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Cherry Picking with Synthetic Controls

Author

Listed:
  • Ferman, Bruno
  • Pinto, Cristine
  • Possebom, Vitor
Abstract
We show that a lack of guidance on how to choose the matching variables used in the Synthetic Control (SC) estimator creates specification-searching opportunities in SC applications. This undermines one of the potential advantages of the method, which is providing a transparent way of choosing comparison units and, therefore, being less susceptible to specification searching than alternative methods. To address this problem, we provide recommendations to limit the possibilities for specification searching in the SC method. Finally, we analyze the possibilities for specification searching and our recommendations in two empirical applications.

Suggested Citation

  • Ferman, Bruno & Pinto, Cristine & Possebom, Vitor, 2017. "Cherry Picking with Synthetic Controls," MPRA Paper 78213, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:78213
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    More about this item

    Keywords

    inference; synthetic control; p-hacking; specification searching;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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