Synthetic Controls with Imperfect Pre-Treatment Fit
Bruno Ferman and
Cristine Pinto ()
Papers from arXiv.org
We analyze the properties of the Synthetic Control (SC) and related estimators when the pre-treatment fit is imperfect. In this framework, we show that these estimators are generally biased if treatment assignment is correlated with unobserved confounders, even when the number of pre-treatment periods goes to infinity. Still, we show that a demeaned version of the SC method can substantially improve in terms of bias and variance relative to the difference-in-difference estimator. We also derive a specification test for the demeaned SC estimator in this setting with imperfect pre-treatment fit. Given our theoretical results, we provide practical guidance for applied researchers on how to justify the use of such estimators in empirical applications.
Date: 2019-11, Revised 2021-01
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1911.08521
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