Financial Liberalization and Investment (Routledge Studies in Development Economics, No. 4)

FINANCIAL LIBERALIZATION AND INVESTMENT

For two decades thinking on economic policy has been dominated by the idea of economic liberalization in general and financial deregulation in particular. This field has become both extensive and controversial, yet there is no single book that treats financial deregulation in a coherent and complete manner. Financial Liberalization and Investment rectifies this by focusing specifically on the consequences of interest rate deregulation for the real sectors of the economy. What happens to savings, investment, income, and growth if governments allow interest rates to be determined by market forces? Using both analytical and simulation models, the authors analyze this question under a wide array of assumptions about the behavior of consumers, firms, banks, informal credit market, governments, and foreign aid. The study provides guidance to a number of controversial issues in the field, and suggests avenues for further research. Kanhaya L.Gupta is Professor of Economics at the University of Alberta. He has published widely on macroeconomics and monetary economics. In addition to five books he has published articles in American Economic Review, Econo-metrica, Economica, International Economic Review, Quarterly Journal of Economics, Review of Economics and Statistics, and the Review of Economic Studies. Robert Lensink is Assistant Professor of Economics at Groningen University, the Netherlands. He currently researches in development and international economics. His Ph.D. dissertation deals with capital flows between North and South, and he has recently published in Economic Modelling.

ROUTLEDGE STUDIES IN DEVELOPMENT ECONOMICS

1 Economic Development in the Middle East Rodney Wilson 2 Monetary and Financial Policies in Developing Countries Akhtar Hossain and Anis Chowdhury 3 New Directions in Development Economics (Growth, Envir onmental Concerns and Government in the 1990s) Edited by Mats Lindahl and Benno J.Ndulu 4 Financial Liberalization and Investment Kanhaya L.Gupta and Robert Lensink

FINANCIAL LIBERALIZATION AND INVESTMENT

Kanhaya L.Gupta and Robert Lensink

London and New York

First published 1996 by Routledge 11 New Fetter Lane, London EC4P 4EE Simultaneously published in the USA and Canada by Routledge 29 West 35th Street, New York, NY 10001 Routledge is an imprint of the Taylor & Francis Group This edition published in the Taylor & Francis e-Library, 2003. © 1996 Kanhaya L.Gupta and Robert Lensink All rights reserved. No part of this book may be reprinted or reproduced or utilized 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. British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloguing in Publication Data A catalogue record for this book has been requested ISBN 0-203-43775-6 Master e-book ISBN

ISBN 0-203-74599-X (Adobe eReader Format) ISBN 0-415-13879-5 (Print Edition)

To Carole and Ans

CONTENTS

ix xi xii

List of figures List of tables Acknowledgements 1

INTRODUCTION Appendix 1

2

THE BASE MODEL The model Financial liberalization and the supply of credit to the private sector Financial liberalization and private investment Concluding remarks Appendix 2 Appendix 3

3

4

1 8

ROLE OF FOREIGN AID AND THE GOVERNMENT The fiscal response to foreign aid The model when government expenditures and taxes are endogenized Financial liberalization when foreign aid is exogenous The role of foreign aid when aid is endogenized Conclusions Appendix 4 THE ROLE OF INFORMAL FINANCIAL MARKETS Different types of informal financial intermediaries Theories on the working of informal financial markets Role of interest rate deregulation in the presence of curb markets: A brief survey

vii

10 11 19 21 25 26 28 30 31 34 38 42 45 47 50 51 54 58

CONTENTS

The model Financial liberalization and private investment Conclusions Appendix 5 5

6

ALLOCATIVE EFFICIENCY AND FINANCIAL DEREGULATION The Galbis model Some empirical evidence The model How to measure the improvement of the allocative efficiency? The impact of deregulation of the formal deposit rate on the allocative efficiency Conclusions BANKING EFFICIENCY AND PRIVATE INVESTMENT The Viaene model The model Banking efficiency and private investment if the private sector is credit constrained Banking efficiency and investment if the private sector is not credit constrained Concluding remarks

60 63 67 67 69 70 71 75 79 79 85 86 87 87 89 93 94

7

SOME SIMULATION RESULTS The model The simulation strategy The simulation results Concluding remarks Appendix 6

96 97 107 113 142 143

8

FINANCIAL REPRESSION AND FISCAL POLICY The simulation strategy The simulation results Concluding remarks

146 147 147 164

9

SUMMING UP

166 168 171 179

Notes Bibliography Index

viii

FIGURES

7.1 7.2 7.3 7.4 7.5 7.6 7.7 7.8 7.9 7.10 7.11 7.12 7.13 7.14 7.15

7.16

Base model simulations Base model simulations Base model simulations Base model simulations Base model simulations Base model simulations Alternative simulation 1: no substitution between deposits and capital Alternative simulation 1: no substitution between deposits and capital Alternative simulation 2: only investment is credit constrained Alternative simulation 2: only investment is credit constrained Alternative simulation 3: consumption not affected by real interest rates Alternative simulation 3: consumption not affected by real interest rates Alternative simulation 4: higher wealth effect in investment equation Alternative simulation 4: higher wealth effect in investment equation Alternative simulation 5: higher reserve requirements in formal banking sector and only investment credit constrained Alternative simulation 5: higher reserve requirements in formal banking sector and only investment credit constrained

ix

114 115 116 117 118 119 121 122 123 124 125 126 128 129

130

131

FIGURES

7.17 Alternative simulation 5: higher reserve requirements in formal banking sector and only investment credit constrained 132 7.18 Alternative simulation 6: aid increases with 5% 134 7.19 Alternative simulation 6: aid increases with 5% 135 7.20 Alternative simulation 6: aid increases with 5% 136 7.21 Alternative simulation 6: aid increases with 5% 137 7.22 Alternative simulation 7: aid increases with 5% and government investment positively affects private investment (γ1=0.3) 138 7.23 Alternative simulation 7: aid increases with 5% and government investment positively affects private investment (γ1=0.3) 139 7.24 Alternative simulation 7: aid increases with 5% and government investment positively affects private investment (γ1=0.3) 140 7.25 Alternative simulation 7: aid increases with 5% and government investment positively affects private investment (γ1=0.3) 141 8.1 Tax on bond interest income: private investment 149 8.2 Tax on bond interest income: government investment 150 8.3 Tax on bond interest income: government consumption 151 8.4 Tax on bond interest income: inflation 152 8.5 Tax on bond interest income: private wealth 153 8.6 Borrowing at concessional rates: private investment 154 8.7 Borrowing at concessional rates: government investment 155 8.8 Borrowing at concessional rates: government consumption 156 8.9 Borrowing at concessional rates: inflation 157 8.10 Borrowing at concessional rates: private wealth 158 8.11 Higher reserve requirements for formal banks: private investment 159 8.12 Higher reserve requirements for formal banks: government investment 160 8.13 Higher reserve requirements for formal banks: government consumption 161 8.14 Higher reserve requirements for formal banks: inflation 162 8.15 Higher reserve requirements for formal banks: private wealth 163

x

TABLES

2.1 The accounting framework of the model 3.1 Effects of aid on government expenditures and taxes 4.1 The accounting framework of the model including informal financial markets 5.1 Costs of borrowing of 68 manufacturing industries 5.2 Costs of borrowing for 28 industries in Turkey 5.3 Measures of efficiency of the allocation of investment in Indonesia 5.4 Measures of efficiency of the allocation of investment in Ecuador 7.1 Notations and definitions used in the model 7.2 The accounting framework of the model 7.3 Parameters of the asset demand equations and private consumption 7.4 Parameters of the government equations, initial values and exogenous variables 8.1 Effects of financial repression

xi

11 34 62 72 73 74 74 97 99 111 112 164

ACKNOWLEDGEMENTS

Our most sincere thanks to the referee of the publisher for constructive criticisms and suggestions and to Charlene Hill for her excellent typing. A good deal of this work was done while Kanhaya Gupta was a visiting professor in the department of economics, University of Groningen, the Netherlands, during May to July 1994. He extends his deep appreciation for the department’s invitation, facilities and its hospitality.

xii

1 INTRODUCTION The purpose of this brief introduction is to explain the motivation for our work and provide a brief outline of the chapters to follow. Inspired by the influential works of McKinnon (1973) and Shaw (1973), and by the requirements of the IMF/World Bank sponsored structural adjustment programs, the effects of financial liberalization on investment in developing countries have drawn much attention. The major thrust of this literature has been to understand the mechanisms by which interest rate deregulation and the elimination of other forms of financial repression—for example, changes in reserve requirements—affect savings and investment. Broadly speaking, we can distinguish two sets of approaches in the literature: those based on non-optimizing models and those which involve optimizing frameworks. The former includes works which essentially build on the model suggested by McKinnon (1973). This body of literature is extensively summarized in Fry (1988) and Gibson and Tsakalotos (1994). The optimizing models draw their inspiration from the pioneering works of Romer (1986) and Lucas (1988) on endogenous growth models. This part of the literature is extensively surveyed by Berthelemy and Varoudakis (1994), De la Fuente and Marin (1993), Pagano (1993) and Schiantarelli et al. (1994b), but see also the appendix to this chapter. Our work is in the tradition of the non-optimizing models. Instead of giving a survey of the existing literature, our approach is to discuss the relevant literature within the context of our model in each chapter. Consequently, in this introduction we only explain the motivation for our work and then give a brief review of the chapters to follow. In addition to the literature on the effects of financial liberalization, there is also much work on the role of informal credit markets in meeting the needs of households and firms. Other areas of important concern have been the role of foreign aid in the growth of developing countries, the implications of the credit needs of the governments to finance budget deficits, the implications of financial repression for raising government revenues, and the importance of wealth effects. However, in

1

INTRODUCTION

virtually no work on the effects of financial liberalization that we are aware of are all these different strands of thought brought together in an integrated framework. Of course, there are efforts which try to combine one or more of these issues. For example, Van Wijnbergen (1983a, 1983b), and others in the ‘neostructuralist’ school, examine the role of informal credit markets, but pay very little attention to the role of foreign aid, wealth effects, crowding out of private credit by the needs of the government to finance budget deficits and so on. Morisset (1993) examines the effects of crowding out of private credit caused by the government’s budgetary needs and a shift in the public’s portfolio caused by interest rate deregulation. But he treats government budgets as being exogenously given, ignores the role of foreign aid and informal credit markets and treats savings as being exogenously determined, thus eliminating all indirect effects of interest rate deregulation via changes in wealth. The aim of this study is to provide a systematic analysis of the whole range of questions which have been raised in the literature with respect to financial liberalization. More specifically, our study is distinguished by the following features: 1 It analyzes three aspects of financial liberalization. These three aspects are the effects of interest rate deregulation on the quantity of investment, the effects on the allocative efficiency of investment and the effects of an improvement in banking efficiency on investment. It is only the first of these effects that has received considerable attention in the literature. This is curious since the other two are mentioned almost as often as the first one. 2 Its second distinction is that it takes into account many mechanisms by which a financial liberalization may affect investment which have hitherto not been incorporated in the existing models. In particular the role of wealth effects, effects of portfolio changes and crowding out by government budgetary behavior are allowed simultaneously. We accomplish this task by using an integrated model of portfolio selection and consumption—saving, which has not been done before. Similarly we endogenize government budget deficit, thus explicitly analyzing the effects of interest rate deregulation on government expenditures, revenues and interest payment. At the same time we also incorporate informal credit markets.

2

INTRODUCTION

3 While there is a good deal of literature on foreign aid and economic growth in developing countries, as well as the conditionally of IMF/World Bank on the granting of concessional loans on the adoption of financial deregulation policies, there is, to our knowledge, no formal treatment in which the effects of financial deregulation and foreign aid on investment are modelled simultaneously. Our study tries to fill this gap by considering both sides of the structural adjustment program simultaneously. 4 While the above exercises fill many of the gaps in the existing literature and open up some new avenues, the fact still remains that our ability to derive analytical results from a model which combines all of the aspects mentioned above remains limited. One of the options is to formulate a general model and carry out simulations. This is precisely what we do. The model is based on the foundations laid out in 1, 2 and 3 above. Simulations are carried out under a variety of assumptions about the behavior of the economic agents involved in the model. These simulations help us shed light on a number of controversial issues in the literature on economic liberalization in general and financial liberalization in particular as discussed in the chapter outlines which follow. Chapter 2 constitutes the foundation for the entire work. Assuming a given government budget deficit and a demand-determined world, we specify our model and explain how it differs from the existing works. It distinguishes three sectors: a consolidated private sector, a consolidated banking sector and a government sector. Unlike the existing works, we assume that the private sector’s decisions about portfolio selection and consumption—saving are integrated, in which wealth plays an important role and where the private sector is credit constrained. This part of the model draws on the work by Owen (1981) and others on portfolio selection modeling. In this chapter we then go on to derive the conditions under which an interest rate deregulation can lead to an increase in the supply of bank credit to the private sector in the presence of crowding out effects of government’s borrowing requirements from the banks, the crowding out being induced by a reallocation of the private sector’s portfolio consequent upon interest rate changes on deposits. The chapter then goes on to derive the conditions under which McKinnon’s well-known ‘complementarity’ hypothesis

3

INTRODUCTION

holds. It is shown that the conditions are far more stringent than is recognized in the literature so far. It is also shown that the outcome is greatly affected by our assumption that the private sector’s portfolio decision and consumption—saving decision are integrated. The model in Chapter 2 assumed that government budget deficit was exogenously given and that it was entirely financed by domestic resources. In Chapter 3 we introduce two innovations compared to the rest of the literature in the field. First we endogenize the deficit. This we do by drawing on the literature on the fungibility of foreign aid. For this purpose we use an optimizing model of the government’s fiscal behavior. The second innovation is that we introduce foreign aid. While there is voluminous literature on the effects of foreign aid on the economies of developing countries, there is virtually none which tries to assess the implications of such aid for the success or failure of interest rate deregulation policies. This omission is rather curious in that in the structural adjustment programs of the IMF/World Bank a condition for the provision of concessional loans/ aid is often conditional on the adoption of reforms in the financial sector including interest rate deregulation. We try to model such an interaction using the basic model specified in Chapter 2. We show that an interest rate deregulation without foreign aid may lead to a sub-optimal situation. In the case where financial liberalization does not lead to a fall in government investment, probably the crowding out of the supply of credit to the private sector by the government will be large. Otherwise, in the case where the government tries to avoid these crowding out effects, a decline in government investment will probably be the result. We also show that foreign aid might neutralize the crowding out effects of private credit. However, it is not a guarantee for a halt in the decline in government investment. This depends on the pattern of usage of such aid, i.e. on the degree of ‘fungibility’ of such aid. In the models discussed previously we have abstracted from informal credit markets. However, recently many authors have pointed out the role of the informal financial sector in financing the credit needs of the private sector. In the literature two views with respect to the financial intermediation of the informal sector are distinguished. Traditionally, the informal lenders are associated with monopolistic moneylenders who exploit the poor charging usurious interest rates and are stereotyped as being exploitative. In this view, informal financial intermediation is very inefficient and costs are high so that a substantial part of total savings goes to informal banks

4

INTRODUCTION

as a reward for the services supplied. However, many recent studies argue that the informal financial market is a highly efficient competitive market with developed linkages with the official markets. In Chapter 4 we incorporate the informal financial market in the Chapter 2 model and assess the impact of interest rate deregulation on private investment under different assumptions about the workings of the informal financial market. We show that most of the existing works are special cases of our more general model and, once again, that the way we model the private sector’s behavior about portfolio selection and consumption—saving has important bearing on the outcomes. We also go on to derive the conditions under which informal credit markets are helpful to the effectiveness of interest rate deregulation policies. The analysis so far has dealt with the scale effects of financial deregulation, namely the effects on the quantity of investment. However, the literature also emphasizes another channel through which such deregulation may enhance growth. This has to do with the allocative efficiency effect. The idea is that higher interest rates, by inducing the selection of projects with higher rates of return, will raise the average productivity of investment and hence growth, even if the effect on savings and thus total investment was negligible. The main difficulty in dealing with this issue is how to measure improvements in allocative efficiency which are induced by financial deregulation. Using a two-sector model, Galbis (1977) tried to analyze this problem. However as we explain his model is just an assertion of his results and that it cannot be used to answer the question being considered. Besides he ignores the informal credit market which apparently plays a crucial role in this debate. In Chapter 5 we develop a two sector version of the model in Chapter 4. Then we suggest how to assess the effects of interest rate deregulation on allocative efficiency. Finally, we show the conditions under which allocative efficiency may improve as a consequence of interest rate deregulation. It is shown that such deregulation does not always guarantee an improvement in overall productivity. The outcome depends on how the two sectors react towards the formal and the informal banking sectors as lenders and as borrowers which ultimately affects the portfolio behavior of the two sectors and consequently allocative efficiency. In the previous chapters we have paid attention only to the consequences of changes in interest rates on deposits. Another important issue with respect to the effects of financial deregulation

5

INTRODUCTION

relates to the effects of changes in banking efficiency on private investment. It has been argued that a high spread between deposit and lending rates reflects high cost of financial intermediation and, therefore, lower banking efficiency. Although this issue has been raised in the literature, there is little formal analysis of it. In Chapter 6 we make an attempt to model the effects of improvement in banking efficiency on private investment. Again, this is done by using a variant of the model in Chapter 2. More specifically, we approach the concept of banking efficiency by distinguishing between effective and nominal rates of return on deposits and cost of loans. It is shown that a financial liberalization in the conventional way, i.e. an interest rate deregulation, leads to an increase in both the effective deposit and lending rates, whereas an improvement in banking efficiency leads to an increase in the effective deposit rate and a decrease in the effective lending rate. Further, it is shown that while the effects of an improvement in banking efficiency cannot be determined a priori, under several circumstances the possible negative effects of interest rate deregulation on private investment may be mitigated or even overcompensated by the positive effects of an improvement in banking efficiency. There are three major limitations of the analysis of Chapters 2–6 (particularly Chapters 2, 3 and 4). These are the partial nature of the model used. Partial in the sense that in each case we ignored some of the features. For example, in Chapter 2 we treated budget deficits as being exogenous and completely ignored informal credit markets and foreign aid. In Chapter 3, while we endogenized the deficit and incorporated foreign aid, we still excluded the informal credit markets. In Chapter 4, we rectified this shortcoming but only at the cost of the assumptions about the deficit and aid in Chapter 2. These respective simplifications were introduced so that we could derive some analytical results to highlight the significance of the attribute under consideration. But obviously a more appealing approach would be to take all of these factors into account simultaneously. The second shortcoming is the assumption about inflation. We have assumed that it was given. This is not an unusual assumption in demand-determined models. But still it is unsatisfactory. In Chapter 7 we formulate a simulation model which rectifies all of these shortcomings. But the basic structure of the model is derived from that used in Chapters 2, 3 and 4. Thus, this model is based on an integrated model of portfolio selection and the consumption—

6

INTRODUCTION

saving decision of the private sector with appropriate adding-up restrictions, with endogenous budget deficits, explicitly recognizing the role of foreign aid including the implications of the ‘fungibility’ of foreign aid as well as the role of informal credit markets without imposing any a priori restrictions on the degree of its intermediation capacity. Further, inflation is endogenized by explicitly treating the aggregate supply side. Finally, we explicitly introduce an external sector, albeit in a somewhat rudimentary form. This model is simulated to ask the same question: does interest rate deregulation affect private investment? In order to answer this question we can simulate the model in a variety of ways. But we believe that the most illuminating way for our purpose is to concentrate on one sector at a time and then do what amounts to a sensitivity analysis compared to a baseline simulation. While the possibilities are far too numerous to be outlined or examined, we concentrate on those which highlight a number of contentious issues in this area. In brief, we simulate the effects of interest rate deregulation under seven alternative assumptions about the model. These are: (1) no substitution between deposits and capital: (2) only investment or only consumption is credit constrained; (3) consumption and therefore saving is not affected by real interest rates—the standard assumption in much of the literature; (4) higher wealth effects on investment; (5) higher reserve requirements in the formal banking sector; (6) higher foreign aid; and (7) complementarity between government and private investment. As we shall see these simulations allow us to shed light on many issues. For example, we get some idea about the importance of liquidity constraint. Recently Jappelli and Pagano (1994) have shown that if financial liberalization can eliminate or relax liquidity constraints for the household, then it may lead to a reduction in savings and thus in growth. Similarly, the simulations have something to say about the sequencing of liberalization reforms, a topic that McKinnon (1991) has much to say about, namely, should budgetary reforms precede financial reforms? In Chapter 8 we add to a relatively new type of literature. So far we have concentrated on the effects of financial deregulation on the real economy. In this literature the focus is on public finance. It is beginning to be argued that financial repression can be, and is being, used by governments to extract more resources from the economy (see Sussman (1991) and Giovannini and De Melo (1993)). We deal with this issue by using the simulation model of the previous

7

INTRODUCTION

chapter. We assess the cost of financial repression in terms of its effects on inflation, private and public investment and the pattern of public consumption. The indicators of financial repression are those which are meant to raise additional revenues for the government. The measures of financial repression studied are: (1) the government levying a tax on interest income from government bonds held by the non-bank private sector; (2) the government borrowing from the banks at rates lower than those charged to the private sector; and (3) government borrowing from the banking sector by increased reserve requirements of the formal banking sector. While this approach does not provide a true cost-benefit analysis of the government’s attempts to raise revenues through financial repression, nevertheless we believe that it sheds significant light on the issues involved. Chapter 9 sums up the main findings and limitations. APPENDIX 1 There is by now a sizable literature on the optimizing models in this area. For example: Bencivenga and Smith (1991, 1992, 1993), Berthelemy and Varoudakis (1994), Bernanke and Gertler (1989, 1990), De Gregorio (1992, 1993, 1994), De la Fuente and Marin (1993), Gertler and Rose (1994), Greenwald and Stiglitz (1989), Greenwood and Jovanovic (1990), Greenwood and Smith (1993), Gylfason (1993), Jappelli and Pagano (1994), King and Levine (1993a, 1993b, 1993c), Levine (1991, 1992), Roubini and SalaiMartin (1991, 1992a, 1992b), Saint-Paul (1992a, 1992b), Sussman (1991, 1993), Sussman and Zeira (1993), Varoudakis (1992), among others. Not all of these papers use the endogenous growth models as their starting point nor do they all suggest the same mechanisms by which financial growth affects real growth, but nevertheless we can get a feel for what they do by considering the framework used in Pagano’s (1993) useful survey of this area. Using the ‘AK’ model, he shows that

where g is the real growth rate, A the social marginal productivity of capital, φ the proportion of savings not lost in the process of financial

8

INTRODUCTION

intermediation, s the private rate of saving and δ the depreciation rate. Assuming that δ is constant, financial intermediation or financial factors can affect real growth by affecting any of the other three parameters. Many of the papers cited above try to show which one of the three parameters and how it can be influenced by financial intermediation. For details the reader is asked to refer to the other survey papers or the original articles. We can only give a flavour here by referring to some of the recent works which are also used in our work above. First note that anything that can affect banking efficiency, as discussed in our Chapter 6, can affect φ. Some discussion of what those factors might be can be found in Sussman (1993). The role of financial intermediation in affecting A essentially relates to the allocational efficiency issue as discussed in our Chapter 5. In this literature, this issue has been discussed by Bencivenga and Smith (1991), Greenwood and Jovanovic (1990), Levine (1991) and Saint-Paul (1992a and 1992b), among others. There is much literature on how financial factors may affect s. But here we mention two contributions which have a bearing on our model too as we point out. These are the contributions by De Gregorio (1994) and Jappelli and Pagano (1994). Both papers use the OLG model. Jappelli and Pagano show that financial liberalization, by relaxing or eliminating liquidity constraints from the household, may depress saving, thus affecting growth unfavourably. De Gregorio, however, shows that if the borrowings by the household are also for investment in human capital, then not relaxing the liquidity constraint can harm growth. In other words, once we consider both effects, the outcome is ambiguous. Some of the papers also address the opposite question, namely, what causes financial growth. Here an interesting contribution is by Sussman (1993). Finally, some of the papers also present models in which financial and real growth take place simultaneously. Here three interesting contributions are: De la Fuente and Marin (1993), Greenwood and Jovanovic (1990) and Saint-Paul (1992a and 1992b).

9

2 THE BASE MODEL In this chapter, as pointed out in Chapter 1, we develop the base model which serves as the main framework for the subsequent chapters. The distinctive feature of the model developed here is that, unlike the rest of the works in this area, it treats the consumption— saving and portfolio allocation decisions as being jointly determined. Other authors determine these decisions as either being sequential (see, for example, Bourguignon et al., 1992) or assume that savings are exogenously determined, being independent of the rate of interest (see for example, Morisset, 1993). It is by now widely agreed upon that while the separation of the two decisions may be empirically convenient, it is not conceptually defensible (see for example, Pissarides (1978), Buiter (1980)). Pissarides, for example, has argued that the presence of transaction costs in some asset markets implies the interdependence of consumption and asset choices: If individuals are aware of these costs, they will also be aware of the importance of their portfolio, since it will, in general, be cheaper to finance consumption by running down liquid assets than by selling long-term assets before maturity. (Pissarides, 1978, p. 281) Similarly, the assumption about the exogeneity of savings or its insensitivity to changes in interest rates is grounded on appeals to empirical findings, but the evidence on this issue is far too uncertain to warrant such an extreme assumption (see for example, Gupta, 1987). Thus, a preferred alternative is to follow the route adopted by studies which treat the two decisions as being integrated. Apart from this, the model also explicitly allows for the role of liquidity constraints as faced by households and firms. Such constraints, as we know by now, may arise because of financial market imperfections. These imperfections in their turn may be caused either by government regulations of, say interest rates—a common phenomenon in developing countries—or because of asymmetric information in liberalized markets which can lead to equilibrium credit rationing (Stiglitz and Weiss, 1981).

