to permanent deviations from the standard model; Theses descriptive alternative elements lead to political positions completely different from the usual neoclassical one on competition policy.

For the future, some research is needed to further develop Post Keynesian microeconomics in the following areas: first, an extended exploration of the self-financing of businesses and its implication for economic theory and economic policy (as mainstream theory always focuses on the choice between debt and equity issuance, as was the case in the Modigliani–Miller theorem); second, a better exploration of the theory of the consumer to have a better understanding of household choices and its implications for analytical macro models and policy implications.

Notes 1 For a discussion on the New Keynesian theory of prices and a comparison with Post Keynesian theory, see for example Melmiès (2010). 2 Kalecki will only reject profit maximisation later, at the end of his career.

References Ball, L. and Mankiw, N. G. (1994), “A Sticky-Price Manifesto,” Carnegie Rochester Conference Series on Public Policy, Vol. 41 (Dec.), 127–151. Ball, R. J. (1964), Inflation and the Theory of Money, George Allen and & Unwin, London. Basile, L. and Salvadori, N. (1984–85), “Kalecki’s Pricing Theory,” Journal of Post Keynesian Economics, Vol. 7, No. 2 (Winter), 249–262. Baumol, W. J. (1958), “On the Theory of Oligopoly,” Economica, New Series, Vol. 25, No. 99 (Aug., 1958), 187–198. Blinder, A. S., Canetti, E. R. D., Lebow, D. E. and Rudd, J. B. (1998), Asking about Prices: A New Approach to Understanding Price Stickiness, Russell Sage Foundation, New York. Bunting, D. (2003), “Consumption,” in King, J. E. (ed.), The Elgar Companion to Post Keynesian Economics, Edward Elgar, Cheltenham. Colander, D. C. and Landreth, H. (1996), The Coming of Keynesianism to America: Conversations with the Founders of Keynesianism Economics, Edward Elgar, Brookfield, VT.

Microeconomics  87 Crotty, J. (2002), “The Effects of Increased Product Market Competition and Changes in Financial Markets on the Performance of Nonfinancial Corporations in the Neoliberal Era,” Political Economy Institute, University of Mass. Amherst, Working Paper Series, No. 44. Crotty, J. (2003), “The Neoliberal Paradox: The Impact of Destructive Product Market Competition and Impatient Finance on Nonfinancial Corporations in the Neoliberal Era,” Review of Radical Political Economics, Vol. 35, No. 3 (Sep.), 271–279. Dallery, T. (2009), “Post-Keynesian Theories of the Firm under Financialization,” Review of Radical Political Economics, Vol. 41, No. 4, 492–515. Dallery, T. and Melmiès, J. (2014), “Price Competition, Inter-Firms Relationships, Bank Discrimination and Wage Inequalities: A Post Keynesian Perspective,” Revue de la regulation, Vol. 16, No. 2 (Autumn). Davidson, P. (1992), “Would Keynes Be a ‘New’ Keynesian?” Eastern Economic Journal, Vol. 18, No. 4, 449–463. Dullien, S. (2011), “The New Consensus from a Traditional Keynesian and a PostKeynesian Perspective: A Worthwhile Foundation for Research or Just a Waste of Time?” Économie Appliquée, Vol. 64, No. 1, 173–201. Eichner, A. S. (1973), “A Theory of the Determination of the Mark-Up under Oligopoly,” The Economic Journal, Vol. 83, No. 332 (Dec.), 1184–1200. Eichner, A. S. (1976), The Megacorp and Oligopoly: Micro Foundations of Macro Dynamics, Cambridge University Press, New York. Fontana, G. and Gerrard, B. (2004), “A Post Keynesian Theory of Decision Making under Uncertainty,” Journal of Economic Psychology, Vol. 25, No. 2 (Oct.), 619–637. Galbraith, J. K. (1958), The Affluent Society, Houghton Mifflin, Boston, MA. Georgescu-Roegen, N. (1954), “Choice, Expectations and Measurability,” Quarterly Journal of Economics, Vol. 68, No. 4 (Nov.), 503–534. Harcourt, G. C. and Kenyon, P. (1976), “Pricing and the Investment Decision,” Kyklos, Vol. 29, No. 3, 449–477. Kaldor, N. (1957/1980), “A Model of Economic Growth,” in Kaldor, N. (ed.), Essays on Economic Stability and Growth, Gerland Duckworth, London. Kalecki, M. (1936), “Pare uwag o teorii Keynesa,” Ekonomista, Vol. 36, 18–26; reprinted in: Osiatynski, J. (ed.), Collected Works of Michal Kalecki, Vol. 1, Capitalism, Business Cycles and Full Employment, Clarendon Press, Oxford, 1990, 223–232. Kalecki, M. (1937), “The Principle of Increasing Risk,” Economica, New Series, Vol. 4, No. 16, 440–447. Kalecki, M. (1939), Essays in the Theory of Economic Fluctuations, Allen and Unwin, London. Kalecki, M. (1940), “The Supply Curve of an Industry under Imperfect Competition,” in Osiatynski (1991), 51–78. Kalecki, M. (1941), “A Theory of Long-Run Distribution of the Product of Industry,” in Osiatynski (1991), 78–89. Keynes, J. M. (1936), General Theory of Employment, Interest and Money, MacMillan, London. King, J. E. (2012), The Microfoundations Delusion, Metaphor and Dogma in the History of Macroeconomics, Edward Elgar, Cheltenham. Kregel, J. A. (1971), Rate of Profit, Distribution and Growth: Two Views, MacMillan, London. Lavoie, M. (1992), Foundations of Post-Keynesian Economic Analysis, Edward Elgar, Cambridge.

88  Jordan Melmiès Lavoie, M. (1994), “A Post Keynesian Theory of Consumer Choice,” Journal of Post Keynesian Economics, Vol. 16, No. 4 (Summer), 539–562. Lavoie, M. (2014), Post-Keynesian Economics: New Foundations, Edward Elgar, Cambridge. Lazonick, W. and O’Sullivan, M. (2000), “Maximizing Shareholder Value: A New Ideology for Corporate Governance,” Economy and Society, Vol. 29, No. 1, 13–35. Lee, F. S. (1998), Post Keynesian Price Theory, Cambridge University Press, Cambridge. Lee, F. S. (2000), “Organizing the U.S. Post Keynesians and Macro-dynamics, 1971–1972,” Research in the History of Economic Thought and Methodology, Vol. 18C, 115–159. Lee, F. S. (2013a), “Heterodox Approach to Cartels and Market Competition.” Paper presented at the annual URPE meeting at the ASSA Conference, San Diego, CA, Jan. Lee, F. S. (2013b), “Competition, Going Enterprise, and Economic Activity,” in Moudud, J. K., Bina, C. and Mason, P. L. (eds.), Alternative Theories of Competition, 160–173, Routledge, Abingdon, UK. Lee, F. S. and Samuels, W. (1992), The Heterodox Economics of Gardiner C. Means: A Collection, M. E. Sharpe. Melmiès, J. (2010), “New Keynesians versus Post Keynesians on the Theory of Prices,” Journal of Post Keynesian Economics, Vol. 32, No. 3 (Spring), 445–466. Melmiès, J. (2015), “Effects of Competition on Profit Margins from a Post-Keynesian Perspective,” in Tae-Hee, J. and Zdravka, T. (eds.), Advancing the Frontiers of Heterodox Economics: Essays in Honor of Frederic S. Lee, Routledge, London. Melmiès, J. (2017), “Industrial Seigniorage: The Other Face of Competition,” Review of Radical Political Economics, Vol. 49, No. 2, 286–302. Milberg, W. (2009), “Pricing and Profits Under Globalized Production: A Post-Keynesian Perspective on U.S. Economic Hegemony,” in Lavoie, M., Rochon, L. P. and Seccareccia, M. (eds.), Money and Macrodynamics: Alfred Eichner and Post-Keynesian Economics, M.E. Sharpe Inc. Modigliani, F. (1944), “Liquidity Preference and the Theory of Interest and Money,” Econometrica, Vol. 12, No. 1 (Jan.), 45–88. Rancan, A. (2016), “The Wage-Employment Relationship in Modigliani’s 1944 Article,” European Journal of the History of Economic Thought, Vol. 24, No. 1, 143–174. Robinson, J. V. (1933), The Economics of Imperfect Competition, MacMillan, London. Robinson, J. V. (1952), The Rate of Interest and Other Essays, MacMillan, London. Robinson, J. V. (1970), “Harrod after Twenty-One Years,” The Economic Journal, Vol. 80, No. 319 (Sep.), 741–742. Robinson, J. V. and Wilkinson, F. (1983), “Ideology and Logic,” in Vicarelli, F. (ed.), Keynes’s Relevance Today, 206p, University of Pennsylvania Press, Philadelphia. Shapiro, N. (2005), “Competition and Aggregate Demand,” Journal of Post Keynesian Economics, Vol. 27, No. 3 (Spring), 541–549. Stockhammer, E. (2004), “Financialisation and the Slowdown of Accumulation,” Cambridge Journal of Economics, Vol. 28, No. 5 (1 Sep.), 719–741. Wood, A. (1975), A Theory of Profits, Cambridge University Press, London.

5

Microeconomics in a complex social world1 Michel S. Zouboulakis

Crisis and the insufficiencies of mainstream economic theory Although there are many and conflictual definitions of rational behaviour, mainstream microeconomic theory starts with the assumption that individuals usually (if not always) take the right decisions that maximise their individual goals (utilities and profits) and that somehow, all decisions balance each other to produce a generalised equilibrium between producers and consumers.2 So, whenever there is a persistent disequilibrium in in the markets, a neoclassical economist will always put the blame on human interference – public or private – that has somehow impeded the clearing processes of the market. From this point of view, an economic crisis is either the fault of the government and its interfering activities, or the result of the monopolistic behaviour of some influential agents who have violated the rules of the competitive game of the market, willing to maximise their individual profits at the expense of other competitors. Behind this perception lies a deep-rooted faith in the natural stability of the markets as a result of the non-coordinated and non-opportunistic behaviour of rational agents. Nothing describes better this firm socio-political conviction than the abuse of Adam Smith’s celebrated metaphor, as a self-important argument: Households and firms interacting in markets act as if they are guided by an “invisible hand” that leads them to desirable market outcomes. One of our goals in this book is to understand how this invisible hand works its magic. As you study economics, you will learn that prices are the instrument with which the invisible hand directs economic activity. (Mankiw, 2012: 11, emphasis added) The thing is that Adam Smith was referring to a geographically limited market where everyone knew everyone else, and where individuals exchanged under the moral constrain of the sentiment of “mutual sympathy” (Zouboulakis, 2014: 7). In contrast, Mankiw refers to the impersonal mechanism of the market and uses anachronistically an old rhetorical device to support the magic work of the market as it is. The vision of natural stability of the market is further self-protected by numerous assumptions and axioms that knowingly defy the reality, to serve the

90  Michel S. Zouboulakis theoretical requirements of the general equilibrium model. It is thus assumed that both consumers and producers act in an environment of unlimited and exhaustive information of the present and future conditions as well as being prompt to decide instantaneously under full certainty conditions (Stiglitz, 1994: 29). By the same token, perfect information deactivates the role of money as a precautionary means for future needs and as a means for speculation, depicting a false image of an automatic adjustment (Mirowski, 2010: 428). Except that in the real economy, decisions are taken by considering the existing sum of money (in circulating or fixed capital) and above all by calculating the eventual risk of every placement in the short or in the long run. In other words, money is not only an endogenous element of the markets – as we have known at least since Keynes – but also a fundamental cause for the instability and cyclical fluctuations of the economic system (Minsky, 1980; Wray, 2015). A crisis occurs when investors massively change their behaviour and start selling their accumulated assets, thus creating a sudden increase of demand for liquidity. As the financial crisis of 2008 demonstrated, markets are far from being efficient, in the sense that transactions are rarely made in prices that correspond to the exact value of the good or service that is exchanged (Tsoulfidis, 2010: 330). More generally, “the myth of the end of the business cycle is at odds with fundamental properties of the capitalist system” (Acemoglu, 2009). Failing to recognise the non-exceptionality of crises marks “a systemic failure of the economics profession” (Colander et al., 2009). These facts should lead economists to reconsider the whole idea of the theoretical representation of the market system as a closed and static equilibrium-seeking world. On the contrary, the basis should be that of an open and constantly evolving world, which is inhabited by interdependent and interacting individuals (Chick & Dow, 2001: 719; Kirman, 2009). Complexity of economic phenomena is not a situation to be studied at the final semesters of economic studies, after the accumulation of many static and simple systems, but should be introduced to students in the very first lectures of ECON 101. Insisting on the instruction of simple formal models based on the hypothesis of fully independent and non-interacting actors can be merely an introductory pedagogical device, which has to be clearly distinguished from real economic relations. In the real world, individuals are not omniscient and follow adaptive adjustments to reach their goals. Students need not be misguided because of the limits of the formal instruments economists use for their own research strategies. Keynes marvellously described the limits of this attitude some 80 years ago: It is a great fault of pseudo-mathematical methods of formalizing a system of economic analysis [. . .] that they expressly assume strict independence between the factors involved and lose all their cogency and authority if this hypothesis is disallowed; [. . .] Too large a proportion of recent “mathematical” economics are merely concoctions, as imprecise as the initial assumptions they rest on, which allow the author to lose sight of the complexities and interdependencies of the real world in a maze of pretentious and unhelpful symbols. (Keynes, 1936: 297–298)

Microeconomics in a complex social world  91 Many years before the recent global financial crisis, there were numerous reactions to the way economic theory is professed in higher education institutions. Back in the early 1990s, an official investigation in American colleges and universities pointed out the excessive practice of mathematical techniques in economics departments (see Report of the Commission on Graduate Education in Economics, 1991). In the conclusion, a universal concern was openly expressed: “The Commission’s fear is that graduate programs may be turning out a generation with too many idiots savants, skilled in technique but innocent of real economic issues” (Krueger et al., 1991: 1044–1045). This situation was the consequence of a longstanding tendency towards homogenisation in the economic curricula of American universities from interwar pluralism to post-war neoclassicism. The tradition of the Old Institutionalist School (Veblen, Hamilton, Ayres, Commons, Mitchell), as well as the tradition of economic history at Harvard (Schumpeter, Gershenkron, Kuznets) and other eclectic economists (J.M. Clark and F. Knight), was replaced by a monolithic way of thinking that changed the “professional ethos of economics” (Barber, 1997; Morgan & Rutherford, 1998: 1–25). The post-war era greatly facilitated the process of mathematical formalisation. A plausible explanation for this was the exceeding demand of the labour market for economists: business and research institutions wanted more technically skilled economists instead of broadly educated ones. The same demand for technical expertise was explicit in organisations such as the IMF, the OECD and, even more, the Rand Corporation.3 Thus, economics suffered in a peculiar way because it had established a type and degree of formalism that allowed research output to be assessed principally in terms of mathematical interest and elegance. Economists were judged and became employable for their aptitudes for statistical analysis or predictive models. (Hodgson, 2009: 1216) The homogenisation of economic knowledge was obtained through the elevation of formal technique, as against its substance. But, as Keynes wrote to Roy Harrod in 1938, “in economics . . . to convert a model into a quantitative formula is to destroy its usefulness as an instrument of thought” (quoted in Hodgson, 2013: 11). In that sense, the solution to the crisis in economic education concurs with the hunt for more useful Economics. In Europe, with many national traditions of economic thought and the lack of such organisations until recently, the tendency towards the homogenisation of Economics was less evident until the end of the 1990s. In Coats (2000), economists from ten Western European countries have studied the growth of higher economic education and postgraduate training, the professionalisation of the discipline, the evolution of research groups and institutes, the homogenisation of academic rules and norms of scientific publication and the role of the economist’s profession in the post-war economic and social development of Europe. One of the main conclusions was that despite the undeniable trend towards Americanisation, differences on a national level were still present in all European countries.

92  Michel S. Zouboulakis Nonetheless, there was also in Europe a bottom-up reaction movement of students in France in the year 2000, known as Autisme-Economie, supported by as many as 145 professors, and which has initiated a public debate in the columns of the daily newspaper Le Monde. This movement against excessive formalisation and the lack of pluralism in economics departments has involved many well-known economists such as Amartya Sen, Robert Solow, Olivier Blanchard, James Galbraith etc. An outcome of that reaction was the debate about the worthiness of standard microeconomic theory – i.e. the general equilibrium model – that many professors agreed should be simply abandoned (Guerrien, Keen, Dorman, Halevi in Guerrien et al., 2002). To summarise this debate, critics insist upon three things: (a) the lack of empirical and theoretical relevance of standard microeconomics, (b) its poor cognitive contain and (c) the use of abusive assumptions. Less negative critics believe that microeconomic theory is useless unless it captures “the complexity of interaction in economies” (Mayhew in Guerrien et al., 2002: 14, 7); that some central issues, such as the notion of choice and the supply and demand curves, have some pedagogical value insofar as they are incorporated into a teaching program that serves the general goal of promoting wellbeing (Nelson). More constructive critics hold that “basic economic reasoning” contained in microeconomic theory is truly important and worthy of being taught to students (Caldwell in Guerrien et al., 2002: 13, 3); and, also that “the core ideas of neoclassical ideas should not be excluded from the curriculum but placed alongside alternatives,” at least unless a more “adequate conceptualization of the human agency and decision making” appears (Hodgson in Guerrien et al., 2002: 14, 5); and finally that microeconomic theory can be “properly taught” with many applied economic problems as case studies, instead of the usual formalistic tools of General Equilibrium Economics (McCloskey in Guerrien et al., 2002: 15, 1). In a more recent paper, Colander (2005) went a step further, suggesting an end to the tension between what economists do in their research – complex, applied and empirical work – and what they teach in the classroom – simple, theoretical and abstract models. Taking the above into consideration, as well as the general malaise in our profession after the lack of anticipation of the global financial crisis, a significant reorientation ought to be made in the subject matter of teaching. We suggest next some changes in the orientation of teaching undergraduate microeconomics.

Teaching instructions for relevant microeconomics Some things are worth keeping from standard microeconomics – especially those inherited from Classical Political Economy – even though many things have to be revised in both the way and the material of teaching it. On the contrary, teaching heterodox microeconomics as against the mainstream, as has been suggested (Lee & Keen, 2004; Lee, 2005), will only confuse many undergraduates, to convince only the few already willing to hear an alternative narrative. Better to transform the official narrative with many amendments. May the reader allow us to

Microeconomics in a complex social world  93 advance some useful instructions, as a result of long-term personal teaching experience: 1

2

3

Give emphasis to economic substance over mathematical technique, as many scholars have suggested (McCloskey, 2000: 218; Hodgson, 2009; Krugman, 2009). That means giving priority to economic concepts instead of sacrificing realism for the sake of the technical apparatus (Fine & Milonakis, 2009: 135). Research and teaching should be appropriate to the relevant causal factors at work. An outstanding example of the doctrine of excessive commitment to analytical rigour, by all means, is the representation of completely rational individuals who are gifted with perfect foresight and yet unable to act before the imaginary auctioneer cries out equilibrium prices. The time has come to abandon the theory of price takers and profess the idea of price-making agents, as in Classical Political Economy. The whole idea of the firm as a technical unit that gathers instantaneously and without any transaction cost the best available resources to produce what the consumer needs, whenever a businessman foresees a profit in a particular industry, should definitely be replaced by the notion of firms as durable rent-seeking organisations with strong internal hierarchy. Recognise that individuals have limited cognitive and computational capacities in pursuing their economic interests and therefore rarely optimise; they mostly choose the solution that satisfies their aspiration level (as Henry Simon has shown). Additionally, recognise that economic decisions are often determined by “animal spirits – a spontaneous urge to action than inaction” (Keynes, 1936: 161–162; cf. Akerlof & Shiller, 2009: 5). In some cases, both consumers and investors are optimistic about the imminent future and do buy valuable things and invest in the stock market and in state bonds. In other cases, they are pessimistic and prefer not to act. The recognition of these facts will help the student to understand from the beginning of her studies that markets are endogenously unstable, no matter the soundness of the policy program of the government. Following Keynes, “we are merely reminding ourselves that human decisions affecting the future, whether personal or political, or economic, cannot depend on strict mathematical expectation, since the basis for making such calculations does not exist” (1936: 162–163). Admit, consequently, that though the aim of the economist continues to be to grasp the word in a quantitative way, not everything is quantifiable and measurable in economic phenomena. Usually in economic modelling, the non-measurable is simply ignored (Mayer, 1996). So, many culturally determined behaviours that greatly affect entrepreneurship, saving, investment and even consumption are not taken into account. Concisely put, Akerlof and Shiller concluded their bestselling book saying, “evidence abounds for the animal spirits discussed in the first five chapters: confidence, fairness, corruption, money illusion, and stories. These are real motivations for real people” (2009: 174). Confidence, fairness, corruption and stories – i.e.

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widespread social representations of an era – are culturally determined social norms. Relevant literature on the influence of social norms, custom, routines and habits goes far beyond Nelson and Winter (1982) – to J.S. Mill and Alfred Marshall (cf. Zouboulakis, 2015) – and has grown significantly in the last 20 years, to a degree that it is impossible to ignore when dealing with human behaviour (cf. Hodgson, 1997, 2003; Schlicht, 1998; Hardin, 2002; Khalil, 2003). Preserve some crucial economic microeconomic concepts, many of which have survived throughout 240 years of economic thought (since 1776). Hence, we should continue to introduce students to the concepts of opportunity cost, scarcity conditions, productive factors, division of labour and productivity, marginal increase of production, diminishing returns, increasing returns to scale, producer’s surplus, the law of demand, price and income elasticities, variable and fixed costs, the functions of money, money illusion, profit and the remuneration of capital, interest rate, rate of wages, competition and market power, concentration of capital, product differentiation, price discrimination etc. The historical persistence and explanatory power of these theoretical concepts reinforces the scientificity of economic discourse in the minds of students more effectively than a solid logical construction of mathematical equations describing an imaginary world. The fact that some of these concepts are at the core of every neoclassical textbook does not mean they belong to that tradition as reported (Lee & Keen, 2004). In their majority, they belonged to the old Classical tradition and even before (e.g. the law of demand dates from 1696, the law of diminishing returns from 1815 etc.). Analyse thoroughly the chapters of mainstream theory that focus on the strategic interdependence between economic actors, such as duopoly, monopolistic competition, and interactive game theory. Perfect competition should be only mentioned as an exceptional market and merely in order to introduce the idea of large competition prevailing in some international commodity trade markets, the fish market and the stock market. Emphasis should be put on the applied fields of microeconomics in order to reveal the interaction between hard-core economic concepts and the institutional structures of the real economy. In the fields of industrial economics and agricultural and labour economics, there are plenty of “good quality data that can be directly related to variables that appear in the corresponding economic theories” (Backhouse, 1997: 215). Offer an important part of the course in describing concretely market failures using real examples of externalities in production and consumption. The huge Law and Economics literature is a goldmine of very instructive case studies, let alone their tendency to overextend economic reasoning in other social fields. Analogously, one can insist on problems of agency, of asymmetric information, adverse selection, moral hazard and inefficient allocation of property rights using examples from the world of real business. The historical evolution of firms and the knowledge of their complex internal

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organisation since the first joint-stock companies of the late sixteenth century would be a fruitful way to demystify the legend of full competition between small and powerless enterprises who are supposed to act as if they were individuals with a single mind or a single purpose. Finally, admit that the economic world is a complex system and that, as such, it contains emergent properties that arise from the collaborative functioning of its actors and do not belong to any individual actor of that system. These properties cannot be explained individually but only in reference to the social context in which they emerge (Colander, 2005: 250; Keen, 2017: 31). Accordingly, the institutional structure matters in both making things possible and shaping transactions, and that should be clearly explained to students. As Joan Robinson (1977: 1320) wrote, “micro questions – concerning the relative prices of commodities and the behaviour of individuals, firms, and households – cannot be discussed in the air without any reference to the structure of the economy in which they exist, and to the processes of cyclical and secular change.”

Nevertheless, to construct a relevant course in microeconomics, economic knowledge is not enough as long as it rests on a partial view of the economic world. Therefore, to elevate the substance of microeconomic analysis, we need to broaden our perspectives and to strengthen its content with material from other social disciplines that deal with socially interacting individuals.

With a little help from our friends Learning from the past To offer a teaching more relevant to the real economy, the first thing to do is to strengthen the place of both the economic history and the history of economic thought. As to the former, the economic historian and Nobel Prize winner in Economics Douglass North wrote that economic history is a depressing tale of miscalculation leading to famine, starvation, defeat in warfare, death, economic stagnation and decline, and indeed the disappearance of entire civilizations. And even the most casual inspection of today’s news suggests that this tale is not a purely a historical phenomenon. (North, 2005: 7) Thus, a pedagogically fruitful way to deal with the crisis of 2007–2008 is to compare it with the depressions of 1873–1896 and 1929–1939. Students will then have the opportunity to realise many of the dimensions of the actual crisis by knowing how the system has responded and changed in many aspects in order to overcome the previous crises. We mean not only the changes in policy priorities and in money and banking regulation but also the changes at the microeconomic level in industrial

96  Michel S. Zouboulakis organisation, in labour protection, in consumer activities etc. Other episodes – such as the “tulip mania” in 1637 and the “South-Sea bubble” in 1720 – also possess a strong pedagogical value. Needless to say, the specifics of the so-called Industrial Revolution are of huge importance for understanding the fundamental genetic characteristics of the economic system we still live in. Young economists should learn that conceptions of how best to run the economy have changed dramatically with major economic and financial crises. This will give them the feeling of dealing with a science that is not fixed through the ages but that rather has an historical character, a past, a present and a future (Cf. Hodgson, 2001: 5). Additionally, more emphasis should be put on the history of economic thought, a sub-discipline that offers an absolute advantage in discovering new ideas and eliminating incorrect perceptions, as many economists recognise. Arjo Klamer and David Colander (1990) have suggested that one of the main reasons why only a very small minority of young economists has a “thorough knowledge of the economy” has to do with their lack of understanding of the past of economic thought and economic history (Cf. McCloskey, 1985: 183). To that, Paul Krugman (1996: 140) observed that “when if one tries to reinvent a field without knowing what came before, one is too likely simply to reinvent old ideas, most them bad.” Geoffrey Harcourt also wrote that “often the same issues arise, and then it will be found that the greats of the past had something of lasting value to say about them” (in Fullbrock, 2003: 70). Even more emphatically Ronald Coase (2002) said: It is a striking [. . .] feature of economics that it has such a static character. It is still the subject that Adam Smith created. It has the same shape, the same set of problems. Now of course we’ve made improvements, we’ve corrected some errors, we’ve tightened the argument, but one could still give a course based on Adam Smith. Furthermore, teaching the evolution of economic thought is an excellent means to promote the idea of scientific controversy and theoretical pluralism within our discipline. Economics and the social sciences in general are constantly in a state of internal division in many rival schools of thought, with such great differences that one may certainly speak about competing “Scientific Research Programs,” in Lakatos’s sense. The study of how different “Programs” interact and compete with one another is a valuable starting point for the historical analysis of major “problem-shift” episodes, like the Marginalist or the Keynesian “revolutions” and the birth of alternative approaches to economics.4 Debates and quarrels are natural in every scientific field. Yet, a student in physics, chemistry or biology is always able to get the state of the art by reading the latest edition of any bestselling textbook. Quite the opposite, in the social sciences, differences exist in textbooks on not only the presentation of the major themes and the focus upon them but also the methods and techniques, the definition of major concepts and even the demarcation of the domain and the main purposes of every social discipline itself. The simple recognition of this de facto pluralistic situation should lead the teacher of economics to deal with equal respect the competing SRPs and theories,

Microeconomics in a complex social world  97 to the best of his knowledge. Complementary to the traditional teaching methods of “talk and chalk” (Becker, 1997), we can follow Raveaud (in Fullbrock, 2003: 67) who suggested “to teach through controversies,” meaning to present before the students the competing views on recurring economic problems. The history of economic thought is full of controversies that are still relevant. Raveaud quotes the example of the Vining–Koopmans controversy in the late 1940s (more widely known as the “measurement without theory controversy”) about the use of statistical data without a proper theory of economic behaviour. It was concluded that inductive inferences based on data collection are only good for establishing empirical relationships unreliable for prediction or policy purposes (cf. Boumans and Davis, 2010: 38–41). A more significant example for microeconomics is the “fullcost controversy.” Initially, Robert Hall and Charles Hitch in 1939–1940 contested empirically the profit maximisation hypothesis, claiming that entrepreneurs set their prices by comparing not the marginal cost to the marginal revenue, but by simply matching up to a rough notion of total cost of the market price. Richard Lester, seven years later, also contested the empirical relevance of the marginalist principle, initiating a huge debate in the American Economic Review from 1946 to 1953, involving economists such as Machlup, Stigler, Eiteman, Apel, Bishop, R.A. Gordon, Haines, Bronfenbrenner, Reynolds, Papandreou, Kaplan, Ritter and others.5 Even more instructive is the “Friedman–Samuelson–Machlup debate” in the early 1960s, also known as the “positivist–descriptivist controversy” about the empirical status of the maximisation hypothesis. As is known, the controversy unfortunately concluded with the prevalence of Friedman and his thesis that “theories are good for predictions only.” In his sense, it is useless to criticise the unrealistic nature of economic assumptions like economic rationality, since the aim of any assumption is to provide only the basis for successful predictions. This is the meaning of the notorious F-twist: “the more significant the theory, the more unrealistic the assumptions.” Finally, there is the Galbraith–Becker–Stigler debate in the late 1960s on the role and functions of advertising in shaping consumers’ preferences and conditioning their needs (Hodgson, 2003: 160; Komlos, 2014: 35). Psychology matters A second thing to do is to enrich the subject of microeconomics with the findings of psychology and behavioural science in particular. British students even claimed so publicly, sending a “Letter to Her Majesty” in 2009. Psychologists like Daniel Kahneman and Amos Tverskya put emphasis on experimentally observed behaviour using social, cognitive and emotional factors in understanding the economic decisions of individuals and organisations when performing economic functions. Kahneman and Tversky (1979) provided experimental evidence showing that people prefer lower but more certain gains, rather than greater and more uncertain ones. In other words, people seem to be risk-averse over gains and risk-lovers over losses. They have also demonstrated that individuals are treating gains and losses asymmetrically, meaning that they do not assign the same value to expected utility and disutility. A series of experiments was put forward aiming at exploring the

98  Michel S. Zouboulakis heuristic the individuals follow and the biases to which they are prone in decisionmaking under uncertainty. Results from laboratory experiments have shown that individuals tend to be error prone and possibly irrational, suffering from “mindless behaviour,” “insensitivity to sample size,” “base rate neglect,” “misconceptions of chance,” “cognitive illusions,” “confirmatory bias,” “belief perseverance,” “anchoring” etc. (Rabin, 1998: 24–30). Other experiments confirmed the fact that decision-making is shaped by “framing effects”: the semantic description of possible outcomes greatly affects the individual’s choice; decision makers are inclined to accept passively the formulation of different choices and are particularly influenced by the default option. “Framing effects” are closely related to the phenomenon of “preference reversals” discovered by Lichtenstein and Slovic in 1971. These two psychologists have shown that gamblers make inconsistent choices by reversing the order of their preferences, once the choice between two alternative lotteries is reformulated (see Hausman, 1992: 227ff.). Therefore, the observation of consumer and producer behaviour under different market structures and choice frames gave birth to a more realistic representation of rational economic behaviour. These massive empirical findings cannot be ignored and should be incorporated into microeconomics textbooks, even at the expenses of a fictional generality. Social exchanges The third thing to do to enhance the empirical relevance of microeconomics in the classroom is to adopt a socially broader view on economic agency. Mainstream economic theory professes the idea that individuals live alone in a pre-social state of society and act in isolation from other human beings (Arnsperger & Varoufakis, 2006). The mainstream view, for theoretical, technical or ideological reasons, denies in fact the very essence of inter-personal exchanges between interacting individuals. However, individual actions are not a matter of atomistic behaviour emerging from a continuous interplay between neural systems inside the decision maker’s mind, but are essentially the result of social interaction with other individuals. Thus, major economic issues – like externalities, money illusion and trust – do affect greatly economic decisions and subsequent transactions. There has never been an economic exchange between atomistic humans in social vacuum conditions (Komlos, 2014: 68). Quite the contrary, humans at all times had the capacity for dividing up tasks, communication, interaction and exchange inside the specific social context they lived in. Even the most intrinsic preferences “do not magically appear into people’s minds” (Duina, 2011: 55). Tastes and preferences appear and evolve inside particular social contexts, and therefore should be openly discussed despite Becker and Stigler’s famous prohibition. As Kenneth Arrow (1994: 2) has suggested, to recognise the action of the social context upon individual behaviour is to identify “the ineradicable social element in the economy.” Or even better said, “rational deliberation is not possible except through interaction with the fabric of social institutions” (Hodgson, 2003: 163). Subsequently, economic sociologists such as Mark Granovetter, Neil Smelser, Richard Swedberg, Carlo Trigilia, Viviana Zelizer and many others have produced

Microeconomics in a complex social world  99 over the last decades a significant theoretical and empirical work that deepens our knowledge about the way economic transactions are really made (Granovetter & Swedberg, 2001). Findings about the weight of non-material motives in economic transactions; the significance of the system of rotating credit associations in developing countries; the role of informal arrangements and cooperation between industrial firms; the meaning of credit and commercial circuits among family members and other personal connections; the ways that different societies actually understand the meaning of “ownership” – all of these findings demonstrate the narrowness of mainstream analysis of economic exchanges, which has expelled outside the study of economic phenomena many significant elements of social structure that really shape the efficiency of economic outcomes. Initial endowments, property rights and the distribution of wealth in general, preferences, social norms and habits, culture and ideology should not be taken for granted considering that they are somehow internalised in every individual’s pattern of behaviour. They need to be exposed and revealed to the students, to give them an idea of the omnipresent social interaction in market exchanges. These unquestionable facts beg for a broader methodological departure than strict individualism as well as for a less autarchic economics, separated from other social disciplines. Above all, these findings stress the partiality of the economic analysis. Dealing with economic phenomena as they were independent from their social substratum is the source of the economist’s inability to capture the entire economic “realm” in modern societies. To do so, economists need to reconsider the whole idea of economics as an isolated and fully autarchic science. As Ronald Coase (2002) recognised, “economists should enlist the support of lawyers, sociologists, anthropologists, and others in our work in order to understand why transaction costs are what they actually are. It’s the opposite of economic imperialism.”

Economics as a useful science More than 30 years ago, Colander (1987) asked provocatively “Why Economists Aren’t as Important as Garbage Men.” He answered that economists care too much to convince each other, instead of caring to convince the public and the decision makers. In that sense, Colander asked economists to be more involved in social matters instead of being “outsiders,” in order to be as useful to society as dentists or engineers, or even garbage men. In contrast, when an outstanding neoclassical microeconomist, Hal Varian (1997), asked “what use is economic theory?” he claimed that although “it offers a useful insight in explaining an economic phenomenon” (ibid.: 115), “no theory in Economics is ever exactly true” [sic], since – following Friedman – it focuses unilaterally into one dimension of economic phenomena. But this is incompatible with Varian’s own initial claim that “economics is a policy science and, as such, the contribution of economic theory to economics should be measured on how well economic theory contributes to the understanding and conduct of economic policy” (1997: 109, emphasis added). This acknowledgement should lead Varian in the opposite direction than the one he opted for. What a policy sensible theorist should do is to promote theories based

100  Michel S. Zouboulakis on assumptions that sufficiently correspond to the operating frame of the real economy (Cf. Rosenberg, 1994: 233). Colander et al. (2004) have reported that mainstream economics changed during the last two decades before the crisis. Ante-crisis empirical surveys among graduate students in economics in seven major American universities (Colander, 2005: 181. Cf. Colander, 2005a) showed a promising change in their perception of the importance of knowledge of the real-world economy, as against formal modelling, although they continue to complain about the lack of policy relevance just as they did 20 years earlier (Klamer & Colander, 1990; Krueger et al., 1991). Judging from the lack of apprehension of the biggest economic destabilisation since 1929, mainstream economics apparently haven’t changed enough! Colander et al. (2004) made the distinction between orthodox and mainstream economists, in order to identify those neoclassical economists who are critical of the standard theory and work “at the edges” of orthodoxy.6 Yet, it is excessively unsafe to announce the arrival of a “Kuhnian shift” by this time; the suggestion that we are living the moment of the gradual transition time lag from the old conception of the market economy as a self-equilibrating mechanism to a new one “centred on dynamics, recursive methods and complexity theory” is too good to be true. Core microeconomic theory today continues to suffer from the nineteenth-century “Physics’ envy” and has shared the same “icon of scientificity” since Jevons and Walras (Mirowski, 1989). A very recent bibliographic survey of some 443,000 articles, before and after the last crisis, has revealed that “unlike the Great Depression of the 1930s, the current financial crisis did not lead to any major theoretical or methodological changes in contemporary economics” (Aigner et al., 2018). There is still lot to be done, both in research and in teaching towards more relevant and therefore more useful microeconomics. After all these considerations, what should a good textbook of microeconomics look like? We believe that it should offer sufficient space to the history of our discipline, analyse promptly the factors of production and provide a realistic description of the market mechanism and pricing of goods and services; it should also introduce the student to a solid theory of capital and profit under different market structures, as well as offer a clear overview of the labour market. An example of all that was proposed four decades ago by Joan Robinson and John Eatwell (1973), although it contained some obsolete chapters on socialist planning. Other fine works which are serving the same purpose are Understanding Microeconomics by Robert Heilbroner and Lester Thurow (1984) and the more recent Understanding Capitalism by Samuel Bowles et al. (2005). Fred Lee (2017) has also left a textbook of “heterodox microeconomics” that explains the economy as the social provisioning process focusing on the structure and use of resources, the structure and change of social wants, the structure of production and the reproduction of the business enterprises. Teaching a more relevant theory that is both theoretically sound and policy relevant will help provide a better understanding of the economic phenomena at the level of the firm and the household. Then, one should keep in mind the right questions to answer: what is production and consumption for? By whom? For whom?

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Notes 1 This chapter revises and expands Zouboulakis (2017). 2 For the evolution of the meaning of economic rationality, see Zouboulakis (2014). 3 Not accidentally, among many other illustrious scientists, far too many brilliant economists worked in RAND Co. and, even more significantly, ten of them won the Bank of Sweden’s Prize in the memory of Alfred Nobel. These were (alphabetically): Arrow, Aumann, Markowitz, Nash, Phelps, Samuelson, Schelling, Shapley, Simon and Williamson. 4 For a concise evaluation of SRP methodology in economics, see Backhouse (1997: 88–95), Boumans and Davis (2010: 108–114). 5 See Hausman (1992: 158–162), Tsoulfidis (2010: 241–242), and Zouboulakis (2014: 63–67). 6 In their survey, Colander et al. (2004: 493) include in this category: Paul Samuelson, Kenneth Arrow, Robert Solow, Thomas Schelling, Amartya Sen, Joseph Stiglitz, Chris Sims, Michael Woodford, George Akerlof, Richard Thaler, Anne Krueger and Jagdish Bhagwati.

