Financial Sector Development & Inequality: A Development Policy Perspective

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School of Management University of Tampere (Finland)

Department of Economics University of Fribourg (Switzerland)

Master’s Thesis

European Master in Public Economics and Public Finance March 2012

FINANCIAL SECTOR DEVELOPMENT & INEQUALITY

A DEVELOPMENT POLICY PERSPECTIVE

S

INI

L

ASSILA

Supervisors:

Hannu Laurila University of Tampere Solène Morvant-Roux University of Fribourg

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TIIVISTELMÄ

Tampereen yliopisto Johtamiskorkeakoulu

LASSILA, SINI: Financial Sector Development & Inequality:

A Development Policy Perspective Pro gradu -tutkielma: 65 sivua, 3 liitesivua

Kansantaloustiede Maaliskuu 2012

Avainsanat: rahoitussektori, tulonjako, pääomamarkkinat, mikrorahoitus

Modernien kehitystalouden teorioiden mukaan pääomamarkkinoiden epätäydellisyydet estävät tuloerojen tasoittumisen pitkällä aikavälillä. Markkinoiden epätäydellisyydet kuten maantieteelliset esteet ja informaatioasymmetriaongelmat rajoittavat vähätuloisten pääsyä rahoitusmarkkinoille.

Tutkielma käsittelee rahoitussektorin kehityksen ja tuloerojen suhdetta kehityspoliittisesta näkökulmasta teoriaan ja empiirisiin tutkimuksiin nojaten.

Rahoitussektorin kehitys jaetaan sektorin syvenemiseen eli kokonaiskasvuun ja laajenemiseen eli palvelujen ulottumiseen vähätuloisille kotitalouksille ja luottorajoitteisille yrityksille. Viime vuosikymmenten aikana rahoitussektorin laajentumista on tutkittu lähinnä mikrorahoituslaitosten tarjoamien palveluiden kautta. Mikäli mikrorahoituksella on köyhyyttä lieventäviä vaikutuksia, voidaan sen katsoa tasoittavan tuloeroja. Toisaalta tuloerot voivat myös kasvaa, mikäli mikrorahoitus aiheuttaa polarisaatiota vähätuloisten keskuudessa. Rahoitussektorin syvenemistä tutkitaan tasapainomallien avulla, laajenemisen kohdalla painopiste on mikrotutkimuksissa.

Rahoitussektorin kehittämisstrategioiden yhteydessä tarkastellaan lisäksi rahoitusmarkkinoiden liberalisoinnin tulojaollisia vaikutuksia.

Tarkasteltujen tutkimusten mukaan rahoitussektorin kokonaiskasvu tasoittaa tuloeroja.

Mikrorahoituksen hyvinvointivaikutuksille löydetään vain heikkoa näyttöä ja havaitut vaikutukset hyödyttävät usein vain osaa lainaajista, mikä viittaa tulojen polarisointivaikutuksiin.

Rahoitussektorin liberalisoinnista hyötyvät ensisijaisesti pienet luottorajoitteiset yritykset. Pitkällä aikavälillä pienten yritysten kasvu voi johtaa työn kysynnän lisääntymisen kautta tuloerojen tasoittumiseen, mutta vaikutukset riippuvat maakohtaisista erityispiirteistä.

Rahoitussektorin kehittymisen tulee perustua vahvoille instituutioille, jotka tukevat luottotietojärjestelmien ylläpitoa, uskottavia luotto-oikeuksia sekä optimaalista rahoitusmarkkinoiden sääntelyä. Subventoidusta luotosta tulisi siirtyä säästämispalveluiden kehittämiseen, tukien ohjaamiseen köyhien perustarpeiden tyydyttämiseen sekä rahoitussektorin laajentumiseen tähtäävien teknologisten innovaatioiden tukemiseen. Rahoitusmarkkinoiden uudistusten toimeenpano kehitysmaissa on usein hankalaa heikon hallinnon vuoksi. Taloudellisen ja poliittisen vallan liiallinen keskittyminen voi johtaa uudistuksiin, joilla on tuloeroja kasvattavia vaikutuksia.

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1. INTRODUCTION

The trend of rising income inequality is an economic paradox affecting both developed and developing economies. In developing countries income disparities are the most apparent and severe, and governments have been either powerless or unwilling to properly address them. Redistributive policies are not seen as a viable solution in low-income countries with large budget deficits and large proportions of population living in poverty. Moreover, inequality has a substantial impact on macroeconomic outcomes. Many researchers have shown its negative effect on growth, although opposing results exist as well. Nevertheless, any impact on the overall development of an economy motivates to study the underlying factors that either amplify or reduce distributional differences. In addition, income inequality carries considerable political and social implications beyond economics. Large differences in income distribution are intolerable by society in the long run, provoking social unrest.

Reducing income inequalities implies a disproportionate increase in the incomes of the poor relative to the incomes of the rich. How can this shift be attained in developing countries in a way that is not detrimental to overall economic development? Several development theorists have introduced models linking together finance, development and inequality. According to the Kuznets hypothesis inequality is assumed to be most severe during the early phases of development of an economy. At the first stages of development, only the group with the highest income is able to save and earn a reasonable return on investments. Along with changes in the sectoral structure of the economy, inequality is assumed to increase until a certain point after which differences in income begin to decrease and the economy starts to converge. Although there are several historical examples supporting the Kuznets hypothesis, a similar evolution has not been witnessed in developing economies. The Kuznets hypothesis has been applied to study the links between financial sector development and inequality, but economists have also developed alternative theories, predicting either convergence or non-convergence. Modern theories suggest that capital market imperfections are the underlying cause to persisting intergenerational inequalities, which in turn have an impact on the aggregate output of an economy.

Financial sector development can affect inequality in different ways. It can bridge the gap between differences in opportunities by providing low-income households a chance to save and to invest in

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their children’s education, making them qualified to enter the labour market and thereby increase household welfare. Financial development can also contribute to growth opportunities of small enterprises, which in turn raise the demand for labour and thus indirectly affect household welfare.

On the contrary, financial development can at some level be considered to raise income inequality as talented individuals gain access to higher returns – a factor that has been neglected in the mainstream theories of inequality assuming individuals are identical in terms of talent.

The principal objective of this paper is to understand how financial sector development affects levels of inequality in low and middle-income countries. What are the most significant financial market imperfections, how are they linked to the distribution of income and in which ways are they addressed? We explore the links between financial development and inequality by differentiating between financial deepening and broadening and discuss the direct and indirect channels of impact.

