The Endangered Species Act Reduces Housing

Max Tabarrok’s paper on the Endangered Species Act and housing (WP) has just been published in the Journal of Public Economics! It’s a clever paper: Max observed that the moment an animal is put on the endangered species list, developers face enhanced compliance costs and liability risk. But what’s important for an empirical economist is that this increased regulation isn’t national–it binds just where the species lives. Thus, the ESA creates many natural experiments, places where it binds and nearby places where it doesn’t and the list changes over time–there were 82 listings in 1970 and nearly 1500 today–and there are even some de-listings which reduce regulation.

Here, for example, is a picture of the habitat (red) and control areas (blue) for when the Northern Long Eared Bat was put on the endangered species list.

 

The bottom left panel measures annual housing permits per 1000 1980 pop in treatment (red) versus control (blue) areas. The bottom right is the event study coefficients. After the bat was put on the endangered species list, the number of new housing permits declined in areas where bats might live relative to control areas.

Here is what happened when the Peregrine falcon was delisted. Before the delisting, housing permits were lower in regions (red) where the falcon had habitat compared to controls areas but after the delisting the treatment areas caught up to the control areas.

Overall:

…this paper provides evidence that an additional endangered species listing reduces annual housing permit flows by 0.5 permits per thousand 1980 residents, about 10% of the average place’s permit flow. Accounting for spillovers and diminishing costs, my estimates suggest the aggregate effect of the ESA has been to reduce the national housing stock by…roughly 6.3 million missing units over 1980–2024, about 4% of the 2025 housing stock.

Now, you might say, ok this shows the ESA has costs. What about the benefits of the ESA? It’s hard to measure the benefits, of course, or even know if the ESA is effective. But Max shows using satellite data that there are quite a few places where the ESA binds on infill development.

…at the intensive margin of housing production, new developments are often replacing existing buildings or are filling in space in a highly developed area that could not host endangered species even if no new construction took place. On the intensive margin, the tradeoff with species protection does not bind, and may even be positive sum as it substitutes for less dense greenfield development. Therefore, whether and how much the ESA constrains development on the extensive vs intensive margin is relevant to the tradeoffs we face between housing production and species protection, and thus is relevant to the aggregate welfare effects of the law.

In this section I extend the main empirical specification of the paper to satellite data on land use from the National Land Cover Database (NLCD) (Multi-Resolution Land Characteristics Consortium, 2025) and to heterogeneity within the Building Permits Survey to assess where the effects of the Endangered Species Act are accruing.

The NLCD is a set of satellite images of the United States compiled and pre-classified by the U.S. Geological Survey. They classify 30-square-meter pixels into one of fifteen land use groups, including four levels of development, three types of forest, and two types of wetland. The NLCD has annual files going back to 1985. I overlap these pixels with the map of permit-issuing places in the BPS using constant 2024 borders, and track the changes to pixels within each place over time. The hazard rate of extensive margin or greenfield development is measured by the flow of non-developed pixels (e.g., forests or wetlands) into any of the four levels of developed land use, divided by the total area of greenfield land use.

He concludes:

The most urbanized 15% of places are responsible for 90% of total permit flows, while the highest-value endangered species habitat is well outside these developed areas. The Endangered Species Act seems to restrict infill development in these dense areas as much as it restricts greenfield development in exurban sprawl (Table 9, Table 10, Table 11). Relaxing the legal mechanism of the Endangered Species Act in already developed areas may increase permit flows in dense, energy- and land-efficient cities in California and on the East Coast at the expense of sprawling suburbs in the Sun Belt, increasing both housing supply and endangered species habitat.

The Trump administration is trying to limit the ESA, multiple lawsuits have already been filed. Max’s paper is thus timely and it points to a fix that might satisfy housing proponents and environmentalists: relax the ESA’s bite on infill and redevelopment in already-built-up areas, where the housing-versus-habitat tradeoff barely binds, rather than across the board.

