Category: Economics
What should I ask Luis Garicano?
Yes I will be doing a Conversation with him. From Wikipedia:
Luis Garicano Gabilondo (pronounced [ˈlwis ɣaɾiˈkano]; born 1967) is a Spanish economist and politician who was a Member of the European Parliament (MEP) from 2019 to 2022. He was also vice president of Renew Europe and vice president of the European political party Alliance of Liberals and Democrats for Europe (ALDE Party). Before entering politics, he was a professor of strategy and economics at IE Business School in Madrid and at the London School of Economics (LSE). After leaving the European Parliament he has returned to academia as a visiting professor at Columbia Business School and at the University of Chicago Booth School of Business. In 2023, returned to LSE as full professor at the School of Public Policy.
He is one of the leading European economic liberals, here is his home page. Here is his Google scholar page. Here is Luis on Twitter. he also has a very good book coming out called Messy Jobs, co-authored with Jim Li and Yanhui Wu. So what should I ask him?
The small business boom
Across the country, founders like Ms. Winkler are powering an entrepreneurial renaissance.
Jump-started by the pandemic, when a confluence of factors including mass layoffs and remote work led to a flood of business creation, and supercharged by the rise of artificial intelligence, start-up activity is booming after a decades-long slump.
Americans filed 5.7 million applications last year to start new businesses, according to the Census Bureau, the most in the two decades the government has kept track. New business applications through the first half of this year continued to climb…
More recently, there are signals that A.I. is adding fuel.
A recent paper from economists at the University of British Columbia and the Stockholm School of Economics found that generative A.I. was “spurring entrepreneurial activity” in the United States, both by giving rise to new ventures built around the technology and by making it cheaper to start enterprises.
“A.I. tools can do very many different things very well,” said Jan Bena, an associate professor at the University of British Columbia and one of the study’s authors. “That’s the reason why you see so much entry.”
According to a recent report from Gusto, a small-business payroll and benefits service, nearly 60 percent of founders on its platform who started businesses last year said they used A.I., and half said the technology made it cheaper and faster.
Here is more from Sydney Ember at the NYT. Via Josef.
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.
Governing agentic AI
From a new paper by Shruti Rajagopalan:
AI agents now transact, publish, and act on external systems without contemporaneous human approval, creating new regulatory challenges. A growing literature has responded with proposals for legal personhood. This Article argues that personhood is neither necessary nor sufficient, shifting the question from status to enforcement. The Article first shows that for two millennia, nonhuman legal personality, from the Roman universitas to the corporation, the Hindu idol, the waqf, and the river, has operated through human officeholders the law can locate, question, prosecute, and replace. Agentic AI inverts that design, exercising practical agency without legal status, sometimes with no identifiable human in the responsibility-bearing role. The Article then sorts deployments into three categories: first, where one firm builds and deploys the agent; second, where the developer and deployer are separate but known; and third, where there is no identifiable developer or deployer. The Article stress tests each agent deployment category against five liability doctrines: agency law, products liability, enterprise liability, negligence, and strict liability. It demonstrates that each fails at different points in the third category for the same reason: the absent responsibility-bearer. Bare personhood would supply a caption without a representative, assets, or a mechanism for cessation. Finally, the Article assembles an alternative from regimes governing aircraft, ships, drones, driverless cars, and motor carriers. It develops a six-layer stack—registration, identification, verification, financial responsibility, lifecycle traceability, and suspension—so a responsibility-bearer can be identified, liability imposed, and the activity suspended. These layers place the human back at the end of the chain.
I would say that social science now has new frontiers, let us hope it blossoms in response.
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.