Does the size of the financial sector matter? Is microfinance a viable financial broadening strategy?

Can it reduce inequalities by alleviating poverty of does it exclude and create disparities among low-income populations? What is the role of financial liberalisation in broadening financial access to small enterprises and what are the distributional outcomes of such reforms? With the support of theory and evidence, we will discuss the role of governments in supporting inclusive, credible and well-functioning financial markets.

The paper is structured as follows. The opening section introduces the theoretical framework to the study of inequality and financial development. We compare traditional and recent theories of inequality and take the predictions of modern theory as a premise to assess the role of wealth distribution and capital market imperfections in persisting inequalities. We provide an in-depth outlook on different barriers preventing low-income households and small enterprises from entering the formal financial system and discuss issues related to measuring financial access. Alongside a brief panorama on the current financial intermediation scene we take a look at the origins of subsidised credit and the evolution of financial sector development policies.

In our empirical review we examine the distributional impacts of financial development by bringing together parts of evidence from a variety of studies. First we focus on financial deepening in order to assess the indirect impacts of financial development driven by the growth of the financial sector.

Evidence on the link between economic growth and financial development has been well documented, but the effect of growth on income distribution is not as clear. This indirect effect is assessed through general equilibrium models. Does overall financial development lead to the rich

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being richer while the incomes of the poor remain the same or does financial development cause a trickle-down effect which compensates for the rise in inequality? Which effect is stronger, the overall growth of GDP per capita or the change in income distribution?

We continue by discussing financial broadening strategies with a particular focus on microfinance programs and their impact on inequality. Contrary to general equilibrium models assessing the trickle-down effects of financial deepening, the focus of impact analysis of financial broadening is on micro studies. It is plausible to presume that targeting financial services to the poorest parts of the population would raise their incomes while the incomes of other groups are assumed to remain unchanged, leading to reductions in inequality. However, how much do we know about the true impact of microfinance on the incomes of the poor? Does microfinance raise the incomes of program participants and moreover, how are non-users of the services offered by microfinance institutions affected? The matter is closely related with the notion of outreach, defining who and what proportion of the poor are actually served by microfinance institutions. If microfinance has an impact on the incomes of the poor but excludes parts of the population belonging initially to the same income group, microfinance can have a detrimental effect on inequality by increasing inequalities among the poor. We review the main findings of eight impact evaluations applying a lowest threat to validity selection criterion and make prudent assessments on the directions of distributional impacts. Moving on from quantitative analysis to a debate on which structure of inequality is least tolerable by society turns into a question of subjective value judgement.

We also deal with the distributional impacts of financial liberalisation by referring to an empirical study using calibrated data on the Thai economy. Do the short and long-term impacts of financial liberalisation follow a pattern? At first glance financial liberalisation, leading to an expansion of growth opportunities of small enterprises, would seem to have a positive indirect impact on low- income households through an increased demand for labour. A closer look at the net welfare gains of financial liberalisation and the way benefits spread in the economy raises the question of how winners and losers of financial liberalisation are distinguished.

Finally, we concentrate on policy implications and the problems of implementing financial reform in the developing country context. Institution building is featured as the primary determinant of any successful financial sector policy. We suggest a new role for microfinance as a financial broadening mechanism and go through the priorities of financial sector reform in addressing market and government failure in developing countries. As in the implementation of any development policy,

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the quality of governance has a central role. Wealth and power distributions can prevent or slow down welfare enhancing financial reform in countries where economic and political power is overly concentrated. Ex ante inequality can also lead to risks being allocated in an unfair way causing further deterioration in inequality. How should political economy factors be understood and what are the possibilities of overcoming them in the implementation of fair financial sector policies?

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2. INEQUALITY AND IMPERFECT CAPITAL MARKETS

2.1. Inequality, Finance and Development: Theoretical Framework

During recent years, income inequality has been on the rise all over the world. According to the United Nations Human Development Report (2010, 72-73), the most significant increases have taken place in former countries of the Soviet Union, which started with relatively low levels of income inequality. The majority of the population were state employees and although inequality existed, it was not measurable in terms of income. Similar tendencies are visible in former central planned governments of Asia, notably China and Vietnam, Mongolia being the only exception.

Other parts of Asia have experienced increasing inequality due to the contrast between fast industrial growth in urban centres and low productivity of agriculture in rural areas. In Sub-Saharan Africa inequality rates have decreased since the recession in 1980s but risen in the long run. As for Latin America and the Caribbean, the reasons behind income inequality have for long been tied to the distribution of land and education, high fertility rates of the poor and higher returns of educated workers. However, during the past couple of decades many countries, such as Brazil, Ecuador and Paraguay, have been able to successfully narrow down the differences between the rich and the poor by well-designed redistributive policies. Nevertheless gaps remain wide.

The study of inequality has its roots in the early stages of development economics but as a concept, inequality is not uniform. In economic literature, the concepts overlap. From the perspective of economics, inequality generally refers to the distribution of income or wealth. While income inequality signifies differences in income that individuals earn during their lifetime by engaging in income-generating activities, the distribution of initial wealth is, as we will see in the following chapters, one of the root factors explaining inequality in the developing world. When broadened to a more general level of society, the concepts of income inequality and wealth inequality generally go hand in hand with inequality of opportunity, which can be further narrowed down to economic opportunity. Inequality can also take the form of social discrimination due to characteristics such as gender, ethnicity and age. In this paper we tackle inequality from the perspective of unequal distribution of wealth and income, which eventually brings us to address issues linked to the distribution of wealth and power.

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Traditional welfare economics based on utilitarism provide little insight to the study of inequality.

In fact, the utilitarist social welfare function is defined as the sum of individual utilities, ignoring interpersonal comparison (Sen 1973). A concern for the harmful consequences of unequal income distribution has put pressure on defining measures that incorporate inequality in general welfare assessments. These measures provide diverse but potentially misleading insight on the structure of income distribution in an economy.

