The source, of course, was Avis Car Rental — an AI-enabled transportation company with distributed resources accessible to a highly-educated cohort of high-mobility workers and leisure consumers, uniquely suited to guide the development of society in the 21st century:

Yes, the rental car company. Efficient markets at work. But it did provide me with the opportunity of a very long career:

The broader point is that we are now seeing that which was unthinkable only a few years ago. Another forecast from my passive work that has (unfortunately for markets, but good for my credibility) come true.

Many critics of my work believe I am arguing that “valuation doesn’t matter” in the long-run and they retreat to the safety of their efficient market cathedral. This week we demolish it, because “in the long-run” we’re all dead. And I will not go quietly into that night.

We continue to be in the largest divergence in history between returns and “value.” If this week taught us anything, it’s to strap in — there’s a wild ride ahead.

Read more

You have likely seen the confusing headlines:

Got it? Perfectly clear. To help you understand this complex topic, we bring you Samuel Jackson:

What?

“Iran” no longer exists as a unified political voice. The IRGC, the National Security Council, and the diplomatic class are arguing publicly:

“Following the unexpected tweet from the Foreign Minister about the liberation of the Strait of Hormuz, Iranian society has been plunged into an atmosphere of confusion.”
They also directly called out the “absolute silence” of the Supreme National Security Council and the negotiating team, demanding explanations so the “narrative of the enemy” doesn’t fill the vacuum. — Fars News Agency (IRGC outlet)

“Bad and Incomplete Tweet by Araghchi and Incorrect Ambiguity-Creation Regarding the Reopening of the Strait of Hormuz.”
“Publishing this tweet, without any verbal explanation or at least sufficient written explanations, constitutes a complete lack of tact in communication.” — Tasnim

Now some in the media are, of course, seizing on the confusion to highlight that Trump is once again deeply out to a Taco Bell salad lunch. And I want to emphasize that there can be two truths — Trump can be deeply disturbed AND Iran’s leadership has fractured as the US prevails in the conflict. We have precedent. After victories in Italy, Germany, AND Japan in WW2, internal conflict prevented consolidated messaging. After Hitler’s suicide and contested elevation of Karl Dönitz, pockets of German and Czech military refused to accept the surrender.

The US Navy is fully in control of the Hormuz. Those carriers hanging outside missile range are no longer threatened.

We’ve moved from Iran enforcing a blockade, to the US enforcing a blockade ON Iran. The terms to open the SoH from Iran? “Stop being so mean to us! It’s not fair you’re blocking the way!”

Feels pretty spot on with the outline from exactly a month ago:

This bifurcated dynamic is the foundation of the macro landscape. The Hormuz crude issue is an asymmetric warfare problem that U.S. air and naval superiority will resolve within weeks to months. Once escorts and minesweeping begin, signaling American control, it’s largely over. Marine deployments will likely limit incursion to control of coastal regions, leaving the Iranian people to resolve their remaining internal conflicts. Unlike Iraq, a shadow government embraced by the people is ready to go.

Now I know many readers will say, “You can’t know this!” And they’d be right. There is no “knowing” until it’s over. But it’s pretty much over. There was no 5-D chess. Just math.

The oil story collapsed under its own weight on Friday. Sure, Trump was the catalyst. But the reality that many are recognizing now has been well publicized on these pages — much of the oil was already making it out and demand destruction, particularly in emerging markets has been significant:

By my calculations, roughly 2MMbd in demand has already been destroyed. Had prices maintained at these levels, within six months we were looking at 10-20MMbd. Some of that lost demand will return as prices fall and we restock strategic reserves, but some will be permanently lost. We don’t run HVAC twice as much after skipping for a day, nor do we make two trips to the store to make up for the one we skipped last week. Combined with modestly increased production and (as predicted) removal of restrictions on Russian exports, oil will be increasingly well supplied. Meanwhile, the disruption is likely to prove unhelpful to a fuel likely already at peak demand.

Equity markets have recovered, albeit narrowly (poor breadth). Again unsurprising — “macro” products (SPX) have dominated single stock. It’s “RISK” on, not “specific risk” on. With that said, though positioning remains muted overall as the flow has been dominated by retail inflows and short-covering, the PACE of inflows is among the fastest in history:

I am reminded of the language of 1968:

“And all through the stormy course of 1967 and 1968, when things had been coming apart and it had seemed that the center really couldn’t hold- the rising national economic crisis culminating in a day when the dollar was unredeemable in Paris, the Martin Luther King and Robert Kennedy Assassinations, the shame of the Chicago Democratic convention, the rising tempo of student riots– the silly market had gone its merry way, heedlessly soaring upward as if everything were O.K. or would surely come out O.K. as mindlessly, maniacally euphoric as a Japanese beetle in July. Or as a doomed man enjoying his last meal. One could only ask: Did Wall Street, for all its gutter shrewdness, have the slightest idea what was really going on?” — The Go-Go Years, John Brooks

As history can tell us, 1968 was not “the end.” But it WAS the beginning of the end. With the late 1960s, the IPOs slowed and the torrid pace of retail participation began to disappear despite markets making new all-time highs. By the early 1970s, corporate distress was beginning to restructure the American economy as “old economy” behemoths could no longer cover their mounting pension bills.

My hunch is that this will be similar. Not because inflation will return and the Fed will be forced to hike rates to 13%, as “accommodative” Arthur Burns did in 1974, but because the economy is slowing and restructuring. High-tech buildouts and tariffs are slowly leading to a recovery of domestic manufacturing capacity which has expanded for 48 consecutive months — a new post-2000 record:

In contrast, Services PMI has been below the series average for the last three years. We are slowly healing from our 25 year manufacturing devastation, but that sector has shrunk to ~20% of the US economy and only 8% of employment. Meanwhile, as I hypothesized almost exactly three years ago, services is retreating (pre-ChatGPT btw):

The US economy has undergone a significant shift towards a services-driven economy over the years. However, there has been a recent downshift in services consumption per capita growth, even before the pandemic. This downshift is similar to the decline observed from 1907 to the end of World War II. — Yigaf, May 2023

The late Industrial Revolution was really a revolution in services. Washer women became washing machines. Single-viewing theater performances became “movies.” Singers and orchestras became records. Lamp lighters became light switches. Over this period, lifestyles changed radically. As I posited in 2023, we are on the edge of a similar shift where LLMs and “AI” will radically shift our experience of services from “work” to “products.” And with that shift, we’ll likely see services employment plummet as a fraction of work:

Where this stops, we don’t know. But with self-driving cars, autonomous delivery robots, humanoid robots, and “self-programming computers” either here or on the near horizon, I can rest confidently that while our war in Iran is winding down, our war with the machines is just beginning.

So let’s pivot to the conservative movement…

What’s Left to Conserve?

Why the “Invention of Conservatism” is Fracturing

I had the pleasure of attending the Spring 2026 meeting of The Philadelphia Society. For the uninitiated, this is the intellectual “town square” of the American Right, founded in 1964 following the Goldwater defeat. It was intended as a sanctuary for the movement’s brightest—academics, journalists, and high-conviction activists—to debate the future of freedom away from the immediate, distorting pressures of the next election cycle.

Read more

War Update

In the summer of 1989, I returned from freshman year college to live and work in San Francisco. I held three jobs — mail clerk at a law firm, valet parking attendant, and designing an inventory control system for an apparel company. You can guess which one paid the bills (hint: it paid good tips). But I also picked up my lacrosse stick for the first time in six months and played adult club lacrosse with some of my high school buddies.

I was a mediocre crease defense. Good enough to play varsity at the high school level, but nowhere good enough for Penn. Fine for club. But one day that summer, I pulled an All-American NCAA lacrosse attackman as my coverage. It did not go well. Our goalie stopped a shot, and pitched it out for me to clear. Being clever and lazy, as most 19-year-old men are, I decided I’d pull that attackman off the midfield line, towards me, and increase the space available to my mids. I distinctly remember the look of exasperation on his face — “Are we really going to do this?” He began to jog towards me. I patiently waited. When he pulled far enough off the mids, I prepared to pass. His jog became a sprint. The ball left my stick headed to a midfielder…

Which was when this attackman jumped seventeen feet into the air, picked off the pass, and before he hit the ground had dumped an assist to wide open wing attack. And that was when I knew I had better work harder on that inventory control system. Because my future was not in sports.

The relevance? “Are we really going to do this?”

I know what the headlines say, “Talented upstart defenseman holds all-star attack at bay in early play!” I also know what really happened.

Oil is now transiting the Straits of Hormuz. The US Navy is in the Strait. The IRGC appears powerless to stop them. You’re welcome to disagree. But facts are facts.

Inflation

A “disappointing” inflation report reinforced a few key themes. First, remember that “residual seasonality” has corrupted the seasonally adjusted inflation data we receive. As a result, CPI is overstated in Q4 & Q1 and understated in Q2 & Q3. The February PCE and March CPI captured the two largest seasonal impact months; that is over now.

Read more

We’ve been here before:

Let there be no mistake about the cost of war. We have arrayed an impressive international coalition against Iraq, but when the bullets start flying, 90 percent of the casualties will be Americans. It is hardly a surprise that so many other nations are willing to fight to the last American to achieve the goals of the United Nations. It is not their sons and daughters who will do the dying. Most military experts tell us that a war with Iraq would not be quick and decisive, as President Bush suggests; it’ll be brutal, and costly. It’ll take weeks, even months, and will quickly turn from an air war to a ground war, with thousands, perhaps even tens of thousands, of American casualties. — Senator George Mitchell, Jan 11, 1991

I fielded a call this week from a hedge fund manager who told me I was delusional. His exact assessment was that “Iran has already won.”

It was a perfect, real-time distillation of the consensus analytical trap. He sees the Strait of Hormuz functionally closed, U.S. interceptors being drained by cheap drones, and Brent crude elevated. To a standard model, that looks like an unmitigated U.S. defeat.

If this is an Iranian “victory,” it is the most suicidal victory in modern history. Winning a war of attrition by threatening your own country with a return to the pre-industrial age is only a victory if your goal is martyrdom. And some monolithically ascribe that goal to the Iranian people. I do not. But if Iran has “won” by breaking the global energy plumbing—specifically the structural 3-to-5-year hole in LNG and refining from the Ras Laffan strikes—who are the actual losers?

It is not the United States.

The consensus is screaming about a permanent, 1970s-style geopolitical rupture. But the commodity term structure is calling their bluff.

Look at the COZ6 (Dec 2026 Brent) contract. It is sitting at $79.02. That is up a mere 12.5% from June of last year—a period when the market was completely asleep. This is an absolute joke for a “World War III” energy crisis. The back of the curve is telling you the Strait of Hormuz will be cleared quickly. If you disagree, there are plenty of trades available. The on-the-ground reality is that over 50% of the blocked oil has already found alternate routes. Traffic is slowly opening in the Strait through the Oman coastline (~1.6 MMBpd starting this week), Saudi pipelines are maxed out (7 MMBpd), UAE pipelines are flowing (~1.5MMbpd), and Iran is shipping it’s own oil and tolling additional oil (~2MMbpd). While press headlines scream “$2MM toll!”, that is a $1 per barrel premium for a VLCC. And those deals become free if the IRGC falls. For those counting, that’s roughly 11MM of the 20MMbpd. The threshold for complete replacement, given gains in pipelines, increased production, and likely demand destruction, is 35%. We’re already well ahead of COVID…

Tanker rates are falling, but insurance remains expensive at 4x normal if you can get it. Both are likely to continue to retreat. But impressive as the numbers you may hear sound, that quadrupling of tanker insurance adds about $0.50 per barrel.

And remember that the “lost” 20MMbpd were from an oversupplied 105MMbpd total market. So we’re now delivering roughly 96MM of 105MMbpd pre-war demand. That excludes releases from strategic petroleum reserves (which must ultimately be made up in the future). The net result is that the alarming inventory drawdown of 10.2MMbpd will be lower this week. And likely even lower the week after that. And the 2025 floor of ~7700 mb is important, but we can go lower if needed. Rich countries can afford it. Poor countries cannot. Sucks to be poor, I’m sure. Never given it much thought (since it is 2026, I feel obliged to add the “/s”. At least it’s not March 2020).

Super backwardation in oil markets — prompt delivery at a 30% premium to spot, spot at a 30% premium to Dec 2026 futures — is incentivizing inventory release into markets; and the premium of prompt for both crude and products is destroying demand. Leisure travel is being reduced, work from home is being deployed, and emerging markets are introducing emergency rationing.

More importantly, the imminent arrival of U.S. ground troops fundamentally alters the kinetic math. The moment Marines land, the IRGC can no longer afford to waste their degraded missile inventory lobbing shots at passing tankers. They must pivot 100% of their surviving assets to a defensive, anti-invasion posture. By forcing Iran to fight a symmetric ground war, the U.S. functionally neutralizes Iran’s asymmetric anti-ship campaign. The crude blockage is temporary, even if the UAE LNG hole is structural. If traders actually believed in a permanent oil void, that Dec ‘26 contract would be in the triple digits. Maybe you believe differently. The markets are there for you to place your bets.

With this degree of positive carry, shorting is somewhat pointless. If I’m right, those Dec 2026 contracts fall to $60 (perhaps lower, depending on supply and demand). If I’m wrong, the carry from $79 to $110 (or higher) eats me alive. There is no trade on the short side. So you are hearing the motivated reasoning of crude oil longs in market commentary, and the cowardly voice of “no position” on the other side. I’ll remind you, that my insights took you for a 30% loss in Oil vs Gold last September… or a 44% gain, depending on how you want to look at it. Right now, there is no clear trade in either asset in my opinion.

Where I do think there is a trade, the US 2-year yield has violently reversed more quickly. We watched it spike to a 4.00% high in mid-March, prompting pundits to declare a new regime of structural inflation and endless Fed hikes. That was an illusion. It was a mechanical liquidity event—a VaR shock where levered yield-curve steepeners hit margin calls, and front-end Treasuries were indiscriminately liquidated to reduce gross exposure. Inflation is not the concern. I continue to believe Truflation is the “most” honest reporter of current prices:

But if you don’t believe them, perhaps you should check out Penn State, which, like Truflation, uses current real estate prices:

Today, that 2-year yield has fallen back under 3.80%. The mechanical liquidation is exhausted. The global panic is actually funding the U.S. Treasury market, as capital flees the structurally “doomed” industrial centers of Europe and Asia and floods into the only sovereign safe haven that is a net-energy exporter. But it didn’t reach 3.80% in a straight line. A “stellar” jobs report and rising PMI prices has raised doubts that the Fed will need to cut. First PMI Prices… whatever could it be? Oh… oil.

“Yeah, you’re delusional, Mike. Fine… so PMI is being driven by oil… I get it. But oil is a pass-through to everything else.”

Yes, by and large it is. A doubling of oil prices will raise prices… by about 1.5%. You know what else causes prices to rise? Tariffs. And we’re about to celebrate the anniversary of the largest tariff increase in nearly 100 years… with CPI down 0.4% YoY. Inflation swaps have this figured out… short-term inflation up. Forward inflation down. They did the same thing last year when tariffs were introduced:

“OK… but the strong job report…”

Yeah… about that:

And that’s before we get to the still-not-fixed Birth/Death adjustment, plugging away, adding roughly 100K to-be-revised-away jobs per month:

Which just might leave the BLS in the same position as private credit… “lying.”

And now… what you have all been waiting for…

The Toll Booth: Bitcoin’s Extraction Machine in Practice

Part 2 of “Bitcoin Is Not Sound Money”

Introduction to Part 2

Part 1 established the theoretical machine: Bitcoin’s design hardwires a temporal caste through perfectly inelastic supply, front-loaded issuance, and zero holder accountability. The extraction mechanism is not a bug—it is the system operating exactly as its parameters dictate.

More fundamentally, Part 1 demonstrated that Bitcoin does not fix the pathologies its proponents often correctly diagnose in the existing monetary system. The Cantillon effect is made permanent and immune to democratic correction. Wealth concentration is intensified and stripped of any productive obligation. Rent-seeking is perfected into a “constitutionally protected” (code) activity requiring zero effort.

That was the mechanism. This is what it looks like in the world—what it would become at scale—and why the maximalist endgame would make every problem they identify in fiat catastrophically worse.

Read more

Read more

YIGAFers,

I apologize in advance. This note is asking you to read roughly 5,000 words across two long, dense letters — Radigan Carter’s extraordinary Twitter post and the one I publish below. Market conditions leave me no choice. We are in live conflict with real energy infrastructure offline, a violent bond repricing underway, and a Fed credibility trap colliding with mechanical market plumbing. Half-measures won’t cut it. The stakes require both lenses.

I wrote “The Fed’s Credibility Trap Meets the Flow-Inelastic Unwind” before reading Radigan’s letter. My thesis was already locked from the data: front-end yields at 3.9%, December 2027 Fed funds futures pricing almost no cuts, and the MOVE Index spiking 28% to 109. Only later did I see Radigan’s framework, and the contrast was immediate.

Radigan writes as the Operator — visceral, scarred by two decades of GWOT failure and his direct experience in nation-building in Iraq. From Oman, evacuating his wife while watching missiles fly, he walks you through the physical reality of a shattered Ras Laffan LNG train: custom vessels, Mammoet heavy-lift crews, sulfur cascades, fertilizer spikes, and the 6-week freight-contract trigger that locks in CPI pain no matter what any president tweets. His Shia theology lens explains the expected Iranian resolve. His “Suez moment” framing sees this as the definitive unravelling of the American empire. Phase 3 — summer earnings misses, AI-for-survival cost cuts, midterms panic — becomes his buying window. It is human, friction-filled, and impossible to dismiss from someone who actually commissioned those LNG facilities. And it mirrors many of the concerns you will read in the popular press.

My note is the Tactitian’s structural calculus with a laser focus on the front of the curve. I separate the reversible oil/Hormuz shock (solvable in weeks to months once Navy escorts and minesweeping begin) from the structural 3–5 year LNG hole at Ras Laffan. The Fed and market, still haunted by 2020–2023, are over-pricing permanence and erasing 2026 cuts — most visibly at the front end. That mispricing was triggered not by thoughtful repricing but by a flow-inelastic unwind: levered steepener books hit margin calls, the MOVE Index exploded, and Treasuries were liquidated first to raise cash. Europe and Asia eat the multi-year pain while the U.S., as net exporter, captures the windfall. The pivot will come from a violent K-shaped credit fracture — youth and non-college cohorts absorbing the entirety of net job destruction and credit stress — once oil normalizes faster than the market expects.

The two views clash in important ways. Radigan’s perspective is shaped by Iraq, where he saw, in person, the limits of U.S. power to reshape a tribal society held together only by Saddam’s brutality — a conflict turned worse by Iranian support for insurgency. That fuels his emphasis on theological resilience and inevitable quagmire. In my view, his Shia theology lens risks conflating the Iranian people with the IRGC regime that now cynically controls and weaponizes it — as evidenced by the new religious leader’s elevation in direct defiance of the former Ayatollah’s wishes and the new leader’s own compromised stature. This suggests the regime may prove more brittle under sustained pressure than the martyrdom narrative implies.

Yet the frameworks reinforce each other powerfully. Radigan’s ground-level friction — 6-week trigger, summer earnings pain, desalination risks, regional militias — keeps my models honest on repair lags and escalation. My front-of-the-curve mechanics and flow-inelastic unwind highlight the U.S. advantage that pure operator cynicism can underweight.

The practical synthesis is clear: use his physical timelines to time the exact moment delinquencies spike and the front end snaps. When that credit fracture arrives, the violent reversal in yields, the dollar, and the policy response will be profound.

I recommend keeping some cash and watching for the first clear Hormuz convoy catalyst. When the US fleet enters the Straits, the conflict is functionally “over.” But for now, the conflict continues to evolve (largely as I’ve expected). The opportunity remains.

The Fed’s Credibility Trap Meets the Flow-Inelastic Unwind

The bond market has undergone a violent repricing in recent weeks. Readers may remember that I turned structurally bearish bonds on a seasonal inflation framework last December 2027 Fed funds futures now imply a terminal rate around 3.75%–4.00%. Two-year Treasury yields closed near 3.88–3.91%, the 10-year Treasury yield settled at 4.39%, and equities weakened further—S&P 500 at 6,506.48, Nasdaq at 21,647.61. The US Dollar Index (DXY) ended around 99.50–99.65, elevated on safe-haven flows.

The mainstream narrative claims this stems from a geopolitical energy shock colliding with a Federal Reserve that may be forced to hike to contain oil-driven inflation.

This narrative is structurally false. It fundamentally misunderstands both the internal dynamics of the Fed and the mechanical plumbing of the bond market.

Read more

For the last two years, a fierce debate has raged over why. Now that the dust is settling, the macroeconomic establishment is busy writing the official post-mortem. But a close look at the recent literature reveals that academia and the Federal Reserve are relying on contaminated statistics and accounting illusions to explain away what actually happened. And, of course, they are doing it to benefit the elite and corporate interests that increasingly dominate the discussion.

Let’s look at two of the most prominent recent attempts to explain the disaster—one pinning the blame on fiscal deficits, the other absolving corporate pricing power—and why the math underneath both of them completely falls apart when you look at the actual receipts.

Part I: The Fiscal Mirage and the Endogeneity Trap

A popular narrative among macroeconomists is the “fiscal mechanism”—the idea that unexpected government deficits were the primary driver of the unexpected surge in global inflation. A recent high-profile paper by Ricardo Reis attempts to prove this by plotting the unexpected deficit shocks of OECD countries against their unexpected inflation shocks, drawing a neat red trendline through the scatter plot.

It looks like a definitive macroeconomic law: countries that ran bigger deficits suffered worse inflation. My partner, Harley Bassman, would be thrilled (always a sign of errors in analysis). But to get that trendline, Reis errs in two massive, highly revealing ways.

