Predicting elections from biographical information about candidates
Symposium on Leadership and Individual Differences, Lausanne, November 30 - December 1, 2009
Armstrong, J. S. & A. Graefe (2009), Predicting Elections from biographical information about candidates, MPRA Working Paper, Available at: http://mpra.ub.uni-muenchen.de/16702/.
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.