The most widely used measure of income inequality is the Gini coefficient, derived from the Lorenz curve. Household cumulative income is plotted against the number of households with income ranging from the lowest to the highest. The Gini coefficient is calculated as the ratio of the area between the Lorenz curve and a 45-degree curve of perfect equality to the entire area under the curve of perfect equality. From this definition we see that the Gini coefficient ignores relative differences among income groups. Therefore we cannot say much about the actual degree of poverty on the basis of the value of the Gini. Another factor that could be considered as a shortcoming to the use of the Gini coefficient, particularly in comparative studies, is that it only accounts for relative differences in the distribution of income in an economy. In other words, it ignores absolute distributional differences between economies. It is thus possible that two economies that represent two completely different stages of development in terms of GDP per capita may have the same Gini value. If special attention is to be given to poverty, another way to measure income inequality is to divide the income groups of an economy into quintiles. The share of income earned by the poorest 20 per cent gives more understanding on the magnitude of inequality as a social issue affecting developing economies. Income quintiles combined with Gini values provide a satisfactory benchmark for the study of inequality.

Theoretical literature on the relation between inequality and macroeconomics has evolved significantly through the phases of modern economic thought. Predictions provided by theory on the connections between financial development and inequality are nevertheless quite contradictory.

Traditional theories suggest an inverted U-shaped pattern with rising inequality during the first stage of development, decreasing as the economy develops further. More recent theories indicate diverse development paths stemming from underlying inequalities and capital market imperfections that may prevent the economy from developing. According to these modern theories, economies with more imperfect capital markets have higher levels of inequality. These models thus suggest a

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negative linear relationship between inequality and financial sector development (Clarke et al.

2003, 4). The basic hypotheses of the alternative theories are presented in Figure 1.

Figure 1. The inverted U vs. the linear hypothesis.

The first studies on inequality in economic theory date back to Keynes (1936) associating income distribution with aggregate demand. Kuznets (1955), on the other hand, was the first to study the connection between economic growth and income inequality. With the introduction of the inverted U-hypothesis, Kuznets set a foundation for further study on inequality. According to the hypothesis, inequality rises with the early stages of development. This is reasoned by the sectoral structure of an economy and the higher productivity of the modern sector compared with the traditional agricultural sector. As in developing economies savings are possible only at significantly higher relative income levels than in developed economies, the concentration of assets at the top of the pyramid is even more evident. Due to low productivity at the agricultural sector, differences in income are smaller the bigger the agricultural sector. As the modern sector continues to grow at the expense of the traditional sector, inequality rises. Eventually, as growth attains more significant levels and more people shift from the traditional to the modern sector, differences in productivity decrease, income starts to spread more widely and inequality gradually begins to decrease. The inverted U-hypothesis thus implies a shift of an economy characterised by the majority being poor to an economy where the majority is rich, through a phase of high inequality where large shares of rich and poor coexist.

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Building on the Kuznets hypothesis, Greenwood and Jovanovic (1990) present a similar pattern of development and inequality with regard to the development of the financial sector. During the first stages of development, the financial system of the economy is nearly nonexistent but slowly growing as capital allocation takes place. Little by little a financial structure starts to emerge as the economy approaches intermediate stages of development. This leads to increases in growth and savings rates, and inequality between low and high-income groups grows wider. The financial system gradually develops into a strong sector where financial intermediaries effectively allocate capital to its most productive use. Finally, the economy reaches a stage where inequality stabilises, savings rate falls and the economy converges towards a new steady state. (Greenwood & Jovanovic 1990, 1076-1079.)

The dynamics of such non-linear development process is based on the intertwined aspects of economic growth, institutional development and the distribution of income. It highlights the importance of financial intermediaries in facilitating trade by providing individuals an opportunity to obtain both a higher and a safer return on investments. Firstly, information gathered by financial intermediaries allows investments to flow to their most profitable use. Secondly, a well-developed financial system provides a means to pool risks, which in turn contributes to a more efficient allocation of resources. Pooling of risks is made possible by financial intermediary coalitions, which impose a fixed cost that low-income groups cannot afford. Assuming that both income groups have the same savings rate, the income gap widens as the wealthier group earns higher returns for investments with higher risk. Holding for the assumption of economic growth, the excluded low-income groups eventually enter the intermediated sector given that the entry cost is fixed. Over time the expected return across individuals converges to the highest possible return, leading to a decrease in income inequality and to a long-run stabilisation. (Greenwood & Jovanovic 1990, 1078.)

Despite the theoretical appeal of the inverted U-hypothesis, empirical evidence supporting it, particularly with regard to developing countries, has been weak. As a response, the models of Banerjee and Newman (1993) and Galor and Zeira (1993) propose alternative mechanisms. These modern theories present capital market imperfections as the fundamental factor in persisting inequalities. By determining occupational choices or human capital investment decisions, the models demonstrate how lack of access to finance may slow down growth in the long run.

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Banerjee and Newman (1993) formulate a theory of occupational choice combining underlying inequality with capital market imperfections. Wealth distribution is endogenous and defines how individuals make their occupational choice between entrepreneurship, self-employment, waged work and subsistence. A certain level of inequality is required for employment to arise. Due to imperfect capital markets only wealthy individuals have the possibility to borrow and to invest in indivisible technologies with high return. The occupational structure, determined by the distribution of wealth, defines the behaviour of individuals in terms of saving and risk bearing which further shapes the pattern of a new distribution of wealth. By exploring the evolution of the patterns through which labour services are exchanged, the model seeks to find an explanation to why certain economies prosper while others remain in stagnation.

The model assumes that all individuals begin with an endowment of one unit of labour and a certain level of initial capital that equals the size of inheritance received from their parents. This leads to individuals choosing an occupation that determines their use of labour and investment of capital. As for capital, there are three ways to invest. The first option is a divisible, safe asset yielding a fixed return that does not require labour. As an alternative, the individual can choose to invest in a risky, indivisible project requiring one unit of labour but no skill to operate. Finally, one can invest in monitoring technology permitting aggregate production by enabling the entrepreneur, investing one unit of labour, to monitor the actions of a certain number of individuals. These options result in two types of production: an individual choosing either self-employment and running projects for himself, or running projects for someone else against a wage while being monitored. The projects themselves are considered similar in technology, differences lie namely in the contracts defining distribution of output. (Banerjee & Newman 1993, 278-280.)

