1. Bivariate Probit Analysis: Minimum Chi-Square Methods.
- Author
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Amemiya, Takeshi
- Subjects
- *
CHI-squared test , *STATISTICAL hypothesis testing , *ANALYSIS of variance , *VARIATIONAL inequalities (Mathematics) , *ESTIMATION theory , *DISTRIBUTION (Probability theory) , *MATHEMATICAL models , *CHARACTERISTIC functions , *PROBABILITY theory - Abstract
In this article we propose two minimum chi-square estimators for a bivariate probit model. We call one estimator the Full Information and the other Limited Information Minimum Chi-Square because the first takes account of all the a priori information while the second does not. Both estimators are shown to be consistent. Moreover, the first is shown to be asymptotically as efficient as the maximum likelihood estimator and yet is computationally much simpler. For illustration, estimates are computed for the data used by Ashford and Sowden [1970.] [ABSTRACT FROM AUTHOR]
- Published
- 1974
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