Category: Economics
Predictions for economics, given AI
With math essentially being delegated to OpenAI, here’s what I predict for economics and the social sciences more generally:
The top tier of research will just become better and it will be normal human-led research where AI is used for scale (e.g. conducting qualitative interviews with relevant populations, running behavioral interventions in the field, analyzing massive text data, etc.)
Field experiments will rise in value and generally making “connections” with firms and being able to run stuff (potentially testing AI pipelines) will be in high demand
Research with administrative data will become even more valuable, but the benefits might be concentrated among some prolific authors who are allowed by the government agencies to use local models to analyze the data at scale. PhD students can probably forget about it
Economic history will have a very exciting boom and there will be an enormous race and big rewards for digitizing archives as a source to both identify new research strategies and document new descriptive facts.
Review and verification systems will become massively improved with AI assistance and it will become standard practice to do a 360 review of the paper + code + data at the *submission* stage.
Research that in principle can already be almost completely outsourced to the AI (download and analyze public data, run simple survey experiments, write theory models) is in for a big shock. This would be very bad from the perspective of researchers who depend on this “bread and butter” research, but I think this type of work will just be outsourced to public agencies who can answer their own questions without the need for “peer-reviewed” research.
All of those make sense to me.
Against Laissez-Faire Democracy
In a new paper, Brennan and Freiman argue persuasively that:
the arguments against laissez-faire capitalism apply in a rather straight way against laissez-faire democracy. This should be a rather startling result, considering that laissez-faire capitalism is widely rejected, yet laissez-faire democracy is widely accepted.
All the typical market failure arguments–externalities, asymmetric information, principal-agent problems, behavioral issues–apply to democracy. For example:
democracies also suffer from obvious externality problems. Indeed, this is the key difference between markets and politics. Market decisions are usually and mostly internalized; negative externalities are seen as an anomaly to be corrected. Political decisions are by nature public. For instance, about 37% of the eligible
voting public, and 26% of the entire population of the UK voted in favour of Brexit, but the effects of Brexit are borne by everyone else, including losing voters, eligible voters who abstained, children and other citizens ineligible to vote, future generations, and foreigners.…The problem is similar to the pollution of individual automobile drivers or airline passengers. We drive too much and pollute too much because we bear the benefits of these actions but pass the costs onto others. Individually we matter little but collectively we matter a great deal. If externality regulation is prima facie justified in the case of pollution, it is prima facie justified in the case of voting.
They go on to suggest regulations that might apply to democracy. Noting first that:
…pretty much everyone already accepts some government actions which are plausibly seen as vote or democratic regulation. For instance, some issues are put directly to voters, while others are left to elected leaders, while others are left to judges and bureaucracies, and still others are removed from political consideration entirely. The timing and place of elections, who is permitted to vote (at what age), who is permitted to run for office, and so on are kinds of regulation. Government funding of public education is in part meant to be a non-laissez-faire subsidy meant to increase voter competence. Many readers are likely comfortable with government regulation of campaign donations, campaign expenditures and even which kinds of speech are permitted. Probably almost all readers reject straight up markets in votes (Freiman 2014). Each of these things is a kind of government regulation of democracy which inhibits laissez-faire democracy.
The authors sketch possible regulations while stipulating, for the sake of argument, universal, equal suffrage—no weighted votes or knowledge tests for voting eligibility. Possibilities include paying citizens to pass a voluntary civics exam; tracking campaign promises and fining deceptive claims; regulating political advertisements more like drug advertisements; and requiring supermajorities for certain decisions. See the paper for more.
You may object that these regulations would be captured by special interests, be administered by biased officials, or have unintended consequences. Indeed, welcome to the argument for laissez-faire.
