Category: Education
UATX Is Ending Tuition Forever
Thanks to a $100 million gift from Jeff Yass — the largest donation since UATX was founded in 2021 — we’re breaking the chains. His gift marks the launch of a $300 million campaign to build a university that sets students free.
Our bet: Create graduates so exceptional they’ll pay it forward when they succeed, financing the tuition of the next generation. When our students build important companies, defend our nation, advance scientific frontiers, build families, and create works that elicit awe, they’ll remember who made their excellence possible. And they’ll give back.
Here is the full announcement.
My excellent Conversation with Sam Altman
Recorded live in Berkeley, at the Roots of Progress conference (an amazing event), here is the material with transcript, here is the episode summary:
Sam Altman makes his second appearance on the show to discuss how he’s managing OpenAI’s explosive growth, what he’s learned about hiring hardware people, what makes roon special, how far they are from an AI-driven replacement to Slack, what GPT-6 might enable for scientific research, when we’ll see entire divisions of companies run mostly by AI, what he looks for in hires to gauge their AI-resistance, how OpenAI is thinking about commerce, whether GPT-6 will write great poetry, why energy is the binding constraint to chip-building and where it’ll come from, his updated plan for how he’d revitalize St. Louis, why he’s not worried about teaching normies to use AI, what will happen to the price of healthcare and hosing, his evolving views on freedom of expression, why accidental AI persuasion worries him more than intentional takeover, the question he posed to the Dalai Lama about superintelligence, and more.
Excerpt:
COWEN: What is it about GPT-6 that makes that special to you?
ALTMAN: If GPT-3 was the first moment where you saw a glimmer of something that felt like the spiritual Turing test getting passed, GPT-5 is the first moment where you see a glimmer of AI doing new science. It’s very tiny things, but here and there someone’s posting like, “Oh, it figured this thing out,” or “Oh, it came up with this new idea,” or “Oh, it was a useful collaborator on this paper.” There is a chance that GPT-6 will be a GPT-3 to 4-like leap that happened for Turing test-like stuff for science, where 5 has these tiny glimmers and 6 can really do it.
COWEN: Let’s say I run a science lab, and I know GPT-6 is coming. What should I be doing now to prepare for that?
ALTMAN: It’s always a very hard question. Even if you know this thing is coming, if you adapt your —
COWEN: Let’s say I even had it now, right? What exactly would I do the next morning?
ALTMAN: I guess the first thing you would do is just type in the current research questions you’re struggling with, and maybe it’ll say, “Here’s an idea,” or “Run this experiment,” or “Go do this other thing.”
COWEN: If I’m thinking about restructuring an entire organization to have GPT-6 or 7 or whatever at the center of it, what is it I should be doing organizationally, rather than just having all my top people use it as add-ons to their current stock of knowledge?
ALTMAN: I’ve thought about this more for the context of companies than scientists, just because I understand that better. I think it’s a very important question. Right now, I have met some orgs that are really saying, “Okay, we’re going to adopt AI and let AI do this.” I’m very interested in this, because shame on me if OpenAI is not the first big company run by an AI CEO, right?
COWEN: Just parts of it. Not the whole thing.
ALTMAN: No, the whole thing.
COWEN: That’s very ambitious. Just the finance department, whatever.
ALTMAN: Well, but eventually it should get to the whole thing, right? So we can use this and then try to work backwards from that. I find this a very interesting thought experiment of what would have to happen for an AI CEO to be able to do a much better job of running OpenAI than me, which clearly will happen someday. How can we accelerate that? What’s in the way of that? I have found that to be a super useful thought experiment for how we design our org over time and what the other pieces and roadblocks will be. I assume someone running a science lab should try to think the same way, and they’ll come to different conclusions.
COWEN: How far off do you think it is that just, say, one division of OpenAI is 85 percent run by AIs?
ALTMAN: Any single division?
COWEN: Not a tiny, insignificant division, mostly run by the AIs.
