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Citizen Forecasting: Can Voters See into the Future?

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  • Lewis-Beck, Michael S.
  • Skalaban, Andrew

Abstract

Political science, unlike economics, does not have a long tradition of forecasting models. However, this is changing. Currently, there is considerable interest in election forecasting. The basis for the interest is a flurry of related publications on House, Senate and presidential elections. A common goal for these studies is the development of a model, inevitably based on aggregate time-series data, which predicts election returns. The resulting models, some of which are quite accurate, can differ a good deal in specification and estimation. Also, they vary in complexity, making them more or less accessible to the engaged voter.

Suggested Citation

  • 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.
    • Handle: RePEc:cup:bjposi:v:19:y:1989:i:01:p:146-153_00
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    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. Franch, Fabio, 2021. "Political preferences nowcasting with factor analysis and internet data: The 2012 and 2016 US presidential elections," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    3. Quinlan, Stephen & Lewis-Beck, Michael S., 2021. "Forecasting government support in Irish general elections: Opinion polls and structural models," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1654-1665.
    4. Meffert, Michael F. & Gschwend, Thomas, 2008. "Strategic Voting in Multiparty Systems: A Group Experiment," Sonderforschungsbereich 504 Publications 08-10, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
    5. Meffert, Michael F. & Gschwend, Thomas, 2007. "Polls, coalitions signals, and strategic voting : an experimental investigation of perceptions and effects," Papers 07-63, Sonderforschungsbreich 504.
    6. 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.
    7. Lennart Sjöberg, 2009. "Are all crowds equally wise? a comparison of political election forecasts by experts and the public," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(1), pages 1-18.
    8. 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.
    9. Huber, Sascha & Gschwend, Thomas & Meffert, Michael F. & Pappi, Franz Urban, 2008. "Erwartungsbildung über den Wahlausgang und ihr Einfluss auf die Wahlentscheidung," Papers 08-01, Sonderforschungsbreich 504.
    10. 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.
    11. 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.
    12. 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.
    13. Meffert, Michael F. & Gschwend, Thomas, 2007. "Voting for Coalitions? The Role of Coalition Preferences and Expectations in Voting Behavior," Sonderforschungsbereich 504 Publications 07-64, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
    14. Ron Johnston & Todd Hartman & Charles Pattie, 2019. "Predicting general election outcomes: campaigns and changing voter knowledge at the 2017 general election in England," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(3), pages 1369-1389, May.
    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. 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.

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