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It's about time: Forecasting the 2008 presidential election with the time-for-change model

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  • Abramowitz, Alan I.

Abstract

The popular vote for president can be predicted accurately before the national nominating conventions based on three factors: the incumbent president's approval rating at mid-year, the growth rate of the economy during the first half of the election year, and the length of time that the president's party has controlled the White House. Regardless of who wins the Democratic and Republican nominations, 2008 will be a time-for-change presidential election. Based on President Bush's approval rating in June of 2007, the recent growth rate of the economy, and the fact that the Republican Party will have controlled the White House for eight years, the Democratic nominee would be predicted to win the national popular vote by a comfortable margin. For the Republican nominee to have a reasonable chance of winning the 2008 presidential election, there would have to be a dramatic improvement in President Bush's approval rating during the next 12Â months.

Suggested Citation

  • Abramowitz, Alan I., 2008. "It's about time: Forecasting the 2008 presidential election with the time-for-change model," International Journal of Forecasting, Elsevier, vol. 24(2), pages 209-217.
    • Handle: RePEc:eee:intfor:v:24:y:2008:i:2:p:209-217
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    1. Fair, Ray C, 1978. "The Effect of Economic Events on Votes for President," The Review of Economics and Statistics, MIT Press, vol. 60(2), pages 159-173, May.
    2. Douglas Hibbs, 2000. "Bread and Peace Voting in U.S. Presidential Elections," Public Choice, Springer, vol. 104(1), pages 149-180, July.
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    Cited by:

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    3. Graefe, Andreas & Küchenhoff, Helmut & Stierle, Veronika & Riedl, Bernhard, 2015. "Limitations of Ensemble Bayesian Model Averaging for forecasting social science problems," International Journal of Forecasting, Elsevier, vol. 31(3), pages 943-951.
    4. Turgeon, Mathieu & Rennó, Lucio, 2012. "Forecasting Brazilian presidential elections: Solving the N problem," International Journal of Forecasting, Elsevier, vol. 28(4), pages 804-812.
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    6. Lauderdale, Benjamin E. & Linzer, Drew, 2015. "Under-performing, over-performing, or just performing? The limitations of fundamentals-based presidential election forecasting," International Journal of Forecasting, Elsevier, vol. 31(3), pages 965-979.
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    8. Norpoth, Helmut & Gschwend, Thomas, 2010. "The chancellor model: Forecasting German elections," International Journal of Forecasting, Elsevier, vol. 26(1), pages 42-53, January.
    9. 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).
    10. Kurrild-Klitgaard, Peter, 2012. "Too close to call: Growth and the cost of ruling in US presidential elections, with an application to the 2012 election," MPRA Paper 42464, University Library of Munich, Germany.
    11. 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.
    12. Ji Won Jung & Jinhwan Oh, 2020. "Determinants of presidential approval ratings: Cross-country analyses with reference to Latin America," International Area Studies Review, Center for International Area Studies, Hankuk University of Foreign Studies, vol. 23(3), pages 251-267, September.
    13. Wiesen, Taylor, 2023. "Aggregate earnings and market expectations in United States presidential election prediction markets," Advances in accounting, Elsevier, vol. 60(C).
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    16. John Sides & Michael Tesler & Lynn Vavreck, 2016. "The Electoral Landscape of 2016," The ANNALS of the American Academy of Political and Social Science, , vol. 667(1), pages 50-71, September.

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