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Forecasting proportional representation elections from non-representative expectation surveys
Institution:1. Department of Political Science, Washington University in St Louis, One Brookings Drive, 63105, Saint Louis, MO, United States;2. Department of Political Science, Instituto Tecnológico Autónomo de México (ITAM), Río Hondo 1, Col. Progreso Tizapán, 01080, Mexico City, Mexico;1. Department of Political Science, University of Gothenburg, PO Box 711, 405 30 Gothenburg, Sweden;2. Department of Political Science, University of Amsterdam, PO Box 15578, 1001 NB Amsterdam, The Netherlands
Abstract:This study tests non-representative expectation surveys as a method for forecasting elections. For dichotomous forecasts of the 2013 German election (e.g., who will be chancellor, which parties will enter parliament), two non-representative citizen samples performed equally well than a benchmark group of experts. For vote-share forecasts, the sample of more knowledgeable and interested citizens performed similar to experts and quantitative models, and outperformed the less informed citizens. Furthermore, both citizen samples outperformed prediction markets but provided less accurate forecasts than representative polls. The results suggest that non-representative surveys can provide a useful low-cost forecasting method, in particular for small-scale elections, where it may not be feasible or cost-effective to use established methods such as representative polls or prediction markets.
Keywords:Election forecasting  Citizen forecasts  Electoral expectations  Expert judgment  Forecast accuracy  Wisdom of crowds  Prediction markets
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