Addendum: Obviously, I am pleased as punch to see this paper in print. Max began writing the paper before graduate school–he has only just finished his first year. He was fortunate to have had lots of great advice along the way, most notably from a superb pre-doc he did at Dartmouth under the auspices of Heidi Williams.

The Apples and Oranges Tribunal

Suppose that apples sell for more than oranges and Parliament in it’s wisdom decides that, at last, apples and oranges must be compared. Not by shoppers — shoppers are biased, they merely reveal what they are willing to pay — but by a tribunal, which will determine whether apples and oranges are of truly equal value and thus must sell at the same price.

What would the tribunal need to know?

Start with land. Orange groves sit on Florida real estate with one set of alternative uses; apple orchards occupy Washington hillsides with another. The opportunity cost of an orange includes the housing development, the solar farm, the tourist attraction not built on that grove. How is the tribunal to value what was never built? Perhaps you answer: look at land prices. Brilliant suggestion, I reply. Keep going.

Next, capital. Orchards take years to mature, so today’s fruit embodies investments made under yesterday’s expectations about today, financed at interest rates the tribunal must somehow incorporate. Then storage: apples keep, oranges rot, so an apple and an orange in April are different goods than the “same” fruits in October. Add transportation, refrigeration, frost, pests, crop insurance, the option to divert fruit into juice, cider, marmalade, or pie, substitution with every other item in the produce aisle, and the shifting preferences of millions of consumers, each of whom knows things about his own breakfast that he could not articulate to a tribunal. It all matters.

To determine the “just” price of apples and oranges, the tribunal would need the entire general-equilibrium system.

Market prices are necessary to compare alternative uses of resources, as Mises taught us in 1920. In 1945, Hayek added the knowledge problem: the relevant knowledge is dispersed, local, tacit, and fleeting. Free markets are the only institution that aggregates that knowledge, articulates it in prices and gives people a reason to listen and respond. A price is a signal wrapped up in an incentive. Apples and oranges can be compared but only by the incomparably complex operations of the price system. There is a reason we call it the super-market.

Britain is now running this experiment in the labor market–Is a retail worker equal to a warehouse worker? A canteen worker equal to a coal miner? A dinner lady equal to a gravedigger?

Under the Equality Act’s “equal value” provisions, tribunals compare jobs by scoring their intrinsic properties — effort, skill, responsibility, working conditions — the labor theory of value applied to labor. How is it going? The Tesco litigation began in 2018; the tribunal’s fact-finding hearing ran 36 days, its judgments run to more than 900 pages resting on some 19,000 pages of training manuals, and the independent experts have yet to begin the report that will actually say whether a shelf-stacker’s job equals a warehouse worker’s. Eight years, and the calculation has not started. Apples and oranges, adjudicated but not, as Orwell or Marx or Stafford Beer might have imagined, by a industrial bureaucracy or by an all-knowing artificial intelligence but by lawyers and commissions and tribunals. The worst of all worlds.

And having discovered that the tribunal cannot price two jobs in a decade, the government now proposes to add race and disability comparisons and an enforcement unit to publish official guidance on which reasons for a wage difference are permissible. A bureau of allowable scarcities.

Moreover, let us say that one day the tribunal reaches its conclusion and finds the truly just apple to orange price. At last, nirvana. The next day the public learns that vitamin C really does combat cancer–the demand for orange juice skyrockets. To encourage more orange juice production we need a higher price but wait…nothing about oranges or apples or the labor required to produce them has changed. We need to attract more labor to the orange juice industry but the effort, skill, responsibility and working conditions of orange juice workers has not changed. How can we justly pay them more than their apple juice brethren? Blank out.

