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



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Estimating marginal treatment effects using parametric and semiparametric methods

Scott Brave
Federal Reserve Bank of Chicago
Chicago, IL
sbrave@frbchi.org
Thomas Walstrum
University of Illinois at Chicago
and
Federal Reserve Bank of Chicago
Chicago, IL
twalstrum@frbchi.org
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.

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

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