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α: calibrated so average coauthorship-adjusted count equals average raw count
What accounts for the discrepancy between microfinance impact claims of development practitioners and the far smaller impacts found in experimental studies? We demonstrate in a simple theoretical framework why “before-and-after” observations of practitioners overstate microfinance impacts and why estimations in some recent randomized trials understate the average treatment effect on the treated (ATT). Our empirical study uses a unique data set from eastern Nepal to study the impact of microfinance in villages where microfinance did not previously exist. We find that approximately three-fourths of the apparent impact of microfinance observed by practitioners is an illusion driven by correlated unobservable factors.