Average treatment effect estimates robust to the “limited overlap” problem: robustate

• Autores: Yuya Sasaki, Takuya Ura
• Localización: The Stata journal, ISSN 1536-867X, Vol. 22, Nº. 2, 2022, págs. 344-354
• Idioma: inglés
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• Resumen

  • We introduce a new command, robustate, that executes the inverseprobability weighting estimation and inference for the average treatment effect with robustness against limited overlap (that is, weak satisfaction of the common support condition). This command produces estimates, standard errors, p-values, and confidence intervals for the average treatment effect. The utility of the command is demonstrated with both simulated and real data of right heart catheterization. These illustrations show that the proposed estimator implemented by the robustate command indeed exhibits more robustness against limited overlap than the traditional inverse-probability weighting estimator. The main method of thecommand is proposed in Sasaki and Ura (2022, Econometric Theory 38: 66–112)