ALTMAN: Some small single-digit number of years, not very far. When do you think I can be like, “Okay, Mr. AI CEO, you take over”?
Of course we discuss roon as well, not to mention life on the moons of Saturn…
Andrej and Dwarkesh as philosophy
If you follow AI at all, you probably do not need another recommendation of the Andrej Karpathy and Dwarkesh Patel podcast, linked to here:
I hardly ever listen to podcasts, but at almost two and a half hours I found this one worthwhile and that was at 1x (I don’t listen to podcasts at higher speed, not wanting to disrupt the drama of the personalities). What struck me is how philosophical so many aspects of the discussion were. Will this end up being the best “piece of philosophy” done this year? Probably. Neither participant of course is a trained philosopher, but neither were Plato or Kierkagaard. They are both very focused on real issues however, and new issues at that. And dialogue is hardly a disqualifying medium when it comes to philosphy.
Some guy on Twitter felt I was slighting this book in my tweet on the matter. I’ll let history judge this one, as we’ll see which issues people are still talking about fifty years from now (note I said nothing against that book in my tweet, nor against contemporary philosophy, I just said this podcast was philosophical and very good). I’ve made the point before (pre-LLM) that current academic philosophers are losing rather dramatically in the fight for intellectual influence, and perhaps more of a serious engagement with these issues would help. I’ve seen plenty of philosophical work on AI, but none of it yet seems to be interesting. For that you have to go to the practitioners and the Bay Area obsessives.
Observations on browsing economics job market candidates
The number of people on the market seems much lower this year, perhaps because of the lag with Covid, as well as more general demographic trends. Even adjusting for the lower number of candidates, I found fewer interesting papers this year than usual, as research interests continue to narrow. There is too much emphasis on showing quality technique by answering a small question well, rather than addressing more important questions more imperfectly. Harvard had by far the most interesting students, as most of them were considering questions I cared about. LSE looked pretty good too. In terms of topics, I saw a lot of papers on educational testing, urban economics and mobility, and AI. Theory seems to be permanently on the wane. The number of co-authors continues to rise.
Overall I came away with a bad feeling from this year’s perusal, noting there are some departments I have not looked at yet. In the aggregate it did not seem vital enough or exciting enough to me?
I still will be putting up some more of the papers I found of interest.
“Gender without Children”
What would the lives of women look like if they knew from an early age that they would not have children? Would they make different choices about human capital or early career investments? Would they behave differently in the marriage market? Would they fare better in the labor market? In this paper, we follow 152 women diagnosed with the Mayer-Rokitanski-Kuster-Hauser (MRKH) type I syndrome. This congenital condition, diagnosed at puberty, is characterised by the absence of the uterus in otherwise phenotypically normal 46, XX females. Using granular health registries matched with administrative data from Sweden, we confirm that MRKH is not associated with worse health, nor with differential pre-diagnosis characteristics, and that it has a large negative impact on the probability to ever live with a child. Relative to women from the general population, women with the condition have better educational outcomes, tend to marry and divorce at the same rate, but mate with older men, and hold significantly more progressive beliefs regarding gender roles. The condition has also very large positive effects on earnings and employment. Dynamics reveal that most of this positive effect emerges around the arrival of children in women in the general population, with little difference before. We also find that women with MRKH perform as well as men in the labor market in the long run. Results confirm that “child penalties” on the labor market trajectories of women are large and persistent and that they explain the bulk of the remaining gender gap.
That is from recent work by Tatiana Pazem, with co-authors Camille Landais, Peter Lundberg, Erik Plug & Johan Vikstrom. Tatiana is on the job market from LSE, with her main job market paper being “Pension Reforms and Consumption in Retirement: Evidence from French Transactions and Bank Data.”
Does economics make you more sexist?
