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Forecasting presidential elections: When to change the model

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  • Lewis-Beck, Michael S.
  • Tien, Charles

Abstract

Here, we address the issue of forecasting from statistical models, and how they might be improved. Our real-world example is the forecasting of US presidential elections. First, we ask whether a model should be changed. To illustrate problems and opportunities, we examine the forecasting history of different models, in particular our own, which has tried to foresee presidential selection since 1984. We apply what we learn to the question of whether our Jobs model, which offered an accurate ex ante point estimate for 2004, should be changed for 2008. We conclude there is room for judicious, theory-driven adjustment, but also raise a caution about inadvertent curve-fitting. Some evidence is offered that simple core models, based on strong theory, may perform almost as well as more stretched models.

Suggested Citation

  • Lewis-Beck, Michael S. & Tien, Charles, 2008. "Forecasting presidential elections: When to change the model," International Journal of Forecasting, Elsevier, vol. 24(2), pages 227-236.
    • Handle: RePEc:eee:intfor:v:24:y:2008:i:2:p:227-236
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    Cited by:

    1. Alesina, Alberto & Furceri, Davide & Ostry, Jonathan D. & Papageorgiou, Chris & Quinn, Dennis, 2020. "Structural Reforms and Elections: Evidence from a World-Wide New Dataset," CEPR Discussion Papers 14371, C.E.P.R. Discussion Papers.
    2. Jastramskis, Mažvydas, 2012. "Election forecasting in Lithuania: The case of municipal elections," International Journal of Forecasting, Elsevier, vol. 28(4), pages 822-829.
    3. Nadeau, Richard & Lewis-Beck, Michael S. & Bélanger, Éric, 2010. "Electoral forecasting in France: A multi-equation solution," International Journal of Forecasting, Elsevier, vol. 26(1), pages 11-18, January.
    4. Arnesen, Sveinung, 2012. "Forecasting Norwegian elections: Out of work and out of office," International Journal of Forecasting, Elsevier, vol. 28(4), pages 789-796.
    5. Wang, Samuel S.-H., 2015. "Origins of Presidential poll aggregation: A perspective from 2004 to 2012," International Journal of Forecasting, Elsevier, vol. 31(3), pages 898-909.
    6. Toros, Emre, 2012. "Forecasting Turkish local elections," International Journal of Forecasting, Elsevier, vol. 28(4), pages 813-821.
    7. Toros, Emre, 2011. "Forecasting elections in Turkey," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1248-1258, October.
    8. Lewis-Beck, Michael S. & Tien, Charles, 2012. "Japanese election forecasting: Classic tests of a hard case," International Journal of Forecasting, Elsevier, vol. 28(4), pages 797-803.
    9. Mongrain, Philippe & Nadeau, Richard & Jérôme, Bruno, 2021. "Playing the synthesizer with Canadian data: Adding polls to a structural forecasting model," International Journal of Forecasting, Elsevier, vol. 37(1), pages 289-301.
    10. Tomi Ovaska & Ryo Takashima, 2019. "Export Jobs, Special Interest Groups, and the US Presidential Election of 2016: The Case of West Virginia," Journal of Private Enterprise, The Association of Private Enterprise Education, vol. 34(Winter 20), pages 75-97.

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