Economic Freedom and the Success of Microfinance Institutions

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1 Economic Freedom and the Success of Microfinance Institutions Draft: August 2006 PETER R. CRABB School of Business and Economics Northwest Nazarene University Abstract This study looks at the relationship between the success of microfinance institutions and the degree of economic freedom in their host countries. Many microfinance institutions are currently not self-sustaining and research suggests that the economic environment in which the institution operates is an important factor in the ability of the institution to reach this goal, furthering its mission of outreach to the poor. The sustainability of the microlending institutions is analyzed here using a large cross-section of institutions and countries. The results show that microfinance institutions operate primarily in countries with a relatively low degree of overall economic freedom and that various economic policy factors are important to sustainability. This work is supported by the Watson Fellowship of Northwest Nazarene University. I am grateful to Timothy Keller for research assistance on this subject. Address and contact information: 623 Holly Street, Nampa, ID 83686, phone: fax: , All errors and omissions are my own and any comments are welcome. 0

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3 I. Introduction The general purpose of small lending in developing countries is to provide the poor with financial services and capital in the hopes that they can break the cycle of poverty through business development. For years, non-governmental agencies have operated microlending, or microfinance, institutions but have been limited in the amount of people they reach because they remain dependent on donations. While microfinance institutions (MFIs) continue to serve nearly 100 million poor and near-poor individuals, it is estimated that more than 1 billion people have no access to basic financial services. 1 In recent years MFIs have begun seeking financial freedom from their donors and government agencies. That is, these groups now seek sustainability. Operational or financial sustainability is vital to the long-term success of each institution and the microfinance system as a whole. This large cross-sectional study looks at microfinance institutions around the world to see how important the economic conditions in a country are to the sustainability of the institution. Morduch (1999) describes the need for more empirical work on the sustainability of MFIs. He points out, Empirical understandings of microfinance will also be aided by studies that quantify the roles of the various mechanisms in driving microfinance performance The empirical work on microfinance institutions to date is limited to case studies and small sample reviews of financial conditions. The data for this study is a large cross section of institutions, from many parts of the world, and measured over a significant period of time. The panel data collected here provides a unique opportunity to identify key factors, both institutionally and economically, in an effort to assist MFI 1 1

4 management and help them achieve sustainability. The results of this study will assist managers and organizations that support these institutions by identifying the economic situation in each country that will lead to their success. The following section is a review of the literature on microfinance programs and factors affecting their success. Section III presents an empirical model for study here. Section IV describes the data used to estimate the model and the results are presented in section V. The final section reviews the key findings and provides recommendations for further research. II. Literature Review It is now widely accepted that financial sustainability is a necessary long-term goal for microfinance institutions. According to the Consultative Group to Assist the Poorest (1995), Microfinance institutions can and indeed need to be self sustaining if they are to achieve their outreach potential providing rapid growth in access to financial services by poor people. Sustainability is now considered a necessary precondition for achieving growth, and therefore greater outreach to the poor. Sustainability is also desirable because it allows MFIs to access the formal sector as a source of capital, rather than relying on subsidies to bring about growth. Access to commercial capital includes the ability to source capital more rapidly and increase leverage. This allows MFIs to expand their operations and increase the level of outreach (see Drake & Rhyne, 2002). Brau and Woller (2004) conduct an extensive review on the microfinance literature. In the section on sustainability of MFIs they site many articles concluding that institutional 2

5 sustainability is a necessary goal as subsidized loan funds generally are more fragile and less focused. Factors affecting the sustainability of an MFI can broadly be divided between institutional variables and environmental variables. Institutional variables are those factors that are specific to the institution, while environmental variables relate to the policy and economic setting of the country the institution operates in. The business and regulatory environment is now considered an important factor in the success of microfinance institutions. Armendariz and Morduch (2004) conclude that MFIs cannot provide effective financial intermediation without a well-functioning regulatory framework in the country. Woller and Woodworth (2001) cite many impact studies and conclude that governments must create a macroeconomic environment characterized by stable growth, low inflation, and fiscal discipline. They further suggest that poor macroeconomic, regulatory, and trade policies will undermine the viability of small business owners and the MFIs that support them. Hubka and Zaidi (2005) find that governments can help market-based microfinance by eliminating unfair competition from public institutions; undertaking overall regulatory reform; and improving the overall business environment. Ledgerwood (1999) discusses the impact of policy and regulatory issues on MFIs. Many policy issues are addressed, but two are recognized as playing a large role for sustainability - an appropriate regulatory environment, and strong property rights. Zeller and Meyer (2002) also found that improvements in the policy environment of a country contribute to the overall performance of its institutions. They site China as an example where administrative interference and distorted pricing systems resulted in a low level of 3

