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Predicting elections from biographical information about candidates: A test of the index method

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  • Armstrong, J. Scott
  • Graefe, Andreas

Abstract

This study uses 59 biographical variables to create a "bio-index" for forecasting U.S. presidential elections. The bio-index method counts the number of variables for which each candidate rates favorably, and the forecast is that the candidate with the highest score would win the popular vote. The bio-index relies on different information and includes more variables than traditional econometric election forecasting models. The method is useful in combination with simple linear regression to estimate a relationship between the index score of the candidate of the incumbent party and his share of the popular vote. The study tests the model for the 29 U.S. presidential elections from 1896 to 2008. The model's forecasts, calculated by cross-validation, correctly predicted the popular vote winner for 27 of the 29 elections; this performance compares favorably to forecasts from polls (15 out of 19), prediction markets (22 out of 26), and three econometric models (12 to 13 out of 15 to 16). Out-of-sample forecasts of the two-party popular vote for the four elections from 1996 to 2008 yielded a forecast error almost as low as the best of seven econometric models. The model can help parties to select the candidates running for office, and help to improve on the accuracy of election forecasting, especially for longer-term forecasts.

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  • 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.
    • Handle: RePEc:eee:jbrese:v:64:y:2011:i:7:p:699-706
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    1. 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 159-173, May.
    2. Erik Snowberg & Justin Wolfers & Eric Zitzewitz, 2007. "Partisan Impacts on the Economy: Evidence from Prediction Markets and Close Elections," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(2), pages 807-829.
    3. Amy King & Andrew Leigh, 2009. "Beautiful Politicians," Kyklos, Wiley Blackwell, vol. 62(4), pages 579-593, November.
    4. Nelson, James, 2005. "Corporate governance practices, CEO characteristics and firm performance," Journal of Corporate Finance, Elsevier, vol. 11(1-2), pages 197-228, March.
    5. Berggren, Niclas & Jordahl, Henrik & Poutvaara, Panu, 2010. "The looks of a winner: Beauty and electoral success," Journal of Public Economics, Elsevier, vol. 94(1-2), pages 8-15, February.
    6. 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.
    7. 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.
    8. Allan Lichtman, 2006. "Keys to the White House: Forecast for 2008," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 3, pages 5-9, February.
    9. Cuzán, Alfred G. & Bundrick, Charles M., 2009. "Predicting Presidential Elections with Equally Weighted Regressors in Fair's Equation and the Fiscal Model," Political Analysis, Cambridge University Press, vol. 17(3), pages 333-340, July.
    10. Jason Dana & Robyn M. Dawes, 2004. "The Superiority of Simple Alternatives to Regression for Social Science Predictions," Journal of Educational and Behavioral Statistics, , vol. 29(3), pages 317-331, September.
    11. Berg, Joyce E. & Nelson, Forrest D. & Rietz, Thomas A., 2008. "Prediction market accuracy in the long run," International Journal of Forecasting, Elsevier, vol. 24(2), pages 285-300.
    12. Paul W. Rhode & Koleman S. Strumpf, 2004. "Historical Presidential Betting Markets," Journal of Economic Perspectives, American Economic Association, vol. 18(2), pages 127-141, Spring.
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    Cited by:

    1. von der Gracht, Heiko A. & Hommel, Ulrich & Prokesch, Tobias & Wohlenberg, Holger, 2016. "Testing weighting approaches for forecasting in a Group Wisdom Support System environment," Journal of Business Research, Elsevier, vol. 69(10), pages 4081-4094.
    2. Armstrong, J. Scott & Green, Kesten C. & Graefe, Andreas, 2015. "Golden rule of forecasting: Be conservative," Journal of Business Research, Elsevier, vol. 68(8), pages 1717-1731.
    3. Cote, Joseph A., 2011. "Predicting elections from biographical information about candidates: A commentary essay," Journal of Business Research, Elsevier, vol. 64(7), pages 696-698, July.
    4. Graefe, Andreas, 2023. "Embrace the differences: Revisiting the PollyVote method of combining forecasts for U.S. presidential elections (2004 to 2020)," International Journal of Forecasting, Elsevier, vol. 39(1), pages 170-177.
    5. Graefe, Andreas, 2015. "Improving forecasts using equally weighted predictors," Journal of Business Research, Elsevier, vol. 68(8), pages 1792-1799.
    6. Philippe Jacquart & J. Scott Armstrong, 2013. "The Ombudsman: Are Top Executives Paid Enough? An Evidence-Based Review," Interfaces, INFORMS, vol. 43(6), pages 580-589, December.
    7. Woike, Jan K. & Hoffrage, Ulrich & Petty, Jeffrey S., 2015. "Picking profitable investments: The success of equal weighting in simulated venture capitalist decision making," Journal of Business Research, Elsevier, vol. 68(8), pages 1705-1716.
    8. David Stadelmann & Marco Portmann & Reiner Eichenberger, 2018. "Military Service of Politicians, Public Policy, and Parliamentary Decisions," CESifo Economic Studies, CESifo, vol. 64(4), pages 639-666.
    9. Graefe, Andreas & Armstrong, J. Scott & Jones, Randall J. & Cuzan, Alfred G., 2017. "Assessing the 2016 U.S. Presidential Election Popular Vote Forecasts," MPRA Paper 83282, University Library of Munich, Germany.
    10. Graefe, Andreas & Armstrong, J. Scott & Jones, Randall J. & Cuzán, Alfred G., 2014. "Combining forecasts: An application to elections," International Journal of Forecasting, Elsevier, vol. 30(1), pages 43-54.
    11. Andreas Graefe & Kesten C Green & J Scott Armstrong, 2019. "Accuracy gains from conservative forecasting: Tests using variations of 19 econometric models to predict 154 elections in 10 countries," PLOS ONE, Public Library of Science, vol. 14(1), pages 1-14, January.
    12. Marco Portmann & David Stadelmann, 2013. "Testing the Median Voter Model and Moving Beyond its Limits: Do Characteristics of Politicians Matter?," CREMA Working Paper Series 2013-05, Center for Research in Economics, Management and the Arts (CREMA).
    13. Armstrong, J. Scott, 2011. "Illusions in Regression Analysis," MPRA Paper 81663, University Library of Munich, Germany.

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