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Mixed Logit Models for Multiparty Elections

Published online by Cambridge University Press:  04 January 2017

Garrett Glasgow*
Affiliation:
Department of Political Science, University of California, Santa Barbara, Santa Barbara, CA 93106. e-mail: [email protected]://www.polsci.ucsb.edu/faculty/glasgow

Abstract

Mixed logit (MXL) is a general discrete choice model thus far unexamined in the study of multicandidate and multiparty elections. Mixed logit assumes that the unobserved portions of utility are a mixture of an IID extreme value term and another multivariate distribution selected by the researcher. This general specification allows MXL to avoid imposing the independence of irrelevant alternatives (IIA) property on the choice probabilities. Further, MXL is a flexible tool for examining heterogeneity in voter behavior through random-coefficients specifications. MXL is a more general discrete choice model than multinomial probit (MNP) in several respects, and can be applied to a wider variety of questions about voting behavior than MNP. An empirical example using data from the 1987 British General Election demonstrates the utility of MXL in the study of multicandidate and multiparty elections.

Type
Research Article
Copyright
Copyright © 2001 by the Society for Political Methodology 

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