What is the relationship between the development of microfinance institutions and economic growth? Rose Barzilai* June 2016 Abstract
In this paper the direct effect of the development of microfinance institutions and economic growth is studied using an empirical approach. Various indicators of the development of microfinance institutions and control variables are used. Economic growth is regressed to one indicator in each regression with a bunch of control variables. The growth equation has been estimated using a pure cross-‐section sample by averaging among the 2001-‐2007 time dimension. From the regression results it can be concluded that the development of microfinance institutions is an important determinant of economic growth.
*Student BSc Economics and Business, specialization Economics and Finance, Faculty Economics and Business, University of Amsterdam, Amsterdam, The Netherlands.
Student number: 10572449. Supervisor: Rui Zhuo
Statement of originality
This document is written by Rose Barzilai who declares to take full responsibility for the contents of this document.
I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.
The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
Table of Content
1 Introduction……….4
2 Literature review……….…….……..………6
2.1 Microfinance institutions………..………..6
2.2 Theoretical review………..………..………..8
2.2.1 Microfinance institutions and financial development……….…….……….8
2.2.2 Financial development and economic growth……….….………..9
2.2.3 Microfinance institutions and economic growth……….……….…..11
2.3 Empirical results……….………….…….12
3 Data and Methodology……….……….………..………15
3.1 Data………..………15 3.2 Methodology………..……..……….……15 4 Empirical results……….…..……….18 4.1 Control variables……….18 4.2 Explanatory variables………19 5 Conclusion……….……..……….……21 6 References……….……..……….……23 7 Appendix……….……..……….……27
1. Introduction
“The poor stay poor, not because they are lazy but because they have no access to capital” Milton Friedman quoted. Hermes and Lensink (2007) stated that many people in developing economies remain poor because of the lack of access to credit. Lending to this group is not profitable because the poor cannot put acceptable collateral and the costs of screening and monitoring the activities and of enforcing their contracts are too high (Hermes and Lensink, 2007).
Microfinance has been introduced as a policy option to reduce poverty. It can be defined as financial instruments such as loans, savings, insurances and other instruments that are only for clients that have been excluded from the formal banking sector. The majority of the borrowers use the financial instruments to finance self-‐employment activities and taking loans as small as $75, repaid over several months or a year (Morduch, 1999). James Wolfensohn, president of the World Bank, pointed out that helping 100 million households means that 500-‐600 million poor people could benefit (Morduch, 1999). The first microfinance institutions have been established in the 1980s such as the Grameen bank founded by Muhammad Yunus.
The central question of this paper is what is the relationship between the
development of microfinance institutions and economic growth? Plenty of literatures focus on the relationship between microfinance institutions development and financial
development. Also the link between financial development and economic growth is a popular research question as well. This may suggest an indirect effect of microfinance institutions development on economic growth via the financial development, but not much work has been done to prove the direct effect. Therefore, this research aims to provide
some evidence to the direct impact of microfinance institution development on economic growth.
Barr (2005) argues that microfinance plays an important role in financial development. Hermes, Lensink and Meesters (2009) state that the relation between microfinance institutions may be positive or negative. Moreover, from the theoretical and empirical literature, it is expected that there is a positive link between the financial
development and economic growth. However, the evidence of the direct effect of microfinance institutions on economic growth is limited supported by the literature. However, the study offers no definitive evidence that micro enterprises directly drives economic growth (Leegwater and Shaw, 2008).
In this paper, the direct link between microfinance institutions development and economic growth is studied using an empirical approach. This researches defines various indicators of microfinance institutions development and regresses the economic growth to one indicator in each regression with a bunch of control variables. A cross-‐section data set is constructed by 30 developing countries where microfinance got extensively applied during the time period 2001-‐2007. Then the relevant coefficients are estimated by OLS.
From the regression results it can be concluded that the development of
microfinance institutions is an important determinant of economic growth. The variables MFI, ASSETS and GLP have a positive significant effect on GDP growth. However, the variable BOR does not have a significant effect on economic growth. This may be caused by the small number of countries and the critical aspects that were not taken into account.
The rest of the paper organizes as follow. Section 2 gives an overview of the relevant theoretical and empirical work done so far. Section 3 describes the data selection and the
methodology for the empirical analysis. Subsequently, Section 4 gives an overview of the empirical results. In section 5 an answer to the research question is formulated.
2. Literature review
In this literature review the relationship between the development of microfinance institutions and economic growth will be examined. First, details about microfinance institutions is provided. Second, a review of theoretical work on how the rising of
microfinance affects growth of a country is conducted. Finally, the empirical results on this topic are summarized.