Error 1: The Outlier Illusion vs. Statistical Rigor

In the paper, Reis explicitly notes that if you selectively discard two glaring outliers on the far left of the chart (Norway and Denmark), his regression line steepens and his R-sq improves. But subjectively cherry-picking which countries to exclude to make a theory look better is terrible statistics.

If you instead apply standard statistical rigor to the dataset—such as a 5% Windsorization, which objectively trims the extreme tails on both sides of the distribution rather than subjectively dropping two data points—the narrative collapses. The R-sq doesn’t improve; it drops by nearly 50%, falling to a meager 0.189. The trend is a fragile mirage entirely dependent on extreme outliers.

Error 2: Unnecessarily Complicating the Y-Axis

Worse, Reis unnecessarily complicates the inflation story. If you want to explain the consumer cost-of-living crisis, you should plot Consumer Price Inflation (CPI). But Reis didn’t do that. Because he is aiming to prove the Fiscal Theory of the Price Level (FTPL), his Y-axis uses a convoluted “debt impact” analysis, measuring how much the national debt was erased by unexpected inflation (the denominator effect).

It’s a niche academic debt metric, not a measure of household purchasing power. And it fundamentally distorts the data, hiding the mechanical effects of inflation on government balance sheets behind an accounting identity.

The Receipts: What Happens When We Clean the Data?

We can strip out these illusions. If we go to the IMF’s World Economic Outlook and Fiscal Monitor databases, we can rebuild this chart using the metrics that actually matter:

1. A Clean X-Axis: The Cyclically Adjusted Primary Balance, which explicitly strips out cyclical noise, inflation-tax windfalls, and interest payments to isolate the actual discretionary legislative choices made by politicians.

2. A Clean Y-Axis: The actual 5-year unexpected surge in pure consumer inflation, throwing out the convoluted “debt impact” math.

When you plot the clean structural data against actual consumer prices, the vaunted “fiscal mechanism” begins to breakdown even further. First, the full sample R-sq falls to only 0.08, weak sauce at best. Second, Windsorization now IMPROVES the outcomes, suggesting that there very well may be a mechanism with a similar coefficient (0.25) to the fabricated Reis’ result:

But the coefficient is far from statistically significant. You can always draw a regression line through a scatter plot—but if it collapses into statistical insignificance, you must look elsewhere.

Another method of testing this is to extend the regression into polynomial form. I’ve included a four-factor polynomial just for kicks, as it’s oddly shaped like my career trajectory and I always like to remind myself that this is the downslope, but the point remains — any higher order (2 factor, 3 factor, 4 factor, etc) regression suggests that there’s a “magic middle” fiscal deficit that drives unexpected inflation. Or maybe not. Because when we look at the countries, a different grouping falls out naturally:

This approach groups countries by WHY they experienced inflation. Estonia, Latvia, Lithuania, etc are all sitting on the front lines of the Russia embargo. Countries like the UK chose to subsidize domestic energy, keeping a lid on prices, but exploding deficits. Zero covid countries did zero covid things. And of course windfall exporters, e.g. Norway, experienced inflation largely as a result of economies booming due to oil exports. Asia? Safe havens? They remained structurally deflationary in a sea of elevated inflation. Can we rethink this chart even further and offend 90% of the world’s population in the process? Well, yes, this is YIGAF, and that’s our specialty:

The only trend I can actually identify that has any statistical validity is in the “increasingly European” path navigating between Scylla (unlucky) and Charybdis (stupidity). I’m sure my European readers are familiar with this trajectory. Relatively deflationary conditions persist in the “old.” And the United States? Really, the only country that aggressively engaged in fiscal stimulus? It’s sitting right in the center of the universe where Donald Trump thinks it belongs.

We can find statistical support for these groupings using the “coefficient of variation” — basically a test of “do groupings make sense?” If the coefficient of variance declines when data are grouped, it statistically suggests that the datapoints indeed share a common descriptive. If it increases versus the total sample, there is little evidence that the groupings are valid. This is exactly what we see — inflation CV falls when grouped. The same grouping results in an expansion of the deficit CV. This is yet another demonstration that Reis’s approach is completely wrong, and that deficits are not “the” driver of increased inflation. But then again, he’s in the UK, so fully in the grasp of the Charybdis whirlpool.

When you throw out the politics-contaminated math, the truth emerges. Inflation was a byproduct of who you relied on (Russia) and how stupid your politicians were. Both of these are solvable for almost any nation. Just not through deficit targeting.

Part II: The Fed’s “Flat Markup” Illusion

This kind of methodological blind spot isn’t isolated to academia’s fiscal theories. It’s exactly the same type of statistical gaslighting that the Federal Reserve Bank of San Francisco (FRBSF) used to confidently dismiss the “Greedflation” narrative.

During the inflation surge, critics argued that highly concentrated firms used the fog of global volatility to aggressively hike prices and pad their profit margins. In their May 2024 Economic Letter, the FRBSF attempted to put this debate to rest. They concluded that “aggregate markups... have stayed essentially flat” and that the post-pandemic path of markups “is not unusual compared with previous recoveries”. Therefore, they argue, corporate pricing power was not a main driver of the inflation surge.

To prove this, they plot the cumulative change in aggregate markups during the last four recoveries (1991, 2001, 2008, and 2020). To make the lines comparable, they index the start of the 2020 recovery to the exact moment the NBER declared the recession over (Q2 2020).

But treating the summer of 2020 like a normal business cycle trough is absurd. The economy wasn’t “recovering” in the traditional sense; it had been legally halted by government mandate and was waiting to be thawed by trillions in fiscal stimulus.

When you adjust for this and look at what happens when the economy actually reopens and the stimulus fully hits the system (starting in Q4 2020), the Fed’s “normal” narrative completely implodes.

Read more

1. A shared presentation with fun family photos

2. Another comment on credit

3. A warning on flow chasing

4. An answer to the question, “What do you mean by ‘running the table’?”

   ---

1. A quick share: I had the privilege of speaking at TCU this past week. My niece is a senior there and asked if I could guest lecture a class, sharing my work on markets, geopolitics, and thoughts on life. If you’re interested, you can find the presentation here.

   

2. For the US, the week was all about credit, with a host of voices joining my long-term refrain on private credit (from a prior piece):

Read more

I sometimes remind people that the right mental model for Xi and Putin is Tony Soprano — not particularly bright, but devastatingly ruthless. In my early advisory work for the US military, I often emphasized, “We should not become China to defeat China.” Unfortunately, I think we have made significant strides on both fronts. I’ll take the good (geopolitics), and hopefully, we still have a chance against the crime families.

The US is on the verge of “running the geopolitical table” to use a straight pool term. Control of the Western Hemisphere is within reach, geopolitical chokepoints are increasingly closed to China, strategic sourcing is increasingly solved with TSMC and Mountain Pass now both operational on US soil (do not confuse military strategic sourcing with “no concerns on the consumer/industrial front”). Drones deployed in the Iranian attack are the 21st-century equivalent of the WW2 Liberty ships — not invented here, but cheap as chips to deploy.

While I’ve been privileged to have the opportunity to help “solve” the problems of America, I’ve been making incredible progress on my work on passive — theory, book, speaking, understanding, and implementation. Many of you may have noticed a change in my tone in recent discussions. It matters, so let’s discuss.

Read more

Let’s recap where we are.

In Part 1, we showed that in a world of geometric growth and volatility, talent doesn’t win — buffers do. The Gifted Poor went extinct at 25x the rate of the Normie Rich. The Ferrari broke an axle on the dirt road.

In Part 2, we added the costs of actual life — eating, children, and retirement — and watched the model reproduce the American economy with eerie precision. The average wealth skyrocketed while the median flatlined. The bottom 80% were pinned to the subsistence floor. The top quintile retirees became Capital itself — compounding, extracting, and never resetting. We called it the Gerontocracy, and it wasn’t a metaphor. It was the physics.

We ended with a question: Can you tax your way out of this?

You might expect the answer to be simple. Tax the rich. Redistribute. Done. It wasn’t simple at all. In fact, the first two “obvious” reforms made things worse. But the third — the one that most policy experts would dismiss as politically impossible — produced something I did not expect.

The simulation independently derived the tax code of the 1950s.

The Three Prescriptions

We tested three distinct tax philosophies against our baseline model (the untaxed Gerontocracy from Part 2). Same economy. Same agents. Same unemployment shocks. Same random seed. The only thing that changed was the tax structure.

Prescription 1: The “Orthodox” Reform

This is the tax code that both libertarians and mainstream economists call “optimal.” The logic: capital is sacred. Don’t tax it. Instead, shift the burden to consumption. Cut labor taxes (from 10% to 5%), eliminate capital gains taxes entirely, eliminate estate taxes, and introduce a 15% consumption tax. The idea is that by making capital “free,” you accelerate growth, and the rising tide lifts all boats.

Prescription 2: The “Naive Progressive” Reform

This is the populist left’s instinct. Tax capital gains aggressively — 30% annually on all gains — and redistribute the proceeds as a universal dividend. No estate tax. The logic: take from the rich every year and give to the poor.

Prescription 3: The “Deferred” Reform

Let capital compound freely during life. Zero annual capital gains tax. But at the point of intergenerational transfer — death — impose a 50% estate tax. Redistribute the proceeds as a universal dividend. This is, in essence, the structural logic of the New Deal tax code.

Let’s see what happens.

Prescription 1: The Orthodox Failure

The consumption tax is the darling of think tanks. It is “efficient.” It is “neutral.” It does not “distort” capital allocation.

It is also a torpedo aimed at the hull of every low-SES (low socioeconomic status, i.e. “poor”) household in the economy.

Here’s why. A consumption tax is functionally a tax on survival. In our model, every agent must “eat” — $50/year in non-negotiable cost-of-living. A 15% consumption tax raises that floor from $50 to $57.50. That’s $7.50 per year taken directly from the ability to form a buffer.

For the High SES agent sitting on $500 in savings, this is a rounding error. For the Low SES agent entering the workforce with $0 and trying to save $5/year (the gap between their $55 salary and their $50 cost of living), it is catastrophic. Their already razor-thin surplus — the only dollar that could compound — gets taxed before it can be saved.

The consumption tax doesn’t tax consumption. It taxes the attempt to build a buffer.

The results confirm the mechanism:

Read that again. The “optimal” reform made every metric worse. Aggregate wealth fell slightly (less capital formation from buffer-depleted agents). The median didn’t move — it was already zero. And the solvency rate — the percentage of the population with more than a dollar to their name — declined.

The “rising tide” argument requires that you already have a boat.

I want to be precise about the mechanism, because it maps perfectly to the empirical data. The consumption tax is regressive, not because of some abstract distributional concern, but because of the physics of geometric growth. A dollar taxed from the consumption floor of a low-SES agent destroys more future wealth than a dollar taxed from the surplus of a high-SES agent — because the low-SES agent’s dollar was the marginal dollar that determined whether they could compound at all.

This is not a political argument. It is a mathematical one.

Prescription 2: The Naive Progressive Disaster

If the right’s instinct (free capital, tax consumption) fails because it depletes buffers, surely the left’s instinct (tax capital, redistribute) succeeds?

No. It is worse. Much worse.

A 30% annual tax on capital gains doesn’t just redistribute wealth. It destroys the compounding mechanism itself. Every year, the tax skims 30% of any positive return. This is equivalent to reducing the effective return on capital from 8% to approximately 5.6% — but with a critical asymmetry: the tax takes on the upside, but the agent bears the full downside.

This converts an already volatile growth engine into a systematically sub-critical one. The agents can no longer outgrow their costs. The buffer — the very thing that drives survival — can never form:

The aggregate wealth didn’t just decline. It collapsed. From $1.48 billion to $32,555. That is not a typo. That is a 99.998% destruction of total wealth. The solvency rate fell from 16.7% to 8.1%. You made more people destitute, not fewer.

This is the trap that the simulation reveals with brutal clarity: annual capital taxation and consumption taxation fail for the same reason. They both attack the buffer during the accumulation phase — the precise moment when the low-SES agent is most vulnerable to the Volatility Tax and the high-SES agent is on the border of compounding wealth that ultimately benefits society. One taxes the input (consumption). The other taxes the output (returns). Both destroy the same thing: the ability to compound.

The simulation doesn’t care about your ideology. It cares about where you interrupt the compounding process.

The Insight: When You Tax Matters More Than How Much

Let’s pause on this, because it’s the key to everything that follows.

The first two prescriptions share a fatal design flaw: they are synchronous taxes. They extract revenue in real-time — every month, every year — while the agent is still trying to build the buffer that determines their survival.

Imagine a farmer planting a field. You can tax the harvest (which arrives once, at the end of the season). Or you can tax the seeds, the water, and the fertilizer — every day, as they’re applied. Oh, and lop the tops of the plants as they grow as well.

The first approach lets the crop grow. The second prevents it from ever forming.

The question is not how much to tax. The question is when.

Prescription 3: The Tax Code We Already Had

The third scenario is structurally different. It lets capital compound freely during life with zero annual capital gains tax. But at the moment of intergenerational transfer, it imposes a 50% estate tax. The revenue is redistributed as a universal dividend.

This is a deferred, asynchronous tax. It does not interrupt buffer formation. It does not destroy the compounding mechanism. It waits. It lets every agent — High SES and Low SES alike — participate in the growth engine for their entire working life and retirement. And then, at the point of dynastic transfer, it reclaims half of the accumulated surplus and recycles it into the system as new buffers.

The results are not incremental. They are transformative:

Read that table slowly.

The aggregate wealth is lower — about 26% less than the baseline. The “pie” is smaller. Every economist trained in the last fifty years will tell you this is a failure. The system is less “efficient.”

But the median — the household in the middle, the one that votes, the one that sends kids to public school — went from functionally zero to $32,703. And the solvency rate — the percentage of the population with meaningful wealth — went from 16.7% to 100%. Every single agent in the simulation is solvent.

The pie is smaller, but everyone gets a slice.

The Quintile Transformation

This is where the simulation stopped being a model and started being a before-and-after photograph of the American middle class.

Look at those two tables, because they tell the entire story of the last seventy years of American economic history.

In the baseline, Q1 through Q4 have nothing. The bottom 80%, parents and retirees alike, are pinned to zero. All the wealth sits in Q5, and within Q5, the retirees hold 4x more than the parents. This is the Gerontocracy. This is the buffer-ocracy. This is America in 2026.

Under the 1950s code, every quintile has meaningful wealth. Q1 parents hold $10,059. That’s not luxury. But it’s a buffer — two years of breathing room. Q3 parents hold $37,508. That’s a down payment on a house. Q4 parents hold $77,114. That’s a college fund for their kids.

And look at the retirees. Under the baseline, Q5 retirees held $3.5 million, while every other retiree cohort held zero. Under the 1950s code, Q5 retirees still hold $2.1 million; they are still wealthy, but Q3 retirees hold $35,265, and Q1 retirees hold nearly $10,000. They can eat. They can live. They can care for grandchildren. They have dignity.

The 1950s code didn’t abolish wealth. It didn’t punish success. The Q5 agents are still rich. What it did was break the dynastic lock that prevented the bottom 80% from ever entering the compounding regime.

The Gini Tells the Story

For the economists in the audience, here is the same transformation expressed in the language you were trained in.

The Gini coefficient measures inequality on a scale from 0 (everyone has the same wealth) to 1 (one person has everything). The current U.S. wealth Gini is approximately 0.85 — already one of the highest in the developed world. The income Gini sits around 0.41.

In our simulation, the Gini tracks the trajectory of the system’s inequality over 100 years:

Look at the trajectories, not just the endpoints.

The baseline and orthodox scenarios march steadily toward a Gini of 0.98 — a system in which one agent holds essentially all the wealth. This is not an aberration. It is the mathematical inevitability of geometric compounding without a reset mechanism. The consumption tax doesn’t slow it down. It doesn’t even register.

The annual capital gains tax is a fascinating failure. It starts lower — a Gini of 0.50 at Year 10 because the tax successfully suppresses capital accumulation. But by Year 100, it converges to 0.97 anyway. Why? Because it destroyed the compounding engine for everyone. When nobody can build wealth, the Gini rises not because the rich got richer, but because everyone got poorer. The economy collapsed into a shared destitution that is, paradoxically, almost as unequal as the baseline — because even at the floor, the tiny differences between agents get amplified when there’s nothing left to distribute.

And then there’s the 1950s code. It is the only scenario where the Gini stabilizes. It rises to 0.87 around Year 50, then declines slightly to 0.85 by Year 100. The system finds an equilibrium. Inequality exists — it must, because agents have different ages, different compounding histories, different luck — but it is bounded. The estate tax creates a ceiling on dynastic accumulation while the universal dividend creates a floor on destitution. The system breathes.

A Gini of 0.85 is still high. But it is approximately where the U.S. wealth Gini sits today. The question is not whether we can achieve perfect equality. The question is whether we can prevent the system from converging on 0.98, where democracy itself becomes a formality.

A careful reader will object: the simulation above uses a uniform age distribution. Real America in 2025 does not have a uniform age distribution. Real America has the Baby Boomers — the largest, wealthiest generation in human history — sitting on approximately $78 trillion in household wealth, aged 61 to 79, and about to die.

So we reran the simulation. Same four tax scenarios. But instead of a uniform age-wealth distribution, we initialized the population to match 2025 America: a Boomer bulge aged 61-79 holding the majority of wealth in a Pareto distribution (a few with enormous wealth, many with moderate), Gen X with moderate accumulation, Millennials with little, Gen Z with nearly nothing. The starting Gini: approximately 0.85 — exactly where the U.S. sits today.

The results are not merely different. They are alarming.

Under the baseline — no estate tax — the Boomer wealth concentration drives the Gini from 0.85 to 0.995 by Year 100. That last digit matters. At 0.98 in the uniform model, the system was already approaching feudalism. At 0.995, it has arrived. The Boomer bulge doesn’t just reproduce the inequality problem — it accelerates it, because the wealth is concentrated in agents who are still alive, still compounding, and approaching the generational boundary all at once.

And here is what alarms me: the 50% estate tax — the rate that produced 100% solvency in the uniform model — does not work under real-world demographics. The Gini under the 50% rate keeps rising straight through the Boomer death wave. It reaches 0.94 at Year 25, 0.94 at Year 40, and 0.97 by Year 60. Solvency reaches only 75%. The dividend generated by a 50% rate, spread across the entire population, is simply too thin to push agents above escape velocity when wealth is this concentrated.

The uniform model was a proof of concept. It showed that the estate tax mechanism works — deferred, asynchronous taxation at the generational boundary. But it understated the required dose. When you initialize the simulation with actual American wealth concentration, 50% is not enough.

This is why the window is now.

The Boomers hold approximately $78 trillion. They are between 61 and 79 years old. The actuarial peak of the death wave begins around 2030 and crests around 2045. Every year that passes without an effective estate tax is a year in which Boomer wealth flows into the perpetual trust architecture we described earlier — into the vampires, into South Dakota, into legal structures specifically designed to ensure that this wealth never triggers a generational transfer event.

The concentration of wealth in a single generation is not just a problem — it is an opportunity. It is the largest potential buffer-recycling event in American history. But it is a one-time event. Once the wealth has passed into perpetual trusts, the generational boundary ceases to exist, and the mechanism never fires.

We are not arguing for a policy that would be nice to have someday. We are arguing for a policy with a window of approximately fifteen years before the opportunity closes permanently.

So the question becomes: if 50% is not enough, what is?

50% Is Not Enough

The Gini Coefficient still rises during the first 25 years of the Boomer death wave, even with a 50% estate tax. The dividend generated at a 50% rate is insufficient to push agents above escape velocity when wealth is concentrated in a single generational cohort rather than distributed uniformly across age groups.

So we swept the rate. Same Boomer demographics. Same simulation. Seven estate tax rates from 0% to 90%.

At 50%, the Gini never inflects. It keeps climbing straight through the death wave. Solvency reaches only 75% — better than the baseline, but a system that still condemns a quarter of the population to financial death.

At 70%, the Gini finally peaks and reverses — the inflection occurs around Year 25, precisely during the death wave. Solvency reaches 87.5%.

At 77% — the actual top marginal estate tax rate from 1941 to 1976 — the system achieves 99.4% solvency. The Gini peaks at 0.87, then falls to 0.82 during the death wave and stabilizes at 0.83. This is the rate at which the dividend just barely exceeds the threshold needed to push agents above escape velocity under real-world wealth concentration.

The number 77% is not arbitrary. It is the critical rate — the point at which the estate tax dividend, distributed across the population, generates enough buffer to overcome the compounding advantage of the surviving wealthy. Below it, the system improves but does not heal. Above it, the system heals, but at the cost of unnecessary compression. At 77%, it finds equilibrium.

They Knew

Here is the part of this story that stops me cold.

The top marginal estate tax rate in the United States was 77% from 1941 to 1976. Not 50%. Not 60%. Not “somewhere in the 70s.” Exactly 77%. The rate was reached through a series of legislative increases: 10% at inception in 1916, 25% in 1917, 40% in 1924, 70% in 1935, and finally 77% in 1941, where it stayed for thirty-five years.

Did the policymakers who set that rate understand the mechanism revealed by our simulation? Did they know about absorbing barriers, escape velocity thresholds, and the minimum dividend required to overcome geometric compounding under concentrated wealth?

No. Not in those terms. But they understood something arguably deeper.

In 1889, Andrew Carnegie argued that wealth did not belong to the wealthy — it was merely entrusted to them temporarily by the society that made its accumulation possible. He advocated heavy inheritance taxes and declared that a man who dies rich dies disgraced.

