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An Empirical Analysis of Microfinance: Who are the Clients?

论文编号:lw200701051115103769 所属栏目:微观经济学论文 发布日期:2018年01月15日 论文作者:无忧论文网
An Empirical Analysis of Microfinance: Who are the Clients? 1. Introduction Major projects by the World Bank and the US Agency for International Development (USAID), and smaller undertakings by non-governmental organizations (NGOs) seek to catalog the benefits of microenterprise finance. From the beginning, Mohammed Yunnis, the founder of the Grameen Bank in Bangladesh, has proposed that there is a sustainable way to lend to poor microentrepreneurs. USAID’s research efforts are centered in the AIMS Project, Assessing the Impact of Microenterprise Services, which proposes that microfinance services will impact not only the microentrepreneur who takes the loan, but her household, enterprise and community (Chen and Dunn 1996, Dunn 1999). Despite these widely held beliefs about the benefits of microfinance, these institutions are now under increasing pressure to provide proof to skeptics and government budget makers that credit programs are a cost-effective way to assist the poor in their own economic development. These recent studies aim to prove, unequivocally, that entrepreneurs who access credit have larger incomes, higher standards of living, more diversified income sources, and a better self-image as a direct result of the loans that they receive. This hasn't been easy. Although proponents of microfinance like to assert that they are assisting the poorest of the working poor, early evidence is stating otherwise. In a study of four microfinance institutions operating in the Philippines, Uganda, Bolivia and Bangladesh, most of the microenterprise clients were clustered around the poverty line (those just below the poverty line and the “vulnerable non-poor” households) (CGAP 2000b). The Consultative Group to Assist the Poorest (CGAP 2000a) finds the same clustering among MFIs in East Africa, which may suggest that the claims of the proponents of microfinance need to be curtailed: they are indeed helping the poor, but something will need to change before they can say truthfully that they are helping the ‘poorest of the poor’. These findings by CGAP relate to the findings of the dynamic model of microfinance in the previous essay, which indicated that we may expect pre-existing differences between entrepreneurs who choose to access credit and those who do not. First, for a given level of risk, a more profitable microentrepreneur will seek credit, and a less profitable microentrepreneur may not find it optimal to apply for a loan. Second, for microentrepreneurs with the same level of profitability, a borrower pool who faces lower risk or has the means to deal economically with that risk, will find it optimal to borrow and will able to do so, while those who are more risk-prone will not be able to afford the high interest rates that sustainability requires. Microfinance clients, especially those who are participants in lending programs that do not rely on group-based incentives, are more likely to operate businesses that have a higher cash flow, and are less prone and susceptible to adverse economic shocks—meaning that they are also more likely to be at or above the poverty line. For the microfinance institution, having such clients—ones with better businesses and lower levels of risk—will enable them to operate at sustainable levels. Thus, the model’s implications support the fears of economists that selection bias is prevalent among microfinance programs. Upon inspection, it is easy to see that two potential selection problems could cloud impact results . First, the self selection of entrepreneurs into a lending program may mar results of impact assessments. Microentrepreneurs who borrow may have unobservable traits, such as more entrepreneurial ability, that would make them more likely to have higher levels of the impact variables, even without access to credit. Secondly, program placement across a region may not be random: programs may be located where the prospects of repayment are high, such as areas