We consider estimation of a linear regression model using data where some covariate values are missing but imputations are available to fill in the miss- ing values. This situation generates a tradeoff between bias and precision when estimating the regression parameters of interest. Using only...

We introduce two new Stata commands for the estimation of an or- dered response model with sample selection. The opsel command uses a standard maximum-likelihood approach to fit a parametric specification of the model where errors are assumed to follow a bivariate Gaussian distribution. The...

In this article, we describe the estimation of linear regression models with uncertainty about the choice of the explanatory variables. We introduce the Stata commands bma and wals, which implement, respectively, the exact Bayesian model-averaging estimator and the weighted-average least-squares...

We discuss the semi-nonparametric approach of Gallant and Nychka (1987, Econometrica 55: 363-390), the semiparametric maximum likelihood ap- proach of Klein and Spady (1993, Econometrica 61: 387-421), and a set of new Stata commands for semiparametric estimation of three binary-choice models....