In the model of Banerjee and Newman, the labour market is competitive with wage equalizing supply and demand. Entrepreneurial production defines the demand for labour, while the supply of labour comes from occupational choices of agents of the economy. Concerning credit markets, the only reason for an agent to borrow is to finance self-employment or entrepreneurship. However, obtaining a loan is dependent on the initial wealth of an agent assuming that enforcement of loan contracts is imperfect and an agent will have to provide all his wealth w as collateral in order to obtain a loan L to finance a project. He now has the possibility to flee with the money, costing him the loss of collateral wr. The borrower pursues his investment projects that yield the return V(L). If he decides to flee, the lender does not find him with a probability 1−π and the borrower avoids paying Lr. In the case that the borrower is caught, he would face a non-monetary punishment of F

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that would enter in his utility function. Therefore, fleeing would yield a payoff of

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V(L)−πF while repaying the loan would yield

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V(L)+wr−Lr. The borrower will thus default if

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wr+πF <Lr, which leads to lenders only lending amounts satisfying

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L≤w+(πF/r). (Banerjee & Newman 1993, 280-281.)

This condition reveals the limitations low-income individuals face on credit markets as it implies that only agents with a certain level of initial wealth have the possibility to obtain a loan. According to Banerjee and Newman, the distribution of initial wealth goes on to define the occupational choices of agents in the economy. In fact, abilities and preferences are assumed to be identical and have no effect on choice of occupation. For employment contracts to be possible in the first place, a certain level on inequality is required. In a case of perfect equality, the choice would be left between self-employment and subsistence. A minimum wealth level of w* is necessary to obtain a loan large enough to enable self-employment, whereas in order to become an entrepreneur, the required minimum wealth level rises to w** entailing costs resulting from employee monitoring. If all agents in an economy were above w*, everyone would be self-employed. Employment contracts arise only if a part of the population is under w* and another part above w** and in the case that all agents were under w*, there would be only subsistence. The equilibrium level of wages is determined by the initial distribution of wealth and the occupational structure of the economy.

(Banerjee & Newman 1993, 281-283.)

Banerjee and Newman (1993) extend the static equilibrium model of the theory of occupational choice into a dynamic framework in order to examine the long-run development path of an economy. Unlike the majority of dynamic studies on the distribution of income and wealth, Banerjee and Newman construct a non-linear model, where individual transitions are dependent on aggregate variables. When moving on from a stationary study, the distribution of wealth is assumed to change over time, which in turn causes changes in the prevailing wage. If the ratio of very poor people to very rich in an economy is high, the development process dries out resulting in low employment and low wages, whereas an economy with a lower poor-rich ratio will likely converge to a steady state with high employment and high wages.

Similarly to Banerjee and Newman, Galor and Zeira (1993) rely on financial market imperfections as the basis of their theory on income distribution and suggest that an unequal distribution of wealth can lead to diverse growth paths. With a two-period equilibrium model (see Annex for a mathematical presentation), they investigate the macroeconomic outcomes of income distribution

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by studying the effects of investment in human capital. Individuals live for two periods and in the first period, either invest in education or work as unskilled. In the second period, they work as either skilled or unskilled, depending on whether they had acquired human capital or not. Under the assumption of imperfect capital markets, the interest rate for borrowing is higher than the interest rate for lending. Furthermore, assuming that individuals differ only with regard to initial wealth, it is the inheritance from the previous generation that determines whether an individual has the possibility to invest in education.

Galor and Zeira (1993, 40-43) extend the model into a long-run equilibrium in order to illustrate the dynamics of wealth distribution. Groups with higher initial wealth keep investing in human capital and earning higher returns as skilled labour, whereas groups with low initial wealth are bound to continue working as unskilled and leaving modest inheritance for generations to come. Hence, according to the model, an economy with an imperfect capital market combined with an initially uneven distribution of income will remain unequal in terms of wealth and not attain growth rates of similar economies with a more equal distribution of wealth. Depending on the distribution there are several possible growth paths and long-run equilibria. The equilibrium the economy will converge to depends on the initial distribution of wealth; logically an economy with little initial wealth ends up poor while an economy with large initial wealth ends up rich. However, if wealth is very concentrated, even an economy with a large initial amount of wealth will end up poor. Thus, the distribution of wealth is central from a macroeconomic perspective, affecting output and investment both in the short run as in the long run.

Clarke et al. (2003) combine modern hypotheses of finance and inequality with the idea of Kuznets (1955) on the sectoral structure of the economy as a determinant of inequality. According to this augmented Kuznets hypothesis, sectoral structure has an effect on the way financial development affects inequality. Following Kuznets (1955), the modern sector is characterised as a high-income sector with higher inequality as opposed to the low-income agricultural sector with low inequality.

Inequality will thus be higher in economies where the modern sector is large. Furthermore, inequality is amplified if talented individuals can earn even higher returns with better access to finance. Therefore economies characterised by a larger modern sector and a deeper financial sector will have higher levels of inequality. (Clarke et al. 2003, 4-6.)

So far we have looked at different theories suggesting that economies will either converge towards higher income and smaller inequality or that inequality will persist. According to the modern

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theories of development and inequality, non-convergence is due to capital market imperfections.

We have seen how capital market imperfections can limit the occupational choice of agents with low initial wealth or their investment in human capital. Moreover, sectoral structure can play a role in defining the relationship between financial development and inequality. The motivation of this paper lies on the assumption of imperfect capital markets as the root cause of persisting inequality.

In the next section we will look into some empirical evidence on the theoretical predictions presented. However, before that we open up the concept of capital market imperfections by discussing the common restrictions concerning access to finance.

2.2. Barriers to Financial Access

Large parts of the population are underserved by the financial sector and regulatory frameworks for financial intermediaries are often insufficient in order to attain efficiency in the sector. Financial inclusion can be translated into an absence of price and non-price barriers to financial services (Demirguc-Kunt et al. 2008, 22). When analysing access to financial services, we look at the demand of both households and enterprises. At the household level, access to financial services is related to the possibility to deposit savings in order to reduce vulnerability to shocks, to attain consumption smoothing, and to obtain credit for income-generating activities and investments in human capital and health. As for enterprises, access to financial services is crucial in order to make investments for future growth and to insure against risks. With growth, enterprises create employment and this way the impacts of finance are spread more widely to society. In this section we will turn to discuss the different dimensions of access to financial services: measurement of access to finance, market frictions and barriers limiting access as well as obstacles to entrepreneurial activity.

In order to attain measures of financial inclusion relevant to analysis and policy prescriptions, it is important to begin by differentiating between access to and use of financial services. Access is the supply of credit while the use of credit is the intersection of supply and demand that would theoretically adjust according to the price of financial services. Households and firms decide whether at a certain price, they will or will not use financial services. Voluntary exclusion can be due to several reasons; certain households not using financial services may see no need for it or might exclude themselves voluntarily due to cultural or religious reasons (Claessens 2006, 210.). In

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fact, political, cultural and religious factors in the context of financial inclusion have only recently gained more attention (see e.g. Shipton 2010).

