Estimation of multivalued treatment effects under conditional independence

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Abstract

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-influencefunction estimator, which can be interpreted as having the double-robust property. Our implementation jointly estimates means and quantiles of the potentialoutcome 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. © 2013 StataCorp LP.

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Cattaneo, M. D., Drukker, D. M., & Holland, A. D. (2013). Estimation of multivalued treatment effects under conditional independence. Stata Journal, 13(3), 407–450. https://doi.org/10.1177/1536867x1301300301

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