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Synthetic Controls in Action

Author

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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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    References listed on IDEAS

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    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.
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    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.
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    Cited by:

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    2. Ignacio Martinez & Jaume Vives-i-Bastida, 2022. "Bayesian and Frequentist Inference for Synthetic Controls," Papers 2206.01779, arXiv.org, revised Jul 2024.
    3. Yiping Lu & Jiajin Li & Lexing Ying & Jose Blanchet, 2022. "Synthetic Principal Component Design: Fast Covariate Balancing with Synthetic Controls," Papers 2211.15241, arXiv.org.
    4. 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.

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