WSJ’s survey of economists reports that inflation expectations for 2025 were around 2% before the election, but are closer to 3% now. Their economists expect GDP growth slowing to 2%, unemployment ticking up slightly but staying in the low 4% range, with no recession. The basic message that 2025 will be a typical year for the US macroeconomy, but with inflation being slightly elevated, perhaps due to tariffs.
Kalshi has a lot of good markets up that give more detailed predictions for 2025:
For those who hope for DOGE to eliminate trillions in waste, or those who fear brutal austerity, the message from markets is that the huge deficits will continue, with the federal debt likely climbing to over $38 trillion by the end of the year. This is one reason markets see a 40% chance that the US credit rating gets downgraded this year.
While the US has only a 22% chance of a recession, China is currently at 48%, Britain at 80%, and Germany at 91%. The Fed probably cuts rates twice to around 4.0%.
Will wage growth keep pace with inflation? It’s a tossup. Corporate tax cuts are also a tossup. The top individual rate probably won’t fall below it’s current 37%.
If you want to make your own predictions for the year, but don’t want to risk money betting on Kalshi, there are several forecasting contests open that offer prizes with no risk:
ACX Forecasting Contest: $10,000 prize pool, 36 questions, must submit predictions by Jan 31st
Bridgewater Forecasting Contest: $25,000 prize pool, half of prizes are reserved for undergraduates. Register now to make predictions between Feb 3rd and March 31st. Doing well could get you a job interview at Bridgewater.
Last week I laid out my own expectations for what economic policy would look like in a Trump or Harris presidency. Now after yesterday’s market reaction, we can infer what market participants as a whole expect by roughly doubling the size of yesterday’s market moves. Prediction markets had a 50-60% change of Trump winning as of Tuesday morning’s market close, which moved to a 99+% chance by Wednesday morning. Look at how other markets moved over the same time, multiply it by 2-2.5x, and you get the expected effect of a Trump presidency relative to a Harris presidency. So what do we see?
Stocks Up Overall: S&P 500 up 2%, Dow up 3%, Russell 2000 (small caps) up 6%. My guess this is mostly about avoiding tax increases- the odds that most of the Tax Cuts and Jobs Act gets renewed when it expires in 2025 just went way up. Lower corporate taxes boost corporate earnings directly, while lower taxes on households mean that they have more money to spend on their stocks and their products. Lower regulation and looser antitrust rules are also likely to boost corporate earnings.
Bond Prices Down (Yields Up): 10yr Treasury yields rose from 4.29% to 4.4%. This is the flip side of the tax cuts- they need to be paid for, and markets expect they will be paid for through deficits rather than cutting spending. The government will issue more bonds to borrow the money, lowering the value of existing bonds.
Dollar Up: The US dollar is up 2% against a basket of foreign currencies. I think this is mostly about the expected tariffs. People like the sound of the phrase “strong dollar” but it isn’t necessarily a good thing; it makes it cheaper to vacation abroad, but makes it harder to export, even before we consider potential retaliatory tariffs.
Crypto Way Up: Bitcoin went up 7% overnight, Ethereum is now 15% up since Tuesday. Crypto exchange Coinbase was up 31%. Markets anticipate friendlier regulation of crypto, along with a potential ‘strategic Bitcoin reserve’.
Single Stock Moves: Private prison stocks are up 30%+. Tesla is up 15%, mostly due to Elon Musk’s ties to Trump, but also due to tariffs. Foreign car companies were way down on the expectation of tariffs- Mercedes-Benz down 8%, BMW down 10%, Honda down 8%.
Sector Moves: Steel stocks are up on the expectation of tariffs, while solar stocks (which can’t catch a break, doing poorly under Biden despite big subsidies and big revenue increases) were down 12% in the expectation of falling subsidies. Bank stocks did especially well, with one bank ETF up 12%. This gives us one hint on what to me is now the biggest question about the second Trump administration- who will staff it? I could see Trump appointing free-market types, or wall-streeters in the mold of Steve Mnuchin, or dirigiste nationalist conservatives in the JD Vance / Heritage Foundation mold, or an eclectic mix of political backers like Elon Musk and RFK Jr, or a combination of all of the above. The fact that bank stocks are way up tells me that markets expect the free-marketers and/or the Wall-Street types to mostly win out.
