What Will End The AI Bull Market?

James BaileyLeave a comment

It’s feeling like the late ’90s, with an impressive new technology pushing tech stocks and the broader US market to all-time highs. Retail investors are using new platforms to get in on the action, tech companies are doing more IPOs to take advantage of the higher stock prices, and other companies are trying to boost their stocks by saying they are pivoting to the new technology (though often they aren’t really changing).

The excitement drives valuations to record levels:

Shiller CAPE Ratio

In the ’90s, the internet really was a transformational new technology that would enable lots of profitable new companies. But the market got ahead of itself, a bubble that led to a crash- the S&P fell by almost half, while the tech-heavy NASDAQ fell by over 3/4 and took 15 years to recover.

History rhymes, but it doesn’t repeat exactly. I don’t currently expect a big crash driven by AI stocks; it helps that unlike in the ’90s, many of the big players are currently profitable. But I also don’t expect the NASDAQ to keep posting 20+% returns every year.

If the AI bull market doesn’t end in a dramatic crash, how will it end? It’s already shrugged off a war. A US recession is unlikely this year, though plausible next year.

The end I see slowly approaching comes from crowding out. What Robert Solow said about computers in 1987 is true about AI today: you see the AI age everywhere expect the productivity statistics. There’s only so much money to go around in markets when productivity growth is unexceptional and savings rates are falling.

We’re already seeing the war hit certain markets (if not US stocks). Iran’s gulf neighbors are now putting lots of money into missile defense, money they now won’t be spending on data centers or gold (down 16% from pre-war), and everyone else has to spend more on oil.

Interest rates have been rising- partly due to central bank attempts to fight inflation, partly due to ongoing high rates of government borrowing, and partly due to financing the AI buildout itself. Higher rates make it more expensive for companies to invest in the physical AI buildout, and make investors discount future AI revenues more while making bonds a more attractive substitute for stocks today. 10-year TIPS now yield 2% over the inflation rate, a sharp contrast to the 2021 stock boom when they yielded less than inflation. If I were older I’d be loading up on TIPS, and even at 38 I’m starting to get tempted.

Trying to call the top exactly is a fool’s errand, but if I were feeling foolish, I’d point to the big upcoming IPOs. SpaceX just filed for an IPO that would be the biggest ever both for the amount of money raised ($75 billion) and the total company valuation ($1.77 trillion). This shatters the previous records for the biggest overall raise ($29 billion raised by Saudi Aramco when it went public in 2019) and the biggest raise by an American company ($18 billion raised by Visa in 2008). OpenAI and Anthropic are likely to follow with IPOs that would also break the previous records- making 3 companies each trying to raise more than the $45 billion raised by the entire US IPO market in 2025. Even if the process of going public doesn’t reveal any flaws in the companies, that money has to come from somewhere- and it takes up a substantial proportion of all net inflows to US stocks in a typical year (IPOs plus new money into existing stocks).

In short- where will the money come from? What are investors going to sell in order to buy into these IPOs? Technically they could do it all with cash, but I think it’s at least plausible that they start selling other stocks. The selling pressure will continue after the IPOs as employees of the newly-public companies see their stocks vest and other early investors become able to sell off.

I’m not trying to time the market. Even if this is a ’90s re-run, we could easily still be in the 1998 buildup, not the 2000 peak and crash. But I am diversifying. US stocks are currently the world’s most expensive. Investors value US stocks that highly because there’s a real chance that US companies are profitably building the technologies that will drive the future. But there’s also a real chance they aren’t– and if that state of the world comes to pass, I’d prefer to own a significant chunk of bonds, foreign stocks, and real assets.

The “Reality Index” of Price Inflation Isn’t Grounded in Reality

Jeremy Horpedahl1 Comment

Over the years, many people have tried to create alternatives to the CPI for measuring inflation. Probably the most famous is “Shadow Stats,” which Tim Lee has convincingly shown isn’t actually measuring price inflation (it’s just adding a fixed factor to the CPI).

But the CPI critics keep coming. One that was recently released is called the “Reality Index.” This index tries to improve on the CPI-U in two ways. First, it uses fixed weights for the items in the basket, and importantly it uses the 2024 weights and applies them to past years (this is called a Paasche index). Second, it takes out some BLS prices to avoid using hedonically adjusted prices, and other price calculations that the Reality Index author thinks are weird.

