Alan Abramowitz’s Model Has Correctly Predicted Every Presidential Election Outcome Since 1992

The election model that’s most in vogue — that scored the highest when applied to presidential elections since World War II, correctly predicting every outcome since 1992 — is one created by Emory political scientist Alan Abramowitz called “Time for a Change.” Abramowitz argues that the fundamentals in a presidential election are bedevilingly simple: the incumbent president’s approval rating in late June or early July, the rate of real GDP growth in the second quarter, and how many terms the party has been in the White House.

In 2012, for instance, Obama’s relatively lopsided victory may have shocked Republicans on Election Night, but by Abramowitz’s reckoning it was practically preordained. Although second-quarter real GDP growth was a relatively unimpressive 1.5 percent and Obama’s approval rating was a good-but-not-great 46 percent that June, he was seeking reelection, and, according to Abramowitz, “first-term incumbents rarely lose.” In fact, he believes that being a first-term incumbent is worth 4 percentage points. There was nothing in the Abramowitz model that looked good for John McCain in 2008 (bad economy, bad approval ratings of a second-term president from McCain’s party). In 1988, by contrast, George H.W. Bush was also running to give his party a third term, but Q2 real GDP growth that year was a booming 5.24 percent and Ronald Reagan’s approval rating was above 50 percent.

Jason Zengerle writing for New York about how Hillary Clinton stacks up as a candidate, and whether or not being a “good candidate” actually means anything in terms of winning the presidency.

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