Texas-Canada Fact of the Day
Texas produces more than Canada with three quarters of the population. Rough numbers for 2025:
| Texas | Canada | Texas / Canada | |
|---|---|---|---|
| Population | 31.7 million | 41.7 million | 0.76 |
| GDP, nominal (US$) | $2.9 trillion | $2.3 trillion | 1.27 |
| GDP per capita, nominal | $91,500 | $55,700 | 1.64 |
| GDP per capita, PPP | $94,000 | $66,700 | 1.41 |
| GDP, PPP (int’l $) | $3.0 trillion | $2.75 trillion | 1.09 |
Sources: BEA (Texas GDP, preliminary 2025; regional price parity), Census Bureau (Texas population), World Bank and IMF (Canada). Texas PPP figures divide nominal GDP by the BEA regional price parity.
Hat tip: Chris Powers.
The Great Accretion and the Great Depression
A very old idea, returning with a vengeance:
The Second Industrial Revolution sparked a wave of new products and industrial processes, fueling an optimistic Roaring Twenties. But did excitement about technological progress contribute to an over accumulation of investment, despite a slowdown in new product development and satiated demand during the 1920s? And, was this over investment worsened by continuous process innovation? Could these factors have played a role in triggering the Great Depression? To explore these questions, a macroeconomic model that incorporates both process and product innovation is proposed. Proof-of-concept simulations are performed to assess whether these factors can help explain the Great Depression. The answer is yes.
That is from a recent NBER working paper by
Rising concentration for economics awards
We analyze the academic affiliations of nearly 6,000 award-winning researchers in 18 major fields in the natural sciences, engineering, and social sciences from the 1820s to the 2020s, focusing on the 1960s onward. The analysis reveals a trend of declining concentration in the institutional affiliations of award-winning researchers, shifting from a few science-strong universities in high-income countries to a more diverse set of institutions across the world. The decline in concentration is observed in all fields except one: economics. The institutional affiliations of prizewinning economists have become more concentrated over time, making economics the most concentrated field. We associate the higher concentration of prizewinning work in economics with the field’s stronger sorting by institutional prestige, its lower reliance on specialized equipment and instruments, and its assessment of findings based on a synthesis of evidence rather than on decisive experiments or proofs. We discuss the benefits and costs of this high and rising institutional concentration of prizewinning economists.
Here is more from
The Greg Clark Symposium
Earlier I wrote “Greg Clark may well be the most important social scientist of the 21st century.” Thus, the symposium in Econ Journal Watch on Clark’s new but perhaps not forthcoming book is very welcome. The symposium includes serious critics, most notably Stuhler and Benning, but I suspect even the critics would agree with Arden and Plomin who write:
We agree wholeheartedly with Clark’s overall message that genetics accounts for outcomes long assumed to be due to nurture. Like other books in his trilogy, Clark marshals evidence from diverse sources to support his argument.
The data reach in this book—1600–2026—is jaw-dropping. Clark (and his colleague Neil Cummins) turned to wedding-register marks, probate courts, Huguenot wills, Oxbridge matriculation rolls, Sandhurst cadet lists, Wedgwood servants, and the Guild of One-Name Studies, to name a few. These data are imaginative, arresting, and inspiring. The analyses conducted, given the manifest complexities of harmonising across data types, time, and place, are impressive.
…This audacious scholarly book properly lights a fire under important questions. We look forward to following the work, its critics, and its rebuttals. It’s a terrific scientific contribution; because it is so thoroughly interdisciplinary, it will enrich and enliven the conversation about social status, its causes, and malleability.
One thing I am struck with from the critics (not just those in the symposium) is that most acknowledge that twin and adoption studies have badly undermined the claim that parental investments are big determinants of adult ability and earnings. The critics are correct that more elaborate environmental models can reproduce genetic-looking correlations but keeping an environmental explanation alive is not the same as vindicating the explanation people originally believed. Clark and many others have pushed the debate far into new territory.
There is also a basic asymmetry between the competing explanations. Genetics supplies independently established inheritance rules. When an environmental model reproduces the same patterns by choosing transmission rules precisely because they mimic genetic inheritance, it is accommodating the evidence, not independently predicting it. True, Clark also requires some free parameter choices, but he is clear that these can and need to be independently estimated.
