Predictions for economics, given AI
With math essentially being delegated to OpenAI, here’s what I predict for economics and the social sciences more generally:
The top tier of research will just become better and it will be normal human-led research where AI is used for scale (e.g. conducting qualitative interviews with relevant populations, running behavioral interventions in the field, analyzing massive text data, etc.)
Field experiments will rise in value and generally making “connections” with firms and being able to run stuff (potentially testing AI pipelines) will be in high demand
Research with administrative data will become even more valuable, but the benefits might be concentrated among some prolific authors who are allowed by the government agencies to use local models to analyze the data at scale. PhD students can probably forget about it
Economic history will have a very exciting boom and there will be an enormous race and big rewards for digitizing archives as a source to both identify new research strategies and document new descriptive facts.
Review and verification systems will become massively improved with AI assistance and it will become standard practice to do a 360 review of the paper + code + data at the *submission* stage.
Research that in principle can already be almost completely outsourced to the AI (download and analyze public data, run simple survey experiments, write theory models) is in for a big shock. This would be very bad from the perspective of researchers who depend on this “bread and butter” research, but I think this type of work will just be outsourced to public agencies who can answer their own questions without the need for “peer-reviewed” research.
All of those make sense to me.
Thursday assorted links
2. How the math breakthroughs might matter.
3. Short proof of quasi-Riemann.
4. App for finding art exhibitions.
5. Podcast on African economic growth.
6. New and very good book: The Madrid Model: How Freedom and Openness Created an Economic Powerhouse, by Diego Sánchez de la Cruz.
How and why did the Victorians succeed?
From Samuel Hughes, in Works in Progress:
The elites of Victorian Britain operated differently. Their schools and universities were not terribly academic and had very little STEM. As adults, they got up late, drank a lot, and spent a remarkable share of their waking hours partying. They loved feasting, sports, holidays, dancing, and dressing up. Contrary to their stodgy reputation, they were probably a lot of fun.
Here is some further detail:
Most socially elite Victorian boys began formal education at the age of seven or eight, spending about five years in a ‘preparatory school’ before passing on to a ‘public school’ (which, to the enduring confusion of international observers, is a kind of elite private school). There was a hierarchy of public schools, with the nine ‘Clarendon schools’ at the top, and just one, Eton College, clearly at the apex. About 30 percent of nineteenth-century cabinet ministers and 40 percent of prime ministers were Old Etonians.
Most students at both preparatory and public schools were boarders, meaning that elite Victorians were generally sent away from home by the age of eight and spent their childhoods more with peers than with family. In this respect they were distinctive even in their own time: elite families in continental Europe and the United States were far more likely to keep their children at home and educate them at small local private schools. It is plausible that this contributed to the lack of subnational loyalties in the British elite, in contrast to the distinct elites of, for example, the Southern United States, Catalonia in Spain, or Hungary in the Austrian Empire.
Nor did the Victorians wake up early in the morning. Recommended, there is much more at the link, though the answer to the question remains somewhat of a mystery to me.
What I’ve been reading
1. Begoña Gómez Urzaiz, The Abandoners: On Mothers and Monsters. A wonderful book about mothers who abandon their children, and properly unsentimental. You will never think about Muriel Spark the same way again. Vashti Bunyan gets a section too. Recommended.
2. Evan Gershkovich, This Cursed Beautiful Land: A Russian-American Story. Yes he is the WSJ reporter who was arrested by the secret service in Putin’s Russia and held for eighteen months before being traded back home. He starts off naive, but does not finish that way. A compelling read, with good background information on what it is like to live in Russia in recent times, namely early years of the war with Ukraine. In prison it seems he was treated better than most. Excerpt: “I remembered what Eugenia Ginzburghad written about her two years in a maximum-security Yaroslavl prison before being sent to the Gulag — that during this period she was the best version of herself, at her most patient, kind, and thoughtful.”
3. Reinier de Graaf, architect, verb: The New Language of Building. A fun read, with chapters on the various prizes in architecture, Vancouver and city liveability, Richard Florida, and more. The book closes with a fun list of b.s. terms often heard from both academics and bureaucrats.
