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Kernel-based semiparametric multinomial logit modelling of political party preferences

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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.

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Acknowledgments

The authors would like to thank Walter Zucchini and two anonymous referees for helpful comments on earlier versions of this paper. Furthermore, the authors are very grateful to Thomas Kneib for helping us with the use of the BayesX software to realize the comparison with his method. The third author acknowledges financial support from the Swiss National Science Foundation, project 100018-140295.

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Authors and Affiliations

  1. University of St Andrews, St Andrews, UK

    Roland Langrock

  2. Georg-August-Universität Göttingen, Göttingen, Germany

    Nils-Bastian Heidenreich

  3. Université de Genève, Geneva, Switzerland

    Stefan Sperlich

Authors
  1. Roland Langrock
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  2. Nils-Bastian Heidenreich
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  3. Stefan Sperlich
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Corresponding author

Correspondence to Roland Langrock.

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Langrock, R., Heidenreich, NB. & Sperlich, S. Kernel-based semiparametric multinomial logit modelling of political party preferences. Stat Methods Appl 23, 435–449 (2014). https://doi.org/10.1007/s10260-014-0261-z

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