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A Monte Carlo Comparison of Semiparametric Tobit Estimators

  • Moon, Choon-Geol
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    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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