Spreading AI to the rest of the world
Another job we’ll have, I call this imperialism, but I mean that in a value neutral way. But AI comes to different parts of the world at different speeds. I think the countries where AI changes a lot of things first, there’ll be a very high demand for people from those places, which I’ll think to be the US, possibly UK, to go around the rest of the world and teach people in other places how to integrate AI into what we have. And a lot of those demands won’t be fully rational. They won’t be, oh, give us the best possible AI. They’ll be like, oh, we’re Peruvians. We want to keep things a certain way. You may or may not agree, but we want you to give us a version of AI that helps keep it that way. And that will be the job. And I think Americans in particular, probably Brits as well, huge growth sector will be living in other parts of the world spreading AI. And again, the fact that AI can do it better may or may not be true, but I don’t think it’s what will matter. I think the Peruvians or some analogue will want humans to come and listen to their concerns and assure and persuade them as humans, that’s what they’re going to get. I’m not saying it’s always going to go well, but that will always be, I think, a big job for humans to do.
It’s already a growth sector for Americans to want to live abroad. Like we have all this accumulated wealth. Life in America can be a bit dull. Life in Europe in particular is amazing. Personally, I love life in most parts of Latin America. So it’s already a trend for Americans to live overseas. For another reason, it’s nothing to do with AI. So if there are all these future job opportunities, like full of meaning, like come to Kenya, help Kenya, you can save 73 lives or maybe like 73,000 lives, help them build out their AI in a way that’s acceptable to them. That’ll just be this phenomenally rich inner and outer life. And I think it’ll be a great source of job creation.
I have already linked to the transcript of the talk.
My GOAT book now has updated software/AI
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.
Persistent Inequality in Publishing in Economics
This paper documents new facts about concentration in publishing in economics. First, the profession grows downward . The number of economists grew almost sixfold since 1990, but new entrants publish in lower-tier journals while incumbents hold the top. Second, there is high and persistent concentration at the top. Along with the downward growth, the top-1% authors accounted for 38.4% of top-5 publication credit in 1990 and for 78.3% in 2025. Third, the persistence is widespread within cohorts, within subfields, and within gender. Fourth, new journals only slightly dilute concentration. Fifth, elite authors diversify on topics faster than the rest of the profession. We interpret the findings with a screening model of attention under information overload. The evidence is consistent with the model: as the field grows, citations concentrate on established work and the conditional citation premium of top-author papers narrows.
By Ricardo Dahis, via the excellent Samir Varma.
*Who Thinks Like an Economist?*
That is the title of a recent book by Beatrice Magistro. Some key results are:
Economic knowledge consistently predicts higher support for welfare-enhancing policies (Eurozone membership, free trade, and EU immigration), independent on whether individuals stand to gain or lose initially from globalization. This challenges conventional self-interest accounts and instead highlights the role of economic knowledge — and potentially time preferences — in shaping globalization attitudes.
Economic knowledge also predicts a lower discount rate, even after adjusting for years of education.
I would say that over the years I have altered my perspective a bit on these issues. I used to think these factors were correlated, in large part, through a kind of wisdom. I now think that more of the effect, however much I may sympathize with it, runs through sociological expectation and perceived obligation, combined with conformity and signaling pressures.
That was then, this is now
One of the cool things about European football is that it provides good evidence that high-income, high-ability individuals move in response to tax rates…
That is from Jeremy Horpendahl, citing research by…Emanuel Saez.
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 farmland. Flevoland, 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.
Single-payer health care systems are looking worse all the time
That is the theme of my latest Free Press piece, here is one excerpt from it:
Government-run systems often (not always) do a perfectly fine job setting a broken arm or administering a long-standing, well-known medication. They do much less well when it comes to developing, financing, and delivering a new immunological approach to fighting cancer, personalized to your individual genome at a cost of hundreds of thousands of dollars. In our rapidly arriving biomedical future, innovation capacity will matter above all else. And though they may not see it today, the people with the most life ahead of them will reap nearly all of the benefits of a dynamic system, or suffer the consequences of a paralytic one.
Thirty years ago, it was often debated whether the Canadian or British healthcare systems were better than what we have in the U.S. After all, they offered a kind of guaranteed access to health services. The details could differ, but often the healthcare had no upfront price or only a low user fee. In America, in contrast, healthcare was more expensive, there were many millions of uninsured people, and dealing with sometimes rapacious insurers and hospitals could involve significant emotional trauma.
