Author: Joy Buchanan

Should Practicing Economists Read Tyler’s New Marginalism Book

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Tyler Cowen’s new (free online) book entitled The Marginal Revolution: Rise and Decline, and the Pending AI Revolution is going to be “interesting,” but should you read it?

Mike Makowsky explained that Academic economists are overcommitted

If you are already struggling to meet your deadlines for referee reports you owe to editors, should you take the time? If you don’t have time to indulge your curiosity about the 18th century and dead thinkers, right in the middle of the semester, should you look at it now or maybe browse it over the summer?

I think it’s worth going straight to the last chapter right now.

“Chapter 4: Why Marginalism Will Dwindle, and What Will Replace It?“

It was written for you and released quickly for this moment. Tyler does not personally have to worry about his job, but you might.

This link will take you straight to an in-browser e-reader https://tylercowen.com/marginal-revolution-generative-book/app/

Or you can download the PDF at https://tylercowen.com/wp-content/uploads/2026/03/TheMarginalRevolution-Tyler_Cowen.pdf

You might face mental resistance to reading this chapter, because you don’t want to hear the message. If that’s you, then it’s especially useful to read this chapter. He’s not correct about everything. Develop your counter argument, to go forth and save marginalism. You can only do that if you understand and name the threats. This is more about methods/professions and less about ideology than you might think from the title.

Here are some quotes that stood out to me

The ties of empirical work in economics to economic theory are evolving, and in particular the explicit ties to intuitive microeconomic reasoning, and marginalist thinking, are being cut. In much of traditional econometrics, the emphasis is on testing pre-existing models…

in machine learning, we let the algorithm build the “theory” for us, noting it may have tens of millions of variables and thus not count as a theory…

So much for prediction, what about hypothesis generation? Well, there is a new approach to that too, using machine learning.

A lot of economists do not regularly describe what they actually do for work. Yes, we are saving the world by writing papers, but what exactly do you do? Do you generate hypotheses? Is that what you are teaching your students to do?

It’s not fun to think of how the econ profession might need to reposition, but we owe it to students. Who better to work on this than tenured professors? 

I think the case for undergraduates students to major in economics is strong. I also think the case for doing 4 years of college is strong for students who want to learn.

Last summer I wrote: Students still need to learn principles

If economics is “more interesting” than hard science, then it might serve to scoop up good thinkers at the undergraduate level and get them doing something more technical than what they would end up doing in a humanities program. When I graduated from college, the fact that most econ student had accidentally learned to code was a benefit to them.

College graduate humans ought to be able to read and pass the Turing Test if they are going to be effective complements to AI.

Economists championing marginalism for students, today, write: For Gen Z, Economics May Be the Key to Success in the New AI World

Let me plug Mike as well for thinking about what research econs do in 2026: The actual AI problem in academic economics “Oh, what shall all the candlemakers do now that the sun has risen?” made me laugh.

Oil Price Lesson Plan for Economic Principles

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Alex Tabarrok noted in Oil versus Ice Cream that he and Tyler, as textbook authors, “chose the oil market as our central example. Oil is always in the news…”

when a student sees that the price of crude has surged past $100 a barrel because Iran closed the Strait of Hormuz—choking off 20% of the world’s oil supply—they have the framework to understand what is happening. Supply shock, inelastic demand, expectations and speculation, the macroeconomic transmission to GDP—it’s all right there in the headlines.

In a classroom, a good way to begin is to ask the students to tell you what they have noticed recently about oil or gas prices. Having the students obtain the oil price data themselves could be fun, if you are in an environment with screens/computers.

A data source for undergrads is the FRED chart for WTI crude oil prices. It is clean and easy to explain in class. An instructor with slides could pull this up in real time. https://fred.stlouisfed.org/series/DCOILWTICO

Ask students: “Is this price change primarily explained by

  1. Increase in demand
  2. Decrease in demand
  3. Increase in supply
  4. Decrease in supply

Correct answer: d. Decrease in supply

If you cover elasticity, this is especially helpful as an example. “Why would the price jump more when demand is inelastic?”

It’s not too late to work this into a lesson plan for the Spring 2026 semester, economic teachers. I might use it to illustrate supply shocks next week.

This event is a classic example of a negative supply shock: a disruption in the Strait of Hormuz would reduce the amount of oil reaching world markets, pushing energy prices sharply upward. Because oil is an important input for transportation, manufacturing, and heating, higher oil prices raise costs across much of the economy. Firms may cut production, households may spend more on gasoline and utilities and less on other goods, and overall economic activity can slow. That is why economists worry that large oil supply shocks can contribute to recessions. They do not just make one product more expensive; they can ripple outward, reducing real income, lowering consumer confidence, and weakening GDP growth while inflation rises.

Related posts. The whole crew showed up this month:

James from March 12: Is a US Oil Export Ban Coming?

Jeremy from March 18: Gasoline Prices Have Increased at Record Rates, but Remain At About Average Levels of Affordability

Tyler from March 22: How much more will oil prices have to go up?

