A CRITICAL APPRAISAL OF INDIAN MICROFINANCE INSTITUTIONS IN INDIA

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1 A CRITICAL APPRAISAL OF INDIAN MICROFINANCE INSTITUTIONS IN INDIA Kashif Beg Research Scholar, A.M.U., Aligarh India Mohd. Qasim Khan Research Scholar, A.M.U., Aligarh India ABSTRACT Microfinance aims to reduce poverty & generate profit by providing financial services to poor & unprevleged section of society. This study uses cross sectional high quality data from mix market of 50 microfinance institutions in India for the period 2005 to 2013 to test how different lending methodology of microfinance institutions contributes to loan repayment, cost reduction & mission drift. We also examined the patterns of financial viability of Indian micro finance institutions. We used weighted least square method one type of Robust regression in order to investigate the determinants of Profitability or financial self sustainability. Keywords: micro finance, mission drift, financial viability, mix market 1. Introduction and issues MFIs offer various types of financial services to unprivileged and poor section of society. MFIs in India exist in institutional and legal form. As Microfinance is a costly business due to high transaction cost, which mean they are not self sufficient, Hermes and Lensink (2011). In 1990, the issue of self sufficiency of microfinance institutions gives rise to two opposing approaches but having the same goal i.e. institutionalist approach and welfarist approach (Robinson, 2001). Mordoch (1998) refers this controversy as Microfinance schism. Institutionalist Approach: emphasizes importance of sustainable microfinance institutions which are not dependent on any kind of subsidy and donations. This approach stresses the importance that MFIs must cover their cost of lending money from self generated income and to reduce operational cost as much as possible. They emphasize that providing credit in long term without financial sustainability is not being possible. Welfarist and poverty lending approach: The welfarist emphasizes that Poor can afford higher interest rate. Therefore providing credit to poor at subsidized rate of interest. Therefore aiming financial sustainability is contrary to the goal of the serving large no poor clients. The believer of Institutionalist approach emphasizes that empirical evidence nether shows poor cannot afford higher interest rates and nor there is empirical evidence on negative correlation Financial sustainability and Poverty level of clients. They emphasizes that financial services to poor on long term basis is not possible until and unless MFIs are self reliant and sustainable (Hermes and Lensink, 2011). Most of the parties in this debate favour Institutionalist approach. Microfinance institutions are constrained to achieve double objective of self sustainable i.e. covering enough cost so that reliance on subsidy can be overcome and serving unreached poor clients with financial services (outreach). In order to determine that MFIs are able to meet challenge of financial sustainability, there is no other alternative but to assess the performance of MFIs. Understanding 161

2 the financial performance scenario of MFIs in India. There is not enough empirical investigations on Indian MFIs using large datasets and sound methodology.. The evaluation literature on Microfinance is rich but focused on case studies of small no of MFIs. As India s Microfinance sector is rated as one the most growing sector in world. But financial sustainability aspect of Indian MFIs using large datasets for longer period is uncovered. Only Crombrugge et al. (2008) study is based on 45 MFIs in India. According to the report of (Deutsche bank, 2007) only 1_2% MFIs are financially sustainable. Mostly larger MFIs are profitable. 70% of all MFIS are heavily dependent on subsidies. In this paper we determine the factors which impact on financial self sustainability of MFIs in India. The paper is organized as follows. In section 2 we first present the Literature review of various studies related to financial sustainability and mission drift issue. In section 3, we discuss about the present loan delivery models of MFIs in India. Section 4 discusses about the Methodology and section 5 discuss about the variables used in the study. Section 6 concludes. 2. Literature Review Cull, Kunt and Morduch(2007) investigates three questions : Does raising interest rates exacerbate agency problems increasing defaults decreasing profitability? Is there tradeoff between profitability and outreach to Poor? Have Micro banks moved away from serving poor clients in pursuit of commercial viability? By using datasets of 124 Microfinance institutions from 49 countries the authors have examined the following questions. They find that effects of prices and cost depend on lending methodology of MFIs Institutions which follow Individual lending methodology are more profitable than others but up to a certain limit. But when interest is raised substantially, Individual lenders generate lower profit and weak portfolio. The institutions that invest higher staff cost are more profitable than others. Group based lenders that charge higher interest rates are more profitable than others. On the evidence of Mission drift Positive results were found financial self sustainable and lending to the poor clients and women can go hand in hand. Group based lenders that charge higher interest rate has weakened loan repayment rates. Hermes, lensink and Meesters(2011) in their empirical evidence, outreach and efficiency of microfinance institutions find convincing evidence that outreach is negatively related to efficiency of microfinance institutions. The large set of 435 institutions for the period were used to determine the relationship between cost efficiency of MFIs and depth of outreach measured on the basis of average loan balance and percentage of women borrowers..they applied SFA (stochastic frontier analysis) to calculate the cost efficiency of Microfinance institutions and then correlation analysis to determine the tradeoff between outreach and efficiency. Their finding suggests MFIs that have more women borrower and lower average balance are also less efficient. The finding of correlation between efficiency and outreach shows that outreach is negatively related to efficiency of MFIs. The contribution of Mersland and Storm(2010) examines the Mission drift by using panel dataset of 379 mission drift with Generalized method of movements(gmm) and logistics regression method for other depth measures. The data were collected by the rating agencies during the period This study investigates about the mission drift by using average loan size as main proxy; lending methodology and gender bias as further mission drift measures. Their empirical findings did not find any evidence of mission drift. The econometric evidence supports that average loan size increases with an increase in average profits and average operational costs. Gakhar and Meetu (2013) in their empirical study on MFIs in Indian economy study the tradeoff between outreach and financial performance on MFIs in Indian economy. This study analyses the data of 40 Microfinance institutions taken from MIX database for the period of2004 to The regression analysis model is used to identify a trade off outreach and financial performance. The evidence of analysis suggests that increased level of outreach improve financial performance. They conclude that MFIs can achieve 162

