Temporal horizons and presidential election forecasts

In this article we present a simple forecasting model that has been successful at predicting past presidential elections. The two variables included in the model are cumulative per capita income growth and presidential approval. These ''fundamental'' variables predict the vote especially well when measured shortly in advance of the election, when the outcome is already becoming clear in the polls. Their predictive power drops quite quickly as one steps back from the election, however; readings of income growth and approval taken early in the election year only modestly predict readings of the same variables just prior to the election. Thus we turn to leading economic indicators that allow us to forecast presidential elections by giving advance indication of changes in the economy and approval during the election year. For 1996, our model offers a cautious prediction of a Clinton victory.