We provide direct evidence on explicit and implicit biases against women among students in economics relative to other fields. We conducted a large scale survey among undergraduates in Chile, among both entering first-year students and students in years 2 and above, combining a wide battery of measures to create an index of gender bias. Economics students are more biased than students in other fields. There is some evidence that economics students are more biased already upon entry, before exposure to economics classes. The gap becomes more pronounced among students in years 2 and above, especially for male students.
That is from a newly published paper by Valentina Paredes, M. Daniele Paserman, and Francisco J. Pino.
*The Master of Contradictions*
The author is Morten Jensen, and the subtitle is Thomans Mann and the Making of The Magic Mountain. An excellent introduction to Mann’s tome, and it many fine discussions. Here is one excerpt:
It becomes possible, then, to read The Magic Mountain as a novel partly about the limits and failures of the more positivistic strain of nineteenth-century liberalism — a triumphalist worldview that failed to recognize or halt Europe’s drift toward nationalism, reaction, and the industrial carnage of the First World War. Settembrini, the noveläs representative of this worldview, shares its myriad flaws, beliving, for instance, that self-perfection is the ultimate goal of humankind. And like so many nineteenth-century liberal utopians, he celebrates technology as “the most dependable means by which to bring nations closer together, furthering their knowledge of one another, paving the way for people-to-people exchanges, destroying prejudices, and leading at last to the universal brotherhood of nations.
…More than just a vessel for a philosophical point of view, however, Settembrini is, or becomes, one of The Magic Mountain’s most endearing characters. One cannot help but smile a little — half with affection, half with pity — whenever he enters the stage. It’s one of the novel’s great distinctions that its central characters are never merely reducible to the philosophical worldview they represent; Settembrini, even when Mann is at his most sarcastic, is always first and foremost Settembrini, as if Mann were gradually convinced by his fictional creation as a dynamic individual rather than a static representation.
Recommended.
Emergent Ventures India, 11th cohort
Saket Sinha is an accomplished bansuri virtuoso with more than seventy students worldwide. His grant enables a move to Mumbai.
Riddhi Jain, 17, received her grant to build an AI-powered mental health system addressing unaffordable and stigmatized therapy.
Advik Kapoor, 16, received his grant for Exerton, to help builders get started with their dream projects.
Vibhuti Bafna, Aliya Mamadfozilova, Julian Drotkiewicz and Enya Dumitru are high-schoolers in four different countries. They received their grant for Waste2o, turning agricultural waste into potable water.
Ishan Khire, 18, received his grant for Rural Analytics, to make rural development data more accessible for researchers.
Nikitaa Sivaakumar received her grant to develop interactive visual aids for high school science teachers.
Jhillika Trisal (with Falguni Shrivastava and Souvik Ghosh) received her grant for building Cognitii, an AI‑plus‑human learning platform for children with special needs; the grant scales pilots and the personalization engine.
Piyush Jha, 18, founder of Vasudeva Innovations, received his grant to turn wastewater into clean energy while earning carbon credits.
Ambreen Deol is an aspiring surgeon who has rotated at Cleveland Clinic, Stanford, Mount Sinai and UAB, received her grant for travel and general career support.
Anjali Jayaraman, 14, received her grant for Repay Smart, to help young adults make smarter financial decisions using gamification.
Arjun Khemani received his grant for the Arjun Khemani Podcast, and work on his writing. His latest book Lords of the Cosmos (With Logal Chipkin) is out now.
Adwait Dandwate received his grant for Vardhishnu, to create learning spaces for children from vulnerable backgrounds.
Amruth Ravindranath is a neuroscience researcher, and received his grant to develop cognitive assessments and AI models that personalize mental health chatbots to each person’s unique cognitive fingerprint.
Shaunak Agarkhedkar is a novelist, and received his grant to write novels challenging myths about stray animals.
Kaustubh Bankapure received his grant to create an online learning model of applied theatre education for Indian educators.
Kavish Garg, 18, a sophomore studying math and philosophy at Stanford, received his grant for conference and travel support.
