Difference-in-Differences Estimators of Intertemporal Treatment Effects

Clément de Chaisemartin and Xavier D'Haultf{\oe}uille
Authors registered in the RePEc Author Service: Xavier D'Haultfoeuille

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Abstract: We study treatment-effect estimation using panel data. The treatment may be non-binary, non-absorbing, and the outcome may be affected by treatment lags. We make a parallel-trends assumption, and propose event-study estimators of the effect of being exposed to a weakly higher treatment dose for $\ell$ periods. We also propose normalized estimators, that estimate a weighted average of the effects of the current treatment and its lags. We also analyze commonly-used two-way-fixed-effects regressions. Unlike our estimators, they can be biased in the presence of heterogeneous treatment effects. A local-projection version of those regressions is biased even with homogeneous effects.

Date: 2020-07, Revised 2024-12
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (40)

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http://arxiv.org/pdf/2007.04267 Latest version (application/pdf)

Related works:
Working Paper: Difference-in-Differences Estimators of Intertemporal Treatment Effects (2022)
Working Paper: Difference-in-Differences Estimators of Intertemporal Treatment Effects (2022)
Working Paper: Difference-in-Differences Estimators of Intertemporal Treatment Effects (2022)
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2007.04267

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