4. China Mieville, The Rouse. This novel is 1200 pp. plus, with pretty big pages, and I am on p.350 or so. It seems very good. At what point can I judge it? Can it sustain itself? Is “ah, but it fell apart on p.1137” actually a possibility? Past what page number is it in the clear? I guess I will find out.
Wednesday assorted links
1. Palo Alto Networks (cybersecurity firm, check out YTD).
2. OAI doing math again. Quasi-Riemann! And just one metric of import.
3. The AI agents pitching literary magazines.
4. Redux of my 2022 post on the effective altruists.
Against Laissez-Faire Democracy
In a new paper, Brennan and Freiman argue persuasively that:
the arguments against laissez-faire capitalism apply in a rather straight way against laissez-faire democracy. This should be a rather startling result, considering that laissez-faire capitalism is widely rejected, yet laissez-faire democracy is widely accepted.
All the typical market failure arguments–externalities, asymmetric information, principal-agent problems, behavioral issues–apply to democracy. For example:
democracies also suffer from obvious externality problems. Indeed, this is the key difference between markets and politics. Market decisions are usually and mostly internalized; negative externalities are seen as an anomaly to be corrected. Political decisions are by nature public. For instance, about 37% of the eligible
voting public, and 26% of the entire population of the UK voted in favour of Brexit, but the effects of Brexit are borne by everyone else, including losing voters, eligible voters who abstained, children and other citizens ineligible to vote, future generations, and foreigners.…The problem is similar to the pollution of individual automobile drivers or airline passengers. We drive too much and pollute too much because we bear the benefits of these actions but pass the costs onto others. Individually we matter little but collectively we matter a great deal. If externality regulation is prima facie justified in the case of pollution, it is prima facie justified in the case of voting.
They go on to suggest regulations that might apply to democracy. Noting first that:
…pretty much everyone already accepts some government actions which are plausibly seen as vote or democratic regulation. For instance, some issues are put directly to voters, while others are left to elected leaders, while others are left to judges and bureaucracies, and still others are removed from political consideration entirely. The timing and place of elections, who is permitted to vote (at what age), who is permitted to run for office, and so on are kinds of regulation. Government funding of public education is in part meant to be a non-laissez-faire subsidy meant to increase voter competence. Many readers are likely comfortable with government regulation of campaign donations, campaign expenditures and even which kinds of speech are permitted. Probably almost all readers reject straight up markets in votes (Freiman 2014). Each of these things is a kind of government regulation of democracy which inhibits laissez-faire democracy.
The authors sketch possible regulations while stipulating, for the sake of argument, universal, equal suffrage—no weighted votes or knowledge tests for voting eligibility. Possibilities include paying citizens to pass a voluntary civics exam; tracking campaign promises and fining deceptive claims; regulating political advertisements more like drug advertisements; and requiring supermajorities for certain decisions. See the paper for more.
You may object that these regulations would be captured by special interests, be administered by biased officials, or have unintended consequences. Indeed, welcome to the argument for laissez-faire.
Texas-Canada Fact of the Day
Texas produces more than Canada with three quarters of the population. Rough numbers for 2025:
| Texas | Canada | Texas / Canada | |
|---|---|---|---|
| Population | 31.7 million | 41.7 million | 0.76 |
| GDP, nominal (US$) | $2.9 trillion | $2.3 trillion | 1.27 |
| GDP per capita, nominal | $91,500 | $55,700 | 1.64 |
| GDP per capita, PPP | $94,000 | $66,700 | 1.41 |
| GDP, PPP (int’l $) | $3.0 trillion | $2.75 trillion | 1.09 |
Sources: BEA (Texas GDP, preliminary 2025; regional price parity), Census Bureau (Texas population), World Bank and IMF (Canada). Texas PPP figures divide nominal GDP by the BEA regional price parity.
Hat tip: Chris Powers.