Moreover, the coexistence of formal and informal financial markets affects the demand of finance.

In the case that informal credit is available from friends or family members, formal financial institutions may be regarded unnecessary. However, due to certain barriers that prevent or complicate access to financial services, a large part of the population is excluded involuntarily.

(Claessens 2006, 210.)

When looking at involuntary exclusion, it is important to understand the variety of potential reasons behind it. Large parts of the developing world are underserved by the banking sector due to insufficient income or high risk of the customer. Other reasons behind exclusion are discrimination, contractual or informational frameworks required in the use of services and price and product features of the services available. (Beck et al. 2009, 119-123.)

The biggest problem in analysing access to finance in a reliable manner is the lack of data, a challenge confronted by the entire field of development economics. For instance, it is relatively simple to find out the number of existing bank accounts, but as many individuals and firms hold multiple accounts, the figure does not reveal the actual number of individuals with an account. Not all financial institutions or regulators track this data and household surveys, although best fitted for this purpose, are still insufficient in scale. Therefore, measures must be kept simple. (Beck et al.

2009, 123.)

Beck et al. (2009, 123) list three main approaches to measuring access to financial services: number of users of basic financial services, quality of financial services available as subjective assessments of firms, and physical and cost barriers to access. None of the approaches comes without problems.

Measuring access in mere numbers does not take into account the quality or price of the services, whereas subjective assessments on quality pose problems of comparison. Finally, some barriers to access are easier to measure than others and therefore can result in misleading policy responses.

Despite the challenges discussed, policy makers have understood the importance of reliable quantitative data and more resources are starting to be channelled for this purpose. In fact, the scope of data collection, although still highly insufficient in many countries, is constantly improving.

Financial Access 2010, a report evaluating the worldwide post-crisis state of financial inclusion

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published by the Consultative Group to Assist the Poorest (CGAP 2010), presents indicators on access to savings, credit and payment services in regulated financial institutions. The report uses survey data on financial regulators such as central banks and bank supervisory agencies from 142 countries.¹ According to the report survey, 51 per cent of financial regulators collect at least some data through one survey instrument (household surveys, survey of financial institutions, survey of firms). GCAP reports aggregated data that was collected on a number of key financial access indicators: the number and value of both deposit and loan accounts, the number of banks branches, automated teller machines (ATMs) and point-of-sale terminals and other measures of the use of financial services. Figures 2 and 3 provide insight on differences in financial access between high and low-income countries in terms of numbers of loan and deposit accounts and physical accessibility to bank branches and ATMs.

Figure 2. Number of loan and deposit accounts per 1000 adults in high and low-income countries.

Source: CGAP (2010)

Regarding the number of deposit accounts in commercial banks, the median per 1 000 adults in developing countries was 737 compared to 2 022 in high-income countries. The corresponding medians for loan accounts were 258 in developing countries to 701 in high-income countries.

1 Questionnaires were sent to 151 economies, excluding small islands and economies at war, covering over 94 per cent of the world’s population. The response rate was 94 per cent. (CGAP 2010.)

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Figure 3. Number of ATMs and bank branches per 100 000 adults in high and low-income countries.

Source: CGAP (2010)

As for bank branches the median per 100 000 adults in developing countries was 10 versus 32 in high-income countries. The corresponding figures for the number of ATMs were 29 for developing countries relative to 94 in high-income countries. (CGAP 2010.)

Due to the wide lack of micro-level data and the difficulties in collecting compatible cross-country data on users, researchers have come up with solutions combining existing research results with data on number of accounts and financial depth indicators. These so-called headline indicators approximate for example the proportion of the population with access to a bank account with a non- linear function of the number of accounts in banks or microfinance institutions and the average size of these accounts. Data from the World Bank show low access to financial services in many developing countries where less than half of the households had a bank account, whereas the equivalent proportion in developed countries was over 90 per cent. (Beck et al. 2009, 123-124.)

If capital markets functioned perfectly, there would be no need for financial intermediaries. In fact, these institutions exist to reduce various market frictions. Market frictions are mainly due to attributes of low-income customers and the operational environment of financial institutions.

Firstly, screening and monitoring of borrowers and processing savings and other services lead to

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transaction costs that do not always correspond proportionately to the size of the transaction. Fixed costs exist not only at the client level but also at the institution level when putting in place accounting systems and purchasing e.g. legal services. Moreover, some of these costs may arise from the system level in the form of regulatory costs and infrastructure. Most of the fixed costs carried by the financial institution are independent of both the number of clients and the number of regulated institutions operating in the area. High transaction costs associated with smaller loan sizes bring up the interest rate that the lender has to charge to attain cost-recovery. This in turn increases the probability of default on a loan. Another set of market frictions is caused by limits to idiosyncratic risk diversification. This induces lenders to add a risk premium in the interest rate, which pushes the interest rate even higher. Limits to risk diversification are mainly due to insufficient markets for insurance products. (Beck 2007, 112-113.)

Another major factor behind capital market imperfections is information asymmetries, resulting in problems of adverse selection and moral hazard. Adverse selection occurs when lenders are unable to differentiate between borrowers who are likely to be more risky than others (Armendáriz &

Morduch 2005, 7). Lenders would charge riskier borrowers higher interest rates than safer ones in order to compensate for a higher probability of default. However, not knowing which of the customers are the more risky ones raises the interest rates for all borrowers leading to a rise in the overall interest rate. Higher interest rates then make services unaffordable to some groups and prospective customers representing low risk are adversely excluded. Adverse selection thus leads to credit rationing. Not knowing which risk type the borrowers represent, suppliers of credit adjust the quantity of services, leading to an equilibrium with excessive demand (Stiglitz & Weiss 1981).

Adverse selection is not the only information asymmetry problem associated with capital markets.

Moral hazard is caused by the fact that lenders cannot ensure that borrowers pursuing their investment projects are putting in maximum effort required for the project to be successful. The problem arises also as lenders cannot be sure about the honesty of borrowers, and the possibility of the borrower escaping without repaying the loan may discourage the lender to issue the loan in the first place. Both information asymmetry problems are amplified due to difficulties of enforcing contracts in regions without a strong judicial system. (Armendáriz & Morduch 2005, 7.)

