ssm

Models

ssm is a wrapper for gllamm to estimate endogenous switching and sample selection models for binary, count, and ordinal variables by maximum likelihood using adaptive quadrature. The model consists of two submodels: the outcome model and the selection or switching model.

For binary or ordinal outcomes, the outcome model is a logit or probit model; for counts the outcome model model is a Poisson model. If the problem is an endogenous switching problem, the switching variable appears as a covariate in the outcome model.

The switching or selection model is a probit model.

The commands option causes ssm to print out all data manipulation commands and the gllamm command for estimating the model. gllamm itself can then be used to extend the model or to make predictions or simule data gllapred or gllasim.

Reference: Miranda and Rabe-Hesketh (2006). Maximum likelihood estimation of endogenous switching and sample selection models for binary, count, and ordinal variables. The Stata Journal 6, 285-308.

Installation

   . ssc describe ssm
   . ssc install ssm
   . ssc install ssm, replace /* to replace previous version */