Working Paper: NBER ID: w29734
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 shown 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. We use those alternative estimators to revisit Wolfers (2006a).
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 |
|---|---|
| TWFE regressions may produce biased estimates (C51) | incorrect average treatment effect (ATE) estimates (C22) |
| treatment effects are heterogeneous across groups or over time (C32) | TWFE regressions may produce biased estimates (C51) |
| the assumption of constant treatment effects across groups and time is often unrealistic (C22) | bias in TWFE estimates (C51) |
| the limitations of TWFE regressions (C51) | the need for alternative methods (Q42) |
| alternative methods can yield more accurate results than traditional TWFE regressions when assumptions of TWFE do not hold (C51) | more reliable estimates (C51) |