Statistical Analysis of the 2024 U.S. Presidential Election: Demographics and Swing States

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F25%3A00646627" target="_blank" >RIV/67985556:_____/25:00646627 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/67985807:_____/25:00645857

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Statistical Analysis of the 2024 U.S. Presidential Election: Demographics and Swing States

Popis výsledku v původním jazyce

This paper provides an analysis of the 2024 U.S. presidential election using advanced statistical techniques. The study models the popular vote as a response to eight demographic predictors at the state-wide level, incorporating results from the 2020 election to enhance the analysis. A particular focus is given to the application of two recently developed tools inspired by the least weighted squares estimator (LWS): LWS-lasso estimator and LWSquantiles, which are robust methods designed to handle datasets under multicollinearity, heteroscedasticity, and the presence of outliers. The findings emphasize the critical influence of demographic factors in shaping electoral outcomes, illustrating how demographic shifts impact the dynamics of the 2024 election. Special attention is given to the results in seven key swing states, offering precise insights into their pivotal roles in the electoral landscape. Based on the analysis, we propose a novel classification of the swing states into three distinct clusters, taking into account both their demographic outlyingness and their role in the linear model, offering new insights into their strategic importance in the electoral process.

Název v anglickém jazyce

Statistical Analysis of the 2024 U.S. Presidential Election: Demographics and Swing States

Popis výsledku anglicky

This paper provides an analysis of the 2024 U.S. presidential election using advanced statistical techniques. The study models the popular vote as a response to eight demographic predictors at the state-wide level, incorporating results from the 2020 election to enhance the analysis. A particular focus is given to the application of two recently developed tools inspired by the least weighted squares estimator (LWS): LWS-lasso estimator and LWSquantiles, which are robust methods designed to handle datasets under multicollinearity, heteroscedasticity, and the presence of outliers. The findings emphasize the critical influence of demographic factors in shaping electoral outcomes, illustrating how demographic shifts impact the dynamics of the 2024 election. Special attention is given to the results in seven key swing states, offering precise insights into their pivotal roles in the electoral landscape. Based on the analysis, we propose a novel classification of the swing states into three distinct clusters, taking into account both their demographic outlyingness and their role in the linear model, offering new insights into their strategic importance in the electoral process.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10103 - Statistics and probability

Projekt

<a href="/cs/project/GA24-10078S" target="_blank" >GA24-10078S: Nové neparametrické nástroje pro ekonometrickou analýzu dat</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

RELIK 2025 Conference Proceedings

ISBN

978-80-245-2571-6

ISSN

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e-ISSN

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Počet stran výsledku

10

Strana od-do

181-190

Název nakladatele

University of Economics and Business

Místo vydání

Prague

Místo konání akce

Prague

Datum konání akce

13. 11. 2025

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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