3 dual objective of tradeoff between outreach and financial performance. Quayes (2012) in his paper investigate the dual relationship between depth of outreach and financial sustainability. The data of 702 MFIs from 83 countries for the year 2006 were taken from MIX (Microfinance information exchange). Average loan size/gni, percentage of women borrower, dummy variable of operational self sufficiency is used as outreach variable. Ordinary least square is used to investigate the relationship between financial efficiency and outreach. They did not find any evidence of tradeoff except for low disclosure MFIs. 3. Loan Delivery models of MFIs in India a. Individual-based lenders: institutions that use standard bilateral lending contracts between a lender and a single borrower. Liability for repaying the loan rests with the individual borrower only, although in some cases another individual might serve as a guarantor. b. Self help group: Self-help Group concept has its origin in India. SHGs are now considered to be very important bodies in rural development and are therefore found in almost all parts of the country and their number is still rapidly growing. SHGs are formed by Non-Government Organizations as well as Government agencies and are used as channels for various development programmes. A Self-Help Group is an association of generally up to members, preferably women from the same socio-economic background. SHGs are facilitated by Government agencies or NGOs for members to come together for discussing and solving their common problems either financial or social through mutual help. An SHG can be all-women group, all-men group, or even a mixed Group. However, it has been the experience that women s groups perform better in all the important activities of SHGs. Mixed group is not preferred in many of the places, due to the presence of conflicting interests. c. Joint liability group: JLG model is quite similar to the Grameen model of Bangladesh. These are group of individuals coming together for the purpose of availing bank loan from the financial institution. They share responsibility ( liability ) and stand as guarantee for each other. There is a Group Leader in such JLGs, many MFIs prefer such group in urban business areas. Such JLGs do not hold periodic meetings. While lending in such JLGs is to individual members small JLGs still provide some sort of comfort to the MFIs. Also collection can be done from a single point, generally from the Group leader rather than going to each individual. d. Diversified Lending model: Diversified is the combination of all the above three model INDIVIDUAL, JLG, SHG, because some MFIs grant loan according to the need and preference of consumer i.e. in group form and individual. 4. Methodology We analyzed financial data of 50 Indian Microfinance institutions for the period in this exercise. The database was constructed by the Microfinance information exchange Inc.(MIX), the largest, global web based microfinance information exchange in Microfinance industry which provide financial and social performance data of all the MFIs around the globe. The objective of benchmark regression is to investigate the determinants of Profitability or financial self sustainability in order to determine factors affecting financial self sufficiency and in order to explore which lending model performs better than other. In order to explore this question we used financial self sufficiency as dependent variable and other significant determinants as independent variable. In order to construct data for present study, the data is disaggregated on the basis of loan lending model as 24 MFIs follow jlg model, 16MFIs shg model, 4MFIs individual model and 6MFIs diversified model. 163

