Friday assorted links
1. Best DC art works? (FT) Surely Manet’s The Railway should be on the list? Does Dulles Airport count? The Iwo Jima Memorial or Vietnam Memorial? Maybe even the Air Force Memorial?
2. The raccoon culture that was Virginia and I suppose still is a little bit?
3. Stoppard’s liberal individualism.
4. Jerry Z Muller on conservatism.
5. SPEAK, new organization for free speech in the UK.
Political pressure on the Fed
From a forthcoming paper by Thomas Drechsel:
This paper combines new data and a narrative approach to identify variation in political pressure on the Federal Reserve. From archival records, I build a data set of personal interactions between U.S. Presidents and Fed officials between 1933 and 2016. Since personal interactions do not necessarily reflect political pressure, I develop a narrative identification strategy based on President Nixon’s pressure on Fed Chair Burns. I exploit this narrative through restrictions on a structural vector autoregression that includes the President-Fed interaction data. I find that political pressure to ease monetary policy (i) increases the price level strongly and persistently, (ii) does not lead to positive effects on real economic activity, (iii) contributed to inflationary episodes outside of the Nixon era, and (iv) transmits differently from a typical monetary policy easing, by having a stronger effect on inflation expectations. Quantitatively, increasing political pressure by half as much as Nixon, for six months, raises the price level by about 7% over the following decade.
That is not entirely a positive omen for the current day.
Emergent Ventures winners, 50th cohort
Geby Jaff, Berkeley, publication medium for AI-generated science.
Laura Ryan, London, data for the AIs.
Tara Rezaei, MIT, general career support/AI/o1.
Mihir Rao, Princeton, bio and AI.
Lorna MacLean, London, AI medical diagnosis of endometriosis.
David Yu, Waterloo, Ontario/Taiwan, fellowship program for agentic Taiwanese college students.
Aniket Panjwani, Lombard, Illinois, EconNow, AI-based software for economics.
Zixuan (Eric) Ma, GMU, to write about China.
Ivan Khalamendyk, Lviv, “I’m an independent Ukrainian physicist developing a ψ-field model of the universe – a single real wave ψ(x,t) that reproduces quantum matter, forces and gravity.”
José Luis Sabau, Mexico City, Perpetuo, Substack for Mexico.
Soleil Wizman, Yale University, longevity.
Thursday assorted links
1. Protestant magic and occultism in Ireland.
2. Funny that academics should feel the need to provide a defense of the positive benefits of status.
3. Immersive summer workshops on rationality for teens.
4. New Justin Sandefur blog/newsletter.
5. Evan Goldfine music recommendations.
Innovations in Health Care
The latest issue of the journal Innovations focuses on health care and is excellent. It’s a very special issue–a double Tabarrok issue!
My paper, Operation Warp Speed: Negative and Positive Lessons for New Industrial Policy, asks what can learn from the tremendous success of OWS about an OWS for X? What are the opportunities and the dangers?
My son Maxwell Tabarrok’s paper is Peptide-DB: A Million-Peptide Database to Accelerate Science. Max’s paper combines economics and science policy. Open databases are a public good and so are underprovided. A case in point is that there is no big database for anti-microbial peptides despite the evident utility of such a database for using ML techniques to create new antibiotics. The NIH and other organizations have successfully filled this gap with databases in the past such as PubChem, the HGP, and ProteinDB. A million-peptide database is well within their reach:
The existing data infrastructure for antimicrobial peptides is tiny and scattered: a few thousand sequences with a couple of useful biological assays are scattered across dozens of data providers. No one in science today has the incentives to create this data. Pharma companies can’t make money from it and researchers can’t produce any splashy publications. This means that researchers are duplicating the expensive legwork of collating and cleaning all of this
data and are not getting optimal results, as this is simply not enough information to take full advantage of the ML approach. Scientific funding organizations, including the NIH and the NSF, can fix this problem. The scientific knowledge required to massively scale the data we have on antimicrobial peptides is well established and ready to go. It wouldn’t be too expensive or take too long to get a clean dataset of a million peptides or more, and to have detailed information on their activity against the most important resistant pathogens as well as its toxicity to human cells. This is well within the scale of the successful projects these organizations have funded in the past, including PubChem, the HGP, and ProteinDB.
Naturally, I am biased towards Tabarrok-articles but another important paper is Reorganizing the CDC for Effective Public Health Emergency Response by Gowda, Ranasinghe, and Phan. As Michael Lewis wrote in The Premonition by the time of COVID the CDC had became more akin to an academic department than a virus fighting agency:
The CDC did many things. It published learned papers on health crises, after the fact. It managed, very carefully, public perception of itself. But when the shooting started, it leapt into the nearest hole, while others took fire.
