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Combining Aggregate Data and Exit Polls for the Estimation of Voter Transitions

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Listed:
  • André Klima
  • Thomas Schlesinger
  • Paul W. Thurner
  • Helmut Küchenhoff

Abstract

Our objective is the estimation of voter transitions between two consecutive parliamentary elections. Usually, such analyses have been based either on individual survey data or on aggregated data. To move beyond these methods and their respective problems, we propose the application of so-called hybrid models, which combine aggregate and individual data. We use a Bayesian approach and extend a multinomial-Dirichlet model proposed in the ecological inference literature. Our new hybrid model has been implemented in the R-package eiwild (= Ecological Inference with individual-level data). Based on extensive simulations, we are able to show that our new estimator exhibits a very good estimation performance in many realistic scenarios. Application case is the voter transition between the Bavarian Regional election and the German federal elections 2013 in the Metropolitan City of Munich. Our approach is also applicable to other areas of electoral research, market research, and epidemiology.

Suggested Citation

  • André Klima & Thomas Schlesinger & Paul W. Thurner & Helmut Küchenhoff, 2019. "Combining Aggregate Data and Exit Polls for the Estimation of Voter Transitions," Sociological Methods & Research, , vol. 48(2), pages 296-325, May.
    • Handle: RePEc:sae:somere:v:48:y:2019:i:2:p:296-325
    DOI: 10.1177/0049124117701477
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    References listed on IDEAS

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    1. Elff, Martin & Gschwend, Thomas & Johnston, Ron J., 2008. "Ignoramus, Ignorabimus? On Uncertainty in Ecological Inference," Political Analysis, Cambridge University Press, vol. 16(1), pages 70-92, January.
    2. Himmelweit, Hilde T. & Biberian, Marianne Jaeger & Stockdale, Janet, 1978. "Memory for Past Vote: Implications of a Study of Bias in Recall," British Journal of Political Science, Cambridge University Press, vol. 8(3), pages 365-375, July.
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    Cited by:

    1. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    2. Pablo Sandoval & Silvia Ojeda, 2023. "Estimation of electoral volatility parameters employing ecological inference methods," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(1), pages 405-426, February.

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