Working Paper: NBER ID: w29691
Authors: Clément de Chaisemartin; Xavier Dhaultfoeuille
Abstract: Linear regressions with period and group fixed effects are widely used to estimate policies' effects: 26 of the 100 most cited papers published by the American Economic Review from 2015 to 2019 estimate such regressions. It has recently been show that those regressions may produce misleading estimates, if the policy's effect is heterogeneous between groups or over time, as is often the case. This survey reviews a fast-growing literature that documents this issue, and that proposes alternative estimators robust to heterogeneous effects.
Keywords: two-way fixed effects; regressions; differences-in-differences; parallel trends; heterogeneous treatment effects; panel data; repeated cross-section data; policy evaluation
JEL Codes: C21; C23
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Traditional TWFE regressions (C29) | Biased estimates of treatment effects (C21) |
| Heterogeneous treatment effects (C21) | Biased estimates of treatment effects (C21) |
| Failure of parallel trends assumption (C22) | Misleading conclusions (G41) |
| TWFE estimators (C51) | Biased for the average treatment effect on the treated (ATT) (C22) |