nate silver wrote:In 16 years of running election forecasts, I’ve never seen such a close election.

Our polling averages in seven swing states — in alphabetical order: Arizona, Georgia, Michigan, Nevada, North Carolina, Pennsylvania and Wisconsin — are within 2 percentage points. A systematic polling error, or a shift in the race in the final six weeks of the campaign, could result in one candidate sweeping all of these states. In our simulations this morning, Kamala Harris swept all seven of these battlegrounds 20 percent of the time, and Donald Trump did in 23 percent of the time.

But that leaves a majority of cases where the election will probably be close, and it’s worth sorting through the electoral math in case it is. So that’s what today’s newsletter is about. It’s going to be rather prosaic. I’ll go through the most important states in descending likelihood of Kamala Harris winning them — starting with my home state, Michigan.

Michigan: Harris win probability 63%. Tipping-point probability 14%.

Who’s ahead in the Michigan polls?

Michigan has been somewhat to the left of the other Blue Wall states in recent elections. Since 2000, it’s voted Democratic by an average of 6.2 percentage points, versus 3.8 points for Pennsylvania and 3.5 points for Wisconsin.

One potential concern for Harris in the state is Michigan’s substantial Arab American population in the event that some voters shift their votes because of Gaza. But Harris seems to have somewhat defused the issue relative to Joe Biden, and it’s only about 2 percent of the electorate — and the war isn’t necessarily a voting issue for rank-and-file swing voters. The polling in Michigan has been a bit odd — with some Harris +7s and Harris +5s, along with other polls showing the race as a tie. But if you average the numbers out, it’s the one swing state you could probably say is leaning Harris rather than a pure toss-up....

People treat probabilistic predictions as deterministic ones, e.g. if Trump goes from a 48 percent chance of winning Wisconsin to a 52 percent chance, you’ll get a lot of Nate Silver is calling Wisconsin for Trump!!! even though the forecast expresses a high degree of uncertainty and nothing in the model has really changed. And that’s on a good day. There are a lot of partisans — some acting in good faith and some not — who can become literally conspiratorial about the model.

Look, the election is probably going to be close. The Biden-Trump election might not have been close, but Democrats were smart enough to replace their candidate, and the Harris-Trump election probably will be close.

... But these polls aren’t telling us anything we didn’t know. On November 5th, we’ll all wake up with a lot of uncertainty about who will win. And we might go to bed with a lot of uncertainty, too: if recent American elections are any guide, the outcome could take several days to resolve. (There’s even almost a 10 percent chance of a 2000-style recount in a decisive state, the model figures.)

Anything I say about the election, or anything any poll says, isn’t going to change that. If you care about the outcome, then vote, donate, volunteer, or try to persuade your friends. But don’t be an asshole on social media because it isn’t going to help.

And keep in mind that polls come with a margin of error. Let’s say that if we had Nostradamus-like abilities, we knew that the true state of the race is that Kamala Harris would win Wisconsin by 1 percentage point in an election held today. A typical poll has about 800 respondents. Well, the margin of error in an 800-person poll is plus or minus 3.5 points. Except, that substantially understates the case because the margin of error pertains only to one candidate’s vote share. In an election like this one where third-party candidates play little role, basically every vote that isn’t a Harris vote is a Trump vote and vice versa. So the margin of error on the difference separating the candidates is roughly twice that: about 7 points.

That means if the true state of the race is Harris +1, you’ll get some Trump +5s and Harris +7s just from sampling error alone (from surveying a random sample of the population rather than every voter). And that’s before getting into all the other ways that polls can go wrong. Or the fact that the margin of error is only supposed to cover 95 percent of the cases: about 1 time in 20, you’ll get a true outlier — a Harris +10 or a Trump +8 — provided that pollsters are being honest, which they probably aren’t. (In practice, pollsters tend to herd toward the consensus and suppress outlier results.)

Averaging different polls together helps, but only so much. Let’s say you have four recent polls of Wisconsin, for instance: this is equivalent to having a sample size of 3200 voters. The margin of error on the difference separating the candidates is still 3 or 4 points, so even if the true state of the race is Harris +1, the average might come out with a Trump +2 or a Harris +4.

Models like the Silver Bulletin model take some further steps, like by making inferences about what the polls in one state say based on polls of other states. That’s some of their value. But their more important function is by accounting for another possibility: the chance of a systematic polling error — of the sort that, for instance, led polls to substantially underestimate Trump in both 2016 and 2020. That’s where the probabilities in the forecast come from: they’re derived from how accurate the polls really have been, in practice — and in practice, the margins of error are considerably wider than they are in theory.

If one candidate has a big lead, there’s a bit less mental strain from all of this. Harris +8 doesn’t feel that different from Harris +4, and an 85 percent probability of her winning doesn’t feel that different than 75 percent. But when the probabilities are in the vicinity of even, it can seem like you’re ping-ponging between radically different universes. A forecast showing Harris as a 55/45 favorite will be interpreted much differently from one showing Trump as a 55/45 favorite instead, even though they’re basically saying the same thing: the election is more or less a coin flip.

If you enjoy what gamblers call the sweat, navigating the vicissitudes of these slightly changing probabilities, I get it, and the model is here for you. But if you don’t, there’s another option beyond voting, donating and volunteering: chilling the eff out. The dunk you make on Twitter isn’t going to make Trump lose. The nasty comment you leave isn’t going to make Trump win. You can unskew the polls, but usually, you’re only fooling yourself. So lead your best life, and have the serenity to accept the things you cannot change.

GuyLaCroix wrote: Mon Sep 23, 2024 11:18 pm I wouldn't trust Nate Silver to accurately guess this, he didn't the last couple times. One was completely off (16) and the other was a wildly closer decision than his projections.

The conservatives that matter, the ones who don't go in for the buffoon showmanship but rather show up and vote, they are not participating in polling like this. That's part of the Liberal Media.

Nixon looks up from Hell and smiles as the Silent Majority goes about their business.

hbiden@onlyfans.com wrote: Tue Sep 24, 2024 2:35 am

GuyLaCroix wrote: Mon Sep 23, 2024 11:18 pm I wouldn't trust Nate Silver to accurately guess this, he didn't the last couple times. One was completely off (16) and the other was a wildly closer decision than his projections.

The conservatives that matter, the ones who don't go in for the buffoon showmanship but rather show up and vote, they are not participating in polling like this. That's part of the Liberal Media.

Nixon looks up from Hell and smiles as the Silent Majority goes about their business.

nate is not a pollster. his model takes into account the margins of error that you mention. i trust him when he says it's close but you are probably right that trump is ahead.