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Nobel Guesses

by Greg Rosalsky

And the winner of the 2026 Nobel Prize in economics is… we don’t know yet. That announcement is scheduled for Monday, and we’ll be covering it here in the Planet Money newsletter and The Indicator podcast.

In the meantime, the week before the announcement is a great time to partake in a nerdy pastime: remembering all the amazing economics research that hasn’t yet gotten a Swedish medal, and guessing who might get the world’s most coveted wake-up call.

One quick note: the official name is the Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel. It’s a mouthful, so we’ll stick with “Nobel Prize in economics.” Unlike the original Nobel prizes, this one wasn’t established by Alfred Nobel’s will. Sweden’s central bank created it in 1968 — a history we’ll explore in a forthcoming episode of The Indicator.

Many factors go into choosing a Nobel laureate. Winners tend to be older, partly because the committee wants the passage of time to help them assess the candidates’ impact on the field and/or broader world. Sometimes the committee picks research that speaks to the zeitgeist. Other times it’s because of very technical work that has given economists stronger empirical tools to study the world.

So how might we make a guess? Well, there’s one tool that economists love for making predictions: markets. Markets can aggregate the scattered information held by countless people, boiling down what they know about the world into a single number: a price — an idea famously articulated by economist Friedrich von Hayek, who, naturally, won a Nobel prize back in 1974.

Those prices can sometimes offer clues about the future. For example, take the stock market. Many economists view it as a kind of giant information-processing machine. In this view, a company’s stock price reflects the crowd's beliefs about that company’s future profits. It can provide a kind of crystal ball. Although, of course, the crowd can be wrong.

[🎧There is, of course, a classic Planet Money episode about this, and also about a cow.]

The same idea applies to prediction markets, which have really taken off in recent years. Instead of betting on a company’s future profits, traders bet on whether a particular event will happen — say, who will win a Nobel Prize.

And, wouldn’t you know it, there’s a prediction market for who will win the 2026 Nobel in economics. There’s just one problem: it’s incredibly small, or as traders might call it, thin. Maybe economists are too rational — or too busy — to bet on something this unpredictable?

As of this writing Tuesday afternoon, October 6th, this prediction market for who will win the 2026 prize had recorded about $11,000 in trading volume. For comparison, Kalshi’s main market for the 2024 presidential election recorded about $670 million — tens of thousands of times as much. That prediction market correctly favored Donald Trump to win the election.

With such little trading, however, this Nobel prediction market seems less like the wisdom of crowds, and more like the guesstimates of a small number of nerdy gamblers. As we sat down to write this on Tuesday, we watched, somewhat frustratingly, as the market swung wildly over who was favored to win based on what seemed to be relatively small new bets.

But let’s give this prediction market the benefit of the doubt and call it a starting point. It at least provides an excuse to explore some big economic ideas and methods and the people behind them.

By late Tuesday afternoon, we decided to stop hitting refresh. Ariel Pakes and Susan Athey were trading places at the top of Kalshi’s rankings, with Robert Barro rounding out the top three.

KENA BETANCUR / Getty Images

Ariel Pakes: What happens when competitors merge?

Ariel Pakes is an economist at Harvard University who has made big contributions to an area of economics known as industrial organization. It studies how industries are organized and how that structure affects competition and the prices and choices of consumers. For example, how do prices and product offerings differ when a market is dominated by a single company versus many competing ones?

In 1995, Pakes, together with Steven Berry and James Levinsohn, published a landmark paper about the American automobile industry. The method they developed, known as BLP, helps economists figure out how consumers choose among competing products. Those estimates can help simulate whether a proposed merger or acquisition will raise prices, and by how much.

This isn’t just an academic exercise. The BLP model has evolved over time, and antitrust regulators use these tools to estimate how a proposed merger could affect consumers — giving them evidence to weigh when deciding whether to challenge a deal.

Why has Pakes been leading the pack on Kalshi? Maybe it’s because antitrust is hot right now, and his research speaks to the zeitgeist. Maybe it’s because the empirical tools he’s helped develop have had a considerable impact on policymaking. Or maybe it’s because one high roller placed a bet with inside knowledge, or because they were like a Pakes superfan… We can’t know. Anyways, moving on.

Susan Athey: Using machine learning to understand cause and effect

Susan Athey is the economics of technology professor at Stanford Graduate School of Business. As her title hints, she is a leading authority on the economics of digital technology, from the internet to cryptocurrencies to artificial intelligence.