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Teaching macroeconomics after the crisis1 Irene van Staveren

Introduction The popular British economic magazine the Economist asked in July 2009, when the crisis was at its depth, what had gone wrong with economics? This was quite surprising coming from the Economist, because that magazine generally favours the orthodox approach to economic theory and policy, in particular free markets and neoliberal policy. The 2007 financial crisis opened a window of opportunity for pluralist economics. I grabbed this opportunity to publish a pluralist economic textbook – the book I would have liked to have had as a student. The dominance of one theory When I studied economics at Erasmus University Rotterdam, I only gradually became aware that I was being taught a particular theory, namely neoclassical economics. I remember my first discovery of the existence of Keynesian economics and its apparent disagreement with what I was being taught, when rumours went around that the professors on the eighth floor of the Economics Department in Rotterdam and those of the other floors were not on speaking terms. Another instance of my growing awareness that one theory dominated my education was when my favourite class, history of economic thought, was scheduled on Monday mornings at nine o’clock and was the only course for which we were not required to sit exams. Together with a friend, I read the chapters in our history of economics book that were skipped in class and we discovered the basic ideas of John Stuart Mill and Karl Marx. From then on, we became the outsiders among our fellow students, eventually doing our MA theses on unorthodox topics and using unorthodox methods, my friend in Mexico and myself in Indonesia. I decided to go for a PhD in economics and wrote a proposal, partly inspired by the writings of development economist Amartya Sen. The other part of my inspiration came from my engagement with feminism, through which I learned about the gender division of labour and caring work. I realised that economics had several blind spots, of which ethics, power and gender were only three. Then followed many rejections of my PhD research proposal by professors of economics. Nobody I approached was willing to be my supervisor – they advised me to go to sociology,

Teaching macroeconomics after the crisis  105 anthropology, political science or gender studies. And when I found an interested professor abroad, I could not find the funding to study there. After eight years, a Dutch professor of economics who had spent several years at universities in the US came back home. He had interviewed Sen and had done unorthodox work related to ethics. We met at the same university where I had received my undergraduate training, and he made me cry by simply listening to me and nodding, intrigued at hearing my bold plans. I quit my job, did my PhD and then was offered a job at the institute where I still work, with much pleasure and gratefulness for its openness to pluralism in economics: the International Institute of Social Studies, which later became, ironically, part of my alma mater, Erasmus University Rotterdam. But for teaching, still no pluralist textbook existed, and I increasingly felt this as a binding constraint for my teaching. Even until today, the most popular economic textbooks almost exclusively present the orthodox, that is, neoclassical economics perspective, as the default theory of economics. They teach that economics is about choices under conditions of scarcity, simplifying human rationality, values and complexities in the social and natural context. Popular textbooks refer very little to other theories, and if they do, often only to concepts that have been adapted to fit neoclassical economics. There are very few introductory economics textbooks, which include serious attention to a diversity of economic perspectives. Moreover, all available introductory textbooks, orthodox and heterodox, employ a dominant Western economy perspective. They take the US economy or a different developed economy as the standard. I felt that there was something very wrong with how economics was being taught. Going back to the question asked by the Economist: where did it go wrong? There are various answers to this question, and economists disagree about details. But what is generally agreed upon is that the dominant neoclassical economic belief in efficient markets, with fully rational (read: self-interested) agents, prevented the large majority of economists from seeing the bubble in the housing market and the systemic risk in the banking system of the enormous increase in mortgage-backed securities connected to this bubble. This blindness of most economists was caused by the dominant economic theory to which most economists adhere. It is precisely this theory, neoclassical economics, which has contributed to the self-fulfilling prophesy in the economic behaviour in assets markets and its governance with an unexpected and very serious side effect. Many economists agree that this theory and the lack of regulation combined with financial models based on it, which is a major causal factor behind the 2007 financial crisis in the developed world as well as the 1997 financial crisis in Asia. More evidence that it was the dominant theory that got it wrong is that the key policy response to the crisis by governments was not a neoclassical one but relied on other theories, that had been up to then marginalised in economic teaching and research. First, the key Post Keynesian tool: increased public expenditures to stimulate economic recovery. Second, institutional reform of banks and banking regulation. The self-fulfilling prophesy of neoclassical economics, which contributed to the crisis, has two dimensions. First, in neoclassical economics, all economic agents are supposed to act entirely independently and in their self-interest (even when

106  Irene van Staveren they do things for others). They are assumed to ask themselves all the time: wiifm (what’s-in-it-for-me)? Second, neoclassical economics assumes that all economic agents rely on individual, probabilistic risk of gain and loss for each individual decision they make. At the macro level, neoclassical economists recognise that individual risk adds up to aggregate risk. But they ignore systemic risk. This is interlinked risk through social interaction within and between banks, households, firms and the government. These linkages of risk reinforce individual risk so that aggregate risk becomes much larger than simply the adding up of your risk and my risk. Together, these two neoclassical economic assumptions which most textbooks teach – individual self-interest and independent risk – have resulted in economic models, business strategies and policy advice that have increased risk levels in the financial sector worldwide. Moreover, the financial sector has partially shifted the downside risk to others through self-interested behaviour and inequalities of power: to the taxpayer, the unemployed and the poor. The financial crisis and its aftermath had a variety of causes, and the self-fulfilling prophesy of the two key foundations of neoclassical economics were clearly part of these. Although heterodox economists had warned of increasing instability, neoclassical economists were taken by surprise by the unfolding events. In the words of Alan Greenspan, the former Chair of the Federal Reserve Bank, in a hearing of the US Congress in October 2008: “Yes, I found a flaw . . . in the model that I perceived is the critical functioning structure that defines how the world works.”2 He added that it was the crisis which made him realise that the model does not live up to what it is supposed to do, namely, providing reliable forecasts in a complex world. “We have this extraordinarily complex global economy, which as everybody now realizes is very difficult to forecast in any considerable detail.” On a TV show in October 2013, Greenspan even made a plea for a capital reserve ratio for banks of at least 20%. The EU only required 3% then. Of course, others, like the British economist Keynes who had studied the 1929 financial crisis, had realised this long before him. Frederic Mishkin, a well-known professor at Columbia Business School and author of an American textbook on finance, also realised only after the crisis hit that his belief in rational and efficient markets was unjustified. In a neoclassical analysis of Iceland’s economy, he had claimed that Iceland enjoyed financial stability, only two and a half years before the financial meltdown of that country.3 Both Greenspan and Mishkin, as well as all other neoclassical economists, were taken by surprise by the crisis. And they said that no one could have seen it coming. This last claim is wrong. There were whistle blowers within the financial system whose warnings were dismissed. And there were heterodox financial economists who had warned of a crisis for five years. The online Real-World Economics network, with 11,000 members, has, in response to the “we-could-not-know” claim, awarded the Revere Award to three economists who have strongly warned about a serious crisis.4 The winner was Steve Keen of the University of Western Sydney, Australia. He had published a strong critique of neoclassical economics (Keen, 2001), but he went further. In 2006, he started a website on the increasing debt problem in the US and published monthly updates. The second prize was awarded

Teaching macroeconomics after the crisis  107 to Nouriel Roubini of New York University. In the summer of 2005, he predicted that real home prices in the US would fall by 30%, and a year later he warned that this could trigger a crisis. The third prize went to Dean Baker, of the Centre for Economic and Policy Research in the US, who warned about a housing bubble in 2002 and 2004, noting that the ratio of mortgage debt to home equity was at a record high in 2003. Economics teaching The second part of the question asked by the Economist, namely about economic knowledge and teaching, is that the crisis somehow would change the teaching that self-interest and spread of risk help markets to flourish. The Economist hoped – optimistically or naively – that the crisis would automatically lead to a correction of economic theory and economic teaching. Unfortunately, in five years very little had changed in economics, even though heterodox economic theories have been around longer than economics as an independent discipline. And even though it was heterodox economic policies which had been implemented in reaction to the crisis. So, somebody had to re-write the economic textbooks to teach students the richness, diversity and policy relevance of heterodox economic theories. Despite wide variation, a key difference of heterodox economics is that it does not share the neoclassical assumptions of individual self-interest, independent risk, market equilibrium, and independence of economic behaviour. Instead, heterodox theories assume that economic agents behave more like real-world men and women, interdependent and with a variety of motivations, in real-world contexts with fundamental uncertainty and interdependent risk, driven by social-level phenomena such as power, caring, status, beliefs, cooperation and norms. This should inform economic teaching, as argued by Robert Shiller (2010: 407), who was among those who predicted the crisis: For me, alternative views that must be incorporated in our teaching include those promoted by the other social sciences: psychology, sociology, political science, and anthropology. For me, maintaining a proper perspective on alternative views means also incorporating historical analysis. For me, too, we also must keep in view the fundamental importance of institutions – our established organisations, practices, laws – and remind our students that these must be taken into account before judging any economic model. Why has the crisis not led to a victory of heterodox economics over the orthodoxy? That is a good question. But if it were so easy for an economic crisis to simply change the supply of economic analysis and teaching, and that students would then simply adapt their demand to it, we would again assume that markets would do what they are ideally supposed to do in neoclassical economics. We would still believe that market supply creates its own demand, resulting in an equilibrium in which everyone benefits from an allocation of scare resources that is the most efficient as possible. But the crisis has demonstrated clearly that markets often are

108  Irene van Staveren not up to this task . . . Instead, neoclassical economics has suffered a blow, but yet remains dominant. In the view of New Keynesian economist Paul Krugman, some heterodox insights are now taken on board by some neoclassical economists in high-level policy positions, and this should be seen as a victory.5 But this add-on approach by mainstream economists is not the same as a level playing field for a diversity of economic theories and policies. Economists are just like people. They try to hold on to their worldview and put in much effort to protect their vested interests as academics, policy advisors and teachers based on the skills they have acquired and invested in. Moreover, the teaching of neoclassical economics at universities in the developing world, with Western textbooks and professors with degrees obtained at Western universities, and supported with training courses by economists from the World Bank and IMF, limits the space for heterodox learning worldwide. But there are signs that justify the Economist’s optimism that the crisis has helped to change the dominance of neoclassical economics teaching. The menu of economic policies has broadened in response to the crisis, and students demand knowledge about this because they hear about it in the news. The curriculum of finance courses at prestigious business schools now pays more attention than before to the social responsibility of banks.6 And in-depth heterodox economic studies on the causes of the crisis receive more attention than heterodox research did before the crisis. Heterodox economists, plus a few neoclassical economists who want to look for answers to the painfully revealed flaws in the dominant theory, have set up think tanks and networks to cooperate in research, policy advice and teaching for an economy that is more stable and equal, less wasteful and better at contributing to livelihoods for all. For example, the network IDEAS was initiated in India, a forum for heterodox economists from the developing world. It was this forum which first showed the parallels between the US-originated financial crisis on the one hand and the earlier Asian financial crisis. And the same forum has demonstrated the marked differences in policies by the IMF towards Asia then, reinforcing enormous economic losses of income, jobs and businesses, and IMF policy towards the US and EU now, where the IMF supports state assistance for banks and accepts high government budget deficits in order to stimulate the economy. The main demand for change in the economic curriculum comes from students. Before the crisis, it was groups of PhD students of economics who had already raised critical questions about the dominance of neoclassical economics and mathematics in their education. This resulted in what first became known as the PostAutistic Economics Network and later turned into the World Economics Association with its online newsletter Real-World Economics Review.7 Since the crisis, many more initiatives have emerged, all over the world. Students at the University of Manchester in the UK sent a petition to the Economics Department asking for more real-world economic skills training. They also set up the Post-Crash Economics initiative with a new course, which the university, however, decided not to accredit.8 The International Student Initiative for Pluralism in Economics includes many associations of economics students from more than 30 countries, including

Teaching macroeconomics after the crisis  109 from India, Brazil, Russia, Pakistan, the US and the Netherlands.9 They published an open letter titled “Rethinking Economics.” The University of Pretoria, in South Africa, has set up an initiative called the “Human Economy” at the Faculty of Humanities to contribute to a more human economics.10 The Institute for New Economic Thinking (INET) supports a curriculum called CORE: Curriculum Open-access Resources in Economics.11 But this has rightly been criticised for not being ambitious enough.12 I realised that we need a new textbook that does not merely modify neoclassical economics and adds a few new insights. A pluralist textbook was needed that builds on the hitherto marginalised but solid, renowned schools of thoughts in the discipline. Schools of thought that had delivered various Nobel Prize winners, such as Gunnar Myrdal, Amartya Sen and Elinor Ostrom. The main strength of heterodox economics, that its analysis is closer to realworld people and contexts, is also considered a weakness because it does not allow for the neat, closed mathematical models with probabilistic economic predictions that so many economists seek. But neoclassical economics also has not lived up to this idealistic criterion for judging economic theories: economic prediction is finally agreed to be unattainable – as Greenspan acknowledged, the economy is far too complex to be able to predict outcomes of prices and output. Heterodox economics was never much concerned with predictions and is more open-ended, accepting that economic reality is complex and uncertain. Heterodox economics takes a more realistic view of both human behaviour and social processes and structures, such as power, opportunism, short-sightedness, cooperation and fairness. It does not reduce these complexities to neat mathematical models and mathematically calculable market equilibriums. Heterodox economists would rather be roughly right than precisely wrong. So, a genuinely pluralist textbook should have much less emphasis on math and formalism and much more on understanding real-world economic processes. I set out to do this and delivered a textbook of pluralist economics (van Staveren, 2015) and later a free online course.13 The book presents both heterodox and orthodox perspectives on the economy, showing their respective weaknesses and strengths and why these matter. Pluralism means good science. It involves the space for competition between theories. But, more importantly, pluralism creates the room for complementary explanations, which are context-dependent. That is precisely why this book provides a wide diversity of contexts, with many realworld examples. The structure of the book is pluralist – with all standard topics of a textbook presented through four theoretical lenses. These are, from broad to narrow, social economics, institutional economics, Post Keynesian economics and the idealised perspective of neoclassical economics, which students will recognise as applicable only to specific static and stable situations. In the chapter for this book on alternative economic theories, I will show how the textbook deals with several macroeconomic topics: the macroeconomic flow, wellbeing and poverty and economic growth. I will do so by ignoring the neoclassical economic perspective here, for the sake of space. I will only present the three alternative perspectives mentioned above. The text that follows consists of excerpts from the textbook with some adaptations for the reader of this book. For example,

110  Irene van Staveren I have left out most of the general introductions to the topics and some examples with calculations. I hope that this overview helps to show how heterodox theories can be presented at the introductory level. Not merely as critiques of neoclassical economics but as theories in their own right – which they deserve.

The macroeconomic flow The circular flow of goods and money The macroeconomic flow, or circular flow, is a metaphor of the macro economy as a circular flow-system, in which households, firms and the government are connected through flows of goods and flows of money. This is pictured in a circular flow diagram,14 as shown in Diagram 6.1. Each economic theory has its own view of the circular flow. The circular flow diagram shows three types of agents: households, the government and firms. You will learn in this chapter that every theory extends the circular flow diagram in a different way. The simple version of the circular flow diagram shows two flows, in opposite directions. Flows of goods and services (including labour power), and flows of money as payments for goods and services or as tax payments for the financing of public goods. For the government, there are two flows with transfer payments, the public expenditures on social policy, such as social security and social safety nets. Net government expenditures is G − T. Diagram 6.1 shows six flows: LS = labour supply from households to firms C = spending on consumer goods by households from firms Y = income earned by households from firms (wages & profits) C = consumer goods from firms to households G − T = transfer payments between the government and households: the difference between government expenditure (G) and taxes paid by households (T) G − T = transfer payments between the government and firms: the difference between government expenditure (G) and taxes paid by firms (T) labour supply (Ls) and consumer spending (C)

households

transfer payments (G − T)

government

transfer payments (G − T)

income (Y) and consumer goods (C)

Diagram 6.1  Basic macroeconomic circular flow.

firms

Teaching macroeconomics after the crisis  111 The embedded economy: social economics Social economics perceives the economy as part of society and human life at large. This means that the economy is seen as embedded in society and nature. This embeddedness means that the economy as a whole, at the aggregate level, is only a part of wider society and nature and is therefore strongly influenced by society and nature. It is not the case that social relations, politics and culture are part of the economy, but the other way around: society and nature are the larger systems, and the economy makes up part of these and is embedded in these larger systems. Embedded in society The embeddedness of the economic system in society implies two things for the circular flow. First, every economic agent and economic relationship is affected by social influences, such as power, values, beliefs and cooperation. Second, the economy has an additional sector, named the community economy, of unpaid work and caring. Below, I will discuss the social embeddedness of households, the government and firms, and I will discuss the role of the care economy. HOUSEHOLDS

The relations within households are primarily social, and only secondarily economic. This shows, for example, in the gender division of labour and the extent to which households are nuclear or extended families. Economic roles and flows of goods and resources in households are derived from the social relations in households. Also, the economic relationships of households with the rest of the economy, particularly the market and the government, are built upon underlying social relations between these agents. This leads to a social contract. A social contract is a society-wide agreement about rights and duties and the distribution of costs and benefits of social and economic behaviour. It includes social protection and investment in new generations and governs which transactions occur in the market, the state and the community economy. For example, labour relations between individuals and firms are embedded in a social contract and go well beyond an agreement about wages and benefits. Labour relations also involve social security, differences in bargaining power between labour and capital and silent agreements about the extent of tolerable discrimination, for example. Another example of how the social contract of a society influences the behaviour of households in the economy is through consumer behaviour. The consumer relationships of households are governed by a combination of free choice to move between suppliers of goods and services (“exit”), consumer power through collective action influencing price and quality of goods (“voice”) and the social bonds developed in social groups with particular firms and their brands and in production in the care economy (“loyalty”). So different social contracts will emphasise

112  Irene van Staveren different modes of consumer relationships: exit, voice and loyalty. Neoliberal societies are likely to give priority to the exit relationship, stimulating consumers to make cost–benefit calculations and change health insurance, energy supplier or cell phone company regularly. Small-scale societies with strong bonding social capital are more likely to emphasise the loyalty relationship, with strong bonds between consumers and suppliers, perhaps through a dominance of cooperative firms or an extensive care economy. Different societies will have different social contracts, so that the embedded economic relationships will be affected differently by social relations in each society. In the macroeconomic flow, the social embeddedness of households has two major implications for macroeconomic variables. First, for labour supply, household members need to survive and hence will supply additional labour when the economy is in a downturn of the economic cycle: the added worker effect. This increases labour supply, but with unemployment and a decline in wages in an economic downturn, this will often not result in an increase in household income. So, there will be more labour supplied without additional labour income as a return flow. This is indicated in the embedded flow diagram (Diagram 6.2) below as Ls. The second implication of the social embeddedness of households is that households will reduce their consumer expenditures in bad economic times. They do so partly by increasing their unpaid workload, providing unpaid services. They supply unpaid work within the same household and to other households. This implies an increase in unpaid work time from the household to the community economy: Lup. And, in return, households enjoy the consumption of unpaid services: Cup.

nature society L, C

C up

C up

L up G−T

households L up

government

communities

Y, C

Diagram 6.2  Embedded macroeconomic flow.

G−T firms

Teaching macroeconomics after the crisis  113 FIRMS

Although firm relations are largely exchange relations in markets, they are not immune to social influences. That is because supply and demand relationships are decided upon and carried out by humans, in their role as economic agents. Firms include the hiring of labour power, which is governed by a society’s social contract, as was explained above. Firms also demand resources, require governance and supply intermediate and final products. Society norms and values influence which resources can be legitimately used. For example, for energy, some societies use nuclear power plants and others don’t. Also, the governance of firms is largely determined by social relationships and varies from very hierarchical to more horizontal forms of governance, and varies between independent competing entities to strongly interconnected firms through the social networks of board members. Finally, the supply of goods is also socially influenced. Social norms determine which goods are considered legitimate to be traded, and which goods should not be left to the market and commercial firms but to non-profit firms, the state or civil society. These social influences on the market and firm behaviour cannot be easily quantified in macroeconomic variables. But various studies have shown that prosocial norms have a positive effect on aggregate demand (AD) because they tend to reduce transaction costs. GOVERNMENT

The social relations of the government influencing economic behaviour are twofold. On the one hand, these relationships are political and a formal expression of social values, and on the other hand, they are purely social and often informal. The political relationships determine the extent of taxation and regulation that a society finds acceptable. They determine the role of the government in the economy in general. The social relationships are expressed in how households and firms interact on a day-to-day basis with the government. This includes corruption and discrimination in terms of contracts, payments and access of labour supply to public sector jobs and access of households to public services. Hence, this is how government’s representatives act in the economy, following the dominant culture of state interactions. In terms of macroeconomic variables, the political and social relationships of the government are likely to affect the role of the government in the economy. With political effectiveness, democratic control, and effective public service delivery, the role of government is relatively larger in an economy because of the political and social support for it. Hence, transfer payments are likely to be larger: more tax revenues and more public expenditures in the economy. This is shown in an increase of transfer payments: G. Together, society strongly influences the economic behaviour of households, firms and the government. That is what social embeddedness of the economy means.

114  Irene van Staveren COMMUNITY ECONOMY

Social economics explicitly recognises the key role of the community economy in the macroeconomic flow. Therefore, it is added as an additional sector, with its own agency centred on loyalty rather than exit and voice. In the embedded economy, this sector receives unpaid labour from households and delivers services to households. Also, this sector is responsible for caring for nature. This concerns unpaid work from households, through the community economy to nature. And, in return, nature provides environmental services through the community economy back to households. These flows are pictured as follows. One flow between households and the community economy: Lup from households to the community economy and unpaid services in return, Cup. The other unpaid flow is between households and nature, through environmental services from nature, Cup, and unpaid work to nature, Lup. Embedded in nature Social economics not only recognises the economy as embedded in society but also in nature. Nature is the wider system, in which society and the economy are embedded. The embeddedness of the economy in nature occurs in two relationships. The first is about resource use and concerns a flow from nature to the economy. The second is about environmental damage, such as pollution, and concerns a flow from the economy to nature. However, this is not as a two-way relationship between two independent entities, economy and nature, but rather as a two-way relationship of the economy with nature in which the economy is embedded in nature. So, nature comes first and enables the economic system to function. Why? Because nature provides all the material inputs that go into production. Of course, human labour transforms these inputs, but they originate in nature: from grain to bread and from iron ore to steel. Even labour supply and the human capital underlying it come from nature through human reproduction. Without an economy, nature will function as it has done for millions of years. Without nature, the economy will come to a standstill. By understanding the relationship as an embedded one, social economics emphasises that the relationship should not break. This implies that nature’s ability to serve the economy and society should not be undermined by too high resource-use or too much damage. The long-term functioning of the economy and society therefore require limits to resource use and pollution. This is precisely the definition of sustainable development, which was formulated in the 1987 UN report Our Common Future on sustainable development. This report defines sustainable development as development that meets the needs of the present without compromising the ability of future generations to meet their own needs. This is a social economic definition of sustainable development because it puts people’s needs at the centre, while putting limits on the economy’s use of nature. The caring behaviour of economic agents vis-à-vis nature is captured, as was already explained above, as a flow of unpaid work from the community economy to nature, Lup. There is also a return flow, which consists of

Teaching macroeconomics after the crisis  115 environmental services, such as enjoying walking in nature, listening to birdsong or watching the sunset: the consumption of environmental services: Cup. The embedded macroeconomic flow The social economic perspective of economic embeddedness is pictured in Diagram 6.2 as three interlocked systems: the wider natural system (nature), in which the social system is embedded (society), in which the economic system is embedded (economy). The embedded macroeconomic flow of social economics is particularly useful for a comparative analysis of different economic systems. It helps to explain differences between, for example, welfare states and more market dominant economies, or between communist economies and hunter–gatherer societies. The differences are explained with reference to differences in societies (including politics and culture) and natural conditions (ecological conditions, natural resources, climate). The embedded macroeconomic flow also enables the analysis of the community economy at the macroeconomic level. It helps to answer questions about how big the community economy is, and what its relationship is with firms, households, the government and nature. Macro level institutions: institutional economics In this section, we focus on how institutions affect the macroeconomic level, other than through the sum of micro decisions. In other words, institutional macroeconomics recognises that some institutions mediate behaviour at the meso level, in between micro and macro, or directly at the aggregate level. Institutional economics orders institutions from macro to micro, in which the most aggregate level is the world level, affecting trade and investment flows between countries. Therefore, the circular flow diagram for the institutional economic theory explicitly includes the rest of the world (symbolised as RoW). Macro institutions and macroeconomic variables What are the major macro economy institutions? These are formal and informal institutions which affect the relative size and stability of macroeconomic variables. What are the main macroeconomic variables and how are they related? Macro level institutions influence the relative size and stability of Y through AD. Let us consider the influence of macro level institutions on each of the macroeconomic variables that make up AD. CONSUMPTION

Formal institutions may constrain the consumption function by increasing taxes by law. Remember, consumption is partly out of income. This is, of course, out of net income (Yn, or in short Y) after taxes, also called disposable income

116  Irene van Staveren (Y = Yg − T). So, the higher income taxes, the less income available for consumption: C = C * + c (Yg − T ) = C * + cY Formal institutions may also enhance the consumption function by lowering taxes and providing social security and welfare benefits. In that case, net income, or disposable income, becomes higher and hence you can consume more. Informal institutions may influence the consumption function due to cultural values such as immaterialism or solidarity. This may increase savings or equalise consumption across population groups. Informal institutions may enhance the consumption function through a culture of borrowing, with increasing social acceptance of household debt. This may even lead to consumption levels above income levels: C > Y. This is possible when C* increases strongly due to increasing consumption standards. Or C > Y is made possible by a very high propensity to consume, c > 1, because of the use of savings and assets as collateral (like a house) for borrowing or the use of credit lines based on regular income. Of course, a value of c higher than one implies a negative propensity to save: dissaving and borrowing. So, when c = 1.3, this means that s = −0.3. Remember that c + s = 1, so that 1.3 − 0.3 = 1. In other words, when a household spends 30% more on consumption than its income, savings will decline by 30% of income in order to finance this. As the aggregate households, as a whole, borrow more than they earn, that debt is 30% of income. Debt is precisely the opposite of saving; it is dissaving. So, a debt of 30% of income is the same as negative saving. Institutions reflecting a materialist culture with short consumption horizons (“I want it now”) are likely to become increasingly indebted. This is pictured in the institutional macroeconomic flow as increased C and decreased S. INVESTMENT

Formal institutions may enhance investment, for example by a low central bank interest rate. But formal institutions can also constrain investment, for example by capital reserve controls requiring higher levels of equity capital or minimum investment periods from foreign investors. This implies that the formal institutions arrow from the government to firms can either increase I or decrease I. Informal institutions can constrain investment by contributing to negative expectations about returns, so, a negative investment confidence. The opposite is also possible, optimism about future returns, and hence investor optimism (or even over-confidence, which may lead to bubbles in asset markets). GOVERNMENT TRANSFERS

Formal institutions can constrain the net government transfers (expenditures minus revenue) by strict budgeting rules, for example. Other formal institutions may

Teaching macroeconomics after the crisis  117 enable net government expenditures, in particular automatic stabilisers in the budget. For example, when the total sum of unemployment benefits increases in times of economic crisis. Informal institutions may also affect government transfers. Think about corruption, which reduces the effectiveness of public services, or, to the contrary, a high tax morale, which increases government revenues. EXPORTS AND IMPORTS

Formal institutions can also affect exports. For example, the exchange rate or export taxes, which influence the price that economic agents abroad need to pay for your country’s products. Informal institutions also affect the size of exports. This may be due to language barriers, for example: former French colonies in Africa tend to trade more with each other and with France than with former English colonies and the UK. The institutional macroeconomic flow Diagram 6.3 shows the institutional macroeconomic flow. It includes the rest of the world (RoW), but more importantly, formal and informal institutions. Formal institutions (FI) are laws and regulations, and hence flow from the government sector to firms and households and the RoW. Informal institutions concern social norms and show a two-way relationship with every sector: households, firms, the government and RoW.

L, C

IM

EX

RoW

FI

T

G

−

−

G FI

informal institutions

government

Y, C Diagram 6.3  Institutional economic flow.

firms

T

households

118  Irene van Staveren The economy as an open system: Post Keynesian economics Post Keynesian economics’ major contribution is in macroeconomics. Keynes rejected the old classical assumption that the macro level is the sum of all micro level behaviour. Instead, he argued that there is a fallacy of composition at the macro level. The fallacy of composition is the wrong assumption that the aggregate is the sum of the parts. What makes sense at the level of individual households or firms does not necessarily make sense for the economy as a whole. Macroeconomic variables are not necessarily a summing up of micro level variables. The reason is that in the economic process, interactions take place which interfere with a simple aggregation of micro-behaviour to macro-behaviour. The sum is bigger than the parts. Keynes has demonstrated various cases of the fallacy of composition. The two best known are herd behaviour in financial markets and the paradox of thrift in households. Herd behaviour is the non-rational following of others’ behaviour in markets, either in selling or buying assets, which leads to bubbles and bursts. The paradox of thrift refers to the contradictory phenomenon of savings as wise at the micro level (to keep resources for a rainy day) and as unwise at the macro level (because it lowers aggregate consumption), lowering AD and, hence, the level of GDP. The paradox of thrift is therefore defined as the virtue of saving at the individual level to counter uncertainty, and the vice of saving at the aggregate level because it reduces AD. So, at the micro level, more saving helps to balance livelihoods during a downturn of the economic cycle, whereas at the macro level, more aggregate saving reduces AD and keeps the economy at a low level at the economic cycle, due to lower consumer expenditures. In Post Keynesian economics, uncertainty is a key concept. This leads to prices not reflecting real values, to volatility and to expectations that may be optimistic or pessimistic, driving investments below or towards full capacity utilisation of an economy’s resources. As a consequence of the combination of uncertainty and the fallacy of composition, macroeconomic equilibrium does not necessarily imply that an economy operates at full capacity with full employment. When firms decide not to invest but to sell their stocks first, and when households decide to consume less and to save more, production will be sub-optimal, and unemployment will result. The economy does not automatically tend towards a desired outcome of full employment and no waste of resources. It simply balances where demand equals the supply of goods, at whatever level of output this is the case. This is what is meant by the economy as an open system: it does not necessarily arrive at a stable equilibrium with all resources being used, but it is dynamic, responding to confidence, expectations and social dynamics of imitation, which drives economic cycles. Open system economics is the study of the economy in which there is no automatic balance between savings and investments and, hence, where macroeconomic equilibrium does not automatically eliminate excess supply in the markets for production factors. Open system dynamics Keynes developed his insights from studying the 1929 financial crisis and the subsequent Great Depression of the 1930s. He found that despite macroeconomic equilibrium in product markets (AS = AD), an economy may suffer from

Teaching macroeconomics after the crisis  119 unemployment. Because employment depends on the level of AD, and not on an equilibrium between aggregate supply (AS) and AD. It is the size of AD in the economy (the sum of C, I, G and EX − IM) which determines capacity utilisation, which in turn determines the demand for labour. Only when AD is located at a sufficiently high level will it be able to absorb all labour supplied in the economy. In other words, macroeconomic equilibrium does not imply equilibrium in the labour market (absence of excess demand or excess supply). See Diagram 6.4, which will be explained below. Does AS not have any role to play in this? No, not in the view of Keynes. Because the driving force for aggregate supply is investment, which is the only way in which potential production capacity can be expanded. And investment is part of AD: so, investment helps to increase employment and GDP through the demand side of the economy. On the supply side, the amount actually invested and leading to additional production depends on savings available in the economy, expectations about future sales and the extent to which banks are willing to lend out money. Hence, investment will go up when there is both more savings available and optimism about the development of AD by firms, and optimism by banks about risk of lending out money. According to Keynes, the level of investment does not depend on the interest rate, which is the price of investment. Isn’t this inconsistent? If the demand for apples depends on the price of apples, why doesn’t the demand for investment depend on the price of investment? Good question. Keynes gave the answer: because investment requires savings, and savings depend on income. This was already explained: both C and S depend on income. And the more you consume, the less you save, and the other way around. So, it is the level of income, Y, which determines savings, and not the level of the interest rate (of course, only in a closed economy). The interest rate plays a minor role,

Y AS

AD

Y*

N*

Diagram 6.4  Effective demand.

N

120  Irene van Staveren namely in enabling credit. But what is more important for the amount of credit available in an economy is expectations about the future. When entrepreneurs do not expect sales to increase, they will not take out credit to invest, however low the interest rate at which they can borrow is. After the 2007 financial crisis, the interest rate remained historically low in the US and Europe, like it has been for many years in Japan. But low demand and pessimistic expectations implied high savings combined with low consumption and low investment. So, in Post Keynesian economics, savings equate the level of investment in an economy not though the level of the interest rate but through the level of income. The higher the income, the more savings and the more optimistic expectations about the future, and hence, investments. This creates a virtuous circle in the economic flow: Households consume more (C) and save more (S) absolutely (because of Y) Households save more relatively to consumption (S > C), because the higher the income (Y) the lower the propensity to consume (c) and the higher the propensity to save (s) Firms will invest more because more savings become available (S => I) Firms will invest more because they become more optimistic about the future when incomes grow: they expect households to consume even more (C => I) It is precisely because of the typical macroeconomic phenomena, driven by nonrational motivations and the paradox of thrift, that the circular flow in Post Keynesian theory is understood as an open system. Not as a closed system, which after a shock quickly comes to equilibrium, but as a system in which relationships do not necessarily tend to equilibrium. Open systems may experience long-term nonequilibrium and may even lead to chaos, due to spiralling upwards or downwards dynamics. That is exactly why Post Keynesian economics can explain cycles, with its booms and bursts. These are instances in which the system is moving away from an equilibrium, possibly into chaos, of bank-runs, governments insolvency, bankruptcies and sky-high levels of unemployment. Aggregate demand with a positive slope In the Post Keynesian perspective, the AS can function either at its maximum level of capacity utilisation (cumax) or below this level (< cumax). Below this level, there is excess capacity, not only in the use of capital goods and land but also in the use of labour. This implies that labour demand is insufficient to generate full employment. Full employment is indicated as Nmax, when unemployment is zero: U = 0. So, when capacity utilisation in the economy is less than its maximum (cu < cumax), unemployment is the result (U > 0). That is why in the Post Keynesian perspective, the diagram for macroeconomic equilibrium is not pictured in a space of income and price level, but in the space of income and employment, or in the space of income and capacity utilisation.

Teaching macroeconomics after the crisis  121 And, it is not really an equilibrium in the sense of an absence of excess supply or excess demand throughout the economy. Therefore, Post Keynesians do not refer to the intersection between AS and AD as an equilibrium, but give it the more appropriate name of effective demand. Effective demand is the intersection between aggregate supply and AD in an economy, which determines the level of output and employment. Diagram 6.4 shows the Post Keynesian macroeconomic diagram with effective demand, in the income – employment space. The intersection where AS = AD shows equilibrium output (Y*) and employment (N*), which may be below full capacity utilisation and below full employment. The diagram shows that both AD and AS are upward sloping. AS does so because more production requires more labour. In fact, the aggregate supply function describes the relationship between expected earnings by firms and the labour they want to hire for that expected level of earnings. So, more expected earnings increases production, and this requires hiring more labour. As a consequence, an increase in AS leads to an increase in employment (assuming that labour supply remains unaffected, of course – a ceteris paribus assumption). AD slopes upward because more expenditures in the economy requires more income and more income can only be produced with hiring more labour. Again, this stimulates employment. But the slope of the AD curve is less steep than the slope of the AS curve. Why? The difference in slope between the AS curve and the AD curve means that for every increase in income of a fixed amount, the employment effect at the demand side (AD) is larger than at the supply side (AS). The reason is that at the supply side, there are no endogenous effects between supply and employment: hiring labour simply contributes to higher output. But at the demand side, there are endogenous effects between demand and employment: more labour employed means not only that this is coupled by more investment by firms (you need to have more machines, computers, office space or land to put more labour to work). But also that more employment means more wage earnings and, hence, more consumer spending, in the aggregate. That is because now more households have wage earners. Moreover, the more employment, the higher the tax revenue from labour income for the government (T). This allows for more government expenditures (G). So, through the AD curve, more income generates more employment than through the AS curve. Since consumption takes up the biggest part of AD, let us analyse the Post Keynesian consumption function at the aggregate level more closely. C = C * + cY Diagram 6.5 shows the aggregate consumption function in the space of income (Y) and consumption (C). The diagram shows that consumption is never zero. The minimum level is C*, the autonomous consumption: the level that people consume, irrespective of their income level. The next observation is that the line is not linear. Indeed, the relationship between consumption and income is not linear: cY varies over the level of

122  Irene van Staveren C

C*

Y

Diagram 6.5  Post Keynesian aggregate consumption function.

income. We can distinguish three parts of the relationship between Y and C. The part closest to the Y-axis is where consumption levels are low: people spend most or all of their income on consumption, sometimes even more. At this part, the propensity to consume, c, is 0.8 or more. Halfway the curve, at intermediate levels of income, people begin saving money. They consume more than they save, hence c lies in between, say, 0.5 and 0.8. In other words, they save between 20% and 50% of their income. The last part of the curve, furthest to the right, is where people earn high incomes. This part reflects the richest households in an economy’s income distribution. This group can afford to save just as much as they consume or even more: c will lie below 0.5. The important insight from the above aggregate consumption function is that an increase in income is likely to lead to a proportionate, or almost proportionate, increase in consumption for poor households, but to a much smaller increase in consumption by rich households. Apparently, the extent to which AD helps an economy to grow or to move out of an economic downturn depends partly on whether economic policy benefits the poor (big effect on AD) or the rich (small effect on AD). This brings us to the last key feature of Post Keynesian macroeconomics, namely leakages and injections, which can be analysed with multiplier effects. Multiplier effects Let us go back to Diagram 6.4, showing effective demand in Y – N space. We have seen that for a given increase in income, AD generates more jobs than aggregate supply. Now, the reverse is also true. For a given increase in employment, aggregate supply generates much more output than AD. That is because the additional fixed amount of labour hired contributes directly to output (AS). But a fixed amount of additional jobs is weakened in its effect on demand (AD). This weakening is caused by leakages in the circular flow.