Both of these changes are problematic. I will explain why.

1. Fixed Basket of Goods/Services Doesn’t Make Sense

Many critics of the CPI complain about the shifting weights in the CPI. “We just want to measure the cost of a fixed basket over time.” But measuring a fixed basket over time isn’t actually that useful. I will explain why in a moment. But that’s not even what the Reality Index does! Instead, it takes the 2024 CPI weights (which come from the Consumer Expenditure Survey), and then consistently applies those weights to past years. The Index isn’t measuring the cost of a fixed basket of goods from some past year — it is using the 2024 basket, and assuming that’s what people consumed in the past.

The author of the Reality Index, Tom Elliott, is either confused about this or is being deliberately misleading, for example in a recent WSJ essay promoting the Index, he says “That same basket, the one the government says rose 1.87 times since 2000, has actually risen about 2.4 times.” But that’s false. To do that calculation, you would need to use the 2000 CPI weights and follow them forward to 2024 (this is called a Laspeyres index). Instead, he uses the 2024 weights and follows them backwards. He could do the calculation that he references in the WSJ essay, but he does not.

To see why this is a bad approach, let’s compare the weights in the Reality Index with a few past years. I have done my best to translate the weights for the 10 categories listed on this page to actual BLS categories, though I will admit that none of their category weights matched exactly to what I found at BLS. But I’m pretty confident it is correct.

I am also pretty confident that the “discretionary” category is just a residual for everything that wasn’t in the other 9 categories, though I can’t find them explicitly saying this. Yellow highlighting indicates the category in past years was smaller than the 2024 weights. Green highlighting indicates past years were larger weights.

The first thing you might notice is that the CPI weights have changed significantly over time. Relative to 1970, housing/shelter gets almost twice as much weight today. Conversely, groceries/food at home gets about half the weight today as it had in 1970. The “discretionary” category (the residual to make it add to 100%) used to be 30 percent of a household budget, using this approach! That should really give you pause: do we really think a typical household in 1970 considered 30% of their budget to be “discretionary”? I highly doubt it. That discretionary category includes clothing, which was over 10% of household spending in 1970 (it’s around 2% today).

Related to that, you may also notice that categories which have had above average inflation over this time frame — such as housing, healthcare, and education — all have bigger weights today than in the past. Meanwhile, food and clothing have seen less price inflation, but they are weighted much less. This process will tend to overstate inflation of the past, as the CPI in 1970 placed less weight on, say, housing, so when you put more weight on it, of course the inflation rate will go up. And indeed, as the Reality Index’s historical analysis shows, the biggest gaps in inflation between the RI and CPI were in the 1970s (4.9% gap in 1979 and 4.7% gap in 1978). But this is ahistorical: people were not spending 37% of their budget on shelter in the 1970s! In fact, they were spending almost as much on groceries in 1970 as they did on shelter.

The Reality Index is essentially projecting backwards to a fake reality of the past, because it uses the 2024 weights in all past years. But this isn’t capturing anything real about the world, and it is at best an interesting thought experiment. Of course, part of the reason people now spend more of their budget on housing and healthcare is because they have gotten more expensive and to some extent crowded out other spending. But they are also categories we might expect demand to increase as incomes increase (normal goods). And notice this is the opposite of the standard critique of the CPI: as things get more expensive, critics claim the CPI assumes people spend less on those items. Instead, the CPI-U weights are updated each year based on the latest Consumer Expenditure Survey data, and goods/services with higher rates of inflation now consumer more of the weight of the CPI than in the past.

(*Note: the “pet” category is listed as 0% in 1970 because BLS didn’t itemize it separately due to it being so small. That’s of little consequence, since it is such a small share in every year — I’m surprised they didn’t just stuff pets in the discretionary category.)

2. Swapping Quality-Adjusted Measures for Nominal Prices is Often a Bad Idea

Using the 2024 weights for past years is reason enough to not find the Reality Index useful. But let me just say a few words about the substitute prices that the Reality Index uses. The changes are either trying to use something that isn’t hedonically adjusted for quality, or to overcome some of the strange calculations, especially for housing and health care.