Ria Khurana and Tanmaya Gulati, both 22 and studying medicine, and founders of RNT Health Insights, received their grant to develop medical devices detecting early-stage gastrointestinal cancers.
Those unfamiliar with Emergent Ventures can learn more here and here. The EV India announcement is here. More about the winners of EV India second cohort, third cohort, fourth cohort, fifth cohort, sixth cohort, seventh cohort, eighth cohort, ninth cohort, and tenth cohort. To apply for EV India, use the EV application, click the “Apply Now” button and select India from the “My Project Will Affect” drop-down menu.
And here is Nabeel’s AI engine for other EV winners. Here are the other EV cohorts.
If you are interested in supporting the India tranche of Emergent Ventures, please write to me or to Shruti at [email protected].
TC again: I thank Shruti for writing this post for me.
Harvard graduate admissions
The Faculty of Arts and Sciences slashed the number of Ph.D. student admissions slots for the Science division by more than 75 percent and for the Arts & Humanities division by about 60 percent for the next two years.
The scale of reductions in the Social Science division was not immediately clear, though several departments in the division experienced decreases over the coming two years ranging from 50 percent to 70 percent.
The reductions — detailed by five faculty members and in emails obtained by The Crimson — stipulate smaller Ph.D. admissions quotas across dozens of departments. Departments were allowed to choose how they would allocate their limited slots across the next two years.
Here is the full article, via Chris Brunet.
The MR Podcast: Our Favorite Models, Session 2: The Baumol Effect
On The Marginal Revolution Podcast this week we continue discussing some of our favorite models with a whole episode on the Baumol effect (with a sideline into the Linder effect). I say our favorite models, but the Baumol Effect is not one of Tyler’s favorite models! I thought this was a funny section:
TABARROK: When you look at all of these multiple sectors, the repair sector, repairing of clothing, repairing of shoes, repairing of cars, repairing of people, it’s not an accident that these are all the same thing. Healthcare is the repairing of people. Repair services, in general, have gone up because it’s a very labor-intensive area of the economy. It’s all the same thing. That’s why I like the Baumol effect, because it explains a very wide set of phenomena.
COWEN: A lot of things are easier to repair than they used to be, just to be clear. You just buy a new one.
TABARROK: That’s my point. You just buy a new one.
COWEN: It’s so cheap to buy a new one.
TABARROK: Exactly. The new one is manufactured. That’s the whole point, is the new one takes a lot less labor. The repair is much more labor intensive than the actual production of the good. When you actually produce the good, it’s on a factory floor, and you’ve got robots, and they’re all going through da-da-da-da-da-da-da. Repair services, it’s unique.
COWEN: I think you’re not being subjectivist enough in terms of how you define the service. The service for me, if my CD player breaks, is getting a stream of music again. That is much easier now and cheaper than it used to be. If you define the service as the repair, well, okay, you’re ruling out a lot of technological progress. You can think of just diversity of sources of music as a very close substitute for this narrow vision of repair. Again, from the consumer’s point of view, productivity on “repair” has been phenomenal.
TABARROK: That is a consequence of the Baumol effect, not a denial of the Baumol effect. Because of the Baumol effect, repair becomes much more expensive over time, so people look for substitutes. Yes, we have substituted into producing new goods. It works both ways. The new goods are becoming cheaper to manufacture. We are less interested in repair. Repair is becoming more expensive. We’re more interested in the new goods. That’s a consequence of the Baumol effect.
You can’t just say, “Oh, look, we solved the repair problem by throwing things out. Now we don’t have to worry about repairs.” Yes, that’s because repair became so much more expensive. A shift in relative prices caused people to innovate. I’m not saying that innovation doesn’t happen. One of the reasons that innovation happens is because the relative price of repair services is going up.