Gowda, Ranasinghe, and Phan agree.
The COVID-19 pandemic revealed significant weaknesses in the CDC’s response system. Its traditional strengths in testing, pathogen dentification, and disease investigation and tracking faltered. The legacy of Alexander Langmuir, a pioneering epidemiologist who infused the CDC with epidemiological principles in the 1950s, now seems a distant memory. Tasks as basic as collecting and providing timely COVID-19 data, along with data analysis and epidemiological modeling—both of which should have been the core capability of the CDC—became alarmingly difficult and had to be handled by nongovernmental organizations, such as the Johns Hopkins University Coronavirus Resource Center.
A closer examination of the CDC’s workforce composition reveals the root cause: a mere fraction of its employees are epidemiologists and data scientists. The agency has seen an increasing emphasis on academic exploration at the expense of on the-ground action and support for frontline health departments. (Armstrong & Griffin, 2022).
The authors propose to reinvigorate the CDC by integrating it with the more practical and active U.S. Public Health Service. This is a very good suggestion.
For one more check out Bai, Hyman and Silver as a primer on Improving Health Care. The entire issue is excellent.
The importance of the internet
From my recent chat with Alex, mostly about fiscal policy:
TABARROK:To be clear, a 0.5% increase in the rate of productivity growth, that doesn’t seem like a lot, but that would be historically a bigger increase than we got from anything. A bigger increase than the internet. Sure, yes.
COWEN:It is the internet in a way, but yes.
TABARROK:It was founded on the internet, yes. The internet was the agar culturefor the growth of the AI.
COWEN:That’s why the internet’s important. We’re just beginning to realize this,right?
TABARROK:Exactly, yes.
COWEN:It’s why a lot of people can’t admit AI might be a good thing, because then they’d have to admit the internet was a good thing. They’re so committed to never saying that.
TABARROK:Is that why?
COWEN:That’s why, yes.Believe me. That’s why.
TABARROK:It is funny that I think historically, when we look back, I think you’re right, we’ll think about what was the internet. The growth culture was putting everything online, was for the AI. It wasn’t for us.
Wednesday assorted links
1. Dwarkesh speaks. And Dwarkesh on AI progress.
2. Merve Emre on what makes Goethe special. A good piece, but has anyone actually captured and expressed this yet?
3. Japanese washing machine for humans?
4. Anthropic estimates the productivity impact of Claude. And the Twitter summary. And Zvi on Claude Opus 4.5. And Dean Ball. It loves Op.132.
Congressional leadership is corrupt
Using transaction-level data on US congressional stock trades, we find that lawmakers who later ascend to leadership positions perform similarly to matched peers beforehand but outperform them by 47 percentage points annually after ascension. Leaders’ superior performance arises through two mechanisms. The political influence channel is reflected in higher returns when their party controls the chamber, sales of stocks preceding regulatory actions, and purchase of stocks whose firms receiving more government contracts and favorable party support on bills. The corporate access channel is reflected in stock trades that predict subsequent corporate news and greater returns on donor-owned or home-state firms.
That is from a new NBER working paper by Shang-Jin Wei and Yifan Zhou. Of course Alex T. has been on this issue for a long time now.
Tuesday assorted links
1. Brangus on women, the incels need this, noting I do not agree with all the points. But better than the PUA stuff.
2. The monarchy returns in Tonga.
3. Hail the Swiss. 80 percent rejection. And Johann notes to me: “Only two municipalities voted yes on the recent ballot measure for a 50% inheritance tax over 50 million francs: The city of Bern with about 140’000 inhabitants and the village of Schelten with 34.”
4. Woman on a mission to photograph every species of hummingbird.
5. Parties of the Right rising in Honduras, party of the Left plummeting. But when will the ruling party resume the count or make the count public? And it seems the two leading candidates are both ethnically Palestinian?
6. Why many people have trouble with the concept of strong AI or AGI.
7. Is the Mississippi reading miracle in part statistical illusion?
The myth of the $140,000 poverty line
That is my latest piece for The Free Press, focusing on the claims of Michael W. Green. Excerpt:
Most of all, there is a major conceptual error in Green’s focus on high prices. To the extent that prices are high, it is not because our supply chains have been destroyed by earthquakes or nuclear bombs. Rather, prices are high in large part because demand is high, which can only happen because so many more Americans can afford to buy things. I am reminded of the old Yogi Berra saying: “Nobody goes there anymore. It’s too crowded.”