Continue reading →

Urban Homesteader Starts with Garden Beds and Chickens

Scott Buchanan4 Comments

Somewhere in the vast metropolis that stretches from Boston to Washington lives a friend of ours with a long-term dream.  To protect her privacy, I will not give her name or town. For over thirty years she has wanted to do some form of homesteading, where you raise most of your own food, plus some extra to sell for cash. She and her husband contemplate moving someday to a rural area in the South, where they could buy cheaper land in a warmer climate to raise goats or pigs or cattle, and grow more extensive crops.

However, that move just never happened (so far), what with the usual limitations on jobs and finances. She decided a few years ago, though, to not just keep putting food production off forever. She is doing what she can, with considerable help from her husband, on an urban/suburban lot of just over a quarter acre.  He constructed numerous raised beds in an area that was formerly just grass, and had many trees taken down to admit more sunlight. She sprouts seeds into plants indoors, to get a head start in the spring.  

It started about ten years ago, with just two raised beds. Now the garden area looks like this:

….

Those are pictures I took near the beginning of May. By the end of May, the gardens had exploded:

Plantings there include potatoes, onions, squash, peas, peppers, garlic, tomatoes, strawberries, arugula, and lettuce. The brassicas such as cabbage, broccoli, kale, and cauliflower are covered with a tent; otherwise, cabbage moths can decimate these plants. In a rock bed they have horseradish and comfrey. They have four blueberry bushes. The next big project would be an asparagus bed.

For livestock, they put in chickens about four years ago. In the foreground is a self-contained coop with about 8 birds, and behind it is a second coop with a run behind it, which houses about 18 birds:

They are raising dual-purpose chickens, which are pretty good egg layers, and OK for meat. (There are some breeds that are champs at laying eggs, and others like Cornish Cross whose purpose in life is to grow to eating size in an astonishing 8 weeks). All told, they get some 7-10 dozen eggs a week, spring/summer/fall. This is enough for them to eat and have plenty to sell or give away. In winter, with the cold and shorter daylight, egg production drops to 1-2 dozen/week. To transform a walking, clucking bird with feathers into breasts and drumsticks is a task I will gloss over here, but that is something that homesteaders also must do.

The main ongoing work with their chickens is filling the 7-gallon waterers every couple of days, and throwing a scoop of feed onto the floor of each coop every day. These birds get a “salad” of greens at least once a week, for variety. Here is a shot of the “girls” eagerly pecking away at their dinner; I see at least one egg on the ground in the background:

Chicken poop is pretty nasty, but it is managed by a deep bed system. There are several inches of straw in the bottom of the coops and the run. The birds continually dig around in the straw and mix it. That seems to dilute and dry the poop enough that the “farmers” only need to change out the litter a couple times a year. It just goes on the compost pile, to become fertile planting soil.

Chickens seem to be the most popular animal for budding homesteaders. They are called the “gateway animal”, to get you started/hooked. They tend to require little management, and are versatile eaters, so you don’t need to feed them just purchased grain. Some homesteaders feed them select table scraps, and even raise worms to feed the birds. If you have a large yard or pasture, you can put chickens in a movable “tractor” coop during the day, to forage for insects and greens in the fresh grass under the tractor for that day’s position.

Regulations on selling slaughtered meat are onerous, but it is easy to sell fresh eggs. In their township, chickens are allowed, but no roosters. (No one wants to hear crowing at 3:00 AM). So, our friend’s chicks that hatch out as males end up going to “freezer camp” just before they fully mature. Livestock such as goats and pigs are legal. Our friend wanted to raise a couple of pigs (pigs can also put on weight at an impressive rate, mushrooming from a 50-pound piglet to a harvestable 400-pound hog in 6-7 months). Her husband, however, declined to support that odiferous project.

Growing food is one thing, preserving it for later eating is another. She wrote me:

I can everything. Fruit, jams, veggies, potatoes, meat, fish, and meals. I have chili in jars, along with lamb stew, and onions for Frech onion soup. I make spaghetti sauce too. Yes, I’ve canned our own homegrown chicken.