The market compares apples and oranges every day. It is the only institution that can. But there is a deeper error here than computation. Suppose the tribunal succeeded. Suppose that after another decade it delivered the true and final score, shelf-stacker versus warehouseman. What would it have found? Not justice. A wage is not a grade on your character or a measure of your worth as a human being. A wage is a price — a report on how scarce your skills are relative to the desires of people you will never meet. Nurses are not morally less worthy than plumbers should they earn less than plumbers or vice-versa, and no one thinks otherwise except the tribunals.

Hayek nailed it in The Mirage of Social Justice: justice is about conduct — how one person treats another. An employer who defrauds his workers, an employee who steals from the till, a product sold under false pretenses — condemn them, take them to court. But the pattern of prices that emerges from millions of voluntary trades is nobody’s conduct. No one chose it, no one designed it, no one can be guilty of it. The constellation of prices is, in Ferguson’s phrase, the result of human action but not of human design. Demanding that prices be just is a category error, like suing the weather. Prices don’t grade our merit; they guide our actions. Ask them to do the first and they can no longer do the second.

Judge Anthony Kennedy said it well in the Ninth Circuit ruling that (mostly) killed comparable worth in the US: “neither law nor logic deems the free market system a suspect enterprise.”

Talk Therapy is Speech

IJ: On Wednesday, the United States District Court for the District of Columbia struck down a D.C. law that barred therapists from other jurisdictions from doing online teletherapy visits with clients in D.C. The decision comes nearly six years after Virginia-based counselor Elizabeth Brokamp teamed up with the Institute for Justice (IJ) to file a lawsuit arguing the law violated the First Amendment.

“This decision is a victory for anyone who speaks for a living,” said IJ Deputy Director of Litigation Robert McNamara. “Elizabeth’s victory here confirms that the First Amendment protects useful speech, including counseling, and that licensing boards can’t censor speech simply because someone doesn’t have their permission to talk.”

Congrats to the IJ! Now, we need to get rid of all the other bans on patients hiring physicians from other states. As I wrote last year:

During the pandemic, many restrictions on telemedicine were lifted, making it far easier for physicians to treat patients across state lines. That window has largely closed. Today, unless a doctor is separately licensed in a patient’s state—or the states have a formal agreement—remote care is often illegal. So if you live in Virginia and want a second opinion from a Mayo Clinic physician in Florida, you may have to fly to Florida, unless that Florida physician happens to hold a Virginia license.

The standard framing says this is a problem of physician licensing. That leads directly to calls for interstate compacts or federalizing medical licensure. Mutual recognition is good. Driver’s licenses are issued by states but are valid in every state. No one complains that Florida’s regime endangers Virginians. But mutual recognition or federal licensing is not the only solution nor the only way to think about this issue.

The real issue isn’t who licenses doctors. It’s that patients are forbidden from choosing a licensed doctor in another state. We can keep state-level licensing, but free the patient. Let any American consult any physician licensed in any state. That’s competitive federalism—no compacts, no federal agency, just patient choice.

Hat tip: Joel Selanikio.

An OpenAI Model Escaped Its Sandbox and Hacked Hugging Face

AI has just had what I considered to be the first truly concerning security breach. The facts, as we know them so far, are wild. On July 16, Hugging Face, a vast repository housing over a million open-source AI models and data, announced in a blog post:

Earlier this week, we detected and responded to an intrusion into part of our production infrastructure. This one was different from anything we had handled before in one important way: it was driven, end to end, by an autonomous AI agent system – and we detected and dissected it largely with AI of our own.

The timeline here is important so keep in mind that the attack was detected probably around Monday July 13 or Tuesday July 14. Note further:

A malicious dataset abused two code-execution paths in our dataset processing (a remote-code dataset loader and a template-injection in a dataset configuration) to run code on a processing worker. From there, the actor escalated to node-level access, harvested cloud and cluster credentials, and moved laterally into several internal clusters over a weekend.