Athey has been a prolific scholar. In 2007, she won the John Bates Clark Medal, a top prize for economists under 40 who make “the most significant contribution to economic thought and knowledge.” The American Economic Association cited her contributions to “economic theory, empirical economics, and econometrics.” She was the first woman to win the prize.

Since then, Athey has continued to tackle a wide range of topics. We previously cited her theoretical work aimed at designing a market that creates incentives to remove carbon from the atmosphere and slow or reverse climate change.

Athey also helped pioneer the use of machine learning — a branch of artificial intelligence — in economics. Machine learning is good at finding patterns in data and making predictions. Athey and her collaborators have helped adapt those tools to answer questions about cause and effect. For example, does a job-training program help workers make more money, and which workers see bigger benefits?

In addition to her theoretical and empirical contributions to the field, Athey has been an outspoken critic of her field’s culture of bullying, discrimination, and sexual harassment. We spoke to her back in 2019, when the profession was reckoning with the underrepresentation and mistreatment of women amid the MeToo movement.

Robert Barro: Why expectations matter

Next up: Robert Barro. He’s another economist at Harvard University. He, alongside Nobel laureates like Robert Lucas and Thomas Sargent, helped reshape modern macroeconomics around a simple idea: people and businesses look ahead, and policymakers have to account for that. Their expectations about future taxes, inflation, and government actions shape how they respond to efforts to stimulate the economy or control inflation.

Barro is particularly known for helping to develop a theory known as “Ricardian equivalence.” The basic gist: if the government cuts people’s taxes by borrowing, that may have a smaller stimulative effect than policymakers hope. That’s because people anticipate that the resulting debt will eventually require higher taxes — and they may decide to save the extra money instead of spending it. Ricardian is a reference to the 19th century British economist David Ricardo. “Equivalence” refers to the idea that, under certain assumptions, taxing people now or borrowing and taxing them later has the same effect on consumer spending. That’s because, according to this theory, people will save the extra money to cover higher taxes down the road.

This idea has been hotly debated for decades. Critics stress that many households don’t plan that far ahead, and those who are short on cash tend to spend the money instead of saving it.

Other potential winners

As we stated above, not many people seem to be betting at the Kalshi prediction market on the 2026 Nobel Prize in economics. And their rankings hardly exhaust the possibilities. Here are some other potential contenders:

Thomas Piketty and Emmanuel Saez: Tracking the rise of the very rich. Piketty is a professor of Economics at the Paris School of Economics. Saez is at UC Berkeley. The two did pathbreaking work on inequality that helped get us talking about “the one percent.” (Check out our recent episode of Planet Money, “Middlegarchs are the new oligarchs,” which touches on this research).

Raj Chetty: Mapping the American Dream. If you read this newsletter, you probably know we’re fanboys and fangirls of Raj. He’s an economist at Harvard University, and he and his many collaborators have used massive government datasets and clever empirical methods to tackle some of the biggest questions in economics, including a bunch of work on how to revitalize the American Dream. (Raj Chetty has been a fixture in the Planet Money newsletter and podcast; check out: “Why the American Dream is more attainable in some cities than others”; “This housing program helped kids escape poverty — by changing who they befriended”; and “Affirmative action for rich kids: It's more than just legacy admissions”).

David Autor: How technology and trade reshape work. Autor, of MIT, is one of the most influential labor economists of our time. His research has helped transform our understanding of how technology changes work. He and his collaborators helped explain how the computer revolution contributed to growing income inequality. He also, of course, did very influential research on the “China Shock,” which is still shaping heated conversations about the effects of free trade on the economy. (We’ve explored Autor’s work many times in the Planet Money newsletter and podcasts. For a taste, check out, “What if AI could rebuild the middle class?”; “Why economists got free trade with China so wrong”; “Are Cities Overrated?”; and “What the future of work means for cities”).

Janet Currie: Showing how childhood matters for the economy. Currie, an economist at Yale, has done a bunch of important work on how the conditions kids grow up in shape their economic outcomes as adults. Her research explores how disadvantages, from poverty to pollution, can have lasting consequences. And she’s studied how various government programs can improve kids’ health and ultimately their economic prospects.

Of course, some of these are our picks, and they're not listed on Kalshi. And newsletter writers, no matter how well versed in the economics literature, don't have crystal balls. Nor do prediction markets. They merely aggregate information from a crowd of people willing to bet about the future. And, in the case of this prediction market, that crowd doesn’t seem very big.

Stay tuned for next week’s Planet Money newsletter for our analysis of who ended up actually winning the prize and why. If you’re not already subscribed, you can subscribe here: npr.org/planetmoneynewsletter

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