6 outreach and high fragility of many MFIs. In all, the overall economic condition of the host country is extremely important to the success of any MFI. Data measuring countrywide policy issues such as those mentioned above are used in this study to assess their impact on the sustainability of microfinance institutions. Some empirical work has shown institutional variables to be of minimal importance to the success of MFI. Christen, et al (1995) found few institutional variables to be significant. In particular, direct unit-cost-related variables in an institution had no statistical significance in a regression on returns. As the authors mention, we should expect programs with high operating costs to be less viable. Christen et al also considered non-institutional factors; finding four key aspects of the policy environment to be important for microenterprise development - recent economic growth, macroeconomic stability, the extent of financial repression, and the regulatory environment for financial institutions. The results suggest the economic situation faced by the MFI may be of greater importance than any institutional factor. The study, however, is limited to only eleven institutions, and most of these institutions have been around long enough that they must all achieved some level of sustainability. Woller (2000) reviews the financial viability of village banking, a common lending program for MFIs, using data for nine institutions. Woller looks at the relationship between the return on the institution s loan portfolio and various operational cost measurements. As with Christian et al it is difficult to make strong conclusions from the small sample, but Woller finds three strong indicators of financial health portfolio yield (return), the interest spread, and number of borrowers. The study found that many efficiency variables were uncorrelated with the return on the portfolio, that is, many 4

7 institutional factors are relatively less important. Of these three key indicators, only number of borrowers can effectively be managed by the institution. Thus, MFIs may better achieve sustainability by increasing the size of their operations. In contrast, Woller (2001) finds no relationship between institutional size and sustainability but a measure of the institution s yield on its portfolio is once again positively related to sustainability. Many institutional variables were not found to be significant but there was a positive relationship between financial self-sufficiency and depth of outreach. The study used data over a three year period from thirteen institutions operating village banking operations. The data set is robust, including many measures of institutional operations, but only 13 of the 148 institutions in the MicroBanking Bulletin could be reviewed and the regression results could not be measured using fixed effects procedures. The results presented here incorporate some of these findings in Woller s study and are measured using fixed effect regressions. Other empirical research to date suggests that a country s political, economic, and cultural environment plays a key role in the ability of microfinance institutions to meet their mission. Sharma (2004) found case studies that show the importance of the broader national environment in facilitating the growth of institutions, comparing, for example, success in India and not in Nepal. Growth of the MFI in Nepal leveled off just as expansion of the institution in India accelerated. This coincided with the Maoist insurgency in Nepal and an improving economic environment in India. The results presented here are more robust than case study reports. Cross-sectional and time-series data measuring country-wide policy issues are used in this study to assess their impact on 5

8 the sustainability of microfinance institutions, while also controlling for many institutional variables. III. Empirical Model The above literature review suggests that the economic environment of the host country influences the sustainability of a microfinance program. Determination of the dependent variable, operational sustainability, for this study is guided by the current conventions in the industry. As noted above, previous studies have used return on assets as the measure of the institution s ability to sustain its operations. More recently, MFIs have reported operational self-sufficiency, which is calculated as the ratio of total financial revenue to total financial expenses, loan loss provisions, and all other operating expenses. This measure is used over another widely discussed ratio financial selfsufficiency. Financial self-sufficiency is likely to include revenues or expenses from activities other than loans to the poor and is not reported in the data set obtained for this study. This section presents the empirical model used in the study and the expected factors that determine operational self-sufficiency. A general econometric model to study the issue takes the form Y ijt = α + β X jt + Γ Z it + ε ijt (1) where Y ij t is the operational self-sufficiency of MFI i in country j for period t. The first independent variable, X jt is a measure of the economic freedom in the country j in period t. Z it is a vector of institutional control variables for MFI i in period t. In the data 6

