Targeted instruction is one of the most effective educational interventions in low- and middle-income countries, yet reported impacts vary by an order of magnitude. We study this variation by aggregating evidence from prior randomized trials across five contexts, and use the results to inform a...

This paper assembles a panel data set that measures cognitive achievement for 128 countries around the world from 1965 to 2010 in 5-year intervals. The data set is constructed from international achievement tests, such as the Programme for International Student Assessment and the Trends in...

Bayesian hierarchical models serve as a standard methodology for aggregation and synthesis, used widely in statistics and other disciplines. I use this framework to aggregate the data from seven randomised experiments of expanding access to microcredit, assessing both the general impact of the...

This paper shows that market fragility and mass default can arise in microcredit markets as a result of the strategic interaction between a microlender using a reputation-based mechanism and a traditional lender using physical collateral. In our model, borrowers solve a dynamic programming...

Policymakers often test expensive new programs on relatively small samples. Formally incorporating informative Bayesian priors into impact evaluation offers the promise to learn more from these experiments. A Colombian government program which aimed to increase exporting was trialed...