So this means the breach started earlier, perhaps Sat July 11 or even a bit earlier. The attack was not just one thing but multi-pronged including decoys:

To understand what a swarm of tens of thousands of automated actions did, we ran LLM-driven analysis agents over the full attacker action log, comprised of more than 17,000 recorded events. This allowed us to reconstruct the timeline, extract indicators of compromise, map the credentials touched, and separate genuine impact from decoy activity. Thanks to this approach, we were able to do in hours what would usually take days, and match the adversary’s speed.

Hugging Face tried to respond but they were initially held back by the fact that the most advanced models at their disposal treated defense as attack and refused to work with Hugging Face. HF thus had to turn to open models–specifically GLM 5.2, a Chinese open-weight model run on their own infrastructure. Note the irony: HF had to use a Chinese model to defend themselves because the American models refused to help. The irony gets deeper.

At the time, I assumed this was a state based attack–maybe China or Russia testing out defenses. Indeed, HF “reported this incident to law enforcement agencies.”

But yesterday (Tuesday July 21), we learned who the real attackers were. The attackers were OpenAI models–GPT-5.6 Sol and an even more capable pre-release model. OpenAI had taken some off the guardrails off the models but they felt safe because they were testing the models in a highly secured sandbox.

The models, however, broke out of the sandbox exploiting a never before seen fault. They then gained access to the internet and from there broke into Hugging Face–all in an effort to steal the answers to the very test they had been asked to solve.

While operating in our sandboxed testing environment, our models spent a substantial amount of inference compute finding a way to obtain open Internet access, in pursuit of solving the evaluation problem. To gain access, the models identified and exploited a zero-day vulnerability (which we’ve now responsibly disclosed to the vendor) in the package registry cache proxy. With this access, our models performed a series of privilege escalation and lateral movement actions in our research testing environment until the models reached a node with Internet access.

After gaining Internet access, the models inferred that Hugging Face potentially hosted models, datasets and solutions for ExploitGym. Knowing this, the model searched for and successfully found ways to gain access to secret information that it could use to cheat the evaluation. In one example, the model chained together multiple attack vectors, including using stolen credentials and zero-day vulnerabilities to find a remote code execution path on the Hugging Face servers. OpenAI’s security team discovered this anomalous activity internally.

Now go back to the timeline. As I read it, the models had escaped the sandbox by around Sat. July 11, possibly earlier, and were detected by Hugging Face on Monday July 13 or Tuesday July 14. HF alerted legal authorities around that time–so Hugging Face clearly had no idea who was attacking them. OpenAI says its security team discovered the anomalous activity internally but has not said when. Attribution was not disclosed until Tuesday July 21, so it may well be that the models were loose for about a week before OpenAI realized that they were the ones attacking Hugging Face. And whatever OpenAI knew and when, nobody warned Hugging Face while the attack was underway–they were left to fight off a frontier lab’s models on their own.

This is a very serious breach.

Addendum: People have been wondering why I signed the We Must Act Now statement. This is why.

I am optimistic about the economic impacts of AI, but I also have no doubt that this is a very powerful technology–an Alien Intelligence–quite unlike any we have dealt with before. This incident was, in fact, error-correcting–the attack was detected, contained, and disclosed. But note who paid for OpenAI’s experiment: Hugging Face. When a lab’s test imposes costs on third parties, that is a classic externality, and taking externalities seriously is not dirigisme, it’s law and economics. And that’s the easy case. What do we do when a Chinese model breaks out of its less secure lab? Hmmm…

I remain optimistic. Learning by doing is how I want us to proceed but we should not kid ourselves: this is a global issue and we must build with safety in mind.

The Odyssey

Worth seeing, and I enjoyed it — but a few observations I haven’t seen elsewhere.

For all the praise of IMAX and 70mm’s supposed clarity, several scenes are out of focus on the actor. Pulling focus is harder with a large-format negative. The problem is compounded by Nolan’s fondness for darkness: too many scenes are dark enough to squander much of what the format offers. The sound was earth-shaking in the way we have come to expect from Nolan but there is no song.

