Comparative election forecasting: Further insights from synthetic models. (September 2015) - Lewis-Beck, Michael S.; Dassonneville, Ruth
Abstract: As an enterprise, election forecasting has spread and grown. Initial work began in the 1980s in the United States, eventually traveling to Western Europe, where it finds a current outlet in the most of the region's democracies. However, that work has been confined to traditional approaches – statistical modeling or poll-watching. We import a new approach, which we call synthetic modeling. These forecasts come from hybrid models blending structural knowledge with contemporary public opinion, to generate ongoing nowcasts of Western European national contests, from six months prior to Election Day itself. These test results, based on election pools from Germany, the United Kingdom, and France, encourage similar research on other European electorates. Highlights: We import synthetic modeling to forecasting elections in European democracies (Germany, the United Kingdom and France). Synthetic models blend structural forecasting models and vote intention polls. Synthetic models add a dynamic perspective to forecasting elections and result in a gain of accuracy. Both the structural and the vote intention part are important and their importance varies from one context to another. The synthetic approach to forecasting elections should be investigated further and tested in more democracies.