Why most stereotypes are negative
Stereotypes are a foundational construct in psychological science, often defined as beliefs concerning characteristic group attributes. We present a cognitive-ecological theory of social perception that predicts and explains why such characteristic attributes are likely negative, that is, why most stereotypes are negative. The theory assumes that, cognitively, people characterize groups by attributes that distinguish them from other groups. Ecologically, positive social information is more frequent (i.e., positivity prevalence), and negative social information is more diverse (i.e., negativity diversity. If negative attributes are less frequent and more diverse relative to positive attributes, then they must be more likely to distinguish one group from another. Consequently, the attributes people see as characteristic of a group are likely to be negative. We illustrate the predicted stereotype negativity across two studies and two existing data sets. We then formalize the theory and illustrate it with simulations showing that rare attributes can be highly diagnostic of group membership while applying to only a minority of group members. Thus, the theory explains why most stereotype content is likely negative, despite the well-documented positivity prevalence, and why stereotypes may be diagnostic and comparatively accurate, despite being descriptively inaccurate. The theory explains stereotype negativity without requiring motivational derogation, essentialist group differences, or a general negativity bias, and it clarifies when positive stereotypes should occur. We also discuss the theory’s relation to dimensional models of stereotype content and consequences for interventions aimed at reducing stereotype negativity.
That is from a recent paper by Christian Unkelbach, Anne Irena Weitzel, and Hans Alves, via the excellent Kevin Lewis.
Effective altruism is useful at the margin
That is the theme of my latest Free Press essay, here is one excerpt:
I feel I am well aware of the limitations of effective altruism, and I have outlined many others in an hour-long dialogue I had with MacAskill, arguably the father of the movement, in 2022.
Nonetheless, at the margin I think more effective altruism would be a good thing.
First, I am not worried that the desires of current human beings will be devalued or ignored. Such desires rule the politics of all Western nations and many others as well. If anyone tried to pass a bill to advance shrimp welfare, I do not think it would get a single vote in Congress. In the meantime, we still do treat animals with excessive cruelty, relative to improvements we might make (you could start by eating less chicken and more beef, because a demand for beef kills fewer cows, given the larger size of the cow.) It would be better if people paid at least partial heed to the strictures of effective altruism on this and many other points.
What about the AIs? Well, artificial intelligence is going to fundamentally transform our world. Many connected to effective altruism may exaggerate its effects, or perceive a high risk of doom without sufficient evidence. Nevertheless, it would be a good thing if we paid more attention to AI issues, and to AI safety in particular. Score another point for effective altruism, at least if you make marginal rather than fully extreme adjustments.
As for aid to Africa and poor nations everywhere, I am not sure of the exact policy to pursue, but foreign aid is currently well below 1 percent of the U.S. federal budget, and the Trump administration pared it back. We are hardly sacrificing our seed corn in America to elevate the rest of the world. In the meantime, if you support some charitable public health programs in Africa and save some lives instead of donating to Harvard, that is probably a better decision.
Again, effective altruism is directionally correct, even if you should not follow its recommendations all the way.
Recommended.
Brazil election notes (from my email)
From Diego Costa:
“Hi Tyler,
If you’re still interested in the fallout from Brazil’s elections, here are some observations that add texture to the usual narratives:
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Nine of the 10 candidates who received the most votes for the Lower Chamber are under 40. The exception is 41. Their average age is 31.6. They’re all very online and cultural-war centered. Four are pro-woke and six are anti-woke. The biggest vote-winner, anti-woke Nikolas Ferreira, will still be too young to run for president in 2030.
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There is a divergence between evangelical influencers and the big evangelical churches. While evangelical politicians with strong personal followings did well, several major big church machines lost seats, particularly in Rio.
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Brazil is expected to have its most female Senate ever, with 18 of 81 senators, driven by women on the right. All three senators representing the Federal District will be right-wing, including Jair Bolsonaro’s wife, Michelle Bolsonaro.
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This might be the end of Lulismo. Lula or his chosen candidate has run in every presidential election since 1989, but he has no obvious successor. If he loses the runoff, his personal presidential record will stand at three wins and four losses. Several historical PT historical figures also lost their bids. And Lula, who began his career with votes from the educated middle class in Brazil’s industrial Southeast, is ending it by leading only in the poorest income bracket and the poorer Northeast region.
