Imperial Tribute

A government with budget deficits around 6% of GDP, debt above 120%, and a worker-to-retiree ratio under three is headed for a crisis. In recent years, our model has been to expect that governments will generally choose the path of least resistance from among the options available.

In the spirit of Herman Kahn, we thought it would be useful to make a list. Kahn's approach to difficult problems was to begin with a blank whiteboard and write down every possible solution, even the unlikely ones.

There are basically four ways to solve an overindebtedness problem: cut expenses, grow out of it, broaden the tax base, or keep borrowing and kicking the can.

The government could reduce expenses in two ways: cutting waste and fraud, and through major improvements in public health. Universal Ozempic could save quite a bit of money. But the largest obligations are Social Security and Medicare, and those promises are not even included in that public debt figure that now exceeds 120% of GDP. An expense cut large enough to materially change the trajectory would amount to a partial default on benefits owed to taxpayers who paid into the system their entire working lives. Outright default on Treasury debt seems even less likely and certainly not the path of least resistance when you issue your own fiat currency.

Growing out of the problem would be the best outcome. Productive investment raises output and helps keep inflation and borrowing costs under control. Recently we have found ourselves thinking that Claude and other large language models may help. LLMs could prove to be a genuine general-purpose technology that raises the economic growth rate via increased productivity. 

The demographic backdrop, however, is daunting. If debt is 120% of GDP and the government is running a meaningful primary deficit, growth does not merely have to exceed interest rates. It has to exceed them by enough to offset the primary deficit as well. At 120% debt-to-GDP, every percentage point by which interest rates exceed growth adds roughly 1.2% of GDP to the annual debt burden before accounting for the primary deficit. Growth would have to be extraordinarily strong to solve the problem by itself.

Still, growth is the one genuinely optimistic path. AI is also the one development on the horizon that might allow capital to substitute for workers who were never born. If there is a way out that does not involve financial repression, it runs through productivity.

We also considered a more unconventional solution. Call it "broadening the tax base" by broadening it very far. The Trump administration's National Security Strategy last year placed the combined economic weight of America's treaty allies and partners at roughly $35 trillion, in addition to our own $30 trillion economy. If the United States could somehow collect 5% of that allied output, it would amount to roughly $1.75 trillion per year, about equal to the current deficit. 

We jokingly called the idea "Imperial Tribute."

People who dismiss foreign extraction by saying that tariffs just tax Americans are thinking too small. The hegemon does sit on top of an immense foreign income base, and a few percentage points of it really would change everything. 

The problem is that Imperial Tribute is really a bet on coercive power: pay, or we hurt you. This year that power was tested at the easy end of the scale and fell short. Iran closed the Strait of Hormuz, mined it, and declared allied shipping a target, and traffic through the strait dropped by more than ninety percent. One medium-sized country, with its leader dead and its territory hit at will, was still able to fight the U.S. to a standstill by closing the Strait of Hormuz with cheap drones and setting off a global fuel crisis. 

When Trump asked allies to help reopen the strait, Germany, the UK, Japan, South Korea, Australia and others flatly refused, with Berlin saying it wasn't their war. The junior partners wouldn't even share the burden of a shared-interest oil crisis, let alone hand over a surplus. (And the failed extraction didn't just fail, it produced an oil price spike and higher interest rates on government debt, tightening the overindebtedness spiral.) If the hegemon can be forced to back down by a country with 1% of its GDP, it's over for Imperial Tribute.

The failed attempt would also have highlighted a second problem. Coercive pressure does not merely risk failure. It can backfire. Higher energy prices, weaker growth, and higher interest rates would worsen the fiscal position they were intended to improve.

The closest precedent for taxing sovereign allies is the Delian League. It started as a voluntary alliance, with members paying into a shared fund to defend against Persia. (That's more or less the ancestor of the burden-sharing we now demand from NATO.) Athens turned those payments into tribute, moved the treasury to Athens, spent the money on its own temples, and put down the members who tried to leave. The resentment that built up helped cause the war that ended Athenian power.

Britain taxed India, but Britain governed India, with an army, a civil service, and a hundred years of administration. Even then the take was modest next to the cost of holding the place, and it reversed the moment the navy could no longer back it up. Britain never taxed sovereign France, because nobody can. 

The Trump administration strategy paper is not a plan for empire and tribute. It is a plan for pulling back. Its authors say outright that the days of "propping up the entire world order like Atlas are over," and they say it because they already know a coercive surplus cannot be collected. 

The U.S. cannot solve a trillion-dollar fiscal problem by directly extracting resources from nominal allies. Reserve currency status, Wall Street intermediation, technology rents, and geopolitical influence may all be worth something. Hegemony is not a fiscal free lunch large enough to close a 6%-of-GDP deficit. 

The path of least resistance is inflation, or more exactly financial repression: holding nominal rates below the rate of nominal growth. That is how the country took its debt from about 120% of GDP down to 30% over the thirty-five years after 1945. The bondholder was the designated loser. He lost much of his real principal without a formal default ever occurring.

Inflation is the tax nobody votes on, which is why it is the path of least resistance. Explicit taxes will do some of the work (a point or two of GDP), but they can't close a six-point gap. And inflation is itself a tax, since it quietly raises real revenue through brackets and nominal gains that are not indexed. So taxation and inflation are not really rivals. (See The Missing Billionaires!) They tend to work together.

One thing about our situation is different from the postwar version, and it points to more inflation rather than less. As Carmen Reinhart and M. Belen Sbrancia observed, the postwar liquidation of debt occurred within a system of capital controls, interest-rate restrictions, and regulatory structures that created a captive audience for government debt. The government could repress financial claims gradually because investors had fewer places to go.

Those conditions no longer exist. Capital moves freely. Investors have alternatives. Much of the debt reprices relatively quickly. There is less opportunity to inflate away long-term obligations slowly and only once. The work therefore has to come from either sharper episodes of inflation or from rebuilding some version of the repression machinery.

The only thing that could alter this conclusion is faster economic growth. Even then, a productivity boom would probably not eliminate repression entirely. It would simply improve the arithmetic by widening the gap between growth and interest rates while reducing the primary deficit. 

AI may be the one technology capable of putting capital to work in place of the workers who were never born. So far, however, the promised productivity gains from LLMs have not yet appeared in the aggregate data. For now, growth remains a hope rather than a forecast.

The conclusion is that the government will probably run negative real rates against paper claims for a very long time. Growth may help. Taxes may contribute. Entitlements may eventually be trimmed at the margins.

