IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v133y2019icp90-103.html
   My bibliography  Save this article

Hierarchical model for forecasting the outcomes of binary referenda

Author

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

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.

Suggested Citation

  • Wiśniowski, Arkadiusz & Bijak, Jakub & Forster, Jonathan J. & Smith, Peter W.F., 2019. "Hierarchical model for forecasting the outcomes of binary referenda," Computational Statistics & Data Analysis, Elsevier, vol. 133(C), pages 90-103.
  • Handle: RePEc:eee:csdana:v:133:y:2019:i:c:p:90-103
    DOI: 10.1016/j.csda.2018.09.007
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167947318302354
    Download Restriction: Full text for ScienceDirect subscribers only.

    File URL: https://libkey.io/10.1016/j.csda.2018.09.007?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. P. J. Brown & D. Firth & C. D. Payne, 1999. "Forecasting on British election night 1997," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 162(2), pages 211-226.
    2. Kinder, Donald R. & Kiewiet, D. Roderick, 1981. "Sociotropic Politics: The American Case," British Journal of Political Science, Cambridge University Press, vol. 11(2), pages 129-161, April.
    3. Drew A. Linzer, 2013. "Dynamic Bayesian Forecasting of Presidential Elections in the States," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(501), pages 124-134, March.
    4. John Curtice & David Firth, 2008. "Exit polling in a cold climate: the BBC–ITV experience in Britain in 2005," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(3), pages 509-539, June.
    5. Jens Großer & Arthur Schram, 2010. "Public Opinion Polls, Voter Turnout, and Welfare: An Experimental Study," American Journal of Political Science, John Wiley & Sons, vol. 54(3), pages 700-717, July.
    6. Peter Lynn & Roger Jowell, 1996. "How Might Opinion Polls be Improved?: The Case for Probability Sampling," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 159(1), pages 21-28, January.
    7. Lynn, Peter & Jäckle, Annette & Roberts, Caroline, 2008. "Assessing the effect of data collection mode on measurement," ISER Working Paper Series 2008-08, Institute for Social and Economic Research.
    8. Gelman, Andrew & King, Gary, 1993. "Why Are American Presidential Election Campaign Polls So Variable When Votes Are So Predictable?," British Journal of Political Science, Cambridge University Press, vol. 23(4), pages 409-451, October.
    9. Duch,Raymond M. & Stevenson,Randolph T., 2008. "The Economic Vote," Cambridge Books, Cambridge University Press, number 9780521881029.
    10. Auld, Tom & Linton, Oliver, 2019. "The behaviour of betting and currency markets on the night of the EU referendum," International Journal of Forecasting, Elsevier, vol. 35(1), pages 371-389.
    11. Annette Jäckle & Caroline Roberts & Peter Lynn, 2010. "Assessing the Effect of Data Collection Mode on Measurement," International Statistical Review, International Statistical Institute, vol. 78(1), pages 3-20, April.
    12. Lock, Kari & Gelman, Andrew, 2010. "Bayesian Combination of State Polls and Election Forecasts," Political Analysis, Cambridge University Press, vol. 18(3), pages 337-348, July.
    13. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    14. Duch,Raymond M. & Stevenson,Randolph T., 2008. "The Economic Vote," Cambridge Books, Cambridge University Press, number 9780521707404.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. repec:cup:judgdm:v:15:y:2020:i:5:p:863-880 is not listed on IDEAS
    2. Chun-Fang Chiang & Jason M. Kuo & Megumi Naoi & Jin-Tan Liu, 2020. "What Do Voters Learn from Foreign News? Emulation, Backlash, and Public Support for Trade Agreements," NBER Working Papers 27497, National Bureau of Economic Research, Inc.
    3. Andrew Gelman & Jessica Hullman & Christopher Wlezien & George Elliott Morris, 2020. "Information, incentives, and goals in election forecasts," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 15(5), pages 863-880, September.
