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Econometrica Vol. 66 No. 3 1998

An Alternative Estimator for the Censored Quantile Regression Model

Moshe Buchinsky; Jinyong Hahn

Abstract

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 minimizer is obtained in a finite number of simplex iterations. The estimator has a square root of n-convergence rate and is asymptotically normal. A Monte Carlo study performed shows that the suggested estimator has very desirable small sample properties.

DOI
10.2307/2998578
Volume
66
Issue
3
Pages
653
Sources
openalex crossref bibtex:phds-export.bib

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