But there are not enough politically feasible claimants available to absorb the adjustment except holders of nominal claims. 

For investors, that creates an uncomfortable problem. Bonds are the obvious target of repression, while large public equities increasingly trade at valuations shaped by passive flows and benchmark inclusion. That is why we have spent so much time looking at assets that are too small or too oddly structured to be swept into passive indexes. If the adjustment must fall somewhere, we would rather own the assets that politicians cannot easily print.

Thursday Night Links

• If defeat seems a strong word, consider what we do know about how this war will end. Iran has suffered significant damage from U.S. and Israeli military action. But as I and others warned at the outset, killing people and bombing things do not by themselves produce victory. The reality is that the war will close with the regime in Tehran intact and in the grip of the Islamic Revolutionary Guard Corps; the Strait of Hormuz will remain under the threat of Iranian attacks; Iran will continue to possess significant drone and missile stocks; the regime will maintain the capability to be a state sponsor of terror; and many sanctions will be lifted and billions of dollars in unfrozen assets will flow to Iran. In other words, the Iranians have achieved their key strategic aims—regime survival above all—while the Americans have achieved none of their own. [The Atlantic]
• Before the war, Iran didn’t control the strait, simply because it didn’t realize it could. Drone technology had advanced to the point where Iran was able to shut down Hormuz, but Iran didn’t know that until the U.S. attack forced it to try the risky and desperate move of actually shutting down the strait. The gambit paid off spectacularly, and now Iran knows that modern drone weaponry gives it an advantage it didn’t have in previous decades. So it controls Hormuz. It’s kind of wild to step back and consider how good of a position Iran’s leaders are in now, compared to the situation before the war. Iran had lost most of its proxy armies in the Middle East — Hezbollah, Assad, most of Hamas. The regime had been rocked by massive nationwide protests, which it only managed to quell by murdering tens of thousands of innocent Iranian citizens. The country’s economy was slowly dying. Now the leaders are firmly entrenched in power, their economy will be revived, and they find themselves the masters of Hormuz for the first time. Anyway, I don’t see any sense in which this is not a classic military defeat for Donald Trump and the United States. [Noah Smith]
• Even the head of Nigeria’s population commission doesn’t believe that the 2006 census was trustworthy, and indeed said that “no census has been credible in Nigeria since 1816.” (Nigeria’s president fired him shortly thereafter.) There are plenty of reasons to think that Nigeria’s population might be overstated. It would explain, for instance, why in so many ways there appear to be tens of millions of missing Nigerians: why so few Nigerians have registered for national identification numbers, or why Nigerian voter turnout is so much lower than voter turnout in nearby African nations (typically in the 20s or low 30s, compared to the 50s or 60s for Ghana, Cameroon, or Burkina Faso), or why SIM card registration is so low, or why Nigerian fertility rates have apparently been dropping so much faster than demographers expected. [David Oks]
• It was originally named "Westinghouse Electric & Manufacturing Company" and was renamed "Westinghouse Electric Corporation" in 1945. Through the early and mid-20th century, Westinghouse Electric was a powerhouse in heavy industry, electrical production and distribution, consumer electronics, home appliances and a wide variety of other products. They were a major supplier of generators and steam turbines for most of their history, and were also a major player in the field of nuclear power, starting with the Westinghouse Atom Smasher in 1937. A series of downturns and management missteps in the 1970s and 1980s combined with large cash balances led the company to enter the financial services business. Their focus was on mortgages, which suffered significant losses in the late 1980s. In 1992 they announced a major restructuring and the liquidation of their credit operations. In 1995, in a major change of direction, the company acquired the CBS television network and renamed itself CBS Corporation. Most of its remaining industrial businesses were sold off at this time. CBS Corp was acquired by Viacom in 1999, a merger completed in April 2000. The CBS Corporation name was later reused for one of the two companies resulting from the split of Viacom in 2005. [Westinghouse Electric Corporation]

You Cannot Grow an Acre

Right now, there are nine companies in the S&P 500 with market capitalizations over one trillion dollars: NVDA, AAPL, GOOGL, MSFT, AMZN, AVGO, TSLA, META, and MU. (SpaceX has not been added to the index.) These nine trade for 32 times earnings and throw off a 1.5 percent free-cash-flow yield on enterprise value. (All free-cash-flow figures here are net of stock-based compensation.)

We were wondering whether you could hide from this overvaluation elsewhere in the S&P index. The first, obvious thought would be to skip the top nine and own the other 491. They trade for 27 times earnings and throw off 2.6 percent on the same basis. Cheaper, but still expensive.

So we looked at various ways of slicing up SPY. We screened out every company with meaningful stock-based compensation, on the theory that the companies paying employees in stock also have the most overvalued shares. (This line of thought actually gave us a good Apple entry point in April 2024.) The low-SBC survivors yielded 2.1 percent, worse than the index, because the screen mostly caught the bid-up defensive complex: utilities, staples, telecom, the names people own for safety. We tried another screen, keeping only the companies that have shrunk their share count over the past five years. That group was the best of the lot at 3.2 percent, but it is not a number worth writing home about.

Put the four cuts together and the ladder of free-cash-flow yields runs from 1.5 to 3.2 percent of enterprise value. None of them are "cheap." Unfortunately, the 491 are not a bargain hiding behind the nine. They are slightly lower-quality businesses, on average, at a quality-adjusted price that is roughly the same. There is no secret cheap slice in the index, because the index as a whole is pretty expensive on the cash that actually reaches an owner.

One option would be to sit in cash and bonds and wait. If the correction doesn't come in a year, you'll be rooting for the world to end. Also, the U.S. federal debt to GDP and the deficit are both high enough that the government will be sorely tempted to inflate its way out, and a government that wants inflation usually gets it. In that world, cash and bonds hand you a negative real return after tax. 

That is the box. Stocks are expensive, but bonds are expensive too. We need a "third way."

There are two ways for a good business to slip through the cracks and be excluded from the passive, indexation bid. One is structure: a master limited partnership or other pass-through cannot go into the index, because the funds that track it cannot hold those companies without tax problems. The other is size: a company too small to move the index gets no meaningful flows. Either way the price is set by people doing valuation arithmetic rather than by a machine that has to buy. These have been called "orphaned securities."