Since [the storage room] stays cool in the winters (60ish F) I can store hard skin squash and keep fresh potatoes for frying or baking til January or February. I also dehydrate herbs/veggies and meat and fruit. Some veggies don’t can well, they get mushy like zucchini.

“Canning” in this context does not mean sealing into metal cans like you see in stores. It usually means putting the food in special glass “Mason” jars, heating them in a hot water bath (or, better but more work, in a pressure cooker) to sterilize the contents, then sealing them with a lid. Seems like a lot of work, but I am told by friends from the old South that canning your vegetables was a normal household activity there well into the 1960s or so.

Finally, our friends have a beehive on loan from a neighbor. Zoom in to see the bees going in/out at the bottom:

I found it inspiring to see what this couple was able to accomplish in the way of food sufficiency in a quasi-urban setting, and I wish them well in their quest to relocate to where they can grow their own red meat and hear their rooster crow.

A thought on the SpaceX IPO

mdmakowskyLeave a comment

The SpaceX IPO is set for June 12th, with an anticipated market cap after day one between $1.5 and $2.5 trillion. Most of that valuation is based on the prospect of dominating the market for satellites, putting data centers in space, and the endless demand for computing power from AI. It is essentially an AI-related market power play.

I have no speculative insight into the value of SpaceX stock as an investment, but I am an inveterate, unrepentant consumer of irony. An IPO is a speculative investment, but it’s also the act of becoming a publicly held company. A large part of being a public company is getting the accounting right. Modern accounting has all kinds of informational value, but from the point of view of large companies it’s mostly about minimimizing taxes while maximizing perceived value. Both of those ambitions include strong incentives for malfeasance, which is why we have audits, financial regulation, and the IRS. The IRS and financial regulation have been defanged, however, mostly due to a lack of personnel from aggressive destaffing, at least some of which you can lay at the feet of DOGE. You can’t audit a massive company effectively without accountants.

Or can you?

I can’t think of a technical task that is more perfectly suited to AI than auditing a public companies accounts and SEC filings. You feed AI a billion previous filings, all of the associated laws and regulations, and then flag all the records previously found in violation. Then you feed it new ones and say “show me the violations and discrepancies in rank order of dollar value.” A hundred good accountants using a dedicated AI, that’s exactly the kind of story that leads to the order of magnitude increase in labor output that the biggest proponents of AI are looking for.

Never forget that the event that initially popped the dotcom bubble was Microstrategy getting caught cooking the books.

I know you can’t write history like a novel, but “IRS, previously destaffed by Musk-headed DOGE, is forced to use AI enabled audits and finds massive revenue discrepancies, leading to panicked sell-off of Musk-headed IPO record holding company and kicking off AI stock sell-off”…that’s too easy, right?

Would you steal a lemon?

Joy BuchananLeave a comment

My latest at EconLog is

Would Hasan Piker Steal A Car?

Click the link above to read but here are some quotes:

Hasan Piker implied that he might steal a car if it carried no consequences. In the interview, author Jia
Tolentino also casually admits to shoplifting lemons from Whole Foods. Although petty theft is common, the interview clip spread quickly …

In my recent paper with Bart Wilson, “You Wouldn’t Steal a Car: Moral Intuition for Intellectual Property,” we test how people think about taking different types of goods.

What would Piker think of a world where the “microlooting” he claims to approve happens at scale?

Absolute Measures of Portfolio Performance

Zachary BartschLeave a comment

The basic idea is that we want to compare the performance of different portfolios or their managers. This is relatively easy as long as the portfolios contain the same assets. Then, the portfolios are simply characterized by the different weights among the different assets. But how do we compare the performance of portfolios whose assets are different? In finance, we usually assume that everyone can invest in everything. But there are plenty of cases in which that’s a bad assumption: when clients want exposure to particular industries, when there are statutory limitations on holding certain assets, or when an individual company is considering specific projects within the same company under conditions of scarce financing.

