This person is buying the pills direct from the supplier, in consultation with a doctor. It is amazing. Resurrection. The Great Stagnation is over. Go get this stuff. It’s funny how many people are already on it, but it doesn’t come up until you initiate a conversation.
As a behavioral economist… it’s pretty wild. Folks were eating things that part of themselves wanted to eat and part of themselves did not want to eat. And, instead of getting rid of the junk food, or somehow training people out of overeating, we’ve chemically quieted the desires.
I feel like the healthy people could have done more on choice architecture, in the old days (pre-2025). It was hard for the people trying to lose weight to avoid junk food. I’m not trying to introduce the boot of the state into kids’ birthday cakes but just pausing to reflect on how many people died because of our choices. Humans are supposed to just walk past an aisle of candy bars? (My parents explicitly and intentionally trained me from a young age to never buy anything at the “check out aisle” because it’s always going to be a stupid impulse purchase. As an adult, I buy a chocolate bar at check out about once a year and feel like I’m getting away with robbing a children’s hospital.)
Here’s Paul pondering these issues 2000 years ago (shortened by me): Romans 7:15-19 15 I do not understand what I do. For what I want to do I do not do, but what I hate I do. 16 And if I do what I do not want to do, I agree that the law is good. … For I have the desire to do what is good, but I cannot carry it out. 19 For I do not do the good I want to do, but the evil I do not want to do—this I keep on doing.
When I was a kid, my family didn’t get JELLO puddings – or any puddings for that matter. As an adult, I realized that a lot of those are just sugar, cornstarch, and stabilizers. So, they became less appetizing.
You’re going to laugh at me.
A few years ago my wife and I went to a nice little breakfast restaurant for brunch in old town Fredericksburg, VA. I got this coconut milk chia seed parfait. I was blown away. That seems silly to say, but it was really nice.
For years we spoke longingly of that chia parfait and we’d speculate about when we might go there again. It was one of those conversations that married people have.
“Hey, remember that really good thing?”
“Yeah, it was really good.”
“We should try that again sometime.”
Then one day, while visiting Virginia, we noticed that the restaurant had closed. It wasn’t surprising because the restaurant had only been ‘fine’, except for the healthy and delectable layered treat from years past.
Now we have a handful of kids and we try different things periodically to make the morning routines go more smoothly. Having a responsible treat to entice juveniles from their room isn’t the worst thing that we’ve tried.
My wife, in her laudable creativity, refined a new creation that’s inspired by our now frustrated longing for a nice chia parfait.
Below is a recipe for peanut butter chocolate chia seed pudding. Basically, you mix it the night before and stir it again in the morning and it’s ready to go. It’s a crowd pleaser.
Who benefits from trade between the US and China? If China subsidizes their exporting industries, should the US see this as a threat that undermines our industries, or thank China for lowering prices for US consumers? Does it matter that China runs a persistent trade surplus (exporting more than they import), while the US runs a persistent trade deficit?
Everyone has a take on these questions, but the answers I hear even among economists rarely draw from the leading modern models in the international trade literature. Krugman (1980) (10k citations) shows how large home markets matter for industries with increasing returns to scale. In a simple increasing returns model, unlike with Econ 101 comparative advantage, temporary subsidies can permanently flip which country an industry efficiently operates in.
Melitz (2003) (20k citations) extends the Krugman model to include firm-level productivity differences. Rubini (2014) extends the Melitz model to include innovation. Now Xiao (2025) has extended the Rubini model to include unbalanced trade, then calibrated the model with data from the US and China. Now that the mathematical models are able to incorporate more and more features of the real world, what do they show?
China’s trade surplus and the US trade deficit have tradeoffs. Specifically, China’s trade surplus leads them to be more productive than they otherwise would be, but have lower welfare, because so much of the fruit of their production is enjoyed by other countries. Conversely the US trade deficit leads us to produce less than we otherwise would, but to have higher welfare thanks to consumers enjoying the cheaper foreign goods.
In one sense this recapitulates some of the same debates people had without the math. Some people like trade because it benefits US consumers and overall present-day US wellbeing. Some don’t like it because it harms US manufacturing and our resiliency in any potential future conflict.
One advantage of the models is that it puts numbers on the tradeoffs. In this case, the welfare benefit to the US may be small relative to China’s welfare loss and relative to both countries’ productivity changes:
the average productivity increase caused by trade surplus ranges from 1.2 percentage points to 5.46 percentage points when the innovation cost changes. These results explain China’s long-term export promotion policies and align with its new policy goal of developing “new productivity forces”. I also identify a negative effect on China’s trade partners’ productivity (namely, the US), of between -2.74 percentage points and -5.89 percentage points. This comes at a welfare cost, equivalent to between 3 percentage points and 5.7 percentage points of consumption units. Correspondingly, China’s cheaper goods increase welfare in the US by between 0.26 percentage points and 1.22 percentage points
In addition to the big complex model, Xiao’s paper shares nice background on the sheer size of Chinese export subsidies, noting that they account for 2/3 of all manufacturing subsidies in G20 countries, and that export tax rebates are almost 2/3 as large as Chinese net exports. In short, China’s trade surplus is not simply driven by differing preferences and production capabilities across countries, but is largely driven by deliberate policy choices.
