Forecasting proportional representation elections from non-representative expectation surveys

• Expectation surveys work well with non-representative samples for forecasting proportional representation elections.
• Expectation surveys are a useful low-cost method for forecasting elections, in particular small-scale elections.
• Surveying more interested and knowledgeable citizens improves forecast accuracy.
• Future research is necessary to assess the predictive value of non-representative expectation surveys.

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.