Predicting Elections from Biographical Information about Candidates

Armstrong, J. Scott and Graefe, Andreas (2009): Predicting Elections from Biographical Information about Candidates.

Abstract

Using the index method, we developed the PollyBio model to predict election outcomes. The model, based on 49 cues about candidates’ biographies, was used to predict the outcome of the 28 U.S. presidential elections from 1900 to 2008. In using a simple heuristic, it correctly predicted the winner for 25 of the 28 elections and was wrong three times. In predicting the two-party vote shares for the last four elections from 1996 to 2008, the model’s out-of-sample forecasts yielded a lower forecasting error than 12 benchmark models. By relying on different information and including more variables than traditional models, PollyBio improves on the accuracy of election forecasting. It is particularly helpful for forecasting open-seat elections. In addition, it can help parties to select the candidates running for office.

• Item Type: MPRA Paper
• Language: English
• Keywords: forecasting, unit weighting, Dawes rule, differential weighting
• Subjects: C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods; D - Microeconomics > D7 - Analysis of Collective Decision-Making > D72 - Political Processes: Rent-Seeking, Lobbying, Elections, Legislatures, and Voting Behavior

References

Abramowitz, A. I. (1996). Bill and Al's excellent adventure: Forecasting the 1996 presidential election, American Politics Research, 24, 434-442.

Armstrong, J. S. (1985). Long-range forecasting: From crystal ball to computer, New York: John Wiley.

Armstrong, J. S. (2001). Combining Forecasts. In: J. S. Armstrong (Eds.), Principles of Forecasting. A Handbook for Researchers and Practitioners. Norwell; Kluwer Academic Publishers, pp. 417-439.

Armstrong, J. S. & Cuzán, A. G. (2006). Index methods for forecasting: An application to the American Presidential Elections, Foresight, 2006, 10-13.

Burgess, E. W. (1939). Predicting success or failure in marriage, New York: Prentice-Hall.

Campbell, J. E. (1996). Polls and votes: the trial-heat presidential election forecasting model, certainty, and political campaigns, American Politics Research, 24, 408-443.

Campbell, J. E. (2008). The Trial-Heat Forecast of the 2008 Presidential Vote: Performance and Value Considerations in an Open-Seat Election, PS: Political Science & Politics, 41, 697-701.

Cuzán, A. G. & Bundrick, C. M. (2008). Predicting presidential elections with equally-weighted regressors in Fair's equation and the fiscal model, University of West Florida, Working Paper. Available at http://www.uwf.edu/govt/documents/CuzanandBundrick-2008-PredictingPresidentialElections6-23-08.pdf.

Cuzán, A. G. & Heggen, R. J. (1984). A fiscal model of presidential elections in the United States, 1880-1980, Presidential Studies Quarterly, 14, 98-108.

Czerlinski, J., Gigerenzer, G. & Goldstein, D. G. (1999). How good are simple heuristics? In: G. Gigerenzer & Todd, P. M. (Eds.), Simple heuristics that make us smart. Oxford University Press, pp. 97-118.

Dana, J. & Dawes, R. M. (2004). The superiority of simple alternatives to regression for social science predictions, Journal of Educational and Behavioral Statistics, 29, 317-331.

Einhorn, H. J. & Hogarth, R. M. (1975). Unit weighting schemes for decision-making, Organizational Behavior & Human Performance, 13, 171-192.

Fair, R. C. (1978). The effect of economic events on votes for president, Review of Economics and Statistics, 60, 159-173.

Gough, H. G. (1962). Clinical versus statistical prediction in psychology. In: L. Postman (Eds.), Psychology in the making. New York; Knopf, pp. 526-584.

Graefe, A. & Armstrong, J. S. (2008). Forecasting Elections from Voters’ Perceptions of Candidates’ Ability to Handle Issues, Available at http://www.forecastingprinciples.com/PollyVote/images/articles/index_us.pdf.

Graefe, A., Cuzán, A. G., Jones Jr, R. J. & Armstrong, J. S. (2009). The PollyVote: Combining forecasts to predict U.S. Presidential Elections, Working Paper, Available from the author.

Hogarth, R. M. (2006). When simple is hard to accept. In: P. M. Todd & Gigerenzer, G. (Eds.), Ecological rationality: Intelligence in the world (in press). Oxford; Oxford University Press, pp.

Jones, R. J. & Cuzán, A. G. (2008). Forecasting U.S. Presidential Elections: A brief review, Foresight, 2008, 29-34.

Lichtman, A. J. (2008). The keys to the white house: An index forecast for 2008, International Journal of Forecasting, 24, 301-309.

Simonton, D. K. (1993). Putting the best leaders in the White House: Personality, policy, and performance, Political Psychology, 14, 537-548.

Wlezien, C. (2001). On forecasting the presidential vote, PS: Political Science and Politics, 34, 25-31.