P.S. The paper’s author, Aochen Xiao, is on the econ job market.
Two months ago I wrote about gasoline prices and tried to give the current prices some historical context. Gas prices have, of course, only continued to increase since then. Here’s a chart I created to give a bit more context, using an idea from Ryan Radia: how much does it cost to drive a car 250 miles? Since fuel efficiency has increased over time, we might be understating how much it costs to drive today relative to the past. And of course, to give the “cost” proper context I have stated in terms of hours worked at the average wage (note: the final data point is from April 2026, as we don’t have wage data for May yet):
In April 2026 it took about 1.4 hours of work at the average wage ($32.23) to purchase enough gasoline to drive 250 miles (10.7 gallons) at the average fuel efficiency (23.4 miles per gallon). That average fuel efficiency figure is from 2024, the latest available, so it could be a bit higher today. Maybe it’s a little easier than 1.4 hours of work to buy it, but even if fuel efficiency had crept up to 25 mpg (that would be a big increase in 2 years, historically speaking), it would still be 1.3 hours of work.
1.4 hours of work is certainly a big jump from earlier in 2026, but you’ll notice it is still on the low end in this chart, and well below the peak we saw in June 2022 of just over 2 hours of work to buy 250 miles worth of gasoline.
But 23.4 miles per gallon is pretty low, as this is includes lots of trucks and SUVs with pretty bad fuel efficiency. What if we looked at some more fuel efficient vehicles?
Here’s a few I checked on (all for 2026 models, with gas and electricity at current national averages):
Toyota Camry: 0.71 hours of work
Chrysler Pacifica Hybrid: 0.61 hours on electric, 1.18 hours on gasoline
Tesla Model Y: 0.37 hours of work
It will probably not surprise you that the all-electric Tesla Model Y is cheaper than the average car to operate at current prices, but you may not have realized that it is almost four times cheaper. But the Toyota Camry, with all models operating as hybrids now, also comes in pretty good at about half the cost of the average vehicle to operate (and the Camry is a very affordable car to purchase). The Chrysler Pacifica hybrid minivan does pretty well too, though even operating only on electricity (30 miles at a time), it’s only slightly more fuel efficient than the Camry.
I read Straw Dogs, a critique of modern society by English political philosopher John Gray, shortly after it was published in 2002. (No relation to the movie with the same name). Wikipedia summarizes the author’s view as, “Gray blames humanism, and its central view of humanity, for much of the destruction of the natural world, and sees technology as just a tool by which humans will continue destroying the planet and each other.” I cannot recommend the book as a whole – the reader is left in a state of despairing passivity. My AI justly notes, “Critiques of John Gray’s Straw Dogs: Thoughts on Humans and Other Animals generally center on its extreme pessimism, logical inconsistencies, and rhetorical excesses.”
All that said, the book did contain many interesting observations. One line of thought that struck me at the time was that, with increasing efficiencies in the production of basic goods and services, more and more human effort will go into simply entertaining or “distracting” each other:
The days when the economy was dominated by agriculture are long gone. Those of industry are nearly over. Economic life is no longer geared chiefly to production. To what then is it geared? To distraction. Contemporary capitalism is prodigiously productive, but the imperative that drives is not productivity. It is to keep boredom at bay. With wants so quickly sated, the economy soon comes to depend on the manufacture of ever more exotic needs.
I was reminded of that line of thought when, at a recent gathering of PhD chemical engineers, I heard that one of our number has become somewhat well-known for a late-career shift. She goes by the name Andrea Hulamyhoop these days. (I happen to know her real last name and approximate age, but she wishes to keep those private).
Her father was a chemical engineering professor, and she earned a PhD in the discipline at Princeton University. She was just going along living a fairly normal sort of life, with a regular job, when without warning, it happened:
Then one day, she saw a girl hula hooping. “She looked really free and happy, and I thought, interesting, maybe I’ll try it.” A few minutes at a time quickly became an obsession. Turns out, there are whole online communities of hula hoopers who share tips and support. Conferences. And many shows and events looking for a pro to dazzle and inspire audiences.
“The hula hoop has changed everything in my life,” she says. “I didn’t know I could become a fit, sporty person. I didn’t know I was one. I love performing, and I love people, and I love parties.