But over time the British and Canadian systems look worse and worse. The queues and rationing have increased, as giving healthcare away for free makes it hard to satisfy demands in a timely manner. In Canada, for instance, the median wait time has risen from 9.3 weeks in the early 1990s to 28.6 weeks today. In the British National Health Service, only 65.3 percent of patients start treatment within 18 weeks.
Worse yet, both of those systems are undercapitalized. In Britain, healthcare is badly understaffed and underfunded. Yet the country already has high taxes, high debt, and slow economic growth, so it is not clear where the new money will come from to recapitalize the system.
And this sentence:
This entire dynamic will be intensified as the pace of medical innovation picks up.
Your life may depend on it.
Why we stopped making land
From Zigmund Forrest and Maxwell Tabarrok in Works in Progress:
In total, around eight percent of the land in America’s major coastal cities was underwater in the 1890s and has since been reclaimed. This includes the land under several major airports, like Newark, Logan, and SFO, as well as neighborhoods like the Financial District in San Francisco, the Back Bay in Boston, and Camden in Philadelphia. Some cities, like Boston and Charleston, have doubled in size by reclaiming land.
Today, reclamation should be more common than ever. Land values in some cities are thirty times what they were in 1950, and high-tide flooding is four to eight times as frequent. Reclamation could extend and protect our coastal cities as it has for centuries. But rather than reclaim more land, we have virtually ceased to reclaim any at all. Since the completion of Battery Park City in 1976, there has not been a single major urban land reclamation project in the United States and only a handful of port expansions.
…Reclamation stopped abruptly in the 1970s when a wave of environmental regulations made it enormously expensive to reshape the landscape. And it halted at the same time in every other country that passed similar laws.
Recommended.
From Prediction Markets to Decision Markets and Beyond!
Arin Dube points to a great illustration of the power of prediction markets. Yesterday due to a new scandal the probability that Graham Platner would drop out of the Maine Democratic primary exploded from 9% to 96% (+87 percentage points). At the same time, the probability that the Democrats would win the election jumped by about 9 percentage points, from 54% to 63%. What does this tell you?
The market is signaling that Platner reduces the Democrats’ chances of victory. We can be more precise. If an 87-point increase in the probability of dropping out gets you 9 points of winning, then a 100% chance of dropping out implies a gain of 9/0.87 ≈ 10.3 percentage points.
Thus the market’s best estimate is that Platner is reducing the Democrats’ chance of winning by about 10 percentage points (compared to an unknown replacement). That’s a pretty big number! Democrats should surely use this information to make better decisions.
Now, I have been a bit loose. We have implicitly assumed that the news mainly moved the probability of Platner dropping out, rather than independently changing the Democrats’ general-election prospects. The issue is we are trying to reverse engineer two conditional prices, P(win|drop) and P(win|stay), from one unconditional price, P(win), and its comovement with P(drop). It works pretty well here as an illustration but Robin Hanson’s idea is that we can do better yet by trading the conditionals instead of inferring them.
Hanson’s decision markets would run contracts of the form “pays $1 if Democrats win, conditional on Platner dropping out — bet refunded if he stays.” Plus the mirror contract conditioned on staying. The refund provision makes the price a conditional probability: a trader pricing the first contract doesn’t need any view on whether Platner drops out, only on how the race goes if he does. With this structure we would get cleaner estimates of the conditional probabilities–in this case whether the Democrats do better with Platner in or out–which is exactly what a decision maker needs.
We were able to plausibly reverse engineer our estimate because the market happened to move 87 points in a single day. But a decision market would have posted the number continuously, no scandal required. In other words, with decision markets in play, not just prediction markets, we could have seen how much Platner was costing the Democrats before the latest scandal hit—which is precisely when the information would have been most useful.
It’s been fun to see prediction markets catch on with the public but the world is still decades behind Hanson’s decision markets—let alone futarchy!