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Comparative politics and the synthetic control method revisited: a note on Abadie et al. (2015)

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  • Stefan Klößner

    () (Statistics and Econometrics, Saarland University)

  • Ashok Kaul

    (Saarland University
    University of Zurich
    IPE Institute for Policy Evaluation)

  • Gregor Pfeifer

    () (University of Hohenheim)

  • Manuel Schieler

    (Saarland University
    IPE Institute for Policy Evaluation)

Abstract

Recently, Abadie et al. (Am J Polit Sci 59:495–510, 2015) have expanded synthetic control methods by the so-called cross-validation technique. We find that their results are not being reproduced when alternative software packages are used or when the variables’ ordering within the dataset is changed. We show that this failure stems from the cross-validation technique relying on non-uniquely defined predictor weights. While the amount of the resulting ambiguity is negligible for the main application of Abadie et al. (Am J Polit Sci 59:495–510, 2015), we find it to be substantial for several of their robustness analyses. Applying well-defined, standard synthetic control methods reveals that the authors’ results are particularly driven by a specific control country, the USA.

Suggested Citation

  • 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.
  • Handle: RePEc:spr:sjecst:v:154:y:2018:i:1:d:10.1186_s41937-017-0004-9
    DOI: 10.1186/s41937-017-0004-9
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    References listed on IDEAS

    as
    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.
    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. Eduardo Cavallo & Sebastian Galiani & Ilan Noy & Juan Pantano, 2013. "Catastrophic Natural Disasters and Economic Growth," The Review of Economics and Statistics, MIT Press, vol. 95(5), pages 1549-1561, December.
    4. Henrik Jacobsen Kleven & Camille Landais & Emmanuel Saez, 2013. "Taxation and International Migration of Superstars: Evidence from the European Football Market," American Economic Review, American Economic Association, vol. 103(5), pages 1892-1924, August.
    5. 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.
    6. Abadie, Alberto & Diamond, Alexis & Hainmueller, Jens, 2011. "Synth: An R Package for Synthetic Control Methods in Comparative Case Studies," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 42(i13).
    7. 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.
    8. 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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    Citations

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    Cited by:

    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. Martin Becker & Stefan Klößner & Gregor Pfeifer, 2018. "Cross-Validating Synthetic Controls," Economics Bulletin, AccessEcon, vol. 38(1), pages 603-609.
    3. 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.
    4. Jason Poulos & Shuxi Zeng, 2017. "RNN-based counterfactual prediction, with an application to homestead policy and public schooling," Papers 1712.03553, arXiv.org, revised Sep 2020.
    5. Klößner, Stefan & Pfeifer, Gregor, 2015. "Synthesizing Cash for Clunkers: Stabilizing the Car Market, Hurting the Environment," Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113207, Verein für Socialpolitik / German Economic Association.
    6. Kaul, Ashok & Klößner, Stefan & Pfeifer, Gregor & Schieler, Manuel, 2015. "Synthetic Control Methods: Never Use All Pre-Intervention Outcomes Together With Covariates," MPRA Paper 83790, University Library of Munich, Germany.
    7. Corinne Autant-Bernard & Ruben Fotso & Nadine Massard, 2020. "Evaluating the impact of public policies on large firms: a synthetic control approach to science industry transfer policies," Working Papers halshs-02733210, HAL.
    8. Essers, Dennis & Ide, Stefaan, 2019. "The IMF and precautionary lending: An empirical evaluation of the selectivity and effectiveness of the Flexible Credit Line," Journal of International Money and Finance, Elsevier, vol. 92(C), pages 25-61.
    9. Rok Spruk & Mitja Kovac, 2020. "Does a ban on trans fats improve public health: synthetic control evidence from Denmark," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 156(1), pages 1-32, December.

    More about this item

    Keywords

    Synthetic control methods; Cross-validation;

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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