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...

Full description

Saved in:
Bibliographic Details
Published in:Applied economics 2000-11, Vol.32 (14), p.1841-1851
Main Authors: Fu, Tsu-Tan, Li, Lung-An, Lin, Yih-Ming, Kan, Kamhon
Format: Article
Language:English
Subjects:
Applied economics
Consumption
Economic behaviour
Economic models
Estimating techniques
Estimation
Modelling
Multivariate analysis
Studies
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c567t-96d2222aba897ff575bae1ad17525c0b62154b4f4313f73d1f625031de010bd3
cites cdi_FETCH-LOGICAL-c567t-96d2222aba897ff575bae1ad17525c0b62154b4f4313f73d1f625031de010bd3
container_end_page 1851
container_issue 14
container_start_page 1841
container_title Applied economics
container_volume 32
creator Fu, Tsu-Tan
Li, Lung-An
Lin, Yih-Ming
Kan, Kamhon
description 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.
doi_str_mv 10.1080/000368400425062
format article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_crossref_primary_10_1080_000368400425062</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>39088696</sourcerecordid><originalsourceid>FETCH-LOGICAL-c567t-96d2222aba897ff575bae1ad17525c0b62154b4f4313f73d1f625031de010bd3</originalsourceid><addsrcrecordid>eNqFUE1v1DAQtRBILIUzV4sDt1CPv5JwqyoKlYq49G45sa26cuJgewv775nVVhxWQliaD3vee54ZQt4D-wRsYJeMMaEHyZjkimn-guxAat1JPoiXZHesdljWr8mbWh_xClz0O3J7RVNcYvOOxjXkstgW80p9bRHTXCi-0fbg6bJPLT7ZEm3zNBcXV5voVvIUG12y8-kteRVsqv7dc7wg9zdf7q-_dXc_vt5eX911s9J960btOB472WHsQ1C9mqwH66BXXM1s0hyUnGSQAkTohYOgcR4BzjNgkxMX5ONJFv_-ucc-zRLr7FOyq8_7asTIhkGPGoEfzoCPeV-w62o4cD1yyTiCLk-gueRaiw9mKzh4ORhg5rhWc7ZWZHw_MYrf_PwX3myw25bw5ckIKzi6AxpHOoaIBhLddkwGCQYGBeahLaj3-aT3vP5fuSSHcoeUSyh2nSPO9O9m1H_JZxzTfjfxB50Mp08</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>212692402</pqid></control><display><type>article</type><title>A limited information estimator for the multivariate ordinal probit model</title><source>International Bibliography of the Social Sciences (IBSS)</source><source>EBSCOhost Econlit with Full Text</source><source>Access via Business Source (EBSCOhost)</source><source>Taylor and Francis Social Sciences and Humanities Collection</source><creator>Fu, Tsu-Tan ; Li, Lung-An ; Lin, Yih-Ming ; Kan, Kamhon</creator><creatorcontrib>Fu, Tsu-Tan ; Li, Lung-An ; Lin, Yih-Ming ; Kan, Kamhon</creatorcontrib><description>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.</description><identifier>ISSN: 0003-6846</identifier><identifier>EISSN: 1466-4283</identifier><identifier>DOI: 10.1080/000368400425062</identifier><identifier>CODEN: APPEBP</identifier><language>eng</language><publisher>London: Taylor &amp; Francis Group</publisher><subject>Applied economics ; Consumption ; Economic behaviour ; Economic models ; Estimating techniques ; Estimation ; Modelling ; Multivariate analysis ; Studies</subject><ispartof>Applied economics, 2000-11, Vol.32 (14), p.1841-1851</ispartof><rights>Copyright Taylor &amp; Francis Group, LLC 2000</rights><rights>Copyright Routledge Nov 15, 2000</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c567t-96d2222aba897ff575bae1ad17525c0b62154b4f4313f73d1f625031de010bd3</citedby><cites>FETCH-LOGICAL-c567t-96d2222aba897ff575bae1ad17525c0b62154b4f4313f73d1f625031de010bd3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925,33223,33224</link.rule.ids><backlink>$$Uhttp://econpapers.repec.org/article/tafapplec/v_3a32_3ay_3a2000_3ai_3a14_3ap_3a1841-1851.htm$$DView record in RePEc$$Hfree_for_read</backlink></links><search><creatorcontrib>Fu, Tsu-Tan</creatorcontrib><creatorcontrib>Li, Lung-An</creatorcontrib><creatorcontrib>Lin, Yih-Ming</creatorcontrib><creatorcontrib>Kan, Kamhon</creatorcontrib><title>A limited information estimator for the multivariate ordinal probit model</title><title>Applied economics</title><description>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.