COWEN: That’s a minor effect. It’s not the case that, oh, I started listening to YouTube because it became too expensive to repair my CD player. It might be a very modest effect. Mostly, there’s technological progress. YouTube, Spotify, and other services come along, Amazon one-day delivery, whatever else. For the thing consumers care about, which is never what Baumol wanted to talk about. He always wanted to fixate on the physical properties of the goods, like the anti-Austrian he was.
It’s just like, oh, there’s been a lot of progress. It takes the form of networks with very complex capital and labor interactions. It’s very hard to even tease out what is truly capital intensive, truly labor intensive. You see this with the AI companies, all very mixed together. That just is another way of looking at why the predictions are so hard. You can only get the prediction simple by focusing very simply on these nonsubjectivist, noneconomic, physical notions of what the good has to be.
TABARROK: I think there’s too much mood affiliation there, Tyler.
COWEN: There’s not enough Kelvin Lancaster in Baumol.
Here’s the episode. Subscribe now to take a small step toward a much better world: Apple Podcasts | Spotify | YouTube.
AI and the First Amendment
The more that outputs come from generative AI, the more the “free speech” treatment of AIs will matter, as I argue in my latest column for The Free Press. Here is one excerpt, quite separate from some of my other points:
Another problem is that many current bills, including one already passed in California, require online platforms to disclose which of their content is AI-generated, in the interest of transparency. That mandate has some good features, and in the short run it may be necessary to ease people’s fears about AI. But I am nervous about its longer-run implications.
Let’s say that most content evolves to be jointly produced by humans and AI, and not always in a way where all the lines are clear (GPT-5 did proofread this column, to look for stylistic errors, and check for possible improvements). Does all joint work have to be reported as such? If not, does a single human tweak to AI-generated material mean that no reporting is required?
And if joint work does have to be reported as joint, won’t that level of requirement inevitably soon apply to all output? Who will determine if users accurately report their role in the production of output? And do they have to keep records about this for years? The easier it becomes for individual users to use AI to edit output, the less it will suffice to impose a single, supposedly unambiguous reporting mandate on the AI provider.
I am not comfortable with the notion that the government has the legal right to probe the origin of a work that comes out under your name. In addition to their impracticality, such laws could become yet another vehicle for targeting writers, visual artists, and musicians whom the government opposes. For example, if a president doesn’t like a particular singer, he can ask her to prove that she has properly reported all AI contributions to her recordings.
I suspect this topic will not prove popular with many people. If you dislike free speech, you may oppose the new speech opportunities opened up by AIs (just build a bot and put it out there to blog, it does not have to be traceable to you). If you do like free speech, you will be uncomfortable with the much lower marginal cost of producing “license,” resulting from AI systems. Was the First Amendment really built to handle such technologies?
In my view free speech remains the best constitutional policy, but I do not expect AI systems to make it more popular as a concept. It is thus all the more important that we fight for free speech rights heading into the immediate future.
The Economics Nobel goes to Mokyr, Aghion and Howitt
The Nobel prize goes to Joel Mokyr, the economic historian of the industrial revolution and the growth theorists Phillippe Aghion and Peter Howitt best known for their Schumpeterian model of economic growth.
Here’s a good quote from Nobelist Joel Mokyr’s the Lever of Riches.
Yet the central message of this book is not unequivocally optimistic . History provides us with relatively few examples of societies that were technologically progressive. Our own world is exceptional, though not unique, in this regard. By and large, the forces opposing technological progress have been stronger than those striving for changes. The study of technological progress is therefore a study of exceptionalism, of cases in which as a result of rare circumstances, the normal tendency of societies to slide toward stasis and equilibrium was broken. The unprecedented prosperity enjoyed today by a substantial proportion of humanity stems from accidental factors to a degree greater than is commonly supposed. Moreover, technological progress is like a fragile and vulnerable plant, whose nourishing is not only dependent on the appropriate surroundings and climate, but whose life is almost always short. It is highly sensitive to the social and economic environment and can easily be arrested by relatively small external changes. If there is a lesson to be learned from the history of technology it is that Schumpeterian growth, like the other forms of economic growth, cannot and should not be taken for granted.
