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.
All Science Journal Classification (ASJC) codes
- Mathematics (miscellaneous)
- Generalized propensity score
- Inverse-probability weighting
- Multivalued treatment effects
- Semiparametric estimation
- Treatment effects