Executives Swap "Recession" for "Affordability" · Morning Gist
Saturday, October 315 stories · 15 min
Executives Swap "Recession" for "Affordability"
Companies now worry about squeezed customers more than a downturn. Profits are running ahead of stock prices, and a few big winners are driving returns everywhere.
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"Recession" came up on just 2 of 477 S&P 500 earnings calls last quarter, while "affordability" appeared on about a quarter of them. story 1 ↓
A New York Fed study finds LinkedIn's jobs-per-jobseeker ratio predicts inflation and wages better than the standard measure, and it arrives weeks earlier. story 2 ↓
SpaceX's IPO lifted UNC's endowment nearly 38% against a 16.1% median. Over three years, the average endowment trailed a Vanguard stock-bond fund. story 3 ↓
US wealth grew from about 4 to 5.5 times GDP on rising stock prices, and most of the gain went to owners of stocks and private businesses. story 4 ↓
S&P 500 profits are up almost 30% this year but prices only 12%. Micron and Nvidia account for a third of the profit growth. story 5 ↓
Anthropic's IPO filing lists 94 pages of risks. One analysis picks the two that say the most about how the company makes money.
1/5HumbleDollar· Daniel Oliveira· Oct 30
S&P 500 executives stopped mentioning recession and started saying "affordability"
A count of S&P 500 earnings calls found that recession came up on just 2 of 477 calls in July–September 2026. "Affordable" or "affordability" came up on 25.6%, the highest share since at least early 2024.
Why it matters · If the problem is that customers are squeezed by high prices rather than heading into a recession, damage to company profits arrives slowly, through sales volumes and margins, not in one dramatic quarter.
Know this first
Context from the editor, not the article · 26 sec
1 · What earnings calls are
Each quarter, public companies hold a call to present results. Executives give prepared remarks, then Wall Street analysts question them. Analysts are expected to push management on risks, so the topics they raise reveal what worries investors.
2 · Price level vs. inflation
Inflation is how fast prices are rising. When inflation slows, prices stop climbing as quickly, but they rarely fall back. Households still face the higher level, and they feel squeezed until their pay catches up.
3 · The April 2025 tariffs
In April 2025 the US announced broad new import tariffs. Markets fell sharply and recession fears jumped. That moment serves as the article's peak for recession talk.
2/5Liberty Street Economics (NY Fed)· Oct 30
New York Fed finds a LinkedIn jobs ratio predicts inflation better than the standard gauge
New York Fed economists tested three LinkedIn measures of how hard it is to hire. One, attractive job openings per active jobseeker, predicted price and wage inflation better than the usual government-data benchmark, and is available weeks sooner.
Why it matters · Wage pressure from a tight job market feeds into inflation and Fed rate decisions, so a reliable gauge that arrives a month early gives an earlier read on where rates are heading.
Know this first
Context from the editor, not the article · 25 sec
1 · Labor market tightness
A labor market is tight when there are many open jobs per available worker. Employers then compete for workers by raising pay, which can push up wages and, eventually, consumer prices.
2 · The standard yardstick
Economists usually measure tightness with the vacancies-to-unemployment ratio, or V/U: job openings from the government's JOLTS survey divided by the number of unemployed people. A reading above 1 means more openings than jobless workers.
3 · Why timing matters
Official job-openings data arrive about five weeks after the month ends. Policymakers setting interest rates want earlier signals, which is why private data from hiring platforms and job boards draws interest.
3/5HumbleDollar· Adam M. Grossman· Oct 31
SpaceX's IPO split college endowment returns; an adviser says skip private funds anyway
Schools that owned SpaceX before its IPO, at a valuation near $2 trillion, posted endowment gains of 32–38%. The median school made 16%. Adviser Adam Grossman argues that luck like this can't be repeated, and that individuals should stick with index funds.
Why it matters · Private funds are being pitched to ordinary savers, including through 401(k)s. This year's endowment results show how much their returns depend on owning one or two lucky holdings.
Know this first
Context from the editor, not the article · 30 sec
1 · How endowments invest
University endowments are large, long-term pools of money. Many follow the "endowment model" that Yale made famous: a big share goes into private assets such as venture capital, private equity and hedge funds instead of only public stocks and bonds.
2 · What private funds are
Private funds invest in companies or strategies that aren't traded on public exchanges. They face lighter regulatory disclosure, usually require large minimum investments, lock up money for years, and charge much higher fees than index funds.
3 · The 401(k) push
4/5Conversable Economist· conversableeconomist· Oct 30
US wealth has outgrown the economy, and the top's share has grown
Economist Timothy Taylor uses Federal Reserve data to show US wealth growing faster than the economy, the richest households taking a bigger share, and stocks driving the gains. He prefers estate-tax changes to a wealth tax.