Just Ask Prediction Markets: If you want to know what markets expect from a Presidency, you can do what I just did, look at moves the big traditional markets like stocks and bonds and try to guess what is driving them. But increasingly you can skip this step and just ask prediction markets directly- the same markets that just had a very goodelection night. Kalshi now has markets on both who Trump will nominate to cabinet posts, as well as the fate of specific policies like ‘no tax on tips‘
I doubt anyone has been waiting for my take on the Trump and Harris economic plans to decide their vote. More than that, it is entirely reasonable to vote based on things other than their economic plans entirely- like foreign policy, character, or preservingdemocracy. But either Trump or Harris will soon be President, and thinking through their economic plans can help us understand how the next 4 years are likely to go.
The bad news is that both campaigns keep proposing terrible ideas. The good news is that, thanks to our system of checks and balances, most of them are unlikely to become policy. The other good news is that our economy can handle a bit of bad policy- as Adam Smith said, there’s a lot of ruin in a nation. After all, the last Trump admin and the Biden-Harris admin did all sorts of bad economic policies, but overall economic performance in both administrations was pretty good; to the extent it wasn’t (bad unemployment at the end of the Trump admin, bad inflation at the beginning of Biden-Harris), Covid was the main culprit.
Note that this post will just be my quick reactions; the Penn Wharton Budget Model has done a more in-depth analysis. They find that Harris’ plan is bad:
We estimate that the Harris Campaign tax and spending proposals would increase primary deficits by $1.2 trillion over the next 10 years on a conventional basis and by $2.0 trillion on a dynamic basis that includes a reduction in economic activity. Lower and middle-income households generally benefit from increased transfers and credits on a conventional basis, while higher-income households are worse off.
We estimate that the Trump Campaign tax and spending proposals would increase primary deficits by $5.8 trillion over the next 10 years on a conventional basis and by $4.1 trillion on a dynamic basis that includes economic feedback effects. Households across all income groups benefit on a conventional basis.
We are already running way too big a deficit; candidates should be competing to shrink it, not make it worse. This isn’t just me being a free-market economist; Keynes himself would be saying to run a surplus in good economic times so that you have room to run a deficit in the next recession.
Now for my lightning round of quick reactions:
No tax on tips: both campaigns are now proposing this; it is a silly idea, there is no reason to treat tips differently from other income. The good news is that this almost certainly won’t make it through Congress.
Taxes: Trump’s Tax Cuts and Jobs Act of 2017 is set to expire in 2025. He says he wants to renew it and add more tax cuts, though he will need a friendly Congress to do so. Harris wants to let most of it expire, but renew and expand the Child Tax Credit while raising taxes on the wealthy and corporations. There’s a good chance we end up with divided government, in which case probably only the most popular parts of TCJA (increased standard deduction and child tax credit) get renewed and no big new changes happen.
Price controls: both campaigns, especially Harris‘, have talked about fighting ‘price gouging’, leading economists to worry about the price controls (any intro micro class explains why these are a bad idea). My guess is that no real bill gets passed, President Harris gets the FTC to make a show of going after grocery stores but nothing major changes.
Tariffs: Harris would probably leave them where they are; Trump is promising to raise them 10-20% across the board and 60% on China. This would lead to higher prices for US consumers and invite retaliation from abroad; we saw the same things when Trump raised tarriffs in his first term, but he is promising bigger increases now. This is worrisome because the President has a lot of power to change tariffs unilaterally; it would take a bill getting through Congress to stop this, and I don’t see that happening.
Regulation / One in two out: The total amount of Federal regulation stayed fairly flat during the Trump administration thanks to his one in two out rule, while regulation increased during the Biden-Harris administration. I expect that a second Trump admin would behave like the first here, while a Harris admin would continue the Biden-Harris trend.
Antitrust: FTC and DOJ have been aggressive during the Biden-Harris administration, blocking reasonable mergers and losing a lot in court. But Trump’s VP candidate JD Vance thinks FTC Chair Lina Khan is “doing a pretty good job”, so we could see this poor policy continue either way. More generally, voters should consider what a Vance presidency would look like, because making him Vice President makes it much more likely (Trump is 78 and people keep trying to shoot him; plus VPs get elected President at high rates).
