Uncategorized – Economist Writing Every Day

Learn to Ode 2026

February 28, 2026March 14, 2026Joy 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.

Supply and demand has a mind of its own

February 23, 2026February 22, 2026mdmakowskyLeave a comment

I think there’s a lot of crosstalk about AI in part because proponents tend to focus on the immenient supply side shifts from innnovation, while critics seem to happily observe failures to stoke consumer demand. Not being much of a futurist, I’m largely content to watch and wait with minimal speculation. At the same time, I see signs of increasing demand for other products, in blatant disregard for past and present identity politics. It’s probably good to remember that supply and demand are less a beast to be wrangled than a rocking ocean to be adapted to.

Learning the Bitter Lesson at EconLog

February 21, 2026Joy BuchananLeave a comment

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“.

Bad ideas are costly

February 16, 2026February 16, 2026mdmakowskyLeave a comment

I know this has gotten coverage at other econ blogs, but I’ve been thinking about this paper for a couple days now.

Combine this with the classic Besley and Burgess paper on the political economy of government responsiveness to natural disasters, and you have a perfect Venn diagram of how bad ideas and bad political incentive alignment can lead to truly awful outcomes. An unfortunately “evergreen” mechanism in political economy.

Markets adjust: Superbowl quarterback edition

February 9, 2026February 9, 2026mdmakowskyLeave a comment

Yesterday’s super bowl was fun for a variety of reasons, but your 147th favorite economist was especially happy to see that markets continue to keep things interesting. The NFL was a “only teams with elite quarterbacks can win” league…until it wasn’t. After Brady, Manning, Brees, and Maholmes winning two decades of Super Bowls, we have back to back years of decidedly average quarterbacks winning (within-NFL average, to be clear. These are all objectively incredible athletes). How did this happen? Is it tactical evolution, flattening talent pools, institutional constraints, or markets updating? The answer is, of course, all of the above, but updating markets is the mechanistic straw that stirs the drink.

The NFL is a salary capped, which means each team can only spend so much money on total player salaries. As teams placed greater and greater value on quarterbacks, a larger share of their of their salary pool was dedicated accordingly. These markets are effectively auctions, which means eventually the winner’s curse kicks in, with the winner of the player auction being whoever overvalues the player the most. Iterate for enough seasons, and you eventually arrive at a point where the very best quarterbacks are cursed with their own contracts, condemned to work with ever decreasing quality teammates. Combine that with a little market and tactical awareness, and smart teams will start building their teams and tactics around the players and positions that market undervalues. And that (combined with rookie salary constraints), is how you arrive at a Super Bowl with the 18th and 28th salary ranked quarterbacks.

Whenever a market identifies an undervalued asset (i.e. quarterbacks 25 years ago) there will, overtime, be an update. Within that market updating, however, is a collective learning-as-imitation that eventually results in some amount of overshooting via the winners curse. This overshoot, of course, may only last seconds, as market pressure pushes towards equilibrium. In markets like long term sports contracts or 12 year aged whiskey, that overshoot can be considerable, as mistakes are calcified by contracts and high fixed cost capital.

What does this predict? In a market like NFL labor, I’d expect a cycle over time in the distribution of salaries, iterating between skewed top-heavy “star” rosters and depth-oriented evenly distributed rosters. At some point a high value position or subset of stars are identified and distproportionately committed to, but the success of those rosters eventually leads to over-committment, so much so that the advantage tilts towards teams that spread their resources wider across a larger number of players undervalued teams whose fixed pie of resources are overcommitted to a small number of players. That’s how you get the 2025 Eagles and 2026 Seahawks as super bowl champions.

I wonder when it will cycle back and what the currently undervalued position will be?

IP Paper on Econlog

February 7, 2026February 7, 2026Joy BuchananLeave a comment

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.”

Unweighted Bayesians get Eaten By Wolves

February 2, 2026February 2, 2026mdmakowskyLeave a comment

A village charges a boy with watching the flock and raising the alarm if wolves show up. The boy decides to have a little fun and shout out false alarms, much to the chagrin of the villagers. Then an actual wolf shows up, the boy shouts his warning, but the villagers are proper Bayesians who, having learned from their mistakes, ignore the boy. The wolves have a field day, eating the flock, the boy, and his entire village.

I may have augmented Aesop’s classic fable with that last bit.