The kinds of parental effects being demonstrated also matter. The nurture effects the environmentalists point to often seem to be for optional, steerable, or transferable choices than for more fundamental abilities, that is, changing what a child chooses to do with a given set of abilities, versus changing those abilities. Parents, for example, have more influence over religious identification than over religiosity, more influence over wealth than income, more influence over educational attainment than IQ.
The genetic arguments in the book draw the most criticism and yet the book has much else offer as Clark notes. For example:
Social status is inherited as strongly as height. Even relatives as distant as nine generations apart, 270 years, still show significant correlation in social status.
That is a very striking finding–especially given the intervening industrial revolution, multiple wars, huge changes in social mores etc.–but if it stands, it does so independent of the genetic explanation.
The fact that this monumental and challenging book–right or wrong–cannot find a major academic publisher is an intellectual scandal. The editors at Princeton University Press and the University of Chicago Press should be ashamed.
Addendum: See previous MR posts on Clark including Tyler’s Conversation.
China fact of the day
With surrogacy illegal in China, an industry of agencies, consultants and fertility clinics has emerged to connect clients with women overseas willing to carry their children. While there is no data on the number of children born to Chinese parents via surrogacy, a recent study showed nearly a third of intended parents for surrogate babies in the US were international and some 40 per cent of those were from China.
Early demand largely came from couples struggling with fertility. But there was growing interest from younger women physically capable of becoming pregnant but reluctant to accept its impact on their bodies and careers, said consultants, clients and doctors interviewed by the FT…
Other destinations include Georgia and Kyrgyzstan, where packages can cost as little as $63,000.
Here is more from Eleanor Olcott at the FT.
Does Costco Cause Cancer?
In December 2025, researchers led by Yazan Alwadi at Harvard’s T.H. Chan School of Public Health published a paper in Environmental Health that claimed to find that cancer incidence increased for people living closer to nuclear power plants in Massachusetts. In March, the same researchers published an expanded nationwide study claiming a similar result—this time looking at cancer mortality rates, rather than incidence—in Nature Communications. This was followed by a paper in the Journal of Exposure Science & Environmental Epidemiology that looked at associations of lung, breast, and colon cancers. Most recently, a study of total mortality, not just cancer, was published in the European journal Environmental Epidemiology.
The problem? Using the same methods pretty much everything causes cancer. An amazing takedown from Deric Tilson and Adam Stein:
For instance, living near a private four-year university is associated with a 15-fold increase in cancer mortality when compared to living near a nuclear power plant.
Costco has the largest effect of all the locations we have tested. Over 2.2 million cancer deaths can be attributed to Costco; that’s more than 20% of all cancer deaths between 2000 and 2018. Hot dogs, bulk spices, and reasonably priced clothes come with a cost.
What went wrong?
[The authors] chose nuclear power plants because a story could be built around that framework. When the researchers got positive results across our nation’s nuclear power plants, they didn’t check what their shiny new methodology would do using other landmarks. This is their pitfall: by taking the easy way out—getting results and making up a story around those results without double-checking their method—the authors could have no idea that what they were actually capturing was the methodology itself.
…The attributable number of deaths from this methodology is probably zero, but the attributable number of bad papers is at least four.
Words to live by?
In the past year American markets have digested the largest-ever initial public offering (SpaceX), equity raise by a public company (Google) or a foreign firm (SK Hynix), private-funding round (OpenAI) and private-debt deal (Broadcom), as well as most of the biggest bond issue in history (Amazon). There was the first $1trn exchange-traded fund, or ETF (Vanguard), a record-breaking cash pile (Berkshire Hathaway) and stock-buyback programme (Nvidia), and the consummation of the largest-ever leveraged buyout (Electronic Arts). Then there are the enormous mergers in railways (Union Pacific and Norfolk Southern), utilities (NextEra and Dominion Energy) and media (Paramount and Warner Bros Discovery)—the last of which led, this week, to the largest ever junk-bond offering, beating a record set only last week (SoftBank). New markets have been created out of thin air (for compute) or become much bigger (for predictions). Worries about massive corporate scandals (First Brands) and hedge-fund blow-ups (Situational Awareness), which would have once occupied investors’ attention for months, are steamrollered by the relentless, totalising and extraordinarily flexible machine that is American finance.”