4 Besides we suspect that some of the assumptions of regression analysis are not fulfilled after trying all the techniques including transformation of variable and so on. These are very common problem in empirical exercise and there are ways by which we can transform the data and adjust the model against unruly data. As our data do not satisfy the assumptions of regression analysis. Therefore we used weighted least square method one type of robust regression method in all estimates. Robust regression is one such technique which provides an alternative to least square regression model when fundamental assumptions are unfulfilled fully or partially. The objective of the benchmark regressions is to determine the factors of several performance indicators of profitability or sustainability. In order to investigate how different loan model performs, the regression model is given below. Y i = α + β X i +γ Z i + μ AB i + u i The dependent variable Y is a measure of financial self sufficiency; X is asset of two baselines variables which are always shown in regression equation. Z is a measure of Real Gross portfolio yield and AB is a set of two control variables drawn from a pool of possible variables empirically or theoretically with financial self sufficiency. Both Z and AB are drawn from same pool of variables. u is used as error term. The index i represents a single observation. 5. Dependent and independent variables Dependent variable The key dependent variable in our analysis of profitability is the financial self sufficiency (FSS) ratio, a measure of an institution s ability to generate sufficient revenue to cover its costs. Values below one indicate that it is not doing so. The financial self sufficiency ratio bests other measures of financial performance because the data readjusted as described above and because it offers a more complete summary of inputs and outputs than standard financial ratios such as return on assets or equity. For robustness, however, we also use as dependent variables an unadjusted measure of operation self sufficiency (OSS). Independent variables Yield on gross loan portfolio: Portfolio yield is a percentage that shows institutions ability to generate revenue to covers it s financial and operating expenses. It represents average gross returns as a proportion of portfolio outstanding. The study of Cull(2005) shows that gross portfolio yield Is positively and significantly related with all three measures of financial self sufficiency (Operational self sufficiency, Financial self sufficiency, Return on Assets).The study of Crombrugge(2007) founds that the Portfolio Yields affects the financial self sufficiency. The findings of the study show that Yield and FSS is positive through interest and fees revenue. This variable is hypothesized to be inversely related with financial self sufficiency. Average Loan Size (Depth of outreach):the average loan size (defined as the average gross loan portfolio divided by the number of active borrowers) is a proxy for depth of outreach. Smaller loans are generally taken to indicate greater depth of outreach. This variable measures the efficiency of microfinance institutions in selling loans. The study of Gonzalez(2007) shows that larger loans are associated with higher cost efficiency and thereby profitability. However the findings of cull(2007) is against the findings of above two studies. Average loan size is hypothesized to be inversely related with financial self sufficiency. 164

5 Age of an MFI: Sustainability could also relate to the age of MFI. The age refers to the period that an MFI has been in operation since its initial inception. Studies indicate that the MFIs age relates to the financial sustainability (Bogen et al. 2007)Cull et al, 2007; Gonzalez, 2007). Nyamsogoro(2010) found that Age of MFIs is not significantly related to financial self sufficiency. Age of MFIs is hypothesized to be positively related with financial self sufficiency. Size of an MFI: Another factor that can affect the financial performance of an MFI is its size. The size of an MFI is measured by the value of its assets (Mersland and storm, 2009; Hermes et al, 2008; Mersland and storm, 2008; Bogan et al, 2007; Hartarska, 2005). According to Cull et al (2007) the size of an MFI is significantly positively linked to its financial performance. The study of Nyamsogoro(2010) found that the size of MFIs significantly affets financial self sufficiency. Similar findings were also disclosed by the study of Cull et al(2007); Robinson(2001); Bogan et al(2007); Mersland and storm(2009). It is hypothesized to be positively related with financial self sufficiency. Portfolio at risk (30) Days: The portfolio at risk (PAR) measures indicates how an MFI is efficient in making collections. The higher the PAR indicates low repayment rates, as indication of inefficient microfinance institution. The higher the PAR, the more inefficient the microfinance will be and, therefore, the less financially sustainable. The study of cull (2007) concludes that higher interest rates are associated with higher rates of non repayment but only for individual lenders only. Moreover, according to one specification individual based lenders charging higher interest rates enjoy higher profit than those charging intermediates rates. The empirical findings of the study of Nyamsogoro(2010) shows that there is a significant and negative relationship between portfolio at risk and financial self sufficiency. Portfolio at risk is assumed to be negatively associated with financial self sufficiency. Capital cost to assets ratio: Berger,A.N. and Banaccorsi di patti E.(2006) capital structure and Firm performance a new approach to testing agency theory and an application to the banking industry. High capital assets ratio signify that MFis are operating overcautiously and profitable investment opportunities. Berger (1995) conclude that cost of insurance against bankruptcy can be high for MFIs with a low capital assets ratio, suggesting appositive relationship between financial performance and capital assets ratio. Capital cost to Assets is hypothesized to be negatively associated with financial self sufficiency. Gross loan portfolio to total assets ratio: This ratio is considered a measure of risk exposure. In order to analyze for MFIs social mission, we include this variable. The study of cull et al(2007) shows significant and positive relationship between portfolio to assets ratio with financial sustainability and return on assets. However, insignificant relationship was found with operational self sufficiency. It is hypothesized to be negatively or positively related with financial self sufficiency. 165