In addition to the market frictions discussed above, some barriers to access are geographical or contractual. Long geographical distances prevent clients located in remote areas from physical access to bank branches or ATMs. Geographic barriers can to some extent be overcome by

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providing services via internet or mobile phones but in general, access to most financial services still require a visit to a branch. (Beck et al. 2009, 125.) In some areas, however, certain innovations have shown promising potential in lowering barriers. Examples of such innovations are handheld computers for a faster approval of micro loans and prepaid cards for small transactions (Claessens

& Perotti 2005, 12).

Other barriers constraining access to finance can arise from the requirements specific to the financial institution. Normally at least some document of identification is required when opening a bank account, yet in developing countries most people living in remote areas lack such documents (Beck et al. 2009, 125). Moreover, most banks refuse to deal with customers without an official address (Claessens & Perotti 2005, 10). In addition to administrative constraints, many financial institutions require a minimum deposit when opening an account. Some institutions also impose administrative fees excluding those who cannot afford to pay. (Beck et al. 2009, 125.)

How do barriers to financial access translate to our concern about inequality? The link between barriers to financial services and inequality has been explored by a cross-country study conducted by Mookerjee and Kalipioni (2010). As a measure of inequality the study uses Gini coefficient data provided by UN-Wider. The proxy for financial development used is the number of bank branches per 100 000 people in a sample of 70 developed and developing countries. To explore the relationship between barriers to access, the study analyses barriers to establishing a savings account and barriers to obtaining a loan, measured by the minimum amount needed to open a bank account and the number of locations to submit a loan application. Controlling for aggregate income, macroeconomic stability, trade orientation and infrastructure², the results conclude that higher access to financial services benefits the poor and mitigates differences in income distribution.

Therefore the study supports micro focused measures of financial development. Barriers to opening a savings account were found to increase income inequality whereas the results regarding the second proxy on locations for submitting a loan application were mixed.

At the enterprise level, barriers to financial access are only part of the obstacles that aspiring entrepreneurs face. Most barriers to starting a business are associated with a high level of bureaucracy and corruption, both common characteristics of developing countries. Obstacles to

2 Aggregate income was proxied by GDP/capita, macroeconomic stability by inflation, trade orientation by the share of exports and imports of total GDP and infrastructure by the number of telephones per 1 000 people.

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establishing a business in the formal sector can arise from the number of necessary licences or complicated procedures of different agencies handling these licenses, as well as from high fees and taxes. Some barriers are more informal including frequent inspections by authorities expecting bribes, and unequal regulatory and contractual enforcement procedures biased in favour of establishes businesses. (Claessens & Perotti 2005, 4-5.)

Why are formal entry barriers a problem typical to developing countries? According to Pigou’s public interest theory of regulation (1938), regulation is a way for governments to protect the society from market failures, such as monopolies, low-quality products and negative externalities.

However, in reality the regulatory structure in developing countries is far from this ideal and highly corrupt. It is common that regulations do not serve the purpose of social efficiency but rather benefit industries and public authorities. As specified by Stigler (1971) regulations increase the market power of established players of the industry by creating barriers for new entrants, all this at the expense of the consumer. Another strand of public choice theory, known as the tollbooth theory (Shleifer & Vishny 1998), emphasizes the rent-seeking behaviour of politicians and bureaucrats instead of the established industry, considering regulations principally as a means for collecting bribes.

From the point of view of the tollbooth theory, wealth distribution can be a significant factor in determining economic opportunity, simply because regulatory barriers can be overcome with sufficient amounts of money. Claessens & Perotti (2005, 6) therefore see lack of finance not only as a barrier in itself but also as an indirect barrier to entrepreneurship. Easier and more affordable access to finance would equalise opportunities for low-wealth individuals by providing a possibility to overcome some of these formal barriers.

Weaknesses in the legal system and high enforcement costs can also be a major issue limiting access to finance. However, enforcement costs do not tell the whole story as the lack of services provided to low-income groups touches also services that do not include risk of default.

Enforcement costs can be high due to institutional failures, which at least speculatively could be corrected by reform. Shortcomings in the legal system also include weak property rights, which in turn complicate formal contract enforcement. (Claessens & Perotti 2005, 11.) The central barriers to financial access affecting both households and enterprises are summarised in Table 1.

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Barrier type Examples Primary object High transaction costs Screening and monitoring Households

Geographical barriers Distance between branch and customer

Households

Information asymmetries Adverse selection, moral hazard

Households and enterprises

Administrative barriers Lack of identification document or address;

Licences and heavy

administrative processes

Households and enterprises

Legal barriers High enforcement costs, weak property rights

Enterprises

Table 1. Barriers to financial access.

To sum up, limits to financial access that according to the modern theories presented in chapter 2.1 link finance and inequality together are caused by various factors characteristic to developing economies. Cost barriers and information asymmetries are in the core of credit constraints of low- income households while geographical and contractual barriers further complicate the setting. Some barriers can be measured with the help of various proxies but others can be examined only at a theoretical level. In contrast, starting a business in the formal sector faces barriers to entry that can in fact be more constraining than other barriers to access. However, formal barriers to entry can at the same time be lowered with easier access to finance. This acknowledged, development policies have striven to promote better accessibility to finance but have nevertheless not been able to so without avoiding some pitfalls of misconception regarding the nature of financial sector development.

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2.3. Financial Intermediation and the Evolution of Financial Inclusion Policies

In this section we have looked at the consequences of capital market imperfections on the patterns of wealth distribution and economic development in theoretical light. We have also discussed barriers to financial access as the underlying reason behind financial exclusion. To conclude this section on capital market imperfections we are left with the question of what has been done to lower financial barriers of low-income populations. The objective of the chapter is two-fold: firstly to give a brief overview of the financial institutions offering services to excluded parts of the population and secondly to shed light on the evolution of financial inclusion policies implemented during the past decades.

So far we have dealt with financial inclusion from the perspective of demand. Financial intermediaries i.e. the suppliers of financial services to credit-constraint households and enterprises differ considerably in terms of target market, structure and operations. Hence, their performance cannot be evaluated by the same criteria. The natural dividing line categorising financial institutions would be between commercial banks and non-banking financial institutions. However, especially in the developing country context, the operational boundaries between institutional types may be less obvious as many financial institutions that started as non-governmental organisations have, in the pursuit of financial sustainability, transformed into profit-seeking banks yet still operate towards a social objective.