10

THE BASE MODEL

To the extent that liquidity constraints are pervasive in developing countries, their explicit treatment in the model, as will be shown, sheds important light on the role of financial liberalization on investment. The model is in the spirit of the recent work by Morisset (1993). However, he treats savings as being an exogenous variable, the point which differs from our model. But quite apart from this and other differences, as Appendix 2 to this chapter shows, his model is overidentified, because it includes not one but two investment functions which makes it virtually impossible to draw any conclusions from his comparative static exercises and his empirical results. This chapter is organized as follows. Section 2.1 presents the model. Section 2.2 looks at the effects of an increase in the deposit rate—our measure for financial liberalization in this chapter—on the supply of credit to the private sector under different assumptions. Section 2.3 examines the comparative static effects of financial liberalization on private investment. Finally, Section 2.4 summarizes the chapter. 2.1 THE MODEL The model distinguishes a private sector (PS), a banking sector (CB: the central bank; PB: private banks), a government sector (GS) and an external sector (ES). There is no explicit treatment of the external sector (ES) and the supply side is completely ignored. We abstract from these latter factors in order to highlight the implications of the central feature of the model, which is the integrated nature of the consumption—saving and the portfolio allocation decisions. In later chapters, we allow for the external sector and the supply-side effects. Table 2.1 gives the accounting relationships of the model.

Table 2.1 The accounting framework of the model

Note: * NE=net exports.

11

THE BASE MODEL

Non-bank private sector We start the presentation of the model by considering the nonbank private sector. It is assumed to be a consolidated sector consisting of households and firms. The budget constraint of this consolidated sector is given by column 1 of Table 2.1:

The variables represent the following: four assets, namely, real domestic money (bank deposits: m), real government bonds (b), real physical capital (k) and an inflation hedge (foreign assets, represented by/and denominated in domestic currency). Cp represents real private consumption, Lp stands for real private credit, y for real non-interest income (or real Gross Domestic Product), T for taxes and y d for real disposable income, which is assumed to be exogenous.1 The consolidated budget constraint warrants some discussion. The private sector here consists of households and firms. Following Barro (1984) we can assume that investment takes place in this sector and thus justifies the budget constraint. However, the issue of consolidation is more important than that. Depending on the purpose of the exercise, one may argue that the disaggregation of the consolidated sector into its components would be more desirable as, for example, is done by Bourguignon et al. (1992) in their study of the effects of structural adjustment programs on income distribution. But they accomplish this task by imposing restrictions which would be unacceptable for our purpose. For example, they assume that households are not liquidity constrained and that not only is the consumption—saving decision independent of the portfolio selection decision, but that the latter is also sequential in terms of the liquidity of the assets. It is possible that our consolidation approach has certain shortcomings, even for our purpose. For example, it may be argued that the effects of the crowding out of the private sector credit by the government sector— an important point of the exercise here—could shed greater light on the outcome if we were able to identify whether the effect of such crowding out is confined to households or to firms. This is because the implications of the two are or, at least, can be different. The model in the simulation chapter shows that if crowding out effects are confined to firms they affect investment not only from

12

THE BASE MODEL

the demand side, but also from the supply side. Of course, one may argue that liquidity constraints may also affect the supply side from the household side by affecting the labor-leisure choice. The point is that it would be preferable to disaggregate the private sector rather than adopt the approach that we have. The main reason we haven’t done this is that one of the major aims of the study is to show the effects of government borrowing from the banking sector and its crowding out effects. If we were to disaggregate the private sector, we would have to spell out a mechanism to distribute this effect on the two components— namely, the households and the firms. This extension would make the derivation of any analytical results virtually impossible. Hence our approach. We now turn to the specification of the behavioral equations for the private sector.

im, ik, ib, and if are the exogenous nominal rates of return on deposits, physical capital, government bonds and foreign assets, respectively. Sp stands for real private savings, W for real private wealth. Finally, πe represents the exogenous expected rate of inflation. Using the taxonomy introduced by Brillembourg (1978), there are three possible reactions to portfolio disequilibrium, which, in the case under consideration, would be caused by the liberalization of interest rates leading to excess demand for bank deposits. These reactions are:

13

THE BASE MODEL

(a) a reallocation of the existing portfolio; (b) a reallocation of a given aggregate of savings by changing the menu of assets; and (c) a change in the aggregate flow of savings, which, assuming that bank deposits are a normal good, will increase their demand. In our model we incorporate reactions (a) and (c), though not (b). For this purpose, we use the integrated model of portfolio selection and consumption—saving decision proposed by Owen (1981), which itself is based on the works of Brainard and Tobin (1968), Purvis (1978), Smith (1978), Pissarides (1978), among others. A special implication of this model is that it not only allows for the ‘direct’ effects of changes in the deposit rates on the demand for money and other assets, but also for the ‘indirect’ effects which operate via wealth effects. These ‘indirect’ effects are ignored in the literature on the issue of this book, but it will be shown that once we allow for these ‘indirect’ effects, the conditions under which the ‘complementarity’ hypothesis operates turn out to be far more restrictive than is recognized in the literature so far. Equations 2, 3, 4 and 5 present the asset demand equations.2 These have been derived by using the multivariate adjustment function proposed by Brainard and Tobin (1968) in which changes in wealth (W) enter as a separate explanatory variable (see Appendix 3). This allows us to incorporate effects (a) and (c) identified above. However, it should be noted that the above equations do not include the lagged values of the various assets as specified in the BrainardTobin framework. This is because the comparative static exercises carried out in this chapter do not depend on their inclusion. Therefore, they have been excluded for convenience. However, they are included in the chapters on simulation, because the timepaths of the endogenous variables clearly depend upon their presence. Following the usual practice of this literature, it is assumed that the coefficients of disposable income and wealth are positive in each case, implying that all assets are normal goods; the coefficients of ∆Lp are also positive. The asset demands are assumed to be positively affected by the own rates of return and negatively by the alternative ones, implying that the assets are gross substitutes. Equation (6) presents the consumption function. It should be noted that this equation does not include wealth or the lagged values of the various assets. The exclusion of wealth follows from the main explicit assumption of the Owen model (1981)—namely, that the ‘end of

14

THE BASE MODEL

period wealth’ is a consequence of the consumption—saving decision and not a determinant of it. The exclusion of the lagged asset terms, although present in the Owen model, is justified for the same reasons as in the asset equations. In terms of the signs of the various coefficients in equation (6), it is assumed that 00. With respect to the interest rates it is assumed that the negative substitution effect exceeds the positive income effect. However, in the calculations below, we will also consider the opposite case. The inclusion of private credit in the asset and the consumption equations also warrants some justification. This term is meant to represent liquidity constraints for firms as well as for households. There is considerable evidence that households face such constraints in developing countries caused by the presence of incomplete credit markets (see, for example, Rosenzweig and Wolpin, 1993). The presence of the credit variable in the consumption equation is meant to capture the role of such market imperfections.3 A somewhat analogous argument may be advanced for the asset equations. But, given the fact that the major concern of this study is private investment, it may be worth noting that there is by now a good deal of justification in the literature on the inclusion of such variables. For example, Fazzari et al. state that: the supply of investment finance is not perfectly elastic for firms that face asymmetric information in capital markets. This result is independent of how one models the demand side of the investment decision…. Regardless of the true economic process at the foundation of investment demand, the supply of low cost finance, and therefore the level of internal cash flow, enters the reduced-form investment equations of firms for which internal and external finances are not perfect substitutes. (Fazzari et al. 1988, p. 163) Equation (7) defines savings, assuming that yd is exogenously given (this assumption is relaxed in the chapters on simulation where the supply side is explicitly considered). Equation (8) is the definition of private wealth. It should be noted that ∆Lp is treated as being exogenous to the private sector. The rationale for this will become clear later on in the discussion. We can now proceed to an examination of the significance of the above model for our purpose. We start by considering a simple

15

THE BASE MODEL

example. Suppose there is an increase in im with πe constant. Then from equation (2), this will lead to an increase in the demand for m via the portfolio reallocation effect (reaction (a) above). But the same increase in im will also lead to an ‘indirect’ effect through a reallocation of a given level of income between consumption and saving (from equation (6)), the change in wealth being defined by equation (8) (reaction (c) above). This last increase will lead to a further change in the demand for m in equation (2), given that a2≠0. The next step is to derive the adding-up restrictions of the above sub-model. It can be shown that (1) is satisfied if and only if the following holds:

It should be noted that in (9a) to (9g), there is no adding-up restriction which consists of the coefficients of the wealth variable only. As pointed out by Owen (1981), in the integrated model, wealth can change only if one or more of the variables affecting the consumption—saving decision changes and wealth, of course, is not one of those variables. These adding-up restrictions are used later on in the analysis of the model. The symmetry restrictions for this model require that

16

THE BASE MODEL

Banking sector The sub-model above, while allowing for the direct and the indirect effects of variables like yd and im on the portfolio allocation decision, does not take into account the credit effects highlighted by McKinnon (1973) and Shaw (1973) and which lie behind the ‘complementarity’ hypothesis. This effect can be incorporated, following Morisset (1993), by considering the balance sheet of the banking sector and the supply of credit to the private and the government sectors. Here the central bank and the commercial banks have been consolidated into a single sector. The budget constraint of this consolidated sector, which can be derived from consolidating column 2 and column 3 in Table 2.1, is specified as

where, in addition to the variables already defined, ∆Lg denotes bank credit to the government sector.4 The budget constraint of the consolidated banking sector warrants some discussion. Assets of the private bank consist of credit to the private sector and required reserves held at the central bank. Deposits (money) of the private sector are the liabilities of the private banks. The central bank extends credit to the government (∆Lg) and holds reserves of the private banks (R). It can be seen that the consolidation of the central bank and the commercial bank implies that bank reserves, ∆R, cancel out. Equation (10) states that, given ∆Lg and ∆m, the supply of credit to the private sector is residually determined. There is no equation for the demand for loans from the private sector since it is assumed that this sector is credit constrained. This is why it is treated as being exogenous in the private sector’s budget constraint. From (10), we can see how the McKinnon-Shaw mechanism would work. Assume that ∆Lg remains constant, but that the demand for deposits (m) goes up in response to liberalization of interest rate on deposits. This would mean an increase in total bank credit, including an increase in credit to the private sector. Since, in equation (3), a13>0, this would mean an increase in private investment. In other words, a given increase in im would lead to an increase in the demand for m as well as k, thus confirming the ‘complementarity’ hypothesis.

17

THE BASE MODEL

Government sector The above argument assumes that L remains constant. But there is g sufficient evidence to suggest that governments in developing countries often use bank credits to finance their budget deficits (Gupta, 1992). Assuming this to be the case, the possibility of crowding out of the credit for the private sector by government’s demand for credit from the banking sector immediately arises. In other words, even if a portfolio reallocation takes place in favor of m, both via the ‘direct’ and the ‘indirect’ effects discussed above (due to the deregulation of interest rates on deposits, leading to an increase in total supply of bank credit) there is no guarantee that a complete, or even a greater than complete, crowding out may not take place. This possibility can be incorporated into the model via the government’s budget constraint, which is given in column 4 of Table 2.1, as follows:

where Cg stands for government consumption, Ig for government investment, DEF for government deficit5 and A for foreign aid. In this chapter it is assumed that a change in the deposit rate does not affect government deficit, so that we consider government expenditures and taxes to be exogenous. Moreover, it is assumed that foreign aid is exogenous. These assumptions will be relaxed in Chapter 3. Equation (11) says that a given budget deficit is financed by borrowing from the banking sector and/or by selling bonds to the non-bank private sector and/or by foreign aid. It can be easily seen that a one dollar reduction in the demand for government bonds, given A, must mean a one dollar increase in government borrowing from the banking sector. The increase in government borrowing from the banking sector is determined by the budget constraint of this sector. This explains how a crowding out of private sector credit may occur if the government has to borrow from the banking sector. It is assumed here that the government fixes the interest rate on its bonds and the quantity of the bonds sold is then entirely determined by the nonbank private sector’s portfolio selection behavior. External sector As mentioned previously, in this chapter, there is no explicit treatment of the external sector. The current account position (net

18

THE BASE MODEL

exports: NE), is implicitly determined by the equilibrium condition on the balance of payments, or in other words the budget constraint of the foreign sector (column 5 in Table 2.1). The change in foreign assets (∆f) is determined by portfolio behavior of the non-bank private sector. As said before, foreign aid is assumed to be exogenous. By considering the budget constraints of the different sectors (equations 1, 10 and 11 and column 5 in Table 2.1) it can be shown that the goods market is automatically in equilibrium. This completes the model. The answer to the question: do changes in real interest rates affect private investment?, proceeds in two steps: first, we examine the effect of change in the real interest rate on deposits on the supply of credit to the private sector; and second, we use the results of the first step to derive the effects on private investment. 2.2 FINANCIAL LIBERALIZATION AND THE SUPPLY OF CREDIT TO THE PRIVATE SECTOR The complete model is solved to derive the following result:

It is assumed throughout that πe remains constant, so that a change in im also reflects an equal change in the expected real rate on deposits. It is easy to verify that the multiplier effect in (12) cannot be signed. However, we can get some insight into what is going on if we consider some special cases. We start by considering the case when the government does not borrow from the banking system. This case is equivalent to assuming that the demand for government bonds remains constant, implying that α21=—=α28=0. With these restrictions, equation (12) is reduced to

In terms of the signs of the coefficients in (13) and the adding-up restrictions, it can be easily verified that the denominator of (13) is positive.6 As for the numerator, a2 and a4 are positive, but in fact the sign of a44 is indeterminate, depending as it does on combinations of a negative substitution effect and a positive income effect.

19

THE BASE MODEL

In the model we have made the conventional assumption that the negative substitution effect exceeds the positive income effect, implying that ∂C/∂im<0 or that ∂S/∂im>0. In this case, ∂∆Lp/∂im>0, suggesting that in the absence of government borrowing from the banking sector, financial liberalization, as defined here, leads to an increase in the supply of bank credit to the private sector. On the other hand, if the positive income effect exceeds the negative substitution effect, the sign of ∂∆Lp/∂im is indeterminate. These two outcomes highlight the significance of using the integrated approach to the portfolio-allocation decision and consumption— saving decision used here. The above-mentioned point can be brought out more sharply by assuming that consumption is exogenous—that is, that the consumption—saving decision is irrelevant to the portfolio-allocation decision. In terms of the model this implies that α41=—=α48=0. With these parameter restrictions, equation (13) is reduced to

which is unambiguously positive, assuming that α3<1. Before we draw general conclusions from the above discussion, it is interesting to consider two weaker versions of equation (13). Instead of assuming that savings are exogenously determined, let us just assume, first, that consumption is not liquidity constrained, implying that α43=0. In this case, equation (13) becomes

Assuming that the numerator in (13) and (15) is positive as discussed above, it is clear that ∂∆Lp/∂im in (15)> ∂∆Lp/∂im in (13). Alternatively, let us assume that consumption—saving is not interest-rate sensitive, implying that α44=α45=α46=α47=0. In this case, equation (13) is reduced to

A comparison of (13) and (16) shows that ∂∆Lp/∂im in (13) >∂∆Lp/∂im in (16).

20

THE BASE MODEL

We can draw a number of conclusions from the above results regarding the effects of financial liberalization on the supply of bank credit to the private sector. To the extent that an increase in the supply of credit is the channel which determines whether physical capital and money are complements, our results can shed some interesting light. First, if the government finances its budget deficits by borrowing from the banking sector, it is a priori not possible to predict the effect of financial liberalization on the supply of credit to the private sector. Second, in the absence of government borrowing from the banking sector, the effect can be unambiguously determined, provided that consumption—saving is interest-rate sensitive in the conventional sense—namely that ?C/?i <0 or if consumption—saving m decision is exogenous and has no bearing on the portfolio selection. The effect in both cases will be positive. Third, the multiplier effect of financial liberalization on ?L is greater when consumption is not p liquidity-constrained or when savings are interest-sensitive. Of course, the multiplier effect is even stronger when both factors operate. In short, the above discussion demonstrates the importance of the integrated model of portfolio decision-making and the consumption—saving decision being used here and shows that both ‘direct’ and ‘indirect’ effects are important in analyzing the importance of financial liberalization on the supply of bank credit to the private sector and for examining the conditions under which the ‘complementarity hypothesis’ may hold. 2.3 FINANCIAL LIBERALIZATION AND PRIVATE INVESTMENT In order to examine the effects of financial liberalization, that is: a change in im, on private investment, we solve the entire model and use the results of the previous section where it was shown how changes in im affect ∆Lp. It can also be shown that

In equation (17) and in the subsequent equations, a14 may be replaced by a5 as in view of the symmetry conditions specified in 21

THE BASE MODEL

(9h). It is interesting to examine the four terms on the right-hand side of (17). The first term represents the ‘direct’ effect due to portfolio reallocation. This term is unambiguously negative. The second term (α12α44) represents the ‘indirect’ effect via the wealth effect on ∆k caused by a change in im on C. Under the usual assumption with respect to α44, this term is positive. The third term (α13-α12α43) represents the net credit effect per unit, while the last term in curly brackets is the same as the right-hand side of equation (12), which shows the total effect of changes in im on ∆Lp. The product of the last two terms shows the total effect of changes in credit supply to the private sector induced by changes in im. It is clear that the righthand side cannot be unambiguously signed in its general form. Therefore, to get some insight into the issue, we proceed as in the previous section and consider a number of special cases. Once again, we start with the case where the government does not finance its budget deficit by borrowing from the banking sector. In this case, equation (17) is reduced to

In equation (18), the first two terms on the right-hand side are the same as in equation (17), but the term in curly brackets now is identical to equation (13). Under the assumption that an increase in the deposit rate has a negative effect on consumption, ∂∆Lp/∂im >0 in equation (13). However, in spite of this, it is still the case that the effect of financial liberalization on private investment remains indeterminate. We next consider the implications of the simultaneity of the portfolio-allocation decision and the consumption—saving decision, by exploiting the various restrictions which can be imposed in equation (6). Suppose that the consumption—saving decision is exogenous, meaning that wealth remains constant. This, as before, implies that α41=—-α48=0. In this case, equation (18) is reduced to

In this equation, α4/(1-α3) is the same as equation (14) which is positive since α13>0, α4α13/(1-α3)>0. In equation (19), there are two 22

THE BASE MODEL

clear effects: the ‘direct’ negative substitution effect and the total credit effect, which is positive. The net outcome will depend on the relative strength of the two. In the spirit of Section 2, we again consider two weaker versions of equation (18). Instead of assuming that consumption—saving is exogenous, we first assume that it is not liquidity constrained, so that α43=0. In this case (18) becomes

The term in curly brackets is the same as equation (15) and therefore >0 i.e., ∂C/∂im<0. We have already discussed the other terms in equations (18). The other weaker case is when consumption—saving, though endogenously determined, is not interest-rate sensitive, i.e., α44=0. This is the case assumed by Morisset (1993), for example. With this assumption, equation (18) is reduced to

In equation (21), the term in curly brackets is the same as equation (16) and therefore can be assumed to be positive. The first term on the right-hand side is negative, while the second term is indeterminate in sign. The upshot of equations (19), (20) and (21) is that the outcome is quite sensitive to the assumptions about the endogeneity or the exogeneity of the consumption—saving decision. Moreover, if this is endogenous, it depends on the coefficient a12, which represents the wealth effect on ∆k. It should be noted that since the terms in the curly brackets in equations (17) to (21) represent equations (12) to (16) respectively, we can examine the credit effect on ∆k under the various assumptions discussed in Section 2. In all of the cases considered so far, we have not been able to sign ∂∆k/∂i m unambiguously and therefore validate the ‘complementarity’ hypothesis. We now consider whether some additional restrictions would yield that result. We consider the case where physical capital and deposits are poor substitutes in the private sector’s portfolio. Consider the extreme case of no substitutability

23

THE BASE MODEL

between the two and assume that α14=0. In this case, equations (19), (20) and (21) become (22), (23) and (24) respectively, as written below:

The signs on (22), (23) and (24) can be derived by considering the discussion of equations (19), (20) and (21). The results in equations (22) and (23) are interesting for they both confirm the prediction of the ‘complementarity’ hypothesis. From equations (22) and (23), we can conclude that the support for the ‘complementarity’ hypothesis depends on the following assumptions: (a) that the government does not use bank credit for financing budget deficits; (b) that money and physical capital are poor substitutes in the private sector’s portfolio; (c) that the consumption—saving decision is exogenously determined, implying that wealth remains constant so that there are no wealth effects; or (d) that if the consumption—saving decision is endogenous, so that the wealth effects are present, consumption must not be liquidity constrained and ∂C/∂im<0 or ∂S/∂im>0. It may be interesting to note here that our equation (22) is the same as derived by Morisset (1993). However, his outcome is dependent on assumptions (a) and (b) only. But our conditions (c) and (d) clearly show that in the integrated model of portfolio selection and consumption—saving being used here, the support for the ‘complementarity’ hypothesis is based on far more restrictive assumptions. To the extent that the exogeneity of the consumption— saving decision is a highly dubious assumption, the importance of our conditions (c) and (d) can hardly be overemphasized. Leaving aside the question of the validity of the ‘complementarity’ hypothesis, it is clear from equation (17) that the eventual effect of

24

THE BASE MODEL

financial liberalization, as defined in this paper, is indeterminate on an a priori basis. Furthermore, the credit effect, emphasized by McKinnon and Shaw, is very sensitive to the assumptions one makes about whether the portfolio-allocation and the consumption—saving decisions are made jointly as assumed in our model or as sequentially, as assumed in the Brainard-Tobin model. It is obvious that not only the ‘direct’ effects but also the ‘indirect’ effects of changes in i on m portfolio allocation are important in determining the effect of financial liberalization on private investment. Finally, the crowding-out effect on the supply of private credit by governments borrowing for bank credit to finance budget deficit can also reduce the effectiveness of the credit effect and therefore of financial liberalization on private investment. But note, once again, that this crowding-out effect in our model will be different from models which only take into account the ‘direct’ effect of changes in i on the demand for government m bonds but not the ‘indirect’ effects. To some extent the ‘indirect’ effects may mitigate the pure substitution effect due to the ‘direct’ effect. 2.4 CONCLUDING REMARKS In this chapter we have presented a simple model to analyze the effects of interest rate liberalization on private investment. The model allows for the fact that the private sector jointly determines its consumption—saving and its portfolio-allocation behavior. The McKinnon-Shaw credit effects and the crowding-out effects of government borrowing from the banking sector are incorporated by extending the model to include the behavior of the banking sector and the government sector via their budget constraints. It is shown that the outcome of the models which treat savings as being exogenous and thus consider the portfolio-allocation decision as being independent of the consumption—saving decision, is a special case of our more general model. To the extent that the constancy of the savings rates, and therefore of wealth, is a highly dubious assumption, it is suggested that a better approach to examining the relationship between financial liberalization and investment is within the framework of the model proposed here. The model examined in this chapter is deliberately specific. Its aim is to highlight the significance of using the integrated model of consumption—saving and portfolio-allocation decisions by the private sector. It would be useful to examine the implications of

25

THE BASE MODEL

expanding the model to incorporate other aspects of the credit markets and of the public sector’s behavior in developing countries. The various extensions and applications of the above model, as outlined in the introduction, are the subject matter of the chapters that follow. APPENDIX 2 The aim of this Appendix is to show that Morisset’s (1993) model is overidentified and that therefore his comparative static results and his empirical results are of dubious value. The source of the problem lies in the fact that his model embodies two equations for private investment, which implies two equations for government bonds. The second of these equations treats physical assets and government bonds as being perfect substitutes in the private sector’s portfolio. This last point can be seen from his equations (2b) and (10). Using his (2b) and (10), we can write, say,

Clearly (2b’) implies a coefficient of unity on ∆b, which, of course, means that physical assets and government bonds are perfect substitutes. The above equation can just as well be written for ∆b with ip on the right hand side. The second equation for private investment is given by his equation (7) which is explicitly derived from an accelerator-type model. Now consider his equation (8) which shows the effect of r on i p in the absence of a government budget constraint. In order to derive his (8), we must proceed as follows: Rewrite his equation (1) as

26

THE BASE MODEL

but this is precisely his equation (8). However, this means that his budget constraint in equation (1) is irrelevant and the private sector holds not four but only two assets! Now suppose that we use his model consisting of equations (2) to (5) to derive dip/dr. Then we get

The question is: which is correct: (8) or (1?)? Alternatively, which is the relevant budget constraint: (1) or the implicit (1')? His equations (11), (12) and (13) are also problematic. Thus, using his definition (10), it is clear that the equation for Ah includes the effect of ∆Lp/P on both ∆b and ip. The result is that when he computes the effects of r on ∆Lp/P, ∆h and ip, he double counts the effects of ∆Lp/P on ip. The problem arises because in equation (1) he consolidates the firms and the households (his footnote 4), but then introduces firms as a separate sector to specify another investment function. This can be seen most clearly from his equation (1) which can be rewritten by substituting his equation (10) in (1). His main empirical results in Table 3 are problematic because of the difficulties pointed out above. Table 3 shows that d(∆b/dr) ≠ d(∆L /P/dr). But this cannot be correct. From his equation (9) it is g obvious that with DEF and ∆D /P being given, a decline in the g g demand for government bonds by, say, one dollar must be matched by a dollar increase in the demand for bank credit by the government. His reported anomalous result is, once again, the consequence of the two investment functions and therefore two functions for ?b. We can show this as follows. Recall his equation (10), namely,

27

THE BASE MODEL

Now we can substitute (10b) into his (9) to get

Thus (10b) and (10c) clearly show that d(∆Lg/P)/dr= -d(∆b)/dr. He does not get this result because his estimation of d(∆Lg/P)/dr is based on our (10c) which uses our (10b) for d(∆b)/dr. But it would seem that his reported estimate of d(∆b)/dr is based on the equation for ∆b derived from his equation for ∆h (2b). This means, using his (10),

It is immediately clear that (10b) and (10g) are not equal, which accounts for the anomaly in his Table 3. Finally, the two investment functions raise yet another problem. His equations (6) and (7) assume that the firms are liquidity constrained, with the cost of funds, as measured by, say, r, being of no relevance to the determination of ß since r is excluded from equation (6). But this assumption is incompatible with the one implied by the budget constraint given in equation (1). If this is the case, then his equation (6) should also include r among the determinants which would alter all his comparative static results as well as the empirical results. APPENDIX 3 The modeling of the n asset demand equations in our book is based on the work of Owen (1981) and Morisset (1993). Owen (1981)

28

THE BASE MODEL

assumes a stock-adjustment process so that the change in the different assets can be written as:

where an and an(-1) are the end- and beginning-of-period holdings of the rth asset (in our model: bank deposits (m); real government bonds (b), real physical capital (k) and foreign assets (f)). is the desired holding of the rth asset. Furthermore, following the work of Owen (1981) we assume that

where Xi is the vector of explanatory variables which are relevant in the asset demand equations (X0 is disposable income, y; Xi, for i=1,...m-2, are the real interest rates on the various assets; that is im, the nominal rate of return on government bonds, ib, the nominal rate of return on foreign assets, if, and the nominal rate of return on physical capital, ik, taking into account the expected rate of inflation, πe; Xm-1 is the availability of bank loans, ∆Lp, which is taken into account following Morisset (1993); Xm is end of period real wealth, W). If (2) is substituted into (1) it follows that

The asset demand equations used in this chapter are found in the case where the lagged values of the assets are eliminated. The consumption function is derived by assuming that

In this chapter the lagged assets for the consumption function are also eliminated.