Theodore Roosevelt, in his 1906 address to Congress, called for an inheritance tax “increasing rapidly in amount with the size of the estate” — to prevent what he called “swollen fortunes” from perpetuating. His language anticipated our simulation’s findings almost precisely: the tax should be small on moderate estates — don’t interrupt buffer formation — and heavy on the largest — clip the dynastic tail.

Franklin Roosevelt warned in 1936 that “economic royalists” had “carved new dynasties” and that “new kingdoms were built upon concentration of control over material things.” He wanted a 100% tax on incomes above $25,000. Congress negotiated him down. The Revenue Act of 1935, called the “Soak the Rich Act” at the time, pushed the estate tax to 70%. By 1941, it reached 77%.

Keynes, writing in 1936, argued that there is “social and psychological justification for significant inequalities of incomes and wealth, but not for such large disparities as exist today.” He called for the “euthanasia of the rentier” — the functionless investor who lives off capital scarcity rather than productive effort. He explicitly advocated “a scheme of direct taxation which allows the intelligence and determination and executive skill of the financier... to be harnessed to the service of the community on reasonable terms of reward.” This is almost verbatim our distinction between taxing passive returns from luck and infrastructure while exempting active returns from skill.

Even Eisenhower — the Republican who maintained the 77% rate — warned that any society tolerating a “fabulously wealthy” class is asking for trouble.

They did not have agent-based simulations. They did not have ergodicity economics or stochastic process theory. What they had was thirty years of iterative calibration. They kept turning the dial up — 10%, 25%, 40%, 70%, 77% — because each lower setting proved insufficient to prevent dynasty formation. They were empirically converging on the same number that our simulation derives from first principles.

And before them, the Torah commanded Jubilee. The Babylonians decreed misharum. The Romans limited the concentration of ager publicus. Every durable civilization, through experience, arrived at the same structural insight: geometric accumulation requires a periodic reset at a natural boundary, and the reset must be large enough to actually recycle the buffer.

Five thousand years of civilizational experience. Three decades of American legislative calibration. And now a simulation with 5,000 agents and 1,200 monthly time steps. Three entirely independent methodologies. The same answer: approximately 77%.

Policymakers in the 1950s didn’t have our simulation. But they had something better: experience refined through iteration. And they got the number right. And then the business lobby, fronted by Reagan and Friedman, undid it.

And here is the final perversity. The ultra-wealthy already know this.

In 2010, Warren Buffett and Bill Gates launched the Giving Pledge — a commitment by billionaires to donate at least 50% of their wealth to charity during their lifetimes or at death. The remaining 50% is then, in theory, subject to the current 40% estate tax. Do the math: 50% donated, plus 40% of the remaining 50% = a 70% effective transfer rate. The billionaires are voluntarily self-prescribing an estate disposition almost identical to the rate our simulation identifies as the minimum threshold for systemic healing.

They know the wealth needs to be recycled. They just insist on choosing the recipient. The Giving Pledge routes the transfer through private philanthropy — where the donor names the building, selects the cause, retains reputational control, and employs their progeny in perpetuity — rather than through a public dividend, where the democratic process allocates the buffer. The effective rate is nearly identical. The difference is who decides.

This is not generosity. It is the last-ditch defense of allocation authority by a class that understands, intuitively if not mathematically, that the wealth must flow back. They would rather give 70% on their own terms than have 77% recycled on society’s terms.

The rich have already conceded the principle. They have merely reserved the right to administer it privately. The simulation says that’s not good enough.

Why It Works: The Buffer Recycling Mechanism

The estate tax is not a punishment. It is a buffer recycler.

Here’s the mechanism. When a wealthy individual dies, up to 77% of their accumulated capital above the exemption threshold is returned to the system as a universal dividend. That dividend does something specific and measurable: it raises the wealth of every low-SES agent above the critical threshold where compounding can begin.

Think of it in terms of our simulation’s physics. Below a certain wealth level, the Volatility Tax — unemployment shocks, restart costs, the cost of eating — consumes every dollar of surplus before it can compound. The agent is stuck in the Capital Decay Regime. No amount of talent or effort can escape it, because the math prevents escape.

The estate tax dividend pushes agents above the escape velocity. It provides the buffer that allows the compounding engine to finally engage. Once above the threshold, the agent’s own returns do the rest. The system becomes self-sustaining.

But there is a design problem that the simulation glosses over: timing risk. In the model, deaths are distributed uniformly, so the dividend flows smoothly. In reality, estate tax revenue is lumpy. A billionaire dies in 2027; the fund swells. No billionaire dies in 2028; the fund starves. A child born in 2028 receives a smaller buffer than a child born in 2027 — not because of anything about them, but because of the accident of when a stranger died. We have replaced one form of birth lottery with another.

The solution is, ironically, to use the vampire’s own weapon: a trust. Not a perpetual dynastic trust designed to hoard wealth across generations, but a public buffer trust — a sovereign fund that receives estate tax revenue, invests it in U.S. government debt, and distributes the dividend on a smoothed, predictable schedule. The trust absorbs the volatility of revenue timing and converts it into a steady stream. The same way a pension fund smooths contributions over decades to deliver predictable benefits, the buffer trust smooths the generational harvest to deliver predictable buffers.

This is not a new idea. Norway’s sovereign wealth fund, Alaska’s Permanent Fund, and Singapore’s Temasek all operate on variants of this principle — public capital pools that convert volatile revenue streams into stable citizen dividends. The mechanism is well understood. The engineering is solved. What’s missing is the revenue source, and the estate tax provides it.

This is why the solvency rate nears 100%. It’s not that the government is supporting everyone indefinitely. It’s that the buffer recycling mechanism gives everyone enough runway to support themselves. The tax code isn’t redistributing income. It is redistributing the ability to compound.

And here I need to address something directly, because it is the first objection that any fiscal conservative will raise: “You want to grow government.”

No. Emphatically, no. And this is why the universal dividend is the critical design choice, not a detail.

The federal government already spends roughly $6 trillion per year. The vast majority of that spending on social programs operates through a pass-through architecture: federal dollars flow to states, states administer benefits through local bureaucracies, and at every layer of the chain, the dollar is diminished. Administrative overhead. Compliance costs. Eligibility determinations. Case workers. Appeals processes. The bureaucratic friction that exists between a federal tax dollar and a low-SES family’s bank account is enormous — and it is a feature, not a bug, of the current system. It sustains an entire class of administrators, consultants, and state-level political operators whose livelihoods depend on the complexity of the redistribution apparatus.

We monitor charities for efficiency. A charity that spends 60 cents of every dollar on overhead and delivers 40 cents to its mission gets an F rating and donors flee. Yet the federal-to-state-to-local benefit pipeline routinely operates at comparable or worse ratios, and we call it “government spending.”

The universal dividend bypasses this entirely. It is a direct transfer. No state administration. No eligibility bureaucracy. No means testing. No case workers determining whether you are sufficiently poor to deserve a buffer. The estate tax revenue goes in; the dividend comes out. To every American citizen. Upon naturalization and age of maturity, there are catch-up distributions — so that no one is penalized for the accident of when they entered the system. The efficiency ratio approaches 1:1.

This is not a libertarian fantasy about eliminating government. Government has essential functions: defense, courts, infrastructure. Public goods that markets cannot provide. But the redistribution function — the buffer recycling mechanism — does not require a bureaucracy. It requires a ledger. And in 2026, we have the technology to maintain that ledger at trivial cost.

The simulation models this as a direct, frictionless transfer for a reason: because that is how it should work. Every dollar consumed by administrative overhead is a dollar that never becomes a buffer. Every layer of bureaucratic intermediation is a tax on the tax — a synchronous friction applied to the very mechanism we are trying to optimize. The same physics that tells us not to tax consumption during buffer formation tells us not to filter the dividend through five layers of government on its way to the recipient.

We are not proposing bigger government. We are proposing fewer intermediaries between the tax and the buffer.

The Gerontocracy Dissolves

Notice something else in the quintile tables. Under the baseline, the generational divide was obscene: Q5 retirees held $3.5 million vs. Q5 parents at $814,000 — a 4.3x ratio. Under the 50% estate tax, Q5 retirees hold $2.1 million vs. Q5 parents at $742,000 — a 2.8x ratio. A 77% rate normalizes it further still.

The Gerontocracy doesn’t vanish entirely; older agents have compounded longer, and they should be wealthier. But the 50% estate tax reduces the dynastic acceleration that turns retirees into a separate economic species. It clips the tail of the distribution at the exact point where intergenerational transfer would otherwise create an aristocracy. The 77% rate “solves it.”

The 1950s code doesn’t fight the physics. It uses physics as a judo master might use their opponent’s strength. It acknowledges that geometric compounding will always produce concentration over a lifetime, and it introduces a reset mechanism at the natural boundary between generations.

But We’ll Be LESS Wealthy!

The 77% estate tax does have an unfortunate reality: the aggregate absolute wealth DOES decline versus baseline. By nearly 60%! But that’s because we’re defining wealth narrowly. Look what happens to the number of children… consumption… the number of participants with ownership stakes. You want “the ownership economy” replete with the social goods (safety, reduced crime, greater civic engagement) we were promised? This is the path. A small segment of our society will be worse off in relative terms. A not insignificant number of my readers (and my children) will be among them. But our society will be richer; our trust will be higher.

Addressing Sandy’s Objection

One of the most thoughtful comments on Part 2 came from Sandy, who raised a structural point I want to address directly. Sandy argued that the 1950s tax code was the last layer of a multi-layer buffer system: manufacturing employment providing wage floors, unions providing surplus transfer, employer benefits providing non-wage buffers, and then the tax code compressing top-quintile decoupling. Today, three of those four layers are gone.

The estate tax is the only one of the four mechanisms that works through the compounding channel. Unions and manufacturing provide income floors — they raise the salary line at the risk of higher unemployment. Employer benefits reduce the cost line, but the predictable risk is that they lock workers into coercive relationships. The estate tax operates on neither. It operates on the starting condition — the buffer, the endowment, the initial coordinate that our simulation has shown is THE driver of lifetime outcomes.

The other three layers address symptoms. The estate tax addresses the root cause.

You can have unions without an estate tax and get a strong middle class for one generation. But without the estate tax, the dynastic compounding eventually overwhelms every other buffer. The aristocracy reconstitutes itself. Which is, of course, exactly what happened in the real world.

The political obstacles to this reform are real — we'll return to them. But first, the mechanism requires more than a tax rate.

But the Vampires Already Thought of This

I can hear the objection already: “The estate tax exists. We already have one. It doesn’t work.”

And that objection is correct — but not for the reason most people think.

Regular readers will recall my January 2025 piece, “The Undead Among Us,” where I detailed how the American elite effectively achieved immortality through legal engineering. The estate tax has a statutory rate of 40%. The effective rate is approximately zero. And the mechanism by which this was accomplished is one of the most elegant pieces of financial engineering in history — far more impressive than anything Wall Street has produced.

It starts with the Generation-Skipping Trust (GST). Prior to 1986, English and subsequently American law had limited trusts to 21 years past the death of the creator — the Rule Against Perpetuities. This was not an accident. For 500 years, the common law understood that allowing wealth to compound in perpetuity, beyond the reach of any living person’s judgment, was a threat to the social order.

Then came the 1986 tax reform, which created a GST tax exemption. The idea was modest: allow a small amount to pass to grandchildren without double taxation. But it opened a door. Almost simultaneously, states began competing to attract trust business by abolishing the Rule Against Perpetuities. South Dakota won the race to the bottom. Today, South Dakota — a state most people associate with plains and cold weather — holds more than twice the banking assets of New York. $3.4 trillion vs. $1.7 trillion. It is the world capital of the perpetual trust.

Here is what a perpetual trust does in the language of our simulation: it removes the generational boundary entirely. The agent never dies. Its wealth compounds forever. It pays no estate tax because there is no estate — the trust owns the assets, and the trust is immortal. It pays no capital gains tax because nothing is ever sold — the trust distributes income while the principal compounds untouched. The step-up in basis at death? Irrelevant. There is no death.

In our simulation, the estate tax works because every agent dies at 85 and the wealth is recycled. In reality, the Q5 retirees figured out how to become vampires. They created a legal structure that compounds like a corporation — forever — while being taxed like a dead person — never. And like Chicago, the “undead” get to vote through Citizens United.

The 1950s tax code worked because the vampires hadn’t been invented yet. The Rule Against Perpetuities was still intact. Trusts expired. Wealth was recycled. The generational boundary was real. Today, it is fictional, and the estate tax is a Maginot Line — impressive on paper, trivially circumvented in practice.

So our simulation tells us the mechanism that works. But to implement it, we need to slay the vampires first.

The Complete Prescription

The simulation has identified the core principle: tax at the generational boundary, not during accumulation. But the real world has created legal structures specifically designed to eliminate that boundary. A complete reform must address not just the tax rate, but the avoidance architecture that renders it meaningless.

Here are the five pillars:

With detail:

Pillar 1: Restore the Generational Boundary

Abolish perpetual trusts. Restore the Rule Against Perpetuities — the 500-year-old principle that trusts must terminate within a generation of their creator’s death. Eliminate the GST tax exemption. Every dollar of wealth must eventually pass through the generational boundary where the estate tax applies. No exceptions. No South Dakota. No vampires.

This is not radical. This is restoration. For half a millennium, Anglo-American law understood that immortal wealth was incompatible with a free society. We abandoned that principle in a fit of deregulatory enthusiasm in the 1980s, and we are living in the wreckage.

Pillar 2: Tax Scarcity, Reward Development — The Land Value Tax

Henry George figured this out in 1879, and the economics profession has spent 150 years pretending he didn’t. A land value tax — a tax on the unimproved value of land, not on the buildings or improvements upon it — is the only tax in existence that even Milton Friedman called “the least bad tax.” I’ll add more to this discussion in future pieces, but grant me the grace to consider it for now despite the lack of simulation.

Land value is not created by the landowner. It is created by the community — by the roads, the schools, the hospitals, the neighbors, the economic activity that surrounds the parcel. When a landowner’s property appreciates because a new subway stop is built nearby, that appreciation is pure societal luck. It is the equivalent of our simulation’s “Luck Bucket.” Taxing it does not interrupt buffer formation, because the landowner did nothing to create it. It is a tax on scarcity rent, not on productive effort.

Better yet, the LVT actually encourages development. A vacant lot in Manhattan and a skyscraper on an adjacent lot of the same size pay the same land tax. The skyscraper pays nothing additional for the improvement. This reverses the perverse incentive of our current property tax system, which penalizes building and rewards holding empty land as a speculative asset.

In the language of our simulation, the LVT is an asynchronous tax on positional scarcity — it extracts revenue from a source that cannot flee, cannot be hidden in South Dakota, and whose taxation does not destroy productive incentive. It is the ideal complement to the estate tax.

Pillar 3: Distinguish Luck from Skill — Passive vs. Active Investment

This is where we connect directly to the work I’ve been doing on passive investing for the past decade.

Our simulation treats all capital returns identically — 8% with 25% volatility. But in the real world, there is a critical distinction between active investment (selecting companies, building businesses, allocating capital based on judgment) and passive investment (buying an index fund that mechanically allocates capital based on market weight).

Active investing is an attempt at skill. It can fail. It adds information to markets. It performs the essential capitalist function of price discovery — directing capital toward productive enterprises and away from unproductive ones. In the language of our simulation, the active investor is the “Gifted” agent: high return, high risk, high social value.

Passive investing is societal luck. The passive investor makes no judgment about which companies deserve capital. They buy everything in proportion to its existing size. They are, in the language of our simulation, free-riding on the price discovery performed by others. And as I’ve documented extensively, when passive investing exceeds a critical threshold — roughly 40-50% of total flows — it creates a mechanical feedback loop that inflates prices based on index weight rather than fundamentals. The Price-Weight Spiral.

The tax code should reflect this distinction. Active capital gains — from businesses you built, stocks you selected, risks you took — should be taxed lightly during life and at the generational boundary at death. Passive capital gains — from index funds that mechanically benefit from the societal infrastructure of price discovery without contributing to it — should be taxed at a higher rate. Not because passive investors are bad people, but because the return is a social externality that the investor did not create.

This is the same logic as the land value tax: tax the returns from luck and societal infrastructure. Exempt the returns from effort and skill. Both Henry George and Adam Smith would approve.

Pillar 4: The Estate Tax That Actually Works

With Pillars 1-3 in place, the estate tax can finally function as the simulation predicts. A progressive estate tax reaching 77% on the largest estates — the actual rate that prevailed from 1941 to 1976 — with no step-up in basis, no GST exemption, no perpetual trust escape hatch. Revenue recycled as a universal buffer dividend. Our rate sweep under real-world Boomer demographics shows that 50% is not enough — it achieves only 75% solvency when wealth is concentrated in a single generation. The 77% rate is the critical threshold: the point at which the dividend just barely exceeds escape velocity for the bottom quintiles. Below it, the system improves but does not heal. At 77%, solvency reaches 99.4%, and the Gini inflects and reverses during the death wave.

The key insight is that the estate tax alone is insufficient without closing the immortality loopholes on the collection side and the bureaucratic friction on the delivery side. But with both cleared, it is transformative. The expectation that each successive generation should expect to do better than their parents is restored.

Pillar 5: Abolish Public-Sector Collective Bargaining — Clear the Delivery Channel

This is the pillar that will make the left uncomfortable, just as Pillar 1 makes the right uncomfortable. Good. Discomfort is symmetry.

The simulation models the universal dividend as a frictionless transfer — estate tax revenue divided equally, deposited directly. The real world interposes a bureaucracy between the tax and the buffer, and that bureaucracy has, since 1962, been unionized. Kennedy’s Executive Order 10988 granted federal employees collective bargaining rights. The political logic was impeccable: it built a permanent Democratic coalition. The economic logic was catastrophic: it created a constituency whose employment relies on the complexity of the redistribution architecture.

Every means test requires a case worker. Every eligibility determination requires an appeals process. Every layer of federal-to-state-to-local pass-through requires administrators at each level. The universal dividend eliminates all of them. It replaces an army with a ledger. And the army, understandably, will fight.

This is not an argument that public employees are lazy or undeserving. It is a structural observation identical in form to Pillar 1. Perpetual trusts are a private architecture that prevents wealth from reaching the generational boundary where the estate tax can harvest it. Public-sector bargaining rights are the public architecture that prevents the harvested revenue from reaching the citizen as an efficient buffer. One blocks collection. The other blocks delivery. Both must be dismantled for the mechanism to work.

FDR, notably, agreed. He explicitly opposed collective bargaining for public employees, writing that “the process of collective bargaining, as usually understood, cannot be transplanted into the public service.” The 1950s policymakers who built the tax code our simulation rediscovered did not build it on top of a unionized delivery mechanism. Kennedy added that layer later, selling out the taxpayer for electoral victory, and the efficiency of every social program has suffered since.

The Synthesis

Let me pull this together, because the five pillars are not independent policies. They are a system — each addressing a different failure mode that our simulation has identified.

The estate tax addresses the core problem: dynastic compounding across generations. It is the generational reset mechanism.

Abolishing perpetual trusts prevents the legal circumvention of the generational boundary. It ensures that the estate tax actually collects.

The land value tax provides revenue from a non-distortionary source — scarcity rent that the owner did not create — without interrupting buffer formation during the accumulation phase.

The passive/active distinction aligns the tax code with the economic function of capital allocation — rewarding skill and price discovery, taxing free-riding on societal infrastructure.

Abolishing public-sector collective bargaining clears the delivery channel, ensuring that the collected revenue actually reaches citizens as buffers rather than being consumed by administrative friction. It ensures that the estate tax actually arrives.

Pillars 1 and 5 are mirror images: one dismantles the private immortality architecture that blocks collection, the other dismantles the public complexity architecture that blocks delivery. Together, they create an unobstructed channel from the generational boundary to the citizen’s account. The estate tax is the pump. The pillars clear the pipes.

Together, the five form a coherent system that respects the physics of geometric growth while preventing the inevitable concentration that uninterrupted compounding produces. They do not punish success. They do redistribute income — let’s be honest about that. But they redistribute it with a specific purpose: not to provide consumption, but to create buffers. To give the next generation a starting condition from which compounding can begin. The distinction is not whether redistribution occurs, but whether the redistribution creates the capacity to compound rather than merely the capacity to consume.

And critically, for those inclined toward the Charles Murray objection: bad decisions are still penalized under this system. The buffer is not a guarantee of outcomes. It is a guarantee of survivable mistakes. A kid from Q1 who picks the wrong degree financed with $80,000 in debt is not “learning a valuable lesson.” He is experiencing a catastrophic, irreversible shock that the simulation tells us pushes agents below the absorbing barrier from which there is no recovery. The same kid from Q5 who makes the same mistake? His family writes a check or calls a friend. He resets. He tries again. He compounds.

The system we are proposing does not eliminate consequences. It eliminates the asymmetry where identical mistakes produce recoverable setbacks for the wealthy and permanent financial death for everyone else. It gives low-SES kids — and their families — the same reset that wealthy families already provide privately. The conservative who objects to this is not defending meritocracy. He is defending a system in which the punishment for being eighteen and wrong is lifelong, but only if your parents are poor.

The Political Economy Problem

Now the hard part.

The simulation can derive the optimal system. It cannot implement it. And this is where I must be honest with you, because the political economy problem is genuinely harder than the policy design problem.

The estate tax was effectively dismantled between 1981 and 2017 — from a top rate of 77% with a $175,000 exemption to a top rate of 40% with an $11 million exemption. The perpetual trust was created. The GST exemption was expanded. The step-up in basis at death was preserved. Each of these changes was the product of a fifty-year campaign by precisely the cohort that our simulation identifies as the primary beneficiary of the Gerontocracy: wealthy retirees in Q5. They funded the think tanks. They wrote the talking points. They convinced the bottom 80% — the people harmed by the policy — to vote for it, using the language of “family farms” and “death taxes” and “double taxation.”