Take Enterprise Products Partners. EPD is a partnership, so the index cannot own it, trades for 11x ttm EBITDA, which allows a 5.9% dividend that is largely tax deferred to be well covered. That is several times the owner yield of the index, for a toll road whose revenue is largely contracted. The standard objection is obsolescence: pipelines are a melting ice cube in an electrifying world. But a large share of EPD's business is natural gas liquids and petrochemical feedstock, and petrochemicals are a secularly growing market, not a shrinking one. Demand for plastics and chemicals rises with population and income whether or not anyone buys another gallon of gasoline. The terminal-value fear is priced as if the whole franchise rides on crude oil. It does not.

Or take a land base. Rayonier (RYN) owns timberland and trades below what the dirt would fetch in the private market. It is a real-estate trust, so in theory it could be indexed, but it is far too small ($6 billion market cap) for the popular indices. Natural Resource Partners owns mineral and royalty land and is orphaned twice over, a partnership and tiny (only $1.3 billion market cap). Neither one has factories to run or fashions to chase. They own real assets that throw off cash, with no large operating or capital budget to eat into the return. In a world where the currency is being diluted, a perpetual claim on an acre or a ton is exactly the thing to own. 

Something falls out of this search that we did not go looking for. The orphans are close to the perfect assets for a great inflation. In many cases they are inflation-protected bonds wearing equity clothing, and  the index-ignored corner of the market is not where you would expect to find them.

It is not a coincidence. A land or royalty asset returns its cash because there is nothing to reinvest in. You cannot grow an acre. That single fact is why it is the right thing to own in an inflation: a real claim paying a real coupon, with no plant or equipment whose replacement cost keeps climbing. And it is the same fact that orphans it. Cash that has nowhere to compound has no reason to sit inside a corporation paying the double tax, so the asset is wrapped in a partnership. An asset that never reinvests never swells into something the index notices, so it stays small. Return your cash and you are orphaned twice, by structure and by size.

So the index runs an inadvertent filter. It bids up the businesses that retain and reinvest, which is most of what is expensive, and it leaves alone the ones that pay everything out, which is where the yield is. That is the bargain. You collect a real yield on the assets best built for the world the deficits are inviting, and you collect it precisely because the largest pool of money in the market is forbidden to bid against you. The only thing asked of you is the willingness to buy what no one is forced to buy, and to hold it on the days when no one is forced to buy it back.

Monday Night Links

• The trillion-dollar cluster—+4 OOMs from the GPT-4 cluster, the ~2030 training cluster on the current trend—will be a truly extraordinary effort. The 100GW of power it’ll require is equivalent to >20% of US electricity production; imagine not just a simple warehouse with GPUs, but hundreds of power plants. Perhaps it will take a national consortium. (Note that I think it’s pretty likely we’ll only need a ~$100B cluster, or less, for AGI. The $1T cluster might be what we’ll train and run superintelligence on, or what we’ll use for AGI if AGI is harder than expected. In any case, in a post-AGI world, having the most compute will probably still really matter.) [Situational Awareness]
• South Bow (SOBO) on May 29 announced open season results for its Prairie Connector project, securing 20-year binding commitments from Hardisty, Alberta to US delivery points. The company also revealed several key project details, giving the market more visibility on a potential new Canadian crude egress path. The project would add 380 km (~236 miles) of new 36-inch pipe and use 150 km (~93 miles) of preserved 36-inch pipe, plus two existing pump stations. Based on a typical oil pipeline flow velocity of 3-10 ft/sec, a 36-inch line implies ~300-1,100 Mb/d of theoretical capacity. SOBO is targeting a final investment decision (FID) by mid-2027. [East Daley Analytics]
• A year and a half ago, our city’s one bookshop went up for sale. My wife and I bought it. The place had 20,000 books, a good music system that probably played 3,000 hours of Bach per year, and a black cat named Raven. It even had an entire room just for theology and philosophy books. (Steubenville, Ohio, is an unusual town.) Now we’ve been running the shop for a little while. Experientia docet, said our ancestors. Experience teaches. I prefer Vivaldi to Bach, so you’ll hear more Vivaldi around here now. Raven died and my children are now tending a litter of six kittens, grooming a replacement. And experience has taught us something heartening: Our customers have great taste in books. I write this because I hope it will be as great a consolation to you as it has been for us. People tell us all the time that civilization is finished, that the world is coming to an end. But then we look at our sales details and we smile. [John Byron Kuhner]
  
• In the early 1970s, the Bretton Woods Agreement—the post-world war pact that instituted a fixed-exchange rate regime for the major world nations— had begun to show its structural flaw. Finance ministers were finding it increasingly difficult to dictate the value of currencies relative the dollar in a world where value changes were constant and information and capital free flowing. On August 15, 1971, President Nixon announced an emergency economic package that sent a seismic shock through the entire financial world. On that day, the United States suspended the dollar's convertibility into gold thereby ending fixed exchange rates between currencies. The Chicago Mercantile Exchange was the first major futures exchange to recognize the market potential of the upheavals unleashed by this event. Supported by Nobel laureate Milton Friedman, the CME was the first exchange to assert that the principles of agricultural commodities futures could be applied successfully to financial instruments. Thus, currency futures—which began trading on the CME's International Monetary Market (IMM) on May 16, 1972—ushered in the era of financial futures, thereby forever changing the scope and utility of futures markets. One year later, the Chicago Board of Trade launched the Chicago Board Options Exchange (CBOE) and added a new dimension to the repertoire of risk management instruments. Three years later, Treasury bond futures at the Chicago Board of Trade made their debut and became the most actively-traded financial instrument. Within a decade, a vibrant new industry was born that subsequently opened the curtain on the index markets of the 1980s. The successes of these markets propelled the futures and options industry to unparalleled greatness. In the last decade alone, the volume in U.S. futures and options skyrocketed from 76 million contracts in 1979 to a record of 323 million contracts in 1989. These successes also prompted University of Chicago Professor Merton H. Miller, 1990 Nobel laureate in Economics, to nominate financial futures as "the most significant financial innovation of the last twenty years." [Leo Melamed]
  
