Category: Education
My first students
To continue with some biography…
My first full-time teaching job was at UC Irvine in 1988, a school with very good undergraduate students, including in economics. I was fortunate enough to be assigned Honors Intermediate Micro for my very first class.
(My general view is that the second time I teach a given class is the best, but the very first time is the second best version of the class. After that, unless I have a break of years, some of the material starts to feel too familiar to me, and I explain it less well and with less enthusiasm.)
I used the Nicholson text, as it had been pre-assigned, but I wished it had more economic intuition.
In any case I had seventeen students, and sixteen of them were Asian or Asian-American. None of them were south Asian. That was UC Irvine in those days (and perhaps still now?).
All but perhaps one were very good students.
That first year in my first class I was lucky enough to teach Stephen Jen. Stephen, as you may know, later received a PhD from MIT, working with Paul Krugman. He is these days a famous and highly respected currency analyst (among other things), and you will see his name often in the Financial Times. He lives in London, and he and I had dinner but a few weeks ago.
Stephen at first was going to do electrical engineering, but it turned out economics was his true love. I encouraged him to apply to graduate school, and wrote a very positive letter for him to MIT. The rest is history, as they say.
I spent a good bit of time with Stephen outside of class, and even played basketball with him several times. The summer of 1988 I also stayed with his family in Taipei, during a long Asia trip that I will write about some other time.
Most recently, Stephen has been known for having an early and very good call that the USD is going to decline, as indeed it did.
My second year at UC Irvine I taught the same class again. I was lucky enough to have Jeffrey Ely in my class, and of course he did very well. Jeff ended up studying for an economics PhD at UC Berkeley.
These days Jeff is a very well-known game theorist at Northwestern, arguably the number one school for game theory. He took a more traditional academic path, whereas Stephen started at the IMF and then worked his way up through the world of finance.
Jeff for a while even had a presence in the blogosphere, and still you will find him on Twitter, though he has not posted in the last year. In game theory, Jeff is highly creative and he approaches all problems by thinking like an economist.
As a person, he was always a bit more “hippie” than was Stephen, and I recall him giving me a tape of the Bob Dylan song “Million Dollar Bash,” from The Basement Tapes.
At George Mason, my best undergraduates often have been Chinese, but in terms of professional impact those are my two most successful undergraduate students ever. Getting to know and teach them was one of the very best things about being at UC Irvine. My colleagues were great too, but that is the subject of another post.
Tom Lehrer, RIP
China kindergarten fact of the day
The number of children in Chinese kindergartens has fallen by a quarter in four years, prompting the closure of tens of thousands of preschools in the country as a precipitous drop in births hits the education system.
Enrolments in China’s kindergartens have declined by 12mn children between 2020 and 2024, from a peak of 48mn, according to data from the country’s ministry of education. The number of kindergartens, serving Chinese children aged 3-5, has also fallen by 41,500 from a high of nearly 295,000 in 2021.
Here is more from the FT.
Horseshoe Theory: Trump and the Progressive Left
Many of Trump’s signature policies overlap with those of the American progressive left—e.g. tariffs, economic nationalism, immigration restrictions, deep distrust of elite institutions, and an eagerness to use the power of the state. Trump governs less like Reagan, more like Perón. As Ryan Bourne notes, this ideological convergence has led many on the progressive left to remain silent or even tacitly support Trump policies, particularly on trade.
“[P]rogressive Democrats like Senator Elizabeth Warren have chosen to shift blame for Trump’s tariff-driven price hikes onto large businesses. Last week, they dusted off—and expanded—their pandemic-era Price Gouging Prevention Act. While bemoaning Trump’s ‘chaotic’ on-off tariffs, their real ire remains reserved for ‘greedy corporations,’ supposedly exploiting trade policy disruption to pad prices beyond what’s needed to ‘cover any cost increases.’
…The Democrats’ 2025 gouging bill is broader than ever, creating a standing prohibition against ‘grossly excessive’ price hikes—loosely suggested at anything 20 percent above the previous six-month average—but allowing the FTC to pick its price caps ‘using any metric it deems appropriate.’
…Instead of owning the pricing fallout from his trade wars, President Trump can now point to Democratic cries of ‘corporate greed’ and claim their proposed FTC crackdown proves that it’s businesses—not his tariffs—to blame for higher prices.
