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Cherry Picking with Synthetic Controls

Bruno Ferman, Cristine Pinto () and Vitor Possebom ()

Journal of Policy Analysis and Management, 2020, vol. 39, issue 2, 510-532

Abstract: We evaluate whether a lack of guidance on how to choose the matching variables used in the Synthetic Control (SC) estimator creates specification‐searching opportunities. We provide theoretical results showing that specification‐searching opportunities are asymptotically irrelevant if we restrict to a subset of SC specifications. However, based on Monte Carlo simulations and simulations with real datasets, we show significant room for specification searching when the number of pre‐treatment periods is in line with common SC applications, and when alternative specifications commonly used in SC applications are also considered. This suggests that such lack of guidance generates a substantial level of discretion in the choice of the comparison units in SC applications, undermining one of the advantages of the method. We provide recommendations to limit the possibilities for specification searching in the SC method. Finally, we analyze the possibilities for specification searching and provide our recommendations in a series of empirical applications.

Date: 2020
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https://doi.org/10.1002/pam.22206

Related works:
Working Paper: Cherry Picking with Synthetic Controls (2017) Downloads
Working Paper: Cherry picking with synthetic controls (2016) Downloads
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