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

Rachael Meager

American Economic Review, 2022, vol. 112, issue 6, 1818-47

Abstract: 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.

JEL-codes: G21 G51 L25 O16 P34 (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations: View citations in EconPapers (13)

Downloads: (external link)
https://www.aeaweb.org/doi/10.1257/aer.20181811 (application/pdf)
https://doi.org/10.3886/E155821V1 (text/html)
https://www.aeaweb.org/doi/10.1257/aer.20181811.appx (application/pdf)
https://www.aeaweb.org/doi/10.1257/aer.20181811.ds (application/zip)
Access to full text is restricted to AEA members and institutional subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:aea:aecrev:v:112:y:2022:i:6:p:1818-47

Ordering information: This journal article can be ordered from
https://www.aeaweb.org/journals/subscriptions

DOI: 10.1257/aer.20181811

Access Statistics for this article

American Economic Review is currently edited by Esther Duflo

More articles in American Economic Review from American Economic Association Contact information at EDIRC.
Bibliographic data for series maintained by Michael P. Albert ().