Immigration: Immigration rates have been high under the Biden-Harris admin, while Trump’s top two planks in his platform are “seal the border” and “carry out the largest deportation operation in American history”. Economically, this would lead to a reduction in both supply and demand in many sectors, with the relative balance (so whether prices go up or down) depending on the sector. The exclusion of Mexican farmworkers in the 1960’s led to a huge increase in mechanization, to the point that domestic farmworkers saw no increase in their wages; presumably this also limited the potential harm to the food supply.
Crypto: The Biden admin has been fairly negative on crypto; both Harris and Trump are making pro-crypto statements in their campaigns, particularly Trump.
Marijuana: The Biden admin is in the process of rescheduling marijuana to no longer be in the most restricted category of drugs. I think Trump would probably see the process through, while Harris definitely would.
Elon Musk / Civil Service: Elon Musk has thrown his support hard behind Trump, spending lots of money, tweeting continuously, and attending rallies. It’s hard to know how much of this is genuine support for a range of Trump’s policies, how much is to get the Federal government to stop suing his companies so much, and how much is to get himself a direct role in government. In any case, it is a safe bet that more Federal civil servants get fired in a Trump admin than in a Harris admin. What’s much harder to say is how many get fired, and what proportion of firings come from a genuine attempt to improve efficiency vs a purge of those Trump sees as disloyal. Personally I think government could stand to treat its employees a bit more like the private sector, making it easier to fire people for genuine poor performance (not political views), but also allowing for more flexibility on improved pay, benefits, and the ability to focus on achieving goals more than following the way things have always been done. But I doubt that’s on the table either way.
CFTC/ Prediction Markets: The Biden CFTC has tried to crack down on prediction markets, though they have mostly failed in the courts, and the growth of Kalshi and Polymarket mean that prediction markets are now bigger than ever. Most of the anti-prediction-market decisions have been 3-2 votes of the democrats vs the republicans, so a new republican appointee could lock in the legal gains prediction markets have made, though this is far from guaranteed (not all Rs support this).
Final Thoughts: So much of how things turn out will depend not just on who wins the Presidency, but on whether their party wins full control of Congress. Because the Democrats have a lot more Senate seats up for grabs this year, Harris is much more likely to be part of a divided government (especially once you consider the Supreme Court).
Because of this, and because of the ability of the President to raise tariffs unilaterally, I see Trump as the bigger risk when it comes to economic prosperity, as well as non-economic issues. Harris with a Republican Senate is the best chance of maintaining something like the status quo, whereas a Trump victory is likely to see bigger changes, many of them bad.
That said, predicting the future is hard, and this applies doubly to Presidential terms. I’m struck by how often in my lifetime the most important decisions a President had to make had nothing to do with what the campaign was fought over. Who knew in 1988 that the President’s biggest task would be managing the breakup of the Soviet Union? In 2000, that it would be responding to 9/11? Bush specifically tried to distinguish himself from Gore as being the candidate more against “nation-building”, then went on to try just that in Afghanistan and Iraq. In 2004, who knew that the biggest issue of the term would be not Social Security or foreign policy, but a domestic financial crisis and recession? In 2016, who knew that they were voting on the President that would respond to the Covid pandemic? In 2020, who knew that they were voting on who would respond to Russia’s invasion of Ukraine?
The most important issue for the next President could easily be how they address China or AI, because those are clearly huge deals. I won’t vote based on this, because I don’t know who has the better plan for them, because I have no idea what a good plan looks like. Or the most important issue could be something that comes completely out of left field, like Covid did. Not even the very wise can see all ends.
What I do know is that, while much of the Libertarian Party has recently gone from its usual “goofy-crazy” to “mean-crazy“, Chase Oliver is so far the only candidate pandering to me personally. But it’s not too late for other politicians at all levels to try the same.
See you all again next Thursday, by which time the election will, I hope, be over.
Kalshi just announced that they will begin paying interest on money that customers keep with them, including money bet on prediction market contracts (though attentive readers here knew was in the works). I think this is a big deal.
First, and most obviously, it makes prediction markets better for bettors. This was previously a big drawback:
The big problem with prediction markets as investments is that they are zero sum (or negative sum once fees are factored in). You can’t make money except by taking it from the person on the other side of the bet. This is different from stocks and bonds, where you can win just by buying and holding a diversified portfolio. Buy a bunch of random stocks, and on average you will earn about 7% per year. Buy into a bunch of random prediction markets, and on average you will earn 0% at best (less if there are fees or slippage).
