DID_MULTIPLEGT: Stata module to estimate sharp Difference-in-Difference designs with multiple groups and periods
Clément de Chaisemartin,
Xavier D'Haultfoeuille and
Yannick Guyonvarch
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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 - IP Paris - Institut Polytechnique de Paris - ENSAE Paris - École Nationale de la Statistique et de l'Administration Économique - IP Paris - Institut Polytechnique de Paris - CNRS - Centre National de la Recherche Scientifique
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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).
Date: 2019
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Software Item: DID_MULTIPLEGT: Stata module to estimate sharp Difference-in-Difference designs with multiple groups and periods (2024) 
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