Cyprus and multiple state sovereignties
I am struck by how many layers of sovereignty there are in Cyprus, sometimes but not always conflicting. There is Greek Cyprus, Turkish Cyprus (the Turkish interpretation), Republic of Cyprus under Turkish occupation (the Greek interpretation), unified Cyprus (recognized by the EU and also many Cypriot citizens, though the Turkish part is exempt from EU laws and obligations, in any case not recognized by Turkey), the EU, and last but not least Britain claims and possesses, as full sovereign, three percent of Cyprus territory, an arrangement contested by no one.
Arguably you could add “Turkey” to that list. The Turkish government does not claim sovereignty over any part of Cyprus, but they put the flag everywhere, they guarantee defense, the currency is the Turkish lira, and they have a de facto veto over major decisions. It is Turkey in everything but name, though there is a passport check when visitors fly in from Istanbul. Keep in mind that the earlier 1974 Turkish invasion deprived what is now Greek Cyprus of its then main cargo port and main airport.
While matters have been peaceful for some while now, I fear these political arrangements limit the ability of Cyprus to exploit scale. The island has only about 1.3 million people, so complications do not help their ability to attract high-productivity investment.
Is the AI sector currently a bubble?
Possibly, but do not jump to that conclusion too quickly, as I argued in my latest Free Press column. Excerpt:
Nvidia is often considered a bellwether AI stock. That’s because much of its revenue comes from selling graphics processing units to power advanced AI systems, meaning that its success gives investors insight into the health of the sector overall. Currently, Nvidia’s stock-price-to-earnings ratio is in the 54 to 55 range, roughly twice the typical market average. That means the market expects great things from this stock. Those projections may or may not be validated, but it’s hard to conclude they’re entirely divorced from reality…
Keep in mind that the tech sector as a whole is still earning more than it is shelling out in capital expenditures. The current AI boom is being financed by earnings more than by new issuance of debt, which makes it less prone to a sudden crash. By one estimate, capital expenditures in Big Tech are about 94 percent of cash flow in 2025. You could imagine that number moving into unstable territory, but so far, the U.S. tech sector is managing to pay its bills without going into debt.
You may recall we are coming off a period when everyone complained that the big tech companies were sitting on trillions of dollars in cash and capital. Now, they are spending it, and complaints are heating up once again. Damned if they do, damned if they don’t.
In fact, what we are seeing right now is a shortage in the AI sector’s capacity to meet demand. Major tech companies are investing in more computing capacity, but they still cannot serve all the customers who want access to AI systems. That augurs well for the future of the sector, even if there are dips and spills along the way.
As usual, we will see, but if you are calling it a bubble after an initial price dip or corporate shake-out, that is exactly the fallacy you are not supposed to be slipping into.
Tuesday assorted links
1. “Underrated reason for this [relative non-politicization] being true is not that econ has more political diversity (though it does) but instead a more *international* faculty than humanities and other social sciences. Like literally 2/3rd. Domestic politics and identity fights necessarily play a smaller role.” From Kevin A. Bryan.
3. Ruxandra on IVF (NYT).
4. And more from Gavin Leech, this time on Chinese AI models.
5. Has there been upward genetic drift for the British?
6. New J.S: Bach music discovered and now recorded. Starts at 15:30. Decent but not great.
The MR Podcast: Tariffs!
On The Marginal Revolution Podcast this week, Tyler and I discuss tariffs! Here’s one bit:
COWEN: I have a new best argument against tariffs. It’s very soft. I think it’s hard to prove, but it might actually be the very best argument against tariffs.
TABARROK: All right, let’s hear it.
COWEN: If you think about COVID policy, the wealthy nations did a bunch of things. Some of them were quite bad, and the poorer nations all copied that. They didn’t have to copy it, but there was some kind of contagion effect, or that seemed like the high-status thing to do. I believe with tariffs, something similar goes on. There’s a huge literature about retaliation. Of course, retaliation is a cost, that’s bad, but simply the copying effect that it was high status for the wealthy nations to have tariffs. They can afford it better, but then places like India had their own version of the same thing. That was just terrible for India at a much higher human cost than, say, it was for the United States. Again, it’s hard to trace or prove, but that I think could actually be the best argument against tariffs, simply that poorer countries will copy what the high-status nations are doing.
