Title: “Verifying the internal validity of a flagship RCT: A review of Crépon, Devoto, Duflo and Parienté”: A rejoinder

Type Dataset Crépon, Bruno, Devoto, Florencia, Duflo, Esther, Parienté, William (2019): “Verifying the internal validity of a flagship RCT: A review of Crépon, Devoto, Duflo and Parienté”: A rejoinder. Harvard Dataverse. Dataset. https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/C6OW6C

Authors: Crépon, Bruno (Centre de Recherche en Économie et Statistique) ; Devoto, Florencia (Abdul Latif Jameel Poverty Action Lab) ; Duflo, Esther (Massachusetts Institute of Technology) ; Parienté, William (Universite Catholique de Louvain) ; Crépon, Bruno (Centre de Recherche en Économie et Statistique) ; Devoto, Florencia (Abdul Latif Jameel Poverty Action Lab) ; Duflo, Esther (Massachusetts Institute of Technology) ; Parienté, William (Universite Catholique de Louvain) ;

Links

• Item record in Abdul Latif Jameel Poverty Action Lab Dataverse
• Digital object URL

Summary

In a recent paper, Bédecarrats, Guerin, Morvan-Roux and Roubaud (2019) re- analyze the data from a randomized controlled trial of the impact of the program of Al Amana, a microcredit organization in Morocco, which we published in 2015 (Crépon, Devoto, Duflo, and Parienté, 2015). They make a number of strong claims about the validity of our approach, and the lack of robustness of our results to alternative assumptions. In this paper, we argue that their own quantitative results in fact demonstrate the robustness of our initial analysis. We question several of their suggested modifications to our analysis. Finally, in the spirit of serious scholarship, we provide our own candid re-analysis of our data, with more robust methods. Overall, our careful analysis of their paper, their code, and our own data suggest that the results we presented in our 2015 paper are in fact quite robust, contrary to what is claimed in their paper. In particular, we find strong support for large impacts on top quantiles of business profits, assets, and sales, no effect at the lower quantiles, a result that is robust to the method used for inference. Due to fat upper tail of the distribution of profit, the average treatment effect on profit is noisier than standard inference methods imply. Impacts on average treatment effects for the other business variables remain significant no matter the method used for inference. We continue to find off-settings effect on labor supply and no impact on average per capita consumption.

More information

• DOI: 10.7910/DVN/C6OW6C

Subjects

• Social Sciences

Dates

• Publication date: 2019
• Submitted: October 07, 2019
• Updated: October 28, 2019

Rights

• info:eu-repo/semantics/openAccess
• https://creativecommons.org/publicdomain/zero/1.0/ CC0 Waiver

Format

electronic resource