The boy is certainly a crushing failure at his job, but here’s the thing: the village is equally foolish, if not more so. The boy revealed his type, he’s bad at his job, but the village failed to react accordingly. They updated their beliefs but not their institutions. “We were good Bayesians” will look great on their tombstones.

They had three options.

A) Update their belief about the boy and ignore him.

This is what they did and look where that got them. Nine out of ten wolves agree that Good Bayesians are nutritious and delicious.

B) Update their beliefs about the boy, but continue to check on the flock when the boy raises the alarm.

They should have weighted their responses. Much like Pascal taking religion seriously because eternal torment was such a big punishment, you have to weight you expected probability of truth in the alarm against the scale of the downside if it is true. You can’t risk being wrong when it comes to existential threats.

C) Update their beliefs about the boy and immediately replace him with someone more reliable.

It’s all fine and good to be right about the boy being a lying jerk but that doesn’t fix your problem. You need to replace him with someone who can reliably do the job.

So this is a post about fascism. Some think that fascism is already here, others dismiss this as alarmism, others splititng the difference claiming that we are in some state of semi- or quasi-fascism. Within the claims that it is all alarmism, what I hear are the echoes of villagers annoyed by 50 years of claims that conservative politics were riddled with fascism, that Republicans were fascists, that everything they didn’t like was neoliberalism, fascism, or neoliberal fascism. Get called a wolf enough times and you might stop believing that wolves even exist.

Even if I am sympathetic, that doesn’t get you off the hook. It hasn’t been fascism for 50 years will look pretty on your tombstone.

Let’s return to our options

A) Don’t believe the people who have been shouting about fascism for years, but take seriously new voices raising the alarm.
B) Find a set of people who, exogenous to current events, you would and do trust and take their warnings seriously.
C) Don’t believe anyone who shouts fascism, because shouting fascism is itself evidence they are non-serious people.
D) Start monitoring the world yourself

Both A) and B) are sensible choices! If you’ve Bayesian updated yourself into not trusting claims of fascism from wide swaths of the commentariat, political leaders, and broader public, that’s fine, but you’ve got to find someone you trust. And if that leads you to a null set, then D) you’re going to have to do it yourself. Good luck with that. It takes a lot of time, expertise, and discipline not to end up the fascism-equivalent of an anti-vaxxer who “did their own research.”

Because let me tell you, C) is the route to perdition in all things Bayesian. Once your beliefs are mired in a recursive loop of confirmation bias, it’s all downhill. Every day will be just a little dumber than the one before. And that’s the real Orwellian curse of fascism.

Drawbacks of Long Term Thinking

January 30, 2026January 30, 2026Zachary BartschLeave a comment

This post is just some thoughts about perspective. I apologize for any lack of organization.

My academic influences include North, Weingast, Coase, Hayek, the field of Public Choice, and others. I’m not an ‘adherent’ to any school of thought. Those guys just provided some insights that I find myself often using.

What lessons did they teach? Plenty. When I see the world of firms, governments, and other institutions, I maintain a sharp distinction between intention and outcome. Any given policy that’s enacted is probably not the welfare maximizing one, but rather must keep special interests relatively happy. So, the presence of special interests is a given and doesn’t get me riled up. When I see an imperfect policy outcome, I think about who had to be enticed to vote for it. We live in a world where ‘first bests’ aren’t usually on the table.

Historically, or in lower income countries, I think about violence. Their rules and laws are not operating in a vacuum of peaceful consent. There is always the threat of violence. Laws are enforced (or not) conditional on whether and what type of violence that may result. All of the ideal legislation is irrelevant if theft and fraud are the lay of the land.

I think about institutional evolution with both internal and external pressures. I’m a bit worried about the persistence of the US republic, or at least worried for its pro-growth policies. I’m not worried about China in the long run. I don’t think they have the institutions that get them to ‘high income’ status. I do think that they are a tactical concern in the short run and that the government does/will have access to great volumes of resources in the medium run. That’s a bit of a concern. But like I said, I’m not super worried in the long run.

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What is the price of obvious lying?

January 26, 2026January 26, 2026mdmakowskyLeave a comment

Pushing beyond the despair and doomerism of “Nothing matters”, the question has never been is there a price for lying in politics, but rather what is the price of lying in politics. Note that “in politics” is doing a lot of heavy lifting here. In day to day life, the price of lying is the threat to your reputation. A reputaton for being untrustworthy is always very costly in the long run. But politics, however, has different layers across which the price of lying is heterogeneous. And yes, there are contexts where that price can go negative.

