The Economics of Financial Cooperatives: Income Distribution, Political Economy and Regulation [1 ed.] 0367358395, 9780367358396

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The Economics of Financial Cooperatives: Income Distribution, Political Economy and Regulation [1 ed.]
 0367358395, 9780367358396

Table of contents :
The Economics of Financial Cooperatives
Contents
Figures
Tables
Acknowledgements
Acronyms
1 Introduction
1.1. Introduction
1.2. Financialization, distribution, and the political economy of finance
1.3. Financial cooperatives for egalitarian development
1.4. Avoiding an idealisation trap
Bibliography
2 Finance, distribution, and the economic objective of financial cooperatives1
2.1. Introduction
2.2. Model setup
2.3. Income and wealth distribution with credit rationing
2.4. Income and wealth distribution with financial cooperatives
2.5. Financial cooperative economic objective function
2.6. Concluding remarks
Note
Bibliography
3 Financial cooperatives and income inequality
3.1. Introduction
3.2. Finance and income inequality
3.3. Data and method
3.4. Results
3.5. Concluding remarks
Bibliography
4 Political economy theory for financial cooperative development1
4.1. Introduction
4.2. Political history of financial cooperatives
4.3. A political economy theory of financial cooperatives
4.4. Concluding remarks
Notes
Bibliography
5 Political institutions and financial cooperative development
5.1. Introduction
5.2. Data and method
5.3. Results and discussion
5.4. Conclusion
Notes
Bibliography
6 The origin and rationale for financial cooperative regulation in underdeveloped economies
6.1. Introduction
6.2. The historical origins of financial cooperative laws in underdeveloped economies
6.3. Current models of financial cooperative laws
6.4. Rationale for financial cooperative regulations
6.5. Conclusion
Note
Bibliography
7 Regulation, supervision, and deposit insurance for financial cooperatives
7.1. Introduction
7.2. Regulation, supervision, and deposit insurance for financial cooperatives
7.3. Data and method
7.4. Results and discussion
7.5. Conclusion
Notes
Bibliography
Discussion and conclusions
Appendix Chapter 1: Econometric methods
Bibliography
Index

Citation preview

The Economics of Financial Cooperatives

Building on theories of finance and distribution, and the political economy of finance, this book explains the influence of financial cooperatives on wealth and income distribution, and institutional factors that determine the development of financial cooperatives. The book discusses the dynamics of income and wealth distribution with and without financial cooperatives and defines the economic objective for financial cooperatives. Through explaining the influence of political institutions and regulations on the development of financial cooperatives, this book examines why financial cooperatives grew in some emerging economies and not in other similar ones. The book is of interest to scholars interested in financial economics, political economy of finance, alternative banking and development finance, and banking regulation. The book also gives valuable output to central bankers and financial and monetary policy makers in underdeveloped economies. In addition, it will be of particular interest to practitioners in international development institutions, especially those engaged in development finance and rural finance. Amr Khafagy works at the Countryside and Community Research Institute, University of Gloucestershire, UK. His research explores the political economy of finance and the dynamics of income and wealth distribution, the economics of cooperatives, and the political economy of the Middle East. He has worked in the banking and microfinance sectors in Egypt and India.

Banking, Money and International Finance

12 Equity Home Bias in International Finance A Place-Attachment Perspective Kavous Ardalan 13 Frontier Capital Markets and Investment Banking Principles and Practice from Nigeria Temitope W. Oshikoya and Kehinde Durosinmi-Etti 14 French Banking and Entrepreneurialism in China and Hong Kong From the 1850s to 1980s Hubert Bonin 15 Banking, Lending and Real Estate Claudio Scardovi and Alessia Bezzecchi 16 The Regulation of Financial Planning in Australia Current Practice, Issues and Empirical Analysis Angelique Nadia Sweetman McInnes 17 Financial Risk Management in Banking Evidence from Asia Pacific Shahsuzan Zakaria; Sardar M. N. Islam 18 The Economics of Financial Cooperatives Income Distribution, Political Economy and Regulation Amr Khafagy

For more information about this the series, please visit www.routledge.com/ series/BMIF

The Economics of Financial Cooperatives Income Distribution, Political Economy and Regulation Amr Khafagy

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 Amr Khafagy The right of Amr Khafagy to be identified as author of this work has been asserted by him 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 A catalog record has been requested for this book ISBN: 978-0-367-35839-6 (hbk) ISBN: 978-0-429-34219-6 (ebk) Typeset in Times New Roman by codemantra

To Wahiba and Mohamed

“Once we were present, then we were defeated, and meaning was defeated with us. But nothing will constrain the strong, nor shape the margins of freedom and justice, nor define spaces of beauty and possibilities for a common life except the weak, who insist that meaning should prevail — even after defeat. Seizing opportunities to produce meaning remains a necessity. Without it we will never get beyond defeat.” —Alaa Abd El Fattah

Contents

List of figures List of tables Acknowledgements List of acronyms 1 Introduction: why financial cooperatives matter now 1.1. Introduction 1 1.2.  Financialization, distribution, and the political economy of finance 2 1.3.  Financial cooperatives for egalitarian development 8 1.4.  Avoiding an idealisation trap 9 Bibliography 11 2 Finance, distribution, and the economic objective of financial cooperatives 2.1. Introduction 14 2.2.  Model setup 18 2.3.  Income and wealth distribution with credit rationing 22 2.4.  Income and wealth distribution with financial cooperatives 28 2.5.  Financial cooperative economic objective function 33 2.6.  Concluding remarks 35 Bibliography 36 3 Financial cooperatives and income inequality: empirical evidence 3.1. Introduction 39 3.2.  Finance and income inequality 40 3.3.  Data and method 44 3.4. Results 48 3.5.  Concluding remarks 56 Bibliography 56

ix xi xiii xv 1

14

39

viii Contents 4 Political economy theory for financial cooperative development 4.1. Introduction 59 4.2.  Political history of financial cooperatives 59 4.3.  A political economy theory of financial cooperatives 61 4.4.  Concluding remarks 69 Bibliography 70 5 Political institutions and financial cooperative development: empirical evidence 5.1. Introduction 73 5.2.  Data and method 75 5.3.  Results and discussion 79 5.4. Conclusion 86 Bibliography 86 6 The origin and rationale for financial cooperative regulation in underdeveloped economies 6.1. Introduction 88 6.2.  The historical origins of financial cooperative laws in underdeveloped economies 90 6.3.  Current models of financial cooperative laws 91 6.4.  Rationale for financial cooperative regulations 93 6.5. Conclusion 104 Bibliography 105 7 Regulation, supervision, and deposit insurance for financial cooperatives: an empirical investigation 7.1. Introduction 108 7.2.  Regulation, supervision, and deposit insurance for financial cooperatives 109 7.3.  Data and method 114 7.4.  Results and discussion 125 7.5. Conclusion 132 Bibliography 134 Discussion and conclusions

59

73

88

108

137

Appendix Bibliography 141

139

Index

175

Figures

1.1 Domestic credit and top 1% share of pre-tax income (global) 1.2 Domestic credit and top 10% share of pre-tax income (global) 1.3 Market capitalization of listed domestic companies and top 1% share of pre-tax income (global) 1.4 Market capitalization of listed domestic companies and top 10% share of pre-tax income (global) 2.1 Wealth per income class with financial sector dominated by investor-­owned bank 2.2 Wealth per income class with diversified financial sector (investor-owned bank and financial cooperative)

4 4 5 5 26 31

Tables

3.1 Empirical literature on the effect of the financial sector on income inequality 41 3.2 Data sources and variables used 46 3.3 Data description 47 3.4 Fixed-effects regression results for gross Gini coefficient against share of financial cooperatives’ credit in the credit and financial markets 49 3.5 Fixed-effects and two-stage instrumental variable regression results for change in gross Gini coefficient against change in the share of financial cooperatives’ credit in the credit and financial markets 51 3.6 Fixed-effects regression results for change in gross Gini coefficient against change in the share of financial cooperatives’ credit in the credit and financial markets (clustered by the size of financial market) 54 3.7 Fixed-effects regression results for change in the share of financial cooperative credit in the total domestic credit and financial market against change in gross Gini coefficient (reverse regression) 55 5.1 Information on the data sources and variables used 77 5.2 Data description 79 5.3 Pairwise correlation coefficients among the dependent, explanatory, and instrumental variables 80 5.4 Fixed-effects OLS regression results for financial cooperatives indicators against democracy, political rights, and civil liberties indices (underdeveloped economies 1995–2014) 81 5.5 Fixed-effects IV 2SLS regression results for financial cooperatives indicators against democracy, political rights, and civil liberties indices (underdeveloped economies 1995–2014) 82 7.1 Regulation and supervision approaches of financial cooperatives in 1995 vs 2014 110

xii Tables 7.2 Data description 114 7.3 Information on the data sources and variables used in the analysis 115 7.4 Fixed-effects regression results for financial cooperatives indicators and regulations 119 7.5 Fixed-effects regression results for financial cooperatives indicators and supervision 125 7.6 Fixed-effects regression results for financial cooperatives indicators and deposit insurance 130 A3.1 List of countries included in the analysis 142 A5.1 L  ist of countries included in the analysis and main indicators as of 2011 (in %) 143 A5.2 O  LS regression results for financial cooperatives indicators against democracy, political rights and civil liberties indices (underdeveloped economies 1995–2014) 144 A7.1 Random-effects regression results for financial cooperatives indicators and regulations 146 A7.2 R  andom-effects regression results for financial cooperatives indicators and supervision 152 A7.3 Random-effects regression results for financial cooperatives indicators and deposit insurance 158 A7.4 List of regulations reviewed 160 A7.5 L  ist of supervisory authorities and deposit insurance schemes 169

Acknowledgements

I first became interested in cooperatives after reading an article by Wael Gamal published on 1 May 2011 in the Egyptian newspaper El Shorouk entitled ‘It is time to regain our economy from aliens’. I am thankful to him and many other authors and scholars who have transformed the way I engage with politics and economics, shaped my thinking and been an inspiration for me. This book is based on my doctoral research, and my sincere gratitude goes to my supervisor Volker Nienhaus, for his help in developing my ideas and for his overall support of my work. His rich knowledge on financial sector development was essential to articulate this work. I am also grateful to the reviewers and editors of the Journal of Institutional Economics, Annals of Finance, and Annals of Public and Cooperative Economics for their constructive comments and feedback. I would also like to express my sincere gratitude to Kristina Abbotts and Christiana Mandizha at Routledge for their encouragement and support with this book. This work was made possible by the financial support granted by the German Academic Exchange Service (DAAD). I am very thankful to Raffael Beier, Mohamed El Shewy, and Daniel Alcalde Puente who have significantly helped in discussing and reviewing important parts of this work. I am also grateful to Sara Madani for her spontaneous help and effort in providing me with secondary data. I have benefited considerably from discussions with Salam Alhaj Hasan, Hari Purna Tripura, Callistus Agbaam, and I am very grateful for their suggestions and feedback which improved the quality of this work. The members of the Institute of Development Research and Development Policy (IEE) have great contribution to my personal and academic time in Bochum. I am indebted to Gabriele Bäcker, Wilhelm Löwenstein, Anja ­Zorob, and Martina Shakya for their unreserved help and guidance throughout my whole research. I am especially indebted to Jasmin Fritzsche-El Shewy, Nicole Dittrich, Henrike Roth, and Salma AlSayyad, as well as Ali Assem Lali, Loubna Abi Khalil, and Mariana Vilmondes. I truly appreciate their precious friendships and personal support as well as their good advice and collaboration. I am also grateful to the Institute’s

xiv Acknowledgements staff for their reliable support and assistance especially Irene Wedler, Tania De Giorgio, Sevilay Recber, Thanh Long Quan, and Timeela Manandhar. I am very thankful for the personal support and encouragement I received during my stay in Bochum from Chantal Kurumlu, Jens Houpt, and Flo Engel. I am also thankful to the handball team of SV Teutonia Riemke III for the lovely time and opportunity to play a sport I truly love. I am indebted to my old friends in Cairo, of whom many are unsurprisingly called Ahmed: Ahmed Diaa, Ahmed Aly, Ahmed Ghobashy, Ahmed Khaled, and Ahmed Ahsmawy as well as Tamer El-Zayat, Khaled Mouneer, Israa El Lakany, Walaa El Lakany, Aya Safwat, Mohamed Gamal, Haneen Shaheen, and Pakinam El-Shamy. I am also indebted to the one who prophesied the legacy of Professor Amaouro from Nichelino: Dagmawi Habte-­ Selassie, and to those who blindly believed in it: Elisa Rivera, Giacomo Laracca, Nardin Rezkalla, Federica Rampinini, and Arny Helgadottir. For a long time, many people knew me as just ‘Farid’s brother’, I will always be proud of this name. For that, I am extremely grateful to Adam and Asser Khafagy for giving me real reasons for pure happiness and joyful hope. I am more than grateful to my parents Wahiba Khadr and Mohamed Khafagy for the love and life support that goes beyond anything I would ask for. Amira Elwakil has substantially helped in finalising and reviewing this work. Thank you for your support, our discussions, companionship, and much more.

Acronyms

Autoregressive Distributed Lag Error-Correction Model European Association of Co-operative Banks First Difference Instrumental Variable Financial Cooperatives Fixed Effects Fixed Effects Instrumental Variable Generalized Method of Moments Gross Domestic Product Gross National Income Independent and Identically Distributed Instrumental Variable International Labour Organization International Monetary Fund Luxembourg Income Study Ordinary Least Squares Organisation for Economic Co-operation and Development Random Effects Savings and Credit Cooperatives Small and Medium Enterprises Standardized World Income Inequality Database Structural Vector Autoregressive Two-Stage Least Squares Unrestricted Error Correction Model World Council of Credit Unions World Income Inequality Database

ARDL ECM EACB FD-IV FC FE FE-IV GMM GDP GNI IID IV ILO IMF LIS OLS OECD RE SACCOs SMEs SWIID SVAR 2SLS UECM WOCCU WIID

1 Introduction Why financial cooperatives matter now

1.1. Introduction Financial cooperatives are financial intermediaries owned by the same ­people they intend to serve. Founded in the mid-nineteenth century, the focus on communal solidarity and unlimited liability of members enabled Raiffeisen’s and Schulze-Delitzsch’s cooperative models to overcome information asymmetry problems and provide credit, savings, and insurance services for low-income farmers and artisans at times when access to credit was nearly impossible. Financial cooperatives hold a significant market share in Europe and Latin America, as well as a few countries in Sub-Saharan Africa. They also have a strong presence in Asia, Australia, and the United States. According to the World Council of Credit Unions (WOCCU), there were 68,882 financial cooperatives in 109 countries in 2016, serving more than 235 million members, with total assets exceeding 1.7 trillion dollars. It is worth noting that the WOCCU’s data do not include some major financial cooperative networks in Europe, such as Germany, Finland, France, Denmark, and Italy. In many high-income economies, financial cooperatives hold significant market shares of the banking sector. The market share of financial cooperatives in the Small and Medium Enterprises (SMEs) credit market by the end of 2016 was 37% in Finland, 45% in France, 33% in Germany, 43% in the Netherlands, and 22% in Canada. In Germany, Volksbanken-­Raiffeisen banks have a market share of approximately 21% of domestic credit and domestic deposits. In the Netherlands, RaboBank holds 34% of deposits, and in France cooperative banks (Crédit Agricole, Crédit Mutuel and BPCE Group) possess more than 59% of domestic credit and 61% of domestic deposits. In Finland, OP financial group holds 35% and 38% of domestic credit and deposits, respectively, and in Canada, Desjardins holds around 42% of domestic deposits and 22% of domestic credit (EACB, 2017; WOCCU, 2017). There are many types of cooperative financial institutions with different names across the world, including financial cooperatives ­(‘cooperativa financiera’ is the Spanish term used in Latin ­A merica), cooperative banks, credit unions, and savings and credit cooperatives (‘cooperativa de ahorro

2 Introduction y crédito’ in Spanish or ‘coopérative d’épargne et de credit’ in French-­ speaking countries). This book discusses the influence of cooperative financial institutions on income distribution and the institutional factors that determine the development of cooperative financial institutions. It responds to the following questions: does the ownership structure of financial institutions affect income inequality? If so, then how can member-owned financial institutions promote a more egalitarian distribution of income? If cooperative financial institutions have a comparative advantage over other banking models when it comes to micro, SME lending, and accordingly with regard to income distribution, then why did financial cooperatives grow in some emerging economies and not in other similar economies? The book addresses two institutional factors that may influence the development and growth of financial cooperatives. In particular, it explores how political institutions can dictate the development of financial cooperatives and the motives behind the behaviour of these political institutions. In addition, it explores the regulatory and supervisory approaches that would better support the growth and resilience of the sector in underdeveloped economies. This book contributes to literature on the political economy of finance (Nienhaus, 1993; Pagano and Volpin, 2001; Rajan and Zingales, 2003; Perotti, 2014), finance and income distribution (Greenwood and Jovanovic, 1990; Banerjee and Newman, 1993; Galor and Zeira, 1993; Aghion and Bolton, 1997; Piketty, 1997), financial sector regulations (Vittas, 1992; Brunnermeier et al., 2009), as well as the economics of cooperative financial intuitions (Münkner, 1986; Ferguson and McKillop, 1997; Poyo, 2000; Cuevas and Fischer, 2006; Ferri et al., 2014).

1.2.  Financialization, distribution, and the political economy of finance The essential motive behind the interest in the economics of financial cooperatives is to explore aspects related to control over financial resources and how that influences the distribution of wealth and political power. Financial cooperatives can mobilise local financial resources and attract external funds for the benefit of local economies. In many low- and middle-income economies, deposits are channelled from small depositors, famers, pensioners, and workers to big banks outside the local communities of the original depositors (money owners). Original owners of these funds are rarely able to benefit from them, as the concentration of banks’ ownership serves the interests of a few large shareholders or narrow corporatists commonly linked to the governing political authorities. That makes financial cooperatives not only important for financial inclusion and economic growth, but their distinctive ownership structure also allows them to be practical instruments for redistributing economic resources and political bargaining power. This book aims to highlight and recognise the political and economic potentials

Introduction  3 of financial cooperative, as grassroot organisations owned by the people they are supposed to serve, and which have the ability to represent their interests and strengthen their political bargaining power. While the financial sector should respond to the needs and interests of societies, especially low- and middle-income classes, the sector seems to be functioning for the sole interest of a narrow group of rentiers. There are growing concerns about unequal income and wealth distributions, especially in the current period of financial capitalism, and the rapid expansion of the sector is a heated topic at the heart of the current political and economic debate over wealth and income distribution. The 2007–08 financial crisis intensified criticism over the financialization of the economy and the role of the financial sector in causing a global economic crisis, with ruinous economic and political consequences that are still being experienced. Banks and capital markets became disconnected from their societies, pursuing short-term profits at the expense of the longer-term macroeconomic benefits, with privatised gains for a few financiers and shareholders and socialised losses that are disproportionately distributed on the rest of the society with lower classes bearing higher burdens. A number of recent studies suggest that too much finance harms the real economy and tends to have negative impacts on economic growth (Law and Singh, 2014; Arcand et al., 2015; Cecchetti and Kharroubi, 2015). The allocation of capital by the financial system directly affects the rate of economic growth and the demand for labour, both of which have direct implications on poverty and income distribution (Demirgüç-Kunt and ­Levine, 2009). Economic theory and recent empirical literature provide contradictory results on the impact of the financial sector on income distribution. A number of theories suggest that financial sector growth would have a positive influence on economic growth and would reduce income inequality. In a perfect credit market, financial institutions channel money from agents who have surplus savings to agents who have high-return investment opportunities. The assumption of diminishing marginal returns on capital suggests that low-capital investments should be more preferable to lend as they yield higher marginal returns than high-capital investments, and consequently, low-income agents will have the opportunity to benefit from the capital channelled through financial intermediaries coming from wealthy agents (Beck et al., 2007; Ben Naceur and Zhang, 2016). But this is not how financial sectors work in the real world of imperfect credit markets. Financial institutions usually serve those who have sufficient collaterals or political connections to acquire credit, while low- and middle-income agents are more likely to be excluded from the credit market, especially in the early stages of economic development. Limited access to capital has long been recognised as a reason for persistent and increasing income inequality. Lowand middle-income agents are likely to be credit rationed from the credit market because information asymmetries and weak contract enforcement institutions discourage banks from lending to them and from exploiting

4 Introduction potential high-return investments. Figures 1.1–1.4 show how domestic credit and capital markets as a percentage of Gross Domestic Product (GDP) have remarkably increased globally during the last 25 years, as well as the parallel growth in the share of the top 1 and 10% earners as percentage of pretax national incomes. These data were obtained from the World Inequality Database and the World Bank Open database. Overcoming credit constraints would benefit the lower income classes, reduce wealth inequality, foster economic growth, and improve the efficiency of capital allocation (Banerjee and Newman, 1993; Galor and Zeira, 1993; Aghion and Bolton, 1997; Piketty, 1997). However, empirical studies on finance and inequality have focused only on the size and not the structure of the financial sector. Existing empirical literature on finance and income inequality tends to treat the financial sector as consisting of homogeneous lenders and does not account for the heterogeneity among financial institutions in terms of ownership structure. The influence of the financial sector structure and banks’ ownership on wealth and income distribution remains remarkably understudied. 190%

23%

% of GDP

21% 20%

150%

19%

130%

18% 17%

110%

16%

90% 70%

% of national income

22%

170%

15% 1980 1987 1994 Domestic credit provided by financial sector

14% 2001 2008 2015 Top 1% share of Pre-tax national income

190%

58%

170%

56% 54%

150%

52%

130%

50%

110%

48%

90% 70% 1980 1987 1994 Domestic credit provided by financial sector

46% 44% 2001 2008 2015 Top 10% share of Pre-tax national income

Figure 1.2  Domestic credit and top 10% share of pre-tax income (global).

% of national income

% of GDP

Figure 1.1  D  omestic credit and top 1% share of pre-tax income (global).

Introduction  5 23%

130%

% of GDP

21% 20%

90%

19%

70%

18%

50%

17% 16%

30% 10%

% of national income

22%

110%

15% 1980

1987

1994

2001

Market capitalization of listed domestic companies

2008

2015

14%

Top 1% share of Pre-tax national income

140%

58%

120%

56%

100%

54%

80%

52%

60%

50%

40%

48%

20%

46%

0%

1980

1987

1994

Market capitalization of listed domestic companies

2001

2008

2015

% of national income

% of GDP

Figure 1.3  Market capitalization of listed domestic companies and top 1% share of pre-tax income (global).

44%

Top 10% share of Pre-tax national income

Figure 1.4  Market capitalization of listed domestic companies and top 10% share of pre-tax income (global).

Lenin (1999: 45 [1916]), building on Hilferding’s (1981 [1910]) seminal thesis on finance capitalism, argued that a key feature of the growth of capitalism is the expansion of the banking industry and the tendency to become concentrated in a small number of institutions. Banks underwent a transformation from simple financial intermediaries into powerful monopolies controlling a large proportion of money capital in the economy, which originally belonged to capitalists and small businesses, as well as wage and salaried workers. Concentration of the financial sector and concentration of ownership over these institutions placed a large proportion of the means of production and sources of raw materials in the hands of small elite that allocates financial resources according to its narrow interests, and there is no guarantee or incentive for banks to pursue social or communal goals. Existing literature that discusses ownership structures focuses only on the comparison between private and state ownership, or between domestic and

6 Introduction foreign ownership, but the concentration of ownership and its influence on distribution is nearly neglected from current academic or political debates. Concentration of ownership is mainly discussed focusing on the efficiency and stability of banks and the financial sector. For instance, diffused ownership is thought to decrease the effective control of shareholders over the firm and transfers the control to the management because shareholders will not have enough incentives to monitor the management of the firm. Besides, conflicting interests between several controlling shareholders may affect timely and efficient decision-making. On the other hand, the concentration of ownership improves corporate control by strengthening monitoring over management because large shareholders bear most of the failure cost and they have a strong incentive to monitor the management (Berle and Means, 1933; Shleifer and Vishny, 1986). But large shareholders are also capable of expropriating minority shareholders if conflicting interests exist between both shareholding groups (Gomes and Novaes, 1999, 2005). Overall, ownership and management monitoring can be substituted by increased regulation. In comprehensively regulated industries, like the financial sector, managers may be efficiently monitored by the regulators, which in turn reduce the potential risks and benefits of controlling ownership (Demsetz and Lehen, 1985; Elyasiani and Jia, 2008). Iannotta et al. (2007) showed that concentrated ownership of banks is correlated with lower asset and insolvency risks and improved loan quality. Recently, Sawyer and Passarella (2017) developed an interesting Stock Flow Consistent model for the financial sector, based on the Monetary Circuit theory, presenting a modernised financialized economy with endogenous money creation by commercial banks. They divided the financial sector into commercial banks, which are able to create money, and other financial institutions that can provide financial services but cannot create money. They differentiated between ‘workers’ and ‘rentiers’ to highlight changes in income distribution and showed how financialization in advanced economies increased the probability that households become net borrowers while non-financial firms become net lenders. This transformation, along with access to bank credit based on class, is the main factors for widening income inequality and increasing households’ debt. However, Sawyer and Passarella’s model does not examine the influence of the banks’ concentration of ownership but the influence of money creation by commercial banks. Decisions concerning credit allocation among different groups, classes, industries and regions, and the type and features of credit in terms of amount, period, instalments, and price are subject to the ownership structure of financial institutions. Control over financial resources is crucial for economic growth and income distribution as well as political power structure; however, it is remarkably absent from current ­political and institutional economics discourses. This is why the book starts in Chapter 2 by proposing an economic model where the structure rather than the size of the financial sector explains its influence on income distribution, in order to show how different ownership

Introduction  7 structures of financial institutions can influence the distributional output of the credit market. The model proposed attempts to explain how financial cooperatives can adjust the distributional output of the financial sector. But to do that, we also need to identify an economic objective function for financial cooperatives which maximises the welfare of the members through financial intermediary services. The proposed objective function for ­financial cooperatives will define a desired deposit and lending interest rates, as well as the optimal total credit supplied for the members and the possibility to seek external borrowing, all of which aim at increasing the income of cooperative members at a rate higher than the average growth rate of the economy. Chapter 3 empirically investigates whether the structure of the financial sector influences income distribution, by exploring the relationship between the market share of financial cooperatives in the financial sector and income inequality, suggesting that the share of financial cooperatives in credit and financial markets has a negative correlation with the level of income inequality only in low- and middle-income countries. In addition, changes in the share of financial cooperatives in credit and financial markets have a negative correlation with changes in income inequality in the entire sample. Later on, the book focuses on growth determinants or institutional factors that support the development of the financial cooperative sector in low- and middle-income economies. The book addresses two main institutional factors: political institutions and regulatory frameworks. Chapter 4 proposes a political economy theory for financial cooperatives based on the origins and history of cooperatives in developing countries, alongside pressure groups theory and political economy theory of the financial sector. It argues that autocratic regimes deliberately oppose the development of a well-­functioning financial cooperative sector to maintain their political influence and prevent the formation of strong pressure groups that can threaten the current political status quo and reduce the governing elites’ economic benefits from an underdeveloped and exclusive financial sector. To empirically examine this theory; Chapter 5 analyses the influence of political institutions on the development of financial cooperatives, showing that democracy, political rights, and civil liberties promote financial cooperative development. Political economy theories argue that political institutions shape the structure of the financial system. Political and industrial elites use their influence to secure preferential access to finance. The state’s position as a regulator, mediator of financial contracts, and borrower can drive its rules towards opportunistic behaviour. It can be unwilling to enforce contracts to benefit politically connected agents and directly influence the allocation of credit by state banks or allowing concentrated ownership over banks. Neoclassical and heterodox economists have intensively discussed the political economy of finance, yet the political economy of financial cooperatives is overlooked. Financial cooperatives are naturally politicised as they were founded by politicians during a revolutionary period in Germany in

8 Introduction the mid-nineteenth century. Since then, they have been extremely susceptible to both state harassment and support. This has ranged from being over-controlled by the state in many authoritarian regimes or being actively engaged—even indirectly—in local politics in other countries, such as Italy in the present day (Gutiérrez, 2008: 13). In addition, there is a clear observation that large financial cooperative sectors tend to function and grow under non-totalitarian political systems as shown in Chapter 5.

1.3.  Financial cooperatives for egalitarian development Control by members may guide financial cooperatives to pursue communal objectives that go beyond traditional financial services. Birchall (2013), and Cuevas and Fischer (2006) explain how control by members promotes sustainability and reduces the chances of engaging in risky investments. Furthermore, members’ involvement in decision-making helps to reduce the problem of information asymmetries, as mutualism can be considered a ‘natural solution’ to the credit rationing problem, enabling cooperatives to provide credit to lower-income members with low or no collaterals, and with very low monitoring costs. Birchall (2013) argues that the advantage of ownership could exist even if cooperative members were poorly involved in management and decision-making, as, even in the absence of direct control, the opinions of members will still count for major decisions. Clearly, that applies only if managers, governments and other interest groups are not over-controlling cooperatives. Members’ control over financial resources is the distinguishing feature between the cooperative model and modern microfinance, which is highly celebrated by international development agencies and international financial institutions (like the World Bank Group and multilateral development banks). The not-for-profit orientation of modern microfinance has gradually been replaced by full-cost recovery and self-sustainable microfinance approaches. The microfinance model originated in the early 1980s in Bangladesh by Mohamed Yunus to promote economic development and poverty reduction through a micro-scale lending model is being absorbed by market-­oriented or for-profit institutions in most underdeveloped economies. The current dominant model of microfinance, whether it is provided by not-for-profit or for-profit institutions, places the control over financial resources and their allocation in the hands of small number of microfinance providers that benefit from the highly profitable sector. Financial cooperatives are different in many aspects from standard microfinance institutions, both for-profit and not-for-profit organisations. Although group lending may seemingly share some similarities with cooperative concepts, in terms of joint liability, the distinctions are much bigger, especially when it comes to autonomy, mobilisation and control over resources, legal and organisational identity, and decision-making. Early financial cooperatives founded in Germany were more able to provide larger loans relative to the borrowers’ income, with longer-term maturity at lower interest rates compared to

Introduction  9 modern standard microfinance institutions. The main source of funds for cooperatives are local savings, while microfinance institutions in underdeveloped economies rely heavily on donations, foreign funds, external borrowing, or on retained earnings, which implies high interest rates. High interest rates, short-term maturities, and tight repayment schedules are destructive instruments for low- and middle-income borrowers which may lead to serious debt traps, or in best scenarios will not support any sort of capital accumulation. Without improving the ability of agents to earn, save, and accumulate wealth, there are no real economic gains from financial markets to the lower- and middle-income populations. Cuevas and Fischer (2006); Fonteyne (2007); Labie and Périlleux (2008); Ferri (2012); and Birchall (2013) have widely discussed the comparative advantages of the ownership structure of cooperatives. Financial cooperatives can have a comparative advantage over other types of financial institutions, since they are formed locally, focusing on narrow geographic areas, and there is usually a degree of homogeneity and previous social relations between the members (Guinnane, 2001: 370), which enable cooperatives to serve agents who were previously credit rationed from state and investor-owned banks. Financial cooperatives are important vehicles for the growth of SMEs compared to commercial banks, and are better able to reach and serve low- and middle-income agents compared to other microfinance institutions. Empirical literature suggests that financial cooperatives provide credit to small businesses at lower costs compared to large domestic commercial banks and foreign-owned banks (Angelini et al., 1998; Hasan et al., 2017). Similarly, many cross-country studies have shown that cooperatives are more likely to charge lower interest rates compared to banks and not-for-profit (like NGOs) or for-profit microfinance institutions. All the literature reviewed for this book has indicated that cooperatives tend to have lower portfolio yield and even sometimes lower operational costs (for recent studies see Cull et al. 2018 and Meyer, 2019). More interestingly, the financial crisis (2007–08) and the sovereign debt crisis (2010–13) did not affect the lending growth of cooperative banks, as they did with commercial and savings banks (Meriläinen, 2016). Financial cooperatives also proved to be more stable compared to other investor-owned banks (Cuevas and Fischer, 2006: 55; Hesse and Cihak, 2007; Ayadi et al., 2010: 116; Birchall, 2013: 24; ­ hiaramonte et al. (2015) found that high market share Hasan et al., 2017). C of cooperative banks in the OECD have positive influence on the stability of the banking system during the financial crises. Butzbach and von Mettenheim (2014: 33–41) provide a comprehensive overview on empirical literature that discusses the comparative performance of financial cooperatives.

1.4.  Avoiding an idealisation trap This book does not intend to idealise the cooperative banking model. The movement and the sector have witnessed several failures and challenges, similar to other financial institutions, and also because of the distinctive

10 Introduction ownership structure of cooperatives, that can stimulate corporate governance issues and attract political interferences. For instance, the Swiss banking regulator has recently reported that Raiffeisen Schweiz bank has suffered from serious corporate governance drawbacks that included conflict of interests between the supervisory board and the management leading to significant violations of supervisory laws and practices. The British Co-operative Group has lost the ownership of the Co-operative Bank in 2013 to US-based hedge funds that owned its debts, after the Prudential Regulation Authority reported that the bank was not sufficiently capitalised and needs around GBP 1.5 billion. The United Kingdom still has a wide network of building societies and customer-owned banks, like Nationwide Bank. The Cyprus Co-operative Bank has also lost its cooperative status during the country’s financial crisis after being bailed out by the government in 2013 upon suffering from enormously high non-performing loans. The majority ownership went to the State, whereas the Hellenic Bank has purchased the performing portfolio of the cooperative bank. Between the 1980s and 1990s, around one-third of the Savings and Loan Associations in the United States were closed or resolved, in what is known now as the thrift or savings and loan crisis (Curry and Shibut, 2000). Failure of financial cooperatives does not always have to be as massive as the thrift or the Cyprus cooperative bank crises. Several other financial cooperatives have collapsed or struggled with inadequate performance like other financial institutions. The roots of the failure of financial cooperatives can be macroeconomic shocks that affect the entire financial sector, or can be banking failures that are not uniquely associated with cooperatives alone. This may include mismanagements, corporate governance issues, state control, or corrupt and fraudulent practices by the banks’ management. But the cooperative structure imposes additional stress on the governance of financial cooperatives especially that no individual member has a majority control because of the one member one vote rule that may encourage free riding or disengagement of members. Alexopoulos and Goglio (2011) have highlighted the current problems and challenges that may face the sector, pointing out on the challenges to diversify their loan portfolios, agency problems, political aspirations of the board or management members, and governance difficulties. That is why regulations and supervisions are crucial for the safety and growth of the sector, especially when the sector expands and becomes more complex. Adequate regulatory framework is crucial for the sustainability and effectiveness of financial cooperatives, in order to keep providing the financial services needed by the members, and the community, and also to support the expansion of the sector. Chapters 6 and 7 are devoted to the regulations and supervisions of financial cooperatives in low- and middle-income economies. Chapter 6 gives an overview of the historical background and rational behind financial cooperative regulations, focusing mainly on protection from state interference, overcoming agency problems, setting adequate capital requirements, enabling institutional integration between cooperatives,

Introduction  11 and protection of members’ deposits. While Chapter 7 shows how indicators of financial cooperative development are positively correlated with the existence of specialised regulation, supervision under non-bank financial supervisory authorities, and the presence of deposit insurance schemes, whereas the regulations of banking and general cooperative society are negatively correlated with financial cooperative indicators. The econometric methods used in Chapters 3, 5, and 7 are further discussed in the appendix.

Bibliography Aghion, P. and Bolton, P. (1997), ‘A theory of trickle-down growth and development’, The Review of Economic Studies, 64(2), 151–172. Alexopoulos, Y. and Goglio, S. (2011), ‘Financial cooperatives: problems and challenges in the post-crisis era’, Journal of Rural Cooperation, 39(1), 35–48. Angelini, P., DI Salvo, R. and Ferri, G. (1998), ‘Availability and cost of credit for small businesses: customer relationships and credit cooperatives’, Journal of Banking and Finance, 22(6), 925–954. Arcand, J. L., Berkes, E. and Panizza, U. (2015), ‘Too much finance?’, Journal of Economic Growth, 20(2), 105–148. Ayadi, R., Llewellyn, D., Schmidt, R., Arbak, E. and Pieter De Groen, W. (2010), ‘Investigating Diversity in the Banking Sector in Europe: Key Developments, Performance and Role of Cooperative Banks’, Brussels: Centre for European Policy Studies. Banerjee, A. V. and Newman, A. F. (1993), ‘Occupational choice and the process of development’, Journal of Political Economy, 101(2), 274–298. Beck, T., Demirgüç-Kunt, A. and Levine, R. (2007), ‘Finance, inequality and the poor’, Journal of Economic Growth, 12(1), 27–49. Berle, A. A. and Means, G. C. (1933), ‘The Modern Corporation and Private Property’, New York: Macmillan. Ben Naceur, S. and Zhang, R. (2016), ‘Financial development, inequality and poverty: some international evidence’, Working Paper no. 16/32. Washington, DC: International Monetary Fund. Birchall, J. (2013), ‘Resilience in a Downturn: The Power of Financial Cooperatives’, Geneva: International Labour Organisation. Brunnermeier, M., Crockett, A., Goodhart, C., Hellwig, M., Persaud, A. and Shin, H. (2009), ‘The Fundamental Principles of Financial Regulation’, Geneva Reports on the World Economy, No. 11. Butzbach, O. and von Mettenheim, K. (2014), ‘The Comparative Performance of Alternative Banks before the 2007–08 Crisis’, in Butzbach, O. and von Mettenheim, K. (eds.), ‘Alternative Banking and Financial Crisis’, New York: Pickering and Chatto, pp. 29–42. Cecchetti, S. G. and Kharroubi, E. (2015), ‘Why does Financial Sector Growth Crowd Out Real Economic Growth?’, London: Centre for Economic Policy Research. Chiaramonte, L., Poli, F. and Oriani, M. E. (2015), ‘Are cooperative banks a lever for promoting bank stability? Evidence from the recent financial crisis in OECD countries’, European Financial Management, 21(3), 491–523. Cuevas, C. E. and Fischer, K. P. (2006), ‘Cooperative Financial Institutions: Issues in Governance, Regulation, and Supervision’, Washington, DC: World Bank.

12 Introduction Cull, R., Demirgüç-Kunt, A. and Morduch, J. (2018), ‘The microfinance business model: enduring subsidy and modest profit’, The World Bank Economic Review, 32(2), 221–244. Curry, T. and Shibut, L. (2000), ‘The cost of the savings and loan crisis: truth and consequences’, FDIC Banking Review, 13, 26. Demirgüç-Kunt, A. and Levine, R. (2009), ‘Finance and inequality: theory and evidence’, Annual Review of Financial Economics, 1(1), 287–318. Demsetz, H. and Lehen, K. (1985), ‘The structure of corporate ownership: causes and consequences’, Journal of Political Economy, 93, 1155–1177. Elyasiani, E. and Jia, J. J. (2008), ‘Institutional ownership stability and BHC performance’, Journal of Banking & Finance, 32(9), 1767–1781. European Association of Co-operative Banks. (2017), ‘Key Statistics – Financial indicators 2016’. www.eacb.coop/en/cooperative-banks/key-figures.html Ferguson, C. and McKillop, D. (1997), ‘The Strategic Development of Credit Unions’, Chichester: John Wiley & Son Ltd. Ferri, G. (2012), ‘Credit Cooperatives: Challenges and opportunities in the new global scenario’, Working Papers No. 1231. Trento: European Research Institute on Cooperative and Social Enterprises (Euricse). Ferri, G., Kalmi, P. and Kerola, E. (2014), ‘Does bank ownership affect lending behavior? Evidence from the Euro area’, Journal of Banking and Finance, 48, 194–209. Fonteyne, W. (2007), ‘Cooperative Banks in Europe—Policy Issues (No. 2007–2159)’, Washington, DC: International Monetary Fund. Galor, O. and Zeira, J. (1993), ‘Income distribution and macroeconomics’, The Review of Economic Studies, 60(1), 35–52. Gomes, A. and Novaes, W. (1999), ‘Multiple large shareholders in corporate governance’, Rodney L. White Center for Financial Research. The Wharton School. University of Pennyslvania. Gomes, A. and Novaes, W. (2005), ‘Sharing of control versus monitoring’, PIER Working paper 1, 29. Greenwood, J. and Jovanovic, B. (1990), ‘Financial development, growth, and the distribution of income’, Journal of Political Economy, 98(5), Part 1, 1076–1107. Guinnane, T. W. (2001), ‘Cooperatives as information machines: German rural credit cooperatives, 1883–1914’, The Journal of Economic History, 61(2), 366–389. Gutiérrez, E. (2008), ‘The reform of Italian cooperative banks: discussion of proposals’, Working Paper no. 08/74. Washington, DC: International Monetary Fund. Hasan, I., Jackowicz, K., Kowalewski, O. and Kozłowski, Ł. (2017), ‘Do local banking market structures matter for SME financing and performance? New evidence from an emerging economy’, Journal of Banking and Finance, 79, 142–158. Hesse, H. and Cihak, M. (2007), ‘Cooperative banks and financial stability’, International Monetary Fund Working Paper no. 07/2. Hilferding, R. (1981 [1910]), ‘Finance Capital’, London: Routledge Kegan Paul. Iannotta, G., Nocera, G. and Sironi, A. (2007), ‘Ownership structure, risk and performance in the European banking industry’, Journal of Banking & Finance, 31(7), 2127–2149. Labie, M. and Périlleux, A. (2008), ‘Corporate governance in microfinance: credit unions’, Working Papers No. 08/003, Brussels: Centre Emile Bernheim (CEB). Law, S. H. and Singh, N. (2014), ‘Does too much finance harm economic growth?’ Journal of Banking and Finance, 41, 36–44.

Introduction  13 Lenin, V. I. (1999 [1916]), ‘Imperialism: The Highest Stage of Capitalism’, Chippendale: Resistance Books. Meriläinen, J. M. (2016), ‘Lending growth during the financial crisis and the sovereign debt crisis: the role of bank ownership type’, Journal of International Financial Markets, Institutions and Money, 41, 168–182. Meyer, J. (2019), ‘Outreach and performance of microfinance institutions: the ­i mportance of portfolio yield’, Applied Economics, 51(27), 2945–2962. Münkner, H. H. (1986), ‘Participative law-making: a new approach to drafting ­cooperative law in developing countries’, Verfassung und Recht in Übersee/Law and Politics in Africa, Asia and Latin America,19(2), 123–137. Nienhaus, V. (1993), ‘The political economy of development finance’, Managerial Finance, 19(7), 8–20. Pagano, M. and Volpin, P. (2001), ‘The political economy of finance’, Oxford Review of Economic Policy, 17(4), 502–519. Perotti, E. (2014), ‘The political economy of finance’, Capitalism and Society, 9(1), Article 1. Piketty, T. (1997), ‘The dynamics of the wealth distribution and the interest rate with credit rationing’, The Review of Economic Studies, 64(2), 173–189. Poyo, J. (2000), ‘Regulation and supervision of credit unions’, in Westley, G. and Branch, B. (eds.), ‘Safe Money: Building Effective Credit Unions in Latin America’, Washington, DC: Inter-American Development Bank, pp. 137–160. Rajan, R. G. and Zingales, L. (2003), ‘The great reversals: the politics of financial development in the twentieth century’, Journal of Financial Economics, 69(1), 5–50. Sawyer, M. and Veronese Passarella, M. (2017), ‘The monetary circuit in the age of financialisation: a stock‐flow consistent model with a twofold banking sector’, Metroeconomica, 68(2), 321–353. Shleifer, A. and Vishny, R. W. (1986), ‘Large shareholders and corporate control’, Journal of Political Economy, 94(3), Part 1, 461–488. Vittas, D., ed. (1992), ‘Financial Regulation: Changing the Rules of the Game’, Washington, DC: World Bank Economic Development Institute. World Council of Credit Unions. (2017), Statistical Reports. www.woccu.org/ our_network/statreport

2 Finance, distribution, and the economic objective of financial cooperatives1

2.1. Introduction Economic theory and empirical literature provide contradictory predictions for the impact of the financial sector on income inequality. A number of theories suggest that a developed financial sector should boost economic growth and reduce inequality. That is because, theoretically, financial intermediary institutions channel money from those who have surplus savings to those who have high-yield investment opportunities. In that sense, according to the theory of diminishing marginal returns on capital, low-capital investments should be more preferable to lend as they yield higher marginal returns than high-capital investments, thus low-income people will have the opportunity to benefit from the money channelled through financial intermediaries from wealthy people (Beck et al., 2007; Ben Naceur and Zhang, 2016). Banerjee and Duflo (2005: 479–484) provide intensive overview on theoretical and empirical evidence for high marginal returns on low-capital investments. The allocation of capital through the financial sector can also affect the rate of economic growth and the demand for labour, both of which have direct implications on poverty and income distribution (DemirgüçKunt and Levine, 2009). However, credit market imperfections distort this process, making financial development only beneficial for those who have sufficient collateral and/or political connections to access bank credit. Constraints on access to capital are a main reason for persistent and increasing income inequality. Low-income populations are usually excluded from the development of the financial sector because information asymmetries discourage banks from lending to them. Overcoming credit constraints will benefit the poor, reduce wealth inequality, enhance growth, and improve the efficiency of capital allocation, through allowing low-income populations to exploit productive investment opportunities (Banerjee and Newman, 1993; Galor and Zeira, 1993; Aghion and Bolton, 1997; Piketty, 1997). Greenwood and Jovanovic (1990) propose a non-linear relationship (inverted U-shaped curve) between financial development and income inequality. In the early stage of economic development, trade is unorganised and financial services are nearly non-existent. In the intermediate stage of

Finance, distribution, and economic objective  15 development, income levels and saving rates increase, and a functioning financial sector begins to be formed, but income inequality widens as the rich start to have preferential access to financial services. Finally, in the maturity stage of economic development, the financial sector overcomes its imperfections and becomes more inclusive, allowing a stable distribution of income and higher growth rates. Galor and Zair (1993: 36) argue that in the presence of credit constraints and indivisibility of human capital investments, initial wealth inequality will have short- and long-run consequences on wealth distribution because only rich agents will be able to afford investing in human capital. Banerjee and Newman (1993: 276) argue that credit-­ constrained agents will choose their occupations between working for wage or being self-employed, since poor agents are not able to borrow because the credit market is imperfect and consequently they cannot invest in highyield projects. Wage contracts will replace credit contracts where wealthier agents hire and monitor poorer agents. Wage rate and occupational opportunities will depend on the initial wealth distribution, and long-run wealth distribution will be determined by occupational choice and wage rate, as well as the savings behaviour of poorer agents. Similarly, Piketty (1997: 173) shows that, in a perfect credit market, the marginal product of capital would only influence the equilibrium interest rate that will be identical across all borrowers irrespective of their initial level of wealth. On the other hand, in an imperfect credit market, unequal initial wealth distribution may result in self-sustaining high interest rates that slow down the rate of capital accumulation for credit-constrained individuals. Aghion and Bolton (1997: 152) argue that even with credit market imperfections, wealth may trickle down if there is high rate of capital accumulation, but that will not be sufficient enough to achieve efficient distribution. They argue that permanent redistribution policies would be needed because one-shot redistribution will not have long-run effects on distribution. In return, redistribution enhances the efficiency of the economy as there will be equal investment opportunities and it will speed up the trickle-down process. This chapter presents a model that argues that the structure rather than the size of the financial sector explains its influence on income distribution. Because of information asymmetries, a financial sector dominated solely by profit-maximizing financial intermediaries will widen income and wealth inequality, as it gives preferential access to credit for high-income agents, while a diversified financial sector that includes alternative models of banking, such as financial cooperatives, will be more inclusive and will reduce the income inequality gap. It further proposes an objective function for financial cooperatives to define a desired deposit and lending interest rates, as well as optimal total credit supplied for the members and the possibility to seek external borrowing, all of which aim at increasing the income of the cooperative members at a rate higher than the average growth rate of the economy.

16  Finance, distribution, and economic objective The model proposed here attempts to explain how financial cooperatives may adjust the distributional output of the financial sector. In imperfect credit markets with asymmetric information and a costly screening process, the credit decision depends mainly on the value of the borrower’s collaterals relative to the loan size (leverage ratio) and the lender-borrower relationship, acquired from persisting social interaction or previous credit transaction. The lender-borrower relationship can be thought of as the borrower’s credit social capital. In a credit market dominated solely by an investor-owned bank, where low- and middle-income agents have no credit social capital, only high-income agents will be able to borrow and hire additional workers with a wage rate lower than the marginal product of labour. Meanwhile, those who have low wealth and low credit social capital will be credit rationed and will be unable to adopt new production techniques or invest in their human capital to improve their productivity, as they cannot borrow at an interest rate below the marginal return on their capital. The income of low- and middle-income agents from self-employment or from wages will be constrained to their initial productivity, and wealth inequality will continue to increase depending on the initial wealth distribution, convexity of savings rate and heterogeneity of production techniques. High-income agents will finance their new investments from the deposits of low- and middle-­income agents after utilising all of their deposits. However, if middle-income agents can pool their deposits together in a new financial institution that they own themselves based on some homogeneity among them, then they can increase their individual credit social capital. Assuming that the cooperative is less exposed to asymmetric information and moral hazards, it will lend middle-­ income agents the required capital to upgrade their production function at an interest rate lower than the marginal product of capital. But only middle-­ income agents are able to mobilise enough deposits to form a financial cooperative, while low-income agents will remain credit rationed. As a result, in a credit market where both types of institutions operate, the income and wealth gap between middle- and high-income agents will narrow, but the same level of inequality may continue to persist between middle- and low-income agents. Finally, the model develops a simple economic objective function for financial cooperatives, where the aim of a cooperative is to increase the income of its members at a rate higher than the average growth rate of the economy, so that the member of the cooperative can improve (or maintain) her wealth ranking in the class structure. The key assumptions in the model below are based on the assumption of credit market failure and traditional assumptions for financial cooperatives, which are particularly relevant to underdeveloped and emerging financial cooperative sectors. These include, first, being small and bound to geographical or sectorial concentration (closed defined membership) to allow members’ direct participation in decision-making, peer monitoring and social sanctions. Second, local management that is independent from the government or the centralised network (federation). Third, the ability to

Finance, distribution, and economic objective  17 mobilise sufficient deposits from the members as the main source of funds available for credit, with no access to capital markets. Finally, the ability to have institutional integration between primary financial cooperatives. However, while most financial cooperatives share the same basic principles, different models of cooperative banking exist, as a result of historical and cultural factors, how cooperatives were introduced and the way they evolved, as well as the structure of the financial sector and of the economy, political institutions, the level of development and the regulatory framework, as discussed in Chapters 4 and 6. For instance, most of the European cooperatives were founded as grassroots, independent, self-help associations that emerged spontaneously, while the development of cooperatives in developing countries is strongly dependent on the colonial governments that implanted cooperatives as instruments to implement their own economic policies. Cooperatives remain government instruments in some less developed economies, where the objective of cooperatives is not to create alternative contractual arrangements that govern the relationship between the members and the market, and among the members themselves, but to follow the policies of the state. Moreover, although financial exclusion is a significant obstacle for growth and distribution in less developed and emerging economies, it is no longer a major problem in most industrialised economies. Investor-owned banks in mature financial systems are able to finance small and medium businesses as asymmetric information and moral hazard problems are better mitigated by strong contract enforcement and verifiable information about prospective borrowers, all of which limits the comparative advantage of financial cooperatives. Furthermore, matured financial cooperative sectors have access to the capital market, while surpluses in less developed financial cooperative sectors are the only source to obtain additional capital, since their shares are usually untradeable. Deposit insurance schemes may also have weakened members’ incentives to monitor cooperatives’ operations, but deposit insurance schemes are not widely available or effective yet in less developed financial cooperative sectors. Likewise, some large cooperative movements in Europe have evolved into national networks with centralised business functions to gain from economies of scale, which weakened members’ participation in decision-making. While networks and federation in less developed financial cooperative sectors are formed to secure liquidity positions, if possible, through short- or long-term borrowings, acting like lenders of last resort, and in some countries closely supervise and monitor the performance of their primary cooperatives, but there is rarely centralised management over the whole sector. There are four main implications for modelling the desired and actual lending and deposit fees of cooperatives based on the model’s proposed economic objective, which give indications of the optimal decisions that a cooperative can make to increase the welfare of its members. First, it provides a plausible explanation on why financial cooperatives may not be able to improve the relative welfare of their members and reduce income inequality.

18  Finance, distribution, and economic objective Second, and more importantly, it recommends optimal lending and deposit fees that can help the cooperative decision-making and is more applicable in small cooperatives and cooperatives with homogeneous borrowers. Third, it highlights the desired total credit supply for the members. Finally, it assesses the need and potential of the cooperative to seek external borrowing. Section 2.2 presents the model setup, the assumed production function and determinants of income. Section 2.3 describes the dynamics of income distribution in a closed economy with a financial sector that consists of only profit-maximizing investor-owned banks, and the resultant transfer of capital from low-middle income agents to high-income agents. Section 2.4 examines the dynamics of income distribution when the financial sector consists of a profit-maximizing investor-owned bank and a member-owned financial cooperative. Section 2.5 proposes an economic objective function for financial cooperative institutions and the concluding remarks are in Section 2.6.