2.1 Microfinance institutions
Microfinance institutions are financial intermediaries that provide small collateral-‐free loans, saving deposits, insurances, remittances, leasing and money transfers to low income citizens that are used to support their family business or productive activities (Armendariz de Aghion & Morduch, 2005). These tiny family businesses financed with microfinance loans improve their knowledge and skills, health, housing and have alternative employment opportunities. The microfinance institutions have been introduced in many developing countries like, the Grameen Bank in Bangladesh, Banco Sol in Bolivia and Bank Rakyat in Indonesia. The number of microfinance institutions increased from 618 in December 1997 to 3133 in December 2005. During the same period the number of people who received credit from these
microfinance institutions increased from 13.5 million to 113.3 million (Hermes and Lensink, 2007).
There are two approaches of microfinance: the institutional approach and the welfarist approach. Each approach differs in how the services of microfinance institutions should be derived, on the technology they should use and on how their performance should
be assessed. The microfinance industry is dominated by the institutional approach (Brau and Woller, 2004). The institutional approach focuses on serving clients who are underserved by the formal financial systems and want to achieve finance self-‐sufficiency. Brau and Woller (2004) concluded that for the provision of financial services to low income citizens
institutional sustainability is needed and that financial self-‐sufficiency was a necessary condition for institutional sustainability. Morduch (2000) estimated that only 1 percent of the microfinance institutions are currently financial self-‐sustainable and no more than 5 percent would ever be. In contract, the welfarist approach focuses on improving the well-‐ being of participants and focus on reaching the poorest and help alleviate poverty (Bhatt & Thang, 2001). Their methods are intended to determine whether the institutions are achieving poverty reduction. Welfarists claim that microfinance institutions can achieve sustainability without financial self-‐sufficiency (Brau and Woller, 2004). This debate between the institutionists and the welfarists is called the “microfinance schism” (Morduch, 2000). It looks like two nations divided by a common language (Woller and Dunford, 1999). According to Ledgerwood and White (2006) many studies found a strong link between sustainability and outreach. Debates on the achievement of social as well as financial goals are hindered by a lack of information on social performance. Therefore, there has been tendency to emphasize the financial objectives of microfinance. The social objectives seem to cause over lending by not providing microfinance to the right people (Zeller and Meyer, 2003).
Microfinance institutions operate with two different forms of microfinance programs which are joint liability group lending and individual-‐based lending (Hermes and Lensink, 2007). The joint liability group lending is the most well-‐known innovation in the microfinance programs. Microfinance institution focus on social collateral via group lending, because borrowers do not have physical capital (Brau and Woller, 2004). There is a joint
responsibility for the loan which results in lower levels of default. When one member is not able to repay the loan, the other members are required to cover the loan, otherwise they lose access to future loans. Also the dynamic incentives, regular payment schedules and collateral substitutes provide successful repayments (Gutiérrez-‐Nieto et al., 2007). 2.2 Theoretical review
The growth of microfinance institutions has an impact on financial development, which will be summarized first. Next, the growth effect of financial development in general will be examined. Combining these two branches of literatures gives the indirect channel of
microfinance institutions development on economic growth. Then, researches on the direct link between microfinance institutions and economic growth will be reviewed.
2.2.1 Microfinance institutions and financial development
Barr (2005) argues that microfinance plays an important role in financial development. First, microfinance institutions might achieve financial self-‐sustainability and attract private capital flows, which are attractive because governments have to spend less on development aid. Second, microfinance institutions might be an important development strategy in the face of weak, incompetent or corrupt governance. Third, microfinance institutions can strengthen the banking system and therefore promote the financial development. Last, MFI’s play an important role in the domestic demand for the better governmental and market institutions required for financial development. Barr (2005) suggests that thinking about financial development from a microfinance point might increase the probability that financial development contributes to poverty alleviation.
According to Hermes, Lensink and Meesters (2009) microfinance institutional performance is related to financial development. This relationship may be positive or negative. There are different arguments for the positive relationship. First, financial
development leads to an increase in commercial banks and their services, therefore the loans of microfinance institutions may also increase. Furthermore, microfinance institutions may be stimulated to reduce costs and increase efficiency of the operations by the increased competition. Second, there may be positive spill-‐over effects like improving skills caused by commercial banks. Third, financial development helps improving the efficiency of
microfinance institutions because of the sophisticated regulation and the supervision of financial institution (Hermes, Lensink and Meesters, 2009).