29

3 ROLE OF FOREIGN AID AND THE GOVERNMENT In the previous chapter, it was assumed that the budget deficit was given and that foreign aid played no role in financing government budget deficits. In this chapter, unlike all other works in this area, budget deficits are endogenized. This is done by using an explicit optimizing model for a government’s fiscal behavior. This approach allows us to consider the implications of deregulation policies when the budget deficit is no longer fixed. Moreover, we introduce foreign aid into the government budget constraint. While there is voluminous literature on the relationship between aid, growth, savings and investment (see, for example, Gupta and Islam, 1983; Lensink, 1993a and 1993b; Mosley et al., 1987; Papanek, 1973; Riddell, 1987; and White, 1992a and 1992b, among others), there is virtually none about the role which aid might play in the success or failure of interest rate deregulation policies. This omission is rather strange given the fact that in the structural adjustment programs of the IMF/ World Bank the adoption of reforms of the financial sector including interest rate deregulation is a condition for the provision of concessional loans/aid. Using an extended version of the model in Chapter 2, we examine the implications of financial deregulation and foreign aid on investment. Section 3.1 deals in detail with the recent studies in the field on aid and government behavior relevant to this chapter. Next, Section 3.2 specifies the model, taking into account foreign aid as an additional source of funds for the government and allowing for the endogeneity of government expenditure and revenue. Section 3.3 assesses the impact of an interest rate deregulation on private and government investment when aid is exogenous, but government expenditures are endogenized. Section 3.4 investigates the impact of an increase in the deposit rate in the case where foreign aid is endogenized. Finally, Section 3.5 concludes this chapter.

30

ROLE OF FOREIGN AID AND THE GOVERNMENT

3.1 THE FISCAL RESPONSE TO FOREIGN AID In the literature on foreign aid and its economic impact, three major types of studies can be detected. These are: strictly macroeconomic studies which deal with the effect of aid on macroeconomic aggregates like saving rate, investment, growth rate and so on (for a survey, see White, 1992a, 1992b); the other relates to what might be called micro or project related studies (for an extensive survey see Cassen, 1986) and finally, there is the field which examines the impact of aid on a public authority’s fiscal behavior. It is this last part of the literature which is relevant to the subject matter of this chapter. The basic point for our purpose is that since foreign aid relaxes the budget constraint of the government as specified so far and further that aid may be ‘fungible’ in the sense that government may be able to use it for purposes other than it is intended, it may have implications for the effectiveness of financial deregulation as defined in our study. Therefore, in this section we briefly summarize this literature. The fiscal response literature of foreign aid started some time ago with a wellknown article by Heller (1975). He empirically assessed the fiscal response to an inflow of foreign aid for a group of African countries. In his theoretical model he specified a utility function for the government of the following form:

where ∆Lg is defined as before and Ig, Cg, T and A represent government investment, government consumption, tax revenues and foreign aid, respectively. The corresponding variables with the ‘asterisk’ represent target values.1 The main justification of this type of utility function is based on the idea that a positive and a negative deviation from the target values are undesirable. This utility function is minimized, subject to two budget constraints of the following form:

31

ROLE OF FOREIGN AID AND THE GOVERNMENT

where, in addition to the variables already defined, A represents foreign aid. Heller justifies the usage of two budget constraints by referring to empirical evidence in developing countries, which, in his view, shows that developing countries do not borrow for current expenditures and by referring to the aid-savings literature which shows that foreign aid is not only used for consumption. The two constraints allow us to examine whether foreign aid is being used to finance consumption expenditure. Thus, if ? =0, then foreign aid 2 is clearly not fungible. It is being used precisely for the purpose it is being provided for—namely, to finance investment. If, however, ? 2 is significantly greater than zero but less than unity, then partial fungibility is indicated. The closer the value of ? to unity, the greater 2 the degree of fungibility. Heller solves the optimization problem to obtain structural equations for government consumption, taxes and government investment. The obtained structural equations are then estimated. Khan and Hoshino (1992) follow Heller’s procedure by borrowing his theoretical model and then estimate the resulting structural equations for a group of Asian developing countries. Gang and Khan (1991) and Gupta (1993a) take a similar approach for India. Recently, Heller’s approach has been criticized along two lines. First, for example, Binh and McGillivray (1993) show that the utility function implies that maximum utility for the government is not achieved in the case where government consumption, government investment, taxes and borrowing are set at the target values, which was the basic justification for the utility function. They show that maximum government utility is reached in the case where government consumption and investment overshoots the target values for these variables and when taxes and government borrowing are lower than their target values. Clearly, this implies that Heller’s method leads to inconsistent results. As a solution to the above-mentioned problem, Binh and McGillivray (1993) propose to delete the additive terms in the public authorities utility function. This implies a utility function of the following form:

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ROLE OF FOREIGN AID AND THE GOVERNMENT

However, this type of utility function has the disadvantage that overshooting and undershooting of the target variables are equally weighted, which was not the case for Heller’s utility function (see Gang, 1993). Nevertheless, in our view the quadratic utility function is preferable since it ensures that government’s utility is maximized when all variables are at their target levels. The Binh and McGillivray type of utility function is used in studies of Mosley et al. (1987) and Mosley (1987). The Heller approach has also been criticized along a different channel. White (1994a, 1994b) states that the usual procedure to minimize government’s utility function subject to two budget constraints is overly restrictive. First, White (1994a) denies that governments in developing countries do not borrow for current expenditures, so that the rationale for the separate budget constraints does not hold. Moreover, and more importantly for the fungibility discussion, the separate budget constraints for government consumption and government investment imply that the allocation of taxes, government borrowing, and foreign aid is predetermined. White (1994a, p. 42) argues that ‘such an allocation should be the outcome of the utility maximization problem.’ White (1994b) shows that the separate budget constraints imply that the optimal solutions for the decision variables do not correspond to their target values. Clearly, the optimal solution -U=a , using the utility function above— 0 is only found when aid, taxes and government borrowing are optimally allocated. However, this is not the case since the distribution is determined in advance, and is not a result of the optimization process. Therefore, White (1994b) proposes to use a single budget constraint. It will be shown in the next section that, also with one budget constraint, ‘fungibility’ of aid can be assessed (see also White, 1993). Using one budget constraint, however, is not without costs: it precludes distinguishing between different types of aid. Before going to our model and explaining how we assess ‘fungibility’ of aid, we briefly discuss empirical evidence on ‘fungibility’ of aid. Heller’s (1975) results are given in Table 3.1. What can be concluded from these results? First, it appears that the coefficients depend strongly on the group of countries and the definition of aid (total or official) which are concerned. Second, if the differences in the absolute magnitude of the coefficients are taken for granted, the results clearly confirm the ‘fungibility’ hypothesis: aid leads to a decline in taxes and government borrowing and aid does not lead to an equiproportional increase in government investment.

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Table 3.1 Effects of aid on government expenditures and taxes

Source: Heller (1975, Table 4). Notes: ‘Pooled Sample’ refers to the whole sample of African countries. ‘Anglophone’ refers to the Anglophone countries in his data set. ‘Total’ refers to the estimates for total grants; ‘official’ refers to the estimates for official grants.

Most other studies in this field confirm the existence of fungibility. White (1992b) gives a survey of these studies. It appears that many studies find that almost 60 percent of aid was used for investment, the remaining 40 percent was mainly used to reduce taxes or to reduce domestic borrowing. However, there are considerable differences. Boone (1994) concludes that almost 75 percent of total aid goes to government consumption and 25 percent to private consumption. Government investment and government taxes are not affected. On the other hand, Gang and Kahn (1991) conclude that foreign aid grants and loans do not have a significant effect on government consumption. Khan and Hoshino (1992) conclude that not all aid is going to investment. However, their results differ considerably for loans and grants. With respect to loans 85 percent goes to investment, whereas for grants it is only 32 percent. Concerning taxes they conclude that an inflow of grants reduces the tax burden, whereas loans increase it. Pack and Pack (1993) conclude that foreign aid in the Dominican Republic has led to major shifts in government expenditures away from government investments, whereas Pack and Pack (1990) found no evidence for fungibility of aid in the case of Indonesia. But Gupta (1993a) reports evidence of fungibility of aid for India. 3.2 THE MODEL WHEN GOVERNMENT EXPENDITURES AND TAXES ARE ENDOGENIZED We proceed by presenting the model we use to assess the impact of an interest rate deregulation in the presence of aid. The basic model is the same as in Chapter 2, but it is now assumed that the government budget deficit is financed by issuing bonds, by taxes and by foreign aid, so that the government’s budget constraint may be written as

34

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where all variables are as defined before. Recall that the budget deficit in Chapter 2 was taken as given. Here we drop this assumption and endogenize it by specifying the functions for I , C , ∆L and T. In line with Chapter 2 we assume that g g g ∆b is demand-determined, and hence exogenous for the government. Moreover, it is assumed that A is exogenously given. Now the usual procedure for specifying functions for C , I , ∆L and T is to use g g g some ad hoc reasoning. However, we draw upon the literature, mentioned in the previous section, which deals with the ‘fungibility of foreign aid’ by analyzing the fiscal behavior of public authorities in an optimizing framework. The procedure starts with the specification of a loss function for the public authorities. For reasons explained above we choose the form proposed by Binh and McGillivray (1993), namely,

where the corresponding variables with the ‘asterisk’ represent target values. This loss function is minimized, subject to the budget constraint in (1). It is now easy to solve for C , I , ∆L and T as functions of ∆b, A g g g and the target values. Define the Lagrangian as:

Here λ is the Lagrange multiplier. The relevant first order conditions are given by:

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ROLE OF FOREIGN AID AND THE GOVERNMENT

Thus, we have five unknowns, Ig, Cg, T, ∆Lg and λ, in five equations (4) to (8). These can be solved by substitutions in the usual way. The solutions are as follows.

where

It can easily be seen that

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By substitution it can be seen that:

Equations (13a) and (13b) give the adding-up restrictions of the above sub-model for the government. When (13a) and (13b) hold, the budget constraint of the government is satisfied. This implies that the model becomes overdetermined in the case when we use equation (1) and equations (9) to (12) in the calculations. Therefore, we can only use three of the four equations, with the fourth variable being determined by the government budget constraint. In the case where all four government equations are taken into account, the budget constraint becomes redundant if (13a) and (13b) are taken into account. As can be seen by considering equations (9) to (12) foreign aid may be used to increase government investment or government consumption, or fund a decrease in taxes or government borrowing. Hence, fungibility of aid is possible even when only one budget constraint is taken into account. It is assumed for this chapter that the target variables and C*g’ ∆Lg* are T* given exogenously. However, we do take into account a relationship yielding the target variable for Ig*. This variable is modelled as follows:

Equation (14) determines a link between private and government investment. Since private and government investment may be complementary or substitutional, the sign of ?1 is left indeterminate. The following truncated versions of the government equations can now be derived:

Equations (9a), (10a), (11a) and (12a) can be used in the body of the chapter without any loss. However, we would use explicit determinants of the other targets and a more extended modeling of

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the target for government investment and their implications in the simulation in Chapters 8 and 9.2 Before presenting the multipliers, we make some simplifying assumptions. First, the consumption—saving decision is assumed to be exogenous so that wealth remains constant (a …a =0). Second, 41 48 we assume that physical capital and deposits are not substitutes in the private sector’s portfolio (a =0), and third we assume that with 14 respect to the private sector only investment is liquidity constrained, implying that a =1 and a , a , a , a =0. These assumptions do not 13 3 33 33 43 mean that we consider these effects unimportant. On the contrary, we underline the importance of them. However, the implications of these assumptions are extensively spelled out in Chapter 2 and will again be taken into account in the simulation chapters. We make these assumptions in this chapter in order to make the calculations somewhat more transparent and to clarify as much as possible the implications of endogenizing the government equations and the effects of foreign aid. Disposable income equals GDP plus net interest receipts minus taxes. In line with Chapter 2 it is assumed that GDP and net interest receipts are exogenous. However, taxes are endogenous now. The truncated version of the relevant behavioral equations for the private sector, and the budget constraint for the banking sector, in which all non-relevant exogenous variables are suppressed, now become:

The model for this chapter is now complete. It consists of the equations 9a to 12a, 13a, 13b, 15 to 18 and the adding-up restrictions for the private sector (see Chapter 2). 3.3 FINANCIAL LIBERALIZATION WHEN FOREIGN AID IS EXOGENOUS In this section we assess the impact of an increase in the deposit rate on private and government investment. Rewriting of the model gives:

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where

As can be seen, the signs of the multipliers are a priori indeterminate. However, one thing becomes clear immediately. In case the target value of government investment is not affected by changes in private investment, which implies that γ1=0, the effect on government investment is unambiguously negative under the assumption that ß2>0 and government bonds and bank deposits are substitutes (α24>0). This first assumption will always hold when government bonds (and foreign aid) are partly used to fund government investment. In order to get some further insights we assess the implications of different extreme assumptions with respect to government’s usage of government bonds (and aid). First, we assume that increases in government bonds do not affect government expenditures or government taxes directly. In this case bonds do only substitute with government borrowing from the banking sector. It implies ß2=ß4=ß6=0 and ß8=1, so that:

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In this case an interest rate liberalization positively affects private investment when the total increase in bank loans (given by a4) exceeds the increase in demand for loans by the government, due to a decline in demand for government bonds (a24). If this holds the effect of an interest rate liberalization on private investment is greater in the case where target government investment and private investment are substitutes (g1<0). It can be seen that although the decline in demand for government bonds does not have a direct negative effect on government investment it now has an indirect negative effect due to the change in the target value of government investment. Otherwise, if private investment and target government investment are complements (g1>0), the impact of an interest rate liberalization on private investment becomes smaller. But now, government investment is positively affected. If target government investment is not affected by private investments (g1=0) government investment is not affected by an interest rate liberalization. This last case corresponds to the analysis of Chapter 2, when the additional assumptions made in the former section are taken into account. Second, we assume that government bonds are only used to finance government investment. This implies that ß =ß = ß =0 and 4 6 8 ß =1, so that: 2

An interest rate liberalization now unambiguously affects private investment positively. However, there is a strong negative effect on government investment since the decline in demand for government bonds falls totally on government investment. Note that the sign of γ1 is irrelevant for the outcomes. This is partly the result of the fact that ß1=0 due to the adding-up restrictions. Third, we assume that government bonds are only used to finance government consumption. This implies that ß =ß = ß =0 and ß =1. 2 6 8 4 Hence:

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For this case the effects of interest rate liberalization on private investment are also unambiguously positive. In the case where γ1=0 an increase in the deposit rate does not affect government investment negatively either: the decline in demand for government bonds leads to a dollar-for-dollar decline in government consumption, which implies that dCg/dim=-a24. However, if target government investment and private investment are substitutes an interest rate deregulation still affects government investment negatively. The last case we consider is where government bonds only fund a decline in taxes. In this case the decline in funds available for the government is counteracted by a one-for-one increase in taxes. This implies that ß2=ß4=ß8=0 and ß6=1, so that:

Again, an interest rate liberalization ambiguously affects private investment. Now, private investment is not crowded out by an increase in government demand for loans from the banking sector but by an increase in taxes. In the case where γ1=0 the increase in taxes affects private investment negatively by a direct effect due to a decline in disposable income (represented by an) and by an indirect effect due to a decline in demand for deposits and hence total bank credit available (represented by α1). For this case an interest rate liberalization again has no effect on government investment. What are the main conclusions from the analysis so far? First, the analysis points to a dilemma—namely, private investment is unambiguously positively affected when government bonds are only used to fund government investment. However, this will only be possible at the expense of a decline in government investment. Otherwise, if one tries to avoid a decline in government investment, the decline in demand for government bonds will probably lead to an increase in taxes or an increase in government borrowing from the banking sector, both of which will have a negative effect

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on private investment. It is interesting to note here that most evaluations of the impact of structural adjustment programs point to a negative effect on government investment. Of course, the structural adjustment programs do not contain measures with respect to financial liberalization only, so that our results cannot fully explain the findings of the recent evaluations. However, our analysis certainly gives one possible reason for a decline in government investment. Only when the decline in demand for government bonds falls totally on government consumption do these negative effects on private investment not exist. But, in practice this is often not a politically viable solution. Moreover, even if this will be the case it is not yet sure how government investment is affected: the effect depends on the sign of γ1. Second, for almost all cases it appears that the effects of an interest rate deregulation on government investment depend crucially on the relationship between private and government investment. This implies that it is highly important to take feedback effects between both types of investment into account. 3.4 THE ROLE OF FOREIGN AID WHEN AID IS ENDOGENIZED In this section we allow aid to be endogenous unlike in Section 3.3 where it was exogenous. The essence of our argument is that the granting of foreign aid depends on the adoption of reforms in the financial sector by the recipient country. But it is not clear how we should model the dependence of foreign aid on financial liberalization policies. Consequently, we adopt an, admittedly ad hoc approach. We assume that the increase in aid depends on the willingness of the recipient country to implement policies aimed at financial liberalization. Thus, we can write where α50>0 and d is a constant. The effect of financial liberalization on the two types of investment for this case is given by:

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As in Section 3.3 we proceed by distinguishing different cases with respect to spending behavior of the government. If it is assumed that increases in aid and government bonds do not directly affect government expenditures or government taxes, the multipliers become:

A comparison of equation (26) with (37) shows that crowding out of private credit by government’s demand for credit declines since the decline in demand for government bonds is partly financed by an increase in development aid. Thus, the importance of foreign aid in combination with policies of financial liberalization becomes apparent. What about government investment? Clearly, if the increase in aid only has a direct effect on governments borrowing from the banking sector, the change in government investment depends totally on the relationship between private and government investment. If private and government investment are complements, an interest rate deregulation positively affects investments of the government, assuming that the effect on private investment is positive. However, then the positive impact on private investment becomes smaller. Otherwise, government investment is negatively affected when both types of investments are substitutes. Clearly, for this case the positive impact on private investment increases. The impact of an interest rate deregulation on private investment increases when investment of both sectors are substitutes, but then the impact on government investment becomes negative. If target government investment is not affected by private investment, an interest rate deregulation does not affect investment of the government. If it is assumed that aid and government bonds are only used to finance government investment the results are:

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The impact of an interest rate deregulation on private investment is equal to the case where foreign aid was assumed to be exogenous (equation 28). Again, an interest rate deregulation positively affects private investment and the change in private investment does not depend on the relationship between target government investment and private investment. However, now government investment may be positively affected by an interest rate deregulation as well. Government investment is negatively affected by the decline in government bonds, which may be counteracted by a positive effect stemming from the increase in foreign aid. If we compare (37) with (39) and assume that ?1=0, the impact of an interest rate deregulation on private investment, if aid and government bonds substitute only with government borrowing from the banking sector, exceeds the impact of an interest rate deregulation on private investment when aid and bonds are only used for government investment in the case where a24
44

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It can easily be seen that, if aid and government bonds are only used to finance government consumption, the impact of an interest rate deregulation on both types of investment does not depend on the endogeneity of foreign aid. The results are given by equations (30) and (31). Finally, if aid and government bonds only affect taxes, the multipliers become:

Comparing (32) with (41) shows that the effect of an interest rate deregulation on private investment increases when aid is endogenized and used as a substitute for taxes, since the increase in taxes due to a decline in demand for government bonds is now partly counteracted by an increase in aid which negatively affects taxes. The impact on government investments is not influenced by the endogeneity of aid when aid is only used to substitute for taxes. Finally, an interesting by-product of the model in this chapter is that it allows us to examine the effect of aid on macrovariables like private and government investment by allowing for additional channels which have not been taken into account before. The results are shown in the Appendix to this chapter. 3.5 CONCLUSIONS This chapter has made a first attempt at assessing the impact of an interest rate deregulation in the presence of foreign aid. The ‘fiscal response literature’ formed the background for the way we tried to link interest rate deregulation, aid and government expenditures. One very important difference between our approach and the traditional ‘fiscal response’ studies is that we explicitly took into account feedback effects between private and government investment. This chapter has shown that foreign aid could have an important role in mitigating the crowding out effects of an interest rate deregulation and at the same time assuring that government investment does not decline. However, it is not a guarantee for a halt in the decline in government investment. This depends, for

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example, on the pattern of usage of such aid; that is, on the ‘fungibility’ of aid. Even in the case where the financial institutions substantially increase their aid efforts, the impact of financial liberalization on government investments depends on the way in which aid is spent. If the increase in aid donations is used for investment purposes it might well be that government investment is not influenced by a financial liberalization. However, if aid is used for consumption purposes or used to decrease tax efforts, government investment may still decline as a result of financial liberalization. Clearly, the impact of financial liberalization, in combination with an increase in development aid on government and private investment, remains an empirical issue. It is clear that the result depends mainly on government behavior. The investigations on the relationship between government behavior and inflows of aid may give some information. Heller (1975), and others, has shown that a substantial part of aid is not used for government investment. White (1992b) gives a survey of these studies. It appears that many studies find that almost 60 percent of aid was used for investment, the remaining 40 percent mainly being used to reduce taxes or reduce domestic borrowing. Although the above-mentioned results are subject to all kinds of qualifications they certainly point to a possible problem. The increase in aid as financial support for the financial liberalization may for a substantial part be used for unproductive purposes. It may even be that the decline in government investment due to the decline in demand for government bonds, is not neutralized by more government investment as a result of the aid inflow: the additional aid inflows may primarily be used for government consumption or to fund a decline in taxes. Maybe even more important this chapter suggests that a proper analysis of the effects of an interest rate deregulation on private and government investment and a proper analysis of the so-called ‘fungibility’ problem require a careful modeling of the relations between government and private investment. We have shown that even in the case where aid is not directly used for government investment, aid might positively affect government investment via a positive link with private investment. This implies that feedback effects between both types of investment should be taken into account. Most ‘fiscal response studies’ have ignored these effects, which may imply that the conclusions of these studies are too pessimistic with respect to the impact of foreign aid on government investment. White (1994a) has shown that feedback effects of aid

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may also be the result of positive effects of aid on income so that, even when aid has a direct negative effect on taxes, the total effect on taxes may become positive. This effect cannot be shown by the model of this chapter since it is assumed that income is exogenous. However, in our simulation chapters we will come back to this by taking all kinds of other feedback effects into account as well. APPENDIX 4 Effects of an increase in aid donations The aim of this appendix is to show how aid might affect investment in our model. We start by giving the effects of aid when no additional assumptions are made. The multipliers then become:

This can be rewritten as:

It appears that the influence of an increase in aid donations on private and government investment is a priori indeterminate. As before, we proceed by assessing the implications of different assumptions with respect to government usage of foreign aid (and bonds). If foreign aid does not directly affect government expenditures or government taxes the multipliers become:

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Assuming that -1<γ1<1, an increase in aid has always a positive effect on private investment. In the case where private investment does not affect target government investment an increase in aid donations leads to a one-for-one increase in private investment, since then the decline in government’s borrowing from the banking sector equals the additional inflow of aid. These additional funds will be used by the private sector for investment purposes. The effect of an increase in aid on government investment depends on the sign of γ1. This implies that to properly assess the effects of aid on government investment it is highly important to take into account the feedback effects of private investment on government investment, which is ignored in almost all fiscal response literature mentioned in Section 3.1. When aid and government bonds are only used to finance government investment or government consumption the multipliers become, respectively:

The last assumption we make is again that government bonds and aid have only a direct effect on taxes. The multipliers now become:

It can be seen that when γ1=0, an increase in aid donations has a positive effect on private investment due to a decrease in taxes. Private investment is then crowded in by an increase in aid. In this

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case government investment is not affected. However, in the case where private investment and target government investment are complements, it appears that government investment increases even when aid is not directly used for government investment. One of the main conclusions which can be drawn from the calculations in this Appendix is that, even when the government does not use aid for the purposes it is meant for (that is, government investment), aid may have a positive effect on private investment. Moreover, even when aid is fully fungible, in the sense that it is in the first instance only used for a decrease in taxes and not for government investment, the total effect on government investment may be positive. This is the result of taking into account feedback effects between private and government investment, which are ignored by most other studies in this field. The analysis, for example, shows that to assess the effects of aid the relationship between private and government investment is crucial.