This is like Rob Henderson’s idea of luxury beliefs, beliefs which the elite can proffer at low cost but which have negative consequences when adopted by working and lower classes. Tariffs aren’t great for the US but the US is so large and rich we can handle it but if the idea is adopted by poorer nations it will be much worse for them. I wish I had been clever enough to say this during the podcast but I never know what Tyler will say in advance.
Here’s another bit:
TABARROK: Here’s the question which the Trumpers or other people never really answer is, what are we going to have less of? Yes, we’ll have more investment. Let’s say we get another auto plant. The unemployment rate is 4%, so it’s not like we have a lot of free resources around. Most of the time, we’re in full equilibrium. If we have more auto plant workers and more cars being produced in the United States, we’re going to have less of something. I think it is incumbent on people who want tariffs in order to get more employment in manufacturing or something like that to say, “Well, what are we going to have less of?”
COWEN: The more sophisticated ones of them, I think, would say, well, the US is super high on the consumption scale, even relative to our very high per capita incomes. If we end up spending some of that consumption on boosting real wages, it’s actually a good investment, if only in political sanity, stability, fewer opioid deaths. It’s a very indirect chain of reasoning. I would say I’m skeptical. Again, it’s not a crazy argument. It’s a weird kind of industrial policy where you channel resources away from consumption into investment and higher wages. A lot of those plants are automated. They’re going to be automated much yet. It’s further stuff, maybe to other robotics companies or the AI companies. Again, I think that’s what they would say.
TABARROK: I don’t think they would say that.
COWEN: No, the more sophisticated ones.
TABARROK: Are there? I haven’t seen too many of those….
Here’s the episode. Subscribe now to take a small step toward a much better world: Apple Podcasts | Spotify | YouTube.
Comparing health outcomes across countries (from the comments)
I think it has come up repeatedly on MR that comparing international statistics in health outcomes is nearly impossible — definitions of live-birth, infant mortality, maternal mortality, cancer survival, cause of death, etc etc are simply too different between countries. Patterns of driving behavior, military service and violence affect life expectancy independently of health care, as do patterns of immigration.
The US tends to compare quite well on life-expectancy in later life, which is the point at which quality of health care (rather than e.g. traffic accidents) is a key factor in survival.
That is from Marie. I take this understanding, and most of all its absence, as one of the key markers of whether a person is actually trying to think things through.
Do (human) readers prefer AI writers?
It seems so, do read through the whole abstract:
The use of copyrighted books for training AI models has led to numerous lawsuits from authors concerned about AI’s ability to generate derivative content. Yet it’s unclear whether these models can generate high quality literary text while emulating authors’ styles/voices. To answer this we conducted a preregistered study comparing MFA-trained expert writers with three frontier AI models: ChatGPT, Claude, and Gemini in writing up to 450 word excerpts emulating 50 awardwinning authors’ (including Nobel laureates, Booker Prize winners, and young emerging National Book Award finalists) diverse styles. In blind pairwise evaluations by 159 representative expert (MFA-trained writers from top U.S. writing programs) and lay readers (recruited via Prolific), AI-generated text from in-context prompting was strongly disfavored by experts for both stylistic fidelity (odds ratio [OR]=0.16, p < 10^-8) and writing quality (OR=0.13, p< 10^-7) but showed mixed results with lay readers. However, fine-tuning ChatGPT on individual author’s complete works completely reversed these findings: experts now favored AI-generated text for stylistic fidelity (OR=8.16, p < 10^-13) and writing quality (OR=1.87, p=0.010), with lay readers showing similar shifts. These effects are robust under cluster-robust inference and generalize across authors and styles in author-level heterogeneity analyses. The fine-tuned outputs were rarely flagged as AI-generated (3% rate versus 97% for incontext prompting) by state-of-the-art AI detectors. Mediation analysis reveals this reversal occurs because fine-tuning eliminates detectable AI stylistic quirks (e.g., cliché density) that penalize incontext outputs, altering the relationship between AI detectability and reader preference. While we do not account for additional costs of human effort required to transform raw AI output into cohesive, publishable novel length prose, the median fine-tuning and inference cost of $81 per author represents a dramatic 99.7% reduction compared to typical professional writer compensation. Author-specific fine-tuning thus enables non-verbatim AI writing that readers prefer to expert human writing, thereby providing empirical evidence directly relevant to copyright’s fourth fair-use factor, the “effect upon the potential market or value” of the source works.
