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<p>This article attempts to get closer to the phenomenon of “swing states” and the role of US governors in the US presidential election campaign in terms of quality and quantity. We first work out essential characteristics of the “swing states” and hypothesize that the respective governors in these US states, who are initially uncertain for the candidates themselves, can reduce this uncertainty. Namely, if they directly or indirectly support the candidate of their own party. In the quantitative part of the article, we discuss the current “swing states” of the election campaign in 2024, present Kamala Harris’ chances of winning in various scenarios, and use a&#xa0;statistical test based on observations since 1919 to examine how likely it is (conditional forecast) for a&#xa0;presidential candidate to win individual “swing states” if the incumbent governor stems from his own party (Democrats, Republicans). We compare the results obtained in this way with the latest election polls and, at the end, with the actual election results of November 5th, 2024. This shows that our own forecast performs well compared to the election polls shortly before election day and is quite close to the actual election results.</p>

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The “US governor in the back” hypothesis: a long wave tool for the prediction of US presidential election results

  • 期刊论文

  • 发表日期：

    2025年3月13日

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  • Friedrich L. Sell,
  • Jürgen Stiefl

摘要

This article attempts to get closer to the phenomenon of “swing states” and the role of US governors in the US presidential election campaign in terms of quality and quantity. We first work out essential characteristics of the “swing states” and hypothesize that the respective governors in these US states, who are initially uncertain for the candidates themselves, can reduce this uncertainty. Namely, if they directly or indirectly support the candidate of their own party. In the quantitative part of the article, we discuss the current “swing states” of the election campaign in 2024, present Kamala Harris’ chances of winning in various scenarios, and use a statistical test based on observations since 1919 to examine how likely it is (conditional forecast) for a presidential candidate to win individual “swing states” if the incumbent governor stems from his own party (Democrats, Republicans). We compare the results obtained in this way with the latest election polls and, at the end, with the actual election results of November 5th, 2024. This shows that our own forecast performs well compared to the election polls shortly before election day and is quite close to the actual election results.