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Flávio Bolsonaro’s Liberal Party won 121 seats in the Chamber and should hold 28 in the Senate, a record for any party since the 1988 Constitution. It will nevertheless remain short of a majority in both houses. The Chamber will feature 20 parties, down from the 30 elected in 2018.
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The Bolsonaro family elected two senators (Jair’s wife Michelle and son Carlos) and two federal deputies (his son Jair Renan and brother Renato). His son Flávio is leading going into the presidential runoff, while his other son Eduardo might become minister. That is possibly the highest concentration of national political power in one immediate family since the Brazilian Republic was founded in 1889.
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Lava Jato’s leading figures made a strong electoral comeback. Sergio Moro, the former judge who convicted Lula, won the governorship of Paraná in the first round. Deltan Dallagnol, who led the prosecution, won enough votes for a Senate seat, although his eligibility may be contested in the superior courts.
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Anger over corruption and power grabs by Supreme Court justices was a defining factor in the first-round result. I expect a confrontation between the new Senate and the court over limits on its powers to become a major story in 2027. Brazil’s Supreme Court issued over 100,000 decisions in 2025 alone.”
Tuesday assorted links
1. What is the real rate of Chinese economic growth?
2. An Abundance caucus rolls out a bipartisan agenda.
3. Canada fell to 18th from 9th in global ranking of economic freedom.
4. Will there ever be a Latin Bomb?
7. Seb Krier!
8. Good review of the new Kevin Roose book (NYT).
9. Research taste in foundation models is rising rapidly.
10. “Shares of South Korean cybersecurity companies surged by as much as 30% Tuesday.” (WSJ)
Paul Graham Versus the Pope
Pope Leo XIV recently tweeted that there is “an ontological difference, even before an aesthetic one, between art and what a machine can generate through statistical calculation based on millions of images created by others.”
As a description of how today’s models work, that’s fair enough. AI learned to paint by looking at our paintings.
Paul Graham (also a painter!) notes that this is about to change. Robots wired into the world will soon perceive it for themselves. A robot or AI that learns from its own sensors isn’t borrowing images from others. LLMs were founded on our words but their words will dominate the future.
So picture a robot on a beach at dusk. It watches the sun go down, then paints what it saw. Is it art? The Pope would no doubt still assert an ontological difference. But once the factual distinction between borrowing and perceiving fades, what makes that more than a statement of faith?
The Great Accretion and the Great Depression
A very old idea, returning with a vengeance:
The Second Industrial Revolution sparked a wave of new products and industrial processes, fueling an optimistic Roaring Twenties. But did excitement about technological progress contribute to an over accumulation of investment, despite a slowdown in new product development and satiated demand during the 1920s? And, was this over investment worsened by continuous process innovation? Could these factors have played a role in triggering the Great Depression? To explore these questions, a macroeconomic model that incorporates both process and product innovation is proposed. Proof-of-concept simulations are performed to assess whether these factors can help explain the Great Depression. The answer is yes.
That is from a recent NBER working paper by
Rising concentration for economics awards
We analyze the academic affiliations of nearly 6,000 award-winning researchers in 18 major fields in the natural sciences, engineering, and social sciences from the 1820s to the 2020s, focusing on the 1960s onward. The analysis reveals a trend of declining concentration in the institutional affiliations of award-winning researchers, shifting from a few science-strong universities in high-income countries to a more diverse set of institutions across the world. The decline in concentration is observed in all fields except one: economics. The institutional affiliations of prizewinning economists have become more concentrated over time, making economics the most concentrated field. We associate the higher concentration of prizewinning work in economics with the field’s stronger sorting by institutional prestige, its lower reliance on specialized equipment and instruments, and its assessment of findings based on a synthesis of evidence rather than on decisive experiments or proofs. We discuss the benefits and costs of this high and rising institutional concentration of prizewinning economists.
Here is more from