It was, as Sandy noted in the comments to Part 2, strategically coherent. You cannot sustain low capital taxation if unions retain the power to recapture surplus at the point of production. So you dismantle unions first. Then you dismantle the estate tax. Then you create the perpetual trust. Then you cut capital gains rates. Each step is logically prerequisite to the next. Whether it was explicitly coordinated is irrelevant — the sequence was functionally optimal for the beneficiary class.

This creates what I’d call the Reform Paradox: the cohort with the resources to fund political change is the cohort that benefits from the current structure. And the cohort that would benefit from reform — the Sandwich Generation, the buffer-less workers, the Low SES agents trapped in the Capital Decay Regime — has neither the capital nor the political bandwidth to organize. They are too busy surviving.

Systems that reproduce their own conditions across generations are not typically reformed from within by the cohorts they disadvantage.

But they are occasionally reformed from without — by coalitions organized around clarity rather than ideology. The New Deal was one such moment. The physics haven’t changed. The design problem is solved. The question is whether enough people understand the mechanism to demand its implementation.

Left and right have been arguing about redistribution for fifty years. The simulation shows that the argument is malformed. This is not about taking from the rich and giving to the poor. It is about when you tax, not how much. Let capital compound. Let people build. Let the Ferrari run on fresh asphalt. And at the natural generational boundary, recycle the buffer so the next generation can run too.

This is not socialism. It is not libertarianism. It is the mechanical insight that a system governed by geometric growth and volatility requires a periodic reset at the point of intergenerational transfer, or it will inevitably produce an aristocracy.

This is not even a new idea. It is arguably the oldest economic idea in civilization. The Torah commands a Jubilee every fifty years — debts forgiven, land returned to its original holders, slaves freed. Leviticus 25:10: “Consecrate the fiftieth year and proclaim liberty throughout the land.” The Babylonians practiced misharum — periodic royal edicts canceling debts and resetting economic claims. Roman law limited the concentration of ager publicus — public land — in private hands, and the failure to enforce those limits was, by the republic’s own historians, a proximate cause of its collapse.

Every durable civilization in recorded history understood that geometric accumulation, left unchecked, eventually consumes the society that enables it. They didn’t have simulations. They had experience. And they arrived at the same answer: a periodic reset at a natural boundary.

The Founders understood this. Jefferson wrote about it. Adams warned against it. And for thirty years — from roughly 1945 to 1975 — we actually built it.

We can build it again. But only if we stop treating the economy as a morality play and start treating it as what it is: a physical system with knowable dynamics and designable interventions.

This concludes the Summer Slide Economy series. The full executable code for all simulations, including the tax policy scenarios in this piece, is available here. The code runs in Google AiStudio or any Python environment with numpy and matplotlib.

If you found this series valuable, please share it. The paywall is down. The argument is free. The only question is whether enough people hear it.

Read more

A Quick Review

Last week, we showed that in a world governed by geometric growth and volatility, talent doesn’t win—buffers do. The “Gifted Poor” went extinct at 25x the rate of the “Normie Rich.” The market selected for safety, not skill. The Ferrari broke an axle on the dirt road.

But that simulation was still a game. The agents didn’t eat. They didn’t have children. They didn’t retire.

This week, we add all three. And the model stops looking like a thought experiment, and it starts looking like a census report.

Phase 3: The Volatility Trap (or, “Why You Can’t Save Your Way Out”)

In Phases 1 and 2, our agents lived in a frictionless world. They bet, they won or lost, and the only cost was the bet itself. But in the real economy, you have to eat—every single day, whether you won or lost.

So we introduced the physical requirement of survival.

The Setup:

We gave every agent a job paying $55/year and a non-negotiable cost-of-living allowance of $50/year. That’s a theoretical 10% savings rate—generous by American standards. We then introduced a realistic unemployment shock: a 4% steady-state rate with a 3-month average duration.

Here’s the critical addition: re-employment isn’t free. Every restart costs $10—the new clothes, the lost security deposit, the COBRA payment, the repo’d car. That’s the “Restart Haircut.” It’s a small number that produces catastrophic results.

We split our agents into two classes. Not by talent—everyone is equally skilled. The only difference is the starting buffer:

• High SES (high socioeconomic status): Starts with $500. Ten years of breathing room.

• Low SES: Starts with $50. Exactly one year of subsistence.

The Result: A massive widening of outcomes.

Importantly, note that we are assuming 100 years(!). The compounding eventually takes over, which is an important clue to our current gerontocracy. But with only a 40-year working life, the median low-SES ends up worse off than they started. Less than 10% of high-SES people end up worse off than they started.

The High SES group compounding is nearly uninterrupted. Their buffer absorbs decades of shocks. They barely notice unemployment, the way you barely notice a pothole in an SUV.

The Low SES group enters what we can call the Capital Decay Regime. For the unlucky agent, the Restart Haircut and the unemployment shocks overwhelm the 10% savings rate. They spend their working lives recovering from the previous restart rather than compounding. Two unemployment events in a decade—which is not unusual, it is average—is enough to drive their wealth to zero.

The survival rates are the most damning output. The High SES group: near 100%. The Low SES group: nearly 13% ruin rate (bankrupt). And remember this is with a constant 4% unemployment rate — near the lowest in history. Same talent. Same work ethic. Same economy. Different starting coordinates. Different outcomes.

If we introduce recessions every 10 years, with unemployment rising to 8% and the duration of unemployment during recessions doubling to 6 months. Look familiar?

The Insight: Redundancy—starting wealth—is THE driver of outcomes. Without a buffer, the low-wealth agent is trapped in a sub-critical regime where growth is challenged, regardless of skill or effort. We have built a system where the “Cost of Survival” is set by the average, but the “Ability to Survive” is denied to the median.

I want to pause on that, because it maps perfectly to the empirical data.

When researchers decompose the White-Black lifetime earnings gap, two factors explain the overwhelming majority of the differential at the low end: years of full-time work (largely a proxy for unemployment frequency) and possession of health insurance. Not education. Not “grit.” Not IQ. Time in the game and a buffer against medical ruin.

At the 85th percentile—the high-outcome cohort—these factors explain almost nothing. Why? Because by definition, the people at the top already have the buffers. The variance has been absorbed. Of course, “they” think talent explains everything and that meritocracy asserts itself over time; unfortunately, we readers of YIGAF know that to be “untrue.” From the summit, the road looks smooth, and we can comfort ourselves that we “deserve” what we’ve made.

This is also why wealthy people don’t want to pay for universal healthcare. They literally cannot see the point. Their buffer makes the problem invisible.

Phase 4: The Sandwich Generation

Having established that buffers drive outcomes more than talent, we asked the obvious next question: What happens over a lifetime? Not just one agent’s lifetime—across generations.

We added three things that economists love to model in the abstract but rarely simulate in combination: children, retirement, and inheritance.

The Rules:

• The Inheritance Gap: High-SES children enter the workforce at 20 with a $500 buffer (their parents’ gift). Low-SES children enter with $0.

• The Parent Trap: You can only have a child if your wealth exceeds $375—roughly three years of subsistence. Each child costs $25/year for 18 years. Maximum three children.

• The Sandwich Transfer: Workers pay 10% of their salary to a retiree pool. Think of it as Social Security, Medicare, and the informal family obligations combined.

• Retirement: At 70, your salary disappears. You survive on accumulated capital (still compounding at 8%) and the transfer pool.

We ran this for 100 years—a full “Post-New Deal Era.”

The First Graph: Average vs. Median

The Average Wealth line shoots upward. If you were an economist looking at aggregate GDP, you would say the system is working. The pie is growing. As Nick Maggiulli correctly points out, the average wealth is disrupted by inheritance dilution, but the family wealth continues to compound.

The Median Wealth line crashes and flatlines. The typical household—the one in the middle, the one that votes, the one that sends kids to public school—cannot compound. The combination of child costs, the retiree transfer, and the ever-present unemployment shock consumes every dollar of surplus before it can grow.

This is the Ensemble Illusion. The average is being pulled upward by the top 1%, whose buffers are so large that they operate in a fundamentally different economy. The median is treading water. And the bottom quartiles are drowning. It’s an America where “we’ve never been richer” and “59% of households can’t afford a $1,000 emergency expense.”

The Second Graph: The Quintile Breakdown

This is where the simulation stopped being a model and started being a photograph.

When we broke the terminal wealth into quintiles and compared Parents (ages 25-45) against Retirees (ages 70-85), the picture was devastating.

Q1 through Q4: There is no meaningful difference between working-age parents and retirees in the bottom 80% of the economy. Both groups are pinned to the subsistence floor. The 10% transfer and the 8% capital returns are insufficient to lift the median retiree out of the Capital Decay regime. If you didn’t enter retirement with a massive buffer, you’re just as broke as the young family down the street.

Q5—The Decoupling: The only meaningful wealth accumulation happens in the top 20%. And within that quintile, the Retirees pull away from everyone else. They are the only cohort with enough capital to actually benefit from 50 years of compounding. They receive the transfer payments. They consume a shrinking fraction of their wealth. They have zero dependent costs—their children are grown. They don’t work, so they take no unemployment shocks.

They have become Capital.

Not “people who have capital.” Capital itself. A wealth object that compounds, extracts, and never resets.

The most profitable strategy in our simulation wasn’t to invent the future. It was to have already invented it 40 years ago and get “lucky.”

The Gerontocracy Is Not a Metaphor

We have inadvertently created a society in which the old hold all the capital, and the young are burned as fuel to keep them warm.

This isn’t generational warfare rhetoric. It’s the physics of the system.

The retiree class in Q5 benefits from every feature of the economy simultaneously: compound returns on a large base, transfer payments funded by workers, zero labor risk, zero child costs, and—here’s the kicker—preferential tax treatment on capital gains. The step-up in basis at death means that a lifetime of untaxed gains can be passed to heirs with the tax liability erased entirely.

Meanwhile, the Sandwich Generation (ages 30-50) is simultaneously funding:

• Their own rent (Cost of Living)

• Their children ($25/year per child for 18 years)

• The retiree transfer (10% of salary)

• The restart risk (unemployment shocks with no buffer)

They are paying for everything and compounding nothing.

I recently saw Rob Arnott present data showing the “declining fortunes” of wealthy individuals across generations and label it “hopeful”—evidence that wealth doesn’t persist. But he misread his own data. What he was seeing wasn’t degradation; it was inheritance dilution. The family dynasty’s wealth continues to compound. It’s just being split across more heirs. The per capita decline is an illusion. The dynastic wealth is growing faster than ever.

The Mechanism We Refuse to See

What our simulation reveals is that the American economy has a caste system, and it is not based on race, gender, or even education. It is based on Redundancy at birth.

If you enter the labor market with a buffer—parental wealth, a paid-for education, a family home to fall back on—you can survive the volatility. You can take risks. You can fail and try again. You can be a Ferrari on fresh asphalt.

If you enter without one, the math is against you from day one. You are not lazy. You are not untalented. You are simply operating in a sub-critical regime where the physics of geometric growth cannot help you, because every dollar of surplus is consumed by the cost of survival before it can compound.

We haven’t built a meritocracy. We’ve built a buffer-ocracy. And the biggest buffer of all is age—specifically, having been born early enough to accumulate capital before the ladder was pulled up.

The Cliffhanger

We have now diagnosed the disease: a system that selects for starting resources over talent, that concentrates wealth in retirees, and that traps the working-age population in a subsistence loop.

The obvious question was: Can you tax your way out of this?

I expected the answer to be simple. It wasn’t.

When we tested the reform that both libertarians and orthodox economists call “optimal”—cutting taxes on capital and raising them on consumption—the system didn’t just fail to improve. It got worse.

But when we tested a different structure entirely—one that most policy experts would dismiss as politically impossible—the simulation independently derived something remarkable: the tax code of the 1950s.

Part 3: “The Tax Code We Already Had” next week.

Read more

There are FOUR parts to this piece, the first three are brief, but important.

(1) An update on the search for candidates with a follow up discussion with Phil Andrew, who remains the sole candidate I’ve found that I can completely endorse. Several of my readers went to Phil’s congressional campaign site and came back complaining about his concerns on ICE. Long before the current headlines, Phil made a prescient call regarding the degradation of training standards at ICE. He warned that you cannot slash training curriculums—reducing months of instruction to mere weeks—and expect a professionalized force capable of handling complex enforcement scenarios. We are now seeing the results of those decisions. Phil breaks down exactly why "enforcement" without "professionalization" is a liability, not an asset.

Competent expertise proves prophetic. Funny how that works. Check out my most recent video, and please, please help. We face an uphill battle in restoring our Republic. We will NOT keep it under the current trajectory. One voice can make a difference. If you know anyone in Chicago, and remember it’s Chicago, so both the living and the dead vote, please forward the video.

(2) A brief update on markets

What I am watching VERY closely is the uptick in credit spreads as we see growing awareness that lending to the SAAS/software complex is metastasizing. Credit spreads ticked higher this week even as the cyclical elements of the economy are showing signs of life. I continue to think we’ll see the economy turn lower, but at least headline data says I’m wrong (PMI rebounds). Bankruptcies, credit card delinquencies, auto delinquencies, etc continue to march higher.

(3) A full-throated endorsement that ALL readers check out Marco Rubio’s speech at the Munich Security conference. There are adults in the room and this articulation was brilliant.

For the last few decades, we have lived under the “End of History” delusion—the idea that unfettered free trade and financialization would inevitably lead to global peace. Rubio’s speech was a systemic dismantling of that failure. He didn’t just offer “America First” slogans; he offered a coherent, intellectual rejection of the policies that deindustrialized the West and hollowed out our middle class.

Rubio explicitly linked the “euphoria” of globalization to the fragility we face today. This is the exact argument I have been making regarding market structure and labor arbitrage: when you prioritize efficiency over resilience, you lose your sovereignty. To hear this articulated from the podium in Munich—framing America not as a separate entity but as a “child of Europe” that must save the West from its own managed decline—signals a return to competence in US foreign policy that is deeply aligned with my own views.

Which brings us to the main event. As compensation to paid subscribers, the full code for all simulations is below the paywall. Have fun!

(4) The Achilles Heel — the domestic economy. I am not worried about our ability to win based on capacity. Nor am I quite as hyperbolic as Alex Karp (I have my own special hyperboles). Like most “foes”, China’s strengths are overstated. Their vulnerabilities are often ignored. We can win, but only if we build a system at home that utilizes the best of all of my fellow citizens. And to do that, we have to stop gaslighting. Milton Friedman, The Chicago School, and the Business Lobby took us on a fifty-year detour that threatens the foundations of our society. We can reclaim it, but first we must understand what we have lost. So let’s slide into summer…

Part 1 (of 3): The Summer Slide Economy

We tell ourselves a comforting story about success. It goes like this: The economy is a sorting mechanism. “Talent” (intelligence, grit, risk-tolerance) naturally rises to the top. If you are smart and unafraid, you will win. Everyone else is just drafting off your wake.

It is a seductive narrative. But it is physically wrong.

I didn’t arrive at this conclusion by debating philosophy. I arrived here by looking at the data—specifically, by trying to understand why poor kids fall behind rich kids, even when they are just as smart.

The “Twin Study” Sleight of Hand

To sustain the meritocratic narrative, defenders often point to Twin Studies. They cite data showing that identical twins have similar IQs, and then, in a magician’s sleight of hand, insist this proves that Wealth is genetic.

They are conflating the engine with the road.

While IQ has heritable components, Wealth is not a biological trait. It is an environmental condition. The most rigorous recent work on this, such as Fagereng, Mogstad, & Rønning (2020), uses adoption data to sever the biological link. Their finding is stark: Genes explain very little of who gets rich. Inheritance—specifically the ability to accumulate assets without interruption—explains almost everything. A more accessible version that extends the dataset to the UK is available here.

Same Salary, Different Outcome

Consider homeownership rates in the UK. When we compare children from wealthy families against children from poor families, we see a massive divergence.

The solid lines show reality: Rich kids buy houses; poor kids rent. But the dashed lines are the smoking gun. They represent a simulation where we control for the child’s income.

The result? Take two 30-year-olds with the exact same job, the exact same salary, and the exact same “grit.” The one with wealthy parents buys a house. The one with poor parents rents. The “merit” (income) is identical, but the outcome is strictly determined by the starting condition.

The Clue: The Summer Slide

This dynamic isn’t limited to housing. Years ago, education researchers stumbled upon a “natural experiment” that explains this perfectly.

They tracked the learning growth of students—high-income vs. low-income—over a calendar year.

• During the School Year: When structure, meals, and supervision (buffers) were provided by the state, the learning growth rates of poor kids and rich kids were statistically identical. The “Talent Gap” vanished.

• During the Summer: When those buffers were withdrawn, the divergence exploded. Rich kids continued to grow (camp, books, travel). Poor kids stagnated or regressed.

The “Achievement Gap” wasn’t a measure of intelligence; it was the mathematical sum of volatility shocks accumulated over twelve summers.

This led to a terrifying question: What if the entire economy is just one long Summer Slide?

The Simulation: A Thriller in Two Acts

To test this, we built a simulation of the US economy. We didn’t program it with ideology; we programmed it with the physics of Geometric Growth subject to Volatility.

Phase 1: The “Talent” Extinction Event We started with a world of “Pure Meritocracy.” No taxes, no safety nets, just raw probability. We created “Gifted” agents (High Return/High Risk—think Ferraris) and “Normie” agents (Low Return/Low Risk—think Camrys).

The Result? The “Gifted Poor” went extinct. While the Average Wealth of the talented group skyrocketed (driven by a few lucky survivors), the Median Wealth told a horrifying story. The typical “Gifted Poor” agent ended up poorer than the “Normie Poor.”

Why? Because high-risk strategies are geometrically unstable. Without a buffer to absorb the shocks, the “Gifted Poor” hit zero (bankruptcy) at nearly 25x the rate of the “Normie Rich.” The market didn’t select for Talent; it selected for Low Variance. The Ferrari breaks an axle on a rough road.

Phase 2: The “Volatility Tax” Next, we modeled the impact of random life shocks—unemployment, health crises, or family emergencies.

• High SES (Buffered): When a shock hits, they pause. They rely on savings or family support to smooth the blow.

• Low SES (Unbuffered): When a shock hits, they crash. They are forced to liquidate assets, take predatory loans, or move homes.

The result was a divergence engine. Even with identical talent and identical income, the Unbuffered group fell permanently behind. Inequality wasn’t driven by who worked harder. It was driven by who paid the Volatility Tax.

The Cliffhanger We had proven that volatility kills talent. But our simulation was still missing the most expensive parts of real life: Eating and Children.

When we added those to the model, the results went from “unfair” to “catastrophic.”

Part 2: “The Rise of the Gerontocracy” next week.

Read more

Appendix: Python Code

Can be executed in Google AiStudio: https://aistudio.google.com/prompts/new_chat?model=gemini-3-pro-preview. Make sure you have “Code Execution” selected on the lower right portion of your screen.