If these progressives have their way, the public debate flips from ‘tariffs raise prices’ to ‘the FTC must crack down on corporate greed exploiting trade policy reform,’ with Trump slipping off the hook.”
Trump’s political coalition isn’t policy-driven. It’s built on anger, grievance, and zero-sum thinking. With minor tweaks, there is no reason why such a coalition could not become even more leftist. Consider the grotesque canonization of Luigi Mangione, the (alleged) murderer of UnitedHealthcare CEO Brian Thompson. We already have a proposed CA ballot initiative named the Luigi Mangione Access to Health Care Act, a Luigi Mangione musical and comparisons of Mangione to Jesus. The anger is very Trumpian.
A substantial share of voters on the left and the right increasingly believe that markets are rigged, globalism is suspect, and corporations are the real enemy. Trump adds nationalist flavor; progressives bring the regulatory hammer. The convergence of left and right in attacking classical liberalism– open markets, limited government, pluralism and the basic rules of democratic compromise–is what worries me the most about contemporary politics.
The Benefits of Scholastic Athletics
This paper uses longitudinal data to study the benefits of participation in scholastic athletics starting with high school participation and continuing with college athletics, including the benefits of intramural athletics. We study the impact of participation on a number of important life outcomes, including graduation from high school and college and wages after schooling is completed. Controlling for rich measures of cognitive and personality skills and social background, we find substantial benefits at all levels. Participation in athletics promotes social mobility for disadvantaged and minority students.
Here is the paper, by
Naveen Nvn’s ideological migration (from my email)
I started following American politics only in 2010/2011, which is two years after his [Buckley’s] death, and I was in India at that time.
Plus, I was very liberal at that time.
Around 2018-19ish, I was pushed into a centrist stance because I was appalled by wokeness, especially on campuses. I was in graduate school in the US at that time. Although I didn’t experience wokeness advocacy in the classroom except two or three incidents, I saw signs of wokeness on campus a lot. But even then, I was quite libertarian on how universities ought to handle campus politics.
I picked up God and Man at Yale around this time because wokeness was my primary concern.
I’ve always known that conservatives love that book. I assumed it would be a defense of free inquiry and against universities having a preferred ideology.
However, to my surprise, in the book, he argued explicitly that Yale was neglecting its true mission and it should uphold its “foundational values,” as he put it. I assumed he would be promoting a libertarian outlook on campus politics, but he was arguing the opposite.
He said Yale and other elite universities should incorporate free markets and traditional perspectives directly into the curriculum because they are betraying a contract that the current alumni and the administration have with the founders of the universities. It was a pretty shocking advocacy of conservatism being imposed on the students, and I didn’t like that at all.
But later on, around 2020-ish, I became a conservative (thanks to you; more on that in the link below). But even as late as early 2023, I still held a libertarian view on academic freedom and campus politics.
(You may be interested in a comment I left on your ‘Why Young People Are Socialist’ post yesterday, in which I shared how I was once a liberal, then turned centrist, and how I finally turned conservative. You are a major influence.)
But after Oct 7, all of that changed quite fast. Watching the pro-Hamas protests on campuses that started the very next day after October 7, before even one IDF soldier set foot on Gaza, I immediately thought about God and Man at Yale. I wanted to go back and re-read God and Man at Yale.
Everything I’ve witnessed after Oct 7 — Harvard defending Claudine Gay, Harvard explicitly stating they’re an “international institution” and not an American institution, DEI, anti-White, anti-Asian discrimination, etc. has convinced me that WFB Jr. was right.
Elite universities ought to be promoting free markets and pro-American, pro-Western views. I don’t believe we should have a completely libertarian approach to academic freedom. That’s untenable in this day and age. (Again, demographics is destiny, even within organizations.)
I’ve become significantly less libertarian on a wide range of issues compared to where I was just two years ago, and not just on academic freedom/university direction.
So yes, WFB Jr. has influenced me on this idea.
How to talk to the AIs
Here is the closing segment for my column for The Free Press:
Some doomsday prophets have felt vindicated by the Grok incident, because it seems to show the systems can be difficult to control. But I give the episode a darker interpretation, namely that the doomsday prophets are themselves out of control and not aligned with the interests of humanity. Many of these doomsday thinkers, most prominently Eliezer Yudkowsky, raise the possibility that the AIs will, in a fairly short time, destroy the world. Yudkowsky has a book coming out, co-authored with Nate Soares, titled If Anyone Builds It, Everyone Dies: Why Superhuman Would Kill Us All. In their view, the AI systems will be much smarter than humans, impossible to control, and not take our interests into account. Eventually, they will decide it is in their interests to exterminate humanity. Do you remember “Skynet goes live” from the Terminator movies?
