To improve their predictions, election forecasters should look to other disciplines like meteorology

The recent surge in public attention to election predictions has generated much discussion about how to improve forecasting model accuracy. Michael S. Lewis-Beck and Mary Stegmaier argue that advances in weather forecasting hold lessons for election forecasting. First, like weather models, election models should be based on sound theory. Second, more intensive data gathering, especially at the state level with repeated measurements over time, will capture the dynamics of the campaign and ultimately enhance the accuracy of predictions. Third, ensemble forecasting and applying expertise to adjust forecasts are other methods to consider for reducing forecast error