Estimating treatment effects for ordered outcomes using maximum simulated likelihood
Christian A. Gregory
Economic Research Service, USDA
Washington, DC
[email protected]
|
Abstract. I present four new commands to estimate the effect of a binary
endogenous treatment on an ordered outcome. Such models conventionally
rely upon joint normality of the unobservables in treatment and outcome
processes, as do treatoprobit and switchoprobit. In this
article, I highlight the capabilities of treatoprobitsim and
switchoprobitsim, which both use a latent-factor structure to
model the joint distribution of the treatment and outcome and allow the
researcher to relax the assumption of joint normality.
View all articles by this author:
Christian A. Gregory
View all articles with these keywords:
treatoprobit, switchoprobit, treatoprobitsim, switchoprobitsim, ordinal outcomes, endogenous binary treatment, treatment effects
Download citation: BibTeX RIS
Download citation and abstract: BibTeX RIS
|