Put simply, what is the cost here? Is Greg Bovino, head of US Border Patrol, worried about his reputation? Is he worried about future personal legal liability? Is he worried about maintaining cooperative alignment across the administration and within the ranks of the Border Patrol and ICE? There’s a saying in politics – the worst thing you can do is tell the truth at the wrong time. But that’s more relevant to “lying by omission”, about simply abstaining from speaking on a subject so that you are not forced to choose between lying and paying a high political cost. This is different. I’m picking on this one person in the administration because Alex Pretti was summarily executed in the street in cold blood by a thicket of federal agents for the apparent crime of being in attendance and trying to help a woman while she was being pepper sprayed, but it is the subsequent lying that I am concerned with here. It follows a pattern that continues to darkly fascinate me.

Rather than simply “say nothing”, this administration has committed to the broad tactic of stating things that are factually, obviously untrue. That, more important, it is highly likely they know are untrue. That’s not something we’ve seen a lot of before. Politicians were known for being “slick” and “slippery”. For bending the truth, torturing the facts, or managing to fill entire press conferences without saying or committing to anything of substance. This administration, as I’ve said before, is different.

I see two likely explanations:

The price of lying is zero because no one believes anything anymore. The truth is subjective and siloed.
The price of lying is negative because constant and consistent commitment to the party can only be demonstrated by bearing the personal cost of telling obvious lies. In doing so you maintain the group, save yourself from being purged, and everyone in the group lives to fight another day. The net of which is a negative price for lying.

So what is it? Are we through the lol-nothing-matters looking glass, or are we witnessing an administration circle the wagons and solidify their committment to one another by blatantly lying on national television? I’m (perhaps obviously) of the belief that everything matters, that lying does have a cost, but the need for unity is so strong within this administration and it is, in fact, the lying that is holding it together. Until, of course, it doesn’t. Remember the most important lesson of The Folk Theorem – you can sustain cooperation in the Prisoner’s Dilemma, but only until you learn when the game is going to end. Then all bets are off.

Why ICE’s cruelty is only outpaced by their incompetence

January 19, 2026mdmakowsky3 Comments

This paper has escalated from relevant to mission critical

From the summary:

“Who serves in secret police forces? Throughout history, units such as Hitler’s Gestapo, Stalin’s NKVD, or Assad’s Air Force Intelligence Directorate have been at the core of state repression. Secret police agents surveil, torture, and even kill potential enemies within the elite and society at large. Why would anyone do such dirty work for the regime? Are these people sadistic psychopaths, sectarian fanatics, or forced by the regime to terrorize the population? While this may be the case for some individuals, we believe that the typical profile of secret police agents is shaped by the logic of bureaucratic careers.”

The details and history in the paper are illuminating. The economic logic is simple, but it remains fascinating to be reminded of how far the reinforcing incentives of shame, power, and labor market demand can go when trying to understand the world. To recap the obvious

For some the opportunity for cruelty is benefit and others a cost, no doubt heterogeneous across context for many (but not all). The selection effects into ICE officers is obvious.
Shame selects as well. The larger the fraction of the American public that view ICE behavior as shameful and cruel, the fewer and more specific the individuals who will select in.
Labor demand for individuals is heterogeneous in multiple dimension, but it always weaker for those who are broadly incompetent.

Combine those three and you get what we are observing: those with the weakest opportunities in the labor market are selecting into ICE service because they face the lowest opportunity cost. If there is a positive correlation between enjoying cruelty and weak labor market opportunties (which I am willing to believe there is. Few enjoy working with ill-adjusted, cruel people), then the broad incompetence selected into ICE ranks will be stronger. If being ill-adjusted and cruel limits the scale of your social network, leaving you isolated and lonely, then the expected shame of ICE services is lower, selecting for still greater cruelty within officers. Through this mechanism cruelty and incompetence don’t just correlate, they reinforce, until you are left with a very specific set of individuals exercising violent discretion.

To be clear this isn’t a complex or profound model. The individual insights are obvious, but it remains useful to consider them within the framework of a toy model because they emphasize how mutually-reinforcing incentives can create shocking institutional outcomes.