There are now numerous excellent criticisms of the same piece, for instance by Scott Winship and Noah Smith. As my piece was in the works, Green published this response to some of the criticisms.
Séb Krier
Huge fan of multi agent systems, agent based modelling, and social intelligence – these frames still seem really absent from mainstream AI discourse except in a few odd places. Some half-baked thoughts:
1. Expecting a model to do all the work, solve everything, come up with new innovations etc is probably not right. This was kinda the implicit assumption behind *some* interpretations of capabilities progress. The ‘single genius model’ overlooks the fact that inference costs and context windows are finite.
2. People overrate individual intelligence: most innovations are the product of social organisations (cooperation) and market dynamics (competition), not a single genius savant. Though the latter matters too of course: the smarter the agents the better.
3. There’s still a lot of juice to be squeezed from models, but I would think it has more to do with how they’re organised. AI Village is a nice vignette, and also highlights the many ways in which models fail and what needs to be fixed.
4. Once you enter multi-agent world, then institutions and culture start to matter too: what are the rules of the game? What is encouraged vs what is punished? What can agents do and say to each other? How are conflicts resolved? It’s been interesting seeing how some protocols recently emerged. We’re still very early!
5. Most of the *value* and transformative changes we will get from AI will come from products, not models. The models are the cognitive raw power, the products are what makes them useful and adapted to what some user class actually needs. A product is basically the bridge between raw potential and specific utility; in fact many IDEs today are essentially crystallized multi agent systems.
Here is the link.
*Liberal Worlds: James Bryce and the Democratic Intellect*
By H.S. Jones, an excellent book. For all the resurgence of interest in government and its problems, Bryce has received remarkably little attention. But his theory of low-quality, careerist politcians, combined with imperfectly informed voters, seems highly relevant to our current day. Public opinion is slow, and largely reactive, but potent once mobilized. Leadership can truly matter, and he stresses national character and civic education. In other words, Bryce’s The American Commonwealth is a book still worth reading.
I had not known that Bryce was born in Belfast, or that he was so opposed to women’s suffrage. Or that he was so interested in Armenia, climbed Mount Ararat, and was fascinated by the inevitability of interracial marriage and its consequences (no, not in the usual racist way). He was an expert on Roman law.
Recommended, and also very well written.
Monday assorted links
Meta-analytical effect of economic inequality on well-being or mental health
Some of us have known this for some time:
Exposure to economic inequality is widely thought to erode subjective well-being and mental health, which carries important societal implications. However, existing studies face reproducibility issues, and theory suggests that inequality only affects individuals in disadvantaged contexts. Here we present a meta-analysis of 168 studies using multilevel data (11,389,871 participants from 38,335 geographical units) identified across 10 bibliographical databases (2000–2022). Contrary to popular narratives, random-effects models showed that individuals in more unequal areas do not report lower subjective well-being (standardized odds ratio (OR+0.05) = 0.979, 95% confidence interval = 0.951–1.008). Moreover, although inequality initially seemed to undermine mental health, the publication-bias-corrected association was null (OR+0.05 = 1.019; 0.990–1.049)17. Meta-analytical effects were smaller than the smallest effect of interest, and specification curve analyses confirmed these results across ≈95% of 768 alternative models. When assessing study quality and certainty of evidence using ROBINS-E and GRADE criteria, ROBINS-E rated 80% of studies at high risk of bias, and GRADE assigned greater certainty to the null effects than to the negative effects. Meta-regressions revealed that the adverse association between inequality and mental health was confined to low-income samples. Moreover, machine-learning analyses19 indicated that the association with well-being was negative in high-inflation contexts but positive in low-inflation contexts. These moderation effects were replicated using Gallup World Poll data (up to 2 million participants). These findings challenge the view that economic inequality universally harms psychological health and can inform public health policy.
That is now published in Nature, by Nicholas Sommet, et.al., via the excellent Kevin Lewis.
Popular music of 2025
Usually I wait until the year passes before dipping too deeply into these offerings, but this year I have been impressed by:
Bad Bunny, ‘DeBÍ TiRAR MáS FOToS’.
Geese, Getting Killed.
Rosalia, Lux.
Oklou, Choke Enough.
Saya Gray, Saya.
Fontaines D.C., Romance, late 2024.
Jeff Tweedy, Twilight Override.
Raye, assorted songs.
There will be more, that is my first cut at a list of interest.