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The Stata Journal
Volume 15 Number 3: pp. 756-774



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Estimating treatment effects for ordered outcomes using maximum simulated likelihood

Christian A. Gregory
Economic Research Service, USDA
Washington, DC
cgregory@ers.usda.gov
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.
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