Subscribe now

Phase 1: The “Talent” Extinction Event

import numpy as np
import matplotlib.pyplot as plt

def run_phase_1_final_three_panels_v2():
    # Parameters
    n_agents = 5000 
    T = 40
    dt = 0.1
    steps = int(T / dt)
    
    W0 = 1000.0
    W_barrier = 200.0  # Ruin Barrier
    
    # Groups: (Name, Mu, Sigma, Color, Style)
    # Using distinct colors/styles to ensure all 4 are visible
    groups = [
        ("Normie / High SES", 0.05, 0.10, "tab:blue", "-"),      # Safe / Safe
        ("Normie / Low SES", 0.05, 0.20, "tab:cyan", "--"),      # Safe / Risky
        ("Gifted / High SES", 0.08, 0.20, "tab:green", "-"),     # Risky / Safe
        ("Gifted / Low SES", 0.08, 0.40, "tab:red", "--")        # Risky / Risky
    ]
    
    # Store data
    results_avg = {}
    results_median = {}
    results_survival = {}
    
    np.random.seed(42)
    
    for name, mu, sigma, color, style in groups:
        wealth = np.full(n_agents, W0)
        alive = np.ones(n_agents, dtype=bool)
        
        avg_hist = [W0]
        median_hist = [W0]
        survival_hist = [1.0]
        
        for t in range(steps):
            if np.any(alive):
                z = np.random.normal(0, 1, n_agents)
                growth = (mu - 0.5 * sigma**2) * dt + sigma * np.sqrt(dt) * z
                
                # Update wealth for alive agents
                wealth[alive] *= np.exp(growth[alive])
                
                # Check Ruin
                ruined = (wealth < W_barrier) & alive
                alive[ruined] = False
                wealth[ruined] = 0.0
            
            avg_hist.append(np.mean(wealth))
            median_hist.append(np.median(wealth))
            survival_hist.append(np.mean(alive))
            
        results_avg[name] = avg_hist
        results_median[name] = median_hist
        results_survival[name] = survival_hist

    # Plotting
    fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(18, 6))
    time = np.linspace(0, T, steps + 1)
    
    # Common function to plot with distinct styles
    def plot_lines(ax, data_dict):
        for name, data in data_dict.items():
            # Retrieve style info
            grp = next(g for g in groups if g[0] == name)
            color = grp[3]
            style = grp[4]
            # Plot
            ax.plot(time, data, label=name, color=color, linestyle=style, linewidth=2.5, alpha=0.9)

    # Panel 1: Average
    plot_lines(ax1, results_avg)
    ax1.set_title('Average Wealth (The Illusion)', fontweight='bold')
    ax1.set_ylabel('Wealth ($)')
    ax1.grid(True, alpha=0.3)
    ax1.legend(loc='upper left', fontsize='small')
    
    # Panel 2: Median
    plot_lines(ax2, results_median)
    ax2.set_title('Median Wealth (The Reality)', fontweight='bold')
    ax2.grid(True, alpha=0.3)
    ax2.legend(loc='upper left', fontsize='small')
    
    # Panel 3: Survival
    # Multiply by 100 for percentage
    results_survival_pct = {k: np.array(v)*100 for k, v in results_survival.items()}
    plot_lines(ax3, results_survival_pct)
    ax3.set_title('Survival Rate (The Mechanism)', fontweight='bold')
    ax3.set_ylabel('% Surviving')
    ax3.set_ylim(0, 105)
    ax3.grid(True, alpha=0.3)
    ax3.legend(loc='lower left', fontsize='small')
    
    plt.tight_layout()
    plt.show()

run_phase_1_final_three_panels_v2()

Phase 2: The Summer Slide Economy

import numpy as np
import matplotlib.pyplot as plt

def run_phase_2_random_shocks():
    # Parameters
    n_agents = 5000
    T = 20  # Years
    dt = 1/12 # Monthly steps
    steps = int(T / dt)
    
    W0 = 1000.0
    W_barrier = 200.0
    
    # Common Baseline (Stable Times)
    mu_stable = 0.08
    sigma_stable = 0.25
    
    # Shock Parameters
    shock_prob = 1/12 # Probability per month
    
    # High SES (Buffered) Shock
    mu_shock_H = 0.00
    sigma_shock_H = 0.25
    
    # Low SES (Unbuffered) Shock
    mu_shock_L = -0.20
    sigma_shock_L = 0.45
    
    # Setup Groups
    groups = [
        ("High SES (Buffered)", "green", "-"),
        ("Low SES (Unbuffered)", "red", "--")
    ]
    
    # Data Storage
    results_avg = {g[0]: [W0] for g in groups}
    results_median = {g[0]: [W0] for g in groups}
    results_survival = {g[0]: [1.0] for g in groups}
    
    wealths = {
        groups[0][0]: np.full(n_agents, W0),
        groups[1][0]: np.full(n_agents, W0)
    }
    alives = {
        groups[0][0]: np.ones(n_agents, dtype=bool),
        groups[1][0]: np.ones(n_agents, dtype=bool)
    }
    
    np.random.seed(42)
    
    for t in range(steps):
        for name, color, style in groups:
            w = wealths[name]
            alive = alives[name]
            
            if np.any(alive):
                # Determine who gets shocked (Individual Shocks)
                is_shocked = np.random.rand(n_agents) < shock_prob
                
                # Parameters for each agent
                # Default to stable
                mus = np.full(n_agents, mu_stable)
                sigmas = np.full(n_agents, sigma_stable)
                
                # Apply shock params
                if name == "High SES (Buffered)":
                    mus[is_shocked] = mu_shock_H
                    sigmas[is_shocked] = sigma_shock_H
                else:
                    mus[is_shocked] = mu_shock_L
                    sigmas[is_shocked] = sigma_shock_L
                
                # Geometric Brownian Motion Step
                z = np.random.normal(0, 1, n_agents)
                growth = (mus - 0.5 * sigmas**2) * dt + sigmas * np.sqrt(dt) * z
                
                # Update Wealth
                w[alive] *= np.exp(growth[alive])
                
                # Check Ruin
                ruined = (w < W_barrier) & alive
                alive[ruined] = False
                w[ruined] = 0.0
            
            results_avg[name].append(np.mean(w))
            results_median[name].append(np.median(w))
            results_survival[name].append(np.mean(alive))

    # Plotting
    fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(18, 6))
    time = np.linspace(0, T, steps + 1)
    
    def plot_panel(ax, data_dict, title, ylabel=None, ylim=None):
        for name, color, style in groups:
            y_vals = np.array(data_dict[name]) * 100 if "Survival" in title else data_dict[name]
            ax.plot(time, y_vals, label=name, color=color, linestyle=style, linewidth=2.5)
        
        ax.set_title(title, fontweight='bold')
        if ylabel: ax.set_ylabel(ylabel)
        if ylim: ax.set_ylim(ylim)
        ax.grid(True, alpha=0.3)

    plot_panel(ax1, results_avg, 'Average Wealth', ylabel='Wealth ($)')
    plot_panel(ax2, results_median, 'Median Wealth')
    plot_panel(ax3, results_survival, 'Survival Rate', ylabel='% Surviving', ylim=(0, 105))
    
    # Legend
    lines, labels = ax1.get_legend_handles_labels()
    fig.legend(lines, labels, loc='lower center', ncol=2, bbox_to_anchor=(0.5, -0.05))
    
    plt.tight_layout()
    plt.subplots_adjust(bottom=0.15)
    plt.show()

run_phase_2_random_shocks()

Phase 3: Eating

import numpy as np
import matplotlib.pyplot as plt

def run_phase_3_4pct_unemployment():
    # Parameters
    n_agents = 5000
    T = 100  # 100 Years
    dt = 1/12  # Monthly steps
    steps = int(T / dt)
    
    # Calibration for 4% Unemployment Rate:
    # If duration (D) = 3 months, and prob (p) is monthly:
    # Steady State Rate (u) = p*D / (1 + p*D - p)
    # 0.04 = 3p / (1 + 2p) -> 0.04 + 0.08p = 3p -> 0.04 = 2.92p -> p ≈ 0.0137
    shock_prob = 0.0137 
    unemployment_duration = 3 # months
    
    # Endowments (Latent Heat)
    w_high = np.full(n_agents, 500.0)
    w_low = np.full(n_agents, 50.0)
    
    # Economic Physics
    salary_yr = 55.0
    col_adult_yr = 50.0
    job_penalty = 10.0 # Restart penalty
    
    mu_cap = 0.08    # 8% annual return on savings
    sigma_cap = 0.25 # 25% annual volatility
    
    results = {
        "High SES": {"avg": [], "median": [], "survival": []},
        "Low SES": {"avg": [], "median": [], "survival": []}
    }
    
    np.random.seed(42)
    
    for name, wealth in [("High SES", w_high), ("Low SES", w_low)]:
        w = wealth.copy()
        alive = np.ones(n_agents, dtype=bool)
        unemp_timer = np.zeros(n_agents)
        
        for t in range(steps):
            if np.any(alive):
                # 1. Labor Market Dynamics
                # Check for new shocks
                new_shock = (np.random.rand(n_agents) < shock_prob) & (unemp_timer == 0)
                unemp_timer[new_shock] = unemployment_duration
                
                # Monthly Salary
                monthly_salary = np.full(n_agents, salary_yr * dt)
                monthly_salary[unemp_timer > 0] = 0.0
                
                # Apply Job Penalty at re-employment (end of month 3)
                just_hired = (unemp_timer == 1) 
                w[just_hired & alive] -= job_penalty
                
                # Decrement timer
                unemp_timer[unemp_timer > 0] -= 1
                
                # 2. Capital Growth (Multiplicative)
                z = np.random.normal(0, 1, n_agents)
                growth_mask = (w > 0) & alive
                growth = (mu_cap - 0.5 * sigma_cap**2) * dt + sigma_cap * np.sqrt(dt) * z
                w[growth_mask] *= np.exp(growth[growth_mask])
                
                # 3. Fixed Costs (Eating)
                current_col = col_adult_yr * dt
                w[alive] += monthly_salary[alive] - current_col
                
                # 4. Survival Check
                ruined = (w <= 0) & alive
                alive[ruined] = False
                w[ruined] = 0.0
                
            results[name]["avg"].append(np.mean(w))
            results[name]["median"].append(np.median(w))
            results[name]["survival"].append(np.mean(alive) * 100)

    # Visualization
    fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(20, 6))
    time = np.linspace(0, T, steps)
    
    for name, color, style in [("High SES", "green", "-"), ("Low SES", "red", "--")]:
        ax1.plot(time, results[name]["avg"], label=name, color=color, linestyle=style, linewidth=2)
        ax2.plot(time, results[name]["median"], label=name, color=color, linestyle=style, linewidth=2)
        ax3.plot(time, results[name]["survival"], label=name, color=color, linestyle=style, linewidth=2)
    
    ax1.set_title('Average Wealth (The Illusion)', fontweight='bold')
    ax2.set_title('Median Wealth (The Struggle)', fontweight='bold')
    ax3.set_title('Survival Rate (The Attrition)', fontweight='bold')
    for ax in [ax1, ax2, ax3]:
        ax.grid(True, alpha=0.3)
        ax.legend()
    ax3.set_ylim(0, 105)
    plt.tight_layout()
    plt.show()

run_phase_3_4pct_unemployment()

Phase 4: The Sandwich Generation

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

def run_phase_4_silver_aristocracy():
    # ---------------------------------------------------------
    # 1. Global Parameters (Phase 4 Logic)
    # ---------------------------------------------------------
    n_agents = 5000
    T = 100            # 100-year Post-New Deal Era
    dt = 1/12          # Monthly steps
    steps = int(T / dt)
    np.random.seed(42)
    
    # Endowments (The Inheritance Gap)
    # High SES: $500 (Latent Heat / Buffer)
    # Low SES: $0 (The Sub-Critical Floor)
    w = np.concatenate([np.full(n_agents//2, 500.0), np.full(n_agents//2, 0.0)])
    is_high_ses = np.concatenate([np.ones(n_agents//2, dtype=bool), np.zeros(n_agents//2, dtype=bool)])
    
    # Demographics
    age = np.random.randint(0, 85, n_agents).astype(float)
    unemp_timer = np.zeros(n_agents)
    
    # Child Tracking (Max 3 Children per household)
    n_children = np.zeros(n_agents, dtype=int)
    child_timers = [np.zeros(n_agents) for _ in range(3)] 
    
    # Economic Constants
    salary_yr = 55.0        # Labor Income
    col_adult_yr = 50.0     # Baseline "Eating" Cost
    child_cost_yr = 25.0    # Fixed 50% "Child Tax"
    job_penalty = 10.0      # Restart Haircut (delta)
    parent_threshold = 375.0 # Required wealth (3yrs CoL)
    
    # Market Risk/Return
    mu_cap = 0.08           # 8% "Gifted" Potential
    sigma_cap = 0.25        # 25% "Ferrari" Volatility
    shock_prob = 0.0137     # Calibrated for 4% steady-state unemployment
    unemployment_duration = 3 
    
    # Storage for time-series visualization
    results_median = []
    results_avg = []
    
    # ---------------------------------------------------------
    # 2. Main Simulation Loop
    # ---------------------------------------------------------
    for t in range(steps):
        age += dt
        
        # A. Death & Dynastic Replacement (Inheritance)
        dead = (age >= 85)
        if np.any(dead):
            # The next generation begins - High SES inherit, Low SES reset to 0
            w[dead & is_high_ses] = 500.0
            w[dead & ~is_high_ses] = 0.0
            age[dead] = 0
            n_children[dead] = 0
            for i in range(3): child_timers[i][dead] = 0
            unemp_timer[dead] = 0

        # B. Labor Market (The Effort Bucket)
        is_worker = (age >= 20) & (age < 70)
        is_retiree = (age >= 70) & (age < 85)
        
        # Unemployment shocks
        new_shock = (np.random.rand(n_agents) < shock_prob) & (unemp_timer == 0) & is_worker
        unemp_timer[new_shock] = unemployment_duration
        
        salary_mo = np.zeros(n_agents)
        salary_mo[is_worker & (unemp_timer == 0)] = salary_yr * dt
        
        # Apply Job Penalty (Restart Cost) at the moment of re-employment
        just_hired = (unemp_timer == 1)
        w[just_hired] -= job_penalty
        unemp_timer[unemp_timer > 0] -= 1
        
        # C. The Sandwich Transfer (10% Wage tax from workers to retirees)
        total_transfer_pool = np.sum(salary_mo) * 0.10
        salary_mo[is_worker] *= 0.90 
        
        num_retirees = np.sum(is_retiree)
        if num_retirees > 0:
            w[is_retiree] += (total_transfer_pool / num_retirees)
            
        # D. Capital Growth (The Luck Bucket)
        z = np.random.normal(0, 1, n_agents)
        growth = (mu_cap - 0.5 * sigma_cap**2) * dt + sigma_cap * np.sqrt(dt) * z
        w[w > 0] *= np.exp(growth[w > 0])
        
        # E. The Parent Trap (Reproduction Mechanic)
        can_have_kid = (age >= 25) & (age < 45) & (w >= parent_threshold) & (n_children < 3)
        # Random birth chance if threshold is met
        new_kid = can_have_kid & (np.random.rand(n_agents) < (1/48))
        for i in np.where(new_kid)[0]:
            idx = n_children[i]
            child_timers[idx][i] = 18.0
            n_children[i] += 1
        
        # F. Fixed Drains (Eating + Children)
        active_child_costs = np.zeros(n_agents)
        for i in range(3):
            is_active = child_timers[i] > 0
            active_child_costs[is_active] += (child_cost_yr * dt)
            child_timers[i][is_active] -= dt
        
        w += salary_mo - (col_adult_yr * dt) - active_child_costs
        
        # G. The Ruin Barrier (Volatility Trap)
        w[w < 0.01] = 0.01 
        
        results_median.append(np.median(w))
        results_avg.append(np.mean(w))
        
    # ---------------------------------------------------------
    # 3. Visualization
    # ---------------------------------------------------------
    fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(16, 7))
    time = np.linspace(0, T, steps)
    
    # Figure 1: Average vs Median
    ax1.plot(time, results_avg, label='Average Wealth (Ensemble)', color='green', linewidth=2)
    ax1.plot(time, results_median, label='Median Wealth (Typical Agent)', color='red', linestyle='--', linewidth=2)
    ax1.set_title('Figure 1: 100-Year Wealth Divergence (Post-New Deal Era)', fontweight='bold')
    ax1.set_xlabel('Years')
    ax1.set_ylabel('Wealth ($)')
    ax1.legend()
    ax1.grid(True, alpha=0.3)
    
    # Figure 2: Log-Quintile Distribution
    retiree_w = w[(age >= 70) & (age < 85)]
    parent_w = w[(age >= 25) & (age < 45)]

    def get_quintile_means(data):
        if len(data) == 0: return [0.01]*5
        data_sorted = np.sort(data)
        chunks = np.array_split(data_sorted, 5)
        return [np.mean(c) for c in chunks]

    p_quint = get_quintile_means(parent_w)
    r_quint = get_quintile_means(retiree_w)
    
    x = np.arange(5)
    width = 0.35
    ax2.bar(x - width/2, p_quint, width, label='Parents (Ages 25-45)', color='navy', alpha=0.8)
    ax2.bar(x + width/2, r_quint, width, label='Retirees (Ages 70-85)', color='darkorange', alpha=0.8)
    ax2.set_title('Figure 2: Wealth Concentration by Quintile (Log Scale)', fontweight='bold')
    ax2.set_xticks(x)
    ax2.set_xticklabels(['Q1', 'Q2', 'Q3', 'Q4', 'Q5'])
    ax2.set_yscale('log')
    ax2.set_ylabel('Wealth ($)')
    ax2.legend()
    ax2.grid(True, which="both", ls="-", alpha=0.2)
    
    plt.tight_layout()
    plt.show()

# Execution
run_phase_4_silver_aristocracy()

Phase 5: Tax Policy

import numpy as np
import matplotlib.pyplot as plt

def run_comparative_tax_simulation():
    # ---------------------------------------------------------
    # 1. Global Parameters
    # ---------------------------------------------------------
    n_agents = 5000
    T = 100            # 100 Years
    dt = 1/12          # Monthly time steps
    steps = int(T / dt)
    
    # Common Economic Parameters
    salary_yr = 55.0        
    col_adult_yr = 50.0     
    child_cost_yr = 25.0    
    job_penalty = 10.0      
    parent_threshold = 375.0 
    mu_cap = 0.08           # 8% Return (The "Ferrari")
    sigma_cap = 0.25        # 25% Volatility
    shock_prob = 0.0137     # 4% Unemployment Rate
    unemployment_duration = 3 
    
    # The Two Scenarios
    scenarios = [
        {
            "name": "Scenario A: Annual Tax (30% Cap / 0% Estate)", 
            "labor_tax": 0.10, 
            "annual_cap_tax": 0.30, 
            "estate_tax": 0.0
        },
        {
            "name": "Scenario B: Deferred Tax (0% Cap / 50% Estate)", 
            "labor_tax": 0.10, 
            "annual_cap_tax": 0.0, 
            "estate_tax": 0.50
        }
    ]
    
    results = {}

    print(f"Running Simulation for {T} Years with N={n_agents} Agents...")

    for sc in scenarios:
        # Reset Agents
        # High SES start at $500; Low SES start at $0
        w = np.concatenate([np.full(n_agents//2, 500.0), np.full(n_agents//2, 0.0)])
        is_high_ses = np.concatenate([np.ones(n_agents//2, dtype=bool), np.zeros(n_agents//2, dtype=bool)])
        
        # Consistent demographics reset
        np.random.seed(42) 
        age = np.random.randint(0, 85, n_agents).astype(float)
        unemp_timer = np.zeros(n_agents)
        n_children = np.zeros(n_agents, dtype=int)
        child_timers = [np.zeros(n_agents) for _ in range(3)] 
        
        median_history = []
        aggregate_history = []
        
        # Re-seed for loop dynamics
        np.random.seed(42) 

        for t in range(steps):
            age += dt
            
            # --- DEATH & ESTATE TAX (The Harvest) ---
            dead = (age >= 85)
            estate_tax_revenue = 0.0
            
            if np.any(dead):
                dead_wealth = w[dead].copy()
                
                # Apply Estate Tax
                tax_collected = dead_wealth * sc["estate_tax"]
                estate_tax_revenue = np.sum(tax_collected)
                
                # Inheritance (Heir gets the remainder)
                w[dead] -= tax_collected
                
                # Reset Demographics for Heir
                age[dead] = 0
                n_children[dead] = 0
                for i in range(3): child_timers[i][dead] = 0
                unemp_timer[dead] = 0

            # --- LABOR MARKET ---
            is_worker = (age >= 20) & (age < 70)
            
            new_shock = (np.random.rand(n_agents) < shock_prob) & (unemp_timer == 0) & is_worker
            unemp_timer[new_shock] = unemployment_duration
            
            salary_mo = np.zeros(n_agents)
            salary_mo[is_worker & (unemp_timer == 0)] = salary_yr * dt
            
            just_hired = (unemp_timer == 1)
            w[just_hired] -= job_penalty
            unemp_timer[unemp_timer > 0] -= 1
            
            # --- LABOR TAX ---
            tax_labor_rev = np.sum(salary_mo * sc["labor_tax"])
            salary_mo *= (1 - sc["labor_tax"])
            
            # --- CAPITAL GROWTH & ANNUAL TAX ---
            current_w = w.copy()
            z = np.random.normal(0, 1, n_agents)
            growth = (mu_cap - 0.5 * sigma_cap**2) * dt + sigma_cap * np.sqrt(dt) * z
            w[w > 0] *= np.exp(growth[w > 0])
            
            # Annual Capital Tax (Only for Scenario A)
            annual_tax_rev = 0.0
            if sc["annual_cap_tax"] > 0:
                gains = w - current_w
                taxable_gains = np.maximum(gains, 0)
                tax_collected = taxable_gains * sc["annual_cap_tax"]
                annual_tax_rev = np.sum(tax_collected)
                w -= tax_collected
            
            # --- DIVIDEND (The Mechanism) ---
            # Pool all three sources: Labor Tax + Annual Cap Tax + Estate Tax
            total_revenue = tax_labor_rev + annual_tax_rev + estate_tax_revenue
            dividend = total_revenue / n_agents
            w += dividend
            
            # --- COSTS ---
            active_child_costs = np.zeros(n_agents)
            for i in range(3):
                is_active = child_timers[i] > 0
                active_child_costs[is_active] += (child_cost_yr * dt)
                child_timers[i][is_active] -= dt
            
            w += salary_mo - (col_adult_yr * dt) - active_child_costs
            
            # Floor (Absorbing Barrier)
            w[w < 0.01] = 0.01 
            
            # Reproduction
            can_have_kid = (age >= 25) & (age < 45) & (w >= parent_threshold) & (n_children < 3)
            new_kid = can_have_kid & (np.random.rand(n_agents) < (1/48))
            for i in np.where(new_kid)[0]:
                idx = n_children[i]
                child_timers[idx][i] = 18.0
                n_children[i] += 1
            
            median_history.append(np.median(w))
            aggregate_history.append(np.sum(w))
            
        results[sc["name"]] = {"median": median_history, "aggregate": aggregate_history}

    # ---------------------------------------------------------
    # 2. Visualization
    # ---------------------------------------------------------
    fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(16, 6))
    time = np.linspace(0, T, steps)
    
    # Plot Aggregate Wealth
    for name, data in results.items():
        color = 'red' if "Annual" in name else 'green'
        style = '--' if "Annual" in name else '-'
        ax1.plot(time, data["aggregate"], label=name, color=color, linestyle=style, linewidth=2)
    
    ax1.set_title('Figure 1: Aggregate Wealth (The Pie)', fontweight='bold')
    ax1.set_ylabel('Total Wealth ($) - Log Scale')
    ax1.set_xlabel('Years')
    ax1.set_yscale('log') # Log scale needed to see the magnitude difference
    ax1.legend()
    ax1.grid(True, which="both", ls="-", alpha=0.2)
    
    # Plot Median Wealth
    for name, data in results.items():
        color = 'red' if "Annual" in name else 'green'
        style = '--' if "Annual" in name else '-'
        ax2.plot(time, data["median"], label=name, color=color, linestyle=style, linewidth=2)
    
    ax2.set_title('Figure 2: Median Wealth (The Household)', fontweight='bold')
    ax2.set_ylabel('Median Wealth ($)')
    ax2.set_xlabel('Years')
    ax2.legend()
    ax2.grid(True, alpha=0.3)
    
    plt.tight_layout()
    plt.show()
    
    # Print Final Stats
    print("\nFinal Statistics (Year 100):")
    for name, data in results.items():
        print(f"{name}:")
        print(f"  Aggregate Wealth: ${data['aggregate'][-1]:,.0f}")
        print(f"  Median Wealth:    ${data['median'][-1]:,.0f}")
        print("-" * 30)

run_comparative_tax_simulation 

Read more

We invoke “American Exceptionalism” constantly without pausing to ask where the idea came from. The origin of the term is far more precise—and far less flattering—than its modern usage suggests. But there is a deeper version of the idea, one that predates the phrase by 150 years, and it begins with a man giving power away.

