Premium
A Monte Carlo comparison of semiparametric Tobit estimators
Author(s) -
Moon ChoonGeol
Publication year - 1989
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/jae.3950040405
Subject(s) - estimator , tobit model , monte carlo method , mathematics , econometrics , extremum estimator , statistics , minimum variance unbiased estimator , m estimator
This paper focuses on a performance comparison of semiparametric Tobit estimators. Firstly, a conditional expectation version 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.