Abstract
In this article, we briefly review the role of the propensity score in estimating dose–response functions as described in Hirano and Imbens (2004, Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives, 73–84). Then we present a set of Stata programs that estimate the propensity score in a setting with a continuous treatment, test the balancing property of the generalized propensity score, and estimate the dose–response function. We illustrate these programs by using a dataset collected by Imbens, Rubin, and Sacerdote.