In the unlikely event you haven’t heard, President Biden had a tough time at the first presidential debate on June 27. Is there a way to measure? how Having a rough time?
Type: Betting market on who will win the election. June 27 at 8:40 pm (shortly before the debate begins) A market aggregator gave Biden a 36 percent chance. By 11pm? down to 24 percent.
It’s pretty much the same reaction I encountered on social media (“Wow, Biden looks bad and can’t win”), but presented with the tenacity and addiction of the swaying New York Times. Election day needle. You can even see Biden’s numbers rebound – slightly – from about 10 percent to 13 percent during his 45-minute press conference yesterday evening. Markets were the vibe translated into concrete numbers.
But are the concrete numbers accurate? And is there a way to relate to them helpfully?
Markets are perhaps the best way to integrate new information and quickly arrive at new pictures of important questions. When a company releases a bad earnings report, for example, its stock price drops almost immediately, as experts adjust their bets from that earnings report on how much the stock will be worth in the future. Humans (and, increasingly, AI algorithm) Those who are good at their job earn money, and those who are bad at their job lose money. In this, the entire world benefits from fast, accurate pricing.
The dream of the election prediction market is that we can create something similar for political questions. Over the past two weeks, as electoral betting markets have swung wildly in response to every twist in the news surrounding Biden, the promise of that dream — and its acute current limitations — have been on full display.
Forecast market commitment
An open secret about all election models, From Nate Silver to that The New York Times, that they involve a thick sprinkling of expert judgment. Yes, they use polling a lot, but how to weight each vote, how much movement to build, and how to weigh the vote against economic fundamentals is all a judgment call. I do not agree with those who predict the election More art than scienceBut only because I think they make mistakes about how many judgment calls go into science.
Most of these selection models work by running countless computer simulations under various assumptions and publishing the results. A prediction market, In contrast, there is a much simpler setup.
You can buy “Biden,” which pays you $1 if Biden wins the election, or “Trump,” which pays you $1 if Trump wins the election, or any other name, which pays if that person wins the election. How much are people willing to pay for “Biden wins the election and you get $1”? This is how the market judges Biden’s chances of winning.
Right now, people are only willing to pay 12 cents for the right to collect $1 if Biden wins the election; If you think they’re underrating him, you can buy all these contracts from them and be very rich if Biden wins.
(In compliance with Vox’s ethics policy, I don’t bet money on the areas I cover, so I don’t participate in the election betting market. Still, I try to publicly register what I buy if I disagree with them; e.g. , here at the beginning of 2020, I said I thought there was a 60 percent chance that Biden would be the Democratic nominee when the forecast markets He had 33 percent.)
There are many reasons to believe that markets can be very good at predicting elections – in principle, at least. Published studies have found While prediction-market-like projects have worked in many contexts in the past, aggregators like SciCast and now Metaculus show a surprisingly good track record on policy questions.
And the track record of the betting market on election day morning very good: If the market says someone has a 20 percent chance of winning, they usually win about 20 percent of the time
Another argument is that markets are robust to these kinds of problems – where there are lots of smart people thinking about it and lots of available data, but lots of challenging judgment calls to integrate that information and act on it, and where we know there will eventually be a correct answer. .
People are better at predicting if they have to put some money in their mouth, and The wisdom of the crowd A real thing. So the market tends to lose money to those who are bad at prediction who are good at it.
But the simplest argument is that if Nate Silver consistently outperforms the market, people will trade on his predictions until the markets simply reflect what Nate Silver thinks. A high-volume, highly liquid market should at least not underperform any other source, since any underperformance is an opportunity to make money.
But while prediction markets can be a very effective and reliable way of predicting elections, they also have some serious flaws – flaws that have been amply demonstrated over the past two weeks.
What’s wrong with betting on elections?
This entire newsletter ignores a fairly important point: prediction markets for elections are not, strictly speaking, generally legal in the United States. predict There is an exemption due to Commodity Futures Trading Commission (CFTC) research Constantly threatening to shut down. The other major markets I mentioned throughout this piece, Betfair and Polymarket, generally do not allow Americans to participate. (Betfair makes exceptions for Americans in some states.)
There are two major downsides to this restriction. One is that the people who know most about the election – such as journalists or political activists – are usually restricted from betting on it, which means that markets are much less effective as gatherers of information. (A futures market for, say, soybeans will be much less accurate if companies that know the soybeans cannot participate.) Without intelligent individuals allowed to participate, the crowd is inherently less intelligent.
Perhaps more importantly, these restrictions mean that there is generally limited liquidity in the market. (Liquidity refers to how much money is changing hands in the market.) For big questions, like “Biden vs. Trump,” liquidity is just — Hundreds of millions of dollars exchanged hands.
But for smaller markets, it’s a huge problem. One revelation: The market has a persistent tendency to overrate long-shot candidates like Michelle Obama, and shortly after the debate, California Gov. Gavin Newsom emerged as a potential replacement for Biden opposite Vice President Kamala Harris. , which seems highly unlikely.
All these conditions mean that there is not enough trade to correct such errors. Low liquidity means that markets are relatively easy to manipulate, which has happened at least once
Ironically, the potential for election fraud is the main reason why the CFTC wants to ban prediction markets, which some elected officials have said. “A clear threat to our democracy,” But the fact that they are effectively banned makes them much easier to manipulate. Manipulating commodity prices would cost hundreds or thousands of times more than manipulating the odds of a selection bet, because trading commodities is legal.
These disadvantages make prediction markets a double-edged sword. On the one hand, they are powerful aggregators of public opinion, with a built-in accountability mechanism and a good track record for those questions where there is a lot of trading. On the other hand, they are very easy to manipulate, especially for small markets, managing unlikely candidates poorly. Don’t go beyond professional forecastersAnd as a result, can sometimes feel more like a distraction than a source of truth
Towards a better electoral market
Over the past two weeks I’ve been observing another dynamic, and while I’m not sure whether to call it an upside or a downside, it looks to me like a way that the prediction markets are falling short of their potential.
Markets were quick to say that Biden had a bad debate and odds were that Democrats would narrowly pick another nominee. On July 4, Biden’s chances of resigning peaked at 35 percent. But after Biden doubled down, markets again said he was likely to be the nominee — jumping to an 83 percent chance he would last until July. 9.
Then George Clooney and a select few Democrats criticized He, and the odds of staying in his office slide steadily again. And then, there was the Thursday evening press conference and Biden did well enough Bring back his odds.
Is it a reasonable response to new information? Is it a wild, vibes-driven pendulum? Are markets looking for truth or are they, as Andrew Gelman once said expressed concern, “Just some kind of noisy news collector”? As for the pressing question of whether there will be enough public pressure to oust Biden, is there an important difference between rational consolidation and a vibes-driven stampede?
Where it looks like prediction markets can be most valuable is in conditional markets: “If this person is the Democratic nominee, will they beat Trump?” After all, this is the question most Democrats care about most. This is not a market offer Biden should be replaced. But such markets are much smaller and much less liquid, and as a result, it’s not clear to me that they add much clarity to our public discourse.
I don’t think prediction markets are a bad thing if they are an expression of general sentiment about whether Biden will resign. But what I dream of is a world where markets reliably and accurately answer the question, “Which Democrat is most electable this November?” This could effectively guide the public conversation about Biden’s resignation. Better would be a world in which markets recognized Biden’s cognitive decline and related electoral weakness quickly, Instead of the exact same moment as everyone else.
Markets will be seen as a major force for policy decision-making. We are not there yet.
A version of this story originally appeared in the Future Perfect Newsletter. Register here!
