Similarly, a one-point increase in annualized real GDP growth during the second quarter is worth just over half a percentage point in vote share for the candidate of the president’s party. later term based on terms for incumbent party.Īccording to these results, a one-point increase in net approval for the incumbent president is worth just over one-tenth of a percentage point in vote share for the candidate of the president’s party.
Notes: Dependent variable is percentage of major party vote won by candidate of incumbent party first vs. Table 1: Estimated regression coefficients for Time for Change Model, 1948-2012 The estimated coefficients for all three predictors are highly statistically significant and the model has an impressive adjusted R-squared of. These estimates are based on the results of an OLS regression analysis using data on the 17 presidential elections between 19. What does the Time for Change model predict for 2016? Estimated weights of the three predictors for the 2016 presidential election are displayed in Table 1. Using these three predictors, it is possible to forecast the incumbent party’s share of the major party vote with a high degree of accuracy around three months before Election Day. This model is based on three predictors - the incumbent president’s approval rating at midyear (late June or early July) in the Gallup Poll, the growth rate of real GDP in the second quarter of the election year, and whether the incumbent president’s party has held the White House for one term or more than one term.
The Time for Change forecasting model has correctly predicted the winner of the national popular vote in every presidential election since 1988.
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