The main argument for the negative relationship is the substitution effect. Borrowers may substitute their loans from microfinance institution for loans from commercial banks because of the lower costs, the flexibility and the larger amount of loans that can be borrowed (Hermes, Lensink and Meesters, 2009).
2.2.2 Financial development and economic growth
The existence of the correlation between financial development and economic growth has been researched first by the economic historians Cameron (1967), Goldsmith (1969) and McKinnon (1973). Financial development causes a more efficient allocation of capital and therefore improves macroeconomic performance (Levine, 2005). More developed countries have more developed financial markets. Therefore, it is expected that there is a positive link between the financial development and economic growth (Kahn and Senhadji, 2001).
Levine (2005) reviewed theoretical and empirical work on the relationship between microfinance institutions and economic growth. Levine (2005) researched that better developed financial systems ease external financing constraints and this alleviates the mechanism through which financial development influences economic growth.
There are five functions that may have an effect on saving and investment decisions. First, mobilizing and pooling savings leads to higher return activities with positive implications for
economic growth. Second, producing information ex ante about possible investments and allocating capital lead to economic growth. Third, monitoring investments and exerting corporate governance improves efficiency. Fourth, facilitating the trading, diversification and management of risks promote economic growth through enhanced liquidity, reduced
liquidity risk and increased liquidity. Last, facilitating the exchange of goods and services promotes specialization, technological innovation and growth. Because these functions have an effect on savings and investment decisions they also have an effect on economic growth (Levine, 2005).
Zhuang et al. (2009) reviewed theoretical and empirical literature on the role of financial sector in facilitating economic growth and supporting poverty reduction. They found the following conclusions. First, evidence from cross-‐country and country-‐specific studies generated that financial sector development plays a vital role in facilitating economic growth. The empirical study also found that currency crises are easier to avoid in financial developed countries. Moreover, the effects of financial effects of financial sector
development on economic growth are more persistent and larger in developing countries than in developed countries. Last, industries composed of smaller firms grow faster in economies with a better developed financial sector. The second conclusion is that financial sector development contributes to poverty reduction, through the major channel of
economic growth. Also Rousseau and Wachtel (2000) find a positive link between indicators of bank and stock market development and economic growth.
Nevertheless, there were significant disagreements on the financial development and economic growth nexus. Some economists argued that correlation does not imply causality. So the question was whether financial sector development causes economic growth or economic growth generates the need for financial sector development (Zhuang et
al., 2009). For example, Robinson (1952) argues that finance does not cause growth, but it responds to demands from the real sector.
2.2.3 Microfinance institutions and economic growth
Microfinance has been growing fast since the 1970s with the aim to reduce poverty and to stimulate economic growth. Levine (2004) states that financial systems facilitates growth through five functions as mentioned above. These five functions promote
private sector development, public sector, consumption smoothening, infrastructure and the household’s ability to invest in human capital. This is a channel through which microfinance contributes to economic growth. The production created by small entrepreneurship,
improvement in human development indicators like health, nutrition and education and reduction in poverty effects economic growth (Ravallion, 2001). For example, Kai and Hamori (2009) showed that microfinance institutions tend to reduce income inequities directly by easing credit constraints of low income citizens. They used cross-‐sectional data from 61 developing countries for 2007 and used the number of microfinance institutions as the measure for microfinance intensity. They also used the 2005-‐2007 pooled data for regression with the number of borrowers as the measure of microfinance intensity.
Leegwater and Shaw (2008) explored the relationship between micro enterprises and economic growth by averaging the 1997-‐2005 time period. It was the first empirical study to examine cross-‐country evidence for micro enterprises. The study tests two hypotheses. First, countries with larger micro enterprises sectors have more rapid economic growth in per capita income than their counterparts, even after controlling for other known sources of economic growth. Second, greater micro enterprises prevalence actually causes more rapid growth in per capita income. They used OLS regression models and the IV approach to test the hypotheses. They defined microenterprises as firms with fewer than 10 employees and
as firms with fewer than 20 employees. From the OLS estimation it can be concluded that there is no significant relation between micro enterprises and economic growth. Moreover, the evidence of a causal relationship for the 10-‐ and 20-‐employee definition lacks statistical evidence. Therefore, the study offers no definitive evidence that micro enterprises directly drive economic growth. Last, they found that the business environment may matter more for the larger of the manufacturing micro enterprises. Hypothesis 2 is supported for micro enterprises with fewer than 20 employees.
