TITLE:
A Comparison of the Performance of Various Estimators of Parametric Type1 Tobit Model
AUTHORS:
El Ouali Rahmani, Abdelali Kaaouachi, Said El Melhaoui
KEYWORDS:
Type 1 Tobit Model; Parametric Estimation; Monte Carlo Simulation
JOURNAL NAME:
Open Journal of Statistics,
Vol.3 No.1,
February
20,
2013
ABSTRACT: In this paper, we use Monte Carlo
simulations to compare parametric estimators of Type 1 Tobit model. In
particular, we examine the performance for finite samples of three different
estimators of simple Tobit model: the least squares (LS) estimator, the Heckman
(H) estimator and the maximum likelihood (ML) estimator. These three estimators
are consistent and asymptotically normal in the case where the density error is
specified. However, these properties are sensitive to the situation where the
error distribution is not specified. The purpose of this article is to
determine properties of the three estimators, namely bias and convergence, by
using Monte Carlo simulations.