Aghion and Howitt’s Schumpeterian model of economic growth shares with Romer the idea that the key factors of economic growth must be modelled, growth is thus endogenous to the model (unlike Solow where growth is primarily driven by technology, an unexplained exogenous factor). In Romer’s model, however, growth is primarily horizontally driven by new varieties whereas in Aghion and Howitt growth comes from creative destruction, from new ideas, technologies and firms replacing old ideas, technologies and firms.
Thus, Aghion and Howitt’s model lends itself to micro-data on firm entry and exit of the kind pioneered by Haltiwanger and others (who Tyler and I have argued for a future Nobel). Economic growth is not just about new ideas but about how well an economy can reallocate production to the firms using the new ideas. Consider the picture below, based on data from Bartelsman, Haltiwanger, and Scarpetta. It shows the covariance of labor productivity and firm size. In the United States highly productive firms tend to be big but this is much less true in other economies. In the UK during this period (1993-2001) the covariance of productive and big is considerably less than half the rate in the United States. In Romania at this time the covariance was even negative–indicating that the big firms were among the least productive. Why? Well in Romania this as the end of the communist era when big, unproductive government run behemoths dominated the economy. As Romania moved towards markets the covariance between labor productivity and firm size increased. That is the economy became more productive as it reallocated labor from low productivity firms to high productivity firms.
Aghion and Howitt’s work centers on how new ideas emerge and how creative destruction turns those ideas into real economic change through the birth and death of firms. But creative destruction is never painless—growth requires that some firms fail and that labor be displaced so resources can flow to new, more productive uses. Aghion and Howitt will likely point to the United States as dealing with his process better than Europe. Business dynamism has declined in Europe relative to the United States, a worrying fact given that business dynamism has also declined in the United States. Nevertheless, the US has a more flexible labor market and appears more open to both the birth of new firms (venture capital) and the deaths of older firms. Yet, in both the United States and around the the world the differences between high productivity and low productivity firms appears to be growing, that is the dispersion in productivity is growing which means that the good ideas are not spreading as quickly as they once did. Aghion and Howitt’s work gives us a model for thinking about these kinds of issues–see, for example, Ten Facts on Business Dynamism and Lessons from Endogenous Growth Theory.
Claims about education and convergence
This paper studies how human capital shapes the economic geography of development. We develop a model in which the cost of acquiring human capital varies across space, and regions with higher human capital innovate more. Locations are spatially connected through migration and trade. There are localized agglomeration economies, and human-capital-augmenting technology diffuses across space. Using high-resolution data on income and schooling, we quantify and simulate the model at the 1° x 1° resolution for the entire globe. Over the span of two centuries, the model predicts strong persistence in the spatial distribution of development — unlike spatial dynamic models without human capital, which predict convergence. Proportionally lowering the cost of education in sub-Saharan Africa or Central and South Asia raises local outcomes but reduces global welfare, whereas the same policy in Latin America improves global outcomes. An alternative policy equalizing educational costs across sub-Saharan Africa generates relatively worse outcomes, as population reallocates within the region toward less productive areas. Central to these results is the estimated negative correlation between the education costs and local fundamentals, as well as inefficiencies in the spatial allocation due to externalities.
That is I think a genuinely new idea? Here is the NBER working paper from
Is the earned income tax overrated?
This policy has been so popular with economists on a bipartisan basis, yet a recent piece in ReStud raises some doubts, as the wage subsidies induce many to drop out of school:
As a complement to the federal earned income tax credit (EITC), some states offer their own EITC, typically calculated as a percentage of the federal EITC. In this paper, we analyse the effect of state EITC on education using policy discontinuities at US state borders. Our estimates reveal that an increase in the state EITC leads to a statistically significant increase in the high school dropout rate. We then use a life-cycle matching model with directed search and endogenous educational choices, search intensities, hirings, hours worked, and separations to investigate the effects of EITC on the labour market in the long run and along the transitional dynamics. We show that a tax credit targeted at low-wage (and low-skilled) workers reduces the relative return to schooling, thereby generating a powerful disincentive to pursue long-term studies. In the long run, this results in an increase in the proportion of low-skilled workers in the economy, which may have important implications for employment, productivity, and income inequality. Finally, we use the model to determine the optimal design of the EITC.
