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Estimation in a Class of Simultaneous Equation Limited Dependent Variable Models

Richard W. Blundell and Richard J. Smith
The Review of Economic Studies
Vol. 56, No. 1 (Jan., 1989), pp. 37-57
Published by: Oxford University Press
Stable URL: http://www.jstor.org/stable/2297748
Page Count: 21
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Estimation in a Class of Simultaneous Equation Limited Dependent Variable Models
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Abstract

Estimation in a class of simultaneous equation limited dependent variable models is considered. The minimum Chi-squared method is used to compare the asymptotic relative efficiency of marginal and new conditional maximum likelihood estimators for this class of models. Efficient minimum Chi-squared estimation procedures are described. A two-step algorithm based on a conditional maximum likelihood estimator provides a natural framework for both computing a linearized and locating the joint maximum likelihood estimator. The unimodality of the simultaneous equation tobit likelihood function is proved and this model is used to illustrate the empirical application of some of the estimators considered in the paper. The relative efficiency of these estimators in the simultaneous equation tobit model is examined in a set of Monte-Carlo experiments.

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