• The Silicon Data Token Expenditure Index, which tracks total spending on large language model usage, has roughly doubled since late 2025 even as the price of a single token has fallen more than 90% since 2023. This is Jevons paradox in action. As tokens get cheaper, companies don't spend less but instead run more AI agents, automate more workflows and generate more code, pushing aggregate expenditure higher even as the unit cost of intelligence collapses. [Apollo]
• From our vantage point at KKR, the current U.S. policy mix looks meaningfully different from the 2000-2019 period, which was defined by low growth, low inflation, global interdependence, and tighter fiscal constraints. In the current environment, we expect our asynchronous global recovery thesis, characterized by rolling recoveries and rolling recessions across regions and sectors, to not only continue but also gain broader acceptance. If we are right, the long-term implications for asset allocation could be significant, including the need to own more Real Assets across portfolios. Indeed, in a world where dispersion is rising and traditional diversification is less dependable, we continue to favor return streams anchored in hard assets and collateral-based cash flows. These exposures do not eliminate volatility, but they can improve the controllability of outcomes through seniority in the capital structure, stronger recovery prospects, and cash flows tied to essential activity in the real economy. [KKR]
• If this were true—that an LLM, lacking consciousness, must instead constantly confabulate its own behavior and motives and reasoning—then, even if an LLM is extremely intelligent, we should expect errors to accumulate differently in LLMs vs. humans. And as philosopher Toby Ord has demonstrated, this is exactly what’s observed. In his analysis of METR’s data on AI task-length doubling times, Ord identified that the available data also fit there being a simple “half-life” for the success of an AI agent, and so have a “constant hazard rate” for long tasks. As Ord writes about what this suggests concerning an AI’s prospects for completing long tasks: "the chance of failing at the next moment is independent of how far you’ve come—just like how the chance of a radioisotope decaying in the next minute is independent on how many minutes it has survived so far." Ord even shows that humans, when their success rate at long tasks is analyzed, appear to deviate from an equivalent constant hazard rate. A strong contender as to why is because we have interpretable access to our own previous thoughts and actions, i.e., our consciousness, in a way that LLMs simply don’t have. [The Intrinsic Perspective] 
• By choosing to treat the 1930s as a form of extreme payback for extreme excess—“no generation exempt”—Sorkin stages morality play rather than history. He also helps set policymakers up for the kind of grand theatrical action they are inclined to take anyhow whenever markets turn down. In other words, another 1933- or 2008-style rescue: flooding the market with liquidity, and stringing up wrongdoers and even the better Wall Streeters, such as the Mitchells whom Sorkin seeks to rehab. The same subpar results are likely to follow. [Amity Shlaes]
• In terms of AI progress per resource, or per dollar, things are probably getting worse on most measures. This is what the pessimism about scaling laws is getting at. Measures of quality are increasing far slower than the exponentially mounting costs. So why were people like Ilya Sutskever and Dario Amodei so impressed by the scaling laws? The answer is that there was a lot of headroom in compute — a lot of room to scale those costs.  Even if the resources needed would be thousands of times larger than the largest ever ML experiment, they saw that this (1) was still within the feasible set of things a large company could fund and (2) would still be a good deal given the vast potential benefits. For on the high end of possibilities, we are talking about something that could potentially replace more than half of all human labour in the world, and perhaps bring forward scientific and technological advances that human labour would have taken centuries to reach. In other words, while the costs could escalate wildly, a deep-pocketed project might reach benefits of extreme value before it ran out of money. And those benefits might be worth more than enough to justify those (very high) costs. More prosaically, we can note that it is entirely possible that financial returns will scale very quickly as a function of the technical measures of AI quality. If so, then even though standard measures of AI quality scale poorly as a function of resources, the financial returns might still scale very well as a function of resources. Indeed, if they scale better than linearly, that would create a paradigm of increasing marginal returns which would explain a landscape with a small number of players, each investing as much as they possibly can. [Toby Ord]
• It will come as a surprise to most that a company so stiff and humorless as CME Group currently is, once used to run an aggressive and somewhat jingoistic ad campaign in the mid 1970s for the purpose of celebrating free markets.  As I recently obtained a second set of these somewhat rare prints from a retired former CME marketing employee, it's worth taking a deeper look into the story behind them. [Trading Pit Blog]
• Mr. Chairman, there are no commodity exchanges in Moscow; there is no Peking Duck Exchange in China; there is no Havana Cigar Exchange. The farmers of those countries have no need for a mechanism that offers risk transference, price projection, or price protection. In those countries, the governments establish the prices at which farmers can sell their products. Consequently, the farmers' primary risk is entirely removed. Alas, by removing the risk, that system also removes the incentive. The sorry history of such systems is that they have been abysmal failures. [Leo Melamed]

How much bitcoin would be too much to own?

Imagine if you had most of your net worth in Bitcoin. How might this have happened? Maybe you are a Bitcoin enthusiast who has been stacking and "hodling" for a long time. Or perhaps you recently remembered a forgotten password that unlocked a bitcoin trove. In either case, the assumption is that this is a large holding as a percentage of your net worth and you have a low cost basis, which would mean substantial capital gains taxes if you sold. What should you do?

Most people in this position resolve the question with a feeling. The bull feels that selling would be a betrayal of the thesis that made him rich. The accidental holder feels paralyzed by the tax bill. Neither feeling is a good answer. There is, however, a framework that produces an actual number, and it has been sitting in the mathematical literature since 1956. Before we get to it, we need to be honest about what Bitcoin is, and about the best case that can be made for it.

Not a First-Class Asset
I have a general rule for windfalls: invest them in first-class assets for the benefit of future generations, and consume only the income (at most). First-class assets are productive. A business generates earnings. Timberland grows wood. Farmland yields crops. An apartment building collects rent. You can hold these assets forever, live on their output, and pass the principal on intact. The income is a signal that the asset is real and not just a speculation.

Bitcoin produces no income. It pays no dividend, collects no rent, earns no royalty. Whatever you eventually get out of it must come entirely from a future buyer. This does not make Bitcoin worthless but it disqualifies it from the category of first-class assets you build a family fortune on, and it puts it squarely in the category of speculation. Speculation is a legitimate activity, but it obeys different rules, and the most important rule of speculation is position sizing.

The Best Case for Bitcoin
Let me give the bulls their due, because the strongest argument for Bitcoin is genuinely strong, and it was prescient of Murray Stahl to argue this at least as far back as 2019. It goes like this: add up the market value of garbage currencies like the Brazilian real, the Iranian rial, and the Russian ruble (just a few bad currencies that happen to start with "r") and you arrive at something well over $2 trillion of combined value. Why couldn't a new, better currency (with an algorithmically fixed supply and the ability to transfer virtually) rival any one of those currencies, or even all three together?