MattY from March 24: Why hasn’t oil gotten even more expensive?

Austin Vernon: https://www.austinvernon.site/blog/thestrait.html

The Heartwarming Sincerity of Gravity Falls

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I learned about the children’s cartoon Gravity Falls this year from my kids.  

Bluey is wonderful for kids and adults, but it does feel like a baby show since the younger dog Bingo is 4. If you are getting out of the baby stage with kids, Gravity Falls is great next step with 12-year-old twins. The jokes are funny, especially for American parents today who would have grown up with the cultural references.

Gravity Falls has emotional depth. These days the young folks are in “situationships” trying not to catch feelings (I hear). In Gravity Falls, everyone catches feelings so hard. It’s tragically beautiful like Anna Karenina.  You can watch it on Disney+ and YouTube.  

Young Scholars or Any Scholars

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The Economic Science Association has listed some exceptions to the under-40 rule for being considered a success. I approve.

– *ESA Young Scholar Prize*: This prize is to be awarded to one young scholar whose research has made a significant contribution to experimental methodology. Nominees must

  • be under the age of 40; ESA will consider nominations of individuals over the age of 40 who started their research career late, or have had career interruptions, (b) hold an untenured position, or (c) have completed their PhD at most 10 years previously.

One does start to question if we ought to use the word “young” at all, if we are going to admit all those exceptions, since Awards for young talent are antinatalist.

Perhaps the worst thing about older people is a lower willingness to move-to-opportunity geographically. That’s not so bad from the perspective of an institution that has already made a hire, but it is bad from the perspective of a subfield or with respect to graduate admissions.

Experimental Economics is a small world, so I think there was a genuine impact on the way of thinking due to the success of Gary Charness.

Claude writes:

Charness did not follow the standard trajectory of a prodigy moving seamlessly from PhD to tenure-track stardom. He earned his doctorate from UC Berkeley relatively late, in 1999, after a career in business and industry. He was in his early 40s when he entered the academic job market — an age at which many economists assume a researcher’s most creative years are already behind them.

Despite entering academia so late, Charness went on to become one of the most cited and prolific experimental economists in the world. He continued producing high-impact work well into his 60s, with no visible declining trajectory in the originality or influence of his research.

Joy again:

Notice the move-to-opportunity at the age of 50, as indicated by Wikipedia “After commuting for three years between San Francisco and Barcelona (and floating free for another year), Gary accepted a position as an assistant professor at UCSB in 2001.”

In case you are missing the reference, this is how it’s typically used: “Evaluating the Impact of Moving to Opportunity in the United States” 

Whether full-time permanent research jobs or research awards for writing papers will still exist at all in 20 years, because of changes wrought by AI, I do not know. This week a student walked into my office to ask for help with Excel, which I was happy to provide. I told her that she could have just asked AI, but she claimed that, “Claude was acting up this week.” The year 2026 is odd because I am trying to synthesize the claim that “AGI is here” with the fact that AI still cannot perform most basic tasks correctly. Do organizations need a contingency plan for when Claude is “acting up?”

Learn to Ode 2026

Joy Buchanan1 Comment

Joke: https://x.com/TheLincoln/status/2027215235103207693

Writing about the Citrini Research report on February 28 feels like a being 6 years behind (it was only 6 days ago).

“THE 2028 GLOBAL INTELLIGENCE CRISIS: A Thought Exercise in Financial History, from the Future”

Two things the white-collar chattering class fears is that their jobs will disappear or their stock portfolios will crash. The Citrini note put that feared scenario in a picture frame so we could stare at it, like Annie Jacobsen’s book on nuclear war. The post imagines a 2028 scenario: AI automates white-collar work, companies collapse, private credit blows up, mortgages default, unemployment hits 10%.

Brian Albrecht responded: “We don’t need to just make up fantasy stories: Using economics to read Citrini Research’s AI”

Tyler encouraged us to consider a response put out by Citadel “The 2026 Global Intelligence Crisis“

Even cognitive automation faces coordination frictions, liability constraints, and trust barriers. It seems more likely that AI will be a complement rather than a substitute for labor is many areas.

One barrier to AI taking all the white-collar jobs as quickly as 2028 is just physical scaling constraints.

Having done research on “learn to code” (Buchanan 2022), I always watch new developments with interest. In 2023, I told an auditorium full of students in Indiana to learn to code if they don’t hate the work too much. At that time I had forecast that AI tools would make coding less miserable but not eliminate the need for technical human workers. Even if that was good advice at the time, is it still good advice today? I wish I had time to put up a blog on this topic every week.

Adjustments can happen along the margin of price as well as quantity. Wages to programmers can come down from their previously exalted heights, which could help the market absorb some of the young professionals who listened to “learn to code” in 2023.

So, now that the value of coding skills is in question, people are turning back to the value of the maligned English degree. It has been true for a long time that employers felt soft skills were more scarce than STEM degrees. I might add that an economics degree conveys a highly marketable blend of hard and soft skills.