49

4 THE ROLE OF INFORMAL FINANCIAL MARKETS In the previous chapters it was assumed that informal finance played no role in financing private investment: loans consisted only of formal finance. However, the formal banking sector in some developing countries, especially in Sub-Saharan Africa, is relatively unimportant for the financing of investment projects. In many developing countries a flourishing informal financial sector exists which is sometimes much more important for financing needs. Although precise estimates of the size of the informal financial sector are rare, the share of informal finance in total finance seems to range from about one-third to about three-quarters (Montiel et al., 1993, p. 17). For instance, for Malawi the informal financial sector, measured by the amount of lending to the private sector, is estimated to be three times as large as the formal financial sector, and in Ghana more than 60 percent of all rural savings are in the informal sector (Aryeetey and Hyuha, 1991). Miracle et al. state that the great bulk of the African population makes little or no use of formal savings and lending institutions. There are few banks in most areas, and those that are found are either not available to, or if available not used by, the majority of the population for a variety of reasons. (Miracle et al. 1980, pp. 701–702) In rural areas especially, there is a lack of formal banks. This applies not only to the African countries. For instance, Nagarajan et al. (1992) state that rural credit in the Philippines mainly consists of informal finance; Sanderatne (1994) estimates that in Sri Lanka the share of informal finance in total rural credit amounted to 45 percent, and Onchan (1994) states that the share of informal finance in the total rural finance of Thailand is about 30 percent. Informal finance, however, is not only important in rural areas. Recent research in several Asian countries, such as Bangladesh, India and the

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Philippines, shows that informal finance is also very important in urban areas (Wai, 1994, p. 371). Because of the relative importance of informal finance, this chapter explicitly focuses on the impact of interest rate deregulation in the presence of an informal financial sector. The chapter starts by giving an overview of the different informal financial institutions that may exist in developing countries (Section 4.1). Next, Section 4.2 summarizes different theories on the working of the informal financial sector. Section 4.3 briefly surveys the existing studies on the effects of interest rate deregulation in the presence of curb markets. Our model, including the informal financial sector, is explained in Section 4.4. Section 4.5 assesses the impact of interest rate deregulation in the presence of an informal financial sector, under different assumptions with respect to the working of this sector. Section 4.6 summarizes this chapter. 4.1 DIFFERENT TYPES OF INFORMAL FINANCIAL INTERMEDIARIES This chapter considers informal finance as all financial activities that lie beyond the control of the official sector. Other terms used in the literature are: the ‘curb,’ ‘parallel,’ ‘underground,’ ‘black,’ ‘segmented,’ or ‘unorganized’ markets. We prefer the term ‘informal market’ since most informal markets are very well organized. The difference between formal and informal finance primarily relates to government regulation. However, there are also all kinds of intermediate forms in which links between the formal and the informal sector are established leading to a situation where the informal sector is partly regulated by the government. These intermediaries may be called semi-(in)formal financial institutions.1 The informal financial sector in developing countries is very heterogeneous. A classification of the different types of informal financial intermediaries can be made in several ways. Roe (1991), for instance, distinguishes non-commercial finance, commercial finance and group arrangements. Another classification is given by Montiel et al. (1993). They distinguish four types of informal financial institutions: occasional lending, regular money lending, tied credit and group lending. We use the latter classification in this section. Occasional lending consists of lending by individuals and institutions with a temporary surplus of funds. In most cases the lenders are friends, neighbors and/or close relatives to the borrower. Money is provided on a non-commercial basis with no interest

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charged or collateral required. Loans are provided on the basis of reciprocity: the current lender receives the possibility of borrowing in the future from the current borrower. According to Adams (1991) this type of informal finance is probably one of the most important. In some countries informal loans made by friends and relatives make up more than half of all informal loans. However, these loans are usually short-term and small. Especially in situations where it is very difficult to monitor the borrower and where enforcement mechanisms are weak, occasional lending is very important. The monitoring costs are low, since moral hazard is nearly absent as a result of the close relationship between the borrower and the lender. Sometimes occasional lending takes place on market terms, whereby firms with a temporary surplus of funds deposit these funds on the informal market from which other firms may borrow. Regular moneylending consists of moneylenders (in Sub-Saharan Africa they are called ‘katapila’), pawnbrokers and all kinds of sophisticated but unregulated institutions, such as mobile banking. In general, moneylenders use their own funds to extend credit to a relatively small group of borrowers. However, borrowing from the formal sector also exists. In most cases, collateral is not demanded, while the interest rates are relatively high. The moneylender usually lends to investors with whom he or she has personal connections. According to Christensen (1993, p. 725) professional moneylenders are more important in Asia than in Africa. Pawn-brokers are a special category of moneylenders. They only lend in exchange for valuables provided as collateral. Pawnbroking is not a strict credit transaction, since the item that is used as a collateral is sold to the pawnbroker and bought back afterwards. This implies that the need for information about the borrower is not as acute as for the moneylender and the formal institutions. A limitation of pawnbroking is that the amount of goods which can be ‘pawned’ is restricted to easily marketable goods. An example of pawnbroking contracts are the land pawning contracts. In such a contract the cultivation rights are temporarily exchanged for a loan. For the lender (the pawnee) the returns from the land represent implicit interest receipts from the borrower (the pawner). Nagarajan et al. (1992), in a study on land pawning contracts in the Philippines, argue that land pawning contracts are important in many Asian countries, like Bangladesh, India, Indonesia and Thailand. Land pawning contracts, where explicit interest charges are forbidden, are especially popular in Islamic countries. In addition to moneylenders and pawnbrokers,

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all kinds of unregulated institutions emerge which act like normal banks but are not regulated. An important example is the mobile banker, which in Africa is sometimes called the single-collector susu system. In this system a mobile banker regularly visits his clients, usually traders, and collects funds. After some time period the savings, less an agreed sum, are returned. Hence, instead of earning interest on deposits the saver pays a service. The advantage for the depositor is the access to credit for various purposes. The loans are characterized by their short-term nature. The mobile banker determines the creditworthiness of the client by the regularity of the deposits, for example. In Ghana informal saving and borrowing mobilization occurs especially by means of the single-collector susu system. The importance of this system can be gauged from the fact that nearly 75 percent of all savers in Ghana use it (Aryeetey and Hyuha, 1991). In the case of tied credit the main activity of the lender does not refer to credit activities. Credit is extended between individuals who have a continuing relationship in some other way. An important example of this form of credit relationship is the situation in which landlords provide credit to their tenants. The most important example of group lending is the ‘ROSCA.’ A ROSCA is a rotating savings and credit association consisting of a homogeneous group of members who share a basis of common trust. In most cases they are from one family or from one village. Each member of the group periodically deposits an amount of money in a common pool. On rotation, the members have the opportunity to borrow the total sum of money saved. Especially in African countries, where they are called ‘tontines,’ ROSCAs are important. In Africa ROSCAs and fixed-fund associations (see below) are found in nearly half of the existing countries (Miracle et al., 1980, p. 703). In addition to the ROSCAs, there also exist credit groups in which the periodically collected funds are not distributed on rotation between the members. These groups are called ‘savings groups’ or ‘fixed-fund associations.’ Members of fixed-fund associations also periodically give funds to a treasury. Sometimes the fixed-fund association has only a savings function. In most cases the organization lends the money saved to members and possibly to non-members. Since social ties are strong among the members of the ROSCAs and the fixed-fund association, and since a rejection from the association also implies a rejection from the community, the enforcement costs are low and adverse incentive

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and moral hazard problems are nearly absent. There are many studies on the working of ROSCAs (see, for example, Bouwman, 1977; Von Pischke, 1994). The studies point at extreme differences between the ROSCAs. Graham (1994), for instance, shows that in Niger the amount borrowed on rotation varies between 2 US dollars and 700 US dollars. The average for all assessed ROSCAs in Niger was 111 US dollars, which was higher than the amount normally borrowed from the formal financial institutions. Schrieder and Cuevas (1994) estimate that in Cameroon the average amount a group has lent to a member was about 490 US dollars, varying between 3 and 14,060 US dollars. In this country the lending groups represented more than a fourth of all credit to the private sector and more than half of total savings of the private sector. Also, the amount of members per group varies considerably. In Cameroon the smallest group consists of five members, whereas the largest group has 350 members (Schrieder and Cuevas, 1994). In Niger the amount of members varies between four and 40 (Graham, 1994). 4.2 THEORIES ON THE WORKING OF INFORMAL FINANCIAL MARKETS The previous section clearly showed that there is no standard informal financial market: the informal financial sector is extremely diverse. Therefore, it seems relevant that a study on the efficiency of informal financial intermediation distinguishes between different forms of informal financial intermediation. Christensen (1993), in a study on the limits of informal financial intermediation, distinguishes informal financial agents and informal financial institutions. However, mostly, theories with respect to the working of the informal financial sector refer to the informal financial sector in general. Some economists associate the informal lenders with monopolistic moneylenders who exploit the poor by charging usurious interest rates and are stereotyped as being exploitative. In this view informal financial intermediation is highly inefficient and costs are high so that a substantial part of total saving goes to informal banks as a reward for the services supplied. The formal and informal financial markets are assumed to function in isolation, links between borrowers and lenders are mainly based on personal knowledge, and borrowers in the informal financial market have

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no access to the formal financial market (see, for example, the references cited in Owen and Solis-Fallas, 1989, p. 347). In fact, the analysis of McKinnon (1973) and Shaw (1973) is based on this view with respect to the informal credit markets. The observed high interest rates in the informal credit markets are explained by the monopoly power of the informal lenders (for example, Chandavarkar, 1965). Some empirical evidence for monopoly power as an important determinant of the high interest rates is given by, for example, Saleem (1987) with respect to Sudan and by Fernando (1988) for Sri Lanka. Studies in this field, among others, argue that the monopolistic informal lender forces borrowers to back their loans with underpriced collateral (see, for example, Basu, 1984; Bhaduri, 1977, 1980; Rao, 1980; Ghose, 1980). Finally, informal financial loans are assumed to be of a short-term nature. Wai (1977), for instance, suggests that approximately one-third of the demand for informal credit is for ‘non-productive’ purposes. Based on the idea that the (rural) informal lenders are extremely exploitative, governments in many developing countries have often tried to drive the traditional moneylender out of the market by the creation of credit programs. These programs, consisting of institutional alternatives like co-operatives, government-owned agricultural banks and credit activities included in multipurpose development agencies (see, for example, Adams and Vogel, 1986), were to promote agricultural production and to provide cheap credit. However, it appeared that most of these programs were unsuccessful. Credit was in most cases only available for the wealthiest part of the rural sector so that loans were poorly distributed, savings were inadequate due to negative real interest rates and loan discipline was very low (see, for example, Adams and Graham, 1981). Moreover, despite increased competition the informal financial lenders did not disappear and the interest rates in the informal financial sector did not decline (Hoff and Stiglitz, 1990). Although the relative importance of the informal financial sector declined in many countries where the formal financial sector developed it appears that the absolute volume of the informal financial sector still increased. In some cases formal finance seems to be a substitute for informal finance, whereas in other cases it seems to be complementary (Wai, 1994, p. 372). The fact that the informal financial lenders were not driven out by the credit programs did not come as a surprise for a group of economists having a totally different view about the working of the informal financial

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market. This group disputes the claim that the informal financial market is exploitative (for example, the different articles in Von Pischke et al., 1983; Adams, 1991). According to these authors the observed high interest rates in the informal credit markets are not high due to monopoly profits. They are mainly explained in terms of a premium for informal lenders’ risk (for a formal explanation, see, for example Bottomley, 1975 and Stigler, 1967) and high opportunity costs. For instance, Singh (1968), in a study on cost components of interest rates for informal consumption loans in Indian villages, finds that monopoly profits accounted for only 6 percent of the interest charged. Harris (1983, p. 235), also in a study on the informal financial sector in India, concludes that the high interest rates are certainly not explained by monopoly costs since competition between lenders was high. Conclusions along similar lines are provided by Wilmington (1983) in a study on Sudan, Rahman (1992) for the informal financial sector in Bangladesh, and Ghatak (1975) and Iqbal (1988) for India. Adams states Because of the lack of barriers to entry, the large number of forms of finance, and the large number of people who are willing to enter markets where high rates of return are realized, it is difficult to see how informal lenders can regularly extract substantial monopoly profits. (Adams, 1991, p. 35) Hence, the informal financial market is seen as a highly efficient competitive market. It is also argued that highly developed linkages between the formal and the informal financial sector exist and that competition between both sectors takes place. Moreover, it is denied that informal credit is only used for unproductive expenditures, like consumption. The ‘new structuralists’ (for example, Taylor, 1983; Van Wijnbergen, 1982, 1983a, 1983b, 1985a) base their analysis of financial liberalization on this view with respect to the working of the informal financial market. Van Wijnbergen (1982, 1985a) also gives some empirical evidence for his view. His analysis shows that the substitutability between informal deposits and formal deposits in South Korea is higher than between formal deposits and unproductive assets (money in his model). This suggests the existence of developed linkages between both credit markets. How can the differences between the two views with respect to the working of the informal financial market be explained and which view is correct? The literature suggests that both explanations of the

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working of the informal credit market are partly correct. According to Owen and Solis-Fallas (1989) the disagreement mainly stems from the different informal markets the two groups of authors have in mind. The authors assuming that the informal credit market is a highly efficient market with developed links with the formal market clearly have in mind the more developed informal markets, whereas the authors emphasizing the fragmentary and noncompetitive character of the informal markets rely on the very traditional moneylenders. In fact, the informal credit market can be classified into two categories: the competitive informal market with close relationships with the formal sector, and the non-competitive informal market with no relations with the formal sector. Chang and Jung (1984) take these two categories of informal financial markets into account in their analysis of a financial liberalization in a developing country. Although both aforementioned theories can partly explain the working of the informal financial markets, both theories seem to be unsuitable for explaining several practical features of informal financial markets. A different theory on the working of informal financial markets which seems to be more promising in this respect is given by Hoff and Stiglitz (1990). Their theory is basically inspired by the well-known article of Stiglitz and Weiss (1981). Hoff and Stiglitz (1990) base their analysis on the existence of market imperfections due to imperfect information. In their view neither the ‘monopoly’ view nor the ‘competitive’ view can explain the practical features of informal financial markets. They argue that the imperfect information paradigm can better explain the common features of these markets. They point at, for example, the facts that informal and formal sectors coexist, despite the lower formal interest rates, the unavailability of credit in certain periods (credit rationing) and the segmentation of (informal) credit markets. Aleem (1990) gives evidence on the imperfect information view. He argues, in a study of the rural credit market in Pakistan, that the informal credit market can best be explained by a model of monopolistic competition. There is relatively free entry, but informational imperfections for the borrower as well as the lender lead to product differentiation. Also, Siamwalla et al. (1990), in a study of the Thai rural credit system, support the imperfect information paradigm. They argue that the informal sector is competitive and that the high interest rates stem from high information costs. In a way, Das-Gupta et al. (1989), in a study on urban informal credit markets in India, support the imperfect information view on the working of the

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informal credit markets. Some of their major conclusions are: (a) interest rates on informal deposits and informal loans in general exceed the formal sector rates; (b) informal credit is mainly used for productive activities; (c) the high informal lending rates cannot be explained by monopoly profits; (d) informal credit markets can better be explained by a competitive market type than by a situation of monopoly. Fragmentation is the result of informational problems, and (e) in some cases informal credit was allocated efficiently, in other cases not. 4.3 ROLE OF INTEREST RATE DEREGULATION IN THE PRESENCE OF CURB MARKETS: A BRIEF SURVEY Following the works of McKinnon (1973) and Shaw (1973), we can briefly distinguish four sets of studies which examine the role of interest rate deregulation in the presence of curb markets. These are the works by ‘neostructuralists’ like van Wijnbergen (1983a, 1983b, 1985a), Taylor (1983) and Buffie (1984), among others; and by Tsiang (1979); Liang (1988) and Bencivenga and Smith (1992). Since more will be said about the works of the ‘neostructuralists’ in the next section, here we only highlight their main point so as to bring into sharp focus the other works which have not received as much attention but which shed quite different light on the issues under consideration. The paper which brings out most clearly the implications of the neostructuralists’ critique of the McKinnon and Shaw type of financial liberalization policy is that by Bencivenga and Smith (1992). The neostructuralists maintain that if such liberalization only succeeds in drawing funds from the curb market, then the total supply of funds to firms will decline, thus nullifying the positive effects of financial liberalization. Bencivenga and Smith use a model which embodies the Diamond and Dybvig (1983) model of financial intermediation in an overlapping generations model. This model is then expanded to incorporate an active curb market. In this model they show that the neostructuralists’ results do emerge in that financial liberalization is not expansionary. But they then go on to demonstrate that financial liberalization is optimal even in such an environment. This is because risk is shared more efficiently in the organized financial sector, and because such liberalizations increase the inflation tax base.

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Thus not all the gains from organized intermediation take the form of increased output. (Bencivenga and Smith, 1992, p. 256) Tsiang (1979) and Liang (1988) take a somewhat different approach than Bencivenga and Smith, but they also suggest some positive real effects of financial liberalization in the presence of curb markets. There are certain similarities but also dissimilarities in the two approaches. In both papers, the way the banks ration credit plays a crucial role in the outcome. In fact, Liang defines efficient allocation of funds analogous to that used by Tsiang. Completely efficient allocation implies that banks allocate funds only for those projects whose rate of return equals or exceeds the rate prevailing in the curb market. The logic of this definition, according to Tsiang is that the potential marginal cost of funds to the entrepreneurs is the rate on the funds from the curb market. The way this coefficient of allocation (Liang’s terminology, 1988, p. 543) plays the role in the two models, however, differs and leads to quite different conclusions in some respects though not in others. Tsiang considers a simple loanable funds model consisting of the banking sector and the curb market. Then, by assuming that the banks do not allocate their funds perfectly efficiently (in the sense defined above), reaches the conclusion that an increase in the official deposit rate will lead to a decline in the curb market rate, thus reducing the gap between the two rates and increasing the efficiency of the allocation of banking funds. This will tend to reduce the size of the curb market. He asserts, though, that under plausible assumptions about the behavior of the supply and demand curves for funds, the total supply of loanable funds will increase, thereby leading to greater investment. This, in spite of less than perfect allocation by the banks. Unfortunately, Tsiang’s arguments are based on a diagram which merely asserts the relative shifts of the demand and supply curves of funds and are not derived from any underlying model. The difficulties of his model and its conclusions become apparent when we consider Liang’s work. If we confine ourselves to the same case as the one by Tsiang—namely, that the ‘coefficient of efficient allocation’ is positive but less than one—then his conclusions about the effects on the curb market rate are almost the opposite. He considers two versions of his model: the ‘classical’ case where the money wage is perfectly flexible and the Keynesian case where

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the money wage is rigid. He shows that in the former the curb rate will rise when the official deposit rate rises. But in the Keynesian case the effect is ambiguous. Only when the ‘coefficient of efficient allocation’ is unity is the effect negative. Thus Liang’s model does not predict a narrowing of the gap between the two rates, although it does predict a reduction in the scale of operations of the curb market. But in one important respect, Liang’s analysis supports Tsiang’s results. This has to do with the expansionary effects of an increase in the official deposit rate. True, this happens only in the case where the money wage is rigid. The mechanism leading to this result in the two models is, however, quite different. In Tsiang’s case the effect is via the increased ‘availability’ of non-inflationary finance which occurs in spite of the shrinkage of the curb market. In Liang the mechanism takes place rather differently. An increase in the official deposit rate leads to a reduction in the demand for money balances, which in its turn leads to an increase in the price level. With a fixed money wage, this is expansionary. Since Tsiang uses a partial equilibrium framework while Liang uses a general equilibrium model, it is difficult to say to what extent the differences in their results are caused by the differences in the level of generality of their models. But notwithstanding this conceptual difference, what is interesting about both these papers is that they explicitly point out circumstances in which a policy of interest rate deregulation, even in the presence of curb markets, can have expansionary effects. These results are obviously quite different from those of the neostructuralists. The upshot of this brief survey is that there is no consensus about the answer to the question: does the presence of curb markets improve the effectiveness of financial liberalization policies? We do not claim to give a definitive answer either. However, the next section points out some additional channels not recognized in the existing literature which may allow financial liberalization to play a more active role even in the presence of curb markets. 4.4 THE MODEL In this section our model is extended by incorporating an informal unorganized banking sector. The modeling of the informal financial sector is primarily based on the imperfect information paradigm, since in our view this approach can best explain the working of the informal financial market. This means, for example, that, in contrast

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to the ‘competitive’ and hence the ‘neostructuralists’ view, we explicitly take into account the existence of credit rationing by the informal financial intermediaries. This implies that in our model, in line with the structure of the base model, the informal deposit rate is exogenous, whereas in the ‘neostructuralists’ models the informal interest rate is a market clearing rate. On the other hand, in contrast to the ‘monopoly view,’ our model explicitly takes into account possible substitutabilities between formal and informal deposits. Within the basic framework of our model we try to be as general as possible and distinguish different extreme cases which are in line with the ‘monopoly’ and the ‘competitive’ view. To avoid complicating the analysis we have tried to keep the model as simple as possible. In contrast to, for instance, Chang and Jung (1984), we have not modeled different informal financial intermediaries. We model the informal financial market as one single sector. This implies that the introduction of the informal financial sector in our model enlarges the menu of assets of the non-bank private sector by only informal deposits. Moreover, the non-bank private sector may use credit from the informal financial sector to finance their investment or consumption expenditures. However, as said before, the modeling of this sector is extremely general so that by changing the parameters the different informal financial sectors may be approximated. In order to clarify the implications of the informal financial sector we make some simplifying assumptions. First, that the government does not borrow from the non-bank private sector by issuing bonds (i.e. the demand for government bonds cancels out). Second, that taxes and government investment are exogenous. This implies that disposable income in the asset demand equations in the model of this chapter, as in Chapter 2, is exogenous. Third, that only investment and consumption are liquidity constrained, so that formal and informal credit does not enter in the asset demand equations for foreign assets, formal and informal deposits. Fourth, that capital and formal demand deposits are not substitutes. Fifth, that there is no foreign aid. Sixth, as said before, that the informal deposit rate is exogenous, like all rates of return. Finally, that reserve requirements of the formal and informal banks are used for unproductive government expenditures, say government consumption.2 Table 4.1, in which the exogenous variables taxes and government investments are not included, gives the accounting framework.

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Table 4.1 The accounting framework of the model including informal financial markets

Notes: *NE=net exports.

In Table 4.1, UB is defined as the unorganized financial market and ∆Lu, ∆u and ∆Ru represent net domestic credit from the informal financial market, real demand deposits of the informal financial market and reserves of the informal financial sector, respectively. The other variables are as defined previously. The structure of the model is the same as in the previous two chapters. The full specification of the model for the non-bank private sector including the informal financial sector is given in the Appendix to this chapter. Here we only present a truncated version of the model for the non-bank private sector. In the equations all of the above-mentioned assumptions are taken into account and the irrelevant exogenous and lagged variables are excluded.

For this truncated model the adding-up restrictions are:

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The banking sector now consists of a formal private bank, a central bank and an informal private bank. The assets of the formal and informal private banks are in the form of reserves and credit extended to the private sector. Liabilities of the formal and the informal banking sector consist of formal and informal demand deposits of the nonbank private sector, respectively (see Table 4.1).3 Reserves of the formal and the informal banking sectors are assumed to be a fixed percentage of formal and informal bank deposits, respectively. The real budget constraints of the formal and the informal private banking sectors read as

where hf and hu are fixed percentages of formal and informal deposits, respectively, which are held as reserves. It is assumed that 0艋hf, hu艋1. 4.5 FINANCIAL LIBERALIZATION AND PRIVATE INVESTMENT By solving the entire model the following multipliers can be derived:

The effect of an interest rate deregulation on investment appears to be ambiguous. The supply of formal credit available for the non-

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bank private sector is positively affected if hf, hu⫽1. However, the impact of an interest rate deregulation on informal credit available for the private sector is ambiguous. We proceed by assessing the implications of the existence of an informal financial market on the effectiveness of financial liberalization by distinguishing two views with respect to the efficiency of the informal market. The informal financial market is an efficient market. As mentioned before, the ‘neostructuralists’ assume that the informal financial sector is an efficient market with 100 percent intermediation from lender to borrower (i.e. hu=0) and that informal and formal financial bank credits are only used for investment (i.e. a13=a20=1, which implies that a43=a50=0). Applying these assumptions to our model gives the following results:

where

Still, the effects of an interest rate deregulation are ambiguous. The neostructuralists’ case is found by additionally assuming that consumption—savings is not interest-rate sensitive, implying that a44=0. In combination with the assumption that all credit is used for investment this implies that consumption is exogenous, which implies that a43=a44=a50=0. The equations now become

where

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Equations (18), (19) and (20) show that the McKinnon-Shaw complementarity hypothesis only holds when the increase in the deposit rate does not induce an outflow of resources from the informal sector which is larger than the inflow of resources in the formal financial sector. Since the formal banking sector provides imperfect intermediation, due to reserve requirements, and the informal financial sector provides perfect intermediation, an increase in the bank deposit rate likely leads to a decline in funds available for the private sector. This is the basic critique of the neostructuralists. By using the adding-up restriction (which under the assumptions made above are a 4-a34-a54=0) it appears that increases in interest rates on bank deposits only positively affect investment in the case where bank deposits are closer substitutes for the inflation hedge (the ‘unproductive asset’) than for informal sector loans, which is exactly the outcome of Van Wijnbergen’s model. The neostructuralists’ case appears to be a special case of our model. However, a comparison of equations (18), (19) and (20) with (15), (16) and (17) clearly shows their conclusions are based on more restrictive assumptions. The neostructuralists’ conclusions are only found when in addition to their assumption that the informal credit market is efficient it is also assumed that consumption—saving is not interest-rate sensitive. Equations (15), (16) and (17) show that the neostructuralists’ critique does not hold when positive wealth effects stemming from the decrease in consumption are substantial (this is also emphasized by Buffie, 1984). If the negative substitution effect exceeds the positive income effect, which is assumed here, an interest rate deregulation leads to an increase in wealth which may have a direct positive effect on investment (a12a44). The increase in wealth has an additional indirect positive effect via the supply of formal credit (a2a44). The increase in wealth may even result in an increase in the supply of informal credit (a52a44), despite the portfolio shift in favor of formal deposits. This again shows the importance of using a model which jointly determines the consumption—saving and the portfolio allocation decision in order to assess the effects of an interest rate deregulation.

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The informal financial market is an inefficient market. As we have mentioned in the previous sections some authors, however, argue that informal financial intermediation differs substantially vis-à-vis financial intermediation of the formal banking sector. The informal financial sector is seen as extremely inefficient. For instance, it is a priori not clear why informal financial institutions do not hold reserves (Montiel et al., (1993, p. 60), if informal financial intermediation is highly inefficient so that a substantial part of total saving goes to informal banks as a reward for the services supplied, or more in general that informal banks also hold reserves, hu⫽0. If we still assume that informal and formal credit is used for investment, and that the consumption—saving decision is irrelevant, the multiplier for private investment becomes

Hence, only in the case where the amount of reserves held by the formal banks exceeds the loss of savings in the intermediation process of the informal banking sector is the neostructuralists’ critique justified. The authors who agree with the view that informal financial markets are inefficient mostly also state that links between the informal financial market and the official markets are weak and that links between borrowers and lenders are mainly based on personal knowledge. In our model this view can be represented by assuming that the substitutability between bank deposits and informal deposits is very low, a54=0. Still assuming the irrelevance of the consumption— saving decision and that consumption is not liquidity constrained, this implies that

The usual McKinnon-Shaw complementarity hypothesis now results if reserve requirements of the formal banking sector are 0艋hf<1. Finally, authors who support the view that the informal financial markets are inefficient also emphasize that informal financial loans are of a short-term nature. In our model the short-term unproductive

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nature of informal intermediation can be introduced by assuming that all informal loans are used for consumption, whereas formal loans are used for investment (a =0 and a =1). If the consumption— 20 13 saving decision is irrelevant for the portfolio allocation decision the multiplier then becomes,

Again, when 0=h f<1, the McKinnon-Shaw complementarity hypothesis results. 4.6 CONCLUSIONS This chapter has shown that the impact of financial liberalization on private investment, taking into account the informal financial sector, is a priori indeterminate. If it is ignored that the consumption—saving and portfolio decisions are made simultaneously, which is the case in nearly all studies, the neostructuralists are right if the informal financial institutions channel saving to informal loans as efficiently as the formal banking sector channel savings to formal loans and if informal loans are used as productively as the formal bank loans. However, if savings are endogenized and hence the simultaneous portfolio allocation and consumption—saving decision is taken into account, it appears that, even in the case where the assumptions of the neostructuralists hold, a rise in the deposit interest rate may stimulate investment by means of a positive wealth effect. APPENDIX 5 The full model for the non-bank private sector including the informal financial sector reads.