2.2.  Model setup The model presented here follows Banerjee and Newman (1993), Piketty (1997), and Aghion and Bolton (1997) to a large extent. Assuming a closed economy that has infinite discrete time horizon t = 0,1,2,… and a constant continuum of risk-neutral infinitely-lived population N = (1,2,… n ), and at each period t, every individual neN has an initial wealth wt and one indivisible labour unit, and gains income yt by supplying labour and/or capital. The economy consists of two sectors: a one-good manufacturing sector and the financial sector. The financial sector consists of two institutions: one is an investor-owned bank, which will be referred to as the Bank, and the other type is a financial cooperative, hereafter referred to as the Cooperative. The current distribution of wealth is represented by a distribution function Gt ( w ), and aggregate wealth of the whole economy is W . The economy is divided into three economic classes, and the aggregate wealth of each class can be wm

wl

represented by Wl , Wm and Wh . Where Wl =

∫ w dG (w), W = ∫ w dG (w) t

0

w

and Wh =

m

t

wl

∫ w dG (w). G (w ) represents the fraction of low-income populat

wm

l

tion with current wealth equal or below wl , G ( wm ) represents the fraction of middle-income population with current wealth above wl and equal or below wm, and G ( wh ) represents the fraction of high-income population with current wealth above wm. Similar to Banerjee and Newman (1993), agents are divided into five groups based on their occupations: inactive, skilled, unskilled, self-employed, and capitalist, so that agents of low-income population G ( wl ) can be inactive, unskilled or self-employed, and G ( wm ) can be inactive, skilled, or self-employed, while G ( wh ) can only be inactive or

Finance, distribution, and economic objective  19 capitalist. To avoid unnecessary complexity, assume a constant proportion for each of the three classes in total population, so that we have only occupational mobility within the same wealth class but no mobility across the classes. Accumulated wealth of each agent w at any time t is equivalent to her total deposits at the banking sector d and her tradeable assets pT , so w = d + pT . The quantity of tradeable assets for each agent varies among agents based on their initial wealth, and their values change with time based on changes in their market price. At the end of each period, income yt is divided between consumption ct and savings st, in the form of additional deposits or additional tradeable assets, which are added to the current wealth to constitute the individual’s initial wealth next period, so that wt +1 = wt + st and st = dt + ptT . I ­assume a convex savings function following Kaldor (1955: 95), Stiglitz (1969: 389) and Bourguignon (1981: 1469–1470), implying that high-income agents have higher marginal propensity to save than low- and middle-income agents do, and that the propensity to save increases with income, so st = s i yt , with s i as the propensity to save, which differs among economic classes. 2.2.1.  Production function The production function follows the approach of Acemoglu (2003) and Jones (2005) to incorporate both capital and labour-augmenting technological progresses. The aggregate production function is a concave, constantreturns-to-scale function. F ( A, K , L ) = AK K α AL L1−α . K and L are aggregate capital and aggregate labour, and AK and AL are the economy’s general capital-augmenting and labour-augmenting technological progresses. The parameter A can be thought of as a collection of production techniques available in the economy, and individual agents can choose from a set of A aki , ali , where i = {1,2,…, n}, a1k < ak2 < akn , and al1 < al2 < aln. In the short-run, high-income agents are already using the optimum production techniques available in the economy akn , aln , while low- and middle-income entrepreneurs are using less advanced technologies than the economy’s optimum level of technology. Finally, a is a parameter that lies between 0 and 1 representing the share of capital in the output, and capital does not depreciate. The output generated from each agent’s investment has the form of f ( ak k, al l ) = ak k α al l 1−α , where l is the number of workers, equals 1 if the agent is self-employed with K no workers, and k = is the amount of capital per worker. The producl tion function at both macro and individual level has the characteristics f ( k ) : f ( 0 ) = 0, f ′ ( k ) > 0, f ′′ ( k ) < 0, f ′ ( 0 ) = ∞ and f ′ ( ∞ ) = 0, and f ( k ) can shift because of changes in the adopted production techniques.

(

)

(

)

20  Finance, distribution, and economic objective In addition, agents are assumed to have heterogeneous skills, so the production function at the individual level is allowed to be stochastic, with f ( k ) taking different values depending on the probability of success of the investment p ( e ), which is a function of the level of effort exerted by each individual. The level of effort is defined in more detail below, but generally if the borrower exerted the required effort then e = 1 and e = 0 otherwise. However, within each income class the weight of idiosyncratic effects will be offset at the aggregate level and will not critically disturb the mean income of each income class and of the total economy. We can expect u = y − u ′ ( e ) to be the individual’s indirect utility from investment, where u ′ ( e ) is the disutility from exerting the effort e. 2.2.2.  Income determinants Agents can either borrow b from banks at a lending rate equal to rb in order to invest and gain (at least) the return on the capital invested pf ( k ), where k in this case is total capital invested equal to b + d; or not borrow and invest only their deposits, in which case k = d. In addition, the agent can either be self-employed or hire other workers to carry on the labour effort and pay v wages for l workers. The investments of the self-employed are similar to the investments of high-income capitalists and differ only in their size. Generally, the individual income if she borrowed the amount b, with interest rate rb and hired a number of l workers will be y = pf (( d + b )) – (1 + rb ) b − lv, while if she failed to borrow the required capital she will only gain y = pf ( d ). If the agent chose to invest, she will not gain returns on her deposits in the form of interest rates rd but rather as part of the overall investment return pf ( k ). If the agent chose not to invest and to be inactive, she will only gain returns on her deposits that will be equal to the current deposit rate rd , and her total return will be equivalent to deposit rate y = rd d . Finally, the agent can work for another agent and gain returns on her deposits in addition to wage v, such that vt is the wage paid for unskilled agents, and vt is the wage paid for skilled agents, while lv is the total wage paid for l workers. Finally, the minimum accepted wage (v for unskilled and v for skilled worker) must be higher than the expected return from low-middle income self-employment pf ( k ) less safe return from deposits rd d . Therefore, capitalists can choose a wage rate between the return of self-employed low- and middle-investment and the marginal product of labour, and wages will be bounded by pf ( k ) − rd d < v < ak al (1 − α ) k α l −α .

(2.1)

Additional capital does not have to yield diminishing marginal returns and agents can have increasing or constant total growth in output by hiring additional labour or adopting advanced production technology. Accordingly, since high-income agents are using the optimal production technique in the

Finance, distribution, and economic objective  21 short run, then additional capital can yield increasing or constant growth rates as long as additional labour units balance the marginal returns on capital. Taking the defined wage rate in Equation (2.1), then high-income investors can always hire additional workers if the expected return of a self-employed investment (low or middle) less deposit rates is below the marginal product of labour. Similarly, new capital for low- or middle-income agents can help the agent to hire one or more workers and again additional units of labour will balance the additional capital. Moreover, the ability to borrow increases low- and middle-income agents’ opportunities to enhance their production techniques, by advancing the productivity of their physical or human capital (e.g. modern machinery or individual skills), so they will not be limited to the marginal rate of return of their existing production capacity (as if ak or al were constant). Therefore, I assume that ∀ p > 0 : f ( d + b ) > f ( d ) and f ′ ( d + b ) > f ′ ( d ). Meaning that for low- and middle-income agents, if the probability of success of the investment is above zero, the output of an investment funded by both the agent’s deposit and external borrowing will yield higher marginal return than if the investment is funded solely by the agent’s deposits, because the loan will shift the production function curve. The income of each occupation is  y u = rd dt     e yt  y = pf ( k, l ) − (1 + rb ) b − lv  yw = vt + rd dt .  



(2.2)

where y u , ye, and yw represent the income for inactive agents, entrepreneurs (self-employed) and skilled/unskilled workers, regardless of their income level, the growth in the income of each group will be  dr  y' u = d   dt   'e dv y′  y = pf ′ ( k, l ) − rb −   (2.3) dt   dv drd .  y' w = +  dt dt  Lastly, yl ,  ym , and yh are the incomes of low-, middle-, and high-income agents and the distribution of income is represented by a Gini formula that follows Sen (1973: 31), Deaton (1997: 139), and Jenkins (1991: 16). G = 1+

1 2 − N N2y

N

∑h y . j i

i =1

where N represents the total number of agents, y is the mean income of the economy, and h j is the income rank of the income-group j, such that

22  Finance, distribution, and economic objective j = {1,2,3} and h1 = yh, h2 = ym and h3 = yl . Therefore, disproportionate growth of income among the classes due to credit market dynamics can be reflected in the Gini formula.

2.3.  Income and wealth distribution with credit rationing In a first-best credit condition, the ability to obtain capital from a p ­ erfect credit market—where there is no moral hazard and asymmetric ­information— will be entirely based on the feasibility of the investment and not on the value of collaterals, so that no agent will be credit rationed based on her initial wealth (Piketty, 1997: 176). If banks have full information about their clients and there is perfect contract enforcement, then the allocation of productive capital between agents will be independent from the current distribution of wealth, as banks will be willing to lend all agents, regardless of their initial wealth, and without collaterals. Moreover, in a perfect credit market, where there is full competition between lenders, no transaction costs and no borrowing constraints, the lending rate will be equivalent to the marginal rate of return on capital, and agents can borrow any desired amount that enable them to choose the optimum investment using the best production techniques available in the economy. All agents will thus be subject to the same production function of the economy, and because of the diminishing marginal returns assumption, poor agents will experience higher growth rates than richer agents. Therefore, we can expect that ‘rich agents will lend capital to poor agents so as to equalise the marginal product of capital throughout the economy, overall production units’ (Piketty, 1997: 176). However, in imperfect credit markets, banks cannot directly observe the borrower’s behaviour, and they are unable to determine whether the borrower will supply the required high effort e = 1 to guarantee the success of the investment or not e = 0 . The amount of capital that an agent can borrow has to be relative to the value of collaterals she can provide, and the lender will try to predict the borrower’s repayment ability subject to the success and failure of the investment f ( k ) after borrowing k − b by predicting the level of effort that the borrower will supply. Similar to Stiglitz and Weiss (1981: 395–396), after adding the effort exerted by the borrower, the lender expects a return of

{

}

yb = min pf ( k ) + ptT+1; b (1 + rb ) . While the borrower expects a return subject to

{

}

yi = max pf ( k ) − b (1 + rb ) − lv − u ′ ( e ) ; − ptT+1 . Therefore, the lender predicts that a borrower will decide to supply the high effort  e only if the return of the investment less the effort exerted, wages

Finance, distribution, and economic objective  23 and the loan repayment exceeds the loss of collaterals. Therefore, I define e to be  1if f ( k ) + pT − lv − u ′ ( e ) > b (1 + r ) b  t +1 . e= T  0 if f ( k ) + pt +1 − lv − u ′ ( e ) ≤ b (1 + rb )

(2.4)

We can predict the expected level of effort exercised by the borrower as a function of the expected return from the investment in case of full success p = 1, the value of collaterals, the value of repayments to the lender and disutility of exercising the high effort. The conditions of Equation (2.4) shows that the borrower is more likely to exercise high effort if the expected return is sufficiently high to compensate the disutility of work, or if she has highvalue assets held as collaterals that she may lose if she failed to repay the loan. Equation (2.4) also shows how the borrower will exercise less effort if the value of the loan repayment is high, as she will gain less from the returns of her effort, and since the repayment increases as the interest rate increases, the lender will expect high interest rates to have negative effects on repayment. The main instrument to constraint agents from borrowing will be the interest rate, and so we need to calculate what determines the interest rate when the lender cannot predict the borrower’s behaviour ex-ante. Interest rates will vary fundamentally between different loan contracts because of the default probability of the borrower, and the monitoring costs to mitigate such risk, assuming each loan bears a proportionate share of the cost of fund rd and the required profit pˆ equivalent to the loan size. In addition, z l reflects the inverse relation between the size of the loan b relative to the b average loan size of the bank’s portfolio z and administration costs l, because, as Banerjee and Duflo (2010: 63–64) point out, there are fixed costs associated with every contract irrespective of its size. So small loans bear higher proportionate costs than bigger ones. However, each loan has unique monitoring costs m. So the interest rate of each loan contract is determined to cover the cost of fund, monitoring costs, administration or operational costs, and the desired net profit of the lender, as follows: r = rd + l

z + m + +pˆ . b

(2.5)

z , b the main variable that will vary among the agents is the monitoring costs. Monitoring costs will be determined ex-ante based on the expected endvalue of the borrower’s tradeable assets ptT+1 that can be held as collaterals, and lender-borrower relationship, that can be thought of as the credit social capital of the borrower acquired either from previous lending contracts with Besides loan size relative to the average loan size of the bank’s portfolio

24  Finance, distribution, and economic objective the lender or other social ties between the lender and the borrower. The monitoring costs will be m=g

b − h. ptT+1 (1 − y )

(2.6)

Recalling that b is the loan amount, ptT+1 is the value of the borrower’s tradeable assets at the maturity of the lending contract, and the new notation here g is a coefficient attributed to monitor the uncollateralised part of the b loan T (standard leverage ratio). Moreover, y represents liquidation costs pt +1 for selling the tradeable assets ptT+1, and h denotes the lending relationship between the lender and the borrower or the borrower’s credit social capital. From Equation (2.6), we can formulate a simple relationship between monitoring costs and the size of the loan, wealth and social capital of the agent. Such that, in line with Baxter (1967) and Copeland and Weston (1988: 498–499), we have a positive relationship between monitoring costs and the leverage ratio, implying a positive relationship between the monitoring effort exerted and the size of the loan. At the same time, there is a negative relationship between monitoring costs and the value of the borrower’s wealth (tradeable assets after accounting for liquidation costs), as well as a negative relationship with her social capital. If monitoring is just a function of loan size and collaterals, such that g b, ptT+1 , then the relation with the loan size will be easily predicted as a positive slope curve or straight line g ′ ( b ) > 0 and g ′′ ( b ) > 0 that is not expected to converge. However, the function g ptT+1 is a little challenging to define. Stiglitz and Weiss (1981: 402–405) theorems number 10 and 12 indicate that wealthier borrowers might be more willing to undertake riskier investments. So g ptT+1 should take a U-shaped curve, in which low-wealth agents are assigned with high monitoring efforts, and the required monitoring efforts should decreases as the borrower’s wealth increases until the borrower’s wealth reaches a threshold in which the monitoring efforts assigned to oversee her investment start to increase as her wealth increases. However, I do not find it reasonable here for a U-shape assumption in Equation (2.6). Because Equation (2.6) considers the cost of liquidating the borrower’s collaterals, then there is no reason for monitoring to increase for rich agents, even if the risk of their investments is recognisably high. For instance, consider ptT+1 (1 − y ) ≥ b , (e.g. all tradeable assets held as collaterals are cash deposits with zero liquidation costs). Obviously, such a loan is almost risk-free for the lender, and there is no need to increase the monitoring effort for that contract. For that, I expect a downward slope representing a negative relation between coefficient of monitoring efforts and the borrower’s wealth g ′ ptT+1 < 0 and g ′′ ptT+1 < 0. Equations (2.5) and (2.6) indicate that the lender charges high-leveraged agents who have no or low credit social capital with higher interest rate. In

)

(

(

)

(

(

)

(

)

)

Finance, distribution, and economic objective  25 neo-classical settings, high interest rate will reduce the demand for credit. Assuming a risk-averse agent who can truly predict the value of her expected returns, then she will not seek additional credit, in the first place, if the cost of additional capital rb is higher than her marginal return on capital. Additionally, since high interest rate increases the value of repayments, and given the positive relation between the value of collaterals and the expected effort exerted by the borrower established in Equation (2.4), then the lender anticipates that low- and middle-income agents will not have enough incentives to supply the sufficient effort. The probability of the success of their investment will be low (or almost zero). Thus, the ability of an agent to borrow (her credit worthiness) will completely depend on her wealth and her social capital, and agents with low wealth and low credit social capital are credit rationed. This is assuming that there is a minimum capital k * required for using an advanced production technique ak* , al* , in which low- and middle-income agents need to improve their productivity, whereas without this minimum production technique, production of low- and middle-income agents will be limited to their initial production technology and we can expect diminishing marginal returns to strictly hold. Assume also that the average deposit of low- and middle-income agents is lower than the minimum required capital, such that dl < d m < k * . In addition, high-income agents are already using the optimum production techniques available in the economy akn , aln . Figure 2.1 suggests future dynamics for wealth distribution if the financial sector consists only of investor-owned banks, where only high-income agents have enough collateral and lending relationships with the bank, and lowand middle-income agents are credit rationed because they do not meet the lending criteria. It predicts that there will be no convergence in the wealth distribution, and aggregate wealth of high-income agents will grow faster than the aggregate wealth of the two other classes and faster than the average wealth of the economy w. Accordingly, the distance on the vertical axis between the future wealth of high-income agents wht +1 and the future wealth of low- and middle-income agents wlt +1 and wmt +1 would widen compared to the original distance represented on the horizontal axis for wht , wlt and wmt . The inability of low- and middle-income agents to raise capital for potential investments restricted their expected income from self-employment and, as a result, from wages as well. Self-employed low- and middle-income agents will be more likely to have diminishing marginal returns, because investing only their deposits—with their low propensity to save affecting their future investments as well—do not allow them to improve their productivity by using advanced production techniques. If the potential return of low- and middle-income self-employment remained below the marginal return on labour of high-income production (from Equation (2.1)), then high-income agents can hire additional workers with wage rates favouring capital owners and thus maintain increasing net-returns—given that they are able to increase both factors of production simultaneously, and profiting

(

)

(

)

26  Finance, distribution, and economic objective

+1

+1

Figure 2.1  Wealth per income class with financial sector dominated by investor-­ owned bank.

from the marginal return on capital as well as the difference between the potential return of low- and middle-income self-employment and the marginal return on labour y ′ = f ′ k − rb + f ′ ( l ) −  f ′ ( k ) − rd  . Moreover, the convexity of the savings function enables high-income agents to invest a larger portion of their savings in future investments, which increases their capital stock at a rate faster than other classes. Finally, although believing that long-term dynamics are beyond such a simple economic model, even if we assume that the growth of income will reach zero, wealth of high-­ income agents in a steady state will continue to grow at a higher rate than n other classes because wealth w* when g *y = 0 is w* = 1 + s i y*  wt − n. Thus, inequality in wealth distribution will continue to increase because of initial wealth distribution, propensity to save, production techniques, and the corresponding initial level of income. In addition, the high rate of capital accumulation can help high-income agents to enhance the optimum production technologies already available. While if low- and middle-income agents remain credit rationed and with low propensity to save, then there will be no reason to assume that they will endogenously be able to accumulate enough capital to enhance their production techniques as well. Such

( )

Finance, distribution, and economic objective  27 growth in wealth inequality is adjusted, usually in reality, by government interventions or socio-political shocks that redistribute wealth exogenously. In many cases, social and political movements are driven by high inequality levels in the first place and claim that they intentionally seek to redistribute wealth on a more equitable basis. 2.3.1.  Capital transfer Contrary to the desired and assumed results of a perfect credit market, in an imperfect credit market high-income agents, after utilising all their deposits, will finance their new investments from the deposits of low- and middle-income agents. To simply see that, denote B as the aggregate outstanding loans provided in the economy; B represents aggregate loans to low- and middle-income agents at interest rates r; and B is the aggregate loans provided to high-income agents at interest rates r , such that usually r > r . Similarly, the aggregate deposits are denoted by D, D is low- and middle-­income deposits and D is high-income deposits, with the same interest rate on deposits rd . Government expenditures are G, and total taxes are T . Putting Rs to denote the regulatory reserves, then the credit market’s balance sheet constraints can be written as B + G ≤ T + D − Rs , and can further be expanded to B + B + G ≤ D + D + T − Rs .

(2.7a)

When low- and middle-income agents are credit rationed or their share in the credit market is minimal so that B ≈ 0, and when government expenditures exceed tax returns G > T , then part of these expenditures will be financed through debt from the credit market at the lowest lending interest rate r*, and it will have the priority to be financed because it is fully secured. We will d ­ enote aggregate government loans as Bˆ g . Similarly, when high-­income agents utilise all or more of their deposits B ≥ D, then we will denote ­additional credit for high-income agents as Bˆ h. We can then rewrite the balance sheet of the credit market as Rs + Bˆ g + Bˆ h − B ≤ D.

(2.7b)

From this simple representation, it is easy to see that when low- and middle-­ income cannot borrow from the credit market, and when government expenditures exceed tax revenues and/or when high-income agents utilise all their deposits, then any additional credit for government expenditures or for high-income individuals will be financed by the deposits of the low- and middle-income agents: namely, the deposits of inactive and salaried agents, to stay in line with our initial assumption that self-employed agents invest their deposits while save their tradeable assets. That will be the case even if the marginal return on capital and the interest rate on low- and middle-sized

28  Finance, distribution, and economic objective investments are higher than the marginal return on capital and interest rates of government expenditures and high-income agents’ investments. Because of the high leverage and low credit social capital of low- and middle-­income loan contracts with the bank, the risk associated to these contracts is high and puts pressure on the lending interest rate, keeping f ′ ( b ) < r. So, even if f ′ bg < f ′ b < f ′ ( b ), and the return of the banks is r > r > r*, the bank will still prefer the less risky loan contracts given to the government, followed by high-income borrowers. Another way to express this idea is to think about the net return of the lender (from Equation 2.5) when choosing between three loan contracts: for the government, a high-income agent and for a low- or middle-income agent.

( )

( )

 z z p b ( B ) = max  pb r − m − l ;  r* ;  pbr − m − l  . b b 

(2.7c)

Although the interest rate on a low- or middle-income loan contract is higher than the interest rates charged for the government or a high-income agent r > r > r*, the lender will prefer the latter two contracts. This is unsurprising as the probability of success (and repayment) of the government and a high-income agent is higher pg > p > p pg ≅ 1 , and because the monitoring costs of a high-income agent’s contract are lower than the costs of a low- or middle-income agent’s contract m < m.

(

)

2.4.  Income and wealth distribution with financial cooperatives The type of lender assumed in the previous scenario is similar to traditional investor-owned banks and, as the screening process depends on the borrower’s expected return, collaterals and reputation (or relationship with lender), low- and middle-income agents are credit rationed. However, if the lender is less exposed to asymmetric information and moral hazards, then the lending rate can be reduced and more people can have access to additional capital. A financial cooperative can have a comparative advantage over the Bank because it is formed locally, targeting a small geographic area, and there is usually a degree of homogeneity and previous social relations between the members themselves (Guinnane, 2001: 370), making the Cooperative able to serve some of the agents who were previously credit rationed by the Bank. Since the lending rate is a function of targeted net profit of the lender and monitoring costs, it is reasonable to assume that the interest rate of the Cooperative will be lower than that of the Bank ( rc < rb ) for any b = k − d . Because, theoretically, the desired net profit of a Cooperative is lower than a Bank (p c < p b ), and high social relation with the borrower hc > hb . That comes from the fact that financial cooperatives are not-for-profit organisations, and so the desired rate of profit of a financial cooperative per loan p c is most likely to be lower than the profit of a traditional bank p kb .

Finance, distribution, and economic objective  29 In addition, monitoring costs are low for financial cooperatives compared to traditional banks ( mc < mb ) because social capital h is high in the Cooperative monitoring formula while it is almost zero for low- or middle-income agents dealing with the Bank. In Mersland (2009: 471), out of 586 microfinance institutions globally, cooperatives had the lowest operating expense to loan portfolio ratio (OER) and portfolio yield (interest income to portfolio), of 14% and 23%, respectively, compared to 20.8% and 34.2% for shareholders banks, and 27.7% and 38.6% for non-profit organisations. Identical results were reported in Tchakoute-Tchuigoua (2010: 440). In Périlleux et al. (2012: 396), cooperatives had the lowest average interest rate per loan and at the same time the highest average deposit rate in the sample. However, in all of these studies, the average loan size of cooperatives was higher than shareholder or not-for-profit organisations, so that low lending rates and operating costs can be associated with the loan size rather than only social capital. Angelini et al. (1998) defined two hypotheses under which the Cooperative can screen potential borrowers better than the Bank. The first one is the long-term interaction hypothesis, suggesting that financial cooperatives are more engaged in their communities’ social life, and so they have cost-free information that investor-owned banks can obtain by costly monitoring. In addition, cooperatives can rely on ‘social sanctions’ to penalise defaulters (Banerjee et al., 1994; Besley and Coate, 1995; and Angelini et al., 1998). Second is peer-monitoring hypothesis, suggesting that members of financial cooperatives have additional incentives to monitor the actions of their peers. That is because members are liable, completely or in part, for the default of any loan taken by other members. If a borrower defaults, then other members lose some of their savings because part of each loan is financed by other members’ money. Moreover, the interest paid on the part of the loan that is financed by other members is the income of these members, as returns on deposits, so they have incentive in ensuring that the loan and its interest are paid (­Banerjee et al., 1994: 492). Peer monitoring is a mechanism that exists not only in cooperatives but also in similar group lending programs. Stiglitz (1990) demonstrated that by making the individual borrower co-sign his neighbour’s loan, peer-monitoring transfers risk from the lender (bank) to the co-signer, and imposes additional risks on the co-signer. A co-signer of a loan agreement is, thus, a borrower him/herself who agrees to guarantee the repayment of a part of his neighbour’s loan in case his neighbour has defaulted. This joint agreement allows both borrowers to obtain additional funds at lower interest rate, which cannot happen without this agreement. The utility of both borrowers is high only if both of them are successful; but if one borrower fails and the other succeeds, the second borrower’s utility will be low, even if his project succeeds. Stiglitz (1990) argues that peer monitoring improves borrowers’ welfare because the lender will compensate the co-signer for undertaking this additional risk by providing a larger loan that will have a higher return when invested in the safe project, which in return eliminates the borrowers’ incentives to invest in the risky project (Stiglitz, 1990: 361).

30  Finance, distribution, and economic objective The analysis here focuses on the loan size with specific collateral and the corresponding interest rate that the cooperative can provide middle-income agent compared to the bank. However, the cooperative’s information and enforcement advantage allows it to provide credit to the members in favourable terms in general, not only interest rates. Guinnane (2001: 379–380) explained how early cooperatives in Germany provided long-term loans with low collaterals relying on co-signers and the locality of cooperatives. Hence, if rc < rb for any b = k − d , and recalling that the level of effort exerted by the agent is the main determinant for the probability of success and is inversely related to the interest rate, then pc ( e ) > pb ( e ) and pc f ′ ( k ) − rc > pb f ′ ( k ) − rb, and accordingly: pc f ′ ( k ) − b (1 + rc ) − lv − u ′ ( e ) > pb f ′ ( k ) − b (1 + rb ) − lv − u ′ ( e ).

( )

(2.8)

( )

Now, if there is b* = k * − d with lending rate rc b* lower than f ′ k * , and f k * + ptT+1 − lv − u ′ ( e ) > b* (1 + rc ), then low- and middle-income agents who can borrow at lending rate rc b* will escape the concavity of their initial production function and the wage rate of skilled and unskilled workers will increase correspondingly. However, the division of the economy into three classes imposes two setups with different resulting paths for income distribution with the existence of financial cooperatives. The first and idealistic setup is if there is no high disparity in the initial wealth distribution between low- and middle-income agents. Under this assumption, both classes will have nearly the same deposits and tradeable assets to form their cooperatives and benefit from its financial services, as well as attracting external borrowings collectively from the high-income class. Then we could treat both classes as one class from the beginning, which would be less realistic to assume especially in early stages of development, where class differences are substantial compared to later, more developed stages where heterogeneity in wealth and skills may be less severe between the classes. It is reasonable to assume that only middle-­ income agents are capable of forming financial cooperatives because establishing a cooperative requires the pooling of a minimum capital and deposits that enable the cooperative to successfully provide financial services and even attract external funding from outside its own members. This is also in line with Bowles and Gintis (1997: 243) and their modelling of workers’ cooperatives, which suggests that the number of workers who probably join cooperative firms increases with the wealth of the workers. Although Jones and Kalmi (2009) have not found a strong statistical correlation between inequality and the formation of cooperative organisations, however, this assumption is still reasonable as the average loan size of cooperatives is reported to be higher than microcredit providers as mentioned earlier in­ Mersland (2009), Tchakoute-Tchuigoua (2010), and Périlleux et al. (2012). If only middle-income agents are able to borrow b* at lending rate rc b* , Figure 2.2 shows that only middle-income agents will experience a high

( )

( )

( )

Finance, distribution, and economic objective  31

+1

+1

Figure 2.2  Wealth per income class with diversified financial sector (investor-owned bank and financial cooperative).

growing rate of returns, above the average growth of the economy. Moreover, the income and wealth gap will narrow between high- and middle-income agents, because middle-income agents are able to enhance their productivity by better technology or invest in their own human capital. They can correspondingly hire additional workers that compensate for the additional growth of capital. However, the same level of inequality may continue to persist between middle- and low-income agents as long as low-income agents are credit rationed. Their income will increase only for the short or medium run because of increasing demand on labour from middle-income entrepreneurs as well as high-income ones. The low supply of skilled labour— because more middle-income agents prefer to be self-employed—may also motivate high-income agents to invest in the skills of low-income agents and thus improve their productivity and wage rate simultaneously. Nevertheless, in the absence of targeted policies to channel credit for lower-income agents, by government or civil society, their income in the long run will continue to be limited to their outdated initial production techniques without sufficient capital accumulation to adopt new technologies. For that, it is hard to predict that the introduction of financial cooperatives alone will lead the

32  Finance, distribution, and economic objective aggregate wealth distribution to totally converge to a steady state where all agents have a nearly similar level of wealth, irrespective of the initial wealth distribution and individual skills. This last argument may apply for middle-­ income agents as well. If the initial wealth disparity between high- and middle-income agents is too wide and middle-income agents do not have sufficient initial capital to mobilise to form a cooperative, then they will not be able to provide the required capital for their borrowers or entrepreneurs, and will not be able to collectively obtain additional funds from high-class agents. As a result, their wealth will also be limited to the concavity of their initial productivity. As for capital transfer, a cooperative does not only rely on members’ deposits to finance its credit services; it can also mobilise external funds from inside the cooperative system, usually from the regional or national cooperative federation; more rare, but not unheard-of, is for funds to come from similar primary cooperatives. External funds can also come from outside the cooperative system, usually through the federation that can borrow from a financial institution in the credit market. In both cases, because the members of the cooperative are acting as collective debtors and relying on their joint liability, they are able to raise funds at interest rates and credit conditions that would not be available if they approached the credit market individually. External borrowing is crucial also for liquidity mismatch risk (Guinnane, 1997: 252, 2001: 370). Given the ability to approach the bank collectively, and going back to Equations (2.7a, b, and c), the collective loan contract will be favoured now to the bank compared to the individual’s contract. The loan acquired by the cooperative as a whole from the bank is denoted by as   b (e.g. b =

∑ b, with monitoring effort m and interest rate   r .

The size of the collective loan will reduce the monitoring effort compared to an individual loan, thus the interest rate will be lower because of less  z z monitoring effort as well as less administration costs  l  < l  and p > p b  b (Equations 2.5 and 2.6). It is convenient that the net return of the bank extracted from Equation (2.7c) can be: pb r − m − l

z z ˆ ˆˆ − m ˆ −l , < pbr b bˆ

z z ˆ ˆˆ − m ˆ − l   ≥  pbr − m − l , only if   rˆ ≥ r . pbr b bˆ So the net return from a collective loan is certainly higher than a loan to an individual middle-income agent. The second condition states that the return from the cooperative collective loan can be more preferred if it carries a higher interest rate than the high-income agent’s loan. The ability for the cooperative collective loan to bear a higher interest rate comes from the fact

Finance, distribution, and economic objective  33 that the individual production function of the agents themselves will still witness high returns, as the condition of f ′ b < f ′ ( b ) still holds in the presence of additional capital. Thus, financial intermediation may be able, in this scenario, to channel surplus funds from high-income agents to middle-income ones who can invest it in projects yielding higher marginal returns.

( )

2.5.  Financial cooperative economic objective function The economic objective of a financial cooperative is to maximise the welfare of its members who are also the owners, by providing financial intermediary services, and not only to maximise its profit, as dividends are only part and not all of the owners’ gains. Taylor (1971) argues that financial cooperatives should minimise interest spread, that is, minimise the difference between interest rates charged on loans to members and interest rates paid on members’ deposits. Smith et al. (1981) and Smith (1984) suggest that the objective of financial cooperatives is to increase the monetary gains of their members: that is, providing lower interest rates to their borrowers and higher interest rates to their depositors compared to the market rate. In line with all that, since members’ wealth is the accumulation of savings from previous yearly incomes, I write the objective function of financial cooperatives as a function of maximizing yearly income of the members by providing higher deposits rates and lower lending rates that compensate the income growth of the rest of the economy. More generally, if we stayed in line with our theory that financial cooperatives have potentials to reduce income inequality, then the economic objective function of a financial cooperative must aim at increasing the income of its members at a rate higher than the average growth rate of the economy. For example, returns from interests on deposits will be the only source of income for an inactive net-depositor. Thus she will prefer that the rate of change of the interest rate on deposit is not less than the average nominal growth rate of the economy, so that she can improve (or maintain) her wealth ranking in the class structure. Similarly, the increase in income of a net borrower who is a self-employed agent after acquiring additional capital should exceed the average economy’s nominal growth rate after paying the interest rates on the loan. Accordingly, the financial cooperative economic objective function will be V (c ) =

m

∑  f ′ ( k ) − r − g  +  drdt − g . i

c

d

(2.9)

i =1

where members are i = {1,2,…, m} and g denotes the nominal growth of income per capita, f ′ ( ki ) is the marginal return on capital equivalent to the additional return from the loan, rc is interests paid on the loan (for net-­ dr borrowers), and d rate of change of interests gained on deposits (net dedt positors). It is clear from the equation above that the only two factors that

34  Finance, distribution, and economic objective the financial cooperative can alter are the deposit and lending rates. The desired deposit and lending fees are then constrained with following inequalities in order to satisfy the objective function defined above: drˆd ≥ g, dt f ′ ( k ) − rˆc ≥ g. To analyse how a financial cooperative can determine their deposit and lending rates in favour of the members’ welfare we will have to link the cooperative’s interest rate with a market interest rate that we will consider as the safe investment that the cooperative can make using the money mobilised from its members. We will denote such a market rate as   r*, similar to the above lending rate to the government. Accordingly, the desired deposit rate of a financial cooperative will be rˆd = r* − qˆ , and qˆ is a deposit fee to cover the operational costs of providing depository services. Similarly, the desired lending rate will be rˆc = r* + fˆ , with fˆ as a lending fee. Therefore, qˆ and fˆ can be written as: qˆ ≤ r* − rdt −1 ( g + 1) ,

(2.10a)

fˆ ≤ f ′ ( k ) − g − r*.

(2.10b)

Such that rd = rdt −1 ( g + 1). The cooperative has cash flow constrains that dictate its pricing behaviour. We will first define the total deposits as D, total interest bearing assets as I , where I = (1 − Rs ) D , and Rs is the legal required reserves. Moreover, x is the fraction of I raised by external borrowing, 1− x is the fraction raised by deposits, z is the fraction of I invested in loans, and 1 − z is the fraction of I invested in the safe investment (e.g. government securities). And, as earlier, q and f will denote deposit and lending fees, in addition to a similar representation for fees on external borrowing that will be denoted by d. Finally, we will put the desired net return of the cooperative with all the operational expenses, which includes salaries, administration costs, loan-loss provisions, and interest paid on the legal reserves under one variable. We will call them e , and calculate it by taking the total amount of expenses and net return as percentage of interest bearing assets. Now we can easily define the cash flow of a financial cooperative similar to DeAngelo and Stulz (2015: 226).

(

)

(

) (

)

z r * + f + (1 − z ) r * = (1 − x ) r * − qˆ + x r * + d + e . From that we can derive the actual deposit and lending fees. q=

zf − xd − e , x −1

(2.11a)

Finance, distribution, and economic objective  35 f=

q ( x − 1) − xd + e . z

(2.11b)

There are four main implications for this simple modelling for the desired and actual lending and deposit cooperative fees. First, it gives a possible explanation for why cooperatives may fall short in improving the relative welfare of their members and reducing income inequality. Second, and more importantly, it recommends an optimal lending and deposit fees that can help the cooperative decision-making. For instance, if qˆ > q and fˆ < f , may be because of industry slow-down or any similar reasons that reduce the potential returns of borrowers, accordingly, Equation (2.11b) suggests that equalizing the actual deposit fees with the desired on qˆ ≈ q will simultaneously reduce the actual lending rate, thus compensating for the expected reduction in the borrower’s returns. A further example may be that it shows how deposit and lending rates, and consequently the welfare of members, would change if the operational efficiency e of the cooperative changed as well. The third implication is to determine the desired total credit to be supplied for the members. The final implication is assessing the need and potential of the cooperative to seek external borrowing. z=

q ( x − 1) − xd + e , f

(2.12a)

x=

zf + q − e . q +d

(2.12b)

Equations (2.12a and b) suggest optimal loans ( z ) and/or external borrowings ( x ) as a percentage of total interest bearing assets ( I ). Again, combined with Equations (2.10 and 2.11), it gives more insights into the optimal decision that a cooperative can make to increase the members’ welfare if qˆ > q and/or fˆ < f , through increasing/reducing the loan supply and/or external borrowings. In addition, it clarifies the optimal response for the change in the external borrowing rate r* + d due to a change in d.

2.6.  Concluding remarks The ability to obtain capital from a perfect credit market—where there is no moral hazard or asymmetric information—would be entirely based on the projected cash flow of the desirable investment, whereas in imperfect credit markets, providing credit depends on the borrower’s collaterals and the lender-­ borrower relationship. If the financial sector consists solely of investor-­owned banks, then only high-income agents will obtain additional capital because they have enough collateral and lending relationships with the bank, whereas low- and middle-income agents will be credit rationed. The inability of lowand middle-income agents to raise capital for potential investments restricts their expected income from self-employment as well as from wages. That is

36  Finance, distribution, and economic objective because they cannot adopt more advanced production techniques or invest in their human capital, so their income will be limited to their initial production technology and we can expect diminishing marginal returns to strictly hold. Moreover, high-income agents can hire additional workers at wage rates that favour capital owners, thus maintain increasing net returns if the potential return of low- and middle-income self-employment remained below the marginal return on labour of high-income production. High-­income agents will be able to increase both factors of production simultaneously, and because of the convexity of the savings function, they will increase their capital stock at a rate faster than other classes. Thus, the aggregate wealth of high-income agents will grow faster than the aggregate wealth of the two other classes and faster than the average wealth of the economy. When government expenditures exceed tax revenues and/or when high-­ income agents utilise all their deposits, then any additional credit for government expenditures or for high-income individuals will be financed by the deposits of the low- and middle-income agents. Financial cooperatives are expected to be less exposed to asymmetric information and moral hazards and are thus more able to lend middle-income agents the required capital to upgrade their production function at an interest rate lower than the marginal product of capital. The potential of financial cooperatives to reduce income inequality depends on their ability to increase the income of their members at a rate higher than the average nominal growth rate of the economy. Since only middle-income agents are able to mobilise enough deposits to form a cooperative, low-income agents will remain credit rationed and the financial sector alone cannot achieve full convergence in income distribution. In conclusion, it is therefore important—especially for less developed e­ conomies—to advocate and promote the creation and growth of well-functioning member-owned financial institutions, rather than just pushing towards more financialization as an end by itself and not as a means for inclusive prosperity.

Note 1 This chapter is largely based on the following publication: Khafagy, A. (2019). Finance, distribution and the economic objective of financial cooperative institutions, Annals of Public and Cooperative Economics, 90(3), 487–511. ‘Reprinted with permission’.

Bibliography Acemoglu, D. (2003), ‘Labor and capital augmenting technical change’, Journal of the European Economic Association, 1(1), 1–37. Aghion, P. and Bolton, P. (1997), ‘A theory of trickle-down growth and development’, The Review of Economic Studies, 64(2), 151–172. Angelini, P., DI Salvo, R. and Ferri, G. (1998), ‘Availability and cost of credit for small businesses: customer relationships and credit cooperatives’, Journal of Banking and Finance, 22(6), 925–954.

Finance, distribution, and economic objective  37 Banerjee, A. V. and Newman, A. F. (1993), ‘Occupational choice and the process of development’, Journal of Political Economy, 101(2), 274–298. Banerjee, A. V. and Duflo, E. (2005), ‘Growth theory through the lens of development economics’, in Aghion, P. and Durlauf, S. N. (eds.), Handbook of Economic Growth, vol. 1A, Amsterdam: Elsevier, pp. 473–552. Banerjee, A. V. and Duflo, E. (2010), ‘Giving credit where it is due’, Journal of Economic Perspectives, 24(3), 61–80. Banerjee, A. V., Besley, T. and Guinnane, T. W. (1994), ‘The neighbor’s keeper: the design of a credit cooperative with theory and a test’, The Quarterly Journal of Economics, 109(2), 491–515. Baxter, N. D. (1967), ‘Leverage, risk of ruin and the cost of capital’, The Journal of Finance, 22(3), 395–403. Beck, T., Demirgüç-Kunt, A. and Levine, R. (2007), ‘Finance, inequality and the poor’, Journal of Economic Growth, 12(1), 27–49. Ben Naceur, S. and Zhang, R. (2016), ‘Financial development, inequality and poverty: some international evidence’, Working Paper no. 16/32. Washington, DC: International Monetary Fund. Besley, T. and Coate, S. (1995), ‘Group lending, repayment incentives and social collateral’, Journal of Development Economics, 46(1), 1–18. Bourguignon, F. (1981), ‘Pareto superiority of unegalitarian equilibria in Stiglitz’ model of wealth distribution with convex saving function’, Econometrica, 49(6), 1469–1475. Bowles, S. and Gintis, H. (1997), ‘Democratic firms and the distribution of wealth’, in Roemer, J. (ed.), ‘Property Relations, Incentives and Welfare’, Basingstoke: ­Palgrave Macmillan, PP. 243–265. Copeland, T. E. and Weston, J. F. (1988), ‘Financial Theory and Corporate Policy’, 3rd Edition, Reading: Addison-Wesley. Deaton, A. (1997), ‘The Analysis of Household Surveys: A Microeconometric Approach to Development Policy’, Washington, DC: World Bank. Demirguc-Kunt, A. and Levine, R. (2009), ‘Finance and inequality: theory and evidence’, Annual Review of Financial Economics, 1(1), 287–318. Galor, O. and Zeira, J. (1993), ‘Income distribution and macroeconomics’, The Review of Economic Studies, 60(1), 35–52. Greenwood, J. and Jovanovic, B. (1990), ‘Financial development, growth, and the distribution of income’, Journal of political Economy, 98(5), Part 1, 1076–1107. Guinnane, T. W. (1997), ‘Regional organizations in the German cooperative banking system in the late 19th century’, Research in Economics, 51(3), 251–274. Guinnane, T. W. (2001), ‘Cooperatives as information machines: German rural credit cooperatives, 1883–1914’, The Journal of Economic History, 61(02), 366–389. Jenkins, S. (1991), ‘The measurement of income inequality’, in Osberg, L. (ed.), ‘Economic Inequality and Poverty’, New York: M. E. Sharpe, 3–31. Jones, C. I. (2005), ‘The shape of production functions and the direction of technical change’, The Quarterly Journal of Economics, 120(2), 517–549. Jones, D. C. and Kalmi, P. (2009), ‘Trust, inequality and the size of the co‐operative sector: cross‐country evidence’, Annals of Public and Cooperative Economics, 80(2), 165–195. Kaldor, N. (1955), ‘Alternative theories of distribution’, The Review of Economic Studies, 23(2), 83–100. Mersland, R. (2009), ‘The cost of ownership in microfinance organizations’, World Development, 37(2), 469–478.

38  Finance, distribution, and economic objective Périlleux, A., Hudon, M. and Bloy, E. (2012), ‘Surplus distribution in microfinance: differences among cooperative, nonprofit, and shareholder forms of ownership’, Non-profit and Voluntary Sector Quarterly, 41(3), 386–404. Piketty, T. (1997), ‘The dynamics of the wealth distribution and the interest rate with credit rationing’, The Review of Economic Studies, 64(2), 173–189. Sen, A. (1973), ‘On Economic Inequality’, New York: Oxford University Press. Smith, D. J., Cargill, T. F. and Meyer, R. A. (1981), ‘Credit unions: An economic theory of a credit union’, The Journal of Finance, 36(2), 519–528. Smith, D. J. (1984), ‘A theoretic framework for the analysis of credit union decision making’, The Journal of Finance, 39(4), 1155–1168. Stiglitz, J. E. (1969), ‘Distribution of income and wealth among individuals’, Econometrica, 37(3), 382–397. Stiglitz, J. E. (1990), ‘Peer monitoring and credit markets’, The World Bank Economic Review, 4(3), 351–366. Stiglitz, J. E. and Weiss, A. (1981), ‘Credit rationing in markets with imperfect information’, The American Economic Review, 71(3), 393–410. Taylor, R. A. (1971), ‘The credit union as a cooperative institution’, Review of Social Economy, 29(2), 207–217. Tchakoute-Tchuigoua, H. (2010), ‘Is there a difference in performance by the legal status of microfinance institutions?’, The Quarterly Review of Economics and ­Finance, 50(4), 436–442.

3 Financial cooperatives and income inequality Empirical evidence

3.1. Introduction Empirical studies on finance and inequality have focused only on the size and not the structure of the sector. This chapter investigates whether the structure of the financial sector determines its distributional output rather than the size of the sector, which is frequently measured by credit to private sector as percentage of GDP. The structure of the financial sector here means the type of financial institutions that provide credit, and the controlling ownership of these institutions. It is reasonable to expect a financial sector dominated solely by profit-maximizing financial intermediaries to increase income and wealth inequalities, because it gives preferential access to finance for high-income agents, as opposed to a diversified inclusive financial sector with alternative models of finance, like cooperatives. The argument adopted here is that a diversified financial sector, represented by the market share of financial cooperatives, will have a negative correlation with income inequality, in both income inequality levels and period-to-period differences. Investor-owned, profit-maximizing financial intermediaries tend to exclude low- and middle-income agents, as they do not have sufficient information on these borrowers (the information asymmetries problem). The previous chapter argues that member-owned financial institutions may correct imbalances in income distribution that result from imperfect credit markets with asymmetric information and costly screening process. Access to credit depends mainly on the value of the borrower’s collaterals relative to the loan size (leverage ratio), and the borrower’s credit social capital, that is, the lender-borrower relationship developed from social relations or previous credit contracts. Therefore, in a credit market controlled solely by for-profit financial intermediaries, only high-income agents will be able to borrow and employ additional labour at a wage rate below the marginal product of labour. Meanwhile, agents with low wealth and low credit social capital will be credit rationed and will not be able to improve their production techniques or invest in their human capital to increase their productivity because they can only obtain credit at an interest rate higher than the marginal return on their capital. Thus, the income of low- and middle-income agents

40  Financial cooperatives and income inequality from self-employment or from wages will be constrained to their initial productivity, and wealth inequality will continue to increase depending on the initial wealth distribution, convexity of savings rates and heterogeneity of production techniques. However, if middle-income agents can pool their deposits together in a new financial institution that they own themselves based on some homogeneity among them, then they can increase their individual credit social capital. Assuming that the cooperative is less exposed to asymmetric information and moral hazards, it will lend middle-income agents the required capital to upgrade their production function at an interest rate lower than the marginal product of capital. But only middle-income agents are able to mobilise enough deposits to form a financial cooperative, while low-income agents will remain credit rationed. As a result, no full convergence in income distribution can be realised through finance only, and there is still a need for redistribution policies, and in a credit market where both type of institutions operate, the income and wealth gap between middle and high-income agents will narrow, but the same level of inequality may continue to persist between middle- and low-income agents. Using fixed-effects and two-stage instrumental variable regression methods, this essay explores the relationship between the market share of financial cooperatives in the financial sector and income inequality in 67 countries for the period 1995–2014. For a list of countries included in this study, see Table A3.1 in the appendix. Section 3.2 briefly discusses theoretical and empirical literature on finance and income inequality. Section 3.3 describes the data and methodology used. Section 3.4 presents the results, and the concluding remarks are in Section 3.5.

3.2.  Finance and income inequality Empirical literature investigating the relationship between the credit market and income inequality provide conflicting results. This section provides a detailed overview of the most cited and/or more recent previous empirical work on finance and income inequality. In addition to these studies, Table 3.1 summarises the results, countries, period covered, econometric methods and indicators of financial sector used in other, less-cited empirical works. Beck et al. (2007) used data for 65 countries for the period from 1960 to 2005 and found a negative relationship between the growth rate of the Gini coefficient and financial development (measured by private creditto-GDP: credit provided by financial intermediaries to the private sector). Similarly, Clarke et al. (2006) concluded that financial development reduces income inequality using data covering 83 countries for the period from 1960 to 1995. Kappel (2010) found that financial development reduces income inequality in high-income countries, but the impact of financial development on income inequality becomes rather weak in developing countries, using a cross-country analysis of 59 countries and a panel analysis covering 78 countries for the period 1960 to 2006. The results of Hamori and Hashiguchi

Linear—negative

Linear—positive

Type of effect

1982–2012

1963–2002 1961–2011

India 138 (E) and (D) Bangladesh Kazakhstan 65 (E) and (D) 78 (E) and (D) 49 (E) and (D) 83 (E) and (D) 126 (E) and (D) 143

Jauch and Watzka (2016) Wahid et al. (2012) Shahbaz et al. (2017) Beck et al. (2007) Kappel (2010)

Li et al. (1998) Clarke et al. (2006)

Hamori and Hashiguchi (2012) Ben Naceur and Zhang (2016)

Mookerjeea and Kalipioni (E) and (D) (2010) Batuo et al. (2012) 22 African countries

1994–2002

49 (E) and (D)

OLS GMM

1990–2004

OLS and IV

FE and GMM

FE ARDL and ECM ARDL and UECM OLS and GMM Cross-country: OLS and 2SLS. Panel: RE Pooled OLS, IV OLS and 2SLS RE

ARDL

OLS including country fixed-effects SVAR

GMM

FE, RE, and IV

2000–2005

1947–1994 1960–1995

1960–2008 1985–2006 1990–2014 1960–2005 1960–2006

1974–2011

OECD

1987–2011

45 (E)

Denk and Cournède (2015) Gimeta and LagoardeSegot (2011) Sehrawat and Giri (2015)

1975–2005

121 (E) and (D)

De Haan and Sturm (2017) Seven and Coskun (2016)

Period covered Econometric method

Countries included

Study

Table 3.1  Empirical literature on the effect of the financial sector on income inequality

(Continued)

M2, credit to private sector, and liquid liabilities (separately and composite index)

Credit to private sector, bank accounts per 1,000 adults, net interest margin, ratio of regulatory capital to riskweighted assets Number of bank branches per 100,000

M2 Credit to private sector, claims on the nonfinancial domestic sector by deposit money banks M2 and credit to private sector

Liquid liabilities, credit to private sector, bank deposits Credit to private sector and value added of finance Credit to private sector, interest rate spread, liquid reserves to asset Domestic credit to private sector and market capitalisation Credit to private sector Credit to private sector Credit to private sector Credit to private sector Credit to private sector

Credit to private sector

Financial sector indicators (mostly as percentage of GDP)

Brazil India Pakistan China 138 (E) and (D) 52 (E) and (D) 23 Central and Eastern Europe 65 (E) and (D) China (urban) Iran 35 (E)

Bittencourt (2010)

Ang (2010)

Shahbaz and Islam (2011) Jalil and Feridun (2011) Jauch and Watzka (2016) Nikoloski (2013) Cojocaru (2011)

Liu et al. (2017)

Shahbaz et al. (2015) Tan and Law (2012)

Kim and Lin (2011)

Countries included

Study

1965–2011 1980–2000

1996–2012

1960–2005

1971–2005 1978–2006 1960–2008 1962–2006 1990–2008

1951–2004

1985–1994

Period covered

ARDL and VECM GMM

GMM

IV

ECM and ARDL ARDL GMM FE and GMM FE and GMM

time-series, Pooled OLS,≈FE, FD-IV, and E-IV ECM and ARDL

Econometric method

Credit to private sector, liquid liabilities, domestic assets of deposit money banks Total loans provided by banks and sum of stock market value traded and banking credit Domestic credit to private sector Credit to private sector and liquid liabilities

Credit to private sector Credit to private sector Credit to private sector

Credit to private sector, M3 minus Ml, number of bank offices per population. Credit to the private sector

M2, M3, credit to the private sector and credit to individuals

Financial sector indicators (mostly as percentage of GDP)

(E) = Emerging (D) = developed. OLS = Ordinary least squares. 2SLS = Two-stage least squares. FE = Fixed-effects. RE = Random-effects. FE-IV = Fixed-effects instrumental variable. FD-IV = First difference instrumental variable. GMM = Generalised method of moments. ECM = Error-correction model. ARDL = Autoregressive distributed lag. SVAR = Structural vector autoregressive. UECM = Unrestricted error correction model.

U-shape

Inverted U-shape

Type of effect

Financial cooperatives and income inequality  43 (2012) indicate that both M2/GDP and private credit-to-GDP have a negative correlation with estimated household income inequality using panel fixed-effects and GMM analysis for a sample of 126 countries for the period from 1963 to 2002. Ben Naceur and Zhang (2016) found that financial development (measured by access, efficiency, deepening, and stability) reduces income inequality and poverty, using a sample of 143 countries for the period from 1961 to 2011. Recent empirical evidence challenges the promising positive impact of finance on the reduction of income inequality. Denk and Cournède (2015: 13–15) explored the relationship between finance and income inequality in OECD countries for the period from 1974 to 2011. They found that a 10% increase in intermediated credit as percentage of GDP (as a measure for financial size) is positively correlated with an increase in the Gini coefficient by 0.13 points. But that does not necessarily imply that less finance would decrease income inequality. Moreover, higher inequality is assumed by several economic theories to increase the amount of finance in the economy because low-income households would seek credit to reduce consumption inequality as suggested by Panico et al. (2012). Nevertheless, Denk and Cournède (2015: 22) found no evidence for that in the euro area, as the debt of low-income households debt as percentage of total credit is not high in countries with high income inequality compared to more egalitarian countries. Thus, they associated the increase of income inequality with the decline of the wage share in the OECD countries over the past half century. In general, their results indicated that for the period from 1961 to 2011, per capita growth of real household disposable income was negatively correlated with intermediated credit. An increase in intermediated credit as percentage of GDP by 10% is associated with a slowdown of disposable income growth by 0.3 percentage points. They found that higher intermediated credit is negatively correlated with the growth of disposable income for all income deciles except the top 10% earners. An increase in intermediated credit by 10% will probably reduce growth of disposable income of the bottom 10% by 0.8 percentage points, and by 0.4–0.5 percentage points for the two middle deciles, while increasing the growth of disposable income of the top decile by 0.1 percentage points (Denk and Cournède, 2015: 25). ­Similarly, using a panel fixed-effects model for a sample of 121 countries covering 1975–2005, de Haan and Sturm (2017) found that financial development increases income inequality. These results do not change when the model is estimated using random-effects estimation, or when instrumenting financial development by legal origin. Finally, and consistent with the theory of Greenwood and Jovanovic (1990), the results of Kim and Lin (2011) suggest that the positive impact of financial development on income distribution occur only after the financial sector has reached a threshold level of development, using a sample of 65 countries for 1960–2005. Similarly, Law et al. (2014) used a cross-sectional analysis for a sample of 81 countries covering the period from 1985 to 2010 and found that financial development

44  Financial cooperatives and income inequality reduces income inequality only after the country has achieved a certain level of institutional development. A possible reason for the contradictory empirical results is the period and countries covered by each study. We can observe that all the studies that suggested a negative impact for financial development on income inequality cover a period that starts in the 1960s and do not include the years following the financial crisis (Clarke et al., 2006; Beck et al., 2007; Kappel, 2010; Hamori and Hashiguchi, 2012). On the other hand, studies indicating that financial expansion is associated with increased income inequality include the years following the financial crisis (Denk and Cournède, 2015; Seven and Coskun, 2016), or only cover the last thirty years prior to the financial crisis where income inequality noticeably increased (Gimeta and Lagoarde-Segot, 2011; Jauch and Watzka, 2016; de Haan and Sturm, 2017).

