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Causal Mediation in Panel Data – Estimation Based on Difference in Differences

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  • Holm, Anders
  • Breen, Richard

Abstract

We propose a novel way of estimating direct and indirect causal effects for panel data. Our method applies when the treatment and the mediator can be coded as binary variables. We exploit pre-treatment and pre-mediator differences in outcomes between the mediated and non-mediated groups within the treated units. Our method is applicable when the mediator is realized both before and after treatment or when it is only a consequence of the treatment. We apply our method to the New Jersey minimum wage policy data and show that a minimal effect on overall employment is mediated through part-time employment.

Suggested Citation

  • Holm, Anders & Breen, Richard, 2023. "Causal Mediation in Panel Data – Estimation Based on Difference in Differences," SocArXiv kwscz_v1, Center for Open Science.
  • Handle: RePEc:osf:socarx:kwscz_v1
    DOI: 10.31219/osf.io/kwscz_v1
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