Formal financial institutions can be either regulated or non-regulated. GCAP (2010) classifies regulated financial institutions into four categories: commercial banks; cooperatives, credit unions and mutuals; specialised state financial institutions; and microfinance institutions. Commercial banks operate with a full banking licence and offer retail-banking services to the competitive market. Cooperatives, credit unions and mutuals represent an institutional form that is neither fully commercial nor non-commercial, providing financial services to the members who also own and control the institution. Specialised state financial institutions, on the other hand, are government institutions supporting economic development by offering savings, payment and deposit services to the public and operate as postal banks, government savings banks, SME lending facilities, agriculture banks and development banks. Microfinance institutions, by the definition of CGAP (2010, 45), provide credit and other financial services to the poor by adapted lending

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methodologies, mainly by group lending. Despite this classification, many commercial banks as well as cooperatives and state financial institutions extend their services to microfinance. However, target groups as well as lending strategies vary significantly between countries and institutional types.

Although the microfinance movement has experienced its greatest spotlight during the past couple of decades since the foundation of the Grameen bank in Bangladesh, the idea of offering credit to low-income populations is not so new. State-owned agricultural development banks were introduced after the Second World War to respond to the need of supplying long-term agricultural credit or to meet the needs of high-risk customers that the traditional banking sector had no incentive or means to target. Development banks received the majority of their funding from international donor agencies, national or provincial governments and central banks. However, dependence on public funds in providing credit at subsidised interest rates led to insolvencies of most development banks. One of the main reasons to why development banks could not successfully attain their goals was their strong focus on agriculture that led to problems arising from factors such as geographic barriers, an unfavourable policy environment towards the agricultural sector as well as material and informational features characteristic to agriculture. After repetitive capitalisations development banks eventually lost donor support and practically all rural credit supplies dried out. (Gonzalez-Vega & Graham 1995, 10.)

Gonzalez-Vega (2003, 7-10) analyses the developments of rural finance over the past three decades.

The failure of state-owned development banks that were once the primary provider of agricultural credit left behind a shattering infrastructure and took down organisations and specialised credit programs. The greatest loss was not so much the downturn of fiscal transfers but the organisational collapse, as creating institutions is difficult especially in the rural setting. The decline of development banks left behind a large unmet demand, represented mainly by small and medium- sized borrowers with good credit histories. Although representing only a small proportion of the total rural population, these borrowers had established strong relationships with development banks, which implied significant social costs as they practically disappeared from financial markets.

Losses from default were mainly due to the rent-seeking behaviour of large influential borrowers leading to the disintegration of organisational infrastructure and ruling out the only possibility small borrowers had for obtaining credit. Moreover, development banks failed in establishing sufficient screening and monitoring practices, having negative effects on repaying culture. Operating costs and losses from default and inflation could not be covered by sufficient interest rates and portfolios

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lost their value. These factors demonstrate how excessive political interest turned out to be harmful for state-owned development banks, especially in countries of poor quality of governance.

As a response to the inability of development banks to serve their original purpose, agendas of financial liberalisation gained more attention. Liberalisation policies were based on the hypothesis of McKinnon (1973) and Shaw (1973), analysing the effects of reducing financial restrictions behind repressive policies. The main contribution of the hypothesis was that removing interest rate ceilings and leaving them to be determined by market forces would increase savings and investment and lead to economic growth.

The fact that the decline of rural credit programs occurred simultaneously with structural adjustment programs and the implementation of financial liberalisation policies gave a chance for certain interest groups to advocate for a return to earlier regimes. However, most development banks were highly unsustainable before the implementation of any financial reform, but it was the reforms bringing existing problems to daylight. A return to earlier protectionist policies would neither have solved the mistakes of the past, nor would it by any means have helped to boost the private supply of financial services in rural areas. (Gonzalez-Vega 2003, 9-10.)

Based on the persisting demand for financial services that state-owned development banks failed to meet in a sustainable way, different types of financial intermediaries have slowly come to expand services to excluded clients. Microfinance institutions, both commercial and subsidy-based, have engaged in the broadening of the financial sector whereas the effects of financial liberalisation reforms can be analysed both at the intensive and at the extensive margin.

As we have seen, capital market imperfections are a fundamental obstacle for developing economies in overcoming inequality that has its origins in the unequal distribution of wealth. In this section we have looked at capital market imperfections from three viewpoints. We started with a theoretical framework linking together finance and inequality and discussed the consequences of capital market imperfections in persisting inequalities. We analysed barriers to financial access as reasons behind imperfect capital markets. Finally, we looked at efforts to alleviate capital market imperfections from the perspective of institutions and policies.

Financial development has certainly taken leaps forward during the past decades, but how much has financial sector development actually contributed to the welfare of the poorest parts of the

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population? Have financial inclusion policies come anywhere near to correcting the market in a way that would expand investment opportunities, whether occupational as in the model of Banerjee and Newman (1993) or educational as in the model of Galor and Zeira (1993)? In the next section we will turn to discuss the impacts of financial sector development through existing empirical evidence by looking at the effects of aggregate growth of the financial sector on inequality (financial deepening), and the consequences of broadening financial access to households. Finally, we will shed light on the distributional impacts of a financial liberalisation reform as a means of financial deepening by broadening financial access to credit constraint enterprises.

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3. DISTRIBUTIONAL IMPACTS OF FINANCIAL SECTOR DEVELOPMENT

3.1. Financial Deepening

After a synthesis on the alternative theories on financial development and equality and an overview on access to finance, we will now turn to assess the impacts of financial development through the lens of existing empirical evidence. Financial development can be understood in two distinct ways, as deepening and broadening of the financial system. Financial deepening refers to the growth of the sector itself – the increase in the supply of financial services provided to the population.

Financial deepening does not give specific importance to low-income groups excluded from credit.

The widely used proxy to measure financial deepening is the value of credit by financial intermediaries to the private sector divided by GDP. Financial broadening, on the other hand, signifies the expansion of access to financial services, and more specifically, deals with the provision of direct access to credit for those formerly excluded from the formal financial system due to various credit constraints.

What is the real impact of financial deepening resulting from overall economic growth on inequality? The intuitive response would be that improvements in the quality of financial services offered to existing users, representing the high end of the income distribution, would cause a rise in inequality. However, when taking into account the indirect effects of financial deepening, benefits can spread to groups who are mainly excluded from finance and therefore it is the net impact that matters the most. If financial development benefits the economy as a whole, inequality remains unchanged. If financial development benefits mainly the rich, inequality rises. Decreases in inequality are only possible if financial deepening disproportionately benefits the poor population.

