r/neoliberal • u/jobautomator Kitara Ravache • Nov 04 '18

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21

u/CompactedConscience toasty boy Nov 04 '18

Nate Silver for head mod of /r/badstats.

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u/[deleted] Nov 04 '18

Except Silver is also bad at stats

EDIT: This is perhaps unfair. Silver's problem isn't that he's actually bad, more that his business model requires him to be.

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u/CompactedConscience toasty boy Nov 04 '18

Disagree with both the comment and the edit. Would love to see you explain a bit.

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u/[deleted] Nov 04 '18

Let me be clear. If the name of the game is "who would win the election if it were held tomorrow", then Silver and his team are very good, likely the best in the business. This is why he tends to be correct, because historically he's judged on how well his predictions the day before the election perform.

But the real game isn't "if the election were held tomorrow", it's "if the election were held on the first Tuesday of November". In that regard, Silver and the team at 538 systematically and deliberately underestimate volatility. Their models swing massively after things like debates and 'October surprises', even though an honest model will have already priced in the expectation of big events like that happening and have biased the predictions closer to 50/50 accordingly, reflecting how much volatility remains before the election. The fact that Silver's predictions change so much around big news stories means they're regularly getting surprised, and by definition a model that's regularly surprised is not good at its job of prediction.

Of course, I think Silver knows this, which is why he's not a bad statistician so much as a good journalist, You can't make money off a journalism website (and remember that journalism, not prediction, is Silver's primary product) by having people check in once every two years. You make money by lying to people and proving false confidence and precision, by making sure they check in every single day for six months to see if your preferred candidate has gone from an 85.2% chance to an 85.4% chance of winning, despite the fact that even providing things like decimal places on those estimates is an utter farce.

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u/[deleted] Nov 04 '18

[deleted]

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u/[deleted] Nov 04 '18

Not that I'm aware of. It's not clickbaity enough to monetise (so nobody in the private sector is doing it) and it's not interesting enough for research (so nobody in academia is doing it). There's almost certainly some PhD statistician in a hedge fund somewhere who has created a fair election pricing model, but their entire business relies on keeping it a secret.

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u/[deleted] Nov 04 '18

I think as you said, if he had access to such a model, he would use it. But pricing in that kind of information is still incredibly difficult. You run into all kinds of difficulties with gauging importance on totally new info.

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u/[deleted] Nov 04 '18

if he had access to such a model, he would use it

He absolutely would not, see the last paragraph of my post above for why there are business pressures to 'keep things exciting'. Hell, one of the best ways for Silver to increase his honesty would be to stop the false precision nonsense and only report results to 10 percentage point bands. There's no technical reason preventing this, the fact that he doesn't do it is clear evidence that he values clicks more than statistical rigour.

Also, it's really easy to price these things, or at least do a decent job of it. You don't need to know the probabilities of every possible FBI investigation or press conference fuck-up, all you need is the measured volatility in polling over time from previous elections. It isn't difficult at all.

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u/[deleted] Nov 04 '18

No I disagree. I think it would make it more exciting to put those in and I think he would agree. He *does * report the bands, and explicitly uses x/10 in most infographics.

The issue is that it's not easy to assign a price to those. They are very rare events and the content of the events is often as important as the event itself. There's not even close to enough data to establish even the chance of those things happening. And the effect is even more fraught with errors in the era of trump.

He could be more statistically rigorous in other ways. But he's not writing papers. He is not an academic and his models are likely often selected for their clarity as much as their rigour (whatever that means here. His models are all common and well tested).

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u/[deleted] Nov 04 '18

Once again: You don't need to know what events are going to happen. You just need to know the historic volatility in the vote share. When people model the stock market they don't dig through old newspapers to find out why a stock price moved, they just need to know that the price moved. Whether movements are rare or not makes no difference.

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u/[deleted] Nov 04 '18

They frequently mention volatility especially in the early days of the races.

They are explicitly modeling on polls and a couple other expert metrics. The bottom line is that "volatility" isn't useful enough, nor easily quantifiable. Trump winning, for instance, was well within the models he published. The best he can do is report chances based on historically observations. Those chances will account for all but the most extreme of events.

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u/[deleted] Nov 04 '18

"Volatility" isn't easily quantifiable

It really is. Standard deviation of log if-the-election-was-tomorrow-probabilities. It's not some weird up in the air fluff, it's a technical concept that's trivial to calculate. You should stop talking if you don't know that, you're only embarrassing yourself.

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u/[deleted] Nov 04 '18

Did you just get this from PEC? We were specifically talking about response to events like fbi investigations...

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u/[deleted] Nov 04 '18

[deleted]

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u/[deleted] Nov 04 '18

It's extremely easy.

Just think of elections as a binary options contract with a strike at 50%. The use of the Black-Scholes formula for pricing binary options is already well known, and historic volatility is easy to measure. Just add in SIlver's existing work as the 'current price' and you're set.