Accuracy of German federal election forecasts, 2013 & 2017

• Published in: International journal of forecasting Vol. 35; no. 3; pp. 868 - 877
• Main Author: Graefe, Andreas
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.07.2019
• Subjects: Combining forecasts; Econometric models; Election forecasting; Expert judgment; Polls; Prediction markets; Expert judgment; Econometric models; Election forecasting; Combining forecasts; Prediction markets; Polls
• ISSN: 0169-2070; 1872-8200
• DOI: 10.1016/j.ijforecast.2019.01.004

The present study reviews the accuracy of four methods (polls, prediction markets, expert judgment, and quantitative models) for forecasting the two German federal elections in 2013 and 2017. On average across both elections, polls and prediction markets were most accurate, while experts and quantitative models were least accurate. However, the accuracy of individual forecasts did not correlate across elections. That is, the methods that were most accurate in 2013 did not perform particularly well in 2017. A combined forecast, calculated by averaging forecasts within and across methods, was more accurate than three of the four component forecasts. The results conform to prior research on US presidential elections in showing that combining is effective in generating accurate forecasts and avoiding large errors.