Aggregating Distributional Treatment Effects: A Bayesian Hierarchical Analysis of the Microcredit Literature

Expanding credit access in developing contexts could help some households while harming others. Microcredit studies show different effects at quantiles of household profit, including negative effects; yet these findings also differ across studies. I develop new Bayesian hierarchical models to aggregate the evidence on distributional for mixture-type outcomes such as profit. Applying them microcredit, find a precise zero effect from fifth seventy-fifth quantiles, and uncertain large upper tails, particularly with business experience. These quantile estimates are more reliable than averages because data fat tailed. (JEL G21, G51, L25, O16, P34)