2026-04-01 02:39:04
Bryan Caplan keeps hammering this point home, it is good to see follow-up work:
In the United States, college dropout risk is sizable. We provide new empirical evidence that beliefs about the likelihood of earning a bachelor’s degree predict college enrollment, and that the distribution of these beliefs exhibits widespread optimism. We incorporate this distribution of beliefs into an overlapping generations model with college as a risky investment that can be financed via federal loans, grants, family transfers, or earnings. We then examine the welfare impact of access to federal student loans. We find that access can reduce welfare for young adults who are low-skilled, poor, and optimistic, due to their mistaken beliefs.
That is from AEJ: Macroeconomics, by Emily G. Moschini, Gajendran Raveendranathan, and Ming Xu. Via the excellent Kevin Lewis.
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2026-04-01 01:58:39
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2026-03-31 23:50:29
1. “… presenting Economics as empirical and socially relevant may broaden the profile of those who consider the field.” But it does not get more people interested.
2. Youth happiness has been rising in many places, possibly most.
3. The NIH as an implicit regulatory body.
4. The Lebron critique of prediction markets.
5. Adam Tooze: “It is a truism of the moment that China is the last adult in the room.”
6. Quantum breakthroughs? And another account. Will the Satoshi wallet remain safe?
7. Shall we organize scientific literatures around claims rather than papers?
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2026-03-31 15:26:36
Yes, there are skills AIs haven’t mastered. But if your skill still appears to be the exclusive province of humans, that might mean the major AI companies do not yet consider it very important to master right away. Eventually it will rise to the top of the list.
Here is more from my Free Press essay on AI. If not for the copied passage, it seems no one was noticing this book review? (NYT, read the emendation)
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2026-03-31 12:45:44
Specification Searching in the Race between Education and Technology: Joseph Francis criticizes a canonical model of the American labor market, which has been used to advocate for more funding for education to reduce inequality. He shows how the model has routinely failed to predict the evolution of the college wage premium. Ad hoc econometric adjustments have been necessary to make the model fit the data, most notably in Claudia Goldin and Lawrence F. Katz’s well-known book. (The commented-on authors are hereby invited to reply in a future issue.)
Globalization and the China Shock: A Reassessment: David Autor, David Dorn, and Gordon Hanson estimated the effect of imports of manufactured goods from China from 1990 to 2007 on employment, wages, and social welfare payments in the USA, concluding that imports from China reduced manufacturing employment and lowered wages of workers in non-manufacturing industries. Robert Kaestner argues that the authors’ focus only on Chinese imports, which are correlated with imports from other countries and likely other omitted variables, muddles the interpretation and usefulness of their results. Kaestner argues that their estimates do not measure the effect of Chinese imports on employment and wages holding all other things equal, and do not even measure the broader equilibrium effect of Chinese imports on outcomes that includes changes in imports from other countries. Overall, the evidence suggests that omitted variable bias is likely, which renders their estimates uninformative. (The commented-on authors are hereby invited to reply in a future issue.)
Learning on machine learning on the housing supply impact of land use reforms: An Urban Studies article reports relatively modest housing-stock gains from liberalization, based on a dataset of reforms identified via machine learning applied to newspaper coverage. Researchers at the American Enterprise Institute challenge the article’s methodology and conclusions, and the Urban Studies authors respond.
An Article in Science on Covid Origins Contains a Fundamental Error: An influential article claimed that Bayesian analysis of the molecular phylogeny of early SARS-CoV-2 cases indicated that the likelihood that two successful introductions to humans had occurred was greater than the likelihood that just one had occurred. After correcting a fundamental error in Bayesian reasoning, the results presented in that paper imply larger likelihood for a single introduction, reducing the plausibility of the wet-market zoonosis account of Covid’s origins. (The commented-on authors were invited to reply and the invitation remains open.)
A Critique of Synthetic Control Method Studies on Covid-19 Policy—Evidence from Sweden: Five studies employing the Synthetic Control Method (SCM) conclude that Sweden would have experienced lower mortality had it imposed a mandatory lockdown in early 2020. Dividing Sweden into four hypothetical countries based on winter holiday timing—a proxy for pre-lockdown viral seeding—Jonas Herby shows that the estimated lockdown effect varies dramatically across regions with identical policies, suggesting SCM captures variation in viral spread rather than a causal policy effect. Sweden’s low excess mortality in the end suggests that Sweden’s state epidemiologist, Anders Tegnell, was right all along. (The commented-on authors are hereby invited to reply in a future issue.)
Central Banking Research Is Increasingly Directed to Environment, Inequality, Gender, and Race: Radu Șimandan and Cristian Valeriu Păun use the Scopus database to show how environment, inequality, gender, and race have soared as topics in research outlets supposedly focused on money and banking. They discuss the hazards of subverting price stability and other traditional central bank mandates.
Power Analysis Is Essential—A Case Study in Rounded Shapes: A Journal of Consumer Research article reported an A/B test where simply rounding the corners of square buttons increased click-through rate by 55 percent, but provided no power analysis. Ron Kohavi and coauthors show that the original study was highly underpowered. They report that three high powered A/B replications, each over two thousand times larger, had estimated effects approximately two orders of magnitude smaller than initially claimed. (The commented-on authors are hereby invited to reply in a future issue.)
“Impartial spectator” in Adam Smith’s The Theory of Moral Sentiments: In the previous issue, a critique alleged that numerous scholars flatten Smith’s “impartial spectator.” Jack Weinstein responds with “Adam Smith’s Impartial Spectator Is Neither Divine Nor an Ideal Observer,” and the critics renew their case against flattening “impartial spectator.”
The Ideological Profile of France’s Economic Bestsellers: Alexis Sémanne inspects the 100 economics bestsellers for 2024, as listed by a leading French bookseller. He develops seven categories and evaluates each book for its ideological tendency. Quite few of the books offer a freedom-oriented perspective.
Green Vanities in Europe: John Constable reviews A Green Entrepreneurial State? Exploring the Pitfalls of Green Deals, edited by Magnus Henrekson, Christian Sandström, and Mikael Stenkula, a book which reveals more than the fact that green deals in Europe have been failures.
EJW thanks its referees and others who contribute to its mission.
EJW Audio:
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2026-03-31 02:53:15
This matters for the AI question, and the book leaves it unfinished. If the breakthroughs of the past required social conditions, not just cognitive capacity, then what does it mean when the next breakthroughs are produced by systems that have no social conditions at all? A neural net does not need a university chair or financial independence from the church. It does not need to reorganize its commitments. It does not, in any recognizable sense, have commitments. The machine that replaces the marginalist is not a better marginalist. It is a different kind of thing entirely.
That is from Jônadas Techio, presumably with LLMs, this review of The Marginal Revolution is interesting throughout. And this:
Maybe the book demonstrates only that Cowen personally remains good at something the field no longer needs.
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