Why it matters · Whether gains at the top come at everyone else's expense depends on how fast total wealth grows, and that shapes which tax fixes make sense.
Know this first
Context from the editor, not the article · 26 sec
1 · Wealth versus income
Wealth is what a household owns minus what it owes: homes, stocks, businesses, savings. GDP measures a year of output. Wealth-to-GDP compares the stock of assets with the economy's yearly production.
2 · The Fed's wealth data
The Federal Reserve's Distributional Financial Accounts split national household wealth by wealth group. The groups are the top 0.1%, the next 0.9%, the next 9%, the next 40% and the bottom 50%. The data is updated every quarter.
3 · Capital gains at death
Under US law, inherited assets are revalued ("stepped up") to their market value at death. Heirs who sell then owe no tax on gains built up during the original owner's lifetime.
5/5A Wealth of Common Sense· Ben Carlson· Oct 30
S&P 500 profits are up almost 30% in 2026, but stocks only 12%
Ben Carlson notes that S&P 500 company profits have grown almost 30% this year while the index is up about 12%, so stocks have become cheaper relative to earnings. He argues that gaps like this are normal.
Why it matters · Earnings and prices can drift far apart for years. Expecting that helps you avoid buying or selling every time headlines and returns don't match.
Know this first
Context from the editor, not the article · 28 sec
1 · Earnings per share
S&P 500 earnings per share (EPS) is the combined profit of the 500 companies, scaled to one 'share' of the index. Analysts forecast it and revise those forecasts as each quarterly reporting season comes in.
2 · The price-to-earnings ratio
The P/E ratio is the index price divided by earnings. A forward P/E uses the next 12 months of forecast earnings. When profits rise faster than prices, the P/E falls and stocks look cheaper.
3 · The AI spending boom
Big tech firms are spending heavily on AI data centers. That money becomes revenue and profit for suppliers such as chipmakers Nvidia and Micron. Investors worry the spending, and the profits that come with it, may not last.
Executives at America's largest companies have nearly stopped talking about recession. A count by 1 covered 2 held by companies in the 3, the index of about 500 large US companies. It found that from July to September 2026, someone discussed the chance of an economy-wide recession on just 2 of 477 calls, about 0.4%. Daniel Oliveira shared the count on the HumbleDollar forum.
How far the talk has fallen
Earnings calls are the quarterly meetings where executives present results and take questions from analysts, whose job is to press them on risks. Recession came up on 8.2% of calls in early 2024. It jumped to 22.2% right after the April 2025 tariff announcements, when broad new US import taxes set off a market sell-off. Last quarter, analysts raised it on none of the calls.
The only recession executives still describe is a 4. In trucking and shipping, that means a long slump in shipping volumes and rates. It can hit one industry while the rest of the economy grows.
The word that replaced it
"Affordable" or "affordability" came up on 25.6% of calls last quarter, the highest share since at least early 2024. Every utility used it. So did 19 of the 30 5 companies, the makers of groceries and household goods.
What it means for investors
Oliveira writes as an 6 investor. He argues that companies aren't describing a downturn. They're describing customers whose budgets are stretched by the 7. Inflation measures how fast prices are rising. The price level is how high they already are. Inflation can cool while prices stay well above where they were a few years ago, so households still feel squeezed.
In his view, that kind of strain doesn't produce one dramatic bad quarter. It shows up slowly, in sales volumes (fewer units sold) and 8 (less room to raise prices).
Caveats
A word count measures what people talk about, not what will happen. Executives may avoid the word "recession" on purpose. "Affordability" can also mean different things: customers struggling, a company promoting its cheaper products, or a utility arguing over rates with regulators. The full Equibles write-up includes quotes from the calls, but the post only links to it. The comparison also only goes back to early 2024, so it says nothing about the 2022 inflation peak.
Daniel Oliveira, writing on the HumbleDollar forum, points to a word count that sums up how corporate America describes the economy in late 2026. A count by 1 covered 2 held by companies in the 3, the index of about 500 large US companies. It found that "recession" has nearly dropped out of these calls, and that "affordability" now comes up far more often. The post doesn't say what Equibles is beyond this count.
What an earnings call is, and why its words matter
Every quarter, a public company holds a call to report results. Executives read prepared remarks, then take questions from sell-side analysts, the researchers at banks and brokerages who cover the stock. Executives tend to steer toward good news. The analysts' job is to push back and ask about the risks. That makes the question-and-answer section a rough gauge of what investors are worried about. Counting how often a word comes up across hundreds of calls is a crude tool, but it can show how the shared story is shifting.