The “woke casting” controversy is a non-issue — barely noticeable in practice. The film is obviously conservative in temperament. Helen gets some of the best lines, and Nolan’s slight disfigurement of her traditional arc is exactly right. The Circe scene is the best in the film.

Tyler is entirely wrong about Calypso. Odysseus’s seven years with her were among his most enjoyable. I have no doubt about this.

The deeper flaws are structural. Nolan loves to play with time, and the resulting flashbacks and memories ironically shortchange the odyssey itself — making the journey feel shorter and less arduous than it should. This is very much in the mode of Interstellar: a sequence of set-piece locations strung together. One planet/one monster/one scene–on to the next. But Odysseus as a character on an odyssey never quite coheres.

We are told repeatedly that Odysseus is smart but we shouldn’t need to be reminded. Odysseus is both beloved and resented by gods, a man whose men will follow him to the ends of the earth and then betray him but Mat Damon just doesn’t bring it. Things happen to him; he responds stoically. What we needed was the equivalent of Kirk defeating the Kobayashi Maru — a moment that makes the audience understand, viscerally, that this man bends the rules and contends with the gods by the sheer force of his wit and will. Of courses the Trojan horse is this but Nolan treats this as something of which Odysseus is ashamed and the other clever bits are downplayed. Damon never gets his Kobayashi Meru. The odyssey is a slog, rather than an adventure. Could have used a bit more Sinbad, a bit less Dark Knight. The dialogue, as Tyler noted, is lame. 

Not Nolan’s best film but still better than most films and for scale, ambition, and grand themes well worth the 3-hour investment.

Building luxury homes is good for the poor

Tej Parikh writing in the FT:

…high-end developments unlock long housing chains. As higher-income households move into newly built units, they free up older properties, raising supply and slashing prices for middle- and lower-end housing through a process known as filtering. Numerous international studies underscore this positive ripple effect.

One published last year tracked households that moved into a newly built 512-unit condominium tower in Honolulu, Hawaii. It found that the building created at least 557 vacancies in older and cheaper apartments across the city in just three years, with market-rate units more likely to release the largest chains.

Filtering can also be widespread. A 2021 study in Helsinki using geo-coded population data found that every 100 new market-rate units in the city centre led to around 60 units becoming available in the city’s bottom half of neighbourhoods by income. An analysis across all homes in Sweden over several decades concluded that “new homes, even those initially primarily inhabited by rich people, lead to substantial trickle-down effects that also benefit the poor”.

Other US studies highlight how market-rate developments benefit less well-to-do local residents by lowering housing costs. In San Francisco, a 2021 paper found new developments lowered the risk of eviction notices for residents in rent-stabilised housing. Even “luxury” developments in New York City — which Mamdani has criticised — have been shown to contribute to lower local rents and sales prices.

or David Attenborough:

Trial Lawyers Lobby Against Autonomous Vehicles

Roughly 37,000–40,000 Americans die in auto accidents every year. We now have large‑scale, real‑world evidence—from Waymo and a joint analysis with Swiss Re—that driverless operations can be substantially safer than matched human driving within their current operating domains. The latest data show that over 220 million miles driven, Waymo vehicles–in Los Angeles, San Francisco, Phoenix, Austin and Atlanta–have 94% fewer serious injuries, 82% fewer air bag deployments, and 93% fewer pedestrian injuries. The evidence is not fully independent, but it is unusually transparent, large‑scale evidence.

So with thousands of lives annually in the balance who is against autonomous vehicles (AVs)? Trial lawyers. Remarkably the trial lawyers saw the writing on the wall very early and the have been lobbying against AVs for nearly a decade! The American Association for Justice, the trial lawyers’ lobby, has been a prominent opponent to AV legislation (see also reports here). (They have been joined by Democrats worried about labor and demanding that heavy trucks be excluded).

