Combining Forecasts for U.S. Presidential Elections: The Pollyvote
Ludwig Maximilians University of Munich - Department of Communication Science and Media Research
Alfred G. Cuzan
University of West Florida
Randall J. Jones
University of Central Oklahoma
J. Scott Armstrong
University of Pennsylvania - Marketing Department
January 1, 2009
In the PollyVote, we evaluated the combination principle to forecast the five U.S. presidential elections between 1992 and 2008. We combined forecasts from three or four different component methods: trial heat polls, the Iowa Electronic Markets (IEM), quantitative models and, in the 2004 and 2008 contests, periodic surveys of experts on American politics. The forecasts were combined within as well as across components. On average, combining within components reduced forecast error – and increased predictive accuracy – by 17% to 40%. Combining across components led to additional error reductions ranging from 7% to 68%, depending on the forecast horizon. In addition, across all five elections, the PollyVote predicted the correct election winner on all but 4 out of 957 days. The gains from applying the combination principle to election forecasting were much larger than those obtained in other fields.
working papers series
Date posted: August 9, 2010
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