3.3.  Data and method The following empirical analysis tries to explore whether or not the structure of the financial sector matters to understand the impact of financial sector development on income inequality. The main argument is that the structure of the financial sector, and not only the size of the sector, determines the distributional output of finance. A financial market dominated by profit-driven investor-owned financial institutions, or capital market, will probably witness high levels of income inequality, in both income inequality levels and period-to-period differences, compared to a diversified sector where financial cooperatives have a significant share in the financial market. For that, fixed-effects and instrumental variable regression methods are used to analyse the relationship between the market share of financial cooperatives’ credit and income inequality in more than 60 countries. All regression analyses are estimated using five-year averages for the period from 1995 to 2014. The study here argues that the share of financial cooperatives’ credit in the credit market and capital market (first regression tests) can predict the level of income inequality. In addition, the change in income inequality can be explained (partly of course) by the change in the share of financial cooperatives’ credit in the financial market (second and third regressions). The fourth regression test is a reverse regression to see the direction of the correlations between the main variables (inequality and financial cooperatives). The data used are discussed at the beginning; then the features of the econometric methods are discussed. 3.3.1.  Inequality measurements It is difficult to have a standardised cross-country measurement for income inequality for long periods that allows for consistent comparisons of the trends and levels of inequality. Income inequality measurements differ in

Financial cooperatives and income inequality  45 their sources, units of measurements, and methods. For instance, income inequality as measured across households will probably differ from income inequality measured across households per capita, as the size of households are not constant and vary across countries as well as within a country over time. In the same way, inequality as measured by net income will be different from inequality in expenditures, because savings and consumption patterns are different among households of the same country, as well as between countries. Moreover, the difference between gross and net income inequality will differ between countries and within a country over time depending on the tax and redistribution policies adopted by each country in a specific period. One of the most comprehensive cross-national panel datasets of Gini coefficients is the Standardized World Income Inequality Database (SWIID), which incorporates the Luxembourg Income Study (LIS) with observations obtained from other sources, such as the World Income Inequality Database (WIID), EuroStat and similar sources, as well as national surveys and academic literature. The SWIID uses the LIS series as the baseline measurement and standardises the observations of the other sources in order to be compatible with the LIS data. The LIS series is divided into net and market Gini coefficients, where the net Gini measures income inequality before taxes and transfers, and the market Gini measures inequality before tax deductions and welfare transfers (Solt, 2016: 1269–1272). Several scholars including Bergh and Nilsson (2010), Tan and Law (2012), Ostry et al. (2014), Acemoglu et al. (2015), and Jauch and Watzka (2016) used the SWIID. I chose the market (or gross) Gini because credit provided by financial cooperatives should affect the gross income of the cooperatives’ borrowers or increase the wage rate by lowering the supply of labour to market, as more workers can open their own businesses. Both assumptions should have the impact of income distribution before tax deductions and welfare transfers. Tables 3.2 and 3.3 provide overview over variables used and data description. 3.3.2. Methodology The relationship between the share of financial cooperatives in the credit and financial market and income inequality is examined using unbalanced panel data covering the period from 1995 to 2014 for 67 countries. All regression analyses are estimated using five-year averages. In the first regression test (Table 3.4), yi is the natural logarithm of the gross Gini coefficient. In Table 3.4 is the correlation between the size of financial cooperatives’ share in total domestic credit, and the total financial market (credit and capital markets) is regressed for all countries in the sample and separately for high-income, middle-income, and low-income countries. The division of countries is based on their gross national income per capita and follows the World Bank classification by income level (World Bank, 2017).

Outstanding credit provided by financial cooperatives as percentage of domestic credit provided by financial sector. Outstanding credit provided by financial cooperatives as percentage of the financial market (credit and capital market).

Credit provided by the financial sector to all sectors of the economy, including the government divided by the gross domestic product at current prices. The financial sector consists of the central bank (or its equivalent), deposit-taking financial institutions and similar financial institutions. Sum of the domestic credit by financial sector and the market capitalisation of listed domestic companies divided by the gross domestic product at current prices. Market capitalisation is calculated as the end of year price of shares times the number of outstanding shares of all listed companies in the stock market. Domestic credit provided by financial sector as percentage of financial market.

Financial cooperative credit to domestic credit Financial cooperative credit to financial market

Domestic credit provided by financial sector

Polity

Trade (% GDP) Financial openness

Unemployment rate

GNI per capita

Inflation rate

Domestic credit to financial market GDP per capita growth

Year-to-year growth rate of the GDP per capita. GDP per capita is the total gross domestic product at constant local currency divided by the country’s population. Calculated using the GDP implicit deflator, that is, GDP in current prices divided by GDP in constant prices. Gross national income divided by the population. GNI is the total income of country’s residents (domestic and overseas). Percentage of labour forces without work but which are available, willing and seeking employment. Total exports and imports including goods and services as percentage of the GDP. Measuring the degree of capital account openness. The index is used here to reflect the financial liberalisation policies of a country. Measuring the characteristics of political institutions. This ranges from +10 to −10, where +10 is strongly democratic and −10 is strongly autocratic.

Originally ranges from 0 to 100, in which zero represents perfect equality. Here I divided the measurement by 100 to range from 0 to 1.

Natural logarithm of gross Gini coefficient

Financial market (% GDP)

Description

Variable

Table 3.2  D  ata sources and variables used

Polity IV project

Chinn-Ito index

Standardized World Income Inequality Database (SWIID) World council of credit unions (WOCCU), the key statistics of the European Association of Co-operative Banks (EACB) and the OECD banking statistics. World Bank open data

Source

Financial cooperatives and income inequality  47 Table 3.3  D  ata description Variable

Mean

Std. Dev. Min

Ln gross Gini FC credit to domestic credit FC credit to financial market Domestic credit to financial market Financial market (% GDP) Ln GNI per capita Trade (% GDP) Financial openness Unemployment GDP per capita growth Inflation Polity

−0.772 0.048

0.142 0.085

0.033

0.065

0.000

0.650

0.172

1.465 9.224 0.874 0.651 0.079 0.023 0.081 0.071

Max

Obs.

Countries

259 247

67 67

0.437

203

65

0.044

0.975

219

67

1.107

0.109

7.440 219

67

1.084 0.575 0.338 0.055 0.022 0.170 0.044

6.465 0.173 0 0.008 −0.074 −0.033 −0.09

−1.251 −0.370 0.000 0.521

11.228 4.102 1 0.348 0.094 2.314 0.1

268 266 264 268 268 268 268

67 67 66 67 67 67 67

In the second and third regression tests (Tables 3.5 and 3.6), yi is the first difference of the natural logarithm of the gross Gini coefficient. While in the fourth regression test, yi is the first difference of credit from financial cooperatives as a percentage of total domestic credit and as a percentage of the total financial market. For the explanatory and control variables Xi, in the first regression ­(Table 3.4), the main explanatory variables are outstanding credit from financial cooperatives as a percentage of domestic credit provided by the financial sector and as a percentage of the total financial market (domestic credit and market capitalisation). There is also a set of variables to control for the size of the credit and capital markets, represented by domestic credit provided by the financial sector as percentage of GDP and the financial market as percentage of GDP; as well as lagged values of the natural logarithm of gross Gini, GDP per capita growth, inflation rate, level of economic development (the natural logarithm of Gross National Income per capita), unemployment rate, trade as percentage of GDP, degree of financial liberalisation (financial openness) and quality of political institutions ­( polity). Meanwhile, the main explanatory variables in the second and third regressions (Tables 3.5 and 3.6) are the first difference of credit from financial cooperatives as a percentage of total domestic credit and as a percentage of the total financial market. The main explanatory variable in the last regressions is the first difference of the natural logarithm of the gross Gini coefficient. Finally, I attempted to instrument for the changes in the share of financial cooperatives credit as a percentage of domestic credit and financial market. In the model presented in panels B and C of Table 3.5, the change in

48  Financial cooperatives and income inequality financial cooperatives’ share in credit and financial market are the endogenous variables and are instrumented by their lagged values at level (not first-differenced) besides the lag of financial cooperatives’ credit as percentage of GDP. Sargan-Hansen’s test of overidentifying restrictions does not indicate that the instruments used are invalid.

3.4. Results The results from four main regression tests are reported below. In the first tests (Table 3.4), the natural logarithm of the gross Gini coefficient is regressed against credit provided by financial cooperatives as a percentage of total domestic credit, and as a percentage of the total financial market using fixed-effects estimations. Additionally, there are other explanatory variables to control for main economic factors such as the level of economic development, growth, unemployment, inflation, and the size of the credit and capital markets, as well as the degree of financial liberalisation and the quality of political institutions. In the second tests (Table 3.5), the change in the gross Gini coefficient (first-difference) is regressed against the change in credit provided by financial cooperatives as a percentage of total domestic credit and as a percentage of the total financial market. Moreover, the first-difference regressions also use the lagged values of the gross Gini as an explanatory variable for the change in income inequality. In the instrumental variable regressions, the first-difference of the main explanatory variables (FC credit to domestic credit and FC credit to financial market) are instrumented by their lagged values in addition to the lag of financial cooperative credit as percentage of GDP. The third regressions (Table 3.6) explore the correlation between the change in financial cooperatives’ share in credit and financial markets and income inequality at different levels of financial sector development. Countries are clustered into two groups based on the sample’s average financial market as percentage of GDP and number of observations per country, in order to maintain a minimum of two observations per country. The last regressions (Table 3.7) present the reverse correlation between change in income inequality and changes in the share of financial cooperatives in credit and financial markets. Columns 1 and 2 in Table 3.4 suggest that total domestic credit provided by the financial sector, as well as the sum of the domestic credit by the financial sector and the market capitalisation of listed domestic companies (financial market) and have a positive correlation with income inequality. These results are in line with the findings of Denk and Cournède (2015), de Haan and Sturm (2017), Seven and Coskun (2016), and Jauch and Watzka (2016). Columns 3 and 4 suggest that the size of financial cooperatives’ credit as a percentage of total domestic credit and as a percentage of the whole financial market (credit and capital markets) has a statistically significant negative correlation with the level of income inequality only in low- and middle-income countries. However, there is no statistical significance for high-income economies as well as the total sample. In addition, the size of

0.006 (0.005) −0.498** (0.202) −0.093 (0.084) 0.024 (0.026) 0.456** (0.189) 0.029 (0.051) −0.005 (0.051) −0.087 (0.394) −1.026*** (0.242) 0.135 2.830*** 192 64

−0.158 (0.158)

(2)

PCI ≤ $12,475

0.128* (0.073) 0.017** (0.008) −0.415 (0.490) −0.064 (0.078) 0.044 (0.036) 0.175 (0.427) 0.000 (0.078) 0.040 (0.060) 0.291 (0.329) −1.266*** (0.314) 0.224 9.660*** 107 37

−0.928*** (0.149)

(3)

PCI > $12,475

−0.003 (0.006) −0.747* (0.427) −0.085 (0.080) 0.035 (0.038) 0.173 (0.415) −0.008 (0.084) 0.042 (0.062) 0.090 (0.387) −1.058*** (0.320) 0.149 5.520*** 106 36

−1.213** (0.444)

(4)

−0.024 (0.081) 0.020 (0.018) −0.014 (0.254) 0.641** (0.268) 0.076 (0.049) 0.924*** (0.225) 0.050 (0.031) −0.097*** (0.025) −3.895*** (1.331) −1.260*** (0.335) 0.562 28.520*** 87 29

−0.084 (0.068)

(5)

*, ** and *** denote statistical significance at the 10%, 5% and 1% level, respectively. Standard errors in parentheses.

R 2 (within) F(10,65) Number of obs. Number of groups

Constant

Polity

Financial openness

Trade (% GDP)

Ln GNI per capita Unemployment

−0.191 (0.138)

FC credit to domestic credit FC credit to financial market Domestic credit to financial market Financial market (% GDP) GDP per capita growth Inflation

0.098* (0.058) 0.015** (0.007) −0.217 (0.277) −0.102 (0.082) 0.023 (0.027) 0.396** (0.195) 0.034 (0.050) −0.007 (0.052) 0.012 (0.353) −1.105*** (0.233) 0.166 4.500*** 194 66

(1)

Dependent variable: Ln gross Gini

All

0.022 (0.017) 0.028 (0.275) 0.618*** (0.213) 0.070* (0.035) 0.908*** (0.182) 0.054* (0.030) −0.098*** (0.025) −3.694*** (0.908) −1.237*** (0.285) 0.561 32.020*** 86 28

−0.088 (0.076)

(6)

Table 3.4  F  ixed-effects regression results for gross Gini coefficient against share of financial cooperatives’ credit in the credit and financial markets

50  Financial cooperatives and income inequality the financial market as percentage of the GDP has a positive statistically significant correlation with the level of income inequality in the total sample as well as low- and middle-income countries. Remarkably, there is no other explanatory factor, whether economic or institutional, that seems to provide a significant explanation for the variation in the level of income inequality between low- and middle-income countries. For high-income economies, it seems that the overall size of the financial sector (total domestic credit and financial market as percentage of GDP) and its structure do not appropriately explain the variation in the level of income inequality between high-income economies, whereas other economic and institutional factors do. Thus, inflation and unemployment have a positive correlation, and financial liberalisation (openness) and democracy (polity) have negative correlations with the level of income inequality, all statistically significant at the 1% level. In line with Acemoglu et al. (2015), it seems that the quality of political institutions or the level of democracy provides the highest explanation for the level of income inequality in high-income economies, given the high coefficient recorded in Table 3.4. Also for high-income economies, Column 6 suggests that a country’s income per capita and the size of foreign trade, measured as percentage of GDP, have positive correlations with income inequality, both statistically significant only at the 10% level, albeit with very small coefficients. Table 3.5 reports the main results in the analysis here, showing that changes in the gross Gini coefficient can be explained by the change of financial cooperatives’ share in the credit and financial markets. These results remain statistically significant after controlling for the lagged value of the Gini coefficient and even after controlling for other economic and institutional factors. The robust results of the instrumental variable regressions reported in panel B in Table 3.5 also support the argument that the structure of the financial sector, and not only the size of the sector, can explain the changes that occur in income distribution. Although the statistical significance of the correlations decreased, the magnitude (or coefficients) remained similar to the results of panel A, with the results of the Sargan-Hansen tests not indicating the invalidity of the instruments used. Moreover, there are negative correlations between changes in the Gini coefficient value with its lagged value, economic growth, and the lagged volume of foreign trade, all statistically significant at the 1% level, and the coefficient of correlation between the rate of economic growth and the change of income inequality is the highest compared to other explanatory variables. Table 3.6 suggests that a change in the share of financial cooperatives share in credit and financial markets has a stronger correlation with the change of income inequality when the financial sector (credit and capital markets) is still in its developing phase, and that such correlation is weaker in larger financial markets. Thus, although all results in Table 3.6 indicate statistically significant negative correlation between changes in the Gini coefficient and changes in credit provided by financial cooperatives as a percentage of the credit and financial markets, the coefficients and level of significance differ

R 2 (within) F(10,65) Number of obs. Number of groups

Constant

Polity (t-1)

Financial openness (t-1)

Trade (% GDP) (t-1)

Domestic credit to financial market (t-1) Financial market (% GDP) (t-1) Ln GNI per capita (t-1) Unemployment (t-1)

∆ FC credit to Domestic credit ∆ FC credit to financial market ∆ Domestic credit to financial market ∆ Financial market (% GDP) GDP per capita growth Inflation

Ln gross Gini (t-1)

Dependent variable: ∆ Ln gross Gini

Panel A: fixed-effects

0.032 (0.197) 0.117 5.850*** 143 66

−0.004 (0.004) −0.001 (0.021)

−0.615*** (0.154)

(1)

0.125 (0.200) 0.115 3.700** 131 60

0.017 (0.014) −0.015 (0.022)

−0.952*** (0.316)

(2)

0.002 (0.006) 0.034 (0.021) 0.109 (0.269) −0.095* (0.048) −0.047 (0.037) 0.443* (0.230) −0.588*** (0.213) 0.522 11.440*** 141 65

−1.416*** (0.305) 0.038 (0.143)

−0.510*** (0.122) −0.474*** (0.145)

(3)

0.043*** (0.013) 0.013 (0.021) 0.151 (0.289) −0.094** (0.043) −0.072* (0.036) 0.416* (0.247) −0.474 (0.216) 0.545 10.490*** 129 59

−1.356*** (0.312) −0.096 (0.159)

−0.650** (0.257)

−0.561*** (0.131)

(4)

0.052 (0.067) 0.022 (0.022) −1.187*** (0.275) −0.057 (0.185) 0.062 (0.075) 0.054** (0.025) 0.004 (0.029) 0.214 (0.310) −0.100** (0.045) −0.061 (0.041) 0.524* (0.244) −0.469 (0.309) 0.558 8.420*** 129 59

−0.555*** (0.137) −0.440*** (0.155)

(5)

(Continued)

0.053** (0.025) 0.006 (0.026) 0.154 (0.286) −0.098** (0.044) −0.069* (0.037) 0.420 (0.252) −0.416 (0.263) 0.547 9.900*** 129 59

0.011 (0.020) −1.332*** (0.316) −0.094 (0.161)

−0.650** (0.260)

−0.550*** (0.137)

(6)

Table 3.5  Fixed-effects and two-stage instrumental variable regression results for change in gross Gini coefficient against change in the share of financial cooperatives’ credit in the credit and financial markets

R 2 (within) F(10,65) Number of obs. Number of groups Sargan-Hansen (P-value)

Constant

Polity (t-1)

Financial openness (t-1)

Trade (% GDP) (t-1)

Unemployment (t-1)

Domestic credit to financial market (t-1) Financial market (% GDP) (t-1) Ln GNI per capita (t-1)

∆ FC credit to Domestic credit ∆ FC credit to Financial market ∆ Domestic credit to Financial market ∆ Financial market (% GDP) GDP per capita Growth Inflation

Ln gross Gini (t-1)

Dependent variable: ∆ Ln gross Gini

Panel B: fixed-effects IV 2sls

0.042 (0.197) 0.115 2.300* 143 66 0.866

−0.004 (0.008) −0.002 (0.022)

−0.706** (0.277)

(1)

0.136 (0.225) 0.112 2.290* 131 60 0.311

0.019 (0.021) −0.016 (0.026)

−1.106** (0.428)

(2)

0.002 (0.007) 0.034 (0.022) 0.109 (0.248) −0.095** (0.044) −0.047 (0.039) 0.443** (0.219) −0.588*** (0.215) 0.522 6.800*** 141 65 0.642

−1.416*** (0.336) 0.039 (0.185)

−0.510*** (0.098) −0.477* (0.239)

(3)

0.044** (0.018) 0.013 (0.025) 0.150 (0.255) −0.095** (0.045) −0.070* (0.039) 0.414* (0.225) −0.468** (0.230) 0.545 6.960*** 129 59 0.404

−1.360*** (0.350) −0.089 (0.198)

−0.711* (0.359)

−0.555*** (0.102)

(4)

0.049 (0.084) 0.022 (0.027) −1.194*** (0.404) −0.050 (0.206) 0.060 (0.088) 0.054* (0.027) 0.004 (0.030) 0.213 (0.266) −0.102** (0.047) −0.059 (0.042) 0.523** (0.244) −0.460 (0.300) 0.558 5.330*** 129 59 0.776

−0.549*** (0.109) −0.473* (0.248)

(5)

0.053** (0.026) 0.006 (0.029) 0.152 (0.257) −0.101** (0.046) −0.067 (0.040) 0.417* (0.226) −0.407 (0.258) 0.546 6.300*** 129 59 0.402

0.011 (0.023) −1.337*** (0.356) −0.082 (0.199)

−0.739** (0.357)

−0.541*** (0.105)

(6)

0.195* (0.098) −0.011 (0.080) 0.530 20.540***

−0.821*** (0.134)

−0.001 (0.003) 0.005 (0.009)

−1.291*** (0.146) 0.430*** (0.068) 0.014 (0.055) 0.583 23.420***

0.000 (0.005) 0.001 (0.006)

(2)

0.190* (0.110) −0.028 (0.116) 0.551 7.250***

−1.298*** (0.169) 0.435*** (5.670) 0.009 (0.110) 0.589 7.670***

−0.001 (0.006) 0.001 (0.009) 0.004 (0.087) 0.005 (0.015) 0.005 (0.013) 0.021 (0.077)

0.015 (0.120) 0.050 (0.066)

0.010 (0.181) 0.148 (0.095) 0.000 (0.004) 0.006 (0.012) 0.032 (0.133) −0.004 (0.024) 0.022 (0.020) 0.066 (0.117) −0.800*** (0.156)

0.010 (0.034)

(4)

0.021 (0.053)

(3)

*, ** and *** denote statistical significance at the 10%, 5% and 1% level, respectively. Standard errors in parentheses.

R 2 (within) F(10,65)

FC credit to domestic Credit (t-1) FC credit to financial market (t-1) FC credit (% of GDP) (t-1) Constant

Polity (t-1)

Financial openness (t-1)

Trade (% GDP) (t-1)

Unemployment (t-1)

Domestic credit to financial market (t-1) Financial market (% GDP) (t-1) Ln GNI per capita (t-1)

∆ Domestic credit to financial market ∆ Financial market (% GDP) GDP per capita growth Inflation

Ln gross Gini (t-1)

(1)

Panel C: first-stage of fixed-effects IV 2sls

0.235* (0.122) 0.014 (0.163) 0.579 5.510***

0.025 (0.059) −0.047 (0.046) −0.012 (0.015) −0.107 (0.219) 0.148 (0.109) −0.044 (0.049) −0.007 (0.015) 0.007 (0.016) −0.038 (0.145) 0.000 (0.026) 0.021 (0.022) 0.049 (0.133) −0.858*** (0.172)

(5)

−1.330*** (0.169) 0.446*** (0.077) −0.044 (0.088) 0.600 7.260***

−0.010 (0.009) 0.008 (0.010) 0.002 (0.086) 0.009 (0.016) 0.002 (0.013) 0.019 (0.076)

−0.010 (0.008) −0.004 (0.120) 0.046 (0.066)

−0.002 (0.035)

(6)

54  Financial cooperatives and income inequality Table 3.6  F  ixed-effects regression results for change in gross Gini coefficient against change in the share of financial cooperatives’ credit in the credit and financial markets (clustered by the size of financial market) Financial market (% GDP) > 140%

Financial market (% GDP) ≤ 140%

Dependent variable: ∆ Ln gross Gini

(1)

(2)

(3)

(4)

Ln gross Gini (t-1)

−0.882*** (0.195) −0.472* (0.240)

−0.864*** (0.147)

−0.301** (0.119) −0.554** (0.244)

−0.277** (0.105)

∆ FC credit to domestic credit ∆ FC credit to financial market ∆ Domestic credit to financial market ∆ Financial market (% GDP) GDP per capita growth Inflation Domestic credit to financial market (t-1) Financial market (% GDP) (t-1) Ln GNI per capita (t-1) Unemployment (t-1) Trade (% GDP) (t-1) Financial openness (t-1) Polity (t-1) Constant R 2 (within) F(10,65) Number of obs. Number of groups

−0.002 (0.159) −0.005 (0.026) −0.620 (0.395) −0.415 (0.784) 0.087 (0.227) 0.049* (0.026) −0.029 (0.024) −0.157 (0.370) 0.011 (0.061) −0.078* (0.044) 0.587** (0.212) −0.476 (0.451) 0.778 32.320*** 63 28

−0.684** (0.329) −0.001 (0.020) −0.653 (0.425) −0.353 (0.706) 0.054** (0.024) −0.019 (0.023) −0.304 (0.284) −0.012 (0.046) −0.075* (0.040) 0.692*** (0.180) −0.500* (0.251) 0.759 23.440*** 63 28

0.042 (0.103) −0.023 (0.079) −1.752*** (0.629) 0.188 (0.350) 0.037 (0.142) −0.019 (0.111) 0.063 (0.068) 0.496 (0.467) −0.129 (0.105) −0.072 (0.101) 0.471* (0.235) −0.671 (0.622) 0.508 12.450*** 66 31

−0.918*** (0.233) −0.051 (0.068) −1.948*** (0.526) 0.119 (0.289) −0.021 (0.102) 0.070 (0.064) 0.505 (0.468) −0.133 (0.094) −0.097 (0.087) 0.385* (0.213) −0.651 (0.514) 0.548 16.140*** 66 31

*, ** and *** denote statistical significance at the 10%, 5% and 1% level, respectively. Standard errors in parentheses.

according to the size of the financial market. That is reasonable, suggesting that a change in the structure of the financial sector in the early stages of financial development probably has a stronger impact on the distribution of investment opportunities and income. On the other hand, the response of the dynamics of income distribution to changes in the financial sector structure will be slower in big credit and financial markets.

Financial cooperatives and income inequality  55 Finally, Table 3.7 does not indicate a reverse correlation between change in income inequality and changes in the share of financial cooperatives in credit and financial market, giving more support that there may be a one-­direction causal correlation between credit provided by financial cooperatives and income distribution, at least in the sample analysed here. ­Table  3.7  indicates that only the lagged value of financial cooperatives’ share in the domestic credit market together with a lagged inflation rate can Table 3.7  Fixed-effects regression results for change in the share of financial cooperative credit in the total domestic credit and financial market against change in gross Gini coefficient (reverse regression) Dependent variable

FC credit to domestic credit (t-1) FC credit to financial market (t-1) ∆ Ln gross Gini ∆ Domestic credit to financial market ∆ Financial market (% GDP) GDP per capita growth Inflation Domestic credit to financial market (t-1) Financial market (% GDP) (t-1) Ln GNI per capita (t-1) Unemployment (t-1) Trade (% GDP) (t-1) Financial openness (t-1) Polity (t-1) Constant R 2 (within) F(10,65) Number of obs. Number of groups

∆ FC credit to domestic credit

∆ FC credit to financial market

(1)

(2)

−0.529** (0.245) −0.113 (0.070) −0.026 (0.031) −0.003 (0.012) −0.234 (0.183) 0.161* (0.084) −0.018 (0.037) 0.007 (0.015) 0.006 (0.011) −0.019 (0.127) −0.025 (0.027) 0.016 (0.014) 0.099 (0.074) −0.018 (0.097) 0.575 3.030*** 129 59

−0.406 (0.275) −0.086 (0.052) −0.004 (0.006) −0.173 (0.128) 0.077 (0.0619) 0.007 (0.011) 0.007 (0.006) −0.013 (0.092) −0.023 (0.020) 0.000 (0.008) 0.015 (0.044) −0.040 (0.053) 0.396 2.340** 129 59

*, ** and *** denote statistical significance at the 10%, 5% and 1% level, respectively. Standard errors in parentheses.

56  Financial cooperatives and income inequality explain the future changes in the share of cooperatives in the credit market. No other factor in the model here provides sufficient explanation for changes in the share of financial cooperatives in the total financial market, as indicated by Column 2.

3.5.  Concluding remarks This chapter examined the effect of the market share of financial cooperatives in the total domestic credit market and the total financial market (credit and capital markets) on income inequality. The main findings of the empirical analysis suggest that the growth of financial cooperatives’ share in the credit and financial markets may help in reducing income inequality, as there is a negative correlation between changes in the Gini coefficient and changes in financial cooperatives’ market share. The magnitude and level of the correlation varies at different stages of financial development, as changes in the market share of financial cooperatives has a stronger negative correlation with changes in income inequality when the financial sector is still relatively small, while the correlation is weaker in larger financial markets. Finally, the reverse regression tests cautiously suggest a one-­d irection causal correlation between the share of financial cooperatives in credit and financial markets and income distribution. The argument and findings are not surprising since increasing empirical evidence suggests that financial cooperatives are a key source of financing for small and medium enterprises, with a focus on simple and basic financial intermediation services, and hold a low volume of trading assets and less involvement in capital markets. All of which serves the real economy and the income of a large portion of the population, unlike large commercial banks. It is therefore important—­e specially for less developed economies—to advocate for and promote the creation and growth of well-­ functioning member-owned financial institutions rather than just pushing towards more financialization as an end by itself and not as a means for inclusive prosperity.

Bibliography Acemoglu, D., Naidu, S., Restrepo, P. and Robinson, J. A. (2015) ‘Democracy, redistribution and inequality’, in Atkinson, A. B. and Bourguignon, F., (eds.), ‘Handbook of Income Distribution’, vol. 2A, Amsterdam: North-Holland, pp. 1885–1967. Ang, J. B. (2010), ‘Finance and inequality: The case of India’, Southern Economic Journal, 76(3), 738–761. Batuo, M. E., Guidi, F. and Mlambo, K. (2012), ‘Financial Development and Income Inequality: Evidence from African Countries’, Tuins: African Development Bank. Beck, T., Demirgüç-Kunt, A. and Levine, R. (2007), ‘Finance, inequality and the poor’, Journal of Economic Growth, 12(1), 27–49. Bergh, A. and Nilsson, T. (2010), ‘Do liberalization and globalization increase income inequality?’, European Journal of Political Economy, 26(4), 488–505.

Financial cooperatives and income inequality  57 Ben Naceur, S. and Zhang, R. (2016), ‘Financial development, inequality and poverty: Some international evidence’, working paper no. 16/32. Washington, DC: International Monetary Fund. Bittencourt, M. (2010), ‘Financial development and inequality: Brazil 1985–1994’, Economic Change and Restructuring, 43(2), 113–130. Clarke, G., Xu, L. C. and Zou, H. (2006), ‘Finance and income inequality: What do the data tell us?’, Southern Economic Journal, 72(3), 578–596. Cojocaru, L. (2011), ‘Financial Development, Growth, Inequality and Poverty: Evidence from the Former Communist Countries’, Newark: University of Delaware. de Haan, J. and Sturm, J. E. (2017), ‘Finance and income inequality: A review and new evidence’, European Journal of Political Economy, article in press. Denk, O. and Cournède, B. (2015), ‘Finance and income inequality in OECD countries’, working paper no. 1224, Paris: OECD publishing. European Association of Cooperative Banks. (2015), ‘Key Statistics – Financial ­Indicators 2014’, www.eacb.coop/en/cooperative-banks/key-figures.html Gimeta, C. and Lagoarde-Segot, T. (2011), ‘A closer look at financial development and income distribution’, Journal of Banking & Finance, 35(7), 1698–1713. Hamori, S. and Hashiguchi, Y. (2012), ‘The effect of financial deepening on inequality: Some international evidence’, Journal of Asian Economics, 23(4), 353–359. Jalil, A. and Feridun, M. (2011), ‘Long-run relationship between income inequality and financial development in China’, Journal of the Asia Pacific Economy, 16(2), 202–214. Jauch, S. and Watzka, S. (2016), ‘Financial development and income inequality: A panel data approach’, Empirical Economics, 51(1), 291–314. Kappel, V. (2010), ‘The effects of financial development on income inequality and poverty’, working paper 10/127, Zurich: Centre of Economic Research at ETH. Kim, D. and Lin, S. (2011), ‘Nonlinearity in the financial development-income inequality nexus’, Journal of Comparative Economics, 39(3), 310–325. Li, H., Squire, L. and Zou, H. F. (1998), ‘Explaining international and intertemporal variations in income inequality’, The Economic Journal, 108(446), 26–43. Liu, G., Liu, Y. and Zhang, C. (2017), ‘Financial development, financial structure and income inequality in China’, The World Economy, 40(9), 1890–1917. Mookerjeea, R. and Kalipioni, P. (2010), ‘Availability of financial services and income inequality: The evidence from many countries’, Emerging Markets Review, 11(4), 404–408. Nikoloski, Z. (2013), ‘Financial sector development and inequality: Is there a financial Kuznets curve?’, Journal of International Development, 25(7), 897–911. Ostry, M. J. D., Berg, M. A., and Tsangarides, M. C. G. (2014), ‘Redistribution, ­Inequality, and Growth’, Washington, DC: International Monetary Fund. Panico, C., Pinto, A. and Anyul, M. P. (2012), ‘Income distribution and the size of the financial sector: A Sraffian analysis’, Cambridge Journal of Economics, 36(6), 1455–1477. Sehrawat, M. and Giri, A. K. (2015), ‘Financial development and income inequality in India: An application of ARDL approach’, International Journal of Social Economics, 42(1), 64–81. Seven, U. and Coskun, Y. (2016), ‘Does financial development reduce income ­i nequality and poverty? Evidence from emerging countries’, Emerging Markets Review, 26, 34–63.

58  Financial cooperatives and income inequality Shahbaz, M. and Islam, F. (2011), ‘Financial development and income inequality in Pakistan: An application of ARDL approach’, Journal of Economic Development, 36(1), 35. Shahbaz, M., Loganathan, N., Tiwari, A. K. and Sherafatian-Jahromi, R. (2015), ‘Financial development and income inequality: Is there any financial Kuznets curve in Iran?’, Social Indicators Research, 124(2), 357–382. Shahbaz, M., Bhattacharya, M., and Mahalik, M. K. (2017), ‘Finance and income inequality in Kazakhstan: Evidence since transition with policy suggestions’, ­Applied Economics, 49(52), 5337–5351. Solt, F. (2016), ‘The standardized world income inequality database’, Social Science Quarterly, 97(5), 1267–1281. Tan, H. B. and Law, S. H. (2012), ‘Nonlinear dynamics of the finance-inequality nexus in developing countries’, Journal of Economic Inequality, 10, 551–563. Wahid, A. N., Shahbaz, M., Shah, M. and Salahuddin, M. (2012), ‘Does financial sector development increase income inequality? Some econometric evidence from Bangladesh’, Indian Economic Review, 89–107. World Bank. (2014), ‘World Development Indicators’, Washington, DC: World Bank. World Bank. (2017), ‘Atlas of Sustainable Development Goals 2017: World Development Indicators’, Washington, DC: World Bank. World Council of Credit Unions. (2014), Statistical Reports. www.woccu.org/ our_network/statreport

4 Political economy theory for financial cooperative development1

4.1. Introduction There are several possible factors that can explain the evolution and performance of financial cooperatives in underdeveloped economies, including the economic structure, the degree of development of the financial sector, the legal framework that governs financial cooperatives’ activities as well as the cultural uniqueness of each country. Yet, since political institutions significantly influence all these factors—keeping in mind that the political structure itself is influenced by these factors as well—it is important to understand how they can dictate the development of financial cooperatives, and the motives behind the behaviour of these institutions. There is no political economy theory that explains how the behaviour of political institutions influences the development of the financial cooperative sector. This chapter proposes a theoretical analysis that can explain the behaviour of political institutions towards financial cooperatives. Political institutions can provide supportive or obstructive environment for financial cooperatives through legislations and other institutional arrangements. For instance, Bamrungwon (1994: 55–62) noticed that excessive control by the state is strongly maintained by regulations. This is clear from similarities in the cooperative laws of several developing countries, where regulations did not only emphasize statutory provisions (such as licensing, membership, governance structure, property protection, and equity structure) but also included several provisions concerning the authority of government officials over cooperatives. The remainder of the chapter is organized as follows: Section 4.2 highlights the political history of financial cooperatives. Section 4.3 proposes a political economy theory for financial cooperatives. Section 4.4 gives concluding remarks.

4.2.  Political history of financial cooperatives The early history of financial cooperatives cannot be detached from political history. The movement was founded by politicians, during a revolutionary

60  Political economy theory period in Germany in the mid-nineteenth century and was extremely exposed to government’s harassment at the beginning—as viewed with deep suspicion—and later with support. Inspired by the success of cooperative organizations in other sectors (especially consumer and workers cooperatives), three separate financial cooperative movements evolved in Germany. First, Hermann Schulze-Delitzch in the late 1840s followed by Friedrich Raiffeisen in the late 1850s and Wilham Haas in the 1860s. The three initiatives were indirect results for the failed revolution of 1848 (Guinnane, 2011: 80). Following the 1848 revolution, Germany saw several practical and non-direct political initiatives to support the rights of the working class. The first workers’ associations were created in 1848 (Spangenberg, 2015: 24), and the first credit cooperative was founded, approximately, two years later at Delitzsch in 1850 (Chisholm, 1911: 383). Almost all leaders of the early financial cooperative movement were politicians. Schulze-Delitzsch, who is widely considered as the founder of financial cooperatives, was a popular national liberal politician at his time. He was a lawyer and a judge and later became a member of the left liberal Progressive Party. He was also appointed for several German parliaments (Guinnane, 1995: 5; Prinz, 2002). Hans Crüger, Schulze-Delitzsch’s successor, was also a member of the Reichstag, the Prussian Landtag, and the city council of Charlottenburg. Wilham Haas was a senior official in the Hesse administration and later he joined the National Liberal Party. Haas was also a long-time member of the Landstände Grand Duchy of Hessen and became its president for nearly 13 years. And while Raiffeisen was never politically active, many leaders of the Raiffeisen cooperative movement held elective office at his time (Prinz, 2002; Guinnane, 2012: 10–11). Before the enactment of the 1868 Cooperatives Act for the North German Confederation, cooperatives did not have any legal framework that recognizes their functioning for nearly two decades. During the 1850s and 1860s, the Prussian government was suspicious about the increasing popularity of the cooperative movement and tried to oppress the early development of it. Schulze-Delitzsch was accused of sedition by the Prussian government and was dismissed from the Prussia’s Second Chamber in 1849 (Chisholm, 1911: 383). In law, sedition is a public behaviour—a speech or forming ­organization—that seeks to threaten the current established political order. Moreover, the government made use of the cooperatives’ lack of legal status and used the same law that prohibits political assembling to ban some of Schulze-Delitzsch cooperatives. Other cooperatives had to accept the presence of individuals whom they suspected to be undercover police agents (Guinnane, 2012: 20). But the political engagement of the movement’s pioneers was significant for its survival in that early stage; especially Schulze-Delitzsch’s influence which was crucial for the movement’s spread across Germany. In 1861, once again Schulze-Delitzsch became a member of the Prussian Chamber and was able to write and advocate for the first Prussian law of associations in

Political economy theory  61 1867. One year later, the law became adopted in the whole North G ­ erman Confederation, and Schulze-Delitzsch continued his contribution to promote and write cooperative legislations for almost all German states (Chisholm, 1911: 383). Schulze-Delitzsch’s cooperative law model was easily imitated and spread across Europe. His vision for a cooperative law was very practical, as it was developed from the by-laws and guidelines of already functioning credit cooperatives. The law respected the autonomy nature of cooperatives; allowing them to adjust their by-laws based on their needs, and recognized cooperatives as a special type of associations aim to serve the economic benefits of their members based on the principles of selfhelp, self-administration, and self-responsibility (Münkner, 2013: 6).

4.3.  A political economy theory of financial cooperatives The political economy theory of financial cooperatives established in this study is based on the origins and history of cooperatives in developing countries, alongside pressure groups theory and political economy theory of the financial sector. Both theories belong to traditional ‘new institutional economics’ that try to explain how economic behaviour is shaped by the evolution and behaviour of institutions. According to these theories, the government is not a neutral agent in the economy but is a prominent player who influences and benefits from the economic system. North (1990) and O ­ lson (1993) argue that those in power shape economic policies and institutions that enable them to stay in power and to enrich themselves. An autocratic political system will probably have a strong incentive to adopt an opportunistic behaviour that exploits the economy’s resources and outputs, in order to maximize the rents of the ruling elites and those who influence the political decision-making. Thus, the distribution of these economic resources and benefits will depend on the bargaining power of different groups in the economy (North, 1990: 49; 2005: 67; Olson, 1993: 569). But even though political institutions shape economic ones, the causality goes both directions. Property rights, contract enforcement, and opportunity distribution are designed and enforced by political institutions; however, the economic structure of a society also shapes its political structure (North, 1990: 48). Following the same line of reasoning, an underdeveloped financial cooperative movement may be the result of intentional policies by political decision-makers. In a political system dominated by narrow elite groups, political decision-makers may deliberately oppose the formation of other pressure groups that represent a broad range of people with strong bargaining power against the ruling elites, and who will have more control over their own resources, mainly their deposits in the case of financial cooperatives. That is because (1) an autocratic ruler and governing elites will prefer to control cooperatives to extend their popularity and their political influence, and with that, people’s sense of belonging and ownership of cooperatives will decrease, as well as their participation (Section 4.2.1); (2) well-organized

62  Political economy theory associations will have stronger political bargaining power against the ruler and the governing elites (Section 4.2.2); and (3) the economic benefits gained by the governing elites, from underdeveloped and exclusive financial system, will be threatened and diminished (Section 4.2.3). It must be acknowledged that the behaviour of autocrats towards financial cooperatives is not linear and is not identical amongst all non-democratic regimes. For instance, a stable autocrat, as a matter of ruling for a long-term period, will have the incentive to increase the overall productivity of the society in order for him, and the governing elite, to extract the maximum possible rent from the economy (Olson, 1993: 569). State control in this case will intend to encourage a minimum level of savings by the low-income class to secure enough finance for the higher income class to invest in projects with relatively high expected marginal return. Also, stable autocrats will try to guarantee a minimum level of return for low-income populations to avoid social dissatisfaction and political unrest. Thus, there will always be a minimum level of financial services provided to the lower income class, through cooperatives or any other institutions, even in the most oppressive and autocratic regimes. 4.3.1.  History of state control over cooperatives in developing countries The evolution of cooperatives in developing countries is strongly dependent on the colonial governments that implanted these institutions. Cooperatives did not intend to be independent self-help associations that emerge spontaneously, but rather to be instruments for colonial governments to implement their own economic policies (Cuevas and Fischer, 2006: 27; Münkner, 2013: 13). The organizational nature of cooperatives changed from instruments intended to create alternative contractual arrangements that govern the relation between the members and the market—and amongst the members themselves—into government instruments that transfer credit and subsidies to mass populations and follow state policies (Cuevas and Fischer, 2006: 28). Thus, in developing countries, what are sometimes labelled as ‘cooperative organizations’, are not really cooperatives (Birchall, 2004: 6). Fals-Borda et al. (1976: 442) describe how most post-independence governments in developing countries have adopted a compulsory cooperative strategy to force people, especially peasants, to become members in state-organized cooperatives. Forcing people to join cooperatives was made possible through three ways: ‘(1) direct compulsion and coercion, (2) the creation of a monopolistic situation in which the individual is deprived of certain economic benefits if he decided to stay out, and (3) the offering of inducements in the shape of prospective benefits’ (Fals-Borda et al., 1976: 442). They noted that in the 1960s, the ruling parties in Iran, Venezuela, and other Latin American countries strove to extend their political influence in order to spread their ideologies through their control over the cooperative movement. Cooperatives were organized by the State in order to secure the

Political economy theory  63 political support of peasants for the existing regimes. They also remarked that leaders of cooperative societies in Latin America and Africa were extremely over-controlled by government officials. Cooperative leaders ceased to be true representatives of the members, and instead, they carried out instructions from government officials and communicated them to the members and sometimes they were even members of the local administration or part of the political hierarchy. Cooperatives’ elections did not take place on a regular basis in many cases and some leaders were re-elected indefinitely (Fals-Borda et al., 1976: 440–441). Similarly, Gagnon (1976: 376) pointed out that, during the 1960s and 1970s, cooperatives in Cuba, Senegal, and Tunisia were not spontaneous grassroots movements but were rather organized and controlled by the states and political parties in power to spread their policies and ideologies. And whenever cooperatives ‘[…] had the opportunity to become social movements, to enter the political arena, and to threat the dominant classes, they were rapidly curtailed by the ruling powers […]’ Gagnon (1976: 376). The history of the cooperative movement in the former communist countries provides additional evident for that. In Russia, the once-autonomous consumer cooperatives were the main suppliers for basic goods to urban populations before the revolution of 1917. State control over cooperatives during the totalitarian regime that followed the revolution had abolished the movement’s autonomy and was nationalized by Stalin in 1935. Agricultural cooperatives that existed before the revolution were replaced by collective farms and were falsely named ‘cooperatives’. The same trend took place in many other so-called socialist countries, in which the number of cooperatives and their members immensely grew but without any real autonomy or member control (Birchall, 2004: 3, 16). Another interesting historical event was the dissolution of the Egyptian Confederation of Agricultural Cooperatives in 1976. The early founded cooperatives in Egypt were relatively independent from the state. However, the post-independence regime led by Nasser seized control of the cooperative movement and completely changed its nature to a state-controlled organization. When Sadat took office after Nasser in 1970, he chose one of his prot’eg’es, Ahmed Yunis, to be the president of the Confederation of ­Agricultural Cooperatives. However, Yunis tried to establish an independent movement that ‘[…] would not only fall outside the domain of state control, but which would challenge the government and demand a say in state policy making [sic] especially that related to agriculture’ (Fahmy, 2002: 208–209). In 1976, Yunis refused the governmental pressure on the confederation to support the ruling party in the parliamentary elections. He stated that the confederation should be politically neutral and non-partisan, and called for the confederation’s full independence from any government intervention. In return, the government led a publicity campaign against Yunis, accusing him of mismanagement and corruption (Fahmy, 2002: 210). Not long after, Sadat disbanded the confederation in 1976 under Law 824 and

64  Political economy theory transferred the functions of cooperatives to the state-owned Agricultural Bank. With the dissolution of the confederation, Sadat made sure that cooperatives could never be used to mobilize any opposition against his regime. The confederation remained dissolved until 1983, after Sadat’s assassination. The ruling party at that time won all the seats of the confederation council in its first elections (Fahmy, 2002: 211). In brief, as Develtere and Pollet (2008: 64–65) explained, governments can either maintain cooperatives’ autonomy and independence or they can take control over the sector. Government control can be ‘defensive’ or ‘instrumental’. A ‘defensive’ attitude is when a government attempts to keep tight control over all civil society activities for its own political interests. ‘Instrumental’ attitude on the other hand is when a government uses cooperatives as instruments to implement its economic development policy. 4.3.2.  Theories of pressure groups Olson (1965: 111–112) relates the development of pressure group theories to the rise of pluralism; a political philosophy that argues for a greater constitutional and political role for private associations of all types—­especially labour unions, churches and cooperatives—whilst the state should have limited control over these associations. ‘Pluralism tends to create a mood favourable to pressure groups primarily because it emphasizes the sponta­ lson neity, the liberty and the voluntary quality of the private association’ O (1965: 112). Politics can be affected by organized groups in two ways: directly, by lobbying to influence political decision-makers, and indirectly, by mobilizing voters or demonstrations. Modern pressure group theories emphasize the influence of pressures produced by different groups, as the fundamental determinant of economic structure and distribution of political power in a society (Becker, 1983; Bentley, 1995 [1908]; Commons, 1950; Latham, 1952; Truman, 1958). Pressure group theories date back to the nineteenth and early twentieth centuries political philosophers, especially Alexis de Tocqueville (1805–59) and Pierre-Joseph Proudhon (1809–65). In the United States, Arthur Bentley (1870–1957) argued that conflicting group pressures are the key to understanding government policies. He shaped his argument in denying any significance to individual interests, stressing that the main effective forces in societies are groups’ interests and actions. Nevertheless, as no one group can represent all the members in a society; people will naturally tend to group together in associations, unions, cooperatives, and other representative associations that can protect their interests and increase their bargaining power. Bentley states that ‘all phenomena of government are phenomena of groups pressing one another, forming one another and pushing out new groups and group representatives’ (Bentley, 1908: 269). Following Bentley’s view, Earl Latham (1952) stressed the importance of studying groups’ interests as the primary force in economics and politics. For him, ‘the structure of society is associational’ (Latham, 1952: 17). Like

Political economy theory  65 Bentley and Latham, David Truman (1958: 33–35) pointed out that there are inevitable disturbances and dislocations from economic institutions that will naturally lead to the formation of occupational associations like workers and farmers associations, in order to influence government policies. Commons (1950: 30) had strongly supported the formation of economic pressure groups, arguing these groups, such as cooperatives, labour unions and farmers’ associations, were the most dynamic institutions and ‘the lifeblood of democracy’ (Olson, 1965: 116). Commons promoted occupational pressure groups as the ideal representative and beneficial actors in economic policies. He based his argument on the view that market mechanisms alone cannot bring fair outcomes for all groups in the economy, and the reason behind that is the unequal bargaining power that different groups possess. Such inequalities in bargaining power will exist as long as the wealthy group dominates political institutions, and thus, pressure groups are essential in Commons’ argument to achieve a just and rational economic system ­(Olson, 1965: 115). The most relevant part for the argument here is Commons’ opinion on the United States Bill of Rights. For him, the Bill is important not only because it guarantees freedom of speech, press, and investigation, but most importantly, that it protects the rights of association. He further explains how the totalitarian authorities of Russian Communism and Italian Fascism after the First World War weakened labour unions and cooperative movements. As Commons puts it, ‘the civil liberties that make possible the voluntary associations of labour unions, farmers unions, business cooperatives, and political parties … [is] the refugee of modern Liberalism and Democracy from Communism, Fascism, or Banker Capitalism’ (Commons, 1990: 901–903). Mancur Olson (1965) in the Logic of Collective Action pointed out that all large well-organized economic groups that have significant lobbying power were originally organized for another non-political purpose in the first place. He noted that, ‘[…] the common characteristic which distinguishes all of the large economic groups with significant lobbying organizations is that these groups are also organized for some other purpose’ (Olson, 1965: 132). Olson recognized that most of group formation costs are start-up costs, and once a group has been organized, the costs associated with engaging in political actions become relatively low. Political actions, such as lobbying to influence the political and economic policies, become natural by-products of the group with relatively low-costs, since the costs of group formation has already been mobilized. Labour unions, farmers cooperatives, and all large economic organizations that were able to create influential lobbies initially had ‘the capacity to mobilize a latent group with selective incentives’, in ­order to overcome the collective-action problem (Olson, 1965: 132). Financial cooperatives can easily overcome the ‘collective-action problem’ of group organizing identified by Olson, due to their ability to provide ‘selective incentives’. According to Olson, organizations that can provide ‘selective incentives’ are those that (1) have the ability to be coercive or (2)

66  Political economy theory have the ability to provide positive incentives. Many independent and strong cooperative federations in developing countries had succeeded in influencing the policies and legislations regulating the operations of their affiliates, for example, ANGKASA, Malaysia; SNCF, Singapore and URECOCI, Cote d’Ivoire (International Labour Office, 2001: 63). Similarly, the Kenya Union of Savings and Credit Cooperatives (KUSCCO) had recently opposed the retrenchment policies in Kenya, mainly because many public sector employees are members in Savings and Credit Cooperative Societies (SACCOs). KUSCCO also advocated against the taxation of SACCOs (Owen, 2007: 18), and it was behind the enactment of the SACCO Act in 2008 (Wanyama, 2008: 91). On the other hand, many autocratic governments in developing countries would naturally resist the development of such representative associations because of their potential political power. 4.3.3.  Political economy theories of financial development2 Political economy theories of financial development explain the distributional output of the financial sector and argue that political institutions shape the level of an economy’s financial development. Narrow political and industrial elites, who control political institutions, will use their influence and networks to have preferential access to finance, whilst ensuring other potential competitors’ accessibility to finance is reduced. However, democracy should limit the influence of narrow elite groups and redistribute political power to a wider range of people who would favour a well-functioning financial sector (Girma and Shortland, 2008: 568). The State’s position as a regulator, mediator of financial contracts, and as a borrower can derive its rules towards opportunistic behaviour. The State can default in loans, seize banks, assets or firms, or adopt exploitive regulatory control over the financial sector. It can also be unwilling to enforce contracts to benefit politically connected agents. Or as Haber and Perotti (2008: 7) explained: ‘the state can influence directly the allocation of credit; either by state banking or by allowing concentrated ownership over banks’. Rajan and Zingales (2003: 18–21) proposed an interest group theory of financial development where industrial and financial elites have a direct interest in opposing financial development. As they are small enough to organize (Olson, 1965), and have large economic weight, these elites can successfully influence political leadership to keep the financial sector underdeveloped. Large firms can finance new opportunities without the need for external capital, or can obtain finance by pledging their assets as collaterals. Thus, in underdeveloped financial system, they have positional rent in their markets resulting from their privileged access to capital. Additionally, even if new entrants can obtain capital, the narrow group of industrial and financial elites will still be able to capture most of the returns gained by these new entrants, through higher interest rates, since they own and control financial institutions. These rents will diminish or even disappear with financial development.

