The Library
Hierarchical model for forecasting the outcomes of binary referenda
Tools
Tools
Tools
Wiśniowski, Arkadiusz, Bijak, Jakub, Forster, Jonathan J. and Smith, Peter W. F. (2019) Hierarchical model for forecasting the outcomes of binary referenda. Computational Statistics & Data Analysis, 133 . pp. 90-103. doi:10.1016/j.csda.2018.09.007 ISSN 0167-9473.
|
PDF
WRAP-hierarchical-model-forecasting-outcomes-binary-referenda-Forster-2019.pdf - Published Version - Requires a PDF viewer. Available under License Creative Commons Attribution 4.0. Download (1042Kb) | Preview |
Official URL: http://dx.doi.org/10.1016/j.csda.2018.09.007
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.
| Item Type: | Journal Article | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Subjects: | C Auxiliary Sciences of History > CB History of civilization H Social Sciences > HC Economic History and Conditions H Social Sciences > HM Sociology Q Science > QA Mathematics |
||||||||
| Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||||||
| Library of Congress Subject Headings (LCSH): | Public opinion polls, Forecasting, Bayesian statistical decision theory, European Union -- Great Britain, Mathematical statistics | ||||||||
| Journal or Publication Title: | Computational Statistics & Data Analysis | ||||||||
| Publisher: | Elsevier | ||||||||
| ISSN: | 0167-9473 | ||||||||
| Official Date: | May 2019 | ||||||||
| Dates: |
|
||||||||
| Volume: | 133 | ||||||||
| Page Range: | pp. 90-103 | ||||||||
| DOI: | 10.1016/j.csda.2018.09.007 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Access rights to Published version: | Open Access (Creative Commons) | ||||||||
| Date of first compliant deposit: | 28 January 2020 | ||||||||
| Date of first compliant Open Access: | 28 January 2020 | ||||||||
| RIOXX Funder/Project Grant: |
|
||||||||
| Related URLs: |
Request changes or add full text files to a record
Repository staff actions (login required)
 |
View Item |
Downloads
Downloads per month over past year