That is by One simple lesson is that policy economics is often not easy. Via the excellent Kevin Lewis.
MR Podcast: Our Favorite Models, Session 1
The Marginal Revolution Podcast is back and this time Tyler and I discuss some of our favorite models or ways of thinking about the world. We begin with Spence on Monopolies, Harberger on Incidence and Solow on Growth. Here’s one bit:
TABARROK: You have an increase in the corporate tax. What happens?
COWEN: One lesson of the Harberger model is actually anything can happen. Who bears the burden? Is it capital, is it labor, or is it consumers? In the simplest versions of the model, what you have is both a substitution, capital versus labor in the taxed sector, and you have substitutions across sectors. You have a whole series of different effects. One of the first and simplest lessons from Harberger, which is really neat, but people just hadn’t gotten it before, is if you tax the corporate sector under a lot of reasonably general assumptions, the rate of return on capital goes down equally in both sectors, which to us is standard fare.
What will happen is capital flows out of the corporate sector into the noncorporate sector, that lowers the marginal rate of return on capital in the nontaxed sector, and simply the notion of capital can suffer in both sectors. Again, a revelation, maybe self-evident to us having written this principles textbook, but it shocked people. The partial equilibrium models never show that.
TABARROK: When you tax the corporations, you’re also taxing the mom-and-pops.
COWEN: And the nonprofits and whatever, wherever else the capital might flow.
TABARROK: Yes. This was one of the first useful applications of general equilibrium.
COWEN: That’s right. On that, it’s really held up. International affairs, one of the lessons is if you turn the other sector or add another sector that’s international, basically small economies cannot afford to tax capital at very high rates because so much of the capital will flow elsewhere.
TABARROK: Instead of it flowing to the noncorporate sector, it just flows out of the country.
COWEN: That’s right, which is like the other sector not affected by this particular tax. In 1962, a lot of small economies treated their capital very badly. Many still do, but there’s been a real revolution where even fairly statist economies—like the Nordics over time shifted to treating capital income pretty generously. Singapore would be another example. Again, it’s simple once you know it, but the Harberger model taught us that.
TABARROK: What about the labor margin?
COWEN: The debate since then has been how much of the tax is borne by capital and how much is borne by labor? On one hand, the Harberger model teaches you anything can happen. That’s useful intuitively. In fact, when you investigate it empirically, it’s what you would expect to happen that mostly happens. That is, capital does bear more of the tax than labor.
TABARROK: Labor bears a chunk.
COWEN: Yes. A typical estimate might be a third. There’s no free lunch from the point of view of labor. Furthermore, a lot of the capital is owned by labor through pension funds. If you take that into account, I don’t have an exact number for you, but I think it’s plausible to think labor might bear half the burden of the corporate tax. Again, you can show that pretty simply. The estimates are not exact, but just a big advance for economics. If you ask me, what ideas do I use all the time, that’s one of them.
The Harberger basic model, it doesn’t have land, but there’s the issue of what if you have three factors in the model, you would start with the Harberger model. If you’re a NIMBY who thinks there’s this kind of land monopoly in a city or land rents are very high because we stifle building, the incidence of a lot of taxes, even in general equilibrium models, can fall on the land for a city.
TABARROK: Yes, because the land can’t escape.
COWEN: That’s right.
TABARROK: As we say in the textbook, elasticity is equal to escape, right?
Here’s the episode. Subscribe now to take a small step toward a much better world: Apple Podcasts | Spotify | YouTube.