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Class War in the Voting Booth

Bias Against High‐Income Congressional Candidates

Bibliographic Data

ID6300770
AuthorsJohn D Griffin (0000-0001-8331-7561, University of Colorado Boulder), Brian Newman (0000-0002-0410-2210, Pepperdine University), Patrick Buhr (US House of Representatives)
Year2020
Volume45
Issue1
Pages131-145
Publication date2020-02-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueLegislative Studies Quarterly (JOURNAL)
Journal identifiersISSN: 0362-9805 • E-ISSN: 1939-9162
PublisherWiley (PUBLISHER • GB)
DOI10.1111/lsq.12253
OpenAlexW2971958501
LanguageEN
Citations received8
References cited26

Do Americans care how much money congressional candidates earn? We conducted three experiments to examine how candidates' incomes affect voters' perceptions of the candidates' traits and ultimately their vote intention. Subjects evaluated otherwise identical candidates with annual incomes randomly varying between $75,000, $3 million, and a candidate with no income information provided. Results from the three experiments are remarkably similar. Subjects viewed the $3 million earner as significantly more intelligent than the candidate with no income information provided, but this benefit of high income was overshadowed by significant biases against the $3 million candidate. Subjects consistently viewed the $3 million earner as less honest, less caring, and less representative of them than the other candidates. Ultimately, subjects were less likely to say they would vote for the $3 million candidate. These findings demonstrate that the campaign advantages that high‐income candidates enjoy are somewhat offset by voters' initial bias against them

Affect (linguistics · Demographic economics · Economics · Offset (computer science · Perception · Political science · Voting · Computer Science · Electoral Systems and Political Participation · Gender Politics and Representation · Law · Psychology · Social and Intergroup Psychology · Social Psychology

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Unique citing works8
Citations per year2,67
Citation span2023 - 2025 (3)
Citation velocityrecent
Highly citedNo
Citation typesNeutral: 8

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