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Synthetic Control Inference for Staggered Adoption: Estimating the Dynamic Effects of Board Gender Diversity Policies

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  • Jianfei Cao
  • Shirley Lu

Abstract

We introduce a synthetic control methodology to study policies with staggered adoption. Many policies, such as the board gender quota, are replicated by other policy setters at different time frames. Our method estimates the dynamic average treatment effects on the treated using variation introduced by the staggered adoption of policies. Our method gives asymptotically unbiased estimators of many interesting quantities and delivers asymptotically valid inference. By using the proposed method and national labor data in Europe, we find evidence that quota regulation on board diversity leads to a decrease in part-time employment, and an increase in full-time employment for female professionals.

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  • Jianfei Cao & Shirley Lu, 2019. "Synthetic Control Inference for Staggered Adoption: Estimating the Dynamic Effects of Board Gender Diversity Policies," Papers 1912.06320, arXiv.org.
    • Handle: RePEc:arx:papers:1912.06320
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    References listed on IDEAS

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    Cited by:

    1. Eli Ben‐Michael & Avi Feller & Jesse Rothstein, 2022. "Synthetic controls with staggered adoption," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(2), pages 351-381, April.
    2. Youngho Kim, 2024. "Payments for Ecosystem Services Programs and Climate Change Adaptation in Agriculture," Economics Series Working Papers 1054, University of Oxford, Department of Economics.
    3. repec:ags:aaea22:335971 is not listed on IDEAS

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