Teaching macroeconomics after the crisis  123 Macroeconomic leakages are non-consumption-uses of income, which reduce AD. There are three leakages: savings, taxes and imports: SAVINGS LEAKAGE

When additional income for labour or capital is not spent on consumption but is added to savings (S). TAXATION LEAKAGE

When additional income is taxed away to reduce government debt, so that it is not spent on consumption or on government expenditures (T). IMPORT LEAKAGE

When additional income is spent on imports instead of domestically produced goods (IM). Macroeconomic leakages make macroeconomic policies less effective. For example, the government may want to stimulate economic growth by lowering its budget deficit through higher taxes. This policy could signal “sound public finances” to international financial markets, attracting foreign investors. This would increase I in the long run with more foreign investments. But the increased taxes will decrease C in the short run because more taxation will lower the disposable income of households, and hence, their consumer expenditures. This will decrease AD in the short run. Whether that will be compensated by higher investments, from foreign sources, in the long run, is uncertain, because foreign investment depends on more factors than “sound public finance.” It also depends, for example, on social economic stability and effective property rights. Next to leakages, the macroeconomic flow also includes injections. Macroeconomic injection is a stimulus to AD through I, G or EX. The two major injections are through government expenditures (G) and investment (I). If the government increases its expenditures (remember, we refer standardly to net expenditures, so taxes remain the same), we will see in the AD function that G increases, ceteris paribus: G. This will have a direct positive effect on Y through AD, which can be seen from the macroeconomic equation: Y = C + I + G + EX − IM But there is also an indirect effect of G, namely through the employment created through G, increasing income and in turn increasing consumer expenditures: C. And if G is spent on stimulation of the export sector, it may also boost exports: EX. And on and on until the effects become zero over time. This will take a few rounds of effects, because when C and/or EX increase, the government will earn more tax revenues (sales tax or profit tax from exporting firms), and hence, can further increase G without creating a budget deficit. The higher government

124  Irene van Staveren expenditures will generate again more C and/or more EX, and so on and so on, but smaller than the first time due to leakages until the initial effect has worked out. Adding up all the direct and indirect effects, we have what we call a multiplier effect. A multiplier is an accelerator on AD through an initial injection and its stimulating effects on other demand variables. Next to the government multiplier (through G), we have the investment multiplier (through I). This multiplier could be triggered by a decrease in the interest rate by the central bank. This makes investment cheaper, ceteris paribus, because it makes borrowing cheaper. So, a lower interest rate functions as an injection to AD, stimulating investment: I. There are also indirect effects here. Increased investment will lead to more jobs, and hence to more labour income. This will stimulate consumption: C. It may also result in higher profit taxes due to more sales by firms that have invested, and more income tax from the additional income earnings, which will allow an increase in net government expenditures: G. After several rounds of such effects, which become smaller over time due to leakages, we can calculate the investment multiplier: the total effect of an increase in investment on AD, and hence, on Y. The open system circular flow The open system circular flow, or the Post Keynesian macroeconomic flow (Diagram 6.6), adds the FIRE sector (FIRE stands for: Finance, Investment, Real Estate). This sector mediates savings (S) and investments (I), but also directly generates financial investments (I). The open systems character is expressed by leakages and injections. They are included in the flows. Leakages can be found for S, T and IM. Injections can be found for I, G and EX. Ls, C IM

I

fire sector

S

EX RoW

T households

G

G T

government

Y, C Injection Leakage

Diagram 6.6  Post Keynesian economic flow.

T

firms

Teaching macroeconomics after the crisis  125

Wellbeing and poverty Introduction: GDP Gross Domestic Product (GDP) is the most widely used measure for the economy. GDP can be measured by adding up the market value of all consumer expenditures (C), investments, (I) net government expenditures (G − T), and net trade (EX − IM). And when divided by population size, we get GDP per capita (GDPpc), which allows us to compare the wellbeing between countries. Even though every economic theory acknowledges flaws in this measure of wellbeing, they all make use of it, because alternative measures lack sufficient data, are complex or focus on other partial aspects of wellbeing. Here we will discuss alternative wellbeing measures for every theory. Nevertheless, GDP remains dominant in economics. Let us therefore chart its major biases. Although it has more flaws, the three major biases of GDP as a measure of wellbeing are the following: GDP ignores distribution, counts damage as wellbeing and excludes unpaid production. Social economics: multidimensional wellbeing and poverty Multidimensional wellbeing Social economics looks beyond income and regards wellbeing as multidimensional. But there is no agreement on which dimensions to include and how to measure them. It may sound trivial, but being alive is a precondition to achieve anything else in life . . . and we have a widely available indicator to measure this, namely life expectancy. In countries where average life expectancy is barely 60 years, wellbeing can be considered as less than in countries where life expectancy exceeds 80 years. Not only because they have the opportunity to live longer lives, but also because life expectancy is a measure of health: the more people die prematurely, the less healthy their lives will have been. The Indian economist Amartya Sen was, together with the Pakistani economist Mahbub ul Haq, founder of a simple and widely available alternative to GDP in 1990. It has only three dimensions: gross national income per capita (GNIpc). health (life expectancy) and education (school enrolment and literacy). This wellbeing measure has become the widely known Human Development Index (HDI), published annually by UNDP. It is an index with a value between 0 and 1. The higher the value, the higher human development. So, each country has a value of HDI and each country is ranked according to its HDI value, from high (a HDI value close to one) to low (a value close to zero). Human development is wellbeing in terms of basic capabilities such as health, education and purchasing power. The HDI allows for a comparison with GNI (which also is included in the HDI, so it can also be considered as an adaptation of GDP rather than an alternative) through ranking countries twice. First according to their GNI per capita score, second according to their HDI score. When the HDI rank is subtracted from the GNIpc rank, we can immediately see whether a country transforms

126  Irene van Staveren Table 6.1  Human Development Index and performance, South Asia, 2012. Country

GNIpc value (USD)

GNIpc rank

HDI value

HDI rank

GNIpc rank – HDI rank

Sri Lanka Maldives India Bhutan Pakistan Bangladesh Nepal Afghanistan

5.170 7.478 3.285 5.246 2.566 1.785 1.137 1.000

110 95 135 110 137 156 168 173

0.715 0.688 0.554 0.538 0.515 0.515 0.463 0.374

92 104 138 141 146 147 157 176

18 −9 −3 −31 −9 9 11 −3

Source: Human Development Report 2013. New York: UNDP. Note: GNPpc = gross national income per capita.

its income effectively in human development or not. Negative outcomes (GNIpc rank − HDI rank < 0) indicate that a country is wasting human development, because it is not investing its national income as efficiently as possible  to obtain human development. On the contrary, countries which show positive outcomes (GNIpc rank − HDI rank > 0) manage to translate their income quite effectively into human development. Table 6.1 shows the country scores for South Asia. The table shows some interesting results about human development in South Asia. First, the countries are ranked in the table according to their HDI value, which shows that Sri Lanka has the highest level of human development. Even though its income is much lower than that of the Maldives: 5.170 dollars per year for Sri Lanka, vs. 7.478 dollars per year for the Maldives. This results in a large positive score in the last column for Sri Lanka, the income rank minus the human development rank: +18. And a negative score for the Maldives of −9. This means that Sri Lanka is much more effective in translating national income into human development than the Maldives. A second interesting insight from Table 6.2 is that Pakistan and Bangladesh, with equal scores on human development, show very different efforts of translating their income into human development. Whereas Bangladesh does this quite efficiently, with a +9 score in the last column, Pakistan, with a higher income level, does not score so well: −9. Finally, we need to discuss the remarkable result for Bhutan. It has its own National Happiness Index as an alternative wellbeing measure to GDP. It is a multidimensional measure of wellbeing, which is broader than the HDI. It includes cultural and ecological dimensions of wellbeing. But Bhutan scores very low on the income rank minus human development rank: −31, as shown in Table 6.1. It is the worst-scoring country in South Asia. How is this possible? The answer is related to the emphasis on “national” in the Bhutanese policies supporting national happiness. It involves a very strong protection of national identity, leading to the exclusion of immigrants and refugees with

Teaching macroeconomics after the crisis  127 different religions and languages, such as the Nepalese minority in Bhutan,15 even though these minorities contribute to national income with their agricultural labour. Such social exclusion results in low scores of health and education for part of the population, lowering the average HDI score relative to income. Multidimensional poverty When we measure wellbeing in a multidimensional way, we also need to measure poverty as such. Of course, this can be done with the same measure, such as HDI: the lowest ranking countries can be considered poor whereas the highest-ranking countries can be regarded as rich. But poverty requires more policy attention than richness: poverty is a priority economic problem. So, the more precisely we measure poverty, the better we can understand how it changes in response to economic development, crises or macroeconomic policies. And good poverty indicators enable close monitoring of poverty. That is why the UNDP has developed, next to the HDI, the Multidimensional Poverty Index: MPI. The MPI covers the same three dimensions and structure as the HDI but focuses on deprivations. According to the MPI, one-third of the population of the 109 countries included in the MPI, 1.7 billion people, can be considered extremely poor. This number is higher than the income measure of poverty, counting the number of people living below 1.25 US dollars per day. The MPI has two advantages over the income measure. First, it measures what people are able to do with their income in terms of health and education. Second, it reveals the most urgent needs that need to be addressed in order to reduce poverty, based on the scores on nine indicators. The multidimensional poverty indicators are shown in Table 6.2. Table 6.3 shows the value of the MPI and the percentage of the population living in multidimensional poverty, for the same region as Table 6.1 did for the HDI: South Asia. It shows that, as for the HDI. Sri Lanka and the Maldives do quite well: these countries score low on the MPI and have only 5% of their population living in poverty. Bangladesh, India and Pakistan have high MPI values and have poverty Table 6.2  Multidimensional poverty indicators. Assets Living standards

Education Health

floor electricity water cooking fuel children enrolled years of schooling child mortality nutrition

Source: Human Development Report 2013. New York: UNDP.

128  Irene van Staveren Table 6.3  Multidimensional Poverty Index and indicators, South Asia, 2012. Country

Data year

MPI value

Poverty (%)

Sri Lanka Maldives India Bhutan Pakistan Bangladesh Nepal Afghanistan

2003 2009 2006 2010 2007 2007 2011 –

0.021 0.018 0.283 0.119 0.264 0.292 0.217 –

5.3 5.2 53.7 27.2 49.4 57.8 44.2 –

Source: Human Development Report 2013. New York: UNDP.

rates around 50%. The combination of the HDI and MPI measures gives a more complete indication of the extent of poverty in a country. When we look at Bangladesh, for example, which did quite well in transforming income into human development according to HDI, it nevertheless has a poverty rate of almost 60%, when we use the MPI poverty measure. Nepal, with less income, has a much lower poverty rate. What explains multidimensional poverty? In social economics, the explanation is social exclusion. There are basically three drivers of social exclusion. MARKET FORCES

Often, markets are not fully competitive. This results in market power by firms over consumers (driving up consumer prices) and suppliers (pushing down the sales prices for the products produced by small-scale entrepreneurs). And where labour unions are weak, firms have market power over labour, pushing wages down. But even when markets are fully competitive, some groups find themselves socially excluded from participation in markets on an equal basis. For example, labour markets may be in equilibrium with high levels of unemployment, discouraged workers and underemployment. This weakens the bargaining power of those employed, resulting in low wages. And land markets may be in equilibrium, but landless farmers have no access to land due to lack of purchasing power, lack of access to credit, lack of collateral to obtain credit or no permission from husbands, brothers or fathers to buy or sell property, or their communal land has been appropriated or informal land rights have been ignored by municipal governments seeking land to expand urban housing and industrial areas. Finally, small-scale entrepreneurs may have no access to skills, tools and sales markets, so that they are locked into low value added activities, competing with each other for a limited size and geographical spread of market demand. This often results in a local oversupply of the same types of medium quality goods.

Teaching macroeconomics after the crisis  129 SOCIAL NORMS

Social norms can be discriminating against certain social groups: migrants, ethnic groups, women or low caste people. This explains why poverty is also persistent in the developed countries. In Europe, the partially nomadic Roma and Sinti people are among the most deprived. In the Arab world, migrant workers from South Asia are the ones living in poverty. And in the world’s largest cities, slums are populated by rural–urban migrants, who cannot find jobs and lack the skills and capital to set up a profitable business. And throughout the Western world, women are less financially independent than men. SOCIAL PROTECTION DEFICIENCIES

Even when people are not excluded from markets, do not suffer from disasters and do not belong to a discriminated group, they may find themselves poor. The reason is not only a low level of economic development, although it obviously is a major reason for widespread poverty. But it also due to a lack of social protection provided by communities and the state. Without any social protection, in the shape of relief by central government, foreign aid or social security, external shocks and bad luck may drive people to poverty. Often, the extent of social protection in a country reflects power relations: elites often have organised state social protection for themselves, for example through pensions in the formal sector. The organisation of health care insurance, old-age pensions and disability benefits can take many years to develop, in particular in countries with high levels of inequality. Institutional economics: relative wellbeing and poverty Inequality and social norms Relative wellbeing measures poverty not in absolute terms, such as HDI and MPI, but as inequality. So, it does not measure how many children are out of school, or the extent of child mortality, but how unequal wellbeing is distributed. This can be done by measuring inequality in a vertical way, ranking individuals or households along a continuum, or in a horizontal way, grouping individuals or households along particular social stratifications. So, vertical inequality ranks people along a continuum of a single dimension, often income. It focuses on incomes, because income inequality cuts across social groups: there are poor and rich immigrants, poor and rich women and poor and rich farmers. Horizontal inequalities are group inequalities along social dimensions, such as ethnicity, geography and gender. Institutional economics focuses on inequality rather than on absolute poverty, because it recognises the importance of social norms for wellbeing, in particular norms about status and fairness. These are particularly relevant for analysing poverty at the micro level: between individuals and households and social groups.

130  Irene van Staveren STATUS

People tend to strive for the levels of wellbeing of those above them in the income distribution: the grass-is-greener-at-the-Joneses effect. The economic benefit of this is that people are concerned with achievement and, hence, with investing in their skills in order to obtain higher incomes. The economic cost of this is that status and materialism result in high ecological footprints. And it may lead to a decline in social cohesion, in particular when social classes increasingly distinguish themselves from those below them. This may lead to segregated neighbourhoods, segregated education and discrimination in the labour market. FAIRNESS

Who deserves what in the economy? This is the driving economic question of fairness. Societies differ in their average answer to this question. Meritocratic societies closely connect fairness with contribution: those who work hardest, have the most unique skills in demand or take the most risky investments are generally agreed to be most deserving of high income. A meritocratic view of fairness is not much concerned with inequality. Those at the top of the income distribution can earn extremely high salaries and bonuses without much jealousy or criticism from the rest of society. Millionaires and billionaires rather evoke admiration in meritocratic societies. Those at the bottom of the income distribution in meritocratic societies are considered as deserving their status, too: they are seen as not putting in enough effort to obtain economic success. More egalitarian societies, such as social welfare states, connect economic fairness with the value of human dignity: nobody deserves to be poor. Such societies provide social protection for the poor, even when part of the receivers of welfare benefits are considered to be free-riders or suckers who waste every opportunity provided to them to obtain a job or to start a business. In fact, such societies show that the majority of the population values equality as an intrinsic value, and hence, for everyone, also the suckers – because they’re considered as our suckers. So, the likeliness for an individual to live in an unequal society and to suffer from very low levels of wellbeing depends, in institutional economics, importantly on whether one lives in a society where meritocratic norms are dominant or in a society where egalitarian norms are dominant. Income inequality Income inequality in developed and developing countries increased by 10% between 1990 and 2010, according to the UN.16 Income inequality has real effects. In developing countries, we find that children in the poorest 20% of households are up to three times more likely to die before their fifth birthday than children in the richest 20% of households. And women in rural areas in developing countries are up to three times more likely to die while giving birth than women living in cities. In developed countries, data show that in the more equal countries, like Germany, Italy and Japan, less than 10% of the population suffers from mental

Teaching macroeconomics after the crisis  131 illness (in particular drug and alcohol addiction), whereas in the more unequal countries, like the US, UK and Australia, the rate is around 25%.17 Moreover, more unequal developed countries appear to have more social problems of all kinds, as compared to less unequal developed countries. The social problems include high mortality, obesity, low educational performance, high homicide rates and high rates of imprisonment.18 It also seems that more inequality makes the most disadvantaged in a society more concerned with social status, in particular in meritocratic societies. We have seen already that economists use the Gini-coefficient to measure income inequality. Remember that the Gini-coefficient is zero for full equality and one for complete inequality. Over the period 1990–2010, the Gini-coefficient for developed countries increased from 41.4 to 45.3, while for developing countries it increased from 38.5 to 41.5.19 Regional averages show a more varied picture. Africa shows the largest decline in the Gini-coefficient, from 48.0 to 44.4. Europe and the Commonwealth of Independent States show the largest increase, from 33.0 to 43.8. So, income inequality has gone down in Africa, but up all over Europe. The Gini-coefficient is a very crude measure of income inequality, because the biggest inequalities are found at the very top. That is why it is insightful to compare the income earned by the top 1% of households with the other 99% – just like the slogan of the Occupy movement, critiquing the power of the financial sector, the wealth of bankers and their responsibility for causing the financial crisis: “we are the 99%.” The top 1% earns 20% of national income in Colombia, 17% of national income in South Africa, and 13% of national income in Singapore.20 In Western countries, the inequality is highest in the US, where the top 1% takes home 20% of national income.21 What are the causes behind income inequality? There are three main categories of causes. GLOBALISATION

Globalisation concerns capital flows and trade in goods and services, while they are related in the so-called global assembly line, through which production is organised and in global value chains. Financial globalisation has resulted in global investment flows to low-cost labour production sites and to emerging investment opportunities in a wide variety of assets. The first has created a downward pressure on wages, due to the strong bargaining power of footloose companies vis-à-vis the weak bargaining power of immobile labour. This certainly has created more jobs in the global South than it has destroyed in the global North, but at much lower wages. The second has resulted in an increasing share of global investment going to the financial sector itself, creating high-risk–high-return assets with increasing volatility, instead of jobs in productive activities. TECHNOLOGICAL CHANGE

Wages are theoretically related to productivity: the higher labour productivity, the higher wage incomes, because workers produce more output per hour and therefore can be compensated more income per hour. If not, they may reduce their

132  Irene van Staveren productivity out of frustration (slow down) or protest (strikes). But in the context of globalisation, technological change has only increased capitalist earnings and not labour income. Since the 1980s, the labour share of income has declined steadily: technological change still translates into higher labour productivity, but no longer in relatively higher wages. Moreover, technological change increases the demand for skilled labour and reduces the demand for unskilled labour, so that wages of better-educated workers are more likely to increase while wages of less educated workers are likely to reduce. This is another driver of income inequality, in particular in developed countries. MARKET LIBERALISATION WITH REDUCED GOVERNMENT PROTECTION

The liberalisation of markets since the 1980s went hand in hand with reductions in government expenditures and weaker social protection of the poor through social floors (minimum wages) and social safety nets (welfare benefits). Lower tax revenues constrain governments to implement adequate social policies. In particular in developing countries, tax revenues as percentage of GDP remain limited, from 15% in Asia to 21% in transition economies. This is shown in Diagram 6.7.

30

25

20

15

10

5

0 Africa

Latin America East, South and Southeast Asia

Transition economies

Developed countries

Diagram 6.7  Tax revenue as % of GDP, 2006–2010. Source: Humanity Divided: Confronting Inequality in Developing Countries. New York: UNDP.

Teaching macroeconomics after the crisis  133

Peru

Mexico

Bolivia

Uruguay

Brazil

Argentina –8.00%

–7.00%

–6.00%

–5.00%

–4.00%

–3.00%

–2.00%

–1.00%

0.00%

Diagram 6.8  Conditional cash transfers in Latin America: reductions in Gini-coefficient. Source: Humanity Divided: Confronting Inequality in Developing Countries. New York: UNDP.

Tax revenue is the input-side of social policy. What matters also is the outputside. When countries succeed in spending tax money effectively, including on social policy, the effects can be significant for the reduction of income inequality. An example is the improved taxation in Latin America and the conditional cashtransfer policies for the poor. Conditional cash transfers are a social policy of income support to poor households on the condition that they send their children to school or other social policy criteria. Diagram 6.8 shows the percentage decline in the Gini-coefficient due to cash-transfer policies in Latin America. Horizontal inequality Horizontal inequality was defined above as group inequalities along social stratifications, such as ethnicity, geography, gender and caste. Its causes are a combination of social exclusion, as explained in the social economic theory of poverty, and social norms, which may legitimise inequality. Horizontal inequalities can be large and persistent, in particular regional inequalities, because they are often correlated with social divisions along the lines of ethnicity and concentration of economic activity. In Thailand, for example, regional inequalities are relatively large as compared to its neighbouring countries. And the disparities have remained stable over the past ten years. The inequality in household income, for example, was a factor five between the poorest and richest

134  Irene van Staveren Table 6.4  Regional disparities in human development in Thailand, 2014. Rank (top five)

Province

HAI value

Rank (bottom five)

Province

HAI value

1 2 3 4 5

Bangkok Phuket Nontaburi Trang Phayao

0.697 0.691 0.671 0.666 0.666

76 75 74 73 72

Mae Hong Son Tak Si Sa Ket Nakhon Phanom Surih

0.521 0.565 0.571 0.578 0.586

Source: UNDP. Advancing Human Development through the AEAN Community. Thailand Human Development Report 2014. Bangkok: UNDP.

province. Table 6.4 shows a summary of the regional disparities in human development in Thailand between its 76 provinces. They are measured not in HDI but with a Human Achievement Index (HAI), which the UNDP office in Thailand developed in 2003 in order to take more dimensions of wellbeing into account than the HDI. The HAI consists of eight dimensions, rather than three: health, education, employment, income, housing and living environment, family and community life, transport and communication and participation. To put it simply, HAI is an “HDIplus”: it contains five more dimensions than the HDI. Table 6.4 shows a summary of the human development scores of the top five and bottom five provinces. The left-hand side three columns show the top five and the right-hand side three columns show the bottom five provinces. The province of Bangkok, with the capital city, ranks top, whereas the province of Mae Hong Sun is at the very bottom. The human development value for Bangkok is 34% higher than that for Mae Hong Sun. This is quite a large difference within a single country, pointing at high regional inequality in multidimensional wellbeing. One of the institutional policies which the Thai government has designed to reduce the regional inequalities is to reduce the relative isolation of the poorer provinces. This is done through the development of so-called economic corridors, which connect the various provinces within the country as well as with neighbouring countries and partners in the ASEAN trade union. Another major form of horizontal inequality is gender inequality. This is a special type of horizontal inequality because it cuts right through households, unlike inequalities of ethnicity or geography. That is why it is called an intra-household level inequality. And it is caused by a combination of factors within and outside households. Institutions are a major driver of gender inequalities. This involves both formal institutions and informal institutions. Recent data even allows this to be measured: not only the extent of gender inequality in a country but also the various formal and informal asymmetric institutions that drive this type of horizontal inequality. Table 6.5 shows the Gender Equality Index (GEI) and two indicators from the Social Institutions of Gender Index (SIGI) for the MENA region (Middle East and North Africa). The first SIGI-indicator measures women’s access to resources and, hence, formal gendered institutions. The second SIGI-indicator measures women’s

Teaching macroeconomics after the crisis  135 Table 6.5  GEI and gendered institutions in the MENA region, 2010–2012. Country

GEI

Formal gendered institutions (access to resources)

Informal gendered institutions (civil liberties)

Oman Lebanon Morocco Tunisia West Bank & Gaza Libya Bahrain Iran Jordan Algeria Syria Egypt Iraq UAE Yemen

0.70 0.69 0.68 0.68 0.68 0.68 0.67 0.67 0.67 0.66 0.66 0.65 0.64 0.63 0.59

0.51 0.51 0.35 0.18 0.51 0.51 0.00 0.51 0.51 0.00 0.51 0.30 0.35 0.65 0.51

0.96 0.78 0.11 0.48 0.54 0.76 0.72 0.99 0.11 0.97 0.74 0.79 0.70 0.93 1.00

Source: author’s calculations from OECD: Social Institutions and Gender Index. 2012.

civil liberties and, hence, informal gendered institutions. GEI is measured positively: the higher the score, the more gender equality. The gendered institutions from SIGI are measured negatively: the higher the score, the more restrictive the gendered institutions are for women. Table 6.5 ranks the MENA-region countries according to their level of gender equality (GEI). Oman and Lebanon top the ranking. Yemen and the United Arab Emirates (UAE) have the lowest GEI-scores. Post Keynesian economics: the dynamics of wealth inequality Wealth inequality Wealth can be measured as the total stock of capital: cash and savings, financial assets, buildings, productive land, machines, techniques, brands and copyrights. Wealth is more unequally distributed than income. The reason for this is accumulation, not only individually, over a lifetime, but also through inheritance over generations, reproducing the capitalist class. Capital income is accumulated through inheritance, profits, dividends, interests, rents and royalties. The French economist Thomas Piketty (2014) has recently carried out detailed historical research of wealth inequality in various countries. His research is helpful to explain the Post Keynesian theory of inequality, which is rooted in capital accumulation and the difference between capital income and labour income. I will use Piketty’s two equations, which he refers to as the fundamental laws of capitalism,

136  Irene van Staveren to present the Post Keynesian perspective of wellbeing and poverty. The first wealth equation describes that wealth accumulation is a product of the capital stock and the return on capital: α = r ×β in which α is the share of national income from capital earnings, r is the return on capital, and β stands for the capital/income ratio, the value of the stock of capital expressed in the value of annual income of a country. This equation shows that the higher the return on capital, and the higher the stock of capital accumulated, the higher the capital share will be in a country’s income. As a consequence, with an increasing value of capital income, α, the labour share of income (which can be calculated from the equation above as 1 − α) will be lower. Capitalist economies will therefore increase the capital share of income vis-à-vis the labour share of income, unless returns on investment are very low or negative for a long period of time. As Diagram 6.9 shows, the value of β, the capital/income ratio, was around 600–700% of annual national income at the end of the nineteenth century. The return on capital was (and is) around 4–5%. As a consequence, the value of α. the share of income going to capital is approximately 5% × 600% = 30%. So, capital earned 30% of national income and labour earned, as a consequence, 70% of

800%

Market value of private capital (% national income)

700% 600% 500% 400% 300% 200% 100% 0%

1870 1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 Germany

France

Britain

Diagram 6.9  Capital/income ratio in Germany, France and Britain, 1870–2010. Source: Piketty, Thomas, Capital in the Twenty-First Century. The Belknap Press of Harvard University Press. 2014. Note: Aggregate private wealth was worth about 6–7 years of national income in Europe in 1910, about 2–3 years in 1950 and 4–6 years in 2010.

Teaching macroeconomics after the crisis  137 national income. This distribution of capital and labour income was common for a long period of time. Only in the period of the two world wars was the stock of capita significantly lower. The first wealth equation is also valid at the firm level: with a capital stock of, say, 400% of its annual returns (such as the total value of a factory) and a rate of return on capital of 6%, the capital share of the firm’s income will be 6 × 400 = 24%. Hence, the labour share of income in the firm will be 76%. With the investment in a new factory, the value of the capital stock will increase, say, up to 500%. With the same rate of return on the investment, the capital share of the firm’s earnings will now be 6 × 500 = 30%. As a consequence, the labour share will decline from 76% to 70%. Not because labour has become less productive but, to the contrary, the new machines and logistics are likely to have made labour more productive than in the previous year. It is the capital accumulation process which is responsible for the higher share of capital earnings of the firm, as the first wealth equation explains. This shows the Post Keynesian point that there is no clear relationship between labour productivity and wages. The distribution of income between capital and labour is not related to labour productivity but depends on the bargaining power of capital over labour, which is in favour of capital, and the capital stock, unless labour markets are so tight during an economic boom that sufficient quality and numbers of workers can only be hired and retained by paying them higher wages. The second equation of wealth accumulation is a dynamic one. It explains the capital/income ratio from the first equation as the ratio of the savings rate (s) over the per capita economic growth rate (g): β=s/g This equation explains long-run capital accumulation. The higher the savings rate and the lower the GDP per capita growth rate, the higher the capital/income ratio in a country. Remember that the savings rate, which is the same as the propensity to save, is the complement of the propensity to consume: s + c = 1. The more capitalists, the richer the capitalists, and the more very-high-wage earners, the higher the savings rate. Hence, the second wealth equation also shows an endogenous process of accumulation: the more income inequality, the more likely it is that the savings rate will be higher, and the higher the capital/income ratio in future. For example, if the savings rate is 20%, which is not unusual for a country, and the per capita economic growth rate is 3%, which is the average for all developing countries over the past 20 years (1990–2010), we can calculate that β will be 20 / 3 = 667%. This was the value of β for developed countries during half a century before World War I. Historically, per capita economic growth rates have been much lower than 3%. GDP growth was 0.1% annually for the period from the year zero up to around 1700. With population growth also being 0.1%, this resulted in a per capita GDP growth rate of 0.1 − 0.1 = 0.0%. Hence, despite some economic progress in technology and skills, economic growth was negligible for 17 centuries. The next century, of the Industrial Revolution, showed GDP per capita growth

138  Irene van Staveren of 0.1% up to 1820. From 1820 to 1913, world output grew by 0.9% per capita. Only after World War I did output grow at the unprecedented rate of 3%. Corrected for the increased population growth rate of 1.4%, due to better health care, GDP grew 1.6% per capita over the period 1913–2012. Only since the 1970s has the world known countries with higher per capita growth rates, such as Japan and China. But Japan is “back to normal,” and so are the US and Europe. China’s growth has also slowed down recently. Based on historical growth figures, GDP per capita growth is likely not to be more than 1.2% annually in the long run over the twenty-first century.22 Going back to the example for the second wealth equation, the assumption of a 3% per capita growth is very optimistic for the long run. So, let us replace it with the expected long-run growth rate of 1.2%. In that case, keeping the savings rate at 20%, β will be 20 / 1.2 = 1667%. This is, of course, an enormous amount of capital. And the world has never seen this before, not for a single country. It took the US, for example, several centuries to beat Europe’s capital/income ratio. The actual numbers used in this example are quite realistic, in historical perspective. But the effect on β is alarming. And when we put its long-run value of 1667% in the first wealth equation, even when using a low return on investment of r = 3%, it results in a very high share of income going to capital, namely 50%, implying very high inequality, with only 50% of income going to labour: α = 3% × 166% = 50% In conclusion, the result of the ever-faster capital accumulation and relatively low long-run economic growth rate in capitalist economies is very high inequality. In the words of Thomas Piketty: “in a quasi-stagnant society wealth accumulated in the past will inevitably acquire disproportionate importance.”23 Like the first equation of wealth accumulation, the second can also be applied to the firm level. Remember that the Post Keynesian perspective explained that firms tend to grow until their return on investment gets close to their rate of growth, or equals it: r ≤ g. So, a firm will invest in expansion until the rate of return on investment is no longer higher than the growth rate. This makes sense for a firm. Why invest more if it does not lead to more sales? For countries, a similar rule of thumb may be reasonable. But there are no CEOs in charge of r and g. As the two equations of wealth accumulation demonstrate, it is the market driving the values of these two variables. So, it requires redistributive policies, preferably at world scale, to reverse the trend towards further increasing inequality. Now, suppose that a country does enforce r to be no more than g, as in r ≤ g at the firm level. This lower rate of return on capital can be enforced by wealth taxation, limiting after tax returns on investment. Let us go back to the earlier example. Now if r is taxed so that net r = 2.5%, and we start from the current capital/income ratio of 600% (β), the first equation of wealth accumulation gives α, the capital/ income share, of r × β = 2.5 × 600 = 15. Hence, the labour share of income is quite high, namely 85%. This does not reflect high inequality favouring capital owners.

Teaching macroeconomics after the crisis  139 Hence, when the difference between r and g becomes smaller, through wealth taxation, inequality will be less. So, what was rational at the firm level seems good guidance for macroeconomic policy as well: bring r down closer to the long-run average of g, so that the current accumulation trend of r > g will be bend towards r ≤ g. Economic drivers and effects of increasing inequality There are two endogenous factors helping to reduce economic inequality (inequality in income, wealth or human development): education and technology. Higher levels of technology generate higher labour productivity, which creates the space for wage increases for workers, in particular production workers. Steady technological advancement, and its widespread across countries and sectors, will help to reduce labour income inequalities. Education is the other endogenous factor behind more equality. Over time, technological development requires higherskilled labour. When individuals therefore invest in higher levels of education, they will be able to obtain higher-skilled jobs and hence be able to earn higher wage incomes – although this is not automatic but depends on the bargaining power of labour. Even with good and accessible education, there remain winners and losers. There are also endogenous counter-forces at work. The major driver of more inequality is the level of economic growth, coupled with the rate of return of capital, as we have seen above. And this force was more powerful in history than the forces of technology and education. As a consequence, inequality was historically high between 1870 and 1914, then declined with the capital destruction of the two world wars, and then has gone up again since the 1980s, with the current era of globalisation. Both periods of high inequality have shown low economic growth rates, so that the rate of return on capital was higher than the GDP growth rate. This has happened irrespective of economic cycles: it is a long-run phenomenon in which the accumulation of capital dominates the economic growth rate. What is, next to the social problem, the economic problem of inequality? Post Keynesian economics provides four macroeconomic reasons why high inequality is bad for the economy: social conflict, low AD, underinvestment and increasing financial fragility. These will be explained briefly below. SOCIAL CONFLICT

High inequality may eventually result in social conflict. This may vary from relatively mild efficiency losses through labour strikes, to serious costs through political destabilisation and damage to physical capital stocks. This will, in turn, affect investment. Recent economic history has shown many examples of capital flight, when domestic investors move their capital abroad where it is more secure against damage and appropriation. Moreover, foreign investors are not willing to invest in a country with high social and political instability.

140  Irene van Staveren LOW AGGREGATE DEMAND

High inequality implies high capital income and low labour income, plus a very unequal distribution of labour income, where most of the income is earned by a small elite. This leads to a high savings rate for most of the income and, hence, a low propensity to consume. Overall, this leads to relatively low AD. And this implies that an economy gets stuck at a low level of capacity utilisation with high unemployment rates. UNDERINVESTMENT

Lack of access to resources by the poor leads to underinvestment in production. This is low investment in a resource, leading to low returns. Very unequal land distribution is inefficient, because it leads to lower levels of agricultural production than a more equal distribution of land. Large landowners do not work their land as intensively as small landowners do because they only use the parts that are accessible for machines or cattle, leading to lower yields per hectare than farmers who own small plots. Moreover, insecurity of land ownership prevents farmers from investing in the improvement of the land, because they are not sure whether they can reap the returns on such investments. Child labour in households where parents earn below-living wages results in limited or no education at all for these children, which is an underinvestment in human capabilities. Finally, large income inequalities negatively affect social cohesion. This, in turn, may make the poor distrustful of higher income groups and the government, which may be seen as representing the interests of the elites. The poor may decide no longer to vote, or they may expect hand-outs by political parties seeking votes rather than redistribution and jobs. Low social cohesion discourages long-term investments in any sector of the economy, including the public sector. INCREASING FINANCIAL FRAGILITY

High income and wealth inequality, and the subsequent high propensity to save, results in increasing investments in the FIRE sector of the economy, where capital is accumulating steadily. Without much capital taxation and with continuously newly designed rent-seeking and moral hazard opportunities, the FIRE sector will attract more and more investments at the cost of the real economy. This growing dis-balance towards dominance of financial investments increases financial fragility in the economy. And through financial globalisation it also increases asset price volatility worldwide.

