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For those watching the Presidential election, things have been looking very bad for Kamala lately, with national polls tightening, and Trump ahead in several key states. Although it remains too close to call, Trump's odds have shot up to 57% according to Polymarket.
Harris's 1.4% lead in national polls is cold comfort given that, at a similar point in the election, Biden was up by 9.4% and Clinton was up by 6.7%.
Democratics are panicking about Trump's support in the black community, which has traditionally voted 90/10 in favor of Democrats. While Trump will still lose the black vote by large margins, his style is more appealing to black voters (especially men) then previous Republican candidates like Mitt Romney. Democrats have responded by trying to shame black voters. Recently, Barack Obama was even unearthed to chastise black men for not wanting to vote for Harris.
Enter the latest vote-buying scheme, which I think is the most naked attempt to buy votes I've ever seen in recent US politics, even more than college debt forgiveness.
https://x.com/KamalaHarris/status/1845993766441644386
Harris-Walz have proposed a 20k forgiveable loan for up to 1 million Black (capital B) entrepreneurs to start a business. The fact that the loan is forgiveable means that this is essentially a gift to any grifter who wants to take advantage. But most importantly, it's explicit racial discrimination against the 86% of the country who isn't black.
Personally, I think this appeal is likely to backfire as most swing voters are sick of handouts to people who aren't them.
Will Trump counter with some asinine scheme of his own? Probably.
I know very little about prediction markets, so can someone explain to me how likely it is that Trump's surge on for example Polymarket is the result more of speculative behavior than of people rationally trying to predict the winner of the election? I don't really see any reason to currently view the race as being anything other than pretty close to 50-50. People might say well, if I believe that then why not try to make some money on it? And maybe that's fair. But that does not necessarily mean that the betting odds on Polymarket are actually an accurate guide to the likely election outcome.
Other countries have let people bet on politics for a long time and no, they’re far from always accurate. Right before Brexit, the betting market hugely favored remaining in the EU for example.
Prediction markets are well-calibrated when there is sufficient liquidity.
A 20% chance is not a 0% chance. It will happen 1 in 5 times. When it does happen, the prediction market is not "wrong".
This is what Nate Silver had to say over and over again in the wake of 2016 when he made a "wrong" prediction by giving Trump only a 30% of winning. Most people simply fail to understand how prediction works.
Yes, but for a non-repeatable event it’s also very easy for a pollster to say they were right. After all, even someone who predicts a 95% likelihood of A winning can say “well, the 5% likelihood of B winning happened to be the outcome in this scenario, my forecast was in fact entirely correct” and this is completely unfalsifiable.
Is probability even well-defined for a one-off event? It's not like we can random sample the multiverse on how the election actually went. At the same time, nothing is absolutely certain (supervolcano as October surprise!).
Maybe it makes sense from a Bayesian perspective: given the current knowledge of the system state (polls, voter registrations, demographics, maybe even volcanology reports) we can estimate the probability of a specific outcome. But a frequentist view seems nonsensical, even if a lot of predictions seem to present themselves that way.
I completely agree, the frequentist view is nonsensical. This is why forecasters need to be nailed down to a specific outcome (or ‘I don’t know / it’s too close to call’ but this has to be acknowledged as opting-out).
That's my main problem with Nate Silver's modelling.
There should be large error bars around the prediction that slowly close in as the predicted event approaches.
It shouldn't be "X% Trump, Y% Kamala," it should be "X% Trump, Y% Kamala, Z% irreducible uncertainty."
The logic is "if the election were held today then here's the probability." But... the elections won't be held today. That's the whole point of the prediction for a future event, and I think it behooves them to acknowledge that uncertainty is inherent to the modelling process.
If they'd included that back when it was Trump vs. Biden, the conserved probability would have accounted for Biden suddenly dropping out and wouldn't have broken the model instantly. Also helps reflect the chance that one of the candidates dies... which also almost happened.
And if Nate trusts his model, there's a ton of money to be made in the prediction markets.
What would this irreducible uncertainty mean for an event with a binary outcome? I think Silver already accounts for increasing uncertainty as he propagates his current prediction into the future (what he calls forecast vs. nowcast).
Error bars would make sense around the expected vote percentage. Of course the probability distribution over vote percentages becomes broader as you look into the future, and perhaps he does show that to paying customers. But in the end you still have to integrate over that when the layman asks for the probabilities of who wins the election. And that still amounts to two numbers that sum to 100%.
Evaluating a predictor's performance seems straightforward to me via the usual log-likelihood score. Record the final outcome and take the log of the predictor's probability for that outcome. That score can then be summed over multiple different elections, if you like. (Not sure though if I'd call that scoring rule particularly frequentist.)
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There's not a ton of money to be made if you believe the odds are 50/50. Prediction markets give Trump 60/40 odds, while Nate's model gives 50/50 odds. If your bankroll is $1M, then it's only rational to bet 167k, for an expected value of 40k. Not nothing, but not a ton of money either.
That also ignores other costs, like counterparty risk. Nate also has to deal with reputational risk: people might value his published models less if they thought he was making bets on markets that were influenced by his models. Since that's his main source of actual income, a bet would be substantially negative EV for him.
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