IDEAS home Printed from https://ideas.repec.org/a/eee/intfor/v31y2015i3p916-929.html
   My bibliography  Save this article

The wisdom of crowds: Applying Condorcet’s jury theorem to forecasting US presidential elections

Author

Listed:
  • Murr, Andreas E.

Abstract

Increasingly, professional forecasters rely on citizen forecasts when predicting election results. Following this approach, forecasters predict the winning party to be the one which most citizens have said will win. This approach predicts winners and vote shares well, but related research has shown that some citizens forecast better than others. Extensions of Condorcet’s jury theorem suggest that naïve citizen forecasting can be improved by delegating the forecasting to the most competent citizens and by weighting their forecasts by their level of competence. Indeed, doing so increases both the accuracy of vote share predictions and the number of states forecast correctly. Allocating the state’s electoral votes to the candidate who the most weighted delegates say will win yields a simple but successful forecasting model of the US Presidency. The ‘wisdom of crowds’ model predicts eight presidential elections out of nine correctly. The results suggest that delegating and weighting provide easy ways to improve citizen forecasting.

Suggested Citation

  • Murr, Andreas E., 2015. "The wisdom of crowds: Applying Condorcet’s jury theorem to forecasting US presidential elections," International Journal of Forecasting, Elsevier, vol. 31(3), pages 916-929.
    • Handle: RePEc:eee:intfor:v:31:y:2015:i:3:p:916-929
    DOI: 10.1016/j.ijforecast.2014.12.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0169207014001770
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ijforecast.2014.12.002?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. Samuel E. Bodily, 1979. "Note--A Delegation Process for Combining Individual Utility Functions," Management Science, INFORMS, vol. 25(10), pages 1035-1041, October.
    2. Michael D Ward & Brian D Greenhill & Kristin M Bakke, 2010. "The perils of policy by p-value: Predicting civil conflicts," Journal of Peace Research, Peace Research Institute Oslo, vol. 47(4), pages 363-375, July.
    3. Raphael Kazmann, 1973. "Democratic organization: A preliminary mathematical model," Public Choice, Springer, vol. 16(1), pages 17-26, September.
    4. Lloyd Shapley & Bernard Grofman, 1984. "Optimizing group judgmental accuracy in the presence of interdependencies," Public Choice, Springer, vol. 43(3), pages 329-343, January.
    5. Nitzan, Shmuel & Paroush, Jacob, 1982. "Optimal Decision Rules in Uncertain Dichotomous Choice Situations," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 23(2), pages 289-297, June.
    6. 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.
    7. Bernard Grofman, 1975. "A comment on ‘democratic theory: A preliminary mathematical model.’," Public Choice, Springer, vol. 21(1), pages 99-103, March.
    8. Lewis-Beck, Michael S. & Skalaban, Andrew, 1989. "Citizen Forecasting: Can Voters See into the Future?," British Journal of Political Science, Cambridge University Press, vol. 19(1), pages 146-153, January.
    9. Lewis-Beck, Michael S. & Tien, Charles, 1999. "Voters as forecasters: a micromodel of election prediction," International Journal of Forecasting, Elsevier, vol. 15(2), pages 175-184, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Leiter, Debra & Murr, Andreas & Rascón Ramírez, Ericka & Stegmaier, Mary, 2018. "Social networks and citizen election forecasting: The more friends the better," International Journal of Forecasting, Elsevier, vol. 34(2), pages 235-248.
    2. Vincenz Frey & Arnout van de Rijt, 2021. "Social Influence Undermines the Wisdom of the Crowd in Sequential Decision Making," Management Science, INFORMS, vol. 67(7), pages 4273-4286, July.
    3. Temporão, Mickael & Dufresne, Yannick & Savoie, Justin & Linden, Clifton van der, 2019. "Crowdsourcing the vote: New horizons in citizen forecasting," International Journal of Forecasting, Elsevier, vol. 35(1), pages 1-10.
    4. Khan, Urmee & Lieli, Robert P., 2018. "Information flow between prediction markets, polls and media: Evidence from the 2008 presidential primaries," International Journal of Forecasting, Elsevier, vol. 34(4), pages 696-710.
    5. Liu, Yezheng & Ye, Chang & Sun, Jianshan & Jiang, Yuanchun & Wang, Hai, 2021. "Modeling undecided voters to forecast elections: From bandwagon behavior and the spiral of silence perspective," International Journal of Forecasting, Elsevier, vol. 37(2), pages 461-483.
    6. Oliver Merz & Raphael Flepp & Egon Franck, 2021. "Underestimating randomness: Outcome bias in betting exchange markets," Working Papers 390, University of Zurich, Department of Business Administration (IBW).
    7. Steve Alpern & Bo Chen, 2022. "Optimizing voting order on sequential juries: a median voter theorem and beyond," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 58(3), pages 527-565, April.

