Kernel-based semiparametric multinomial logit modelling of political party preferences

Roland Langrock (), Nils-Bastian Heidenreich and Stefan Sperlich ()

Statistical Methods & Applications, 2014, vol. 23, issue 3, 435-449

Abstract: Conventional, parametric multinomial logit models are in general not sufficient for capturing the complex structures of electorates. In this paper, we use a semiparametric multinomial logit model to give an analysis of party preferences along individuals’ characteristics using a sample of the German electorate in 2006. Germany is a particularly strong case for more flexible nonparametric approaches in this context, since due to the reunification and the preceding different political histories the composition of the electorate is very complex and nuanced. Our analysis reveals strong interactions of the covariates age and income, and highly nonlinear shapes of the factor impacts for each party’s likelihood to be supported. Notably, we develop and provide a smoothed likelihood estimator for semiparametric multinomial logit models, which can be applied also in other application fields, such as, e.g., marketing. Copyright Springer-Verlag Berlin Heidelberg 2014

Keywords: Kernel regression; Multiple choice models; Profile likelihood; Semiparametric modelling; Voter profiling (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1007/s10260-014-0261-z

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