*! version 1.0.0 3mar2014
help switchoprobit
also see: switch_oprobit postestimation

Ordered Probit Switching Regression

switchoprobit -- Estimate effect of binary treatment on discrete, ordered outcome.

Syntax

switchoprobit
y_ordered x_ordered
[if] [in]
[weight]
, treat
(y_treat x_treat)
[ options]

Main
cluster(varname) cluster standard errors using varname

robust compute robust variance covariance matrix / standard errors

pweight, iweight, aweights are allowed; see weight

Description

switch_oprobit estimates a model in which treat is a binary indicator for a treatment (y_treat) for which selection is believed
correlated with the outcome of interest, y_ordered. The model assumes that the unobservables in treatment and outcome equations have a bivariate
normal distribution, and that outcomes for treated and untreated groups are distinct. (A test for the hypothesis that the treated and untreated groups
belong to a single outcome regime are reported as part of standard output.) Parameters of the model are estimated by maximum likelihood.

Examples

Let self assessed health SAH be ordered on a 1-5 scale (excellent, very good, good, fair, poor), and medicaid be an indicator of participation in Medicaid:

. switch_oprobit sah female married, treat(medicaid female married)

. switch_oprobit sah female married [pweight=weight], treat(medicaid female married) robust

Author

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