What do these models say? One of the more popular forecasting models is Alan Abramowitz’s “time for change” version. It has two variants. The first, which we might call “Time for Change Classic,” looks at net presidential approval, GDP growth in the second quarter, and how many terms the party in control has held the White House. The second, which we’ll call “New Time for Change,” adds a polarization variable.
So what does the classic version tell us? Let’s first use CBO’s estimate of 4 percent growth. This is probably on the high side (CBO has been forecasting a surge in GDP just around the corner for five years now) so we’ll asterisk it as a high-end probability. President Obama’s job approval rating is -10.8 percent today. If we plug these two variables into Time for Change Classic, it suggests that Republicans should be favored to win by about three points: 51.7 percent to 48.3 percent.
But, you say, with 4 percent growth, Obama is unlikely to remain at -10.8 percent approval. Fair enough. But even if we move him up to a net-neutral job approval, the models forecast a narrow Democratic loss, 50.5 percent to 49.5 percent. Obama would have to reach a net job approval of +6 before the model would forecast the Democrat to win (narrowly). Obama has accomplished this four times in his six years in office: During his two post-election “honeymoons,” after the shooting of Gabby Giffords, and after killing Osama bin Laden. If he ties his post-2009 best of +12 percent net approval, the model would favor the Democrat by a point.
But what if the Fed forecast of 2.6-to-3 percent growth is more accurate? At 2.8 percent growth and using Obama’s current job approval, the model forecasts a Democratic loss of 4.6 points; at neutrality it forecasts a Democratic loss of 2.4 points, and even improving to a +12 percent net approval rating would suggest a very narrow Democratic win (.198 points, to be exact)