The disappearance of "recession"
The count tracks how often anyone on a call discussed the chance of an economy-wide recession:
Period
Share of S&P 500 calls mentioning economy-wide recession
Early 2024
8.2%
Just after the April 2025 tariff announcements
22.2%
July–September 2026
2 of 477 calls (about 0.4%)
The April 2025 peak lines up with the broad US import tariffs announced that month, which set off a sharp market sell-off and widespread recession forecasts. Eighteen months later, the topic has nearly vanished. Analysts raised recession on none of last quarter's calls. Oliveira finds this telling, because asking about downside risk is exactly their job.
One kind of recession still comes up: a 4 in trucking and shipping. In that industry's language, a freight recession means a prolonged slump in shipping volumes and rates. It can happen in one sector while the wider economy keeps growing.
The rise of "affordability"
"Affordable" or "affordability" came up on 25.6% of calls last quarter. That is the highest share since at least early 2024, which is as far back as the comparison goes. The word was concentrated in two sectors:
Utilities: every utility in the index used it on its call.
Consumer staples: 19 of the 30 companies used it. These are the makers of groceries and household goods people buy whether times are good or bad.
The article doesn't explain why these two sectors stand out. One plausible reading, from general knowledge rather than the post: both sell necessities. Utility rates are set through regulatory proceedings, where customer affordability is an explicit issue. Staples companies have raised prices a lot since 2021 and are now watching shoppers trade down to cheaper brands or buy less.
Oliveira's reading
Oliveira writes as an 5 investor, someone who owns the whole market rather than picking stocks. He argues the companies are not describing a downturn. They are describing customers whose budgets are stretched by the 6. The distinction is between inflation, the rate at which prices rise, and the price level, how high prices already are. Inflation can cool while prices stay well above where they were a few years ago. Households then feel squeezed even in a growing economy with jobs available.
In his view, that kind of strain shows up differently from a recession. It doesn't bring one dramatic quarter of collapsing earnings. It works slowly, through sales volumes (fewer units sold) and 7 (less room to raise prices to cover costs). Here is an illustrative example, not taken from the article. A staples company might report revenue up 2%, made up of prices up 4% and volumes down 2%. That looks fine in the headline number. Repeat it for several quarters, and the company runs out of room to keep raising prices.
Caveats
The evidence has limits, and the post is short.
Mentions are not forecasts. A word count shows what people talk about, not what will happen. Executives may also avoid the word "recession" on purpose, and the word ran hot in 2025 partly because it was in the news.
Context is flattened. A mention of "affordability" could mean customers are struggling. It could also be a company advertising its own cheap products, or a utility discussing a rate case with regulators. The full Equibles write-up includes quotes from the calls. The post only links to it.
Short baseline. The comparison starts in early 2024, so "highest share since at least early 2024" says nothing about earlier periods, such as the 2022 inflation peak.
Calls cover big companies. S&P 500 firms are not small businesses or households. Their language reflects how their own customers are doing.
The post ends with a question for readers rather than a conclusion: has anyone changed their spending or investing because of prices, rather than recession fears? For an investor, the takeaway is modest. The risk executives describe right now builds slowly, through volumes and margins, rather than arriving as a sudden recession, and it is worth watching for in the details of earnings reports.
Remember
Recession mentions on S&P 500 calls fell from 22.2% after the April 2025 tariffs to about 0.4%.
Every utility and 19 of 30 consumer staples companies mentioned affordability last quarter.
Price-level strain wears down sales volumes and margins over several quarters, not in one bad quarter.
Three economists at the Federal Reserve Bank of New York, Elizabeth Li, Giorgio Topa and Jacob Weber, tested whether new labor-market data from LinkedIn can help predict inflation. They found that one measure, the 1, did better than the standard government-based gauge at predicting both consumer prices and wages. It is also published weeks sooner.
The problem
2 describes how hard it is for firms to find workers. When openings far outnumber job seekers, employers bid up pay, and that can feed into inflation. The usual measure is the vacancies-to-unemployment ratio (3): job openings from 4, the Labor Department's Job Openings and Labor Turnover Survey, divided by the number of unemployed people. The catch is that JOLTS comes out about five weeks after the month it covers.
What LinkedIn measures
LinkedIn publishes three monthly indicators:
JPJI: "attractive" openings divided by the number of members who applied to at least one job that month. An opening counts as attractive if the employer paid to promote it or posted it by hand, and it drew at least one local applicant.
Jobs per Application Index (JPAI): the same openings divided by the total number of applications.