This big problem just went away, at least for election markets (soon to be all markets) on Kalshi. But the biggest benefit could be how this improves the accuracy of certain markets. Before this, there was little incentive to improve accuracy in very long-run markets. Suppose you knew for sure that the market share of electric vehicles in 2030 would over 20%. It still wouldn’t make sense to bet in this market on that exact question. Each 89 cents you bet on “above 20%” turns into 1 dollar in 2030; but each 89 cents invested in 5-year US bonds (currently paying 4%) would turn into more than $1.08 by 2030, so betting on this market (especially if you bid up the odds to the 99-100% we are assuming is accurate) makes no financial sense. And that’s in the case where we assume you know the outcome for sure; throwing in real-world uncertainty, you would have to think a long-run market like this is extremely mis-priced before it made sense to bet.
But now if you can get the same 4% interest by making the bet, plus the chance to win the bet, contributing your knowledge by betting in this market suddenly makes sense.
This matters not just for long-run markets like the EV example. I think we’ll also see improved accuracy in long-shot odds on medium-run markets. I’ve often noticed early on in election markets, candidates with zero chance (like RFK Jr or Hillary Clinton in 2024) can be bid up to 4 or 5 cents because betting against them will at best pay 4-5% over a year, and you could make a similar payoff more safely with bonds or a high-yield savings account. Page and Clemen documented this bias more formally in a 2012 Economic Journal paper:
We show that the time dimension can play an important role in the calibration of the market price. When traders who have time discounting preferences receive no interest on the funds committed to a prediction-market contract, a cost is induced, with the result that traders with beliefs near the market price abstain from participation in the market. This abstention is more pronounced for the favourite because the higher price of a favourite contract requires a larger money commitment from the trader and hence a larger cost due to the trader’s preference for the present. Under general conditions on the distribution of beliefs on the market, this produces a bias of the price towards 50%, similar to the so-called favourite/longshot bias.
We confirm this prediction using a data set of actual prediction markets prices from 1,787 market representing a total of more than 500,000 transactions.
Hopefully the introduction of interest will correct this, other markets like PredictIt and Polymarket will feel competitive pressure to follow suit, and we’ll all have more accurate forecasts to consult.
The Fed has now almost landed the plane, bringing us down from 9% inflation during the Covid era to something approaching their 2% target today. But it is not yet clear how hard the landing will be. Back in March I thought recurrent inflation was still the big risk; now I see the risk of inflation and recession as balanced. This is because inflation risks are slightly down, while recession risk is up.
Inflation remains somewhat above target: over the last year it was 3.3% using CPI, 2.7% by PCE, and 2.8% by core PCE. It is predicted to stay slightly above target: Kalshi estimates CPI will finish the year up 2.9%; the TIPS spread implies 2.2% average inflation over the next 5 years; the Fed’s own projections say that PCE will finish the year up 2.6%, not falling to 2.0% until 2026. The labels on Kalshi imply that markets are starting to think the Fed’s real target isn’t 2.0%, but instead 2.0-2.9%:
The Fed’s own projections suggest this to be the somewhat the case- they plan to start cutting over a year before they expect inflation to hit 2.0%, though they still expect a long run rate of 2.0%. In short, I think there is a strong “risk” that inflation stays a bit elevated the next year or two, but the risk that it goes back over 4% is low and falling. M2 is basically flat over the last year, though still above the pre-Covid trend. PPI is also flat. The further we get from the big price hikes of ’21-’22 with no more signs of acceleration, the better.
But I would no longer say the labor market is “quite tight”. Payrolls remain strong but unemployment is up to 4.0%. This is still low in absolute terms, but it’s the highest since January 2022, and the increase is close to triggering the Sahm rule (which would predict a recession). Prime-age EPOP remains strong though. The yield curve remains inverted, which is supposed to predict recessions, but it has been inverted for so long now without one that the rule may no longer hold.
Looking through this data I think the Fed is close to on target, though if I had to pick I’d say the bigger risk is still that things are too hot/inflationary given the state of fiscal policy. But things are getting close enough to balanced that it will be easy for anyone to find data to argue for the side that they prefer based on their temperament or politics.
To me the big wild card is the stock market. The S&P500 is up 25% over the past year, driven by the AI boom, and to some extent it pulls the economy along with it. The Conference Board’s leading economic indicators are negative but improving overall this year; recently their financial indicators are flat while non-financial indicators are worsening.
