See, this is why the "fundamentals" are kind of overrated. It's not at all obvious that they would have favored Bush in 1988 or Clinton in 1992 **unless you know the outcomes in advance**. https://twitter.com/gelliottmorris/status/1296975170830315521

1988? Bush going for a 3rd straight term for Republicans amid an average economy. VERY similar to 2000 and 2016, which were photo finishes. (Incumbent party lost the Electoral College but won the popular vote). No particular reason to expect a Bush landslide.

1992? The economy went into recession in 1990. But it ended by March 1991, and the economy was recovering, though slowly (especially in data published at the time vs. later revised). Bush was coming off the extremely popular Gulf War. Not at all obvious why he collapsed so badly.

Of course, rather than accepting some intrinsic degree of ambiguity and uncertainty, you can test out 300 different model specifications on a sample size of n=10 and find something that "fits" the data. And even manage to convince yourself that you've found a persuasive "story".

But these "fundamentals" models have been terrible when used to actually predict elections when they didn't know the results in advance. Rather than using them, you literally would have been better off just guessing the election would be 50:50. https://fivethirtyeight.com/features/models-based-on-fundamentals-have-failed-at-predicting-presidential-elections/