</description><subject>Applied economics</subject><subject>Consumption</subject><subject>Economic behaviour</subject><subject>Economic models</subject><subject>Estimating techniques</subject><subject>Estimation</subject><subject>Modelling</subject><subject>Multivariate analysis</subject><subject>Studies</subject><issn>0003-6846</issn><issn>1466-4283</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2000</creationdate><recordtype>article</recordtype><sourceid>8BJ</sourceid><recordid>eNqFUE1v1DAQtRBILIUzV4sDt1CPv5JwqyoKlYq49G45sa26cuJgewv775nVVhxWQliaD3vee54ZQt4D-wRsYJeMMaEHyZjkimn-guxAat1JPoiXZHesdljWr8mbWh_xClz0O3J7RVNcYvOOxjXkstgW80p9bRHTXCi-0fbg6bJPLT7ZEm3zNBcXV5voVvIUG12y8-kteRVsqv7dc7wg9zdf7q-_dXc_vt5eX911s9J960btOB472WHsQ1C9mqwH66BXXM1s0hyUnGSQAkTohYOgcR4BzjNgkxMX5ONJFv_-ucc-zRLr7FOyq8_7asTIhkGPGoEfzoCPeV-w62o4cD1yyTiCLk-gueRaiw9mKzh4ORhg5rhWc7ZWZHw_MYrf_PwX3myw25bw5ckIKzi6AxpHOoaIBhLddkwGCQYGBeahLaj3-aT3vP5fuSSHcoeUSyh2nSPO9O9m1H_JZxzTfjfxB50Mp08</recordid><startdate>20001101</startdate><enddate>20001101</enddate><creator>Fu, Tsu-Tan</creator><creator>Li, Lung-An</creator><creator>Lin, Yih-Ming</creator><creator>Kan, Kamhon</creator><general>Taylor &amp; Francis Group</general><general>Taylor and Francis Journals</general><general>Taylor &amp; Francis Ltd</general><scope>DKI</scope><scope>X2L</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8BJ</scope><scope>FQK</scope><scope>JBE</scope></search><sort><creationdate>20001101</creationdate><title>A limited information estimator for the multivariate ordinal probit model</title><author>Fu, Tsu-Tan ; Li, Lung-An ; Lin, Yih-Ming ; Kan, Kamhon</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c567t-96d2222aba897ff575bae1ad17525c0b62154b4f4313f73d1f625031de010bd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2000</creationdate><topic>Applied economics</topic><topic>Consumption</topic><topic>Economic behaviour</topic><topic>Economic models</topic><topic>Estimating techniques</topic><topic>Estimation</topic><topic>Modelling</topic><topic>Multivariate analysis</topic><topic>Studies</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Fu, Tsu-Tan</creatorcontrib><creatorcontrib>Li, Lung-An</creatorcontrib><creatorcontrib>Lin, Yih-Ming</creatorcontrib><creatorcontrib>Kan, Kamhon</creatorcontrib><collection>RePEc IDEAS</collection><collection>RePEc</collection><collection>CrossRef</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>International Bibliography of the Social Sciences</collection><collection>International Bibliography of the Social Sciences</collection><jtitle>Applied economics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Fu, Tsu-Tan</au><au>Li, Lung-An</au><au>Lin, Yih-Ming</au><au>Kan, Kamhon</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A limited information estimator for the multivariate ordinal probit model</atitle><jtitle>Applied economics</jtitle><date>2000-11-01</date><risdate>2000</risdate><volume>32</volume><issue>14</issue><spage>1841</spage><epage>1851</epage><pages>1841-1851</pages><issn>0003-6846</issn><eissn>1466-4283</eissn><coden>APPEBP</coden><abstract>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.</abstract><cop>London</cop><pub>Taylor &amp; Francis Group</pub><doi>10.1080/000368400425062</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 0003-6846
ispartof Applied economics, 2000-11, Vol.32 (14), p.1841-1851
issn 0003-6846
1466-4283
language eng
recordid cdi_crossref_primary_10_1080_000368400425062
source International Bibliography of the Social Sciences (IBSS); EBSCOhost Econlit with Full Text; Access via Business Source (EBSCOhost); Taylor and Francis Social Sciences and Humanities Collection
subjects Applied economics
Consumption
Economic behaviour
Economic models
Estimating techniques
Estimation
Modelling
Multivariate analysis
Studies
title A limited information estimator for the multivariate ordinal probit model
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-01T06%3A30%3A08IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20limited%20information%20estimator%20for%20the%20multivariate%20ordinal%20probit%20model&rft.jtitle=Applied%20economics&rft.au=Fu,%20Tsu-Tan&rft.date=2000-11-01&rft.volume=32&rft.issue=14&rft.spage=1841&rft.epage=1851&rft.pages=1841-1851&rft.issn=0003-6846&rft.eissn=1466-4283&rft.coden=APPEBP&rft_id=info:doi/10.1080/000368400425062&rft_dat=%3Cproquest_cross%3E39088696%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c567t-96d2222aba897ff575bae1ad17525c0b62154b4f4313f73d1f625031de010bd3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=212692402&rft_id=info:pmid/&rfr_iscdi=true