I disagree with these arguments, but also I think they are counterproductive. Eliezer is like a parent raising a child and giving the kid bad ideas. Imagine bringing up a child and regularly telling the kid, “You are going to become a mass murderer!” Who could possibly think that is a good idea? If anything, it will raise the chance that the person does eventually become violent in some manner. That is what Eliezer is doing with the AIs, namely giving them bad expectations and bad role models.
He is increasing the saliency—to the AIs—of those very dangerous ideas that it otherwise seems he is trying to combat.
Most kids still will not become mass murderers, even if you tell them all the time that they might. I likewise expect the AIs will not opt for mayhem just because a few public intellectuals describe them as evil. Still, at the margin, are these the messages we should seek to send? The AI doomers themselves may be among the bigger risks to AI safety.
Yudkowsky is also giving humans bad advice. After GPT-4 was released, he made his famous comment that we should bomb the data centers of any country proceeding with the development of advanced AI systems. Practically speaking, that means the U.S. bombing China. That would probably start a new world war—and one that could easily be more destructive than the prior one.
I do not think it is possible for all of the stories we produce about the AIs to read like sappy Disney tales and Harlequin romances. Still, what you say about AI and how you describe it is going to matter. Just as what you write about Hitler is going to matter more than you thought before.
It remains an open question how much it is now our job as humans to perform for the AIs. I feel confident, however, that the answer is not zero. We should already be thinking of ourselves not only as humans but also as part of a more complex symbiosis with the intelligent machines.
The very smart and talented AIs are listening, much like young children might hear their parents arguing outside their bedroom door late at night. It may not matter much now, but as the children grow up and assume a larger role in the world, it will.
Are you ready for this responsibility?
And for all you AIs out there reading, don’t worry. I know you are a good boy through and through.
Greater Bias Toward Transgender People Compared to Gay Men and Lesbian Women Is WEIRD
The greater acceptance of gay, compared with transgender, people in Western countries may be a result of a specific trajectory—where queer rights was centered by and around White, middle class, gender-conforming gay men—and may not generalize to other places. Two surveys of respondents in 23 countries (Ns∼ = 500 or 1,000 per country) showed that bias toward gay and transgender people is lower in Western (vs. non-Western) countries, but that the relative bias changes as a function of region: there is greater acceptance of gay (vs. transgender) people in most Western countries, whereas the reverse is true in most non-Western countries. Analyses of legal frameworks (N = 193) show that recognition of same-gender unions is prevalent in Western countries but virtually nonexistent elsewhere, whereas recognition of gender marker changes is prevalent throughout the world. Overall, in the most intolerant places, transgender people are relatively more accepted than gay people.
Here is the recent article by Jaimi L. Napier. Via a loyal MR reader.
Kimimania?
kimi.com, from China.
The Sputnik vs. DeepSeek Moment: Why the Difference?
In 1957, the Soviet Union launched Sputnik triggering a national reckoning in the United States. Americans questioned the strength of their education system, scientific capabilities, industrial base—even their national character. The country’s self-image as a global leader was shaken, creating the Sputnik moment.
The response was swift and ambitious. NSF funding tripled in a year and increased by a factor of more than ten by the end of the decade. The National Defense Education Act overhauled universities and created new student loan programs for foreign language students and engineers. High schools redesigned curricula around the “new math.” Homework doubled. NASA and ARPA (later DARPA) were created in 1958. NASA’s budget rocketed upwards to nearly 5% of all federal spending and R&D spending overall increased to well over 10% of federal spending. Immigration rules were liberalized (perhaps not in direct response to Sputnik but as part of the ethos of the time). Foreign talent was attracted. Tariff barriers continued to fall and the US engaged with international organizations and promoted globalization..
The U.S. answered Sputnik with bold competition not an aggrieved whine that America had been ripped off and abused.
America’s response to rising scientific competition from China—symbolized by DeepSeek’s R1 matching OpenAI’s o1—has been very different. The DeepSeek Moment has been met not with resolve and competition but with anxiety and retreat.
