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Predicting elections from politicians’ faces

Author

Listed:
  • Armstrong, J. Scott
  • Green, Kesten C.
  • Jones, Randall J.
  • Wright, Malcolm

Abstract

Prior research found that people’s assessments of relative competence predicted the outcome of Senate and Congressional races. We hypothesized that snap judgments of "facial competence" would provide useful forecasts of the popular vote in presidential primaries before the candidates become well known to the voters. We obtained facial competence ratings of 11 potential candidates for the Democratic Party nomination and of 13 for the Republican Party nomination for the 2008 U.S. Presidential election. To ensure that raters did not recognize the candidates, we relied heavily on young subjects from Australia and New Zealand. We obtained between 139 and 348 usable ratings per candidate between May and August 2007. The top-rated candidates were Clinton and Obama for the Democrats and McCain, Hunter, and Hagel for the Republicans; Giuliani was 9th and Thompson was 10th. At the time, the leading candidates in the Democratic polls were Clinton at 38% and Obama at 20%, while Giuliani was first among the Republicans at 28% followed by Thompson at 22%. McCain trailed at 15%. Voters had already linked Hillary Clinton’s competent appearance with her name, so her high standing in the polls met our expectations. As voters learned the appearance of the other candidates, poll rankings moved towards facial competence rankings. At the time that Obama clinched the nomination, Clinton was ahead in the popular vote in the primaries and McCain had secured the Republican nomination with a popular vote that was twice that of Romney, the next highest vote-getter.

Suggested Citation

  • Armstrong, J. Scott & Green, Kesten C. & Jones, Randall J. & Wright, Malcolm, 2008. "Predicting elections from politicians’ faces," MPRA Paper 9150, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:9150
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    File URL: https://mpra.ub.uni-muenchen.de/9150/1/MPRA_paper_9150.pdf
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    References listed on IDEAS

    as
    1. Berggren, Niclas & Jordahl, Henrik & Poutvaara, Panu, 2006. "The Looks of a Winner: Beauty, Gender and Electoral Success," Ratio Working Papers 104, The Ratio Institute.
    2. Stuart, Elnora W. & Fuller, Barbara K., 1991. "Clothing as communication in two business-to-business sales settings," Journal of Business Research, Elsevier, vol. 23(3), pages 269-290, November.
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    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Becoming President of the US: a good face is enough
      by Economic Logician in Economic Logic on 2008-06-19 18:51:00

    Citations

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    Cited by:

    1. J. Scott Armstrong & Kesten C. Green & Willie Soon, 2008. "Polar Bear Population Forecasts: A Public-Policy Forecasting Audit," Interfaces, INFORMS, vol. 38(5), pages 382-405, October.
    2. Rothschild, David, 2015. "Combining forecasts for elections: Accurate, relevant, and timely," International Journal of Forecasting, Elsevier, vol. 31(3), pages 952-964.
    3. Armstrong, J. Scott & Graefe, Andreas, 2011. "Predicting elections from biographical information about candidates: A test of the index method," Journal of Business Research, Elsevier, vol. 64(7), pages 699-706, July.
    4. Daniel E Re & David W Hunter & Vinet Coetzee & Bernard P Tiddeman & Dengke Xiao & Lisa M DeBruine & Benedict C Jones & David I Perrett, 2013. "Looking Like a Leader–Facial Shape Predicts Perceived Height and Leadership Ability," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-10, December.
    5. Graefe, Andreas & Armstrong, J. Scott, 2008. "Forecasting Elections from Voters’ Perceptions of Candidates’ Positions on Issues and Policies," MPRA Paper 9829, University Library of Munich, Germany.

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    More about this item

    Keywords

    accuracy; appearance; forecasting methods; snap judgments;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods

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