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On the role of covariates in the synthetic control method

Author

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  • Irene Botosaru
  • Bruno Ferman

Abstract

SummaryAbadie 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.

Suggested Citation

  • Irene Botosaru & Bruno Ferman, 2019. "On the role of covariates in the synthetic control method," Econometrics Journal, Royal Economic Society, vol. 22(2), pages 117-130.
  • Handle: RePEc:oup:emjrnl:v:22:y:2019:i:2:p:117-130.
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    1. Laurent Gobillon & Thierry Magnac, 2016. "Regional Policy Evaluation: Interactive Fixed Effects and Synthetic Controls," The Review of Economics and Statistics, MIT Press, vol. 98(3), pages 535-551, July.
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    10. Susan Athey & Mohsen Bayati & Nikolay Doudchenko & Guido Imbens & Khashayar Khosravi, 2021. "Matrix Completion Methods for Causal Panel Data Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(536), pages 1716-1730, October.
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    18. Abadie, Alberto & Diamond, Alexis & Hainmueller, Jens, 2010. "Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California’s Tobacco Control Program," Journal of the American Statistical Association, American Statistical Association, vol. 105(490), pages 493-505.
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    More about this item

    Keywords

    Synthetic controls; covariates; perfect balance;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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