Synthetic Control Inference for Staggered Adoption

Fuente: arXiv
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Autori principali: Cao, Jianfei, Lu, Shirley, Wu, Hang
Natura: Preprint
Pubblicazione: 2019
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author Cao, Jianfei
Lu, Shirley
Wu, Hang
author_facet Cao, Jianfei
Lu, Shirley
Wu, Hang
contents We introduce a synthetic control methodology to study policies with staggered adoption. Many policies, such as the board gender diversity policies, 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 regulation on board gender diversity leads to an increase in full-time employment for female professionals.
format Preprint
id arxiv_https___arxiv_org_abs_1912_06320
institution arXiv
publishDate 2019
record_format arxiv
spellingShingle Synthetic Control Inference for Staggered Adoption
Cao, Jianfei
Lu, Shirley
Wu, Hang
Econometrics
We introduce a synthetic control methodology to study policies with staggered adoption. Many policies, such as the board gender diversity policies, 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 regulation on board gender diversity leads to an increase in full-time employment for female professionals.
title Synthetic Control Inference for Staggered Adoption
topic Econometrics
url https://arxiv.org/abs/1912.06320