An excellent passage, from The Economist.
New issue of Econ Journal Watch
Volume 23, Issue 2, September 2026
In this issue:
“China shock” fragility: According to David Autor, David Dorn, and Gordon Hanson (2013), the “China shock” hit the United States from 1990 to 2007. When corrections by Kirill Borusyak et al. (2022) are fully applied, Joseph Francis argues, the harm of Chinese imports to unemployment, labor force participation, wages, and household incomes disappear. “China shock,” Francis argues, illustrates how the “credibility revolution” very much leaves the con in econometrics. (The commented-on authors are hereby invited to reply in a future issue.)
The predictions did not come true: A June 2023 decision, SFFA v. Harvard, held that race-based admissions are unconstitutional. Thirty-three selective colleges forecast Black enrollment declines of 50 to 70 percent. Fifteen research universities assured the Court that race-neutral admissions “would undercut” the diversity they seek. David Card estimated that eliminating racial preferences would cut the Black share of Harvard’s admitted class from 14 percent to 6 percent. Three years on, David Kane reports that the predictions did not come anywhere close to true.
Science confections: Following up on his critique of Jonathan Pekar et al. in Science, Michael Weissman now criticizes Michael Worobey et al. in Science, who claim that case locations and nucleic acid samples showed that SARS-CoV-2 had first been introduced to humans at the Huanan Seafood Market. Several lines of evidence suggest the introduction to humans was earlier and elsewhere. (The commented-on authors are hereby invited to reply in a future issue.)
The fall of Fama-French and momentum factors: Commenting on Clifford Asness, Eugene Fama, and Kenneth French, Michael O’Connor argues that momentum’s circa-2003 demise and that of market capitalization and the book-to-market ratio about a decade later represent a structural break or ‘regime change.’ (The commented-on authors are hereby invited to reply in a future issue.)
All in the family: Kenneth Judd and Karl Schmedders take issue with an article in Journal of Economic Literature by Jesús Fernández-Villaverde. They say that he overstates the newness of neural-network or “deep learning” solvers and that such solvers should be understood as inside the family of projection and weighted-residual solvers. (The commented-on author is hereby invited to reply in a future issue.)
Is chatbot validation valid? Alexis Akira Toda reports on Gemini, Refine, Claude, and ChatGPT on errors in four published papers in mathematical economics. The chatbots generated false positives—endorsing flawed proofs—and varied in how much guidance they needed to find the error. ChatGPT Pro performed best, Claude was middling, and Gemini worst. Corrections of the original errors had already been published at the time of the experiment, and so a chatbot’s success might reflect its canvassing for published commentary. Since the chatbots generated false positives, however, we know that they are fallible one way or another.
How are so-called digital public goods provided? The United Nations and its Digital Public Goods Alliance have constructed an ambitious framework for certifying, funding, and deploying open-source software in developing countries. The soundness of the UN’s approach is, according to Vidar Andre Utvik and coauthors, illustrated by the rapid development of Covid-19 surveillance tools in Sri Lanka and Norway. Here, John Levendis argues that their own evidence reveals that local professionals cooperated voluntarily and that community innovation preceded WHO guidance, not the reverse. (The commented-on authors are hereby invited to reply in a future issue.)