6 INDEPENDENT VARIABLES VARIABLE DESCRIPTION VARIABLE NAME IN THE REGRESSION MODEL EXPECTED RESULT Age of mfis Log of Total Assets of MFIs Age Positive Real Gross Portfolio Yield (Yield on gross portfolio (nominal) Inflation rate) / (1+ Inflation rate) Yogp Negative Capital cost to Assets (Rent + transportation + depreciation + office + other) / total assets Ccta Negative Gross Loan portfolio to Assets Adjusted gross loan portfolio/ Adjusted Total assets Glpta Positive or Negative Average loan balance per borrower Adj. GLP/Adj. Number of Active Borrowers Albpb Negative Portfolio at risk The fraction of loan portfolio that is overdue past 30 days or more; that is PAR 30 = Portfolio at risk/gross loan portfolio P30 Negative Labour cost to assets Personnel expenses/total assets Pea Positive Size of MFI Log of Total Assets of MFIs ass Positive 166

7 DEPENDENT VRIABLE: FINANCIAL SELF SUFFICIENCY RATIO (FSS) AND OPERATIONAL SELF SUFFICIENCY RATIO (OSS) VARIABL ES JOINT LIABILIT Y GROUP (fss) JOINT LIABILIT Y GROUP( oss) SELF HELP GROUP (fss) SELF HELP GROUP( oss) INDIVID UAL (fss) INDIVID UAL (oss) DIVERSIFIE D(fss) DIVERSIFIE D(oss) const [3.46] ] ] [1.94] ] [0.39] ] [1.51] 0.54 Y [7.00] 1.42 [8.82] 1.67 [3.39] 1.35 [6.67] 2.31 [2.83] 4.04 [2.04] 2.12 [1.90] ] cca 6.75] 7.82] 3.50] 6.22] 1.66] ] 3.77] ] loga [3.90] [2.08] 0.01 [2.21] 0.02 [1.58] 0.01 [2.05] 0.09 [1.75] ] [2.25] 0.06 albpbg [5.83] [4.01] [5.65] ] ] ] [3.39] ] glpta [4.16] 0.32 [4.55] 0.33 [4.86] 0.45 [6.08] 0.68 [1.16] 0.47 [3.49] [1.03] 0.00] [2.07] 0.33 Ps 1.15] ] [1.91] 0.04 [3.42] ] ] [0.25] 0.02 [0.02]

8 p ] [7.85] ] ] ] [0.45] ] [0.12] albpb [3.76] 0.20 [3.30] 0.18 [4.07] ] ] [0.40] 0.04 [2.97] ] log_age [2.29] ] ] ] [2.52] ] [0.63] 0.03 R square Observat ions Note: values given in parenthesis are t values and values without parenthesis are coefficients.,,, means significant at 1%, 5% and 10% respectively. 6 Conclusion The coefficient of real gross portfolio yield (the measure of average interest rate to customers) is highly significant and positive across the entire lending model in both profitability indicators (financial self sufficiency and operational self sufficiency) except in diversified lending model. It indicates that SHG, JLG, and Individual tend to be more profitable when their yield on gross portfolio i.e. interest rates are higher. This suggest that increasing rates are clearly associated with improved level of financial performance. capital cost to assets The specification also show that capital cost to assets is negatively associated in both profitability indicators across all lending models except in individual FSS model. It indicates that capital cost to assets is an important factor influencing financial performance of all lending models in India. The result of regression analysis show that that rising capital cost is reduce profitability across all type of lending models. For individual based lenders rising capita cost are related with higher decline in profitability as compared to other lending model. log assets An institution size is positively linked to financial performance except in diversified lending FSS model. The coefficient is highly significant at 1% level in both measure of financial performance of JLG model. However, the coefficient is not strongly related in individual lending model. The coefficient of size is negatively associated and significant at 5% level in only Diversified FSS lending model. This indicates that increase in size of an MFI will lead to increase in financial performance of both type of group lending model. However the relationship is not strongly significant in individual 168