LinkedIn Hiring Rate (LHR): the share of members who added a new employer to their profile, indexed to 2016.
August data can be out in the first week of September. The drawback is that LinkedIn users don't represent the whole US workforce.
How well they track
From July 2019 to April 2026, the JPJI's correlation with V/U was 0.733. From 2021 on, the LHR's correlation with the official JOLTS hires rate was 0.95.
The inflation test
The authors used each measure to "nowcast" the current period's inflation before official figures came out, and to forecast the next period's. They did this for the monthly Consumer Price Index (CPI) and the quarterly 5, a wage measure. They scored accuracy by prediction error and compared every measure against V/U.
The JPJI had the lowest error in every test, beating V/U on both prices and wages.
The LHR beat V/U on forecasting both measures. For nowcasts it beat V/U on prices but not on wages.
The JPAI and the JOLTS hires rate mostly did worse than V/U. The one exception: the JPAI beat V/U at forecasting wages.
Caveats
The sample is short, under seven years, and dominated by the pandemic swings. The post reports rankings but doesn't say how large the accuracy gains are. It also doesn't explain why counting jobseekers works better than counting applications. A likely reason is that application counts rise when tools like one-click applying make applying easier, even if the number of people looking doesn't change.
Three economists at the Federal Reserve Bank of New York, Elizabeth B. Li, Giorgio Topa and Jacob P. Weber, have tested three new labor-market indicators built by LinkedIn from its own user data. They asked whether these indicators can predict inflation as well as the gauges economists already trust. One of them, the 1, predicted both consumer-price and wage inflation more accurately than the standard benchmark. It is also available about a month sooner.
Why tightness matters, and why the usual measure is slow
2 (LMT) describes how hard it is for firms to find workers. When there are few job seekers per opening, employers compete by raising pay. Wage gains can then show up in prices. That chain is why central bankers watch tightness closely when they set interest rates.
The workhorse measure is the vacancies-to-unemployment ratio, or 3. The numerator comes from 4, the Bureau of Labor Statistics' (BLS) Job Openings and Labor Turnover Survey, which counts the openings employers report each month. The denominator is the number of unemployed people. A V/U of 1.5 means 1.5 openings for every jobless person. JOLTS is a careful survey but it is slow: it is published with roughly a five-week lag. A policymaker in early September is still looking at July.
The three LinkedIn measures
All three are monthly. All three depend on a definition of an "attractive" job opening. A LinkedIn listing qualifies only if two things are true. First, the employer either paid to promote it or listed it manually, so it cost them money or time. Second, it received at least one application from a LinkedIn member in the same local labor market during the period. An application can be a direct submission through LinkedIn's 5 button, or it can be inferred when a member clicks through to apply on an outside site. The filter is meant to drop stale or automatically posted listings that nobody is actually trying to fill.
Jobs per Jobseeker Index (JPJI): attractive openings divided by the number of members who submitted at least one application that month. This is the closest relative of V/U: openings per person looking.
Jobs per Application Index (JPAI): attractive openings divided by the total number of applications. The difference from the JPJI is the denominator. A person who sends ten applications counts once in the JPJI and ten times in the JPAI.
LinkedIn Hiring Rate (LHR): the number of members who added a new employer to their profile, divided by the relevant member base (for example, US members). It is seasonally adjusted and indexed to the average month of 2016, so a reading of 1.05 means hiring is 5% above that baseline. It has been published since 2017. The other two are newer and have usable history only from mid-2019.
LinkedIn can release August figures in the first week of September. The obvious weakness is coverage. These numbers reflect only jobs posted and applied to on LinkedIn, and that skews toward certain occupations and types of worker. So the authors asked two questions: do these measures move with the official ones, and do they actually help predict inflation?
Do they track the official data?
The sample runs from July 2019 to April 2026. After converting every series to z-scores (each value's distance from its mean, in standard deviations), the JPJI's correlation with V/U was 0.733. The JPJI ran a little above V/U just after the COVID-19 shock and a little below it from late 2022 to mid-2024. The LHR was compared with the JOLTS hires rate, the official share of workers newly hired. Starting in 2021, which leaves out the extreme swings of spring 2020, the two had a correlation of 0.95.
The prediction test
Tracking well is not the same as forecasting well, so the authors ran two real-time exercises. They predicted monthly Consumer Price Index (CPI) inflation and quarterly 6 inflation. The ECI is the BLS's measure of growth in pay and benefits.
7 means estimating the current period's inflation before the official number is out. For each period t, the authors fitted a regression of inflation on a tightness measure using data only through t–1, the last period with official inflation data. They then plugged in the tightness reading for t to get the nowcast. The regressions roll forward, so each estimate uses only information that would have existed at the time.