Political economy theory  67 An inclusive financial sector enhances competition as it facilitates the entry of new firms in previously concentrated industries and accordingly reduces the profits of politically connected firms and financial institutions. Improving disclosure rules and contract enforcement in the financial market will reduce the comparative advantage of agents’ collaterals and political connection and allows the entry of new agents to the industry. The same applies for incumbent financiers. With poor disclosure and enforcement, financing decisions are usually based on lender-borrower relationship. Thus, the financer’s main skill relies heavily on the previous connections with the borrowers and the influence of the financer over managers, shareholders, other lenders, and politicians rather than the ability to predict potentially successful investments. So that ‘financial development not only introduces competition, which destroys the financial institution’s rents and relationships it also destroys the financier’s human capital’ (Rajan and Zingales, 2003: 18–19). Direct-entry restrictions; like license barriers, land and other resources distribution, and financial underdevelopment can be used as complementary instruments. While politically connected firms can pose other direct-entry restrictions, financial underdevelopment remains more favourable, since direct-entry restrictions can be very costly and may be ineffective if innovation can create substitutes. In addition, those direct-restrictions are visible and easily identifiable leading to political dissatisfaction of the citizens, especially when goods and services are poor. Contrary to financial underdevelopment, which is less noticeable and can be shadowed under claims of protecting depositors or borrowers, as financial underdevelopment is a result of inaction by the State with barring low costs and less criticisms ­(Rajan and Zingales, 2003: 20). Rajan and Zingales (2003: 22) have also argued that economic openness, in term of trade and capital flows, will weaken the industrial and financial elites’ ability to resist financial development. That is because foreign trade increases competition and reduces domestic rents, putting pressure on industrial elites. Similarly, cross-border capital flow will reduce the financiers’ oligopolistic position if domestic corporates can have access to cheaper finance. However, that does not provide a clear explanation to the behaviour of political institutions towards financial development, especially that economic openness is argued to be a political choice in itself (Perotti, 2014: 17). Barth et al. (2006: 278–286) proposed a social conflict view of bank supervision and regulation that explains why some countries may intentionally choose inefficient banking regulatory and supervisory policies that produces inefficient outcomes. The social conflict view argues that financial regulatory and supervisory policies are not chosen by the entire society or for the benefit of the whole society. The state is more concerned about distribution and not efficiency, and the ruling group does not seek to maximize the total social welfare but rather to maximize its own. In closed autocratic regimes, financial regulations then will be chosen by those in power for the benefit of a narrow politically influential group, whereas a more open and democratic political system may reduce the power

68  Political economy theory and benefits of such narrow elites. However, democracy will not totally eliminate their influence. Inefficient banking policies are also favoured by autocratic regimes because they can protect the interests of elites by limiting other groups’ economic and political potentials. Girma and Shortland (2008: 570–571) explained how in underdeveloped financial systems, access to capital will be associated with connections or wealth. The allocation of credit will depend on borrowers’ collaterals, social position, and political connections, whilst a well-developed financial system allows firms and individuals to obtain credit upon the feasibility of their economic activities and needs. Therefore, the government and elite groups will tend to determine the level of financial development based on the costs of increased competition incurred from easing the accessibility of credit. In political economy theory, the ‘equilibrium’ level of financial development is then determined by the relative power of financial development beneficiaries and adversaries. Also, when the financial sector is underdeveloped, small and rural households tend to keep a portion of their savings in the form of real assets (e.g. gold and jewellery). The other portion is mobilized in the hands of few large banks that refuse to provide credit to these small depositors afterwards. In both cases, these small communities and rural areas are confronted with an inefficient resources utilization problem, because local resources are rarely utilized in productive investments inside these local communities. Financial cooperatives are best able to mobilize local resources for the benefit of the local economy (Nienhaus, 1993: 18). Rajan and Zingales (2003) were the first to propose and provide empirical evidence that governments controlled by narrow elite groups obstruct the development of the financial sector. Similarly, Girma and Shortland (2004) also found a statistically significant relationship between the annual change in financial development and the degree of democracy and stability of the political system. Barth et al. (2006: 286–305) examined the relationship between political institutions and bank supervisory and regulatory frameworks. Their findings suggest that autocratic political regimes tend to have large state-owned banks and are more likely to impose regulatory restrictions on bank operations. They argued that autocratic regimes have large state-owned banks to easily channel financial resources towards the ruling elite and to control financiers by creating regulatory restrictions. There are empirical evidence that politically connected firms receive more favourable credit from State banks (Haber and Perotti, 2008: 28), as they are more likely to receive larger capital at the same interest rates similar to unconnected firms; however, they are more likely to default (Khwaja and Mian, 2005; Joh and Chiu, 2004; Faccio, 2006). And many studies found that politically connected firms tend to have higher debt to equity ratio (Cull and Xu 2005, Khwaja and Miang 2005; Faccio, 2010). La Porta et al. (2002) suggests that government ownership of banks is correlated with financial underdevelopment and lower growth rates. Briefly, a banking system dominated only by state-owned or private commercial banks, investment and lending decisions lie in the hands of the

Political economy theory  69 government and banks’ large shareholders. Thus, the allocation and use of depositors’ money will not be controlled by the depositors themselves, who are the real owners of the money; instead, it will be in the hands of a narrow elite group that is formulated by large capitalists and that can influence political decision-makers. As a result, an independent financial cooperative sector that can mobilize local resources for the benefit of the mass population will not be favoured by autocratic political decision-makers, as cooperatives would limit the exploitation capacity of the government and narrow elite groups.

4.4.  Concluding remarks I tried here to explain how political institutions can influence the trend of development of financial cooperatives, arguing that autocratic regimes may deliberately oppose the existence of a strong financial cooperative sector. Certainly, there is no single factor that can explain the evolutionary development of financial cooperatives, as they do not operate in isolation. Like any other economic institutions, financial cooperatives are the product of the surrounding economic structure, and get influenced by the performance of the whole financial sector, and the presence of supportive legal framework, as well as the historical and cultural uniqueness of each country. All these factors are of no less importance for the development of financial cooperatives and should be empirically explored in future research. However, political institutions and those who possess large political power have a strong incentive to influence all these factors, and the results presented in this study suggest that political institutions are major determinant for the development of financial cooperatives. In the current phase of financial capitalism, and the legitimate growing concern about unequal wealth distribution, it is important to establish well-functioning financial sector that serves the interests of the masses and not just few large shareholders or narrow governing elites, and that the financial sector is efficiently able to reallocate people’s deposits in value-added investments that serve the real economy and the whole society. Thus, it is important to recognize the political and economic potentials of financial cooperatives, as independent members-owned financial intermediary institutions that represent the interests of the low- and middle-income populations and that can help in redistributing economic resources and political power in societies. In many developing countries, small households and rural populations are confronted with a problem of inefficient resources utilization, especially their savings. As large portion of people’s savings are transferred to larger banks outside the local community; financial cooperatives are best able to mobilize these resources for the benefit of the local economy and are also able to attract external funds; otherwise, these resources are rarely utilized in productive investments inside these communities. There is a common concern over the politicization of the cooperative movement coming from historical practices, although it is clear that

70  Political economy theory the cooperative movement can hardly be isolated from politics. The focus should rather be on making sure that cooperatives do not become controlled by the government or absorbed by political parties, nor narrow elites that do not seek the benefits of the members and the society. But a political role for financial cooperatives is merely inevitable. Financial cooperatives are not only financial intermediaries; they are also civil society organizations, with a main objective of realizing the social and economic interests of their members. By protecting and advocating for their members’ interests, they can become representing and defending the interests of particular groups in the society, usually the low- and middle-income classes, and who are rarely represented by any political or economic groups in most developing countries. Financial cooperatives can also act as ‘schools of democracy’. Democratic participation by citizens in the public sphere does not only imply voting in elections or enrolment in political parties. Citizens’ participation can also take the form of joining pressure or advocacy groups, federations or unions, or any other means that enable them to express their voices and pursue their interests.

Notes 1 This chapter is largely based on the following publication: Khafagy, A. (2017). Political institutions and financial cooperative development, Journal of Institutional Economics, 13(2), 467–498. ‘Reprinted with permission’. 2 For a comprehensive overview on theories of political economy of finance, see Pagano and Volpin (2001) and Perotti (2014).

Bibliography Bamrungwon, C. (1994), ‘State Control over Cooperatives in Co-operative Legislation’, Background Paper No. 2a in The Relationship between the State and Cooperatives in Cooperative Legislation, Geneva: International Labour Organisation, pp. 55–63. Barth, J. R., Caprio, G. and Levine, R. (2006), ‘Rethinking Bank Regulation: Till Angels Govern’, Cambridge: Cambridge University Press, pp. 278–305. Becker, G. S. (1983), ‘A theory of competition among pressure groups for political influence’, The Quarterly Journal of Economics, 98(3), 371–400. Bentley, A. (1995), ‘The process of government: a study of social pressures’, The University of Chicago Press, p. 269, originally published in 1908. Birchall, J. (2004), ‘Cooperatives and the Millennium Development Goals’, Geneva: International Labour Office. Chisholm, H. (1911), ‘Schulze-Delitzsch, Franz Hermann’, Encyclopædia Britannica. 24 (11th ed.). Cambridge University Press. p. 383. Commons, J. R. (1950), ‘The Economics of Collective Action’, New York: Macmillan. Commons, J. R. (1990), ‘Institutional Economics: Its Place in Political Economy Vol.  II’, New Brunswick, NJ: Transaction Publishers. pp. 901–903, originally published in 1934. Cuevas, C. E. and Fischer, K. P. (2006), ‘Cooperative Financial Institutions: Issues in Governance, Regulation, and Supervision’, Washington, DC: World Bank.

Political economy theory  71 Cull, R. and Xu, L. C. (2005), ‘Institutions, ownership, and finance: the determinants of profit reinvestment among Chinese firms’, Journal of Financial Economics, 77(1), 117–146. Develtere, P. and Pollet, I (2008), ‘Renaissance of African cooperatives in the 21st Century: lessons from the field’, in Develtere, P., Pollet, I. and Wanyama, F. (eds.), ‘Cooperating Out of Poverty: The Renaissance of the African Cooperative Movement’, Geneva: International Labour Office, pp. 38–90. Faccio, M. (2010), ‘Differences between politically connected and nonconnected firms: a cross‐country analysis’, Financial Management, 39(3), 905–928. Fahmy, N. S. (2002), ‘The Politics of Egypt: State-Society Relationship’, Abingdon, OX: Routledge, pp. 208–211. Fals-Borda, O., Apthorpe, R. and Inayatullah (1976), ‘The Crisis of Rural Cooperatives: Problems in Africa, Asia, and Latin America’, in Nash, J., Dandler, J. and Hopkins, N. S. (eds.), ‘Popular Participation in Social Change: Cooperatives, Collectives, and Nationalized Industry’, The Hague: Mouton, pp. 439–456. Gagnon, G. (1976), ‘Cooperatives, participation, and development: three failures’, in Nash, J., Dandler, J. and Hopkins, N. S. (eds.), ‘Popular Participation in ­Social Change: Cooperatives, Collectives, and Nationalized Industry’, The Hague: ­Mouton, pp. 365–380. Girma, S. and Shortland, A. (2008), ‘The political economy of financial development’, Oxford Economic Papers, 60(4), 567–596. Guinnane, T. W. (1995), ‘Diversification, Liquidity, and Supervision for Small ­Financial Institutions: Nineteenth-Century German Credit Cooperatives’, ­Economic Growth Center, Yale University. Guinnane, T. W. (2011), ‘The early German credit cooperatives and microfinance organizations today: similarities and differences’, in Beatriz, A. and Marc, L. (eds.), The Handbook of Microfinance, Singapore: World scientific, pp. 77–100. Guinnane, T. W. (2012), ‘State support for the German cooperative movement, 1860–1914’, Central European History, 45(2), 208–232. Haber, S. and Perotti, E. (2008), ‘The political economy of financial systems’, ­Tinbergen Institute Discussion Paper no. 08–045/2. International Labour Office. (2001), ‘Report V (1): Promotion of cooperatives, 89th Session’, Geneva. Joh, S. W. and Chiu, M. M. (2004), ‘Loans to distressed firms: political connections, related lending, business group affiliation and bank governance’, In Econometric Society 2004 Far Eastern Meetings (No. 790). Econometric Society. Khwaja, A. I. and Mian, A. (2005), ‘Do lenders favor politically connected firms? Rent provision in an emerging financial market’, The Quarterly Journal of Economics, 120(4), 1371–1411. La Porta, R., López de Silanes, F., Shleifer, A. and Vishny, R. (2002), ‘The regulation of entry’, Quarterly Journal of Economics, 117(1), 1–37. Latham, E. (1952), ‘The Group Basis of Politics’, New York: Cornel University Press, pp. 10–17. Münkner, H. H. (2013), ‘Worldwide Regulation of Co-operative Societies – An Overview’, Euricse Working Paper n. 53|13. Nienhaus, V. (1993), ‘The Political economy of development finance’, Managerial Finance, 19(7), 8–20. North, D. C. (1990), ‘Institutions, Institutional Change and Economic Performance’, Cambridge: Cambridge University Press.

72  Political economy theory North, D. C. (2005), ‘Understanding the Process of Economic Change,’ Princeton: Princeton University Press. Olson, M. (1965), ‘The Logic of Collective Action’, Cambridge, MA: Harvard University Press. Olson, M. (1993), ‘Dictatorship, democracy and development’, American Political Science Review, 87, 567–576. Owen, G. R. (2007), ‘Rural Outreach and Financial Cooperatives: SACCOs in Kenya’, Agriculture and Rural Development Department, Washington DC: World Bank. Pagano, M. and Volpin, P. (2001), ‘The political economy of finance’, Oxford Review of Economic Policy, 17(4), 502–519. Perotti, E. (2014), ‘The political economy of finance’, Capitalism and Society, 9(1), Article 1. Prinz, M. (2002), ‘German rural cooperatives, Friedrich-Wilhelm Raiffeisen and the organization of trust 1850–1914’, In XIII IEHA Congress Paper Buenos Aires, Session (Vol. 57). Rajan, R. G. and Zingales, L. (2003), ‘The great reversals: the politics of financial development in the twentieth century’ Journal of Financial Economics, 69(1), 5–50. Spangenberg, S. (2015), ‘Hermann Schulze-Delitzsch: the cooperative idea in G ­ erman liberal thought’, Global Journal of Human-Social Science Research, 15(1), version 1, 23–33. Truman, D. B. (1958), ‘The Governmental Process. Political Interests and Public Opinion’, New York: Alfred A. Knopf, pp. 33–35. Wanyama, O. (2008), ‘The qualitative and quantitative growth of the cooperative movement in Kenya’, in Develtere, P., Pollet, I. and Wanyama, F. (eds.), ‘Cooperating Out of Poverty: The Renaissance of the African Cooperative Movement’, Geneva: International Labour Office, pp. 91–127.

5 Political institutions and financial cooperative development Empirical evidence1

5.1. Introduction This chapter tries to empirically investigate why financial cooperatives grow in some emerging economies and not in other similar ones. It examines the validity of the political economy theory proposed in the previous chapter which argues that the quality of political institutions, in terms of the degree of openness and democracy, has influence on the development of the financial cooperative sector. The main argument here is that autocratic regimes may deliberately oppose the development of a well-functioning financial cooperative sector, whereas democracies are more willing to support the development of financial cooperatives. I do not argue that every country fits into this theory, but the argument comes from clear observable evidence that large financial cooperative sectors in many cases exist within democratic political systems. In 2014, the market share of cooperative banks in many European democracies was quite large, amounting to 62% of the domestic deposits in France, 36% in the Netherlands, 35% in Austria, 34% in Finland, 33% in Italy, 27% in Cyprus, and 21% in Germany (EACB, 2015). The argument is also derived from some examples where the growth of financial cooperatives in underdeveloped economies is associated with a relatively open political system and, to a large extent, guaranteed civil rights. The definition of ‘underdeveloped economies’ here is based on the International Monetary Fund’s (IMF) classification of ‘emerging and developing economies’ in the World Economic Outlook of 2012 (IMF, 2012: 181) (For a list of countries included in this study, see Table A4.1 in the appendix). In Latin America, where almost all countries in the region are democracies since the 1980s, the average penetration rate2 in 2014 was 21.6% and the average assets per GDP was 2.6%, with Jamaica, Ecuador, and Costa Rica, have impressively high penetration rates of 76%, 63%, and 23%, respectively, and assets per GDP of 8%, 5.2%, and 7.4% (WOCCU, 2014). Similarly, Benin and Senegal are amongst the most stable democracies in West Africa and had the highest members’ penetration rate in Africa by the end of 2014 and noticeably high deposits per GDP compared to their counterparts in the region. For the last 20 years, Benin was ranked as free

74  Political institutions and financial cooperative development by Freedom House and Senegal as free or partly free. On the other side of the continent, the total assets of Kenyan financial cooperatives were 8.3% of its GDP in 2014, one of the highest in developing countries, with 29% members’ penetration rate. Kenya had implemented several s­ ocial and political reforms in the last decade, including the adoption of a new Cooperative ­Societies Act in 2004, a new financial cooperative law in 2008 and a new Constitution in 2010. Kenya is ranked as partly free by Freedom House since 2002, following the national elections that witnessed the change in political leadership and parliamentary majority (Freedom House, 2015). Relatively low penetration rates and deposits per GDP can be noticed in other African countries like Ethiopia and Zimbabwe, where rights of associations remain tightly restricted and financial cooperatives are regulated under outdated and insufficient regulatory frameworks. Zimbabwe and Ethiopia ranked 44 and 46, respectively out of 53 countries in the ‘Rights sub-category’ of Ibrahim Index of African Governance 2015 (Mo Ibrahim Foundation, 2015). A similar comparison can be found in Southeast Asia, where penetration rates and assets per GDP are high in India, the Philippines and Thailand. India and the Philippians are electoral democracies that have vibrant civil societies, and are classified as free or partly free by Freedom House for the last 20 years. Thailand, according to Freedom House measurements, the political environment persisted in the last three decades—until 2014—gave citizens opportunities to actively participate in the political sphere and provided legal protection for their civil rights. Thailand ranked as free or partly free from 1979 till 2006, following a military coup in 2006 that overthrew the democratically elected prime minister at that time. But the country was ranked as partly free again in 2008 after democratic elections were held in 2007. On the other hand, low penetration rates and assets per GDP can be observed in two of the severely autocratic political regimes in the region, Cambodia and Laos. Both countries are non-electoral democracies and are classified as not free by Freedom House for the last 20 years. Civil societies’ activities are extremely restricted, as freedoms of assembly and of association, as well as other human rights, are not respected. This chapter presents the econometric analysis for a panel data of 65 underdeveloped economies covering the period from 1995 to 2014, to test the correlation between indicators of democracy, political rights, and civil liberties against variables representing the degree of financial cooperatives development. Countries covered in the study are those with total population greater than 500,000 per country and are classified as ‘emerging and developing economies’ by the IMF’s World Economic Outlook of 2012 (IMF, 2012: 181). The remainder of the chapter is organized as follows: Section 5.2 defines the data used and the methodology adopted. Results are presented and interpreted in Section 5.3. Section 5.4 serves as a conclusion.

Political institutions and financial cooperative development  75

5.2.  Data and method 5.2.1.  Measuring financial cooperatives development The development of the whole financial sector is usually measured using indicators covering the sector’s size, depth, efficiency, and stability (Beck et al., 1999). However, statistics on financial cooperatives that cover all these indicators are not available in most countries. The variables used here to measure financial cooperatives development can only reflect the sector’s size and depth but do not give insight on the level of efficiency or stability of the sector. Financial cooperatives’ data were obtained from the World Council of Credit Union’s (WOCCU) statistical reports, which are based on financial cooperatives responses to the WOCCU’s annual survey, and are the most comprehensive dataset available for financial cooperatives. Only for India, additional data were collected from the National Federation of State Cooperative Banks regarding primary agricultural credit societies, which are not covered by the WOCCU dataset. Three indicators are used as dependent variables that can define the degree of development in the financial cooperative sector. First variable is member penetration rate, which is calculated as the country’s total number of financial cooperatives’ members as percentage of the total economically active population (obtained from International Labour Organization—ILO). The penetration rate shows the proportion of citizens who are members in financial cooperatives. This variable can reflect the financial cooperatives’ ability to attract and organize people. Second and third variables are total assets per GDP and total deposits per GDP. Both variables show the sector’s size in the national economy. The three variables were log transformed to normalize data distribution. Assuming here that, high penetration rate, total assets per GDP, and total deposits per GDP reflect a well-developed financial cooperative sector in a country. 5.2.2.  Measuring the quality of political institutions Finding reliable measurements for the quality of political institutions is challenging, mostly because the meaning of democracy has been a controversial issue in political science (Acemoglu and Robinson, 2005: 48). Three measurements for political institutions are used here: Freedom House’s political rights and civil liberties indices, and Polity index from the Polity IV Project. The Freedom House’s political rights and civil liberties indices have been previously used for studying trends in democracy by various scholars including Barro (1999: 160–162) as well as Acemoglu and ­Robinson (2005: 48–63) who only used the political rights index. Originally, both indices range from 1 to 7, in which 7 represents the least political ­freedom—in terms of political rights and civil liberties—and 1 represents the freest. However, the values of both indices were reversed so

76  Political institutions and financial cooperative development that 1 becomes the lowest score in political rights and civil liberties score and 7 represents the highest score. The Polity index was also used by Acemoglu and Robinson (2005: 48–63), and it ranges from +10 to −10, in which +10 represents strongly democratic institutions and −10 represents strongly autocratic ones. The Polity index is computed by subtracting the democracy and autocracy indices of the Polity IV project. Both, the democracy and autocracy indices range from 0 to 10. (Marshall et al., 2014: 14–16). 5.2.3. Methodology The relationships between financial cooperatives’ indicators and indicators of democracy, political rights, and civil liberties are examined using unbalanced panel regressions covering the period from 1995 to 2014 for 65 underdeveloped economies. A list of countries included in the analysis is reported in the appendices. The dependent variables in this analysis are the logarithm of variables used as indication for the development of the financial cooperative sector. Specifically, they represent log(penetration rate), log(deposits per GDP), and log(assets per GDP). The explanatory variables are Polity index, political rights index, and civil liberties index, in addition to a set of variables to control for annual economic growth rate, GDP per capita, unemployment rate, percentage of people living in urban areas (urban population), domestic credit provided to private sector by banks as percentage of the GDP, financial freedom, property rights and geographic region. ­Tables 5.1 and 5.2 provide a brief description on the variables included in the model. In the two-stage instrumental variable regression, democracy, political rights, and civil liberties indices are instrumented by the World Bank’s ‘political stability and absence of violence’ and ‘government effectiveness’ indices. It is not an easy task to find valid instruments for political indicators, as Treisman (2007: 236) pointed out that researchers have not found any consistent instruments for political institutions; however, I attempted to instrument for democracy, political rights, and civil liberties indices using the World Bank’s political stability and government effectiveness indicators. The political stability and absence of violence indicator measures perceptions of the possibility that the government will be replaced by unconstitutional or violent actions, including politically driven violence that causes political unrest. The government effectiveness indicator measures perceptions of the quality of public and civil services, and the government’s ability to design and implement effective policies independently from political pressures, as well as the credibility of the state to commit to such policies (Kaufmann et al., 2009: 6). The relationship between democracy and political stability is highly controversial. Some scholars argue that a prerequisite for the existence of democratic institutions is to secure domestic safety and stability, whereas many political scientists claim that the causal mechanism

Description

Total deposits of financial cooperatives in a country as percentage of the Gross Domestic Product (GDP) at market prices. The variable was log transformed. Total assets of financial cooperatives in a country as percentage of the Gross Domestic Product (GDP) at market prices. The variable was log transformed.

Total deposits per GDP

Government effectiveness

Political stability and absence of violence

World Council of Credit Unions and International Labour Organization World Council of Credit Unions and World Bank Open Data

Source

Freedom House Measures the citizens’ ability to voluntarily participate in the political process, including the right to vote in transparent and legitimate elections to choose freely among different alternatives; the right to compete for public office; the right to voluntarily form and join political parties and associations; and to choose representatives who participate in the formation of public policies and are accountable to the people. Measures the protection of the right to organise and freedom of associations, as well as freedoms of expression and believe, and the protection of the overall personal freedom. Reflects the institutionalised political characteristics of a regime. Polity IV project

(Continued)

Measures perceptions of the possibility that the government will be replaced World Bank’s World by unconstitutional or violent actions, including politically driven violence Governance Indicators that causes political unrest. Measures perceptions of the quality of public and civil services, and the government’s ability to design and implement effective policies independently from political pressures, as well as the credibility of the state to commit to such policies.

Excluded instrumental variables

Polity

Civil liberties

Political rights

Political institutions variables (explanatory variables)

Total assets per GDP1

Total number of financial cooperatives’ members in a country as percentage of the total economically active population. The variable was log transformed to normalize data distribution.

Penetration rate

Financial cooperatives variables (dependent variables)

Variable

Table 5.1  Information on the data sources and variables used

Source

Calculated using the implicit deflator of the annual growth rate of the GDP that is a ratio of GDP in current local currency to GDP in constant local currency. Measures the degree to which private property rights are secured by clear and Index of Economic enforceable laws or not, and evaluates the independence and corruption Freedom released by the of the judiciary, as well as the ability of individuals and firms to enforce Heritage Foundation contracts. Measures the independence of the banking sector from government control and interference. A dummy variable that takes the value of (1) for African countries, (2) for Asian countries, (3) for European countries, and (4) for countries from Latin America and the Caribbean.

Annual percentage of Gross Domestic Product (GDP) growth rate at market World Bank Open Data prices. Calculated as the annual Gross Domestic Product (GDP) divided by midyear population of a country. Data are in constant 2005 U.S. dollars and were log transformed. Percentage of unemployed labour force that is available and willing to be employed. Percentage of a country’s population living in urban areas as defined by national statistical offices. Financial resources provided by depository institutions to the private sector that create a claim for repayment, as percentage of the Gross Domestic Product (GDP) at market prices.

Description

1 Missing data for total assets in West African countries (Benin, Burkina Faso, Cote d’Ivoire, Guinea Bissau, Mali, Niger, Senegal, and Togo) were calculated using average total assets to total deposits ratio from other available years of the same country. 2 Data for Uzbekistan were collected from the IMF country reports (No. 07/133; 08/235; and 13/278) and for Zimbabwe from the Central Bank, under domestic statistics (available at http://www.rbz.co.zw/assets/monthly-economic-data-from-2009-to-date.pdf).

Geographic region

Financial freedom

Property rights

Domestic credit provided to private sector by banks as percentage of GDP2 Inflation rate

Urban population

Unemployment rate

GDP per capita

Annual GDP growth rate

Control variables

Variable

Political institutions and financial cooperative development  79 Table 5.2  Data description Variable

Mean

Standard Deviation

Min

Max

Obs.

Log penetration rate Log deposits per GDP Log assets per GDP Political rights Civil liberties Polity Annual GDP growth rate GDP per capita Unemployment rate Urban population Credit provided to private sector by banks as percentage of GDP Inflation rate Property rights Financial freedom Political stability and absence of violence Government effectiveness

–1.505 –2.643 –2.460 4.612 4.545 4.598 0.044 3.168 0.078 0.476 0.335

0.754 0.920 0.906 1.812 1.325 5.421 0.040 0.473 0.061 0.208 0.261

–4.471 –5.997 –5.706 1.000 1.000 –9.000 –0.177 2.104 0.001 0.098 0.014

–0.109 –0.924 –0.835 7.000 7.000 10.000 0.352 4.051 0.393 0.952 1.657

1108 1065 1035 1108 1108 1108 1107 1108 1108 1108 1108

0.095 0.408 0.483 –0.411

0.181 0.158 0.163 0.707

–0.270 0.050 0.100 –2.390

4.158 0.900 0.900 1.057

1108 1108 1108 921

–0.321

0.571

–1.585

1.278

921

is reversed. Many scholars argued that democratic systems are vulnerable to social discontent which may lead to social and political instability, while others suggested that democracies promote political stability through several mechanisms that absorb social dissatisfaction, settle political conflict and redistribute economic opportunities (Tusalem, 2015). Government effectiveness, on the other hand, is assumed to be correlated with democracy, in line with La porta et al. (1999: 239) who found democracy and political rights measurements to be correlated with low level of government intervention, more efficiency and better public goods provided. I do not argue here that there is an absolute one-way causal relationship between perceptions of political stability or government effectiveness and the quality of political institutions, rather what matters for the analysis is that political stability and government effectiveness should explain a considerable part of the variation in the democracy, political rights and civil liberties indices, and to be uncorrelated with financial cooperatives’ penetration rate, deposits per GDP and assets per GDP. Table 5.1 provides an overview over variables used.

5.3.  Results and discussion Table 5.3 shows pairwise correlation coefficients between indicators of financial cooperative development and political institutions and the IV. Generally, Table 5.3 gives preliminary support for the argument adopted here that financial cooperatives correlate with the governing political

80  Political institutions and financial cooperative development Table 5.3  Pairwise correlation coefficients among the dependent, explanatory, and instrumental variables Log Log penetration deposits rate per GDP

Log Political Civil assets per rights liberties GDP

Polity

Financial cooperatives against political institutions Political rights Civil liberties Polity N

0.233*** 0.306*** 0.261*** 1108

0.162*** 0.214*** 0.154*** 1065

0.161*** 0.218*** 0.157*** 1035

Instrumental variables against financial cooperatives and political institutions Political 0.089*** stability Government 0.071** effectiveness N 921

–0.005

–0.008

0.413*** 0.504*** 0.238***

–0.007

–0.014

0.571*** 0.600*** 0.467***

883

868

921

921

921

*, **, and *** indicate statistical significance at the 10%, 5%, and 1% level respectively.

institutions. Results indicate that penetration rate, deposits and assets per GDP are positively correlated with political rights, civil liberties and polity indices, significant at the 1% level, with higher correlation between financial cooperatives’ indicators and civil liberties. Deposits and assets per GDP are not significantly correlated with the IV; political stability and government effectiveness, whereas penetration rate are positively correlated with the IV significant at the 1% level and 5% level, respectively, the magnitude of the correlations is quite low which do not largely disturb the validity of the instruments. More importantly, political rights, civil liberties and polity indices are positively correlated with political stability and government effectiveness with relatively high correlation coefficient and significant at the 1% level. Tables 5.4 and 5.5 present the results of the FE OLS and the IV2SLS regressions. In these regressions, each of the three financial cooperatives’ indicators: penetration rate; deposits per GDP; and assets per GDP (all dependent variables are in natural logarithm), is regressed against variables representing indicators of political rights, degree of democracy, and civil liberties, in addition to a set of variables to control for economic growth, GDP per capita, inflation rate, unemployment rate, credit to private sector as percentage of the GDP, financial freedom, and property rights. Columns 1 to 9 in Table 5.4 show statistically significant positive correlations between the quality of political institutions and the degree of financial cooperatives development, with the magnitude of the coefficients increase considerably in the IV 2SLS regression compared to the FE OLS regressions, especially for the civil liberties regressions in Columns 2, 5, and 8. The R 2 (within) for the fixed-effects estimations ranged between 33.8% and 39.9%, whereas the

0.048* (0.029)

0.121** (0.057) –0.311 –0.244 (0.631) (0.593) 1.174* 0.887 (0.671) (0.690) –0.216° –0.195° (0.134) (0.124) 2.122° 2.238* (1.277) (1.276) 2.182* 2.367* (1.269) (1.238) 0.848*** 0.780*** (0.283) (0.271) 1.079*** 1.036*** (0.277) (0.277) –1.688*** –1.556*** (0.348) (0.336) –8.083*** –7.789*** (1.731) (1.729) 11.37*** 12.99*** 1064 1064 65 65 0.342 0.3615 –0.818 –0.806

0.207*** (0.070) 0.031** (0.014) –0.287 (0.626) 1.142° (0.695) –0.199 (0.140) 1.934° (1.222) 2.382* (1.337) 0.790*** (0.286) 1.171*** (0.273) –1.490*** (0.347) –7.875*** (1.790) 10.74*** 1064 65 0.3385 –0.825

(6)

0.188** (0.072)

(8)

–0.252 –0.200 (0.558) (0.530) 1.113* 0.856 (0.656) (0.680) –0.219° –0.206° (0.137) (0.127) 1.099 1.177 (1.174) (1.193) 2.557** 2.619** (1.149) (1.106) 0.768*** 0.718*** (0.268) (0.257) 0.938*** 0.903*** (0.290) (0.278) –1.650*** –1.601*** (0.344) (0.324) –7.649*** –7.395*** (1.698) (1.710) 12.96*** 15.53*** 1034 1034 65 65 0.3546 0.3774 –0.818 –0.803

0.069* (0.036)

(7)

Log assets per GDP

0.028** (0.013) –0.282 (0.559) 1.138* (0.666) –0.204 (0.144) 0.940 (1.132) 2.524** (1.175) 0.704** (0.269) 0.990*** (0.279) –1.473*** (0.316) –7.592*** (1.714) 13.89*** 1034 65 0.3576 –0.822

(9)

*, **, and *** indicate statistical significance at the 10%, 5%, and 1% level respectively. ° indicates significance between 10% and 15% level, while no asterisk means the coefficient is not statistically significantly different from zero. Robust standard errors are in parentheses. Huber-White sandwich robust estimator was used to control for the presence of heteroscedasticity and serial correlation in the panel data as determined by Breusch-Pagan/Cook-Weisberg and Lagram-Multiplier tests.

0.038*** (0.011) 0.545* (0.321) 1.169** (0.573) –0.092 (0.139) 0.766 (1.067) 1.109 (1.160) 0.701*** (0.229) 0.645** (0.250) –1.224*** (0.294) –6.031*** (1.491) 12.14*** 1107 65 0.3991 –0.785

0.095*** (0.034)

(5)

(4)

(3)

(1)

(2)

Log deposits per GDP

Log penetration rate

0.660** 0.687** (0.317) (0.312) Log GDP per capita 1.109* 0.958° (0.590) (0.599) Inflation rate –0.105 –0.095 (0.131) (0.127) Unemployment rate 0.965 1.031 (1.113) (1.126) Urban population 1.386 1.429 (1.239) (1.207) Credit to private 0.775*** 0.736*** (0.229) (0.222) sector Financial freedom 0.596** 0.563** (0.267) (0.261) Property rights –1.367*** –1.307*** (0.323) (0.310) Constant –5.978*** –5.852*** (1.539) (1.551) F–stat 10.2*** 11.04*** No. of obs. 1107 1107 No. of countries 65 65 R 2 (within) 0.3718 0.3851 Corr (μi , X) –0.778 –0.764

GDP growth rate

Polity

Civil liberties

Political rights

Dependent variable

Table 5.4  F  ixed-effects OLS regression results for financial cooperatives indicators against democracy, political rights, and civil liberties indices (underdeveloped economies 1995–2014)

F-stat R 2 (within) Corr (μi , X) Sargan-Hansen p-value

_cons

Unemployment rate Urban population Credit to private sector Financial freedom Property rights

Log GDP per capita Inflation rate

GDP growth rate

Polity

Civil liberties

Political rights

Dependent variable

0.508* (0.308) 1.312*** (0.215) 0.199* (0.104) 0.782 (0.686) 0.792° (0.544) 0.613*** (0.107) 0.540*** (0.119) –1.280*** (0.159) –6.628*** (0.639) 48.13*** 0.3326 –0.790 0.001

0.124*** (0.045)

(1)

0.556* (0.315) 0.952*** (0.228) 0.146 (0.112) 1.204° (0.755) 1.102** (0.528) 0.470*** (0.125) 0.432*** (0.134) –1.167*** (0.155) –6.831*** (0.681) 42.08*** 0.2211 –0.801 0.0139

0.392*** (0.105)

(2)

0.115*** (0.025) –0.146 (0.376) 1.605*** (0.246) 0.308*** (0.116) 0.513 (0.747) –0.103 (0.629) 0.346** (0.134) 0.611*** (0.123) –0.909*** (0.159) –7.144*** (0.696) 42.1*** 0.2065 –0.841 0.0904

(3)

Log penetration rate

0.117 (0.441) 1.246*** (0.313) –0.013 (0.149) 2.091** (0.989) 1.934** (0.789) 0.741*** (0.153) 1.102*** (0.171) –1.453*** (0.230) –8.20*** (0.929) 34.36*** 0.2882 –0.815 0.1147

0.079 (0.065)

(4)

0.146 (0.417) 1.012*** (0.304) –0.046 (0.148) 2.335** (0.997) 2.150*** (0.701) 0.652*** (0.165) 1.047*** (0.176) –1.369*** (0.204) –8.272*** (0.903) 35.04*** 0.2989 –0.817 0.1998

0.236* (0.138)

(5)

0.072** (0.034) –0.277 (0.504) 1.390*** (0.329) 0.047 (0.155) 1.815* (1.015) 1.443* (0.838) 0.572*** (0.180) 1.165*** (0.167) –1.219*** (0.214) –8.427*** (0.933) 33.21*** 0.2558 –0.834 0.4383

(6)

Log deposits per GDP

0.006 (0.397) 1.208*** (0.287) 0.086 (0.137) 1.416° (0.905) 2.256*** (0.702) 0.694*** (0.142) 0.923*** (0.156) –1.507*** (0.219) –8.112*** (0.855) 37.14*** 0.2974 –0.828 0.0102

0.122** (0.058)

(7)

0.077 (0.385) 0.808*** (0.295) 0.016 (0.140) 1.711* (0.926) 2.626*** (0.655) 0.562*** (0.153) 0.857*** (0.162) –1.446*** (0.201) –8.127*** (0.844) 36.6*** 0.2781 –0.830 0.0457

0.373*** (0.129)

(8)

Log assets per GDP

0.095*** (0.028) –0.482 (0.455) 1.440*** (0.314) 0.173 (0.147) 1.076 (0.952) 1.562** (0.777) 0.465*** (0.166) 1.00*** (0.160) –1.125*** (0.206) –8.472*** (0.894) 34.33*** 0.2213 –0.848 0.2321

(9)

Table 5.5  F  ixed-effects IV 2SLS regression results for financial cooperatives indicators against democracy, political rights, and civil liberties indices (underdeveloped economies 1995–2014)

(2)

(1) 1.329*** (0.198) –1.228*** (0.411) 7.883*** (1.745) –3.506** (1.376) –0.783 (0.638) 4.405 (4.233) 13.825*** (3.015) 2.254*** (0.658) 0.381 (0.696) –2.069** (0.906) 8.538*** (4.01) 11.52*** 0.1199 921 65

(3) 0.672*** (0.072) 0.299** (0.151) 2.223*** (0.631) –2.417*** (0.501) –0.039 (0.230) 0.517 (1.533) 7.219*** (1.091) 0.275 (0.237) 0.72*** (0.253) 0.880*** (0.329) 8.282*** (1.465) 17.63*** 0.1791 883 65

(4)

Political rights

0.333*** (0.05) –0.044 (0.105) 0.572 (0.438) 0.277 (0.348) 0.156 (0.159) –0.60 (1.064) 1.459* (0.757) 0.429*** (0.164) 0.498*** (0.175) –0.076 (0.228) 2.783*** (1.017) 10.23*** 0.1124 883 65

(5) 1.348*** (0.202) –1.215*** (0.426) 7.70*** (1.774) –3.193** (1.41) –0.673 (0.646) 6.034 (4.311) 13.533*** (3.068) 2.293*** (0.666) 0.156 (0.711) –2.00*** (0.925) 7.688*** (4.121) 11.04*** 0.1202 883 65

(6)

Civil liberties Polity

Log deposits per GDP

0.714*** (0.071) 0.156 (0.148) 2.00*** (0.613) –1.983*** (0.502) 0.019 (0.225) 0.551 (1.496) 6.268*** (1.080) 0.119 (0.235) 0.572** (0.251) 1.119*** (0.327) 7.384*** (1.466) 18.46*** 0.1888 868 65

(7)

Political rights

0.338*** (0.049) –0.134 (0.103) 0.411 (0.428) 0.602* (0.350) 0.222 (0.157) –0.331 (1.043) 0.946 (0.753) 0.337** (0.164) 0.381** (0.175) 0.206 (0.228) 1.922*** (1.022) 10.04*** 0.1124 868 65

(8)

Civil liberties

Log assets per GDP

1.511*** (0.202) –1.634*** (0.423) 7.408*** (1.750) –2.89** (1.432) –0.694 (0.643) 6.071 (4.268) 13.55*** (3.082) 2.062*** (0.671) 0.092 (0.715) –2.15*** (0.934) 6.887* (4.182) 12.48*** 0.136 868 65

(9)

Polity

*, **, and *** indicate statistical significance at the 10%, 5%, and 1% level, respectively. ° indicates significance between 10% and 15% level, while no asterisk means the coefficient is not statistically significantly different from zero. Standard errors are in parentheses.

0.331*** (0.049) –0.079 (0.101) 0.545 (0.428) 0.316 (0.337) 0.159 (0.156) –0.668 (1.037) 1.341* (0.738) 0.404** (0.161) 0.533*** (0.171) –0.036 (0.222) 2.681*** (0.982) 10.62*** 0.1115 921 65

Civil liberties

Political rights

0.673*** (0.07) Government 0.284* (0.145) effectiveness GDP growth rate 2.280*** (0.618) Log GDP per –2.309*** (0.487) capita Inflation rate –0.021 (0.226) Unemployment 0.310 (1.499) rate Urban 7.050*** (1.067) population Credit to private 0.260 (0.233) sector Financial 0.750*** (0.247) freedom Property rights 0.872*** (0.321) _cons 8.005*** (1.420) F-stat 18.35*** R 2 (within) 0.1783 No. of obs. 921 No. of countries 65

Political stability

Dependent variable

Polity

Log penetration rate

First stage least squares regression

Dependent variable

84  Political institutions and financial cooperative development R 2 (within) for IV 2SLS estimations varied between 21% and 33%. These results support the political economy theory developed earlier in this study, which argues that representative and open political institutions tend to have well-functioning financial cooperative sector, represented by high penetration rates, deposits and assets per GDP, whilst autocratic political regimes, on the other hand, are more likely to oppose the development of financial cooperatives. The high magnitude of the civil liberties’ coefficients and their statistical significance in all regressions, compared to political rights and polity coefficients, suggest that underdeveloped financial cooperative movements are likely to be associated with the oppression of civil societies in general, suggesting that non-democratic regimes may perceive financial cooperatives as potential pressure groups that may threaten the current status quo. Countries scoring the lowest rate in the civil liberties index have limited or no freedom of association, that include legal or practical constraints on trade unions, peasant organizations, civic organizations, and interest groups. As for the control variables, the fixed-effects OLS and IV 2SLS regressions in Tables 5.4 and 5.5 show a statistically significant positive correlation between financial cooperatives development and financial freedom index that provides additional support to my hypothesis that strict government control over the allocation of credit and the quality of financial regulations play important role in the development of financial cooperatives. The financial freedom index measures the degree of financial sector independence from government control and interference. Specifically, the index measures the quality of financial regulations (which should be limited to enforcing contractual obligations and controlling market failures), direct and indirect intervention by the state in financial institutions, financial and capital market development, openness to foreign competition and government’s control over the allocation of credit. The results also show statistically significant negative correlation between property rights and financial cooperatives development, in the fixed-effects OLS and IV 2SLS regressions, in Tables 5.4 and 5.5. These results are inconsistent with the law and finance theory, and contradict the broader consensus in favour of property rights protection as a key institutional requirement for financial development, investment, and economic growth. The common argument in favour of property rights on assets and returns is that secure property rights encourages individuals and firms to better allocate their resources and gives incentives for savers to invest in the banking sector and the financial market as a result of increased confidence in legal institutions (Beck and Levine, 2008: 251). Claessens and Laeven (2003: 2401–2402) found that better property rights lead to higher economic growth, and that the impact on growth is higher with improved access to finance, using the same property rights indicator

Political institutions and financial cooperative development  85 obtained from the Heritage Foundation’s Economic Freedom Index. However, the negative correlation between the growth of financial cooperatives and protection of property rights found here is not as odd as it seems. The property rights index measures the degree to which private property rights are protected by clear laws that are efficiently enforced by the state; thus, legal protection over property rights are primarily benefiting those who already possess ‘formal’ assets and therefore can obtain finance from commercial banks in the first place. Whereas members of financial cooperatives are usually part of the informal economy, and workers and self-employed individuals do not usually benefit from these property rights. Strict laws for property rights then may restrict the economic activities of the informal sector, imposing pressure on financial cooperatives’ members. The share of the informal sector to GDP varies from around 30% in Asia and Latin America to 64% in sub-Saharan Africa (Jütting and Laiglesia, 2009), and one-half to three-quarters of non-agricultural employment in developing countries is informal employment, a figure which would significantly increase if informal employment in agriculture is included (ILO, 2002: 5). In any case, there is a need for further theoretical and empirical investigation to understand the relationship between financial cooperatives and property rights. Furthermore, there is a positive correlation between financial cooperatives development and GDP per capita, with the statistical significance increases noticeably in the IV 2SLS regressions. The annual GDP growth rate was found to have a positive correlation with financial cooperatives’ penetration rate, but no statistical significance correlations were found between GDP growth and financial cooperatives’ deposits or assets per GDP. These results are, to a large extend, similar to Périlleux et al. (2016) who only used penetration rate and number of cooperative institutions as indicators for the development of financial cooperatives. However, contrary to Périlleux et al. (2016), domestic credit provided by banks per GDP here is positively correlated with the three financial cooperatives’ indicators, suggesting that there is a strong likelihood that financial sector development is positively correlated with the development of financial cooperatives. Taking into account that Périlleux et al. (2016: 121–122) had reported a slightly small R2 for the penetration rate regressions (0.01 for fixed-effects, 0.04 for random-effects, and 0.1 for IV 2SLS). In addition, unemployment rate was found positively correlated only with financial cooperatives’ deposits per GDP using IV 2SLS regression, whereas the fixed-effects results showed weak or no statistical significance at all. Finally, the percentage of population living in urban areas was found positively correlated with financial cooperatives’ deposits and assets per GDP, suggesting that probably financial cooperatives can mobilize more deposits in countries where urbanization is high, which would be a change in the traditional characteristics of financial cooperatives as they used to focus mainly on rural areas.

86  Political institutions and financial cooperative development

5.4. Conclusion This chapter sought to provide an empirical analysis for the influence of political institutions on the development of financial cooperatives through empirically examining the theory plotted in Chapter 4, which is autocratic regimes deliberately oppose the development of a well-functioning financial cooperative sector. The findings of supported the argument presented in the previous chapter, suggesting that countries with open political institutions tend to have a larger financial cooperative sector. Interestingly, civil liberties appear to be more correlated with financial cooperatives, compared to political rights, indicating that underdeveloped financial cooperative sectors are likely to be associated with the oppression of civil societies in general, suggesting that non-democratic regimes may perceive financial cooperatives as potential pressure groups that may threaten the current status quo.

Notes 1 This chapter is largely based on the following publication: Khafagy, A. (2017). Political institutions and financial cooperative development, Journal of Institutional Economics, 13(2), 467–498. ‘Reprinted with permission’. 2 Penetration rate is the total number of financial cooperatives’ members as percentage of total population above 15 years old, discussed more in Section 5.3.1.

Bibliography Acemoglu, D. and Robinson, J. A. (2005), ‘Economic Origins of Dictatorship and Democracy’, Cambridge: Cambridge University Press, pp. 48–63. Barro, J. (1999), ‘The determinants of democracy’, Journal of Political Economy, 107(S6), S158–S183. Beck, T., Demirgüç-Kunt, A. and Levine, R. (1999), ‘A new database on financial development and structure’, Policy Research Working Paper 2146, Washington, DC: World Bank. Beck, T. and Levine, R. (2008), ‘Legal institutions and financial development’, in Ménard, C. and Shirley, M. (eds.), ‘Handbook of New Institutional Economics’, Berlin/Heidelberg: Springer, pp. 251–278. Claessens, S. and Laeven, L. (2003), ‘Financial development, property rights, and growth’, The Journal of Finance, 58(6), 2401–2436. European Association of Cooperative Banks. (2015), ‘Key Statistics – Financial indicators 2014’. www.eacb.coop/en/cooperative-banks/key-figures.html Freedom House. (2015), ‘Freedom in the World 2015’, Washington, DC: Freedom House. International Labour Office. (2002), ‘The Informal Economy and Decent Work: A Policy Resource Guide’, Geneva: International Labour Office. International Monetary Fund. (2012), ‘World Economic Outlook: Growth Resuming, Dangers Remain’, Washington, DC: World Economic and Financial Surveys, p. 181. Jütting, J. and de Laiglesia, J. R. (eds.), (2009), ‘Is Informal Normal?: Towards more and Better Jobs in Developing Countries’, Paris: Development Centre of the ­ Organisation for Economic Co-operation and Development.

Political institutions and financial cooperative development  87 Kaufmann, D., Kraay, A. and Mastruzzi, M. (2011), ‘The worldwide governance indicators: Methodology and analytical issues’, Hague Journal on the Rule of Law, 3(2), 220–246. La Porta, R., Lopez-de-Silanes, F., Shleifer, A. and Vishny, R. (1999), ‘The quality of government’, Journal of Law, Economics, and Organization, 15(1), 222–279. Marshall, M., Gurr, T. and Jaggers, K. (2014), ‘Political Regime Characteristics and Transitions, 1800–2013’, Polity IV Project, Center for Systemic Peace. pp. 14–16. Mo Ibrahim Foundation. (2015), ‘Ibrahim Index of African Governance (database)’. Périlleux, A., Vanroose, A. and D’Espallier, B. (2016), ‘Are financial cooperatives crowded out by commercial banks in the process of financial sector development?’, Kyklos, 69(1), 108–134. Treisman, D. (2007), ‘What have we learned about the causes of corruption from ten years of cross-national empirical research?’, Annual Review of Political Science, 10, 211–244. Tusalem, R. F. (2015), ‘Democracies, autocracies, and political stability’, International Social Science Review (Online), 90(1), 0_1. World Bank. (2014), ‘World Development Indicators’, Washington, DC: World Bank. World Council of Credit Unions. (2014), ‘Statistical Reports’, Wisconsin: World Council of Credit Unions. www.woccu.org/our_network/statreport

6 The origin and rationale for financial cooperative regulation in underdeveloped economies

6.1. Introduction The financial crisis brought attention to the damaging consequences of rapid financial expansion without an adequate regulatory and supervisory environment, which could have drastic consequences that go beyond the financial sector threaten the stability of the whole economy. In most underdeveloped economies, non-bank financial institutions are the main providers of financial services to small businesses and middle- and low-income households. In some regions, financial cooperatives are the main providers of microfinance services. An enabling regulatory framework is essential to ensure the effectiveness and sustainability of financial cooperatives in providing the financial services needed by their members and to support the expansion of the sector. Particularly as the sector expands and becomes more complex, regulators must be responsive to ensure the stability of the sector and protect the interest of the members. This chapter reviews the origin of and rationale behind financial cooperative regulations. It complements the findings of Chapter 7 and is highly inspired by Cuevas and Fischer (2006). The chapter starts by giving a brief overview of the history of financial cooperative laws and the current approaches adopted to regulate the sector in underdeveloped economies. It then discusses the rationale behind regulating financial cooperatives differently from other financial institutions, given their unique institutional characteristics and the main challenges commonly faced by that sector. This chapter focuses on how regulations should maintain the autonomy of financial cooperatives and protect the sector from destructive government interference; how regulations can address agency problems inherited in their governance structure; and why regulations must support institutional integration between financial cooperatives themselves and facilitate the creation of second-tier cooperatives or federations. It also addresses the importance of capital requirements and the challenges these requirements impose on the growth of financial cooperatives. Finally, it discusses the suitability of deposit insurance schemes to protect members’ deposits. The key objective of financial regulation is to achieve overall economic efficiency, stability, and fairness through controlling market failures in the

Origin and rationale for financial cooperative regulation  89 financial sector caused by externalities, monopolies, and information problems (Vittas, 1992: 40). The key objective of financial regulations is to limit the power of monopolies that lead to serious market distortions. Financial regulations are important to avoid having an oligopolistic financial system controlled by a few ‘champions’ who are too big to fail but also very costly to safe, as was the case during the 2007–08 financial crisis. Financial regulations are also crucial to safeguard the interests and rights of ordinary people by protecting their deposits and to internalise the externality caused by the failure of an individual bank from spreading to other banks, thus mitigating the social and economic costs arising from the insufficient performance of an individual bank (Brunnermeier et al., 2009: 2–5). Vittas (1992: 41) identified six reasons for government intervention in the financial sector through regulation. First, to control the level of aggregate economic activity, and adjust major market imbalances using macroeconomic controls. Second, to redistribute financial resources among different sectors, geographic areas and social or economic classes, using targeted credit programs and subsidised interest rates, through allocative controls. Third, to shape the structure of the financial system by setting market entry requirements, regulating mergers and controlling the activities undertaken by different types of financial institutions through structural controls. Fourth, to maintain public trust in the financial system by guaranteeing the safety and soundness of individual banks through means of prudential controls like licensing criteria, capital requirements, and risk management standards. Fifth, to enforce disclosure of market information using organisational controls to ensure transparency and equality in financial transactions. Sixth, to protect consumers through protective controls, especially individual depositors and nonprofessional borrowers. Small primary financial cooperatives with few members are similar to a formalised type of rotating savings and credit associations (ROSCAs). They benefit from the strong social relations that exist among members of a small group to overcome information asymmetry problems and provide financial services to the members at lower operational costs. However, the comparative advantages of these social relations weaken as the number of members increase, and it becomes important to establish an adequate regulatory framework to organise and oversee their activities (Poyo, 2000: 140). Münkner (1986: 123) recommended that cooperative laws in general should be developed via a participatory law-making process. Cooperative representatives (second-tier cooperatives or federations) directly contribute, along with the legislator, to framing the cooperative legislation. There is a growing trend to regulate financial cooperatives with a specialised regulation, as by 2014, a specialised law regulates 40 out of 64 underdeveloped economies. That takes place in the form of a separate financial cooperative law or under a special or detailed provision in a non-specialised financial cooperative law. This chapter argues that specialised regulation is more suitable for financial cooperatives, rather than traditional bank or cooperative society

90  Origin and rationale for financial cooperative regulation regulations. Financial cooperatives have different economic objectives and ownership structures and are exposed to different risks and challenges, such as destructive government interference, low capital accumulation, access to liquidity facilities, net savers against net borrowers agency problems, and low compensation for managers. The rest of the essay is organised as follows: Section 6.2 presents a brief overview of the historical origins of financial cooperative laws in underdeveloped economies; Section 6.3 discusses current models of financial cooperative laws in underdeveloped economies. Section 5.4 discusses the rationale for financial cooperative regulations, while Section 5.5 compromises the conclusion.

6.2.  The historical origins of financial cooperative laws in underdeveloped economies Hermann Schulze-Delitzsch (1808–83) established the first credit cooperative in 1850 under the name ‘Vorschußverein’ (advance association), and by 1858, there were more than 100 credit cooperatives in Germany, commonly known as ‘Volksbanken’ (people’s banks) and attracting mostly the middle class. Schulze-Delitzsch was an important promoter of financial cooperatives, and his background as a politician and judge helped him in writing the first cooperative law, which was imitated later, and spread easily across Europe. His vision for a cooperative law was very practical, as he developed it from the by-laws and guidelines of already functioning credit cooperatives. By 1868, Schulze-Delitzsch’s Cooperative Societies Act became an official law in ‘Norddeutscher Bund’ (the Northern German Federation) and was effective in all of Germany by 1889. Although the law followed the German legal tradition of being a full codification, it respected the cooperatives’ autonomy to adjust their by-laws based on their needs. The law defined cooperatives as a special type of association that aims to serve the economic benefits of its members based on the principles of self-help, self-­ administration, and self-responsibility (Münkner, 2013: 6). The German model reflected the evolution of cooperatives in Germany, as self-help associations that developed in local conditions, and were able to integrate and create an advanced structure that still exists today. For that, the German cooperative law aimed to provide autonomy for the cooperative movement and to support a self-governance structure that was necessary for the movement’s development (Cuevas and Fischer, 2006: 27). The British interpretation of the German cooperative law model—which evolved earlier, in the mid-nineteenth century—is now considered the most widely applied cooperative legislation in underdeveloped economies (­Cuevas and Fischer, 2006: 27; Münkner, 2013: 13). It started with the ­Indian Credit Co-operative Societies Act that was passed in 1904 and further expanded to regulate all Indian cooperative societies in 1912. According to Münkner (2013: 13), this British-Indian Pattern of Co-operation (BICP) was the origin of the Co-operative Model Law of 1946 that was initiated and

Origin and rationale for financial cooperative regulation  91 recommended by the British Colonial Office to be applied in all colonies under the British rule. However, unlike the grassroots and autonomous ­German cooperative model, the British vision changed the core principals of the cooperative movement. The British vision was to create cooperatives as channels to implement development policies in its colonies. Thus, it changed the organisational nature of cooperatives: from instruments intended to create alternative contractual arrangements that govern the relationship between the members and the market, and between the members themselves, into governmental instruments that transfer credit and subsidies to mass populations and follow state policies (Cuevas and Fischer, 2006: 28). This vision for cooperatives spread all over the underdeveloped world. ­Cuevas and Fischer (2006: 28) noticed that, in the 1960s, the British-Indian cooperative law was carbon-copied in most Latin American countries to enable the creation of legal frameworks that allow governments and donors to channel funds to small farmers. Similarly, Develtere and Pollet (2008) highlighted that most post-independent governments in Africa perceived cooperatives as instruments for implementing state policies. The British cooperative law is still applied, with modifications, in many former British colonies in ­Africa, Asia, and Pacific and Caribbean countries as well as European countries such as Cyprus in 1910 and Malta in 1946 (Münkner, 2013: 13). In addition, the British cooperative model is applied in some Latin American countries through the influence of the United States (Cuevas and Fischer, 2006: 28).