That is from a new paper by Tuhin Chakrabarty, Jane C. Ginsburg, and Paramveer Dhillon. For the pointer I thank the excellent Kevin Lewis. I recall an earlier piece showing that LLMs also prefer LLM outputs?
John Cochrane understands the elasticity of supply
Everyone is focused on building, but “supply” is so much more than building. There is tremendous supply in using more efficiently what we have now. Most cities have laws against renting parts of single family homes, or sharing larger homes. Think how many spare bedrooms are empty every night. There is plenty of housing supply in the US, it’s just not in places where people want to move. Others moving out is “supply,” and greatly impeded. Older people stay in too-big houses and apartments, in locations close to work and school opportunities that young families desire, but the older people no longer need. Why? If they sell, they are taxed on capital gains, even just due to inflation. They lose property tax exemptions, and, of course, rent control protection. Each older person who cashes in, downsizes, or moves to a more neighborhood more suited to them, supplies a house or apartment. The non-portable fixed rate 30 year mortgage, an invention of our federal housing subsidy regime, leads people to stay where they are rather than move to where they want to go, and free up a scarce house or condo for someone else. Strong apparently “consumer protection” laws in rental contracts dry up the supply, especially to the marginalized. If you can’t kick people out, you’re much more careful who you let in. Limits on short term rentals limit rentals. Remove rent controls, permanently, and houses and condos can be rented. Many houses and apartments need rehab, not new construction, which can happen very quickly once owners know they will not be robbed of their investment. Even “affordable” housing leads people to stay where they are, rather than move to better opportunities for them and free up an apartment for someone else, because it’s rationed with long waiting lists.
The rest of the post is an excellent analysis of rent control. On one of John’s closing points, I should note I am not opposed to speculating about motivations.
Monday assorted links
1. Andrej: “Software 1.0 easily automates what you can specify. Software 2.0 easily automates what you can verify.”
2. Transgenerational Epigenetic Inheritance.
3. “The national [cow] herd is now the smallest since the 1950s.” (FT)
4. California housing remains stalled.
Illegal Immigrants Didn’t Break the Housing Market; Bad Policy Did
In an interview, JD Vance claimed:
[H]ousing is way too expensive….because we flooded the country with 30 million illegal immigrants who were taking houses that ought by right go to American citizens.
I noted on Twitter that this framing reeks of socialist thinking, national socialist to be precise. A demand for the state to designate a privileged class that get special rights to scarce goods. Treating housing as a fixed stock to be allocated to a favored in-group while blaming an out-group for shortages is collectivist politics driven by grievance, not market reasoning. In short, grievance and entitlement, zero-sum thinking and central planning wrapped into one ugly bundle.
That criticism set people off. The first rebuttal was predictable “Ha ha, the economist forgot about supply and demand!”—a miss, because my point wasn’t about the mechanics of house-price growth but about Vance’s rhetoric: the collectivism and the cheap politics of blaming outsiders. The second rebuttal was that “America belongs to Americans” so of course illegal immigrants shouldn’t be allowed to buy homes.
The second objection is amusing because who is harmed most when a government bans immigrants from buying homes or deports a chunk of potential buyers? American home sellers. The way such bans “work” is by preventing sellers from accepting the highest bid. In effect, these policies are a tax on sellers combined with a subsidy to a subset of buyers.