Economic growth Introduction Economic growth is a major macroeconomic concern for both economists and policy makers. Economic growth is defined as the increase in Gross Domestic Product (GDP). Negative growth is a decline in GDP. There are three main reasons

Teaching macroeconomics after the crisis  141 why economic growth is considered to be so important: (1) population growth, (2) distributional conflict and (3) poverty. At the same time, economic growth is a major cause of global warming, as will be discussed later. What causes growth? In other words, what are the determinants of growth? All theories agree that these are the production factors in an economy. This is explained in the growth equation. The growth equation explains the determinants of economic growth. Growth is referred to as GDP growth, as ΔY or simply as g. Economic growth is determined by an increase in size and/or efficiency of the use of production factors in an economy. These are simplified in three categories: capital, including land (K), labour (L) and other (X). Each theory has a different interpretation of X, the other variables behind economic growth. Mathematically, the growth equation can be written as follows: (Yt1 − Yt 0 ) / Yt 0 = ∆Y = g = f ( K , L, X ) The rest of this chapter will explain how each economic theory interprets this equation. Social economics of growth Why quality and values matter Economic growth has never had much importance in social economics. There are three reasons for this. First, in social economics it is the quality of growth which matters more than its quantity. Growth of what? Growth for whom? Second, social economists strongly disagree with the dominant measure of growth, as GDP and its variations. They acknowledge the importance of the community economy, or unpaid economy, which is excluded from this measure, and they emphasise that the substantial size of the community economy shows how biased GDP is. And negative externalities, both social and environmental, need to be subtracted from GDP in order to come up with a more reliable measure of wellbeing based on market transactions. Third, social economists see the efficiency of resource use, enabling growth, as inextricably related to the equity of resources use, the access to resources for all groups in an economy. Despite this criticism, there are social economists who analyse growth. They do so from a broad perspective, in particular including social relationships and ethical values. They point at social values which could be conducive to growth, often referred to as social cohesion. This is the connectedness in a society, which is valuable in itself and helps to overcome economic problems of transaction costs, free riding and moral hazard. These pro-social values also enable collective action and the provisioning of club goods in communities. Measuring social cohesion, however, is recognised to be very difficult. Social economists agree that uni-dimensional measures, such as a survey question of whether people in general trust other people, are inadequate. This is because they do not capture the complexity of social connectedness necessary for civic engagement and for the emergence, spread and continuation of pro-social norms throughout an economy. The perfect measure for social cohesion does not exist, because

142  Irene van Staveren social cohesion is a contextual matter, and its meaning varies with culture, time periods and types of economies. An example of two measures that try to capture at least part of social cohesion can be found in the database Indices of Social Development.24 This database contains a set of six indices, each consisting of about 20 indicators, which try to capture social inclusion and social cohesion in societies. Inclusive growth The social economic view of growth is inclusive growth. This can be defined as economic growth of which the benefits extend to all social groups. Hence, it concerns the social quality of growth. Inclusive growth may also include a concern with the natural environment, trying to do justice to the intrinsic values of nature. Chinese economic growth is currently making a major shift towards environmentally inclusive growth in response to the large negative externalities of economic activity on nature.25 Air pollution is so severe that it causes 100,000 deaths each year, while the Yellow River is severely polluted over one-third of its length, leading to dying fish and human health problems. Now, regulation for polluting industries has become stricter, while China has turned quickly into the world’s largest producer of solar energy panels. The reasoning behind inclusive growth is both social and economic. The social justification of inclusive growth is founded upon a human rights perspective, as part of the UN Social and Economic Rights, namely that human dignity requires that everyone benefits from the wellbeing effects of economic growth. The economic justification of inclusive growth is twofold. The first reason is that social conflict undermines social cohesion, creating distrust and lack of cooperation. This often reflects unequal distributions of growth, with an elite benefitting from growth, while the majority of the population benefits much less or not at all. Social conflict creates social cost, such as strikes and shirking, which in turns reduce growth. The second reason for aiming at inclusive growth is that equality in access to and control over resources improves capacity utilisation in the economy. More labour employed, more waste-land in operation and more human capital used in paid and unpaid productive activities result in less waste and more resource use. For human resources, the minimisation of waste also implies that labour needs to be valued and paid according to its contribution, in order to support both intrinsic and extrinsic motivation. So, when the poor and the socially marginalised, such as ethnic minorities, women and immigrants, are given access to resources and control over these resources, and their contributions are valued and paid accordingly, growth will be enhanced, according to social economic theory. Inclusion crowds-in production and productivity. Let me elaborate on these two dimensions of inclusive growth. First, the social conflict dimension, which undermines social cohesion. When growth is accompanied with rising inequalities, or when growth does not remove existing inequalities, it is likely that social conflict will emerge, for example when vertical

Teaching macroeconomics after the crisis  143 65

55

45

08

07

20

06

20

05

20

04

20

03

20

02

20

01

20

00

20

99

20

98

19

97

19

96

19

95

19

94

19

93

19

19

19

92

35

Diagram 6.10  The decline of the labour share of income between 1992 and 2008 in China.

inequalities, between capital and labour, increase. In China, growth is distributed increasingly unequally between capital and labour. Diagram 6.10 shows the steady decline of the labour share of income between 1992 and 2008 in China and, hence, the increase of the capital share of income. The labour share of income declines in this period of high economic growth from 64% to 47% of total income. Although China is still a communist nation, from 2005 onwards, capitalists have benefitted more from China’s economic growth than labourers. The question is how long this trend can continue without affecting growth itself. The declining labour share of income has led to an increase in social unrest in China, in particular labour protest and strikes. Since 2010, China has shown an increasing number of strikes, from Honda and IBM factories to domestic employers and the communities supporting these. The labour protests concern not only higher wages but also social and political rights. The strikes involve opportunity costs for the affected firms (they cannot produce output) and regularly push labour costs up in an ad hoc way (sudden increases in wages and benefits as a response), affecting China’s international position as a low-labour cost manufacturer. This social unrest may affect China’s export growth, which forms an important part of its GDP growth. The second economic dimension of inclusive growth, the equal access to resources dimension, involves both vertical inequality, between classes, and horizontal inequality, across society, such as along the lines of age and gender. Let me give an example for each. First, inequality in access to land, a vertical inequality between the landowning class and the landless class. Empirical studies in South Africa and Brazil, two countries with very unequal land ownership, have

144  Irene van Staveren shown that much land owned by big landowners is not used. It simply brings status to their owners and provides political power. As soon as this land is redistributed to poor landless farmers, it will be used for the production of food crops (to feed the families who work the land) and cash crops (to sell and earn an income). This increases total production and contributes to economic growth. Moreover, the land that is being used by the big landowners is often worked with relatively more machines than labour power. The reason is not that farm labour is too expensive but that the agricultural capital goods are too cheap, thanks to the lobby activities of the big landowners. They manage, through their political power, to obtain capital subsidies and tax breaks for acquiring machines. So, they over-invest in capital goods and replace labour more than they would have done without their powerful position of large land ownership and strong policy influence.26 Hence, the biased agricultural subsidies also contribute to unemployment. Diagram 6.11 shows how land redistribution contributes to efficiency. The second pie chart shows a larger share of production by small farmers; the pie is also bigger, which demonstrates more total production after redistribution from rich to poor farmers. The second example is about a horizontal inequality, namely gender discrimination. Here, the analysis concerns the comparison of low-growth regions with highgrowth regions in the world and the gender gaps in education and employment in these regions. In the Middle East and North Africa, as well as in South Asia, girls’ school enrolment rates are much lower than boys’ school enrolment rates. Moreover, adult women’s employment rates are much lower than adult men’s employment rates. These two gender gaps in education and employment represent lower access to and control over resources for women as compared to men. When comparing these gaps to East Asia, a region with higher average economic growth rates (4% annually compared with 2% annually in the Middle East and North Africa),

Small farmers Small farmers

25%

75%

Diagram 6.11  Land redistribution and efficiency.

33%

67%

Teaching macroeconomics after the crisis  145 we find that the gender gaps in education and employment are much smaller in East Asia. Econometric analysis has shown that the stronger gender gaps in the Middle East, North Africa and South Asia are responsible for a substantial part of the lower economic growth rates between 1960 and 2000 in these regions – between 0.1 and 1.7 percentage points lower growth. And they had 2% growth, so less gender inequality could have increased growth from 2.0 to rates between 2.1 and 3.7%. The gender inequality in education and employment in the Middle East and North Africa hence implies a substantial loss of economic growth. The social economic theory of growth is based on the insight that equity and efficiency are not trade-offs but rather that the first is a necessary condition for the second. So, the social economic growth equation contains measures of equity: inclusion and equality. This implies that the variable X in the standard growth equation consists of measures of inclusion, for example inclusion of minorities and women in the labour market. Moreover, the other two variables, K and L, will not only be included in terms of size but also in terms of distribution, to measure the extent of inequality, such as inequality in agricultural land distribution and inequality in wages paid to men and women and to different ethnic groups for the same work. ∆Y = g = f ( K , inequality of K , L, inequality of L, X ) in which K = capital, L = labour and X = social cohesion, such as inclusion of minorities, gender equality or intergroup cohesion. Institutional economics of growth Formal institutions of growth Detailed historical research of how rich nations became rich has revealed that they all used similar strategies, from Britain in the eighteenth century and the US in the nineteenth century, to Japan, Korea and Taiwan in the twentieth century. They are referred to as developmental states. These are states which guide the market on a long-run economic development path with subsidies, investments and risk absorption for firms. They all used a mix of strategies based on three types of institutions: redistribution, state intervention and trade protection. Of course, developmental states differ widely in economic structure. Some rely on tourism (for example Greece and Mauritius), others on financial services (for example Luxembourg and Cayman Islands) and still others on manufacturing (South Korea, Taiwan and Brazil). Developmental states also differ widely in their governance structures and politics. They include democratic and authoritarian states, and they consist of federal states, republics and kingdoms. But they all rely on a mix of the three types of growth institutions. Below, I list the ten most common growth institutions, as listed by development economist Ha-Joon Chang (2007).

146  Irene van Staveren STATE-OWNED FIRMS BEYOND PUBLIC GOOD PRODUCTION

These include firms in key sectors such as energy, basic chemicals, and agricultural processing industries. These sectors are preconditions for further economic development. If private firms do not emerge, or only foreign companies with their own interests, public firms need to fill the gap in these sectors. STATE-OWNED BANKS AND DEVELOPMENT BANKS

These are required to finance the development of domestic economic sectors, in manufacturing, infrastructure and services. This helps to prevent dependence on foreign investment and multinational companies. For example, all South Korean banks were state-owned when high economic growth took off in the 1970s. In China, banks are still state-owned. LAND REFORM AND INCOME REDISTRIBUTION

Forty years ago, South Korea and the Philippines had very similar economic structures with the same level of GDP per capita. In the year 1969, their GDP per capita incomes were closest: 242 dollars per year for the Philippines and 237 dollars per year for South Korea. Since then, South Korea has carried out substantive land reform programmes and implemented progressive taxes to finance accessible and good quality education and health care. This resulted in much higher economic growth in South Korea as compared to the Philippines. In 2012, GDP per capita of South Korea was sevenfold that of the Philippines: 32,000 USD vs. 4,400 USD. WIDELY ACCESSIBLE AND GOOD QUALITY FREE EDUCATION AT ALL LEVELS

If the Middle East and North Africa had the girl school enrolment rates of South Asia, its economic growth rate would have been much higher. A similar effect occurs for quality improvements in education. GOOD QUALITY HEALTH CARE AND SANITATION

A healthier workforce generates higher labour productivity, even with low-capital intensity, simply because people are ill for fewer days and have a better physical condition, while better nutrition provides more energy to sustain high levels of work effort, whether physical or mental. INDUSTRIAL POLICY INCLUDING SUBSIDIES FOR SELECTED GROWTH SECTORS

The market suffers from many failures, in particular at low levels of economic development. Mauritius is a good example: it used to be a low-growth sugar plantation economy until the Mauritian government forced a shift to textile manufacturing, which also led to other manufacturing activities. And when international competition from low-wage countries reduced earnings in this sector, the

Teaching macroeconomics after the crisis  147 government forced yet another transition. The economy was pushed to luxury tourism, with yet other spin-off activities such as financial services. INITIALLY LABOUR-INTENSIVE PRODUCTION, LATER CAPITAL/TECHNOLOGY CATCH-UP

Only when the labour reserve is usefully employed will firms experience rising wages and be stimulated to become more efficient. This enables both income growth among the poor and international competitiveness. China seems to have entered this phase now, with labour shortages in its export processing zones, forcing factories to pay wage increases up to 50%. CAPITAL ACCOUNT CONTROLS AND SELECTIVE FDI

When countries strictly control foreign inflows and outflows of capital, they prevent the import of foreign financial crises and prevent sudden outflows of capital. While the Asian tiger economies followed this policy in the 1970s and 1980s, they abandoned it in the 1990s under the global wave of neoliberal policies. With the 1997 Asian financial crisis, they paid a high price for this and lost several years of economic growth. Indonesia, for example, experienced a reduction in GDP of 13.5% and even ten years after the crisis investments had not returned to their pre-crisis levels. INFANT-INDUSTRY PROTECTION

All the now-developed counties had high import tariffs, to protect their infant industries. But they required, through the World Trade Organisation, World Bank and IMF, that developing countries lower their tariffs. This is what Korean development economist Ha-Joon Chang calls “kicking away the ladder.” RULE OF LAW, EVEN WITH HIGH CORRUPTION

Economic growth requires stability. Rule of law helps to create such stability. Interestingly, this does not necessarily imply low levels of corruption or limited bureaucracy. Various tiger economies score high on the corruption index, whereas bureaucracy in China and India is quite extensive. Table 6.6 Country scores of the corruptions index (0–100), selected countries, 2012. Country

Score

Denmark Singapore China India Afghanistan Somalia

100 97 39 35 2 0

Source: World Bank, Worldwide Governance Indicators.

148  Irene van Staveren INFORMAL INSTITUTIONS OF GROWTH

The early work on informal institutions of growth was influenced by a major sociological study on economic growth. It dates back to the year 1905, when sociologist Max Weber posed his hypothesis of a “protestant ethic” as the main driver of economic growth in Northwest Europe and the US. He attributed the economic successes of those days of countries like Germany, England, Switzerland, the Netherlands and Scandinavia to the dominance of Protestantism and its Calvinist values in these countries. He argued that the central values of hard work, the rejection of luxury spending and high savings fuelled economic growth. While, in his view, Catholic nations had lower labour productivity standards and a weaker savings morale, in recent decades this hypothesis has been tested and not much empirical support was found. For example, China is not protestant, but it has been the world’s growth champion for three decades. And Ireland, a Catholic country, was the fastest growing European country in the 1990s, nick-named the Celtic Tiger. Apparently, other informal institutions play a role in enabling growth. Today, institutional economists have found that not so much religion as prosocial norms such as trust and honesty are positively correlated with growth. But there is much debate about the actual indicators and their measurement of the relevant pro-social norms. And it is still unclear what the direction of causality is: do pro-social norms promote growth, or does growth enable the emergence and consolidation of such norms? The same ambiguity appears in the empirical literature on normative formal institutions of growth, such as the rule of law and democracy. In addition, it may well be the case that growth comes first and the solidification of pro-social norms in rules and laws follow. What does emerge from the institutional growth literature is that there can be a trade-off between formal and informal institutions of growth. So, countries with a strong rule of law but much corruption and clientelism can still have relatively high economic growth, for example several tiger economies and baby-tigers such as Thailand and Indonesia. The reason is found in strong bonding social capital with inter-personal norms of trust. Alternatively, countries with a weak rule of law may attract foreign investors to their natural resources, such as Angola. For all the above reasons, the formal and informal institutions of growth do not lead to an unambiguous institutional growth equation. But institutions do matter at a general level, which can be included in the growth equation as follows. ∆Y = g = f ( K , L, X ) in which, as in social economics, the distribution of capital matters: the more equal, the higher the growth. But the origin of K also matters: the more domestic origin, the more stable capital, and the more stable private and public firms. This we can indicate as the domestic/foreign capital ratio: Kdom / Kfor. For labour, what matters is not so much the quantity of labour but the quality of human resources. This is indicated through a new variable under X: HR. The higher HR, the higher the growth. Finally, X includes developmental institutional variables. But since there is much debate about their measurement and causality,

Teaching macroeconomics after the crisis  149 these will not be specified here. The institutional growth equation, hence, is as follows: ∆Y = g = f ( K , equality of K , L, HR, developmental institutions ) Post Keynesian growth theory Demand-led growth In Post Keynesian economics, growth is driven by the demand side. So, economic growth analysis focuses on AD. Remember the macroeconomic equation, which defined AD as the aggregation of consumption, investment, government expenditures and net exports: AD = Y = C + I + G + EX − IM This means that growth can be stimulated by four factors: more domestic consumer demand, more investment, more net government expenditures or more export demand. So, growth is a matter of stimulating demand. How can this be done? STIMULATION OF CONSUMER DEMAND: C

This can be done through lowering taxes for households. Think about income taxes and value added taxes. This leads to higher disposable income. With a stable propensity to consume, a higher disposable income translates in higher consumer demand, according to the consumption function: Yd = Y − T C = cYd + C * Let us assume that Y = 1500 billion Euros. The tax rate is 20%, which makes disposable income 1200 billion Euros. When the propensity to consume is 80% and autonomous consumption 140 billion Euros, consumer demand can be calculated as follows (in billion Euros): C = 0.8Yd + 140 C = (0.8×1200) + 140 C = 960 + 140 = 1100 Let us assume that the average tax rate is reduced from 20% to 18%. This increases disposable income: Yd = Y − 0.18 Y Yd = 0.82 Y Yd = 0.82×1500 = 1230

150  Irene van Staveren From this new disposable income, we can recalculate consumer demand: C = cYd + C * C = 0.8Yd + 140 C = (0.8×1230) + 140 C = 1124 So, the new consumer demand has increased from 1100 billion Euros to 1124 billion Euros. With all other variables in the AD equation remaining constant (ceteris paribus), AD will increase directly by 24 billion Euros. Assuming that AS will adjust to this higher demand by increasing domestic production, the economy will grow directly by 24 billion Euros. This is 2% economic growth. But there are also indirect effects, through the multiplier of the increased consumer expenditures. Remember that the multiplier is the increased demand factor multiplied with 1 / (1 − c). In this example, the stimulation of the economy through C is 24 billion Euros. Hence, the multiplier of this stimulation of consumption with a tax reduction is:

24 24 = = 120 billion Euro 1− 0.8 0.2 Hence, the total effect of the tax reduction on economic growth is not 24 billion Euros but 120 billion Euros. This is (120 / 1500) × 100% = 7.5% economic growth. STIMULATION OF INVESTMENT: I

The second variable through which AD can be increased is investment. Limiting ourselves to domestic investment, the Post Keynesian perspective states that this can be increased by providing more stable financial markets with less uncertainty and lower risk, as we have seen in the chapters on financial markets and on money. There is a variety of policy measures possible to contribute to this. One example is to have stable long-term industrial policy, in which a system of subsidies, fiscal advantages, and regional planning is set out clearly and implemented for at least ten years. This may invite private investment in the economy, in particular in growth sectors selected by the state. The increased investment will directly increase AD (again, ceteris paribus), and with a response from AS, the economy will grow by the size of the additional investment. STIMULATION THROUGH AN INCREASE IN NET GOVERNMENT EXPENDITURES: G

The third pathway to Post Keynesian economic growth is through increasing G, without raising T (taxes) to the same extent. This is what is meant by an increase in net government expenditures. Of course, the additional G should be spent in

Teaching macroeconomics after the crisis  151 such a way that it stimulates growth. As we have seen earlier, Keynes argued that as long as it is spent productively, it does not matter how: any increase in G will increase national income, even a public work project of digging holes one day and filling them up the next day. But a more effective and lasting effect on growth would involve smarter policies. For example, extension and improvement of physical or social infrastructure: roads, public housing, sanitation and education. STIMULATION THROUGH EXPORT DEMAND: EX

The fourth and final pathway to stimulate AD is by exporting more goods and services to consumers abroad. This implies the stimulation of foreign demand. How to do this? One way to do this is through a currency devaluation, which makes the exporting country’s currency cheaper for foreign buyers. Hence, their export prices will be lower for foreign consumers, which is an incentive to buy more products from this country. The four pathways to stimulate AD (through C, I, G and EX) are not complete without a fifth policy measure that is key to Post Keynesian theory, namely redistribution. This source of demand relies on the differences between capital and labour classes in their propensity to consume. This parameter, c, is higher for the labour class than for the capitalist class. Simply because the capitalist class has sufficient disposable income to satisfy its consumer needs and therefore is able to save more money. The example below shows how a redistributive policy, through a progressive tax rate, shifts disposable income from capitalists to labourers, and thereby increases C, without changing anything in the other variables, such as taxation or government expenditures. The tax policy simply shifts tax burdens between the two classes but does not change the total tax burden and, hence, it will not change total tax revenue and net government expenditures. With these five types of stimulus to AD, I have described the direct increase in AD and, with an immediate response by AS, in national income (or GDP). This, then, describes economic growth from the demand side of the economy. But these direct effects trigger indirect effects, leading to the multiplier effect. Again, we discussed this earlier: the multiplier effect of a macroeconomic variable involves indirect effects, which together lead to the total effect on AD. Remember that the multiplier effects of C, I, G and EX follow the following processes: • • • •

More demand allows for more product sales, which in turn increases the demand for labour to produce the additional goods and services. More production requires more investment, which in turn increases AD. More employment generates more income for households, which in turn increases consumer demand. More income generates higher tax revenue, which enables increases in government expenditures.

152  Irene van Staveren In conclusion, Post Keynesian growth theory understands economic growth as driven by the demand side of the economy, which has five sources: consumption, investment, government expenditures, exports and redistribution of income from high to low-income earners. The multiplier effect increases initial changes in demand, so that the total effect on economic growth is larger than the initial effect from the five sources of demand. Endogenous growth The Post Keynesian perspective understands economic growth as endogenous, not driven by exogenous factors such as technological innovations or random shocks but rather caused by economic dynamics itself. The foundational equation for endogenous growth is the definition that investments equal savings. And savings are the residual from income minus consumption, as you will remember. In equations this reads: S =Y − C and S=I So, investment is not determined by the level of the interest rate but by the level of savings available after consumer demand is met (if, of course, savings do not leak away to abroad or the FIRE sector). Moreover, the class disaggregation typical for Post Keynesian economics explains that most, if not all, savings come from  capitalist incomes and not from labour incomes. Simplified, all savings come from capitalist incomes, which are earned not from wages but from profits. In an equation: I = sR in which s is the propensity to save out of profit income and R is profit income. When we divide both sides of the equation by the stock of capital, K, we arrive at the following equation: I / K = sR / K Remember that R / K is r, the profit rate. And I / K is the growth rate of the economy, g, when assuming that capital is the binding constraint, and not labour. Labour is assumed to be abundant in Post Keynesian economics, given a labour reserve and persistent unemployment in many real-world economies. So, we can re-write the equation as follows, which gives the Post Keynesian growth equation: g = sr

Teaching macroeconomics after the crisis  153 This equation means that economic growth is the product of the propensity of capitalists to save and the profit rate. This formulation of economic growth is endogenous. Why? Because growth (g) and the profit rate (r) are determined at the same time. Profits in the Post Keynesian model are determined by the bargaining process between capital and labour, in which capital has more bargaining power when there is unemployment. Workers need to find a job and are dependent upon capitalists hiring them, while capitalists can choose among more labour than they need, either due to low AD or due to technological development substituting labour for machines. So, when profit income is high and wage income low, savings will be high and, hence, economic growth will be high through investments out of these savings. If, of course, savings don’t leak away to the rest of the world or remain in financial assets in the FIRE sector . . . And there is another endogenous dynamic at play, namely the demand for goods and services, as we discussed earlier. When wages are low, household consumption will be affected, because workers have low incomes with low wages, so their consumption will be constrained. And with low consumer demand, growth will be constrained (ceteris paribus). When more income flows to wages, incomes increase and hence consumer demand goes up. But the lower profit going to capitalists will reduce the growth rate. You can see that from the growth equation above: when r, the profit rate, declines, g, economic growth, will also reduce. This endogeneity of growth implies that growth may be driven either by profits (but constrained by low consumer demand), or by wages (but constrained by investments, because sR = S = I, so lower profits generate lower investments). For some countries, growth is profit-led, whereas for other countries, growth is wage-led. In the profit-led strategy, low consumer demand is the binding constraint due to low wages. The solution to this constraint is exports, which adds consumer demand from the RoW to the economy. The more exports, the more demand (EX) and, hence, the higher AD. Thus, a profit-led growth strategy can continue to pay low wages, as long as foreign consumers are willing to buy the country’s products. China is a good example of such strategy. In the wage-led strategy, low investment is the binding constraint, due to low profits from which capitalists can save money to invest. Again, the RoW provides a solution through encouraging foreign investment to flow into the country. So, low domestic investment is compensated by investment flows from abroad. This also stimulates AD, not through C, as in the wage-led strategy, but through I, in the profitled strategy. In conclusion, going back to the standard growth equation, growth in the Post Keynesian perspective is not a function of L nor of any other “X-factor.” Growth only depends on capital, but it thereby depends on the distribution of income over capital (R) and labour (W) and on the profit rate obtained from product sales to consumers (C and EX). So, we can re-write the growth equation from a Post Keynesian perspective as follows: ∆Y = g = sr = I / K

154  Irene van Staveren in short: ∆Y = I / K in which I is the complement of consumption (I = S) out of profit income (R): the higher R, the higher capitalist savings (S) and hence investment (I): I = f ( R) and in turn profit depends on the distribution of income over profits and wages: R =Y − W Hence, economic growth, g (= ΔY) partly depends on how Y is distributed. That is precisely what is meant by endogenous growth. China has an average growth rate of 10% over several decades (g = 0.10). The investment rate (i) has been around 40% since 2005 (i = 0.40). Hence, the capital/ output ratio (k) is 4, using the Post Keynesian growth equation above.27 ∆Y = g = I / K 0.10 = 0.40 / 4 Hence, China’s growth is a combination of a high savings rate and a low capital/ output ratio, indicating that the available stock of capital produces relatively much output per unit. Partly thanks to an educated and healthy labour force, generating high labour productivity.

Notes   1 This chapter is based on my textbook (van Staveren, 2015): Economics After the Crisis – an Introduction to Economics From a Pluralist and Global Perspective. London: Routledge.   2 PBS News hour Transcript. 23 October 2008. URL: www.pbs.org/newshour/bb/ business/july-dec08/crisishearing_10-23.html   3 Frederic Mishkin and Tryggvi Herbertsson, “Financial Stability in Iceland.” Reykjavik: Iceland Chamber of Commerce, 2006.   4 http://rwer.wordpress.com/2010/05/13/keen-roubini-and-baker-win-revere-awardfor-economics-2/   5 Paul Krugman, “Frustrations of the Heterodox,” The New York Times, 25 April 2014.   6 Palin, Adam, “Financial Crisis Forced Business Schools to Change Curriculum,” Financial Times, 23 June 2013.   7 www.worldeconomicsassociation.org/   8 www.post-crasheconomics.com/   9 www.isipe.net/ 10 www.up.ac.za/human-economy-programme 11 http://core-econ.org/ 12 www.hetecon.net/documents/The_prospects_for_a_new_economic_curriculum.pdf

Teaching macroeconomics after the crisis  155 13 The course is called Introduction to Economic Theories and has had almost 10,000 learners up to mid-2019. The course can be found on the Coursera platform: www. coursera.org/learn/intro-economic-theories 14 Macroeconomic flow visualiser: http://econviz.org/macroeconomic-circular-flowvisualizer/ 15 Pellegrini, Lorenzo, and Luca Tasciotti, “Bhutan: Between Happiness and Horror,” Capitalism, Nature, Socialism, 2014. Online publication: http://dx.doi.org/10.1080/ 10455752.2014.898673 16 UNDP, Humanity Divided: Confronting Inequality in Developing Countries. New York: UNDP, 2013. 17 Wilkinson, Richard, and Kate Pickett, The Spirit Level. New York: Bloomsbury Press, 2009, p. 67. 18 See note 17. 19 See note 17. 20 See note 17. 21 Thomas Piketty, Capital in the Twenty-First Century. The Belknap Press of Harvard University Press, 2014, p. 249. 22 This is estimated by Thomas Piketty; see note 21. 23 See note 21, page 166. 24 www.IndSocDev.org 25 Source for the numbers for China: Barry Naughton, The Chinese Economy, Transitions and Growth. Cambridge (MA): The MIT Press, 2007. 26 See for the full study on this example: Van den Brink, Rogier, Hans Binswanger, John Bruce, Glen Thomas and Frank Byamugisha (2006) “Consensus, Confusion and Controversy. Selected Land Reform Issues in Sub-Saharan Africa.” Working Paper no. 71. Washington D.C.: World Bank. 27 See note 26.

References Chang, Ha-Joon (2007). Bad Samaritans: Rich Nations, Poor Policies, and the Threat to the Developing World. London: Bloomsbury Press. Keen, Steve (2001). Debunking Economics: The Naked Emperor of the Social Sciences. Annandale: Pluto Press. Piketty, Thomas (2014). Capital in the Twenty-First Century. Cambridge, MA: The Belknap Press of Harvard University Press. Shiller, Robert J. (2010). “How should the financial crisis change how we teach economics?” Journal of Economic Education 41 (4), pp. 403–409. Van Staveren, Irene (2015). Economics after the Crisis: An Introduction to Economics from a Pluralist and Global Perspective. London: Routledge.

7

Asymmetric price adjustment and other issues in Keynesian macroeconomics1 Victor A. Beker

Introduction Most macroeconomics of the past 30 years was spectacularly useless at best, and positively harmful at worst. (Paul Krugman, Economist, 18–24 July 2009: 58) In the last three decades, the methods and conclusions of macroeconomics have deteriorated to the point that much of the work in this area no longer qualifies as scientific research. (Romer, 2016: 1)

In a recent article on the reasons why the Great Recession has had little intellectual impact on economic theory, Krugman (2018) argues it was because the DSGE model was “good enough for government work.”2 The policy responses based on it prevented a new Great Depression. However, he makes an important exception: “The one big exception to this satisfactory understanding was in price behaviour. A large output gap was expected to lead to a large fall in inflation, but did not. If new research is necessary, it is on pricing behaviour.” Precisely this is the main subject of the present chapter. In the real world, prices do not behave symmetrically. Usually, nominal wages and prices are sticky downward but a lot more flexible upward; the latter is illustrated by inflationary and hyperinflationary processes. “As documented by many authors for many countries (e.g. Cover, 1992), positive demand shocks give rise to inflation without affecting output significantly, while negative ones reduce output without affecting inflation” (Dobrynskaya, 2008: 713). In fact, examining quarterly US post-war data, Cover (1992) concluded that positive shocks in the money supply have had no effect on output, whereas negative shocks reduced output. De Long and Summers (1988) had reached similar conclusions in their investigation of annual pre-and post-World War II US data. The same results were obtained by Rhee and Rich (1995) and Karras and Stokes (1999) for European countries by implementing the method regarding asymmetry first introduced by Cover (1992).

Price adjustment and other issues  157 An empirical estimation of the Phillips curve on UK quarterly data for 1977Q1–1995Q1 by Fisher et al. (1999:78) “raises the interesting possibility that the effect of the output gap on inflation is asymmetric, with a positive output gap exerting more inflationary pressure than the deflationary pressure exerted by a negative output gap of the same size.” After studying over 240 markets for consumer and producer goods, Peltzman (2000) concluded prices rise faster than they fall, and price asymmetries are persuasive, substantial and durable and exist in periods of low inflation and high inflation. The author asserts that this asymmetry is fairly labelled a “stylized fact.” This fact poses a challenge to theory. The theory of markets is surely a bedrock of economics. But the evidence in this paper suggests that the theory is wrong, at least insofar as an asymmetric response to costs is not its general implication. (ibid.: 493) So, it is a very well-established empirical regularity that positive demand shocks have a tiny effect on output and they basically pass to prices, while negative shocks are, to a larger extent, passed to output. Nominal prices are sticky-down and the main effect of a negative shock is absorbed by output. However, the downward price flexibility assumption plays a key role in neoclassical economics. Most mainstream economics is built upon the assumption that nominal prices are equally flexible in both directions. Flexible prices are the magic instrument that clears markets. This leads to quite unrealistic and erroneous predictions as far as downturn in economic activity is concerned. In fact, what we usually see – and empirical evidence corroborates – is that, in the presence of a negative shock, quantities – not prices – fall. If nominal prices are downward rigid, they cannot clear markets in the presence of an excess supply, and there is no wealth effect that re-establishes the level of aggregate demand at its full-employment level, as mainstream economics maintains. Even worse, in the presence of inflation, policy recommendations based on the symmetry assumption lead to contractionary measures which depress the level of activity with minimum effect on the price level. Stagflation is the result. Given price asymmetry, it is necessary to do two separate analyses: on the one hand, full-employment macroeconomics (price equilibrium macroeconomics) and, on the other, the macroeconomics of recession and depression (Keynesian macroeconomics). Prices play a role in the first case but none in the second; the mechanisms at work in the first case are quite different from the ones in the second. The reason is that in the real world there seems to be a nonlinear relationship between price flexibility and the inflation rate: prices are downward rigid but become more and more flexible as the inflation rate grows.3 In other words, downward adjustment takes place via quantities rather than prices; the opposite happens in the case of an upturn in demand, when prices respond faster than quantities.

158  Victor A. Beker The present chapter aims to point out the need for reconstructing macroeconomics from a realistic point of view. Why do we need realism in economics? There has been a long-lived discussion on the subject of realism in economics. Its main milestones have been Milton Friedman’s contribution in his 1953 essay “The Methodology of Positive Economics” and Paul A. Samuelson’s response ten years later in “Problems of Methodology: Discussion.” In their famous June 2000 manifesto, the Parisian graduate students who led the struggle against “autistic science” complained, “this disregard for concrete realities poses an enormous problem for those who would like to render themselves useful to economic and social actors.” The main fact that must be taken into consideration is that economics, and especially macroeconomics, is supposed to be a guide for economic policy. This is the context in which the issue of realism must be discussed. Let us give a simple example of what happens when we use unrealistic assumptions. If we assume that lions are herbivorous, we will predict that any human being will be safe in the presence of a lion. Unfortunately, for the human beings in the real world, lions are carnivorous. That assumption may be useful to depict what an ideal world of peaceful coexistence between both species would be, but it is a very dangerous guide for human being action. In the same way, many assumptions in mainstream economics are adopted only because they facilitate the analytical treatment of the problem; in some others, it is just because of elegance.4 As with the case of the lion, those assumptions unfortunately lead to predictions far different from what happens in the real world, and with equally tragic consequences, as the 2008 crisis pointed out. Mainstream economic theory did not even consider the possibility of the type of collapse that the subprime mortgage meltdown unleashed, let alone the appropriate ways to deal with it. It is true that the premises of any economic model are always “inexact” because they make abstract numerous causal factors that are present besides those effectively taken into consideration. This is the method used in all sciences when there is a complexity of causal factors (Hausman, 1992: 148). As Mäki (2005: 304) rightly states, models serve as “substitute systems” of the target system they represent. They are substitute systems in the sense that one does not directly examine the target systems, rather one focuses on the properties and behaviour of the representatives as substitutes of the targets. The target system is too complex to be understood in its entirety, so a simpler model is constructed to explore it (Hodge, 2007: 26). However, not just any substitute system will do; the representative model must adequately resemble the target system where “adequately” depends on the intention or purpose of the model (ibid.). As Mäki asserts, “thought experiments” replace the “material experiments” of the natural sciences.

Price adjustment and other issues  159 Therefore, by definition, every model implies a certain degree of unrealism in its assumptions – it is a simplification of the real world. But it is one thing to simplify reality and quite another to overtly distort it. The representative model must resemble the target system. I have referred elsewhere (Beker, 2016a, 2016b) to several of the unrealistic neoclassical assumptions (price symmetric flexibility, unbounded rational expectations, no coordination problems, the representative agent, etc.) This time, I deal with the price flexibility assumption. This chapter argues that price downward rigidity must be a fundamental assumption in any economic model which tries to explain and predict real-world market behaviour as well as recommend economic policies. I go on arguing that realisticness is precisely one of the features that distinguishes Keynes’s unemployment analysis. For this reason, Keynesian macroeconomics has to be the point of departure for a realistic reconstruction of macroeconomic theory. Keynes’s economic theory was designed to explain the causes of the 1930s economic crisis and fight against its consequences. In principle, this theory seems better equipped to deal with subjects like unemployment, recession and depression than the neoclassical one, which does not even consider a deep crisis as a possibility. I add that price downward rigidity fits perfectly well the Keynesian model, while this does not happen with either the New Keynesian or the Post Keynesian models.

Price symmetry is an unrealistic assumption In the real world, price behaviour is not at all symmetric. It is a curiosity that even Friedman (1953: 165) recognised: “At least in the modern world, internal prices are highly inflexible. They are more flexible upward than downward.” He did this in the context of an argument in favour of flexible exchange rates but he ignored it when dealing with goods market clearing.5 Asymmetry in price behaviour requires one approach to analyse an economy in full-employment and another one to study an economy facing unemployment. We need an economic theory that can explain involuntary unemployment but which, at the same time, allows for the existence of inflation. But, as prices behave in a different way in each case, we need two different approaches. In traditional mainstream economic theory, there is no room for involuntary unemployment. As wages are assumed to be downward flexible, any labour market surplus will be removed by a fall in nominal wages.

Realisticness and Keynesian macroeconomics As I have said before, realisticness is one of the features that characterises Keynes’s analysis. Keynes was a practical-minded economist. In contrast to many past and present economic theorists, he had great practical experience in economic policy. He did use simplifications of economic reality – the propensity to consume is one

160  Victor A. Beker of them – but they allowed him to reach significant practical results. Recovering Keynes’s original legacy and pointing out its relevance for dealing with current economic problems is the starting point for a realistic economic theory. Let me emphasise: I’m just talking of the point of departure. Of course, many things have changed since Keynes published his General Theory in 1936, and there are also some gaps in his reasoning that need to be filled.6 In this chapter, I just argue that Keynes’s approach to macroeconomics is still a relevant model of how to deal with economic issues. Taking it as a departure point, a research program has to be developed in order to update Keynesianism to twenty-first-century realities.7 But as in any building, foundations play a decisive role. I argue here about the foundations of macroeconomics and, particularly, on the role of the asymmetric price behaviour in them. As a matter of fact, from Adam Smith up to John M. Keynes – passing through David Ricardo and Alfred Marshall – economics was understood as an instrument to explain real-world phenomena and guide economic policy. After Keynes, a turning point in economic theory development took place. The assertion by Friedman that assumptions’ conformity to reality has no relevance from a methodological point of view was interpreted as equivalent to anything goes. Since then, economics has become more a branch of mathematics than an empirical science. Assumptions are mainly adopted because they facilitate the analytical treatment of the problem, no matter if they agree or not with what happens in the real world. On the other hand, given the difficulties of testing economic theories, it is very strange to see a theory disregarded because of an apparent disconfirmation. Therefore, neither assumptions agreement with the real world nor conformity between predictions and reality seem to be relevant. The only things that matter are internal consistency – as happens in mathematics – and agreement between predictions and the researchers’ expectations. The return to the Keynesian approach means recovering economics as an empirical science. While Keynesian macroeconomics considers full employment as a particular and unusual case, mainstream neoclassical macroeconomics deals only with full-employment macroeconomics. Many of its predictions and recommendations are flawed because they are based on the assumption that prices are downward flexible. They resemble the recommendations made for a world where lions are herbivorous.

Keynesian macroeconomics Let us make a quick review of Keynes’s ideas. This is necessary in order to distinguish what Keynes really contributed to the economic analysis since interpreted by the anti-Keynesians and several kinds of “Keynesians.” The starting point of Keynesian macroeconomics is that the labour market does not necessarily clear. There is no self-adjusting mechanism in the labour market that ensures full employment. This has been the key contribution from Keynes. The most likely situation in the labour market is one of involuntary unemployment, where labour supply exceeds labour demand.

Price adjustment and other issues  161 C, I

C

I0

I0

45º Y0 (N0)

Y

Figure 7.1  Equilibrium in the goods market.

Involuntary unemployment has nothing to do with real wage rigidity; for Keynes, there is no real wage rigidity. On the contrary, as Keynes argued, although workers will usually resist a nominal wage reduction, they will not resist moderate reductions in real wages because of an increase in prices (Keynes, 2016: 13). While nominal wages are downward rigid, real wages are flexible. The huge fluctuations in employment studied by Keynesian macroeconomics are related to fluctuations in the level of output, not to the level of real wages. In the same way, Keynes also disregarded the role of prices in eliminating any discrepancy between aggregate supply and demand. The equilibrium8 in the goods market is attained when demand (consumption plus investment) equals aggregate supply. If there is a general glut, firms would reduce their supply (and employment), not prices, until equilibrium is reached. Investment (Io in Figure 7.1) plays a key role in determining the level of employment. Employment is determined in the goods market at the intersection point between the aggregate supply and aggregate demand for goods (Yo). Fluctuations in investment are responsible for fluctuations in aggregate output (Y) and thereby in employment. In short, the aggregate demand function is D(N) = C(N) + l

(7.1)

where N is the level of employment, C(N) is consumption and I is investment. The equilibrium in the goods market requires excess aggregate demand to be zero at some level of employment: D(N) – Y(N, K0) = 0

(7.2)

162  Victor A. Beker where Y (N, Ko) is the aggregate supply function for a given level of capital stock Ko. So, employment is determined as the inverse of the excess demand function for given values of investment, namely the exogenous variable: N = g (I, K o )

(7.3)

Given the organisation, equipment and technique of production, employment is a function of the level of investment. Unfortunately, no mechanism guarantees that the level of investment will be the one that leads to full employment. If Q = h (N, Ko) is the aggregate production function and Y = Q × p where p is the general level of prices, the real wage is given by: w / p = Q N ( N, K o ) = h N (I, K o )

(7.4)

where w is the nominal wage and QN(N, Ko) is the marginal productivity of labour for a given level of capital Ko. The real wage rate is a function of the level of employment or, ultimately, of the level of investment.