6.3.  Current models of financial cooperative laws Cuevas and Fischer (2006: 30) identified three main legal approaches adopted to govern the operations of financial cooperatives in most countries. These are a specialised financial cooperative law, a general cooperative society law, and a banking law. A banking law is usually applied either to all financial cooperatives in the country—the European cooperative banking sector is an example—or applied only to the largest cooperatives while smaller ones are regulated by the cooperative society law. Cuevas and Fischer (2006) called this legal approach a ‘dual regime’, widely common in Latin America, where all financial cooperatives are under the cooperative law and only a few of them are also governed by the banking authorities based on specific criteria. There are some arguments in favour of regulating financial cooperatives by specialised regulation. Branch and Grace (2008: 3–4) argued that specialised regulation could guarantee the adaptation of adequate financial management provisions and governance controls, as well as facilitating capital accumulation and distribution and setting up a well-functioning prudential supervisory framework for a large number of small institutions. On the other hand, the regulation of financial cooperatives within a broader legal framework that targets other non-financial cooperatives, banks, or microfinance institutions usually fails to recognise

92  Origin and rationale for financial cooperative regulation the governance structure of financial cooperatives and their deposit-taking function as well as their small scale, narrow scope, and the specific risks they face. General banking regulations without different provisions for financial cooperatives are generally inadequate because, for instance, high initial capital requirements may be unreasonably challenging for financial cooperatives, as low- and middle-income classes will probably be unable to raise large initial start-up capital. General banking regulations may be irrelevant for financial cooperatives also because cooperatives do not have access to capital markets and have limited options for safeguarding their liquidity positions. Moreover, financial cooperatives are not-for-profit organisations with members (shareholders) that are more concerned with receiving adequate financial services than end-of-year profits, and voting power is distributed equally among members (one-member, one-vote vs. one-share, one-vote). Similarly, cooperative society regulations that govern non-financial cooperatives, without specialised provisions for financial cooperatives, are inadequate. Financial cooperatives mobilise deposits from their members and need deposit-safety measures, and regulations should enforce a minimum capital base to absorb and cover unexpected losses. Cooperative society regulations also neglect financial intermediation services, which require prudential financial standards and supervision, and may fail in organising access to liquidity facilities, money transfer, payment, settlement, and clearing networks, all of which must be regulated for a well-­ functioning financial cooperative sector. The World Council for Credit Unions (WOCCU) has designed a ‘Model Law for Credit Unions’ that reflects WOCCU’s extensive experience. The WOCCU (2015) model recommends that prudential regulations for financial cooperatives should at least cover the following 16 areas. These are capital adequacy, asset classifications and allowance for asset losses, licensing and entry requirements, liquidity risk, fixed assets, portfolio diversification, calculation of loan delinquency, external credit, investment activities, standardised accounting, external audits, multipurpose cooperatives, non-member deposits, records preservation, voluntary and involuntary liquidation and merger, and supervisory body sanctions. While setting guidelines for financial cooperatives regulatory frameworks is definitely desirable, Cuevas and Fischer (2006: 33) highlight the shortcomings of setting a concrete model law, along with many development law theorists, who have criticised the implantation of standardised Western laws in underdeveloped economies, ignoring the legal culture of each country. Moreover, the aforementioned model law reflects only the Anglo-Saxon financial cooperative experience. Describing the long experience of inadequate regulatory framework, Cuevas and Fischer (2006: 37) stated that ‘in all countries where the CFI [financial cooperatives] sector is a significant player, the regulator has not attempted to put the institution into a straitjacket designed for another institutional form as has increasingly been the case in developing countries’.

Origin and rationale for financial cooperative regulation  93

6.4.  Rationale for financial cooperative regulations Financial cooperatives benefit from strong social relations between smallgroup members. Small financial cooperatives with few members are similar to formalised ROSCAs that are able to provide financial services to their members at low operational costs, by reducing information asymmetry problems associated with any financial intermediation. However, social relations and informational advantage weaken as the number of members grows, and establishing an efficient regulatory framework becomes necessary (Poyo, 2000: 140). There are strong incentives to put the financial cooperative sector under a prudential regulatory and supervisory framework regardless of their size. Jansson et al. (2004: 51) explained that large financial cooperatives should be regulated under prudential regulation and supervision in order to protect the deposits of large number of cooperative members. Furthermore, common bond is probably weak in large cooperatives making self-supervision more difficult, besides that large financial cooperatives may impose systematic risk to the whole sector. While acknowledging the challenges of applying prudential regulation and supervision on small financial cooperatives, Jansson et al. (2004: 51) do not undermine the importance of putting them as well under the supervision of a qualified authority. In addition to the delegated/auxiliary approach—explained below—they even recommend charging small financial cooperatives a cost-covering supervision fees to ensure adequate supervision and to avoid cross-subsidising by commercial banks. The most desired approach for designing a cooperative law is participatory law-making process as suggested by (Münkner, 1986: 123) in which cooperative representatives (e.g. second-tier cooperatives or federations) directly contribute, along with the legislator, in framing the cooperative legislation. Poprawa (2009: 2) argued that the evolution of FCs’ regulatory and supervisory frameworks in most countries is highly associated with the development stage of the movement. In early stages, regulations focus on licensing and registration only. While in more advanced stages, policy makers introduce prudential measurements, financial and regulatory reporting standards, through the establishment of prudential standards and risk-based supervision framework that aims to assess capital adequacy and mitigate liquidity risks. Finally, in a well-developed financial cooperative system, the regulatory framework enforces a deposit guarantee system that creates confidence to depositors that their money is protected partly or fully. The underlying objective of financial cooperative regulation is to ensure that contracts between different stakeholders are fair and enforceable ­(Cuevas and Fischer, 2006: 3). In most cases, financial cooperatives deal solely with their members, as members are both depositors and borrowers; however, any economic analysis of financial cooperatives has to consider various important relationships between different stakeholders. On one hand, there is the relationship between the members and the cooperative

94  Origin and rationale for financial cooperative regulation itself, and on the other hand, the relationship between the cooperative and the market (Taylor, 1971: 207). The ownership structure of financial cooperatives differs from investor-owned financial institutions in five key features. First, the principle of one member having only one vote. Second, it is not possible to split shares or memberships. Third, owners or the residual claimants are the main suppliers as well as users of funds. Fourth, dividends are distributed to depositors as well as borrowers based on the monetary value of transactions carried out by the member through the cooperative (patronage dividends). Fifth, members’ shares are redeemable (Krahnen and Schmidt, 1999: 19; Cuevas and Fischer, 2006: 10). Cuevas and Fischer (2006: 28–29) pointed out that any supportive legal framework for financial cooperatives must recognise and address main facts about their nature. Financial cooperatives are institutional arrangements created to fix market deficiencies by means of self-governance contractual arrangements, rather than instruments for passing governmental policies. The change in perception from a self-help institution to a government’s political instrument significantly changes the contractual arrangements between its stakeholders, thus affecting the cooperative’s functioning and objectives. Moreover, there are governance-related problems rooted in the nature of financial cooperatives, which can lead to their failure, such as borrower-saver conflict, member-manager conflict, and/or board-manager conflict. Finally, legal frameworks must enable financial cooperatives to create alliances and networks that help to improve their bargaining power, mitigate market risks, and develop their managerial capacities. Branch and Grace (2008: 3) suggest that any resilient regulatory and supervisory framework for financial cooperatives should be prudential, proportional, and predictable. This means that cooperatives must adhere to prudential regulations that protect members’ deposits and the soundness of the financial cooperative sector. Regulations should be proportional, by recognising the distinction risks imposed by financial cooperatives to the entire financial system. Finally, regulations should be predictable to provide financial cooperatives with the stability and certainty that enable them to design their plans and investments. Financial cooperatives regulation should guide basic credit operations such as—among other things—internal credit policy, pricing, defining collaterals, contractual transparency, legal reserves, documentation, risk classification and risk weighting, non-performing loans, loan loss provisions, and write-offs (Jansson et al., 2004: 27–48). In addition, Financial cooperatives regulation should maintain the autonomy of cooperatives and protect the sector from unsupportive government interference (Bamrungwon, 1994: 55–56; Musumal, 1994: 157–158; Münkner, 2014), mitigate agency problems inherited in cooperatives governance structure (Taylor, 1971; Westley and Shaffer, 2000: 87; Branch and Baker, 2000: 210–211; Cuevas and Fischer, 2006). Regulations should also support institutional integration between financial cooperatives and facilitate the creation of second-tier cooperatives or federations (Poyo, 1995: 31; Guinnane, 1997: 251–252; Desrochers and

Origin and rationale for financial cooperative regulation  95 Fischer, 2003; Cuevas and Fischer, 2006: 16–17), and set adequate capital requirements (Davis, 1994; BCBS, 2012, 2015a, 2015b). This chapter only focuses on regulatory issues that are relevant to the distinctive feature of financial cooperatives and highlights the need for specialised financial regulation that is different from regulations targeting investor-owned financial institutions or other types of cooperative organisations. In the following sub-sections, I will try to highlight the rationale behind specialised financial cooperative regulation, focusing on protection from government interference, overcoming agency problems, enabling institutional integration, setting adequate capital requirements, and protecting members’ deposits through the introduction of deposit insurance. 6.4.1.  Protection from government interference The main role of a law for cooperative organisations in general is to reflect and protect internationally recognised cooperative principles, which must be adhered to by cooperative organisations, by translating these principles into practical legal standards (Münkner, 2014: 3). Cooperative organisations may represent groups of producers, such as farmers organised in an agricultural cooperative, or groups of consumers, such as food or housing cooperatives, and since financial cooperatives can be recognised as both producer and consumer cooperatives, they are considered the ‘purest form of cooperation’ (Taylor, 1971: 213). In line with cooperative principles, regulations must give individual cooperatives the autonomy to adjust their bylaws according to the needs of their members (Münkner, 2014: 3); especially since historical evidence shows how excessive government intervention is one of the main reasons for the failure of financial cooperatives (Krahnen and Schmidt, 1999: 18). Chapters 4 and 5 of this book suggest that non-­ democratic regimes have incentives to shape policies that are unsupportive of the development of financial cooperatives, to maintain political control over the movement to extend their popularity, and to avoid any political role that cooperatives can play while representing the true interest of their members. Bamrungwon (1994: 62) observes that excessive control by the state is strongly supported by regulations, which can be observed in similarities in cooperative laws among several underdeveloped economies. In these cases, cooperative regulations do not only place emphasis on statutory provisions such as licensing, membership, governance structure, and property and equity, but also included several provisions concerning the powers and authority of the registrar of cooperatives. It is not uncommon that the powers given to registrars can be very extensive, going beyond supervision to include a degree of managerial control over cooperatives, without appropriate channels for appealing on their decisions (Bamrungwon, 1994: 55–56). An International Labour Organization colloquium was held in Geneva in 1993 under the general theme of ‘The Relationship between the State and Cooperatives in Cooperative Legislation’. The colloquium concluded that

96  Origin and rationale for financial cooperative regulation excessive state control over cooperatives is usually costly and ineffective. It undermines the autonomy and self-dependence of cooperatives. The colloquium concluded that there was an urgent need to introduce significant reforms to cooperative legislations, as these legislations are the major instruments of state control. Furthermore, the colloquium recommends that state control should be limited to basic regulatory functions reflected in ‘normative controls’ only, similar to state control over any other private economic entities, focusing on registration, supervision, sanctioning, and liquidation, without weakening cooperatives’ ability to function well and grow. Most importantly, cooperative legislation must not include provisions that give unrestricted powers to state registrars or authorities, such as appointing or removing cooperative directors or management boards. In addition, cooperative legislation should not facilitate the intervention of state authorities in daily operations or allow compulsory membership (Musumal, 1994: 157–158). 6.4.2.  Overcoming agency problems The conflict between depositors and shareholders is the main agency conflict that stimulates the risk of bank failure in investor-owned financial institutions. Depositors prefer the bank to invest in safe assets that do not threat their savings, while shareholders would prefer investing in more risky assets that bear higher returns for their investments. However, depositor-­ shareholder agency conflict is not relevant to financial cooperatives, as depositors are usually the shareholders, and members in cooperatives have no incentive to increase the risk of the mutual institution, since—at least ­theoretically—they are more interested in having access to financial services in the long run, rather than in short-term gains (Cuevas and Fischer, 2006: 37). Cuevas and Fischer (2006: 8) thoroughly discuss the two main agency conflicts inherited in financial cooperatives’ mutual ownership: these are member-manager conflict and net borrowers against net depositors’ conflict. There is relatively little attention given to borrower-depositor conflict, as it is considered to be less significant. The objectives of financial cooperative members are not homogeneous and may change over time based on the nature of their transactions with the cooperative, unlike shareholders of traditional joint-stock banks whose primary interests are homogenous as they seek to maximise the returns on their capital. Thus, the preference of a net-saver member contradicts that of a net-borrower member (Poyo, 2000: 147). Taylor (1971) provides a theoretical explanation for the conflict between borrowers and savers, explaining that borrower-dominated cooperatives may maintain ineffective lending requirements and conditions, which may increase default rates, whereas saver-dominated cooperatives may impose extremely restrictive lending conditions and high interest rates. Providing loans with low interest rates can reduce the cooperative’s ability to offer high dividends or interest rates on deposits, while providing higher dividend

Origin and rationale for financial cooperative regulation  97 rates may require higher interest rates on loans as well. The opposing motives of these two objectives usually lead to conflict between net-saver members and net-borrower members. The member conflict can produce biased behaviour in favour of one group against the other, and the cooperative can end up adopting either borrower-orientated or saver-orientated behaviour (McKillop and Ferguson, 1998). The saver-borrower agency conflict can impose significant risks on the sustainability of financial cooperatives and may increase failure rates, as has happened previously in Latin America. Therefore, it is crucial that financial cooperative regulations protect the interests of all members, and ensure that financial cooperatives are not biased towards either their depositors or their borrowers (Westley and S ­ haffer, 2000: 87; Cuevas and Fischer, 2006: 10). On the other hand, the not-for-profit nature of cooperatives may not give satisfactory financial incentives for their managers, and there are always potential conflicts of interest between managers and members. The member-­ manager conflict, the classical agency problem, has been widely studied within the idea of ‘expense preference behaviour’. Cuevas and Fischer (2006: 9–11) identified two main attitudes of expense preference behaviour in financial cooperatives: ‘performance structure hypothesis’ and ‘ownership structure hypothesis’. The ‘performance structure hypothesis’ is when rent increases because of the failure of market competitiveness, and weak monitoring of managers’ decisions, which increases the rents of the management board. Moreover, Jensen’s (1986) ‘free cash flow hypothesis’ explains how free or uncommitted funds may increase the possibility that managers will inefficiently invest in unprofitable areas. Therefore, supporting policies, especially government subsidies, may harm the performance of financial cooperatives and encourage opportunistic behaviour by management, thus increasing insolvency risk. Meanwhile, the ‘ownership structure hypothesis’ maintains that weak ownership leads mangers to perform for their own interests rather than members’ interests. That is because the ‘one member one vote’ principle tends to reduce members’ engagement in the organisation, as each member individually does not have enough influence and so may not have the incentive to actively participate in the decision-making process. According to Cuevas and Fischer (2006: 11), expense preference behaviour by management is the primary reason for the failure of financial cooperatives, and prudential regulatory and supervisory frameworks should closely focus on controlling expense preferences. Branch and Baker (2000: 210–211) have proposed seven principles that should be considered in financial cooperative regulations or by-laws to mitigate agency problems. First, regulations and by-laws should separate between decision oversight and decision-making, through clarifying the monitoring and decision oversight roles of the board of directors and not confusing it with daily operational decision-making, which is the management’s role. Second, regulations and by-laws should set clear criteria for the necessary qualifications of board members, in order for directors to have

98  Origin and rationale for financial cooperative regulation sufficient experience that enables them to set the necessary policies and provide valuable guidance to the cooperative. Third, regulations and by-laws must establish clear functions for the supervision committee. Generally, the supervision committee should be responsible for ensuring that the operations of the cooperative are in compliance with its by-laws, that adequate internal controls are established and applied, and that an external audit takes place annually. Fourth, credit analysis and loan approval procedures should be established in detail in a separate credit policy. Nevertheless, regulations and by-laws should clearly identify the responsible body for credit analysis and loan approval, and the required qualifications of the members of the credit committee. Fifth, the board of directors should be accountable to the general assembly for the operating results of the financial cooperative, thus, regulations and by-laws should clearly state the responsibilities of the board of directors, as well as penalties and sanctions for failure to meet their responsibilities. Sixth, regulation and by-laws must create ethical codes and clear criteria for issuing and evaluation insider loans as well as strict controls to avoid conflicts of interest. Insider loans are loans issued to board members, executives and employees, or to their relatives. Finally, regulations and by-laws should set a policy for the rotation of board members, setting a limit on the maximum terms allowed for a board member in order to benefit from new ideas and to avoid the domination of a few board members. 6.4.3.  Setting adequate capital requirements Capital requirements are the most crucial element in financial regulation because one of the essential reasons to regulate the financial sector is to internalise the social costs of possible bank failures (Brunnermeier et al., 2009: vii and 45). According to the Core Principles of the Basel Committee for Banking Supervisions (BCBS), capital adequacy requirements should consider four main aspects. These are the ability of the capital base to absorb potential losses; the appropriateness of risk weight indicators to accurately reflect the risk profile of an institution’s exposures; the ability of reserves and provisions to cover expected losses; and finally, the quality of risk management and controls. However, the Basel Committee does not stipulate full compliance with the capital adequacy requirements of Basel I, II, or III for all types of financial institutions, and it recommends a proportionate approach for setting capital adequacy ratios (BCBS, 2012: 45).1 This approach is practical because, compared to traditional banks, low capital requirements can be adequate for other non-bank depository institutions giving the simplicity of their activities and their risk exposure. In addition, full compliance with advanced measurement techniques of capital adequacy may be beyond the capability of many small depository institutions, in terms of expertise and costs (BCBS, 2015b: 21). Besides, a proportionate approach does not necessarily mean lower capital adequacy ratios. High capital adequacy

Origin and rationale for financial cooperative regulation  99 requirements might be unavoidable, sometimes just temporarily, to compensate for low monitoring capacity or macroeconomic factors. In a recent survey by BCBS, 20 out of 34 financial regulatory authorities stated that they require financial cooperatives to maintain minimum regulatory capital adequacy ratios (BCBS, 2015a). High capital adequacy requirements may, however, restrain the growth rate of financial cooperatives compared to other investor-owned financial institutions (Davis, 1994:  13), as these requirements tie the growth of total assets—including income-­generating assets, such as loans—to the growth of the capital base, which may severely restrict the ability of financial cooperatives to expand quickly. Since financial cooperatives cannot raise their equity from the capital market, because their shares are usually untradeable, the only source for cooperatives to obtain additional capital is through operating surpluses. Thus, for financial cooperatives to achieve rapid growth they need to accumulate large surpluses, which is quite challenging because cooperatives are not-for-profit organisations aiming to provide financial services at competitive prices, and large surpluses implies reducing deposit interest rates and increasing loan interest rates (Davis, 1994: 40). Equity in financial cooperatives is the part of capital solely owned by the cooperative and cannot be claimed by any member or external parties, thus, accumulated reserves are usually considered as the core of cooperatives’ equity. In many cases, the shares held by the members are not treated as part of the equity. Members’ shares are redeemable and members have the right to withdraw their shares, or part of them, at any time upon terminating their membership in the cooperative. In addition, since these shares are also non-tradeable, membership termination reduces the total equity (Balkenhol, 1999: 5). The low equity base in financial cooperatives reduces their ability to seek external debt funding as well (Balkenhol, 1999: 6), which explains why classical cooperative theory suggests that the output of a cooperative increases exclusively by the enrolment of new members (Taylor, 1971: 209). More importantly, there is no difference between equity stakeholders and depositors in a cooperative, thus high capital adequacy requirements aimed at protecting creditors, especially depositors, may be questioned. Since capital reserves are the property of members in the first place, any protection maintained by these reserves to cooperative depositors is a form of self-insurance by the members of the cooperative themselves. Most often, high losses incurred by a financial cooperative affects its members only, such that accumulating a significant capital base implies that members’ accumulated capital rather than their deposits will absorb these losses (Davis, 1994: 35)—taking into account that capital reserves should only absorb abnormal default rates, as provisions for loan losses are normally incorporated in interest rates on loans. Provisions for loan losses are determined to cover normal, expected credit default risks (Davis, 1994: 39). Under Basel III, ‘shares issued by mutual and cooperative banks could be treated as common equity for regulatory purposes provided that they meet

100  Origin and rationale for financial cooperative regulation the permanence and loss absorption criteria’ (BCBS, 2015b: 22). However, this matter is quite controversial and remains under discussion, alongside the ongoing development of international capital standards. That is because, unlike common shares issued by joint-stock entities, capital invested by the members of the cooperative ‘is redeemable and usually not considered high-quality capital’ (BCBS, 2015a: 22), according to the Basel Committee. For that, BCBS (2015b: 22) recommended additional measurements that can be adopted by the supervisory authority of financial cooperatives, depending on the size, structure, and complexity of the sector. The Basel Committee suggests that increasing attention should be given to increasing financial cooperatives’ retained earnings. However, that is also controversial since cooperatives are not-for-profit and capital accumulation through retained earnings could be slow or insufficient. Another recommendation is to limit redemptions of shares if the capital adequacy ratio is close to or below a minimum level, which can be equivalent to or higher than the regulatory requirements. Moreover, the Basel Committee suggests that financial cooperatives should be required to keep cash deposits at a second-tier organisation (e.g. federation or apex). The last recommendation by the Basel Committee is to implement capital adequacy requirements at the second-tier level or on larger cooperatives, rather than on all cooperatives, including primary and small ones. The latter two recommendations rely heavily on the solvency and liquidity of the second-tier organisation, and thus, the entities must be subject to good regulation and supervision. Generally, capital requirements for financial cooperatives are sufficient as long as they are high enough to absorb and cover unexpected losses, to cover initial set-up costs that support sustainable operations, and indicate the minimum expected financial commitment from new applicants. Start-up requirements for financial cooperatives can also specify the minimum number of members and geographic scope, and financial cooperative regulation should clearly include statutory provisions on member withdrawal and the resulting redemption of shares (BCBS, 2015b: 10). 6.4.4.  Enabling institutional integration By their nature, primary cooperatives are small and bound to geographic or sectorial concentration, making them more vulnerable to liquidity risks and mismanagement. For instance, maturity mismatch is more likely to increase in rural cooperatives as they depend on short-term deposits to finance seasonal loans or agricultural machineries. For that, having access to external finance is crucial for their growth, as it may allow financial cooperatives to lower their savings requirements. Financial cooperatives usually have savings requirements that members must fulfil in order to be eligible for acquiring loans. Savings requirements are calculated relative to the desired loan size and can be pledged as collateral for the loan. Accordingly, lowering the

Origin and rationale for financial cooperative regulation  101 savings requirements may increase the demand for the financial cooperative’s services and may consequently increase the total share savings, either by existing members or by attracting new members—keeping in mind, however, that lowering the savings requirements may lead to a demobilisation of deposits in the longer term (Krahnen and Schmidt, 1999: 21). Thus, integration among primary financial cooperatives to form second-­ tier cooperatives or federations is a fundamental institutional practice since the emerging of German’s credit cooperatives in the nineteenth century. Guinnane (1997: 251–252) highlighted how regional integrations helped small German cooperatives to overcome their structural challenges and ­increased public confidence in the financial viability of cooperatives, even in the absence of reliable regulation. Small credit cooperatives relied on regional cooperative banks to secure their liquidity positions through shortor long-term borrowing, acting like lenders of last resort, and on regional auditing associations to monitor their performance closely. Regional banks also accepted deposits from their affiliated cooperatives and they were able to borrow and lend from and to other financial institutions, helping small cooperatives benefit from economies of scale. Similarly, Poyo (1995: 31) described how well-established second-tier institutions supported the development of Dominican Republic financial cooperatives in the 1950–60s. The national federation was, to a large extent, efficient in channelling external technical assistance and subsidised credit. Primary financial cooperatives can effectively assess their members’ demands because they are governed by the members themselves. Through pooling resources from their members, cooperatives should obtain essential inputs that it can transform into outputs of financial services and products for their members. Nevertheless, the small scale of inputs demanded by each individual cooperative produces natural uncertainties. Inputs required by a financial cooperative can be, but are not limited to, capital goods such as land, buildings, furniture, computing equipment; financial products such as external borrowing, deposit and insurance; and many other services including clearing services for cheque, remittances, technical assistance, and liquidity management (Cuevas and Fischer, 2006: 16–17). Desrochers and Fischer (2003) explain that the degree of integration in financial cooperative systems is determined by the risks associated with the procurement of necessary inputs for the financial intermediation process, and that cooperatives form inter-financial cooperative alliances to mitigate these risks by collectively obtaining the necessary inputs. These alliances can be for a short period based on repeated contracts, hybrid relations that target long-term alliances, or can result in a hierarchical integration with full merger of all activities. For these reasons, regulatory frameworks must support and enable the voluntary institutional integration among financial cooperatives that enables them to exploit economies of scale and to limit uncertainties arising from obtaining intermediation inputs (Cuevas and Fischer, 2006: 22).

102  Origin and rationale for financial cooperative regulation 6.4.5.  Protecting members’ deposits Although it is generally recommended to protect depositors’ money by setting explicit deposit insurance schemes, the impact of deposit insurance remains quite debatable. The general economic theory proposes that deposit insurance can improve the stability of banks by reducing the possibility of depositor runs caused by imperfect information. However, such an explicit safety net of insurance may reduce market discipline and create a moral hazard by providing incentives for banks to invest in riskier assets, without monitoring by depositors, as losses are shifted from depositors to the insurance fund. The 1980s savings and loan crisis in the United States has been attributed by many economists to moral hazard created by deposit insurance, regulatory failure and financial liberalisation (Demirgüç-Kunt and Detragiache, 2002: 1378). Grossman (1992) suggests that American thrift institutions covered by deposit insurance schemes were more likely to engage in risky loans than uninsured institutions during the 1930s. Likewise, Alston et al. (1994) investigated the United States rural banking crisis of the 1920s, finding that failure rates were higher in states that suffered from agricultural distress and had deposit insurance schemes. Wheelock and Wilson (1995) drew similar results after analysing banks performance in Kansas state for the period 1910–28, suggesting that banks covered by deposit insurance schemes had higher probability for failure. Demirgüç-Kunt and Detragiache (2002) found that the presence of deposit insurance in a financial system tends to increase bank instability, especially in countries with weak institutional structure, after analysing data from more than 60 countries for the period from 1980 to 1997. Similarly, Ioannidou and Penas (2010) analysed risk-taking behaviour of Bolivian banks before and after the introduction of a deposit insurance scheme, suggesting that banks were more likely to invest in riskier loans after being covered by the deposit insurance scheme. Banks imposed higher interest rates on these riskier loans but without additional collateral requirements or reduced maturities, and thus these loans were associated with higher default and delinquency rates. Moreover, Ioannidou and Penas (2010) found that large depositors reduced their pressure on banks after the introduction of the deposit insurance scheme compared to pre-deposit insurance periods. Generally, large depositors had more incentives to closely monitor banks’ loan portfolios, and to withdraw large sum of their deposits if the risk-taking behaviour of banks increased, as financial safety nets adopted by governments usually have coverage limits per account, which compensates small depositors in the event of bank insolvency, while large depositors are rarely compensated. Gropp and Vesala (2004) argue that these results should not be generalised, as these studies relied on very early historical data from the 1920–30s (Grossman, 1992; Alston et al., 1994; Wheelock and Wilson, 1995), or data from emerging markets, where underdeveloped institutions may aggravate

Origin and rationale for financial cooperative regulation  103 banks’ risk shifting after the introduction of deposit insurance schemes. This argument is partly in line with the results of Demirgüç-Kunt and ­Detragiache (2002), and supported by Cull et al. (2004). Both found that explicit deposit insurance might increase banks’ instability and will negatively affect their growth rates in the long run. Similarly, Hovakimian et al. (2003) found that introducing deposit insurance schemes might increase risk-­ taking behaviour for banks operating in countries with weaker institutional structures such as low political and economic freedoms, high corruption, and poor contract enforcement mechanisms. In addition, Gropp and Vesala (2004) found that European banks’ risk-taking behaviour had significantly decreased after the introduction of explicit deposit insurance. They argued that the probability of banking failure might decrease after the introduction of credible explicit deposit insurance in two cases. First, if there is a strong implicit safety net prior to the introduction of the deposit insurance scheme, in which there is a high commitment from the government to protect claim-holders. Second, if banks’ liabilities contain a relatively high proportion of subordinated debt holders or other uninsured claim-holders, who have a strong incentive to monitor the bank’s risk behaviour especially after the introduction of deposit insurance. Esty (1997) found that investor-owned thrifts in the United States had higher profit volatility compared to mutual thrifts during the period 1982–88, and that mutual thrifts who transformed into investor-owned thrifts were more likely to invest in high-risk assets and to have increased profit volatility. Esty (1997: 26) argues that investor-owned financial institutions are more likely to adopt high-risk financial strategies compared to mutual-owned institutions. Without appropriate monitoring, owners of financial institutions will take high-risk decisions in in the hope of gaining higher returns. The incentive to adopt high-risk behaviour is determined mainly by whether or not the residual and fixed claims are separable. Because claims are not separable in the case of mutual organisations such as cooperatives, the total wealth of members would not be affected by the increase of the institution’s risk behaviour, as the residual claim’s possible gains is balanced by the possible losses on the fixed claim. Karels and McClatchey (1999) found no evidence that credit unions’ risk-taking behaviour in the United States had increased after the adoption of the deposit insurance scheme during the period 1971– 90. Their results showed that liquidity and asset quality improved, suggesting a decrease in risk–taking behaviour during the post deposit insurance period. However, Karels and McClatchey (1999: 132) suggest that the ownership structure that limits risk-taking behaviour is not the only reason for the stability of credit unions, but also the strong regulatory environment adopted in the 1970s that had restricted credit unions’ investment strategies, as regulations at that time imposed limitations on the maximum loan size that can be offered by credit unions, and the maximum maturity for secured and unsecured loans. Similarly, Hannafin, and McKillop (2007) found no

104  Origin and rationale for financial cooperative regulation evidence of risk-shifting behaviour in the performance of Irish credit unions after the introduction of a deposit insurance scheme in 1989. Unlike investor-owned financial institutions, there is no strong evidence in financial cooperative literature that supports the argument that the adoption of deposit insurance schemes increases the likelihood of institutions adopting risk-taking behaviour. That is because, in theory, the mutual ownership structure implies limited risk-taking behaviour. In investor-owned firms, shareholders are only residual claimants, thus they have incentives to adopt riskier behaviour as they can gain benefits from higher dividends or selling shares at market value. Shares in investor-owned financial institutions are considered highly leveraged claims on the institution’s residual profits, unlike mutual institutions where shareholders are also depositors, thus their shares are unleveraged (Karels and McClatchey, 1999: 107–108). Moreover, several approaches can make deposit insurance schemes for financial cooperatives more incentive compatible and reduce agency costs and moral hazard. One approach is limited coverage that makes the insurance force large depositors to closely monitor the performance of the institutions, and which will increase market discipline. A similar approach is coinsurance, in which depositors are not compensated for their total deposits, and thus some of the depositors will be forced to monitor the institutions’ risk strategy as they are exposed to losses (Beck, 2004). Another common approach is risk-based deposit insurance, where insurance premiums are adjusted to reflect the risk of the institution’s assets or capital adequacy performance (Hannafin and McKillop, 2007: 47).

6.5. Conclusion In this review, I attempted to highlight the main reasoning behind regulating financial cooperatives differently from other financial institutions, ­focusing on their unique institutional characteristics and the main challenges and risks that they commonly face. The key points and recommendations of this review can be summarised as follows. First, regulation for financial cooperatives must protect the sector from destructive government control. Cooperative regulations in several countries give unrestricted powers to state registrars or authorities, including intervention in daily operations or allowing compulsory membership, whereas a supportive regulatory framework should maintain legal control over financial cooperatives similar to other private economic entities, ­focusing on registration, liquidation monitoring, capital requirements, and other risk management mechanisms, without weakening cooperatives’ ability to function well and grow. Second, financial cooperative regulations need to pay close attention to the two main agency conflicts that are inseparable from financial cooperatives’ mutual-ownership structure. These are member-­manager conflict and net borrowers against net depositors conflict. ­Regulations should ensure that the decision oversight and decision-making

Origin and rationale for financial cooperative regulation  105 roles of the board are clearly defined and not confused with the management’s role of daily operations. Penalties and sanctions on the board or the management for failure to meet their responsibilities should be clearly defined too, in addition to a policy for the rotation of board members. Moreover, regulation should ensure that there are clear criteria for the necessary qualifications of board members, and clear functions for the internal supervision committee. In addition, regulations should insist on the establishment of a credit committee in financial cooperatives, and clearly identify the committee’s responsibilities for credit analysis and loan approval. Third, it is undeniably essential in financial cooperative regulations to set minimum capital requirements; however, high capital adequacy requirements may not be the optimum approach, given the simplicity of their activities and their risk exposure. High capital requirements may restrict the growth of financial cooperatives, whereas low capital requirements can be adequate as long as they are high enough to absorb and cover unexpected losses, cover initial set-up costs that support sustainable operations, and indicate the minimum expected financial commitment from new applicants. Fourth, regulations should support and enable the voluntary institutional integration among financial cooperatives to help them deal with maturity mismatch and liquidity risks, to allow small primary cooperatives to benefit from external technical assistance provided by bigger cooperatives or federations, and to increase public confidence in the sector. Finally, regulations may include the creation of deposit insurance schemes for financial cooperatives to protect members’ deposits and to build confidence, as well as to attract new depositors (members) or to encourage existing members to invest more in their cooperative.

Note 1 Footnote no. 59 page 45.

Bibliography Alston, L. J., Grove, W. A. and Wheelock, D. C. (1994), ‘Why do banks fail? Evidence from the 1920s’, Explorations in Economic History, 31(4), 409–431. Balkenhol, B. (1999), ‘Introduction: Background and issues’, in Balkenhol, B. (ed.), ‘Credit Unions and the Poverty Challenge: Extending Outreach, Enhancing Sustainability’, Geneva: International Labour Organisation, pp. 1–15. Bamrungwon, C. (1994), ‘State Control over Cooperatives in Co-operative Legislation’, Background Paper No. 2a in The Relationship between the State and Cooperatives in Cooperative Legislation, Geneva: International Labour Organisation, pp. 55–63. Basel Committee on Banking Supervision. (2012), ‘Core Principles for Effective Banking Supervision’, Basel: Bank for International Settlements, September. Basel Committee on Banking Supervision. (2015a), ‘Range of Practice in the Regulation and Supervision of Institutions Relevant to Financial Inclusion’, Basel: Bank for International Settlements, January.

106  Origin and rationale for financial cooperative regulation Basel Committee on Banking Supervision. (2015b), ‘Guidance on the Application of the Core Principles for Effective Banking Supervision to the Regulation and Supervision of Institutions Relevant to Financial Inclusion, Basel: Bank for International Settlements, December. Beck, T. (2004), ‘The incentive-compatible design of deposit insurance and bank failure resolution: Concepts and country studies’, in Mayes, D. G. and Liuksila, A. (eds.), ‘Who Pays for Bank Insolvency?’, London: Palgrave Macmillan, pp. 118–141. Branch, B. and Baker, C. (2000), ‘Overcoming governance problems’, in Westley, G. and Branch, B. (eds.), ‘Safe Money: Building Effective Credit Unions in Latin America’, Washington, DC: Inter-American Development Bank, pp. 203–223. Branch, B. and Grace, D. (2008), ‘Technical Guide: Credit Union Regulation and Supervision’, Wisconsin: World Council of Credit Unions. Brunnermeier, M., Crockett, A., Goodhart, C., Hellwig, M., Persaud, A. and Shin, H. (2009), ‘The Fundamental Principles of Financial Regulation’, Geneva ­Reports on the World Economy, No. 11. Cuevas, C. E. and Fischer, K. P. (2006), ‘Cooperative Financial Institutions: Issues in Governance, Regulation, and Supervision’, Washington, DC: World Bank. Cull, R., Sorge, M. and Senbet, L. W. (2004), ‘Deposit Insurance and Bank Intermediation in the Long Run’, Working Papers No 156, Basel: Bank for International Settlements. Davis, K. (1994), ‘Prudential regulation and Australian credit unions’, Australian Journal of Management, 19(1), 31–46. Demirgüç-Kunt, A. and Detragiache, E. (2002), ‘Does deposit insurance increase banking system stability? An empirical investigation’, Journal of Monetary Economics, 49(7), 1373–1406. Desrochers, M. and Fischer, K. P. (2003), ‘Theory and test on the corporate governance of financial cooperative systems: Merger vs. networks’, Working Paper 03–34. Vancouver: CIRPÉE. Develtere, P. and Pollet, I. (2008), ‘Renaissance of African Cooperatives in the 21st Century: Lessons from the Field’, in Develtere, P., Pollet, I. and Wanyama, F. (eds.), ‘Cooperating out of Poverty: The Renaissance of the African Cooperative Movement’, Geneva: International Labour Office. Esty, B. C. (1997), ‘Organizational form and risk taking in the savings and loan industry’, Journal of Financial Economics, 44(1), 25–55. Gropp, R. and Vesala, J. (2004), ‘Deposit insurance, moral hazard and market monitoring’, Review of Finance, 8(4), 571–602. Grossman, R. S. (1992), ‘Deposit insurance, regulation, and moral hazard in the thrift industry: Evidence from the 1930’s’, The American Economic Review, 82(4), 800–821. Guinnane, T. W. (1997), ‘Regional organizations in the German cooperative banking system in the late 19th century’, Research in Economics, 51(3), 251–274. Hannafin, K. and Mckillop, D. (2007), ‘Deposit insurance and credit unions: An international perspective’, Journal of Financial Regulation and Compliance, 15(1), 42–62. Hovakimian, A., Kane, E. J. and Laeven, L. (2003), ‘How country and safety-net characteristics affect bank risk-shifting’, Journal of Financial Services Research, 23(3), 177–204.

Origin and rationale for financial cooperative regulation  107 Ioannidou, V. P. and Penas, M. F. (2010), ‘Deposit insurance and bank risk-taking: Evidence from internal loan ratings’ Journal of Financial Intermediation, 19(1), 95–115. Jansson, T., Rosales, R. and Westley, G. D. (2004), ‘Principles and Practices for Regulating and Supervising Microfinance’, Washington, DC: Inter-American Development Bank. Jensen, M. (1986), ‘Agency costs of free cash flow, corporate finance, and takeovers’, The American Economic Review, 76(2), 323–329. Karels, G. V. and Mcclatchey, C. A. (1999), ‘Deposit insurance and risk-taking behavior in the credit union industry’, Journal of Banking and Finance, 23(1), 105–134. Krahnen, J. and Schmidt, R. (1999), ‘On the theory of credit unions’, in Balkenhol, B. (ed.), ‘Credit Unions and the Poverty Challenge: Extending Outreach, Enhancing Sustainability’, Geneva: International Labour Organisation, pp. 17–24. Mckillop, D. and Ferguson, C. (1998), ‘An examination of borrower orientation and scale effects in UK credit unions’, Annals of Public and Cooperative Economics, 69(2), 219–242. Münkner, H. H. (1986), ‘Participative law-making: A new approach to drafting cooperative law in developing countries’, Verfassung und Recht in Übersee/Law and Politics in Africa, Asia and Latin America, 19(2), 123–137. Münkner, H. H. (2013), ‘Worldwide Regulation of Co-operative Societies – An Overview’, Euricse Working Paper n. 53|13. Münkner, H. H. (2014), ‘Ensuring Supportive Legal Frameworks for Co-operative Growth’, Nairobi: International Co-operative Alliance. Paper presented at the ICA 11th Regional Assembly. Musumal, C. (1994), ‘Summary of the Discussions. In the Relationship between the State and Cooperatives in Cooperative Legislation’, Geneva: International ­Labour Organisation, pp. 155–162. Report of a Colloquium held at Geneva, 14–15, ­December 1993. Poprawa, A. (2009), ‘Regulation and legislation of cooperative banks and credit union’, New York: Paper Prepared for United Nations Expert Group Meeting on Cooperatives, pp. 28–30. Poyo, J. (1995), ‘Expansion of Rural Financial Services: The Development of a Community-­B ased Rural Credit Union Network in the Dominican Republic (1984– 1993)’, Geneva: International Labour Office. Poyo, J. (2000), ‘Regulation and supervision of credit unions’, in Westley, G. and Branch, B. (eds.), ‘Safe Money: Building Effective Credit Unions in Latin America’, Washington, DC: Inter-American Development Bank, pp. 137–160. Taylor, R. A. (1971), ‘The credit union as a cooperative institution’, Review of Social Economy, 29(2), 207–217. Vittas, D. (ed.) (1992), ‘Financial Regulation: Changing the Rules of the Game’, Washington, DC: World Bank Economic Development Institute. Westley, G. and Shaffer, S. (2000), ‘Credit union delinquency and profitability’, in Westley, G. and Branch, B. (eds.), ‘Safe Money: Building Effective Credit Unions in Latin America’, Washington, DC: Inter-American Development Bank, pp. 61–90. Wheelock, D. C. and Wilson, P. W. (1995), ‘Explaining bank failures: Deposit insurance, regulation, and efficiency’, The Review of Economics and Statistics, 689–700. World Council of Credit Unions. (2015), ‘Model Law for Credit Unions’, 2015 edition, Wisconsin: World Council of Credit Unions.

7 Regulation, supervision, and deposit insurance for financial cooperatives An empirical investigation1

7.1. Introduction An enabling regulatory and supervisory environment is a prerequisite for the growth and development of financial cooperatives, and as the sector grows and becomes more complex, regulations must be responsive to ensure the stability and the effectiveness of the sector. This chapter is highly inspired by Cuevas and Fischer (2006) and also examines the argument laid down in the previous chapter, that specialised regulations are more suitable for financial cooperatives, than traditional bank or cooperative society regulations. The chapter also complements our understanding of why financial cooperatives grow in some emerging economies and not in other similar ones. Results in Chapter 5 suggest that high indicators of financial cooperative development, measured by penetration rate, deposits, and assets per GDP, as well as the growth of the sector are positively correlated with indicators for the quality of political institutions. Here I used unbalanced panel data covering the period from 1995 to 2014 to examine the impact of different regulation and supervision approaches, in addition to deposit insurance schemes, on the development of financial cooperatives in underdeveloped economies. In many emerging or underdeveloped economies, financial cooperatives are fully regulated by a general cooperative societies’ law that regulates all type of cooperative organisations, including non-financial cooperatives (e.g. agricultural, consumer, or housing cooperatives, etc.), ignoring the financial intermediation nature of financial cooperatives. While in other countries, financial cooperatives fall completely under the regulatory and supervisory responsibility of the central bank or the bank superintendence. In the last decade, more countries adopted a specialised law for financial cooperatives or separate and detailed provisions regulating financial cooperatives under a non-specialised financial cooperatives law. In few countries, especially in Latin America, central banks or bank superintendence regulate and supervise large financial cooperatives only while smaller financial cooperatives fall under different regulatory framework. Other countries keep financial cooperatives under legislations intended to govern the operations of all

Regulation, supervision, and deposit insurance  109 microfinance institutions. There is no common agreement over which of these different legal approaches work better to support the growth and resilience of the sector in developing countries. In addition, there is no empirical evidence that argues in favour of a specific supervisory approach to be more suitable for financial cooperatives, or whether deposit insurance schemes enhance or threaten the growth of financial cooperatives. This chapter tries to explore whether the size and outreach of the financial cooperative sector is shaped by the regulatory and supervisory approach adopted, and if deposit insurance schemes support or discourage the development of the sector. Findings of this chapter has important policy implications suggesting that a specialised regulation for financial cooperatives is more likely to support the growth of the sector, while there is a serious concern over the viability of applying commercial banks or cooperative societies’ regulations to financial cooperatives. In addition, the analysis encourages the introduction of deposit insurance as an important instrument that can promote confidence in the sector. The following sections of the chapter are organized as follows: Section 7.2 briefly discusses current regulation and supervision approaches, and the advantages and disadvantages of deposit insurance schemes and their implication on financial cooperatives. Section 7.3 defines the data and the methodology used. Results are presented and interpreted in Section 7.4. Section 7.5 concludes.

7.2.  Regulation, supervision, and deposit insurance for financial cooperatives Cuevas and Fischer (2006: 30) recognized three main legal frameworks that govern the financial cooperative sector in most countries. These are a specialized law for financial cooperatives, a general cooperative society’s law, and a banking law. The latter framework is usually applied on all country’s banking sector, including financial cooperatives, or only applied to large cooperatives while smaller ones are left to the cooperative society’s law. Cuevas and Fischer (2006) called this legal approach a ‘dual regime’, widely common in Latin America, where only few financial cooperatives are governed by the banking authorities based on specific criteria, such as the size of the cooperative or if it provides services to non-members (open financial cooperatives). Table 7.1 follows Cuevas and Fischer (2006: 45) and compares regulation and supervision approaches adopted by countries included in the sample to govern the activities of financial cooperatives in 1995 versus 2014. The table shows how several countries in the last two decades chose to regulate financial cooperatives through a specialised law or separate provisions instead of general cooperative law or commercial bank law. While for supervision, the Basel Committee for Banking Supervisions (BCBS) had recently issued Guidance for the implementation of its ‘Core Principles’ for institutions engaged in financial inclusion, which addresses

Table 7.1  Regulation and supervision approaches of financial cooperatives in 1995 vs 2014

Financial cooperatives regulation and supervision approaches in 1995

Cooperative societies supervision

NBFIs supervisory authority Banking authority supervision

Cooperative society’s regulation

Specialized financial cooperatives regulation

Bangladesh Belarus¹ Benin Côte d’Ivoire Dominican Republic El Salvador Ethiopia Guatemala Guinea-Bissau Guyana Honduras Indonesia Kenya Lesotho Liberia Macedonia² Malaysia Mauritius Moldova Mongolia Nepal Nicaragua Niger Panama Paraguay Romania² Rwanda Sri Lanka Swaziland Tanzania Thailand Togo Uganda Uzbekistan³ Vietnam² Zimbabwe

Cameroon

Peru

Azerbaijan Gambia Lithuania Mali Papua New Guinea Senegal

NBFIs regulation

Dual regulatory regime

General banking regulation

Colombia

Burkina Faso Cambodia4

Brazil Lao PDR Latvia

Financial cooperatives regulation and supervision approaches in 1995 Cooperative society’s regulation Dual supervisory regime Auxiliary supervision

Specialized financial cooperatives regulation

NBFIs regulation

Costa Rica Philippines

Jamaica Malawi Mexico Poland Russia South Africa

Ukraine

Ghana

Dual regulatory regime

General banking regulation

Bolivia Chile Ecuador India Uruguay

Financial cooperatives regulation and supervision approaches in 2014

Cooperative societies supervision

NBFIs supervisory authority

Cooperative society’s regulation

Specialized financial cooperatives regulation

Belarus Dominican Republic Ethiopia Guatemala Guyana Lesotho Liberia Malaysia Mauritius Nicaragua Panama Sri Lanka Thailand Uganda Zimbabwe

Indonesia Paraguay

NBFIs regulation

Dual regulatory regime

General banking regulation

Bangladesh Benin Burkina Faso Côte d’Ivoire Ecuador Guinea-Bissau Kenya Mali Moldova Mongolia Niger Senegal South Africa Swaziland Togo Ukraine (Continued)

112  Regulation, supervision, and deposit insurance Financial cooperatives regulation and supervision approaches in 2014 Cooperative society’s regulation Banking authority supervision

Dual supervisory regime Auxiliary supervision

Auxiliary supervision

Specialized financial cooperatives regulation

NBFIs regulation

Azerbaijan Gambia Lao PDR Latvia Lithuania Macedonia Malawi Papua New Guinea Poland Romania Rwanda Tanzania Uzbekistan³ Vietnam Bolivia Colombia Costa Rica Philippines Uruguay Brazil Mexico Peru Russia

Cambodia Cameroon

Ghana

Dual regulatory regime

General banking regulation

Chile El Salvador Honduras India Nepal

Source: Author’s compilation. 1 Belarus as of 1998; 2 Macedonia, Romania and Viet Nam as of 1996; 3 Uzbekistan as of 2002 and 2010; and 4 Cambodia, as of 1997.

financial cooperatives, among other microfinance providers. The Core Principles provide adequate guidance for supervising banks, as well as non-bank depository financial institutions, proposing that different types of financial institutions should be regulated differently than commercial banks, especially if they do not possess a significant percentage of the financial system’s deposits. In addition, supervision can be reduced to monitoring only when there are large numbers of small non-bank depository financial institutions operating in geographically remote areas. The Guidance encourages proportionate supervision approach, so that countries can allocate supervisory resources efficiently among the financial system based on the risk associated with the financial institution on depositors and the whole financial system (BCBS, 2012: 13 and BCBS, 2015b: 5–9). Currently, there are four types of supervisory approaches adopted to monitor the financial cooperative sector in underdeveloped economies (Cuevas and Fischer, 2006: 45;

Regulation, supervision, and deposit insurance  113 Poprawa, 2009: 2–3). First approach is direct supervision by a prudential regulator over the entire sector. Second approach is direct supervision over large financial cooperatives only, while small financial cooperatives are supervised by another governmental agency (like ministries of cooperatives with limited non-prudential monitoring). Third approach is delegated or auxiliary supervision which gives the supervisory responsibility to a third party—most commonly to the national federation of financial cooperatives. Last approach is supervision by ministries of cooperatives that regulate and supervise the entire cooperative sector, including agricultural or housing cooperatives and other non-financial cooperatives. Finally, deposit insurance schemes are widely recommended to protect depositors’ assets and the total financial system from bank runs; however, the effectiveness of deposit insurance remains quite controversial. The general economic theory suggests that deposit insurance can improve the stability of banks by reducing the possibility of depositors’ runs. However, such explicit safety net of insurance may reduce market discipline and creates amoral hazard by providing incentives for banks to invest in riskier assets, without being sufficiently monitored by the depositors, because any losses incurred will be shifted from the depositors to the insurance fund (Demirgüç-Kunt and Detragiache, 2002: 1378). Several empirical findings suggest that deposit insurance schemes tend to increase banks’ instability and risk-taking behaviour and reduce monitoring of large depositors on banks (Grossman, 1992; Alston et al., 1994; Demirgüç-Kunt and Detragiache, 2002; Ioannidou and Penas, 2010). While Hovakimian et al. (2003) found that introducing deposit insurance schemes might increase risk-­ taking behaviour for banks operating in countries with weak institutional structures such as low political and economic freedoms, high corruption, and poor contract enforcement mechanisms. Contrary to that, Gropp and Vesala (2004) found that risk-taking behaviour of European banks had significantly decreased after the introduction of explicit deposit insurance. But unlike investor-owned financial institutions, there is no evidence in the literature of financial cooperatives supporting the argument that the adoption of deposit insurance schemes increases the likelihood of institutions to adopt risk-taking behaviour. That is because theoretically, the mutual ownership structure implies limited risk-taking behaviour. In investor-owned firm, shareholders are only residual claimants; thus, they have incentives to adopt riskier behaviour as they can gain benefits from higher dividends or selling shares at market value. Shares in investor-owned financial institutions are considered highly leveraged claims on the institution’s residual profits, unlike mutual institutions where shareholders are also depositors, thus their shares are unleveraged (Karels and McClatchey, 1999: 107–108). Moreover, several approaches can make deposit insurance schemes for financial cooperatives more incentive compatible and reduce agency costs and moral hazard. One approach is limited coverage that makes the insurance forces large depositors to closely monitor the performance of the institutions and

114  Regulation, supervision, and deposit insurance which will increase market discipline. Similar approach is coinsurance, in which depositors are not compensated for their total deposits, thus some of the depositors will be forced to monitor the institutions’ risk strategy as they are exposed to losses (Beck, 2004). Another commonly preferred approach is risk-based deposit insurance, where insurance premiums are adjusted to reflect the risk of the institution’s assets or capital adequacy performance (Hannafin and Mckillop, 2007: 47).