2.3 Empirical results
There is a lot empirical work on the relationship between financial development and economic growth. The seminal work on this relationship is done by Goldsmith (1969). He used the value of financial intermediary assets standardized with GNP to measure financial development. He assumed that the size of the financial system is positively correlated with the provision and quality of financial services. He used cross-‐country data on 35 countries over the 1860-‐1963 time period. He found evidence of a positive trend of the ratio of financial institutions assets to GDP. However, his research has some weaknesses. First, his work involves limited observations. Moreover, the size of financial intermediaries may not correctly measure the functioning of the financial system. Last, the direction of the causality between the size of the financial system and economic growth is not identified.
King and Levine (1993b) used purely cross-‐country regressions using data averaged over the 1960-‐1989 period and a pooled cross-‐country time-‐series study using data averaged over the 1960s, 1970s and 1980s so that each country has 3 observations. The lack of
financial data and elimination of major oil exporters restricts the analysis to 80 countries. Indicators of the level of financial development are: 1) the size of formal financial
3) the percentage of credit allocated to private firms and 4) the ratio of credit issued to private firms to GDP. They found that the indicators of financial development are importantly and robustly linked to economic growth. Moreover, they found that the predetermined components of these indicators significantly predict values of growth indicators.
Luintel and Kahn (1999) used a multivariate vector auto regression framework with 10 sample countries to examine the long run relationship between financial development and economic growth. The VAR consists of four variables: 1) Financial depth measured as a ratio of total deposit liabilities of deposit banks to one period lagged nominal GDP, 2) the logarithm of real per-‐capita output measured as a ratio of real GDP to total population, 3) the logarithm of real per capita capital stock and 4) the real interest rate. They analyzed 10 sample countries and used annual data with a time span that ranges from a minimum of 36 years to a maximum of 41 years. The heterogeneity in the sample period across countries is dictated by the availability of the data. VAR is treated cross-‐sectionally by averaging over the sample period and generating one mean observation for each country. The results show the long run financial depth is positively and significantly related to the real income per capita and the real interest rate.
Levine, Loayza and Beck (2000) evaluated whether the exogenous component of financial intermediary development influences economic growth. Two econometric approaches are used. First, generalized method of moments (GMM) dynamic panel
estimators are used to deal with problems of past studies like simultaneity bias and omitted variable bias. Also pure cross-‐sectional instrument variable is used as a consistency check. The three indicators of financial intermediary development are: 1) liquid liabilities of the financial system divided by GDP, 2) the degree to which commercial banks versus the central
bank allocate society’s savings and 3) the value of credits by financial intermediaries to the private sector divided by GDP. The pure cross-‐sectional analysis found that exogenous components of financial intermediary development are positively related to economic growth using five year averages over the period 1960 to 1995 across 74 countries. They also used GMM estimators developed for dynamic models of panel data. The panel consists of 74 countries over the period 1961-‐1995. They averaged data over five year periods, so that there are seven observations per countries. The dynamic panel estimates that the exogenous component of financial intermediary exerts a positive impact on economic growth.
Khan and Senhadji (2001) re-‐examined the empirical evidence on the relationship between financial development and economic growth. The dataset includes 159 countries and covers the period 1960-‐1999. They used a pure cross-‐section sample by averaging along the time dimension and five-‐year-‐average panels. They measured financial depth with the following indicators:
(i) fd1: domestic credit to the private sector standardized with GDP (ii) fd2: fd1 plus the stock market capitalization standardized with GDP
(iii) fd3: fd2 plus the private and public bond market capitalization standardized with GDP
(iv) stock: stock market capitalization
They found a positive and statistically significant relationship between financial depth and growth in the cross section analysis. This result is robust to the four different financial depth indicators. The results were weaker when a time dimension was introduced to the model. A
possible explanation may be that a linear model is not appropriate for explaining growth dynamics of individual countries. Moreover, there is a concave relationship between financial depth and growth. This may reflect that poor countries tend to grow faster than rich countries.
3. Data and Methodology
The purpose of this study is to examine the direct relationship between the development of microfinance institutions and economic growth. First the data sources and variables will be explained. After this, the regression model and estimation method employed in this analysis will be introduced.
3.1 Data
The 30 developing countries used in this empirical research are given in table 1. In these developing countries microfinance got extensively applied. In this paper the outlier removal procedure from Beck et al. (2005) is used to correct for undue influence of outlying data points. Therefore, only 30 countries are used. The research includes the years 2001 to 2007. Within this time period the financial crisis is excluded. The data is obtained from three different sources. The Mix Market Database gives all the relevant information about microfinance institutions. From the Economy Watch Database and Worldbank Database all relevant information about the dependent variable and the control variables is obtained. 3.2 Methodology
In this section all the variables used in the empirical model will be discussed. First, the dependent variable used in the empirical model is the real GDP growth. GDP in constant 2005 U.S. dollars is used to calculate the growth rate.
