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Lessons Learned

Citizen Forecasting, Candidate Resignations, and the 2024 US Presidential Election

Bibliographic Data

ID12378113
AuthorsBrian Thompson-Collart (0009-0001-1569-1786, Université Laval, corresponding author), Hubert Cadieux (0000-0002-5470-8616, Université Laval), Catherine Ouellet (0000-0002-8642-5442, Université de Montréal), Yannick Dufresne (0000-0002-6211-2193, Université Laval)
Year2024
Volume58
Issue2
Pages312-317
Publication date2024-10-15
Open AccessYes
TypeARTICLE
VenuePS Political Science & Politics (JOURNAL)
Journal identifiersISSN: 1049-0965 • E-ISSN: 1537-5935
PublisherCambridge University Press (CUP) (PUBLISHER)
DOI10.1017/s1049096524000969
OpenAlexW4403436801
LanguageEN

Every four years, numerous election-forecasting models attempt to predict the results of the US presidential election. Regardless of the stability of any election system, such as the bipartisan system in the United States, conditions can arise (e.g., candidate resignations) that negatively impact forecasters’ ability to predict electoral outcomes. Citizen forecasting—that is, directly asking respondents who they think will win an election—has a long track record of successfully predicting presidential elections. This study proposes adapting a citizen forecasting measure originally intended for use in multiparty systems to predict the US presidential election in 2024. Using this measure, we created a forecast of the national-level popular vote and vote-share forecasts for seven swing states

Economics · Political economy · Political science · Politics · Presidential election · Presidential system · Electoral Systems and Political Participation · Law · Public Administration

Highly citedNo

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