A Monte Carlo Comparison of Semiparametric Tobit Estimators
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.
Volume (Year): 4 (1989)
Issue (Month): 4 (Oct.-Dec.)
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