    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. Leiter, Debra & Murr, Andreas & Rascón Ramírez, Ericka & Stegmaier, Mary, 2018. "Social networks and citizen election forecasting: The more friends the better," International Journal of Forecasting, Elsevier, vol. 34(2), pages 235-248.
    2. Liu, Yezheng & Ye, Chang & Sun, Jianshan & Jiang, Yuanchun & Wang, Hai, 2021. "Modeling undecided voters to forecast elections: From bandwagon behavior and the spiral of silence perspective," International Journal of Forecasting, Elsevier, vol. 37(2), pages 461-483.
    3. Bryan C. McCannon & Paul Walker, 2016. "Endogenous competence and a limit to the Condorcet Jury Theorem," Public Choice, Springer, vol. 169(1), pages 1-18, October.
    4. Dhillon, Amrita & Kotsialou, Grammateia & Xefteris, Dimitris, 2021. "Information Aggregation with Delegation of Votes," SocArXiv ubk7p, Center for Open Science.
    5. Scott Feld & Bernard Grofman, 1984. "The accuracy of group majority decisions in groups with added members," Public Choice, Springer, vol. 42(3), pages 273-285, January.
    6. Xiaohong Yu & Zhaoyang Sun, 2022. "The company they keep: When and why Chinese judges engage in collegiality," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 19(4), pages 936-1002, December.
    7. Eyal Baharad & Jacob Goldberger & Moshe Koppel & Shmuel Nitzan, 2012. "Beyond Condorcet: optimal aggregation rules using voting records," Theory and Decision, Springer, vol. 72(1), pages 113-130, January.
    8. Sjöberg, Lennart, 2006. "Are all crowds equally wise? A comparison of political election forecasts by experts and the public," SSE/EFI Working Paper Series in Business Administration 2006:9, Stockholm School of Economics, revised 08 Sep 2008.
    9. Karotkin, D. & Nitzan, S., 1993. "Some Peculiarities of Group Decision Making in Teams," Discussion Paper 1993-3, Tilburg University, Center for Economic Research.
    10. Khan, Urmee & Lieli, Robert P., 2018. "Information flow between prediction markets, polls and media: Evidence from the 2008 presidential primaries," International Journal of Forecasting, Elsevier, vol. 34(4), pages 696-710.
    11. Ben-Yashar, Ruth & Nitzan, Shmuel, 2019. "Skill, value and remuneration in committees," Economics Letters, Elsevier, vol. 174(C), pages 93-95.
    12. Temporão, Mickael & Dufresne, Yannick & Savoie, Justin & Linden, Clifton van der, 2019. "Crowdsourcing the vote: New horizons in citizen forecasting," International Journal of Forecasting, Elsevier, vol. 35(1), pages 1-10.
    13. Ben-Yashar, Ruth & Danziger, Leif, 2011. "Symmetric and asymmetric committees," Journal of Mathematical Economics, Elsevier, vol. 47(4-5), pages 440-447.
    14. Baharad, Eyal & Ben-Yashar, Ruth & Patal, Tal, 2020. "On the merit of non-specialization in the context of majority voting," Journal of Mathematical Economics, Elsevier, vol. 87(C), pages 128-133.
    15. Stiers, Dieter & Dassonneville, Ruth, 2018. "Affect versus cognition: Wishful thinking on election day," International Journal of Forecasting, Elsevier, vol. 34(2), pages 199-215.
    16. Ruth Ben-Yashar & Shmuel Nitzan & Tomoya Tajika, 2021. "Skill, power and marginal contribution in committees," Journal of Theoretical Politics, , vol. 33(2), pages 225-235, April.
    17. Lloyd Shapley & Bernard Grofman, 1984. "Optimizing group judgmental accuracy in the presence of interdependencies," Public Choice, Springer, vol. 43(3), pages 329-343, January.
    18. Ruth Ben-Yashar & Igal Milchtaich, 2003. "First and Second Best Voting Rules in Committees," Working Papers 2003-08, Bar-Ilan University, Department of Economics.
    19. Ben Abramowitz & Omer Lev & Nicholas Mattei, 2022. "Who Reviews The Reviewers? A Multi-Level Jury Problem," Papers 2211.08494, arXiv.org, revised Dec 2023.
    20. Eyal Baharad & Ruth Ben-Yashar & Shmuel Nitzan, 2020. "Variable Competence and Collective Performance: Unanimity Versus Simple Majority Rule," Group Decision and Negotiation, Springer, vol. 29(1), pages 157-167, February.

    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:intfor:v:31:y:2015:i:3:p:916-929. 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/ijforecast .

    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.