The most primitive step is to compare the return and standard deviation of two different portfolios. However, higher risk investments tend to have higher returns in dynamic equilibrium. So, if we were to compare the returns of a tech company to a utility company, then we’d often see the tech companies performing better. But, if we compare the volatilities, then the utility companies would tend to perform better. Sharpe stepped in with a ratio to express the excess return (benefit) per standard deviation (the cost). This way, we can compare the price of volatilities between two portfolios. We’ll stick with just these basic 3 measures: return, standard deviation, and Sharpe ratio. (Others do exist)

Let’s put some meat on this with an example. Say that we have two portfolios, each composed of different assets. There’s a utility portfolio that’s composed of NEE, DUK, and SO. There’s also a tech portfolio that’s composed of AMD, MSFT, and NVDA. Both portfolios have weights of (0.33, 0.33, 0.34).  The results of the utility versus the tech portfolio are:

  • Returns: 14.2% vs 136.3%
  • Standard Deviation: 14.9% vs 32%
  • Sharpe: 0.684 vs 4.134

Goodness me! The tech portfolio returns much more in absolute terms and much more per unit of risk. It’s twice as volatile as the utility portfolio, but the returns are almost ten times as high. If you could, then many of us would choose the tech portfolio over the utility portfolio. But, what if, for one reason or another, you can only invest in one of the two industries? Or, what if you want to invest your money with a skilled manager, rather than a risky one?

One way to tackle this problem is to introduce the Markowitz cloud. Specifically, we can essentially list out all of the possible portfolios along with their return and standard deviations. Then, we can compare the actual performance to the entire menu of possible performances within each set of assets. Below are the possible performances for the utility (left) versus the tech (right) portfolio. The actual portfolios are marked with an X.

One way to evaluate the two portfolios is to compare their return, standard deviation, and Sharpe ratio to the other candidates that were achievable with the same assets. As we can see, conditional on the assets, neither portfolio minimized the volatility, maximized return, nor maximized the Sharpe ratio. Furthermore, assuming that the realized rate of return was the goal, neither portfolio minimized the conditional volatility. Assuming that the realized volatility was the goal, neither portfolio maximized the conditional return. Below are two tables that describe some candidate alternatives and how they differ from the realized portfolio.

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Read Grant’s Memoirs

James BaileyLeave a comment

I heard so many recommendations to read Julius Caesar on the Conquest of Gaul and Winston Churchill on the Second World War– and the recommendations were right. We’re incredibly lucky that some great wartime leaders also happened to be great writers who chose to take the time to share their perspective on the history they helped make.

I rarely heard Ulysses S Grant mentioned as being in the same class of writer- but after reading his memoirs I think he should be. He was obviously a central wartime leader like they were, the highest-ranking general in the victorious Union army by the end of the US Civil War. But I’d never heard how he was also a great writer. He makes history like the campaigns of the Mexican and Civil wars feel understandable, while also sharing funny human stories. Some of these asides feel like they could have been written by Mark Twain, who did in fact help Grant edit and publish his memoirs.

It’s the rare doorstopper book that I wish were much longer- Grant was a two-term US President but his memoirs don’t cover those years at all. I don’t know how much of this is because he wanted to avoid the topic (he’s usually considered a much better general than president) and how much is that he simply ran out of time by dying of cancer.

A few highlights to give you an idea of what Grant was like. Certainly more like a modern economist than I expected:

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The US is Building a Lot More Data Centers Than Five Years Ago, But We Are Still Building More Warehouses

Jeremy Horpedahl1 Comment

Data centers seem to be popping up everywhere. And based on the value of current construction, the US is indeed building a lot more data centers than we were in 2020 or 2021, about four times as much data center construction (inflation adjusted).

But… did you know that we build a lot more good-old manufacturing than data centers? Almost four times as much in recent months. And that’s even after a decline in manufacturing construction over the past year and a half.

The US also builds about the same amount of warehouses and chemical plants as we do data centers. Data centers may exceed those two categories in a few years, but for now they are pretty similar.

Keep in mind that manufacturing and chemical facilities also use a lot of electricity and water, and have plenty of local negative externalities! Warehouses probably have a lot less resource consumption and external effects, but it’s not zero either.

Are data centers popping up everywhere? Well, people are certainly noticing them. But so are lots of other types of buildings, which rarely register more than a peep from concerned citizens and local media, unless there is some clear and obvious external effect.