On Haavelmo’s adoption of Neyman-Pearson theory: Trygve Haavelmo’s (1944) monograph “The Probability Approach in Econometrics” is based on a strict adoption of Neyman-Pearson testing theory. Here, Tom Engsted argues that Haavelmo resorted to the notion of a hypothetical infinite population and a distinctly non-frequentist (Bayesian-like) interpretation of probability with the aim of inductive inference, in direct contradiction with Neyman-Pearson theory.
1939–1945: Housing policy in Denmark: In a critique of the primary literature on the subject, Jens Hansen explains the origins of Danish rent control and other housing regulation. The interventions have wrought great hardship and no discernible benefits. The history exemplifies the intervention dynamic.
Where credit is due: Alexis Akira Toda reports on some curious failures to cite predecessors and brings credit to the slighted authors and papers. (The commented-on authors are hereby invited to reply in a future issue.)
Greening on the edge: An article models sustainable product development under crowdfunding and regulation. Here, Marco Sorge argues that the authors disregard corner solutions for environmental quality, which robustly arise across admissible parameter configurations, and conduct comparative statics where no interior solution exists. A complete characterization of the equilibrium corrects, and in some cases contradicts, their conclusions. (The commented-on authors are hereby invited to reply in a future issue.)
Book-manuscript symposium:
Gregory Clark on genetics and social mobility
The third book in Clark’s trilogy is titled To Have and Have Not: The Determinants of Social Status in England, 1600-2026:
- The book manuscript that commenters received.
- Leaders in genetics and social mobility comment:
- Gregory Clark’s reply to commenters.
- Symposium webpage
EJW Audio:
Supply is elastic, installment #1637
For taxes too:
Using administrative data from Scandinavian countries, we provide evidence on international migration responses to wealth taxes and evaluate their aggregate economic implications. We find significant migration responses among the wealthy: A 1 percentage point increase in the top wealth tax rate decreases the stock of wealthy taxpayers by about 2 percent. A large fraction of the wealthy are business owners, and their businesses are negatively affected by owner out-migration. The aggregate effects are nevertheless modest: The migration responses to a 1 percentage point increase in the top wealth tax rate reduce employment by 0.02 percent, investments by 0.07 percent, and value added by 0.10 percent.
That is by Katrine Jakobsen, Henrik Kleven, Jonas Kolsrud, Camille Landais and Mathilde Munoz, in the latest issue of the AER.
My excellent Conversation with Luis Garicano
Here is the audio, video, and transcript. Here is part of the episode summary:
Tyler and Luis start their conversation with Spain — housing, NIMBYism, and the productivity crisis; Spanish literature and why the Civil War still looms so large; and what Chicago taught Luis about party discipline in European politics. Then to the EU’s unanimity problem, capital markets, and Denmark’s flexicurity model; a round of overrated-versus-underrated on Rosalía, Penélope Cruz, and Sgt. Pepper’s; and finally into Messy Jobs — why retraining programs fail, whether AI’s leisure dividend has arrived, and whether Spain could ever achieve AI sovereignty.
Excerpt:
COWEN: Why is there a current productivity crisis in Spain?
GARICANO: Productivity indeed hasn’t grown for three decades, more or less. We’re currently having extensive growth. We’re having immigration, we’re having tourism, but we don’t really have productivity. A lot of it has to do with the political economy. I think if you want to explain the West, not just Spain, you have to understand who is voting and who is this being governed for. Spain is a particularly low-fertility, high life-expectancy country. We have the fifth-lowest fertility and the fifth-highest life expectancy in the world grosso modo, and very high pensions.
Essentially, all the GDP growth we’ve had has gone, 100 percent of the GDP growth we’ve had since 2008 has gone to pensions, to the pensioners. In terms of investment, there is very little in terms of productive investment. We have this fantastic highway network and this high-speed rail network. It’s not really getting the maintenance it needs. Just as one example, the country is basically being governed by and for the older retired people.
COWEN: What does the optimistic scenario look like? You don’t have to predict it’s going to happen, but lay out for me how it could all go well. You would get productivity growth of 1.5 percent a year, and economic growth a bit higher than that.
