Hierarchical model for forecasting the outcomes of binary referenda

Arkadiusz Wiśniowski, Jakub Bijak, Jonathan J. Forster and Peter W.F. Smith

Computational Statistics & Data Analysis, 2019, vol. 133, issue C, 90-103

Abstract: A Bayesian hierarchical model is proposed to forecast outcomes of binary referenda based on opinion poll data acquired over a period of time. It is demonstrated how the model provides a consistent probabilistic prediction of the final outcomes over the preceding months, effectively smoothing the volatility exhibited by individual polls. The method is illustrated using opinion poll data published before the Scottish independence referendum in 2014, in which Scotland voted to remain a part of the United Kingdom, and subsequently validate it on the data related to the 2016 referendum on the continuing membership of the United Kingdom in the European Union.

Keywords: Opinion polls; Forecasting; Bayesian inference; Statistical modelling; United kingdom; Brexit (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:133:y:2019:i:c:p:90-103

DOI: 10.1016/j.csda.2018.09.007

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