9 used for this study a higher value for X is associated with less economic freedom. We would therefore suspect that the sign of β to be negative a lower degree of economic freedom reduces the MFI s sustainability. The control variables for this study are based on the above review of previous studies and are specific to each institution. They include gross loan portfolio, the percent of the portfolio at risk, return on assets, the number of borrowers per staff member, and the number of active clients. The appendix provides a definition for each of these variables. The expected signs of the coefficient on gross loan portfolio, the number of borrowers per staff member, and the number of active clients are positive. These variables all measure economies of scale in the institution - higher economies of scale increase the MFI s sustainability. Return on assets is used to proxy for the yield on the institution s portfolio and its expected sign is positive as previously found. The expected sign of the coefficient for the percent of the portfolio at risk is negative - greater risks increase costs and reduce the sustainability of the institution. Many MFIs use group lending programs to mitigate these risks. The general model in equation (1) can be delineated by the factors affecting a country s economic freedoms. The data used here include 10 government policy and economic environment factors: trade policy, fiscal burden of government, government intervention in the economy, monetary policy, capital flows and foreign investment, banking and finance, wages and prices, property rights, regulation, and informal market activity. Using all ten of the available factors provides a more specific econometric model for study: Y ijt = α + β 1 X 1 jt + β 2 X 2 jt + + β 10 X 10 jt + Γ Z it + ε ijt (2) 7

10 where Y ij remains the operational self-sufficiency of MFI i in country j for period t. The independent variables for economic freedom are measured by X 1jt through X 10jt for country j in period t, and Z it remains the vector of institutional control variables for MFI i in period t. Each factor of economic freedom is accorded a higher value if the economic environment for the country is less free, scored on a system ranging from 1-5. Thus, the expected coefficient sign for each factor is negative a lower degree of economic freedom in the indicated area reduces the MFI s sustainability. The next section further describes these variables as they are used in this study. IV. Data Data for this study were obtained from two public sources - the Microfinance Information Exchange (MIX) and the Heritage Foundation s Index of Economic Freedom. The MIX is a not-for-profit private organization promoting information exchange in the microfinance industry (www.themix.org and The MIX provides reliable, comparable and publicly available information on the financial strength and performance of MFIs. While they do not guarantee the data, the MIX follows a quality control system to help ensure the validity of MFI data by verifying the information posted and reviewing it for coherence and consistency. At the time of the study there were 717 listed MFIs. Annual data from 2000 to 2004 for 511 reporting institutions in 90 different countries was obtained for this study. The Appendix lists and defines the variables collected annually for each MFI in this study over the sample period. 8

11 Data on the level of economic freedom for countries comes from the Heritage Foundation s Index of Economic Freedom (EF). The data can be found at The EF is a set of objective economic data in areas such as trade policy, fiscal burden of government, government intervention in the economy, monetary policy, capital flows and foreign investment, banking and finance, wages and prices, property rights, regulation, and informal market activity. Countries are measured in each of the ten areas and given a score of 1 to 5, and the ratings are averaged to create an overall level of economic freedom ; low scores (less than 2.99) represent a low level of government involvement in the economy and high scores (greater than 3) correspond to a high level of government involvement. A an economy with a high score has significant government involvement in the economy and hence less economic freedom. More detailed measurements of the economic environment are found in the subcategories of the index. The ten subcategories of The Economic Freedom Index are also scored on a system ranging from 1-5. For example, in the Banking and Finance category, a 1 is for a country with little or no government restrictions, regulations, and involvement in the banking or finance industry, while a 5 represents complete government control. In order to earn a 1 in the Property Rights category, a country must have a judicial system free from government influence, strong property rights, and strong contract law. A country earning a 5, on the other hand, exhibits the opposite characteristics. For each annual Index of Economic Freedom, the report covers data for a 12-month period starting 18 months prior. For example, the 2003 Index covers the 9

12 second half of 2001 through the first half of Therefore, the 2003 Index value is matched with the reported 2002 data for the MFI in that host country. V. Results Table 1 shows descriptive statistics for all variables described in the appendix. This large cross-section covers a variety of institutions from many different countries MFIs from 90 different countries over the period of 2000 to There are over 1,500 observations for most variables. Missing data for some institutions in some years results in 1,076 observations for regression analysis. Three important issues can be observed from the details of Table 1. First, the data include observations for MFIs with no active clients and no loans, to ones with nearly 4 million borrowers or well over $1.7 billion in lending activity. In other words, the size of the MFIs is skewed towards large institutions and countries operating with higher average income. To control for resulting heteroskedasticity, gross Loan portfolio is used as a weighting factor in all regression measurements that follow. Second, these institutions operate in primarily unfree countries as defined by the Heritage Foundation s Index of Economic Freedom. The average score for the 90 countries represented here is 3.28, where a country receiving a score greater than 3 is considered to be unfree, and those with a score of 4 or above have little to no economic freedom. The third issue concerns the average operational self-sufficiency. The 1.13 average for these reporting institutions suggests that most have more than achieved their goal of sustainability. It is possible that there is some sample selection bias in the MIX 2 A detailed description of the methodology used in the collection of these data can be found at 10

