Rachael Meager

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I am an Assistant Professor in the Economics Department at the London School of Economics and Political Science with research interests in development economics and econometrics. I work on applied Bayesian modelling of treatment effect heterogeneity at multiple levels within data sets and literatures, with the goal of measuring generalisability and quantifying uncertainty around our knowledge base in development economics. My recent work has focused on aggregating evidence on distributional treatment effects using sets of quantiles or parametric generating models within a Bayesian hierarchical framework. My research in progress is focused on linking group-level distributional effects to individual heterogeneity with high-dimensional covariates using AI/ML methods, selection bias within and across literatures in development economics, and developing robustness metrics for empirical analysis. I hope this work will both improve our understanding of the social and economic systems around us, and improve decision-making under uncertainty for governments, socially-minded businesses and NGOS.

My papers are below. My CV is here. My code and data are here. Any announcements are here.

Economics Publications, Accepted Papers and Pre-Registrations

"Understanding the Average Impact of Microcredit Expansions: A Bayesian Hierarchical Analysis of Seven Randomized Experiments" The American Economic Journal: Applied Economics, January 2019.

Voxdev piece I wrote explaining this article for a general audience can be found here

"What are the Effects of Improving Management Practices on Exporting among SMEs in Middle-Income Countries*? A Comparison of Bayesian and Frequentist Impact Evaluation Approaches" with David McKenzie, Leonardo Iacovone, and Darío Rodríguez Pérez Accepted at the Journal of Development Economics based on the pre-registration report https://www.bitss.org/publishing/rr-jde-about/prospective-articles/ ; eventual publication venue TBD

"Competing Lending Platforms, Endogenous Reputation, and Fragility in Microcredit Markets" with Peter Bardsley, The European Economic Review, 2019

CS/ML Conference Publications

"Fast robustness quantification with variational Bayes" with Ryan Giordano, Tamara Broderick, Jonathan Huggins and Michael Jordan, 2016 ICML Workshop on #Data4Good: Machine Learning in Social Good Applications, New York, NY

Working Papers

"Aggregating Distributional Treatment Effects: A Bayesian Hierarchical Analysis of the Microcredit Literature" (submitted)

Online Appendix for Aggregating Distributional Treatment Effects

Vitamin A Supplements and Child Mortality: Resolving a Controversy in Meta-analysis (Paper completed but embargoed, draft available by email)

Selected Work In Progress

"Combining Experimental and Observational Studies in Meta-Analysis: Leveraging Experimental Structures to Eliminate Selection Bias" with Michael Gechter

"A Multifaceted Approach to Poverty Alleviation in Six Countries: A Bayesian Hierarchical Analysis of the Graduation Program" with Andrew Gelman, Dean Karlan, Chris Udry and Witold Wiecek

"Automatic Finite-Sample Robustness Techniques" with Ryan Giordano and Tamara Broderick