The paper introduces an estimator for the linear censored quantile regression model when the censoring point is an unknown function of a set of regressors. The objective function minimized is convex and the minimization problem is a linear programming problem, for which there is a global...

We develop a simulation based approach that can determine whether the semiparametric efficiency bound of a dynamic discrete choice model with fixed effects is zero or not. We illustrate the usefulness of our approach by considering a simplified version of Keane and Wolpin's (1997) model, where...

This paper introduces an alternative estimator for the linear censored quantile regression model. The estimator also applies to cases where the censoring point is unknown. Since the objective function is globally convex and the estimator is a solution to a linear programming problem, a global...