13 data. Perhaps MFIs begin reporting to the MIX once they have achieved sustainability or are close to it. To look at this issue the EF scores for those 206 institutions in the Mix data not reporting operational self-sufficiency were collected. While the average EF score for the reporting firms is 3.28 as indicated in Table 1. Conversely, the average score for the countries where the non-reporting firms are operating is The difference in these mean values is significantly different (t-statistic of 7.16, p= 0.000). It could be that the non-reporting firms have not achieved sustainability because they operate in very difficult economic environments. A. Univariate Tests As a first look at the relationship between economic freedom and the sustainability of MFIs a test of the means was conducted. The mean operating selfsufficiency for MFIs in countries scored as mostly free (score of 2.99 or less) is 1.07 compared to 1.14 for those institutions operating in mostly unfree countries (score of 3 or higher). While it looks as if the MFIs operating in more restrictive environments may actually be doing better, there is no statistically significant difference in these two groups (t-statistic of , p= 0.105). A second means test confirms the importance of institutional size discussed earlier. The average operating self-sufficiency rate for MFIs with a gross loan portfolio greater than the median value of $1,752,759 is This value is statistically greater than the 1.03 average for smaller MFIs (t-statistic of 8.322, p= 0.000). This result is likely due to the economies of scale achieved by institutions that have been in existence longer. It should be expected that when MFIs have achieved operating self-sufficiency they can continue to grow their portfolio. 11

14 Table 2 reports Pearson correlation coefficients among all variables described in the appendix. Each of the institutional variables is significantly correlated with operational self-sufficiency - the sustainability of an MFI falls as the risk of the loans increases and the rate of return rises, but rises with more borrowers and higher loan values. Interestingly, rate of return and operational self-sufficiency are negatively correlated. However, the relationship is in the expected direction when controlling of other factors in the multivariate tests that follow. The overall score of the country where the country operates is not significantly related to operational self-sufficiency, but five of the factors that make up this score are. The relationship amongst these factors is discussed next in the multivariate analysis. The high number of significant correlations in Table 2 indicates possible multicolinearity problems which are addressed in the following multivariate tests. As previously mentioned, the MFIs in this sample operate in generally better environments than MFIs in the MIX data that did not report their sustainability figure. It may also be the case that MFIs have flourished simply because they operate in environments where the poor have been burdened by the lack of economic opportunity, that is, countries with less overall economic freedom than most. The current trend in operationally self-sufficiency supports this idea. From 1998 to 2004 the average operationally self-sufficiency has risen from 1.04 to 1.18 for all MFIs reporting in the MIX data. Meanwhile, the average score for all countries in the EF data improved from 3.21 to Therefore overall economic freedom is improving but MFIs have improved their operations while still trying to support the poor in mostly unfree environments (average score 3.28). 12

15 B. Multivariate Tests Table 3 presents estimates of the model in Equation 1 for the sample period of 2000 through The dependent variable is operational self-sufficiency. The parameters are measured accounting for fixed effects and gross loan portfolio is used as a weight for each variable to control for heteroskedasticity. The model is overall significant and the results indicate that the overall level of economic freedom in the host country (Score) is not a contributing factor in the ability of an MFI to sustain its operations. This result may be due to the sample selection bias discussed earlier or simply that this aggregate measure does not reflect the key policy issues affecting MFIs. The control variables in the estimates of Equation 1 are all significant and have the expected sign. The coefficient on the variable measuring the percentage of the MFI s portfolio that is at risk shows that this factor is very important to the success of the institutions. The group lending programs used by most MFIs is thought to control this risk. Controlling for the size of the institution, the risk in the portfolio significantly affects the ability of the MFI to meet the objective of sustainability. As previously discussed, the EF score is an average of ten factors. Table 4 presents estimates of the model in Equation 2 to test the implication of each of these factors on the sustainability of MFIs. The dependent variable is again operational selfsufficiency and the parameters reflect controls for fixed effects. The model is overall significant and the control variables remain significant and have the expected signs. Four of the ten factors for economic freedom are significant predictors for operational self- 13