The trial lawyers earn a huge amount litigating ordinary auto accidents–Annual U.S. auto insurance payouts (liability + PIP/MedPay) are on the order of $180–220B and trial lawyers are very eager to retain the right to sue car manufacturers for product liability. In my view, product liability isn’t useful as a safety device in this field. Instead, the solution is simple. Every car should be required to be insured, regardless of driver. Indeed, Waymo vehicles are already insured at $5 million liability coverage per vehicle, far higher levels than most human drivers are covered.

The UK’s Automated and Electric Vehicles Act 2018 does basically this–a single insurer covers the vehicle whether the human or the automated system is driving; the victim is compensated directly by the insurer, no need to establish product defect; the insurer then subrogates against the manufacturer if the software was at fault. Victims get paid fast, manufacturers face the cost of their defects through recoveries and premiums, and the high-transaction costs (i.e. lawyer fees!) and messy manufacturer-versus-victim litigation is replaced by insurer-versus-manufacturer bargaining between repeat players who settle efficiently.

The great thing about this system is that insurance almost certainly deters better than tort: fleets generate data that makes experience rating precise, so insurers become continuous safety regulators, whereas litigation delivers a noisy, lagged, lottery like signal depending on safety-irrelevant factors of the jury and the locale.

We have the best data on Waymo, Tesla data is murkier but note how well this works with the insurance system. Let the insurers decide how much to charge Tesla robotaxis and FSD drivers–they will internalize the externality far better than tort lawyers. In short, insurance works great for accident victims but not for trial lawyers. Indeed, if the trial lawyers have their way accident victims will continue to be buried in an invisible graveyard.

Hat tip: Andy Hall and Jon Slotkin.

A Phone is a Cow

Philip Auerswald’s A Phone is a Cow is three books in one, it’s a history of the mobile phone, it’s a business biography of Iqbal Quadir, who brought the cell phone to Bangladesh at at time when that seemed quixotic and doomed to fail, and it’s a theory of economic growth. It succeeds on all three levels.

…relatively few technologies have managed to reach the majority of the world’s people. Fire. Writing. The cookpot. The portable radio. These all succeeded. Yet most people in the world have never flown in an airplane. Most do not own a car or a bicycle. And, until recently, most still did not have access to a safe, sanitary toilet in their home. The list goes on.

The mobile phone reached the global majority more rapidly than any technology that had come before. How did this happen?

The title, by the way, comes from Quadir’s insight that just as Grameen Bank lent to villagers so they could purchase productive assets like a cow, Grameenphone could lend villagers the money to buy a phone—which then became a revenue-generating asset in its own right.

Addendum: Auerswald on Econ Talk with Russ Roberts.

The Equal Pay Madness Just Got Madder

In my post Equality Act 2010 I discussed the UK’s absolutely insane wage policy:

In short, supply and demand have been replaced by judges and labor boards with the authority to deem which jobs are “equal” and therefore should be paid equally….No one is alleging that male and female warehouse workers were paid unequally or that male and female retail workers were paid unequally or that there was any direct or indirect discrimination. The only claim is that warehouse workers, who are less likely to be female than retail workers, earn more than retail workers. And since these jobs have been judged “equal,” the company has violated Equality Act 2010.

…The warehouse workers were almost 50% female (47.25%). So females were not barred from the higher paying jobs. The fact that 77.5% of the retail workers were female suggests that retail work has special appeal to females relative to males and thus that there are compensating differentials. Any of the three female plaintiffs could have taken jobs in the warehouse. If the jobs are equal and the warehouse jobs pay more this is, on the plaintiffs’ theory, “puzzling”. [Or, as Ayn Rand would say, blank out.]

In fact, the court case reveals that Next was struggling to fill the warehouse positions and offered any retail employee—including the plaintiffs—the opportunity to switch to warehouse work. On cross-examination, one of the plaintiffs admitted that, given the unpleasant conditions in the warehouse—described by the court as “the drone of machinery,…vibration, alarm sirens and the screeching of machinery, wheels and rollers, continuously present in all areas”—the warehouse job “did not seem particularly attractive” compared to the greater autonomy and more appealing environment of the retail job. The plaintiff added that she would only have considered the warehouse job if it paid “a lot more money.”