That argument did not require Bitcoin to dethrone the dollar. It did not require hyperbitcoinization, the orange-pilling of central banks, or the citadel. It required only that Bitcoin function as a more trustworthy store of value than the monetary product of a few chronically mismanaged states. For a citizen of Buenos Aires, Tehran, or Moscow, that proposition is no longer all that speculative.

So the bull case has a floor of plausibility. The question is its ceiling.

Bitcoin Already Worked
The bulls were right - past tense. Over fifteen years, Bitcoin grew from a hobbyist experiment worth essentially nothing to a market capitalization of about $1.2 trillion, approaching the entire value of euro banknotes in physical circulation. That is an extraordinary achievement in monetary entrepreneurship. And the contrarians who bought at $10 billion, or $100 billion, or $500 billion have been handsomely paid for being right.

If you study technological adoption patterns (see Vaclav Smil, or Crossing the Chasm), the penetration rate for a new innovation follows a logistic growth, or "S," curve. The early phase is explosive: that was the contrarians' decade, when Bitcoin's share of global physical currency went from essentially zero in 2011 to roughly 4 percent by 2017, a four-thousand-fold increase in penetration. Then growth decelerates as the addressable market saturates. From 2017 to today, Bitcoin's share of world M0 has grown only about four-fold, despite the same number of years. Plotted on a multi-year moving average (to smooth through the cycles), the trajectory has the unmistakable shape of a logistic curve: near zero through about 2014, a steep climb through 2021, and a clear deceleration since.

At roughly 15 percent of world physical currency today, Bitcoin is no longer in its hypergrowth phase. It is in the part of the curve where the rate of change falls and the asymptote becomes visible.

"Bitcoin worked" and "owning Bitcoin will keep working" are therefore different propositions. The contrarian trade that took Bitcoin from a curiosity to a major monetary unit has already been made; it is no longer on offer. The question now is whether the next move, from this side of the S-curve where saturation dynamics dominate, represents the same kind of opportunity. It doesn't. 

Being contrarian is not, in itself, a strategy. Being contrarian about the right thing at the right time is. Having been right about Bitcoin in 2013 does not generate forward edge in 2025, any more than having been right about Apple in 2003 tells you what to do with AAPL today. The Kelly framework, which we'll come to in a moment, is forward-looking by construction. It does not ask whether Bitcoin was a good bet a decade ago. It asks whether the bet currently available, at current size and against current failure probabilities, is one worth taking, and at what fraction. 

The Ceiling Is Smaller Than You Think
The S-curve raises a structural question the bull case usually papers over: an asymptote against what? Enthusiasts routinely make a category error here, and it is worth dwelling on because the error inflates the apparent upside by an order of magnitude.

The popular version of the moonshot thesis compares Bitcoin to the global money supply, which might be roughly $123 trillion by the M2 measure or even $150 trillion by broader gauges. Against numbers like those, Bitcoin's current market capitalization of roughly $1.2 trillion looks small, and the implied possible upside looks like a hundred-bagger.

But M2 is the wrong yardstick. The bulk of M2 consists of savings deposits, time deposits, and money market funds, all of which are instruments that pay their holders interest. People park money in a savings account because the bank compensates them for doing so. Bitcoin pays nothing. It cannot compete for interest-seeking money, and no mechanism exists by which it ever would. Comparing Bitcoin to M2 is comparing it to a market it cannot address.

The honest comparison is physical currency, the narrowest measure of money, M0: the banknotes and coins of the world. Cash pays no interest either. People hold it anyway, for liquidity, portability, privacy, and crisis insurance. These are precisely the virtues Bitcoin claims for itself. Cash is the incumbent Bitcoin is actually running against.

All the physical currency in the world amounts to something like $8 trillion. 

That is the ceiling. And against an $8 trillion ceiling, Bitcoin at $1.2 trillion has already captured roughly 15 percent of its total addressable market. This is a genuinely astonishing achievement for fifteen-odd years of work. More astonishing than the bulls themselves seem to realize when they reach for the M2 comparison. But it carries an uncomfortable implication: the remaining upside, in the best plausible case in which Bitcoin equals every banknote and coin on Earth, is about 6.7x. 

The Distribution of Outcomes
A 6.7x ceiling would be perfectly attractive if it were the likely or expected outcome. It is neither. It is the far tail of a distribution that includes zero. Curtis Yarvin framed the long run for Bitcoin very succinctly: "One day, everything in the world economy will be priced in Bitcoin. Or, one day, Bitcoin will be regarded as the biggest bubble that ever was. There are stable equilibria between these outcomes, but they are unusual and structurally exotic." 

He put forward three failure modes: Bitcoin could be actively killed by its enemies; it could lose its energy source; or it could be outcompeted by another candidate monetary standard.

None of these is far-fetched. States have banned more popular things than Bitcoin. Proof-of-work rests on an energy-economic equilibrium that regulation or technology could upend. And monetary standards are winner-take-most competitions in which the eventual winner (a central bank digital currency, a successor protocol, something unimagined) need not exist yet.

There is also now experimental evidence bearing on the upside scenario, and it is not encouraging. In 2021, El Salvador became the first country to make Bitcoin required tender, deploying both subsidies (a $30 signing bonus, free transactions, zero capital gains tax) and coercion (businesses were required by law to accept it). After four years, the experiment was dead: crypto remittances had shriveled from 4.5 percent of the total to under 1 percent, and by 2024 just one in two hundred Salvadorans was paying with bitcoin as often as every other week. 

JP Koning, the monetary economist who chronicled the experiment at his blog Moneyness, identified the structural reason it failed. There is a very big hurdle that prevented El Salvador's one-two punch of subsidies and coercion from working: Bitcoin is intrinsically ill-suited to perform as money. The stuff is innately volatile, so risk-shy individuals don't dare hold it or use it for payments. Risk-seekers can tolerate the volatility, but they expect to be rewarded by a dramatic price rise, so they refuse to spend their bitcoins, because they could miss out on the jump. The net result is that no one, neither society's risk-seekers nor its risk-avoiders, ends up paying with bitcoins.

This matters enormously for our probability estimates. The full moonshot (Bitcoin displacing the world's physical currency) requires Bitcoin to actually function as circulating money. A national government just spent four years trying to force exactly that outcome, under maximally favorable conditions, and failed. A rational holder should weight the M0-parity scenario accordingly: it remains possible, but the best natural experiment we have gotten so far argues against it.