9 lending model though the relationship is positive. Average loan balance per borrower The result of regression analysis shows that average loan amount (GNI adjusted) is negatively associated with and highly significant across all the models except individual lending model. It shows that increasing average loan size sharply reduces financial performance. In order to attain better financial performance, the loan amount that MFIS lend to their clients not to be very big size but of optimal size. Gross loan portfolio to total assets ratio The ratio of loan to assets is positively associated in both the indicators of financial performance across all types of lending models except in one model i.e. Diversified FSS model. This indicates that higher loan to assets ratio positively affects the financial performance. This findings is consistent with Cull et al(2007). Profitability status The coefficient of profitability status is only significant at 1% level in SHG model and Individual lending model this suggest that For Profit organization are not good performer in terms of profitability as compared to Not For Profit Organization in SHG and Individual lending model. In JLG and Diversified relationship is not significant. Average loan balance per borrower The coefficient of Average loan balance per borrower is strongly and positively associated with financial sustainability indicators across all lending model except individual lending model. This indicates that increasing the size of average loan size improves financial sustainability. log age The coefficient of age is positively associated and significant at 5% level with financial self sufficiency in JLG and Individual lending model. This suggests that experienced MFIs are better performer with financial sustainability. It indicates that experienced MFIS following SHG lending model are not better performer in terms of financial performance as compared to JLG and Individual model. 169

10 References Berger, A. N., & Di Patti, E. B. (2006). Capital structure and firm performance: A new approach to testing agency theory and an application to the banking industry, Journal of Banking & Finance, 30(4), Brau, J. C., & Woller, G. M. (2004). Microfinance: A comprehensive review of the existing literature, Journal of Entrepreneurial Finance, JEF, 9(1), Bogan, V., Johnson, W., & Mhlanga, N. (2007). Does capital structure affect the financial sustainability of microfinance institutions, Retrieved on, 7(04), Cull, R., & Morduch, J. (2007).Financial performance and outreach: a global analysis of leading microbanks, The Economic Journal, 117(517), F107-F133. De Crombrugghe, A., Tenikue, M., & Sureda, J. (2008). Performance analysis for a sample of microfinance institutions in India, Annals of Public and Cooperative Economics, 79(2), Gonzalez-Vega, C. (1998), Microfinance: Broader Achievements and New Challenges, Economics and Sociology Occasional Paper No. 2518, Rural Finance Program, The Ohio State University, Columbus, Ohio. Gakhar, K. (2013). Financial performance and outreach of microfinance institutions: is there a tradeoff:an empirical study of indian economy, Global Management Review, 7(4). Hermes, N., & Lensink, R. (2011). Microfinance: its impact, outreach, and sustainability, World development, 39(6), Hartarska, V. (2005) Governance and performance of microfinance institutions in Central and Eastern Europe and the newly independent state, World development, 33(10), Morduch, J. (2000).The microfinance schism, World development, 28(4), Mersland, R., & Strøm, R. Ø. (2009).Performance and governance in microfinance institutions, Journal of Banking & Finance, 33(4), Nyamsogoro, G. D.(2010).Financial sustainability of rural microfinance institutions (MFIs) in Tanzani, (Doctoral dissertation, University of Greenwich). Nadiya M. (2011).An inside View of the Factors Affecting the operational self-sufficiency of Indian Microfinance institutions: A mixed method enquiry, Oikos Foundation for Economy and Ecology. Quayes S.(2012).Depth of outreach and financial sustainability of microfinance institutions, Applied Economics, 44(26), Robinson, M. S. (2001).The microfinance revolution: sustainable finance for the poor, World Bank Publications. 170

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