Hierarchical model for forecasting the outcomes of binary referenda

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

Research output: Contribution to journalArticlepeer-review


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 predictions 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.
Original languageEnglish
Pages (from-to)90-103
Number of pages14
JournalComputational Statistics & Data Analysis
Early online date27 Sept 2018
Publication statusPublished - May 2019


  • Bayesian inference
  • Brexit
  • Forecasting
  • Opinion polls
  • Statistical modelling
  • United kingdom


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