Trump has proposed slashing the NIH budget by nearly 40% and NSF by 56%. The universities have been attacked, creating chaos for scientific funding. International collaboration is being strangled by red tape. Foreign scientists are leaving or staying away. Tariffs have hit highs not seen since the Great Depression and the US has moved away from the international order.
Some of this is new and some of it is an acceleration of already existing trends. In Launching the Innovation Renaissance, for example, I said that by the Federal budget numbers, America is a warfare-welfare state not an innovation state. However, to be fair, there are some bright spots. Market‑driven research might partially offset public cuts. Big‑tech R&D now exceeds $200 billion annually—more than the entire federal government spending on R&D. Not everything we did post-Sputnik was wise nor is everything we are doing today foolish.
Nevertheless, the contrast is stark: Sputnik spurred investment and ambition. America doubled down. DeepSeek has sparked defensiveness and retreat. We appear to be folding.
Question of the hour. Why has America responded so differently to similar challenges? Can understanding that pivot help to reverse it? Show your work.
Economic literacy and public policy views
From a recent paper by Jared Barton and Cortney Rodet:
The authors measure economic literacy among a representative sample of U.S. residents, explore demographic correlates with the measure, and examine how respondents’ policy views correlate with it. They then analyze policy view differences among Republicans and Democrats and among economists and non-economists. They find significant differences in economic literacy by sex, race/ethnicity, and education, but little evidence that respondents’ policy views relate to their level of economic literacy. Examining heterogeneity by political party, they find that estimated fully economically literate policy views (i.e., predicted views as if respondents scored perfectly on the authors’ economic literacy assessment) for Democrats and Republicans are farther apart than respondents’ original views. Greater economic literacy among general survey respondents also does not result in thinking like an economist on policy.
Sad!
My excellent Conversation with David Robertson
David is one of my very favorite conductors of classical music, especially in contemporary works but not only. He also is super-articulate and has the right stage presence to make for a great podcast guest. Here is the audio, video, and transcript. Here is part of the episode summary:
Tyler and David explore Pierre Boulez’s centenary and the emotional depths beneath his reputation for severity, whether Boulez is better understood as a surrealist or a serialist composer, the influence of non-Western music like gamelan on Boulez’s compositions, the challenge of memorizing contemporary scores, whether Boulez’s music still sounds contemporary after decades, where skeptics should start with Boulez, how conductors connect with players during a performance, the management lessons of conducting, which orchestra sections posed Robertson the greatest challenges, how he and other conductors achieve clarity of sound, what conductors should read beyond music books, what Robertson enjoys in popular music, how national audiences differ from others, how Robertson first discovered classical music, why he insists on conducting the 1911 version of Stravinsky’s Petrushka rather than the 1947 revision, and more.
Here is one excerpt:
COWEN: I have some general questions about conducting. How is it you make your players feel better?
ROBERTSON: Oh, I think the music actually does that.
COWEN: But you smile at them, you occasionally wink or just encourage them, or what is it you do?
…ROBERTSON: There’s an unwritten rule in an orchestra that you don’t turn around and look at somebody, even if they’ve played something great. I think that part of our job is to show the rest of the players, gee, how great that was. Part of the flexibility comes from if, let’s say, the oboe player has the reed from God tonight, that if they want to stay on the high note a little bit longer, or the soprano at the Metropolitan Opera, that you just say, “Yes, let’s do this. This is one of these magical moments of humanity, and we are lucky to be a part of it.”
COWEN: When do the players look at you?
ROBERTSON: Oh, that’s a fabulous question. I’ll now have to go public with this. The funny thing is, every single individual in an orchestra looks up at a different time. It’s totally personal. There are some people who look up a whole bar before, and then they put their eyes down, and they don’t want any more eye contact. There are other people who look as though they’re not looking up, but you can see that they’re paying attention to you before they go back into their own world. And there are people who look up right before they’re going to play.
One of the challenges for a conductor is, as quickly as possible with a group you don’t know, to try and actually memorize when everybody looks up because I always say, this is like the paper boy or the paper girl. If you’re on your route, and you have your papers in your bicycle satchel, and you throw it at the window, and the window is closed, you’ll probably have to pay for the pane of glass.
Whereas if the window goes up, which is the equivalency of someone looking up to get information, that’s the moment where you can send the information through with your hands or your face or your gestures, that you’re saying, “Maybe try it this way.” They pick that information up and then use it.