So bans on foreign buyers are really about taxing some Americans and subsidizing others. Moreover, although the economic logic of illegals pushing up demand is sound, the numbers don’t add up to much. First, there aren’t 30 million illegals; the best estimates are roughly 14 million. And second illegals are obviously not the reason homes blow past a million dollars in places like San Francisco, San Jose, Washington, or New York! The effect of illegal immigrant on house prices exists but is small—the bigger factors are native population growth, rising incomes, zoning rules, and strict limits on new construction. Block illegal immigrants from buying homes and you will get a pause in price growth, but once demand from natives keeps rising against a capped supply, prices will climb back to where they were.
That gets to the deeper problem with Vance’s style of thinking. If “fixing” housing scarcity means blaming whichever group is politically convenient, you end up cycling through targets: illegal immigrants first, then legal immigrants (as Canada has done), then the children of immigrants, then wealthy buyers, then racial or religious minorities. Indeed, one wonders if the blame is the goal.
If you actually want to solve the problem of housing scarcity, stop the scapegoating and start supporting the disliked people who are actually working to reduce scarcity: the developers. Loosen zoning and cut the rules that choke what can be built. Redirect political energy away from trying to demolish imagined enemies and instead build, baby, build.
Wise Words Addendum (hat tip G. Scott Shand):
There is a cultural movement in the white working class to blame problems on society or the government, and that movement gains adherents by the day….We’ll get fired for tardiness, or for stealing merchandise and selling it on eBay, or for having a customer complain about the smell of alcohol on our breath, or for taking five thirty-minute restroom breaks per shift. We talk about the value of hard work but tell ourselves that the reason we’re not working is some perceived unfairness: Obama shut down the coal mines, or all the jobs went to the Chinese. These are the lies we tell ourselves to solve the cognitive dissonance—the broken connection between the world we see and the values we preach.
There is no great stagnation (not any more — really!)
A remote-controlled robot the size of a grain of sand can swim through blood vessels to deliver drugs before dissolving into the body. The technology could allow doctors to administer small amounts of drugs to specific sites, avoiding the toxic side effects of body-wide therapies.
…The system has yet to be trialled in people, but it shows promise because it works in a roughly human-sized body, and because all its components have already been shown to be biocompatible, says Bradley Nelson, a mechanical engineer at Swiss Federal Institute of Technology (ETH) in Zurich, who co-led the work.
We will see, but it is wonderful that such an idea is even in the running. Here is the full article, via A.J.
“May I meet you?”
Bill Ackman suggests that opener as a way for men to meet women, and notes it worked for him when he was younger and unmarried. Like this: “I would ask: “May I meet you?” before engaging further in a conversation. I almost never got a No. It inevitably enabled the opportunity for a further conversation. I met a lot of really interesting people this way. I think the combination of proper grammar and politeness was the key to its effectiveness. You might give it a try.”
In response, a bunch of people have shrieked that he is a billionaire (he was not then, though perhaps he had Aristotelian billionaire potentiality?), that he is six foot three (he probably was tall back then too), and that he is good looking. Or perhaps effective meeting and dating strategies have changed?
I readily admit I am well below average in this and all related areas concerning either meeting strangers or chatting up women, whether it concerns knowledge or praxis. But I have an opinion nonetheless.
I observe that so many young men these days just do not make much effort at all. They do not approach women with any sort of opening line, whether in person or through apps. If this gets them off the zero point, it is almost certainly a good thing. Maybe it is bad tactics for some people, if only because you are too nerdy and cannot deliver the words with the right charming tone. So be it. The young men with that problem can then adjust and try it some other way. It is still a plus to get them thinking about opening lines at all, and to think about meeting women at all. So I am fully on board with Bill’s suggestion. He never said that is all you should be doing, or to make that your main thing. It is unlikely that his suggestion is the best thing you could be doing, think of it simply as pressing the “activation button” on seeking a partner.
It is a bit like my advice on writing. Your big enemy is not “I did not get enough written today.” Rather it is “I did not write today at all.” That point applies to so many different aspects of life. Discrete choice econometrics!
Addendum: Bill adds that it works better when you are moving. Let’s avoid this equilibrium. And here are some other comments, I am not sure of the proper attribution.
