Abstract
U.S. presidential election forecasting has lately received considerable attention. A leading approach, statistical modeling, has undergone considerable change. We have contributed to that change in two ways, by stressing prediction over explanation and dynamics over statics. For prediction, we offer a proxy model of U.S. presidential election forecasting, based on an empirical (political economy) indicator measured six months in advance. For dynamics, we offer nowcasting, which permits the model to issue updated, current forecasts over time. To illustrate these offerings, we test them against the 2012 contest. Then, we issue our first, ex ante forecast of the 2016 presidential election.
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