Interpreting Event-Studies from Recent Difference-in-Differences Methods
Jonathan Roth
TL;DR
The paper demonstrates that event-study plots from modern difference-in-differences estimators (notably CS and BJS) diverge from traditional TWFE plots even without staggered timing, due to asymmetric pre-/post-treatment construction. It provides a formal comparison of dynamic TWFE, CS, and BJS, and uses simulations to show that standard visual-inference heuristics can be misleading when applied to these newer estimators. Practical recommendations are offered to improve interpretability (e.g., symmetric pre-treatment specification for CS) and to separate testing from estimation in BJS, along with broader guidance for both non-staggered and staggered contexts. The work emphasizes that understanding estimator design is crucial for reliable visual inference in DiD analyses and offers concrete steps to enhance interpretability of event-study plots.
Abstract
This note discusses the interpretation of event-study plots produced by recent difference-in-differences methods. I show that even when specialized to the case of non-staggered treatment timing, the default plots produced by software for several of the most popular recent methods do not match those of traditional two-way fixed effects (TWFE) event-studies. The plots produced by the new methods may show a kink or jump at the time of treatment even when the TWFE event-study shows a straight line. This difference stems from the fact that the new methods construct the pre-treatment coefficients asymmetrically from the post-treatment coefficients. As a result, visual heuristics for evaluating violations of parallel trends using TWFE event-study plots should not be immediately applied to those from these methods. I conclude with practical recommendations for constructing and interpreting event-study plots when using these methods.