Non-price equilibrium economics vs. price equilibrium economics In the previous section, no role was ascribed to prices in reaching equilibrium. In orthodox economics, they are the magic instrument that clears markets. In Keynesian macroeconomics, quantities (income, consumption, investment, savings, et cetera) are related to other quantities, while the role of prices is de-emphasised. For example, in the Keynesian model, a decline in the investment goods demand would have a direct impact on the level of the aggregate output via the multiplier. The reduced level of investment will equal the level of saving at a lower rate of interest. The fall in the rate of interest will only have a second-order effect on the level of consumption, if any. On the contrary, in the neoclassical model the fall in investment would be followed in the first place by a decline in the rate of interest, which will stimulate consumption. Therefore, the level of aggregate demand will remain unchanged: only its composition would change. Phelps (1970) and Lucas (1976) introduced the need for proper microfoundations in macroeconomics. By that they understood the use of the Walrasian microeconomics from the Arrow and Debreu model, where prices are the tool that clears all markets, including the labour market. The Walrasian general equilibrium model is the cornerstone of mainstream economics which, for that reason, should be called price equilibrium economics – not just equilibrium economics, as Lucas baptised it. Once the price clearing markets assumption is introduced in macroeconomics, the possibility of involuntary unemployment disappears. Excess labour supply will push wages down until unemployment vanishes.

Price adjustment and other issues  163 If you accept the Walrasian approach, prices clear all markets. If so, wage/price stickiness seems to be the only line of defence available to justify Keynesian unemployment in a Walrasian context; the New Keynesians resorted to it.

The New Keynesian contribution: real business cycle models plus sticky prices The New Keynesian program was mainly interested in proving the non-neutrality of money in the short run. If money is not neutral, its expansion or contraction will have an impact on output, at least in the short run; then, there is a role for monetary policy. This is the point New Keynesians were interested in making. For this purpose, the New Keynesians needed a microeconomic model in which prices would not fully respond to excess supply or demand. Their starting point had to be imperfect competition, which implies that firms set prices and the demand chooses quantities. Thus, changes in demand always cause changes in output in the same direction. They had empirical support in Blinder et al. (1998). Blinder and his colleagues interviewed, between 1990 and 1992, two hundred randomly selected firms about their pricing behaviour. They collected “what may be the first evidence on price stickiness ever derived from a random sample of the whole economy” (Blinder, 1994: 120). This stickiness appeared to be symmetric. From the theoretical point of view, there are several theories arguing why prices might be sticky. For instance, one argument is coordination failure (Stiglitz, 1999; Cooper and John, 1988; Ball and Romer, 1991). Stiglitz argues that the risks associated with wage and price adjustments may well be larger than those associated with output adjustments, at least for goods that could be stored. Ball and Mankiw (1994) use a menu cost model to explore a possible explanation for price adjustment asymmetry. In order to sell their products, firms have to write prices on menus, catalogues and tags; changing prices may be rather costly. If we assume positive trend inflation, a firm that wants to lower its relative price may save the menu costs just waiting for inflation to do the work. However, as Mankiw (1985) himself had to admit, these menu costs are small and, therefore, they provide a very weak foundation for fixed-price models. It is true that menu costs are usually small, but it is also true that if the rate of inflation is positive, inflation may itself adjust relative prices. The significant argument for price asymmetry is not menu costs but the fact that if you need to reduce a relative price, you can rely on inflation to do it. You do not need to change the price: time will do the job. With trend-expected inflation, nominal prices are sticky when a firm’s optimal real price falls. Note that it is the presence of trend-expected inflation that generates the asymmetric nominal price response. This is an important reason for nominal price adjustment asymmetry in the real world. With Ball and Mankiw’s article as the main exception, most of the New Keynesian contributions tried to identify reasons for the lack of response of prices both up- and downward. In their models, prices are sticky both up- and downward. The New Keynesian point of view is summed up by Ball et al. (1988: 12): after

164  Victor A. Beker recognising that “traditional Keynesian models often imply asymmetric effects of demand shifts,” they argue that “asymmetric effects of shocks could arise from asymmetric price rigidity – prices that are sticky downward but not upward – but this is another appealing notion that is difficult to formalise” (italics mine). However, if we want to reflect what happens in the real world, we need a model where prices do not respond to excess supply, although they may well respond to excess demand. This was the original Keynesian assumption. We need a model that is apt to explain involuntary unemployment but allows for the existence of inflation and hyperinflation. It is true that Blinder et al. (1998) did not find asymmetric stickiness.9 This might be true for environments of very low inflation, but it seems rather difficult to make sluggishness in upward price adjustment compatible with medium and high inflation. On the contrary, overshooting is a common phenomenon in high inflationary processes. In the real world, prices are downward rigid but become more and more flexible as the inflation rate grows.10 Sticky-price models fail to provide a useful empirical description of the inflation process. New Keynesian economics was supposed to be the answer to the Lucas critique. But “New-Keynesian economics is the art of finding Keynesian results in a NewClassical framework” (Melmiès, 2008: 4). The difficulty is that once you take New Classical assumptions, you get New Classical conclusions. The New Keynesian models have little to do with Keynesian macroeconomics. Rather, they are simply real business cycle models supplemented with sticky prices and wages. As Hill (2017) points out, “in Arrow–Debreu, general equilibrium is achieved because the conditional intentions of all the agents are pre-reconciled before final commitments are made.” In the same way, the New Keynesian Dynamic Stochastic General Equilibrium (DSGE) models “implicitly assume that the plans of market participants are pre-harmonized.” On the contrary, “Keynes’s economics is ‘economics without the pre-reconciliation of plans,’ which is really the crucial distinction,” Hill remarks. The New Keynesian program devoted a lot of effort to finding microeconomic foundations for real wage rigidity. However, strictly speaking, unemployment due to rigid wages is the (classical) voluntary kind of unemployment. A reduction in real wages will reduce/eliminate the kind of unemployment found in New Keynesian models; it has nothing to do with Keynes’s involuntary unemployment. Let us remember Keynes’s definition of involuntary unemployment: Men are involuntarily unemployed if, in the event of a small rise in the price of wage-goods relatively to the money-wage, both the aggregate supply of labour willing to work for the current money-wage and the aggregate demand for it at that wage would be greater than the existing volume of employment. (Keynes, 2016: 14) Therefore, in the Keynesian framework, involuntary unemployment persists even if real wages are reduced. In the New Keynesian framework, unemployment is the result of real wage rigidity. Unemployment in New Keynesian models is not at all

Price adjustment and other issues  165 Keynesian. Involuntary unemployment means, by definition, a non-optimising behaviour; that is why it is called “involuntary.” New Keynesians tried to show that unemployment is compatible with optimising behaviour, while Keynes was talking about a non-optimising involuntary behaviour. The New Classical answer to the New Keynesian arguments was straightforward: remove rigidities and you will have no unemployment; in one way or another, unemployment is voluntary. In Lucas’s words, “there is also a voluntary element in all unemployment, in the sense that however miserable one’s current work options, one can always choose to accept them” (Lucas, 1978: 354). Unemployment, in this context, is voluntary by definition: it exists only because there is some constraint which keeps real wages from finding their equilibrium levels. Of course, this means that, for example, you have to call “voluntary” unemployment rates of 25%, as Spain and Greece witnessed not long ago. Then, if you do not feel comfortable calling “voluntary” a 25% rate of unemployment, you better get rid of the wage market clearing assumption. If you want to get involuntary unemployment, you cannot assume that the labour market clears. This is what Keynes did. As we have already shown, in the Keynesian model the level of employment depends on the goods market, where the volatile, and thus determinant, factor is investment. Whenever there is a deficiency in investment – and hitherto in aggregate demand – there will be unemployment. There is no force in the economy that pushes the aggregate demand to its fullemployment level. In Keynes’s words, the propensity to consume and the rate of new investment determine between them the volume of employment, and the volume of employment is uniquely related to a given level of real wages – not the other way around. (ibid: 27, emphasis mine) Thus, there is no self-adjusting mechanism in the labour market that ensures full employment. In the Keynesian model, it is not true that real wages and the level of employment are determined by the intersection of the labour demand with the labour supply. The level of employment (No in Figure 7.2) and the marginal productivity of labour QN define an equilibrium point on the labour demand schedule (A). Involuntary unemployment is measured by the distance AD. Workers earn a real wage (w/p)o which equals the marginal productivity of labour, as shown in Equation (7.4) above, but it does not necessarily equal the marginal disutility of labour. The neoclassical economics argument is that in such a situation wages would fall under the pressure of excess supply. In fact, in the labour market there will be excess supply – there is involuntary unemployment measured by AD – but even if real wages fall – for example, from (w/p)o to (w/p)1 – the volume of employment will not increase; point B depicts this situation, but it is not an equilibrium point because firms are prepared to pay higher real wages (w/p)o for that level of employment.11 A is an equilibrium point, but neither B nor C is an equilibrium point. If there has been no change in the goods market, there is no reason why firms should

166  Victor A. Beker

W/P LD

LS

(W/P)0

A

(W/P)1

B

N0

D

C

N1

N

Figure 7.2  The level of employment in the Keynesian model.

hire N1 instead of No, whatever the real wage is. There are no economic forces at work to drive the labour market to C. But this does not imply that real wages cannot fall to (w/p)1 as New Keynesians assume.

The Post Keynesian approach to price behaviour Post Keynesians economists offer different microeconomic foundations to Keynesian macroeconomics. They argue that prices are sticky because firms prefer stable prices and that is why they do not react to changes in demand. Firms act in a world of fundamental uncertainty, and they want stable prices to cope with that sort of world. “In ‘Post-Keynesian markets,’ price rigidity comes from price stability which is desired by firms on decentralized markets” (Melmiès, 2008: 14). Firms prefer price stability to maximising profits. “Firms set prices they keep unchanged for a certain period. If costs increase during this period, profit margins will decrease” (ibid.). It is output rather than price which fluctuates over the cycle. Prices reflect both production costs at the normal level of output and the demand for retained profits to finance the planned level of investment expenditure. The latter determines the size of the mark-up or margin on costs. Although there are different versions of Post Keynesian price theory, the essential idea is that “firms fix prices based on some measure of costs, rather than as a reaction to demand fluctuations” (Lavoie, 2001: 21).

Price adjustment and other issues  167 For our purposes – which have to do with how to introduce price behaviour in macroeconomics – this argument shares the difficulty pointed out above: prices are sticky both up and down. But sticky prices never prevented inflation from happening in the real world. And Keynes never ignored inflation as a possibility. Therefore, the Post Keynesian approach is, in this respect, subject to the same critique as the New Keynesian one.

How do markets reach a non-price equilibrium? Can markets reach their equilibrium without the intervention of a price mechanism, as we have suggested above Let us start with the aggregate demand and supply functions. The propensity to consume, together with the amount of investment, determines the aggregate demand. Let us first have a look at investment. The amount that firms decide to invest in a given year determines the amount of capital goods that they demand and suppliers sell in that year. If the planned supply of capital goods exceeds that amount, this oversupply will remain unsold in the short run. The consumption component of aggregate demand, as we have seen above, is a function of income. Given the amount of consumption goods demanded, any excess supply will remain unsold, as in the capital goods case. In the long run, real prices in markets with excess supply may fall because of the increase in the general price level; in addition, some firms will downsize and others will shut down; this process will go on until planned supply equals demand. In the long run, the excess supply disappears. Of course, those firms that remain in the market are those that are profitable.12 So, in the short run there will be two sorts of markets: those where demand equals supply, as taught in the textbooks, and those where supply exceeds demand; in the latter case, nominal price downward rigidity means there is no force that can remove the excess supply in the short run. It will only disappear in the long run. Formally, calling z the vector of excess demands, in the short run z ≤ 0, where zi = 0 for i = 1 . . . m and zi < 0 for i = m + 1 . . . n. This is because dpi / dt ≥ 0 for i = 1 . . . n. In the long run, z = 0 because quantities adjust until the excess supply is eliminated. Some scholars may miss the aesthetics, beauty and elegance of the Walrasian general equilibrium approach, where the symmetric adjustments of prices do all the magic. But are these aesthetics, beauty and elegance enough to adopt an approach that has no empirical content? Other economists may feel uncomfortable because they may interpret that, in Barro’s words, we are leaving opportunities for mutually desirable trades or, as Lucas often repeated, we are leaving a $500 bill on the sidewalk. Well, this is the meaning of involuntary: the economy lacks the necessary investment to attain full-employment equilibrium. The more than 6 million unemployed in Spain in 2013 were leaving many $500 bills on the sidewalks, but a fence prevented those people from collecting them. The name of that fence was deficient demand.

168  Victor A. Beker

Why prices do not eliminate the excess supply? If planned output exceeds effective demand, why is it that prices do not go down until markets clear? First of all, let us recall the distinction introduced by Okun between auction and customer product markets. In auction product markets, prices clear competitive markets as the Walrasian general equilibrium model assumes. In customer product markets, firms set prices that do not necessarily equate demand and supply. With a few exceptions (commodity and asset markets), in the twenty-first century real-world customer markets are absolutely predominant. Therefore, there is no reason to base the edifice of microeconomics on the assumption that markets behave as competitive auction markets when they are the exception rather than the rule. It was reasonable in the nineteenth century, but not now. What microeconomic theory did Keynes have in mind when he wrote the General Theory? The General Theory is held to be compatible with both perfect and imperfect or monopolistic competition (Davidson, 1962, 2002). Indeed, in the General Theory, there is no explicit reference to the underlying assumption about the degree of competition. However, in a later paper, Keynes (1939: 46–50) admitted that perfect competition was not a realistic hypothesis and accepted imperfect competition as the benchmark to analyse what he called “the modern quasi competitive system” (ibid.: 46). Getting back to the question asked at the beginning of this section, there are many arguments that explain the aforementioned behaviour at the firm’s level once one leaves the golden realm of perfect competition and enters the intricate labyrinths of the real world. Let us list some of them. 1 2

3 4

5 6

If goods are heterogeneous and each supplier faces an inelastic demand function, there is little or no incentive to reduce prices.13 Firms do not change prices because they do not want to start price wars. “Do not do what can be easily mimicked by your competitor” is a practical rule in business. Facing a decrease in demand, an individual firm will not reduce its price if it expects other firms will follow suit.14 Cutting prices is such an unusual practice that the entrance in the taxi market of a new competitor charging lower rates became front-page news in many countries. As was pointed out above, if we assume positive trend inflation, one can rely on it to reduce a relative price without any need of changing its nominal price. Price reductions are a source of conflict with customers. “Why did I pay more for the same product yesterday?” is a question that firms find difficult to answer if the decrease is not associated with some special event like, for example, a clearance sale. Firms fear that customers may associate a fall in price with a fall in quality. Lowering prices may be interpreted as a signal of difficulties and a lack of confidence in the product. It may have a deleterious effect on the brand.

Price adjustment and other issues  169 We have here six solid, practical reasons why firms do not cut prices in the real world when they face a contraction in demand. They prefer to resort to other tools like improving advertising and marketing, reinforcing the sales task force, stretching the payment period, etc. These are all arguments that explain why nominal prices do not response to excess supply. They are specific to explaining downward price rigidity: they cannot be invoked to justify upward price stickiness, if it exists at all. The result is that, if there is a fall in aggregate demand, prices will not fall; there will be an excess supply in the short run.15 In the long run, the aggregate supply will adjust to the level of aggregate demand. If this implies changes in relative prices, the general price level will increase, as we will see in Corollary I below. Mainstream economists argue that assuming prices downward stickiness is ad hockery because it lacks microfoundations. If a firm does not adjust its price when relevant state variables change, it will not be maximising profits, they argue. This may be true in the frictionless world of theory. However, none of the six reasons which justify price downward rigidity contradicts the profit maximisation assumption. On the contrary, they explain firms’ behaviour in order to maximise profits in the long run in the real world under real-world constraints. Moreover, I don’t find convincing reasons to assume perfect price flexibility except the elegance of symmetry. But elegance should not be confused for truth. If economic models are ever going to provide realistic guides to policy, the real issue is what assumption is a better approach to what happens in the real world. In empirical sciences, whenever there is a conflict between theory and empirical evidence, it is theory which is in trouble. For mainstream economics it is the opposite, as if economics were a branch of applied mathematics and not an empirical science. That is why internal consistency, rather than external consistency – in the sense of conformability with empirical evidence – becomes the criteria for model admissibility (Wren-Lewis, 2009). In Nobel Laurate Paul Romer’s words, “evidence stops being relevant. Progress in the field is judged by the purity of its mathematical theories, as determined by the authorities” (Romer, 2016: 15). If there is someone who still remains unconvinced by the above arguments, remember Solow’s AEA presidential address reflection: I remember reading once that it is still not understood how the giraffe manages to pump an adequate blood supply all the way up to its head; but it is hard to imagine that anyone would therefore conclude that giraffes do not have long necks. At least not anyone who had ever been to a zoo. (Solow, 1980: 7) However, a mainstream economist would argue that, for the sake of internal consistency, zoologists should better assume that giraffes have short necks. Although it is, of course, always desirable to go on improving the arguments that explain price change asymmetry, it seems absolutely much more reasonable

170  Victor A. Beker to assume asymmetric rather than symmetric behaviour anyway, at least for anyone who studies the real-world economy. Moreover, as recalled above, even Friedman agreed that price asymmetric behaviour is a well-established fact in modern economies. However, it is likely he would add that assumptions in economics do not necessarily have to be based on real-world behaviour. Finally, let me remind the reader that Newton’s theory of gravity tells us how bodies attract each other but fails to identify the mechanism responsible of the motion of bodies.

The Fundamental Microeconomic Assumption For all the reasons given above, I propose the adoption of the following Fundamental Microeconomic Assumption (FMA): nominal prices display downward rigidity. Formally, dpi / dt ≥ 0 for i = 1 . . . n. This should be the starting point for the microfoundations of Keynesian macroeconomic analysis. Once the FMA is adopted, it follows that if there is an excess supply, the equilibrium will be reached by an adjustment in quantities, and not in prices, just as Keynes asserted. From FMA, two corollaries immediately follow: Corollary I. Any change in relative prices entails an upward change in the general price level.16 In fact, FMA means that any change in relative prices implies an upward change in at least one price of the economy while, by assumption, none falls. Corollary I implies that, for every economy, there is a natural rate of inflation. This is the rate of inflation which is caused by the necessary changes in the relative prices of that given economy. Corollary II. In the absence of an increase in the money supply equivalent to the natural rate of inflation, there will be a fall in output. In fact, from MV = PT, it follows that if there is an autonomous increase in P and MV is constant, T should necessarily fall. This means that if the money supply rises less than the natural rate of inflation – assuming that V is relatively constant in the short run – the economy will be condemned to stagflation. That is why the natural rate of inflation can also be called the NAURMI (non-accelerating unemployment rate of money increase), because it measures the minimum rate of growth in the money supply necessary to keep the level of output (and employment) constant. To sum up, let us suppose that there are n good markets; let us assume that in m markets there is excess demand. Then prices will increase until supply equals demand, as in the classical model. In the m − n markets where there is excess supply, as monetary prices are downward inflexible, the excess supply will remain unchanged in the short run. Prices remain in these markets at the historically attained levels. Strictly speaking, all markets will be in equilibrium as there is no

Price adjustment and other issues  171 economic force that can change the value of the economic variables in the short run. As stated above, in the long run some firms will lay off some part of the labour force and others will shut down until planned supply equals demand; at the same time, nominal prices in the m markets may rise further until the relative prices equilibrium is attained.

The wealth effect and price asymmetry Keynes never thought the decline in prices could be a way out of involuntary unemployment. He did not consider the possibility of a real balance effect on the goods market, just as nobody did before Pigou (1943). The experience of inflation after World War II, which was attributed to the excess liquidity built up during the war, paved the way for the inclusion of the wealth effect as an argument in the consumption function. For Keynes, the real balance effect was limited to the money market, the socalled Keynes effect. That is to say, an increase in real balances would have a reduction in the interest rate as its main effect. Keynes was a practical-minded economist. He was very sceptical about downward nominal wage and price flexibility in the real world. That is why he insisted that real wages, in practice, can be lowered only by the increase in wage-good prices, not by the contraction of nominal wages. Mainstream orthodox economics has used the wealth effect as the key instrument that leads the economy to full employment: excess supply in the goods market lowers prices and the consequent wealth effect restores the level of aggregate demand at its full-employment level. However, if nominal prices are downward rigid, there is no wealth effect at all and there is no magic key to the full-employment kingdom. Moreover, if the general price level increases in the long run in order to let relative prices achieve their equilibrium, there will be a negative wealth effect which will further reduce aggregate demand and, consequently, aggregate labour demand. Instead of a return to full employment, we will get stagflation. Although the wealth effect may be useful in analysing inflationary processes, it is of little practical relevance when dealing with recession and unemployment, the subject matter of Keynesian macroeconomics.

The Phillips curve The General Theory’s main concern was unemployment. Its aim was to show why an economy can be stuck in unemployment and how to get out of it. The appearance of chronic inflation as an economic problem in the 1970s triggered the antiKeynesian revolution. It was argued that demand stimulus to raise employment would always be associated with higher inflation. Popular folklore has it that Keynes was largely unconcerned with inflation. As a matter of fact, Keynes (2016: 271) admitted that wages and prices would rise gradually as employment increases: “we have in fact a condition of prices rising gradually as employment increases” and “an increasing effective demand

172  Victor A. Beker tends to raise money wages though not fully in proportion to the rise in the price of wage-goods” (ibid.: 275). This was the origin of the idea behind the Phillips curve: there is always a tradeoff between alternative levels of unemployment and wages; the lower the level of unemployment, the higher the level of money wages. The Phillips curve provided a link between the level of employment and the general wage level. The debate on the Phillips curve became a turning point in the development of macroeconomics. Phillips investigated the relationship between unemployment and the rate of change of money wages along one century, from 1861 to 1957, in the United Kingdom. Phillips (1958: 283) found an inverse relationship between the rate of changes in the money wage rate and the rate of unemployment. He argued that when the demand for labour is high and there are very few unemployed we should expect employers to bid wages rates up quite rapidly [. . .] On the other hand it appears that workers are reluctant to offer their services at less than the prevailing rates when the demand for labour is low and unemployment is high so that wage rates fall only very slowly. Therefore, the relationship between the two variables is not only inverse but also highly nonlinear. These findings fit perfectly well within the original Keynesian model. It depicts the consequences of shifts in the demand for labour curve together with downward wage stickiness. Solow and Samuelson substituted the rate of price inflation for the change of money wages. This substitution led to the policy conclusion that there exists an exploitable trade-off between inflation and unemployment. They presented this relationship as a policy menu to determine the costs of full employment. The modified Phillips curve version became highly popular during the 1960s. Decision makers used it to estimate the costs of lowering unemployment in terms of the increase in the inflation rate. However, in the 1970s, the modified Phillips curve was challenged from both the theoretical and the empirical points of view. From the theoretical point of view, Friedman (1968) and Phelps (1967, 1968) pointed out that it is real, not money, wages which vary to clear the labour market. This thesis was sharpened with the help of the rational expectation hypothesis. They proposed an expectations-augmented Phillips curve which shows unemployment as a function of the difference between actual and expected inflation. If an expansionist monetary policy is unanticipated, the general price increase that follows will be interpreted by each agent as an increase of relative prices. Consequently, monetary policy will have a real effect by increasing output and employment. “Because prices are sticky, faster or slower monetary growth initially affects output and employment. But these effects wear off.”17 This explains the existence of a short-run Phillips curve. The faster workers’ expectations of price inflation adapt to changes in the actual rate of inflation, the faster unemployment will return to its long-run level, while inflation will remain at the new higher level.

Price adjustment and other issues  173 Since all expectations are fully realised in the long run, a “natural rate of unemployment” will prevail. In the long run, no trade-off would exist; the Phillips curve would be vertical at the natural rate of unemployment: the natural rate of unemployment is compatible with any rate of inflation. As stated above, the trick consists of introducing real wages as the clearing mechanism in the labour market. Any unemployment above the “natural” unemployment will be eliminated by a fall in the real wage rate. Any remaining unemployment is natural unemployment. The concept of the natural rate of unemployment was later replaced by the NAIRU (non-accelerating inflation rate of unemployment), which is understood as the level of unemployment at which inflation stabilises. NAIRU is considered the equilibrium rate of unemployment to which the system would return after any disturbance. “Only if the real wage desired by wagesetters is the same as that desired by price-setters will inflation be stable. And the variable which brings about this consistency is the level of unemployment” (Layard et al., 1991: 12, emphasis in original). From the empirical point of view, the 1970s witnessed a simultaneous increase in both unemployment and inflation, which apparently contradicted the modified Phillips curve. I say “apparently” because the presence of a simultaneous rise in unemployment and inflation after the OPEC oil price hikes could have been interpreted as just an outward shift in the existing Phillips curve. For example, Lipsey (1960) has already argued that the Phillips curve shifted in the period between 1923–1939 and 1948–1957, in comparison to the pre-World War I period. With many more reasons the same could be argued with reference to the 1970s after OPEC substantially changed its oil price policy. It was an increase in the natural rate of inflation due to the changes in relative prices that followed the oil price escalation in the 1970s. The contractionary monetary policy adopted to fight inflation resulted in the unemployment growth experienced then. The truth is that the main interest in the 1970s had shifted from unemployment to inflation. Hahn (1980: 285) noted that “even ten years ago one would have taken it for granted that a government should and could have a policy designed to reduce the average level of unemployment. Now this is no longer so.” The New Classical counterrevolution was, in Blinder’s (1988: 278) words “a triumph of a priori theorizing over empiricism, of intellectual aesthetics over observation and, in some measure, of conservative ideology over liberalism. It was not, in a word, a Kuhnian scientific revolution.” After burying the Phillips curve, Friedman (1956) revitalised the quantity theory, restating it in terms of a demand for money function that now included an expected inflation term, which affects the expected nominal returns on the various classes of assets. People demand a certain real quantity of money. If the quantity of money unexpectedly increases, people will seek to dispose of their excess money balances. Prices will increase until the real quantity of money held by people coincides with that which they want to hold.

174  Victor A. Beker This means that in the long run all analyses could be conducted in real terms because the price level is proportionate with the stock of money. Monetary policy is neutral: it only affects nominal variables, not real variables.

Stagflation As mentioned above, economic theory and economic policy faced a quite new phenomenon in the 1970s: stagflation. After the first OPEC oil shock in 1974, the world witnessed a simultaneous increase in both unemployment and inflation. The simultaneous presence of those two phenomena marked the end of the Phillips curve’s popularity and, with it, of the Keynesian era. The New Classical economists demolished the Keynesian model with the argument that it could not explain the phenomenon of stagflation. The paradox is they gave no explanation of it at all, unless one considers as such the argument that follows. There is always a natural rate of unemployment; it is compatible with any rate of inflation: a long-run vertical Phillips curve implies a natural rate of unemployment consistent with any given rate of price increase. Then, the problem with stagflation is the inflation component and not the stagnation one. Lucas questioned Friedman’s short-term–long-term split in the analysis of the Phillips curve. He argued that agents are endowed with rational expectations and they efficiently use all available information. The economic agent acts as if she were an econometrician and estimates the model parameters. Authorities cannot “fool” economic agents, not even in the short run. Not only the long-run Phillips curve is vertical at the natural rate of unemployment; the short-run Phillips curve is equally vertical. Expectations play a critical role in New Classical economics. For example, if people expect an expansionary monetary policy, they will adjust their behaviour accordingly, and prices will go up even if the central bank does not expand the monetary supply. The actual unemployment is the natural one. And it is absolutely voluntary: it is the result of the households’ choice because they find the actual real wage rate too low to motivate them to supply their labour services. Policy makers should be concerned with inflation, not with unemployment. Unemployment stays at its natural rate and any increase in monetary creation, if it is anticipated, is inflationary.18 Policy makers who expand the monetary supply to fight unemployment increase inflation without any long-run effect on unemployment. Expansionary policies just push inflation higher, and unemployment rises because inflation decreases the real wage; workers prefer to work less because leisure is cheaper. That is why stagflation exists. This is a very ingenious explanation; the difficulty with it is that during a recession, unemployment is the result of an increase in layoffs, not of a decision by workers to stay at home. The New Classical School gave no valid explanation for the stagflation phenomenon. On the contrary, once the FMA is adopted in the macroeconomic analysis, the stagflation explanation is straightforward: if there is a contraction in the money

Price adjustment and other issues  175 supply to fight inflation, the output will fall while inflation will persist. Far from being an argument against the Keynesian model, stagflation is a phenomenon fully compatible with it once the downward rigidity hypothesis is adopted. But the truth is that the New Classical economists were mainly interested in, and were successful at, changing the focus of economic analysis from unemployment to inflation.

Keynes on monetary and fiscal policies Let us now have a brief look at Keynes’s point of view on monetary and fiscal issues and their influence on price behaviour. Keynes’s monetary theory has as a starting point his theory of liquidity preference. This preference has an opportunity cost: the rate of interest. Thus, the quantity of liquidity demanded is inversely related to the interest rate. When the quantity of money is increased, its first impact is on the rate of interest, which tends to fall. However, Keynes warned that “whilst an increase in the quantity of money may be expected, ceteris paribus, to reduce the rate of interest, this will not happen if the liquidity preferences of the public are increasing more than the quantity of money” (Keynes, 2016: 270). Given the marginal efficiency of capital, a fall in the rate of interest will increase the volume of investment. The increased investment will raise effective demand through the multiplier effect, thereby increasing income, output and employment. As we move from unemployment to full employment, prices gradually rise as employment increases (Keynes, 2016: 271). So, there are a number of “positions of semi-inflation” (Keynes, 2016: 275), “a succession of earlier semi-critical points at which an increasing effective demand tends to raise money wages though not fully in proportion to the rise in the price of wage-goods” (ibid.). The early transmission of money increasing into prices and the possibility of a “liquidity trap” (ibid.: 187) are reasons that explain Keynes’s scepticism on the monetary policy’s ability to deal with unemployment (ibid.: 242). He was much more confident on the effectiveness of fiscal policy to cope with it. He argued in favour of public construction, building houses or even digging holes in the ground if narrow-minded statesmen couldn’t set in motion the former two alternatives. “I expect to see the State [. . .] taking an ever greater responsibility for directly organising investment” (Keynes, 2016: 147). Public expenditure was conceived as the best tool to fill the gap created by deficient demand. During and after the 2008 financial crisis, Keynes’s prevention was confirmed. The Great Recession revealed the limitations of monetary stimulus alone to overcome a severe recession. The Fed doubled the monetary base between September and December of 2008, but that money didn’t reach the people: it only increased bank reserves. The federal funds rate was cut from about 5% in mid-2007 to nearly 0% in late 2008, yet the economy continued to suffer from inadequate aggregate

176  Victor A. Beker demand for goods and services. As Samuelson very graphically said more than 50 years ago: “You can lead a horse to water, but you can’t make him drink.” You can force money on the system in exchange for government bonds [. . .] but you can’t make the money circulate against new goods and new jobs [. . .] You can tempt businessmen with cheap rates of borrowing, but you can’t make them borrow and spend on new investment goods. (Samuelson, 1948: 354) Calvo (2016: 33) calls this situation a “Supply-Side Liquidity Trap”: a point may be reached where printing money increases real monetary balances but has little effect on real liquidity. As Koo (2016: 24) rightly points out, when “private-sector borrowers sustain huge losses and are forced to rebuild savings or pay down debt to restore their financial health,” they have no choice but to pay down debt or increase savings regardless of the level of interest rates in order to restore their financial health. We are here in the presence of an economy in which everyone wants to save but no one wants to borrow, even at near-zero interest rates. Under these circumstances, “there is very little that monetary policy, the favourite of traditional economists, can do to prop up the real economy” (Koo, 2016: 34). It is the time for fiscal policy. As Romer (2011: 3) recognises, “we need instruments of discretionary fiscal stimulus as part of the macroeconomic toolkit” because monetary policy is not enough to stabilise an economy facing a large shock. However, Meltzer criticises Keynes’s recommendations in favour of using fiscal policy against unemployment. Meltzer (1988: 309) argues that short-term fiscal policy has not proven to be an effective tool of stabilisation. He mentions that “attempts to lower unemployment by short-term policy adjustment have been followed by rising prices and capital outflow or currency depreciation.” The recent experience, as Romer points out, vindicates the importance of fiscal policy. Moreover, he mentions a very conclusive example: the fact that the major increases in government purchases in the two world wars and the Korean War were associated with booms in economic activity. The weakness of Keynes’s recommendations is that they were thought of for a closed economy. The challenge, then, is to extend Keynes’s model to an open economy to take into consideration phenomena like capital outflows or currency depreciation mentioned by Meltzer. This implies including foreign trade as another component of aggregate demand as well as adding the possibility of acquiring foreign assets/liabilities. For the open economy, the initial Keynesian workhorse model has been the Mundell–Fleming one. More recently, New Keynesian open-economy models with nominal price rigidities and intertemporally maximising agents have been designed to understand the transmission of shocks across countries, exchange rate pass-through and the effects of different pricing rules. New Keynesian models,

Price adjustment and other issues  177 particularly DSGE, became popular among central banks that use them in their job of setting an appropriate interest rate. Nominal price stickiness ensures that shocks and central bank interventions go beyond mere nominal price effects. Exogenous changes in monetary policy have nontrivial effects on real variables. However, as they assume that wages and/or prices are up- and downward equally sticky, these models forecast symmetric effects for either negative or positive shocks. For instance, Gali (2018: 95) simulates the response to an unanticipated negative demand shock and forecasts inflation taking persistent negative values of up to 25% until the adverse disturbance vanishes. On the other hand, in spite of Krugman’s opinion mentioned at the beginning of this chapter, the 2007–2008 financial crisis strongly damaged the reputation of the New Keynesian DSGE models, whose contribution has been “of minimal value in addressing the greatest macroeconomic crisis in three-quarters of a century” (Romer, 2011: 1–2). For Stiglitz (2017: 1), “the inability of the DSGE model to . . . provide policy guidance on how to deal with the consequences (of the crisis), precipitated current dissatisfaction with the model.” Strange as it may sound, Gali (2018: 108) answers that the New Keynesian model is “alive and well” although “none of the extensions of the New Keynesian model proposed in recent years seem to capture an important aspect of most financial crises” (ibid.: 107).19 Post Keynesians have extended their models to economies that are open to international trade and financial flows. Adding open-economy features alters the potential outcomes of Post Keynesian models in several important ways. The analysis has focused on the effects of changes in the rate of exchange on output and trade balance. Blecker (2010) surveys the empirical results for several Post Keynesian models. The results show that different studies using different methodologies have found different results for the same countries. This outcome is qualified as “disconcerting” by the survey’s author; however, this is a very common situation in economics. Beker (2005) has drawn attention to this fact: “given a certain econometric result, in many cases it is enough to just include another variable, or to slightly modify the model assumptions or the estimation method to get different, and even opposite, results.” There is nothing like a crucial experiment in economics. That is why models accumulate and remain available inside a big toolbox to be used according to the case under analysis and the analyst’s expertise. New and Post Keynesians have developed some valuable instruments that may be useful for making further progress in the understanding of open-economy macroeconomics once the asymmetric price behaviour is taken into consideration. Openness imposes restrictions on monetary and fiscal policies. If domestic prices increase, the substitution of foreign assets for domestic money is an alternative and currency depreciation may be a likely result, aggravating inflationary pressures. This means that inflation should be carefully watched and should not be neglected as it was in some so-called Keynesian policy experiments Meltzer refers to. Unlike several so-called Keynesians, Keynes did not favour inflation: “The money wage level as a whole should be maintained as stable as possible [. . .] This

178  Victor A. Beker policy will result in a fair degree of stability in the price level” (2016: 245). This puts a narrow limit on the use of monetary expansion, as has been underscored by Keynes himself. The policy maker must watch unemployment with one eye and inflation with the other. However, the recent European experience shows it is not so easy for inflation to gain momentum in a weak economy even when this is the central bank’s target. And it also shows that, as has been pointed out above, it is equally difficult to refloat an economy only with monetary policy, even resorting to negative interest rates. Anyway, the monetary and fiscal areas in Keynesian macroeconomics demand an updating and deepening in order to take into account the role of the financial system and trade globalisation in the present economy, explain current economic phenomena and allow economists to formulate sensible economic policy recommendations. In this respect, the 2007–2008 financial crisis and the post-crisis financial management are natural experiments that provide researchers with very rich empirical material for their analysis.

Price stickiness: lessons from the European crisis We have proposed to adopt as FMA the statement that nominal prices display downward rigidity. However, the recent European experience shows that not only has inflation remained far below the rate targeted by the ECB, but that it was even negative in some months. Doesn’t this make our FMA as unrealistic as the downward flexibility neoclassical assumption? The first observation is that the rate of core inflation in Europe has remained always positive, showing that deflation has had to do only with the price of commodities – energy and unprocessed food – that is to say, with goods whose prices are quoted in world auction-like markets. For the rest of the prices, downward inflexibility has been the rule. Even in a country suffering from a very deep recession, like Greece, core inflation remained positive. Although Greece lost 25% of its GDP between 2007 and 2015, it accumulated an inflation of 11.26% over this same period. Compare this figure with a 2013 Goldman Sachs study mentioned in Sinn (2013: 5), in which it was estimated that Greece’s prices would have to come down by 25–35% to achieve external debt sustainability. The Greek case is a very clear example that, due to price and wage downward inflexibility, internal deflation is not a way out of the crisis. In spite of the huge loss in GDP, the price level did not decline and even kept rising. Price asymmetric behaviour means that the only way for Greece, or Italy, to get cut their relative price levels is by means of an increase in the EU price level average. Broadly speaking, deflation failed to materialise in the depths of the Great Recession of 2008–2009, as Krugman (2018) underscores. This is just one example of how FMA is far closer to reality than the usual mainstream economics assumption of symmetric price behaviour. It is time to adjust economic theory to reality instead of waiting for reality to adjust itself to economic theory.