Guide to Using Microsoft’s Free “Scan Document to PDF” PC App

Scott BuchananLeave a comment

Regarding Free PDF Scanning Apps for Windows 11

According to Claude:   Windows 11 includes a built-in “Windows Scan” app (free in the Microsoft Store) that lets you scan documents directly to PDF — simple and reliable for everyday use. “Adobe Scan” offers a free mobile companion but also works via browser. For more features, “NAPS2” (Not Another PDF Scanner 2) is a popular open-source option with batch scanning, OCR, and direct PDF export. “IrfanView” with its scan plugin is another lightweight choice. For advanced control, “VueScan” offers a free version with core functionality. Most modern all-in-one printers also bundle free scanning software compatible with Windows 11.

Why I Chose “Scan Document to PDF”

My HP scanner software seemed pretty snoopy, not localized to my own PC. Not that I have anything dire to hide, but I’d rather not have my private affairs shooting off to a server who knows where. So I tried the built-in Windows “Scan” function for scanning documents on my trusty ink-jet printer/copier/scanner. It would run pages through the feeder, but then freeze up.

I’ve had mixed experiences with free software, often it gratuitously installs crap-ware on your PC. But surely not Microsoft… so I downloaded the free “Windows Fax and Scan” app mentioned by Claude. It did work, but was a bit clunky and limited. You have to first save a file in some graphic image format like PNG or JPEG, then go to Print, and choose “Microsoft Print to PDF”.

But then, I installed another free Microsoft app, “Scan Document to PDF”.  That seems like a sweet spot here. It seamlessly scans to PDF, but has a good deal of extra functions that are intuitively accessible. It can save files as images like jpg if that is what you want. You can activate OCR to make a scanned document searchable. You can scan individual pages, and decide which ones to bundle into a pdf file. You can brighten or rotate pages, etc.

Go to https://apps.microsoft.com/detail/9nwn2l7ncwlx?hl=en-US&gl=US (or go to the Microsoft Store and then to the app) to download and install. Finally, here are the user instructions I typed up as a reminder for my own use:

INSTRUCTIONS FOR “SCAN DOCUMENT TO PDF” ON WINDOWS 11 PC

( 1 ) Click Start icon, to left of Search bar at bottom of Windows screen. Click on Show All, for a list of all programs. Scroll down to Scan Document to PDF and click.

( 2 ) Check scan settings showing on left hand side. Can adjust them here, or by clicking Profiles button.    Paper Source: Glass for one sheet on scanner, or Feeder for auto feeding pages.    Resolution: Suggest 300 dpi.      Bit Depth: Color for a color scan, or usually Grayscale for a black & white final document (sometimes gives better resolution than the “Black & White” setting). 

( 3 ) Click Scan button (top left) to initiate scan. (Note: on the side of that button is a dropdown for options like setting up Batch Scans.)

( 4 ) Scanned pages will show on screen. To save them all as one PDF, click the Save PDF button. Default pdf file destination is /Downloads/ folder. (To save only selected pages into the final PDF, click on the dropdown on side of that button)

MORE OPTIONS

( 5 ) BEFORE SCANNING: (A) You can set up a different Profile of scan settings (scanner device, feeder, resolution, etc.) by clicking on Profiles button.  (B) Click on OCR button to make final pdf searchable (not just a static image).

( 6 ) AFTER SCANNING:  (A) Click Import to import pages from existing PDF, that you can then add to newly scanned pages.  (B) Click Image button and select a page to crop, brighten, rotate, make black&white, etc.

Tall poppies don’t get the calls

mdmakowsky1 Comment

Ask anyone who grew up playing basketball as the tallest player on the court and they will, each and every one of them, tell you that players were allowed to foul them harder and more often. If you were tall you didn’t get the calls, full stop. Why? We could sort through a host of mechanisms, but they all boil down to “Being tall is an unfair advantage. It’s only fair that I, the shorter opposing player, am allow to slap you, chop you, kick you, trip you, grab you.” To be honest, I don’t think this is a particularly shocking phenomenon. “Tall poppies get cut down” is a cultural cliche for a reason. What is interesting is that it persists even amidst billions of dollars in market incentives pushing in the other direction.