7.3.  Data and method Information on regulations governing financial cooperatives, the responsible supervisory agencies, and deposit insurance schemes in 65 underdeveloped economies were self-collected by the author for the period from 1995 to 2014. These data were mainly collected from original legislations, and only from secondary sources for view countries, like central banks reports and international monetary fund reports (and other multilateral institutions). Annex A7.4 presents a list of all laws and sources reviewed. Again, countries covered in the study are those with total population greater than 500,000 per country and are classified as ‘emerging and developing economies’ by the International Monetary Fund’s (IMF) World Economic Outlook of 2012 (IMF, 2012: 181). Tables 7.2 and 7.3 provide an overview over variables used Table 7.2  D  ata description Variable

Mean

Std. Dev. Min

Max

N

Log penetration rate Log deposit per GDP Log assets per GDP Cooperative societies’ regulation Specialized financial cooperatives regulation Dual regulatory regime General banking regulation Non-bank financial institutions regulation Cooperative societies’ supervision Auxiliary supervision Dual supervisory regime Banking authority supervision Non-bank financial institutions supervision Deposit insurance Log GDP per capita Domestic credit to private sector Financial freedom Property rights Legal origin Region

–1.50 –2.64 –2.46 0.40 0.44

0.75 0.92 0.91 0.49 0.50

0.09 0.01 0.05

0.29 0.12 0.23

0 0 0

1 1 1

1108 1108 1108

0.36 0.14 0.16 0.18 0.15

0.48 0.35 0.36 0.39 0.36

0 0 0 0 0

1 1 1 1 1

1108 1108 1108 1108 1108

0.28 3.17 0.34 0.48 0.41 0.86 2.42

0.45 0.47 0.26 0.16 0.16 0.72 1.24

0 2.10 0.01 0.1 0.05 0 1

1 4.05 1.66 0.9 0.9 2 4

1108 1108 1108 1108 1108 1108 1108

–4.47 –0.11 1108 –6.00 –0.92 1065 –5.71 –0.83 1035 0 1 1108 0 1 1108

The total number of financial cooperatives’ members in a country obtained from the WOCCU, as percentage of the total economically active population, obtained from International Labour Organization statistics. The variable was log transformed to normalize data distribution. The total deposits of financial cooperatives in a country, reported by the WOCCU, as percentage of the GDP at market prices. The variable was log transformed. The total assets of financial cooperatives in a country, reported by the WOCCU, as percentage of the GDP at market prices. The variable was log transformed.

Banking authority supervision Dual supervisory regime

Non-bank financial institutions regulation Cooperative societies supervision Non-bank financial institutions supervisory authority

Specialized financial cooperatives regulation General Banking regulation Dual regulatory regime

Cooperative society’s regulation

(Continued)

A dummy variable that takes the value of 1 if financial cooperatives are fully regulated under a general cooperative society’s law that regulate the operations of all forms of organizations with a cooperative ownership structure, without any special provisions for financial cooperatives concerning credit and deposit services, and capital requirements, or statutory provisions concerning financial intermediation activities. A dummy variable that takes the value of 1 if financial cooperatives are regulated by a specialised law or regulated under special or detailed provisions under a non-specialised financial cooperatives law. A dummy variable that takes the value of 1 if financial cooperatives are fully regulated by the banking law. A dummy variable that takes the value of 1 if the financial cooperative sector is regulated by two separate legal frameworks, that is some financial cooperatives are regulated under a general cooperative law, while other financial cooperatives are regulated by the banking law, based on specific criteria (based on assets size, minimum capital requirements, providing services to non-members). A dummy variable that takes the value of 1 if financial cooperatives are fully regulated by a law regulating other nonbank financial institutions (e.g. microfinance laws). A dummy variable that takes the value of 1 if financial cooperatives are supervised by a government authority that supervises and monitors all types of cooperative organizations. A dummy variable that takes the value of 1 if financial cooperatives are supervised by a government authority that supervises and monitors other non-bank financial institutions (microfinance institutions). Noting that I did not include a separate dummy variable for a specialised financial cooperative supervisory authority, because in our sample special governmental supervisory authorities supervise only financial cooperatives in Kenya and South Africa. A dummy variable that takes the value of 1 if financial cooperatives are supervised by banking authorities (e.g. central bank or bank superintendent). A dummy variable that takes the value of 1 if financial cooperatives by two different supervisory authorities, that is some financial cooperatives are supervised by a general cooperative supervisor (e.g. ministry), while other financial cooperatives are supervised by the banking authorities, based on specific criteria (e.g. based on assets size, minimum capital requirements, providing services to non-members).

Regulations, supervision, and deposit insurance variables (explanatory variables)

Total assets per GDP1

Total deposits per GDP

Penetration rate

Financial cooperatives variables (dependent variables)

Table 7.3  I nformation on the data sources and variables used in the analysis

1 Missing data for total assets in West African countries (Benin, Burkina Faso, Cote d’voire, Guinea Bissau, Mali, Niger, Senegal, and Togo) were calculated using average total assets to total savings ratio from other available years of the same country. 2 Data for Uzbekistan were collected from the International Monetary Fund country reports (2006 No. 07/133; 2008 No. 08/235; and 2013 No. 13/278) and for Zimbabwe from the Central bank, under domestic statistics (available at www.rbz.co.zw/assets/monthly-economic-data-from-2009-to-date.pdf).

Geographic region

Legal origin

Financial freedom

Domestic credit to private sector by banks as (%GDP)2 Property rights

This indicator is obtained from the Index of Economic Freedom released by the Heritage Foundation, and measures the degree to which private property rights are secured by clear and enforceable laws or not, and evaluates the independence and corruption of the judiciary, as well as the ability of individuals and firms to enforce contracts. This indicator is obtained from the Index of Economic Freedom released by the Heritage Foundation, which measures the independence of the banking sector from government control and interference. A dummy variable that takes the value of 0 if the country’s legal system is based on British common law, the value of 1 for French civil law origins, and the value of 2 for socialist laws. Data obtained from La Porta et al. (1999). A dummy variable that takes the value of ‘0’ for African countries, ‘1’ for countries from Latin America and the Caribbean, ‘2’ for Asian countries, and ‘3’ for European countries.

Calculated as the annual GDP divided by midyear population of a country. Data are in constant 2005 U.S. dollars as obtained from the World Bank Open Data. This variable was log transformed. Financial resources provided by depository institutions to the private sector that create a claim for repayment, as percentage of the GDP at market prices. Data obtained from World Bank Open Data.

GDP per capita

Control variables

Deposit insurance

A dummy variable that takes the value of 1 if financial cooperatives are supervised by indirect supervisory approach, where the responsible authority allows another organisation to take defined supervisory responsibilities. A dummy variable that takes the value of 1 if financial cooperatives’ deposits are covered by a deposit insurance scheme or other similar arrangements.

Auxiliary supervision

Financial cooperatives variables (dependent variables)

Regulation, supervision, and deposit insurance  117 to measure financial cooperatives development, as well as the classification of regulatory, supervisory, and deposit insurance variables, and the control. The relationship between financial cooperatives indicators and the type of regulation that governs them, the supervisory agency responsible to monitor their activities, and the existence of a deposit insurance scheme was measured using panel data for the period from 1995 to 2014. Panel data are convenient in this study to observe how changes in financial cooperatives’ regulations, supervisory authority, or the introduction of deposit insurance scheme affect the changes in size and depth of the sector in the economy. For each investigation (regulation, supervision, and deposit insurance), three tests are reported in Panels A, B, and C in Tables 7.4, 7.5, and 7.6 and A7.1, A7.2, and A7.3. In Panel A, the dependent variable represents the logarithm of indicators used as proxy for the development of the financial cooperative sector. Namely, the dependent variables are log(penetration rate), log(deposits per GDP), and log(assets per GDP). Since there are three main tests in the study, the explanatory variables represent dummy variables for laws regulating financial cooperatives in the first test; the responsible supervisory agency in the second test; and the existence of deposit insurance scheme in the last test. In addition, the explanatory variables include a set of variables to control for GDP per capita, domestic credit provided to private sector as percentage of the GDP, legal origin, and geographic region. The control variables were selected following findings from Chapter 5. Accordingly, the GDP growth rate, inflation rate, unemployment rate, and percentage of urban population were excluded from the estimations here for weak or lack of statistical significant correlations with financial cooperatives’ indicators. Panels B explain the effect of changing financial cooperatives’ regulatory framework or supervisory approaches or introducing deposit insurance schemes in year (t–1) on the growth of financial cooperatives’ indicators in year t. Thus, the dependent variable in Panels B are the change in financial cooperatives’ indicators using the first difference of log(penetration rate), log(deposits per GDP), and log(assets per GDP). The changes in financial cooperatives’ indicators are regressed against the first lag of the indicators and the first lag of the main explanatory variables (regulations, supervisions, and deposit insurance) in addition to the control variables used in Panels A regressions. Finally, Panels C report results of reversed regressions, to explore whether the size and depth of the sector predetermine the type of regulatory and supervisory approaches and the presence of deposit insurance schemes or not. The reversed regressions also show if the presence of deposit insurance or a specific regulatory and supervisory approach is associated with the level of economic development of a country or the size of its financial sector. For that, the dependent variables in the regressions of Panels C are the dummy variables that represent the type of financial cooperatives regulation and supervision and the presence of deposit insurance. These variables are regressed against the first lags of: financial cooperatives

118  Regulation, supervision, and deposit insurance indicators, GDP per capita, domestic credit provided to private sector, besides the control variables mentioned before. Regression results obtained only from the fixed-effects estimations are reported following Hausman-test results and the high correlation between the country-specific effects µi and the explanatory variables X found in all the regressions, all which suggest fixed-effects estimations to be more efficient than random-effects estimations for the analysis. The random-effects results are reported in the appendices. Moreover, the R-squared within in the baseline regressions (Panels A) range from 29.8% to 38.6%, noting that the reported R-squared ‘within’ obtained from fixed-effects estimations are equivalent to ordinary R-squared of OLS regressions. Table 7.2 provides a brief statistical description on the variables included in the model, and Table 7.3 gives an overview on the data sources and variables used in the analysis.

7.4.  Results and discussion 7.4.1.  Financial cooperatives regulations Table 7.4 shows regression results that examine the relationship between indicators of financial cooperatives and the type of regulation governing their activities. In Panel A, each of the three indicators (natural logarithm of penetration rate, deposits per GDP, and assets per GDP) are regressed against dummy variables representing the type of the relevant regulation. The main explanatory variables are dummy variables representing specialised financial cooperative regulation; dual regulatory regime; banking regulation, non-bank financial institutions (NBFIs) regulation; and general cooperative society’s regulation, in addition to a set of variables to control for GDP per capita, credit to private sector, financial freedom, and property rights. In Panel B, the changes in financial cooperatives’ indicators are regressed against the first lag of the main explanatory variables, and the first lag of the financial cooperative indicator to control for the impact of the sector’s size and outreach on its growth. Finally, Panel C reports the reversed regressions. Columns (1), (6), and (11) in Panels A and B of Table 7.4 suggest a positive statistical correlation between the existence of a specialized financial cooperative regulation and higher members’ penetration rate, deposits per GDP and assets per GDP. Panel B suggests that countries with specialised financial cooperative regulation have experienced positive change in the sector’s penetration rate, deposits and assets per GDP. The results support the argument that a specialised regulation may boost the growth and outreach of the sector, because financial cooperatives need a different legal framework that addresses their unique economic objectives and their distinctive ownership structure that differ from traditional investor-owned financial institutions and also other types of cooperative organisations. Results of Panel C suggest also that countries with high penetration rates are most likely to be regulated by a specialised regulation in the following year. Thus, it might

F-stat No. of obs. No. of groups R2 Corr (μi,X)

Cooperative societies regulation GDP per capita   Credit to private sector Financial freedom   Property rights   Constant

NBFI regulation

Bank regulation

Dual regulation

FC regulation

Dependent variable

(0.258) −1.438*** (0.296) −5.955*** (1.374) 17.01***

0.357 −0.704

(0.220) 0.655**

(0.261) −1.419*** (0.297) −6.095*** (1.387) 13.78***

0.356 −0.715

(0.222) 0.692***

(0.242) −1.349*** (0.280) −5.454*** (1.368) 15.05*** 1108 65 0.378 −0.664

(0.234) 0.677**

(0.431) 0.676***

(0.437) 0.698***

(0.432) 0.685***

1.416***

(0.152)

−0.196

(3)

1.455***

(0.092)

0.096

(2)

1.208***

0.248** (0.102)

(1)

0.355 −0.711

(0.256) −1.425*** (0.296) −5.997*** (1.372) 22.56***

(0.219) 0.660**

(0.431) 0.716***

1.424***

(0.048)

0.063

(4)

Log penetration rate

0.386 −0.660

(0.240) −1.257*** (0.280) −5.187*** (1.407) 15.54***

(0.215) 0.597**

(0.434) 0.691***

1.200***

−0.316*** (0.110)

(5)

(0.272) −1.692*** (0.371) −6.986*** (1.620) 15.75*** 1065 65 0.320 −0.650

(0.272) 1.270***

(0.520) 0.799***

1.271**

0.278** (0.138)

(6)

0.306 −0.703

(0.273) −1.734*** (0.369) −7.727*** (1.631) 15.82***

(0.263) 1.218***

(0.521) 0.796***

1.552***

(0.148)

0.187

(7)

0.322 −0.668

(0.273) −1.791*** (0.366) −7.346*** (1.598) 17.50***

(0.284) 1.270***

(0.508) 0.688**

1.451***

(0.320)

–0.732**

(8)

Log deposit per GDP

Panel A: fixed-effects regressions for financial cooperatives indicators against regulations

0.304 −0.698

(0.272) −1.761*** (0.369) −7.573*** (1.622) 28.66***

(0.262) 1.240***

(0.519) 0.832***

1.504***

(0.051)

0.048

(9)

Table 7.4  Fixed-effects regression results for financial cooperatives indicators and regulations

0.316 −0.658

(0.260) −1.624*** (0.372) −6.902*** (1.657) 15.61***

(0.266) 1.182***

(0.522) 0.808***

1.320**

−0.266*** (0.120)

(10)

(0.263) −1.666*** (0.306) −7.269*** (1.571) 16.23*** 1035 65 0.334 −0.687

(0.256) 1.083***

(0.506) 0.679**

1.453***

0.227** (0.121)

(11)

0.323 −0.723

(0.280) −1.706*** (0.322) −7.800*** (1.586) 16.27***

(0.253) 1.030***

(0.506) 0.697***

1.660***

(0.154)

0.110

(12)

0.333 −0.701

(0.274) −1.744*** (0.317) −7.547*** (1.559) 18.58***

(0.270) 1.066***

(0.495) 0.609**

1.594***

(0.250)

−0.527**

(13)

Log assets per GDP

0.322 −0.719

(0.272) −1.720*** (0.319) −7.701*** (1.573) 48.66***

(0.251) 1.042***

(0.502) 0.715***

1.629***

(0.040)

0.058

(14)

(Continued)

0.332 −0.691

(0.255) −1.602*** (0.304) −7.178*** (1.616) 15.76***

(0.252) 1.003***

(0.509) 0.694***

1.486***

−0.223** (0.110)

(15)

Constant

(2)

(3)

(4)

Change in log penetration rate (5)

0.136 −0.827

0.132 −0.833

(0.047) 0.100 (0.104) −0.227*** (0.068) 0.105

(0.064) −0.470 (0.358) 7.13***

(0.043) 0.108 (0.104) −0.220*** (0.067) 0.099

(0.046) 0.062 (0.099) −0.213*** (0.067) 0.115*

−0.029

(0.073)

−0.094

(0.030)

(0.063) −0.499 (0.358) 7.26***

−0.011

(0.041)

0.005

(0.030)

−0.011

0.062** (0.024)

(0.030)

0.133 −0.835

(0.063) −0.478 (0.359) 7.73***

(0.044) 0.101 (0.104) −0.219*** (0.067) 0.094

−0.009

(0.011)

0.041***

(0.030)

0.142 −0.848

(0.059) −0.373 (0.355) 7.98***

(0.044) 0.070 (0.104) −0.202*** (0.066) 0.094

(0.024) −0.005

−0.071***

(0.031)

−0.165*** −0.157*** −0.158*** −0.157*** −0.168***

(1)

(0.060) −0.404 (0.340) F-stat 7.12*** No. of obs. 1007 No. of countries 65 0.141 R2 −0.844 Corr (μ i,X)

Financial freedom

Property rights

Log penetration rate (t-1) Log deposits per GDP (t-1) Log assets per GDP (t-1) FC regulation (t-1) Dual regulation (t-1) Bank regulation (t-1) NBFI regulation (t-1) Cooperative Societies regulation (t-1) Credit to private sector GDP per capita

Dependent variable (7)

(8)

(9)

(10)

(0.120) −0.497 (0.646) 6.14*** 949 65 0.210 −0.844

(0.080) −0.085 (0.176) −0.400** (0.151) 0.301**

0.213**

0.099** (0.046)

(0.050)

0.202 −0.836

(0.116) −0.645 (0.655) 6.02***

(0.079) −0.013 (0.179) −0.411*** (0.148) 0.270**

0.216**

(0.047)

0.011

(0.049)

0.211 −0.837

(0.119) −0.619 (0.653) 6.05***

(0.088) −0.023 (0.178) −0.438*** (0.147) 0.294**

0.168**

(0.144)

−0.264*

(0.051)

0.203 −0.838

(0.115) −0.606 (0.650) 6.07***

(0.079) −0.026 (0.177) −0.410*** (0.148) 0.263**

0.219***

(0.024)

0.066***

(0.049)

0.208 −0.841

(0.112) −0.453 (0.649) 5.92***

(0.075) −0.069 (0.177) −0.379** (0.153) 0.263**

(0.038) 0.215***

−0.093**

(0.050)

−0.269*** −0.262*** −0.272*** −0.263*** −0.268***

(6)

Change in log deposit per GDP

Panel B: fixed-effects regressions for change in financial cooperatives indicators against regulations

(12)

(13)

(14)

(15)

(0.107) −0.928 (0.699) 4.99*** 917 65 0.208 −0.877

(0.091) 0.067 (0.189) −0.439*** (0.143) 0.280**

0.195**

0.200 −0.880

(0.105) −1.037 (0.721) 4.93***

(0.090) 0.124 (0.194) −0.459*** (0.142) 0.260**

0.212**

(0.073)

0.206 −0.877

(0.109) −1.043 (0.720) 4.90***

(0.099) 0.126 (0.194) −0.473*** (0.141) 0.269**

0.170*

(0.148)

−0.194

0.201 −0.879

(0.104) −1.031 (0.719) 5.35***

(0.090) 0.121 (0.194) −0.452*** (0.142) 0.247**

0.209**

(0.019)

0.069***

0.205 −0.876

(0.101) −0.907 (0.711) 4.88***

(0.085) 0.086 (0.192) −0.420*** (0.144) 0.248**

(0.036) 0.203**

−0.081**

−0.278*** −0.272*** −0.279*** −0.273*** −0.277*** (0.059) (0.059) (0.060) (0.059) (0.060) 0.097** (0.048) −0.028

(11)

Change in log assets per GDP

0.060

(0.136) 0.679**

(0.292) −0.119 (0.197) −0.110

(0.206) −1.459 (0.946) 2.99** 972 65

0.111 −0.542

0.060

(0.133) 0.666**

(0.280) −0.144 (0.203) −0.132

(0.206) −1.409 (0.912) 3.40*** 1007 65

0.122 −0.549

(0.040)

0.108 −0.511

(0.193) −1.363 (0.926) 2.93** 943 65

(0.283) −0.111 (0.205) −0.188

(0.130) 0.651**

0.059 (0.041) 0.095

0.023 −0.406

(0.139) 0.785 (0.576) 0.85 1007 65

(0.197) −0.078 (0.136) 0.131

(0.088) −0.231

0.127

(0.019)

0.062

(4)

(0.053)

(3)

0.022

(2)

0.100*

(1)

FC regulation

0.028 −0.379

(0.135) 0.748 (0.666) 0.76 972 65

(0.215) −0.107 (0.118) 0.117

(0.083) −0.209

0.131

(0.017)

0.020

(5)

0.029 −0.392

(0.121) 0.727 (0.663) 0.90 943 65

(0.213) −0.132 (0.129) 0.187

(0.076) −0.213

0.014 (0.017) 0.127

(6)

Dual regulation

0.055 −0.759

(0.023) 0.264 (0.206) 0.82 1007 65

(0.058) −0.057 (0.041) 0.030

(0.107) −0.071

−0.131

(0.019)

−0.017

(7)

0.073 −0.649

(0.041) 0.080 (0.210) 0.67 972 65

(0.052) −0.079 (0.064) 0.046

(0.111) −0.033

−0.113

(0.028)

−0.031

(8)

0.063 −0.676

(0.032) 0.141 (0.205) 0.66 943 65

(0.053) −0.065 (0.055) 0.030

(0.111) −0.044

−0.025 (0.024) −0.122

(9)

Bank regulation

0.018 −0.466

(0.147) −0.475 (0.489) 0.70 1007 65

(0.160) −0.033 (0.037) 0.107

(0.036) 0.164

−0.042

(0.008)

0.009

(10)

0.019 −0.477

(0.161) −0.514 (0.471) 0.66 972 65

(0.157) −0.038 (0.046) 0.111

(0.035) 0.177

−0.040

(0.006)

0.005

(11)

0.019 −0.471

(0.166) −0.493 (0.483) 0.67 943 65

(0.161) −0.050 (0.052) 0.112

(0.035) 0.172

0.006 (0.006) −0.039

(12)

NBFI regulation

−0.038

(0.029)

−0.054*

(14)

0.150 −0.458

(0.215) 1.835** (0.820) 3.14** 1007 65

(0.247) 0.312 (0.196) −0.136

0.136 −0.509

(0.222) 2.145*** (0.799) 2.88** 972 65

(0.246) 0.343* (0.198) −0.163

(0.108) (0.109) −0.529** −0.613**

−0.014

(0.051)

−0.115**

(13)

0.127 −0.474

(0.232) 1.988** (0.782) 2.78** 943 65

(0.241) 0.358* (0.200) −0.142

(0.111) −0.566**

−0.054 (0.033) −0.060

(15)

Cooperative regulation

*, **, and *** indicate statistical significance at the 10%, 5%, and 1% level respectively, while no asterisk means the coefficient is not statistically significantly different from zero. Standard errors in parentheses.

F-stat No. of obs. No. of countries R2 Corr (μ i,X)

Log penetration rate (t-1) Log deposits per GDP (t-1) Log assets per GDP (t-1) Credit to private sector (t-1) GDP per capita (t-1) Property rights (t-1) Financial freedom (t-1) Constant

Dependent variable

Panel C: fixed-effects regressions for financial cooperatives regulations

122  Regulation, supervision, and deposit insurance also be the case that high penetration rates push governments to introduce specialised laws (or detailed provisions in existing laws) for regulating the sector, as it becomes economically and politically significant. It is difficult to claim with certainty that changes in the type of regulation has a causal effect on the growth of the sector, as generally, the results of fixed-effects regressions do not prove causation, thus it does not imply that a specialised regulation is necessarily leading the growth of the sector. Similar arguments apply also considering the negative correlations discussed below between the size of sector and cooperative societies’ regulations or banking regulations. Nevertheless, the results are coherent with arguments made by Poyo (2000), Jansson et al. (2004: 50), Cuevas and Fischer (2006), Branch and Grace (2008), and WOCCU (2015) that members-owned financial institutions should be regulated under specialised legal framework that addresses their special contractual arrangements, and the distinctive form of agency conflicts inherited in their structure. A specialised regulation should also take into account the risks faced by financial cooperatives which differ from risks faced by other types of cooperatives or investor-owned financial institutions, so that for instance, they require different licensing criteria, capital requirements, monitoring procedures, and risk management standards. The results are also consistent with Cull et al. (2011) who—though not focusing on financial cooperatives—found that profit-oriented microfinance institutions tend to limit their outreach to cover the costs of compliance with prudential regulations while maintaining the same profit rates. In contrast, not-for-profit microfinance institutions are more likely to reduce their profit rates to maintain the same outreach levels. Similarly, the findings of Akande et al. (2016) indicate the need for microfinance regulations to distinguish between the different institutional types of microfinance providers in Africa. It is not surprising then that Columns (5), (10), and (15) in Panels A and B of Table 6.4 indicate a negative statistical correlation between financial cooperatives’ penetration rate, deposits and assets per GDP on one hand and general cooperative society’s regulation on the other hand. That is because a unified general cooperative society’s law that regulate the operation of all cooperative organisations is usually inadequate for financial intermediation activities (Cuevas and Fischer, 2006: 33; Branch and Grace, 2008: 4; WOCCU, 2015: 10). In addition, in many underdeveloped economies there were no tangible reforms introduced to cooperative society’s regulations since they were originally adopted in the 1960s and 1970s, making them insufficient for financial cooperatives (Poyo, 2000: 142). While Hartarska and Nadolnyak (2007) did not find a direct impact for financial regulations on the profitability or outreach of microfinance institutions, they suggested an indirect effect for regulations as they found that high leveraged institutions are able to reach more borrowers. Such argument is also relevant for financial cooperatives, as adequate financial regulation—contrary to general cooperative regulations—will enhance the cooperatives’ ability to attract deposits or seek external funds and thus increase their services’ outreach.

Regulation, supervision, and deposit insurance  123 The results of Columns (8) and (13) in Panel A suggest that laws regulating traditional commercial banks are not associated with high indicators of financial cooperatives, with significant high negative correlations between the presence of a banking regulation and financial cooperatives’ deposits and assets per GDP. In addition to a negative correlation between the change in deposits per GDP and commercial banking regulation reported in and Column (8) in Panel B. These results are not entirely unexpected, as Poyo (2000: 138) and Branch and Grace (2008: 3) have pointed out that financial cooperatives require prudential regulations that differ from traditional commercial banks regulations due to their governance structure, the geographic or sectoral concentration of their loan portfolios, and their focus on micro and small entrepreneurs. Adams (1999: 44) noted that bank-supervising authorities in many developing countries struggle to maintain effective monitoring over commercial banks in the first place, and it is not clear if they have the technical capacity to perform adequate supervision over financial cooperatives as well. In addition, banking authorities in developing countries may impose rules and practices that suit commercial banks but not necessarily adequate for financial cooperatives (Cuevas and Fischer, 2006: 32). Commercial banking regulations may ignore the distinctive structure of financial cooperatives, especially in terms of capital requirements and governance structures. Traditional banking regulations may also impose regulatory burdens that are unreasonable for the non-complex activities of financial cooperatives. On the other hand, the results do not provide supporting evidence to Poyo (2000), WOCCU (2015: 10), and Branch and Grace (2008: 4) argument that legislations intended to govern the operations of all microfinance institutions do not consider the cooperative nature of financial cooperatives and their orientation to mobilise and promote deposit services. In fact, results of Panel B suggest that financial cooperatives regulated by a NBFI regulation have witnessed growth in their penetration rate, deposits and assets per GDP. Results in Panel A do not indicate any significant correlation between financial cooperatives’ indicators and non-bank financial institutions law or dual regulatory framework. Nevertheless, it is important to emphasise that designing a unified law that regulates cooperatives and other microfinance providers should respect the different institutional structure of each type of organisation. More specifically, a unified microfinance law should enable institutional integration among financial cooperatives to form advanced networks and to be able to provide full banking services to their members and not just microfinance services. Thus, equal treatment does not imply identical treatment but unbiased treatment.2 Finally, Panel C shows a positive correlation between specialised financial cooperatives regulation and GDP per capita, statistically significant at 5% level. There is a negative correlation between cooperative societies’ regulation and GDP per capita, also statistically significant at 5% level. Together with the results of Panels A and B, it seems clearly that countries with high GDP per capita tend to have well-developed financial cooperative sector regulated under specialised law instead of a general cooperative law.

124  Regulation, supervision, and deposit insurance The results also demonstrate that the size of the financial sector, as well as property rights and financial freedom do not play major roles in determining the type of law that regulates financial cooperatives. 7.4.2.  Financial cooperatives supervisory authority Table 7.5 presents regression results exploring the correlation between financial cooperatives development—measured by the indicators discussed ­earlier—and the responsible supervisory authority, or the supervision model adopted in case of auxiliary and dual supervision. In these regressions, each of the three financial cooperatives’ indicators were regressed on dummy variables representing the supervisory approach adopted, which are divided into: non-bank financial supervisory authority; dual supervision regime; banking supervisory authority; auxiliary supervision; and cooperative society’s supervisory authority, in addition to the same set of control variables. There is no separate dummy variable for a specialised financial cooperatives supervisory authority because only Kenya and South Africa had special authorities that supervise only financial cooperatives.3 Nevertheless, there is no statistical significant correlation between financial cooperatives’ indicators and a dummy variable constructed for the specialised supervision adopted in Kenya and South Africa (not included in the reported results). Columns (1), (6), and (11) in Panels A and B demonstrate how financial cooperatives supervised by NBFIs supervisory authorities tend to have higher penetration rates with statistical significant positive correlation at the 5% and is positively correlated with high deposits and assets per GDP statistically significant at 10%. Panel B suggests that financial cooperatives supervised by NBFI supervisor are more likely to have positive changes in the size and outreach of the sector. These correlations between the changes in the three financial cooperatives’ indicators and non-bank financial supervision are strongly significant at the 1% level. Whereas, the rest of the regression results do not suggest any statistical significant correlations between indicators of financial cooperatives and other supervisory approaches, namely dual supervision regime; banking supervisory authority, auxiliary supervision; and cooperative society’s supervisory authority. The exception is a negative correlation between penetration rate and the dummy variable of cooperative societies’ supervision at the 5% level. Similar result is obtained from Panel B, suggesting negative correlation between the change in penetration rate and cooperative societies’ supervision. These results are in line with argument that authorities responsible for the promotion and regulation of general cooperative societies may lack the required capacity to conduct sufficient prudential supervision over financial intermediary institutions, thus may hinder the development of financial cooperatives (Adams, 1999: 44; Poyo, 2000; Cuevas and Fischer, 2006: 32; BCBS, 2015a: 20). In addition, Column (13) in Panel B shows a negative correlation between the change in financial cooperatives’ assets per GDP and banking supervision, significant

(1)

NBFI 0.360** supervision   (0.161) Dual supervision   Bank supervision   Auxiliary supervision   Cooperative societies  supervision GDP per capita 1.360***   (0.434) 0.643*** Credit to private sector   (0.191) Financial 0.673** freedom   (0.255) Property –1.286*** rights   (0.266) Constant –5.884***   (1.372) F-stat 15.57*** No. of obs. 1108 No. of countries 65 0.381 R 2 (within) –0.669 Corr (μ i, X)

Dependent variable

1.441*** (0.427) 0.715***

(0.219) 0.675**

(0.258) –1.427***

(0.294) –6.047*** (1.358) 14.24***

0.355 –0.714

(0.219) 0.669**

(0.257) –1.431***

(0.295) –6.026*** (1.366) 13.82***

0.355 –0.714

(0.131)

–0.026

(3)

1.434*** (0.430) 0.715***

(0.132)

–0.016

(2)

(0.216) 0.635**

(0.139) 1.326*** (0.435) 0.704***

–0.226**

(5)

(0.245) 1.245***

1.455*** (0.515) 0.765*** (0.261) 1.248***

1.522*** (0.519) 0.833***

(0.181)

(0.262) 1.256***

1.522*** (0.518) 0.831***

(0.240)

–0.040

(0.264) 1.251***

1.514*** (0.518) 0.838***

(0.309)

0.042

(0.264) 1.213***

(0.151) 1.414*** (0.520) 0.822***

–0.201

(10)

(11)

(0.228) 1.059***

1.573*** (0.498) 0.651***

(0.161)

–0.099

(9)

(0.183)

(8) 0.304*

(7)

0.328*

(6)

Log deposit per GDP

(0.251) 1.054***

1.647*** (0.501) 0.717***

(0.159)

–0.115

(12)

(0.252) 1.065***

1.652*** (0.500) 0.714***

(0.186)

–0.074

(13)

(0.244) 1.040***

1.631*** (0.499) 0.698***

(0.250)

–0.089

(14)

Log assets per GDP

(0.251) 1.038***

(0.143) 1.591*** (0.508) 0.708***

–0.114

(15)

0.356 –0.707

(0.296) –5.983*** (1.369) 14.08*** 0.368 –0.693

(0.278) –5.625*** (1.402) 14.00***

(0.355) –7.486*** (1.603) 16.31*** 1065 65 0.315 –0.667

0.304 –0.704

(0.367) –7.608*** (1.618) 16.17***

0.304 –0.700

(0.368) –7.628*** (1.620) 15.87***

0.304 –0.702

(0.369) –7.614*** (1.630) 15.87***

0.310 –0.682

(0.365) –7.230*** (1.640) 15.45***

(0.294) –7.610*** (1.551) 17.27*** 1035 65 0.335 –0.691

0.323 –0.725

(0.315) –7.734*** (1.567) 16.77***

0.322 –0.721

(0.319) –7.771*** (1.569) 16.30***

0.322 –0.716

(0.318) –7.683*** (1.571) 16.72***

(Continued)

0.324 –0.713

(0.300) –7.552*** (1.603) 16.56***

(0.257) (0.256) (0.268) (0.270) (0.272) (0.270) (0.267) (0.269) (0.270) (0.270) (0.270) (0.266) –1.433*** –1.327*** –1.659*** –1.779*** –1.760*** –1.763*** –1.681*** –1.590*** –1.739*** –1.713*** –1.727*** –1.674***

(0.210) 0.660**

1.426*** (0.429) 0.702***

(0.175)

–0.079

(4)

Log penetration rate

Panel A: fixed-effects regressions for financial cooperatives indicators against supervision

Table 7.5  Fixed-effects regression results for financial cooperatives indicators and supervision

(2)

(3)

–0.017

(0.045) 0.108 (0.105) –0.220*** (0.068) 0.101

(0.064) –0.500 (0.361) 7.37***

0.132 –0.832

(0.064) –0.491 (0.359) 7.78***

0.132 –0.827

–0.010

(0.044) 0.104 (0.105) –0.218*** (0.067) 0.099

–0.010

(0.038)

–0.006

0.132 –0.836

(0.063) –0.502 (0.360) 7.33***

(0.045) 0.107 (0.104) –0.219*** (0.068) 0.101

–0.008

(0.047)

0.015

0.139 –0.842

(0.063) –0.403 (0.353) 8.45***

(0.043) 0.081 (0.103) –0.204*** (0.066) 0.095

–0.009

(0.025)

–0.067**

(0.114) –0.620 (0.639) 7.01*** 949 65 0.210 –0.840

(0.081) –0.034 (0.174) –0.390** (0.147) 0.274**

0.197**

(0.053)

(0.049)

(0.030)

(0.042)

(7)

(8)

(9)

(10)

Change in log deposit per GDP

0.202 –0.833

(0.116) –0.631 (0.650) 6.02***

(0.079) –0.019 (0.178) –0.409*** (0.151) 0.271**

0.217***

(0.055)

0.022

(0.049)

0.208 –0.827

(0.111) –0.714 (0.617) 7.48***

(0.079) 0.008 (0.169) –0.397*** (0.148) 0.297**

0.219***

(0.079)

–0.120

(0.048)

0.204 –0.838

(0.115) –0.668 (0.647) 6.21***

(0.079) –0.012 (0.176) –0.408*** (0.149) 0.279**

0.228***

(0.096)

0.066

(0.049)

0.204 –0.836

(0.116) –0.541 (0.650) 6.02***

(0.078) –0.041 (0.177) –0.396** (0.151) 0.265**

0.215***

(0.042)

–0.062

(0.049)

–0.269*** –0.262*** –0.263*** –0.262*** –0.264***

(6)

0.142***

0.024

(5)

–0.156*** –0.162*** (0.030) (0.029)

(4)

0.068**

–0.164*** –0.156*** –0.156*** (0.030) (0.029) (0.029)

(0.045) 0.101 (0.105) Property rights –0.209*** (0.068) Financial 0.102 freedom (0.064) Constant –0.502 (0.359) F-stat 7.70*** No. of obs. 1007 No. of countries 65 2 0.138 R (within) –0.833 Corr (μ i, X)

Log penetration rate (t-1) Log deposits per GDP (t-1) Log assets per GDP (t-1) NBFI supervision (t-1) Dual supervision (t-1) Bank supervision (t-1) Auxiliary supervision (t-1) Cooperative societies supervision (t-1) Credit to private sector GDP per capita

(1)

Change in log penetration rate

Panel B: fixed-effects regressions for change in financial cooperatives indicators against supervision

(12)

(13)

(14)

(15)

(0.105) –1.054 (0.705) 5.95*** 917 65 0.209 –0.875

(0.088) 0.113 (0.190) –0.420*** (0.140) 0.262**

0.188**

(0.044)

0.200 –0.882

(0.106) –1.067 (0.723) 4.88***

(0.090) 0.134 (0.196) –0.460*** (0.143) 0.256**

0.209**

(0.057)

–0.027

0.207 –0.875

(0.105) –1.123 (0.708) 6.58***

(0.090) 0.150 (0.192) –0.435*** (0.142) 0.280**

0.211**

(0.071)

–0.133*

0.201 –0.881

(0.104) –1.080 (0.713) 5.04***

(0.091) 0.133 (0.193) –0.451*** (0.142) 0.261**

0.216**

(0.090)

0.053

0.201 –0.876

(0.105) –0.986 (0.722) 5.04***

(0.088) 0.111 (0.195) –0.437*** (0.143) 0.252**

0.204**

(0.042)

–0.053

–0.280*** –0.273*** –0.274*** –0.271*** –0.273*** (0.059) (0.059) (0.058) (0.059) (0.059) 0.132***

(11)

Change in log assets per GDP

0.144

(0.094) 0.160

(0.163) –0.197

(0.131) –0.089

(0.093) –0.177 (0.508) 1.45 972 65

0.072 –0.424

0.121

(0.088) 0.127

(0.176) –0.206

(0.148) –0.099

(0.094) –0.035 (0.568) 1.68 1007 65

0.090 –0.302°

(0.027)

0.089 –0.403

(0.102) –0.144 (0.541) 1.61 943 65

(0.161) –0.114

(0.171) –0.274*

(0.099) 0.169

0.048 (0.034) 0.153

0.009 –0.019

(0.026) –0.078 (0.265) 0.69 1007 65

(0.095) 0.028

(0.087) –0.082

(0.041) 0.081

0.010

(0.018)

0.039

(4)

(0.048)

(3)

0.000

(2)

0.082*

(1)

NBFI supervision

0.017 –0.109

(0.026) –0.204 (0.291) 0.69 972 65

(0.085) 0.026

(0.091) –0.129

(0.043) 0.120

0.017

(0.011)

–0.007

(5)

0.011 –0.116

(0.032) –0.176 (0.313) 0.76 943 65

(0.101) 0.046

(0.098) –0.113

(0.042) 0.105

–0.010 (0.013) 0.018

(6)

Dual supervision

0.034 –0.340

(0.115) –0.731 (0.640) 1.10 1007 65

(0.124) 0.244**

(0.187) –0.027

(0.074) 0.245

0.043

(0.025)

–0.010

(7)

0.034 –0.321

(0.120) –0.655 (0.586) 1.11 972 65

(0.138) 0.246**

(0.173) –0.003

(0.072) 0.226

0.027

(0.035)

0.002

(8)

0.026 –0.256

(0.110) –0.442 (0.547) 0.92 943 65

(0.123) 0.205*

(0.161) 0.064

(0.072) 0.156

0.005 (0.030) 0.030

(9)

Bank supervision

0.039 –0.232

(0.048) 0.441 (0.383) 1.10 1007 65

(0.069) –0.096*

(0.120) –0.007

(0.097) –0.066

–0.178*

(0.038)

–0.019

(10)

0.037 –0.258

(0.056) 0.502 (0.353) 1.11 972 65

(0.080) –0.101*

(0.113) 0.022

(0.101) –0.077

–0.192*

(0.036)

0.000

(11)

0.042 –0.147

(0.052) 0.360 (0.328) 1.10 943 65

(0.079) –0.095*

(0.108) 0.004

(0.100) –0.045

–0.020 (0.037) –0.192

(12)

Auxiliary supervision

0.091 –0.274°

(0.139) 1.403* (0.805) 2.19* 1007 65

(0.192) –0.078

(0.241) 0.321

(0.082) –0.387

0.004

(0.042)

–0.053

(13)

0.088 –0.315

(0.139) 1.534** (0.750) 2.09* 972 65

(0.190) –0.083

(0.229) 0.307

(0.086) –0.428*

0.004

(0.026)

–0.034

(14)

0.075 –0.276°

(0.135) 1.402* (0.755) 2.02* 943 65

(0.200) –0.043

(0.229) 0.319

(0.087) –0.385*

–0.022 (0.028) –0.009

(15)

Cooperative supervision

*, **, and *** indicate statistical significance at the 10%, 5%, and 1% level, respectively, while no asterisk means the coefficient is not statistically significantly different from zero. Standard errors in parentheses. ° represents p-value above 5%. of Hausman-test suggesting that random-effects estimations are more consistent (see Table A7.2).

F-stat No. of obs. No. of countries R 2 (within) Corr (μ i, X)

Log penetration rate (t-1) Log deposits per GDP (t-1) Log assets per GDP (t-1) Credit to private sector (t-1) GDP per capita (t-1) Property rights (t-1) Financial freedom (t-1) Constant

Dependent variable

Panel C: fixed-effects regressions for financial cooperatives supervision

128  Regulation, supervision, and deposit insurance at the 10% level. Although the coefficients are not trivial and seem consistent with the results of Table 7.4, that show negative correlation between financial cooperative financial cooperatives’ indicators and banking regulation; however, it is difficult to draw a solid conclusion from this result remotely from other results that does not show any correlation between banking supervision and financial cooperatives. Moreover, the findings here do not provide insightful evidence to examine Cuevas and Fischer (2006: 31–32) argument in favour for dual supervision. Cuevas and Fischer explained how dual supervision puts the few big financial cooperatives that hold a significant number of members and assets under the well-developed supervision of banking authorities at lower cost, which can be adequate for a transition phase until establishing a unified supervisory framework to govern the whole sector. As noted before, effective monitoring and inspection over financial cooperatives is very challenging and expensive, as in many countries, there are hundreds or thousands of geographically remote and small financial cooperatives. Again, there is no evidence that auxiliary supervision (indirect supervision) is associated with higher degree of development in the sector, and the results do not support or contradict the promising perception that auxiliary supervision can overcome these challenges associated with supervising financial cooperatives as suggested by Cuevas and Fischer (2006) and BCBS (2015a) and (2015b). Panel C in Table 7.5 suggests that countries that adopt auxiliary supervision to supervise financial cooperatives tend to have low levels of financial freedom and financial sector development, as shown in Columns (10), (11), and (12), with a negative correlation between domestic credit to private sector and financial freedom with auxiliary supervision, statistically significant at 10%. Whereas Columns, (7), (8), and (9) suggest that the banking supervisory authority is responsible for the financial cooperative sector in countries that have high levels of financial freedom. However, the consistency of these conclusions should be questioned in light of the statistical insignificance of the whole regression under estimation. Anyhow, it is clear that the classification of supervisory approaches analysed in this section does not provide sufficient information on the quality and the capacity of the bank, dual and auxiliary supervisory approaches. Monitoring the operations of financial cooperatives might be handled differently with specialised department or staff even if they fall under the supervision of a banking supervisory authority or an auxiliary supervision. In that case, the supervisor may allocate the required resources, tools, warning systems, and corrective actions, which can be appropriate for effective monitoring of financial institutions with cooperative structure. While in other cases, the bank supervisory authority may apply an inadequate approach for monitoring financial cooperatives or may lack the necessary resources and expertise. Thus, the same dummy variables that represent banking supervisor or auxiliary supervision may include different monitoring and supervision mechanisms.

Regulation, supervision, and deposit insurance  129 7.4.3.  Deposit insurance schemes for financial cooperatives Table 7.6 shows the correlations between financial cooperatives’ indicators and a dummy variable that takes the value 1 if the financial cooperative sector is covered by a deposit insurance scheme, and the value 0 if not, using the same set of control variables. Columns (1), (2) and (3) in Panel A show positive correlations between financial cooperatives’ penetration rate, deposits and assets per GDP on one hand, and the presence of a deposit insurance scheme on the other hand. The correlation is statistically significant at the 1% levels for penetration rate and deposits per GDP and statistically significant at the 5% level for assets per GDP. Panel B also suggests that deposit insurance schemes encourage the growth of financial cooperatives, with positive correlation between deposit insurance and the change in financial cooperatives’ indicators, significant at the 1% level. These results are consistent with Esty (1997: 26) who argued that mutual-owned financial institutions are less likely to adopt high-risk financial strategies because the incentive to adopt high-risk behaviour is determined mainly by whether the residual and fixed claims are separable or not. Claims are not separable in the case of mutual organisations, like cooperatives, so the total wealth of members is unaffected by the increase of the institution’s risk behaviour, as the residual claim’s possible gains is balanced by the possible losses on the fixed claim. That is why cooperatives are less likely to adopt risk-taking behaviour in the first place, even in the presence of deposit insurance systems, taking into account of course that the indicators tested here do not measure the risk-taking behaviour or the financial performance of financial cooperatives. These results, however, provide preliminary evidence that the introduction of deposit insurance may lead the financial cooperative sector to grow, because of increasing confidence in the sector, which helps in attracting new depositors (members), or encourage existing members to invest more in their cooperative. Karels and McClatchey (1999) found no evidence that credit unions’ risk-taking behaviour in the United States had increased after the adoption of deposit insurance scheme, during the period 1971–1990. Their results showed that liquidity and asset quality improved, suggesting a decrease in risk-taking behaviour during the post deposit insurance period. However, Karels and McClatchey (1999: 132) suggested that not only the ownership structure that limits risk-taking behaviour is the reason for credit unions’ stability but also the strong regulatory environment adopted in the 1970s that had restricted credit unions’ investment strategies. As regulations at that time imposed limitations on the maximum loan size that can be offered by credit unions, and the maximum maturity for secured and unsecured loans. Similarly, Hannafin and McKillop (2007) found no evidence of risk shifting behaviour in the performance of Irish credit unions after to the introduction of a deposit insurance scheme in 1989.

Table 7.6  Fixed-effects regression results for financial cooperatives indicators and deposit insurance Panel A: fixed-effects regressions for financial cooperatives indicators against deposit insurance Dependent variable

Deposit insurance   GDP per capita Credit to private sector Financial freedom Property rights   Constant   F-stat No. of obs. No. of countries R 2 (within) Corr (μi, X)

Log penetration rate

Log deposit per GDP

Log assets per GDP

(1)

(2)

(3)

0.293*** (0.096) 1.172*** (0.397) 0.669*** (0.213) 0.626*** (0.222) 1.395*** (0.276) –5.255*** (1.257) 16.48*** 1108 65 0.387 –0.653

0.335*** (0.116) 1.207*** (0.508) 0.779*** (0.271) 1.207*** (0.270) –1.725*** (0.366) –6.703*** (1.584) 18.34*** 1065 65 0.329 –0.634

0.250** (0.012) 1.435*** (0.494) 0.666*** (0.252) 1.016*** (0.252) –1.700*** (0.309) –7.132*** (1.543) 17.14*** 1035 65 0.337 –0.680

Panel B: fixed-effects regressions for change in financial cooperatives indicators against deposit insurance Dependent variable

Log penetration rate (t-1) Log deposits per GDP (t-1)

Change in log penetration rate

Change in log deposit per GDP

Change in log assets per GDP

(1)

(2)

(3)

–0.159*** (0.031)

Log assets per GDP (t-1) Deposit insurance (t-1) Credit to private sector GDP per capita Property rights Financial freedom Constant F-stat No. of obs. No. of countries R 2 (within) Corr (μi, X)

0.018 (0.022) –0.011 (0.044) 0.095 (0.101) –0.222*** (0.067) 0.099 (0.063) –0.465 (0.349) 7.43*** 1007 65 0.132 –0.834

–0.268*** (0.049) 0.072*** (0.027) 0.211*** (0.079) –0.068 (0.179) –0.414*** (0.149) 0.274** (0.114) –0.504 (0.645) 6.25*** 949 65 0.206 –0.837

–0.276*** (0.058) 0.055* (0.030) 0.198** (0.089) 0.096 (0.192) –0.454*** (0.142) 0.252** (0.104) –0.968 (0.706) 5.04*** 917 65 0.202 –0.875

Regulation, supervision, and deposit insurance  131 Panel C: fixed-effects regressions for financial cooperatives deposit insurance Dependent variable

Log penetration rate (t-1) Log deposits per GDP (t-1)

Deposit insurance Deposit insurance

Deposit insurance

(1)

(3)

0.165*** (0.046)

Log assets per GDP (t-1) Credit to private sector (t-1) GDP per capita (t-1) Property rights (t-1) Financial freedom (t-1) Constant F-stat No. of obs. No. of countries R 2 (within) Corr (μi, X)

0.013 (0.128) 0.587** (0.274) 0.078 (0.157) 0.011 (0.214) –1.359 (0.839) 4.57*** 1007 65 0.135 –0.505

(2)

0.095*** (0.035) 0.045 (0.129) 0.686** (0.310) 0.017 (0.157) –0.009 (0.238) –1.647 (0.979) 3.85*** 972 65 0.120 –0.532

0.095** (0.041) 0.067 (0.123) 0.618** (0.302) 0.056 (0.152) –0.003 (0.242) –1.477 (0.964) 3.42*** 943 65 0.106 –0.471

*, **, and *** indicate statistical significance at the 10%, 5%, and 1% level, respectively, while no asterisk means the coefficient is not statistically significantly different from zero. Standard errors in parentheses.  represents p-value above 5% of Hausman-test suggesting that random-effects estimations are more consistent (see Table A7.3).

However, again a causal relation between deposit insurance and financial cooperatives’ size and outreach is difficult to demonstrate here. Panel C shows that countries with deposit insurance schemes tend to have high penetration rate, deposit and assets per GDP in the previous year, and higher GDP per capita than their counterparts. These results are in line with the categorisation of financial cooperative evolutionary stages proposed by ­Ferguson and McKillop (1997 and 2000). According to Ferguson and ­McKillop, the global financial cooperative movement can be divided into mature, transitional, and nascent industries, whereas the establishment of deposit insurance mechanism is one of the key attributes of mature financial cooperative sectors alongside with large asset base. As for the control variables, Panels A in Tables 7.4, 7.5, and 7.6 show statistically significant positive correlation between financial cooperatives’ penetration rate, deposits per GDP, and assets per GDP on one hand and GDP per capita, domestic credit provided by banks, financial freedom on the other hand. Moreover, there is statistically significant negative correlation between the development of financial cooperatives and property rights index. These results are similar to the ones reported in Chapter 5. The positive

132  Regulation, supervision, and deposit insurance correlation between financial cooperatives development indicators and GDP per capita is also consistent with Périlleux et al. (2016) showing that the level of economic development matters for the development of financial cooperatives. It is also in line with results of Panel C in Table 6.4 (discussed above); which suggest that a specialised financial cooperative regulation is associated with high GDP per capita while cooperative societies’ regulations are adopted in countries with lower GDP per capita. Contrary to Périlleux et al. (2016), the results here show a statistically significant positive correlation between financial sector development (measured by domestic credit provided by banks) and financial cooperatives indicators. These findings are further supported by the results of Panel B in Tables 6.4 to 6.6, which show a statistically significant positive correlation between the growth of financial cooperatives’ deposits and assets per GDP and domestic credit provided to private sector. Furthermore, the positive correlation between financial freedom index and financial cooperatives indicators suggests that the development of the financial cooperative sector requires sound financial policies and regulations, and less intervention by the state in the operations of financial institutions or the allocation of credit in the financial sector. Finally, Panels A and B show a statistically negative correlation between property rights index and financial cooperatives’ growth. Chapter 5 argues that the negative correlation between financial cooperatives’ indicators and protection of property rights is reasonable because strict property rights laws aim to protect those who already have ‘formal’ assets and limit the economic activities of the informal sector, where financial cooperatives’ members are usually involved.

7.5. Conclusion This chapter examines the relationship between the development of financial cooperatives and the type of regulation that governs the sector, the supervisory agency responsible to monitor their activities, and the existence of a deposit insurance scheme, using panel data collected for 65 developing countries. Although causality is difficult to establish using only statistical methods, the results of this chapter cautiously provide new empirical evidence to understand what is best suitable for the development of financial cooperatives. The main results can be summarized as follows. First, high indicators of financial cooperatives and the growth of the sector are positively correlated with specialized regulations, giving support for opinions preferring that members-owned financial institutions should be regulated by specialised legislations. That can be considered the central conclusion in the analysis; a specialised regulation for financial cooperatives is more likely to support the growth of the sector because financial cooperatives have different economic objectives, ownership structure and face different risks and challenges, such as access to liquidity facilities, net-savers against net-borrowers agency problems, low compensation for

Regulation, supervision, and deposit insurance  133 managers, etc. All of which require different regulatory approach compared to traditional investor-owned financial institutions and other types of cooperative organisations. Second, there are serious concerns over the viability of applying commercial bank regulations to financial cooperatives in underdeveloped economies, as the findings indicate that commercial bank regulation is negatively associated with financial cooperatives’ deposits and assets per GDP. Commercial bank regulations may ignore the distinctive nature of financial cooperatives, especially its capital and governance structures, and may impose excessive regulatory burdens that are unreasonable for the non-complex activities of financial cooperatives. For instance, high capital adequacy requirements may restrain financial cooperatives’ growth rate compared to other investor-owned financial institutions because equity is the amount of capital solely owned by the cooperative and which cannot be claimed by members or by external parties. For that, accumulated reserves are usually considered the main resource for cooperatives’ equity, and shares held by the members are not treated as part of the equity in many cases. Compared to traditional banks, lower minimum initial capital requirements for financial cooperatives can be adequate giving the simplicity of their activities and their risk exposure. Third, general cooperative societies’ regulations are negatively correlated with penetration rate and deposits and assets per GDP. Such results are consistent with the view that a unified regulation that regulates the operation of all cooperative organisations is usually inadequate for financial intermediation activities. A unified cooperative regulation may not have sound measurements for protecting the members’ deposits or may not stress on creating a minimum capital base that enable cooperatives to mitigate unexpected losses. Financial cooperatives also should apply prudential-financial standards and supervision, as well as facilitating access to liquidity mechanisms, money transfer, payment channels, settlement and clearing networks, all of which may be ignored in a general cooperative societies’ regulation. Fourth, supervision by authorities responsible for supervising non-bank financial institutions is positively associated with high financial cooperatives’ indicators. The results, however, do not support or contradict the arguments in favour for auxiliary supervision, as a promising approach to overcome challenges associated with supervising financial cooperatives, as we found no evidence that auxiliary supervision is associated with higher degree of development in the sector. Fifth, the baseline regression analysis indicated a negative correlation between financial cooperatives’ outreach and supervision under a general cooperative societies’ supervisor, and no statistical correlation with the financial cooperatives’ deposits and assets per GDP. However, it is important to keep in mind that authorities responsible for the supervision of general cooperative societies, in most developing countries, lack the required capacity to conduct sufficient prudential supervision over financial intermediary institutions that negatively affect the development of the sector. Finally,

134  Regulation, supervision, and deposit insurance deposit insurance schemes are positively correlated with financial cooperatives development, providing cautious evidence that the introduction of deposit insurance may encourage the growth of financial cooperatives, by building confidence in the sector and attract new depositors (members) or encourage existing members to invest more in their cooperative. Noting that our calculations do not capture the risk-taking behaviour or the financial performance of financial cooperatives, so we cannot demonstrate whether deposit insurance schemes threaten the stability of the sector or not. Financial cooperatives are not only significant for financial inclusion and economic growth, but their unique organisational structure could enable them to stimulate inclusive economic development by redistributing economic resources and opportunities in their economies. Because of that, financial cooperatives regulations must be flexible and responsive to the distinctive function of cooperatives and the complexity of the overall financial sector, in order to guarantee the stability of the sector and protect the interests of the members. Thus, a specialised legal framework seems to be the most suitable approach to regulate and supervise the sector.

