Two-Way Fixed Effects Estimators with Heterogeneous Treatment Effects

63 Pages Posted: 24 Mar 2018 Last revised: 6 Aug 2018

Clement de Chaisemartin

University of California, Santa Barbara

Xavier D'Haultfœuille

National Institute of Statistics and Economic Studies (INSEE) - Center for Research in Economics and Statistics (CREST)

Date Written: August 2, 2018

Abstract

Linear regressions with time and group fixed effects are widely used to estimate treatment effects. We show that they identify weighted sums of the average treatment effects in each group and period, with weights that can be estimated, and that may be negative. In two articles that have used those regressions, half of the weights are negative, thus suggesting that those regressions are often not robust to heterogeneous treatment effects across groups and over time. We propose another estimator that is robust to heterogeneous treatment effects. In an application, it is of a different sign than the linear regression estimator.

Keywords: Fixed Effects, First Difference, Differences-in-Differences, Heterogeneous Treatment Effects

JEL Classification: C21, C26

Suggested Citation

de Chaisemartin, Clement and d'Haultfoeuille, Xavier, Two-Way Fixed Effects Estimators with Heterogeneous Treatment Effects (August 2, 2018). Available at SSRN: https://ssrn.com/abstract=3148607 or http://dx.doi.org/10.2139/ssrn.3148607

Clement De Chaisemartin (Contact Author)

University of California, Santa Barbara ( email )

Santa Barbara, CA 93106
United States

Xavier D'Haultfoeuille

National Institute of Statistics and Economic Studies (INSEE) - Center for Research in Economics and Statistics (CREST) ( email )

15 Boulevard Gabriel Peri
Malakoff Cedex, 1 92245
France

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