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Cross-Validating Synthetic Controls

Author

Listed:
  • Becker, Martin
  • Klößner, Stefan
  • Pfeifer, Gregor
Abstract
While the literature on synthetic control methods mostly abstracts from out-of-sample measures, Abadie et al. (2015) have recently introduced a cross-validation approach. This technique, however, is not well-defined since it hinges on predictor weights which are not uniquely defined. We fix this issue, proposing a new, well-defined cross-validation technique, which we apply to the original Abadie et al. (2015) data. Additionally, we discuss how this new technique can be used for comparing different specifications based on out-of-sample measures, avoiding the danger of cherry-picking.

Suggested Citation

  • Becker, Martin & Klößner, Stefan & Pfeifer, Gregor, 2017. "Cross-Validating Synthetic Controls," MPRA Paper 83679, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:83679
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    References listed on IDEAS

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    1. Bruno Ferman & Cristine Pinto & Vitor Possebom, 2020. "Cherry Picking with Synthetic Controls," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 39(2), pages 510-532, March.
    2. Alberto Abadie & Javier Gardeazabal, 2003. "The Economic Costs of Conflict: A Case Study of the Basque Country," American Economic Review, American Economic Association, vol. 93(1), pages 113-132, March.
    3. Susan Athey & Guido W. Imbens, 2017. "The State of Applied Econometrics: Causality and Policy Evaluation," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 3-32, Spring.
    4. Javier Gardeazabal & Ainhoa Vega‐Bayo, 2017. "An Empirical Comparison Between the Synthetic Control Method and HSIAO et al.'s Panel Data Approach to Program Evaluation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(5), pages 983-1002, August.
    5. 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.
    6. José G. Montalvo, 2011. "Voting after the Bombings: A Natural Experiment on the Effect of Terrorist Attacks on Democratic Elections," The Review of Economics and Statistics, MIT Press, vol. 93(4), pages 1146-1154, November.
    7. Becker, Martin & Klößner, Stefan, 2018. "Fast and reliable computation of generalized synthetic controls," Econometrics and Statistics, Elsevier, vol. 5(C), pages 1-19.
    8. Stefan Klößner & Gregor Pfeifer, 2018. "Outside the box: using synthetic control methods as a forecasting technique," Applied Economics Letters, Taylor & Francis Journals, vol. 25(9), pages 615-618, May.
    9. Alberto Abadie & Alexis Diamond & Jens Hainmueller, 2015. "Comparative Politics and the Synthetic Control Method," American Journal of Political Science, John Wiley & Sons, vol. 59(2), pages 495-510, February.
    10. Stefan Klößner & Ashok Kaul & Gregor Pfeifer & Manuel Schieler, 2018. "Comparative politics and the synthetic control method revisited: a note on Abadie et al. (2015)," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 154(1), pages 1-11, December.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Pekka Malo & Juha Eskelinen & Xun Zhou & Timo Kuosmanen, 2024. "Computing Synthetic Controls Using Bilevel Optimization," Computational Economics, Springer;Society for Computational Economics, vol. 64(2), pages 1113-1136, August.
    2. Gregor Pfeifer & Fabian Wahl & Martyna Marczak, 2018. "Illuminating the World Cup effect: Night lights evidence from South Africa," Journal of Regional Science, Wiley Blackwell, vol. 58(5), pages 887-920, November.
    3. Klößner, Stefan & Pfeifer, Gregor, 2015. "Synthesizing Cash for Clunkers: Stabilizing the Car Market, Hurting the Environment," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113207, Verein für Socialpolitik / German Economic Association.
    4. Kuosmanen, Timo & Zhou, Xun & Eskelinen, Juha & Malo, Pekka, 2021. "Design Flaw of the Synthetic Control Method," MPRA Paper 106328, University Library of Munich, Germany.
    5. Giulio Grossi & Marco Mariani & Alessandra Mattei & Patrizia Lattarulo & Ozge Oner, 2020. "Direct and spillover effects of a new tramway line on the commercial vitality of peripheral streets. A synthetic-control approach," Papers 2004.05027, arXiv.org, revised Nov 2023.

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    More about this item

    Keywords

    Synthetic Control Methods; Cross-Validation; Specification Search.;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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