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Synthetic Controls in Action

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  • Alberto Abadie
  • Jaume Vives-i-Bastida

Abstract

In this article we propose a set of simple principles to guide empirical practice in synthetic control studies. The proposed principles follow from formal properties of synthetic control estimators, and pertain to the nature, implications, and prevention of over-fitting biases within a synthetic control framework, to the interpretability of the results, and to the availability of validation exercises. We discuss and visually demonstrate the relevance of the proposed principles under a variety of data configurations.

Suggested Citation

  • Alberto Abadie & Jaume Vives-i-Bastida, 2022. "Synthetic Controls in Action," Papers 2203.06279, arXiv.org.
  • Handle: RePEc:arx:papers:2203.06279
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    File URL: http://arxiv.org/pdf/2203.06279
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    References listed on IDEAS

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    1. Acemoglu, Daron & Johnson, Simon & Kermani, Amir & Kwak, James & Mitton, Todd, 2016. "The value of connections in turbulent times: Evidence from the United States," Journal of Financial Economics, Elsevier, vol. 121(2), pages 368-391.
    2. Eli Ben-Michael & Avi Feller & Jesse Rothstein, 2021. "The Augmented Synthetic Control Method," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(536), pages 1789-1803, October.
    3. Dmitry Arkhangelsky & Susan Athey & David A. Hirshberg & Guido W. Imbens & Stefan Wager, 2021. "Synthetic Difference-in-Differences," American Economic Review, American Economic Association, vol. 111(12), pages 4088-4118, December.
    4. 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.
    5. Bruno Ferman, 2021. "On the Properties of the Synthetic Control Estimator with Many Periods and Many Controls," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(536), pages 1764-1772, October.
    6. John J. Donohue & Abhay Aneja & Kyle D. Weber, 2019. "Right‐to‐Carry Laws and Violent Crime: A Comprehensive Assessment Using Panel Data and a State‐Level Synthetic Control Analysis," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 16(2), pages 198-247, June.
    7. Victor Chernozhukov & Kaspar Wüthrich & Yinchu Zhu, 2021. "An Exact and Robust Conformal Inference Method for Counterfactual and Synthetic Controls," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(536), pages 1849-1864, October.
    8. Scott Cunningham & Manisha Shah, 2018. "Decriminalizing Indoor Prostitution: Implications for Sexual Violence and Public Health," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 85(3), pages 1683-1715.
    9. Bruno Ferman & Cristine Pinto, 2021. "Synthetic controls with imperfect pretreatment fit," Quantitative Economics, Econometric Society, vol. 12(4), pages 1197-1221, November.
    10. Alberto Abadie, 2021. "Using Synthetic Controls: Feasibility, Data Requirements, and Methodological Aspects," Journal of Economic Literature, American Economic Association, vol. 59(2), pages 391-425, June.
    11. Nikolay Doudchenko & Guido W. Imbens, 2016. "Balancing, Regression, Difference-In-Differences and Synthetic Control Methods: A Synthesis," NBER Working Papers 22791, National Bureau of Economic Research, Inc.
    12. Cheng Hsiao & H. Steve Ching & Shui Ki Wan, 2012. "A Panel Data Approach For Program Evaluation: Measuring The Benefits Of Political And Economic Integration Of Hong Kong With Mainland China," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(5), pages 705-740, August.
    13. 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.
    14. King, Gary & Zeng, Langche, 2006. "The Dangers of Extreme Counterfactuals," Political Analysis, Cambridge University Press, vol. 14(2), pages 131-159, April.
    15. Alberto Abadie & Jérémy L’Hour, 2021. "A Penalized Synthetic Control Estimator for Disaggregated Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(536), pages 1817-1834, October.
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    Cited by:

    1. Grier, Kevin & Mahmood, Towhid & Powell, Benjamin, 2023. "Anti-sweatshop activism and the safety-employment tradeoff: Evidence from Bangladesh's Rana Plaza disaster," Journal of Economic Behavior & Organization, Elsevier, vol. 208(C), pages 174-190.
    2. Ignacio Martinez & Jaume Vives-i-Bastida, 2022. "Bayesian and Frequentist Inference for Synthetic Controls," Papers 2206.01779, arXiv.org, revised Feb 2023.
    3. Aniket Kesari, 2022. "Do data breach notification laws reduce medical identity theft? Evidence from consumer complaints data," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 19(4), pages 1222-1252, December.
    4. Yiping Lu & Jiajin Li & Lexing Ying & Jose Blanchet, 2022. "Synthetic Principal Component Design: Fast Covariate Balancing with Synthetic Controls," Papers 2211.15241, arXiv.org.

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