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DID_MULTIPLEGT: Stata module to estimate sharp Difference-in-Difference designs with multiple groups and periods

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  • Clément de Chaisemartin

    (UC Santa Barbara - University of California [Santa Barbara] - UC - University of California, ECON - Département d'économie (Sciences Po) - Sciences Po - Sciences Po - CNRS - Centre National de la Recherche Scientifique)

  • Xavier d'Haultfoeuille

    (CREST - Centre de Recherche en Économie et Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - X - École polytechnique - ENSAE Paris - École Nationale de la Statistique et de l'Administration Économique - CNRS - Centre National de la Recherche Scientifique)

  • Yannick Guyonvarch

    (CREST - Centre de Recherche en Économie et Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - X - École polytechnique - ENSAE Paris - École Nationale de la Statistique et de l'Administration Économique - CNRS - Centre National de la Recherche Scientifique)

Abstract

did_multipleGT can be used in DID designs with multiple groups and periods, and where all units in the same group and period have the same treatment (sharp designs), as is for instance the case when the treatment is a county- or state-level variable. It computes the Wald-TC estimator of the instantaneous treatment effect among switchers introduced in Section 3.3 of Chaisemartin and D'Haultfoeuille (2018). It also computes placebo estimators that can be used to assess the plausibility of the common trends assumption underlying the Wald-TC estimator (see Section 3.3 of Chaisemartin and D'Haultfoeuille, 2018). Finally, in staggered adoption designs where treatment is binary and where groups' treatment is weakly increasing with time, it computes Wald-TC estimators of the dynamic treatement effects among switchers (see Section 5.2 of Chaisemartin and D'Haultfoeuille, 2018).

Suggested Citation

  • Clément de Chaisemartin & Xavier d'Haultfoeuille & Yannick Guyonvarch, 2019. "DID_MULTIPLEGT: Stata module to estimate sharp Difference-in-Difference designs with multiple groups and periods," SciencePo Working papers Main hal-03946768, HAL.
    • Handle: RePEc:hal:spmain:hal-03946768
    Note: View the original document on HAL open archive server: https://hal-sciencespo.archives-ouvertes.fr/hal-03946768
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    1. Spagnolo, Giancarlo & Lotti, Clarissa & Muco, Arieda & Valletti, Tommaso, 2022. "Indirect Savings from Public Procurement Centralization," CEPR Discussion Papers 17019, C.E.P.R. Discussion Papers.
    2. William B. Hankins, 2022. "Revisiting the effect of supermajority requirements on fiscal outcomes," Southern Economic Journal, John Wiley & Sons, vol. 88(4), pages 1599-1625, April.
    3. Khurana, Saloni & Mahajan, Kanika & Sen, Kunal, 2023. "Minimum Wages and Changing Wage Inequality in India," IZA Discussion Papers 16600, Institute of Labor Economics (IZA).
    4. Deiana, Claudio & Giua, Ludovica, 2023. "This site is closed! The effect of decommissioning mining waste facilities on mortality in the long run," Journal of Environmental Economics and Management, Elsevier, vol. 119(C).
    5. Bietenbeck, Jan & Leibing, Andreas & Marcus, Jan & Weinhardt, Felix, 2023. "Tuition fees and educational attainment," European Economic Review, Elsevier, vol. 154(C).
    6. Lusher, Lester & Ruberg, Tim, 2023. "Killer Alerts? Public Health Warnings and Heat Stroke in Japan," IZA Discussion Papers 16562, Institute of Labor Economics (IZA).
    7. Espen S. Dahl & Øystein Hernaes, 2023. "Making activation for young welfare recipients mandatory," LABOUR, CEIS, vol. 37(1), pages 96-121, March.

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