On the role of covariates in the synthetic control method
By Irene Botosaru, Bruno Ferman. Econometrics Journal, 2019
116 citations recorded by the source corpus.
Abadie et al. (2010) derive bounds on the bias of the synthetic control estimator under a perfect balance assumption on both observed covariates and pre-treatment outcomes. In the absence of a perfect balance on covariates, we show that it is still possible to derive such bounds, albeit at the expense of relying on stronger assumptions about the effects of observed and unobserved covariates and of generating looser bounds. We also show that a perfect balance on pre-treatment outcomes does not generally imply an approximate balance for all covariates, even when they are all relevant. Our results have important implications for the implementation of the method.
Subfields: Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/3abd2f68057fca9dc08215c38fb17562667dcfbe
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In Statistics and Probability
- Bruno Ferman
- Cristine Pinto
- Avi Feller
- Eli Ben-Michael
- Jesse M. Rothstein
- Stefan Wager
- Alberto Abadie
- Susan Athey
Citations in the corpus
- Synthetic controls with imperfect pretreatment fit (2016, background): “Botosaru and Ferman (2019) analyzed the case in which the perfect balance on covariates assumption is dropped, but there is still perfect balance on pretreatment outcomes. weights w̃∗ as a “perfect pretreatment fit” condition.”
- The Augmented Synthetic Control Method (2018, background): “Botosaru and Ferman (2017) and Kaul et al. (2018) explore the role of auxiliary covariates in SCM and note several pathologies. Ferman and Pinto (2018) consider the behavior of SCM when the weights fail to exactly balance the lagged outcomes, showing that the resulting SCM weights do not converge to”
- On the Properties of the Synthetic Control Estimator with Many Periods and Many Controls (2019, methodology): “Botosaru and Ferman (2019) and Powell (2021) also considered the properties of the SC and related estimators under a perfect pretreatment fit condition.”