A dynamic discrete choice model is set up to estimate the effects of grade retention in high school, both in the short- (end-of-year evaluation) and long-run (drop-out and delay). In contrast to regression discontinuity designs, this approach captures treatment heterogeneity and controls for...

Program evaluations often focus on average treatment effects. However, average treatment effects miss important aspects of policy evaluation, such as the impact on inequality and whether treatment harms some individuals. A growing literature develops methods to evaluate such issues by examining...

In this paper we investigate the causal effect of life expectancy on economic growth by explicitly accounting for the role of the demographic transition. In addition to focusing on issues of empirical identification, this paper emphasizes the role of the econometric specification. We present a...

We document substantial variation in the effects of a highly-effective literacy program in northern Uganda. The program increases test scores by 1.4 SDs on average, but standard statistical bounds show that the impact standard deviation exceeds 1.0 SD. This implies that the variation in effects...

Binary treatments are often ex-post aggregates of multiple treatments or can be disaggregated into multiple treatment versions. Thus, effects can be heterogeneous due to either effect or treatment heterogeneity. We propose a decomposition method that uncovers masked heterogeneity, avoids...

We propose a complete framework for model-free difference-in-differences analysis with covariates, where model-free means data-driven, in particular nonparametric estimation and testing, variable and scale choice. We start with searching for the preferred data setup by simultaneously choosing...

We propose a simple, distribution-free method for pooling synthetic control case studies using the mean percentile rank. We also test for heterogeneous treatment effects using the distribution of estimated ranks, which has a known form. We propose a cross-validation based procedure for model...

Estimation, inference and interpretation of the causal effects of programs and policies have all advanced dramatically over the past 25 years. We highlight three particularly important intellectual trends: an improved appreciation of the substantive importance of heterogeneous responses and of...

We propose a simple, distribution-free method for pooling synthetic control case studies using the mean percentile rank. We also test for heterogeneous treatment effects using the distribution of estimated ranks, which has a known form. We propose a cross-validation based procedure for model...