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Difference-in-Differences Estimators of Intertemporal Treatment Effects

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  • Clément de Chaisemartin
  • Xavier D'Haultfoeuille

Abstract

We study treatment-effect estimation using panel data. The treatment may be nonbinary, non-absorbing, and the outcome may be affected by the treatment lags. We make parallel-trends assumptions, but do not restrict treatment effect heterogeneity, unlike commonly-used two-way-fixed-effects regressions. We propose reduced-form event-study estimators of the effect of being exposed to a weakly higher treatment dose for ℓ periods. We also propose normalized event-study estimators, that estimate a weighted average of the effects of the current treatment and its lags. Finally, we show that the reduced-form estimators can be combined into an economically interpretable cost-benefit ratio.

Suggested Citation

  • Clément de Chaisemartin & Xavier D'Haultfoeuille, 2022. "Difference-in-Differences Estimators of Intertemporal Treatment Effects," NBER Working Papers 29873, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:29873
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    More about this item

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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