We introduce two new Stata commands for the estimation of an orderedresponse model with sample selection. The opsel command uses a standardmaximum-likelihood approach to fit a parametric specification of the model whereerrors are assumed to follow a bivariate Gaussian distribution. The snpopselcommand uses the semi-nonparametric approach of Gallant and Nychka (1987,Econometrica 55: 363–390) to fit a semiparametric specification of the modelwhere the bivariate density function of the errors is approximated by a Hermitepolynomial expansion. The snpopsel command extends the set of Stata routinesfor semi-nonparametric estimation of discrete response models. Compared to theother semi-nonparametric estimators, our routine is relatively faster because itis programmed in Mata. In addition, we provide new postestimation routinesto compute linear predictions, predicted probabilities, and marginal effects. Theseimprovements are also extended to the set of semi-nonparametric Stata commandsoriginally written by Stewart (2004, Stata Journal 4: 27–39) and De Luca (2008,Stata Journal 8: 190–220). An illustration of the new opsel and snpopsel commandsis provided through an empirical application on self-reported health withselectivity due to sample attrition.
|Numero di pagine||27|
|Rivista||THE STATA JOURNAL|
|Stato di pubblicazione||Published - 2011|
All Science Journal Classification (ASJC) codes