Notes 1 This chapter is largely based on the following publication: Khafagy, A. (2018). Regulation, supervision and deposit insurance for financial cooperatives: an empirical investigation, Annals of Finance, 14(2), 143–193. ‘Reprinted with permission’. 2 United Nations (2003, p. 10) cited by Cuevas and Fischer (2006, p. 1). 3 In Kenya by the SACCO Societies Regulatory Authority since 2008 and South Africa by the Co-operative Banks Development Agency CBDA since 2007.

Bibliography Adams, D. (1999), ‘Using credit unions for micro-enterprise lending insights: Latin America’, in Balkenhol, B. (eds.), ‘Credit Unions and the Poverty Challenge: ­Extending Outreach, Enhancing Sustainability’, Geneva: International Labour ­Organisation, pp. 37–50. Akande, O. R., Abu, O. and Obekpa, H. O. (2016), ‘Microfinance organizations in Africa: The challenge of transforming into regulated organizations’, in Achtenhagen, L., & Brundin, E. (eds.), Entrepreneurship and SME Management Across Africa, Singapore: Springer, pp. 67–86. Alston, L. J., Grove, W. A. and Wheelock, D. C. (1994), ‘Why do banks fail? Evidence from the 1920s’, Explorations in Economic History, 31(4), 409–431. Basel Committee on Banking Supervision. (2012), ‘Core Principles for Effective Banking Supervision’, Basel: Bank for International Settlements, September. Basel Committee on Banking Supervision. (2015a), ‘Range of Practice in the Regulation and Supervision of Institutions Relevant to Financial Inclusion’, Basel: Bank for International Settlements, January. Basel Committee on Banking Supervision. (2015b), ‘Guidance on the Application of the Core Principles for Effective Banking Supervision to the Regulation and

Regulation, supervision, and deposit insurance  135 Supervision of Institutions Relevant to Financial Inclusion’, Basel: Bank for International Settlements, December. Beck, T. (2004), ‘The incentive-compatible design of deposit insurance and bank failure resolution: Concepts and country studies’, in Mayes, D. G. and Liuksila, A. (eds.), ‘Who Pays for Bank Insolvency?’, London: Palgrave Macmillan, pp. 118–141. Branch, B. and Grace, D. (2008), ‘Technical Guide: Credit Union Regulation and Supervision’, Wisconsin: World Council of Credit Unions. Cuevas, C. E. and Fischer, K. P. (2006), ‘Cooperative Financial Institutions: Issues in Governance, Regulation, and Supervision’, Washington, DC: World Bank. Cull, R., Demirgüç-Kunt, A. and Morduch, J. (2011), ‘Does regulatory supervision curtail microfinance profitability and outreach?’ World Development, 39(6), 949–965. Demirgüç-Kunt, A. and Detragiache, E. (2002), ‘Does deposit insurance increase banking system stability? An empirical investigation’, Journal of Monetary Economics, 49(7), 1373–1406. Esty, B. C. (1997), ‘Organizational form and risk taking in the savings and loan industry’, Journal of Financial Economics, 44(1), 25–55. Ferguson, C. and McKillop, D. (1997), ‘The Strategic Development of Credit ­Unions’, Chichester: John Wiley & Son Ltd. Ferguson, C. and McKillop, D. G. (2000), ‘Classifying credit union development in terms of mature, transition and nascent industry types’, The Service Industries Journal, 20(4), 103–120. Gropp, R. and Vesala, J. (2004), ‘Deposit insurance, moral hazard and market monitoring’ Review of Finance, 8(4), 571–602. Grossman, R. S. (1992), ‘Deposit insurance, regulation, and moral hazard in the thrift industry: Evidence from the 1930’s’, The American Economic Review, 82(4), 800–821. Hannafin, K. and Mckillop, D. (2007), ‘Deposit insurance and credit unions: An international perspective’, Journal of Financial Regulation and Compliance, 15(1), 42–62. Hartarska, V. and Nadolnyak, D. (2007), ‘Do regulated microfinance institutions achieve better sustainability and outreach? Cross-country evidence’, Applied Economics, 39(10), 1207–1222. Ioannidou, V. P. and Penas, M. F. (2010), ‘Deposit insurance and bank risk-taking: Evidence from internal loan ratings’ Journal of Financial Intermediation, 19(1), 95–115. International Monetary Fund. (2012), ‘World Economic Outlook: Growth Resuming, Dangers Remain’, Washington, DC: World Economic and Financial Surveys, p. 181. Jansson, T., Rosales, R. and Westley, G. D. (2004), ‘Principles and Practices for Regulating and Supervising Microfinance’, Washington, DC: Inter-American Development Bank. Karels, G. V. and Mcclatchey, C. A. (1999), ‘Deposit insurance and risk-taking behavior in the credit union industry’, Journal of Banking and Finance, 23(1), 105–134. Périlleux, A., Vanroose, A. and D’Espallier, B. (2016), ‘Are financial cooperatives crowded out by commercial banks in the process of financial sector development?’, Kyklos, 69(1), 108–134. Poprawa, A. (2009), ‘Regulation and Legislation of Cooperative Banks and Credit Union’, New York: Paper Prepared for United Nations Expert Group Meeting on Cooperatives, pp. 28–30.

136  Regulation, supervision, and deposit insurance Poyo, J. (2000), ‘Regulation and supervision of credit unions’, in Westley, G. and Branch, B. (eds.), ‘Safe Money: Building Effective Credit Unions in Latin America’, Washington, DC: Inter-American Development Bank, pp. 137–160. United Nations. (2003), ‘Environment for Cooperatives’, A Stakeholder Dialogue on Definitions, Prerequisites and Process of Creation., New York: United ­Nations Department of Economic and Social Affairs. World Council of Credit Unions. (2015), ‘Model Law for Credit Unions’, 2015 edition, Wisconsin: World Council of Credit Unions.

Discussion and conclusions

This book provided theoretical and empirical analyses that explain the ­influence of finance on economic distribution and the potential of financial cooperatives to improve wealth and income distribution. The book also identified the economic objective and the institutional factors that determine the development of financial cooperatives. It explained the dynamics of income and wealth distribution with credit rationing, and direction of capital transfer from low- and middle-income classes to upper-income classes, compared to the dynamics of distribution with financial cooperatives. It went on to define desired deposit and lending interest rates, as well as optimal total credit and total external borrowings for cooperatives, all of which aim at increasing the income of cooperative members at a rate higher than the average growth rate of the economy. It also explained the political economy of financial cooperatives and the origin and rationale for financial cooperative regulation in underdeveloped economies. That helped in explaining why financial cooperatives grew in some emerging economies and not in other similar ones and how the behaviour of political institutions and the adopted regulations influence the development of the financial cooperative sector. However, the two theories presented in this book—the political economy theory of financial cooperatives, and the financial cooperative and income distribution theory—do not provide an inclusive understanding of the political economy of financial cooperatives under elite-dominated political systems and its interrelationship with income and political power distribution. There are interesting questions that remain unaddressed, such as why would an elite-dominated state maintain a minimum level of mutual financial cooperation among the masses and how does it oppress any potential expansion of such cooperation? Under what conditions can underrepresented and financially excluded groups successfully form financial cooperation, despite state opposition? How do financial cooperatives overcome the collective-­ action problem to exert pressure on political institutions? How is a narrow, internal elite formed within cooperatives and how does it expropriate its political and economic gains? There is still a need to discover the mechanisms that allow for a minimum level of financial services to be provided to the

138  Discussion and conclusions lower-income class, through cooperatives or any other institutions, even in the most oppressive and autocratic regimes, as stable autocrats will try to guarantee a minimum level of return for low-income populations to avoid social dissatisfaction and political unrest. More importantly, there is a need not only to focus on state behaviour towards mutual financial cooperation formed by the low and middle classes but also to account for the ability of the underrepresented groups to solve the collective-action problem and their potentials for forming financial cooperatives despite the state’s opposition. Understanding the internal politics within a cooperative when it is dominated by narrow elites who may expropriate its political and economic gains will help in building a dynamic political economy model for financial cooperatives that reflect the complexity of the institutional context. That should help form a better understanding of how state opposition and potential collective action determine the outcomes of financial cooperatives in terms of people’s participation, mobilisation of deposits, and allocation of credit, all of which shape the income and political power distribution.

Appendix

Chapter 1: Econometric methods

The econometric methods used throughout the book are similar in C ­ hapters 3, 5, and 7. Detailed information on the relevant data and the methods used in collecting them is discussed within each chapter. Overall, linear relationships are assumed between dependent and independent variables using three methods to estimate the parameter values: ordinary least squares (OLS), random- and fixed-effects OLS (RE and FE OLS), and fixed-effects instrumental variables (IV) regressions. The basic structure for the OLS regression models take the form of yit = α + X it β + mi + νit .

(1.1)

where yit is the dependent variable, α is the intercept, and X is a set of explanatory and control variables (independent variables). The dependent, explanatory and control variables are discussed for each analysis separately in their corresponding chapters. Furthermore, β are the coefficients that need to be estimated to determine the potential relationship between the dependent variables y and each explanatory variable in X. The error term in the panel regression is denoted by mi + νit, where mi denotes the time-invariant and unobservable country-specific effect or idiosyncratic error term, that differs across countries, and not included in the regression (e.g. historical and cultural country-specifications). And, νit is the remainder disturbance which varies across countries and years, with similar characteristics to the usual ‘error term’ of any linear regression equation, assumed to be homoscedastic, normally distributed with a mean equals to zero, uncorrelated with itself, and uncorrelated with mi and X. The OLS estimator ignores the longitudinal structure of the data and assumes that mi is equal to zero, unlike the fixed and random-effects estimators that consider the presence of unobserved heterogeneity between the countries. The fixed-effect estimator, known as the within estimator, assume mi as fixed parameters that do not have a distribution. It controls for all country-specific effects and these time-invariant parameters are omitted. The remainder disturbances νit are assumed to be independent and identically distributed (IID), while X it are assumed to be correlated with mi and

140 Appendix independent from νit for all countries i at any period t (Baltagi, 2005: 12–13 and Stata, 2013: 366). The fixed-effect estimator performs OLS regression on

( yit − yi ) = α + ( X it − X i ) β + (vit − vi ).

(1.2)

Breusch-Pagan / Cook-Weisberg test and Lagram-Multiplier test were estimated to determine the presence of heteroscedasticity and serial correlation in the panel data. Following that, Huber-White sandwich robust estimator was used to correct for the heteroscedasticity and serial correlation found in the panel data. Generally, the coefficients estimated by Huber-White ­robust estimator of variance are similar to the coefficients produced by the non-­ robust estimators, however, Huber-White robust estimator produces ‘correct’ standard errors (in a statistical sense). Using the robust estimator of variance allows us to relax the assumption of identically distributed disturbances  vit over the panels, and the no serial correlation assumption in the fixed-effect regressions (Stata, 2013: 383). Finally, ‘Breusch and ­Pagan Lagrangian multiplier test for random-effects’ was computed to decide between OLS regressions and random-effects regressions, and ‘Hausman Fixed Random Test’ to decide between choosing the random-effects or the fixed-effects models. I report regression results obtained from fixed-effects estimations following Hausman-test results and the high correlation between the country-specific effects mi and the explanatory variables X found in all the regressions, all which suggest fixed-effects estimations to be more efficient than random-effects estimations for the analysis. The fixed and random effects OLS estimators do not solve the possible endogeneity problem in the panel regressions and treat all explanatory variables as exogenous which can make OLS estimates inconsistent, as it will only measure the magnitude of the correlation but not the magnitude and direction of possible causal relation between the independent and the explanatory variables. Endogeneity problem exists when an explanatory variable is correlated with the error term as a result of not including all relevant variables in the model or because of sample selectivity caused by data availability or any other reasons. To assess the possible causal effect of the main explanatory variables on the dependent variables, it is important to control for unobservable variables that are correlated with these explanatory variables and also affect the dependent variable at the same time, taking into account that there is no econometric method that can prove causation in the absolute meaning of the word. One way to address the endogeneity problem in explanatory variables is to use IV two-stage least squares (2SLS) estimator, as recommended by Baltagi (2005: 113) and Stock and Watson (2007: 332–334). The IV regression divides the explanatory variables in set X of Equation (1.1) into endogenous and exogenous variables, where endogenous variables, are assumed to be correlated with the error term mi + νit, and the exogenous variables, X2, are assumed to be uncorrelated with the error term. IV method uses additional variables Z as instruments, to help in

Appendix  141 predicting the values of the endogenous explanatory variables X1, so that Z should be correlated with X1 but also uncorrelated with the error term. The typical IV 2SLS regression can be denoted by the following two equations: X1it = d 0 + Zitd1 + X 2itd 2 + e it ,

(1.3)

yit = α + Xˆ 1it β1 + X 2it β2 + mi + nit .

(1.4)

In the first stage (1.3), the endogenous variables X1 are regressed against the exogenous variables X2 in addition to the excluded instruments Z. The predicted values resulted from the first stage OLS regressions can be denoted ˆ 1it = δˆ0 + Z itδˆ1. Following that, the second stage of the 2SLS described by  X ˆ 1it using OLS rein Equation (1.4), regresses yit on the predicted values X gression to estimate the causal effect of main explanatory variables on the dependent variable. The main idea behind IV regression is to find instruments that can explain part of the variation in the endogenous variables X1 and that is unrelated to the error term. Valid instruments must have a direct and strong correlation with the endogenous explanatory variables, but also must not be correlated with the dependent variables. The second condition is called the ‘exclusion restriction’.

Bibliography Baltagi, B. H. (2005), ‘Econometric Analysis of Panel Data’, 3rd Edition, New York: John Wiley and Sons. Stata Press. (2013), ‘Stata longitudinal-data/panel-data reference manual’, release 13, Stata Press. Stock, J. and M. Watson. (2007), ‘Introduction to Econometrics: International Edition’, 2nd ed., Upper Saddle River, NJ: Prentice Hall.

Chapter 3 Table A3.1  L  ist of countries included in the analysis  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Australia Austria Bangladesh Bolivia Brazil Bulgaria Canada Chile Colombia Costa Rica Côte d’Ivoire Cyprus Denmark Dominican Rep. Ecuador El Salvador Finland France Germany Ghana Greece Guyana Honduras

24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46

Hungary India Indonesia Ireland Italy Jamaica Japan Kenya Korea Luxembourg Macedonia Malawi Malaysia Mauritius Mexico Mongolia Netherlands New Zealand Panama Papua New Guinea Paraguay Peru Philippines

47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67

Poland Portugal Romania Russian Federation Singapore Slovenia South Africa Spain Sri Lanka Swaziland Sweden Switzerland Tanzania Thailand Uganda Ukraine United Kingdom United States Uruguay Viet Nam Zimbabwe

Chapter 5 Table A5.1  L  ist of countries included in the analysis and main indicators as of 2011 (in %) No.

Country name

Penetration rate

Deposits per GDP

Assets per GDP

No. Country name

Penetration rate

Deposits per GDP

Assets per GDP

1 2 3 4 5 6 7 8 9 10 11 12

Azerbaijan Bangladesh Belarus Benin Bolivia Brazil Burkina Faso Cambodia Cameroon Chile Colombia Costa Rica

0.39 0.43 0.06 42.84 9.92 4.26 20.31 0.45 4.57 13.72 9.01 27.20

0.02 0.07 0.00 1.33 2.28 0.73 1.64 0.01 0.78 0.46 0.53 4.19

0.06 0.07 0.00 1.79 2.70 1.13 2.30 0.04 1.01 1.04 1.10 6.37

34 35 36 37 38 39 40 41 42 43 44 45

1.60 1.40 33.16 16.35 7.41 11.20 2.22 3.94 1.73 3.62 6.61 13.30

0.30 0.07 1.13 0.91 0.30 0.25 0.37 1.06 0.07 0.18 1.14 1.54

0.37 0.11 2.09 1.27 0.35 0.55 0.45 1.32 0.08 0.37 2.11 1.73

13 14

Côte d’Ivoire Dominican Republic Ecuador El Salvador Ethiopia Gambia Ghana Guatemala Guinea-Bissau Guyana Honduras India Indonesia Jamaica Kenya Laos Latvia Lesotho Liberia Lithuania Macedonia

21.30 9.26

0.75 0.76

0.65 0.97

46 47

Malawi Malaysia Mali Mauritius Mexico Moldova Mongolia Nepal Nicaragua Niger Panama Papua New Guinea Paraguay Peru

21.94 6.45

2.38 0.88

2.87 1.02

26.42 6.02 0.64 5.78 2.95 17.25 3.48 10.87 21.62 27.77 1.51 73.58 26.22 0.42 2.18 8.23 1.17 4.41 0.74

2.00 1.06 0.06 1.34 0.29 1.50 0.05 0.59 3.04 3.13 0.14 4.26 6.04 0.03 0.06 0.36 0.05 1.18 0.03

2.44 1.31 0.12 1.45 0.35 1.88 0.06 0.83 4.07 4.66 0.16 5.48 9.05 0.05 0.08 0.38 0.06 1.23 0.05

48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65

Philippines Poland Romania Russia Rwanda* Senegal South Africa Sri Lanka Swaziland Tanzania* Thailand Togo Uganda Ukraine Uruguay Uzbekistan* Viet Nam Zimbabwe

10.44 10.97 6.58 0.36 20.23 40.22 0.16 10.35 8.90 4.10 8.79 46.08 8.34 4.89 7.54 1.80 2.96 1.32

0.46 3.53 0.10 0.01 0.88 2.15 0.00 0.08 1.67 0.48 7.89 5.03 0.36 0.10 0.03 0.41 0.97 0.01

0.63 4.63 0.15 0.01 1.17 3.73 0.00 0.11 1.92 1.09 10.02 6.91 0.58 0.21 0.10 0.51 1.19 0.02

15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33

* Statistics here for Rwanda are from 2013; Uzbekistan from 2010; deposits per GDP for Tanzania from 2010; and assets per GDP for Uganda from 2010.

Financial freedom

Credit to private sector

Urban population

Unemployment rate

Inflation rate

Log GDP per capita

GDP growth rate

Polity

Civil liberties

Political rights

Dependent variable

–0.899* (0.524) 0.252*** (0.089) –0.734*** (0.114) –2.536*** (0.375) –1.392*** (0.167) –0.273*** (0.094) 0.935*** (0.150)

0.079*** (0.014)

–0.977* (0.512) 0.165* (0.088) –0.695*** (0.111) –2.579*** (0.365) –1.382*** (0.163) –0.273*** (0.092) 0.774*** (0.147)

0.176*** (0.019) 0.030*** (0.005) –0.783° (0.521) 0.273*** (0.089) –0.71*** (0.113) –2.591*** (0.374) –1.407*** (0.167) –0.325*** (0.095) 0.916*** (0.149) –1.437** (0.645) –0.124 (0.112) –0.869*** (0.139) –3.022*** (0.483) –1.386*** (0.21) 0.142 (0.116) 1.570*** (0.187)

0.085*** (0.018)

–1.484** (0.636) –0.213* (0.112) –0.834*** (0.137) –3.04*** (0.475) –1.362*** (0.207) 0.153 (0.114) 1.419*** (0.186)

0.173*** (0.024)

(5)

(4)

(3)

(1)

(2)

Log deposits per GDP

Log penetration rate

0.018*** (0.006) –1.273* (0.648) –0.111 (0.113) –0.859*** (0.140) –2.938*** (0.487) –1.369*** (0.211) 0.113 (0.117) 1.637*** (0.188)

(6)

–0.989° (0.628) –0.15 (0.111) –0.907*** (0.135) –3.039*** (0.464) –1.51*** (0.208) 0.082 (0.113) 1.564*** (0.184)

0.081*** (0.018)

(7)

–1.064 (0.616) –0.24** (0.109) –0.867*** (0.132) –3.11*** (0.455) –1.495*** (0.204) 0.093 (0.111) 1.415*** (0.181)

0.183*** (0.023)

(8)

Log assets per GDP

0.017*** (0.006) –0.834 (0.630) –0.141 (0.112) –0.90*** (0.136) –2.954*** (0.467) –1.50*** (0.210) 0.051 (0.114) 1.614*** (0.185)

(9)

Table A5.2  O  LS regression results for financial cooperatives indicators against democracy, political rights and civil liberties indices (underdeveloped economies 1995–2014)

(6)

(7)

(8)

Log assets per GDP (9)

–0.122 –0.188 –0.007 –0.637*** –0.662*** –0.432** –0.536*** –0.622*** –0.327* (0.158) (0.151) (0.151) (0.198) (0.19) (0.191) (0.197) (0.188) (0.189) –2.335*** –2.397*** –2.145*** –2.565*** –2.620*** –2.435*** –2.319*** –2.388*** –2.184*** (0.192) (0.187) (0.192) (0.241) (0.238) (0.244) (0.240) (0.235) (0.242) yes yes yes yes yes yes yes yes yes 31.21*** 37.9*** 32.43*** 31.2*** 34.95*** 29.49*** 35.49*** 40.74*** 33.89*** 1107 1107 1107 1064 1064 1064 1034 1034 1034 0.666 0.651 0.663 0.810 0.799 0.815 0.782 0.767 0.787 0.2146 0.2502 0.2213 0.2212 0.2421 0.2114 0.2503 0.2778 0.2415

(5)

(4)

(3)

(1)

(2)

Log deposits per GDP

Log penetration rate

*, **, and *** indicate statistical significance at the 10%, 5%, and 1% level respectively. ° indicates significance between 10% and 15% level, while no asterisk means the coefficient is not statistically significantly different from zero. Standard errors are in parentheses.

Regional control F-stat No. of obs. Root MSE R2 (adjusted)

Constant

Property rights

Dependent variable

Chapter 7 Table A7.1  Random-effects regression results for financial cooperatives indicators and regulations Panel A: random-effects regressions for financial cooperatives indicators against regulations Dependent variable Log penetration rate (1) FC regulation

(2)

Log deposit per GDP (3)

(4)

(5)

(6)

0.286*** (0.097)

Dual regulation

(7)

0.338*** (0.128) 0.110

0.189

(0.091) Bank regulation

(0.125) –0.261* (0.136)

NBFI regulation

0.065* (0.037)

Cooperative societies regulation GDP per capita   Credit to private sector Financial freedom

–0.351*** (0.104) 0.792*** (0.302) 0.727*** (0.216) 0.724***

0.988*** (0.308) 0.757*** (0.209) 0.685**

0.959*** (0.303) 0.722*** (0.227) 0.710***

0.949*** (0.302) 0.776*** (0.210) 0.691***

0.803*** (0.305) 0.735*** (0.210) 0.620**

0.608* (0.364) 0.903*** (0.260) 1.308***

 

(0.243)

(0.267)

(0.264)

(0.263)

(0.243)

(0.264)

Property rights

–1.442***

–1.560***

–1.572***

–1.564***

–1.350*** –1.857***

(0.256)

(0.270)

(0.271)

(0.271)

(0.258)

(0.341)

0.834** (0.371) 0.926*** (0.255) 1.251*** (0.269) –1.964*** (0.338)

Legal origin

–0.527*** –0.443*** –0.447*** –0.449*** –0.533*** –0.636*** (0.140)

(0.148)

(0.146)

(0.147)

(0.141)

(0.160)

(0.167)

Region

–0.021

–0.101

–0.084

–0.083

–0.033

0.001

–0.097

(0.103)

(0.103)

(0.101)

(0.102)

(0.101)

(0.118)

(0.122)

Constant

–3.622***

–3.949***

–3.877***

–3.865***

–3.345*** –4.343*** –4.723***

(0.739) Wald chi2 No. of obs. No. of countries R 2 (overall)

104.43***

(0.751) 99.06***

(0.745)

(0.737)

(0.779)

(0.888)

(0.907)

134.43***

158.10***

103.17***

107.41***

112.01***

1108

1065

65 0.052

–0.527***

65 0.029

0.031

0.026

0.056

0.094

0.055

Log assets per GDP (8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

0.292** (0.113) 0.116 (0.131) –0.806***

–0.602***

(0.295)

(0.226) 0.058

0.072

(0.065)

0.785** (0.362) 0.799*** (0.274) 1.303***

0.784** (0.367) 0.959*** (0.254) 1.272***

(0.052) –0.326***

–0.290***

(0.112)

(0.104)

0.656* (0.365) 0.916*** (0.259) 1.201***

0.707** (0.357) 0.813*** (0.255) 1.144***

0.895** (0.361) 0.853*** (0.250) 1.084***

0.865** (0.352) 0.747*** (0.270) 1.120***

0.856** (0.355) 0.871*** (0.250) 1.094***

0.744** (0.359) 0.833*** (0.252) 1.042***

(0.269)

(0.269)

(0.255)

(0.264)

(0.286)

(0.281)

(0.280)

(0.260)

–1.993***

–1.983***

–1.789***

–1.858***

–1.951***

–1.970***

–1.961***

–1.788***

(0.337)

(0.340)

(0.345)

(0.296)

(0.311)

(0.306)

(0.311)

(0.300)

–0.532***

–0.538***

–0.619***

–0.601***

–0.514***

–0.517***

–0.521***

–0.589***

(0.164)

(0.167)

(0.158)

(0.160)

(0.168)

(0.165)

(0.167)

(0.159)

–0.064

–0.072

–0.027

–0.014

–0.095

–0.073

–0.077

–0.036

(0.117)

(0.119)

(0.117)

(0.118)

(0.120)

(0.116)

(0.118)

(0.117)

–4.589***

–4.618***

–4.145***

–4.340***

–4.642***

–4.554***

–4.558***

–4.159***

(0.890)

(0.896)

(0.910)

(0.848)

(0.871)

(0.856)

(0.859)

(0.885)

129.65***

145.29***

105.73***

107.97***

111.02***

129.01***

153.56***

102.36***

0.034

0.043

0.033

0.060

1035 65 0.071

0.053

0.086

0.065

(Continued)

Panel B: random-effects regressions for change in financial cooperatives indicators against regulations Dependent variable Change in log penetration rate (1) Log penetration rate (t-1)

(2)

(3)

Change in log deposit per GDP (4)

–0.073*** –0.070*** –0.071*** (0.012) (0.012) (0.012)

(5)

(6)

(7)

–0.069*** –0.073*** (0.012) (0.012)

Log deposits per

–0.087*** –0.085***

GDP (t-1)

(0.015)

(0.014)

Log assets per GDP (t-1) FC regulation (t-1)

0.034***

0.071***

(0.012)

Dual regulation (t-1)

(0.025) 0.015

0.006

(0.021)

(0.028)

Bank regulation

–0.068

(t-1)

(0.072)

NBFI regulation

–0.012

(t-1)

(0.014)

Cooperative societies regulation (t-1) Credit to private

–0.030*** (0.011) –0.042*

–0.048**

–0.051

–0.047

–0.042*

0.030

0.018 (0.065)

sector

(0.024)

(0.023)

(0.023)

(0.023)

(0.024)

(0.065)

GDP per capita

–0.014

–0.006

–0.007

–0.008

–0.010

–0.100*** –0.088**

(0.023)

(0.022)

(0.022)

(0.022)

(0.023)

(0.035)

(0.036)

0.034

0.013

0.021

0.020

0.018

0.175

0.146*

(0.034)

(0.037)

(0.034)

(0.033)

(0.033)

(0.079)

(0.086)

0.073*

0.073*

0.072

0.072

0.073*

0.041

0.034 (0.062)

Property rights Financial freedom Legal origin Region Constant Wald chi2 No. of obs. No. of countries 2

R (overall)

(0.039)

(0.041)

(0.041)

(0.040)

(0.039)

(0.059)

–0.015

–0.002

–0.002

–0.002

–0.013

–0.021

0.005

(0.011)

(0.010)

(0.010)

(0.010)

(0.011)

(0.019)

(0.017)

0.017**

0.011*

0.012**

0.012**

0.014**

0.036***

0.027**

(0.007)

(0.006)

(0.006)

(0.006)

(0.007)

(0.011)

(0.011)

–0.107*

–0.101*

–0.102*

–0.095*

–0.085

–0.065

–0.048

(0.056)

(0.056)

(0.058)

(0.056)

(0.057)

(0.093)

(0.094)

44.64***

41.32***

40.96***

41.84***

45.97***

59.01***

55.17***

1007

949

65

65

0.090

0.085

0.086

0.085

0.088

0.091

0.079

Change in log assets per GDP (8)

(9)

(10)

–0.087***

–0.086***

–0.088***

(0.015)

(0.014)

(0.015)

(11)

(12)

(13)

(14)

(15)

–0.086***

–0.083***

–0.085*** –0.084***

–0.086***

(0.017)

(0.016)

(0.017)

(0.016)

(0.016)

0.070** (0.027) –0.001 (0.035) –0.077

–0.072

(0.061)

(0.075) –0.017

–0.011

(0.024)

(0.019) –0.057***

–0.056***

(0.020) 0.016

0.017

0.031

(0.021) 0.042

0.033

0.030

0.033

0.045

(0.066)

(0.065)

(0.066)

(0.067)

(0.066)

(0.067)

(0.066)

(0.068)

–0.089**

–0.090**

–0.091***

–0.090**

–0.077**

–0.077**

–0.077**

–0.082**

(0.036)

(0.036)

(0.035)

(0.039)

(0.039)

(0.038)

(0.038)

(0.037)

0.146*

0.145*

0.138

0.087

0.062

0.062

0.059

0.055

(0.082)

(0.082)

(0.080)

(0.079)

(0.083)

(0.078)

(0.078)

(0.079)

0.037

0.038

0.044

0.064

0.056

0.060

0.060

0.064

(0.062)

(0.060)

(0.060)

(0.066)

(0.065)

(0.066)

(0.065)

(0.065)

0.005

0.005

–0.015

–0.033

–0.007

–0.007

–0.008

–0.026

(0.017)

(0.017)

(0.018)

(0.021)

(0.018)

(0.018)

(0.018)

(0.020)

0.028***

0.027***

0.031***

0.034***

0.024**

0.024**

0.024**

0.029***

(0.011)

(0.010)

(0.010)

(0.012)

(0.011)

(0.011)

(0.011)

(0.011)

–0.057

–0.047

–0.023

–0.049

–0.032

–0.039

–0.032

–0.004

(0.098)

(0.094)

(0.088)

(0.100)

(0.099)

(0.100)

(0.098)

(0.094)

56.37***

54.63***

54.03***

40.47***

41.45***

39.05***

41.57***

42.03***

0.060

0.061

0.060

0.068

917 65 0.080

0.079

0.087

0.072

(Continued)

Panel C: random-effects regressions for financial cooperatives regulations Dependent variable FC regulation (1) Log penetration rate (t-1)

Dual regulation

(2)

(6)

0.024 (0.017)

–0.023 (0.015) (0.013)

0.080**

GDP (t-1)

0.014

(0.038) 0.081

0.082

0.106

(0.122)

(0.124)

(0.122)

0.384**

0.397

(7)

0.019

(0.036)

Log assets per

GDP per capita

(5)

0.078**

GDP (t-1)

sector (t-1)

(4)

0.121** (0.048)

Log deposits per

Credit to private

(3)

Bank regulation

0.384**

(0.013) 0.101

0.109*

0.101*

–0.079

(0.068)

(0.065)

(0.058)

–0.146

–0.132

–0.128

(0.067) 0.014

(t-1)

(0.171)

(0.181)

(0.174)

(0.109)

(0.122)

(0.111)

(0.019)

Property rights

–0.224

–0.196

–0.179

–0.011

–0.051

–0.063

–0.005

(t-1)

(0.189)

(0.183)

(0.188)

(0.119)

(0.106)

(0.117)

(0.018)

Financial freedom

–0.144

–0.131

–0.201

0.111

0.104

0.163

0.029

(t-1)

(0.205)

(0.208)

(0.193)

(0.137)

(0.136)

(0.120)

(0.018)

–0.055

–0.057

–0.001

(0.037)

(0.035)

(0.008)

Legal origin

0.351*** (0.065)

0.353*** (0.068)

0.340*** –0.052 (0.067)

(0.034)

Region

–0.204*** –0.203*** –0.203*** (0.059)

(0.059)

(0.058)

(0.038)

(0.039)

(0.037)

Constant

–0.255

–0.298

–0.224

0.332

0.323

0.285

–0.068

(0.424)

(0.447)

(0.441)

(0.250)

(0.301)

(0.279)

(0.063)

Wald chi2

66.03***

64.57***

57.53***

9.57

9.42

8.12

3.41

No. of obs. No. of countries R 2 (overall)

0.091**

0.091**

0.085**

0.006 (0.007)

1007

972

943

1007

972

943

1007

65

65

65

65

65

65

65

0.256

0.261

0.288

0.086

0.073

0.064

0.022

*, **, and *** indicate statistical significance at the 10%, 5%, and 1% level respectively, while no asterisk means the coefficient is not statistically significantly different from zero. Standard errors in parentheses.

NBFI regulation (8)

(9)

(10)

(11)

Cooperative regulation (12)

0.008 (0.007) –0.025

(13)

(15)

–0.130*** (0.048) 0.006

(0.018)

(14)

–0.069**

(0.007) –0.021

(0.029) 0.007

(0.015)

–0.073**

(0.008)

(0.033)

–0.066

–0.068

–0.025

–0.023

–0.024

(0.066)

(0.064)

(0.036)

(0.032)

(0.032)

(0.094)

(0.093)

(0.096)

0.012

0.010

0.077

0.081

0.078

–0.326**

–0.377

–0.354**

(0.017)

(0.015)

(0.087)

(0.086)

(0.086)

(0.163)

(0.165)

(0.162)

0.000

–0.064

–0.069

–0.079

0.339*

(0.020)

(0.040)

(0.043)

(0.048)

(0.187)

(0.189)

(0.190)

–0.013 (0.026)

–0.029

–0.056

0.373**

–0.067

0.374**

0.041

0.032

0.114

0.116

0.119

–0.118

–0.139

–0.119

(0.028)

(0.022)

(0.144)

(0.157)

(0.162)

(0.211)

(0.219)

(0.228)

–0.008

–0.005

0.013

0.012

0.013

(0.010)

(0.008)

(0.049)

(0.048)

(0.048)

0.007

0.007

–0.046**

–0.047**

–0.046**

–0.309*** –0.293***

–0.282***

(0.067)

(0.066)

0.150** (0.062)

(0.069) 0.152**

(0.008)

(0.007)

(0.023)

(0.023)

(0.023)

–0.097

–0.079

–0.096

–0.104

–0.087

(0.073)

(0.062)

(0.191)

(0.184)

(0.183)

(0.425)

(0.413)

(0.411)

2.61

2.60

5.75

5.73

5.75

51.14***

46.34***

46.47***

1.059**

(0.062)

0.154**

1.224***

(0.061) 1.121***

972

943

1007

972

943

1007

972

943

65

65

65

65

65

65

65

65

0.028

0.023

0.008

0.010

0.012

0.168

0.149

0.171

Table A7.2  R  andom-effects regression results for financial cooperatives indicators and supervision Panel A: random-effects regressions for financial cooperatives indicators against supervision Dependent variable Log penetration rate (1) NBFI supervision  

(2)

Log deposit per GDP (3)

(4)

(5)

0.412*** (0.157)

Dual supervision

(6) 0.394** (0.173)

0.060*

 

0.026

(0.119)

(0.158)

Bank supervision

–0.032

 

(0.128)

Auxiliary supervision  

–0.130 (0.180)

Cooperative societies  supervision GDP per capita  

–0.256 (0.130) 0.904*** (0.304)

Credit to private  sector Financial freedom

(7)

0.690*** (0.180) 0.701***

0.964*** (0.303) 0.773*** (0.210) 0.698***

0.974*** (0.301) 0.775*** (0.211) 0.706***

0.957*** (0.300) 0.748*** (0.196) 0.688***

0.882*** (0.305) 0.763*** (0.210) 0.659***

0.769** (0.364) 0.876*** (0.236) 1.271***

0.957*** (0.254) 1.279***

 

(0.260)

(0.263)

(0.264)

(0.264)

(0.260)

Property rights

–1.396***

–1.562***

–1.566***

–1.568***

–1.444*** –1.848***

–1.982***

(0.242)

(0.270)

(0.270)

(0.269)

(0.256)

(0.338)

Legal origin Region Constant Wald chi2 No. of obs. No. of countries 2

R (overall)

(0.262)

0.798** (0.368)

(0.329)

(0.266)

–0.488*** –0.444*** –0.442***

–0.456*** –0.497*** –0.582*** –0.536***

(0.139)

(0.148)

(0.153)

(0.146)

(0.146)

(0.163)

(0.169)

–0.021

–0.095

–0.093

–0.078

–0.062

–0.019

–0.080

(0.104)

(0.102)

(0.103)

(0.103)

(0.100)

(0.121)

(0.121)

–3.946***

–3.897***

–3.923***

–3.864*** –3.593*** –4.745***

–4.647***

(0.712)

(0.742)

(0.734)

(0.734)

(0.772)

(0.879)

(0.901)

107.10***

99.58***

99.21***

101.91***

97.79***

113.55***

112.25***

1108

1065

65

65

0.065

0.029

0.027

0.033

0.039

0.082

0.054

Log assets per GDP (8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

0.364** (0.155) –0.012 (0.143) –0.036

–0.064

(0.229)

(0.183)

0.809** (0.367) 0.958*** (0.255) 1.287***

–0.030

–0.146

(0.302)

(0.253)

0.797** (0.365) 0.951*** (0.256) 1.277***

–0.247*

–0.175

(0.139)

(0.133)

0.719* (0.368) 0.945*** (0.258) 1.237***

0.834** (0.354) 0.791*** (0.226) 1.107***

0.874** (0.357) 0.870*** (0.249) 1.104***

0.892** (0.356) 0.868*** (0.251) 1.115***

0.878** (0.355) 0.836*** (0.240) 1.089***

0.822** (0.359) 0.861*** (0.251) 1.084***

(0.268)

(0.266)

(0.262)

(0.274)

(0.278)

(0.277)

(0.279)

(0.272)

–1.984***

–1.986***

–1.877***

–1.795***

–1.967***

–1.957***

–1.962***

–1.886***

(0.339)

(0.338)

(0.338)

(0.290)

(0.308)

(0.309)

(0.306)

(0.298)

–0.530***

–0.540***

–0.586***

–0.555***

–0.522***

–0.506***

–0.528***

–0.553***

(0.172)

(0.166)

(0.164)

(0.162)

(0.169)

(0.172)

(0.166)

(0.165)

–0.082

–0.075

–0.052

–0.026

–0.081

–0.093

–0.075

–0.065

(0.123)

(0.121)

(0.118)

(0.121)

(0.119)

(0.119)

(0.118)

(0.116)

–4.674***

–4.641***

–4.346***

–4.681***

–4.597***

–4.640***

–4.587***

–4.405***

(0.895)

(0.897)

(0.907)

(0.834)

(0.865)

(0.863)

(0.861)

(0.882)

112.83***

113.83***

105.85***

115.06***

109.01***

109.67***

112.83***

105.73***

0.033

0.032

0.039

0.043

1035 65 0.053

0.054

0.068

0.058

(Continued)

Panel B: random-effects regressions for change in financial cooperatives indicators against supervision Dependent variable Change in log penetration rate (1) Log penetration rate (t-1)

(2)

–0.075*** –0.071*** (0.013) (0.012)

(3)

Change in log deposit per GDP (4)

–0.069*** (0.012)

(5)

(6)

(7)

–0.069*** –0.071*** (0.012) (0.012)

Log deposits per

–0.089*** –0.087***

GDP (t-1)

(0.015)

(0.015)

Log assets per GDP (t-1) NBFI supervision (t-1)

0.041**

0.046*

(0.017)

Dual supervision (t-1)

(0.027) 0.023*

0.039

(0.012)

(0.032)

Bank supervision

–0.008

(t-1)

(0.017)

Auxiliary supervision (t-1)

–0.006 (0.017)

Cooperative societies supervision (t-1)

–0.025** (0.013)

Credit to private

–0.047*

–0.048**

–0.046**

–0.049*

–0.038

0.018

0.016

sector

(0.024)

(0.023)

(0.023)

(0.025)

(0.024)

(0.067)

(0.067)

GDP per capita

–0.004

–0.005

–0.007

–0.006

–0.012

–0.084**

–0.083**

(0.023)

(0.023)

(0.022)

(0.022)

(0.024)

(0.037)

(0.038)

0.024

0.009

0.018

0.021

0.015

0.147*

0.125

(0.035)

(0.035)

(0.035)

(0.033)

(0.034)

(0.083)

(0.084)

Property rights Financial freedom Legal origin Region

0.070*

0.076*

0.071*

0.070*

0.071*

0.036

0.046

(0.041)

(0.040)

(0.041)

(0.040)

(0.039)

(0.063)

(0.062)

–0.010

–0.002

–0.001

–0.003

–0.009

–0.004

0.005

(0.012)

(0.010)

(0.010)

(0.010)

(0.011)

(0.021)

(0.017)

0.009

0.011*

0.017***

0.012**

0.014**

0.032***

0.022**

(0.006)

(0.006)

(0.006)

(0.006)

(0.007)

(0.011)

(0.010)

Constant

–0.131**

–0.104*

–0.097*

–0.102*

–0.078

–0.087

–0.063

(0.065)

(0.057)

(0.057)

(0.058)

(0.060)

(0.108)

(0.100)

Wald chi2

41.86***

42.83***

41.17***

44.14***

44.18***

62.46***

53.33***

No. of obs. No. of countries R 2 (overall)

1007

949

65 0.089

65 0.086

0.085

0.085

0.087

0.081

0.081

Change in log assets per GDP (8)

(9)

(10)

–0.078***

–0.085***

–0.086***

(0.013)

(0.015)

(0.015)

(11)

(12)

(13)

(14)

(15)

–0.084***

–0.086***

–0.074***

–0.083***

–0.084***

(0.016)

(0.017)

(0.014)

(0.016)

(0.016)

0.029 (0.027) 0.035 (0.031) 0.007

0.012

(0.029)

(0.031) –0.005

0.006

(0.031)

(0.033) –0.042**

–0.047**

(0.020)

(0.021)

0.016

0.016

0.034

0.034

0.032

0.031

0.036

0.052

(0.062)

(0.068)

(0.065)

(0.067)

(0.068)

(0.063)

(0.069)

(0.067)

–0.088**

–0.088**

–0.095***

–0.075*

–0.073*

–0.074**

–0.079**

–0.085**

(0.035)

(0.037)

(0.036)

(0.038)

(0.039)

(0.036)

(0.039)

(0.038)

0.148*

0.133

0.068

0.042

0.085

0.059

0.047

(0.082)

(0.081)

(0.078)

(0.083)

(0.077)

(0.077)

(0.079)

0.166** (0.082) 0.019

0.034

0.037

0.054

0.069

0.038

0.057

0.059

(0.060)

(0.061)

(0.061)

(0.066)

(0.067)

(0.063)

(0.065)

(0.065)

0.006

0.004

–0.006

–0.011

–0.007

–0.007

–0.007

–0.018

(0.016)

(0.018)

(0.018)

(0.020)

(0.018)

(0.017)

(0.018)

(0.019)

0.027***

0.027***

0.030***

0.028**

0.020**

0.023**

0.024**

0.028**

(0.010)

(0.010)

(0.010)

(0.011)

(0.010)

(0.010)

(0.011)

–0.034

–0.052

–0.015

–0.053

–0.045

–0.020

–0.028

(0.011) 0.005

(0.089)

(0.097)

(0.092)

(0.107)

(0.104)

(0.091)

(0.101)

(0.097)

53.60***

54.13***

54.08***

39.73***

40.25***

38.60***

40.77***

39.83***

0.062

0.061

0.060

0.065

917 65 0.079

0.079

0.084

0.061

(Continued)

Panel C: random-effects regressions for financial cooperatives supervision Dependent variable NBFI supervision (1) Log penetration rate (t-1)

(2)

(3)

(4)

0.098** (0.044)

Log deposits per GDP (t-1)

(5)

Bank supervision (6)

0.008 (0.017) 0.049*

–0.003 (0.011) 0.060*

GDP (t-1)

(7) –0.011 (0.024)

(0.026)

Log assets per Credit to private

Dual supervision

–0.003

(0.032)

(0.012)

0.113

0.143

0.145

0.014

0.023

0.024

0.062

(0.084)

(0.092)

(0.094)

(0.041)

(0.043)

(0.042)

(0.070)

0.036

0.059

0.078

0.043

0.079

0.057

0.161

(t-1)

(0.115)

(0.109)

(0.113)

(0.074)

(0.076)

(0.079)

(0.117)

Property rights

–0.205

–0.206*

–0.272*

–0.066

–0.118

–0.095

–0.075

(t-1)

(0.138)

(0.123)

(0.150)

(0.097)

(0.087)

(0.104)

(0.117)

Financial freedom

–0.093

–0.085

–0.108

0.019

0.018

0.034

0.236

(t-1)

(0.097)

(0.096)

(0.104)

(0.111)

sector (t-1) GDP per capita

Legal origin Region Constant Wald chi2 No. of obs. No. of countries 2

R (overall)

0.144**

0.138**

0.128**

(0.064)

(0.063)

(0.065)

–0.155***

–0.154***

–0.161***

(0.038)

(0.038)

(0.039)

0.543*

0.439

0.464

(0.305)

(0.286)

(0.294)

29.69***

24.61***

27.10***

(0.026)

(0.026)

(0.031)

–0.096**

–0.106**

–0.101**

(0.044)

(0.046)

(0.045)

0.109***

0.105***

0.233*** (0.078)

0.107*** –0.116**

(0.038)

(0.038)

(0.038)

(0.047)

–0.134

–0.228

–0.188

–0.360

(0.208)

(0.223)

(0.231)

(0.304)

12.46*

12.51*

12.38*

20.19***

1007

972

943

1007

972

943

1007

65

65

65

65

65

65

65

0.225

0.187

0.200

0.126

0.101

0.101

0.159

*, **, and *** indicate statistical significance at the 10%, 5%, and 1% level respectively, while no asterisk means the coefficient is not statistically significantly different from zero. Standard errors in parentheses.

Auxiliary supervision (8)

(9)

(10)

(11)

Cooperative supervision (12)

–0.029 (0.038)

(13)

(14)

(15)

–0.065* (0.038)

0.002

–0.006

–0.042*

(0.034)

(0.035)

(0.026)

0.005

–0.027

(0.030)

–0.033

(0.037)

(0.027)

0.045

0.041

–0.218**

–0.231**

–0.232**

0.018

0.013

0.007

(0.066)

(0.066)

(0.102)

(0.105)

(0.103)

(0.070)

(0.073)

(0.074)

0.146

0.103

0.082

0.065

0.091

–0.312*

–0.341**

–0.315*

(0.109)

(0.106)

(0.073)

(0.074)

(0.073)

(0.175)

(0.170)

(0.169)

–0.049

0.026

0.038

0.067

0.050

0.311*

0.303*

0.304

(0.127)

(0.109)

(0.072)

(0.081)

(0.079)

(0.184)

(0.182)

(0.190)

0.199*

–0.083*

–0.088

–0.083

–0.072

–0.075

–0.036

0.236** (0.115) 0.241***

(0.106) 0.239***

(0.045)

(0.054)

(0.050)

(0.137)

(0.137)

(0.133)

–0.067

–0.060

–0.067

–0.215***

–0.214***

–0.199***

(0.078)

(0.078)

(0.056)

(0.055)

(0.053)

(0.070)

(0.070)

(0.068)

–0.115**

–0.110**

0.047

0.047

0.045

0.113*

0.115*

0.114*

(0.046)

(0.046)

(0.030)

(0.032)

(0.030)

(0.063)

(0.063)

(0.062)

–0.309

–0.180

–0.133

–0.061

–0.180

(0.284)

(0.287)

(0.203)

(0.205)

(0.204)

19.78***

18.49*

10.21

9.45

10.65

1.061** (0.468) 29.47***

1.137*** (0.437) 27.49***

1.049** (0.447) 26.15***

972

943

1007

972

943

1007

972

943

65

65

65

65

65

65

65

65

0.166

0.190

0.126

0.105

0.132

0.101

0.093

0.102

Table A7.3  R  andom-effects regression results for financial cooperatives indicators and deposit insurance Panel A: random-effects regressions for financial cooperatives indicators against deposit insurance Dependent variable

Deposit insurance GDP per capita Credit to private sector Financial freedom   Property rights Legal origin Region Constant Wald chi2 No. of obs. No. of countries R 2 (overall)

Log penetration rate

Log deposit per GDP Log assets per GDP

(1)

(2)

(3)

0.317*** (0.090) 0.804*** (0.273) 0.699*** (0.209) 0.652*** (0.224) –1.489*** (0.256) −0.471*** (0.146) −0.060 (0.093) −3.516*** (0.674) 106.33*** 1108 65 0.048

0.373*** (0.107) 0.616* (0.353) 0.862*** (0.259) 1.235*** (0.262) –1.889*** (0.336) −0.565*** (0.162) −0.046 (0.110) −4.215*** (0.868) 118.01*** 1065 65 0.088

0.296*** (0.103) 0.747** (0.342) 0.785*** (0.250) 1.061*** (0.253) −1.896*** (0.298) −0.542*** (0.163) −0.060 (0.110) −4.297*** (0.831) 111.69*** 1035 65 0.059

Panel B: random-effects regressions for change in financial cooperatives indicators against deposit insurance Dependent variable

Log penetration rate (t-1) Log deposits per GDP (t-1)

Change in log penetration rate

Change in log deposit Change in log assets per GDP per GDP

(1)

(2)

−0.070*** (0.012)

Log assets per GDP (t-1) Deposit insurance (t-1) Credit to private sector GDP per capita Property rights

0.007 (0.011) −0.048** (0.022) −0.008 (0.022) 0.021 (0.033)

−0.086*** (0.014) (0.016) 0.028 (0.018) 0.011 (0.067) −0.089** (0.035) 0.147* (0.081)

(3)

−0.085*** 0.030 (0.020) 0.026 (0.069) –0.077** (0.037) 0.060 (0.078)

Dependent variable

Financial freedom Legal origin Region Constant Wald chi2 No. of obs. No. of countries R 2 (overall)

Change in log penetration rate

Change in log deposit Change in log assets per GDP per GDP

(1)

(2)

0.069* (0.040) −0.004 (0.010) 0.012** (0.006) −0.098* (0.055) 41.65*** 1007 65 0.085

0.030 (0.058) 0.001 (0.016) 0.027*** (0.010) −0.049 (0.091) 56.13*** 949 65 0.081

(3) 0.054 (0.063) −0.012 (0.017) 0.023** (0.010) −0.036 (0.095) 42.01*** 917 65 0.062

Panel C: random-effects regressions for financial cooperatives deposit insurance Dependent variable

Log penetration rate (t-1) Log deposits per GDP (t-1)

Deposit insurance

Deposit insurance

Deposit insurance

(1)

(2)

(3)

0.169*** (0.040)

Log assets per GDP (t-1) Credit to private sector (t-1) GDP per capita (t-1) Property rights (t-1) Financial freedom (t-1) Legal origin Region Constant Wald chi2 No. of obs. No. of countries R 2 (overall)

(0.035) 0.093 (0.113) 0.306* (0.168) −0.017 (0.147) 0.003 (0.215) 0.156* (0.085) −0.068 (0.058) −0.416 (0.365) 32.15*** 1007 65 0.075

0.106*** (0.031)

0.119 (0.106) 0.365** (0.185) −0.069 (0.141) −0.025 (0.239) 0.139* (0.081) −0.068 (0.058) −0.535 (0.436) 30.08*** 972 65 0.080

0.108*** 0.130 (0.103) 0.330* (0.179) −0.020 (0.134) −0.016 (0.241) 0.135* (0.080) −0.067 (0.057) −0.459 (0.429) 24.35*** 943 65 0.090

*, **, and *** indicate statistical significance at the 10%, 5%, and 1% level respectively, while no asterisk means the coefficient is not statistically significantly different from zero. Standard errors in parentheses.

Table A7.4  L  ist of regulations reviewed No.

Country

Regulation Note: the information collected in this table are obtained directly from the relevant laws unless other sources are mentioned Information on regulations, supervisions and deposit insurance in Latin America relied extensively on Arzbach et al. (2010; 2012; 2014a; and 2014b) for collection or verification

Africa

 1  2

 3  4  5  6

 7

 8

West African Projet De Loi Portant Reglementation des Institutions Mutualistes ou Cooperatives d’epargne et de Credit (Law Governing Mutual or Economic Cooperative Savings and Credit-Institutions PARMEC Law in 1993) and Monetary Projet de Decret d’application de la Loi Portant Réglementation des Institituions Mutualistes ou Cooperatives (Decree on Implementing the Union PARMEC Law in 1993) (WAEMU) Loi portant réglementation des systèmes financiers décentralisés (Lawof 2007 regulating decentralized financial systems: Title V: Provisions relating to institutions or mutual cooperative savings and credit [Article 85 to Article 101]) (BCEAO, 2011) Décret d’application de la loi portant réglementation des systèmes financiers décentralisés (Decree of 2007 for the Enforcement of the Act to regulate decentralized financial systems) (BCEAO, 2011) Adoptation of the new PARMEC law: Benin 2012—Burkina Faso 2009— Cote d’Ivoire 2011—Guinea Bissau 2008—Mali 2010—Niger 2010— Senegl 2008—Togo 2011 (Mees, 2015: 4) Benin Law no. 97-027 of 8 August 1997 on the regulation of mutual or cooperative savings and credit (Ouattara, 2003) Burkina Faso Law No. 59/94 / ADP of 15 December 1994 on the regulation of mutual or cooperative savings and credit and its implementing Decree No. 95-308 / PRES / MEFP of August 1, 1995 (Van Den Boogaerde, 2002; GIABA, 2009a: 106) Cote d’Ivoire Law No. 96-596 of 1996 on the regulation of mutual or cooperative savings and credit and its implementing Decree No. 97-37 of 22 January 1997 enforcing Law No. 96-564 (GIABA, 2013: 110) Guinée Law No. 11/97 of 2 December 1997 on the regulation of mutual or Bissau cooperative savings and credit (IMF, 2013) Mali Law No. 94-040 of 15 August 1994 regulating mutual or cooperative savings and credit and its implementing decree No. 94-302 of 20 September 1994 (Chao-Beroff, 1999; Seibel, 2005) Niger Ordinance No. 96-024 (known PARMEC Act) of 30 May, 96 on the regulation of mutual or cooperative savings and credit and its implementing decree No. 96-416 / PRN / MEF / P 9 November 1996 (GIABA, 2009b) Senegal Law No. 95-03 of January 5, 1995 on the regulation of mutual or cooperative savings and credit and its implementing decree No. 97-1106 of 11 November 1997 amended by Law 2008-47 03 September 2008 on the regulation of decentralized financial systems and its implementing decree No. 2008-1366 of 28 November 2008 (IMF, 2005; GIABA, 2008: 133; Amin, 2009) Togo Law No. 95-014 of 14 July 1995 on the regulation of mutual or cooperative savings and credit Decree 96-038 of 1 April, 1996 for application of the law (GIABA, 2011: 90–136)

No.

