Reweighting is a popular statistical technique to deal with inference in the presence of a nonrandom sample, and various reweighting estimators have been proposed in the literature. This article presents the user-written command treatrew, which implements reweighting on the propensity-score...

This paper presents an implementation of matching estimators for average treatment effects in Stata. The nnmatch command allows you to estimate the average effect for all units or only for the treated or control units; to choose the number of matches; to specify the distance metric; to select a...

We present a new Stata command, bmte (bias-minimizing treatment effects), that implements two new estimators proposed in Millimet and Tchernis (2013, Journal of Applied Econometrics 28: 982–1017) and designed to estimate the effect of treatment when selection on unobserved variables exists and...

Based on the conditional independence or unconfoundedness assump- tion, matching has become a popular approach to estimate average treatment effects. Checking the sensitivity of the estimated results with respect to devia- tions from this identifying assumption has become an increasingly...

In this article, we introduce three commands to conduct robust datadriven statistical inference in regression-discontinuity (RD) designs. First, we present rdrobust, a command that implements the robust bias-corrected confidence intervals proposed in Calonico, Cattaneo, and Titiunik (2014d,...

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...