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Synthetic controls with imperfect pretreatment fit
by
Ferman, Bruno
, Pinto, Cristine Campos de Xavier
in
Bias
/ C13
/ C21
/ C23
/ difference-in-differences
/ Econometrics
/ linear factor model
/ linearfactor model
/ policy evaluation
/ Property
/ Specification
/ Synthetic control
/ Trends
2021
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Do you wish to request the book?
Synthetic controls with imperfect pretreatment fit
by
Ferman, Bruno
, Pinto, Cristine Campos de Xavier
in
Bias
/ C13
/ C21
/ C23
/ difference-in-differences
/ Econometrics
/ linear factor model
/ linearfactor model
/ policy evaluation
/ Property
/ Specification
/ Synthetic control
/ Trends
2021
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Journal Article
Synthetic controls with imperfect pretreatment fit
2021
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Overview
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 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.
Publisher
The Econometric Society,John Wiley & Sons, Inc
Subject
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