Country

Regulation

 9

Cameroon

10

Ethiopia

11

Gambia

12

Ghana

13

Kenya

14

Lesotho

15 16

Liberia Malawi

Law No. 92/006 of 1992, Relating to Cooperative Societies and Common Initiative Groups (Chapter 2. Special provisions applicable to thrift and loan cooperative societies: Section 42 to 48) enforced by the Decree No 92/455/PM of 1992 Prime Ministerial Decree of 1998, No. 94 98/300/PM (laying down the procedures governing credit unions, cooperatives) Rules No. 01/02 / CEMAC / UMAC / COBAC Relating to the Exercise Conditions and Microfinance Activity Control in the Economic and Monetary Community of Central Africa (Reglement No. 01/02/CEMAC/ UMAC/COBAC aux Relatif aux Conditions d’Exercice et de Contrôle de l’Activité de Microfinance dans la Communauté Economique et Monétaire de l’Afrique Centrale) (Mbemap, 2009) Standard n° 01/02/CEMAC/IMAC/COBAC Organization and supervision of microfinance activities in the CEMAC in 2009 (Riquet and Poursat, 2013) Cooperative Societies Proclamation No.138/1983 (Emana, 2009) Cooperative Societies Proclamation No. 147/1998 Cooperative Societies (Amendment) Proclamation No. 402/2004 The Cooperative Societies (Amendment) Rules, 1980: Legal Notice No. 11 of 1980 The Financial Institutions Act, 1992 revised in 2003 Non-bank financial institutions rules and guidelines on policies and procedures: Volume 6: Savings and credit companies/ co-operatives (Category A1 Institutions) Microfinance Operations—Rules and Guidelines on Policies and Procedures (Volume 2: Savings and Credit Associations) Guidelines for the Licensing of Financial Institutions in 1995 Co-operative Societies Decree NLCD 252 of 1968 Cooperative Societies Act 1968 Financial Institutions (non-banking) Law 1993 [PNDCL 328] NBFI business (BOG) rules of 2000 (as applicable to institutions not taking public deposits) Bank of Ghana Act, 2002 [Act 612] Non-Bank Financial Institutions Act, 2008, [Act 774] (Bank of Ghana, 2009) The Co-operative Societies Act No. 39 of 1966: Chapter 490 (Nair, and Kloeppinger-Todd, 2007: 35; Wanyama, 2009) Co-operative Societies Act, 1997 (No. 12 of 1997) (Cap. 490) The Cooperative Societies (Amendment) Act of 2004 Sacco Societies Act (No 14) of 2008 Sacco Societies (Deposit-Taking Sacco Business) Regulations, 2010 Cooperative Societies Proclamation 1948 (UNCTAD, 2013). Cooperative Societies (Protection) Act No. 10 of 1966 Cooperative Societies Act No. 6 of 2000 Cooperative Societies Regulations 2001 (Legal Notice No. 197 of 2001) Financial Institution Act No. 3 of 2012 Cooperatives Act of 1936 (CBL, 2009a and 2009b) Cooperative Societies Act (1946) Cooperative Societies Act (No. 36 of 1998) (Chapter 47:02) Cooperative Societies Regulations of 2002 Financial Services Act 2010 Financial Cooperatives Act 2011 (Continued)

No.

Country

Regulation

17

Mauritius

18

Rwanda

19

South Africa

20

Swaziland

21

Tanzania

22 23 Asia 24 25

Uganda Zimbabwe

Co-operative Societies Act 1976 Banking Act 1988 The Banking Act No. 34of 2004 (only large FCs—under Section 14E) Co-operatives Act 2005 Co-operatives (Amendment) Act 2006 The communiqué issued by the Bank of Mauritius (the Bank) on 14 August 2014 on Liscensing of Credit Unions Law No 31/1988 on the organization of cooperative societies Instructions No. 06/2002 governing Micro-finance Institution National Bank of Rwanda instruction no. 05/2003 on the regulation of saving and credit cooperatives Law No. 50/2007 for the Establishment, Organization, and Functioning of Cooperative Organisations Law No. 40/2008 for Establishing the organization of microfinance activities (Chapter V: specific provisions to savings and credit cooperatives) Regulation No. 02 for 2009 on the organisation of microfinance activity Co-operatives Act, 1981 (Act No. 91 of 1981) Co-operatives Amendment Act 42 of 1985 Bank Act no.94 of 1990 (notice no. 2173 in government gazette no. 16167 on 14 December 1994) South Africa Reserve Bank Notice No. 37 of 1998 Cooperatives Act No. 14 of 2005 (Part 3: Financial services co-operatives) Cooperative Bank Act No. 40 of 2007 Co-operative Societies Act No. 28 of 1964 Cooperative Societies Act No. 5 of 2003 (Analytics G, 2003) Cooperative Societies Regulations, 2005 (L.N. No. 185 of 2005). Financial Services Regulatory Authority Act no. 2 of 2010 SACCOs Licensing and Reporting Guidance Notes of 2013 (Analytics G, 2014) Cooperative Societies Act No. 4 of 1986 of Zanzibar Cooperative Societies Act No. 15 of 1991 Banking and Financial Institutions Act No. 12 of 1991 Cooperative Societies Act No. 20 of 2003 Financial Cooperative Societies Regulations 2004 (Made under section 51[1] of Act No. 12 of 1991) Government notice No. 1 of 2005 on Banking and Financial Institutions (Financial Cooperative Societies) Regulations Banking and Financial Institutions Act No. 5 of 2006 Cooperative Societies Act Chapter 112 of 1991 Co-operative Societies Act (Chapter 24:05) of 1990

26

Cambodia

Azerbaijan Bangladesh

Credit union law of 2000 Cooperative Societies Ordinance, 1984 Cooperative Societies Rules 1987—Credit cooperatives are established to create funds to be on-lent to members [Rule 2(2) (vi)] (International Cooperative Information Center 1997; Rijneveld, 2006: 7) Cooperative Societies Acts, 2001(Ammendment, 2002) Cooperative Society Rule 2004 Microcredit Regulatory Authority Act of 2006 (Act 32 of the year 2006) Microcredit Regulatory Authority Act of 2010 B7-97-147 of 1997 Prakas on Conditions for Banks and Financial Institutions

No.

Country

27

India

28

Indonesia

29

Laos

30

Malaysia

31

Mongolia

Regulation B7-04-205 of 2004 Prakas on License Fees for Banks and Financial Institutions Royal Decree on the Establishment and Functioning of Agricultural Cooperative, Union of the Agricultural Cooperative and the PreAgricultural Cooperative (NS / RKT / 0701 / 234) (2001) Law on Banking and Financial Institutions (1999) B7-00-06 of 2000 Prakas on the Licensing of Microfinance Institutions B7-02-49 of 2002 Prakas on Registration and Licensing of Microfinance Institutions B7-06-209 of 2006 Prakas on Amendment to Prakas on Licensing of Microfinance Institutions B7-07-163 of 2007 Prakas on Licensing of Microfinance Deposit Taking Institutions B7-01-115 of 2001 for interest rates; B7-02-45 of 2002 for reserves requirments;B7-02-47 and B7-06-212 of 2002 for reporting; B7-02-48 of 2002 for liquidity ratio; B7-02-186 of 2002 for rural credit; B7-02-219 of 2002 for chart of accounts; B7-07-132 of 2007 for Networth; B7-07-133 of 2007 for solvency ratio; (NOB, 2008; Chou et al., 2008) Act No. 2 of 1912, Co-operative Societies Act State Cooperative Societies Acts (the Government of India Act of 1919 transfered the regulation of cooperation to provinces and were authorised to adopt their own cooperative laws) The Banking Regulation Act No. 10 of 1949—Part V: Application of the Act to Co-operative Banks [As modified up to January 7, 2013] The National Bank for Agriculture and Rural Development Act, No. 61 of 1981 (amended by Act No. 81 of 1985, Act No. 66 of 1988 Act No. 55 of 2000, and Act No. 48 of 2003) Banking Laws (Application to Co-Operative Societies) Act, 1965 Multi-State Cooperative Societies Act No. 39 (enacted in 2002) Act No. 25 on Cooperatives (enacted in 1992) (Bahasa Indonesia) Ministerial regulation No.9/1995 concerning Savings and Loan Cooperatives Law No. 17/2012 on Cooperatives Decree No. 01/PM, dated 23 January 1992—On the Accounting of the Bank of Lao PDR and the Financial Institutions under the authorization of the Bank of Lao PDR Decree No. 03/PM, dated 08 January 1996—On the Accounting of the Bank of Lao PDR and the Financial Institutions under the authorization of the Bank of Lao PDR Regulation No. 03/BOL/2008 for Savings and Credit Unions Co-operatives Societies Act 1948 The Co-operative Societies Act 1993 (Act 502) was enacted to amalgamate the cooperative law from 22 January 1994 (amended in 2007); Malaysia Co-operative Societies Commission Act 2007 Co-operative Societies Regulations 2010 Cooperative law 1995 Cooperative law 1998 Financial Regulatory Commission (FRC) 2005 (CLARITY, 2006; Rendek and Wiedmaier-Pfister, 2014: 9–10) Law on Savings and Credit Cooperatives 2011 (Rendek and WiedmaierPfister, 2014: 9–10) Approval of operational regulation of Savings and Credit Cooperatives and instructions 2015 (ADB, 2015) (Continued)

No.

Country

Regulation

32

Nepal

33 34

Papa New Guinea Philippines

Commercial Bank Act, 2031(1975) Cooperatives Act No. 8 of 1992 The Cooperatives (First Amendment) Act, (2000) Nepal Rastra Bank Act, 2058 (2002) (NRB, 2013) Directive Issued by Nepal Rastra Bank to Cooperative Societies holding a Limited Banking Transaction License (2002) The Savings & Loan Societies Act enacted in 1962 and amended in 1995

35

Sri Lanka

36

Thailand

37 38

Uzbekistan Vietnam

Europe

Belarus

40

Latvia

41

Macedonia

Republic Act No. 6938 of 1990 for The Cooperative Code of the Philippines (Special provisions in Chapter XIII and Chapter XIV) No. 6939 of 1990 for creating Cooperative Development Authority (World Bank, 2001) Republic Act No. 9520 of 2008 for The Philippine Cooperative Code Of 2008 (Special provisions in Chapter XII, Chapter XV, and Chapter XVI) Circular No. 682 of 2010 on cooperative banks Cooperative Societies Law No. 5 of 1972 Co-operative Societies (Amendment) Act No. 32, 1983 Cooperative Societies (Amendment) Act, No. 11 of 1992 The Cooperative Societies Act B.E. 2511 (1973) The Cooperatives Act B.E. 2542 (1999) (Meagher, 2013: 6) Credit union law of 2002 (Alimukhamedova, 2014) Ordinance on the State Bank of Vietnam in 1990 Law on cooperatives in 1996 (Seibel and Tam, 2010) Law No. 01/1997/QH10 on the State Bank of Vietnam issued in 1997 (Seibel and Tam, 2010) Law No. 02/1997/QH10 on the Credit Institutions issued in 1997 (Seibel and Tam, 2010) Decree No. 48/2001/ND-CP on Organization and Operation of People’s Credit Funds of 2001 Order No. 28/2003/L-CTN of The Law on Cooperatives Belarus Civil Code Law No. 218-Z of 1998: Production cooperatives (Dec 1998, Sec. 3, article 107–112)—Consumer Cooperatives (Section 5, article 116). And articles 1087 and 1088 Resolution of the Council of Ministers on “Mutual credit societies of subjects of small entrepreneurship”, No. 1972 of 1999 Production coops (collective farms): standard kolkhoz statute (Presidential Decree, Feb 2001) Law No. 93-Z of 2002 On Consumer Cooperation (consumer societies, their unions) Law N 150-W of 2002 On Amending the law “On Consumer Cooperation (consumer societies, their unions)” (GET Belarus, 2006) Law N 224-W of 2007 On Making Amendments and Addenda to the Law “On Consumer Cooperation (consumer societies, their unions)” (Lerman and Sedik, 2014) Law on credit Institutions October 1995 (Pirie, 1996) Credit Union Law No. 60 of 2001 and the amending law of 20 November 2003 Law on the National Bank of the Republic Of Macedonia Macedonian Banks and Savings Houses Act No. 29/96 Macedonian Banks and Savings Houses Act No. 37/98

No.

Country

Regulation

42

Moldova

43

Poland

44

Romania

45

Russia

46

Ukraine

The Law no. 1505-XIII from February 18, 1998 on savings and credit associations (GoRM, 1998) Law on Savings and Credit Associations of 2007 Act of 16 September 1982 The Cooperative Law Credit Union Act of 14 December, 1995 (Evans and Richardson, 1999; Światowego, 2010) Law on Credit Unions dated 5 November, 2009, and amended as of 25 October, 2012 Law 122/1996 regarding the activity of credit unions Law No. 540/2002 on pensioners’ unions (IMF, 2012: 26; EMN 2012; Barna and Vamesu, 2015) Civil Code [Article 116] (Bossoutrot, 2005: 31) Law on Agricultural Cooperatives [December 8, 1995] (Bossoutrot, 2005: 31) Law on Consumer Cooperatives (consumer societies and their unions) [July 11, 1997] (Bossoutrot, 2005: 31) Law on Consumer Credit Cooperatives of Citizens (August 7, 2001] (Bossoutrot, 2005: 31) Federal Law No. 190-FZ of July 18, 2009 on Credit Cooperation (Lyman et al., 2013). President of Ukraine decreed Temporary provisions for credit unions in 1993 (Magill and Green, 2000). The Law of Ukraine ‘On Credit Unions’, enacted in 2001

Latin America and the Caribbean 47 Bolivia General Cooperative Societies Act—Enacted on 13 September, 1958 (Buchenau, 2010: 52) Law on Banks and Financial Entities No. 1488—Enacted on 14 April, 1993 (Buchenau, 2010: 52) Central Bank Law No. 1670 Bolivia—Dated 31 October, 1995 (Buchenau, 2010: 52) Supreme Decree 24439—Dated 13 December, 1996—Regulates the scope of the General Law of Cooperative Societies, the Law on Banks and Financial Institutions No. 1488 and the Central Bank of Bolivia No. 1670, for the operation of the credit unions. [Title III—Unions and closed credit] (Buchenau, 2010: 53) Supreme Decree 25703—Dated 14 March, 2000: Regulates the scope of the General Cooperative Societies Act of 13.9.1958 and supplements the provisions of DS 24439 for open credit unions (Buchenau, 2010: 54) Law No. 1488 on Banks and Financial Institutions (Amendments in 2001) Supreme Decree 26581 dated 3 April, 2002: Updates Law 1488 Law 3892 Amendments to the Law on Banks and Financial Institutions No. 1488—Dated 18 June, 2008 (Buchenau, 2010: 55) Regulations for credit union—Circular SB / 0588/2008—Dated 14 October, 2008 (Buchenau, 2010: 56) Regulations for credit union (1st Amendment)—Circular SB / 0602/2008— Dated 22 December, 2008 (Buchenau, 2010: 57) Supreme Decree 29894 of 2009 [changing the Superintendency of Banks and Financial Institutions (SBEF) to become Financial Supervisory Authority System (ASFI) and determine its functions and powers of control and supervision (Buchenau, 2010: 56) (Continued)

No.

Country

48

Brazil

49

Chile

50

Colombia

51

Costa Rica

Regulation Regulations for credit union (2nd Amendment)—Circular ASFI / 020/2009—Dated 23 November, 2009 (Buchenau, 2010: 57) Regulations for credit union (3rd Amendment)—Circular ASFI / 038/2010—Dated 22 February, 2010 [for open FC] (Buchenau, 2010: 58) General Cooperative Law 356 of 2013 Financial Services Act 393 (2013) Law No. 4595, of 31 December 1964 on General Financial Institutions Resolution No. 11 of 20 December, 1965 General Law on Cooperatives (Law No. 5764/71 of 1971) Resolution No. 2771 of 30 August, 2000—Approves regulations governing the establishment and operation of credit unions. Resolution No. 2788 of 30 November, 2000—The establishment and operation of commercial banks and multiple banks under shareholder control of central credit unions. Resolution No. 3106 of 25 June, 2003 (requirements and procedures for the establishment, authorization to operating and statutory changes, as well as the cancellation of the operating authorization of credit unions.) Resolution No. 3859 of 27 May, 2010—Amends and consolidates the rules governing the establishment and operation of credit unions. Complementary Law. 130, of 17 April, 2009 (for the national credit cooperative system and gives the CMN power to provide for guarantee funds) Resolution No. 3106 of 25 June, 2003 (requirements and procedures for the establishment, authorization to operating and statutory changes, as well as the cancellation of the operating authorization of credit unions.) Resolution 2788 (11/2000), 3859 (05/2010), Circular 3502 (2010), and Resolution 4020 (08/2011) More information in Kumar (2005); Pinheiro (2008); and (Soares et al., 2008) Decree No. 445. Santiago, l May 1974—Amending decree RRA. No. 20, 1963 Law of General Cooperatives 1974 [Ley general de cooperativas] Law No. 18840 of 10 October, 1989—Constitutional Organic Law of the Central Bank [Ley Orgánica Constitucional del Banco Central] General Banking Law of 1997 [Ley General de Bancos] Compendium of Financial Standards by the Central Bank of Chile [Compendio de Normas Financieras del Banco Central de Chile] Decree No. 5 of 2003—General Law of Cooperatives [Ley General de Cooperativas—Decree No. 5/2003—Act No. 19832] More information in World Bank (2008) The general law of cooperatives No. 79 of 1988 Decree 663 of 1993, the Fundamental Law of the Financial System (FLFS)—Chapter 6 specified for open cooperatives, in Spanish Estatuto Orgánico del Sistema Financiero (EOSF) Law 510 provisions relating to the financial system and insurance, the public market, the Banking and Securities and some faculties are granted (1999) Unique Decree 2555 “Standards in the financial, insurance industry, and stock market” General Law of Development and Solidarity Economy Control (1998) 454 General Law Promotion Law and State Control of the Solidarity Economy (1998) (establishment of the (Superindent) More information in De la Cruz and Stephanou (2006) Law of Cooperative Associations of 1946 Law Regulating the financial intermediation activity of cooperative associations of 1994 Organic Law of the Central Bank of Costa Rica of 1995

No.

Country

Regulation

52

Dominican Republic

53

Ecuador

54

El Salvador

55

Guatemala

56 57

Guyana Honduras

58

Jamaica

59

Mexico

Cooperative Associations Act (1955)—Ley sobre Asociaciones Cooperativas Law 127 of 1964 of cooperative associations Regulations for the implementation of the law no. 127 of 27 January 1964 (Artículo 105 to Artículo 110) More information in Poyo (1999) Law on Cooperatives of Ecuador (1962) Ecuador’s 1986 General Bank Law The General Law of Institutions of the Financial System of 1994 General regulations to the law institutions of the financial system Executive Decree No. 1852. RO / 475 of 4 July, 1994 Rules for the Constitution, Organization, Operations, and Liquidity of Credit Unions that Perform Financial Intermediation with the General Public, issued through Executive Decree 1227 in March 1998 Organic Law of the People and Solidarity Economy Financial System (2011) Regulation of the Law of Popular Economy and Solidarity (2012) Organic Monetary and Financial Code Law of Financial Institutions (2001) Law of the Monetary System and State Bank Functional Constitution of the Banking Code More information in WOCCU (1998a); Moreno (2002); and Branch and Klaehn (2002) General Cooperative Associations Act (1979) General Cooperative Association Law No. 339, of 1986. Regulation of the General Law of Cooperative Associations Decree No. 560 of 1969 for the Creation Act of INSAFOCOOP Law on non-bank financial intermediaries no. 849 of 2000 Cooperative Banks Act (2008) Organic Law of the SSF (1990) Law of Cooperative Banks and Saving and Credit Corporations More information in World Bank (2010) and IMF (2014) The Guatemalan Cooperative Act of 1978, and amended in 1979 [Ley General de Cooperativas de Guatemala] (WOCCU, 1998b) Cooperative Societies Act 1948 Law on Cooperatives of Honduras issued by No. 65-87 Decree of 30 April, 1987 amended by Decree No. 174-2013 dated 1 September, 2013 Agreement No. 041-2014 Regulation of the law of cooperative—Section V: The credit union The Cooperative Societies Act 1950 More information in Vogel and Schulz (2011) General Law of Cooperative Societies 1994 General Law of Organizations and Auxiliary Credit Activities 1997 DECREE Act Savings and Loan is issued and amending and repealing certain provisions of the General Law of Organizations and Auxiliary Credit Activities and the General Law of Cooperative Societies. (Published in the Official Journal of the Federation on 4 June, 2001) Law for Popular Savings and Credit 2001—Chapter II: Cooperative Societies Savings and Loan Law to regulate the activities of the Cooperative Savings and Loan Societies 2009 (replacing the Law for Popular Savings and Credit 2001) Credit Institutions Act 1990 (since August 2009 based on the previous law) More information in Taber et al. (2004); Moreno-Dodson (2005: 120); and Herrera (2013: 525–539) (Continued)

No.

Country

Regulation

60

Nicaragua

61

Panama

62

Paraguay

63

Peru

64

Uruguay

National cooperative law of 1971 Law No. 499, General Cooperative Law of 2004 (Ley General de Cooperativas) Decree No. 16-2005 of the General regulations for cooperative law of 2004 No. 499 Executive Decree No. 91/2007 Regulating General Cooperatives Law of 2004 Law No. 499 More information in CLARITY (2006 and 2009) LEY No. 38—Legal Regime of Cooperatives Associations of 1980 (Régimen Legal de las Asociaciones Cooperativas) Ley No. 17—Legal regime of Cooperative Associations of 1997 (Régimen Legal de las Asociaciones Cooperativas) Executive Decree No. 137 of 2001 to regulate law No. 17 of 1997 Executive Decree No. 102 of 26 September, 2002 amending law No. 17 of 1997 Executive Decree No. 33 of 6 May, 2002 amending law No. 17 of 1997 More information in IMF (2007) Cooperatives Act No. 438 of 1994—Ley de Cooperativas no. 438 of 1994 Regulatory Decree of Law (1996)—Decreto reglamentario de la Ley Decree No. 14052/96 by which regulates law cooperative No. 438 of 1994 Law Ley No. 2.157/03 Regulating the operation of the national institute of cooperative—Ley creación del INCOOP (2003) Resolution No. 499/04 INCOOP, ‘Whereby the General Framework for Regulation and Supervision of Cooperatives established’ Resolution No. 5,728/10 by which establish minimum requirements to enable agencies, branches, and/or ATMs cooperative in the country or abroad for savings and credit activities Framework for Regulation of Credit Unions (2013)—Marco de Regulación de las Cooperativas de Ahorro y Crédito More information GoP (2014) Decree No. 085 of 1981 New General Cooperative Law (updated in 2004)— Ley de Cooperativas Decree Law No. 25879 of 1992 declares the dissolution and liquidation of the Instituto Nacional de Cooperativas INCOOP (National Cooperative Institute) Regulation for Credit Unions not operating with resources from the general public (Resolution. SBS No. 540-99) of 1999 Resolution S.B.S. No. 621 (2003) amending Regulation of credit unions not authorized to operate with public resources Twenty-Fourth Final and Complementary Provision of the General Law of the Financial and Insurance System and the Organic Law of the Banking and Insurance Superintendence and the Pension Fund Manager, Law No. 26702 More infromation in IDB (1998); Rodriguez and Miranda (2004); Prialé and Dias (2010); and Morales (2013) Cooperative Societies Law No. 10761 of 1946 Decree Law No. 15.322 of 17 September 1982 for financial intermediation, (as amended by Law No. 16.327, dated November 11, 1992, Law No. 17.523 dated 4 August 2002, (Financial Intermediation Law) [Art. 2 of Law No. 16,327 of 11 No. 1992] General Cooperatives Law No. 18407 of 2008—Ley de Cooperativas (Chapter VI—Credit Unions) Amendments made by Decree No. 198/012 (concerning housing cooperatives) More information IMF (2013)

Table A7.5  List of supervisory authorities and deposit insurance schemes Country Africa West African Economic and Monetary Union (WAEMU)

  1 Benin   2 Burkina Faso   3 Cote d’Ivoire   4 Guinée Bissau   5 Mali

 6  7  8  9

Niger Senegal Togo Cameroon

10 Ethiopia 11 Gambia 12 Ghana

13 Kenya

14 Lesotho

15 Liberia

Supervision

Deposit insurance

Ministry of Finance of each country (1994–2007). ‘Cellule d’Appui et de Suivi des Structures Mutualistes ou Coopératives d’Epargne et de Crédit, or support and monitoring unit for savings and credit mutual and cooperative structures’. Since 2007: BCEAO/Banking Commission for large MFIs (savings/loans greater than US$4 million), Ministries of Finance for smaller ones. (p. 4) Regional Central Bank (Banque Centrale des Etats de l’Afrique del’Ouest or BCEAO) Cellule Microfinance—under the Ministry of Finance (Ouattara, 2003: p. 20) Ministry of Finance (Van Den Boogaerde, 2002: p. 14) Ministry of Finance (GIABA, 2013: p. 10 and 185) Ministry of Finance (IMF, 2013: 42)

Since the adoption of the new PARMEC law of 2007

Support Unit and Monitoring Decentralized Financial Systems at the Ministry of the Economy and Finance (Cellule d’Appui et de Suivi des Systèmes Financiers Décentralisés CAS/SFD) (Seibel, 2005: 2) Ministry of Finance (GIABA, 2009: p. 37 and75) Ministry of Finance Ministry of Finance (GIABA, 2011: p. 90) Ministry of Agriculture till 1998. Then under the Ministry of Finance from 1998 to 2005. Central African Banking Commission (COBAC) The Federal Cooperative Agency (FCA) Department of Cooperatives Central Bank of the Gambia Department of Co-operatives Bank of Ghana Ghana Cooperative Credit Unions Association (CUA) is to regulate and supervise all the Credit Unions in the country on behalf of the Bank of Ghana (CUA Ghana, 2016) Commissioner for Cooperative Development/ Co-operatives Directorate—Ministry of Industrialization and Enterprise Development / Ministry of Cooperative Development & Marketing (till 2008) SACCO Societies Regulatory Authority since 2008 Commissioner for Cooperative Development under the Ministry of Trade and Industry, Cooperatives and Marketing (MTICM) #Central Bank of Lesotho since 2012 Cooperative Development Association (CDA) under the Ministry of Agriculture

Since 2012 Since 2009 Since 2011 Since 2008 Since 2010

Since 2010 Since 2008 Since 2011 No

No No Since 2000

In the 2008 Act but not sure if it is already established

No

No (Continued)

Country 16 Malawi

17 Mauritius

18 Rwanda

19 South Africa

20 Swaziland

21 Tanzania 22 Uganda 23 Zimbabwe Asia 24 Azerbaijan

Supervision

Deposit insurance

Registrar of Cooperatives of the Ministry of Industry and Trade till 2010 and delegated inspection function to MUSCCO (MUSCCO, 2016) The Reserve Bank of Malawi (Since 2010) Ministry of Business, Enterprise, and Cooperatives (division of cooperatives) The Bank of Mauritius since 2004 (no license was issued) In 1988; the Ministère du Commerce (MINICOM), In 1997; the Ministère des Affaires sociales (MINAFASO) In 2003 National Bank of Rwanda Savings and Credit Co-operative League of South Africa (SACCOL) till 2007 South African Reserve Bank Co-operative Banks Development Agency (CBDA) since 2007 Department of Cooperative Development—Ministry of Commerce, Industry & Trade The Central Bank of Swaziland Financial Services Regulatory Authority since 2010 Ministry of Agriculture and Cooperatives till 2004 Bank of Tanzania since 2004 The Commissioner of Co-operative Development— Department of Cooperative Development at the Ministry of Trade Industry and Cooperatives Ministry of Small and Medium Enterprises and Cooperative Development

Since 2011

Central Bank of Azerbaijan

Not allowed to mobilize deposits Depositor Security fund are the Microcredit Regulatory Authority No The Deposit Insurance and Credit Guarantee Corporation established under Section 3 of the Deposit Insurance Corporation Act, 1961 Yes No Depositors’ Protection Fund

25 Bangladesh

Registrar of Cooperative Societies from 1984 Microcredit Regulatory Authority since 2006

26 Cambodia 27 India

National Bank of Cambodia Reserve Bank of India National Bank for Agriculture and Rural Development Registrar of Cooperative Societies (RCS)

28 Inodnesia 29 Laos

Ministry of Cooperatives (GOI, 2012) Bank of the Lao

No

No

Since 2007

No

Since 2004 ‘provision of Part V of the Act’ No No

Country 30 Malaysia 31 Mongolia

32 Nepal 33 Papa New Guinea 34 Philippines

35 Sri Lanka 36 Thailand 37 Uzbekistan 38 Vietnam Europe 39 Belarus 40 Latvia 41 Macedonia 42 Moldova 43 Poland

44 Romania 45 Russia

Supervision

Deposit insurance

Department of Cooperative Development Malaysia No till 2008, changed to be Cooperative Commission of Malaysia [CCM] (IMF, 2013: 19) The Association of Cooperatives till 2006 No Financial Regulatory Commission (FRC) established in 2006 is responsible for supervising nonbank financial institutions, including credit unions Department of Cooperative; Deposit guarantee Nepal Rastra Bank (Central Bank) scheme in Nepal from the year 2010 Governor of the Central Bank (IMF, 2011) No Central Bank and Deposit Insurance Co. for cooperative banks Cooperative Development Authority for credit cooperatives societies Ministry of Cooperatives and the Cooperative Development Department (WOCCU, 2001; Kelegama and Tilakaratane, 2014: 17) Ministry of Agriculture and Cooperatives (Cooperative Promotion Department and Cooperatives Audit Department) Central Bank of Uzbekistan (CBU) State Bank of Vietnam (SBV)

Not mandatory

Not sure Ministry of Agriculture and Food Union of Consumer Societies Bank of Latvia Financial and Capital Market Commission since 2002 (also banks) National Bank of The Republic Of Macedonia (NBRM, 2008) The State Supervisory Body of Savings and Credit Associations (SCA)—(SSB) under the Ministry of Finance National Association of Credit Unions (NASCU)—1995 Polish Financial Supervision Commission (2009)

No

National Bank of Romania No external supervision untill 2009 Since 2009: Self-Regulatory Organisations (SROs) Federal Financial Markets Service supervises the SROs (dissolved in september 2013)

No No Yes Yes

Deposit Guarantee Fund since 1998 Since 2000 No The mutual insurance company fund— TUW SKOK The Polish Cooperative Saving and Credit Union Mutual Insurance Society. The state guaranteed deposit insurance No No

(Continued)

Country 46 Ukraine

Supervision

Self-supervision (none)—registered with the National No Bank of Ukraine (NBU) under this decree since 1992 State Commission for Regulation of Financial Services Markets of Ukraine (non-bank financial institutions) since 2001 ((EIB, 2013: 13))

Latin America and Caribbean 47 Bolivia General Directorate of Cooperatives (la Dirección General de Cooperativas—DGCOOP) National Cooperative Institute (Instituto Nacional de Cooperativas—INALCO) Superintendency of Banks and Financial Entities (Superintendencia de Bancos y Entidades Financieras—SBEF)—till 2009 Financial Supervisory Authority System (Autoridad de Supervisión del Sistema Financiero—ASFI) 48 Brazil Central Bank of Brazil BCB Departamento de Supervisão de Cooperativas e Institutioções não Bancárias e de Atendimento de Demandas e Reclamações (DESUC) Cooperative credit networks (eg. SICOOB and SICREDI) (Resolution no. 2771 of 2000. Article 3 and Resolution no. 3106 of 2003. Article 13) 49 Chile Department of Co-operatives (small cooperatives) The Superintendence of Banks and Financial Institutions (SBIF) (large cooperatives) Central Bank of Chile 50 Colombia National Department of Cooperatives— Departamento Nacional de Cooperativas (Dancoop) till 1998 From 1998—The Superintendency of Solidarity Economy (Superintendent)—La Superintendencia de la Economía Solidaria (Superintendencia)—and Financial Superintendence. Also a cooperative and non-bank finacnial institutions supervisor 51 Costa Rica Superintendent of Financial Institutions— Superintendencia General de Entidades Financieras The National Institute for Cooperative Development—Instituto Nacional de Fomento Cooperativo (INFOCOOP) 52 Dominican Republic 53 Ecuador

Deposit insurance

Institute of Development and Credit Cooperative— IDECOOP (Instituto de Desarrollo y Crédito Cooperativo) Ecuador’s Superintendency of Banks and Insurance (for big cooperatives)—Superintendencia de Bancos y Seguros Superintendent of Popular and Solidarity Economy (for small cooperatives)—Superintendencia de la Economía Popular y Solidaria

The Central Bank of Bolivia is the depository of insurance deposits

Since 2009

Yes for large cooperatives Since 1999 the Fondo de Garantias de Entidades Cooperativas (FOGACOOP) INFOCOOP leads a project for implementing a Deposit Insurance Fund to CAC supervised by them (on standby for now). No For large cooperatives since 1998 Agencia de Garantia de Depositos In small cooperatives since 2011

Country 54 El Salvador

55 Guatemala 56 Guyana

57 Honduras

58 Jamaica 59 Mexico

60 Nicaragua

Supervision

Deposit insurance

Central bank for large cooperative banks and societies, but only six banks and two societies are regulated under the 2008 Act Salvadoran Institute for the Promotion of Cooperatives (Instituto Salvadoreño de Fomento Cooperativo)—INSAFOCOOP Superintendent of the Financial System The General Inspector of Cooperatives—INGECOP (Inspección General de cooperativas) Commissioner for Cooperative Development The Cooperative Department of the Ministry of Labour has responsibility for registering, monitoring, regulating, and cancelling Cooperative Societies and Friendly Societies. Honduran Institute of Cooperatives—IHDECOOP (Instituto Hondureño de cooperativas) Superintendent of Credit Unions—CONSUCOOP (Superintendencia de Cooperativas de Ahorro y Crédito) under the NATIONAL COMMISSION ON BANKING AND INSURANCE Since 2011—Comisión Nacional de Bancos y Seguros—National Commission on Banking and Insurance (for cooperative bank and voluntarily 20 credit unions) Department of Co-operatives and Friendly Societies The Jamaica Co-operative Credit Union League Limited (not officially) The Supervisory Board of Federations and the Confederation (General Cooperative Societies Law of 1994) under the National Banking and Securities Commission Public Register of Commerce Finance Ministry (Secretaria de Hacienda y Credito Publico) By registered at the CNBV (National Banking and Securities Commission—Comisión Nacional Bancaria y de Valores—1985 law amended in 2000) By federations since 2001 ‘Auxiliary Supervision Trust for Savings and Loan Cooperatives and Saver Protection’ (law of 2009) Auxiliary Supervision Committee (Comite´ de Supervisio´n Auxiliar). A cooperative may not act without this authorization. The authorization is given by the ‘National Banking and Values Commission (Comisio´n Nacional Bancaria y de Valores)” Ministry of Labor (law of 1971) Instituto Nacional de Fomento Cooperativo (INFOCOOP) from 2004 law Instituto Nicaraguense de Fomento Cooperativo (Nicaraguan Institute for Cooperative Promotion)

Only open cooperatives from 2010

No No

A Cooperative Insurance Fund Deposits (FOSEDE) is created by the amedments made in the+E16 Decree No. 174–2013

No Deposit insurance fund mentioned in the law of 2001; however, implementation was not clear at least till the issuance of the law of 2009. Now almost all regulated financial cooperatives are covered.

No

(Continued)

Country

Supervision

Deposit insurance

61 Panama

Panamanian Autonomous Institute for Cooperatives (IPACOOP) (since the law of 1980)

62 Paraguay

At least since the law of 1994 National Institute of Cooperativism (INCOOP)—Instituto Nacional de Cooperativismo

63 Peru

COFEP Corporation Guarantee Fund, only to Cooperatives (since 1985) INCOOP project to create a Deposit Insurance Fund in final phase of implementation (supported by DGRV) No

Ministry of Production National Federation of Savings and Credit Cooperatives of Peru (FENACREP)—La Federación Nacional de Cooperativas de Ahorro y Crédito del Perú Superintendency of Financial Services—(large FCs— Corporación de Protección del only one now) Ahorro Bancario Internal Audit Office—AIN (Auditoría Interna de (COPAB) only for la Nación) under the Ministry of Economy and large FCs since 2008 Finance (monitoring) National Cooperative Institute—INACOOP (Instituto Nacional de Cooperativismo) (only promotion)

64 Uruguay

Index

Note: Bold page numbers refer to tables and page numbers followed by “n” denote endnotes. Acemoglu, D. 19, 45, 50, 75–6 Adams, D. 123 African countries: deposit insurance schemes 169–70; financial cooperatives regulation 160–2; supervisory authorities 169–70 agency conflict: borrowers against net depositors’ conflict 96–7; depositor-shareholder 96; and financial cooperative regulations 96–8; member-manager conflict 96, 97 Aghion, P. 15, 18 Agricultural Bank, Egypt 64 agricultural cooperatives 63, 95 Akande, O. R. 122 Alexopoulos, Y. 10 Alston, L. J. 102 Angelini, P. 29 ANGKASA, Malaysia 66 Asian countries: deposit insurance schemes 170–1; financial cooperatives regulation 162–4; supervisory authorities 170–1 assets per GDP: in African countries 73–4; FE OLS 81; financial cooperatives indicators against deposit insurance 130; financial cooperatives indicators against regulations 119; financial cooperatives indicators against supervision 125; fixed-effects IV 2SLS regression 82–3; and general cooperative societies 133; in Southeast Asia 74 autocratic regimes, and financial cooperatives 73

Baker, C. 97 Bamrungwon, C. 59, 95 Banerjee, A. V. 14–15, 18, 23 banks/banking 5; and deposit insurance 103, 113; law 91; risk-taking behaviour 102 Barth, J. R. 67–8 Basel Committee for Banking Supervisions (BCBS) 98–100, 109–10; Core Principles 109, 112 Baxter, N. D. 24 Beck, T. 40 Benin 73–4 Ben Naceur, S. 43 Bentley, Arthur 64 Bergh, A. 45 Birchall, J. 8–9 Bolton, P. 15, 18 borrowers against net depositors’ conflict 96–7 Bourguignon, F. 19 Bowles, S. 30 BPCE Group 1 Branch, B. 91, 94, 97, 122, 123 Breusch-Pagan / Cook-Weisberg test 140 British Co-operative Group 10 British cooperative law 90–1 British-Indian cooperative law 91 British-Indian Pattern of Co-operation (BICP) 90–1 Butzbach, O. 9 capital: human 15–16, 21, 31, 36, 39, 67; physical 21; transfer 27–8 capital markets 3; and matured financial cooperative sectors 17

176 Index capital requirements: and equity 99–100; and financial cooperative regulations 98–100 capital transfer 27–8, 32 Chiaramonte, L. 9 civil liberties index 75–6; and political stability 80 Claessens, S. 84 Clarke, G. 40 coinsurance 104, 114 commercial banking regulations 123; and financial cooperatives 133; see also banks/banking Commons, J. R. 65 Co-operative Model Law (1946) 90–1 cooperatives: society regulations 92; state control in developing countries 62–4; see also financial cooperatives Cooperatives Act for the North German Confederation (1868) 60 Cooperative Societies Act (2004) 74, 90 Copeland, T. E. 24 Coskun, Y. 48 Cournède, B. 43, 48 Crédit Agricole 1 Crédit Mutuel 1 credit rationing: income distribution with 22–8; wealth distribution with 22–8 credit social capital 16, 23–5, 28, 39–40 Crüger, Hans 60 Cuevas, C. E. 8–9, 88, 91–2, 94, 96–7, 108–9, 122 Cull, R. 122 Cyprus Co-operative Bank 10 Deaton, A. 21 Demirguc-Kunt, A. 102, 103 democratic political systems: and financial cooperatives 73; and political stability 76, 79 Denk, O. 43, 48 deposit insurance 102–3; and banks’ risk-taking behaviour 103, 113; and depositors’ assets 113; explicit 103, 113; and fixed-effects regression 130; risk-based 104, 114; and risk-taking behaviour of institutions 103–4 deposit insurance schemes 17; for African countries 169–70; for Asian countries 170–1; for European countries 171–2; for financial cooperatives 124–8, 134; for Latin American countries 172–4

depositor-shareholder agency conflict 96 deposits per GDP: FE OLS regression 81; financial cooperatives indicators against deposit insurance 130; financial cooperatives indicators against regulations 119; financial cooperatives indicators against supervision 125; fixed-effects IV 2SLS regression 82–3 Desrochers, M. 101 Detragiache, E. 103 developing countries: and banksupervising authorities 123; and cooperative societies authorities 133; and deposit insurance scheme 132; history of state control over cooperatives in 62–4; informal employment in 85 Develtere, P. 64, 91 distribution 2–8, 14–36 domestic credit 85 dual regime 91; defined 109; Latin America 109 Duflo, E. 14, 23 econometric methods 139–41 Economic Freedom Index 85 economic objective of financial cooperatives 14–36; function 33–5; income and wealth distribution with credit rationing 22–8; income and wealth distribution with financial cooperatives 28–33; income determinants 20–2; production function 19–20 economic pressure groups 65 egalitarian development, financial cooperatives for 8–9 Egyptian Confederation of Agricultural Cooperatives 63 ‘emerging and developing economies’ 73, 74, 114 equity: and financial cooperative capital requirements 99–100; mutual and cooperative banks shares as 99–100 Esty, B. C. 103 Ethiopia 74 European cooperative banking sector 91 European countries: deposit insurance schemes 171–2; financial cooperatives regulation 164–5; supervisory authorities 171–2 EuroStat 45

Index  177 explicit deposit insurance 103; and European banks 113 external borrowing 7, 9, 15, 18, 21, 30, 32, 34–5 external funds 2, 30, 32 Fals-Borda, O. 62 Fascism 65 Ferri, G. 9 finance 14–36; capitalism 5; distribution 2–8; financialization 2–8; and income inequality 40–4; political economy of 2–8 financial cooperatives: and autocratic regimes 73; avoiding an idealisation trap 9–11; and commercial bank regulations 133; and democratic political systems 73; development 75, 137; development variables 114–16; economic objective function 33–5; economic objectives 14–36, 90; for egalitarian development 8–9; financialization 2–8; income distribution with 28–33; and income inequality 39–56, 142; indicators and non-bank financial institutions law 119, 120, 125; indicators of 80; internal politics 138; overview 1–2; ownership structure of 94; penetration rate in African countries 73–4; political economy theory of 2–8, 61–9, 137; political history of 59–61; and stakeholders 93–4; supervision approaches in 1995 vs. 2014 110–12; supervisory approaches of 112–13; supervisory authority 124–8; wealth distribution with 28–33; see also cooperatives financial cooperatives laws: current models of 91–2; historical origins of 90–1 financial cooperatives regulation 88; for African countries 160–2; and agency problems 96–8; for Asian countries 162–4; and capital requirements 98–100; credit operations 94; for European countries 164–5; and fixedeffects regression 119–21; and GDP per capita 120, 123, 125, 126; and institutional integration 100–1; for Latin American countries 165–8; in 1995 vs. 2014 109, 110–12; objective of 93; protecting members’ deposits 102–4; protection from government interference 95–6; rationale for 93–104 financial crisis 44, 88; (2007–08) 8, 9, 89

financial development: political economy theories of 66–9 financial freedom index 84 financialization 2–8 financial regulation: and government intervention 89; importance of 89; objective of 88–9 Finland 1 First World War 65 Fischer, K. P. 8–9, 88, 91–2, 94, 96–7, 101, 108–9, 123 fixed-effect estimator 139 fixed-effects IV 2SLS regression 82–3; assets per GDP 82–3; deposits per GDP 82–3; penetration rate 82–3 fixed effects ordinary least squares (FE OLS) regression 80, 81; assets per GDP 81; deposits per GDP 81; penetration rate 81 fixed-effects regression: for financial cooperatives indicators and deposit insurance 130; for financial cooperatives indicators and regulations 118–20; for financial cooperatives indicators and supervision 119–21 Fonteyne, W. 9 for-profit institutions 8, 9 France, cooperative banks in 1, 73 free cash flow hypothesis 97 Gagnon, G. 63 Galor, O. 15 GDP per capita: and financial cooperatives development 85; and financial cooperatives regulation 120, 124, 125, 126 general banking regulations 92 general cooperative societies: and assets per GDP 133; law and financial cooperatives 108; and penetration rate 133; regulation authorities of 122, 129 German cooperative law 90 Germany 1, 8, 30, 60, 90 Gini coefficient 45, 50, 56 Gintis, H. 30 Girma, S. 68 global economic crisis 3 Goglio, S. 10 government effectiveness 79; index 76; and political rights index 80; and Polity index 80 government interference: and financial cooperative regulations 89, 95–6

178 Index Grace, D. 91, 94, 122, 123 grassroot organisations 3 Greenwood, J. 14, 43 Gropp, R. 102–3, 113 Grossman, R. S. 102 Guinnane, T. W. 30, 101

Jansson, T. 93, 122 Jauch, S. 45, 48 Jenkins, S. 21 Jensen, M. 97 Jones, C. I. 19, 30 Jovanovic, B. 14, 43

de Haan, J. 43, 48 Haas, Wilham 60 Haber, S. 66 Hamori, S. 40 Hannafin, K. 103–4 Hartarska, V. 122 Hashiguchi, Y. 40 Hausman Fixed Random Test 140 Hellenic Bank 10 Heritage Foundation 85 Hilferding, R. 5 Hovakimian, A. 103, 113 Huber-White robust estimator 140 human capital 15–16, 21, 31, 36, 39, 67

Kaldor, N. 19 Kalmi, P. 30 Kappel, V. 40 Karels, G. V. 103 Kenya 74, 124–5, 134n3 Kenya Union of Savings and Credit Cooperatives (KUSCCO) 66 Kim, D. 43

Iannotta, G. 6 Ibrahim Index of African Governance 74 idealisation trap 9–11 income determinants 20–2 income distribution: with credit rationing 22–8; with financial cooperatives 28–33; theory 137 income inequality: data and method 44–8; finance and 40–4; financial cooperatives and 39–56; inequality measurements 44–5; methodology 45–52; overview 39–40 India 74 Indian Credit Co-operative Societies Act (1904) 90 institutional integration: and financial cooperatives 100–1; and regional banks 101; and small credit cooperatives 101 instrumental variables (IV) regressions 140 International Labour Organization (ILO) 95 International Monetary Fund (IMF) 73, 114 investor-owned financial institutions 17, 29, 103–4; shares in 113 Ioannidou, V. P. 102 Italian Fascism 65

Labie, M. 9 Laeven, L. 84 Lagram-Multiplier test 140 Latham, Earl 64 Latin America 73; British-Indian cooperative law 91; deposit insurance schemes 172–4; dual regime 109; financial cooperatives regulation 108, 165–8; supervisory authorities 172–4 Law, S. H. 43, 45 lender-borrower relationship 16, 39 Levine, R. 102 liberalism 65 Lin, S. 43 Logic of Collective Action (Olson) 65 long-term interaction hypothesis 29 low-income agents 3, 21, 25–30, 36, 39–40 Luxembourg Income Study (LIS) 45 Mcclatchey, C. A. 103 Mckillop, D. 103–4 market capitalization 5 member-manager conflict 96, 97 Mersland, R. 29, 30 Mettenheim, K. von 9 microfinance institutions 8–9, 29, 122 middle-income agents 3, 16, 21, 25–32, 36, 39–40 ‘Model Law for Credit Unions’ 92 Monetary Circuit theory 6 multilateral development banks 8 Münkner, H. H. 89, 90 mutual financial cooperation 138 mutual institutions 96, 104, 113 Nadolnyak, D. 122 Nasser, Gamal Abdel 63

Index  179 National Federation of State Cooperative Banks 75 National Liberal Party 60 Nationwide Bank 10 Netherlands, cooperative banks in 1, 73 Newman, A. F. 15, 18 Nilsson, T. 45 non-bank financial institutions: and underdeveloped economies 88 ‘Norddeutscher Bund’ 90 North, D. C. 61 not-for-profit institutions 8, 9, 122 occupational associations 65 OECD countries 9, 43 Olson, Mancur 61, 64, 65 ordinary least squares (OLS) regression 141; basic structure for 139; financial cooperatives indicators against civil liberties indices 144–5; financial cooperatives indicators against democracy 144–5; financial cooperatives indicators against political rights 144–5 Ostry, M. J. D. 45 ownership structure hypothesis 97 Panico, C. 43 Passarella, M. 6 peer monitoring 29 peer-monitoring hypothesis 29 Penas, M. F. 102 penetration rate: and cooperative societies’ supervision 120, 129; defined 86n2; FE OLS regression 81; financial cooperatives, in African countries 73–4; financial cooperatives indicators against deposit insurance 130; financial cooperatives indicators against regulations 120; financial cooperatives indicators against supervision 125; fixed-effects IV 2SLS regression 82–3; and general cooperative societies 133; and political rights index 79; and Polity IV project 80 performance structure hypothesis 97 Périlleux, A. 9, 29, 30, 85 Perotti, E. 66 physical capital 21 Piketty, T. 15, 18 pluralism 64 political economy of finance 2–8

political economy theory 7, 61–9; of financial cooperatives 61–9; of financial development 66–9; history of state control over cooperatives in developing countries 62–4; overview 59; political history of financial cooperatives 59–61; theories of pressure groups 64–6 political history of financial cooperatives 59–61 political institutions: indicators of 80; quality of 75–6 political rights index 75–6; and democracy 79; and government effectiveness 80; and penetration rate 79; and political stability 80 political stability: and civil liberties 80; and democracy 76, 79; and political rights index 80 ‘political stability and absence of violence’ index 76 Polity index 75–6; and government effectiveness 80 Polity IV project 75–6; and penetration rate 80 Pollet, I. 64, 91 Poyo, J. 101, 122, 123 pressure groups 64–6 production function 19–20 profit-oriented microfinance institutions 122 property rights 84–5 Proudhon, Pierre-Joseph 64 Prudential Regulation Authority 10 Prussia’s Second Chamber 60 RaboBank 1 Raiffeisen, Friedrich 1, 60 Raiffeisen Schweiz bank 10 Rajan, R. G. 66 random-effects regressions: for change in financial cooperatives indicators against regulations 148–9; for change in financial cooperatives indicators and supervision 154–5; for financial cooperatives deposit insurance 159; for financial cooperatives indicators against deposit insurance 158–9; for financial cooperatives indicators against regulations 146–7; for financial cooperatives indicators and supervision 152–3; for financial cooperatives regulations 150–1; for financial cooperatives supervision 156–7

180 Index regression see fixed-effects regression; fixed-effects IV 2SLS regression; fixed effects ordinary least squares (FE OLS) regression risk-based deposit insurance 104, 114 risk-taking behaviour 129; of banks and deposit insurance scheme 102–3, 113; of credit unions and ownership structure 103; and mutual ownership structure 104 Robinson, J. A. 75–6 rotating savings and credit associations (ROSCAs) 89, 93 Russian Communism 65 Sadat, Anwar 63–4 Sargan-Hansen tests 50 Savings and Credit Cooperative Societies (SACCOs) 66 Savings and Loan Associations 10 Sawyer, M. 6 Schulze-Delitzch, Hermann 1, 60–1, 90 Sen, A. 21 Senegal 73–4 Seven, U. 48 Shortland, A. 68 Small and Medium Enterprises (SMEs) 9; credit market 1; lending 2 Smith, D. J. 33 SNCF, Singapore 66 sovereign debt crisis (2010–13) 9 stakeholders 99; and financial cooperatives 93–4 Stalin, Joseph 63 Standardized World Income Inequality Database (SWIID) 45 state control over cooperatives 62–4 Stiglitz, J. E. 19, 22, 24, 29 Stock Flow Consistent model 6 Sturm, J. E. 43, 48 supervisory approaches: delegated or auxiliary supervision 113; direct supervision 113; of financial cooperatives 112–13; supervision by ministries of cooperatives 113 supervisory authorities: for African countries 169–70; for Asian countries 170–1; for European countries 171–2; financial cooperatives 124–8; for Latin American countries 172–4

Tan, H. B. 45 Taylor, R. A. 33 Tchakoute-Tchuigoua, H. 29, 30 Thailand 74 theories of pressure groups 64–6 de Tocqueville, Alexis 64 traditional banking regulations 123 Truman, David 65 underdeveloped economies: defined 73; financial cooperatives in 73, 108; historical origins of financial cooperative laws in 90–1; role of nonbank financial institutions 88 United States Bill of Rights 65 URECOCI 66 Vesala, J. 102–3, 113 Vittas, D. 89 ‘Vorschußverein’ 90 wage rate 15, 20–1, 36 Watzka, S. 45, 48 wealth distribution: with credit rationing 22–8; with financial cooperatives 28–33 Weiss, A. 22, 24 Weston, J. F. 24 Wheelock, D. C. 102 Wilson, P. W. 102 World Bank 45, 76; ‘government effectiveness’ index 76; ‘political stability and absence of violence’ index 76 World Bank Group 8 World Bank Open database 4 World Council for Credit Union (WOCCU) 1, 75, 92 World Economic Outlook of (2012) 73–4 World Income Inequality Database (WIID) 45 World Inequality Database 4 Yunis, Ahmed 63 Yunus, Mohamed 8 Zhang, R. 43 Zimbabwe 74 Zingales, L. 66, 68