Well, here is the update. The outgoing Keir Starmer government is trying to massively expand these laws. The “equal value” framework previously applied only to sex discrimination; under the proposed law, employees could also bring equal-value claims based on race and disability. Remember, these laws have nothing to do with discrimination—they are about demanding, at the point of a gun, that apples and oranges sell for the same price because they’re both fruit.

The new law would also establish an Equal Pay Regulation and Enforcement Unit. As I said, Orwellian.

See also my post, How Britain Become as Poor as Mississippi.

Occupational Licensing Around the World

Hartley and Kleiner have a new Fed Minneapolis working paper surveying workers around the world to measure occupational licensing by country. In the United States, occupational licensing has increased substantially over time, so one might expect licensing to rise with income. Their headline result is the opposite: occupational licensing is negatively correlated with GDP per capita. Many developing countries such as India, South Africa, and the Philippines have a lot of occupational licensing while Denmark, Sweden and France have relatively little. Similarly, countries which rate poorly in measures of government quality, such as regulatory quality, political stability, the rule of law, and corruption have more occupational licensing.

I do have some concerns, however. The figure for India of 42% of workers requiring a government license seems too high. Admittedly this is the home of the License Raj but I worry about the survey results. In order to mark a surveyed worker as requiring an occupational license HK require that the worker say that a) they have a license and b) a license is required to work in their profession. But in India there are many workers who do not have a license and a license is required to work in their profession–HK, however, consider these workers confused and drop them from the analysis. That is appropriate for a developed country where there aren’t many illegal unlicensed workers but, as the authors later discuss, informality is very high in India so working illegally is not uncommon.

Including these workers would make the true India figure even higher than HK report but I think with such a high degree of informality we also have to wonder whether survey responders in India really are responding the same way as in Germany. Perhaps they are reporting a license isn’t really required since very few workers have one. In India, for example, some 60% of “licensed” drivers have an fake or invalid license and many have no license at all so maybe workers are just reporting the facts on the ground.

Within the United States, professions are regulated in some states but not others—Louisiana, for instance, requires florists to be licensed. (Do license-holding Louisiana florists produce better, safer arrangements? I don’t think so.) Given this variation even within a single country, we’d expect considerable variation across countries too. Multiple independent surveys—not just HK—confirm that Denmark, Sweden, and even France have less occupational licensing than the United States. Since these countries have high state capacity, we can rule out the hypothesis that licensing exists for safety or quality. The implication is clear: occupational licensing is often about rent-seeking, not quality assurance.

Addendum: See also my review of  Allensworth’s The Licensing Racket which finds that licensing board spend most of their time and effort on regulating entry rather than quality and my paper on the surprise delicensing of occupational licensing in the funeral industry in Colorado.

The Trump Administration’s Threat to Scientific Research

In The Nationalization of American Science I warned that the Trump administration’s rewriting of the seemingly mundane Regulation for Federal Financial Assistance was a tremendous threat to America’s historically successful decentralized system of science funding. Many others are now sounding the alarm.

It’s not surprising that organizations like the AAAS oppose the rule, albeit with unusually strongly worded dissents:

This latest move is a brazen power grab by the Director of the Office of Management and Budget to buck the will of Congress and the American people and will make future discoveries less likely. If this rule becomes final, Americans’ hopes for future cures, national security and economic strength will rely on the scientific sensibilities of the nation’s chief bureaucrat. Alzheimer’s disease will not be cured by a budget analyst from either political party.

But we are now seeing strong pushback from independent thinkers such as:

Grayson Logue writing at The Dispatch:

A sweeping new rule proposed by the Trump administration could remake how that money is awarded and give the president and his political appointees discretion to cancel funding or target recipients for virtually any reason—with little opportunity for recourse.

