Anatomy of Event Studies: Hypothetical Experiments, Exact Decomposition, and Robust Estimation
Conference
65th ISI World Statistics Congress 2025
Format: IPS Abstract - WSC 2025
Keywords: causal inference, observational studies, regression, weighting
Session: IPS 674 - The Role of Statistics and Data Science in Impact Evaluation
Tuesday 7 October 10:50 a.m. - 12:30 p.m. (Europe/Amsterdam)
Abstract
In recent decades, event studies have emerged as a central methodology in health and social research for evaluating the causal effects of staggered interventions. In this paper, we analyze event studies from the perspective of experimental design and provide an alternative approach for estimating causal contrasts. As a particular case of this approach, we offer a novel decomposition of the classical dynamic two-way fixed effects (TWFE) regression estimator for event studies. Our decomposition is expressed in closed form and reveals in finite samples the hypothetical experiment that TWFE regression adjustments approximate. This decomposition offers insights into how standard regression estimators borrow information from various units and time points, clarifying and generalizing the notion of forbidden comparison noted in the literature in simpler settings. We propose a robust weighting approach for estimation in event studies, which allows investigators to progressively build larger valid weighted contrasts by leveraging, in a sequential manner, increasingly stronger assumptions on the potential outcomes and the treatment assignment mechanisms. This weighting approach also allows for the generalization of treatment effect estimates to a target population. We provide diagnostics and visualization tools and illustrate these methods in a case study of the impact of divorce reforms on female suicide.