GARICANO: Spain has amazing fundamentals for the current situation, meaning we could easily be very electricity-energy rich due to solar, wind, and nuclear. We have all this empty space where you could put nuclear plants without much resistance. In fact, we are closing them for political reasons. The energy could be a big advantage. It’s a really amazing place to live. There is no more diverse geography and climate and nature anywhere in Europe, I think, or close to, and beautiful. You could easily see a situation where Spain becomes Florida, or Austin, Texas. Think of Texas. It attracts technology, attracts talent who wants to live there, attracts energy, builds the data centers, et cetera. That scenario is not impossible. The political economy is the tricky part.
COWEN: Doesn’t that mean you actually don’t have good fundamentals? You said you don’t even have a YIMBY movement. Life there really is quite good. I’ve been many times. It’s one of my favorite countries to visit. Isn’t that like a resource curse where there’s no sense of crisis? Old people live for a long time. It’s very comfortable. The weather’s great. The food is amazing. Aren’t those, in fact, liabilities in a time of very rapid change?
And another, on a very different topic:
COWEN: On Messy Jobs, your new and excellent book, you argue very persuasively, “In my view, AI will not lead to anything like mass unemployment, maybe not even to a rise in unemployment, because jobs will become messier and the AIs won’t be able to do them.” Is that a fair description of part of your argument?
GARICANO: I think that’s completely right. Yes.
COWEN: Now, I agree with you, but I think my worry is the opposite, that I know a lot of people, they want simple jobs, they’re okay with some measure of tedium, and that if most jobs become messy jobs, for them, that’s quite stressful, and they’re upset and disoriented. Do you worry about that?
GARICANO: I think that we will have to have a tolerance for human relations. Is that what your friends don’t want? We have a tolerance for relational work that is complex, that has politics in it, that has a big human component, and that’s the part that is going to stay. If people just want to be in their desk typing away, I think two good ways to think about it is work from home and outsourcing. If you think of which jobs were offshored, let me say offshored, in the big offshoring wave to India, those are jobs that are not messy. They’re clean. The company specifies the jobs. They say, “Okay, we can specify this job perfectly. Let’s ship you up.”
Those jobs are the same exact ones that are under complete threat of disruption. A lot of the work from home, when it doesn’t involve a lot of submittings, I guess, has the same feature. Those jobs are clean, single-task, and very often verifiable. You can just see how the performance is going and have your RL, your reinforcement learning loop work on those. I think those are gone.
The messy component that I want to emphasize, many people will say, “Oh, AI will tend to the messiness as well.” I think that there is some messiness that is contingent and that AI can streamline, but there is a lot of messiness that is both relational and has to do with a deeper aspect of the knowledge problem that doesn’t really go away. As AI advances, many aspects of Hayek, Polanyi, and all these knowledge problems are still there.
COWEN: How much retraining will be required and how frequent will that retraining have to be? If I think of me working with agents, I have to retrain myself every month or two. That’s difficult for me. It’s not stressful given my position, but I can imagine it would be stressful. Can we really just put a big chunk of the labor force through that?
Definitely recommended.
Alvin Roth to the rescue, the polity that is Singapore
Singapore has launched a dating platform, the latest social-engineering experiment by the city-state’s government to tackle its fast-declining fertility rate.
The initiative, known as FirstDate, opened under a pilot scheme this month for public sector employees aged 21-35 and uses a Nobel Economics Prize-winning matchmaking algorithm. An additional tool suggests date activities and allows users — who receive only one match at a time — to rate their experience in a survey.
The platform is the product of the annual hackathon held by the Singapore government’s technology agency earlier this year.
“FirstDate started with a question among a group of GovTech officers: does having more potential matches necessarily make it easier to find a suitable match?” the website said.