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where in addition to the variables already defined iu is the exogenous informal deposit rate. Note that the lagged variables are eliminated in the asset demand equations.

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5 ALLOCATIVE EFFICIENCY AND FINANCIAL DEREGULATION So far we have been examining the scale effects of financial deregulation, namely, the effects on the quantity of investment. However, the literature also emphasizes another channel through which such deregulation may enhance growth. This has to do with the allocative efficiency effect. The idea is that higher interest rates, by inducing the selection of projects with higher rates of return, will raise the average productivity of investment (and hence growth) even if the effect on savings and thus total investment was negligible. While there are those who question the validity of this effect on analytical grounds (see Cho, 1986, 1988; Stiglitz, 1991; references cited therein), nevertheless, this effect continues to be emphasized in the literature (Park, 1993). The major difficulty in dealing with this issue is how to measure improvements in allocative efficiency which are induced by financial deregulation. To our knowledge the only attempt so far is by Galbis (1977). Using a two-sector model, he claims that deregulation of interest rates, by transferring capital from the less productive to the more productive sectors, will raise average productivity and hence growth. Unfortunately, as we will see in the next section, his model cannot be solved to answer this question. Instead, he uses a diagrammatic device essentially to assert the proposition. For example, he does not specify the conditions under which such an outcome would occur, in terms of, say, restrictions on the behavior of the economic agents involved. Furthermore, although he includes a backward sector, he does not explicitly consider the role of informal credit markets, which evidently is an important element in this debate. The aim of this chapter is to show, using a two-sector version of the model analyzed in Chapter 4, the conditions under which

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allocative efficiency might improve, following the deregulation of interest rates. The scheme of this chapter is as follows. Section 5.1 briefly explains the Galbis model. In section 5.2 we summarize some of the empirical findings on this subject. Section 5.3 presents our model. Section 5.4 introduces the measure we use for ascertaining the effect on allocative efficiency. In Section 5.5 we analyze various cases. The final section concludes with a brief summary. 5.1 THE GALBIS MODEL Galbis’s (1977) model consists of two sectors, a backward and an advanced, both producing the same good and sold at an identical price. Since the technologies used are different, the rates of return to capital are different with the advanced sector leading the way. He assumes standard neoclassical production functions for both sectors with the marginal productivity conditions holding in both sectors. Consumption and therefore savings in each sector are defined as a constant proportion of income. Investment is defined as a function of the own rate of return and the return on the alternative asset. In the backward sector this alternative asset is the bank deposit and in the advanced sector it is the cost of bank loans. It is assumed that in the backward sector investment opportunities are inadequate so that investment falls short of internal savings of this sector. This means that for this sector a part of the savings is devoted to the accumulation of financial assets, which means bank deposits. On the other hand, there are plentiful investment opportunities in the advanced sector so that intended investment exceeds what can be financed by the savings of this sector. However, this sector, unlike the backward sector, can borrow from the banks, the borrowings being dependent on the accumulation of the deposits by the backward sector. The role of financial intermediation and interest rate deregulation is intuitively obvious. Ceteris paribus, an increase in real rates on deposits will increase the amount of financial assets accumulated by the backward sector. Since investment in the advanced sector is constrained by the availability of investment funds, this means that investment in this sector will immediately go up. Assuming that total investment between the two sectors remains constant, but since the productivity is higher in the advanced sector, this reallocation of funds does mean an increase in average productivity and therefore growth.

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The problem with the model is that in the way it is specified it cannot be used to show the comparative static effects of an increase in the interest rates on the reallocation of investment as against the effect on total investment. So we do not really know under what conditions such an effect would materialize. 5.2 SOME EMPIRICAL EVIDENCE Before proceeding to our model, we briefly summarize some of the evidence on this issue. Simply put, the criterion used is the usual one in microeconomics—namely, that, if after the reforms, the marginal rate of return on credit invested in various sectors becomes more equal than before the reforms, then, ceteris paribus, we can conclude that financial deregulation has resulted in a better allocation of credit. While theoretically the approach seems to be quite simple, its implementation in practice is difficult, both because of data limitations and measurement problems. This is amply recognized in the few studies which are available on this topic. Empirical evidence on this issue is available for Ecuador, Indonesia, South Korea and Turkey. The studies on South Korea and Turkey on the one hand and on Ecuador and Indonesia on the other use different approaches. In essence, however, they both use the opposite sides of the same approach. The basic idea is that profit-maximizing firms try to equate the marginal cost of funds to their marginal rate of return. Consequently, we could either look at the marginal rate of return or the marginal cost across firms/industries/ sectors, before and after financial deregulation and then use some index to compare the two. The studies on South Korea by Cho (1988) and Turkey by Capoglu (n.d.) use the marginal cost of the optimizing condition claiming that the data required to estimate the marginal rates of return are simply not available. Further, they approximate the marginal cost with the average cost because of the data limitations. As an index of comparison, they use the variance of borrowing costs stating that a reduction in the variance of average cost across the sectors signifies an improvement in the efficiency of credit allocation. This inference has been criticized by Schiantarelli et al. (1994a) on the grounds that a reduction in the variance does not necessarily indicate improved efficiency of allocation because such a reduction can be easily induced by state intervention, requiring lending institutions to allocate credit to favoured sectors at uniform rates. But leaving aside these and other possible criticisms, it is

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interesting to note that using the same approach the results for the two countries turned out to be opposite. For South Korea, Cho (1988) reported the results given here in Table 5.1. Cho tested the variance of the borrowing costs for the 68 manufacturing industries. It can be seen from this table that the variance was significantly reduced since 1981 compared to the 1970s. The variance was 5.91 in 1984 compared to 21.44 in 1979, a significant reduction indicating a significant improvement in the efficiency of credit allocation due to financial reforms. Table 5.1 Costs of borrowing of 68 manufacturing industries

Source: Cho (1988.), Table 4.

The results for Turkey from Capoglu (n.d.) are provided in Table 5.2. Capoglu also tested the variance of the borrowing costs. But he concluded that the variance was lower in 1982 than in 1987, thus suggesting that financial liberalization did not result in increased efficiency of credit allocation. If anything the situation seemed to have worsened. The results for Indonesia and Ecuador have been reported by Schiantarelli et al. (1994a). They use the marginal rate of return side of the optimizing condition discussed above. Two alternative measures are used: the rate of profit per unit of capital as a measure of the marginal rate of return (marginal product of capital) and the value added per unit of capital. Using these two measures, they derive two indices of the efficiency of credit allocation. These indices are estimated for the pre- and post-liberalization periods and the two compared. As an example of their calculations, the preliberalization index of the efficiency of credit allocation using the rate of profit as a measure of the marginal rate of return is given by

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Table 5.2 Costs of borrowing for 28 industries in Turkey

Source: Capoglu (n.d.), Table 4.

where the notations are: T0 indicates the beginning year, T1 the terminal year of the pre-liberalization period and Nt is the number of firms in year t. Ilt, Kit and πit stand for real investment, capital stock and operating profits of firm i in year t. Further, I0t and K0t indicate total investment and capital stock in year t for all firms. The measure of efficiency measures the total return on investment divided by the total return the same measure would have yielded if investment funds had been allocated to firms in proportion to their share of capital in the economy. The alternative measure, called B, can be derived by using the value added measure of the marginal return. The estimates of A and B for the post-liberalization period can be derived in the same way. It should be pointed out that they freely admit the various shortcomings of their measures. The results for Indonesia are given in Table 5.3. This table reports the values of the two indices for the aggregate of all firms as well as their sub-aggregates distinguished by various characteristics. Comparing the results for the aggregate sector, both indices suggest an improvement in the allocation of credit. The results for the subaggregates are less clear cut. For example, the two indices give conflicting results when we consider disaggregation by size. The results for Ecuador are given in Table 5.4. The results for the period 1984 to 1985 pertain to the pre-liberalization period and those of the period after that to the post-liberalization period. These results are not as clear cut as the ones for Indonesia for the

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Table 5.3 Measures of efficiency of the allocation of investment in Indonesia

Source: Schiantarelli et al. (1994a), Table 1. Notes: *Total number of firms: 2,970; total number of observations 9,303. † Pre=1981–84; Post=1985–88.

Table 5.4 Measures of efficiency of the allocation of investment in Ecuador

Source: Schiantarelli et al. (1994a), Table 2. Note: *Number of firms 853. Number of observations 3,252.

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aggregate sector. For example, index B gives more favorable results than index A. But, on the whole, we can say that there is no unambiguous evidence of an improvement in the efficiency of credit allocation for Ecuador. It is then clear that the existing empirical studies do not provide any clear answer as to the allocative efficiency effects of interest rates and other financial deregulation measures. These studies further highlight the need to analytically identify the conditions and circumstances under which specific forms of financial reforms may lead to an improvement in allocative efficiency. The next section tries to do precisely that. 5.3 THE MODEL The model deals with a fragmented developing economy in which a backward sector and an advanced sector as well as a formal banking sector and an informal banking sector are distinguished. The budget constraints of the different sectors We start the presentation of the model by considering the budget constraints of the different sectors. The backward sector is considered to be characterized by small backward firms which do not have access to the formal banking sector and produce goods in less efficient ways than the advanced sector. The backward sector borrows only from the informal financial market since, for example, they do not have enough collateral to borrow from the formal banking sector. Formal banks consider lending to the backward sector as being extremely risky and simply decide to give the backward sector no access to formal funds. The informal banks, however, do not ration the backward sector since these lenders have personal connections with the backward sector and can obtain information on the creditworthiness of the backward sector very easily as they often live and work in the same village so that default risk can be minimized. The backward sector holds assets in the form of demand deposits of the informal banking sector (u), demand deposits of the formal banking sector (m) and capital (k). Therefore, the real budget constraint of the backward sector reads

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where yd is real disposable income, Lu is net domestic credit from the curb market, Cp is real private consumption, ∆ denotes a change in a variable. The subscript 1 refers to the backward sector. The advanced sector is a modern sector, with a higher rate of return on capital than the backward sector. The advanced sector has access to formal bank credit as well as informal bank credit. However, since the loan rates of the formal banking sector are assumed to be lower than the loan rates of the informal financial market (e.g. due to financial repression) the advanced sector first tries to fulfil its credit needs by borrowing from the formal banking sector. The amount of formal credit available falls short of the demand for formal credit of the advanced sector so that credit from the formal banking sector is rationed and the advanced sector has to move to the informal banking sector for the rest of the needed funds. The assets of the advanced sector consist of demand deposits of the formal and informal banking sector, as well as capital so that the real budget constraint of the advanced sector can be written as

where Lp is net domestic credit from the formal banking sector and subscript 2 refers to the advanced sector. The formal banking sector is regulated by the government, which sets the deposit rate and the lending rate. The liabilities of the formal banks are the demand deposits held by the advanced and the backward sectors. The assets are in the form of credit extended to the advanced sector.1 It is assumed that the demand for formal credit exceeds the supply of formal credit so that the actual amount of formal credit available is determined by the banks’ supply. The budget constraint2 is

The informal banking sector provides credit to the advanced and backward sector. The liabilities are again the demand deposits of both sectors. In contrast to the previous chapters it is assumed that the market for informal credit is cleared by adjustments in the lending rate so that total demand for and supply of informal credit are equal.3 This implies that

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It is assumed that the actual level of demand deposits of both banking sectors is determined by demand of the advanced and backward sector. The behavioral equations The next step is to present the behavioral equations. The specification of the asset demand equations for the backward private sector is given by the following equations:

The specification of the asset demand equations for the advanced sector are as follows:

where im is the real formal deposit rate, iu is the real informal deposit rate, ik is the real return on capital, r is the real lending rate on informal credit and W is real wealth. All coefficients in the asset demand equations are positive; id, ik and yd are treated as being exogenous. In contrast to the analysis in Chapter 2 we assume that W is given. In Chapter 2 we assess the implications of the endogeneity of wealth. Hence, in that chapter scale effects are taken into account. In this chapter we assess only the impact of an increase in the formal deposit rate on the allocation of capital, so that wealth is constant. Real disposable income in the advanced and backward sector, which in fact consists of GDP and interest

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payments and receipts, is also assumed to be given and not affected by changes in the deposit rate since during the process of financial liberalization the deposit rate on formal deposits and the lending rate on formal credit are both increased and the lending and deposit rates in the informal banking sector are linked so that the impact of a financial deregulation on interest income is minor. The above assumptions imply that private consumption is constant too. In line with the previous chapters the equations above are derived from a standard portfolio stock-adjustment model. It is assumed that the assets are gross substitutes—so that each interest rate positively influences the demand for the asset to which it is associated and negatively influences the demand for other assets—and are normal goods, so that, as wealth increases, the demand for each asset increases. Note that since the advanced sector is constrained in its demand for formal credit the available amount of formal bank loans affects the portfolio decisions of this sector, whereas the cost of formal credit is not an argument in the portfolio equations (see Morisset, 1993). Otherwise, since the market for informal loans clears, the amount of informal loans is not an argument in the asset demand equations, unlike the cost of informal credit. The assumption that the informal market clears implies that equations for the demand for informal credit are also specified. For reasons of convenience, we assume that the demand for formal and informal deposits is not credit-constrained and that the informal and formal deposits are not substitutes with informal and formal credit, so that ß27=ß37=ß41=ß42=ß24=ß34= α41=α42=α24=α34=0. In that case the adding-up restrictions of the above sub-models for the backward and advanced sectors are:

The lending rate on informal credit (r) is endogenous and determined by supply and demand for informal credit (equation 3); iu is 78

ALLOCATIVE EFFICIENCY AND FINANCIAL DEREGULATION

determined by the zero profit condition for the banking system, that is,

5.4 HOW TO MEASURE THE IMPROVEMENT OF THE ALLOCATIVE EFFICIENCY We proceed by explaining how we measure the change in the allocative efficiency of capital. As pointed out before, in line with Galbis (1977), we assume that the advanced sector embodies a technology with a higher constant rate of return to capital than that of the backward sector. This implies that a rise in investments in the advanced sector vis-à-vis investments in the backward sector improves the average productivity of investments. This implies that the allocative efficiency (AF) improves if

However, by adding the budget constraints of the advanced and the backward sector and taking into account the budget constraints of the formal and informal banks we know that total investment stays constant.4 Hence, ∆k1+∆k2 is constant, so that d∆k2/(dim)= d∆k1/(dim). Thus, a sufficient condition for the above condition to hold is:

5.5 THE IMPACT OF DEREGULATION OF THE FORMAL DEPOSIT RATE ON THE ALLOCATIVE EFFICIENCY We now assess the impact of financial liberalization on allocative efficiency. The multiplier defining the impact of a change in the

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interest rate paid on demand deposits, which is our measure of financial liberalization, reads

Note that the denominator of dr/dim is positive since ß47艋1 and ß22=ß32=ß12 and a22=a32=a12. If we use the relevant adding-up restrictions equation 9 can be rewritten as:

which equals d∆k1/dim. Equation (9a) shows that the effect on allocative efficiency is, a priori, indeterminate. But the allocational efficiency unambiguously improves as a result of financial deregulation if dr/dim >0, or if the cost of capital is irrelevant for investment in the backward sector (a14=0) and the informal banks do not change the deposit rate following a change in the lending rate (iu is constant, so that a12 disappears from the multiplier). In order to get a better insight into the conditions under which interest rate liberalization positively affects the allocative efficiency we distinguish different cases. No informal credit market We start the analysis by ignoring the informal financial market. In this case investment of the advanced sector is partly financed by own funds and partly by borrowing from the formal banking sector, whereas investment in the backward sector is entirely self-financed. This case corresponds to that of Galbis (1977). The absence of an informal credit market implies that α12= α 14= α 21= … = α 26= α 32= α 34= α 41= … α 46= ß 12= ß 14= 80

ALLOCATIVE EFFICIENCY AND FINANCIAL DEREGULATION

ß21=…ß27=ß32=ß34=ß41=…ß47=0. The impact of financial liberalization now becomes

An increase in the formal deposit rate has a negative effect on private investment of the advanced sector due to a negative substitution effect between formal demand deposits and capital (ß11). Private investment of the advanced sector increases by the additional amount of formal credit available (ß17[a31+ß31]). However, by considering the adding-up restrictions we can unambiguously sign the effect. Since, in the case where the informal financial market does not exist, ß17=1, ß31=ß11 and a31=a11, the above expression can be rewritten as

Hence, financial liberalization unambiguously improves the allocative efficiency if there is not an informal financial market. The extent by which the allocational efficiency improves is determined by the negative substitution effect of capital in the backward sector with respect to formal demand deposits. This substitution determines the amount of funds which are allocated from the backward sector to the advanced sector. The advanced (backward) sector does not hold informal (formal) deposits Next, we introduce the informal banks. We start by considering the change in the allocational efficiency due to financial deregulation if the advanced and the backward sector do borrow from informal banks, whereas the advanced (backward) sector does not hold informal (formal) deposits. This situation may occur in case the advanced and backward sector are plagued by imperfect information with respect to the informal and formal banking sector, respectively. The advanced sector does not hold deposits at informal banks since it considers the informal banks untrustworthy, so that placing funds at informal bank accounts is very risky. On the other hand, the backward sector does not hold formal deposits, for

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example due to superior information on each other, so that a significant portfolio shift from informal deposits into formal deposits will not occur (see Teranishi, 1994). The case we consider implies in our model that α31=…α36= α11=α21=ß12=ß21=…ß26=ß32=0, so that the multiplier becomes:

The expression seems ambiguous in sign. Investment in the advanced sector is negatively affected by the substitution effect with respect to demand deposits, whereas it is positively affected by an increase in formal credit available (ß17ß31) and a decline in the loan rate of informal credit (ß14ß47ß31/a22+a44+ß44). However, by using the relevant adding-up restrictions it can be shown that the impact becomes unambiguously negative:

The economic mechanism behind this result is as follows. The increase in formal credit available for the advanced sector leads to a decline in demand for informal loans so that the loan rate declines which stimulates investment in the backward sector. Since total investment stays constant this can only occur at the expense of investment in the advanced sector. The advanced sector does not borrow from or lend to informal banks In this case we consider the situation in which the backward sector holds formal deposits but the advanced sector does not borrow from the informal banks and does not hold informal deposits. The reason that the advanced sector does not borrow from the informal lenders for investment purposes can be explained by assuming that the informal loans are of a short-term nature and are mainly used for ‘non-productive’ purposes, which according to Wai (1977), is the case in many developing countries. In our model this implies that ß =ß =ß =ß =…ß = 12 12 14 21 26 ß =ß =…ß =0. The impact of a deregulation on the allocational 32 41 47 efficiency is now given by:

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Since, for this case, ß17=1 and ß11=ß31, the above expression can be rewritten as:

Hence, the allocational efficiency improves unambiguously in a twosector world where the advanced sector does not have any credit relations with the informal market, whereas the backward sector does hold formal deposits. Note that the outcome seems to be equivalent to the case in which informal banks do not exist. The impact of a financial deregulation on allocational efficiency may, however, differ between these two cases since the adding-up restrictions of the backward sector differ. If there are no informal banks a31=a11, whereas now a31=a11+a21. Hence, the portfolio shift into formal deposits originates not only from a decline in demand for investment but also from a decline in demand for informal deposits. The advanced sector does not hold informal deposits Next, we only assume that the advanced sector does not hold demand deposits of the informal banks, whereas the backward sector may hold deposits of the formal banks. This implies that ß =ß =…ß =ß =0. The multiplier now becomes 12

21

26

32

By using the relevant adding-up restrictions or by considering that d∆k2/(dim)=-dk1/(dim) equation (13) can be rewritten as:

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Now, the impact of a deregulation on allocational efficiency is ambiguous. The allocational efficiency improves by the negative substitution effect between formal demand deposits and capital in the backward sector. The efficiency, however, may decrease due to a decline in the lending rate on informal credit. If the lending rate decreases, investment in the backward sector will go up since the cost of lending falls. Moreover, since a decrease in the lending rate leads to a decrease in the deposit rate, investment in the backward sector also increases due to the substitution effect between backward capital and informal demand deposits. Both effects are negative for the allocational efficiency. Since ß47<1, α22-α32=α12 and α21-α31=α11 the impact of a deregulation on the lending rate, and hence the allocational efficiency, is unambiguously positive in the case where the negative substitution effect between formal demand deposits and advanced sector capital (ß11, which equals ß31 if the advanced sector does not hold informal deposits) is low. If the cost of capital is irrelevant for investment in the backward sector (α14=0) and the informal banks do not change the deposit rate following a change in the lending rate, a deregulation of the formal deposit rate will also unambiguously improve allocative efficiency. The backward sector does not hold formal deposits Finally, we consider the case where the backward sector does not hold formal deposits whereas the advanced sector does hold informal deposits and borrows from the informal financial market. This implies that α11=α21=α31=…α36=0. The multiplier now becomes

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The impact of a deregulation on the allocational efficiency is again ambiguous. The allocational efficiency again improves unambiguously if the substitution effect between formal demand deposits and capital of the advanced sector is low (ß11=0). If ß11=0, ß21=ß31, and since ß47<1, ß21-ß47ß31>0. Hence, dr/dim is positive. 5.6 CONCLUSIONS This chapter has examined the effects of financial liberalization, as proxied by interest rate deregulation, on allocative efficiency. This has been done in a two-sector model with the sectors earning different rates of return to capital and operating in an environment which includes both formal and informal banking sectors. The allocative efficiency is assumed to be affected if deregulation leads to a reallocation of a given amount of investments between the two sectors. It is shown that a deregulation does not always guarantee an improvement in overall productivity and thus in growth. The outcome depends on how the two sectors react towards the formal and the informal banking sectors as lenders and as borrowers, which ultimately affects the portfolio behavior of the two sectors and consequently allocational efficiency. The sensitivity of the outcome to the presence of the informal banking sector can best be gauged by the fact that in the absence of an informal banking sector, interest rate deregulation always leads to an improvement in allocative efficiency.

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6 BANKING EFFICIENCY AND PRIVATE INVESTMENT In the previous chapters we have concentrated on the effects of interest rate deregulation on investment. Another aim of financial deregulation can be to reduce the cost of financial intermediation, thus improving the functional efficiency of the banking system. One way to assess the functional efficiency of the banking system is to examine the magnitude of the spread between the deposit and the lending rates. While some attempts have been made to measure this spread for individual developing countries (see, for example, Capoglu (n.d.) for Turkey), there is little formal analysis of the effect of changes in banking efficiency on investment and other real or financial variables. The only exception that we are aware of, and that too for the developed countries, is the one by Viaene (1993). This study is briefly summarized in the next section. The aim of this chapter is to examine the effects of changes in banking efficiency on private investment. For this purpose we introduce the concepts of effective and nominal rates of return on deposits and the cost of loans. The difference between the two is caused by the cost of financial intermediation, which is a measure of banking efficiency. The analysis is carried out within the framework of the base model of Chapter 2 duly modified to incorporate the banking efficiency features. The chapter is organized as follows. In Section 6.1 a brief description of the Viaene (1993) model is given. Section 6.2 presents the model. The comparative static analysis for the base model, in which the non-bank private sector is credit constrained, is carried out in Section 6.3. Section 6.4 presents a comparative static analysis for a slightly modified version of our model. In this section, in contrast to our base model, it is assumed that the non-bank private sector is not credit constrained. A brief summary is offered in the concluding section.

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6.1 THE VIAENE MODEL Viaene specifies a model of an open economy and examines the effects of changes in the internal rate of return caused by the abolition of capital controls and the changes in the cost of financial intermediation or banking efficiency on equilibrium stock of physical capital. This is done within the framework of a capital-wealth accumulation framework. His equations (19b) and (20b) and the Appendix clearly show that unless we are willing to impose specific restrictions on a variety of parameters, it is not possible to sign the effects of changes in banking efficiency either on the steady state stock of physical capital or real value of wealth. Simulation experiments are carried out for five countries: Belgium including Luxembourg, France, Italy, the Netherlands and the United Kingdom. The simulation results seem to provide some support for the proposition that an increase in banking efficiency increases the steady state stock of capital. To the extent that the simulation results are specific to the parameter values used it is difficult to know whether they will carry over to other countries. But what his analytical results do show is that it is worthwhile carrying out analytical studies of the effects of changes in banking efficiency. The next section shifts the focus to developing countries and asks the same questions as examined in this section. 6.2 THE MODEL The model of this chapter distinguishes between a non-bank private sector and a formal banking sector. In contrast to Chapter 3 we do not explicitly consider a government sector and in contrast to Chapter 4 we abstract from an informal banking sector. The nonbank private sector again is a consolidated sector consisting of households and firms. The real budget constraint for this sector now reads

where all variables are as defined before. Real disposable income is defined by

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where y is as defined before, treated as being exogenous, im,e is the real effective deposit rate on bank assets and ilb,e is the real effective loan rate on credit, the concept to be defined below. The assets of the formal private banking sector are in the form of credit extended to the private sector. Liabilities of the formal private banking sector consist of demand deposits of the private sector. Hence, the real budget constraint of the formal private banking sector reads as

The asset demand equations, private consumption, savings and private wealth accumulation are derived in the same way as in our previous chapters. Hence, they are formulated as follows:

where all variables are as defined before. The adding-up restrictions of the above sub-model for the private sector can be easily derived by using the approach we have used in Chapter 2. Bank efficiency Bank efficiency is introduced in the model by defining the effective real deposit and lending rates, namely that

where i and i are as defined before. i and i are assumed to be m lb m lb fixed by the government, which is often the case in financially repressed economies. For reasons of convenience we have assumed

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that i and i , are equal; e is our measure of bank efficiency; 2e m lb equals the effective spread. Bank inefficiency is influenced by several factors, like unproductive employees and inefficient technology. Since the deposit rate and lending rate are fixed by the government, banks use loan terms, other than the deposit and loan rates, by which its inefficiency is passed on to the private sector. For example, banks may shorten the grace period or the maturity time so that the private sector pays a higher rate in effective terms. Otherwise, the effective rates may be influenced by high administration costs, etc. An improvement of bank efficiency in our financially repressed economy, where the government fixes the deposit (and lending) rates, is simply a decrease in e. This leads to a fall in the effective lending rate and an increase in the effective deposit rate. The difference between a financial liberalization in the conventional way (i.e. an increase in the deposit and lending rates) and an improvement in bank efficiency becomes clear immediately. The former leads to an increase in both the effective deposit and lending rates, whereas the latter leads to an increase in the effective deposit rate and a decrease in the effective lending rate. Assuming that noninterest income (or GDP) is given, and taking into account that the private banking sector does not hold reserves, so that L equals m, p this implies that a financial liberalization in the conventional way does not affect the disposable income of the private sector, whereas an improvement in bank efficiency raises the private sector’s disposable income. Abstracting from exogenous non-interest income, disposable income is written as:

6.3 BANKING EFFICIENCY AND PRIVATE INVESTMENT IF THE PRIVATE SECTOR IS CREDIT CONSTRAINED We start the analysis by considering the impact of an improvement in banking efficiency on investment by assuming that the private sector is credit constrained. In this case the full model of Section 6.2 applies. For reasons of convenience, we assume that the demand for deposits is not credit constrained (α26=0). This assumption does not change the basic insights of this chapter, it only simplifies the results.