Many studies have been conducted on the relationship between financial development and growth and show a positive correlation between the two. However, the relationship between financial development and its impact on income distribution is more obscure. As discussed in the preceding section of this paper, no uniform theory on this relationship exists.

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According to the theories of Banerjee and Newman (1993) and Galor and Zeira (1993) reviewed in this paper, the poor population faces credit constraints creating market imperfections, which in turn lead into inefficiencies in capital allocation. From this perspective, financial development would reduce income inequalities by disproportionately lowering the credit constraints of low-income groups, thus implying an improvement in capital allocation. Greenwood and Jovanovic (1990), on the other hand, suggest a non-linear relationship between financial development and income distribution. At early stages of financial development, only the rich can benefit from financial markets whereas the poor still rely on informal sources of credit. Eventually, as the financial sector develops further, more people enter the formal financial system.

Clarke et al. (2003) examine empirically the relationship between income distribution and financial intermediary development in a panel data set of 91 developing and developed countries for the period 1960-1995. Clarke et al. use private credit as an indicator of financial development, i.e.

credit to private firms and households from banks and non-bank financial intermediaries over GPD.

The alternative measure used is claims on the non-financial domestic sector by deposit money banks divided by GDP, positively and significantly correlating with private credit. The variation in financial development measured by private credit in the sample is high, ranging from 5 per cent of GDP in Chile in the period 1970-75 to over 200 per cent in Japan in the period 1990-1995. (Clarke et al. 2003, 1, 7-8.)

Clarke et al. (2003) carry out tests on some hypotheses of the theories presented in this paper. The study examines the inverted U-hypothesis of Greenwood and Jovanovic (1990) and the linear hypothesis of Galor and Zeira (1993) and Banerjee and Newman (1993) suggesting a negative linear relationship between financial development and the Gini coefficient. Building on Kuznets’

intuition about the role of sectoral structure in explaining the relationship between development and inequality, the study also tests the augmented Kuznets hypothesis, i.e. that financial development could have a greater effect on reducing inequality in countries with a smaller modern sector. The hypothesis is based on the assumption that if particularly talented individuals can earn higher returns in the modern sector, these returns could be even higher when having access to finance. This in turn leads to higher inequality within the modern sector compared to the highest possible level of inequality in the traditional sector. (Clarke et al. 2003, 3-6, 15.)

According to the augmented Kuznets hypothesis, inequality is higher in countries characterised by a large modern sector and a deeper financial system compared to countries that have neither or only

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one of these elements (Clarke et al. 2003, 5-6). Further assuming a positive relationship between financial depth and the importance of the modern sector, Clarke et al. estimate the logarithm of the Gini coefficient with the following regression:

€

ln(GiniCoef_it)=α₀+ f(Finance_it)+α₂CV_it+ε_it,

where the focus is on

€

f(Finance_it) taking the form

€

α₁₁Finance_it+α₁₂Finance_it²+α₁₃Finance_it*Modern_it.

According to the Kuznets hypothesis, in order to get the shape of the inverted U, the coefficients

€

α11 and

€

α12 take values

€

α11>0 and

€

α12 <0. The augmented Kuznets hypothesis predicts a positive value for

€

α13. The control variables (

€

CV_it) of the regression consist of linear and squared terms of the log of real GDP per capita to control for a direct effect of economic development on inequality independent of financial intermediary development. Additionally, the regression controls for inflation rate, measures of government consumption, ethno-linguistic fractionalisation, and a measure of the protection of property rights. The effect of the above variables is not necessarily straightforward. For example, government spending can either decrease inequality by redistributing towards low-income groups or increase inequality if the rich use greater political power as a means to exploit the poor. (Clarke et al. 2003, 5-6, 8-10.)

Firstly, the results suggest that inequality is lower in countries with more developed financial sectors and therefore support the linear hypothesis. Secondly, a positive coefficient on the interaction between financial depth and value-added in the modern sector support the augmented Kuznets hypothesis, however, the coefficient is only statistically significant when private credit is used as a measure of financial depth. According to the results, financial sector development reduces inequality until the modern sector represents less than 99,6 per cent of GDP. An increase of 1 per cent of private credit reduces inequality by 0,3 per cent.³ Furthermore, when the share of private credit is over 14 per cent of GDP, an increase in the size of the modern sector increases inequality.

In short, financial development reduces inequality specifically in countries with small modern sectors, whereas growth of the modern sector increases inequality mainly in countries where the

3 This is measured at the mean for value added in the modern sector: 87,4 per cent of GDP (Clarke 2003, 14).

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financial system is more developed. Finally, no evidence is found to support the inverted U- hypothesis. (Clarke et al. 2003 12-15.) The tested hypotheses and results are summarised in Table 2.

Hypothesis Relationship Financial Development - Inequality

Support for Hypothesis Clarke et al. (2003) Inverted U

Greenwood & Jovanovic (1990)

Widening inequality followed by reductions in inequality

No

Linear

Banerjee & Newman (1993) Galor & Zeira (1993

Negative linear relationship:

financial development reduces inequalities

Yes

Augmented Kuznets hypothesis

Inequality higher when larger modern sector and deeper financial sector

Yes

(private credit as measure of financial depth)

Table 2. Results on the test of different theories on the relationship between financial development and inequality (Clarke et al. 2003).

All in all, the test finds empirical support for the linearity hypotheses of the theories of Banerjee and Newman (1993) and Galor and Zeira (1993) in the sense that financial intermediary development resulting in growth carries positive implications on income distribution; however, the effect is likely to be dependent on the structure of the economy (Clarke et al. 2003, 12-15).

Even so, as changes in the use of the Gini coefficient do not differentiate between absolute and relative changes, the study cannot provide insight on the effect financial development has on the lowest income group, but only on the economy as a whole (Clarke et al. 2003, 16). By contrast, an empirical study conducted by Beck et al. (2007) focuses on the income of this lowest quintile by evaluating the impact of financial development on changes in income distribution and changes in poverty – both absolute and relative. The study assesses income inequality by two measures: the Gini coefficient and the income share of the poor, measuring the income of the poorest quintile relative to total national income. The measure of absolute poverty used is the percentage of the population living on less than a dollar per day.