Sunday assorted links
1. Julia Steinberg on Solano County.
2. Mentorship advice from Avital Balwit.
3. Orcas are attacking boats in coordinated fashion. And more.
4. James Brown, Night Train, live.
6. Why don’t people return their shopping carts? (Often I am not sure it is my obligation to? In that context non-return might be Coasean.)
7. From Eliezer.
Why are US Clinical Trials so Expensive?
Dave Ricks, CEO of Eli Lilly, speaking on the excellent Cheeky Pint Podcast (hosted by John Collison, sometimes joined by Patrick as in this episode) had the clearest discussion of why US clinical trial costs are so expensive that I have read.
One point is obvious once you hear it: Sponsors must provide high-end care to trial participants–thus because U.S. health care is expensive, US clinical trials are expensive. Clinical trial costs are lower in other countries because health care costs are lower in other countries but a surprising consequence is that it’s also easier to recruit patients in other countries because sponsors can offer them care that’s clearly better than what they normally receive. In the US, baseline care is already so good, at least at major hospital centers where you want to run clinical trials, that it’s more difficult to recruit patients. Add in IRB friction and other recruitment problems, and U.S. trial costs climb fast.
Patrick
I looked at the numbers. So, apparently the median clinical trial enrollee now costs $40,000. The median US wage is $60,000, so we’re talking two thirds. Why and why couldn’t it be a 10th or a hundredth of what it is?David (00:10:50):
Yeah, brilliant question and one we’ve spent a lot of time working on…“Why does a trial cost so much?” Well, we’re taking the sickest slice of the healthcare system that are costing the most. And we’re ingesting them. We’re taking them out of the healthcare system and putting them in a clinical trial. Typically we pay for all care. So we are literally running the healthcare system for those individuals and that is in some ways for control, because you want to have the best standard of care so your experiment is properly conducted and it’s not just left to the whims of hundreds of individual doctors and people in Ireland versus the US getting different background therapies. So you standardize that, that costs money because sort of leveling up a lot of things, but then also in some ways you’re paying a premium to both get the treating physicians and have great care to get the patient. We don’t offer them remuneration, but they get great care and inducement to be in the study because you’re subjecting yourself quite often, not all the case, but to something other than the standard of care, either placebo or this. Or, in more specialized care, often it’s standard care plus X where X could actually be doing harm, not good. So people have to go into that in a blinded way and I guess the consideration is you’ll get the best care.Patrick (00:12:51):
Of the $40,000. How much of that should I look at as inducement and encouragement for the patient and how much should I look at it as the cost of doing things given the regulatory apparatus that exists?David (00:13:02):
The patient part is the level up part and I would say 20, 30% of the cost of studies typically would be this. So you’re buying the best standard of care, you’re not getting something less. That’s medicine costs, you’re getting more testing, you’re getting more visits, and then there is a premium that goes to institutions, not usually to the physician, the institution to pay for the time of everybody involved in it plus something. We read a lot about it in the NIH cuts, the 60% Harvard markup or whatever. There’s something like that in all clinical trials too. Overhead coverage, whatnot. But it’s paying for things that aren’t in the trial.Patrick (00:13:40):
US healthcare is famously the most expensive in the world. Yes. Do you run trials outside the US?David (00:13:44):
Yeah, actually most. I mean we want to actually do more in the US. This is a problem I think for our country. Take cancer care where you think, okay, what’s the one thing the US system’s really good at? If I had cancer, I’d come to the US, that’s definitely true. But only 4% of patients who have cancer in the US are in clinical trials. Whereas in Spain and Australia it’s over 25%.And some of that is because they’ve optimized the system so it’s easier to run and then enroll, which I’d like to get to, people in the trials. But some of it is also that the background of care isn’t as good. So that level up inducement is better for the patient and the physician. Here, the standard’s pretty good, so people are like, “Do I want to do something where there’s extra visits and travel time?” There’s another problem in the US which is, we have really good standards of care but also quite different performing systems and we often want to place our trials in the best performing systems that are famous, like MD Anderson or the Brigham. And those are the most congested with trials and therefore they’re the slowest and most expensive. So there’s a bit of a competition for place that goes on as well.
