Estimation of multivalued treatment effects under conditional independence

• Autores: David M. Drukker, Matias D. Cattaneo, Ashley D. Holland
• Localización: The Stata journal, ISSN 1536-867X, Vol. 13, Nº. 3, 2013, págs. 407-450
• Idioma: inglés
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• Dialnet Métricas: 5 Citas
• Resumen

  • This article discusses the poparms command, which implements two semiparametric estimators for multivalued treatment effects discussed in Cattaneo (2010, Journal of Econometrics 155: 138�154). The first is a properly reweighted inverse-probability weighted estimator, and the second is an efficient-influence function estimator, which can be interpreted as having the double-robust property. Our implementation jointly estimates means and quantiles of the potential outcome distributions, allowing for multiple, discrete treatment levels. These estimators are then used to estimate a variety of multivalued treatment effects. We discuss pre- and postestimation approaches that can be used in conjunction with our main implementation. We illustrate the program and provide a simulation study assessing the finite-sample performance of the inference procedures