The explanatory variables used in this empirical model are the indicator of
microfinance institution growth: 1) the number of microfinance institutions (MFI, hereafter), 2) gross loan portfolio (GLP, hereafter), 3) net assets (ASSETS, hereafter) and 4) the number of active borrowers (BOR, hereafter). The first variable, MFI, is the number of microfinance institutions that are active in a year per country. The services of microfinance institutions can facilitate economic growth (Zhuang, Gunatilake, Niimi et al, 2009). Therefore, the number of microfinance institutions is used as an explanatory variable. Figure 1 shows a positive relationship between the number of microfinance institutions and economic growth.
The second variable, ASSETS, is the sum of all net assets accounts of the microfinance institutions. Also this variable is standardized with GDP. Microfinance institutions have a more stable financial position to establish their services when they have more assets. Through the channel of financial development net assets can facilitate economic growth (Zhuang, Gunatilake, Niimi et al, 2009). Therefore, the sum of net assets is used as the third explanatory variable. Figure 2 shows a positive relationship between the net assets and economic growth.
The third variable, GLP, adds up the total gross loan portfolios of the active microfinance institutions. Delinquent and renegotiated loans are included, but loans that have been written of are excluded. This variable standardized with GDP. More loans help allocating more scarce financial resources to more profitable and efficient investment projects and therefore improves macroeconomic performance (Levine, 2005). Through this reallocation of resources, the economic activity is expected to increase (Lingelbach, De La Vina and Asel, 2005). Because of this positive effect on economic growth, GLP will be used as
the second explanatory variable. Figure 3 shows a positive relationship between GLP and economic growth.
The last explanatory variable, BOR, is the number of active borrowers. This variable describes the number of individuals or entities that have currently an outstanding loan balance with one of the microfinance institutions in the country and is standardized with the population ratio. The economic growth can be stimulated if the outstanding resources are divided among many borrowers. Figure 4 shows a positive relationship between the number of active borrowers and economic growth.
The control variables used are population growth (POP, hereafter), employment (EMP, hereafter), investment (INV, hereafter) and the domestic credit to private sector (CRED, hereafter). POP, is the annual population growth. EMP is the employment to
population ratio. INV is the total amount of investments as a percentage of GDP. CRED refers to financial resources provided to the private sector by financial corporation as a ratio to GDP, such as loans, purchases of non-‐equity securities, trade credits and other accounts receivable that establish a claim for repayment. This variable controls the channel of financial development on economic growth. It is expected that there is a positive relationship between the domestic credit to private sector and economic growth.
The four different indicators of microfinance institution development give four regression models, each with one indicator and the four control variables:
Regression 1: 𝐺𝐷𝑃$ = 𝛽' + 𝛽)𝑀𝐹𝐼$+ 𝛽-𝑃𝑂𝑃$+ 𝛽/𝐸𝑀𝑃$+ 𝛽1𝐶𝑅𝐸𝐷$ + 𝛽5𝐼𝑁𝑉$+ 𝜀$ Regression 2: 𝐺𝐷𝑃$ = 𝛽' + 𝛽)𝐴𝑆𝑆𝐸𝑇𝑆$+ 𝛽-𝑃𝑂𝑃$+ 𝛽/𝐸𝑀𝑃$+ 𝛽1𝐶𝑅𝐸𝐷$ + 𝛽5𝐼𝑁𝑉$+ 𝜀$ Regression 3: 𝐺𝐷𝑃$= 𝛽'+ 𝛽)𝐺𝐿𝑃$+ 𝛽-𝑃𝑂𝑃$+ 𝛽/𝐸𝑀𝑃$+ 𝛽1𝐶𝑅𝐸𝐷$+ 𝛽5𝐼𝑁𝑉$+ 𝜀$ Regression 4: 𝐺𝐷𝑃$= 𝛽'+ 𝛽)𝐵𝑂𝑅$+ 𝛽-𝑃𝑂𝑃$+ 𝛽/𝐸𝑀𝑃$+ 𝛽1𝐶𝑅𝐸𝐷$+ 𝛽5𝐼𝑁𝑉$+ 𝜀$
In these regression models, 𝐺𝐷𝑃$ stands for the annual real GDP growth in period t. 𝛽) estimates the indicators of the development of microfinance institutions in period t. 𝛽-, 𝛽/ and 𝛽1 estimates the control variables on economic growth in period t. 𝜀$ (the error term) takes on all the other factors that are not in the equation that affect economic growth in period t. The empirical models in this study are estimated using Ordinary Least Squares (OLS).