Overall things remind me a lot of the late ’90s: the real economy running a bit hot with inflation around 3% and unemployment around 4%; the Fed Funds rate around 5%; and a booming stock market driven by new computing technologies. Naturally I wonder if things will end the same way: irrational exuberance in the stock market giving way to a tech-driven stock market crash, which in turn pushes the real economy into a mild recession.
Of course there is no reason this AI boom has to end the same way as the late-90’s internet boom/bubble. There are certainly differences: the Federal government is running a big deficit instead of a surplus; there are barely a tenth as many companies doing IPOs; many unprofitable tech stocks already got shaken out in 2022, while the big AI stocks are soaring on real profits today, not just expectations. Still, to the extent that there are any rules in predicting stock crashes, the signs are worrying. Today’s Shiller CAPE is below only the internet and Covid meme-stock bubble peaks:
Again, this doesn’t mean that stocks have to crash, or especially that they have to do it soon; the CAPE reached current levels in early 1998, but then stocks kept booming for almost two years. I’m not short the market. But the macro risk it poses is real.
I’m back from Manifest, a conference on prediction markets, forecasting, and the future. It was an incredible chance to hear from many of my favorite writers on the internet, along with the CEOs of most major prediction markets; in Steve Hsu’s words, Woodstock for Nerds. Some highlights:
Robin Hanson took over my session on academic research on prediction markets (in a good way; once he was there everyone just wanted to ask him questions). He thinks the biggest current question for the field is to figure out why is the demand for prediction markets so low. What are the different types of demand, and which is most likely to scale? In a different talk, Robin says that we need to either turn the ship of world culture, or get off in lifeboats, before falling fertility in a global monoculture wrecks it.
Play-money prediction markets were surprisingly effective relative to real-money ones in the 2022 midterms. Stephen Grugett, co-founder of Manifold (the play-money prediction market that put on the conference), admitted that success in one election could simply be a coincidence. He himself was surprised by how well they did in the 2022 midterms, and said he lost a bunch of mana on bets assuming that Polymarket was more accurate.
Substack CEO Chris Best: No one wants to pay money for internet writing in the abstract, but everyone wants to pay their favorite writer. For me, that was Scott Alexander. We are trying to copy Twitter a bit. Wants to move into improving scientific publishing. I asked about the prospects of ending the feud with Elon; Best says Substack links aren’t treated much worse than any other links on X anymore.
Razib Khan explained the strings he had to pull for his son to be the first to get a whole genome sequence in utero back in 2014- ask the hospital to do a regular genetic test, ask them for the sample, get a journalist to tweet at them when they say no, get his PI’s lab to run the sample. He thinks crispr companies could be at the nadir of the hype cycle (good time to invest?).
Kalshi cofounder Luana Lopes Lara says they are considering paying interest on long term markets, and offering margin. There is enough money in it now that their top 10 or so traders are full time (earning enough that they don’t need a job). The CFTC has approved everything we send them except for once (elections). We don’t think their current rule banning contest markets will go through, but if it does we would have to take down Oscar and Grammy markets. When we get tired of the CFTC, we joke that we should self certify shallot futures markets (toeing the line of the forbidden onion futures). Planning to expand to Europe via brokerages. Added bounty program to find rules problems. Launching 30-50 markets per week now (seems like a good opportunity, these can’t all be efficient right?).
There was lots else of interest, but to keep things short I’ll just say it was way more fun and informative doing yet another academic conference, where I’ve hit diminishing returns. More highlights from Theo Jaffee here; I also loved economist Scott Sumner’s take on a similar conference at the same venue in Berkeley:
If you spend a fair bit of time surrounded by people in this sector, you begin to think that San Francisco is the only city that matters; everywhere else is just a backwater. There’s a sense that the world we live in today will soon come to an end, replaced by either a better world or human extinction. It’s the Bay Area’s world, we just live in it.
Supporters of prediction markets tend to emphasize how they are great tools for aggregating information to produce accurate forecasts. If you want to know e.g. who is likely to win the next election, you can watch every poll and listen to pundits for hours, or you can take ten seconds to check the odds. This is great for people who want information- but how do prediction markets fare as investments for their actual participants?