The First Refusal

In December 1783, George Washington performed an act of political self-denial that the 18th-century world considered a physical impossibility: he resigned. He held absolute command of the Continental Army and the implicit offer of a crown—and he walked away. In doing so, he reached back across two millennia to the Roman ideal of Cincinnatus, proving that the American experiment would be built not on the reach for power, but on the capacity to refuse it. George III reportedly said that if Washington did this, he would be “the greatest man in the world.” He did it.

This is the founding act of American Exceptionalism. Not the Declaration. Not the Constitution. A man to whom the maximum power was given chose to diminish it in favor of the people. Everything that follows in this essay—every crisis, every choice, every failure—is measured against that standard.

Stalin’s Sneer

In the late 1920s, Jay Lovestone, General Secretary of the Communist Party USA, argued that American capitalism was unusually resilient—temporarily exempt from the “universal laws” of Marxist collapse. When Lovestone defended this view in Moscow in 1929, Joseph Stalin responded with fury. He denounced the argument as a “theory of American exceptionalism,” not as praise, but as a sneer. To Stalin, America wasn’t special; it was just behind schedule. Within months, the Great Depression began, and it appeared the “universal laws” were reasserting themselves.

To understand what happened next—and why it matters for 2026—you have to understand what “money” meant to the men who ran America.

Morgan’s Hierarchy: Money vs. Credit

“Money is gold, and nothing else; all the rest is credit.” J.P. Morgan said this to Congress in 1912, and he wasn’t being poetic. He was defining a hierarchy. Bank deposits were merely a promise to pay money—they were credit. And the “Gold Clause,” a contractual legacy of the fear of Civil War Greenbacks, was the creditor’s insurance policy: all debts were repayable in gold coin at the creditor’s option.

In periods of prosperity, the ratio of credit-to-money (gold) functioned as a useful abstraction. But by 1933, the public stopped believing in the promises. They rushed to convert their “credit” into “money”—physical gold and currency. The math was a physical impossibility. The private sector was legally committed to settling $100 billion in gold-linked contracts. The total gold in private hands was approximately $1 billion.

It was a systemic margin call. And because settlement was at the creditor’s option, any government attempt to devalue the dollar would simply trigger the Gold Clause. The nominal value of the debt would have exploded to match the devaluation, wiping out every debtor in the country instantly.

Three New Deals

Confronted with this impossibility, Roosevelt surveyed a world where the classical liberal model had failed. As Wolfgang Schivelbusch outlines in The Three New Deals, the 1930s offered three distinct paths:

The Mussolini Model (The Corporate State): Enforce the creditors’ claims by force. Use the state to suppress the mob and ensure nominal financial claims remain whole.

The Hitler Model (National Socialism): Nationalize the logic of the nation. The state absorbs private property and industry into a monolithic command structure.

The Roosevelt Model (Principled Abrogation): The “Exceptional” Path. Roosevelt—in the tradition of Washington’s resignation—chose to save the private market by attacking the mathematical ghost that haunted it. He used the Pen to abrogate the Gold Clause, performing a surgical strike on the $100 billion liability.

By choosing this path, Roosevelt effectively “printed” $69 billion in equity for the nation. He saved the railroad equity, the farmer’s land, and the average citizen’s bank deposits by sacrificing the creditors’ unrealistic “option.”

This is the distinction that matters: the Refinancer changes the rules to save the system. The Manager picks winners to control it.

The Business Plot and the Black Book

The creditor class did not take the 1933 abrogation lying down. The Business Plot of 1934 was a plan by financiers — including names like Robert Sterling Clark and allegedly Prescott Bush — to overthrow FDR and replace him with a fascist military state.

The plotters approached Major General Smedley Butler, the most decorated Marine in American history. Butler was the “Refinancer” of the military; a man who had already exposed the structural rot of the defense industry in War is a Racket. He held the pedigree to lead a coup and the credibility to sell it to the rank and file. Butler refused. He went to Congress instead.

In the taxonomy of this essay, Butler was Washington’s echo: a man who held the power to become the Manager and chose constraint. Washington resigned a commission. Butler refused one. The pattern of American Exceptionalism isn’t ideological—it’s behavioral. It is the repeated choice of constraint by those to whom the maximum power was offered.

Roosevelt didn’t just survive the plot; he weaponized it. Instead of a public trial that might have sparked revolution, he worked with the McCormack-Dickstein Committee to suppress the most damning names from the final report. He kept the evidence of treason as a private file of kompromat, ensuring the elite’s subsequent obeisance. They didn’t sign on to the New Deal because they believed in it; they signed on because the President held their lives in his desk drawer.

The Epstein Model: Obeisance by Redaction

This is the historical precursor to the Epstein model of governance: a system where the state ensures elite compliance not through the rule of law, but through the possession of the “black book.” Hoover’s FBI ran the same playbook for decades. The mechanism is always the same: you will do what I tell you, or I remove the blackout.

In 2026, the Epstein Files Transparency Act was supposed to break this pattern. Instead, we are witnessing the logic of 1934 perfected. On January 30, 2026, the Department of Justice dumped 3.5 million pages of files, but the “transparency” is a facade. The DOJ has withheld nearly 200,000 pages under “privilege” and has systematically blacked out the names of public figures while “accidentally” exposing the victims.

The true “Black Book” has simply been moved to a DOJ reading room. On February 2, 2026, the administration announced that only members of Congress—the very people most susceptible to institutional leverage—would be allowed to see the unredacted names. The public gets the redacted mess; the Manager gets the leverage. When Deputy Attorney General Todd Blanche stated that there was “nothing in there that allowed us to prosecute anybody,” he wasn’t declaring a lack of crime; he was declaring a refusal to act. The blackout remains the tool of the Manager. “You will do what I tell you, or I remove the blackout.”

Likewise, the investigation into Jerome Powell—a man I loathe for his intellectual incuriosity, but accept is trying his limited best—is a transparent pretext to remove a “for cause” referee and replace him with a political manager. Kevin Warsh is that man. While reshoring strategic minerals is a valid act of national security, it is being used as a license for bespoke management—dictating winners through executive deals.

Roosevelt saved the country as a Refinancer in 1933 but nearly broke it as a Manager by 1937. The “Roosevelt Recession”—triggered by premature fiscal tightening and ongoing interventionist management of industrial relations—proved that even the most skilled Refinancer becomes destructive once he starts believing he can manage outcomes indefinitely. The surgical act saved the system. The ongoing management destabilized it.

Today, we have the worst of both: a state too weak to refinance the structural imbalances and too arrogant to stop managing the chicken coop. But don’t take my word for it. Look at the numbers.

Where the State Actually Fails

The narrative machinery of the current moment—amplified by figures like Elon Musk through X’s new long-form content prizes—wants you fixated on government spending fraud. The inaugural $1 million X article award went to a piece casting Deloitte as a “$74 billion cancer metastasized across America,” alleging that taxpayer dollars were siphoned and that there were revolving doors of insiders. Runners-up included exposés on welfare fraud in Minnesota—state-level fraud, notably, not federal. The awards align neatly with Musk’s DOGE-adjacent critiques of government waste.

Here’s the irony: Musk himself faces fraud accusations ranging from misleading claims about Tesla’s Full Self-Driving capabilities to the controversial SolarCity acquisition—widely seen as a bailout for his cousins’ failing company. But the deeper irony isn’t the hypocrisy. It’s that the entire spending-fraud narrative is a distraction from where the government actually underperforms—not expense management, where it’s roughly on par with the private sector, but revenue collection, where evasion drains far more.

Private companies collect 97–99 cents on every dollar owed. The U.S. government collects 85–87 cents. That is the number that should define the fiscal debate. Everything below explains why it doesn’t.

On the expense side, the federal government loses an estimated 3–7% of its ~$7 trillion in annual outlays to genuine spending fraud—roughly $233–521 billion per year (per GAO estimates isolating willful misrepresentation from documentation errors where payment was substantively proper). That range is mediocre, not catastrophic—and much of it persists due to a principal-agent problem baked into cooperative federalism. States run programs such as Medicaid with federal funds under matching formulas, in which the federal share ranges from 50–90%, thereby diluting the incentive to enforce aggressively. It’s not their money, it’s yours. This is why high-profile cases, such as Minnesota’s Medicaid schemes, arise at the state level.

The private sector, by comparison, loses 1–5% of its ~$45–50 trillion in gross output to occupational fraud and theft, per the ACFE’s 2024 global survey. Government is worse on expenses, but not by the order of magnitude the headlines suggest.

On the revenue side, the picture is devastating. The IRS projects a net tax gap of $606 billion for tax year 2022—roughly 13% of the $4.7 trillion in true tax liability. Two leading government economists disagree about where the worst abuses of that gap live: Guyton (IRS) uses detection-controlled estimation to capture sophisticated evasion that random audits miss—offshore accounts, pass-throughs, complex partnerships—and finds evasion rates rising sharply with income, with the top 1% driving roughly 30% of the gap. Splinter (Joint Committee on Taxation) argues those multipliers overstate true fraud, conflating gray-area documentation issues with willful evasion—the same measurement critique we correctly apply to spending-side “improper payment” figures. Even under Splinter’s more generous methodology, 65–70% of the gap in dollar terms still concentrates at the top. The debate is about the slope of the evasion curve, not its center of mass.

The Fiscal Mirror: The Spend vs. The Collect

The current narrative focuses on the 3–7% expense-side fraud because it suggests the state is a bumbling thief. We must reduce its power! It ignores the 13% revenue-side gap because doing so would reveal that the state is a selective partner.

The Mussolini Model in Fiscal Form

This is where the fiscal data meets the political philosophy. A genuine Refinancer would attack the revenue side, because that’s where the structural failure actually lives. Closing even one-third of the true intentional tax gap would generate more new revenue than almost any realistic spending cut.

But a Manager doesn’t want to fix the revenue side. The revenue gap is the patronage system.

The ability to selectively enforce tax obligations is itself a form of the black book. You collect from those who don’t comply politically; you look away from those who do. Musk's amplification of the Deloitte story on X constitutes the active construction of the managerial frame—the NRA Blue Eagle of 2026, a symbol of compliance. By awarding prizes for exposés on spending, the Manager ensures the public never asks why the most “Exceptional” citizens are the ones least likely to pay the entry fee for the Republic. It tells the public: your problem is that the government spends too much. It never asks: why does the government collect so little from the people who owe the most?

This is the Mussolini model in fiscal form: not the enforcement of rules, but the management of outcomes. The state doesn’t fix the tax code; it uses the broken tax code as leverage.

The Exceptional Path

Exceptionalism was never about American superiority. It was the willingness of a traitor to his class to accept constraint in order to preserve the system. Roosevelt’s genius in 1933 wasn’t that he was powerful—it was that he used power surgically and then stopped. The Refinancer says: I will change this rule, and then the market will sort itself out. Gerald Corrigan in 1987. The Manager says: I will sort it out myself, permanently. Ben Bernanke in 2008. One requires faith in the system. The other requires faith in the manager.

Today, we are fulfilling Stalin’s prophecy—not by collapsing under Marxist laws, but by choosing the corporate state, where the executive manages outcomes rather than enforces rules, and where the public is kept focused on the 3–7% expense-side problem so they never notice the 13% revenue-side catastrophe.

So the questions for 2026 are the same ones that have defined every genuine crisis in this republic: who is the traitor to his class? Who will accept power and then relinquish it in favor of the people? Washington resigned a commission. Butler refused a coup. Roosevelt abrogated a claim, but needed death to be stopped. Our luck is fading, as we acknowledged with the 22nd and 25th amendments. The Exceptional Path requires someone to whom the maximum power was given to choose to diminish it in favor of the people. We used to believe they would do it from civic duty. We were lulled into complacency by Washington.

Is the current candidate the person firing the Federal Reserve chair? Is it the tech billionaire awarding prizes for spending-fraud exposés while his own regulatory history fills a docket? Or is it someone we haven’t met yet—someone willing to enforce the 97–99% collection rate that the private sector considers standard, hold the narrators to the same arithmetic as the narrated, and then accept the constraint of stopping?

I don’t know. But don’t let the headlines distract you. That’s the point.

Section End

Markets In Space!

Well, let’s see how the year is going?

Bitcoin? Pffthhh… and largely for the reasons I hypothesized — ETF selling

Commodities? Little rocky past few days, but looking good so far, Louis.

Public listings of Trillion Dollar IPOs facilitated by early index inclusion?

Wait… what?

Yep. Nasdaq and Elon Musk are effectively weaponizing the savings of passive investors to provide an exit for a billionaire who settled federal fraud charges and was forced out of his Chairmanship for misleading the public.

We are reaching the end stage. Rome is truly a city for sale to a ready buyer, and, as Adam Butler has highlighted, we are monetizing intergenerational trust for short-term profits. But ewe, dear reader, can still play a role. The Nasdaq comment period is open. You can find it here. Damn the torpedoes and sail into the harbor of action. I’ve made it easy for you. Let’s see if 50K subscribers can change the world:

Email address: indexconsultations@nasdaq.com

Subject: Response to Nasdaq-100 Index Consultation – February 2026

To the Nasdaq Index Committee,

I am writing to formally oppose the methodology enhancements outlined in the February 2026 Consultation Paper, specifically the “5x Free Float Multiplier” (Proposal 3) and “Fast Entry” (Proposal 2).

While these proposals are presented as modernizations to ensure the index captures the largest companies, they essentially function as an engine for insider enrichment and leveraged front-running. By artificially inflating the index weights of low-float securities, Nasdaq proposes to subsidize issuers that restrict public access, thereby forcing passive investors to finance a manufactured squeeze.

My specific objections are as follows:

1. The “5x Multiplier” Incentivizes Liquidity Hoarding

The proposal to weight securities with <20% float at five times their actual free float fundamentally breaks the bargain of public listing. Traditionally, to achieve a high index weighting and the associated lower cost of capital, an issuer must provide commensurate liquidity to the public.

Under Proposal 3, Nasdaq is effectively paying insiders to not sell.

• Enrichment of Insiders: By allowing a company to retain 80-90% of its equity while receiving the index flows of a 50% float company, you create a massive multiplier effect on the stock price. This ensures that insider holdings, options, and RSUs move deep in-the-money immediately upon inclusion, driven by mandated passive buying rather than fundamental value.

• Subsidy for Scarcity: This rule penalizes companies that provide true liquidity and subsidizes those that maintain artificial scarcity. It creates a perverse incentive structure where the optimal strategy for a “Top 40” issuer is to float the absolute minimum required to trigger the multiplier.

2. Structuring a “Leveraged Front-Running” Opportunity

The combination of “Fast Entry” (inclusion at Day 15) and the “5x Multiplier” creates a mathematically guaranteed trade for index arbitrageurs.

• The Squeeze Math: Sophisticated market participants will immediately calculate the imbalance: Index Demand > Available Float. When the index is mandated to buy 5x more exposure than the available liquidity supports, a squeeze is not a risk—it is a certainty.

• Predatory Mechanics: Arbitrageurs will “buy like mad” ahead of the index inclusion, cornering the thin float. By the time passive funds execute their mandated buy orders on Day 15, they will be purchasing inventory from these intermediaries at artificially inflated prices.

• The Loser is the Passive Investor: The ultimate purchaser in this chain is the passive index holder (retirement accounts, pension funds). This proposal systematically transfers wealth from these holders to early speculators and corporate insiders.

3. Conclusion

The proposed changes do not merely “modernize” the index; they weaponize it. They turn the Nasdaq-100 into a mechanism that rewards governance structures designed to restrict supply.

If Nasdaq proceeds with Proposal 3, it will engineer a wealth transfer from the investing public to private insiders, using passive flows as the delivery mechanism. I urge the Committee to reject the “5x Float Multiplier” and maintain a link between index weight and tradable liquidity.

Sincerely,

_______

Your Name Here

As always, questions, comments, space garbage, and sofa lint are appreciated.

And while the Cleveland Fed “All Tenant Rent” index is no longer updating in a timely manner, it suggests that further declines are ahead:

The hedonic deflation of the CPI rent factor has now normalized against private sector measures like Zillow rents. From here, we should expect Zillow rents to remain below CPI rents as an aging housing stock is “artificially” inflated with hedonics:

Adjusting PCE to exclude the POSITIVE impact of these hedonic adjustments again suggests that the near-term risk is deflationary, not inflationary:

The pattern of RESIDUAL seasonality created by the pandemic and Russian invasion of Ukraine will continue for one more year (BLS uses 5-year trailing averages), and exactly as forecast, the Fed has once again abandoned rate cuts due to fears that inflation is not making progress towards the 2% goal, misled by the data adjustments. This residual seasonality is likely to reverse by May:

And as CPI prints “beat” to the downside, driven by seasonality, this is likely to lead to renewed discussions of rate cuts. My estimate is that we will get nearly three cuts priced in over 2026 as the seasonality gives way yet again. In other words, Waller was right to dissent:

Could I be wrong? Of course. If I’m wrong, it will be because the private sector recession ends. We are absolutely seeing a rebound in the cyclical sectors, with a moderate rebound in new orders. We have been in the longest period of GDP-wtd PMI New Orders weakness since the GFC:

On the flip side, government employment is contracting at the Federal level; state and local seem not far behind:

Can the private sector pick up the handoff from government? Or perhaps more salient — does it even matter anymore? For the past three years, new orders have had remarkably little impact on GDP. Will this change? I don’t know. In prior periods, I would have expected downward GDP-revisions; under this administration, that seems unlikely. The BLS lost its head for revisions; will the BEA subject itself to the same?

A Blast from the Past

Occasionally, I go back and review what I wrote many moons ago. This past week, I found myself reviewing my thoughts at the start of 2008. It was illuminating:

My expectation was that a cyclical peak in profitability (then driven by financials and energy) was turning lower and likely to result in much lower than expected EPS. Obviously, I was right in 2008, but it was nowhere near as smooth as my simple forecast implied. In fact, the total return for the S&P500 for the 10yr ended March 2009 was the worst in history, eclipsing the post-WW1 crash. As you might expect, given the mean-reverting nature of this series, we rebounded sharply in 2009.

“Predictably,” few were bullish in 2009 — the start of another great investment period for US equities. One who was bullish was Rich Bernstein of Merrill Lynch:

Bernstein had been notably bearish throughout 2007 and, as late as Nov 2008, remained so:

In my contemporary discussions with him around this time, as I was starting to lean heavily bullish with my cyclical measures suggesting a turn was imminent (see above on trailing 10-year returns). Rich’s comment to me at the time — “I’ll tell you when to be bullish.” (He was arrogant if nothing else.) But he did in fact tell us when to buy:

His clients have done exceptionally well. But Rich may have just rung the bell again:

The terms of the deal were not disclosed, but based on the pending acquisition of Janus Henderson itself, we can confidently assert that Rich will be pocketing between $500MM and $1B, alongside a multi-year compensation and earn-out package as Chief Strategist for the enlarged Janus Henderson. Congratulations to Rich. The well-timed bear-to-bull rotation likely made Rich a near-billionaire. And the rest of us should be wondering, “Why are ewe reading this now?”

The 2007-9 mean reversion in margins was brief and almost immediately reversed. By 2012, margins had already begun to recover from their 2008/9 plunge; while the S&P remained below its 2007 high (it exceeded it in 2013), profit margins never came close to historical levels on the downside excluding the write-offs that hit the over-earning financials:

It’s possible you remember this time period. By December 2012, Apple’s revenues had risen 500% over the preceding three years, and earnings were up 10x. Multiples? AAPL P/E, unadjusted for the massive cash on its balance sheet, was single digits. Apple’s operating margin hit its all-time peak that year:

Few were paying attention. David Einhorn was, but his value discipline led him to sell too soon. Most were too busy preparing for the collapse of the EU, driven by Greek and Spanish defaults. The debate in 2026 seems very similar to the pre-2007 period, except this time it’s the tech co’s that are “overearning”; and like financials in 2007, we won’t know until the write-offs occur. The post-GFC era has been unique for the lack of write-offs. We can see this in the relationship between GAAP EPS (Generally Accepted Accounting Principals) and reported EPS from continuing operations. Write-offs cause the relationship to plunge, and there have been very few:

As a result, we’ve seen book value, largely in the form of intangibles, explode. But consistent with our writings over the past few weeks, the rate of TANGIBLE book value growth has accelerated sharply with the emergence of AI spending. Once again, an indication that the physical world is starting to intrude into our financialized fever dream:

Read more

Their argument is the highest-conviction version of the “Soft Landing” consensus. They posit that we are on the precipice of a “positive supply shock” driven by AI that will raise US potential GDP growth to 4%, crush inflation, and justify an S&P 500 target of 9,000. Their thesis is elegant: Technology (AI) enables us to dematerialize growth, rendering physical constraints such as labor shortages and tariffs irrelevant.

It is a beautiful theory. Unfortunately, it violates the laws of physics — specifically, the physics of our infrastructure networks. And, as the latest research from Jones and Tonetti identifies, it violates the “laws” of economics. Using their projections, it also assumes a catastrophic path for wages vs capital that will not be tolerated:

Fortunately, it will not come to pass. The Hudson Bay thesis rests on a fatal accounting error. It assumes that Machine Labor is infrastructurally equivalent to Human Labor. It assumes that replacing a worker with an AI agent is a 1:1 swap in the economic ledger.