Price adjustment and other issues  179

Conclusions The 2008 financial crisis exposed many of the fallacies of orthodox economic thinking and triggered a deep crisis in economic theory. It is time to rebuild the theoretical edifice of economics. Realisticness is a necessary condition economic theory must fulfil if we try to make meaningful predictions for the real world and sensible political recommendations. In this respect, it is argued that price downward rigidity has to be a fundamental assumption of any model that tries to reach these goals. I argue that realisticness is precisely one of the features that distinguishes Keynes’s analysis. For this reason, Keynesian macroeconomics must be the point of departure for a realistic reconstruction of economic theory. And price downward rigidity fits the Keynesian model perfectly well. Given price asymmetric behaviour, it is necessary to conduct two separate analyses: on the one hand, full-employment macroeconomics (price equilibrium macroeconomics) and, on the other, the macroeconomics of recession and depression (Keynesian macroeconomics). Prices behave differently in each case and play different roles in the adjustment process. We need a theory apt to explain involuntary unemployment as well as inflation. For this purpose, we need two different approaches to the economy’s behaviour, because this behaviour is quite different when the economy faces a positive shock than when it faces a negative one. In the real world, there seems to be a nonlinear relationship between price flexibility and the inflation rate: prices are downward rigid but become more and more flexible as the inflation rate grows. I propose the adoption of the assertion that nominal prices display downward rigidity as the Fundamental Microeconomic Assumption (FMA). This should be the starting point for the microfoundations of Keynesian macroeconomic analysis. The natural rate of inflation is defined as the rate of inflation caused by the changes in the relative prices of a given economy. It can also be called NAURMI (nonaccelerating unemployment rate of money increase), as it measures the rate of growth in the money supply necessary to keep the level of output (and employment) constant. If prices are downward rigid, there is no positive wealth effect at all and there is no magic key to the full-employment kingdom. Many of the predictions and recommendations by traditional mainstream economics are flawed because they are based on the assumption that monetary prices are downward flexible. The New Classical economists demolished the Keynesian model with the argument that it could not explain the phenomenon of stagflation. The paradox is that the New Classical theory gave no explanation of that phenomenon at all. Stagflation appears if the money supply grows less than the natural rate of inflation. Therefore, it is crucial for the monetary authorities to estimate that rate in order to avoid inducing stagflation by an excessively rigid monetary policy. The recent European experience under the effects of the financial crisis shows that price downward inflexibility has been the rule, even in countries like Greece, which lost 25% of its GDP between 2007 and 2015 while inflation was 11.26%

180  Victor A. Beker over the same period. Deflation failed to materialise in the depths of the Great Recession of 2008–2009. The discussion in this chapter has argued that Keynesian macroeconomics (the study of unemployment, recession and depression) should be again at the top of the agenda of economic research. What are the next steps? I single out here some leading examples of where I believe progress can be made. As I mentioned above, Keynes’s model has to be updated in order to take into consideration today’s real world. This is a first area for future research. Keynes modelled a closed economy. The first challenge is to extend Keynes’s model to an open economy. Moreover, the globalisation and financialisation processes as well as the role that supranational institutions play in the contemporary economy have to be taken into consideration in order to update Keynes’s ideas to the present-day reality. New and Post Keynesians have developed instruments that may be useful for making further progress in the understanding of open-economy macroeconomics from a Keynesian perspective. The financial sector now includes not only banks but also other intermediaries such as life insurance companies, investment funds, leasing companies and other finance companies like those which constitute the so-called shadow banking system. All of them play a decisive role in the contemporary economy which cannot be ignored, as the American and European crises prove. Among other things, this new institutional environment has a crucial role in conditioning saving and investment behaviour, which are key factors in macroeconomics. Obviously, institutions like the IMF, ECB or the EU did not exist at the time Keynes wrote his General Theory. These institutional actors have to be taken into consideration at the time of analysing economic policy alternatives and recommendations. A second area for research concerns the empirical estimation of the national natural rate of inflation and what factors affect it. A third area for research consists in analysing what role monetary policy has played in different stagflation processes and what lessons emerge from that analysis. In particular, what economic policies help get out of stagflation. A fourth area for research concerns learning how the 2007–2009 Great Recession was prevented from turning into something like the 1930 Great Depression and, at the same time, the reasons why the recovery has been so slow and feeble.

Notes   1 This chapter is meant to pay homage to the late Argentine economist Julio H.G. Olivera, who passed away in 2016. From him I learned the critical role that price asymmetry plays in today’s real world economy.   2 However, see below for opposite assessments by D. Romer and Stiglitz on New Keynesian DSGE models.   3 Using data from Australia and US, De Abreu Lourenco and Gruen (1995:16) find that “the inflationary impact of relative price shocks depends strongly on expected inflation. When expected inflation is high, a rise in the economy-wide dispersion of shocks is

Price adjustment and other issues  181 inflationary in the short-run. By contrast, when expected inflation is low, a rise in the dispersion of shocks has minimal impact on inflation.” In the same direction, see Eliasson (2001), Clark et al. (1996); Debelle and Laxton (1997); Huh and Jang (2007); Debelle and Vickery (1998).   4 Of course, there is also an ideological component. As De Vroey (2011: 7) points out, “the split is between those who want to give competition its full rein, the defenders of the selfregulating characteristics of markets (or ‘free marketers’) and those, the Keynesians, who think that the market economy, although the best economic system, can buttress failures, in particular an insufficiency in aggregate demand, which it is the state’s role to remedy.”   5 Had he taken into consideration downward stickiness in his monetary analysis, he would have arrived at the non-monetary theory of inflation, developed by Latin American economists using precisely that assumption to arrive at a theory of inflation opposed to Friedman’s.   6 Some of them are mentioned below in the section devoted to Keynes’s thought on monetary and fiscal policies.   7 The globalisation and financialisation processes as well as the role of supranational institutions are some of the new realities an updated macroeconomics has to take into consideration.   8 I use equilibrium with the usual meaning: a state where there is no economic force which can change the value of economic variables.   9 The interview method used by Blinder and his colleagues has two difficulties. First, answers can be influenced by the precise wording of the questions, and second, people may have no incentive to respond truthfully or thoughtfully. 10 This implies a convex Phillips curve. 11 Unless the decline in the real wage is a consequence of a downward shift in the demand for labour curve, in which case B would be an equilibrium point and BC the involuntary unemployment at the new real wage level. 12 This is the general rule in the capitalist world. If costs systematically exceed income, firms cannot survive in the long run, unless they are state-owned or state-backed. 13 Moreover, if after a shift down the demand function becomes more inelastic, it is profitable to increase the price. 14 In his seminal article on oligopoly, Rothchilds (1947: 310) underlined that firms refrain from lowering prices to avoid retaliation from the competitors. 15 Even so, markets will be in equilibrium because, in the short run, excess supply does not generate any movement to eliminate it. 16 This is the essence of the non-monetary theory of inflation as explained, among others, by the recently deceased Professor Julio Olivera. See Olivera (1960, 1964). 17 Milton Friedman “Defining Monetarism” Newsweek, 12 July 1982, p. 64 18 If it is unanticipated, it may increase output and employment, but soon agents will realise that there has been no change in the relative prices and unemployment will return to its natural level while inflation will remain at the new, higher level attained. 19 An extensive list of theoretical as well as empirical problems which plague DSGE models can be found in Fagiolo and Raventini (2012).

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184  Victor A. Beker Lucas Jr., R. E. (1978). Unemployment Policy. The American Economic Review, Vol. 68, No. 2, Papers and Proceedings of the Ninetieth Annual Meeting of the American Economic Association, 353–357. Mäki, U. (2005). Models Are Experiments, Experiments Are Models. Journal of Economic Methodology, Vol. 12, No. 2, 303–315. Mankiw, N. G. (1985). Small Menu Costs and Large Business Cycles; A Macroeconomic Model of Monopoly. The Quarterly Journal of Economics, Vol. 100, No. 2, 529–538. Melmiès, J. (2008). New-Keynesians Versus Post-Keynesians on the Theory of Prices. www.boeckler.de/pdf/v_2008_10_31_melmies.pdf Meltzer, A. H. (1988). Keynes’s Monetary Theory: A Different Interpretation. Cambridge: Cambridge University Press. Olivera, J. H. G. (1960). La teoría no monetaria de la inflación. El Trimestre Económico, October–December, 626–628. México D.F. Olivera, J. H. G. (1964). On Structural Inflation and Latin American ‘Structuralism’. Oxford Economic Papers, Vol. 16, No. 3 (November), 321–332. Peltzman, S. (2000). Prices Rise Faster Than They Fall. The Journal of Political Economy, Vol. 108, No. 3 (June), 466–502. Phelps, E. S. (1967). Phillips Curves, Expectations of Inflation and Optimal Unemployment Over Time. Economica, Vol. 34 (August), 254–281. Phelps, E. S. (1968). Money Wage Dynamics and Labour Market Equilibrium. Journal of Political Economy, Vol. 76 (July–August), 678–711. Phelps, E. S., ed. (1970). Microeconomic Foundations of Employment and Inflation Theory. New York: Norton. Phillips, A. W. H. (1958). The Relation between Unemployment and the Rate of Change of Money Wage Rates in the United Kingdom, 1861–1957. Economica, Vol. 25 (November), 283–299. Pigou, A. C. (1943). The Classical Stationary State. Economic Journal, Vol. 53, 343–351. Rhee, W., and Rich, R. W. (1995). Inflation and the Asymmetric Effects of Money on Output Fluctuations. Journal of Macroeconomics, Vol. 17, 683–702. Romer, D. (2011). What Have We Learned about Fiscal Policy from the Crisis? http://eml. berkeley.edu/~dromer/papers/What%20Have%20We%20Learned%20about%20 Fiscal%20Policy%20from%20the%20Crisis%20May%2020.pdf Romer, P. (2016). The Trouble with Macroeconomics. In The American Economist. SAGE Publications. Rothchilds, K. W. (1947). Price Theory and Oligopoly. Economic Journal, Vol. 57, 299–320. Samuelson, P. A. (1948). Economics: An Introductory Analysis. McGraw-Hill. Sinn, H. W. (2013). Austerity, Growth and Inflation: Remarks on the Eurozone’s Unresolved Competitiveness Problem. CESifo Working Paper No 4086. Solow, R. M. (1980). On Theories of Unemployment. American Economic Review, Vol. 70, No. 1 (March), 1–11. Stiglitz, J. E. (1999). Toward a General Theory of Wage and Price Rigidities and Economic Fluctuations. American Economic Review, Vol. 89, No. 2 (May), 75–80. Stiglitz, J. E. (2017). Where Modern Macroeconomics Went Wrong. NBER Working Paper 23795. www.nber.org/papers/w23795.pdf Wren-Lewis, S. (2009). Internal Consistency, Nominal Inertia and the Microfoundation of Macroeconomics. University of Oxford. www.economics.ox.ac.uk/materials/working_ papers/paper450.pdf

8

Understanding financialisation Standing on the shoulders of Minsky Charles J. Whalen

Introduction In Stabilizing an Unstable Economy, Hyman P.Minsky (1986a: xiii) wrote that John Maynard Keynes provides “the shoulders of a giant upon which we can stand in order to see far and deep into the essential character of advanced capitalist economies.” Even today, Keynes remains relevant, to be sure. However, as we seek to understand and cope with financialisation, we can also stand on the shoulders of Minsky.1 The discussion below is divided into five sections. The first section summarises and briefly reflects on Minsky’s penetrating observations regarding what he called money manager capitalism, a subject on which he focused most of his research in the decade preceding his death in 1996. The next section outlines the powerful analytical framework that Minsky used to organise his thinking and that we can use to extend his work. Then the chapter shows how Minsky’s observations and framework represent a major contribution to the study of financialisation. The penultimate section highlights two keys to Minsky’s insightfulness: treating economics as a grand adventure and stepping beyond the world of theory. Finally, the chapter concludes with a short recap, an acknowledgement of challenges facing economists with a Minsky perspective, and a reason to stay hopeful despite those challenges.

Minsky’s observations on money manager capitalism Minsky is best known for his financial-instability hypothesis, which suggests that the financial structure of advanced capitalist economies becomes more fragile over a period of prosperity.2 But during the last decade of his life, Minsky focused not on that hypothesis but on the emergence of what he labelled money manager capitalism (MMC). Looking primarily at the economy of the United States, Minsky observed that money managers had, since the early 1980s, replaced corporate managers as the masters of private-sector economic activity. In a series of essays, Minsky presented his observations on that development and the dangers he believed it posed to the US economy – including the possibility of slower technological progress, greater economic instability, increased worker insecurity and sharper income inequality.3

186  Charles J. Whalen Money managers According to Minsky, MMC emerged in the 1980s, and by the end of that decade the holders of the largest share of US corporate stocks and bonds were moneymanaging institutions – such as pension and mutual funds, bank trust departments and the annuity arms of insurance companies – rather than individual investors. In an article published just after his death, for example, Minsky and Whalen (1996: 158) observed that money managers saw the fraction of US corporate equities under their control grow from 8% in 1950 to 60% in 1990; over the same period, pension funds increased their share of total business equities from less than 1% to almost 39% and their fraction of corporate debt from 13% to 50%. As the portfolios controlled by fund managers grew, active management replaced a passive “buy-and-hold” strategy. The aim of money managers – and the sole criterion by which they are judged – is maximisation of the total value of investments made by fund holders.4 Thus, active management of such funds means that money managers are always “in the market.” Minsky (1990a: 69) wrote, “these funds do not buy and hold common stocks for long-term increases in dividend income: the annualised rate of return from catching a short-run swing in interest rates or stock prices can easily dominate interest or dividend income.” With MMC taking hold, the short view replaced the long view across the economy. Money managers certainly felt the pressure of the near term – as investors’ resources migrated to the most successful fund managers – but so did corporate executives. The growing influence of money managers forced business leaders to become increasingly focused on quarterly profits and the stock-market value of their corporations – in other words, on shareholder value. This pressure spurred many non-financial corporations to scale back costly and often aging manufacturing operations; engage in mergers and acquisitions at an unprecedented pace; and turn their attention to the sorts of borrowing, investing and lending traditionally associated with financial firms.5 The experience of General Electric (GE) is emblematic of the corporate behaviour that took root as MMC emerged. When Jack Welch became the chief executive at GE in 1981, the firm was a premier US corporation – “as traditional as any large manufacturing firm in the country” (Harrison and Bluestone, 1988: 36). To boost the company’s earnings and stock value, Welch sought to transform the company. In the first five years, he closed a dozen plants and sold off 190 subsidiaries, including the entire small appliances division. He also spent $6.5 billion to acquire RCA (including its broadcasting subsidiary, NBC) and $1.7 billion to purchase the Kidder Peabody investment bank and Employers Reinsurance, a financial services firm. The strategy achieved Welch’s aims and was widely imitated.6 The emergence of MMC was also accompanied by an array of institutional innovations in the financial world. For example, since billion-dollar funds own sizable amounts of stock in individual enterprises, the growth of managed-money funds led to development of block trading through investment banks. When a fund manager seeks to sell fund shares, investment banks buy the shares and then either

Understanding financialisation  187 find a fund willing to buy the entire lot or dispose of the shares in smaller amounts over time (Minsky, 1990a: 70). Other financial innovations arose in large part because fund managers had outgrown portfolios of high-quality stocks and bonds. Always on the lookout for higher returns, money managers provided an eager market for new, specialised instruments such as securitised mortgages, credit-card receivables and junk bonds (Minsky, 1992a: 32). The needs of money managers also spurred the development of program trading and portfolio insurance, observed Minsky (1990b: 213). MMC may have originated in the United States, but Minsky understood from the start that it had global significance; that, is, MMC helped fuel globalisation. In a conference paper delivered in 1988, for example, he wrote that MMC was already “international in both the funds and the assets in the funds” and that it would continue to grow internationally. According to Minsky, “as managed funds grow, we should expect a world in which international portfolio diversification is much more prevalent than it is to date” (1990a: 71).7 Technological progress Minsky worried that MMC came with a number of dangers, including the possibility that technological progress and industrial innovation would stagnate. He offered two reasons: technological development usually demands a longer time horizon than that which drives money managers; and MMC often leaves corporations without sufficient financial resources for such development. Thus, from the perspective of what he called the capital development of the economy, Minsky feared that the financial evolution that produced MMC “may well have been retrograde” (1993: 113). Minsky argued that money-fund managers do not see themselves as guardians of the economy’s capital development, adding that this made them fundamentally different from the earlier leaders of finance admired by Joseph Schumpeter. The emphasis of these new leaders, Minsky continued, is instead on trading profits, which he characterised as “the quick turn of the speculator.” In fact, Minsky suggested that Keynes’s famous remark about speculation and enterprise is especially relevant for MMC: Speculators do no harm as bubbles on a steady stream of enterprise. But the position is serious when enterprise becomes the bubble on a whirlpool of speculation. When the capital development of a country becomes the byproduct of the activities of a casino, the job is likely to be ill-done. (Keynes, quoted in Minsky, 1993: 111–112) As Minsky saw it, MMC pressured non-financial enterprises to choose diversification and other strategies that could be implemented quickly – and to avoid longerterm strategies such as modernisation of plant and equipment.8 Minsky also argued that industrial innovation would be sluggish because companies in the era of MMC are often saddled with a high level of indebtedness,

188  Charles J. Whalen making it difficult for them to invest from internal funds. Such indebtedness often came from a leveraged buyout or other restructuring. Under MMC, Minsky explained, money managers have an incentive to sell their shares to support takeovers and financial-restructuring initiatives that promise to boost near-term portfolio value; they also tend to be the buyers of bonds issued to finance such reorganisations (Minsky, 1990a: 70).9 In short, Minsky wrote that the main purpose of those now in control of corporations (money managers) was no longer to make profits from production and trade. Rather, the purpose had become giving value to stockholders by assuring that the liabilities of corporations are fully priced in the financial market. In practice, that means “pledging a very high proportion of prospective cash flows to satisfy debt liabilities” – and not worrying whether there is much left for capital development (Minsky, 1993: 112). Economic instability Increased economic instability is another danger Minsky associated with MMC. To be sure, Minsky understood that the financial system had already become increasingly fragile in the three decades before MMC emerged in the 1980s. In fact, Stabilizing an Unstable Economy discusses that process in detail: corporations took on more and more debt; banks expanded off-balance-sheet operations; and “fringe banking” grew relative to the rest of the financial system (Minsky, 1986a).10 But MMC added to the increased instability in important ways, Minsky argued: it increased the possibility of a market panic; it fuelled securitisation; and it threatened to trigger an economic crisis that only coordinated international action would resolve. Minsky’s concern that money managers and block traders might contribute to the panic selling of equities was rooted in historical observation. In a paper written for a conference held in 1988, Minsky observed that position-taking by block traders (and the short-term financing provided to them by big banks) disappeared in the stock-market crash of October 1987 and that intervention by the Federal Reserve was needed to stabilise the market. “More than ever,” he wrote, “the profit sustaining effect of government expenditures .  . . together with prompt Federal Reserve intervention is required for aggregate stability” (Minsky, 1990a: 70–71). In the same paper, Minsky (1990a: 71) argued there is a “symbiotic relation between the growth of securitization and of managed money.”11 Having recently returned from a conference convened (in May 1987) by the Federal Reserve Bank of Chicago, Minsky summed up the main takeaway as follows: “That which can be securitized will be securitized” (Minsky, 1990a: 70). But Minsky was ahead of the curve: a year before the conference he had written not only that securitisation was poised to be “the wave of the future” but also that it came with the risk of an asset sell-off, falling asset prices, and “contagion reactions” on an international scale (Minsky: 1986b).12 When mortgage securitisation turned a real-estate bust into a global financial nightmare in 2007, Minsky – who had been dead for over a

Understanding financialisation  189 decade – gained considerable notoriety and was even the subject of a front-page story in the Wall Street Journal (Lahart, 2007).13 Minsky wasn’t merely concerned that MMC could trigger an international economic crisis; he was also worried that it was no longer possible for the United States to act “as the guardian angel for stability in the world economy” (Minsky, 1986b: 15). Rather, he argued, “as the countries that are involved in MMC increase, an international division of responsibility for maintaining global aggregate profits will be necessary” (Minsky, 1990a: 70). A year before his death, Minsky wrote: Global financial integration is likely to characterize the next era of expansive capitalism. The problem of finance that will emerge is whether the financial and fiscal control and support institutions of national governments can contain both the consequences of global financial fragility and an international debt deflation. (1995: 93) Worker insecurity and income inequality Minsky saw rising worker insecurity and income inequality as the flip side of MMC. He considered it no surprise that insecurity and inequality increased as money managers gained influence over the economy. In fact, Minsky offered two reasons for the trend: at the enterprise level, MMC pressured employers to cut labour costs; and at the macroeconomic level, workers were hurt by a grossly overvalued dollar attributable in large part to the portfolio choices of money managers. In 1996, Minsky discussed the influence of money managers on the employment relationship within corporations. He wrote: “There is an almost chronic need to downsize overhead and to seek the lowest possible variable cost.” As a result, workers’ benefits were slashed or eliminated, concessions were demanded from unions, jobs were outsourced and off-shored and many longstanding assurances of continued employment vanished (Minsky, 1996: 363). Later that same year, Minsky and Whalen (1996) offered a further examination of this aspect of MMC by outlining some of the dimensions of growing worker insecurity and inequality. For example, their essay mentions widespread income stagnation, longer job searches, increased family dependence on multiple job-holdings and explosive growth in part-time and temporary work. It also quotes Stephen Roach, chief economist at Morgan Stanley: “Recovery or not, the 1990s are still all about downsizing, longer workdays, white-collar shock and relatively limited opportunities for new employment” (quoted in Minsky and Whalen, 1996: 160).14 Under MMC, all types of labour were increasingly seen by corporations as a “spot market” commodity – just another cost to be minimised. Minsky also saw a macroeconomic dimension to rising worker insecurity. MMC “has rendered obsolete the view that trade patterns determine the short-run

190  Charles J. Whalen movement of exchange rates,” he argued (Minsky, 1990a: 71). Elaborating on this in another essay, Minsky wrote: Because of the links among financial markets brought about by portfolio movements, . . . portfolio choices of money managers drive exchange rates; the balance and terms of trade can change out of proportion to changes in relative production efficiencies. (1990b: 211) Then he connected the exchange rate to problems faced by US workers: Much of America’s industrial decline of the early 1980s was a creation of a grossly overvalued dollar that resulted from interest rate differentials, safe haven portfolio choices towards the dollar, and speculative momentum rather than due to a sudden deterioration of America’s comparative production costs. (Minsky, 1990b: 211)15 Minsky’s observations in retrospect Although Minsky’s observations were made more than two decades ago, he identified trends and dangers that continue to shape economic life in the United States and the global economy. Consider the following, for example. The share of US corporate equities held directly by households has continued its post-World War II decline, and money managers now control about two-thirds of the domestic equity market.16 To be sure, a significant share of today’s fund assets are passively managed (in the form of index funds, for example), but most – 70% – are still actively managed (Miller, 2016). Moreover, shareholder value is now widely recognised as driving corporate governance – along with the complementary strategic orientation of “downsize and distribute,” which has replaced “retain and reinvest” (Lazonick and O’Sullivan, 2000).17 Shortly before the global financial crisis of 2007–2008, the International Monetary Fund (2006) observed the global trend away from traditional banking (sometimes called “lend and hold”) and towards financing through markets and new forms of intermediation such as securitisation (often called “originate and distribute”). All of this was anticipated by Minsky (1990a: 70–71), who wrote – in 1988 – that “the 1950s and 1960s pattern of continuing bank and bank borrower relations is now obsolete.”18 The global financial crisis underscored the worldwide reach of MMC, the associated risk of macroeconomic instability, and the value of international policy coordination.19 In addition, over the past few years (even with a low rate of overall unemployment in the United States), it has become impossible for scholars, policy makers and reporters to ignore the realities of worker insecurity and widening income inequality in the United States and many other nations.20

Understanding financialisation  191

Minsky’s theory of capitalist development Of course, Minsky did not just leave behind perceptive observations that still resonate. He also left us an analytical framework that not only organises and provides a context for those observations but also enables us to extend his work. That framework yielded his theory of US capitalist development – a theory rooted in an evolutionary and institutionally oriented view of the economy; fashioned with an acute awareness of the central role that finance plays in economic life; and centred on the interaction of finance and industry. Evolution and institutions The crucial foundation of Minsky’s theory is his conception of the economy. Minsky argued that the underlying conception of economic life in conventional economics is characterised by endogenous stability: the economic system is believed to be inherently stable, or at least self-regulating, and business cycles and other economic dynamics are caused by exogenous disturbances. Instead, Minsky stood on the shoulders of Karl Marx, Wesley Mitchell, Schumpeter, Michael Kalecki and Keynes, all of whom viewed business cycles – and economic dynamics in general – as largely endogenous. In particular, Minsky saw cycles and other economic evolution as an inherent part of capitalist economic life – a natural consequence of self-interested behaviour taking place in complex systems of economic and financial relations. Moreover, from Minsky’s perspective, the disruptiveness of a bout of instability – indeed, the complexion of all economic outcomes – depends on the aptness of institutions and policy interventions (Ferri and Minsky, 1992). In other words, Minsky did not begin by assuming the inherent efficiency of markets and the validity of a laissez-faire stance towards economic policy. Instead, his starting point was evolutionary and institutionally focused thinking about the economy. Then he took that starting point and used it to analyse “the path of development of an accumulating capitalist economy through historical time” (Minsky, 1986d: 285).21 The centrality of finance The economists who inspired Minsky shared an appreciation of the central role that credit and finance play in a capitalist economy.22 “Because credit is essential to the process of development, a theory of economic development needs to integrate money into its basic formulation,” wrote Minsky (1990a: 55). And, in another essay, he added: “The in-place financial structure is a central determinant of the behaviour of a capitalist economy” (Minsky, 1993: 106). While scholars have long recognised Schumpeterian forces of creation and destruction when looking at products, production, and even industrial organisation, Minsky – who studied with Schumpeter at Harvard – emphasised that Schumpeter also gave attention to changes in financial systems. As a result, Minsky’s theory

192  Charles J. Whalen stressed that financial markets evolve not only in response to the profit-driven demands of business leaders and investors but also as a result of the profit-seeking entrepreneurialism of financial firms. According to Minsky, “nowhere is evolution, change and Schumpeterian entrepreneurship more evident than in banking and finance and nowhere is the drive for profits more clearly the factor making for change” (Minsky, 1993: 106). Minsky was explicit about the centrality of finance in his evolutionary theory. He wrote: To understand the short-term dynamics of business cycles and the longer-term evolution of economies it is necessary to understand the financing relations that rule, and how the profit-seeking activities of businessmen, bankers, and portfolio managers lead to the evolution of financial structures. (Minsky, 1993, 106) In fact, while conventional economics puts consumer choice in the driver’s seat, Minsky rejected that in favour of the vision (conception of economic life) of Schumpeter and Keynes: “Consumer sovereignty is subordinated to the vision of entrepreneurs and the critical analysis of bankers in determining the path of the economy” (Minsky, 1993: 107). The interaction of finance and industry In an essay titled “Money and Crisis in Schumpeter and Keynes,” Minsky (1986e) suggested that The General Theory was written because the Great Depression led Keynes to see a need to move beyond the economics of his previous books. I suspect the essay was written at a time when Minsky was feeling the same way about his own books. In fact, Minsky, who until that time had relied almost exclusively on Keynes for insight, practically says just that: “Further progress in understanding capitalism may very well depend upon integrating Schumpeter’s insights with regard to the dynamics of a capitalist process and the role of innovative entrepreneurs into an analytical framework that in its essential properties is Keynesian” (Minsky, 1986e: 113). “Money and Crisis in Schumpeter and Keynes” marks a turning point in Minsky’s research – towards integrating Schumpeter (and Mitchell) and Keynes. From Keynes, Minsky gained an understanding of how business cycles emerge as existing financial structures become more fragile over time. From Schumpeter, Minsky gained insight into how those structures evolve – taking on new dimensions and reshaping the economy in the process. The result of Minsky’s integration was his sketch of a long-term theory of US economic development, a theory focused on the interaction of finance and industry. Elements of Minsky’s theory are discussed in a number of articles and working papers.23 Taken together, they form an analysis that traces US capitalism through five stages: commercial capitalism (1607–1813); industrial capitalism (1813– 1890); finance capitalism (1890–1933); managerial capitalism (1933–1982); and

Understanding financialisation  193 MMC (1982–present).24 While providing a detailed account of the stages and the evolution of the economy from one stage to another is beyond the scope of this chapter, we can identify and briefly trace changes along some of the important dimensions that Minsky highlighted.25 What follows is a brief look at four dimensions of industry and finance that Minsky discussed when examining US economic development. Changes over time along each of these dimensions help to distinguish one stage from another: • The distinctive activity being financed evolved from trading or processing goods, to industrial expansion (acquisition of factories and machines), to industrial consolidation (trusts and merger), to macroeconomic growth and stability, and – in MMC – to corporate reorganisation or restructuring designed to boost shareholder value. • The pivotal source of financing evolved from the merchant bank (though internal finance was also important), to the investment bank (in both the industrial and finance stages, though such banking was more centralised in the latter stage), to the central bank (though internal finance was once again important) and – in MMC – to managed-money funds. (Moreover, “originate and distribute” became a key feature of financing in MMC, as previously discussed.) • The fundamental entity being financed evolved from a proprietorship or partnership, to an industrial corporation, to a combined corporation, to the private-sector financed through the central banking system (but the conglomerate was the dominant corporate form), and – in MMC – to the international corporation. • The locus of power was initially dispersed among merchants and bankers, but it then shifted to investment bankers during industrial and finance capitalism, to corporate managers (who assumed macroeconomic stabilisation by government), and eventually – in MMC – to money-fund managers. Extending Minsky’s theory By leaving behind a framework for analysis and not just insightful observations, Minsky allows us to stand on his shoulders to extend his theory of development and more clearly understand economic reality. Extensions of Minsky’s theory to date have taken a variety of shapes, including efforts to: enrich his analysis of stages; apply his framework to shed light on subsequent developments in the United States and the global economy; and build on his work so as to better understand developing and emerging economies. A few examples of each are briefly discussed. Some extensions of Minsky’s theory of US capitalist development have sought mainly to enrich or flesh out his analysis. An early effort on my own part was published in 1997; it focused primarily on how MMC and the spread of worker insecurity – the end of “shared prosperity” – were two sides of the same coin (Whalen, 1997). A second article, published in late 2001, explained Minsky’s

194  Charles J. Whalen framework and explored his economic stages and their evolution (Whalen, 2001). William Van Lear has also fleshed out Minsky’s theory. For example, his book A Populist Challenge to Corporate Capitalism enriches the Minsky theory in the course of exploring whether the economy’s evolution accords with fundamental American principles, which Van Lear identifies as a commitment to liberty, representation, property and enterprise. Among his conclusions: the corporation has evolved along a path inconsistent with these principles (Van Lear, 2002). More recently, Van Lear and Sisk (2010) have further fleshed out Minsky’s theory in an article that explores how MMC is similar to the earlier era of finance capitalism. Since Minsky’s death, a number of economists have used his analytical framework to shed light on subsequent developments in the United States and the global economy. In 2002, for example, Zalewski (2002) looked at the rise of retirement insecurity in the age of MMC; and Rima (2002) brought into the picture information technology, venture capital, further globalisation and NASDAQ trading. My own essays explored the technology-driven boom that preceded the dot-com collapse (Whalen, 2002) and updated the interaction between MMC and worker insecurity to the eve of the global financial crisis (Whalen, 2008a). Minsky’s framework has also been employed more recently to examine rising income inequality (Zalewski and Whalen, 2010) and, of course, the global financial crisis (Whalen, 2010; Wray, 2010; Tymoigne and Wray, 2014).26 A growing number of economists have also built on Minsky’s work to understand developing and emerging economies. They include Ventimiglia and Tavasci (2010), who explored how MMC has increased financial fragility in developing countries (such as Chile) primarily dependent on one commodity. Another contribution to this literature is Liang (2011), who examined the flow of capital into emerging market economies from countries where MMC prevails, highlighting the effects on financial-system development, market volatility and macroeconomic policy. Her bottom-line conclusion would have come as no surprise to Minsky: global money managers require greater regulatory scrutiny.

Understanding financialisation Minsky’s observations and framework represent a major contribution to the study of financialisation. Scholars often observe that the financialisation literature lacks cohesion, but a number of strands can be identified. Elements of Minsky’s work represent a contribution to them all – and in some cases, he anticipated much of the work done in recent decades. Van der Zwan’s strands Natascha Van der Zwan (2014) identifies three strands in the financialisation literature. One equates financialisation with the ascendancy of shareholder value as the driver of corporate behaviour. A key contribution to that literature is Lazonick and O’Sullivan (2000). As we have seen above, Minsky anticipated much of the

Understanding financialisation  195 literature that highlights the emergence of a shareholder value orientation and that examines its tremendous economic significance. A second strand equates financialisation with a regime of accumulation – that is, with a new stage of capitalist growth and development. In contrast to the strand of research emphasising shareholder value, which focuses on microeconomic activity, this second strand focuses on macroeconomic sphere. In this strand, financialisation in recent decades is seen as “a pattern of accumulation in which profit making occurs increasingly through financial channels rather than through trade and commodity production” (Krippner, 2005: 181). An important early contribution to this literature is Arrighi (1994), though the tradition can be traced back further, including Aglietta (1979). Minsky’s theory of capitalist development parallels the financialisation work done by Arrighi and other scholars working in the macro sphere. Both lines of research place the US and global economic developments of the past few decades in the context of a broader sweep of history – and both put the interaction of finance and industry at the heart of their analysis. Minsky’s work warrants recognition as part of this strand of financialisation, not just for the observations on MMC but also for the analytical framework that connects those observations and allows us to integrate them with our own findings as the economy continues to evolve. A third strand of financialisation highlighted by Van der Zwan is the financialisation of everyday life. According to Van der Zwan (2014: 111), this strand involves studies that concern themselves with the rise of the citizen as investor. That research includes “a cultural perspective on financialisation, particularly with regard to the encroachment of finance into the realms of everyday life.” Although there are certainly aspects of this third strand that reach far beyond the work of Minsky, there is also some noteworthy overlap. To be sure, Minsky’s scholarship doesn’t contribute much to the work of researchers who examine how financial literacy campaigns affect the way ordinary people see themselves and their role in the economy and society. But also of interest to scholars working in this strand are the material outcomes of economic life for the broader population (Van der Zwan, 2014: 111) – something often overlooked in the other strands. Since a focus on material outcomes relates directly to the connection that Minsky made between MMC and worker insecurity, it seems reasonable to conclude that Minsky offered a contribution of substance to this strand as well as to the others. Additional strands and definitions Gretta Krippner (2005: 181) offers three additional strands of the financialisation literature. One equates financialisation with the rise of mutual funds and the explosive growth in financial trading that followed. Another uses financialisation to describe a shift from bank-based, relational financing to market-based, armslength financing and to increased reliance on new forms of intermediation such as securitisation. A third strand uses the term to refer to an upsurge in the economic and political power of those who derive their income from financial investments (that is, the rentier class). Minsky seldom addressed the political power

196  Charles J. Whalen associated with the rise of MMC, but there is no question that he anticipated much of the recent scholarship on each of the other aspects of financialisation identified by Krippner. Reflecting on the many strands of financialisation research, Gerald Epstein (2005: 3) fashioned a broad definition for his edited volume Financialization and the World Economy: “Financialization means the increasing role of financial motives, financial markets, financial actors, and financial institutions in the operation of the domestic and international economies.” Building on that definition, Thomas Palley argued at the end of 2007that the principal effects of financialisation are to: “elevate the significance of the financial sector relative to the real sector; transfer income from the real sector to the financial sector; and contribute to increased income inequality and wage stagnation” (Palley, 2007: 3). In light of the observations discussed in earlier sections of this chapter, it seems certain that Minsky would have seen Palley’s list as a good summary of the effects of MMC but with one huge omission: increased economic instability and the likelihood of a severe, global downturn. By mid-2008, that omission was apparent to economists and policy makers worldwide.

Understanding Minsky It is often said that Minsky was prescient about many things, including money managers, shareholder value, banking, securitisation and, of course, instability. Where did he get that insightfulness? I attribute his ability – to see what so many others missed and to peer so far into the future – to two features of Minsky’s outlook: he treated economics as a grand adventure, and he was willing, indeed eager, to step outside the world of theory and come into contact with the world of economic practice. Economics as a grand adventure In the early 1990s, a small batch of Minsky’s papers addressed his interactions with Schumpeter at Harvard in the period 1946–1949. Minsky described learning that Schumpeter would sit alone during office hours: the graduate students of the time “did not take Schumpeter seriously,” he observed. The prevailing ethic was careerist. The working postulate . . . was not only that big thinking was in the past, but, in truth, that it was not worth doing . . . In the prevailing view, economics was now a normal science, not a grand adventure, and therefore Schumpeter was irrelevant. (Minsky, 1992c: 362, n. 2) But Minsky looked at things differently. So he joined Schumpeter in his study – often accompanied by classmate Paulo Sylos Labini. Schumpeter encouraged them to develop their own style and follow their own vision.27 The message from Schumpeter: “Normal science was too easy” (Minsky, 1993: 103).

Understanding financialisation  197 Minsky’s vision (conception of the economy) was influenced by his time with Schumpeter, but he actually acquired the notion of economics as a grand adventure during his years as an undergraduate at the University of Chicago (1937–1941). In 1985, Minsky wrote about those years, stressing that economics was presented as part of the study of society: Economic history, political science, sociology, anthropology and economics were part of an integrated sequence aimed at understanding modern society . . . If I had my way, the standard American course in economics would be eliminated and economics would be introduced in the context of social sciences and history. The current American way of teaching economics leads to economists who are well trained but poorly educated. (Minsky, 1985: 214) Minsky’s vision was also shaped by events in the world around him while living in Chicago. Memorable events included local labour strikes (during one strike in 1937, police shot and killed ten unarmed demonstrators) and a swirl of domestic and international developments, including the trials and errors of the New Deal and war in Europe. He also attended many political talks and lectures, including a short course offered by Oscar Lange, which “made economics both interesting and important” (Minsky, 1985: 213–215).28 Another influence on Minsky was his service during and after World War II, which included work in the Manpower Division of the Office of Military Government in Berlin in 1946. His division head was David Saposs, a well-known labour economist and student of John R. Commons. “The experience in Germany – and the interactions with Saposs – impressed upon me the importance of the specific institutions and historical circumstances upon what happens in the world.” In fact, that experience reinforced what Minsky learned from Paul Douglas at Chicago – namely, that any formal analytical tool explains little of what happens in the world and “to be useful analytical tools have to be embedded in an understanding of the institutions, traditions, and legalities of the market” (Minsky, 1985: 212 and 216). After the global financial crisis of 2007–2008, many prominent academics and practitioners were asked how economists were caught flat-footed by the meltdown. Franklin Allen of the Wharton School argued the problem was that such an event was unimaginable to economists: “It’s not just that they missed it; they positively denied it would happen” (Knowledge@Wharton, 2009). Similarly, Wilem Buiter, chief economist at Citigroup in London, wrote that most economists had adopted an efficient-market perspective, resulting in theories “that not only did not allow questions about insolvency and illiquidity to be answered; they did not allow such questions to be asked” (Buiter, 2009). In contrast, Minsky devoted his career to asking such questions; they were part of his attempt to understand the world around him – part of his vision, part of his grand adventure.