“I always thought my life was a bit OK. My kids were grown up. I was enjoying my job,” she says. “But you know, we kind of think, is this all there is? And then to realize there’s this whole world — it’s been incredible. I’m happier than I’ve ever been in my life.”
Andrea Hulamyhoop doesn’t just swirl a hoop around her waist. She can twirl multiple hoops around multiple body parts, with style. She is perhaps best known for her appearance on America’s Got Talent in 2025, where she smashed previous records by bending over and twirling a hoop around her rear end for just over an hour and fifteen minutes. The crowd went wild.
The physics of this feat seem almost impossible, but seeing is believing. Andrea gives a gracious tutorial here.
When I asked who is the most famous holder of a Princeton chemical engineering PhD, both ChatGPT and Claude insisted that former GE president Jack Welch is more well-known than Andrea the butt-hooper, but I doubt that is true below a certain audience age bracket. She has some 17,000 Instagram followers. I’d be willing to bet that in a crowd of under-40’s today, if you asked “Have you heard about the guy who was president of GE in the 1980’s and 90’s?” or “Have you heard about the gal who can twirl a hula hoop on her butt?”, Andrea Hulamyhoop would win.
All this brought back to my mind the notion that as a society we are able to afford to devote a great deal of time to sheer entertainment, rather than growing potatoes. A comment by a certain @petesounds9321 on Andrea’s epic 2025 AGT YouTube showed he had evidently not read Straw Dogs:
“I’d say we need more scientists than hula hoopers but hey…maybe I’m way off.”
This is the chart that I’ve been thinking about today.
The US government has been able to borrow on the cheap for most of it’s existence, with the exception of 70s and 80s when stagflation put the clamp down. Treasury rates are soaring right now…or at least, it feels that way because for most of my adult life the United States has been viewed as arguably the safest borrower in history. What follows are in some ways the only two questions that matter for the US economy. Is the US government a reliable institution? Is economic growth going to keep pace with inflation? The answer to each question (and their subcomponents) is, of course, unknown, but the market seems to think the net of that question is going in the wrong direction.
That said, for all of the neverending parade of (sometimes unintential) nostalgia that seems to pollute the discourse, wow, 1975-1985 was not exactly macroeconomically “aspirational”.
In the world of academic preprints, arXiv has long been the go-to platform for researchers to share work quickly. But with the explosion of generative AI tools, the repository is drawing a line in the sand.
On May 14, 2026, arXiv moderator Thomas Dietterich announced a clarified enforcement policy. If a submission contains incontrovertible evidence that authors didn’t properly check LLM-generated content, all listed authors face serious consequences.
Attention @arxiv authors: Our Code of Conduct states that by signing your name as an author of a paper, each author takes full responsibility for all its contents, irrespective of how the contents were generated. 1/
— Thomas G. Dietterich (@tdietterich) May 14, 2026
What counts as “Incontrovertible Evidence”? The policy targets clear signs of unchecked AI output, including:
Hallucinated or fake references
Meta-comments left by the model (e.g., “Here is a 200-word summary; would you like me to make any changes?” or placeholder instructions like “fill in the real numbers from your experiments”)
Other obvious errors, plagiarized text, biased content, or misleading claims generated by AI
arXiv’s Code of Conduct already holds every author fully responsible for the entire paper’s contents.
The Penalty
One-year ban from submitting new papers to arXiv.
After the ban, future submissions must first be accepted at a reputable peer-reviewed venue before arXiv will host them.
At first researchers discussing the policy online seemed happy about the one-year ban, but when I pointed out that it is essentially a ban for life to use it at a pre-print venue, some people became nervous.
The one-year ban is actually a forever ban on working papers which is more serious https://t.co/1VGUcUoc15
Why now? arXiv has been overwhelmed by low-effort “AI slop.” These papers are marked by fabricated citations and shallow summaries. This erodes trust in the entire preprint ecosystem.
In response to the complaints (someone like me would be worried that I’ll somehow let an error slip through and then be banned for life from posting working papers), Scientific Director Steinn Sigurðsson shared:
on the whole @arxiv flap about hallucinated references etc
you don't see the stuff we reject… some of it is really really egregious
the decision to impose additional consequences is largely to throttle that stuff so n00bs and bad actors don't trash us trying repeatedly
Elon Musk buying Twitter is the big news this week. He wants to enhance free speech on the site and, according to him, make it more open and fun. Some fans are hoping that he will make the content moderation and ban policy more transparent. Maybe that’s possible.
If no one can be banned, then bad actors will bring the whole platform down. Inevitably, good people get caught in the net, and it’s devastating to be locked out of a platform where your peers are sharing.
However, if you want to be taken seriously by tech folk then ask for a system that is possible. A substantially better experience might be incompatible with the site being free to users.
Part of the problem that I don’t hear people talking about is that a free platform is not easily compatible with good customer service.
