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

Trevor Fenner (), Eric Kaufmann (), Mark Levene and George Loizou ()
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Trevor Fenner: Department of Computer Science and Information Systems Birkbeck, University of London, London, UK
Eric Kaufmann: Department of Politics Birkbeck, University of London, London, UK
Mark Levene: Department of Computer Science and Information Systems Birkbeck, University of London, London, UK
George Loizou: Department of Computer Science and Information Systems Birkbeck, University of London, London, UK

International Journal of Modern Physics C (IJMPC), 2017, vol. 28, issue 11, 1-14

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.

Keywords: Referendum results; generative model; multiplicative process; rank-order distribution; beta-like survival function (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (2)

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DOI: 10.1142/S0129183117501327

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