Doubly Robust Difference-in-Differences Estimators

35 Pages Posted: 18 Dec 2018 Last revised: 7 May 2020

See all articles by Pedro H. C. Sant'Anna

Pedro H. C. Sant'Anna

Vanderbilt University - College of Arts and Science - Department of Economics

Jun B. Zhao

Vanderbilt University - College of Arts and Science - Department of Economics

Date Written: November 29, 2018

Abstract

This article proposes doubly robust estimators for the average treatment effect on the treated (ATT) in difference-in-differences (DID) research designs. In contrast to alternative DID estimators, the proposed estimators are consistent if either (but not necessarily both) a propensity score or outcome regression working models are correctly specified. We also derive the semiparametric efficiency bound for the ATT in DID designs when either panel or repeated cross-section data are available, and show that our proposed estimators attain the semiparametric efficiency bound when the working models are correctly specified. Furthermore, we quantify the potential efficiency gains of having access to panel data instead of repeated cross-section data. Finally, by paying particular attention to the estimation method used to estimate the nuisance parameters, we show that one can sometimes construct doubly robust DID estimators for the ATT that are also doubly robust for inference. Simulation studies and an empirical application illustrate the desirable finite-sample performance of the proposed estimators. Open-source software for implementing the proposed policy evaluation tools is available.

Keywords: Causal Inference, Natural Experiments, Policy Evaluation, Treatment Effects

JEL Classification: C31

Suggested Citation

Sant'Anna, Pedro H. C. and Zhao, Jun B., Doubly Robust Difference-in-Differences Estimators (November 29, 2018). Available at SSRN: https://ssrn.com/abstract=3293315 or http://dx.doi.org/10.2139/ssrn.3293315

Pedro H. C. Sant'Anna (Contact Author)

Vanderbilt University - College of Arts and Science - Department of Economics ( email )

Box 1819 Station B
Nashville, TN 37235
United States

HOME PAGE: http://https://sites.google.com/site/pedrohcsantanna/

Jun B. Zhao

Vanderbilt University - College of Arts and Science - Department of Economics ( email )

Box 1819 Station B
Nashville, TN 37235
United States

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