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The impact of an increase in banking efficiency on private investment can be shown to be:

As can be seen, the impact of an improvement in banking efficiency (a decrease in e) on private investment is a priori indeterminate. On the one hand, an improvement in banking efficiency has a direct negative effect on private investment by the negative substitution between bank deposits and capital in the private sector’s portfolio (α11). On the other hand, an improvement in banking efficiency leads to an increase in disposable income, which stimulates investment directly and via an increase in wealth ([α14+α15]Z). Moreover, a change in banking efficiency affects consumption, which influences investment via a change in wealth (α14[dcp/de]). Finally, a change in banking efficiency affects investment via an increase or decrease in available bank credit (a16[d∆m/de]). In order to clarify the differences in the effects of deposit rate deregulation and an improvement in banking efficiency, we also give the multiplier with respect to a change in the deposit rate. This can be shown to be

where D is defined as above.

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By comparing the two multipliers it is clear that

where D and Z are defined as above. Equation (14) clearly shows the difference between a financial deregulation, in the sense of an increase in the deposit rate, and an improvement in banking efficiency. The increase in disposable income brought about by an improvement in banking efficiency might mitigate the possible negative effect of an interest rate deregulation on private investment via a direct positive effect on investment ([α14+α15]Z) and by an additional demand for bank deposits, which stimulates the supply of credit (α16[α24+α25]Z/D). Otherwise, the increase in disposable income might augment the possible negative effect of an interest rate deregulation on private investment by an additional positive effect on consumption which negatively affects wealth (α14[α55+α56α24+α56α25]Z/D). In order to be able to determine the channels by which a change in bank efficiency increases or decreases private investment more clearly we distinguish two cases. No wealth effects The absence of wealth effects implies that α14=α24=α34=0. The impact of an increase in banking efficiency on private investment now becomes:

Still, the impact of an improvement in banking efficiency on private investment is indeterminate. The first term on the right-hand side

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of d∆k/dim is the negative substitution effect between demand deposits and capital. The second term shows the impact of an increase in the effective bank deposit rate on credit available for investment, which positively affects investment when investment is credit constrained. Hence, for this case an improvement of banking efficiency unambiguously stimulates private investment if demand deposits and capital are not substitutes in the private sector’s portfolio. Since α15Z and α16α25Z in (15) are positive, it follows that even in the extreme case where (d∆k)/(dim)<0 an improvement in banking efficiency contributes to mitigate this negative effect. This positive effect is caused by an income effect which increases demand for deposits (α25Z), and hence leads to an additional increase in credit available for investment, and affects investment directly (α15Z). Wealth only affects investment In this case α14⫽0, but α24=α34=0. The multiplier with respect to the banking efficiency parameter e is given by:

Again, the multiplier is ambiguous. As in the previous case, private investment is negatively affected by the substitution effect between deposits and capital, and positively affected by the increase in available credit and the direct positive effect of an increase in disposable income. However, private investment is now also affected by changes in wealth α14(Z+α51-α56α25Z-α55Z- α56α21). An improvement of banking efficiency positively affects wealth by an increase in disposable income (Z) and a direct negative effect on consumption (α51). Since consumption might also increase due to an improvement in banking efficiency (α56α25Z+α55Z+α56α21), the total effect on wealth is, therefore, ambiguous.

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We can get some further insight if we consider the special case where consumption is not credit constrained (α56=0) and the marginal propensity to consume (α55) is not too high. With these assumptions, equation (16) shows that an improvement in banking efficiency positively affects investment in the case when capital and demand deposits are poor substitutes. 6.4 BANKING EFFICIENCY AND INVESTMENT IF THE PRIVATE SECTOR IS NOT CREDIT CONSTRAINED In this case the amount of credit available to the private sector is determined by the demand for credit, so that the cost of credit influences the asset demand equations and consumption. The asset demands and consumption are no longer affected by the availability of domestic credit. This implies that the model of Section 6.2 changes as follows:

Note, that ?lp in this case denotes the demand for bank credit. For reasons of convenience it is assumed that differences between supply and demand for credit are absorbed by reserve changes of the banking sector. This implies that the budget constraint of the banking sector has to be slightly adjusted. Except for this change, the other equations are as in Section 6.2. The impact of an improvement of banking efficiency and an increase in the deposit rate now are given by equations (17) and (18):

Again, it is easy to ascertain that equation (17) cannot be signed as it stands. A look at the terms on the right hand side of (17), though,

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can shed some light. Investment is decreased due to a negative substitution effect between physical capital and demand deposits, but is increased by a decline in the cost of credit (α17), an increase in disposable income (α15Z) and a possible increase in wealth (α14(Z+α51-α55Z-α57]). However, if consumption increases substantially as a result of the increase in disposable income and the decline in the effective lending rate, it may well be that wealth then decreases, which would affect investment negatively. By comparing equation (17) and equation (18) the difference between a financial liberalization in the conventional way and an improvement in banking efficiency becomes clear. Whereas the latter leads to a decrease in the cost of credit, which has a direct positive effect on investment (α17) and an indirect negative effect on investment via an increase in consumption (α57), the former leads to an increase in the cost of credit, which has a direct negative effect and an indirect positive effect on investment. Equation (18) also shows that, in the case where the private sector is not credit constrained, an interest rate deregulation has an unambiguously negative effect on private investment if wealth effects in the investment equation are minor (α14=0). For that case an improvement in banking efficiency still might stimulate private investment due to the decline in the cost of credit and the increase in income (α15Z) 6.5 CONCLUDING REMARKS The usual approach to the analysis of the relationship between financial liberalization and private investment has concentrated on the effects of interest rate deregulation. This chapter has made an attempt to examine the effects of an improvement in banking efficiency on private investment. This has been done by introducing the concepts of effective and nominal rates of return on deposits and cost of loans. It is shown that a financial liberalization in the conventional way leads to an increase in both the effective deposit and lending rates, whereas an improvement in banking efficiency leads to an increase in the effective deposit rate and a decrease in the effective lending rate. This implies that, in contrast to a financial liberalization in the sense of an increase in the deposit and lending rate, an increase in banking efficiency increases the private sector’s disposable income and decreases the cost of capital.

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It appears that an increase in banking efficiency on private investment is ambiguous both for the case where the private sector is credit constrained and for the case where it is not credit constrained. For both cases, the analysis suggests that the effectiveness of an improvement in banking efficiency on private investment is greater the lower the degree of substitutability between bank deposits and capital in the private sector’s portfolio and the greater the sensitivity of private investments to changes in income and wealth, assuming that wealth increases due to an improvement in banking efficiency. Wealth increases unambiguously when the increase in income exceeds the increase in consumption, which will certainly be the case if consumption is not credit-constrained, or the sensitivity of consumption with respect to the cost of capital is low, the marginal propensity to consume is low and the interest-sensitivity of consumption is high. In the case where the private sector is creditconstrained the effectiveness of an improvement in banking efficiency on private investment is also greater, the higher the extent to which investment is credit constrained, assuming that the supply of credit increases due to an improvement in banking efficiency, which will be the case when wealth effects in the equation for demand deposits are minor or when the marginal propensity to consume is low. Otherwise, in the case where the private sector is not creditconstrained, the effectiveness of an improvement in banking efficiency on private investment is greater, in addition to the channels pointed out above, the greater the sensitivity of private investments to the cost of capital. Although it is clear that the net effect of an improvement in banking efficiency on investment cannot be determined a priori, it is also clear that there are circumstances under which the possible negative effects of a change in deposit rates on investment may be mitigated or even overcompensated by the positive effects of an improvement in banking efficiency. However, given the special nature of the circumstances involved, the outcome must remain an empirical issue.

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7 SOME SIMULATION RESULTS In Chapters 2, 3 and 4 we have examined the comparative statics of interest rate deregulation by considering certain factors but by ignoring the others. Thus, for example, in Chapter 2, while we allow for the implications of interdependence between portfolio allocation and consumption/saving decisions and thus for the indirect effects of deregulation via wealth effects, we ignore foreign aid and informal credit markets and assume budget deficits to be exogenously determined. In Chapter 3, while we endogenize budget deficit and introduce foreign aid, we still ignore informal credit markets. While Chapter 4 rectifies this shortcoming, it does so only by ignoring foreign aid and assuming that budget deficit is given. The main reason for the partial approaches adopted in Chapters 2 to 4 is the fact that analytical solutions of more general models are virtually impossible to get. Hence, the attempts to obtain some insights in the presence of specific restrictions on the structures of the economies portrayed. An option which enables us to integrate all of the aspects considered above is, of course, that of a simulation model. This is the aim of this chapter. More specifically, this chapter draws upon earlier chapters to formulate a model which is solidly based on an integrated model of portfolio allocation and the consumption—saving decision of the private sector with appropriate attention to the underlying adding-up restrictions, which treats budget deficit as being endogenous, explicitly recognizing the role of foreign aid including the implications of the ‘fungibility’ of foreign aid as well as the role of informal credit markets without imposing any a priori restrictions on the degree of its intermediation capacity. In addition, unlike the previous chapters, inflation is treated as an endogenous variable by explicitly modeling aggregate supply. The scheme of the chapter is as follows. In Section 7.1, we specify and discuss the model. Section 7.2 discusses the simulation strategy and the parameter values used in the simulations. The simulations

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are reported in Section 7.3. The chapter is concluded with a brief summary and some policy implications. 7.1 THE MODEL The model consists of three sectors: the private sector, the government sector and the banking sector. We now describe each one of these sectors. The list of the notation and the definitions of the variables used is given in Table 7.1. Table 7.1 Notations and definitions used in the model

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Table 7.1 Cont’d

Non-bank private sector In this chapter the non-bank private sector is assumed to hold five assets: government bonds, physical capital, deposits of the formal banking sector and those of the informal banking sector and an inflation hedge, say foreign currency.1 The private sector receives credit from the formal and the informal banking sectors. All variables are in real terms, unless stated otherwise. The real budget constraint can be derived from column 1 in Table 7.2. It is specified as:

Disposable income is defined as:

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Note: *PS=non-bank private sector; CB=central bank; PB=formal private banks; UB=informal private banks, GS=government sector; ES=the external sector.

Table 7.2 The accounting framework of the model*

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In contrast to the previous chapters interest payments of the nonbank private sector are taken into account in the definition of disposable income. The asset demand equations of the non-bank private sector are derived by using the multivariate adjustment function, as explained in Chapter 2. In this chapter we take into account the lagged values of the various assets. However, for convenience and since parameters were not available, all cross adjustment coefficients are assumed to be zero. The asset demand equations2 of the non-bank private sector are then given by:

Note, that it is assumed that agents are concerned about the domestic purchasing power of their holdings of foreign currency, so that the expected domestic rate of inflation is part of the return from holding foreign assets. The consumption function is given by:

For the sake of practicality it is assumed that the coefficients for the different components of net wealth are equal.3 The effect of the beginning of period wealth is incorporated via lagged wealth as explained above. It should be pointed out that all nominal rates of

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return, except for the expected rate of depreciation, are assumed to be exogenously given, but not the real rates of return since inflation is treated as being endogenously determined (see below). Private savings and wealth are defined as:

The adding-up restrictions of the above model can be easily derived following the procedure given in Owen (1981). We do not specify those restrictions here since they were used in the simulations only for deriving the numerical values of some of the parameters involved, rather than being formally imposed on the model in simulations. It is worth pointing out that in this model there is no adding-up restriction which contains the coefficients of wealth only. In the above model, wealth can change only in response to change in a variable which affects the consumption—saving decision (see Chapter 2). In the simulations the demand for foreign currency is derived from the budget constraint. Therefore, an explicit equation for the demand for foreign currency is not specified. It should be pointed out that there are no equations here for the demand for loans from the formal and the informal banking sector by the private sector. This follows from our assumption that this sector is credit constrained and that it will absorb whatever supply of credit is provided by the formal and the informal banking sectors. Since we can determine the flow of assets demanded from the above model, the evolution of the stocks demanded can be formulated as follows:

The government sector The government’s expenditure consists of expenditure on consumption, investment and interest payments on outstanding

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government debt and stock of loans from the formal private banking sector. These expenditures are financed by taxes, by transfers from the central bank, by borrowing from the public (bond issue) and from the private formal banking sector and by foreign aid. The government’s budget constraint is then given by:

There are a number of distinctive features of the government’s budget equation which deserve highlighting. First, it explicitly allows for the role of interest payments on government borrowing. It is often the case that this element is ignored both in analytical works and in simulation models. But, as pointed out a long time ago by Blinder and Solow (1973), this omission can have serious consequences. Second, it allows for the crowding-out effect of government borrowing from the banking sector. In this model, in line with the other chapters, the supply of government bonds is entirely determined by the demand by the private sector. Assuming that transfers of the central bank to the government are exogenous, this means that in the absence of foreign aid, any residual needs for funds to finance a given budget deficit must come from borrowing from the banking sector. In the event that a deposit rate deregulation leads to a reallocation of the private sector’s portfolio against government bonds, it must imply an increase in government demand for bank credit, which, ceteris paribus, implies a reduction in the credit available for the private sector. And finally, this budget constraint allows, as already explained in Chapter 3, for possible interdependence between financial liberalization and foreign aid. The derivation of the government equations is given in the Appendix to this chapter. The procedure used in these equations is the same as in Chapter 3. The results are:

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Given Cg, Ig, T, ∆b, A, ∆Lcb and the net interest payments of the government, IPg, ∆Lg is determined by the government’s real budget constraint. Given ∆L g, we can specify the evolution of the corresponding stock as:

The evolution of the stock of physical capital of the government (kg) is specified as:

The banking sector This sector consists of three subsectors: the central bank, the formal private banks and the informal credit markets. The formal private banks lend to the non-bank private sector and the government. Moreover, they are assumed to hold reserves at the central bank. Liabilities of the formal private bank consist of bank deposits of the non-bank private sector. Reserves are equal to a fixed percentage of bank deposits, hence:

Assuming that reserves at the central bank do not pay interest and that the cost of borrowing for the non-bank private sector and the government sector is the same, the budget constraint of the formal private bank is given by (see column 3 in Table 7.2)

Taking into account capital gains (losses) on reserves net real interest payments of formal banks are specified as:

Given hf, ∆m, IPp and ∆Lg equation (23) determines loans to the nonbank private sector as a residual. Having determined the flow of loans the evolution of the stock is given by

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The lending rate of the formal banking sector is determined by the zero-profit condition for the banking system (see, for example Montiel et al., 1993):

Equation (26) shows that the reserve requirements of the banking sector drive a wedge between the deposit and the loan rate. Turning to the informal banking sector now. The informal bank lends only to the non-bank private sector. Liabilities are in the form of informal deposits held by the non-bank private sector. Also informal banks are assumed to hold reserves at the central bank. In line with the formal private banks, (non-interest paying) reserves are a fixed percentage of deposits; that is,

The supply of informal loans to the non-bank private sector is determined by its real budget constraint (see column 4 in Table 7.2)

Net real interest payments of the informal bank, where again capital gains on reserves are taken into account, are defined as:

Once again, the evolution of the stock of informal loans can be determined by

The lending rate of the informal banking sector is determined according to the following rule

The assets of the central bank consist of loans to the government. The liabilities are the reserves of both the formal and the informal bank. Reserves are distributed to the government in the form of a

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non-interest paying transfer. Note that in contrast to other work in this field, and in contrast to Chapter 4, we do not assume that these transfers are only used for unproductive government expenditures, but that they also affect government investment and taxes. The budget constraint of the central bank is written as (see column 2 in Table 7.2):

The evolution of the stock is:

External sector In contrast to the previous chapters, this chapter explicitly takes into account exports and imports of goods. For reasons of convenience, the modeling is as simple as possible, though. In rate of change, real exports and real imports denoted in foreign prices are specified as a function of the real exchange rate:5

The level of exports and imports is then given by

In real domestic prices imports are defined as:

Real foreign interest payments, denoted in domestic prices, are defined as

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Note that in fact real interest payments on foreign currency only refer to capital gains or losses. The change in foreign assets is determined by portfolio behavior of the non-bank private sector. Development aid (denoted in foreign currency: A*) is exogenous. Aggregate demand, aggregate supply, inflation and exchange rates With private investment, private consumption, government consumption, government investment and imports and exports already determined, we can write aggregate demand as:

Modeling aggregate supply poses serious problems. It is assumed here that firms are operating in a labour-surplus economy, so that labour does not constitute a bottleneck in the determination of aggregate supply. Looking at the rest of the model, it can be seen that gross private investment is determined as part of the private sector’s portfolio allocation and consumption—saving decision, and government gross investment as part of its optimizing behavior. We can describe the evolution of the total net capital stock according to

where

Using a Leontief-type technology, aggregate supply is then determined by

y in the equations (2), (17), (18) and (19) is defined as

The goods market is cleared by price changes. We assume that expected (and actual) inflation is determined by the equilibrium condition on the goods market; that is, from the following condition:

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One virtue of this relationship is that it takes into account how interest rate deregulation drives changes in aggregate supply and aggregate demand and thus inflation. The domestic price level is then calculated as follows:

Note that the balance of payments (the budget constraint of the external sector: column 6 in Table 7.2) is automatically in equilibrium in the case where aggregate demand equals aggregate supply and the budget constraints of the other sectors hold. This implies that there are no changes in foreign reserves that might affect domestic money supply. With respect to the expected devaluation of the exchange rate, we assume, admittedly rather ad hoc and primarily for pragmatic reasons, that it gradually adjusts to purchasing power parity. This implies:

By assuming different values for ?12 we are now able to simulate with a fixed exchange rate regime, or a flexible exchange rate regime in which exchange rates are formed by purchasing power parity. Finally, the level of the exchange rate is specified as follows:

7.2 THE SIMULATION STRATEGY The basic question addressed in this chapter is: does interest rate deregulation affect private investment and/or government investment? In order to answer this question, we can simulate the model in a variety of ways. But we believe that the most illuminating way is to do so by concentrating on one of the sectors of the model at a time and then do what essentially amounts to a sensitivity analysis compared to a baseline simulation. This is the approach adopted here. But this still leaves the question about the selection of sectors. Clearly, in this model we have three options—namely, the nonbank private sector, the banking sector and the government sector.

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Of course, there are the obvious alternatives to this sectoral approach—namely, combining two or more sectors. However, we exclude such an approach here. In this chapter, we mainly concentrate on the consolidated private sector. Our reason for singling this sector out to the exclusion of the other two sectors is that the model allows us to shed light on a number of contentious issues in the literature—for example, on the role of liquidity constraints on the behavior of consumers and firms, on the role of wealth, on the effectiveness of real interest rates in stimulating private savings and on the role of substitutability between deposits and capital. In a partial analysis the implications of these issues are spelled out in Chapter 2. Here we elaborate somewhat more on them, but now in a simulation model in which informal markets, aid, a supply sector and hence inflation and endogenous government deficits are taken into account. Moreover, the analysis in Chapter 2 was a static analysis, whereas in this chapter we explicitly consider the dynamic behavior of the model. This is not to suggest that we consider the other two sectors less important. Quite the contrary. There are equally contentious issues in the banking sector, for example, whether the informal credit markets help or hurt the effectiveness of interest rate deregulation policies and the government sector. However, for reasons of space we decided to make only a few simulations with respect to these sectors. The specific simulations, with respect to the private sector, reported relate to: The nature of the private sector’s portfolio Here the main contentious point is what would happen if physical capital was a poor substitute for money, in our case for the formal and informal deposits. This, of course, does not rule out the possibility that the deposits may be close substitutes for government bonds and/or the inflation hedge. In many models where only two assets are assumed—namely, capital and money (Sussman, 1991)—the issue strictly relates to the degree of substitutability between these two assets. We consider an extreme form of this relationship: the situation in which the two assets are independent of each other in the private sector’s portfolio. This means that the cross-effect of each other’s rate of return is zero.

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Importance of credit constraints Here, four possibilities present themselves. The first one is that which is embodied in the baseline simulation, where both households and the firms are credit constrained. Its opposite extreme is where neither of them is. The other two are intermediate possibilities where either the households or the firms are creditconstrained. The effect of the opposite extremes is examined in the simulations. Importance of interest rates in stimulating private savings This is one of the most contentious issues in the literature. We examine this by considering the case where consumption is not at all affected by changes in real interest rates. It is this assumption which virtually all other studies in this area use to justify treating consumption/savings as an exogenous variable. The importance of wealth effects In the developing countries, this issue can be analyzed along the same lines as for the developed countries. But two points may play a more important role here. The first relates to the importance of internal finance for financing investment in these countries. Given the underdeveloped nature of the capital markets and even the banking sector in these countries, it is plausible to assume that internal funds would play a more important role than in the developed countries, or, at least, an important one. The second relates to the role of wealth in the consumption function. Here the issue is even more complicated. It is possible to show that in a slow-growing economy, wealth will not play a significant role in the consumption—saving decision. The effect of the first possibility is examined in the simulations. With respect to the banking sector we report only one simulation. The importance of reserve requirements In Chapter 4 it is shown that one of the most important assumptions of the ‘structuralists’ with respect to the effect of an interest rate deregulation in the presence of an informal financial sector relates to the reserve requirements of the formal versus the informal banking

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sector. Therefore, we simulate the effects of an interest rate deregulation by assuming that the reserve requirements of the formal banking sector are much higher than those for the informal banking sector. Finally, we report two simulations with respect to the government. Effects of endogenous aid In Chapter 3 we have shown that foreign aid could have an important role in mitigating the crowding-out effects of an interest rate deregulation. An interest rate deregulation might lead to an additional government demand for formal loans, which might crowd out bank loans available for the private sector. If an interest rate deregulation goes together with an increase in foreign aid, this crowding-out effect might be reduced. Effects of the relation between private and government investment In Chapter 3 it was also shown that the effects of an aid increase substantially depend on the assumption with respect to the relation between government and private investment. The effects of an interest rate deregulation on private and government investment, in the presence of aid, depends very much on whether both types of investment are complements or substitutes. In our base model we have assumed that there is no direct relation between the two, but in this last simulation we will assess the effects of an interest rate deregulation by assuming that government and private investment are complements. Our model does not address the problem of actual forecasting. The purpose is to set out different cases which are compared with each other. Since data for a number of variables are lacking we could not estimate the entire model. Although most parameters are based on available econometric estimates for Asian developing countries, they do not pertain to a specific country. We start by presenting the parameters used in the base model. Table 7.3 gives the parameters of the asset demand equations as well as the parameters for private consumption. Estimates with respect to the coefficients in the equation of demand for informal

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deposits and with respect to the coefficients for informal credit in the asset demand and consumption equations are not available. Admittedly rather ad hoc, we assumed that formal and informal credits affect asset demand and consumption alike. Further, we assume that the composite coefficients have the property of symmetry—that is, α5=α14; α6=α24, etc. The sources of the other coefficients are given in Table 7.3. Table 7.4 presents the parameters for the government equations, the initial values and the exogenous variables. All initial values refer to the group of Asian Developing Countries (IMF, IFS and World Bank, World Tables). Where figures for the whole group of Asian countries are not available, figures for India are used (IMF, IFS). Note that all initial values are given as percentages of GDP (y). Some other assumptions: a in the aggregate supply equation is set at 0.33, η10 and η11 in the equation for exports and imports are set at 0.60 and—0.85, respectively (based on Marquez, 1990); η12 in the exchange rate equation is set at 0. Hence, we simulated with a fixed exchange rate regime.6 Table 7.3 Parameters of the asset demand equations and private consumption

Sources: Morisset (1993), Gupta (1993b), Ogawa et al. (1994).

The chapter takes the following approach. In all simulations we assess the impact of a sustained increase in the nominal return on formal bank deposits (i ) by 1 percentage point. Results are m presented as deviations from the baseline, where i has its original m value. We start by running a Base simulation. In that case all coefficients have the values as presented above. In addition to this base simulation we present alternative simulations for the cases

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identified above, which means changes in some of the coefficients in the model. For these simulations also the results are presented as differences from the baseline. Note that the baseline in the alternative simulations differs from the baseline in the base simulation since some coefficients are adjusted. Table 7.4 Parameters of the government equations, initial values and exogenous variables

Sources: Government consumption, investment and taxes, see the Appendix. With respect to the different assets we take averages for some Asian countries. However, not all data were available. The non-available starting values for the assets are constructed in a way that they are consistent with the budget constraints.

