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Election Turnout Statistics in Many Countries: Similarities, Differences, and a Diffusive Field Model for Decision-Making

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  • Christian Borghesi
  • Jean-Claude Raynal
  • Jean-Philippe Bouchaud

Abstract

We study in details the turnout rate statistics for 77 elections in 11 different countries. We show that the empirical results established in a previous paper for French elections appear to hold much more generally. We find in particular that the spatial correlation of turnout rates decay logarithmically with distance in all cases. This result is quantitatively reproduced by a decision model that assumes that each voter makes his mind as a result of three influence terms: one totally idiosyncratic component, one city-specific term with short-ranged fluctuations in space, and one long-ranged correlated field which propagates diffusively in space. A detailed analysis reveals several interesting features: for example, different countries have different degrees of local heterogeneities and seem to be characterized by a different propensity for individuals to conform to the cultural norm. We furthermore find clear signs of herding (i.e., strongly correlated decisions at the individual level) in some countries, but not in others.

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  • Christian Borghesi & Jean-Claude Raynal & Jean-Philippe Bouchaud, 2012. "Election Turnout Statistics in Many Countries: Similarities, Differences, and a Diffusive Field Model for Decision-Making," PLOS ONE, Public Library of Science, vol. 7(5), pages 1-12, May.
    • Handle: RePEc:plo:pone00:0036289
    DOI: 10.1371/journal.pone.0036289
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    References listed on IDEAS

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    1. M. C. González & A. O. Sousa & H. J. Herrmann, 2004. "Opinion Formation On A Deterministic Pseudo-Fractal Network," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 15(01), pages 45-57.
    2. Benny Geys, 2006. "‘Rational’ Theories of Voter Turnout: A Review," Political Studies Review, Political Studies Association, vol. 4(1), pages 16-35, January.
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    Cited by:

    1. H Hernández-Saldaña, 2013. "Results on Three Predictions for July 2012 Federal Elections in Mexico Based on Past Regularities," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-8, December.
    2. Aleksejus Kononovicius, 2017. "Empirical Analysis and Agent-Based Modeling of the Lithuanian Parliamentary Elections," Complexity, Hindawi, vol. 2017, pages 1-15, November.
    3. Maulana, Ardian & Situngkir, Hokky, 2015. "Korelasi Bebas-skala dalam Studi Geo-politik Pemilihan [Scale-free correlation within Geopolitics of Election Studies]," MPRA Paper 66351, University Library of Munich, Germany.
    4. Cardoso, M. & Mendes, R.S. & Souza, J.T.G. & Ribeiro, H.V., 2020. "Gender difference in candidature processes for Brazilian elections," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    5. Cardoso, M. & Silva, L.M.C. & Neli, R.R. & Souza, W.E., 2022. "Electorate involvement disorder: Universal relationship between the amplitude and electorate size in second round of Brazilian Presidential Election," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 591(C).
    6. Rowden, Jessica & Lloyd, David J.B. & Gilbert, Nigel, 2014. "A model of political voting behaviours across different countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 609-625.
    7. Hygor Piaget M Melo & Saulo D S Reis & André A Moreira & Hernán A Makse & José S Andrade Jr., 2018. "The price of a vote: Diseconomy in proportional elections," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-13, August.
    8. Volker Hösel & Johannes Müller & Aurelien Tellier, 2019. "Universality of neutral models: decision process in politics," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-8, December.
    9. Jean-Philippe Bouchaud, 2012. "Crises and collective socio-economic phenomena: simple models and challenges," Papers 1209.0453, arXiv.org, revised Dec 2012.
    10. Braha, Dan & de Aguiar, Marcus A. M., 2018. "Voting contagion: Modeling and analysis of a century of U.S. presidential elections," SocArXiv mzxnr, Center for Open Science.
    11. Hygor P M Melo & Nuno A M Araújo & José S Andrade Jr., 2019. "Fundraising and vote distribution: A non-equilibrium statistical approach," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-9, October.

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