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Combining forecasts: An application to elections
Journal article   Peer reviewed

Combining forecasts: An application to elections

Andreas Graefe, J. Scott Armstrong, Randall J. Jones and Alfred G. Cuzan
International journal of forecasting, Vol.30(1), pp.43-54
01/01/2014
DOI: https://doi.org/10.1016/j.ijforecast.2013.02.005
Web of Science ID: WOS:000329560100005

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Abstract

We summarize the literature on the effectiveness of combining forecasts by assessing the conditions under which combining is most valuable. Using data on the six US presidential elections from 1992 to 2012, we report the reductions in error obtained by averaging forecasts within and across four election forecasting methods: poll projections, expert judgment, quantitative models, and the Iowa Electronic Markets. Across the six elections, the resulting combined forecasts were more accurate than any individual component method, on average. The gains in accuracy from combining increased with the numbers of forecasts used, especially when these forecasts were based on different methods and different data, and in situations involving high levels of uncertainty. Such combining yielded error reductions of between 16% and 59%, compared to the average errors of the individual forecasts. This improvement is substantially greater than the 12% reduction in error that had been reported previously for combining forecasts. (C) 2013 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.

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