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Article Dans Une Revue Journal of Econometrics Année : 2023

Two-way fixed effects and differences-in-differences estimators with several treatments

Résumé

We study two-way-fixed-effects regressions (TWFE) with several treatment variables. Under a parallel trends assumption, we show that the coefficient on each treatment identifies a weighted sum of that treatment's effect, with possibly negative weights, plus a weighted sum of the effects of the other treatments. Thus, those estimators are not robust to heterogeneous effects and may be contaminated by other treatments' effects. We further show that omitting a treatment from the regression can actually reduce the estimator's bias, unlike what would happen under constant treatment effects. We propose an alternative difference-indifferences estimator, robust to heterogeneous effects and immune to the contamination problem. In the application we consider, the TWFE regression identifies a highly non-convex combination of effects, with large contamination weights, and one of its coefficients significantly differs from our heterogeneity-robust estimator.
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Dates et versions

hal-04187969 , version 1 (25-08-2023)
hal-04187969 , version 2 (29-08-2023)

Licence

Paternité - Pas d'utilisation commerciale - Pas de modification

Identifiants

Citer

Clément de Chaisemartin, Xavier D’haultfœuille. Two-way fixed effects and differences-in-differences estimators with several treatments. Journal of Econometrics, 2023, 236 (2), pp.105480. ⟨10.1016/j.jeconom.2023.105480⟩. ⟨hal-04187969v2⟩
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