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Predicting Elections from Biographical Information about Candidates (2009)

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.

Publication details
Download http://mpra.ub.uni-muenchen.de/17709/1/PollyBio.pdf
Repository Munich RePEc Personal Archive (Germany)
Keywords C53 - Forecasting and Other Model Applications, D72 - Economic Models of Political Processes: Rent-Seeking, Elections, Legislatures, and Voting Behavior
Type MPRA Paper, NonPeerReviewed
Relation http://mpra.ub.uni-muenchen.de/17709/