    4. Jonathon M. Clegg, 2016. "Perception vs Reality: How Does The British Electorate Evaluate Economic Performance of Incumbent Governments In The Post War Period?," Oxford Economic and Social History Working Papers _143, University of Oxford, Department of Economics.
    5. Kang, Seungwoo & Oh, Hee-Seok, 2024. "Forecasting South Korea’s presidential election via multiparty dynamic Bayesian modeling," International Journal of Forecasting, Elsevier, vol. 40(1), pages 124-141.
    6. Michael Lewis-Beck & Mary Stegmaier, 2013. "The VP-function revisited: a survey of the literature on vote and popularity functions after over 40 years," Public Choice, Springer, vol. 157(3), pages 367-385, December.
    7. Andrew J. Healy & Mikael Persson & Erik Snowberg, 2016. "Digging into the Pocketbook: Evidence on Economic Voting from Income Registry Data Matched to a Voter Survey," CESifo Working Paper Series 6171, CESifo.
    8. William J Berger & Adam Sales, 2020. "Testing epistemic democracy’s claims for majority rule," Politics, Philosophy & Economics, , vol. 19(1), pages 22-35, February.
    9. Italo Colantone & Piero Stanig, 2017. "The Trade Origins of Economic Nationalism: Import Competition and Voting Behavior in Western Europe," BAFFI CAREFIN Working Papers 1749, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    10. Rodet, Cortney S., 2011. "Fact Finding Trips to Italy: An experimental investigation of voter incentives," MPRA Paper 33193, University Library of Munich, Germany.
    11. Konstantin A. Kholodilin & Vyacheslav N. Ovchinnikov & Marina Yu. Malkina & Igor A. Moiseev, 2021. "Two Dimensions of Political Trust in Russia," Discussion Papers of DIW Berlin 1934, DIW Berlin, German Institute for Economic Research.
    12. Italo Colantone & Piero Stanig, 2016. "Global Competition and Brexit," BAFFI CAREFIN Working Papers 1644, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    13. Montalvo, José G. & Papaspiliopoulos, Omiros & Stumpf-Fétizon, Timothée, 2019. "Bayesian forecasting of electoral outcomes with new parties’ competition," European Journal of Political Economy, Elsevier, vol. 59(C), pages 52-70.
    14. José Garcia Montalvo & Omiros Papaspiliopoulos & Timothée Stumpf-Fétizon, 2018. "Bayesian forecasting of electoral outcomes with new parties' competition," Economics Working Papers 1624, Department of Economics and Business, Universitat Pompeu Fabra.
    15. José García-Montalvo & Omiros Papaspiliopoulos & Timothée Stumpf-Fétizon, 2018. "Bayesian Forecasting of Electoral Outcomes with new Parties' Competition," Working Papers 1065, Barcelona School of Economics.
    16. Zawojska, Ewa & Czajkowski, Mikotaj, 2017. "Are preferences stated in web vs. personal interviews different? A comparison of willingness to pay results for a large multi-country study of the Baltic Sea eutrophication reduction," Annual Meeting, 2017, June 18-21, Montreal, Canada 258604, Canadian Agricultural Economics Society.
    17. Magalhães, Pedro C. & Aguiar-Conraria, Luís & Lewis-Beck, Michael S., 2012. "Forecasting Spanish elections," International Journal of Forecasting, Elsevier, vol. 28(4), pages 769-776.
    18. Henrik Serup Christensen & Lauri Rapeli, 2021. "Immediate rewards or delayed gratification? A conjoint survey experiment of the public’s policy preferences," Policy Sciences, Springer;Society of Policy Sciences, vol. 54(1), pages 63-94, March.
    19. Wang, Wei & Rothschild, David & Goel, Sharad & Gelman, Andrew, 2015. "Forecasting elections with non-representative polls," International Journal of Forecasting, Elsevier, vol. 31(3), pages 980-991.
    20. E Goulas & C Kallandranis & A Zervoyianni, 2019. "Voting Behaviour and the Economy: Evidence from Greece," Economic Issues Journal Articles, Economic Issues, vol. 24(1), pages 35-58, March.
    21. Linda Gonçalves Veiga, 2013. "Voting functions in the EU-15," Public Choice, Springer, vol. 157(3), pages 411-428, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:csdana:v:133:y:2019:i:c:p:90-103. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.