The Review of Economics and Statistics 2026
Difference-in-Differences Estimators of Intertemporal Treatment Effects
open access
Abstract
We study treatment-effect estimation using panel data. The treatment may be nonbinary, nonabsorbing, and the outcome may be affected by treatment lags. We make a parallel-trends assumption and propose event-study estimators of the effect of being exposed to a weakly higher treatment dose for ℓ periods. We also propose normalized estimators that estimate a weighted average of the effects of the current treatment and its lags. We also analyze commonly used two-way, fixed-effects regressions. Unlike our estimators, they can be biased in the presence of heterogeneous treatment effects. A local-projection version of those regressions is biased even with homogeneous effects.
- DOI
- 10.1162/rest_a_01414
- Pages
- 1-18
- Language
- en
- Sources
- openalex crossref