It is not. Per-capita productivity equals throughput divided by population only if capital scales at least proportionally with the population. Wall Street assumes the numerator (throughput) scales infinitely, while ignoring that the denominator (capital stock) is physically capped. This isn’t a Malthusian tale of inevitable collapse—I’m not predicting an endpoint where growth hits zero forever. It’s about the path: the short-run thermodynamic penalties and ergodicity errors that Wall Street’s linear models miss, turning a ‘productivity boom’ into a margin call unless we adapt.

I spent the last week auditing the energy books, and the results are stark. We are not facing a “Productivity Boom”; we are facing a “Thermodynamic Margin Call”. The transition from a human-led economy to a machine-led economy carries a specific topology penalty that Wall Street’s linear models are missing.

This is the Growth Wedge. And it implies that the “Cost of Capital” isn’t going back to zero—it’s going to track the cost of rebuilding the entire US energy grid from scratch.

The Optimist’s Delusion

To understand why the consensus is wrong, we must first steelman their argument. Hudson Bay posits that US exceptionalism is strengthening. They argue that the productivity gains from AI (estimated at 0.5–1.5% annually) will outweigh the stagflationary drag of protectionism.

In their model, AI acts as a deflationary force. By substituting capital (software/compute) for labor, we lower unit costs and expand margins. This justifies a “Sentiment Spread”—a premium valuation multiple—similar to the 1985-2001 period.

The mistake in the AI-optimist model is treating machine substitution as “Hicks-neutral” (a technological change that doesn’t alter the ratio of capital to labor). In reality, this transition is energy-biased and capital-deepening.

The Ergodicity Error

More fundamentally, the AI-optimist model commits an ergodicity error: it confuses the ensemble average with the time average.

Wall Street implicitly assumes that because capital can flow and equilibrate in the long run, it will do so smoothly over the short run. But we do not live in an ensemble of possible economies. We live in a single, path-dependent timeline.

If the copper wires, transformers, and gas turbines cannot be built fast enough to support the AI load in 2027, the system breaks long before it ever reaches the hypothetical 2035 equilibrium.

They see “The Cloud” as a place where value scales infinitely with near-zero friction. But “The Cloud” is not a place. It is a physical infrastructure of aluminum, copper, and megawatts. And unlike the software boom of the 1990s, which ran on the “stranded capacity” of office buildings and efficiency gains from the death of the incandescent bulb, this new boom requires Net New Industrial Capacity (a replay of the DotCom fiber buildout).

Revisionist History: The Decoupling of Throughput

To understand the trap we are in, we have to rewrite the history of the last 50 years. Standard economics holds that the divergence between Productivity and Wages that began in 1973 was a policy failure or the result of corporate greed, the loss of unions, etc.

Institutions and policy certainly shaped how this divergence manifested, but it became unavoidable once throughput migrated from human bodies to owned infrastructure.

Some economists argue that this divergence is a statistical illusion—that if you adjust for inflation correctly (using output prices instead of consumer prices) and include non-wage benefits, pay actually kept up with productivity.

They are missing the point (unsurprisingly). The divergence isn’t a measurement error; it is a Topology Shift.

As the chart above illustrates, Labor and Productivity marched in lockstep for the first half of the 20th century. Why? Because the economy ran on Liquid Fuels and Human Labor. To burn more oil, you needed more men to drive the trucks, man the rigs, and work the assembly lines. Labor controlled the throughput and hence negotiated its proportionate share. In the areas of the economy where this remained true, as the linked paper demonstrates, wages largely tracked productivity:

In 1973, we hit the Thermodynamic Wall. We couldn’t just add more men to burn more oil. We switched to the “Cheat Code” (Offshoring) and began the slow transition to the “Electro-Capital” grid.

The reason “Consumer Prices” (what workers buy) rose faster than “Output Prices” (what workers make)—creating the statistical gap economists struggle to “correct” away—is Global Arbitrage. We used foreign labor to suppress the price of tradable goods (TVs, Toys), but we could not suppress the thermodynamic cost of living (Housing, Energy, Healthcare) in the domestic economy.

Whether you call it the end of the “Family Wage” (Sociology) or the end of “Cheap Oil” (Physics), the result is the same: The Surplus Evaporated.

The Bottleneck Arbitrage:

• Pre-1973: Energy flowed through human bodies (food/transport). Labor captured the gains because Labor was the transmission mechanism.

• Post-1973: Energy began to flow through increasingly privately-owned infrastructure (wires, pipelines, servers). Capital captured the gains because Capital owned the bottleneck.

The “China Shock” and automation were just accelerators of this trend. But the system didn’t totally bypass the human. Ironically, it increasingly consumed their LEISURE as data inputs to the machine.

We didn’t stop working; we just stopped getting paid. We entered a Barter Economy: we trade our “Audience Services” (attention/labor) for “Media Services” (content). The value of this labor is captured in GDP as Advertising Services (Corporate Revenue), but it is absent from Wages (Household Income). We lost the paycheck, kept the work, and called it “content.”

The Global Cheat Code

This wasn’t just an American phenomenon. The entire developed world spent the last 50 years playing a game of thermodynamic arbitrage to avoid the cost of domestic energy production.

• The UK Model: When the UK hit the wall in 1976, they didn’t solve it with efficiency; they solved it with geology (North Sea Oil). When that ran out in 2000, they swapped cheap oil for cheap imported labor.

• The EU Model: Europe combined cheap energy (Russia gas) with successive waves of labor arbitrage. The first phase absorbed high-skill Eastern European labor following EU expansion, effectively delaying automation. As wage convergence and demographic decline closed that channel, Europe substituted quantity for quality via non-EU migration. This preserved headcount but diluted capital per worker, intensifying pressure on housing, infrastructure, and long-standing social norms. The model’s instability reflects the same Hicks-neutral error seen in AI optimism: assuming labor inflows can substitute indefinitely for capital formation.

• The East Asian Model: The “China Shock” wasn’t an isolated event; it was the last gasp of a 50-year strategy to outsource the world’s entropy to a manufacturing sink.

This becomes apparent when we consider the arbitrage that existed in 1990 that allowed the US (and other developed nations, but mostly the US) to outsource human labor:

The crisis today is that all three Cheat Codes are failing simultaneously.

1. The China Valve: Closed by geopolitics and demographics.

2. The Russia Valve: Closed by war.

3. The Migration Valve: Closing due to a Physical Capital Crisis.

The Hicks-Neutral Fallacy of Migration

Just as Wall Street treats AI projections as having access to infinite energy, policymakers treat migration as having infinite infrastructure. The standard assumption was that migrants moving from capital-poor to capital-rich regions would “level up” to Western productivity.

This is not a claim about migration per se. In a capital-abundant regime that builds housing and infrastructure at scale, migration is productivity-enhancing. The failure arises only when policymakers assume Hicks-neutrality and refuse to build. Migration stress arises not from flows per se, but from the slow-moving stock of housing and infrastructure.

If Physical Capital (Housing, Healthcare, Roads, Schools) is constrained, adding more people doesn’t raise the migrant; it levels down the native and forces them to compete (via higher prices) for these increasingly scarce resources. When the capital stock per capita dilutes, the “B-Sector” (Housing/Services) experiences massive inflation. The political backlash closing borders today isn’t just cultural; it is a reaction to the thermodynamic crowding out of the native working class.

The Energy Investment Equation

The end of the “Cheat Code” is visible in the raw physical data.

For twenty years (2000–2019), the US economy pulled off a magic trick. We grew GDP while keeping energy consumption flat. This was the “Negative Slope” anomaly.

That illusion is over.

Since 2020, the US slope has turned positive (Beta = 1.34). To generate the next dollar of GDP, we must once again use more energy. Why? Because “US Exceptionalism” now includes Reshoring. We are bringing aluminum smelting, chip fabs, and data centers back home.

The “14% Bottleneck”

Here is where the math gets violent. The core of the Bull Case is that AI will “fill the gap” left by a stagnating labor force and efficiency will lower overall usage.

But let’s look at the topology of that thesis.

You can’t efficiency your way out of a shortage.

The US primary energy system consumes roughly 100 Quads (29,000 TWh) of energy per year. However, the electrical grid only generates ~4,200 TWh.

• The Reality: The grid handles only ~14% of the nation’s energy flow.

• The Rest: The other 86% flows through liquid fuels (oil/gas) and direct chemical inputs (food/fertilizer).

The Human Engine (Distributed & Diversified)

Humans are energetically expensive (~36,500 kWh/year in biological and chemical energy consumption required to sustain a Western worker) but infrastructurally diversified. We draw ~80% of our energy from the “Off-Grid” system: Gasoline, Natural Gas, and Food. Only ~4,200 kWh of that burden is transmitted to the electrical grid (residential load).

The Machine Engine (Concentrated & Constrained)

Machines are infrastructurally concentrated. An AI Agent draws 100% of its energy from the electrical grid. It cannot eat a sandwich, nor can it burn gasoline.

When you replace a Human with a Machine, you are attempting to route the entire economy through a 14% bottleneck. We can calculate the “Substitution Penalty” using 2024 production data:

• Human Grid Load: ~4,200 kWh/year.

• Machine Grid Load: To generate the same GDP output ($150k), a machine requires ~156,000 kWh of electricity (based on the current economy-wide average capital efficiency of ~1.04 kWh/$, a likely understated assumption as Data Centers run at much higher utilization than the average factory).

Recent work by Jones and Tonetti (2026) provides the mathematical proof: in a system of complementary inputs, growth is constrained by the “Weakest Link.”

The prevailing technocratic interpretation is that Human Labor is this weak link—a drag on efficiency that must be automated away.

This is not just a sociological error; it is a fatal strategic error. You cannot ask a human to build a machine whose stated purpose is to replace the human. It’s as inhumane as asking prisoners of war to dig their own graves. It is not a business plan; it is a declaration of war.

To fund the massive capex required to build the Thermodynamic Grid, we need the political and physical buy-in of the population. We are currently selling them “Fear of Replacement.” We need to sell them “Inheritance.” The Meek don’t want to just serve the machine; they want to inherit the Earth it builds.

Until we correct this narrative — until we make the human a beneficiary rather than a target — the grid will remain the binding constraint. The machine waits for the electron because the voter refuses to dig the trench.

The Predatory Nature of Capital Deepening

Standard economic theory and status quo defending economists assume that “Capital Deepening” (investing in machines) raises wages because it makes workers more productive.

This assumes Energy is elastic. It assumes that if we build a Machine, the grid will expand to feed both the Machine and the Human.

In a 14% Bottleneck world, Capital Deepening can be predatory.

The Machine does not just compete with the Human for work; it competes with the Human for current. The AI Data Center pays for the substation upgrade; the residential neighborhood gets the brownout. And the protests begin:

If you doubt the cost of this transition, look at the divergence between the fuel (Gas) and the product (Electricity).

As the chart above illustrates, the cost of Electricity (White Line) has largely decoupled from the cost of Natural Gas (Orange Line).

• The Molecule (Orange): Remains cheap due to the shale revolution and “Associated Gas” surplus. More on that later.

• The Electron (White): Is soaring in price.

• The Ratio (Green): This is the Topology Penalty. It is the cost of grid congestion, ESG mandates, and transmission complexity. We have plenty of cheap gas, but we cannot turn it into cheap power because the transmission layer is broken.

The counterargument is that the grid can be bypassed or modularized via “behind-the-meter” generation, i.e., Microsoft building power plants. This path has been promoted by the Trump administration. This can be done — but only at the cost of turning software firms into utilities and internalizing capital costs that markets price currently as external. Privatization does not remove the constraint; it converts a public bottleneck into a balance-sheet one, raising the marginal cost of capital for every downstream activity.

The issue is not that this capital cannot be built, but that it cannot be built fast enough, cheaply enough, or uniformly enough to avoid a decade-scale binding constraint.

The “Triple Load” Disaster

Critics might argue that demographic decline will offset this load. This ignores the Transition Period (2025–2035) discussed in my end-of-year post. We are facing a period of Displacement, not just Replacement.

We are squeezing the grid in a Triple Pincer:

1. The Legacy Pincer (The Human Stays): The displaced worker is still alive. They still heat their home and drive their car (increasingly electric). Their 36,500 kWh load remains.

2. The Machine Pincer (The AI Arrives): The AI Data Center comes online to do its job, adding 156,000 kWh of new load to the grid.

3. The Rerouting Pincer (The Electrification): Even the “efficiencies” we are promised (EVs, Heat Pumps) work against us topologically. When you swap a gas car for an EV, you may save energy in aggregate, but you worsen congestion in the constrained layer that sets the system’s price.

The Net Result: We don’t save energy. We add a massive new layer of industrial demand (Pincer 2) while simultaneously dumping the entire transportation load (Pincer 3) onto the same fragile copper wires used by the legacy base (Pincer 1). The policy goal is to raise the grid’s share—but doing so requires rebuilding the transmission layer itself, which is precisely the binding constraint.

We are trying to force a disproportionate share of future growth through a pipe built for a fraction of today’s load.

Read more

A couple of housekeeping thoughts on recent posts from the “intelligentsia.” Matt Yglesias, who has been a fixture of the “left” media since 2002, has recently come under fire from the left for his defense of the status quo, suggesting a return to Obama-style neoliberalism, unfettered free trade, and business-friendly policies. I offer conditional condolences and partial agreement, even as I encourage readers to consider that our current system is extractive and poorly suited to “the pursuit of happiness” for the majority of Americans.

But Matt hits on an important theme in this post, defending billionaires, even as he betrays his alignment with them (one does not simply “think” about billionaire positivity while on vacation in Maine). It’s possible to reform the system without targeting the individuals. In fact, as I’ve noted in many responses to comments, as “good” as retribution may feel temporarily, it’s a societal trap:

I know many billionaires and would echo many of Matt’s sentiments about them as people. It’s key to remember that:

A sizeable fraction of the US Constitution is built around prohibitions on legislation targeting an individual or group, on ex post facto laws, etc. Billionaires are people — often remarkably hard-working, innovative people; sometimes people who have colored (and continue to color) outside the lines. As a nation, we should encourage the former and discourage the ACTIONS of the latter. Laws are prohibitions against acts; they should never be targeted at PEOPLE.

We need to tone down the rhetoric against people and focus our rhetoric on reforming the system. If Jews, or Muslims, or LGBTQRSTUVWXY, or billionaires are targeted, they will understandably resist. And targeted billionaires are dangerous. Noah Smith, whom I don’t always agree with (unsurprisingly), but always appreciate, has by far the best rationale for billionaires:

Revolutions are not led by peasants. Revolutions are led by dissatisfied elites. The peasants are cannon fodder. Something to think about as the cries to “burn it all down” grow louder.

In the same vein, I’m reading more and more about “kids these days.” The literature shelf on this subject is long and tired:

"The children now love luxury; they have bad manners, contempt for authority; they show disrespect for elders and love chatter in place of exercise. Children are now tyrants, not the servants of their households. They no longer rise when elders enter the room. They contradict their parents, chatter before company, gobble up dainties at the table, cross their legs, and tyrannize their teachers." — Socrates ~450BC

But I was struck that Suzy Welch, a noted fan of geriatric billionaires (the second wife of 24-year-senior Jack Welch), has found rebirth advising companies on how to weed out troublesome youngsters. A September 24th, 2025 WSJ editorial asked the question:

And concluded that with Suzy’s help, companies, “if armed with data, could become more targeted in hiring efforts, racing to find the 2% before competitors do.”

Jack Welch was notorious (and lauded) for ruthlessly firing the bottom 10% of employees. With Suzy’s help, companies can exclude 98% of Gen Zers. You should read the article if you have access. But one passage struck me, given my recent focus on “happiness.”

Our first step was to analyze Generation Z’s values in order. In first place is eudemonia, a Greek term my inventory uses to encompass the desire for self-care and personal pleasure. Next comes voice, the value that reflects the priority a person places on expressing authentic individuality. Third, non sibi, the Latin term meaning “not for oneself,” the desire to help people. Fourth is affluence, exactly as it sounds, and fifth, “beholderism,” a desire for things—including yourself—to be beautiful. — Suzy Welch, WSJ 9/25/2025

“Hey Gemini, is ‘eudemonia’ a Greek term that ‘encompasses the desire for self-care and personal pleasure’?” — “No, that’s hedonia, the root of hedonism.”

In my opinion, this misunderstanding sits at the heart of nearly all “kids these days” complaints. Growing up is all about the transition from hedonism to eudaimonia. It’s a transition that, for me, arrived nearly instantly with the birth of my first child at 29. A preview was on New Year’s Eve 1999, when the highlight was the first feel of a baby’s kick (he was massively hopped up on sugar from the three desserts my very pregnant wife had inhaled). Suddenly, joy was no longer derived from river-rafting trips around the globe (6 of 7 continents in my 20s), but from the experiences of parenting and partnership — and the freedom that a little bit of success gave me to explore financial markets. My hunch is that Gen Z will undergo a similar transition; I’ve certainly seen it begin in my children:

Just like Baby Boomers (hippies), Gen X (slackers), Millennials (whiners), and 5th-century BCE youth in Athens, Gen Z (hedonists) will transition to adulthood. And the transition will bring changes for ALL of us. The transition did not go well for Socrates, and my hunch is this will not go well for the Boomers (or Gen X, for that matter).

But before that transition is complete, the proverbial “Fourth Turning”/”End Times” is well underway. Last week, I explored this transition in the context of emergent scarcity, particularly for electricity. This week, I’d like to consider the implications for the most obvious “commodity” dependent on cheap electricity — Bitcoin. (BOO! HISS! SALTY HATER!!!)

The Great Re-Pricing: When the “Digital Gold” Bill Came Due

In April 2025, I asked a simple question in my note, “What is Gold?”:

“If the $1.7 trillion now sitting in bitcoin had flowed into bullion instead, what would the yellow metal trade at?”

My models suggested that bitcoin acted as a “shadow discount” on Gold, depressing its price by 30–50% by diverting monetary flows into a faster, digital horse. I argued that if those flows ever reversed—if the “Passive Bid” for bitcoin evaporated—Gold would violently re-rate to where it belonged.

Eight months later, we have our answer. In 2025, bitcoin and Gold flows became negatively correlated:

Read more

When I think about the future, I try to separate it into “destination” vs “path.” There are only two certainties in life — death and taxes. A destination AND a path. Both are going to increase over the coming decades.

Death rates are rising globally as the global Baby Boomer cohort, first born in 1945, begins to exceed life expectancy.

Once life expectancy is passed, age-specific mortality begins to rise dramatically. At 80, the age-specific mortality is 5%. At 90, it’s 15%. Over the next decade, roughly 35% of the Boomers will move on to the next life. Over the next 15 years, over half “disappear.” This is a period of unprecedented change in global demographics. The closest analog is high schools from 1982 to 1996, where the population of high school students collapsed by nearly 12%:

With the collapse of growth into decline, the construction of educational infrastructure collapsed:

With declining high school populations, the issue was one of neglect. But a much bigger problem faces us for the rapidly aging (and dying) Boomers — we also built hospitals for their BIRTHS (peak hospital construction permits in 1964), but now expect those same deaths to occur with aging hospital infrastructure:

These facilities were built with expansive maternity wards, not for extended convalescence. While the Boomers are ready to critique the Millenials for their “entitlement” in wanting modern homes (as we’ve demonstrated, this is untrue), it is the Boomers themselves that are shunning the extended care facilities of 1950s in favor of “aging in place” or luxury retirement communities, consuming vastly more resources per capita than the “nursing homes” that were “enough” for their parents. Average length of stay in a nursing home bed is 13.4 months (median 5 months); for assisted living it is 29 months (median 22 months). Normalizing capacity by median stay (the right figure for cohort analysis), it has been shrinking even as forward demand is exploding:

The net impact is a looming senior housing crisis that will necessitate a radical rethinking of end-of-life care. But first, we will face a capacity crunch that will force aging Boomers to pay for the labor needed to age in place, because there will be nowhere for them to go.

Yes, EVENTUALLY we will get Optimus-type robots to care for Grandma, but like all innovations, its adoption will be driven by necessity. And the net beneficiaries of the capacity increase will be GenX — who were also the beneficiaries of the high school and college construction booms (“You think I’d get in to Penn today?” is the enduring refrain of my classmates as we fight for our children’s right to party like it’s 1989). The offset? They are politically weak enough that they will likely see heavy restrictions on “senior entitlements” while Boomers are grandfathered in. Doesn’t really matter; many GenXers won’t get to be grandfathers anyway (due to falling birth rates).

It is unlikely we will see a surge in construction to provide low-end end-of-life care from the private sector — the end customer is literally dying out; government is likely to step in, eventually, as they did in the 1960s.

Just like senior housing, a capacity crunch is emerging in health care workers per Social Security beneficiary. As those SocSec beneficiaries age, the intensity of demand will rise, and the implications of the worker shortage will become more pronounced:

For the Boomers, Rich Grandma will initially get the immigrant to change their bedpans until Optimus arrives; Poor Grandma will negotiate with her children. Aren’t you glad we raised them so well?

Of course, this will be politically unacceptable, at least initially, so the government is here to help. As always, California is leading the nation on the “path” — higher taxes:

Wealth taxes to fund health care for seniors while cloaking it in a pitch to expand maternity wards… will hypocrisy ever find bounds? (No) My expectation is that the California initiative will fail. As framed, it is an overt violation of takings clauses and restrictions on individual taxation, AND it is opposed by Governor Newsom. BUT it is the opening salvo in a war in which there will likely be no victors — like passive investing, we made the easy choices for too long, and now it’s likely too late.