For some not-fake work and citations: Buchanan et al. (2024) provided early clear evidence that a mark of LLM-written work is fake citations. And, Buchanan and Hickman (2024) show that certain framings can prompt people to be more suspicious of AI-generated writing, such that they are pushed toward doing a fact-check before believing all claims.
Buchanan, Joy, and William Hickman. “Do people trust humans more than ChatGPT?.” Journal of Behavioral and Experimental Economics 112 (2024): 102239.
Buchanan, Joy, Stephen Hill, and Olga Shapoval. “ChatGPT hallucinates non-existent citations: Evidence from economics.” The American Economist 69.1 (2024): 80-87.
The vast majority of business majors across the US are required to take two or more Economics courses. You can look across the spectrum. All of the top 20 business schools require two or more econ classes. In fact, Wharton is the top-ranked business school and their business program is actually an *economics* program. They don’t have finance/accounting/business degrees. Instead, they have an Economics degree with the various business concentrations. Again – the top business school in the country is an Economics program.
What about at the other end of the spectrum? I live in Florida. Every single Florida state school requires both Micro and Macroeconomics for business majors. These schools include everything from Florida State University to the local Florida state college down the road. I didn’t look at other state-run higher education systems in other states. There are a lot of states…
I teach at a private Catholic university. We’re listed in something called ‘The Newman Guide’ which recommends 17 Catholic schools. Many of these are liberal arts schools, but the list also includes Catholic University of America, which is an R1. Most of these schools also require two or more Economics classes in their Business major programs. The only exception is University of Dallas, which has Economics in the core curriculum.*
So, overwhelmingly undergraduate business programs across the country require two economics courses. But, why? The students are often not happy to be there, and I’ve even heard business professors demean the math as performatively rigorous and superfluous. They argue that plenty of people get rich or are otherwise successful without all of the quantitative skills that economics leverages.
I think that the fear of math is both a red herring and a scapegoat. Rather, Economics confronts students with the liberal arts – whether they like it or not. Be careful. Liberal Arts are not the same as Humanities. They include argumentation, the ability to write and communicate, clear and consistent logic, and, yes, even math. Accounting can tell you how to keep track of the money, but it doesn’t include a theory for when you should produce more or less in contrast to your competitors. Finance does better since it has the time value of money and ‘with vs without’ analysis. That’s closer to marginal thinking. But finance lacks a theory of markets outside of portfolio theory and arbitrage.**
This is a “guest” blog post that I asked Google Gemini Pro to write. Data centers are increasingly becoming a political issue in communities across America. People are asking questions like: “Why do we need these things? How much water will this use?” Because these are sometimes referred to as “AI Data Centers,” people might assume that data centers are primarily about creating cat memes and fake videos. And it’s true that’s a part of AI, and it’s true that much of the new data center construction is for AI.
But… data centers have been around for a while. People are only now taking notice of them, for the most part. To better understand this issue, I asked — what else? — AI to explain how much data centers are used in our daily lives. AI in this case means Google Gemini Pro.
I’ll paste the full guest post below, but I want to point something out first: this blog post makes no mention of AI. Instead, it talks about: GPS and mapping apps; almost everything you do if you work in an office; credit cards and digital banking; news and social media. All of these things rely on data centers and would cease to function without data centers. That’s not because I asked Gemini to leave out AI from the guest post — when I followed up on this omission, Gemini said “It was a calculated omission—partly to keep the focus on the immediate ‘analog’ shock to daily life.” Most people probably wouldn’t care of they lost the ability to create funny images with AI. They would care if they lost all of their photos, access to their Dropbox account, and the ability to send email.
You could interpret all of this as saying we are “too dependent” on data centers and the modern Internet. You could also say we are “too dependent” on electricity. Or modern plumbing. Or modern supply chains. Or agriculture. Modern life is based on modern technology. I don’t know if it really makes sense to say we are “dependent” on these things, other than that we use them and they are beneficial.
Anyway, on to the guest post from Google Gemini Pro:
The Day the Cloud Evaporated: Life After the Data Center Collapse
Imagine waking up tomorrow morning in your suburban home in Ohio, or your apartment in Seattle. You reach for your smartphone to silence the alarm, but the screen is a stubborn, glowing rectangle of error messages. You try to check the weather, but the app’s spinning wheel never stops. You try to text your partner, but the message stays “Sending…” until it eventually fails.
This isn’t just a bad Wi-Fi connection. Every data center on Earth—those massive, humming warehouses filled with silicon and cooling fans—has vanished. In an instant, the “brain” of the modern world has been lobotomized. For the average person in the United States, life wouldn’t just slow down; it would fundamentally reset to 1950, but without the physical infrastructure of 1950 to catch the fall.
Economist Writing Every Day 