16 sufficiency. Two of these factors have positive impacts - less economic freedom in the areas of trade and monetary policy lead to higher sustainability levels. The earlier discussion of MFI success over time may also be true in these specific areas. If the overall economic level of freedom is improving over the sample period it may be true that the MFIs are having success where trade has not opened up extensively and the monetary authority has not controlled inflation. Two of the factors have significant negative impacts on sustainability government intervention and banking. Consistent with the literature, a country with low economic freedom in terms of role that the government takes in the marketplace will have trouble sustaining private business operations. Higher scores on Banking also lead to lower sustainability. A heavy government involvement in financial sector suggests MFIs will have difficulties lending to the poor. A high value for the EF rating on Banking indicates that credit allocation in the country is controlled by government, bank formation is difficult, and evidence of corruption exists. As evidence in Table 2 shows, multicollinearity is present in the data. To address this issue the model in Table 4 was estimated without the two variables receiving high variable inflation factors (VIF) - the number of active borrowers (VIF= 3.38) and the Banking factor (VIF = 4.78). The results (not reported) are qualitatively similar in terms of both statistical significance and coefficient estimates. VI. Conclusions Sustainability is now a necessary long-term goal for almost all microfinance institutions. MFIs seek to cover their operating expenses and achieve growth so as to 14

17 further their outreach to the poor. MFIs no longer wish to rely on subsidies to bring about growth. Many factors contribute to the ability of an MFI to meet these goals and the economic environment in which the MFI operates is one important factor. Particular negative aspects of the economic environment such as government intervention significantly reduce an MFI s ability to achieve sustainability. The empirical results from this large cross-section of institutions over many years support the need for governments to provide good economic environments if MFIs are to meet their goal of breaking the cycle of poverty. A key area of concern in this study is the possible sample selection bias discussed earlier. It is important for all MFIs to report the results of their operations so that organizational managers and governmental officials can support their work. Greater reporting should lead to better analysis of the factors affecting long-term success. Another area of concern in this study is a possible identification problem. The predictors in this study are economic factors in the host country leading to success of the MFI. It is possible to think of successful MFIs helping a country improve its economic environment. That is, when the MFIs are able to achieve sustainability the government can reduce it role in the economy. Further theoretical work on the developmental implications of MFIs and their role in the economy will prove beneficial. 15

18 Appendix Data for the following factors was obtained from the MIX MARKET, a microfinance information platform at in July of Operational Self-Sufficiency: Financial Revenue (Total)/ (Financial Expense + Loan Loss Provision Expense + Operating Expense). A value of 1 indicates full operational self-sufficiency, whereas a value less than one indicates the institution must rely on outside sources. Gross Loan Portfolio: All outstanding principal for all outstanding client loans, including current, delinquent and restructured loans, but not loans that have been written off. It does not include interest receivable. It does not include employee loans. Return on Assets: A measure of the institutions earnings on invested assets and equal to net after-tax operating income divided by average assets for the period. Portfolio at Risk > 30 days Ratio (%): The value of the portfolio for which payments are more than 30 days divided by the gross value of the loan portfolio. Borrowers per Staff Member: Number of active borrowers divided by the number of personnel. Number of Active Clients: Number of individuals who are active borrowers and/or savers with the MFI. A person with more than just one such account (i.e. with a loan and a savings account) is counted as a single client in this measure. 16

19 References Armendariz and Morduch (2004), Microfinance: Where do we stand?, in Financial Development and Economic Growth: Explaining the Links, Charles Goodhart, editor, Palgrave Macmillan, Basingstoke, Hampshire, UK. Brau, James C. and Woller, Gary (2004), Microfinance: A Comprehensive Review of the Existing Literature, Journal of Entrepreneurial Finance and Business Ventures, Vol. 9, p.p Christen, R.P., Rhyne, E., Vogel, R.C., & McKean, C. (1995). Maximizing the outreach of microenterprise finance: An analysis of successful microfinance programs. USAID. Retrieved from Consultative Group to Aid the Poor (1995), Maximizing the outreach of microenterprise finance: The emerging lessons of successful programs. Retrieved from Drake, D., & Rhyne, E. (Eds.). (2002). The commercialization of microfinance: Balancing business and development. Bloomfield, CT: Kumarian Press. Hubka, A., & Zaidi, R. (2005). Impact of government regulation on microfinance. World Bank: Washington, D.C.. Retrieved from overnment_regulation.pdf Ledgerwood, J. (1999). Microfinance handbook: An institutional and financial perspective. World Bank: Washington, D.C. Morduch, Jonathan (1999), The Microfinance Promise, Journal of Economic Literature Vol. 37, p.p Sharma, M.P. (2004). Community-driven development and scaling-up of microfinance services: Case studies from Nepal and India. Retrieved April 4, 2005 from: Woller, Gary (2000), Reassessing the Financial Viability of Village Banking: Past Performance and Future Prospects, MicroBanking Bulletin. Woller, Gary (2001), Poverty Lending, Financial Self-Sufficiency and the Six Aspects of Outreach, SEEP Network Working Group Papers, (http://www.seepnetwork.org/files/691_povertylendingwoller.doc) 17