Forecasting pushes one step further: regress inflation on the previous period's tightness, then use the reading at t to predict inflation at t+1.
Accuracy was scored by 8. RMSE squares each miss, averages the squares and takes the square root, so large misses count heavily. Each measure's average RMSE was expressed relative to V/U's, with V/U set to 100. As an illustration, a score of 90 would mean the errors were 10% smaller than V/U's.
Results
JPJI: the lowest error of all five measures in both nowcasting and forecasting, for both CPI and ECI. It beat V/U in every case.
LHR: second best overall. It beat V/U at forecasting both CPI and ECI. In nowcasting it beat V/U on CPI but did worse on ECI.
JPAI: generally worse than V/U. The one exception was forecasting ECI, where it beat V/U.
JOLTS hires rate: consistently worse than V/U.
The authors conclude that the JPJI and the LHR are as good as or better than trusted measures like V/U, and that their speed is a real advantage.
What to make of it
The finding has practical value. A gauge that matches or beats V/U and arrives a month earlier gives Fed staff and private forecasters an earlier read on wage pressure. That matters most near turning points, when a month can change a rate decision.
Some limits deserve weight. The test period is under seven years and includes a pandemic collapse, a hiring boom and a cooling. That is a lot of variation, but it is one unusual episode, and the result may not hold in a calmer cycle or a slow-building recession. The post shows ranked bar charts but does not report the relative-error figures in its text, so it says nothing about how much better the JPJI is. A narrow win and a large one would mean very different things. The authors also don't report statistical tests of whether the differences are significant.
The post doesn't explain why the JPJI beats the JPAI, either. One plausible explanation, offered here and not by the authors, is that application counts swell when applying gets easier. One-click buttons and AI-written cover letters raise the number of applications without changing how many people are looking, which would add noise to the JPAI. Finally, because LinkedIn controls how these series are defined and revised, their value as public statistics depends on the company continuing to publish them in a consistent way.
Remember
How you count matters: openings per jobseeker predicted inflation well, but openings per application mostly did worse than the benchmark.
LinkedIn's hiring rate moved almost in lockstep with official JOLTS hires (correlation 0.95 since 2021).
The test window is under seven years and pandemic-dominated, and the post doesn't say how large the accuracy gains are.
Fund managers and some policymakers in Washington want to let private-market investments into workplace retirement plans like 401(k)s. They frame it as giving ordinary savers "access" to returns that used to be open only to institutions and wealthy investors.
Image: HumbleDollar
College 1 have reported results for fiscal 2026, which ended June 30, and the gap between schools was unusually wide. The University of North Carolina gained nearly 38%, Washington University more than 37% and Stanford almost 32%. The median school made 16.1%, according to the consulting firm Cambridge Associates. MIT, usually a top performer, made 10.3%.
The SpaceX effect
Adam Grossman, a fee-only wealth manager writing on HumbleDollar, says the difference comes down mostly to SpaceX. Some schools had bought into the company years earlier, either directly or through 2 funds, which are pools that buy stakes in young private companies. When SpaceX went public this year at a valuation of nearly $2 trillion, those schools had a windfall. At UNC, half of the year's return came from the SpaceX stake alone.
That might look like a win for stock picking. It might also seem to support the push to let private funds into 401(k)s, which backers describe as "democratizing access." Grossman disagrees. He still tells nearly all investors to use index funds and avoid hedge funds, 3 and venture capital.
Why private funds start behind
Fees. The usual setup is a 1–2% annual management fee plus 20% of profits. The publicly traded 4 charges more than 3%. S&P 500 index funds charge as little as 0.03%. As an illustration: on a 10% gross year, "5" leaves the investor about 6.4%, while an index fund leaves nearly 10%.
No repeatable formula
Grossman's main point is that private-market returns depend on a handful of specific deals, and owning a SpaceX can't be planned. The record backs him up. Data from the National Association of College and University Business Officers (6) show the average endowment earned 10.0% a year over three years. The Vanguard Balanced Index Fund, an ordinary stock-bond fund, earned 12.5%. Over five years, endowments did beat that fund, by about one point a year. Grossman's argument is that this lead comes and goes with no pattern. Private funds have to beat public markets by a wide margin just to make up for their costs, and nothing guarantees they will.
These windows are short, and endowments have different goals from individual savers. Still, if well-staffed institutions with access to top funds can't reliably beat a cheap balanced index fund, an individual buying in through a 401(k) has even less reason to expect to.
