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Fuzzy differences in differences

Author

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  • Clément de Chaisemartin

    (PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, PSE - Paris-Jourdan Sciences Economiques - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - INRA - Institut National de la Recherche Agronomique - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique)

Abstract

Difference in differences require that 0% of observations are treated in the control group and during period 0 (no "always takers") and 100% in the treatment group in period 1 (no "never takers"). Sometimes, the treatment rate increases more in the treatment than in the control group but there are never or always takers. This paper develops results to identify treatment effects in such settings. They only require one common trend assumption on the outcome of interest Y whereas the standard instrumental variable result also requires common trend on treatment D. I derive bounds for treatment effects which are tight when there are no or few always takers. This can be the case in applications considering the effect of an innovation, where by definition no observations are treated in period 0. I derive other bounds that are tight when the treatment rate does not change much between the two periods in the control group, which can be the case in applications considering the extension of a program to a group previously not eligible. I use my results to measure the efficacy of a new drug for smoking cessation.

Suggested Citation

  • Clément de Chaisemartin, 2012. "Fuzzy differences in differences," Working Papers halshs-00671368, HAL.
    • Handle: RePEc:hal:wpaper:halshs-00671368
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00671368
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    More about this item

    Keywords

    Difference in Differences; Heterogeneous Treatment Effect; Imperfect Compliance; Partial Identification; Smoking Cessation;
    All these keywords.

    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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