Category: Education
The Public Choice Outreach Conference!
The annual Public Choice Outreach Conference is a crash course in public choice. The conference is designed for undergraduates and graduates in a wide variety of fields. It’s entirely free. Indeed scholarships are available! The conference will be held Friday June12- Sunday June 14 , near Washington, DC in Reston, VA. Lots of great speakers including Tyler, myself, Bryan Caplan, Robin Hanson, Jon Klick, Shruti Rajagopalan and more.
Please apply and encourage your students to apply.
Migrant Income and Long-Run Economic Development
We study how international migrant income prospects affect long-run development in origin areas. We leverage the 1997 Asian Financial Crisis exchange rate shocks in a shift-share identification strategy across Philippine provinces. Initial migrant income shocks are magnified six-fold over time, increasing domestic income, education levels, migrant skills, and high-skilled migration. Remarkably, 74.9 percent of long-run income gains come from domestic rather than migrant income. Trade driven impacts of exchange rate shocks are orthogonal to effects via migrant income. A structural model reveals that 19.7 percent of long-run income gains stem from educational investments. International migration fosters broad economic development in origin communities.
That is from a recent AER piece by Gaurav Khanna, Emir Murathanoglu, Caroline Theoharides, and Dean Yang. Here is a good thread on the piece.
Does this have implications for higher ed in particular?
Declining fertility and population loss pose significant challenges for state and federal local governments responsible for providing a range of services to citizens, including education, health care, and infrastructure. Indeed, many areas are already experiencing outright population decline, with roughly half of U.S. counties losing population between 2010 and 2020. This paper examines how shrinking and aging populations affect the operations and fiscal sustainability of state and local governments. Preliminary evidence presented in this paper suggests that scaling down educational services is considerably more difficult than scaling up. The estimated per-enrollee cost increases associated with a 10 percent enrollment decline are four times larger than the cost decreases associated with a 10 percent enrollment increase. Regions with contracting populations will face additional challenges as a smaller working-age population bears the burden of funding pensions and retiree health plans for larger aging cohorts. While lower fertility can create a short run fiscal dividend as local governments serve fewer children, that dividend will only be realized if state and local public officials make efficient retrenchment a priority.
From Jeffrey Clemens, via the excellent Kevin Lewis. As I think JFV mentioned lately, we have not done enough thinking about what a society with low TFR really is going to look like after a while.
Emergent Ventures winners, 53rd cohort
Elif Ozdemir, Ankara, align satellites.
Lily Zuckerman, University of Austin (and NYC), painting and general career support.
Benjamin Unger, NYC, AI to measure the performance of New York governments.
Maarten Boudry, Brussels, to write a book on who is really for progress, or not.
Allan Wandia, San Francisco, foundation models that learn directly from raw experimental data.
Richard Ng, London, AI agents.
Jordan Unokesan, London, trust scoring for government contractors.
Alexander Griffiths, London, infrastructure policy and decisions.
Pio Borgelt, 17, Osnabruck, AI.
Vedant Agarwal, 18, Cambridge UK, biosciences.
Chris Lee, Murietta, 18, CA, police recruitment.
Broderick Cotter, Austin, 17, finding the best materials for 3-D printing.
Jehan Azad, San Francisco, radar and UAPs.
Marius Drozdzewski, with collaborators, Berlin, German liberal periodical Aevum.
Ethan Galloway, London, 16, AI algorithms.
Keelan O’Carroll, Florida, happiness podcast.
Advice for economics graduate students (and faculty?) vis-a-vis AI
From Isiah Andrews, via Emily Oster and the excellent Samir Varma. A good piece, though I think it needs to more explicitly consider the most likely case, namely that the models are better at all intellectual tasks, including “taste,” or whatever else might be knockin’ around in your noggin…I am still seeing massive copium. But the models still are not able to “operate in the actual world as a being.” Those are the complementarities you need to be looking for, namely how you as a physical entity can enhance the superpowers of your model, or should I express that the other way around? That might include gathering data in the field, persuading a politician, or raising money. I am sure you can think of examples on your own.
How should you change your life decisions if we are being watched by alien drone probes?
I’ve asked a few people that question lately, and get either no answer or very exaggerated answers.
Rep. Burchett recently raised the possibility of being terrified and not sleeping at night if UAPs are aliens. But even if that is your immediate response, you need a more constructive medium-term adjustment to the new situation.
One option would be to pray to the aliens as gods, but I do not recommend that.
Another option is to not change anything, on the grounds that the aliens (probably?) have not been interfering in earthly affairs. Or if they have been interfering, they might be interfering in steady ways which are compatible with you continuing your previous life course.