4. Empirical results
In this paragraph the empirical results on the relation between the development of microfinance institutions and economic growth are presented. The dataset includes 30 countries and covers the period 2001-‐2007. The growth equation has been estimated using a pure cross-‐section sample by averaging among the time dimension. Table 2 and table 3 provide the estimation results for the pure cross-‐section.
4.1 Control variables
Table 2 shows the estimation results including the control variable CRED, while table 3 shows the estimates without the control variable CRED. From table 2 it can be concluded that CRED is not significant. The most important issue here is the direction of causality between financial development and economic growth. If the financial development and growth are jointly determined, OLS estimation of the growth equation may be biased (Khan and Senhadji, 2001). Another reason is that the relation between growth and financial depth may involve a “threshold effect”, which means that countries may need to reach a certain level of financial depth before there is a significant effect on economic growth (Berthélemy and Varoudakis, 1996). Therefore, the control variable credit is excluded from the multiple regression models and we take a further look at table 3.
Also EMP and POP are not significant in all regressions. The small number of countries is a main reason for the insignificant findings of these control variables. Also the small amount of control variables taken into account may lead to insignificant results, because there are many factors that influences the economic growth of a country. 4.2 Explanatory variables
The results indicate a connection between the indicators of the development of
microfinance institutions and economic growth. Table 3 summarizes the pure cross-‐sectional results for four regressions where the indicators MFI, ASSETS, GLP and BOR measures the development of microfinance institutions.
The first multiple regression (1) that is used to test the relationship between the development of microfinance institutions and economic growth includes one explanatory variable and three control variables. The first explanatory variable, MFI, is the number of microfinance institutions that are active in a year per country. Noticeable is that MFI has a positive effect on GDP growth and this effect is highly significant, i.e. significant at the 1 percent level. Based on this regression it can be stated that for every unit increase in MFI, a 0.0316 unit increase in GDP growth is predicted. Therefore, we can conclude that the development of microfinance institutions has a significant and positive influence on economic growth.
The second multiple regression model (2) includes the explanatory variable ASSETS and the control variables. The regression results are significant at 1 percent. The coefficient estimated for ASSETS is 0.0131. This means that for every unit increase in assets, a 0.0131 unit increase in GDP growth is predicted. This positive and significant relation between ASSETS and GDP growth shows that the development of microfinance institutions has a significant and positive influence on economic growth.
In the third multiple regression model (3), GLP is used as the explanatory variable. The results for the third explanatory variable are significant at 5 percent. The coefficient for GLP is 0.0164. This means that for every unit increase in GLP, a 0.0164 increase in GDP growth is predicted. This regression model shows a positive and significant relationship between GLP and GDP growth. This implies that the total gross loan portfolios have a significant effect on economic growth.
The last multiple regression model (4) includes the explanatory variable BOR and the control variables. The coefficient of BOR is 0.0155, which means that for every unit increase in BOR there is a 0.0155 increase in GDP growth. However, the results are insignificant. Therefore, the number of active borrowers has no significant effect on economic growth.
Microfinance institution development has a significant positive impact on economic growth if the explanatory variables MFI, ASSETS and GLP are used as indicators. However, when BOR is used as an indicator the coefficient is not significant. This reduces the
robustness of the results. It must be stressed that it’s very difficult to measure the very small contribution of microfinance institutions on economic growth. Moreover, the small number of countries is a main reason for the insignificant findings of this research. Thereby, there are many critical aspects that are not taken into account, for example the level of financial development was excluded because of the insignificant results. Last, there are only three control variables taken into account in the multiple regression models, while there are many factors that influence the economic growth of a country.
In summary, the regression analysis shows that the development of microfinance institutions is an important determinant of the economic growth. However, not all the explanatory variables are significant. MFI, ASSETS and GLP have a positive significant effect on economic growth, but BOR does not have a significant effect on economic growth. This
may be caused by the small number of countries used in this research. Also many critical aspects were not taken into account, like the control variable for financial development. The control variable was excluded because of the direction of causality of financial development and economic growth and the “threshold effect”.
