Forecasting Elections

Forecasting Elections

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Article ID: iaor20162630
Volume: 35
Issue: 4
Start Page Number: 308
End Page Number: 328
Publication Date: Jul 2016
Journal: Journal of Forecasting
Authors: ,
Keywords: statistics: regression, simulation
Abstract:

In this paper we assess opinion polls, prediction markets, expert opinion and statistical modelling over a large number of US elections in order to determine which perform better in terms of forecasting outcomes. In line with existing literature, we bias‐correct opinion polls. We consider accuracy, bias and precision over different time horizons before an election, and we conclude that prediction markets appear to provide the most precise forecasts and are similar in terms of bias to opinion polls. We find that our statistical model struggles to provide competitive forecasts, while expert opinion appears to be of value. Finally we note that the forecast horizon matters; whereas prediction market forecasts tend to improve the nearer an election is, opinion polls appear to perform worse, while expert opinion performs consistently throughout. We thus contribute to the growing literature comparing election forecasts of polls and prediction markets. Copyright 2015 John Wiley & Sons, Ltd.

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