Synthetic Difference-in-Differences

Dmitry Arkhangelsky, Susan Athey, David A. Hirshberg, Guido Imbens and Stefan Wager

American Economic Review, 2021, vol. 111, issue 12, 4088-4118

Abstract: We present a new estimator for causal effects with panel data that builds on insights behind the widely used difference-in-differences and synthetic control methods. Relative to these methods we find, both theoretically and empirically, that this "synthetic difference-in-differences" estimator has desirable robustness properties, and that it performs well in settings where the conventional estimators are commonly used in practice. We study the asymptotic behavior of the estimator when the systematic part of the outcome model includes latent unit factors interacted with latent time factors, and we present conditions for consistency and asymptotic normality.

JEL-codes: C23 H25 H71 I18 L66 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (217)

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Related works:
Working Paper: Synthetic Difference in Differences (2019)
Working Paper: Synthetic Difference In Differences (2019)
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DOI: 10.1257/aer.20190159

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