Since this chapter is primarily concerned with the impact of a financial liberalization as represented by an increase in the nominal deposit rate on private investment, we decided to present, for the Base simulation, figures for private investment as well as figures for all endogenous variables entering the equation for private investment. Because private investment as well as income, wealth, inflation and supply of credit are endogenous variables in our model, the causality of the mechanisms is unclear: all variables are simultaneously determined. Nevertheless, the different endogenous variables entering the investment equation may shed some light on the reasons why private investment increases or decreases during the simulation period. We also present figures for government investment and demand for government bonds. The latter variable gives some insight about the crowding-out effect of government demand for formal credit resulting from a portfolio shift of the private sector. In the Base simulation, for each time period, the variables, except for inflation, are expressed as point elasticities. Figure 7.1 presents the interest rate elasticities of the capital stock of the private sector (elascap) and the government sector (elascapg).7 Figure 7.2 presents the interest rate elasticities of formal bank loans to the private sector (elasloanp), the interest rate elasticities of government loans (elasloang)

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and the interest rate elasticities of informal loans (elasloani). Figure 7.3, 7.4 and 7.5 present the interest rate elasticities of the demand for government bonds (elasbond), net wealth (elaswealth) and disposable income (elasinc), respectively. Finally, Figure 7.6 presents the effects of an increase in the deposit rate on inflation. The variable we present (infld) is defined as the increase in the rate of inflation due to a one percentage increase in the deposit rate. 7.3 THE SIMULATION RESULTS The base simulation We start the analysis by presenting the simulation results for the base model. Figure 7.1 shows that a financial liberalization in our model initially has a negative effect on private capital. However, after ten years an interest rate deregulation starts to have a positive effect on private capital. After ten simulation periods the interest rate elasticity of private capital is positive and increases during the rest of the simulation period. The figure also shows that the capital stock of the government is negatively affected by a financial liberalization. This suggests that capital of the private and government sectors are substitutes. The decrease in the capital stock of the private sector in the first periods is mainly the result of a decline in formal credit available for the private sector, which arises, among others, from an increase in government’s demand for formal credit (see Figure 7.2). Hence, government’s demand for credit crowds out the supply of credit to the private sector. The increase in government’s demand for formal credit is, among other things, caused by a decline in demand for government bonds by the private sector (Figure 7.3). Figure 7.3 also shows that the demand for government bonds starts to increase after 15 simulation periods. The continuously rising increase in government’s demand for credit then starts to weaken. Also the negative effect of an interest rate deregulation on government capital starts to decline.8 An important reason for the increase in the capital stock of the private sector after some simulation periods is the increase in wealth during the simulation period (Figure 7.4) and the positive impact on disposable income (Figure 7.5). The effect on inflation (Figure 7.6) may seem counterintuitive when we consider Figure 7.1. However, this is not necessarily so

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given that the effect on government’s capital accumulation is negative throughout the simulation period and the effect on private capital becomes positive after some simulation periods. And since aggregate demand and aggregate supply are being driven by both private and public investment expenditures, it is not necessarily a surprise that the economy seems to experience excess supply in the

Figure 7.1 Base model simulations

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first simulation periods, and hence decreasing inflation and, later on, excess demand and therefore increasing inflation. However, it is important to consider the magnitude of the effect. It is truly very small, so that the inflationary potential of the interest rate deregulation policy in the base model must be considered rather minor.

Figure 7.2 Base model simulations

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The alternative simulations For the alternative simulations, we present, in the Figure 7.7, differences between the interest rate elasticities of the capital stock of the private sector and the government sector, for the alternative simulation and the base simulation, namely,

Figure 7.3 Base model simulations

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difcap=elascapa-elascapb difcapg=elascapga-elascapgb, where the subscript a denotes alternative simulation and the subscript b denotes the base simulation. If difcap or difcapg is positive this means that an interest rate deregulation in the alternative case

Figure 7.4 Base model simulations

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has a favorable effect on the elasticity of capital in comparison to the base simulation. Besides difcap and difcapg we had a choice of presenting several figures. In order to save space we decided, however, to present, in general, only a figure with respect to wealth behavior. The reason for this is that the behavior of wealth

Figure 7.5 Base model simulations

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appeared to be very important for the effects of an interest rate deregulation on investment. In line with difcap and difcapg the wealth Figure is calculated as the difference between the interest rate elasticities of wealth for the alternative and the base simulation (difwealth).

Figure 7.6 Base model simulations

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No substitution between deposits and capital The advocates of the financial liberalization school, e.g. McKinnon (1973) and Shaw (1973), assume that an increase in deposit rates leads to a portfolio shift out of unproductive assets (cash) into bank deposits. However, this may be a too extreme simplification of reality in developing countries. It is also possible that bank deposits might be close substitutes to productive assets, such as private capital, as well. Clearly, the fact that deposits and private capital are treated as being gross substitutes is one of the reasons why the simulations point to a weak negative effect of a financial liberalization on private capital. In order to assess the implications of substitutability between deposits and private capital, we simulate the effects of a financial liberalization assuming that deposits and private capital are not substitutes. This means that a =a = a =a =0 in the asset demand 14 54 18 55 equations for the private sector. The results of this simulation are displayed in Figures 7.7 and 7.8. Figure 7.7 shows that difcap and difcapg, as defined above, is positive during the whole simulation period. This implies that an interest rate deregulation in the case where deposits and capital are not substitutes has a more positive or less negative effect on government and private capital than when deposits and capital are substitutes. This is what we should expect in view of the fact that there is no direct negative substitution effect on private investment via portfolio adjustment. We can conclude from this that the smaller the degree of substitutability between deposits and capital in the private sector’s portfolio, ceteris paribus, the greater the effect of interest rate deregulation on private capital accumulation. Figure 7.8 shows that in the case where deposits are not substitutes the elasticity of wealth with respect to an interest rate deregulation is lower than that in the base simulation for the first simulation periods, but higher after some time. Only investment is credit constrained This implies that α3=α9=α23=α29=α43=α49=α53=α59=0 and α13=α19=1 in the asset demand equations for the private sector. By deriving the adding-up restrictions, it can be easily verified that in this case the demand for foreign assets is not credit constrained either. The results for this case are shown in figures 7.9 and 7.10. Figure 7.9 shows that difcap is negative almost during the whole simulation period. This shows that if only investment is credit

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constrained, then interest rate deregulation has a more negative effect on private investment. This can be explained by considering Figure 7.2 once more. An interest rate deregulation has a negative effect on credit available for the private sector. This, of course, has a more negative effect on private investment in the case where only

Figure 7.7 Alternative simulation 1: no substitution between deposits and capital

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investment is credit constrained, since then the burden of the crowdingout effect falls entirely on investment. We also did a simulation in which only consumption is credit constrained. For this case the effect of an interest rate deregulation on private investment becomes more positive, which is of course not surprising. For

Figure 7.8 Alternative simulation 1: no substitution between deposits and capital

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reasons of space we do not report these simulation results. Figure 7.10 shows that the effect of an interest rate deregulation on the elasticity of wealth also becomes more negative in the case where only investment is credit constrained. This also explains why the effect of an interest rate deregulation on private capital becomes more negative when only private investment is credit constrained.

Figure 7.9 Alternative simulation 2: only investment is credit constrained

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Figure 7.10 Alternative simulation 2: only investment is credit constrained

Consumption not affected by real interest rates This implies that α44=…α48=0 in the equation for private consumption. The outcome of this case is shown in figures 7.11 and 7.12. Figure 7.11 shows that difcap and difcapg is negative almost during

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Figure 7.11 Alternative simulation 3: consumption not affected by real interest rates

the whole simulation period. This can be explained as follows. In the case where consumption is not affected by a change in the interest rate on deposits, an increase in the deposit rate does not have a direct negative effect on consumption and hence not a direct negative effect on savings and wealth. As Figure 7.12 shows, difwealth is negative

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Figure 7.12 Alternative simulation 3: consumption not affected by real interest rates

during the whole simulation period, which implies that the elasticity of wealth with respect to the interest rate is lower in the case where consumption is not negatively affected by an increase in the real deposit rate, which confirms the above given explanation. Note, however, that the differences between the base simulation and the alternative simulation, as represented in Figure 7.11, are

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very small. This may well reflect the fact that the real interest rate coefficient in the consumption function is only 0.05, so that its replacement with a value of zero is not likely to make any significant difference. However, it should be noted that the seeming irrelevance of the interest rate sensitivity of consumption—saving does not justify the normal practice of treating savings as being exogenous (Morisset, 1993), because consumption/savings is affected not only by real interest rates but also by a host of other factors, as can be readily seen from our model. What is more, even the real interest rate may have an effect, albeit indirectly. Higher wealth effect in investment equation In this simulation it is assumed that the coefficient of net wealth in the investment equation (α12) increases from 0.2 to 0.25. We did some other simulations with respect to the wealth coefficient as well. However, these are, again for reasons of space, not reported here. From these simulations it became very clear that a change in the wealth coefficient has important effects on the results. This would clearly suggest that a proper modeling of investment is most important in order to assess the role of financial liberalization in stimulating private investment. It can be seen from Figure 7.13 that a very small increase in the wealth coefficient has a relatively positive effect on the elasticity of private capital with respect to an interest rate deregulation, as compared to the base simulation, in the first ten simulation periods. Thereafter, the effect on private capital becomes worse than in the base simulation. This behavior can for an important part be explained by the development of wealth. Difwealth in Figure 7.14 is positive for the first simulation periods and negative later on. For capital of the government it is somewhat the other way around. Higher reserve requirements in formal banking sector In this simulation we have increased the required reserve ratio for the formal banking sector (h ) to a value of 0.25. The value for the f reserve ratio of the informal banking sector (h ), however, is assumed u to stay at 0.05. This is clearly a case which is comparable to the case the ‘structuralists’ have in mind: high reserve requirements in the formal banking sector and low, or even no, reserve requirements in the informal banking sector. To make this simulation even more

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comparable to that of the structuralists we also assumed that informal and formal credit is only used for investment (only investment is credit constrained: for the model implications, see pp. 60–66). We would expect that an interest rate deregulation for this case, in comparison to the base simulation, has a depressing effect on private

Figure 7.13 Alternative simulation 4: higher wealth effect in investment equation

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Figure 7.14 Alternative simulation 4: higher wealth effect in investment equation

capital. Higher reserve requirements of the formal banking sector imply that a greater share of formal credit is used by the government and hence a lower share becomes available for the private sector. Figure 7.15, however, shows that this is not the case in our simulation. Difcap is negative for the first five simulation periods,

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which is in line with what we would have expected. But, after five simulation periods, difcap becomes positive. For difcapg also the results are not in line with what we would have expected even for the whole simulation period. To explain these results a bit more, we present some other figures as well. Figure 7.16 shows the effect of

Figure 7.15 Alternative simulation 5: higher reserve requirements in formal banking sector and only investment credit constrained

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an interest rate deregulation on the elasticity of loans to the private sector (again measured as a difference from the base simulation). This Figure shows that difloanp is negative during the whole simulation period, which is in line with what we would have expected: higher reserve requirements lead to a more substantial

Figure 7.16 Alternative simulation 5: higher reserve requirements in formal banking sector and only investment credit constrained

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crowding-out of private credit. How then can the effect on private capital be explained? Again we have to search for the explanation by considering the effect of an interest rate deregulation on the dynamics of wealth, which is normally not considered by the ‘structuralists’. Figure 7.17 shows that difwealth is positive during

Figure 7.17 Alternative simulation 5: higher reserve requirements in formal banking sector and only investment credit constrained

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the whole simulation period. This means that the elasticity of wealth with respect to an interest rate deregulation is more favorable in this alternative case than in the base case. Although the reason for this result is somewhat difficult to explain, since wealth is affected by almost all variables in the model, it again shows that it is extremely important to take into account the effects of interest rate deregulation on wealth when one wants to assess the effects of a financial liberalization on private investment. Higher foreign aid In this simulation we assumed that, in combination with an interest rate deregulation the aid donors decide to increase aid by 5 percent per year. Figure 7.18 gives the result for difcap and difcapg. The behavior of difcapg is what we would have expected: it is positive during the whole simulation period, implying that an interest rate deregulation in combination with an increase in aid has a more favorable effect on government investment than an interest rate deregulation without an increase in aid. The reason for this is that the possible negative effect of an interest rate deregulation on demand for government bonds and hence on funds available for the government may be counteracted by the increase in foreign aid. This also would have a positive effect on loans available for the private sector, since the government does not now have to borrow so much from the banking sector. This is illustrated by Figure 7.19, which shows that government borrowing from the formal banking sector is affected negatively and the loans available for the private sector positively. This all would lead to an expectation that the effect on private capital becomes more favorable as well. However, Figure 7.18 shows that this is not the case. If an interest rate deregulation is combined with an increase in foreign aid our simulation suggests that the effect on government investment is positive, but that the effect on private investment is negative. How can this be explained? Again we might consider the behavior of wealth. It appears that difwealth is negative during the whole simulation period (Figure 7.20), hence the result. An important reason for this behavior of wealth and for the outcome with respect to private investment appears to be the effect of the aid increase on inflation. Figure 7.21 shows the effect of an interest rate deregulation in the presence of aid on inflation. This variable (difinfld) is again calculated in the same way as difcap, etc. The

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result is very interesting. Difinfld is positive during the whole simulation period, implying that an increase in aid stimulates inflation, and may have a negative effect on net wealth and private investment just because of this increase in inflation. This result is in line with studies pointing to possibly negative effects of foreign aid on the competitiveness of a country. Authors like Van Wijnber

Figure 7.18 Alternative simulation 6: aid increases with 5 percent

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Figure 7.19 Alternative simulation 6: aid increases with 5 percent

gen (1985b) argue that aid transfers may lead to a real appreciation of the currency by causing an excess demand for goods and hence by stimulating inflation. This is exactly what happens in our model. Note that, since the nominal exchange rate is assumed to be fixed in our model, the aid increase also causes a real appreciation of the home currency. So, in addition to the channels

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which have been spelled out in Chapter 3, our simulation results point at one very important other channel by which foreign aid may have an effect on private investment: the effects of foreign aid on inflation.

Figure 7.20 Alternative simulation 6: aid increases with 5 percent

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Figure 7.21 Alternative simulation 6: aid increases with 5 percent

Complementarity between government and private investment In Chapter 3 we have also argued that a careful modeling of the relationship between government and private investment is required in order to assess the effects of an interest rate deregulation on government and private investment. In that chapter we have shown

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that even when foreign aid is not directly used for government investment foreign aid might positively affect government investment via a positive link with private investment. In our base simulations we have assumed that there are no direct feedback effects between government and private investment. In this final

Figure 7.22 Alternative simulation 7: aid increases with 5 percent and government investment positively affects private investment (? =0.3) 1

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Figure 7.23 Alternative simulation 7: aid increases with 5 percent and government investment positively affects private investment (γ =0.3) 1

simulation we assess the effects of an interest rate deregulation in the presence of aid (aid increase of 5 percent) by additionally assuming that government and private investments are complements. This is done by assuming that γ1=0.3 (in the equation for target investments). Note, that this implies that η1, η6 and η8

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Figure 7.24 Alternative simulation 7: aid increases with 5 percent and government investment positively affects private investment (? =0.3) 1

had to be recalculated. The results for this simulation are given in Figures 22–25. It can be seen that they are comparable to Figures 18–21. Again, the increase in foreign aid causes an interest rate deregulation to have a negative effect on private capital and a positive effect on government capital, in comparison to the base

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Figure 7.25 Alternative simulation 7: aid increases with 5 percent and government investment positively affects private investment (? =0.3) 1

simulation. However, the positive effect on government capital is smaller in the case where government investment and private investment are complements. The reason is that the decline in private investment has a direct negative effect on government investment when both types of investment are complements.

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7.4 CONCLUDING REMARKS The aim of this chapter is to specify a simulation model which can shed light on a number of controversial issues regarding the effect of interest rate deregulation on private investment. Unlike virtually all other works in this area, our specification includes a portfolio selection model which is integrated with the consumption—saving decision, which includes the informal credit market as distinct from the formal banking sector, and lets the budget deficit be determined endogenously as well as treating inflation as an endogenous variable. A distinct characteristic of the model is its treatment of interest income and interest burden in the budget constraints of the private and the government sectors. An advantage of our model is that it enables us to examine a variety of channels, hitherto unidentified in the literature, which can impact on the relationship between interest rate deregulation and private investment. Since we report only a small selection of sensitivity tests, it is not possible to comment on the overall effectiveness of financial liberalization. The presented simulations shed light on a number of issues, though. First, they show that under a variety of changes to the private sector’s behavior, the effect of deregulation is relatively robust in so far as the quantitative effect is concerned. It is relatively small, although the direction of the effects is sensitive to some of the specific characteristics of the firm’s behavior towards capital accumulation. The outcome of the different simulations appears to be driven mainly by wealth behavior during the simulation period. Moreover, the outcome appears to be strongly influenced by the sensitivity of private investment to changes in wealth. The qualitative outcome of our simulations is similar to the findings reported by other researchers in the field, for example, Lewis (1992) for Turkey, Morisset (1993) for Argentina, Montiel et al. (1993) from a simulation model, and Gupta (1984) for a cross-section of developing countries. These other studies, however, shed little light on the sensitivity issue addressed here. To the extent that our sensitivity results are significant, they clearly suggest the need for a careful modeling of private investment behavior. Second, our results also point to the need for fiscal discipline, particularly in so far as governments’ demand for credit from the banking sector is concerned. This is another way of saying that financial liberalization should be accompanied by budget deficit control. Third, our simulations clearly give some new insights into the effects of an

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interest rate deregulation in combination with an increase in foreign aid. Foreign aid may assure that government investment does not decline as a result of an interest rate deregulation. However, this is not a guarantee that the effect of an interest rate deregulation on private investment becomes more favorable in the case where it is combined with an increase in foreign aid. Quite the contrary: the increase in foreign aid may even end up having a depressing effect on private capital. Here, the issue of what happens to inflation when financial reforms are adopted in combination with an increase in foreign aid must be faced. Our simulations with respect to an increase in foreign aid suggest that interest rate deregulation in combination with an increase in foreign aid may lead to higher inflation. This may have a negative effect on private wealth and hence on private investment. These outcomes are not uncommon in countries adopting IMF/World Bank structural adjustment programmes. Our simulations simply confirm such outcomes. This points to the need for clearly recognizing that during a process of financial liberalization, in combination with an increase in foreign aid, forces are let loose which exacerbate inflationary pressures but have contractionary real effects. This double-edged misfortune would seem to be an inevitable outcome of the interest rate deregulation policies which are not accompanied by appropriate fiscal policies. Finally, our simulations support the wisdom of using our simulation strategy—namely, to analyze the effect of a single policy experiment in the face of alternative assumptions about economic agents’ behavior. APPENDIX 6 The equations for government consumption, investment and taxes are derived as follows. We start with the specification of a loss function for the public authorities (see Chapter 3). For convenience, it is assumed that transfer payments from the central bank to the government are exogenous.

where the corresponding variables with the asterisk represent target values. This loss function is minimized subject to the government

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budget constraint as given in the text. It can be shown that the solutions for Cg, Ig, ∆Lg and T are given by the following equations:

where ß1, ß2, ß3, ß4, ß5, ß6, ß7 and ß8 are as defined in Chapter 3 (see pp. 36–37). The adding-up restrictions are as follows (see also Chapter 3).

In contrast to Chapter 3 we endogenize the target variables. These are specified as follows (for a similar approach see, for example, Heller, 1975; White, 1994b; Khan and Hoshino, 1992):

The following reduced form equations for the government can now be derived:

The demand for loans from the formal private banking sector is derived from the government’s budget constraint.

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Determination of the coefficients in the government equations Since there are no studies available that estimate the reduced form equations as derived above, we had to follow an indirect approach. We tried to use our adding-up restrictions of the sub-model for the government as much as possible so that we only have to ‘guesstimate’ some coefficients. We started by ‘guesstimating’ the values for ß2, ß4 and ß6. The coefficients we have used are based on reduced form effects of aid on government investment, consumption and taxes, respectively, which are provided by the different studies available on the ‘fiscal response’ effect of aid (see Chapter 3 for references). The problem, however, was that the coefficients found in these studies differed enormously from each other and that for some studies it was somewhat difficult to find the real reduced form effects of aid, since the equations were specified in a ‘quasi’ reduced form, with endogenous variables on the right-hand side. The values we used are: ß2=0.2, ß4=0.35 and ß6=0.2. The values of ß1, ß3 and ß5 are then calculated by using the adding-up restrictions. This implies that ß1=0.8, ß3=0.65 and ß5=0.8. Next, we used estimation results with respect to the target values in order to determine the ‘gammas.’ Here, we mainly used the results of Heller (1975). Note that, in contrast to Heller (1975) we did not introduce lagged imports as a determinant for target taxes. The reason for this decision is that it is disputable whether imports should enter this equation because of multicollinearity between imports and income. Since Heller’s estimation results with respect to target taxes suffered from multicollinearity between imports and income we decided not to use his coefficient for income in the tax equation. The ‘gammas’ we used are: ?1=0.0, ?2=0.02, ?3=0.95, and ?4=0.10. The coefficients in the government equations can now be determined by using the adding-up restrictions as specified above.

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8 FINANCIAL REPRESSION AND FISCAL POLICY While the literature on financial repression and its effects on the growth of developing countries is quite voluminous by now, much less attention has been paid to its public finance aspects. In particular, it is beginning to be argued that financial repression can be and is being used by governments to extract more resources from the economy. Two recent interesting attempts in this direction are by Sussman (1991) and by Giovannini and De Melo (1993). Sussman defines financial repression as a tax on interest income from bonds. Using an overlapping intergenerations model, he shows that in the short-run, this form of financial repression always leads to a reduction in capital accumulation and in the rate of inflation. However, in the long-run, while the effect on capital accumulation is unambiguously negative, the outcome for inflation is uncertain, meaning that the certain short-run trade-off is not always guaranteed in the long-run. Giovannini and De Melo, on the other hand, provide empirical evidence on the effect of financial repression on government revenues. They argue that since financial repression enables the government to borrow from domestic sources at a rate lower than what it would be if borrowed at the international rate, the policy in effect amounts to raising additional revenue from this source. Their evidence shows that in many cases the revenue from this source amounts to almost as much as from seigniorage. The aim of this chapter is to add to this small body of literature. More specifically, we use our simulation model, specified in Chapter 7, to assess the cost of financial repression in terms of the effects on inflation, private and public investment and the pattern of public consumption. The indications of financial repression, like those in Sussman (1991) and Giovannini and De Melo (1993), are those which are meant to raise additional revenues for the government. The measures of financial repression studied are: (a) the government levying a tax on interest income from government bonds held by the non-bank private sector; (b) the 146 government

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borrowing from the banks at rates lower than those charged to the private sector; and (c) government borrowing from the banking sector by increasing reserve requirements of the formal banking sector. The scheme of this chapter is as follows. Section 8.1 explains the simulation strategy. The simulation results are presented in Section 8.2. The chapter is concluded with a brief summary and some policy implications of our findings. 8.1 THE SIMULATION STRATEGY The way we examine the cost of the different types of financial repression identified above is as follows. We start with a base solution in which there is no financial repression from any of the three sources described in the introduction. Next, we simulate the model by introducing one type of repression at a time. In the Figures we then plot the alternative simulations as deviations from the base solution,—that is, what we call the no-repression case. This norepression case is the baseline simulation of Chapter 7, where i m has its original value and all parameters, exogenous variables and start values are as specified in the Tables 7.3 and 7.4. We concentrate on only five endogenous variables, rather than on all of them. More specifically, we are interested in the time-path of the deviations of the behavior of private and public capital formation, the pattern of government consumption, inflation and private net wealth. The meaning of the deviations is straightforward. If the deviations are positive, then it implies that capital formation, government consumption and private net wealth are affected adversely by financial repression, but inflation favorably (lower inflation) and, of course, vice versa. 8.2 THE SIMULATION RESULTS The simulations reported relate to: Financial repression caused by taxing interest income on government bonds In the first set of simulations we assess the implications of levying a tax on interest income from government bonds held by the nonbank private sector. For this experiment we change several

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equations in the model: (1) In the asset demand equations and the consumption function of the non-bank private sector we enter the tax rate on interest income from government bonds (tr). For example, the investment equation now becomes:

The adjustment of the other asset demand equations and the consumption function is alike. (2) Disposable income of the nonbank private sector has to be corrected for the tax on interest income on government bonds, so that equation 2 in Chapter 7 changes as follows:

(3) The government’s real budget constraint becomes:

where

and finally (4) tax on interest income from government bonds enters the equations for government consumption, government investment and government taxes. This implies:

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For this set of simulations the no-repression case is represented by a simulation in which the tax rate (tr) is set equal to zero. The

Figure 8.1 Tax on bond interest income: private investment

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financial repression cases are represented by simulating the model for two alternative values of the tax parameter: tr equals 0.50 or 1. The simulation results, which are plotted as deviations from the norepression case, are presented in the Figures 8.1 to 8.5.

Figure 8.2 Tax on bond interest income: government investment

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Figure 8.3 Tax on bond interest income: government consumption

Financial repression due to government borrowing at a concessional rate In this set of simulations we investigate the consequences of a lower lending rate for the government than for the non-bank private sector. This implies that the model should distinguish

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Figure 8.4 Tax on bond interest income: inflation

between a lending rate for the non-bank private sector (ilb) and a lending rate for the government (ilbg), so that, in Chapter 7, ilb enters equation (2) and ilbg enters equation (16). Moreover, in equation (24) the difference between the lending rate of the two sectors has to be taken into account. In the model ilbg is written as: 152

FINANCIAL REPRESSION AND FISCAL POLICY

Figure 8.5 Tax on bond interest income: private wealth

where P is an exogenous parameter, determining the difference between the two lending rates. In Chapter 7 the lending rate of the formal banking sector (equation 26 for which iib=ilbg) is derived from the standard zero153

FINANCIAL REPRESSION AND FISCAL POLICY

profit condition for banks. This implies that a difference between ilb and ilbg requires a rewriting of that equation in order to ensure that banks do not go bankrupt. This is done by rewriting equation (26) in Chapter 7 as follows:

Figure 8.6 Borrowing at concessional rates: private investment

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As can be seen, equation (26a) equals equation (26) when P is zero (i.e. when the lending rates of the two sectors are equal). If the lending rate of the government sector is lower than that of the private sector, which implies that P>O, ilb increases and hence the private sector pays for the lower lending rate of the government; in other words the private sector is taxed.

Figure 8.7 Borrowing at concessional rates: government investment

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For this set of simulations, the no-repression case is represented by a simulation in which P equals zero (and tr is set at zero as well). Financial repression enters the model by assuming that P equals 0.02 and 0.05, respectively. Results of this set of simulations are displayed in Figures 8.6 to 8.10.

