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Standard Synthetic Control Methods: The Case of Using All Preintervention Outcomes Together With Covariates

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  • Ashok Kaul
  • Stefan Klößner
  • Gregor Pfeifer
  • Manuel Schieler

Abstract

It is becoming increasingly popular in applications of standard synthetic control methods to include the entire pretreatment path of the outcome variable as economic predictors. We demonstrate both theoretically and empirically that using all outcome lags as separate predictors renders all other covariates irrelevant in such settings. This finding holds irrespective of how important these covariates are for accurately predicting posttreatment values of the outcome, threatening the estimator’s unbiasedness. We show that estimation results and corresponding policy conclusions can change considerably when the usage of outcome lags as predictors is restricted, resulting in other covariates obtaining positive weights. Monte Carlo studies examine potential bias.

Suggested Citation

  • Ashok Kaul & Stefan Klößner & Gregor Pfeifer & Manuel Schieler, 2022. "Standard Synthetic Control Methods: The Case of Using All Preintervention Outcomes Together With Covariates," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1362-1376, June.
    • Handle: RePEc:taf:jnlbes:v:40:y:2022:i:3:p:1362-1376
    DOI: 10.1080/07350015.2021.1930012
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