When estimating causal effects using observational data, it is desirable to replicate a
randomized experiment as closely as possible by obtaining treated and control groups with …

Propensity score matching (PSM) has become a popular approach to estimate causal
treatment effects. It is widely applied when evaluating labour market policies, but empirical …

This paper synthesizes recent advances in the econometrics of difference-in-differences
(DiD) and provides concrete recommendations for practitioners. We begin by articulating a …

In this article, we consider identification, estimation, and inference procedures for treatment
effect parameters using Difference-in-Differences (DiD) with (i) multiple time periods,(ii) …

To estimate the dynamic effects of an absorbing treatment, researchers often use two-way
fixed effects regressions that include leads and lags of the treatment. We show that in …

This paper proposes tools for robust inference in difference-in-differences and event-study
designs where the parallel trends assumption may be violated. Instead of requiring that …

We use the synthetic control method to analyze the effect of face masks on the spread of
COVID-19 in Germany. Our identification approach exploits regional variation in the point in …

This article proposes doubly robust estimators for the average treatment effect on the treated
(ATT) in difference-in-differences (DID) research designs. In contrast to alternative DID …

We summarize the estimates from over 200 recent studies of active labor market programs.
We classify the estimates by type of program and participant group, and distinguish between …

This book provides the most comprehensive treatment to date of microeconometrics, the
analysis of individual-level data on the economic behavior of individuals or firms using …