So the shape of the bet is: a meaningful chance of losing everything, a meaningful chance of stagnation, and a tail chance of making roughly five to seven times your money. How much of your net worth do you put on a bet shaped like that?

Kelly Tells You the Number
In 1956, John Kelly of Bell Labs derived the formula for exactly this problem: given a bet with known odds and probabilities, what fraction of your bankroll maximizes the long-run growth of your wealth? Bet less than the Kelly fraction and you leave growth on the table. Bet more and volatility itself destroys you. Overbetting a favorable gamble, repeated over time, grinds even a winning hand down to nothing. The Kelly fraction is where aggression and survival balance.

For an asset with several possible outcomes, the procedure is to choose the fraction *f* of your portfolio that maximizes the expected logarithm of wealth:

E[ln(W)] = Σ pᵢ · ln(1 + rᵢ · f)

where pᵢ and rᵢ are the probability and return of each scenario. Solve for the *f* where the derivative equals zero, and you have your allocation. The inputs are estimates, but the discipline of writing them down is most of the value of the exercise. Let us write down three honest sets.

The skeptic thinks Bitcoin is a doomed experiment: a 65% chance it goes to zero, a 28% chance it merely treads water, a 7% chance it doubles by displacing one weak currency. Expected value is sharply negative, and the Kelly fraction comes out negative as well. The formula is telling you the bet is unfavorable: the correct allocation is zero. If these are your probabilities, you should own no Bitcoin at all.

The pragmatic bull believes Bitcoin survives and grows but stops short of conquest: a 45% chance of failure, a 35% chance of stagnation, a 15% chance it displaces all three weak "r" currencies (about $6 trillion, a 5x from here), and a 5% chance it reaches full M0 parity at $8 trillion (a 6.7x). Solving the optimization yields a Kelly fraction of roughly 15% of net worth, and at half-Kelly, the standard discount practitioners apply because real-world probability estimates are soft, about 7%.

The true believer is maximally, but still rationally, bullish: only a 30% chance of failure, a 25% chance of stagnation, a 25% chance of the $6 trillion outcome, and a full 20% probability that Bitcoin swallows the world's physical currency entirely (a probability the El Salvador evidence suggests is generous). Even granting these aggressive inputs, the Kelly fraction is roughly 50%, and half-Kelly says about 25%. Note what those numbers require: a one-in-five chance Bitcoin wins outright against every banknote and coin on Earth, and only a three-in-ten chance of total failure — assumptions that strain against the experimental record.

The defensible range is therefore wide but shaped. The skeptic case gives zero. The pragmatic bull, applying the standard half-Kelly buffer, gives about 7 percent. Only the true believer, with assumptions that don't really survive scrutiny, gets to roughly a quarter of net worth at half-Kelly. To justify the very large or "all-in" allocations of the biggest enthusiasts, you would need probability estimates so lopsided (near-certainty of success, near-zero chance of failure) that writing them down would embarrass you. That is the point of writing them down.

A Second Opinion: The Market Portfolio
Suppose you distrust the whole exercise of assigning probabilities. Fair enough, there is another framework, that requires no views at all.

If you believe markets are efficient, the portfolio you should hold is the global market portfolio: all the asset holdings in the world, weighted by market capitalization. This is the allocation of the investor with no edge and no opinions. What does it contain? World stock market capitalization is roughly $150 trillion. The world fixed income (bond) market is about equal. Global real estate is perhaps $400 trillion. Cryptocurrency, in its entirety (every coin and token on CoinMarketCap) is a couple of trillion, of which Bitcoin's share (its "dominance," in the argot) is about 58 percent.

Run the division and Bitcoin's weight in the total market portfolio comes to roughly 20 basis points. Granted, world real estate in its entirety is not an investable asset class, so one might reasonably narrow the universe. But even against world stocks and bonds together, Bitcoin's weight is well under half a percent. (And against stocks alone, still under 1 percent.)

Two entirely independent frameworks: one (Kelly) that assumes you do have views and rewards you for acting on them; one (the market portfolio) that assumes you have none and tells you to hold assets in proportion to their market valuations. The first, fed honest pragmatic-bull inputs and applying the standard half-Kelly buffer, says about 7 percent. The second says 0.2 to 1 percent. The defensible range for a Bitcoin allocation, then, runs from a fifth of a percentage point to perhaps 25 percent, with where you sit in that range determined by how confident you are that you see something the market doesn't and that you can assign probabilities the El Salvador evidence does not refute. What neither framework produces, under any inputs whatsoever, is a number anywhere near "most of my net worth."

"But the Taxes"
Now return to our holder with the low cost basis. Selling means realizing an enormous gain and handing a quarter or a third of it to the government. But the tax argument, examined closely, is an argument about which loss you prefer. Bitcoin has declined 80 percent or more from its peak multiple times in its short history. If it does so again, or if one of Yarvin's failure modes materializes, the holder who refused to pay a 25% tax will have donated far more than that to the market. Taxes are the price of having won. Drawdowns are the price of refusing to admit it.

One way to translate this thinking into action would be a target allocation consistent with one's probability estimates. Sell down to it over a multi-year horizon, into strength where possible, spreading the tax burden across tax years, and redeploy the proceeds into first-class assets.

The Answer
How much Bitcoin would be too much to own? Under the framework above, allocations beyond roughly a quarter of net worth require probability assumptions that the El Salvador evidence directly undermines. A defensible bull case, sized prudently at half-Kelly, puts the ceiling closer to 7 to 10 percent. The efficient-markets baseline says the neutral weight is closer to a fifth of a percent. The asset produces no income, faces live existential risks, has demonstrably failed its one national-scale audition as actual money, and has already captured something like 15 percent of its total addressable market. The glory days of hundredfold upside are history.

The Kelly Criterion gives you a framework. The framework says: even if you love Bitcoin, keep it to a fraction of your portfolio. Exactly which fraction depends on your honest assessment of the probabilities. But "most of my net worth" is not a defensible answer under a reasonable set of assumptions.

[This essay is a framework discussion, not personalized investment advice. Probability estimates are illustrative; readers should consult their own advisors regarding their specific circumstances and tax situations.] 