5.Conclusion
Many people in developing countries remain poor because they have no access to capital. Microfinance has been introduced as a successful method to deliver financial services to low income citizens in developing countries. Microfinance institutions contribute to poverty reduction and may stimulate the local economy.
The central question of this paper is: what is the relationship between the
development of microfinance institutions and economic growth? The literature focuses on the effect of microfinance institutions on financial development and the effect of financial development on economic growth, which suggests an indirect effect of microfinance institutions development on economic growth via the financial development. However, not much work has been done to prove the direct effect. Therefore, this research provides some evidence to the direct impact of microfinance institutions development on economic
growth.
To research the direct effect of microfinance institutions development on economic growth four regression models are used. Each regression model includes one indicator of microfinance institutions development and three control variables. The explanatory variables are MFI, ASSETS, GLP and BOR. The control variables are POP, EMP and INV. The control variable CRED was excluded from the regression models because of the insignificant results. These insignificant results may be caused by the direction of causality of financial
development and economic growth and the “threshold effect”. The dataset includes 30 countries and covers the period 2001-‐2007. The growth equation has been estimated using a pure cross-‐section sample by averaging among the time dimension.
The regression results show that the development of microfinance institutions is an important determinant of the economic growth. However, not all the indicators of the development of microfinance institutions are significant. The explanatory variables MFI, ASSETS and GLP have a positive significant effect on economic growth while the variable BOR does not have a significant effect on economic growth. This may be caused by the small number of countries and the critical aspects that were not taken into account.
More extensive and advanced research is needed to improve the findings of this study. More countries and more years should be taken into account. Also the effect of microfinance institutions on financial development should be better examined.
6. References
Aghion B.A., Morduch J., 2005. “The economics of microfinance”, Cambridge, Mass.: MIT Press
Barr M.S., (2005), “Microfinance and financial development”, Michigan Journal of International Law Vol.26, 271-‐296.
Bhatt N., & Tang S.Y., (2001), “Delivering microfinance in developing countries: Controversies and policy perspective”, Policy Studies Journal, 29(2), 319–333. Beck T., Demirgüç-‐Kunt, A. and R. Levine, (2005), “SMEs, Growth, and Poverty,” NBER Working Paper 11224.
Beck T., (2008), “The econometrics of finance and growth”, Policy Research Working Paper 4608.
Berthélemy J., Varoudakis A., (1996), Financial development policy and growth (Paris: OECD). Brau J.C., Woller G.M., (2004), “Microfinance institutions: a comprehensive
review of the existing literature.” Journal of Entrepreneurial Finance, JEF, ISSM 1551-‐9570, Vol. 9, lss. 1, pp. 1-‐27.
Cameron R., (1976), “Banking in the early stages of industrialization”, Oxford University Press: New York.
Goldsmith R., (1969), “Financial structure and development”, Yale University Press, New Haven.
Gutierrez-‐Nieto B., Serrano-‐Cinca, C. and Molinero, C.M. (2007), Microfinance
institutions and efficiency. Omega: The International Journal of Management and Science 35(2): 131-‐ 142.
Hassan M. K. and Sanchez B., (2009), “Efficiency analysis of microfinance
Paper 12.
Hermes N., Lensink R., (2007), “The empirics of microfinance: what do we know?” Economic journal, 117 (February), F1-‐F10.
Hermes N., Lensink R., Meesters A., (2009), “Financial development and the efficiency of microfinance institutions”.
Kai H., Hamori S., (2009), “Microfinance and inequality”. Munich Personal RePEc Archive (MRPA) Paper, No. 1757, 1-‐57.
Khan M.S., Senhadji A.S., (2001), “Financial development and economic growth: an overview”, IMF working paper.
King R.G., Levine R., (1993a), “Finance and growth: Schumpter might be right”, The Quarterly Journal of Economics, Vol. 108, No. 3 (Aug., 1993), pp. 717-‐737. King R.G., Levine R., (1993b), “Finance, entrepreneurship and growth: theory and evidence”, Journal of Monetary Economics 32, 513-‐542.
Klasen S., Lawson., (2007), “The impact of population growth on economic growth and poverty reduction in Uganda”, University of Hoettingen Departmental Discussion Papers 133.
Leegwater A., Shaw A., (2008), “How do microenterprises contribute to economic growth in developing countries?”, AMAP micro report, No 135.
Levine R., (1997), “Financial development and economic growth: views and agenda”, American Economic Association Vol 35, No 2, 688-‐726.