That is mostly a defensible stance, but it hardly seems a true marginalist should make zero adjustments in light of the new and very radical piece of information. If nothing else, you need to consider that other people will in time respond, and you will in turn want a response to their choices.
A third option is to write more about the aliens, so that when their presence is (partially?) revealed, you will rise in status and influence.
Should you buy more insurance? But against what exactly?
Hold more defense stocks in your portfolio, if you anticipate more defense spending as the pending human reaction to the revelations?
Consume more? Maybe.
The most plausible decision however is to slightly lower your level of ambition. Consider a few of the core scenarios.
If the aliens go rogue on us and end it all, the efforts you might be making now will have been for naught.
If the aliens are here to cap the level of human achievement, for instance to keep us on Earth and prevent us from exploring the galaxy, yet without harm, you also can scale back your ambition a bit. You do not need to invest so much capital in supporting the space program. Most of your more local ambitions however should remain untouched. You might even become more ambitious in keeping the Earth a safe place, since escape hatches are now less likely. Alternatively, you might think the aliens are our “saviors of last resort,” but that too probably makes you less ambitious.
A more general Bayesian update is simply that human efforts, in the broader scheme of things, have lower relative marginal products than you might have thought. The aliens apparently have lots of powers, at least if they managed to get here. That too militates in favor of lowering your ambitions. Conversely, if you start believing we are the only intelligent, agentic beings in the galaxy, arguably you should increase your ambitions. There will be fewer outside forces to stop, limit, or reverse your efforts.
To be clear, in this Bayesian update large numbers of people still should increase their ambitions, since they were not optimizing in the first place. But they should increase those ambitions slightly less than one used to think. And in some areas, perhaps they should not increase their ambitions at all.
Finally, you should not decrease your ambitions a lot. For one thing, you may need an ongoing high level of energy and ambition to deal with the changes that aliens — or even the perceptions of alien presence — will bring to earthly civilization. Furthermore, since any alien-induced uncertainty about the future is very hard to model, most people will do best by simply continuing on their current tracks. It makes no sense to start waving around a sword to scare off the alien drone probes.
Nonetheless, some of your more extreme ambitions should be carved back just a wee bit. Sorry about that.
I guess it is a good thing nobody is watching then.
Addendum: For this post I am indebted to a useful lunch conversation with Robin Hanson, Bryan Caplan, and Alex T.
My very interesting Conversation with Arthur C. Brooks
Here is the audio, video, and transcript. Here is part of the episode summary:
Tyler and Arthur cover how scarcity makes savoring possible and why knowing you’ll die young sharpens the mind, what twin studies tell us about the genetics of well-being and why that’s not actually depressing, the four habits of the genuinely happy, the placebo theory of happiness books, curiosity as an evolved positive emotion, the optimal degree of self-deception, why Arthur chose Catholicism rather than Orthodoxy, what the research says about accepting death, how he became an economist via correspondence school, AI’s effect on think tanks, the future of classical music, whether Trumpism or Reaganism is the equilibrium state of American conservatism, whether his views on immigration have changed, what he and Oprah actually agree on, which president from his lifetime he most admires, Barcelona versus Madrid, what 60-year-olds are especially good at, why he’s reading Josef Pieper, how he’ll face death, and much more.
Excerpt:
COWEN: What do you think of the view that books on happiness or the meaning of life, they’re a kind of placebo? They don’t help directly, but you feel you’ve done something to become happier, and the placebo is somewhat effective.
BROOKS: I think that there’s probably something to that, although there’s some pretty interesting new research that shows that the placebo effect is actually not real. Have you seen some of that new research?
COWEN: Yes, but I don’t believe it. Nocebos also seem to work in many situations.
BROOKS: I know. I take your broader point. I take your broader point. I think that the reason for that is that when people read most of the self-improvement literature, not just happiness literature, what happens is that they get a flush of epiphany, a new way of thinking. That feels really good. That feels really inspirational. The problem is it doesn’t take root.
It’s like the seeds that are thrown on a path in the biblical parable. They don’t go through the algorithm that I just talked about, and so not all of these things can be compared. I would not have gotten into this line of research and this line of teaching if I thought that it was just going to add another book to a long line of self-improvement books that make people feel good but don’t ultimately change their lives.
COWEN: Say a person reads a new and different book on happiness once a year at the beginning of the year. Now, under the placebo view, that’s a fine thing to do. It’ll get you a bit happier each year. Under your view, it seems there’s something wrong. Isn’t the placebo view doing a bit better there? You should read a book on happiness every year, a different one. It’ll revitalize you a bit. Whether or not it’s new only matters a little.
BROOKS: Yes. It might remind you of some things that you knew to be the truth that you had fallen away from. One of the things that I like to do is I like to read a good book by one of the church fathers, for example. They’re more or less saying the same thing. It reminds me of something that I learned as a boy and that I’ve forgotten as an adult. It might actually remind me to come back to many of these practices and many of these views.