And this “real world” capacity crunch is going to manifest itself across nearly every sector as the surge in capacity created by globalization (logistics, communications, trade) continues to reverse under the breakdown of the post-Cold War peace dividend. The emergence of a “war dividend” — in the form of nuclear power, humanoid and other robots (including drones), and advanced security technology (effectively proto-digital IDs) for military applications (initially) — will emerge, but the uncertainty is whether that dividend will require a down payment in the form of physical war that can further deplete existing infrastructure and labor supplies.

So welcome to the “Fourth Turning” — the capacity crunch across multiple “real world” sectors created by the nonsense of “post-Capitalism” in the 2010s that will endure as the aging Boomers and the emergence of their electronic “workers” drives increased demand for service labor automation — robots, AI, self-driving cars — AND increased demand for service labor itself.

Why “Zero Marginal Cost” is an Accounting Error

The theory of “Post-Capitalism” — championed by thinkers like Jeremy Rifkin and Peter Diamandis — rests on the seductive idea that technology is driving the marginal cost of production to zero, inevitably birthing a world of abundance where the price mechanism collapses.

This theory collapses the moment it encounters the physical world. It is not a prediction of the future; it is a fundamental misunderstanding of the present, reliant on three structural fallacies.

1. The “Cloud” is Heavy Industry (The Rivalry Fallacy)

Post-capitalist theory relies on the “infinite reproducibility” of digital goods. This is a category error. While code is non-rivalrous, the means of execution are intensely rivalrous.

• The Reality: There is no such thing as “the cloud”; there are only other people’s computers. These computers require rare earth minerals, silicon lithography, massive energy inputs, and LAND (including the real estate in front of your eyes).

• The Trap: As long as the hardware (GPUs, Servers, Land) is scarce and privately owned, the “free” software layer is merely a lure. The “Digital Commons” does not liberate the user; it serves as unpaid R&D for the hardware monopolists (Microsoft, Amazon, Nvidia) who charge rent on the physical bottlenecks.

2. The Thermodynamics of “Free” (The Entropy Fallacy)

The concept of a “Zero Marginal Cost Society” is essentially accounting fraud. It can only be sustained by ignoring Depreciation and Entropy.

• The “Turtles” Problem: Proponents argue that automation eliminates labor costs. But machines degrade. A solar panel decays; a robot wears out. The cost of replacing the machine (CapEx) is the hidden “marginal cost” of every unit it produces. It’s “turtles all the way down.”

• The “Sharing” Lie: Rifkin’s vision of “sharing energy” across a grid ignores the Second Law of Thermodynamics. Transmission is not free; it incurs resistance. The grid is not a magical internet of electrons; it is a physical system where moving energy costs energy.

• The “Local” vs “Global” cost curve: The idea that “marginal energy is free” once you install solar panels is a reflection of a local cost curve, not the global cost curve. If I install a 10kW panel array, 0-10kW is “near zero marginal cost.” But 10.0001kW is HIGH marginal cost. As a society, we experienced a period where the local curve did not need to shift to obtain new capacity and we mistook it for “post-scarcity”

  

  :

3. The Capacity Cliff (The Curve Fallacy)

Rifkin and Diamandis conflated a local segmented curve with a global curve.

• The Step Function: Energy is only “free” up to the limit of current capacity (e.g., the max output of a solar panel). The moment demand exceeds that limit by a single watt, the marginal cost explodes, requiring massive new capital investment for a second panel or battery.

• The Conclusion: We are not on a smooth path to post-scarcity; we are trapping ourselves on a jagged step-function of constraints. The ‘Zero Marginal Cost’ narrative relies on a calculus flaw: it assumes the cost of the next unit is effectively zero. But in the real world, capital is ‘lumpy’ and discrete. We don’t buy capacity in single watts; we buy it in billion-dollar blocks. We never conquered scarcity; we simply hit a larger-than-normal Riemann rectangle segment.

  

Hyper-Capitalism in Disguise

What proponents call “Post-Capitalism” is merely monopoly extraction optimized for the digital age. By relying on unpaid “peer production” (identical in function to the unpaid domestic labor that “goosed” GDP as women moved from non-market to market economy), the system offloads costs onto the user while privatizing the profits of the infrastructure. This game is coming to an end.

Far from escaping the market, the “Post-Capitalist” economy is simply a new way to sweat the assets of the physical world while pretending the limits of physical reality don’t exist. In the 2020s, we’re discovering that assumption is wrong.

Investment Implications

The “Pig in the Python” Problem (The Mismatch)

The Riemann sum chart shows that to meet demand, we must step up to the next massive rectangle of capacity (e.g., building a new fleet of nursing homes or power plants).

• The Conflict: Infrastructure is amortized over 30–40 years.

• The Reality: The “Boomer Bulge” (the Pig) only needs this capacity for ~15 years (2025–2040) before they exit the system (mortality).

• The Trap: If we build the “Red Step” (new capacity) to accommodate the peak, we will be left with a massive Stranded Asset in 2045 when the demographic curve collapses behind them.

The Data: The “Global Peak” is Already Baked In

After the Boomers, the “population growth” narrative is dead. The demand curve isn’t just flattening; it is set to invert. I have discussed this previously, but I encourage you to evaluate the slides of Penn professor (but would he get in today?), Jesus Fernandez-Villaverde. We can call him Professor Jesus for short.

• Replacement Rate Breached: “2023 was likely the first year in human history when our fertility rate fell below the replacement rate”.

• The “Extensive Margin” Collapse: Future growth is incredibly challenging, if not impossible, because the “feeder system” (births) has broken. The source of immigrant labor/demand is drying up even before we consider immigration restrictions.

• The Implication: The “Step Function” of inflation we are seeing now is the premium capital markets demand to build assets for a dying civilization. Why would I lend you money for 30 years to build a hospital for a population that will be 20% smaller when the bond matures?

The “Inflationary Span” (2025–2040)

This explains why inflation is “sticky” now but “deflationary” later.

• Phase 1: The Squeeze (Now - 2035): The “Pig” (Boomers) is wider than the “Python” (Infrastructure). We hit the Riemann Cliff. Prices explode because we must squeeze them through. We are forced to build capacity at maximum cost.

• Phase 2: The Glut (Post-2040): The Pig exits. The population drops. We are left with the “New Capacity” we just built, but the demand line crashes. Prices likely collapse.

Implications for Investors: The Terminal Value Trap

The Thesis: We are facing a “Local” Capacity Crisis (The Boomer Bulge) within a “Global” Demographic Collapse (The Fertility Crash). This creates a specific financial trap: Overbuilding for the Bulge.

Investors must distinguish between Structural Scarcity (assets the shrinking young cohort will always need to survive) and Temporal Scarcity (assets the dying old cohort needs right now).

The Commodity Split: Machine Food vs. Human Food

Do not buy “Commodities” as a monolithic asset class. In a depopulating world, the correlation between Energy and Agriculture breaks.

• Long “Machine Food” (Structural Scarcity): Copper, Uranium, Natural Gas, Compute.

  • The Logic: As the ratio of Workers-to-Retirees collapses, civilization must substitute human labor with machine labor. A shrinking workforce requires more energy and compute per capita to maintain GDP. Demand is anti-correlated to population.

• Short “Human Food” (Accelerated Deflation): Wheat, Corn, Soy, and Farmland.

  • The Logic: You cannot automate calorie consumption. Farmland acts as a leveraged short on demographics: demand for farmland shrinks faster than population because the least productive “marginal acres” are abandoned first. Unless the land can be converted to energy production (solar/biofuels), it is a deflationary trap.

• Markets have BEGUN to price this in — but just barely. It shouldn’t be that HARD to find a commodity strategy or CTA strategy that recognizes the difference:

The Duration Mismatch: “Riemann” Assets

We are hitting a “Capacity Cliff” for many assets — housing, energy, medical care — forcing prices higher. However, building new capacity into this spike is suicide.

• The Trap: Financing a 40-year hospital or nursing home to service a demographic wave that will crest in 2035 and vanish by 2045.

• The Trade: Own (or rent) the Incumbents, not the Builders. The most profitable asset is the existing, fully depreciated facility running at 110% capacity. It has pricing power today but no “Terminal Value” risk tomorrow because it requires no new CapEx. But nearly all equity assets (including private equity) have giant terminal values. BUY THE DEBT — but recognize it’s a rocky road and many assets will fail (and you may end up owning a new low-cost competitor if you pick carefully). A hedge might be appropriate if you don’t have this skill set. I know a guy…

The “Growth” Audit

Standard DCF models assume a “Terminal Growth Rate” of 2–3% into perpetuity. This makes no sense in a world where profitability can collapse in 15 years.

• The Reality: For mass-market consumer businesses (Housing, Retail, Autos), the Terminal Growth Rate is negative.

• The Action: Audit your portfolio for companies priced on “infinite customer growth.” If they sell to humans (rather than to the machines that replace humans), their terminal value is possibly zero. Even if you find the “low cost” providers (who are likely to survive), multiple contraction is the fundamental story.

The Passive Overlay

And none of this will matter in the near term as we continue to drive assets into passive strategies. But when the flows slow and reverse, and they must, as seniors confront these shortages that will drive end-of-life care cost surges and 100% taxation on “inheritable assets,” the next bid will likely be much, much lower.

I still don’t see that happening in 2026, but it’s growing increasingly stochastic. Watch the flows!

Read more

Unfortunately, against the advice of my Twitter avatar, I have unintentionally found myself in a land war in Asia. By Asia, of course, I metaphorically mean the discussion of what ails the middle class in America. Once again, the mockery machine is being deployed. This week, The Atlantic provided the following pithy quote:

“Under modest examination, Green’s empirical claims fall apart. But they bespeak a troubling trend among the commentariat—and even some scholars—of exaggerating the extent of poverty in America. Social-justice discourse, whether about environmentalism, racism, sexism, or poverty, has a tendency to advance maximalist claims as a sign of maximal concern. The intention is usually to express solidarity with the oppressed. But collapsing the distinction between the actual poor and the lower-middle class obscures more than it helps. And talking about poverty as intractable or unfixable is a kind of demotivational speaking.” — Idrees Kahloon

If they SAY the claims fall apart enough, then they must be right. Wouldn’t want to demotivate the loyal workers! But you needn’t worry… Scott Winship was kind enough to inform me that my 15 minutes are up — five minutes ago:

And I’m devastated. I was enjoying the opportunity to appear on TV for the first time (/s):

It’s true what they say… the camera adds five pounds.

I’m being silly, of course, but I’m also employing a tool that I would encourage my readers to adopt — “ownership.” Not of your house, but of your convictions and your messaging. I am just as prone as anyone to getting angry (probably slightly more so) and speaking unkindly of opponents (see here… and here… and here). It’s a “gift” born of Irish/Scottish heritage. But when I do analysis and come to a non-consensus opinion, the analysis comes before conformity. For my work on passive, those who know me personally know that I traveled the world in 2016 and 2017 asking, “How am I wrong?” A decade later, no one can dispute my analysis even as they may (understandably) dispute some of my conclusions. Until a SUBSTANTIVE rebuttal exists for my work on precarity/poverty, my hunch is that, like my work on “passive” index investing, this topic will only continue to grow in awareness and concern. We (and I include my readers who forwarded an unreal 1MM copies of “My Life is A Lie”) have had a remarkable impact on a much needed discussion. From non-existent to “nearing breakout”, the topic of the poverty line is on America’s mind:

And if my fifteen minutes are up, I’d be glad to get back to work doing what I love — asking questions and trying to understand problems. These will MOSTLY be in financial markets, and as a full warning, next week there will be NOTHING but market and economic commentary as I put my thinking cap towards 2026. That means the first note of January will be the final installment of “My Life is A Lie” and we’ll return to our regularly scheduled programming with the addition of interviews of political candidates. Paywalls will be put back into “normal” positioning, and I’ll forgive anyone who wants to cancel their subscription because somewhat esoteric discussions of economics and finance, interspersed with various rants on subjects rattling around in my increasingly mediocre brain, is not their cup of tea. Just do me a favor and “cancel” — don’t pretend you don’t know YIGAF when you are billed as that adds surcharges from Stripe and Substack. I appreciate all the additional interest in my work and hope many of you stick around.

I’m going to order this document to highlight a path forward. The primary for Illinois congressional candidates is March 17th. In the 9th District, voters will have a choice — a journalist whose primary qualification is a tag line "I watch Tucker Carlson so you don't have to", a career politician whose primary “fix” for the economy is an illegal (takings clause) wealth tax, and, of course, my dark horse candidate, Phil Andrew, a former FBI hostage negotiator, small business man, and outstanding individual.

Phil has a rough road because his primary shortfall is in name recognition. “Independent” polling highlights the challenge:

But I HOPE we can change that. Please take the time to watch my discussion with Phil. I am framing his candidacy in the context of how we ended this discussion — “more listening, less shouting.” Perhaps it’s a motto we can adopt in our collective hunt for candidates. My apologies for my first attempt at uploading videos to Substack. Hopefully it works! With that said, here it is:

And now, for something completely the same… but hopefully clearer:

The Rule of 65: Part 2, The Land of Milk and “No, Honey”

The Crime Scene

We didn’t drift here. We reasoned ourselves here, much like “passive” index investing, we were following economic theories that turned out to be catastrophically wrong.

In Part 1, we established the physics of the trap: an economy that naturally concentrates wealth (the Equation of Life) requires active re-allocation (Positive Tau) to remain stable. When that re-allocation stops, the middle class isn’t just unlucky. It is mathematically prohibited from thriving.

But math doesn’t pass laws. People do.

The transition from a Pursuit (of happiness) economy (growth-focused) to a Property economy (extraction) wasn’t a conspiracy. It was something more tragic: a series of intellectual errors, made in good faith, by serious people following serious theories.

Public unions. Milton Friedman’s shareholder primacy. Bork’s consumer welfare standard. The Washington Consensus on trade, eliminating tariffs and removing constraints on capital. These weren’t fringe ideas. They were economic orthodoxy. Taught at the best universities. Adopted by administrations of both parties.

And they were wrong.

Phase 1: The Three Structural Breaks

If you look at a chart of the Labor Share of GDP, it doesn’t just drift downward. It breaks at three specific moments in history, each tied to a policy decision that seemed reasonable at the time.

Break 1: The Public Sector Bargain (1962)

The Decision: President Kennedy’s Executive Order 10988 allowed public sector workers to unionize.

The Logic: Private sector workers had won collective bargaining rights. Why should government employees be denied the same protections? It seemed only fair.

The Unintended Consequence: This created what economists call a Double Monopoly (or Soft Budget Constraint). In the private sector, a union is constrained by bankruptcy. If they demand too much, the company dies. In the public sector, the government cannot go bankrupt; it simply raises taxes. The consumer (taxpayer) is captive.

The Result: We broke the feedback loop between cost and value. Politicians, needing votes, granted concessions that future taxpayers couldn’t afford. This contributed to the urban fiscal crises of the 1970s and the erosion of trust in government capacity. Today, municipalities and states are overwhelmed by the deferred costs, contributing to the perception that reform is impossible.

Break 2: The Efficiency Bargain (1982)

The Decision: The adoption of Robert Bork’s Consumer Welfare standard for antitrust enforcement.

The Logic: Bork’s insight was elegant. If a merger produces lower prices for consumers, why stop it? Efficiency should be the goal, not some abstract notion of “too big.”

The Unintended Consequence: We legalized consolidation. Massive corporations bought up competitors as long as they promised efficiency gains. We traded Structure (competitive markets where new entrants could challenge incumbents) for Price (cheap TVs and electronics).

The Result: We crushed the Pursuit (new entrants, entrepreneurship, creative destruction) to protect the Property (incumbent firms, existing market positions). THIS is where the artificially low interest rate policy post-GFC really mattered. When demand returned post-COVID, those consolidated industries had the pricing power to gouge consumers. The efficiency gains went to shareholders. The bill went to you. Oh, and now they want you to bail them out with your 401 (k).

Break 3: The China Bargain (2001)

The Decision: Granting China entry into the WTO.

The Logic: Free trade makes everyone richer. This was Economics 101: comparative advantage. We assumed American capital would flow to China to access Chinese consumers, and that prosperity would make China more democratic.

The Unintended Consequence: Capital didn’t flow to China to sell goods. It went there to arbitrage labor. American corporations bought cheap labor and imported the products back home.

The Result: The greatest labor arbitrage in history. We sold our factories (production) to buy cheap debt (Treasuries), hollowing out the American working class to pad corporate balance sheets. The China Shock decimated manufacturing communities in ways that economists are still measuring. The promised democratization never came. And the workers who lost their jobs never found equivalent ones.

Phase 2: The Tax Shift

While these structural breaks were happening, we also rewired who pays for the country. This wasn’t sold as a transfer. It was sold as Supply Side stimulation.

The Great Reversal (1955 vs. 2024)

The Logic: Lowering corporate taxes would spur investment. Growth would benefit everyone. Trickle down.

The Reality: We swapped a tax on Profits for a tax on Wages.

1955 (The Golden Age): The Corporate Tax generated 28% of federal revenue. The rich paid indirectly via ownership of these assets. The Payroll Tax was a modest 8% of revenues.

2024 (The Malpractice): The Corporate Tax has collapsed to 10% of revenue. To fill the hole even as corporate profits as a share of GDP exploded, the Payroll Tax (which hits every worker from their first dollar) has exploded to 36%.

The capital didn’t trickle down. It pooled at the top. The Top 1% owns roughly 87% of corporate equity but pays a fraction of the historical burden, while the working class shoulders the cost.

Phase 3: The Inflation Gap (The Invisible Divergence)

The technocratic class loves to tell you that you’ve never had it better. They point to the Average Inflation Rate and say wages have kept up.

They are averaging away suffering.

As discussed last week, research by Xavier Jaravel proves we have different CPIs for “poor” and “rich”. I’ve modeled this as “The Land of Milk and ‘No, Honey, we can’t afford milk.’”

Consider two products over a 10-year period:

Organic Milk (The Rich Basket): Innovation drives the price down. The wealthy experience deflation (-5%).

Polluted Milk (The Poor Basket): Consolidation and scarcity drive the price up. The poor experience inflation (+5%).

The Malpractice of Averages: If you average these numbers, the CPI looks stable (around 2-3%). Using “Laspeyres” indices, which weight products by market share and price change lowers it further. The technocrats look at the spreadsheet and say, “Inflation is low!”

But look at the bottom rows of the model:

The Rich: Because costs are falling, they accumulate a Surplus. If their incomes rise at CPI inflation they gain additional surplus because THEIR milk is falling in price.

The Poor: Because costs are rising, they accumulate a Deficit even if we increase their incomes by that same CPI.

The Average CPI hides the suffering of the working class behind the deflation enjoyed by the Gwyneth Paltrow-class. This isn’t a “CPI-lie”. It’s a blind spot in methodology that we understand and should correct.

Phase 4: The Body Count (The Lost Einsteins)

The defenders of this system will tell you inequality is the price of progress. We must protect the Innovators and Job Creators.

The research says otherwise.

Recent work on Inequality and Creative Destruction proves that extreme inequality doesn’t fuel innovation. It suffocates it. Children born to parents in the Top 1% are ten times more likely to become inventors than those born below the median income.

This isn’t because rich kids are smarter. It is NOT explained by IQ. Even among children who score in the top 5% of math tests in 3rd grade, the rich kids become inventors and the poor kids do not. The authors suggest 75% of the potential innovation is being left on the table.

We have built an economy of incumbency, where opportunity is hoarded. By locking the next generation of geniuses out of the lab (because their parents couldn’t afford the entry fee), we are leaving thousands of Lost Einsteins on the table. We chose to protect the assets of the past rather than fund the inventors of the future.

The Proof of Concept: Coney Island Prep

We know this Innovation Gap is solvable because we are seeing it solved in real-time.

Coney Island Prep (CI Prep), a K-12 charter school serving students in Brooklyn, NY, has proven that Exposure is a resource just as critical as electricity or textbooks. Unlike traditional schools that assume students will obtain “exposure” to “Why college matters” or even “Why behaviors matter” outside of school, CI Prep operationalizes the “hidden curriculum” of the wealthy. They use school vacations not for downtime, but to bridge the exposure gap, sending scholars to study abroad in Europe or tour college campuses they never knew existed. All for significantly lower cost than traditional schools.

The result? By manufacturing the cultural capital that rich kids get for free, CI Prep has achieved a 100% college acceptance rate for eight consecutive years, with their scholars graduating at rates five times the national average for their socioeconomic strata. It is a template for success.

My firm, Simplify Asset Management, supports CI Prep with our annual “Entering the Fall” conference supporting CIPrep’s “dream” services: the internships, travel, and college matching that transform a student’s trajectory. Unfortunately, this year we remain behind our target and I’d encourage you to consider adding to CI Prep’s student experiences. I will donate 100% of the subscription fees raised by this post to the cause. Regardless of whether you join me, I encourage you to take advantage of the opportunity to find similar examples of excellence and support them.

The Diagnosis

The autopsy is complete. The cause of death was malpractice and neglect.

An entire generation of credentialed experts, acting in good faith, publishing in peer-reviewed journals, advising presidents of both parties, built a machine that extracts from the many to protect the few. They weren’t evil. Their theories were wrong.

We allowed Monopolies (because we thought efficiency was more important than competition).

We allowed Labor Arbitrage (because we thought trade was always win-win).

We shifted the Tax Burden (because we thought it would trickle down).

We ignored the Cost of Living (because we trusted the Average).

The result is a system where the Physics are set to Extract. And the intellectual immune system that built it has spent forty years rejecting the correct diagnosis.

That’s harder to fix than catching a thief. But it’s not impossible.

In Part 3, we will lay out the Escape Plan, the Rule of 65, and the specific policy levers we can pull to turn the machine back on.

END

Read more