Thursday Morning Links

• It’s official: the world stock market is now as wild as it was during the tech-stock bubble. Since April 2026, we’ve had epic levels of return dispersion. AI excitement is driving extreme price moves, with some large-cap technology stocks up 50% to 100% in a single month. While it’s normal for small-cap stocks to sometimes rise 50% in a month, it’s not normal for the whole market to be meaningfully impacted by extreme winners. The chamber of dispersion has been opened, the beast of volatility has awakened, and the season of chaos is at hand. [Acadian] 
• The fact that short-lived strains are desirable for research because they allow it to go faster has polluted the literature because short-lived, convenient-to-research strains produce unreliable results for the very reasons behind their being short-lived. Pabis et al. therefore argued that, in order to demonstrate longevity benefits credibly, strains with long control lifespans in optimal conditions are needed. [Cremieux Recueil] 
• A short while later, the book ends suddenly and ignobly. It turns out that keeping the army alive one more season was all that was required. The real Spartan army is launching an operation against a Persian satrap in Asia Minor, and Xenophon’s troops get summoned to participate, initially as their own unit and then gradually getting absorbed into the main body of soldiers. In other words, it ends with an acqui-hire, as so many startups do. The dreams of great wealth and fame are over, and their independence is over too. It’s back to being a wagie at AWS. [Mr. and Mrs. Psmith’s Bookshelf]
• Rayonier was founded in 1926 as the Rainier Pulp and Paper Company in Shelton, Washington, with a headquarters office in San Francisco, California. Its name was inspired by Mount Rainier in Washington state. Its first mill opened the next year in Shelton Washington, on the Olympic Peninsula. The mill used Tsuga heterophylla (western hemlock) trees to create a premium bleached paper pulp. In September 1930, Rainier Pulp and Paper began working with the DuPont chemical company to produce hemlock pulp for the manufacture of rayon. Two additional pulp mills were constructed and began operation in the state of Washington at Hoquiam, Washington and Port Angeles, Washington. Rainier Pulp and Paper changed its name to Rayonier, a portmanteau of the words rayon and Rainier, in 1937, when it became a publicly traded company. [Rayonier]
• In response to the demand by residents for the board to stop the wind farm from being built, Supervisor Jason Whiting asked County Attorney Brad Carlyon if the board is legally authorized to prohibit the project. “Bottom line answer: No.” Carlyon further explained that the board’s authorities lie in land use and zoning. “You can’t deny it unless there is a health, safety, or welfare issue.” Chair Darryl Seymour also spoke on the work that was done to regulate incoming development. “The work that we did for two years to make it not easier, but to make it where we had more authority, which is already limited by the state. To make it more conducive and more neighborly to our people that we have.” The board then entered executive session to discuss the development agreement, after which the agreement was approved. [Painted Desert Tribune]
• The Rowlings, who own Omni Hotels & Resorts, in March paid $289 million for Justice family debt partly secured by the Greenbrier from a Virginia-based bank. They say the Justice family has siphoned revenue from the resort to pay bills at their coal mines and other businesses, letting the hotel fall into disrepair, skipping payments to contractors and employees, and risking its value as collateral. Jim Justice is credited with saving the Greenbrier when he purchased it out of bankruptcy in 2009. His daughter, Jill Justice, is president of the resort. Jim Justice said in an interview with The Wall Street Journal Friday that the resort has been profitable, retained its clientele and that he plans to continue investing in it. He called the allegations hurtful. “I’ve poured about everything I’ve got into the Greenbrier, and I’d do it again tomorrow,” he said. “I love that place beyond all good sense. It’s not just bricks and mortar to me.” [WSJ]
• This year, Google became the only large tech company to own a power company with the $4.75 billion acquisition of Intersect, a wind and solar developer that in recent years pivoted to building such projects to support data centers. Intersect has energy projects under development to supply multiple gigawatts of electricity, Google said. One gigawatt can power hundreds of thousands of homes. The company has also amassed a bench of energy-sector experts on its staff. “Google really has hired in-house to develop their data centers, and as a result, they have a more integrated approach that I would suggest is a lot more thoughtful,” said Jigar Shah, an energy entrepreneur who formerly directed the Energy Department’s Loan Programs Office. Having on-site power is becoming a strategic advantage for tech companies. Regulators and power officials in many regions are considering whether data centers built alongside new power sources should be afforded a faster connection to the grid because they would be less reliant on it. [WSJ]
• In Dickens's novels anything in the nature of work happens off-stage. The only one of his heroes who has a plausible profession is David Copperfield, who is first a shorthand writer and then a novelist, like Dickens himself. With most of the others, the way they earn their living is very much in the background. Pip, for instance, ‘goes into business’ in Egypt; we are not told what business, and Pip's working life occupies about half a page of the  book. Clennam has been in some unspecified business in China, and later goes into another barely specified business with Doyce; Martin Chuzzlewit is an architect, but does not seem to get much time for practising. In no case do their adventures spring directly out of their work. Here the contrast between Dickens and, say, Trollope is startling. And one reason for this is undoubtedly that Dickens knows very little about the professions his characters are supposed to follow. What exactly went on in Gradgrind's factories? How did Podsnap make his money? How did Merdle work his swindles? One knows that Dickens could never follow up the details of Parliamentary elections and Stock Exchange rackets as Trollope could. As soon as he has to deal with trade, finance, industry or politics he takes refuge in vagueness, or in satire. This is the case even with legal processes, about which actually he must have known a good deal. Compare any lawsuit in Dickens with the lawsuit in Orley Farm, for instance. [George Orwell]
• First smoking went out of fashion, then daytime drinking. Negroni-drinkers were dying out, or reforming. Wine began to be drowned out by absurd fizzy water. Then the food itself was threatened, partly because business lunches were becoming more businesslike, partly because interviewees were becoming more self-conscious. “Even I have never managed a two-bottle lunch,” laments the FT’s arts writer Peter Aspden, who is thought to have conducted more Lunches than anyone else. “There’s such reluctance now to be seen to be pigging out in any shape or form, and hardly anyone drinks over lunch.” [Financial Times]
• The word embedding approach is able to capture multiple different degrees of similarity between words. Mikolov et al. (2013) found that semantic and syntactic patterns can be reproduced using vector arithmetic. Patterns such as "Man is to Woman as Brother is to Sister" can be generated through algebraic operations on the vector representations of these words such that the vector representation of "Brother" - "Man" + "Woman" produces a result which is closest to the vector representation of "Sister" in the model. Such relationships can be generated for a range of semantic relations (such as Country–Capital) as well as syntactic relations (e.g. present tense–past tense). [word2vec] 
• The distributional hypothesis in linguistics is derived from the semantic theory of language usage, i.e. words that are used and occur in the same contexts tend to purport similar meanings. The underlying idea that "a word is characterized by the company it keeps" was popularized by Firth in the 1950s. The distributional hypothesis is the basis for statistical semantics. Although the distributional hypothesis originated in linguistics, it is now receiving attention in cognitive science especially regarding the context of word use. [Distributional semantics]