Levine R., (2005), “Finance and growth: theory and evidence”, Handbook of Economic Growth, Amsterdam: Elsevier Science, 2005, pp. 865-‐934
Lingelbach D., De La Vina L. and Asel P., (2005), “What’s distinctive about growth-‐oriented entrepreneurship in developing countries?”, UTSA College of Business Center for
Global Entrepreneurship, Working Paper No 1, 1-‐10.
Luintel K.B., Khan M., (1999), “A quantitive reassessment of the finance-‐growth nexus: evidence form a multivariate VAR”, Journal of development economics, Vol 60 381-‐ 405.
McKinnon R.I., (1973), “Money and capital in economic development”, Brookings institution, Washington, DC.
Morduch J., (1999), “The Microfinance Promise”, Journal of Economic Literature, Vol. XXXVII 1569-‐1614.
Morduch J. (2000), “The Microfinance Schism”, Elsevier Science Ltd. Vol. 28, No. 4, pp. 617-‐629.
Pagano M., (1993), “Financial markets and growth: an overview”, European Economic Review 37, 613-‐622.
Ravallion M., (2009), “Growth, inequality and poverty: looking beyond averages”, World development, 29 (11), 23-‐49.
Robinson J., (1952), “The generalization of the general theory”, The rate of interest and other essays. London: Macmillan.
Rousseau P.L., Wachel P., (2000), “Equity markets and growth: cross-‐country evidence on timing and outcomes, 1980-‐95. Journal of Banking and Finance 24, 1933-‐57.
Stock J.H. and Watson M.W., (2015), Introduction to Econometrics: updated third edition, Harlow: Pearson Education Limited.
Vanroose A., and Espallier, B., (2009), Microfinance and financial sector development, CEB Working Paper No. 09/040
Journal of Economic Development, 29-‐64.
Zeller M., Meyer R., (2003), “The triangle of microfinance: Financial sustainability, outreach and impact. Washington, D.C.: The international food policy research institute. Zhuang J., Gunatilake H., Niimi Y., et al., (2009), “Financial sector development, economic growth and poverty reduction: a literature review”, ADB Economics Working Paper Series, No. 173.
7. Appendix
Table 1 Developing countries used in the empirical research
Albania Armenia Benin Bolivia
Bosnia and Herzegovina Brazil Burkina Faso Cambodia Cameroon Costa Rica Dominican Republic Ecuador Egypt Ghana Guatemala Guinea Haiti India Jordan Kazakhstan Kyrgyz Republic Lebanon Madagascar Nepal Nicaragua Paraguay Peru Senegal Tanzania Togo
Table 2 OLS regression for all explanatory variables separately OLS Regression
Dependent variable: gross domestic product
(1) (2) (3) (4) Variables credit 0.0577 0.0531 0.0641 0.0736 (1.15) (0.97) (1.22) (1.40) emp 2.138 0.940 1.115 1.300 (1.54) (0.66) (0.79) (1.01) pop -‐0.388 -‐0.502 -‐0.467 -‐0.201 (-‐0.85) (-‐1.17) (-‐1.01) (-‐0.38) inv 0.262** 0.162* 0.197* 0.210* (2.52) (1.99) (1.99) (1.95) mfi 0.029** (2.41) assets 0.0117** (2.53) glp 0.0153* (1.93) bor 0.0196 (1.03) _cons 2.529* 3.857*** 3.408** 2.777 (1.76) (2.79) (2.52) (1.61) N 30 30 30 30 Notes:
* Statistically significant at 10% level. ** Statistically significant at 5% level. *** Statistically significant at 0% level.
Table 3 OLS regression for all explanatory variables separately OLS Regression
Dependent variable: gross domestic product
(1) (2) (3) (4) Variables inv 0.268*** 0.156** 0.198** 0.220** (2.79) (2.11) (2.20) (2.19) emp 2.202 0.887 1.076 1.1220 (1.43) (0.58) (0.70) (0.86) pop -‐0.619* -‐0.718** -‐0.741** -‐0.602 (-‐1.81) (-‐2.20) (-‐2.04) (-‐1.41) mfi 0.0316*** (2.64) assets 0.0131*** (3.37) glp 0.0164** (2.03) bor 0.0155 (0.77) _cons 3.208*** 4.573*** 4.301*** 4.175*** (2.60) (4.50) (4.35) (3.23) N 30 30 30 30 Notes:
* Statistically significant at 10% level. ** Statistically significant at 5% level. *** Statistically significant at 0% level.
Figure 1 regression line GDP MFI
Figure 2 regression line GDP ASSETS
Figure 3 regression line GDP GLP
Figure 4 regression line GDP BOR
