Forecasting Elections from Voters' Perceptions of Candidates' Ability to Handle Issues

Abstract

When deciding for whom to vote, voters should select the candidate they expect to best handle issues, all other things equal. A simple heuristic predicted that the candidate who is rated more favorably on a larger number of issues would win the popular vote. This was correct for nine out of ten U.S. presidential elections from 1972 to 2008. We then used simple linear regression to relate the incumbent’s relative issue ratings to the actual two-party popular vote shares. The resulting model yielded out-of-sample forecasts that were competitive with those from the Iowa Electronic Markets and other established quantitative models. This model has implications for political decision-makers, as it can help to track campaigns and to decide which issues to focus on.

Keywords: index method, unit weighting, experience table, presidential election, accuracy