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A disaggregate approach to economic models of voting in U.S. presidential elections: forecasts of the 2008 election

Author

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  • Stephen Haynes

    (Department of Economics, University of Oregon)

  • Joe Stone

    (Department of Economics, University of Oregon)

Abstract

By examining disaggregate state-level data, we address two weaknesses of prior estimates of economic voting models in U.S. Presidential elections. First, our disaggregate approach substantially improves statistical power, thus reducing the danger of “over- fitting.” Second, our analysis demonstrates systematic differences in voting behavior across states, which have been ignored: voters in higher-income states respond significantly to inflation, changes in the Dow-Jones stock market average, the number of terms the incumbent party has held office, and measures of national security concerns, yet voters in lower-income states respond significantly only to economic growth. Our forecasts for the 2008 U.S. Presidential election predict a statistical dead-heat overall, but a systematic preference for Senator John McCain in lower-income states and for Senator Barack Obama in higher-income states.

Suggested Citation

  • Stephen Haynes & Joe Stone, 2008. "A disaggregate approach to economic models of voting in U.S. presidential elections: forecasts of the 2008 election," Economics Bulletin, AccessEcon, vol. 4(28), pages 1-11.
  • Handle: RePEc:ebl:ecbull:eb-08d70032
    as

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    References listed on IDEAS

    as
    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. Jayadev, Arjun, 2006. "Differing preferences between anti-inflation and anti-unemployment policy among the rich and the poor," Economics Letters, Elsevier, vol. 91(1), pages 67-71, April.
    3. Stephen E. Haynes & Joe A. Stone, 1994. "Why Did Economic Models Falsely Predict A Bush Landslide In 1992?," Contemporary Economic Policy, Western Economic Association International, vol. 12(2), pages 123-130, April.
    4. Moulton, Brent R, 1990. "An Illustration of a Pitfall in Estimating the Effects of Aggregate Variables on Micro Unit," The Review of Economics and Statistics, MIT Press, vol. 72(2), pages 334-338, May.
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    Cited by:

    1. Graefe, Andreas & Armstrong, J. Scott & Jones, Randall J. & Cuzán, Alfred G., 2014. "Combining forecasts: An application to elections," International Journal of Forecasting, Elsevier, vol. 30(1), pages 43-54.
    2. Graefe, Andreas, 2023. "Embrace the differences: Revisiting the PollyVote method of combining forecasts for U.S. presidential elections (2004 to 2020)," International Journal of Forecasting, Elsevier, vol. 39(1), pages 170-177.

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    More about this item

    JEL classification:

    • D7 - Microeconomics - - Analysis of Collective Decision-Making
    • A1 - General Economics and Teaching - - General Economics

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