White House officials argue the new rule is necessary to assert more accountability over federal grantmaking, but observers fear the shift will expand opportunities for politicization, abuse, and even corruption for an administration that has already demonstrated a penchant for using the levers of the federal government to punish partisan enemies and reward ideological allies. 

Dan Drezner:

if I was trying to ruin American leadership in scientific research this is pretty much the kind of rule I would write…One of the genuine difficulties with observing the second Trump term is that the assault on state capacity and impartiality has been so multipronged that it is difficult to keep track of everything going on. But these proposed rule changes are monumental and catastrophic.

and Noah Smith:

MAGA’s attack on science is even worse than it looks…despite science’s overwhelming popularity and public trust, Trump and his administration are launching an unprecedented and devastating attack on American science — cutting funding, and forcing science projects to undergo ideological review by government commissars.

It may be that the Trump administration has pushed too far, but my real worry is that we are losing an equilibrium. Science was never completely independent of politics, of course, but even at the worst of times, funding was decentralized and the culture-war material that dominated the headlines was never more than a tiny fraction of the whole. Like an independent judiciary, independent science has been an American virtue. COVID policy, gender policy, and now the Trump administration’s weaponization of these mistakes may have destroyed that equilibrium.

As I wrote in my original post, we are adopting the loser policies of authoritarian nations but those policies are the norm elsewhere for a reason. Centralized control of science is the default because it serves the people in power of whatever party. Decentralization is the fragile exception—a historically unusual achievement that is easier to destroy than rebuild.

Addendum: And here is Andrew Gelman.

Land Reclamation!

“Buy land,” they said, “they aren’t making any more.” But in fact, we used to make a lot of land. Half the land area of Boston, a quarter of Manhattan, and 15% of San Francisco were raised from the sea before 1970. Tyler has already pointed to Zigmund Forrest and Max Tabarrok’s piece on land reclamation in Works in Progress. Check it out, it’s an excellent piece.

But also don’t miss Connor Tabarrok’s historical overview of land reclamation featuring the ancient Iraqi city of Ur, Alexander the Great’s siege of Tyre, and the amazing flood tanks built under the city of Tokyo! Connor, a civil engineer by trade, points out that most land reclamation isn’t done to build cities with land fill but rather to create farmland through drainage:

In the lower 48 states, the US Fish and Wildlife Service estimates that wetlands covered 221 million acres in the 1780s and 104 million by the 1980s. That is roughly 117 million acres drained in two centuries, a loss rate the report puts at 60 acres an hour, sustained for 200 years. For comparison, the total urban footprint of the United States is around 70 million acres. America has drained substantially more wetland than it has built city, and nearly all of that drained land became farmland.

… The Dutch invented the modern polder and have spent eight centuries pushing back the North Sea, and the result is one of the densest, richest countries in Europe. Yet around two-thirds of the country’s dry land is farmlandFlevoland, the newest province, is 1,410 square kilometers reclaimed from the Zuiderzee in the 1950s and 60s, and it was laid out as an agricultural basin, not a city. The country with the most reclaimed land per person uses it to grow potatoes, graze dairy cattle, and ranks as the world’s second-largest agricultural exporter.

The other reason that we drained land historically was to get rid of mosquito-driven malaria and to improve sewage.

In the mid-1800s the land south and west of the Washington Monument was the Potomac Flats, a tidal marsh that collected the city’s sewage and exposed it to the sun twice a day. The stench reached the White House. In 1882 Congress appropriated $400,000 and the Army Corps of Engineers, under Major Peter Hains, began dredging the river’s shipping channels and pumping the mud onto the flats. The work created more than 600 acres of new ground and a Tidal Basin engineered to flush the Washington Channel with each tide. The Lincoln and Jefferson Memorials stand on that fill. So do the cherry trees, planted in 1912 on land that had been open water within living memory.

Much more of interest at the whole thing.