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Partisanship Trumps (Almost) All

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Ezra’s discussion of Bartels and Achen and how it applies to the 2016 is very useful:

I sat down with Bartels shortly after the 2016 election, and I had a dozen ideas for how his book helped explain the unusual results. But he wasn’t buying my premise. To him, the election looked pretty typical.

The Democratic candidate won 89 percent of Democratic voters, and the Republican candidate won 90 percent of Republican voters. The Democrat won minorities, women, and the young; the Republican won whites, men, and the old. The Democrat won a few percentage points more of the two-party vote than the Republican, just as had happened four years before, and four years before that. If you had known nothing about the candidates or conditions in the 2016 election but had been asked to predict the results, these might well have been the results you’d predicted. So what was there to explain?

Bartels doesn’t deny that there were interesting oddities to this election. The small but crucial number of Obama-to-Trump voters are worth studying, for instance. The interventions of Russia and then-FBI Director James Comey may well have delivered Republicans the presidency. And surely it’s meaningful that Hillary Clinton and Donald Trump were the least popular nominees in history.

But his point is that we’re so obsessed by what was different in 2016 that we’re missing the big story — how much stayed the same. For all the weirdness of the campaign, Trump and Clinton still got about 95 percent of the vote, and they did so by consolidating their own bases in ways that looked extremely similar to 2012. It’s easy to come up with counterfactuals where Clinton is in the White House today, or where Marco Rubio won the popular vote by 4 percentage points, but the basic similarity between Trump-Clinton and Obama-Romney deserves more attention than it’s gotten.

Given the unprecedented nature of Trump’s capture of the nomination, a lot of people who should know better (and I emphatically include myself here) assumed that the general rule that candidates and campaigns have only a very marginal effect might not apply. But the rule held. Assumptions that Trump was a bad candidate were, in themselves, correct with a major caveat. He underperformed by 3 or 4 points if (like me) you think she was a generic-minus candidate who ran a fairly good campaign, and by 5 or 6 if you think Clinton was a horrible candidate who ran a horrible campaign. Given the context of Comey and Wikileaks and the Gore II media coverage, that’s a really bad performance! Although of course Trump got some of that back because of he had a different regional appeal than a generic Republican — Trump would have been a terrible candidate if the president was selected democratically, but given the actual rules it’s a more complicated question.

But the key point here is that while candidates matter, they matter only very marginally. Given structural conditions that don’t strongly favor one party or another, it’s essentially impossible to for a major party to nominate a candidate who can’t win. And in 2020, Trump’s popularity and the condition of the economy will matter far more than the quality of the Democratic candidate or the choices made by the campaigns, even if the latter factors generate far more discussion.

And I’ve said this before, but Nate Silver still hasn’t gotten enough credit for not committing the gambler’s fallacy of overcompensating for getting the Republican primary wrong. (It’s worth noting here that while The Party Decides is a very good book its thesis was not nearly as robust as the science backing up polling is — Nobody Knows Anything was not the right lesson to draw from Trump getting the Republican nomination.) Don’t focus on the probability percentages — we can never know whether Trump had a 30% chance or a 10% chance of winning. Focus on Silver’s analysis. He stuck by what the data was telling him — Clinton would probably win, but Trump’s voters were more efficiently distributed, so Clinton was vulnerable to a larger-than-usual polling error or a black swan event. The polling actually held up fairly well, but the black swan event happened, so here we are.

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