Alternative Computational Approaches to Statistical Inference In The Multinomial Probit Model

UTSePress Research/Manakin Repository

Search UTSePress Research


Advanced Search

Browse

My Account

Show simple item record

dc.contributor.author Geweke, John en_US
dc.contributor.author Keane, Michael en_US
dc.contributor.author Runkle, D en_US
dc.contributor.editor en_US
dc.date.accessioned 2011-02-07T06:25:49Z
dc.date.available 2011-02-07T06:25:49Z
dc.date.issued 1994 en_US
dc.identifier 2006012700 en_US
dc.identifier.citation Geweke John, Keane Michael, and Runkle D 1994, 'Alternative Computational Approaches to Statistical Inference In The Multinomial Probit Model', Mit Press, vol. 76, no. 4, pp. 609-632. en_US
dc.identifier.issn 0034-6535 en_US
dc.identifier.other C1UNSUBMIT en_US
dc.identifier.uri http://hdl.handle.net/10453/13896
dc.description.abstract This research compares several approaches to inference in the multinomial probit model, based on two Monte Carlo experiments for a seven choice model. The methods compared are the simulated maximum likelihood estimator using the GHK recursive probabilit en_US
dc.language en_US
dc.publisher Mit Press en_US
dc.relation.isbasedon http://dx.doi.org/10.2307/2109766 en_US
dc.title Alternative Computational Approaches to Statistical Inference In The Multinomial Probit Model en_US
dc.parent Review Of Economics And Statistics en_US
dc.journal.volume 76 en_US
dc.journal.number 4 en_US
dc.publocation Cambridge en_US
dc.identifier.startpage 609 en_US
dc.identifier.endpage 632 en_US
dc.cauo.name BUS.School of Finance and Economics en_US
dc.conference Verified OK en_US
dc.for 140302 en_US
dc.personcode 101228 en_US
dc.personcode 998871 en_US
dc.personcode 0000033773 en_US
dc.percentage 100 en_US
dc.classification.name Econometric and Statistical Methods en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity en_US
dc.description.keywords Estimability; Integration; Simulation en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record