Estimation of the Multinomial Logit Model with Random Effects

Nikolaj Malchow-Møller; Michael Svarer

doi:10.1080/1350485032000082018

Estimation of the Multinomial Logit Model with Random Effects

Nikolaj Malchow-Møller, Michael Svarer^*

^*Corresponding author af dette arbejde

Aarhus Universitet

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review

Abstract

In the present paper, it is shown how to perform estimation of the random effects multinomial logit model in the SAS program. Inference in the random effects multinomial logit model is complicated because it requires evaluation of multi-dimensional integrals. Presumably for this reason, no statistical software packages allow for direct estimation of the model. It is shown how modifications of the likelihood function enable the applied researcher to make inference using SAS. While the procedure works well for small samples/models, estimation time might become considerable for larger samples/models. A possible explanation for this is provided.

Originalsprog	Engelsk
Tidsskrift	Applied Economics Letters
Vol/bind	10
Sider (fra-til)	389-392
Antal sider	4
ISSN	1350-4851
DOI	https://doi.org/10.1080/1350485032000082018
Status	Udgivet - 2003

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abstract = "In the present paper, it is shown how to perform estimation of the random effects multinomial logit model in the SAS program. Inference in the random effects multinomial logit model is complicated because it requires evaluation of multi-dimensional integrals. Presumably for this reason, no statistical software packages allow for direct estimation of the model. It is shown how modifications of the likelihood function enable the applied researcher to make inference using SAS. While the procedure works well for small samples/models, estimation time might become considerable for larger samples/models. A possible explanation for this is provided.",

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AB - In the present paper, it is shown how to perform estimation of the random effects multinomial logit model in the SAS program. Inference in the random effects multinomial logit model is complicated because it requires evaluation of multi-dimensional integrals. Presumably for this reason, no statistical software packages allow for direct estimation of the model. It is shown how modifications of the likelihood function enable the applied researcher to make inference using SAS. While the procedure works well for small samples/models, estimation time might become considerable for larger samples/models. A possible explanation for this is provided.

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