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Predicting Elections from Politicians’ FacesJ. Scott ArmstrongUniversity of Pennsylvania - Marketing Department Kesten C. GreenInternational Graduate School of Business; Ehrenberg-Bass Institute for Marketing Science Randall J. JonesUniversity of Central Oklahoma Malcolm WrightUniversity of South Australia - School of Marketing 2010 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.
Keywords: accuracy, appearance, forecasting methods, snap judgments JEL Classification: D72, D79 working papers seriesDate posted: May 4, 2010Suggested CitationContact Information
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