Figure 8.8 Borrowing at concessional rates: government consumption

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Figure 8.9 Borrowing at concessional rates: inflation

Financial repression stemming from a higher reserve requirement for formal private banks In the base model we have assumed that the reserve requirements for formal banks (h ) are only 5 percent (see Table 7.4). In this last f

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Figure 8.10 Borrowing at concessional rates: private wealth

set of simulations we assess the implications of a higher reserve requirement for formal private banks. This is done by comparing simulation results for the case where the reserve requirements are as in the base model with simulation results where the reserve requirements are set at 20 percent and 50 percent, respectively. Again, P and tr are set at zero for the no-repression and the repression

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simulation. The results of this set of simulations are displayed in Figures 8.11 to 8.15 The results of the Figures are summarized in Table 8.1. From Table 8.1 we can make the following observations. (1) All measures of financial repression studied in this chapter are detrimental to

Figure 8.11 Higher reserve requirements for formal banks: private investment

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Figure 8.12 Higher reserve requirements for formal banks: government investment

private capital accumulation, at least after some simulation periods. (2) As far as the effects on government capital accumulation and on government consumption are concerned the effects are positive for financial repression in the form of a tax on interest income on bonds and when the government borrows at concessional rates.

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Figure 8.13 Higher reserve requirements for formal banks: government consumption

Note, however, that the positive effect of these forms of financial repression on government investment declines during the simulation period. It may well be that, for a longer simulation period, the effects of these forms of financial repression on government investment become negative. On the other hand, the positive effects on

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Figure 8.14 Higher reserve requirements for formal banks: inflation

government consumption increase during the simulation period. In contrast to what would have been expected, financial repression in the form of higher reserve requirements for formal banks, especially when these reserve requirements become extremely high (50 percent), have a detrimental effect on government consumption and

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Figure 8.15 Higher reserve requirements for formal banks: private wealth

government investment. A reason for this seemingly somewhat strange result is that the high reserve requirements lead to a decline in private wealth. This decline in private wealth has a depressing effect on the non-bank private sector’s demand for formal demand deposits, which, ceteris paribus, has a negative effect on reserves

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becoming available for the government. In some simulation periods, the reserves becoming available for the government were even less when the reserve requirements ratio was 20 percent or 50 percent than when it was 0.05 percent (the no-repression case). Moreover, during the whole simulation period, it appeared that private income was lower in the repression cases than in the no-repression cases, which also has a negative effect on government investment and consumption. (3) With respect to inflation the effects are mixed. Financial repression in the form of a tax on bond interest income or when the government borrows at lower rates leads to a lower inflation rate compared to the no-repression case in the first simulation periods, but to a higher inflation rate later on. It is interesting to note here that the results with respect to taxing interest income on bonds are similar to the analytical and simulation results reported by Sussman (1991). On the other hand, a financial repression in the form of higher reserve requirements has a favorable effect on inflation during the whole simulation period. Here, it would seem that there is a trade-off between capital accumulation and inflation, in the sense that a lower rate of inflation is achieved only at the cost of a lower rate of capital accumulation, both for the private and the government sectors. Finally, for all forms of financial repression studied in this chapter, effects on private wealth are unfavorable. Table 8.1 Effects of financial repression: favorable (F), unfavorable (U) or neutral (N)

8.3 CONCLUDING REMARKS This chapter is a first attempt to analyze the consequences of government trying to raise revenues through financial repression.

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For this purpose we use the simulation model, developed in Chapter 7, and consider three such policies. While there are differences in the outcomes of the different policies, nevertheless we can make some general observations. First, that such policies are always detrimental to private capital formation, while the effect on government expenditures, both investment and consumption, is somewhat repression-measure specific. Even here the overall effect on public capital formation tends to be relatively unfavorable. Second, for all repression measures the repression policies are conducive to lower rates of inflation in the first simulation periods. However, a tax on interest income on bonds and a lower borrowing rate for the government has an unfavorable effect on inflation in the longer run. Finally, financial repression policies always have a negative effect on private wealth. These observations have some obvious policy implications for financial liberalization. First, attempts to control inflation are necessary if full benefits of financial liberalization are to be realized. And second, that it would be desirable to investigate means of raising additional revenues alternative to financially repressive measures.

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9 SUMMING UP While non-optimizing models have their shortcomings, in our case the model has nevertheless helped us to address a number of issues currently prevalent in the literature on the effects of financial deregulation, in particular the deregulation of interest rates. Furthermore, it has allowed us to address these questions in an integrated framework. One of the more interesting implications of the analysis is the importance of using the integrated approach to portfolio selection and the consumption—saving decision. Regardless of the lack of the empirical strength of the relationship between savings and interest rates so often claimed as the grounds for treating the two decisions as being independent, our results clearly show that the implications of ignoring such simultaneous determination does great violence to the outcomes of the effects of interest rates effects. The framework used enabled us to bring together a number of different strands in the development literature which hitherto have not been considered relevant in the debate about the effects of financial deregulation. Here we are referring to the role of aid and its ‘fungibility’ and the analysis of government’s fiscal behavior in the presence of foreign aid. We found this integration to yield quite a few new insights. The simulation exercises based upon the analytical models yielded rich results. In particular they told us something about the current debate about the sequencing of liberalization policies as well as the sensitivity of the effects of deregulation to changes in economic agents’ behavior. While not explicitly analyzed in the text, these sensitivity tests are clearly relevant to understanding what might happen in the developing countries as they pass through different stages of development. The simulations about the implications for the real variables when the government tries to use financial repression to raise revenues also shed light on this relatively new area. The various policy conclusions derived in the different chapters speak for themselves, but we would like to reiterate one point—

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namely, that for a proper appreciation of the role of interest rate deregulation we need to simultaneously consider the role of the various markets and the agents identified in Chapter 7. We believe that our analysis can be fruitfully extended in several directions. Our treatment of the external sector is obviously rudimentary. For example, we do not carry out a detailed analysis of the implications of foreign borrowings versus foreign aid. We pay virtually no attention to the implications of interest rate deregulation for revenue potential from seigniorage. It could be quite interesting to extend the model by explicitly allowing for this aspect. One could certainly handle expectations better. We have not explored the implications of rational expectations. One could easily point out additional possibilities. What does come out, both from the analytical as well as from the simulation chapters, is the message that interest rate deregulation is not the panacea that it is cracked up to be. But at the same time financial repression seems to have identifiable costs too. This raises the question whether there isn’t an optimal degree of financial repression in all its manifestations. This question is not examined here. But we hope that our results have offered enough reasons to suggest that such an analysis is warranted, and that the extreme views about financial deregulation in general and interest rate deregulation in particular are simply not warranted. As is so often the case the truth may well lie somewhere in between.

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NOTES

2 THE BASE MODEL 1

2

3

4

In fact, real disposable income equals y minus taxes plus net interest receipts. For simplicity we ignore net interest receipts since an increase in the deposit rate normally leads to an increase in the lending rate which affects net interest recepits in opposite directions. Moreover, in this chapter it is assumed that taxes are exogenous. Finally, it is assumed that real non-interest income is not influenced by changes in the deposit rate. The latter assumption follows from our neglect of the supply side. Our assumptions imply that real disposable income is exogenous and hence not influenced by changes in the deposit rate (for a similar assumption, see Morisset, 1993). The use of the nominal rates of return and expected inflation as separate arguments in the asset demand equations and the consumption function needs an explanation. The usual convention is to use pre-tax, ex-ante real rates of return, but this is an overly restrictive practice (as pointed out by Parkin et al. (1975)). It implies that the effects of a 1 percent increase in real interest rate, whether caused by a 1 percent increase in the nominal rate or by a 1 percent decrease in the expected rate of inflation, are identical. However, there is nothing in a priori reasoning why this should be so. At the very least, this should be treated as a testable hypothesis. Consequently, the approach taken in this chapter is to include the various rates of return in nominal terms and expected inflation as separate arguments, it being understood that the coefficient of expected inflation represents a composite coefficient. While the theoretical arguments developed here are not affected, whether we use nominal or real rates of return, once we make appropriate assumptions about what is happening to the expected rate of inflation, in empirical work, it would be more appropriate to use the specification proposed here. Jappelli and Pagano (1994) explicitly focus on the role of liquidity constraints for consumption and savings behavior of households. In their three period overlapping generation model a lessening of liquidity constraints leads to an increase in consumption and hence a decrease in the savings rate. Jappelli and Pagano (1994) empirically confirm this possibility for a sample consisting of OECD countries and some developing countries. Note that we ignore net interest receipts (the change in real bank profits), since we assume, in line with Morisset (1993), that the change in real bank profits is not influenced by changes in the deposit rate.

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NOTES

5 6

Again we ignore net interest receipts. It is possible that under extreme conditions this may be negative; for example, if (1+α2α43)<α3, in which case α3 will have to be sufficiently greater than unity, a highly unlikely possibility. 3 ROLE OF FOREIGN AID AND THE GOVERNMENT

1 2

∆L was not included in Heller’s utility function. In g most studies in this field, target values for these variables are dependent on one period lagged variables which, in our one period model of this chapter, do not affect the results anyway. 4 THE ROLE OF INFORMAL FINANCIAL MARKETS

1 2

3

4

Seibel and Parhusip (1994) describe an experiment in Indonesia which tried to develop a semi-formal financial sector. With respect to the reserve requirements for the formal banks our assumption is in line with most neostructuralist and McKinnon-Shaw models (Fry, 1988, p. 110). In contrast to these models we also take into account that the informal banks may hold reserves. Again, for reasons of convenience, we abstract from interest payments on credit extended to the private sector and from interest receipts from demand deposits. Moreover, we abstract from interest receipts on reserve requirements. This implies, for example, that we do not take into account that reserve requirements of the banking system may drive a wedge between the deposit and the loan rate. In the simulation chapters we will come back to this. Using Table 4.1 it can be derived that ∆Lg=∆R+∆Ru=hf∆m+ hu∆u. The difference with Chapter 2 is that now reserves and hence government borrowing is exogenous, whereas in Chapter 2 reserves and government borrowing are endogenously determined by the government budget constraint. 5 ALLOCATIVE EFFICIENCY AND FINANCIAL DEREGULATION

1

2

3

This chapter only considers allocational effects and abstracts from all scale effects. Therefore we have to assume that formal and informal banks do not hold reserves. Although this assumption does not correspond to real life, it is not relevant for the analysis in this chapter. We abstract from interest receipts and interest payments of the formal and informal banking sectors since borrowing and lending rates are linked so that the effect of changes in the deposit rates on net profits of the banking sector are minor. See Van Wijnbergen (1983a, 1983b) for a similar approach.

169

NOTES

4

Adding the budget constraint of both sectors yields: y d,1 +y d,2 + ∆L u,1 +∆L u,2 +∆L p=C 1 +C 2 +∆m 1 +∆m 2+∆u 1 +∆u 2 +∆k 1 +∆k 2 . The budget constraints of the banking sectors are: ∆L p =∆m 1 +∆m 2 and ∆Lu,1+∆Lu,2=∆u1+∆u2. Hence, ∆ k1+∆k2=yd,1+yd,2- C1-C2=constant, since disposable income and consumption are exogenous. 7 SOME SIMULATION RESULTS

1 2 3 4

5

6 7

This variable could also represent gold or the stock of land. It may be seen as a composite of highly substitutable assets, which serves as an inflation hedge. Note that in contrast to our base model, for reasons of convenience, the nominal rates of return and the expected inflation are not included as separate arguments in the asset demand equations. The starting value of real net wealth is defined as W-=b +k + m +u +f -1 -1 -1 -1 -L -L . 1 p-1 u-1 Note that normally consumption of fixed capital is introduced in the definition of disposable income of the private sector. For pragmatic reasons we, however, decided not to take consumption of fixed capital into account in disposable income, but to subtract it from savings in order to calculate the increase in net wealth. Since depreciation is exogenous and assumed to be equal before and after an interest rate deregulation our assumption does not substantially affect the results. Since we are only interested in net exports (i.e. exports minus imports), we do not take into account effects of changes in income on exports and/ or imports. In fact, we assumed that an increase in income affects real exports and real imports (in domestic prices) likewise. We applied formal stability analysis to a specific version of the model. The model appears to be stable at the knife-edge, meaning that the stability is quite sensitive to rather small changes in some of the parameters. They are defined as follows: elascap=((kp,a-kp,b)/kp,b)*(im,b/(im,a-im,b)) elascapg=((kp,a-kp,b)/kp,b)*(im,b/(im,a-im,b))

8

where kp,a=the stock of physical capital of the private sector after the increase in the deposit rate; kp,b=the stock of physical capital of the private sector before the increase in the deposit rate (the base deposit rate); kg,a=the stock of physical capital of the government sector after the increase in the deposit rate; kg,b=the stock of physical capital of the government sector before the increase in the deposit rate im,b=the base deposit rate; im,a=the deposit rate in the alternative model and hence im,a-im,b=the increase in the deposit rate. All other elasticities are defined similarly. We did a simulation for a longer time period as well. From that simulation it can be seen that eventually an interest rate deregulation also has a positive effect on capital of the government. This, however, occurs only after a very long simulation period.

170

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178

INDEX Adams, D.W. 52, 56; and Graham, D.H. 55; and Vogel, R.C. 55 aggregate demand/supply 106, 114 AK model 8–9 Aleem, I. 57 allocative efficiency 5, 9, 59, 69–70; advanced sector 70, 76, 78, 79, 81–4; application of model to 75–9; backward sector 69, 70, 75–6, 78, 79, 81–2, 84–5; empirical evidence 71–5; Galbis model 70–1; measurement of improvement in 79–85 Aryeetey, E. and Hyuha, M. 50, 53 asset demand 93; equations 14, 28– 9, 61, 77, 100, 110–11 assets 14–15, 17, 26, 76, 78, 88, 101, 104, 170; liquidity of 12 balance of payments 107 banking sector 11, 12, 17, 38, 39, 41, 44, 75, 103–5, 107; application of base model to 87–94; assets 17; consolidated 3; and credit constraints 89–93; efficiency 2, 6, 86, 87–94; formal 129, 153, 157, 169; informal 127, 169; liabilities and reserves 63; not credit constrained 93–4; Viaene model 87; see also formal private banks; non-bank private sector base model, adding-up restrictions 16, 19, 37, 62, 65, 81, 83, 101, 145; alternative simulations 116– 41; applications of 34–8, 60–3, 67–8, 75–9; base simulation 111–12, 113–15; behavioural equations 13–14, 38, 77–9; distinctive features 10; notations and definitions 97–8;

presentation 11–19; significance 15–16; simulation strategy 107– 13; symmetry conditions 21–2; symmetry restrictions 16 Basu, K. 55 Bencivenga, Valerie R. and Smith, Bruce D. 8, 9, 58–9 Bernanke, Ben S. and Gertler, Mark 8 Berthelemy, J-C. and Varoudakis, A. 1, 8 Bhaduri, A. 55 Binh, T. and McGillivray, M. 32, 33, 35 black markets 51 Blinder, A.S. and Solow, R.M. 102 Boone, P. 34 borrowing 102, 147, 160, 167;endogenous/exogenous 169 Bottomley, A. 56 Bourguignon, F. et al. 10, 12 Bouwman, F.J.A. 54 Brainard, W.C. and Tobin, J. 14 Brillembourg, A. 13 budget constraints 17, 18, 27, 30–4, 37, 63, 75–7, 87, 98, 101, 102, 144, 169, 170; consolidated 12– 13 budget deficits 1, 3, 18, 21, 22, 35, 142; endogenous/exogenous 6, 7, 96 Buffie, E.F. 58, 65 Buiter, W.H. 10 capital 113–14, 128, 140–1, 143;accumulation 87, 142, 146, 160, 164; formation 165; gains/ losses 103; no substitution with deposits 120; private 120;stock 116; transfer of 69 Capoglu, G. 71–2, 86

179

INDEX

Cassen, R. 31 central bank 103, 104 Chandavarkar, A.G. 55 Chang, D. and Jung, W.S. 57, 61 Cho, Y.J. 69, 71–2 Christensen, G. 52, 54 coefficient of efficient allocation 59–60 competition, monopolistic 57 complementarity hypothesis 4, 17, 21, 23–4, 65 concessional loans/aid 3, 30 consumption 14–15, 29, 56, 61, 90, 93, 106, 143–4, 146, 162, 170; exogenous 64; not affected by real interest rates 124–7; private 34, 110–11 consumption—savings decision 2, 3, 5, 7, 10–12, 14–16, 20–5, 64– 7, 96, 101, 109, 127, 142, 166; exogenous 38 credit 21, 64, 76; allocation 71–3; effect 25; formal 82, 113; informal 1, 2, 4, 6, 55, 57, 69, 78, 80–1, 82, 103; needs 1; private 2, 15; programs 55; rationing 10, 59; supply of 19– 21; tied 53 credit constraints 78, 101, 109, 120– 4; and private sector 89–95 crowding-out effects 2, 3, 13, 25, 41, 43, 48, 102, 110, 132 curb markets 51; and interest rate deregulation 58–60 Das-Gupta, A. et al. 57 De Gregorio, José 8, 9 De la Fuente, Angel and Marin, José Maria 1, 8, 9 deposit rate 14, 38, 60, 61, 65, 67, 76, 84, 90–1, 92, 168, 169, 170; effective 6; effects of increase in 19–21; nominal 112 deposits 103, 120; demand 75, 80, 88, 94; formal/informal 81–5, 98, 111, 163; no substitution with capital 120 depreciation 101, 170 deregulation 7, 30, 41–2, 84, 86, 166

Diamond, D. and Dybvig, P. 58 direct/indirect effects 14, 18, 21, 22–3, 25 disposable income 14, 38, 61, 77, 89, 91, 92, 98, 148, 168, 170 domestic purchasing power 100 exchange rates 105–6, 107, 111, 135 exports 105–6 external sector 11, 18–19, 105–6 Fazzari, S.M. et al. 15 feedback effects 42, 46, 49, 138 Fernando, N.A. 55 financial markets, formal 50, 54, 57; imperfections 10; intermediation 9, 65, 66, 70, 86 financial repression 7–8, 146–7, 166–7; caused by taxing interest income on government bonds 147–51; due to government borrowing at concessional rate 151–6; simulation strategy 147; stemming from higher reserve requirement for formal private banks 157–64 fiscal response studies 45, 46 fixed-fund associations 53 forecasting 110 foreign, assets 12, 13, 29; currency 100, 101 foreign aid 1, 2, 3, 30, 61, 102, 108, 133–6, 138–40, 143, 167; as additional source of funds 34–8; application of model to 34–8; effects of increase in 47–9; endogenous 42–5, 110; exogenous 18, 19, 38–42; fiscal response to 31–4, 145; fungibility of 4, 7, 31, 32, 33–4, 35, 37, 46, 49, 96, 166; higher 133–7 formal private banks 103, 104; see also banking sector; non-bank private sector Fry, M.J. 1, 169 Galbis, V. 5, 69–71, 79, 80

180

INDEX

Gang, I.N. 33; and Khan, H. 32, 34 Gertler, Mark and Rose, Andrew 8 Ghatak, S. 56 Ghose, A.K. 55 Gibson, H.D. and Tsakalotos, E. 1 Giovannini, A. and De Melo, M. 8, 146 government sector 11, 18, 101–3, 107, 116; bonds 8, 12, 13, 18, 19, 26, 29, 34, 39–40, 42–5, 48, 61, 98, 102, 112, 113; borrowing 8, 13, 18, 21, 25, 32, 33, 39, 41, 44; consolidated 3; consumption 32, 34, 40–1; equations 143–5; exogenous expenditures 34–8; investment 110, 110–13, 112, 114, 133, 163 Graham, D.H. 54 grants 34 Greenwald, Bruce C. and Stiglitz, Joseph E. 8 Greenwood, Jeremy; and Jovanovic, Boyan 8, 9; and Smith, Bruce D. 8 group lending 53–4 growth rate 31 Gupta, K.L. 10, 18, 32, 34, 142; and Islam, M.A. 30 Gylfason, Thorvaldur 8 Heller, P.S. 31–3, 46, 145, 169 Hoff, K. and Stiglitz, Joseph E. 55, 57 imports 105–6, 145 income 12 inflation 6, 7, 13, 29, 65, 100, 101, 106–8, 113, 115, 133–6, 143, 146, 164, 168 informal finance 4–5, 108; application of model to 60–3, 67–8; competitive view 55–7, 61; as highly efficient 56; impact of interest rate deregulation on 63– 7; imperfect information paradigm 57–8; monopoly view 54–5, 61; role of 50–1; theories on working of 54–8; types of 51–4

interest rates 10, 13–15, 18, 19, 21, 23, 30, 34, 40, 55, 56, 69, 102–3, 109, 112–13, 127, 148, 160, 164, 166, 169; deregulation 1, 2, 4, 5, 7, 41–6, 58–60, 70, 85, 91, 96, 109–10, 113, 115, 117–22, 128, 131, 133, 140, 142–3, 167, 170; elasticities 112, 116 investment 1, 15, 30–3, 37–8, 45–6, 70, 73, 81, 106, 127, 143–4, 146; complementarity between government and private 137–41; as credit constrained 120–4; decline 41; effects of aid on 47– 9; effects on 2; exogenous 61; negative effects 39–40, 42, 43, 94, 121, 161; positive effects 41, 43– 4, 46, 94, 122, 161; see also private investment Iqbal, F. 56 Jappelli, Tullio and Pagano, Marco 7, 9, 168 Keynesian 60 Khan, H.A. and Hoshino, E. 32, 34 labor-leisure choice 13 Lagrange multiplier 35 Lensink, R. 30 Levine, R. 8, 9 Lewis, Jeffrey, D. 142 liabilities 88, 104 Liang, M-Y. 59, 60 liquidity constraints 7, 9, 10–13, 15, 20, 38, 61, 66, 108, 168 loans 29, 34, 51–4, 55, 78, 82–3, 102, 103–4, 110, 112, 133, 144, 169; occasional 51–2; rates of 6, 151–5; short-term 66–7 McKinnon, R. 1, 3, 7, 17, 25, 55, 58, 65, 66, 67, 120, 169 Marquez, J. 111 Miracle, M.P. et al. 50, 53 mobile bankers 53 money wage 60 moneylenders 4, 54, 55

181

INDEX

Montiel, Peter J. et al. 50, 51, 66, 104, 142 Morisset, J. 2, 10, 11, 17, 24, 29, 78, 127, 142, 168; model 26–8 Mosley, P. 33; et al. 30 multiplier effect 21

productivity 69, 70, 85 profits, monopoly 56, 58; rate of 72 Purvis, D. 14

Nagarajan, G. et al. 50, 52 negative substitution effects 19–20, 65, 81, 94 neostructuralists 2, 56, 58, 61, 64, 65, 67 non-bank private sector 8, 12–16, 61–3, 87, 98–101, 104, 107, 147– 8, 152, 163; see also banking sector; formal private banks Onchan, T. 50 optimizing/non-optimizing models 1 Owen, P.D. 3, 14–15, 16, 28–9, 101; and Solis-Fallas, O. 55, 57 Pack, H. and Pack, J.P. 34 Pagano, Marco 1, 8 Papanek, G. 30 parallel markets 51 Park, Y.C. 69 Parkin, M.J. et al. 168 pawnbroking 52–3 physical capital 12, 13, 29, 38, 87, 94, 98, 108, 170 Pissarides, C.A. 10, 14 portfolio allocation 10, 11, 16, 17, 20, 22, 24, 25, 65, 67, 96; decisions 78, 85; selection 2, 3– 4, 5, 7, 13–14 positive income effect 19–20, 65 private investment 5, 6, 89–91, 106–14, 133–6, 142–3; equations 26–8; and financial liberalization 21–5; negative effects on 90; and (no) wealth effects 91–3; see also investment private sector 11, 21, 38, 116, 129, 155; consolidated 3; and credit constraints 89–93; not credit constrained 93–4; portfolio 108; supply of credit to 19–21

Rahman, A. 56 Rao, J.M. 55 rates of return 13, 108; effective 86, 88–9, 94–5; internal 87; marginal 72; nominal 86, 94, 100–1, 168, 170 reforms 7 regular money lending 52–3 reserves 103, 104–5, 129, 131, 169; higher in formal banking sector 127–33; requirements 1, 109–10 Riddell, R. 30 Roe, A. 51 Romer, P. 1 ROSCA 53–4 Rosenzweig, Mark R. and Wolpin, Kenneth I. 15 Roubini, Nouriel and Salai-Martin, Xavier 8 Saint-Paul, Gilles 8, 9 Saleem, S.T. 55 Sanderatne, N. 50 savings 1, 13, 15, 31, 67, 125, 170; exogenous 10, 11; groups 53; private 101 Schiantarelli, Fabio et al. 1, 71–2 Schrieder, G.R. and Cuevas, C.E. 54 segmented markets 51 Seibel, H.D. and Parhusip, U. 169 Shaw, E. 17, 25, 55, 58, 65, 66, 67, 120, 169 Siamwalla, A. et al. 57 Singh, K. 56 Smith, G. 14 stability analysis 170 Stigler, G.J. 56 Stiglitz, Joseph E. 69; and Weiss, A. 10, 57 stock-adjustment process 29 structuralists 109, 127–8, 132 substitutability 23–4, 108, 120 supply sector 108 supply-side effects 11

182

INDEX

Sussman, O. 8, 9, 108, 146, 164; and Zeira, J. 8 tax 8, 32, 33, 34, 39, 45–7, 61, 102, 143–6, 148–50, 155, 160, 164, 168; endogenous 38; exogenous 34–8; increase 41 Taylor, L. 56, 58 Teranishi, J. 82 tontines 53 transfer payments 102, 105, 135, 143 Tsiang, S.C. 58, 59 underground markets 51 unorganized markets 51 utility function 31, 32–3

Varoudakis, Aristomène 8 Viaene, J.M. 86, 87 Von Pischke, J.D. 54, 56 Wai, U.T. 50, 55, 82 wealth effects 1, 13, 14–15, 22, 23, 29, 65, 67, 77, 78, 90, 94–5, 100, 101, 108, 109, 118–19, 120, 125– 6, 132–4, 142, 143, 163, 165, 170; absence of 91–2; accumulation 87; higher in investment equation 127; as only affect 92–3 White, H. 30, 31, 33–4, 46 Wilmington, M.W. 56 zero-profit condition 104, 154

Van Wijnbergen, S. 2, 56, 58, 134– 5, 169

183