198  Charles J. Whalen Beyond the world of theory Minsky’s ability to see what other people overlooked cannot be attributed to his vision alone. Another important part of his perceptiveness came from a willingness – indeed, eagerness – to step beyond the world of theory and come into regular contact with the world of practice. An early example of this is suggested by Minsky’s discussion (for a book celebrating his career) of people who influenced his thinking while at Harvard. As one would expect, Minsky mentioned the influence of Schumpeter, but he also mentioned John H. Williams, who served as vice president of research at the Federal Reserve Bank of New York as well as a Harvard professor and administrator (Papadimitriou, 1992: 20). After tenure and promotion at Brown University, Minsky moved to the University of California, Berkeley, and collaborated with acquaintances from Harvard who worked nearby at the Bank of America (BoA). Together, they arranged funding for seminars and lectures that fostered interaction between the bank’s staff and Berkeley faculty and students. At that time, BoA was the largest bank in the United States and had invented the VISA card, then known as Bankamericard. “The interchange of ideas in these seminars helped fashion Hy’s ideas about institutional innovation in banking,” reported Dimitri Papadimitriou (1992: 22) following an interview with Minsky. Minsky later moved to Washington University in St. Louis and began an association with the Mark Twain Banks. When offers from other universities eventually came in, Washington University remained the more attractive option because of Minsky’s relationship with the banks. Asked by Papadimitriou to identify his most important intellectual debs, Minsky responded: It’s hard to say. Certainly [Henry] Simons, Lange and Schumpeter were important, but generally I believe we are all products of our environment. The involvement with the Bank of America staff, and later with the Mark Twain Bancshares was also significant in the development of my ideas. (quoted in Papadimitriou, 1992: 25) Minsky’s engagement continued when he moved from Washington University to the Levy Economics Institute in the early 1990s. There, he participated in regular seminars and conferences that drew practitioners as well as scholars from around the world. He also began each day by reading the Wall Street Journal, Financial Times and other newspapers. Minsky understood what was happening in the economy, especially with respect to money and finance, because he was, to the very end, a voracious student of how it actually functioned.

Conclusion: recap, challenges, and hope For most of his career, Minsky stood on Keynes’s shoulders to understand financial markets and business cycles. Then, in the final decade of his life, he stood on the shoulders of Schumpeter and Keynes to understand the longer-term trends in the

Understanding financialisation  199 US economy. The result was a series of publications in which Minsky offered penetrating observations on the emergence and spread of what he called money manager capitalism. His essays from that period also sketch out a powerful analytical framework that Minsky used to organise his thinking and offer a theory of US capitalist development. Today, we can stand on Minsky’s shoulders. Since his death, a literature on financialisation has developed and rapidly expanded. This chapter has shown that Minsky’s work represents a major contribution to that literature, touching on all strands of contemporary financialisation research. Standing on the shoulders of Minsky, we can update his observations, apply his framework and extend his theory. In the process, we can explore new trends, identify and embark on new directions for research and – equally important – enhance public understanding of what’s happening in the economy. Difficult times These are difficult times in the academy, however, for economists with a Minsky perspective. Minsky’s formidable powers of economic observation surfaced because he treated economics as a grand adventure into matters that were as important as they were interesting. Then he honed those powers, leaving behind an extraordinary legacy of insight and analysis, because he was willing to step beyond the world of theory and come into regular contact with the world of economic practice. Today, however, there is little room for any of that – it was the road less travelled in his time, and is an even more precarious and desolate way in ours, an era in which professional advancement demands publishing in journals that are largely off-limits to unconventional thinkers. Despite the not-too-distant experience of a global financial crisis, much of the economics profession remains in denial about the need to change (Parramore, 2016; Chakrabortty, 2013; Davies, 2012). These are also challenging times outside academia. The US economy has been stuck in low gear for so long that secular stagnation is again part of the profession’s vocabulary.29 Working families in the United States continue to bear the burden of four decades of earnings stagnation and income inequality (Gould, 2017, 2015).30 And money manager capitalism, aka financialisation, remains entrenched – despite contributing not only to macro and labour problems across the nation but also to increased economic and political tensions in Europe and elsewhere.31 Hope Still, all is not lost. The large and interdisciplinary body of literature on financialisation that has emerged in the past couple of decades is evidence of a growing interest in the issues that Minsky raised in the 1980s and 1990s. In addition, as Minsky stressed, economic systems are not natural systems: an economy is a social organisation created by a combination of legislation and evolutionary processes of invention and innovation. “Policy can change both the details and the overall character of the economy, and the shaping of economic policy involves both a

200  Charles J. Whalen definition of goals and an awareness that actual economic processes depend on economic and social institutions” (Minsky, 1986a: 7). Policy – at times intentionally and at other times inadvertently – helped to create and reinforce money manager capitalism.32 Policy can also scale it back, tame it or even replace it. Besides, as Minsky often said, capitalism “comes in as many varieties as Heinz has of pickles,” so we certainly have plenty of options from which to choose.33 Standing on the shoulders of Minsky, we better understand financialisation. This includes the dispiriting realisation that financialisation has accentuated many of the predatory aspects of modern economic life (Minsky, 1996: 363). But we also catch a glimmer of hope in the realisation that there is nothing natural about the economic system and nothing inevitable about our economic future. The task ahead is to use our improved understanding to chart a course towards a future in which the economy is not only more robust and stable, but also more humane.

Notes   1 As will be discussed, financialisation has many meanings. According to Epstein (2005: 3), “financialization means the increasing role of financial motives, financial markets, financial actors, and financial institutions in the operation of the domestic and international economies.”   2 The role played by Minsky’s financial-instability hypothesis has evolved over time. It began (and continues to serve) as the foundation of an investment theory of business cycles (see Minsky, 1975, 1982). Then it also became an explanation for increasing financial fragility in the US economy in the decades following World War II (Minsky, 1986a). Most recently, it has been presented as an alternative to the “efficient market” hypothesis of financial markets that was undermined by the global financial crisis of 2007–2008 (Whalen, 2013: 19).   3 See Minsky (1996, 1993, 1992a, 1990a, 1990b) and Minsky and Whalen (1996). Those sources provide the basis for this chapter’s discussion of Minsky’s observations on money manager capitalism.   4 As Minsky wrote in 1996, “the performance of a fund and of fund managers is measured by the return on assets, which is given by the combination of dividends and interest received and the appreciation in per share value” (Minsky, 1996: 363).   5 Minsky’s observations on what the emergence of MMC meant for corporations (see, for example, Minsky, 1996; Minsky and Whalen, 1996) were reinforced by the work of other economists writing in the 1980s, including Niggle (1988, 1986) and Harrison and Bluestone (1988).   6 The brief discussion of General Electric in this chapter draws on Lueck (1985) and Harrison and Bluestone (1988: 36-37), but for years Jack Welch’s transformation of that company was widely covered by journalists and extensively analysed by academics. For a recent look at Welch’s legacy that is consistent with Minsky’s concerns about money manager capitalism, see Stewart (2017).   7 In a paper delivered in Budapest in 1990, Minsky wrote: “Multinational corporations are of lessening importance; multinational portfolios are of increasing importance” (Minsky, 1990b: 211).   8 As Minsky wrote in 1992, “the emergence of MMC means that the financing of the capital development of the economy has taken a back seat to the quest for short run total returns” (Minsky, 1992a: 32).   9 In a paper written for a conference held in 1990, Minsky (1993: 111) wrote: “Given the tax laws and the way markets capitalized income streams in the 1980s, the total market

Understanding financialisation  201 valuation (value of equity shares plus bonds) of a highly indebted firm was typically greater than the market valuation of a more conservatively financed firm.” 10 Minsky’s “fringe banking” includes lending by finance companies, corporate issues of commercial paper and banks outside the Federal Reserve System. The concept is similar, but not identical, to “shadow banking.” For a recent discussion of shadow banking, see Nesvetailova (2014). 11 According to Minsky, “money managers are a large part of the market for securitized instruments. Sophisticated instruments can be created that mete out the cash flow from a corpus of assets with given cash flow properties to various claimants – the essence of securitization – in a way that is tailor-made to suit the objectives of a particular fund” (Minsky, 1990a: 71). 12 Securitisation put financial regulators in a tough spot, Minsky argued: “The growth of securitization means that, even as the power and authority of the regulators are attenuated, the scope and dimensions of their task increase” (Minsky, 1986b: 14). 13 According to Minsky, “an easier filter for financing ruled after securitization was developed than before.” The reason was simple: originators and underwriters walked away from the deal with net income and no recourse from the owners. “All that was required for the originators to earn their stipend was skill avoiding obvious fraud and in structuring the package” (Minsky, 1992b: 23). 14 Two notes are warranted. First, while Roach mentions “white-collar shock,” it is worth recalling that blue-collar shock had already been widespread for at least a decade, owing to plant closings at facilities making a variety of products including steel, automobiles, consumer electronics and textiles. Second, Minsky and Whalen (1996) cite a companion piece by Whalen (1996) that provides details on divergent trends across household income quintiles and on the rising gap between worker and executive salaries. 15 In another essay, Minsky noted that dollar-denominated debts in the global economy also contribute to worker insecurity in the United States. Because of the magnitude of such debts, the stability of the international financial system requires that the United States maintain both a sizable trade deficit and long-term capital exports, he argued: “The unemployment and industrial disruption in the rust belt are not due solely to ‘industrial’ inefficiencies. They largely are due to exchange rate patterns that emerged as market mechanisms ‘tried’ to attain balance of trade positions which enable debt burdens to be carried. . . . United States workers may lose jobs so that Brazilian debts to Swiss bankers that manage accounts for Arab interests can be validated” (Minsky, 1986c: 4 and 9). 16 Although the holdings of pension funds have decreased somewhat since the year 2000 (consistent with the movement of corporations away from defined-benefit pensions), holdings of mutual funds, hedge funds and exchange traded funds have largely taken their place (Ro, 2015). 17 For a recent look at the “shareholder value” norm and its consequences, see Lazonick (2017). Also see Berger (2014), which provides examples of companies forced – by financial-market pressures and the lure of short-term profits – to move away from activities that would have sustained manufacturing. Consistent with Minsky’s analysis, Berger argues that this trend has been occurring since the 1980s, resulting in a shrunken manufacturing sector. 18 For more on “lend and hold” vs. “originate and distribute,” see Kregel (2008). 19 For a Minsky perspective on globalisation and the need for international action, see Wray (2011); for other perspectives, see Feenstra and Taylor (2014). 20 While much has been written about worker insecurity since Donald Trump’s electoral victory in 2016 – see, for example, Levin-Waldman (2017) – Hacker (2006) is still worth reading. Also noteworthy is the 700-page book on inequality by Piketty (2014), which was a recent bestseller despite its considerable heft. 21 Minsky (1986d) – a paper prepared for a conference that convened in 1983 – contains what I believe is his first (albeit brief) discussion of the emergence of MMC.

202  Charles J. Whalen 22 In addition to Schumpeter, Keynes, Mitchell and the other economists mentioned above, Henry C. Simons also inspired Minsky. Simons’s view of the monetary-financial process and its role in economic life was much closer to that of Keynes and the institutionalists than to more recent “Chicago School” economists, argued Minsky (1982: 71–73). 23 For the most important essays in which Minsky addressed elements of his theory of capitalist development, seeMinsky (1996, 1993, 1992a, 1990a, 1990b) and Minsky and Whalen (1996). 24 In my own writings, I prefer to use the term banker capitalism (a term borrowed from John R. Commons, who aimed to highlight the role of investment bankers) for what Minsky called finance capitalism (a term often traced to Rudolf Hilferding). Since “finance” is an activity taking place at all stages, I find it best to avoid using the term to label a particular stage. However, I use Minsky’s term here, in part because it is often used by other economists – including some who are cited in this chapter. 25 For further discussion of Minsky’s stages and the evolution from one stage to another (including a discussion of the factors leading to money manager capitalism), see Whalen (2008a, 2008b, 2001). 26 Further extensions of Minsky are offered by Brown (2008) and Todorova (2009), who draw on aspects of his framework to examine consumer debt and the household sector. 27 According to Schumpeter, every theory rests on a theorist’s view (vision) of the basic features of society and of what is – and is not – important for understanding economic life (Minsky, 1992c: 365). 28 Minsky also writes about spending a spring vacation (in 1939) in Memphis, Tennessee, where he worked with organisers from the Southern Tenant Farmers Union. “This experience transcended the abstract student concerns with American racism and poverty” (Minsky, 1985: 217). 29 To be sure, real gross domestic product in the United States has shown strong growth in some recent quarters, but the threat of secular stagnation remains (see Summers, 2018). 30 For more on this, see Johnson (2018) and Quart (2018). Moreover, economic challenges in the United States are likely to become more difficult in the coming years owing to the ongoing ageing of the baby-boom generation. 31 For an examination of how financialisation has contributed to slower economic growth as well as greater instability and inequality, see Tomaskovic-Devy et al. (2015). 32 Minsky seldom mentioned the role played by government in the emergence and spread of MMC, but some references and a few complementary articles are listed in Whalen (2008a: 286). Minsky had more to say about how to turn policy in a more progressive direction; see, for example, Minsky (1996) and Minsky and Whalen (1996). 33 Minsky was also not terrified by the word “socialism.” In fact, he thought the label actually had little meaning since some brands of socialism have a lot more in common with certain types of capitalism than with other brands of socialism (and vice versa). He was, however, deeply committed to individual liberty, democracy, social justice and a humane economy (Minsky, 1985: 221; Minsky, 1986a: 9–10 and 293).

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Ecological economics Redefining economics for democracy and sustainability Peter Söderbaum

Introduction According to a textbook definition, economics is “the study of how society manages its scarce resources” (Mankiw and Taylor, 2017: 2). Mainstream texts also suggest specific ideas of what is “efficient” or “rational” for business and consumers as well as at the societal level. Firms are expected to maximise “monetary profits”; consumers maximise “utility” of goods and services, subject to their monetary budget constraint. At the societal level in specific decision situations concerning alternative investments in infrastructure (roads, railway systems, energy systems etc.), that alternative should be chosen which maximises “net present value” in monetary terms (or a monetary benefit–cost ratio). It should be noted first that the neoclassical approach is highly technocratic in the sense that it suggests what is normal for firms and consumers to do and also what is rational in specific decision situations when considering individuals, firms or society as a whole. It should also be observed that the assumed ideas of rationality and efficiency are specific in value or ideological terms. Should we expect firms to maximise monetary profits while forgetting about other interests? Should we look upon individuals as self-interested consumers who disregard all other affected interests? Is there a consensus in society about the objectives of consumers and firms or about the market values built into neoclassical Cost-Benefit Analysis (CBA)? As I see it, there are two main threats in present society. Present development trends are unsustainable in essential ways and democracy is losing ground in relation to dictatorship in some countries. At issue is whether we need to frame economics in alternative ways to better match and deal with the new challenges. As a first step, the present monopoly of neoclassical theory in economics education needs to be replaced with pluralism. We also need to consider alternatives at the level of perspectives. The neoclassical way of framing economics begins with the mentioned definition of economics. It continues with consumers and firms as the actors (or agents) to be considered, and it focuses on their mechanistic interaction in markets for commodities, labour or capital in terms of supply and demand. At the national level, a state is identified as potential agent, being a centre for politics in the form

208  Peter Söderbaum of market regulation. Progress at this national level tends to be understood in terms of “economic growth,” i.e. growth in Gross Domestic Product. GDP is, as we all know, a specific measure of all registered market transactions in an economy.

The sustainability challenge There is an extensive literature on sustainable development (SD). Here it is enough to argue that SD is a “contested concept” (Connolly, 1993). It can be interpreted (and manipulated) for specific purposes. Reference can for example be made to “sustainable profits” in business and “sustainable economic growth” at the national level. In these two cases, being sustainable is expressed in a monetary dimension. In my understanding, “sustainable development” refers primarily to a need to frame issues and analysis in multidimensional rather than one-dimensional monetary terms. Sustainable business in terms of monetary profits is certainly an issue in contemporary society given the existing institutional framework. But the present sustainability challenge is rather about the non-monetary aspects of development. Monetary impacts are still important but reducing analysis to its alleged monetary equivalent, so-called monetary reductionism, is questioned. On the non-monetary side, many dimensions are potentially relevant in analysis and decision-making. In 2015, 17 “Sustainable Development Goals” (SDGs) were sanctioned by the United Nations. They are about no poverty, zero hunger, good health and well-being, quality education, gender equality, clean water and sanitation, affordable and clean energy, decent work and economic growth, industry, innovation and infrastructure, reduced inequalities, sustainable cities and communities, responsible consumption and production, climate action, life below water, life on land, peace, justice and strong institutions and finally, partnerships for the goals. (United Nations, 2018) The list tells us how analysis needs to be broadened. “Economic growth” is still there but so are “responsible consumption and production,” and GDP growth is only one of 17 categories of goals. The main idea, as I see it, is that non-monetary impacts are described in their own terms and not reduced to one-dimensional monetary numbers. The “trade-off philosophy” of CBA, where non-monetary impacts of different kinds can be traded against each other and against monetary or financial impacts, is downplayed or abandoned. Why is this wise strategy? The answer is that we have increasingly understood that inertia and irreversibility are present on the non-monetary side and that the present call for sustainable development largely can be described as being about reducing, and where possible avoiding, negative, irreversible changes that are considered essential for human development. SD can be understood as non-degradation of non-monetary natural and human resources judged essential for survival in communities and in the global society. When natural resources are concerned,

Ecological economics  209 biodiversity loss, water pollution of specific kinds and CO2 emission exemplify such negative, largely irreversible changes.

The political and ideological challenge: democracy as a response Democracy is another contested concept (Connolly, 1993). In the social sciences, we have to live with a number of contested concepts like power, freedom and institution. This means, again, that we need to be explicit about how the term or concept is used in each case, for example by pointing to similarities and differences between different usages of the term. A dictionary definition suggests that “democracy” can be understood in terms of fiveelements of governance: • • • • •

Government by the people or their elected representatives. A political or social unit governed ultimately by all its members. The practice and spirit of social equality. A social condition of classlessness and equality. The common people, especially as a political force. (Collins Dictionary, available at: www.collinsdictionary.com/dictionary/ english/democracy)

Wikipedia refers to political scientist Larry Diamond, who describes democracy as a system of governance with the following components: • • • •

A political system for choosing and replacing the government through free and fair elections. The active participation of the people, as citizens, in politics and civic life. Protection of the human rights of all citizens. A rule of law, in which the laws and procedures apply equally to all citizens. (Diamond, 2004)

The two lists suggest that democracy is a multifaceted phenomenon that cannot be reduced to one single aspect. Voting procedures and the election of representatives in parliament (or other assemblies) is part of democracy but, again, reductionism is a danger. Democracy is about human rights, such as freedom of speech and freedom of organisation. It is about empowering individuals and groups by facilitating dialogue on various arenas. A “rule of law” is essential where the legal institutions are highly independent of the current political leadership and government and where power is divided rather than centralised. The independence of media should be protected. A degree of antagonism or ideological conflict between groups with different ideas of progress in society and between a ruling political party (or group of political parties) and political parties in opposition is regarded as normal (Mouffe, 2005). Democracy, then, can be understood in relation to its

210  Peter Söderbaum opposite, dictatorship. Democracy is about listening to many voices, while dictatorship is about minimising or controlling dialogue in society, a kind of reductionism in terms of voices. In relation to economics and sustainability, which is our main concern here, the opposite of democracy can also be referred to as technocracy. It is a dictatorship of experts where the framing of problems and the values to be considered in a search for optimal solutions are dictated by experts and the ideas and values they have internalised. Technocracy can be exemplified by monopoly for one paradigm in economics education and policy advice, such as neoclassical economics, or one method, such as neoclassical Cost-Benefit Analysis (CBA). In my judgement, dictatorship of an ideological kind, be it at the level of political parties or of economists as experts, is a threat to society. In relation to objectives to get closer to sustainable development, whistle-blowing must be possible, and civil society organisations have to be accepted and even encouraged (as long as they do not go against democracy itself). Of central importance, of course, is that there are more political parties than one, each guided by its ideological orientation, and that actors belonging to the ruling political parties and actors in other political parties have internalised ideas of justice and fairness. Democracy is not something that easily can be defined in either – or terms. Nations that are close to dictatorship may still exhibit elements of a democracy, and democracy, wherever it is judged to exist, can always be strengthened. In Sweden, as an example, a debate about the monopoly of neoclassical theory in economics education or its relationship to the present political economic system is largely avoided in the major media. This is so far a major failure in our ambitions to strengthen democracy. Manipulating dialogue is always a possibility. The idea that one should listen to different voices should include the presumption of respecting actors guided by ideological orientations other than your own ideological orientation. Sustainable development as ideological orientation differs systematically from neoliberalism as ideological orientation, and such differences need to be taken seriously in economic analysis. A paradigm such as neoclassical theory which systematically legitimises the present political economic system should not be given a monopoly position, if democracy is taken seriously.

Redefining economics A reconsideration of the two challenges identified – getting closer to sustainable development and strengthening democracy – suggests that the definition of economics as a discipline needs to be reframed as: Management of multidimensional resources in a democratic society. Why management of multidimensional resources? We have been accustomed to thinking patterns where “quantification is key to management” and “economics is about money.” This is largely made legitimate by neoclassical theory and method. In our daily life, however, we do not make decisions exclusively on the basis of

Ecological economics  211 quantitative and monetary considerations. There are qualitative and non-monetary elements as well in decision-making. Even visual elements are potentially involved. We may even refer to visions and ideological orientations. As ecological economists, not unexpectedly, we do emphasise ecological dimensions, but among non-monetary dimensions, there are for example social and health-related dimensions as well. United Nations has, as mentioned above, sanctioned no less than 17 Sustainable Development Goals with subdivisions in each category. One essential feature of all dimensions, but of non-monetary dimensions in particular, is the existence of inertia. We all know that inertia is a relevant phenomenon in disciplines such as physics and chemistry. But inertia is also relevant for a number of other non-monetary dimensions, ecological and health-related dimensions being examples. When a number of economists suggested that economics need to be reconsidered to take ecological dimensions and the biosphere seriously, this was a reaction to some of the simplifications of neoclassical theory (Costanza, 1991). Pollution of CO2, biodiversity loss and land-use changes exemplify impacts in ecological dimensions that are irreversible or difficult to reverse. It is recommended that such irreversible impacts together with other impacts in terms of inertia (commitments, path dependency, lock-in effects) are illuminated when preparing decisions. The two-stage or multiple-stage character of many decisions needs to be understood, whereas the neoclassical trade-off philosophy in monetary terms appears questionable and even dangerous. In particular, investments in infrastructure and mining projects need to be considered in new ways, and this is certainly also true of some decisions at the individual level. We will return to these issues of project appraisal later on. Why reference democratic society in the suggested definition? Economics is political economics in the sense that values and ideology are necessarily involved. Among respected economists, Gunnar Myrdal argued as follows: Valuations are always with us. Disinterested research there has never been and can never be. Prior to answers there must be questions. There can be no view except from a viewpoint. In the questions raised and the viewpoint chosen valuations are implied. Our valuations determine our approaches to a problem, the definition of our concepts, the choice of models, the selection of observations, the presentation of our conclusions – in fact the whole pursuit of a study from beginning to end. (Myrdal, 1978: 778–779) As I see it, our valuations “influence” the research process rather than, as in the above citation, “determine” it, since “determine” may be understood as if the values of the scholar were the only influential factor. In any case, it should be clear that mainstream neoclassical economics is specific in value or ideological terms and that the same is true of any other paradigm, such as the institutional ecological

212  Peter Söderbaum economics advocated in this chapter. Reference to value-neutrality is no longer possible in social sciences. Having examined orthodox economics and various brands of heterodox economics (feministic, institutional and ecological economics), Tanja von Egan-Krieger concludes that value-free economics is an illusion (2014). Mainstream neoclassical economists do not appear to accept von Egan-Krieger’s view that value-neutrality is an illusion or Myrdal’s argument that “values are always with us” in scholarly work. Neither would they accept my argument that “economics is always political economics.” Instead, an attempt is made in neoclassical texts to distinguish between “positive statements” and “normative statements” where the former are scientific and neutral and the latter value-laden and more ideological and political. N. Gregory Mankiw’s textbook (with Mark Taylor) for introductory economics courses (2017: 23–26) is an example. This view is certainly common, but in combination with the fact that there is a monopoly of neoclassical theory at many university departments of economics, it becomes a dangerous view. There are necessarily normative elements in so-called positive science. Values and ideology get into the picture from the very beginning of defining or understanding economics as a discipline, of pointing out the main agents in the economy, their relationships through markets and in other ways, ideas about efficiency and rationality etc. It can be noted that Myrdal in the above citation argues that “there can be no view except from a viewpoint.” Each actor, scholars in a university context included, refers to some viewpoint, vision, worldview or ideological orientation in my language. Eva Kras uses the word “vision” and points to the need to listen to different “visionaries” (Kras, 2007). These days reference is also made to “narrative” (Korten, 2015; Jakobsen, 2017). A narrative, then, stands for a story that brings together what are regarded as essential elements to facilitate our understanding of ideas about progress in society. What, then, is the narrative or ideological orientation of mainstream neoclassical economics? One, albeit simplified, among possible responses is as follows: individuals are essentially regarded as self-interested managers of money as consumers (to maximise utility), as wage earners and in roles of saving and investing money for different purposes. The market is at the heart of this narrative. Firms maximise profits and economic growth is the measure of progress in the economy as a whole. This neoclassical narrative is close to the ideology of neoliberalism, which has played (and still plays) an important role in contemporary Western politics and in many other parts of the world. In a democratic society with freedom of speech, freedom of organisation etc., those who embrace the neoclassical and neoliberal narrative certainly have the rights to promote what they believe in. What is wrong with the present situation from a democratic point of view is rather the close to the monopoly position of the neoclassical–neoliberal perspective in economics education at universities. Present development trends are unsustainable, and neoclassical economics as a science of governance has a role in this. The fact that ideology is involved means that only pluralism in university economics (and management)

Ecological economics  213 departments is compatible with a democratic society (Söderbaum and Brown, 2010). Neoclassical economic theory is one among many factors that makes neoliberalism and the present political economic system legitimate. If we want to consider changes in the current political economic system in efforts to get closer to a sustainable economy, we should abandon the present protectionism of neoclassical theory and open the door for competing perspectives. The situation in Sweden is an example of the mentioned lack of dialogue at the level of perspectives. Sweden is a functioning democracy in many respects, but education in university economics departments is limited to the neoclassical paradigm. In this way, such publicly financed departments become propaganda centres for a specific ideological orientation in market terms. This means that actors belonging to the main political parties, both social democrats and conservatives, rely on the same narrative about progress in society. It is true that there are other disciplines and university departments such as economic history, political science and management science that may offer partly different narratives, but these disciplines are not unaffected by the mainstream neoclassical – neoliberal agenda. Management science, for example, largely relies on the calculation and accounting methods connected with neoclassical theory and method. A functioning democracy means that there are after all some ways of challenging dominant narratives. But democracy is not only a matter of showing tolerance towards those with a different voice. By opening doors for many voices, democracy may also constructively contribute to problem-solving in governance. It is believed that decisions are improved when compared to a situation with centralised and more authoritarian decision-making. There is, furthermore, a whistle-blowing aspect in the functioning of democracy. The basis of knowledge and information for governance can be considerably improved. In dictatorships, actors may be reluctant to challenge the leadership. In more democratic countries, this kind of problem certainly exists as well but at a different level. It should finally be remembered that sustainable development is as much an issue at the global or planetary level, suggesting that we depend upon each other. If a considerable number of countries move towards dictatorship rather than democracy, then our common security system and learning opportunities will decline.

Proposed conceptual framework for ecological economics In social science and economics in particular, there is a tendency to keep politics at a distance. It appears as if knowledge gained within the scope of neoclassical theory is regarded as accepted by all and is in that sense neutral. Even market instruments (and other instruments) considered in attempts to deal with problems in society are somehow regarded as neutral. Neoclassical economists seldom, if ever, refer to ideology, narratives, worldview or visions as if such concerns were connected with the roles of other actors. This means that discussion in neoclassical texts is essentially limited to the neoclassical–neoliberal framing of problems. This is a case of cognitive inertia. Neoclassical economists appear to be cognitively locked into one perspective.

214  Peter Söderbaum But, as has been argued, unsustainable development trends should also be discussed at the level of perspectives. There may be paradigm failure, ideology failure, institutional failure and even failures at the level of individuals and organisations as actors. Contrary to advocates of the neoclassical mainstream, I believe that we also need to frame sustainability issues at the level of perspectives. If economics necessarily is political economics, then it appears appropriate to understand individuals as political economic persons, i.e. as actors guided by their ideological orientations. Political economic person assumptions Why this reference to political economic persons (PEP) and to “ideological orientation”? Ideology is certainly another contested concept, the use of which needs to be explained. It is here used in broadly the same way as in political discourse. Politicians and political parties refer to their ideologies or ideological orientations when turning to us as citizens for votes in public elections and for other support. And, as citizens, we respond to the ideas of politicians in one way or another, suggesting that we too are guided by something that can be referred to as ideological orientation. Ideology, then, can be described as a means–ends relationship. It is about an individual’s starting position (or the starting position of a collective such as an organisation or community), where one wants to go (future positions) and how to get there (strategy). Ideology is a concept at the level of viewpoint, worldview, vision and narrative and is therefore helpful in bringing ethics and broader concerns into economics. Individuals appear not exclusively in market-related roles but also in roles connected with active citizenship. And the role as citizen may spill over into market-related roles, for example in cases of fair trade. In a democracy, we are all politicians in some sense, and individuals can be regarded as conscious agents of change. Even life-styles need to be reconsidered. In relation to the challenge of sustainable development, there are of course limits to what one can expect from an individual in her different roles and situations. Individuals will differ in how they behave and as economists, at least ecological economists, we can encourage individuals to broaden their views. Abandoned is the claimed neutrality of neoclassical mechanistic theory. We need an economics that opens the door for small or large changes at all levels. A citizen and consumer can consciously influence her/his behaviour and life-style. CO2 emissions, for example, are influenced by our way of choosing means of transportation. Political economic organisation assumptions Our understanding of individuals and organisations is built on social psychology. Individuals within one organisation or belonging to different organisations interact in relationships and networks (Ford, 1990). Reference to political economic organisation (PEO) suggests that firms (or joint stock limited liability companies, to be more precise) represent only one category of organisations. In addition, there are

Ecological economics  215 for example civil society organisations (CSOs), universities, labour organisations, political parties, think tanks, municipal organisations, public agencies and international organisations, and they all play roles in relation to attempts to move closer to sustainable development. Organisations of different kinds are (much like individuals) assumed to be actors guided by their specific ideological orientation or “mission.” Such ideological orientations or missions need to be investigated in each case and not assumed as given. We need also to study how the ideological orientation or mission changes over time, depending upon context for one particular actor and for one category of actors. A political interpretation of markets The neoclassical view of markets is mechanistic. It starts from assumptions about perfect competition. Commodities traded in markets are assumed to be homogeneous, and sellers as well as buyers dispose of perfect or complete information. The interaction of sellers and buyers is expected to lead to equilibrium of prices in a mechanistic sense. Issues of ethics and responsibility play no role in this neoclassical worldview. And neoclassical analysis is static, implying that temporal and accumulative impacts are disregarded. Our worldview is different. Economic behaviour is not limited to behaviour in markets. Individuals and organisations, while largely behaving habitually, make decisions in many situations and contexts. And in market-related roles, it is not enough to focus on prices and quantities bought and sold. If sustainability is taken seriously, we need to estimate all kinds of monetary and non-monetary impacts that follow from a market transaction. Reference to single externalities as in neoclassical theory is not enough (Kapp, 1972). Market actors as PEPs and PEOs are once again guided by their ideological orientation or mission where issues of cooperation, trust, fairness, responsibility and accountability are potentially relevant. Decision-making as a matching process In neoclassical theory, decision-making is generally framed as a process of aiming at optimal solutions in quantitative terms. Our ambition is to also consider qualitative, visual and ethical elements. For these purposes, “ideological orientation” is a useful concept. Decision-making is seen as a matching process between an actor’s ideological orientation and the expected (normally multidimensional) impact profile of each alternative considered (Figure 9.1). Decision-making can similarly be regarded as “pattern recognition.” On the one hand is the actor’s ideas of desired patterns of impacts, and on the other expected patterns of impacts for the case that one specific of the considered alternatives is chosen. In addition, social impacts (positive or negative) upon other actors, including actors belonging to future generations, are potentially considered as part of an actor’s ideological orientation.

216  Peter Söderbaum Cognitive habits and ideological orientation of an actor or decision maker

Expected multidimensional impact profile of each alternative considered

Figure 9.1 Habitual behaviour and decision-making can be understood as the matching of an actor’s ideological orientation and expected impacts in multidimensional terms. Source: Söderbaum (2000: 58)

Within the scope of this worldview or paradigm, there is no attempt to formulate a general idea of efficiency or rationality. This is, once more, regarded as a matter of ideological orientation which varies between actors and for one actor over time and situations. From a sustainability point of view, alternative A1 may be considered as more rational (efficient) than alternative A2, while an ideological orientation limited to optimisation in terms of financial market terms may suggest the reverse order of preference. As already mentioned, neoclassical theory and method is built upon assumptions that objectives as well as impact are formulated in quantitative, precise terms. When viewing the world in terms of the ideological orientation of an actor, exclusive reliance on quantification of goals and impacts is an exception or perhaps a form of partial analysis. It is here suggested that ideological orientation is understood in multidimensional qualitative and quantitative terms, including visual elements, and the same holds for impacts. When buying a house, the price in monetary terms as well as expected monetary operating costs is essential, but also the view or image of the house matters. Why should visual aspects of a commodity or estate be assumed away? It should be added that ideological orientation as well as impacts is normally fragmentary and uncertain. The state of information or knowledge can often be improved, but perfect or complete information is not needed to guide behaviour. Politics of institutional change In a democratic society, there is an ongoing political dialogue. Politicians are expected to play roles in this dialogue, but other political economic persons and organisations also contribute. Change in institutional framework is prepared and implemented at the state level by the responsible government. But institutional change may also result from the activities of individuals and organisations as PEPs and PEOs. Individuals as actors in a business organisation may perceive problems in that the environmental impacts of business operations are not seriously considered when compared with financial (monetary) impacts. Actors in one organisation may share this view with actors in other business entities. A new environmental

Ecological economics  217 management system may be socially constructed and implemented, which is followed by a standardisation scheme such as ISO 14 001, with instructions about how progress in environmental terms can be described, measured and controlled. The process of institutional change or “institutionalisation” can be understood in stages: • • • •

Perception of problem. Suggesting terminology and conceptual framework to deal with the problem. Implementation and manifestation of the new institution. Acceptance of the new institution (thereby increasing legitimacy in relation to additional actors).

The emergence of a new institution such as Environmental Management System as in the above case does not mean that problems are being solved in any final sense. Acceptance is a matter of the ideological orientation (mission) of each actor. The main point here is that institutional change is not only a result of action in the form of new laws instituted by the national government but can be initiated and supported by engaged individuals at many places in the community. We are all political economic persons with potential to make a difference. Sustainability assessment in democratic societies Many nations, cities and other communities face decision situations in the fields of transportation, energy systems, housing. These decisions are complex in nature, with more than one alternative considered and with impacts both within and outside the community. Stakeholders can be identified and additional actors (who may not be stakeholders in a direct sense) may be concerned by the issues. How can one study such decision situations in a democratic society? Mainstream economists claim expertise in dealing with decision-making at the societal level. They advocate Cost-Benefit Analysis (CBA) as a method which is helpful in identifying optimal solutions, i.e. the “best” alternative for society as a whole. As previously mentioned, the monetary dimension is at the heart of CBA. Construction costs and operating costs are estimated for each alternative and different future time periods as well as other costs and benefits. Non-monetary impacts of different kinds are valued in market terms. A discount rate is used to relate future impacts to the present situation and to estimate a “present value” for each alternative of choice. This is a quantitative “trade-off analysis” in monetary terms, where in principle all kinds of impacts can be traded at a price against each other. CBA can be described as a technocratic approach, making the CBA-analyst expert in an extreme sense. To be able to identify an optimal solution for society as a whole, a specific ideological viewpoint is needed. The neoclassical paradigm and the technicalities of the CBA-method (with connected ideology) is useful for these purposes. Actual and hypothetical market prices are used to arrive at an aggregated present value in monetary terms for each alternative of choice.

218  Peter Söderbaum The CBA ideology has been described as a modified economic growth ideology focusing on “net value added” in monetary terms (Johansen, 1977), while our concern is to open the door for alternative ideological orientations such as a specific interpretation of sustainable development. It is clear that the CBA-method suffers from a “democratic deficit.” Economists as analysts have no right to dictate one ideology as being correct while excluding all other ideological orientations. Actually, neoclassical CBA is built upon an assumption that there is a consensus in society about the ideology built into CBA. Ezra Mishan, himself a textbook writer on CBA (1971), later (1980) argued that it is unrealistic to expect such a consensus. He pointed explicitly to environmental issues where there are many opinions. When it comes to poverty, inequality or the interests of indigenous people, a similar argument can be made. We need to respect more than one ideological orientation in society and avoid simplifying assumptions about one way of calculating what is best for society. The present tendency to avoid ethical and ideological dialogue should give way to an open dialogue where each actor has a chance to reconsider ideological orientation and take responsibility for her/his view. When commonalities of interest and conflicts of interest have been illuminated, some actors will hopefully find that they have learnt something for the future and will accept the outcome of majority voting or other decision rules. If CBA does not respond well to normal principles of democracy, how can one socially construct an alternative method that is more in line with democracy? A paradigm and conceptual framework that differs from neoclassical theory is needed. Economics needs to be defined and understood in a different way. As previously argued, monetary trade-off analysis has to be pushed back in favour of multidimensional analysis of a specific kind. Individuals need furthermore to be understood in a different way where the role as citizen and potential participant in public affairs is included. Ideological orientation was proposed as a key concept in guiding behaviour and decision-making. As an alternative to CBA, positional analysis (PA) is suggested. PA is part of a heterodox tradition in economics and goes back to 1973 (see Appendix in Brown et al., 2017). PA can also be understood as an interdisciplinary method comparable to systems analysis (cf. Clayton and Radcliffe, 1996). The purpose of PA is not to “solve” a problem in the sense of pointing to one single optimal solution. The main purpose is to strengthen democracy by “illuminating” an issue in a “many-sided” way with respect to: • • • • • •

Ideological orientations represented among politicians, stakeholders or others concerned by the issue. Alternatives of choice (some of which may correspond to specific ideological orientations identified). Monetary but also non-monetary impacts of different kinds. Issues of inertia and irreversibility illuminated in positional terms. Conflicts of interest. Uncertainty and risks. Conditional conclusions, for example in the form of ranking alternatives based on each ideological orientation considered.