College 1 have just reported results for fiscal year 2026, which ended June 30. The spread between schools was unusually wide. The University of North Carolina's endowment gained nearly 38%, Washington University's more than 37%, and Stanford's almost 32%. The median return, according to the consulting firm Cambridge Associates, was 16.1%. MIT, normally near the top of the rankings, returned 10.3%.
Adam Grossman, a fee-only wealth manager writing on HumbleDollar, puts most of the gap down to one company: SpaceX.
One holding, a whole year
Some schools had invested in SpaceX years before it went public. A few bought shares directly. Others owned it indirectly through 2 funds, which are pools that buy stakes in young private companies. When SpaceX held its initial public offering (3) this year at a valuation of nearly $2 trillion, those early stakes were suddenly worth a great deal. Schools with little or no SpaceX exposure, which describes the typical school, missed out.
The concentration is striking. At UNC, Grossman writes, half of last year's endowment return came from the SpaceX stake alone.
It's tempting to read this as support for two arguments. The first is the stock picker's: pick the right holdings and you beat everyone else. The second is the case for letting private funds into 401(k)s. Advocates call that "democratizing access," and SpaceX looks like exactly the kind of gain ordinary savers have been locked out of. Grossman rejects both readings. His advice is still that nearly all investors should use index funds and stay away from hedge funds, 4 and venture capital.
The four familiar problems
Cost. The standard private fund charges a management fee of about 1–2% of assets each year, plus a performance fee, usually 20% of the year's profits. People call this "5." Packaged versions are expensive too. The Robinhood Ventures Fund (ticker RVI), a publicly traded fund that holds a basket of private companies, charges more than 3%. Funds that track the S&P 500 charge as little as 0.03%.
Here is an illustrative calculation of how much that matters (the numbers are not from the article). Say a private fund earns 10% before fees in a year. Take out a 2% management fee, leaving 8%. The manager then keeps 20% of that, or 1.6 points, so the investor nets about 6.4%. An index fund earning the same 10% nets about 9.97%. To match the index fund after fees, the private fund would need roughly 14.5% before fees. Its managers have to beat the market by about 4.5 points a year just to break even for their investors.
Taxes. Actively managed funds trade a lot, and each sale of a winning position can produce taxable gains that land on the investor. Grossman cites a recent Morningstar roundup of investors in actively managed mutual funds who got unexpected tax bills. He says private funds carry the same risk, though the mechanism is different. You don't control when you owe tax. The manager does.
Oversight. Private funds don't face the same disclosure and scrutiny as publicly traded funds. Grossman argues this leaves more room for wrongdoing.
Illiquidity. Investors can usually withdraw money only during set windows a few times a year. Grossman notes this has caused trouble even for large endowments, which have sometimes had to sell private stakes below market value to raise cash. Individuals, who may need money for a house, an emergency or retirement spending, have less slack. "An asset that can't be sold on demand has limited practical value," he writes, "however attractive it may appear on paper."
The fifth problem: no repeatable pattern
This year adds another point. Private markets are idiosyncratic, meaning results depend on a small number of specific deals instead of on broad market trends. Whether a school did well came down largely to whether it happened to own SpaceX. Grossman argues there's no reliable way to repeat that.
The long-run numbers back him up. Data from the National Association of College and University Business Officers (6) show the average endowment gained 10.0% a year over the past three fiscal years. The Vanguard Balanced Index Fund, a plain mix of roughly 60% stocks and 40% bonds that anyone can buy, returned 12.5% a year over the same period.
Endowments haven't always lagged. Over the past five years, those in NACUBO's database beat the Vanguard fund by about one percentage point a year. Grossman's point is that the lead and the lag come with no pattern. And because private funds start each year behind on fees, taxes and 7, they have to beat public markets by a wide margin just to break even. Nothing guarantees they will.
What to make of it
A few caveats about the comparison. The three- and five-year windows are short. Endowments also have goals an individual doesn't, such as steady payouts to fund university budgets indefinitely. And a balanced index fund isn't a perfect benchmark for every endowment's mix of assets. The article also doesn't say how much of the 16.1% median came from public stocks rather than private holdings, or how widely SpaceX was held.
Still, the main lesson holds up. Even institutions with large staffs, early access to the best venture funds and decades-long time horizons don't reliably beat a cheap two-fund-style index portfolio. A 401(k) saver offered a private-markets option would get the high fees and the lockups. Whether they'd also get a SpaceX is down to luck.
Remember
Half of UNC's endowment gain last year came from one stake, SpaceX. That kind of win can't be planned.
With 2-and-20 fees, a private fund needs roughly 14.5% before fees to match a 10% index return (illustrative).
