A limited information estimator for the multivariate ordinal probit model

A limited information estimator for the multivariate ordinal probit model is developed. The main advantage of the estimator is that even for high dimensional models, the estimation procedure requires the evaluation of bivariate normal integrals only. The proposed estimator also avoids the potential...

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Bibliographic Details
Published inApplied economics Vol. 32; no. 14; pp. 1841 - 1851
Main Authors Fu, Tsu-Tan, Li, Lung-An, Lin, Yih-Ming, Kan, Kamhon
Format Journal Article
LanguageEnglish
Published London Taylor & Francis Group 01.11.2000
Taylor and Francis Journals
Taylor & Francis Ltd
SeriesApplied Economics
Subjects
Applied economics
Consumption
Economic behaviour
Economic models
Estimating techniques
Estimation
Modelling
Multivariate analysis
Studies
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Summary:A limited information estimator for the multivariate ordinal probit model is developed. The main advantage of the estimator is that even for high dimensional models, the estimation procedure requires the evaluation of bivariate normal integrals only. The proposed estimator also avoids the potential problem of encountering local maxima in the estimation process, which is looming using maximum likelihood. The performance of the limited information estimator is shown by Monte Carlo experiments to be excellent and it is comparable to that of the maximum likelihood estimator. Finally, an application of the limited information multivariate ordinal probit to model the consumption level of cigarette, alcohol and betel nut is presented.
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ISSN:0003-6846
1466-4283
DOI:10.1080/000368400425062