Ecological economics  219 Positional analysis is described elsewhere (e.g. Söderbaum, 2000, 2008; Brown et al., 2017). Only two points will be made here. Sustainable development is not only a matter of technicalities. There are different interpretations of SD as ideological orientation (Söderbaum, 2000: 13–22). Some prefer to understand SD in “business as usual” terms (for example, sustainable GNP growth and sustainable business profits in monetary terms); others may refer to “modernisation” (certification schemes, fair pricing and Corporate Social Responsibility). SD may, however, alternatively be understood in terms of a need for radical change of business regulation and political economic system. However understood and described, SD can be compared to mainstream ideological orientation, such as neoliberalism. In a PA study, an attempt is made to clarify such differences. Ideological concerns have to be dealt with openly in a democratic society. “Positional thinking” is another essential element in positional analysis. “Position” is equal to “state” or “stock” and refers to a point in time. It is recommended in PA that decision-making is regarded as a multiple-stage process where inertia, path dependence, irreversibility and lock-in effects are illuminated. It is not enough to deal with land-use changes, biodiversity loss, CO2 pollution and pollution of soil and water systems in monetary trade-off terms. Such impacts and many other non-monetary impacts have to be considered in their own terms. The multiple-stage character of decision-making is perhaps best understood by comparing with a game of chess. Each player takes one step at a time and needs to consider options in the future as a result of the first step before making her move. Similarly, Geographic Position Systems (GPS) are used to navigate geographically in positional terms. We need a number of accounting indicators in ecological, social, health-related and other terms to broaden our ideas about sustainable development.

Concluding comments Our advocacy for pluralism and democracy also suggests that analysis within the scope of neoclassical economics can offer ideas for sustainable development. The application of environmental taxes is one example. But neoclassical theory is based on beliefs in the extraordinary efficiency of markets that are unaffected by state intervention. This suggests that neoclassical economists will not be enthusiastic in relation to proposals to implement Green taxes. It should also be made clear that there are alternatives to the kind of ecological economics advocated here. The previously mentioned book edited by Robert Costanza (1991) and For the Common Good by Herman Daly and John Cobb (1989), as well as a more applied study, The Economics of Ecosystems and Biodiversity (Kumar, 2010), exemplify a North American tradition of ecological economics. A textbook by Costanza et al. (1997) belongs to the same tradition. The present, more radical framing of ecological economics is rather an example of a European version that goes back to William Kapp and his book The Social Costs of Private Enterprise from 1950 (see also von Egan-Krieger, 2014; Söderbaum, 2008, 2015; Jakobsen, 2017; Brown et al., 2017). Fortunately, we do not need to

220  Peter Söderbaum look at the two versions of ecological economics and other versions in mutually exclusive terms. Each one of the two perspectives has something to offer, and a degree of competition and interactive pluralism is not necessarily a bad thing. We are back to the plea for pluralism in economics and the call for democratising economics (Söderbaum and Brown, 2010).

References Brown, Judy, Peter Söderbaum and Malgorzata Dereniowska, 2017. Positional Analysis for Sustainable Development: Reconsidering Policy, Economics and Accounting (Routledge Studies in Ecological Economics 46). Routledge, London. Clayton, Tony, Anthony M. H. Clayton and Nicholas J. Radcliffe, 1996. Sustainability: A Systems Approach. Earthscan, London. Connolly, William E., 1993. The Terms of Political Discourse (3rd edition). Blackwell, Oxford. Costanza, Robert, ed., 1991. Ecological Economics: The Science and Management of Sustainability. Columbia University Press, New York. Costanza, Robert, John Cumberland, Herman Daly, Robert Goodland and Richard Norgaard, 1997. An Introduction to Ecological Economics. St Lucy Press, Boca Raton, Florida. Daly, Herman E. and John B. Cobb Jr., 1989. For the Common Good: Redirecting the Economy Toward Community, the Environment and a Sustainable Future. Beacon Press, Boston. Diamond, Larry, 2004. What Is Democracy? Lecture at Hilla University for Humanistic Studies, 21 January 2004. Ford, David, ed., 1990. Understanding Business Markets: Interaction, Relationships, Networks. Academic Press, London. Jakobsen, Ove, 2017. Transformative Ecological Economics: Process Philosophy, Ideology and Utopia (Routledge Studies in Ecological Economics 45). Routledge, London. Johansen, Leif, 1977. Samfunnsøkonomisk lønnsomhet. En drøfting av begrepets bakgrunn og inhold (Profitability at the Societal Level in Terms of CBA: A Conceptual Study). Industriøkonomisk Institutt, Rapport Vol. 1. Tanum-Norli, Oslo. Kapp, K. William, 1972 (1950). The Social Costs of Private Enterprise. Schocken, New York. Korten, David C., 2015. Change the Story, Change the Future: A Living Economy for a Living Earth. Berrett-Koehler Publishers, San Francisco. Kras, Eva, 2007. The Blockage: Rethinking Organizational Principles for the 21st Century. American Literary Press, Baltimore, Maryland. Kumar, Pushpam, ed., 2010. The Economics of Ecosystems and Biodiversity: Ecological and Economic Foundations. Earthscan, London. Mankiw, N. Gregory and Mark P. Taylor, 2017. Economics (4th edition). Cengage Learning, EMEA, Andover, Hampshire. Mishan, Ezra J. 1971. Cost-Benefit Analysis. Allen & Unwin, London. Mishan, Ezra J. 1980. How valid are economic valuations of allocative changes? Journal of Economic Issues, Vol.14, No. 1, pp. 143–161. Mouffe, Chantal, 2005. On the Political. Routledge, London. Myrdal, Gunnar, 1978. Institutional economics. Journal of Economic Issues, Vol.12, No. 4 (December), pp. 771–783.

Ecological economics  221 Söderbaum, Peter, 2000. Ecological Economics: A Political Economics Approach to Environment and Development. Earthscan, London. Söderbaum, Peter, 2008. Understanding Sustainability Economics: Towards Pluralism in Economics. Earthscan, London. Söderbaum, Peter, 2015. Varieties of ecological economics: Do we need a more open and radical version of ecological economics? Ecological Economics, Vol. 119, pp. 420–423. Söderbaum, Peter and Judy Brown, 2010. Democratizing economics: Pluralism as path toward sustainability. In: Karin Limburg and Robert Costanza, editors, Ecological Economics Reviews, Annals of the New York Academy of Sciences (Vol. 1185, pp. 179–195). New York Academy of Sciences, New York. United Nations, Sustainable Development Knowledge Platform. Available at: www.un.org/ sustainable-development-goals/ (Accessed 10 February 2018). Von Egan-Krieger, Tanja, 2014. Die Illusion wertfreier Ökonomie. Eine Untersuchung der Normativität heterodoxer Theorien. Campus Verlag, Frankfurt.

Conclusions Victor A. Beker

After the 2007–2008 financial crisis exposed the shortcomings of mainstream economic theory, it became clear that a major rethinking of economics was absolutely necessary. We entered a stage of, in Kuhnian terms, competing paradigms. New paradigms are never delivered as ready-to-use products. They require a long process of debate until the “best ideas” win out. The contributions in this volume are meant to be part of this process. In the following pages, a summary of the main conclusions arrived at in the chapters which comprise the present volume is presented. For this purpose, contributions are classified into economics methodology, microeconomics, macroeconomics, financialisation and ecological economics. As far as economics methodology is concerned, the complexity approach and category theory offer new avenues for economic thought. The complexity approach offers an alternative to reductionism for the study of economic systems. Its point of departure is that reductionism is not suitable to study systems with many parts that interact to produce global behaviour. This behaviour goes far beyond what can be explained in terms of interactions between the individual constituent elements: the behaviour of the whole is much more complex than the behaviour of the parts. From the interaction of the parts, new behaviours or new phenomena emerge. The complexity approach changes not just the answers but also the questions economics has to answer. It allows for a general theory to be developed, one which is compatible with fundamental laws in physics, ecology, biology, psychology and anthropology and that is applicable in economics and management science. The evolutionary perspective developed by evolutionary economics, economic historians and political economy can be integrated into complexity economics. Studies in behavioural economics and psychology are a useful guide in modelling economic complexity. New tools in nonlinear dynamics, time-frequency spectra and collective models of the birth–death process can be applied in diagnosing financial crisis and providing advance warning in market regulation. Category theory changes the focus from objects to morphisms. This, in particular, frees economic models from the emphasis on equilibria, which become objects that may or may not exist in the appropriate category. Instead, the relational aspect

Conclusions  223 of morphisms allows for a variety of approaches to be captured in a single framework. Unlike traditional mathematical frameworks that demand every entity be defined in terms of simpler entities, category theory favours a “synthetic” approach, in which objects are given without any consideration to their inner structure, just their interactions with other objects. Category theory allows the relations among the mathematical universes corresponding to different axiom systems to be captured. On the other hand, the model-building approach, grounded in practices more common among computer scientists and physicists, can be clarified by means of categorical tools: a major tool is the structure of information itself. The next subject in this book has to do with micro and macroeconomic theory from Keynesian and Post Keynesian perspectives. The key features of Post Keynesian microeconomic theory are the following: • •

•

•

The basic goal of businesses is not profit maximisation but rather growth maximisation, constrained to a certain level of self-financing. Profit margins are not determined by the short-run degree of competition in the market, but are instead the outcome of two opposite forces: a competitive constraint (the opportunity frontier), which results from long-run competition among firms in the market and competition among firms to conquer market shares of a growing but limited demand. This force drives prices and profit margins downward; and a financial constraint (the finance frontier), which links profit margins to the need to internally finance investment expenses that are necessary to meet growing demands. This force drives profit margins upward, given that firms want to maintain their ability to finance their development on the market. Consumers are not as rational and as sovereign as in the historical mainstream school. They are subject to limited/bounded/procedural rationality, and rely on simple rules of behaviour that lead to permanent deviations from the standard model; Theses descriptive alternative elements lead to political positions completely different from the usual neoclassical one on competition policy.

Another issue is what a good textbook of microeconomics should look like. The answer is that it should offer sufficient space for the history of our discipline, analyse promptly the factors of production and provide a realistic description of the market mechanism and pricing of goods and services; it should also introduce the student to a solid theory of capital and profit under different market structures, as well as offer a clear overview of the labour market. Teaching a more relevant theory that is both theoretically sound and policy relevant will help to provide a better understanding of the economic phenomena at the level of the firm and the household. The neoclassical perspective is suitable only for the special case of ideal markets, absence of uncertainty and fully self-interested agents. Heterodox theories instead assume that economic agents behave more like real-world men and women, interdependent and with a variety of motivations, in real-world contexts with

224  Victor A. Beker fundamental uncertainty and interdependent risk, driven by social-level phenomena such as power, caring, status, beliefs, cooperation and norms. This should inform economic teaching. However, in spite of the blow suffered by neoclassical economics, it remains dominant. In any case, it is true that in-depth heterodox economic studies on the causes of the crisis nowadays receive more attention than heterodox research did before the crisis. Heterodox economists, plus a few neoclassical economists who want to look for answers to the painfully revealed flaws in the dominant theory, have set up think tanks and networks to cooperate in research, policy advice and teaching for an economy that is more stable and equal, less wasteful and better at contributing to livelihoods for all. The main demand for change in the economic curriculum comes from students. A pluralist textbook builds on hitherto marginalised but solid, renowned schools of thoughts in the discipline. A genuinely pluralist textbook should have much less emphasis on math and formalism and much more on understanding real-world economic processes. Pluralism means good science. It involves space for competition between theories. But, more importantly, pluralism creates the room for complementary explanations, which are context-dependent. Given the need to reconstruct macroeconomics from a realistic point of view, it is argued that Keynesian macroeconomics may be its point of departure. Why? Because realisticness is one of the features that distinguishes Keynes’s analysis. Keynes was a practical-minded economist. In contrast to many past and present economic theorists, he had great practical experience in economic policy. Recovering Keynes’s original legacy and pointing out its relevance for dealing with current economic problems is the starting point for a realistic economic theory. In the real world, prices do not behave symmetrically. Usually, nominal wages and prices are sticky downward but a lot more flexible upward; the latter is illustrated by inflationary and hyperinflationary processes. This asymmetric price behaviour has long been recognised by economists of different schools of thought. The difficulty for introducing this notion in economic theory has been that it is difficult to formalise. However, once the downward rigidity hypothesis is adopted, the explanation for phenomena like stagflation is straightforward. And price downward rigidity fits perfectly well with the Keynesian model. For these reasons, it is proposed that price downward rigidity must be a fundamental assumption in any economic model which tries to explain and predict real-world market behaviour as well as recommend economic policies. Financialisation is the next topic addressed in this volume. For most of his career, Hyman Minsky stood on Keynes’s shoulders to understand financial markets and business cycles. Then, in the final decade of his life, he stood on the shoulders of Schumpeter and Keynes to understand longer-term trends in the US economy. The result was a series of publications in which Minsky offered penetrating observations on the emergence and spread of what he called money manager capitalism. Minsky’s work represents a major contribution to the literature on financialisation.

Conclusions  225 The large and interdisciplinary body of literature on financialisation that has emerged in the past couple of decades is evidence of a growing interest in the issues that Minsky raised in the 1980s and 1990s. Financialisation has accentuated many of the predatory aspects of modern economic life. But there is nothing natural about the economic system and nothing inevitable about our economic future. The task ahead is to use our improved understanding to chart a course towards a future in which the economy is not only more robust and stable, but also more humane. Last but not least, this volume deals with ecological economics, which can broadly be understood as “economics for sustainable development.” The focus of neoclassical theory and method on the monetary dimension, so-called monetary reductionism, is questioned, and a multidimensional analysis of a particular kind, positional analysis, is recommended. It is proposed that economics is defined as “multidimensional management of resources in a democratic society.” Individuals and organisations are understood as political actors and are assumed to be guided by their ideological orientation or mission. Strengthening democracy is judged to be one path to a sustainable national and global society.

Index

Adam Smith’s theory of wealth of nations: bifurcation between classical and neoclassical economics 43, 44; complexity in division of labour 44, 45; perplexity in trade imbalance 44, 45; proposed generalised theorem 46; rethinking 43–46; return to political economy 45; trade-off between diversity and stability 45, 46 Agent-based Computational Economics (ACE) 15 Agent-Based Models (ABMs) 15 agents: categorical economic theory see categorical economic theory; interaction among 14, 15; multi-agent systems 15, 56; US housing market model 15 Arrow-Debreu general equilibrium model 10, 39, 162, 164 Austrian economics 21, 46 behavioural economics: categorical economic theory see categorical economic theory; conception of rationality 81; modelling economic complexity 50, 222; non-equilibrium perspective 21 biological clock 23, 29 biology: emerging paradigm of a unifying theory 49, 50; foundation of economic theory 47, 48; systems theory 23, 24 Brownian motion model 19, 21, 22, 29, 37, 47 business cycle theory: biological clock in 28, 29; external shocks vs. endogenous cycle 22; origin of 35; price behaviour 163–166; relative deviation and effective number for macro and finance indexes 35, 36; three-level structure revealed by principle of large numbers 35, 36

capital account controls 147 capital accumulation 135–140 capitalist development: centrality of finance 191, 192; economic evolution and institutions 191; interaction of finance and industry 192, 193; Minsky’s theory 191–194 categorical economic theory: applications of 57; basic concepts 58, 59; behavioural integrated model 61, 62; black box system 60; circularity problem 62–64; compositionality in games 64–66; compositionality of the system 60; conclusions 222, 223; definition of economics 56; diagrammatic reasoning 58, 59; examples of categories 58; focus of 56, 57, 66; interaction with computer science 61; literature on 57–61; mathematics overtaken by 56; relationship between structure and function 60; relevance of 56, 57; tools for representation and analysis 59, 60; uses 57, 58 Catholicism 145 certainty vs. uncertainty in dynamics 21, 22 chaos: absence of chartists 12; biased and unbiased fundamentalist traders 12; butterfly effect 24, 26; Copernicus problem in macro and finance analysis 28; deterministic chaos 24; dynamic noise 13; economics and 13; empirical studies of economic chaos 26–28; high-dimensional chaos 13; high noise level from economic indexes 26, 27; Lorenz chaos model 26; low-dimensional chaos 13; Lyapunov exponent 11, 24; mathematical complexity in economic models 25, 26; models of computational chaos 24–26; noise-cycle separation in

228 Index two-dimensional time frequency space 26, 27; non-linearity and 11, onedimensional chaos model of a logistical map 25; two-dimensional chaos model of a Henon map 26; unpredictability 11; white-chaos in discrete time vs. colour chaos in continuous time 27, 28; whitening filter in econometrics and white noise representation of efficient market 28 chartists: distinction between fundamentalists and 12 Coase theory of transaction costs 40, 41 collective mania 14 community economy: macroeconomic flow 114 competition: Coase theory 40, 41; post Keynesian firm theory 74–86; price behaviour 163, 168 complex adaptive systems (CAS) 20, 29 complexity: definition 9, 10, 19 complexity approach: conclusions 222; emergent behaviours and phenomena 9–16; focus 10, 16; interactive economic system 14, 15; non-linearity 11–13; orthodoxy or heterodox paradigm 16; reductionism and 9–16 complexity economics: complexity approach see complexity approach; complexity science see complexity science; computational economics with complex patterns 28–31; conflicting perceptions of economic information 36–39; dynamic returns to scale and metabolic growth theory 42, 43; empirical patterns and statistical mechanics in econophysics 31–36; empirical studies in economic research 26–28; history of studies in 25–41; increasing returns and path dependence in economy 41; mathematical complexity in economic modelling 25, 26; perpetual motion machines in equilibrium economics 39–41; rethinking Adam Smith and returning to political economy 43–46; simplicity vs. complexity concepts see simplicity vs. complexity concepts complexity science: computational uncertainty in mechanics 23, 24; deterministic chaos 23, 24; dialogue and complementation between history and 48, 49; systems theory in ecology and biology 24; thermodynamics of

evolution and self-organisation in physics 25; three disciplines 23 complexity studies: dynamic returns to scale 42, 43; future directions for 48, 49; increasing returns and path dependence in economy 41; metabolic growth theory 42, 45; rethinking Adam Smith’s theory and returning to political economy 43–46 computational economics with complex patterns: multi-regimes of market and phase transition during crisis 29, 31, 32; persistence of biological clock 29, 30, 31; resilience to regime switch 29; structural stability in parameter space 30, 31; transition probability for calm and turbulent market regimes 32 computer simulation in computational physics 28, 29 consumer demand 149 consumer theory: ecological economics 82, 83; Galbraith theory 83, 84; growth of needs principle 82; nonindependence (and heredity) principle 82; post Keynesian 81–84; quality of goods and services 83; question of rationality 81, 82; satiable needs principle 82; separability/ irreduciblity of needs principle 82; sovereignty of consumers 83, 84; subordination of needs principle 82 consumption (demand) cycle 23 convergence vs. diversity in economic evaluation 21 Copernicus problem in macro and finance analysis 28, 37 corruption 147 Cost-Benefit Analysis (CBA) 207, 210, 217, 218 crisis and insufficiencies of mainstream economic theory 89–92 cybernetics 24 decision-making 215, 216 demand-led growth 149 democracy: contested concept 209; definition 209, 210; dictatorship of experts 210; multifaceted phenomena 209; rule of law 209; sustainability assessment 217–219; technocracy 210 development banks 146 developmental states 145–147 disequilibrium and divergence 10 division of labour, complexity in 44, 45

Index  229 ecological economics: conclusions 225; consumer behaviour 82, 83; CostBenefit Analysis (CBA) 207, 210, 217, 218; decision-making 215, 216; democracy 209, 210; dimensions 211; non-monetary dimensions 211; positional analysis 218, 219; proposed conceptual framework 213–219; questioning monetary reductionism 208, 225; redefining economics 210–213; sustainable development 207–209; systems theory 24, 45, 82, 83; values and ideology 211, 212 economic growth: capital account controls 147; consumer demand stimulation 149, 150; definition 140; demand-led 149; endogenous dynamic 152–154; export demand stimulation 151, 152; formal institutions 145–147; free education at all levels 146; government expenditure stimulation 150, 151; gross domestic product 140, 141; growth equation 141, 148; health care and sanitation 146; importance of and reasons for 141, 142; inclusive growth 142–145; industrial policy 146; infant industry protection 147; informal institutions 148, 149; institutional economics of growth 145–149; investment stimulation 150; labourintensive production 147; land reform 146; post Keynesian theory 149–154; quality of growth 141, 142; religion 148; rule of law 147; social cohesion 141, 142; state-owned banks 146; stateowned firms 146; subsidies 146 economics: definition 56; redefining 210–213 Economist magazine: questions raised on the financial crisis of 2007–2008 104–108 econophysics: empirical patterns and statistical mechanics 31–36 education: economic drivers 139; effect of poverty 127; free at all levels 146; gender gaps 144, 145; institutions 91; sustainable development goals 208; underinvestment 140 Einstein’s theory of relativity 49 emergent properties 10 empirical patterns and statistical mechanics in econophysics 31–36 empirical studies of economic chaos: high noise level from economic

indexes 26, 27; noise-cycle separation in two-dimensional time frequency space 26, 27; white-chaos in discrete time vs. colour chaos in continuous time 27, 28 empirical test of chaotic models 26–28 employment: endogenous growth 152–154; inclusive growth 144, 145; involuntary unemployment see involuntary unemployment; Keynesian model 166; post Keynesian economics 118–123; price asymmetry 157; wealth effect 171 equilibrium: multiplicity 11; unique 11; stable price 14 equilibrium approach: fixed point attractors 11 equilibrium vs. non-equilibrium process 21 evolutionary economics 21, 50, 222 exchange rates: interaction between chartists and fundamentalists 12; nonlinearities and fundamentals 12 exports: formal institutions affect on 117; growth stimulation 151 external shocks vs. endogenous cycle in business cycle theory 22 financial crisis of 2007–2008: banker’s responsibility for 131; comparison with historical depressions 95, 96; failure to foresee 10; fallacy of orthodox economic thinking 179; global trend away from traditional banking 190; interest rates 120; key policy response by governments 105; market inefficiency 90; monetary policies 175, 177; money manager capitalism 190; neoclassical economics major causal factor 105–107; opportunity for pluralist economics 104; peak of chain events preceding 31; root of 36; teaching macroeconomics see teaching macroeconomics post 2007–2008 crisis; wake-up call to economists 46; warnings of crisis 106, 107 financialisation: capitalist development 191–194; centrality of finance 191, 192; conclusions 224; economic instability 188, 189; firms 78, 79; interaction of finance and industry 192, 193; Minsky’s observations 185–200; money manager capitalism (MMC) 185–190; strands of literature and research 194–196;

230 Index technological progress and industrial innovation 187, 188; understanding 194–196; Van der Zwan’s strands 194, 195; worker insecurity and income inequality 189, 190 financial markets: distinction between chartists and fundamentalists 12; efficient market hypothesis 12; nonlinearities 12, 13 firms: aggregate demand and supply 118–124; circular flow of goods and money 110; competition 74–85, 223; determination of profit margins 74–77; financial firms 186, 192; financialisation 78, 79; growth maximisation 72–76, 138; institutional macroeconomic flow 117; investment financing 75–78, 84; market power 128; post Keynesian theory 73–80; macroeconomic flow 113; price behaviour 163, 166–169; social influences 113; state-owned 146 fiscal policies: Keynes’s point of view 175–178 free education at all levels 146 Friedman spirits in market arbitrage 37, 38 Frisch model 39, 40 frequency analysis 22 fundamentalists: biased and unbiased fundamentalist traders 12; distinction between chartists and 12; distinction between optimist and pessimist traders 12; link between exchange rate and 12 game theory: categorical economic theory see categorical economic theory; econophysics 33; multiple equilibria 11 Gender Inequality Index (GEI) 134, 135 global warming: economic growth a cause of 141 globalisation 131 goods, services and money: circular flow 110 government: circular flow of goods and money 110; Coase theory 40, 41, 43; expenditure increase for growth stimulation 150, 151; fiscal policy 175–178; formal institutions constraint on transfers 116, 17; gross domestic product 125, 140, 141; macroeconomic flow 113; macroeconomic leakages 123, 124; reduced government protection 132, 133; social embeddedness 111, 113; social protection deficiencies 129; taxation leakage 123

gross domestic product (GDP) 125, 140, 141 gross national income per capita (GNI) 125, 26 growth: economic growth see economic growth; firm and sales 72, 74–76; higher education and training 91; needs 82, 85, 86 health care and sanitation 146 herd-like behaviour 14, 118 heterogeneity: Agent-based Computational Economics (ACE) 15; element in complexity 9 heterodox economics: complexity approach 16; strength of 109; teaching 107–110 heterodoxy: differences between orthodoxy and 9, 16 history and culture 22, 23 homogenisation of economics 91 homogenous models vs. hierarchal structure 23 households: macroeconomic flow 111, 112 Human Achievement Index (HAI) 134 Human Development Index (HDI) 125–127 IMF policy 108 import leakage 123 industrial policy 146 inequality: economic drivers 139; gender 134; horizontal 133–135; income 130, 131; increasing financial fragility 140; low aggregate demand 140; measuring 129; Minsky’s observations 189, 190; social conflict 139; social norms and 129; underinvestment 140; wealth 135–139 infant industry protection 147 inflation 156, 157, 163, 164, 171–174 information: changing society 38, 39; conflicting perceptions 36–39; cooperative partnerships 38, 39; costs and bounded rationality 37; economist’s use of term 37; entropy 36; Friedman spirits in market arbitrage 37, 38; Maxwell demon of market uncertainty 37, 38; mixed economies 38, 39; nature and sources of 36, 37; physicist’s understanding of 36 institutional economics: growth 145–149; lack of theory 39; metabolic growth 45; macro level institutions 115–117; wellbeing and poverty 129–135; zero transaction costs 21, 22

Index  231 institutional macroeconomics: consumption function 115, 16; exports and imports 117; government transfers 116, 117; institutional macroeconomic flow 117; investment 116; macroeconomic variables 115; poverty see poverty; wellbeing see wellbeing interactions and partial information 10 investment: financing 75–78, 84; formal institutions 116; growth stimulation 150 involuntary unemployment: aggregate supply and demand 118–120, 128, 140; endogenous growth 152, 153; household incomes 111, 112; inflation and 171–174; Keynesian theory 71, 72, 159–162; low aggregate demand 140; market forces 128; new Keynesian contribution 164–166; non-accelerating inflation rate 173; price asymmetry 159; realisticness 159, 160; stagflation 174, 175; wage rates and 171–174 Ising model: of collective behaviour 34; of ferromagnetism 33; of social psychology 33 Keynesian economics: equilibrium vs. non-equilibrium process 21; general theory 49, 70; macroeconomics see post Keynesian macroeconomics; microeconomics see post Keynesian microeconomics; monetary and fiscal policies 175–178; new Keynesian economics 71–73; price behaviour see price behaviour; unifying theory in economics 49, 50 labour-intensive production 147 land reform 146 life expectancy 125 linear model: binary alternative 11, 16 linear vs. nonlinear models 20 liquidity 49, 90, 171, 175, 176 Lyapunov exponent 11, 13, 24 macro and finance indexes 35, 36 macroeconomic or circular flow: community economy 114; diagram 110; embedded in nature 114, 115; embedded in society 111–114; embedded macroeconomic flow 115; firms 113; goods and money 110; government 113; households 111, 112; institutional economics 115–117; leakages 123; macro level institutions

115–117; overview 109; post Keynesian economics 118–124 macroeconomics: post Keynesian economics see post Keynesian macroeconomics; teaching see teaching macroeconomics post 2007–2008 crisis macro level institutions: consumption function 115, 16; exports and imports 117; government transfers 116, 117; institutional macroeconomic flow 117; investment 116; macroeconomic variables 115 management of multidimensional resources in a democratic society: redefining economics as 210–213 market forces 128 market liberalisation 132, 133 market power 128 Markov processes 22 Marshallian model 10 mathematics: categorical economic theory see categorical economic theory; complexity in economic modelling 25, 26; empirical studies of economic chaos 26–28; integrable vs. non-integrable terms 22; methodological individualism 19; network theory 19; origin of complexity science 23–25; role of in economic thinking 46, 47 Marxist economics 21 Maxwell demon of market uncertainty 37, 38 metabolic growth theory 42, 45 methodological individualism vs. system and network thinking 19, 20 microeconomics: business cycle theory 35, 37; crisis and insufficiencies of mainstream economic theory 89–92; economic information 37; linear vs. nonlinear models 20; post Keynesian economics see post Keynesian microeconomics; single vs. multiple equilibria 20; teaching see teaching microeconomics; time-symmetric and time-asymmetric processes 22, 23 Minsky’s observation and framework: beyond the world of theory 198; capitalist development 191–194; challenging times 199; economics as a grand adventure 196, 197; hope for the future 199, 200; money manager capitalism 185–190; understanding financialisation 194–196 models of interaction between agents: Agent-based Computational

232 Index Economics (ACE) 15; Agent-Based Models (ABMs) 15; US housing market model 15; simplicity vs. complexity concepts see simplicity vs. complexity concepts monetary policies: Keynes’s point of view 175–178 money manager capitalism (MMC): economic instability 188, 189; income inequality 189, 190; Minsky’s observations 185–187, 190; technological progress 187, 188; worker insecurity 189, 190 multi-agent systems 15, 56 Multidimensional Poverty Index (MPI) 127, 128 multi-regimes in financial markets 29–31

Newtonian mechanics 23 noise representation 22 non-linear development and divergent evolution 23 non-linearity: assumption and its implications 11; attractors and chaos 11; in the financial markets 12, 13; use of nonlinear models 10, 16 non-price equilibrium economics vs. price equilibrium economics 162, 163

nature: ecological economics see ecological economics; economy embedded in 111, 114, 115; social economics of growth 142 negative feedback 24 neoclassical economics: certainty vs. uncertainty in dynamics 21, 22; convergence vs. diversity in economic evaluation 21; equilibrium vs. nonequilibrium process 21; external shocks vs. endogenous cycle in business cycle theory 22; financial crisis 2007–2008 causal factor 105–107; homogenous models vs. hierarchal structure 23; methodological individualism vs. system and network thinking 19, 20; Newtonian paradigm 21; redefining economics 210–213; representative agent model 19; self-fulfilling prophecy of 105, 106; simplicity model 19, 20; stability 21; stationery vs. nonstationery time series analysis in econometrics 21, 22; sustainability see sustainable development; timesymmetric and time-asymmetric processes in economics 22, 23 neoclassical microeconomics: basic model 20; linear demand and supply curve 20; linear vs. nonlinear models 20; single vs. multiple equilibria 20 neoliberalism 212, 213 net-work architecture 10 new Keynesian economics: aim of 71, 72; art of 72, 73; post Keynesian economics see post Keynesian microeconomics; price behaviour 163–166

perpetual motion machines used in equilibrium economics: Arrow-Debreu model 39; Coasian world with zerotransaction costs 40, 41; Frisch model 39, 40; general equilibrium mechanism without energy costs 39; Walraisian model 39 Phillips curve 171–174 physics: chaos theory 19; computational economics 28, 29; econophysics 31–36; emerging paradigm of a unifying theory 49, 50; empirical tests of chaotic models 26–28; foundation of economic theory 47, 48; homogenous models 23; interactive particle systems 14; origin of complexity science in 23–25; structure analysis 35; thermodynamics of evolution and self-organisation in 25; time symmetric terms 22 pluralism in economics 92, 96, 105, 108, 109, 207, 212, 220, 224 pluralist economics textbook 109, 110, 224 political economics: decision-making as a matching process 215, 216; institutional change 216, 217; political economic organisation assumptions 214, 215; political economic person assumptions 214; political interpretation of markets 215; return to political economy 43–46 post Keynesian macroeconomics: aggregate consumption function 120–122; aggregate supply and demand 118–124; economic growth theory 149–154; fallacy of composition 118; herd behaviour 118; key concept of uncertainty 118; multiplier effects

orthodoxy: approach to economic phenomena 10; differences between heterodoxy and 9, 16; simplification 9; theory developed regarding catastrophic crisis 10 out-of-equilibrium dynamics 10

Index  233 122–124; open system circular flow 124; open system dynamics 118–120; paradox of thrift 118–120; wealth inequality 135–140 post Keynesian microeconomics: alternative to mainstream economics 69–73, 78, 84, 85; competition 69–80, 84, 85; conclusions 223; consumer theory 81–84; convergence 77, 78; descriptive rupture 69, 72, 73, 84; determination of profit margins 74–77; differences between mainstream economics and 72, 73; economic policy and 84, 85; financialisation 78, 79; growth maximisation 72–76; investment financing 75–78, 84; key features 85, 86; microfoundations 69–72; micro theory 69, 70; neoclassical synthesis and its collapse 70, 71; new Keynesian paradigm 71–73; normative rupture 69, 72, 73, 84; objectives of the firm 73, 74; price behaviour 70–73, 166, 167; profit margin determination 74–77; subcontracting 79, 80; theory of the firm 73–80; wage rigidity 70–73 poverty: fairness 130; globalisation 131; horizontal inequality 133–135; income inequality 130, 131; inequality 129; market forces 128; market liberalisation 132, 133; multidimensional measure 127, 128; Multidimensional Poverty Index (MPI) 127, 128; post Keynesian perspective 135–140; reduction in government protection 132, 133; social norms 129; social protection deficiencies 129; status 130; technological change 131, 132 price behaviour: aggregate demand and supply functions 167; asymmetry 159; business cycle models 163–166; competition 168; conclusions 179, 180, 224; cutting prices 168, 169; European experience 178, 179; excess supply 168–170; financial sector’s role 180; Fundamental Microeconomic Assumption (FMA) 170, 171, 179; involuntary unemployment see involuntary unemployment; Keynesian macroeconomics 159–163; market behaviour 168–170; menu cost model 163; monetary and fiscal policies 175–178; necessity for analysis 179; new Keynesian contribution 163–166; non-price equilibrium economics vs.

price equilibrium economics 162, 163; overview 156–159; Philips curve 171–174; post Keynesian approach 166, 167; reaching non-price equilibrium 167; realisticness 159, 160, 179; rigidity 70–73; stagflation 174, 175, 179; stickiness 156, 157, 163–166, 169, 178; symmetry an unrealistic assumption 159; wealth effect and price asymmetry 171 production (supply) cycle 23 profit margin determination 74–77 Protestantism 148 quality of goods and services 83 random walk 21, 22, 29 redistribution of income 146 religion 148 Robinson Crusoe economy 19 Romer model of endogenous growth 45 rule of law 147, 209 Samuelson’s model 29 Schumpeterian economics 21 school enrolment and literacy 125 simplicity vs. complexity concepts: certainty vs. uncertainty in dynamics 21, 22; convergence vs. diversity in economic evaluation 21; equilibrium vs. non-equilibrium process 21; external shocks vs. endogenous cycle in business cycle theory 22; homogenous models vs. hierarchal structure 23; linear vs. nonlinear models 20; methodological individualism vs. system and network thinking 19, 20; single vs. multiple equilibria 20; stationery vs. nonstationery time series analysis in econometrics 21, 22; time-symmetric and time-asymmetric processes in economics 22, 23 single vs. multiple equilibria 20 social economics: embedded economics 111–115; wellbeing and poverty 125–129 Social Institutions of Gender Index (SIGI) 134 social norms 129 social protection deficiencies 129 social temperature vs. social interactions 33 Solow model of exogenous growth 45 speculative bubbles 14, 15 spontaneous order 23

234 Index stagflation 174, 175 stampede phenomena 14 state-owned banks 146 state-owned firms 146 stationery vs. non-stationery time series analysis in econometrics 21, 22 statistical mechanics in econophysics: fat-tail distribution and power law in finance 33, 35; meso foundation of macro fluctuations 35, 36; principal of large numbers 35; relative deviation and effective number for macro and finance indexes 35, 36; social temperature vs. social interactions 33; unsolved issues 33 subcontracting 79, 80 subsidies 146 sustainable development: contested concept 208; Cost-Benefit Analysis (CBA) 207, 210, 217, 218; democratic societies 217–219; interpretation 208; meaning 208; neoclassical assumptions 207, 208; sustainability challenge 208, 209; Sustainable Development Goals 208 synergetics 24 taxation: fiscal policy 175–178; leakage 123 teaching macroeconomics post 2007–08 crisis: demand for change in economic curriculum 108; dominance of one theory 104–107; economic growth see economic growth; Economist magazine questions 104–108; gross domestic product (GDP) 125; initiatives for change 108, 109; macroeconomic flow see macroeconomic or circular flow; neoclassical economics teaching dominance 107, 108; pluralist economics textbook 109, 110; post Keynesian economics 118–124; poverty measure see poverty; wellbeing measure see wellbeing teaching microeconomics: aim of the economist 93; analyse mainstream theory on strategic interdependence 94; behavioural science 97, 98; crisis and insufficiencies of mainstream economic theory 89–92; economic history 95–97; economics as a useful science 99, 100; emergent properties arising 95; giving emphasis to economic substance over

mathematical technique 93; history of economic thought 96, 97; instructions for relevant microeconomics 92–95; learning from the past 95–97; offer part of course on market failures 94; preserve crucial economic microeconomic concepts 94; psychology matters 97, 98; recognition of individuals limited cognitive and computational capacity 93; scientific research programs 96; social exchanges 98, 99; textbook requirements 100 thermodynamics of evolution 25 time-symmetric and time-asymmetric processes in economics 22, 23 trade deficit 10, 44 transaction costs: Coase theory 40, 41 underinvestment 140 unemployment see involuntary unemployment US housing market model 15 wages: effect on employment 171–174; rigidity 70–73 Walrasian general equilibrium model 10, 39, 162, 167, 168 wealth inequality: capital/income ratio 136–139; economic drivers 139; increasing financial fragility 140; low aggregate demand 140; post Keynesian theory 135–140; social conflict 139; underinvestment 140 wellbeing: fairness 130; globalisation 131; gross national income per capita 125, 126; horizontal inequality 133–135; Human Development Index (HDI) 125–127; income inequality 130, 131; life expectancy 125; market liberalisation 132, 133; multidimensional measure 125–127; post Keynesian perspective 135–140; poverty measure see poverty; reduction in government protection 132, 133; relative wellbeing measure 129; school enrolment and literacy 125; status 130; technological change 131, 132 worker insecurity: Minsky’s observations 189, 190 World Economics Association 46