The app, which joins a crowded field of dating apps as well as more bespoke matchmaking services, is Singapore’s latest effort to reverse its falling birth rate, which has made the city-state one of the world’s fastest-ageing countries.
Here is more from Owen Walker at the FT.
The top private sector employers of economics graduates
Here is the link.
Trump Administration Limits Predatory Lending in Education
The New Republic writes “President Trump is banning students majoring in degrees that don’t make enough money from taking out college loans.” Yes, but do note that no student is banned from any major and the lending rule is mild. Undergraduate programs must show:
that their graduates earn more than the typical high school diploma holder…[and] graduate programs will be required to demonstrate that their graduates earn more than the typical bachelor’s degree holder. (emphasis added).
Think about how low that bar is. The comparison group for an undergraduate program is working adults aged 25-34 with nothing more than a high school diploma. A college program that can’t beat that has almost certainly made its students worse off. For graduate programs the bar is the lowest of several bachelor’s benchmarks, including bachelor’s holders in the same field. A master’s in social work need only beat people with a bachelor’s in social work. A program must also fail in two out of three years before it loses loan eligibility. The Department estimates that about 5% of programs will fail in the first year.
I mocked the term “predatory lending” when it first became common in the financial crisis but in this case predatory lending fits the bill because the real borrower isn’t the individual student. Under income-driven repayment, the taxpayer is a forced co-signer, and it’s the taxpayer who gets predated.
Most expansions of the student loan program have been motivated by the picture of an enterprising student who works hard and wants to major in mechanical engineering or nursing but because of their poor circumstances they can’t afford college. “Credit constraints, asymmetric information, you can’t collateralize human capital,” said the economists. Nice theory, what’s the practice?
The economists wanted loans for good investments and insurance against bad luck but the economists can’t swing the vote and once the government is lending, colleges want more tuition money and students want more forgiveness. The result is a subsidy for programs whose graduates are never likely to repay. As Looney and Yannelis document:
Starting in the late 1990s, policymakers weakened regulations that had constrained institutions from enrolling aid-dependent students. This led to rising enrollment of relatively disadvantaged students, but primarily at poor-performing, low-value institutions whose students systematically failed to complete a degree, struggled to repay their loans, defaulted at high rates, and foundered in the job market. As these new borrowers experienced similarly poor outcomes, their loans piled up, loan performance deteriorated, and with it the finances of the federal program.
Indeed, the program worked in reverse of what was promised. The biggest subsidies went to programs whose graduates were least able to repay, rather than programs with the strongest case for public support. As I wrote earlier:
Looney does a back of the envelope calculation and estimates that typical graduates in Mechanical Engineering will on average get a 0% subsidy but graduates in Music will get a 96% subsidy, in Drama a 99% subsidy and Masseuses a 100% subsidy on average. This of course is exactly the wrong approach. If we are going to subsidize, we should subsidize degrees with plausible positive spillovers not masseuses.
The courts later blocked Biden’s Save plan but the problem is built into income-driven repayment. If music, drama and masseuses are promised a 95%+ subsidy who is paying? The taxpayers. Moreover, it’s even worse than this because the very existence of these loans incentivizes the creation of expensive, useless programs. It’s not just the drama colleges, however. Not surprisingly, the law schools have proven adept at using Public Service Loan Forgiveness (PSLF) to rip off the taxpayer. The school raises tuition, then covers the student’s small income-driven payments for ten years, and the taxpayer forgives the rest. In short, protecting students from the cost of failure rewards colleges for producing it.
Fortunately, the same bill limiting loans ended Grad PLUS loans and capped graduate borrowing. You can see the logic: if taxpayers are going to insure the loans, they need some say over which programs qualify and how much is borrowed. I don’t like giving government that power, but this is the Mises–Higgs intervention ratchet in action: subsidize the loans, absorb the losses, then regulate the programs to limit the losses.
My ideal program would get the government out of the student loan business altogether but until then this is a good first step at limiting one of the most expensive and wasteful programs of the federal government.