Aggregating Distributional Treatment Effects: A Bayesian Hierarchical Analysis of the Microcredit Literature
开发贝叶斯分层模型来汇总小额信贷对家庭利润在不同分位数上的影响，发现第5至75分位数效应精确为零，上尾效应不确定但较大，尤其对有商业经验的家庭。
Expanding credit access in developing contexts could help some households while harming others. Microcredit studies show different effects at different quantiles of household profit, including some negative effects; yet these findings also differ across studies. I develop new Bayesian hierarchical models to aggregate the evidence on these distributional effects for mixture-type outcomes such as household profit. Applying them to microcredit, I find a precise zero effect from the fifth to seventy-fifth quantiles, and uncertain yet large effects on the upper tails, particularly for households with business experience. These quantile estimates are more reliable than averages because the data are fat tailed.