But overall, I would say in our diabetes and cardiovascular trials, many, many more patients are in our trials outside the US than in and that really shouldn’t be other than cost of the system. And to some degree the tuning of the system, like I mentioned with Spain and Australia toward doing more clinical trials. For instance, here in the US, everywhere you get ethics clearance, we call it IRB. The US has a decentralized system, so you have to go to every system you’re doing a study in. Some countries like Australia have a single system, so you just have one stop and then the whole country is available to recruit those types of things.
Patrick (00:15:31):
You said you want to talk about enrollment?David (00:15:32):
Yeah, yeah. It’s fascinating. So drug development time in the industry is about 10 years in the clinic, a little less right now. We’re running a little less than seven at Lilly, so that’s the optimization I spoke about. But actually, half of that seven is we have a protocol open, that means it’s an experiment we want to run. We have sites trained, they’re waiting for patients to walk in their door and to propose, “Would you like to be in the study?” But we don’t have enough people in the study. So you’re in the serial process, diffuse serial process, waiting for people to show up. You think, “Wow, that seems like we could do better than that. If Taylor Swift can sell at a concert in a few seconds, why can’t I fill an Alzheimer’s study? There seem to be lots of patients.” But that’s healthcare. It’s very tough. We’ve done some interesting things recently to work around that. One thing that’s an idea that partially works now is culling existing databases and contacting patients.Patrick (00:16:27):
Proactive outreach.
See also Chertman and Teslo at IFP who have a lot of excellent material on clinical trial abundance.
Lots of other interesting material in this episode including how Eli Lilly Direct—driven largely by Zepbound—has quickly become a huge pharmacy. The direct-to-consumer model it represents could be highly productive as more drugs for preventing disease are developed. I am not as anti-PBM as Ricks and almost everyone in the industry are but I will leave that for another day.
Here is the Cheeky Pint Podcast main page.
Best fiction of 2025
Solvej Balle, On the Calculation of Volume I, Volume II. Volume III is due out in English late this year I have read it already in German. A very strong series, reading ahead in German is a good demonstration of how much I like them.
Suat Dervis, The Prisoner of Ankara. A Turkish novel from mid-century, in English for the first time.
Emmanuel Carrere, V13: Chronicle of a Trial. Non-fiction but it is more likely reading fiction, it just happens to be true (supposedly).
Alain Mabanckou, Dealing with the Dead. Most African fiction does not connect with me, and there is a tendency for the reviews to be untrustworthy. This “cemetery memoir,” from the Congo (via UCLA), held my interest throughout.
Kiran Desai, The Loneliness of Sonia and Sunny.
Eça de Queiros, Adam and Eve in Paradise. Originally from the 19th century, but translated into English only this year. A 60 pp. novella about exactly what the title indicates, noting that matters are not as simple as the first telling of that story might have suggested.
The Poems of Seamus Heaney. Not yet received, but obviously this is a winner.
Overall, the Balle, Desai, and Heaney make for very strong entries, so this was a good year for fiction.
Emergent Ventures winners 48th cohort
Minh Nguyen, Dallas, 16, to address problems of space debris.
Serena Chen and Valerie Wu, Taipei and Los Angeles, better blood transportation.
Griffin Li, Boston, 19, general career support, issues in market pricing on apps.
Jamie Croucher, London, for a new scientific society, Society for Technological Advancement.
Sri Anumakonda, Carnegie Mellon, robotic hands.
Ben James, London, lowering the price of electricity.
Lucio Aurelio Moreira Menezes, Fortaleza and Stanford, computational biology.
Lauren Gilbert, London, a progress-oriented magazine for the developing world?
Annika Baberwal, Dubai, 8th grade, helping race cars run faster.
Bernardo Melotti, Bologna/Stanford, equipment to speed biological advances.
Elyas Sepahi, London, mathematics and machine learning.
Harishvin Sasikumar, Vancouver, 17, brain interfaces.