Thursday Night Links

• It is not good news, then, that over the past 10 years, private equity has focused on taking companies private that are both more levered and less profitable than similarly-sized businesses (which we have already established are junky to begin with), all while paying a higher price for them than their size-peers. These companies bank on the same set of factors—that interest rates will remain sufficiently low and the economy sufficiently robust—for them to be able to generate enough cash flow to pay down their debts. Different types of shocks—an economic slowdown, a further pickup in real interest rates if inflation proves sticky, a widening of credit spreads if private credit continues to sour—can all be enough to meaningfully hamper the profitability of these businesses, and to do so in a correlated manner. [GMO]
• The leading indicator of all previous technology transitions has, however, been the growth of the new, which always precedes the destruction of the old.  The transition to mobile telephony wasn’t declared a failure because the global number of landlines continued to grow until 2006, 33 years after the invention of the mobile phone. Similarly, peak US horse population did not occur until 1920, over 34 years after the first internal combustion vehicle hit the roads. [Michael Liebreich]
• Historically, the world seems highly stochastic and slightly cyclic, with vaguely regular cadences of empires, companies, and other organizations rising and falling with their own characteristic half-lives. The fundamental problem here is that at the ‘object level’ almost all the returns to success are positive. This means that naively success should generally beget more success in an exponential fashion. It requires an extremely powerful force to offset this default tendency. Regression to the mean is certainly not powerful enough for this. However, such a force must exist because, in practice, the world looks dramatically different from the simple exponential model. There is a constant random-seeming churn of states, empires, companies, wealth etc vs a world where the rich get richer indefinitely and thus everything ends up controlled by the winners at time t=0 forever after. We do not all live in the grand one-world Sumerian empire which simply grew faster and more successfully than its challengers during the hinge of history in 3000BC. Similarly, the East India Company no longer controls global trade; the Ford motor company does not have an eternal monopoly on cars; IBM does not reign supreme in computers. Similarly with wealth, despite its undeniable exponential properties, compound interest seems to be pretty weak in practice. The descendants of Croesus and Crassus do not lord over us all today. This means that there must not only be positive returns to scale and success but also negative returns. Larger states become harder to govern and more prone to civil strife. Larger companies become slow, unwieldy, and lose that indefinable ‘taste’ that made them stand out in the first place. There also appears to be some kind of phenomenon of increasing ‘entropy’ and decay in organizations or states that have been highly successful for a long time. Exponential systems are always poised on the edge of a knife destined to either explode or collapse, however the world largely seems to stabilize these systems or at least prevent explosions (there are a fair few collapses). Understanding and explaining these dynamics has to be one of the fundamental questions of sociology. [Beren Millidge]
• I think it has become clear to me that there is a universality class of ‘architectures sufficient to scale to AGI’, of which transformers are the first discovered element, and that there are a vast array of other possibilities within this same class, many existing on significantly better pareto curves than the classic transformer. I definitely think an order of magnitude of flop efficiency in both training and inference is easily achievable through superior architectures, and likely this will actually be several OOMs of gains over the next five years or so. The combination of this process plus vast software and hardware efficiency improvements will inevitably drive the cost of intelligence and AGI down to very low levels which, if alignment can be managed well, is good news since it vastly increases the utilons per capita achievable with the cosmic endowment. [Beren Millidge]
• Even in this idealized scenario, inheritance tax and the division of the fortune among children mean that almost all fortunes are barely able to compound long enough to be maintained even with relatively low TFRs (2 children). Beyond this idealized scenario, the real world also contains many negative ‘shocks’ which can tip a fortune from a regime of steadiness and growth towards exponential diminishment and exponentials are very unkind on the downward slope. The real stock market, even when highly diversified, does not return 7% annually smoothly forever. It goes through huge bust periods where valuations can drop by 50% or more and can remain below all-time-highs for decades at a time. These times can often be coupled with periods of high inflation which are also devastating for large existing fortunes. In theory, many down-markets can be weathered if you just reduce spending to maintain the same withdrawal fraction. However, in practice achieving sudden 50% or more budget cuts can be challenging, even for the wealthy. Many ‘big ticket’ items such as mansions, yachts, etc have high fixed maintenance costs which cannot easily be reduced in a downturn without selling the underlying asset at precisely the wrong time. [Beren Millidge]
• Goodspeed shows that British and American expansions do not resemble Dorian Gray, looking beautiful but hiding an inevitable accumulation of malinvestments (objectively bad investments that are destined to fail) and distorted decisions (mistaken economic decisions taken on the basis of bad regulation or flawed prices) that make a correction inevitable. If they did so, he argues, one would expect that as expansions get longer they get more and more likely to end. In his data, however, the relationship between the age of an expansion and the probability of death is essentially zero. Nor do measures of increased investment during the boom correlate with the severity of a downturn. Nor do longer expansions have longer recessions after them. This is why recessions remain essentially unpredictable. Any perceived regularity is likely to be a statistical illusion. Goodspeed shows that attempts to forecast recessions such as inversions of the yield curve (where long-dated government bonds have lower interest rates than short-dated ones) or the Sahm rule (which says a recession is likely underway if the unemployment rate spikes high above its recent lows for three months) are overfitted to US data and don’t work for the UK. [Works in Progress]
•  In 2024, medical spending as a share of GDP was 15% below forecasts made in 2010 and only marginally higher than in 2010. Relative to expectations, the savings were nearly $1 trillion in 2024. In light of this prolonged period of slower growth, we ask the question: has the United States bent the health care cost curve? We start with a model of medical spending that incorporates both the development of new technologies and the equilibrium use of those technologies. Technology development and incentives around its use may add to or subtract from spending growth. We then examine the drivers of the spending slowdown empirically. We attribute slower medical spending growth to five factors: the development of technologies that simultaneously improve health and lower cost; long-run supply elasticities that exceed short-run elasticities; improvements in population health; reimbursement changes that reduce demand and make demand more price elastic; and reductions in the rate of price increases, likely driven by some of these same demand factors. Because these cost slowing mechanisms are expanding over time, we conclude that the United States has bent the health care cost curve, though not as much as it could be or will need to be bent. [NBER]