Over three years, the average endowment returned 10.0% a year versus 12.5% for Vanguard's balanced index fund.
US wealth as a multiple of GDP since about 1960: near 4 for decades, then rising to new highs.1 / 4
Forbes's latest list of the 400 richest Americans puts their combined wealth at $8 trillion. On his blog Conversable Economist, economist Timothy Taylor puts that figure in context using Federal Reserve data.
Large, but finite
Government actuaries project that over the next 75 years, Social Security's promised benefits will exceed its revenue by about $29 trillion, and Medicare's by about $60 trillion. All $8 trillion would cover roughly a quarter of the first gap or an eighth of the second, not both. Taylor's point is that even huge fortunes are small next to promises the government has already made.
Wealth is outgrowing the economy
From the 1960s through the 1980s, total US wealth stayed at about 4 times 1, the economy's yearly output. A 1990s stock boom and a 2000s housing boom pushed it to 4.9 by 2007. It fell back to about 4 after the 2, the 2007–09 downturn. Then stocks rose almost sixfold after 2010, and the ratio peaked near 5.5 in 2021–22. It now appears to be reaching a new high.
This matters for how to read inequality. If total wealth were flat, gains at the top would have to come out of everyone else's holdings. When the total grows faster than the economy, the top can gain a lot while others' dollar wealth stays about the same. Taylor argues that both situations are bad, but in different ways.
Who owns what
The Fed's 3, a quarterly breakdown of household wealth, cover about 134 million households. The top 1% is about 1.34 million of them. Taylor writes that the top 1%'s share rose from 8.6% in 1989 to about 15%, and the bottom 90%'s fell from 77.2% to 68.3%.
Those labels look off. In the Fed's series, 8.6%→15% tracks the top 0.1%, and 77.2%→68.3% tracks the bottom 99%. That puts the top 1% at roughly a third of all wealth. The trend is the same either way, but concentration is sharper than the post says.
The mix of assets also differs. Households at the top hold more of their wealth in stocks and private businesses. Those lower down hold more in real estate, mostly their homes. Because stocks drove the recent surge, the people who own the most stock gained the most.
Taylor's preferred fix
Taylor is skeptical of wealth taxes, noting that several European countries adopted them and later repealed them. He gives three reasons:
Exemptions pile up.
Assets that rarely trade are hard to value.
Wealth can be moved abroad.
Instead he would target the 4, which wipes out taxable gains on inherited assets. For example, shares bought for $1 million and worth $50 million at death pass to heirs with no tax on the $49 million gain. He also says that simply restoring the 5 rules of 2004 would raise about $100 billion a year.
Forbes's latest list of the 400 richest Americans puts their combined wealth at $8 trillion. In a short post on his blog Conversable Economist, economist Timothy Taylor puts that number in context. He looks at three things: how fast US wealth has grown relative to the economy, who holds it, and what form it takes. He then argues for one kind of tax response over another.
A big number with limits
Taylor starts by comparing $8 trillion with promises the government has already made. Government actuaries project that, under current law, Social Security's promised benefits will exceed its expected revenue by about $29 trillion over the next 75 years. Medicare's gap is about $60 trillion. Even if all $8 trillion could somehow be captured, it would cover roughly a quarter of the Social Security shortfall ($8T ÷ $29T ≈ 28%) or an eighth of Medicare's ($8T ÷ $60T ≈ 13%), not both. His point is not that the fortunes are small. It is that they are finite, and existing commitments are much larger.
Wealth has outgrown the economy
The central chart tracks total US wealth as a multiple of 1, gross domestic product, the value of everything the economy produces in a year, since about 1960.
1960s to 1980s: wealth stayed at roughly 4 times GDP. Assets grew in step with the economy.
1990s to 2007: a stock boom in the 1990s and a housing boom in the early 2000s pushed the ratio to 4.9 just before the 2, the 2007–09 downturn.
After 2009: the ratio fell back to about 4.
2010s onward: stock prices rose almost sixfold after 2010 and drove the ratio to a peak of about 5.5 in late 2021 and 2022. It dipped after that and now appears to be setting a new high.
Why the size of the pie matters
Taylor uses this to separate two kinds of inequality. Suppose wealth-to-GDP stayed flat while the top's share grew. Then the top's gains would have to come out of the wealth of the middle and bottom. The pie stays the same size, so a bigger slice for some means smaller slices for others.
When the ratio rises, the pie itself grows faster than the economy. The top can then gain a lot while everyone else's dollar holdings stay about the same.
An illustrative example, not from the article: total wealth rises from $100 to $130. The top's share goes from 30% to about 46%, or $30 to $60. Everyone else still holds $70, but their share falls from 70% to 54%.
