Two-Way Fixed Effects Estimators with Heterogeneous Treatment Effects

Clément de Chaisemartin, Xavier D’HaultfœuilleEconomics计量经济学FT50

American Economic Review2020-09-01University of California, Santa Barbara; ENSAE Paris; Centre for Research in Engineering Surface Technology; Center for Responsible Travel; Centre de Recherche en Économie et StatistiqueDOI

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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)

EstimatorLinear regressionEconometricsMathematicsRegressionEconomicsStatisticsFixed effects modelAverage treatment effectPanel dataAdvanced Causal Inference TechniquesEconomic Policies and Impacts