I think that there are real insights. There’s real value that can come from science-based knowledge about how to live a better life. I think that you and I are both dedicated to science in the public interest and also science in the private interest as well. I think there is some good to be gotten through many of these ideas. Not all. Once again, not all happiness literature is created equal.
And:
COWEN: Why not cram all that contemplation of death into your last three months rather than your last 18 months? Do intertemporal substitution, right? Accelerate it. Ben Sasse probably is facing a pretty short timeline, but he’s done a remarkable job, even publicly, of coming to terms with what’s happening. Isn’t that better than two years of the same?
And:
COWEN: I think it’s fair to say what we call the right wing in America, it’s become much, much more Trumpy. Does this shift you to the left or make you question what the right wing was to begin with, or do you just feel lost and confused, or do you say, that’s great, I’m more Trumpy, too? How have you dealt with that emotionally and intellectually?
BROOKS: Yes. I’ll answer, but you’re going to have to answer after me, will you?
COWEN: Sure.
Interesting throughout.
MRU high school fellowship
My podcast with Russ Roberts on AI and education
On his EconTalk podcast, self-recommending…
The economics of dropout risk
Bryan Caplan keeps hammering this point home, it is good to see follow-up work:
In the United States, college dropout risk is sizable. We provide new empirical evidence that beliefs about the likelihood of earning a bachelor’s degree predict college enrollment, and that the distribution of these beliefs exhibits widespread optimism. We incorporate this distribution of beliefs into an overlapping generations model with college as a risky investment that can be financed via federal loans, grants, family transfers, or earnings. We then examine the welfare impact of access to federal student loans. We find that access can reduce welfare for young adults who are low-skilled, poor, and optimistic, due to their mistaken beliefs.
That is from AEJ: Macroeconomics, by Emily G. Moschini, Gajendran Raveendranathan, and Ming Xu. Via the excellent Kevin Lewis.
I appear on the Coleman Hughes podcast
Grade Caps are Not a Good Solution to Grade Inflation
It’s well known that grade inflation has “degraded” the informational content of grades at many colleges. At Harvard, two-thirds of all undergraduate grades are now A’s—up from about a quarter two decades ago. In response, a Harvard faculty committee has proposed capping A grades at 20 percent of each class (plus a cushion for small courses). That may give professors some cover to resist further inflation, but it doesn’t solve the real problem.
The real problem is not inflation per se. It’s that students are penalized for taking harder courses with stronger peers. A grade cap leaves that distortion intact—and can even amplify it. As Harvard economist Scott Kominers argues:
A grade cap systematically penalizes ambitious students for surrounding themselves with strong classmates. Perverse course-shopping incentives ensue as a result. A student who is prepared for an advanced course but concerned about landing in the bottom 80 percent may choose to drop down preemptively—seeking out a pond where they are a relatively bigger fish. As strong students move into lower-level courses, competition for A grades increases there while harder courses continue to shrink—reducing their A allocation further and driving more students away.
The underlying issue is informational. A grade tries to capture two things—student ability and course difficulty—with a single number. Gans and Kominers show that in general this is impossible: if some students take math and earn B’s while others take political science and earn A’s, there is no way, from grades alone, to tell whether the difference reflects ability or course difficulty.
There is, however, a solution in some cases. Clearly, if every student takes some math and political science courses, informative patterns can emerge. If math students tend to get B’s in math but A’s in political science, while political science students get A’s in their own field but C’s in math, you can begin to separate course difficulty from student ability.
Students don’t all overlap the same classes. But full overlap isn’t necessary—you just need a connected network. If Alice just takes math courses, Joe takes math and political science courses, and Bob just takes political science courses, then Alice and Bob can be compared through Joe. With enough of these links, the entire system can be stitched together. The more overlap, the more precise the estimates.
Valen Johnson proposed a practical method along these lines in 1997. Gans and Kominers embed the same intuition in a much more general framework, showing exactly what can and cannot be inferred, and under what conditions.
The great thing about achievement indexes based on relative comparisons is that they are robust to grade inflation and do not penalize students for taking hard classes or subjects. A political science student who chooses to take a tough math class instead of an easy-A intro to sociology course won’t be penalized because their low math grade will, in effect, by boosted by the difficulty of the course/quality of the students. That’s good for the student and also good for disciplines that have lost students over the years because they held the line on grade inflation.
One final point. Harvard’s cap proposal appears to have been developed with little engagement with researchers who have studied problems like these for decades in the mechanism and market design literature—people like Kominers, Gans, Budish, Roth, Maskin, and Sönmez, some of them at Harvard! Moreover, this isn’t a case of ignoring high-theory for practice. The high-theory of mechanism design has produced real-world systems including kidney exchanges, school choice mechanisms, physician-resident matching, even the assignment of students to courses at Harvard, as well as many other mechanisms. Mechanism design is practical.