Zero Sum
The big problem with prediction markets as investments is that they are zero sum (or negative sum once fees are factored in). You can’t make money except by taking it from the person on the other side of the bet. This is different from stocks and bonds, where you can win just by buying and holding a diversified portfolio. Buy a bunch of random stocks, and on average you will earn about 7% per year. Buy into a bunch of random prediction markets, and on average you will earn 0% at best (less if there are fees or slippage).
Low Liquidity
Current Kalshi order book for “Will June 2024 be the hottest June ever“. Betting $200 on either outcome could move the price by 5 cents (so move the estimated probability by 5pp).
This zero sum problem is close to inevitable based on how prediction markets work. They currently have one other big problem, though it is not inevitable, and is getting better as they grow: liquidity. There are some stocks and bonds where big institutions can buy or sell millions of dollars worth without moving the price. But in markets like Kalshi or PredictIt, I personally move prices often by betting just hundreds, or sometimes even just tens, of dollars. Buying at scale means getting worse prices, if you can even buy at all. PredictIt has a bet limit of $850 per contract for regulatory reasons. This definitely excludes institutional investors, but even for individuals it can mean many markets aren’t worthwhile. Say an outcome is already priced at 90 cents, the most you can make by betting it happens is about $94. That’s not nothing but its also not enough to incentivize lots of in-depth research, especially given the risk of losing the $850 if you are wrong and the opportunity cost of investing the money in stocks or bonds. Kalshi in theory allows bets up to $25k, but most of their markets haven’t had the liquidity to absorb a bet anywhere near that (though this could be changing).
Easy Alpha
Given these negatives, why would anyone want to participate in prediction markets, except to gamble or to generously donate their time to create information for everyone else? Probably because they think they can beat the market. Compared to the stock market, this is a fairly realistic goal. Perhaps because the low liquidity keeps out institutional investors, it isn’t that hard for a smart and informed investor to find mispricings or even pure arbitrages in prediction markets. This seems to be especially true with political prediction markets, where people often make bets because they personally like or dislike a candidate, rather than based on their actual chances of winning; that is exactly the kind of counterparty I want to be trading with.
I’ve been on PredictIt since 2018 and earned a 16% total return after fees; this was on hundreds of separate trades so I think it is mostly skill, not luck. Of course, even with this alpha, 16% total (not annual) return over 6 years is not great compared to stocks. On the other hand, I tended to put money in right before big elections and take it out after, so the money is mostly not tied up in PredictIt the whole time; the actual IRR is significantly better, though harder to calculate. On the other other hand, the actual dollar amount I made is probably not great compared to the time I put in. On yet another hand, the time isn’t a big deal if you are already following the subject (e.g the election) anyway.
Uncorrelated Alpha
The other big positive about prediction markets is that there is no reason to expect your returns there are correlated with your returns in traditional markets. Institutional investors are often looking for investments that can do well when stocks are down, and are willing to sacrifice some expected returns to get it. In fact, there may be ways to get a negative correlation between your prediction market returns and your other returns, hedging by betting on outcomes that would otherwise harm you. For instance, you can hedge against inflation by betting it will rise, or hedge against a recession by betting one happens. If you are right, you make some money by winning the bet; if you are wrong, you lose money on the bet but your other investments are probably doing well in the low-inflation no-recession environment.
Going Forward
Prediction markets have long been in a regulatory grey area in the US, but with the emergence of Kalshi and the current CFTC, everything may soon be black and white. Kalshi has won full approval from the CFTC for a variety of markets, but the CFTC is moving to completely ban betting on elections (you can comment on their proposal here until July 9th).
One great place to discuss the future of prediction markets will be Manifest, a conference hosted by play-money market Manifold in Berkeley, CA June 7-9th. It features the founders of most major US predictions markets and many of the bestwriters on prediction markets. I’ll be there, and as I write tickets are still available.
This is my last post before the US midterm elections on Tuesday, so I’ll leave you with a prediction for what’s coming.
Who is the best predictor of elections? Nate Silver at FiveThirtyEight has had a pretty good run since 2008 using weighted polls. Ray Fair, an economics professor at Yale has a venerable and well-credentialed model based on fundamentals. I typically favor prediction markets, because they incorporate a wide range of views weighted by how willing people are to put their money where their mouth is, and traders are able to incorporate other sources of information (including predictors like FiveThirtyEight). But which prediction market should we trust? There are now many large prediction markets, and the odds often differ substantially between them.
