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Political Analysis Advance Access originally published online on October 30, 2006
Political Analysis 2007 15(1):67-84; doi:10.1093/pan/mpl006
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© The Author 2006. Published by Oxford University Press on behalf of the Society for Political Methodology. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Accounting for Voter Heterogeneity within and across Districts with a Factor-Analytic Voter-Choice Model

Wagner A. Kamakura

Fuqua Graduate School of Business, Duke University, One Towerview Road, Durham, NC 27708

José Afonso Mazzon

Faculdade de Administração e Economia, University of São Paulo, Ave. Prof. Luciano Gualberto, 908, CEP 0558-900 São Paulo, Brazil. e-mail: jamazzon{at}usp.br

e-mail: kamakura{at}duke.edu (corresponding author)

In this study, we propose a model of individual voter behavior that can be applied to aggregate data at the district (or precinct) levels while accounting for differences in political preferences across districts and across voters within each district. Our model produces a mapping of the competing candidates and electoral districts on a latent "issues" space that describes how political preferences in each district deviate from the average voter and how each candidate caters to average voter preferences within each district. We formulate our model as a random-coefficients nested logit model in which the voter first evaluates the candidates to decide whether or not to cast his or her vote, and then chooses the candidate who provides him or her with the highest value. Because we allow the random coefficient to vary not only across districts but also across unobservable voters within each district, the model avoids the Independence of Irrelevant Alternatives Assumption both across districts and within each district, thereby accounting for the cannibalization of votes among similar candidates within and across voting districts. We illustrate our proposed model by calibrating it to the actual voting data from the first stage of a two-stage state governor election in the Brazilian state of Santa Catarina, and then using the estimates to predict the final outcome of the second stage.


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