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Tuesday, June 13, 2017

Initial job approvals... inconsequential

We’ve all seen the job approval polls and at first blush they appear like a catastrophe.  How did that happen, so quickly after President Trump was sworn in?  Recall though that these are the same pollsters/clowns who wrongly gave Hillary Clinton (on Election Eve) a ~90% chance of winning.  On the other hand, this site was among a rarest prominent voices to stick their reputation on the line to repeatedly forewarn that ALL the mainstream pollsters were wrong in what they claimed was a sure thing.  Of course they are still wrong here, in how they are deceiving the American (and global) public that the initial job approval ratings mean anything relevant.  Don’t fall for it, as you and Hillary Clinton fell for it last autumn.  Pollsters peddle appalling work, while pretending to be scientifically accurate. 

Independent voters haven’t suddenly -a day after the election- decided to disapprove of President Trump.  They are far more mature.  But we know exactly which political quadrant of the country is lashing out here.  And even if they weren’t, the polls right now simply provide no insight and contain an embarrassingly 2x or 3x as high actual margin of error than what they presume.  In our case the approval poll estimates should be biased significantly in favor of President Trump (closer to 50% actual job approval) solely based on the most unchanging current confidence interval. 

The other issue is that the main attention for these polls is how it might eventually map to one’s 2020 re-election odds.  Is President Trump a two-termer or not?  And here the initial job approvals (unless they sink well below 30%) have little to do with re-election probabilities!  Clearly the state of the economy in a couple years and the qualifications of whoever the emerging Democratic contender is, will jointly bear on the actual re-election probabilities.  But they will also cause Americans then to reassess President Trump’s job performance accordingly.

So the main variable that matters, in the context of this job approvals article, is what the job approvals value is in a couple years.  Don’t waste your time dreaming.  But know that Presidents who start with low job approvals, as we have here, will generally see the benefits on mean-reversion.  Surely there could be something appalling that President Trump does on his own to self-inflict a mortal wound in his own chances, but barring such ludicrousness, count him in as a strong contender for 2020.

It is imperative to this analysis to appreciate that continuously from President Roosevelt in the late-1930s, to the mid-1970s, presidents almost always become re-elected.  Didn’t matter much about their actual performance!  But progressively, since the 1970s, American voters have changed and are now much choosier.  Surely they expect results, but they also give presidents a fair chance.  Disregard the lunacy you might see at a weekend anti-Trump rally (or from Kathy Griffin), most Americans are giving the President a real chance and he will have some positive surprises as well (and some avoidable boo-boos).

But a probability model to predicting re-election based on the various information discussed so far, should incorporate both the job approval a couple years down the road (and not today’s in any way), as well as the recent several presidential relationships between these future job approvals and the re-election results. 

Thankfully there were some recent losses from incumbents (most recently President Bush in 1992) to gauge the model strength.  See the chart below for prediction of re-elections, using just the 3rd year job approvals for the past dozen applicable presidents, and stretching back nearly 80 years.  Note that for visual simplicity, data are randomly scattered above and below the blue-color model curve.

With President Trump ricocheting high 40s%, we might imply just greater than 50% or so chance of re-election (coincidentally again just better than the odds that established, gambling bookies have for him).  But such a model isn’t the best-fit anyway.  It has a R2 (the entropy, or the generalized calculations) of only in the 0.2s (on a fit scale of 0, to 1).

The strongest version is to incorporate the political changes across the decades, of what these job approvals might suggest.  There we get a much better fit (by a magnitude of 2), with a R2 that is now in the high 0.8s!  Additionally, the confusion matrix shown below provides an extraordinary degree of predictive accuracy (minimize all errors) with only one error in the past 12 elections!  That’s a much better record than Nate Silver and the other fellows, who typically have had terrible election forecasting results.
Predicted re-election win
Predicted re-election loss
Type-2 accuracy
Actual re-election win
9
0
100%
Actual re-election loss
1
2
67%
Signal accuracy
90%
100%
92%



July & October 2017 addendum:

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