When there are many reasonable ways of answering a question or looking at a problem, it can be hard to choose which is best. Often the best answer is not to choose- instead, take all the reasonable answers and average them. Dan Gardner and Philip Tetlock call this approach Dragonfly Eye forecasting, since dragonfly’s eyes see through many lenses. So what does the dragonfly see here?
Lets start with the US House, since everyone covers it.
FiveThirtyEight’s latest forecast shows that Republicans have an 85% chance of taking the House; it shows a range of possible outcomes, but on average predicts that Republicans win the popular vote by 4.3% and take 231 House seats (substantially over the 218 needed for a majority)
The Fair Model predicts that Democrats will win 46.6% of the two-party vote share (leaving Republicans with 53.4%). This has Republicans winning the popular vote by 6.8%, a moderately bigger margin than FiveThirtyEight. The reasoning is interesting; the economy is roughly neutral since “the negative inflation effect almost exactly offsets the positive output effect”, so this is mainly from the typical negative effect of having an incumbent party in the White House.
Prediction markets: PredictIt currently gives Republicans a 90% chance to take the House. Polymarket gives them 87%. Insight Prediction also gives them 87%. Kalshi doesn’t have a standard market on this, but their contest (free to enter, 100k prize) predicts 232 Republican seats.
Its a bit tricky to average all these since they don’t all report on the same outcome in the same way. But the overall picture is clear: Republicans are likely to do well in the House, with an ~87% chance to win a majority, expected to win the popular vote by ~5.55% and take ~232 seats.
The Senate is closer to a coin flip and harder to evaluate.
FiveThirtyEight gives Republicans a 53% chance to win a majority (51+ seats for them; Democrats effectively win if the Senate stays 50-50 since a Democratic Vice President breaks ties for at least 2 more years). The most likely seat counts are 50-50 or 51-49, but confidence intervals are pretty wide and 54-46 either direction isn’t ruled out.
The Fair Model doesn’t make Senate predictions, only House and Presidential predictions.
Prediction markets: PredictIt gives Republicans a 70% chance to win a Senate majority, probably with 52-54 seats. PolyMarket gives Republicans a 65% chance, as does Insight Prediction. Kalshi predicts 53 Republican seats.
Overall we see a much higher variance of predictions in the Senate; a 17pp gap between the highest (70%) and lowest (53%) estimates of Republican chances, vs just a 5pp gap for the House (90% to 85%). This shows up with the seat counts too; everyone agrees there’s a substantial chance Republicans lose the Senate, but if they do win, it will probably be by more than one seat. The average estimate is ~52 Republican seats. FiveThirtyEight and PredictIt agree that the closest Senate races will be Georgia, Pennsylvania, Arizona, Nevada, and New Hampshire (though they rank order them differently), so those are the races to watch.
Forecasts for governors aren’t as comprehensive, but FiveThirtyEight predicts we’ll get about 28 Republican (22 Democratic) governors, while PredictIt expects 31+ Republicans; I’ll split the difference at 30. Everyone agrees that Oregon is surprisingly competitive because of an independent drawing Democratic votes. The biggest difference I see is on New York, where PredictIt gives Republican challenger Lee Zeldin a real chance (26%) but FiveThirtyEight doesn’t (3%).
Overall forecast: moderate red wave, Republicans take the House and most governorships, probably the Senate too. But if they lose anything it is almost certainly the Senate.
These forecasts seem about right to me. Democrats are weighed down by an unpopular (-11) President and the highest inflation in 40 years. This would lead to a huge red wave, but Republicans have their own weaknesses; an unpopular former President lurking in the background, and the Supreme Court making a big unpopular change voters blame them for. This shrinks the red wave, but I don’t think its enough to eliminate it. The effect of Roe repeal is fading with time, and the unpopular Biden is more salient than the unpopular Trump; Biden is the one in office and is more prominent in media coverage. Facebook and recently-acquired Twitter may be doing Republicans a favor by keeping Trump banned through Election day. But if he drags Republicans down anywhere, it will be the Senate, where candidate quality (not just party affiliation) is crucial and his endorsements pushed some weak/weird/extreme candidates through primaries. We’ll also see this “extremist” Trump effect (abetted by cynical Democratic donations to extreme-right candidates) dragging down Republicans in some key governor’s races like Pennsylvania, where Democrats are now 90/10 favorites..