Grade inflation is a mechanism design problem—and we know a lot about how to solve it, if we want to solve it.
Scott Sumner on *The Marginal Revolution*
My favorite part of Tyler’s book is where he asks a very good but non-obvious question: Why did it take so long for economics as a field to develop a coherent model or framework of analysis? Much of the book discusses how three economists simultaneously developed marginal analysis, with a focus on the work of Stanley Jevons. Here I’ll briefly provide the intuition of marginal analysis and then explain why economics is both extremely easy but also quite difficult…
Tyler does a great job explaining why Jevon’s model of marginal analysis (which underlies most of modern microeconomics) is elementary on one level, but also something that wasn’t discovered until the 1860s because it was not at all obvious. Here’s how he concludes Chapter 3:
[This is TC now] By studying the slow intellectual development of economics, and contrasting it with other fields of study, we can learn the following:
1. Some insights are very hard to grasp, even if they are apparently simple once they are understood. People need to “see around corners” in the right way to understand these insights and incorporate them into their world views.
2. Economics is one of those fields, and that is why it took intuitive economic reasoning so long to evolve, marginalism included. Those of us who are educators, or who spend time talking to policymakers, should take this point very seriously.
3. Even very, very smart people are likely unaware that these “see around the corner” insights are missing – did Euclid rue that he did not have access to proper supply and demand and tax incidence theory? Probably not.
4. Economics is not the only such field that is hard to grasp, some other examples being segments of botany, geology, and evolutionary biology.
5. Scientific revolutions come about when many complementary pieces are in place, such as financial support, intellectual independence, and networks of like-minded others to talk with.
Those conditions help people to understand that “seeing around those corners” can bring both high social and professional returns.
Are there major conceptual corners that today still no one can see around? If so, how might we discover what they are? And why are we not working harder on this? Or are we?
Here is the rest of Scott’s commentary. Here is the online book.
*The Marginal Revolution: Rise and Decline, and the Pending AI Revolution*
I am offering a new piece of work — I do not quite call it a book — online and free. It has four chapters, is about 40,000 words, is fully written by me (not a word from the AIs), and it is attached to an AI with a dual page display, in this case Claude. Think of it as a non-fiction novella of sorts, you can access it here. You can read it on the screen, turn it into a pdf (and upload into your own AI), send it to your Kindle, or discuss it with Claude.
Here is the Table of Contents:
1. What Is Marginalism?
2. William Stanley Jevons, Builder and Destroyer of Marginalism
3. Why Did It Take So Long for the Science of Economics to Develop?
4. Why Marginalism Will Dwindle, and What Will Replace It?
Here are the first few paragraphs of the work:
How is it that ideas, and human capabilities, become lost? And how is that new insights come to pass? If eventually the insight seems obvious, why didn’t we see it before? Or maybe we did see it before, but didn’t really know we were on to something important? Why do new insights arrive suddenly, in a kind of flood? How do new worldviews replace older ones?
And what does all of that have to do with the future of science, the future of research, and the future of economics in particular? Especially when we try to understand how the ongoing artificial intelligence revolution is going to reshape human knowledge, and the all-important question of what economists should do.
Those are the motivating questions behind this work, but I will address them in what is initially an indirect fashion. I will start by considering a case study, namely the most important revolution in economics, the Marginal Revolution (to be defined shortly). The Marginal Revolution made modern economics possible. What was the Marginal Revolution? How did it start? Why did it take so very long to come to fruition? From those investigations we will get a sense of how economic ideas, and sometimes ideas more generally, develop. And that in turn will help us see where the science, art, and practice of economics is headed today.
Recommended! I will be covering it more soon.
Ryan Hauser interviews me in print
Here is the link, here is one excerpt:
What was your path into AI, and what are you working on now?
I first became interested in AI when I saw the chess computer Tinker Belle wheeled into a New Jersey chess tournament in I think 1975. I followed the Kasparov matches closely, and the more general progress of AI in chess. I read chess master David Levy telling me that chess was far too intuitive for computers ever to do well. He was wrong, and then I realized that AI could be intuitive and creative too. That was a long time ago.
In 2013 I published a book on the future of AI called Average is Over. I feel it has predicted our current time very accurately. I also taught Asimov’s I, Robot – a work far ahead of its time – for twenty years.
Right now I am simply working to keep afloat and to stay abreast of recent AI developments. I blog and write columns on the topic frequently, and have regular visits to the major labs. I encourage universities to experiment with AI education.
I mention William Byrd and Paul McCartney as well.