Home  >>  Archives  >>  Volume 14 Number 1  >>  st0331

The Stata Journal
Volume 14 Number 1: pp. 191-217

Subscribe to the Stata Journal

Estimating marginal treatment effects using parametric and semiparametric methods

Scott Brave
Federal Reserve Bank of Chicago
Chicago, IL
Thomas Walstrum
University of Illinois at Chicago
Federal Reserve Bank of Chicago
Chicago, IL
Abstract.  We describe the new command margte, which computes marginal and average treatment effects for a model with a binary treatment and a continuous outcome given selection on unobservables and returns. Marginal treatment effects differ from average treatment effects in instances where the impact of treatment varies within a population in correlation with unobserved characteristics. Both parametric and semiparametric estimation methods can be used with margte, and we provide evidence from a Monte Carlo simulation for when each is preferable.
Terms of use     View this article (PDF)

View all articles by these authors: Scott Brave, Thomas Walstrum

View all articles with these keywords: margte, locpoly2, etregress, movestay, marginal treatment effect, average treatment effect, generalized Roy model, local instrumental variables

Download citation: BibTeX  RIS

Download citation and abstract: BibTeX  RIS