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A Monte Carlo Comparison of Semiparametric Tobit Estimators

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Author Info
Moon, Choon-Geol
Abstract

This paper focuses on a performance comparison of semiparametric Tobit estimators. Firstly, a conditional expectation verison of Horowitz's distribution-free least-squares estimator is proposed, together with a short description of the other estimators considered in the later Monte Carlo experiment. Then, a performance comparison of the following selected estimators is made through a Monte Carlo experiment: the standard Tobit maximum-likelihood estimator, the Buckley-James estimator, Horowitz's distribution-free least-squares estimator, a conditional version of Horowitz's estimator and Powell's least absolute deviations estimator. An empirical example of Engel curve estimation with zero expenditures follows. Copyright 1989 by John Wiley & Sons, Ltd.

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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.

Volume (Year): 4 (1989)
Issue (Month): 4 (Oct.-Dec.)
Pages: 361-82
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Handle: RePEc:jae:japmet:v:4:y:1989:i:4:p:361-82

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  3. Arthur Lewbel & Linton, Oliver Linton, 1998. "Nonparametric Censored Regression," Cowles Foundation Discussion Papers 1186, Cowles Foundation, Yale University. [Downloadable!]
  4. Moshe Buchinsky & Jinyong Hahn, 1995. "Quantile Regression Model with Unknown Censoring Point," Cowles Foundation Discussion Papers 1096, Cowles Foundation, Yale University. [Downloadable!]
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