Estimating treatment effects for ordered outcomes using maximum simulated likelihood
Christian A. Gregory
Economic Research Service, USDA
Washington, DC
[email protected]
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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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Christian A. Gregory
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treatoprobit, switchoprobit, treatoprobitsim, switchoprobitsim, ordinal outcomes, endogenous binary treatment, treatment effects
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