The latest version is happening right now as the Oklahoma City Thunder are currently doing their best to end Victor Wembanyama’s nascent career each and every night, and the referees seem uninterested in realigning the incentives otherwise. At the moment the Spurs are currently up 65-43 in game 4 of the series. If the series goes 7, there’s at least a 20% change Wembanyama doesn’t make it to the end. Will they break his foot smashing down on it, break his leg tripping him, or dislocate his shoulder yanking down on it from a leveraged position? Don’t know, but they’re doing their best to make it happen.

Caitlin Clark came into the WNBA as the single greatest talent prospect in the history of women’s basketball. The abuse she suffers is well documented. Wayne Gretzky was the greatest hockey player of all time, but he was arguably only allowed to reach his potential because Bobby Orr’s careers was cut in half by a league that allowed teams to abuse him with little to know punishment. Bobby Orr’s sin was that he was such a better skater than everyone else that, if allowed to play without constant grabbing, hooking, and abuse tantamount to aggravated assault, he would have walked away with too many goals, wins, and Stanley Cups. It wasn’t fair that he was so much better, so they let the players even the odds. Having watched him limp away after only 7.5 seasons, the NHL took the unofficial position that Gretzky’s teammates (specifically, Dave Semenko and Marty McSorley) held carte blanche to assault anyone who touched Gretzkey. While perhaps not a culture-shifting solution, Gretzky did have a 20 year career that brought hockey to new heights of popularity, so it was ostensibly effective.

But none of that gets at the underlying economics. Elite players bring big audiences to sporting events, which in turn, brings in big money for everyone. The owners, players, and everyone in between gets richer when elite players shine under the biggest lights. So why chop them down? Well, first we have a collective action problem to solve, because, yes, the entire market benefits from superstars, but their opposition during the course of play in any one game have the individual incentives to do whatever they can get away with to win. That’s why we have referees, commissioners, and a players union: to solve those collective action problems. All of those rules and institutions are in place specifically to align incentives and bargain for outcomes that maximize welfare. So why aren’t they working?

When you find cliches at the front of your mind, decent chance you’re running up against psychology and behavioral economics. And as Victor Wembanyama is learning each and every night of the playoffs, “tall poppies get cut down”. It’s not fair that he’s the first 7’5″ player with elite NBA level skills to ever play the game. You know, I was never a fan of watching Shaq play basketball per se, but I always knew he should have scored at least 40 points every night. Yes, he committed 7 offensive fouls every game, but he also received 25 fouls that went uncalled. Players were allowed to maul him because it was unfair he was so much bigger, stronger, and more athletic. His career was only as long as it was because his body could endure the abuse. There has never been another player in NBA history who could have survived even 3 seasons receiving the abuse he did.

Putting aside simple behavioral explanations, we also should consider the possibility that NBA team owners and players are so far down the diminishing marginal returns to wealth, that the median participant would actually prefer to earn less money in order to maximize their own chance at winning a championship. They want parity, of a sort. Parity, but only once the playoffs arrive. The regular season is too long and everyone does, in fact, want to make money, so the abuse is minimal, but once the playoffs arrive, the collective preference is for parity delivered via weaker rule enforcement. There are only so many elite players, but everyone is capable of low-level violence. This preference for postseason parity may also explain why Oklahoma City’s best player, Shai Gilgeous-Alexander, has the reputation for simulating being fouled on every play. If you’re going to get fouled no matter what, you might was well maximize the probability of getting a foul call by forcing the referee to be observed observing the incident.

And, to be clear, parity may in fact be revenue maximizing. Just look at the NFL – the entire structure is designed to maximize the number of franchises who believe at the beginning of the season that their team has a chance to win it all. The players are relatively anonymous compared to NBA superstars, but fans are mostly there to root for laundry, and in the NFL, so long as that laundry doesn’t say NY Jets on it, there’s at least a glimmer of hope. Counter point, just look at the NFL. They understood that each team, especially once the playoffs started, had strong incentives to try to end the opposing quarterbacks career on each and every play. So the NFL introduced a battery of rules to protect quarterbacks, and it seems to have worked.

So maybe I’ve come full circle. Maybe this is what the NBA wants. But I really, really it’s hope not. Wemby is special. I’d like to see the very most of what he can become.