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Abstract: 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. (JEL: C21, C23, C24, C25, O12, O16) 1 We thank Mark Pitt for assistance with data and comments on earlier versions; Maren Duvendack and Richard Palmer-Jones for scrutiny of our data set construction; and Xavier Giné, Dean Karlan, and anonymous referees for reviews. Correspondence: droodman@gmail.com. The Impact of Microcredit on the Poor in Bangladesh: Revisiting the Evidence Over the last few decades, microcredit has captured millions of customers, billions of dollars
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