Buchanan, Joy (2022). “Willingness to be paid: Who trains for tech jobs?” Labour Economics,
79, Article 102267.

Learning the Bitter Lesson at EconLog

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I’m in EconLog with:

“Learning the Bitter Lesson in 2026“

At the link, I speculate on doom, hardware, human jobs, the jagged edge (via a Joshua Gans working paper), and the Manhattan Project. The fun thing about being 6 years late to a seminal paper is that you can consider how its predictions are doing.

Sutton draws from decades of AI history to argue that researchers have learned a “bitter” truth. Researchers repeatedly assume that computers will make the next advance in intelligence by relying on specialized human expertise. Recent history shows that methods that scale with computation outperform those reliant on human expertise. For example, in computer chess, brute-force search on specialized hardware triumphed over knowledge-based approaches. Sutton warns that researchers resist learning this lesson because building in knowledge feels satisfying, but true breakthroughs come from computation’s relentless scaling. 

The article has been up for a week and some intelligent comments have already come in. Folks are pointing out that I might be underrating the models’ ability to improve themselves going forward.

Second, with the frontier AI labs driving toward automating AI research the direct human involvement in developing such algorithms/architectures may be much less than it seems that you’re positing.

If that commenter is correct, there will be less need for humans than I said.

Also, Jim Caton over on LinkedIn (James, are we all there now?) pointed out that more efficient models might not need more hardware. If the AIs figure out ways to make themselves more efficient, then is “scaling” even going to be the right word anymore for improvement? The fun thing about writing about AI is that you will probably be wrong within weeks.

Between the time I proposed this to Econlog and publication, Ilya Sutskever suggested on Dwarkesh that “We’re moving from the age of scaling to the age of research“.

Telephone Classroom Game for Teaching Large Language Models

Joy Buchanan1 Comment
LLM_Telephone_Game_SheetDownload

Use the above game to generate interaction in a class setting. Students collectively form an LLM and have fun seeing the final sentence that gets produced. I call this game “LLM Telephone” based on the classic game of telephone. I suggest downloading the file LLM_Telephone_Game_Sheet and handing out printed copies. However, this game could be adapted to a virtual setting.

The nice thing about passing papers in the classroom is that you can have several sheets circulating in a quite room, so when the final sentence is read allowed it comes as a surprise to most people.

If you’d like to have a handout to follow the game with a more technical explanation, you can use this two-page PDF:

LLM_Telephone_Game_ExplainDownload

The game relies on a player presenting two tokens of which the next player can select their favorite. Participants should be bound by the rules of grammar and logic when making their selection and presenting two tokens to the next player.

This game works as a fun ice breaker for any type of class that touches on the topic of artificial intelligence. It is suitable for many ages and academic disciplines.

IP Paper on Econlog

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My research on intellectual property is featured at

Everyone Take Copies (Econlog)

The title of this post, “everyone take copies,” comes from a conversation between the human subjects in an experiment in our lab, on which the paper is based. The experiment was studying how and when people take resources from one another.

Here’s a tip that doesn’t require any piracy. For those of you who are tired of the subscription economy fees, I think it’s safe to say in 2026 that anyone in the United States can find a local thrift store or annual rummage sale with oodles of nearly-free media. DVDs for a dollar. Used books for a dollar. Basically you are paying the transaction costs – the media itself is free. (I typed that dash myself, not AI!)

“Buying” a movie to stream on Amazon Prime can run over $20. Buying a used DVD is usually less than $10.

Something like the above observation probably lead to this parody news headline Awesome New Streaming Service Records Movie Streams Onto Cool Shiny Discs And You Can Buy Them And Own Them Forever

Here’s a response from the prompt “Make a picture of my office with AOL CD-ROMs decorating the wall.”

Update on School Valentines

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I have principles. One of them is that school Valentines are indulgent and bad for the environment.

I have written Markets in Everything for school Valentine’s

And here are some quotes from Do Less for Preschool

Just fail, people. Don’t even put “crazy sock day” on your work Outlook calendar…

Oh no. If AI lifts the constraint of time, then what we are going to get is more crazy sock days. To stay ahead in the status competition, families will have to do Bluey-Crazy Sock Day every week. The ocean will become a thick soup of polyester Bluey-crazy-socks, size 3T, worn only once.

On principle, I did low-effort Valentine’s last year. I spent as little of my own time and money as I could. My kids wrote their friends’ names on the paper things.  Smugly, I imagined that I’d saved the dolphins in the tuna nets and helped some other mom feel like she was doing okay.

Who do you imagine is upset? Not the other moms. My kids. The older one especially feels in his body that failing this test in February of 2026 will result in expulsion from the tribe and death in the outer darkness beyond the reach of the campfire.

Guess what I care about more than dolphins? We will do more this year.

Preschool kids do not care and should not be asked to care. I still believe that parents and daycare directors should do less for preschool. Truly, I see no reason, at all, for a preschool dress up day or Valentine’s Day party. Can someone think of the dolphins before it’s too late and the kid grows up and starts caring about the status wars?