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allsynth: Synthetic control bias-corrections utilities for Stata

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  • Justin Wiltshire

    (University of California, Davis)

Abstract

The synthetic control method has become a widely adopted empirical approach for estimating counterfactuals and treatment effects. The synth module written for Stata (Abadie, Diamond, and Hainmueller 2010) is widely used by practitioners and serves as the foundation for the synth_runner utilities package (Galiani and Quistorff 2018), which enhances functionality. An active literature has proposed numerous modifications to the "classic" approach, including a bias-correction procedure (Abadie and L'Hour 2020), analogous to that in Abadie and Imbens (2011) for matching estimators, to remove bias that results from differences in the predictor variables between a treated unit and its synthetic control donors. allsynth adds functionality to the synth module, which implements this bias-correction procedure and automates extension of the procedure to placebo runs for in-space randomization inference and graphing.

Suggested Citation

  • Justin Wiltshire, 2021. "allsynth: Synthetic control bias-corrections utilities for Stata," 2021 Stata Conference 15, Stata Users Group.
    • Handle: RePEc:boc:scon21:15
    as

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    File URL: http://fmwww.bc.edu/repec/scon2021/US21_Wiltshire.pdf
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    References listed on IDEAS

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