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An Alternative Estimator for the Censored Quantile Regression Model Author info | Abstract | Publisher info | Download info | Related research | Statistics Moshe Buchinsky
Jinyong Hahn
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.
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Article provided by Econometric Society in its journal Econometrica .
Volume (Year): 66 (1998)
Issue (Month): 3 (May)
Pages: 653-672
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Handle: RePEc:ecm:emetrp:v:66:y:1998:i:3:p:653-672Contact details of provider: Phone: 1 212 998 3820 Fax: 1 212 995 4487 Email: Web page: http://www.econometricsociety.org/ More information through EDIRC
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