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Forecasting Elections from Voters’ Perceptions of Candidates’ Positions on Issues and Policies

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  • Graefe, Andreas
  • Armstrong, J. Scott

Abstract

Ideally, presidential elections should be decided based on how the candidates would handle issues facing the country. If so, knowledge about the voters’ perception of the candidates should help to forecast election outcomes. We make two forecasts of the winner of the popular vote in the U.S. Presidential Election. One is based on voters’ perceptions of how the candidates would deal with issues (problems facing the country) if elected. We show that this approach would have correctly picked the winner for the three elections from 1996 to 2004. The other is based on voters’ preference for policies and their perceptions of which policies the candidates are likely to pursue. Both approaches lead to a forecast that Democrat candidate Barack Obama will win the popular vote.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 9829.

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Date of creation: 04 Aug 2008
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Handle: RePEc:pra:mprapa:9829

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Keywords: forecasting methods; regression models; index method; experience tables; accuracy;

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  1. Lichtman, Allan J., 2008. "The keys to the white house: An index forecast for 2008," International Journal of Forecasting, Elsevier, vol. 24(2), pages 301-309.
  2. Fair, Ray C, 1978. "The Effect of Economic Events on Votes for President," The Review of Economics and Statistics, MIT Press, vol. 60(2), pages 159-73, May.
  3. Randall J. Jones, Jr. & Alfred G. Cuzán, 2008. "Forecasting U.S. Presidential Elections: A Brief Review," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 10, pages 29-34, Summer.
  4. 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.
  5. S. Wilks, 1938. "Weighting systems for linear functions of correlated variables when there is no dependent variable," Psychometrika, Springer, vol. 3(1), pages 23-40, March.
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Cited by:
  1. Armstrong, J. Scott & Green, Kesten C. & Graefe, Andreas, 2014. "Golden Rule of Forecasting: Be conservative," MPRA Paper 53579, University Library of Munich, Germany.
  2. Armstrong, J. Scott & Graefe, Andreas, 2009. "Predicting Elections from Biographical Information about Candidates," MPRA Paper 16461, University Library of Munich, Germany.

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