Synthetic Difference in Differences

Fuente: arXiv
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Auteurs principaux: Arkhangelsky, Dmitry, Athey, Susan, Hirshberg, David A., Imbens, Guido W., Wager, Stefan
Format: Preprint
Publié: 2018
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author Arkhangelsky, Dmitry
Athey, Susan
Hirshberg, David A.
Imbens, Guido W.
Wager, Stefan
author_facet Arkhangelsky, Dmitry
Athey, Susan
Hirshberg, David A.
Imbens, Guido W.
Wager, Stefan
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_1812_09970
institution arXiv
publishDate 2018
record_format arxiv
spellingShingle Synthetic Difference in Differences
Arkhangelsky, Dmitry
Athey, Susan
Hirshberg, David A.
Imbens, Guido W.
Wager, Stefan
Methodology
Econometrics
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.
title Synthetic Difference in Differences
topic Methodology
Econometrics
url https://arxiv.org/abs/1812.09970