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    A multiplicative process for generating a beta-like survival function with application to the UK 2016 EU referendum results

    Fenner, Trevor and Levene, Mark and Kaufmann, Eric P. and Loizou, George (2017) A multiplicative process for generating a beta-like survival function with application to the UK 2016 EU referendum results. International Journal of Modern Physics C 28 (11), p. 1750132. ISSN 0129-1831.

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    Abstract

    Human dynamics and sociophysics suggest statistical models that may explain and provide us with better insight into social phenomena. Contextual and selection effects tend to produce extreme values in the tails of rank-ordered distributions of both census data and district-level election outcomes. Models that account for this nonlinearity generally outperform linear models. Fitting nonlinear functions based on rank-ordering census and election data therefore improves the fit of aggregate voting models. This may help improve ecological inference, as well as election forecasting in majoritarian systems. We propose a generative multiplicative decrease model that gives rise to a rank-order distribution, and facilitates the analysis of the recent UK EU referendum results. We supply empirical evidence that the beta-like survival function, which can be generated directly from our model, is a close fit to the referendum results, and also may have predictive value when covariate data are available.

    Metadata

    Item Type: Article
    Additional Information: Electronic version of an article. © World Scientific Publishing Company
    Keyword(s) / Subject(s): referendum results, generative model, multiplicative process, rank-order distribution, beta-like survival function
    School: Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences
    Research Centres and Institutes: Data Analytics, Birkbeck Institute for
    Depositing User: Administrator
    Date Deposited: 30 Oct 2017 14:21
    Last Modified: 09 Aug 2023 12:42
    URI: https://eprints.bbk.ac.uk/id/eprint/20186

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