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Two-Way Fixed Effects Estimators with Heterogeneous Treatment Effects

American Economic Review · 2020 · Vol. 110(9) · pp. 2964–2996

Clément de Chaisemartin✉(University of California, Santa Barbara)Xavier D’Haultfœuille(ENSAE Paris)

Abstract

Linear regressions with period and group fixed effects are widely used to estimate treatment effects. We show that they estimate weighted sums of the average treatment effects (ATE ) in each group and period, with weights that may be negative. Due to the negative weights, the linear regression coefficient may for instance be negative while all the ATEs are positive. We propose another estimator that solves this issue. In the two applications we revisit, it is significantly different from the linear regression estimator. (JEL C21, C23, D72, J31, J51, L82)

Advanced Causal Inference Techniques Economic Policies and Impacts Media Influence and PoliticsEstimatorLinear regressionEconometricsMathematicsRegressionEconomicsStatisticsFixed effects modelAverage treatment effectPanel data

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