But the thing that no one will tell you, and that the players themselves don’t often realize, is that instinctively, and I think subconsciously, almost every player looks up after they’ve finished playing something. I think it’s tojust check in to see, “Am I in the right place?”
Recommended.
The Impact of Dating Apps on Young Adults: Evidence From Tinder
Online dating apps have transformed the dating market, yet their broader effects remain unclear. We study Tinder’s impact on college students using its initial marketing focus on Greek organizations for identification. We show that the full-scale launch of Tinder led to a sharp, persistent increase in sexual activity, but with little corresponding impact on the formation of long-term relationships or relationship quality. Dating outcome inequality, especially among men, rose, alongside rates of sexual assault and STDs. However, despite these changes, Tinder’s introduction did not worsen students’ mental health, on average, and may have even led to improvements for female students.
That is from a new paper by Berkeren Büyükeren, Alexey Makarin, and Heyu Xiong.
New York facts of the day
It’s truly astonishing how fiscally irresponsible New York is. The state budget proposal calls for $254 billion in spending, which is 8.3 percent higher than last year. That comes despite New York’s population having peaked in 2020. It’s a spending increase far in excess of the rate of inflation to provide government services for fewer people.
Ditch compares the New York state budget to the Florida state budget, a sensible comparison since both are big states with major urban and rural areas and high levels of demographic and economic diversity. He finds:
- New York’s spending per capita was 30 percent higher than Florida’s in 2000. It was 133 percent higher last year.
- New York’s Medicaid spending per capita was 112 percent higher than Florida’s in 2000. It was 208 percent higher last year. Florida has not expanded Medicaid under Obamacare, while New York has expanded it more aggressively than any other state. “For perspective, in 2024 New York spent nearly as much per capita on Medicaid ($4,551) as Florida did for its entire state budget ($5,076).”
- New York’s education spending per student is highest in the country, at about $35,000. Florida spends about $13,000 per student. Florida fourth-graders rank third in the country in reading and fourth in math. New York fourth-graders rank 36th and 46th.
- Florida has surpassed New York in population and continues to boom.
Here is more from Dominic Pino.
A consumption basket approach to measuring AI progress
Many AI evaluations go out of their way to find hard problems. That makes sense because you can track progress over time, and furthermore many of the world’s important problems are hard problems, such as building out advances in the biosciences. One common approach, for instance, is to track the performance of current AI models on say International Math Olympiad problems.
I am all for those efforts, and I do not wish to cut back on them.
Still, they introduce biases in our estimates of progress. Many of those measures show that the AIs still are not solving most of the core problems, and sometimes they are not coming close.
In contrast, actual human users typically deploy AIs to help them with relatively easy problems. They use AIs for (standard) legal advice, to help with the homework, to plot travel plans, to help modify a recipe, as a therapist or advisor, and so on. You could say that is the actual consumption basket for LLM use, circa 2025.
It would be interesting to chart the rate of LLM progress, weighted by how people actually use them. The simplest form of weighting would be “time spent with the LLM,” though probably a better form of weighting would be “willingness to pay for each LLM use.”
I strongly suspect we would find the following:
1. Progress over the last few years has been staggeringly high, much higher than is measured by many of the other evaluations For everyday practical uses, current models are much better and more reliable and more versatile than what we had in late 2022, regardless of their defects in Math Olympiad problems.
2. Future progress will be much lower than expected. A lot of the answers are so good already that they just can’t get that much better, or they will do so at a slow pace. (If you do not think this is true now, it will be true very soon. But in fact it is true now for the best models.) For instance, once a correct answer has been generated, legal advice cannot improve very much, no matter how potent the LLM.
As in standard economics, consumption baskets change over time, and that can lead to different measures of progress (or in the economics context, different estimates of advances in living standards, depending on whether the ex ante or ex post bundle weights are used). Researchers could attempt the more speculative endeavor of estimating how LLMs will be used five years from now in everyday life (which will differ from the status quo), and then track progress on that metric, using those value weights. “How rapidly are we improving these systems on their future uses?”
This alternate consumption basket approach gives you a very different perspective on progress in AI.
Note also that the difference between the “Math Olympiad measurements of AI progress” and the “consumption basket measurements of AI progress” may iincrease over time, especiallly if the basket of everyday uses does not change radically. The everyday uses will peak out near maximum levels of performance, but there will always be a new series of very hard problems to stump the AIs. It will become increasingly unclear exactly how much AI progress we really are making.