Statistical Methods & Applications

, Volume 23, Issue 3, pp 435–449

Kernel-based semiparametric multinomial logit modelling of political party preferences

  • Roland Langrock
  • Nils-Bastian Heidenreich
  • Stefan Sperlich
Article

DOI: 10.1007/s10260-014-0261-z

Cite this article as:
Langrock, R., Heidenreich, NB. & Sperlich, S. Stat Methods Appl (2014) 23: 435. doi:10.1007/s10260-014-0261-z
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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.

Keywords

Kernel regression Multiple choice models Profile likelihood Semiparametric modelling Voter profiling 

Supplementary material

10260_2014_261_MOESM1_ESM.r (18 kb)
Supplementary material 1 (r 17 KB)

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Roland Langrock
    • 1
  • Nils-Bastian Heidenreich
    • 2
  • Stefan Sperlich
    • 3
  1. 1.University of St AndrewsSt AndrewsUK
  2. 2.Georg-August-Universität GöttingenGöttingenGermany
  3. 3.Université de GenèveGenevaSwitzerland

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