Political betting has long been in a legal grey area. It seems that the Commodities Futures Trading Commission wants to make everything black and white, but at least for now it has simply made everything murkier.
PredictIt is the largest political betting site in the US; if you want to know who is likely to win an upcoming election, its the best place to find a quick answer. Prediction markets have two great virtues- they are usually right about what’s going to happen, and if they aren’t you can bet, making money and improving their accuracy at the same time.
PredictIt has operated since 2014 under a “no-action letter” from the CFTC. Effectively, the regulators told them “we’re not saying what you’re doing is definitely legal, but we know about it and have no plans to shut you down as long as you stick to the limits described in this letter”. But last week the CFTC withdrew their letter and ordered PredictIt to shut down by February 2023.
My first question was, why? Why shut them down now after 8 years when all their operations seem to be working as usual? The CFTC said only that “DMO has determined that Victoria University has not operated its market in compliance with the terms of the letter and as a result has withdrawn it”, but did not specify which of the terms PredictIt violated, leaving us to speculate. Did the scale simply get too big? Did they advertise too heavily? Did Victoria University, the official operator, let too much be handled by a for-profit subcontractor? Did some of their markets stray too far from the “binary option contracts concerning political election outcomes and economic indicators” they were authorized for?
PredictIt hasn’t been much clearer about what happened, simply putting a notice on their site. Their CEO did an interview on the Star Spangled Gamblers podcast where he said there was no one thing that triggered the CFTC but did mention “scope” as a concern- which I interpret to mean that they offered some types of markets the CFTC didn’t like, perhaps markets like “how many times will Donald Trump tweet this month”.
The other big question here is about PredictIt’s competitors. In 2021 it seemed like we were entering a golden age of real-money prediction markets, with crypto-based PolyMarket and economics-focused Kalshi joining PredictIt. I looked forward to seeing this competition play out in the marketplace, but it now seems like we’re headed toward a Kalshi-only monopoly where they win not by offering the product users like best, but by having the best relationship with regulators. Polymarket had offered markets without even a no-action letter, based on the crypto ethos of “better to ask forgiveness than permission”; this January the CFTC hit them with a $1.5 million fine and ordered them to stop serving US customers.
If the CFTC doesn’t reverse their decision to shut down PredictIt, then February 2023 will see a Kalshi monopoly. This has led to speculation that Kalshi is behind the attack on PredictIt; their cofounder issued this not-quite-a-denial. But it certainly looks bad for the CFTC that they are effectively giving a monopoly to the company that hires the most ex-CFTC members.
For now you can still bet on PredictIt or Kalshi (or even Polymarket if you’re outside the US). If you’d like to petition the CFTC about PredictIt you can do so here. It might actually work; while the CFTC’s recent actions certainly look cronyistic, they’ve been reasonable compared to other regulators. They’re giving PredictIt no fines and several months to wind down, and even Polymarket gets to keep serving non-US customers from US soil. I’d likely make different decisions if I were at CFTC but the ideal solution here is a change in the law itself, as we’ve seen recently in sports betting. Prediction markets are impressive generators and aggregators of information, and politics and policy are at least as valuable an application as sports. To go meta, suppose we want to know- will PredictIt survive past February? There’s a prediction market for that, and its currently saying they’ve got a 20% chance.
After their last meeting in March, the Federal Open Market Committee released the summary of economic projections. Most of the variables they project are inherently difficult to predict: GDP, unemployment, inflation. But their forecasts of the Federal Funds rate should be pretty good, since they’re the ones that get to pick what it will be. The median FOMC member thinks the the Federal Funds rate will be just under 2% by the end of 2022.
I said in my last post that the Fed is under-reacting to inflation. Markets seem to agree, but they also think that the Fed will change. Kalshi runs prediction markets on what the Fed Funds rate will be, which they recently started to summarize using this nice curve:
So traders think that the Fed will raise rates faster than the Fed thinks they will, with rates getting to 2.5% by year end. Traders at the Chicago Mercantile Exchange see an even bigger change, with rates at 2.75% by year end, and 3.5% by July 2023 (the longest-term market they offer).
I lean toward the markets on this one; if they are wrong there is plenty of money to be made by betting so.
Economist Writing Every Day 