20 Woller, Gary and Woodworth, Warner (2001), Microcredit as a Grass-Roots Policy for International Development, Policy Studies Journal, Vol. 29, p.p Zeller, M., & Meyer, R.L. (Eds.). (2002). The Triangle of Microfinance: Financial Sustainability, Outreach, and Impact. International Food Policy Research Institute, Baltimore, U.S. Table 1 Descriptive statistics: Annual data for 511 microfinance institutions from 2000 to 2004; Annual scores from the Heritage Foundation s Index of Economic Freedom (EF) for the countries where these microfinance institutions operate. Variable N Mean Std. Dev. Minimum Maximum a. Institutional data Operational SelfSufficiency 1, Gross Loan Portfolio 1,585 12,398,671 69,419, ,720,072,773 Portfolio at Risk > 30 days Ratio 1, Return on Assets 1, Borrowers per Staff member 1, Number of Active Borrowers 1,546 47, , ,993,525 b. Country data Score 1, Trade 1, Fiscal Burden 1, Gov't Intervention 1, Monetary Policy 1, Foreign Investment 1, Banking 1, Wages & Prices 1, Property Rights 1, Regulation 1, Informal Market 1, Valid N (listwise) 1,313 18

21 Table 2 Pearson Correlation Coefficients: Annual data for 511 microfinance institutions from 2000 to 2004, and annual scores from the Heritage Foundation s Index of Economic Freedom (EF) countries where these microfinance institutions operate. Coefficients significant at the 5% level in bold Operational SelfSufficiency 1 2 Gross Loan Portfolio Portfolio at Risk > 30 days Ratio Return on Assets Borrowers per Staff member Number of Active Borrowers Score Trade Fiscal Burden Gov't Intervention Monetary Policy Foreign Investment Banking Wages & Prices Property Rights Regulation Informal Market

22 Table 3 Parameter estimates for equation 1: Y ijt = α + β X jt + Γ Z it + ε ijt The dependent variable is the operational self-sufficiency of MFI i in country j during t. Score is a measure of the economic freedom in the country j during that period. A higher value for Score indicates less economic freedom in the country. The remaining variables in vector Z are specific to the institution for period t. Annual data for 511 microfinance institutions from 2000 to 2004 and annual scores from the Heritage Foundation s Index of Economic Freedom (EF). Fixed effects estimation weighted by Gross Loan Portfolio. Dependent Variable - Operational Self-Sufficiency Variables Coefficients Std. Error t p-value Intercept Portfolio at Risk > 30 days Ratio Return on Assets Borrowers per Staff member Number of Active Borrowers Score Adjusted R-square N 1,076 20

23 Table 4 Parameter estimates for equation 2: Y ijt = α + β 1 X 1 jt + β 2 X 2 jt + + β 10 X 10 jt + Γ Z it + ε ijt The dependent variable is the operational self-sufficiency of MFI i in country j during t. Ten factors measure of the economic freedom in the country j during that period (trade policy, fiscal burden of government, government intervention in the economy, monetary policy, capital flows and foreign investment, banking and finance, wages and prices, property rights, regulation, and informal market activity). A higher value for each factor indicates less economic freedom in this area for the respective country. The remaining variables in vector Z are specific to the institution for period t. Annual data for 511 microfinance institutions from 2000 to 2004 and annual scores from the Heritage Foundation s Index of Economic Freedom (EF). Fixed effects estimation weighted by Gross Loan Portfolio. Dependent Variable - Operational Self-Sufficiency Variables Coefficients Std. Error t p-value Intercept Portfolio at Risk > 30 days Ratio Return on Assets Borrowers per Staff member Number of Active Borrowers Trade Fiscal Burden Gov't Intervention Monetary Policy Foreign Investment Banking Wages & Prices Property Rights Regulation Informal Market Adjusted R-square N 1,076 21

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