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Impact of Microcredit on the Poor in Bangladesh

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We replicate and reanalyse the most influential study of microcredit impacts (Pitt and Khandker, 1998). That study was celebrated for showing that microcredit reduces poverty, a much hoped-for possibility (though one not confirmed by recent randomized controlled trials). We show that the original results on poverty reduction disappear after dropping outliers, or when using a robust linear estimator. Using a new program for estimation of mixed process maximum likelihood models, we show how assumptions critical for the original analysis, such as error normality, are contradicted by the data. We conclude that questions about impact cannot be answered in these data. 

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Evaluation Fundamentals

Impact evaluations try to measure the change in a participant’s life that occurred because of an intervention. The “intervention” could be a policy, a project, an insurance product, or a specific feature of a product. For instance, the intervention could relate to a particular product feature, such as the extent of coverage, a change of pricing structure, or variations in the distribution channel. . .

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Selective Knowledge: Reporting Bias in Microfinance Data

Answering surveys is usually voluntary, yet much of our knowledge about microfinance depends on the willingness of households and institutions to respond to survey questions. In this study, Financial Access Initiative Managing Director Jonathan Morduch and Jonathan Bauchet explore the implications of voluntary reporting on knowledge about the performance of microfinance institutions, specifically focusing on the MixMarket and Microcredit Summit Campaign databases. They show patterns of systematic biases in microfinance institutions’ choices about which survey to respond to and which specific indicators to report. These patterns in turn affect analyses of key questions on trade-offs between financial and social goals in microfinance. The results highlight the conditional nature of our knowledge and the value of supporting social reporting. 

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Take-up: Why Microfinance Take-up Rates Are Low & Why It Matters

If you listen to the strongest pitches for microfinance, you would imagine that everyone offered microfinance would leap at the chance to be a customer. Yet this is not so. Evidence shows that it’s usual that under half of eligible households participate in microfinance. Moneylenders are still in business, and many individuals in develop- ing countries still rely primarily on family and friends to meet their needs for money. This is not necessarily a bad thing: informal sources of credit provide a useful way to finance profitable investments or respond to life events. But it shows that the demand for existing microfinance institutions and products can’t be taken for granted.

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Research Methodologies: A Closer Look at the Research behind Portfolios of the Poor

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Portfolios of the Poor offers new thinking about how the world’s poorest communities manage their financial lives. To uncover these intimate details, researchers designed a study in which they interviewed poor households twice a month over the course of a year, and recorded the details of how they lived their financial lives. These “financial diaries” encompass data from nearly 250 households in Bangladesh, India, and South Africa, and reflect a mixed-research methodology that is systematic in data collection while simultaneously captures the complexity of people’s lives. 

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The Impact of Microcredit on the Poor in Bangladesh: Revisiting the Evidence, Brief

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Microcredit is commonly credited with reducing poverty, empowering women, and delivering other important impacts, particularly to extremely poor house- holds. Rhetoric, however, has outpaced evidence. Empirical studies are scarce, and existing ones have been influential despite a lack of thorough scrutiny. In this paper, David Roodman and FAI managing director Jonathan Morduch attempt to replicate the two most-noted studies on the impact of microcredit, both based on survey data from Bangladesh collected in the 1990s. Pitt and Khandker (PK, 1998) find that microcredit raises household consumption, especially when lent to women. Khandker (2005) concurs and goes further to say that microcredit has more of an impact on the extremely poor than on the moderately poor. Morduch (1998) finds no evidence for impact on consumption levels, but does find that microcredit. decreases the volatility of consumption. This paper shows that the evidence for impact is weak in all of these studies. But, significantly, it doesn’t find that microcredit causes harm, and it doesn’t prove that the impacts commonly attributed to microcredit—like reducing poverty and empowering women—do not exist. Rather, this paper shows that it’s hard to draw much from these data—and that better answers will need to come from other data sets using other methods.