Taylor says both outcomes can fairly be called unpleasant. They are unpleasant in different ways, though, and call for different policy responses.
Who holds the wealth
The Fed's quarterly data counts households. With about 134 million US households, averaging 2.5 people each, the top 1% is about 1.34 million households and the top 0.1% about 134,000. Taylor writes that the top 1% held 8.6% of wealth in 1989 and holds about 15% today, while the bottom 90%'s share fell from 77.2% to 68.3%.
A caution on those figures. As printed, they look mislabeled. In the Fed's published series, a rise from about 8.6% to about 14–15% matches the top 0.1%. A drop from 77.2% to 68.3% matches the bottom 99%, which means the top 1% went from about 23% to about 32%. In that data the top 10% alone holds about two-thirds of all wealth. The direction of the trend is the same either way. The concentration is sharper than the post's labels suggest.
What the rich own differs
Two charts break down assets by group, first in dollars and then as a share of each group's holdings. The dollar chart needs care. The top-0.1% bar covers only one-ninth as many households as the next bar (the 99th to 99.9th percentile). Both cover far fewer households than the bars for the broad middle and bottom.
The share chart shows the pattern Taylor points to. Households near the top hold more of their wealth in corporate stock and in 3, firms such as partnerships and sole proprietorships that aren't separately incorporated. Households further down hold more of their wealth in real estate, mainly their homes.
This links back to the wealth-to-GDP chart. Stocks drove most of the post-2010 surge, so the groups most invested in stocks gained the most. The rise in concentration is largely the stock market rising.
Taylor's policy view
Taylor is skeptical of wealth taxes, meaning annual taxes on a household's net worth. He notes that several European countries tried them and then repealed them. He gives three recurring problems:
Carve-outs pile up. Lawmakers add exemptions for family farms, family businesses, historic properties, heirlooms, art and more.
Valuation is hard. Assets that rarely trade, such as private firms and art, have no market price to tax.
Wealth moves abroad. Assets held in other countries are hard to reach.
Instead he points to two alternatives:
The 4 at death. At death, the starting value used to calculate capital gains resets to the asset's current market value, so gains built up during the owner's lifetime are never taxed. A worked example: a founder buys shares for $1 million that are worth $50 million at death. The heirs can sell for $50 million and owe no capital-gains tax on the $49 million gain. For the very wealthy, who can borrow against assets rather than sell them, this can mean large gains are never taxed. Taylor has written about this rule in earlier posts.
The 5. Returning the US estate tax to its 2004 rules would raise about $100 billion a year, he says, and he notes that 2004 was "hardly a time of confiscatory taxation." The post doesn't spell out those 2004 rules. Historically, the estate tax then exempted far less per person and had a higher top rate than it does today.
What the post leaves open
The post is a set of snapshots, not a full analysis. It doesn't say which wealth measure is behind the wealth-to-GDP chart. It doesn't address how much of the higher ratio might reverse if stock valuations fall, as the ratio did after 2007. The $100 billion figure is given without a source or a breakdown of how it was calculated.
Remember
Since 2010, US wealth has grown faster than GDP, mainly because stock prices rose almost sixfold.
A growing total lets the top's share rise without others' dollar wealth falling. That is a different problem from a fixed pie.
Taylor prefers ending tax-free capital gains at death and restoring 2004 estate-tax rules over a wealth tax.
How analysts' 2026 S&P 500 earnings estimate rose from about $310 as the year went on1 / 4
Ben Carlson of A Wealth of Common Sense points out a gap in this year's market. Profits at S&P 500 companies have grown almost 30% in 2026. The index itself is up only about 12%.
Even one-year forecasts missed
Carlson starts with how bad forecasting is, even over short horizons. In January, analysts expected S&P 500 1, the index's combined profit per share, of a little more than $310 for 2026. Several quarterly reporting seasons then came in well above expectations. The full-year estimate is now nearly 20% higher. These weren't forecasts for 2030. They were forecasts for the year already under way. Carlson takes this as a reason to doubt anyone who confidently predicts how the AI cycle will play out years from now.
Stocks got cheaper during a boom
When profits rise faster than prices, the 2 ratio falls. Here is a rough worked example: prices up 12% and earnings up 30% shrink the P/E by about 14% (1.12 ÷ 1.30 ≈ 0.86). Many investors assume valuations soar in boom times. This year they fell. Carlson shows a chart of a "what if": had 3 ratios simply stayed flat, stock returns around the world would have been much higher.
One possible reason is caution. Investors may suspect that AI spending, known as capital expenditure or 4, is inflating profits that will later shrink.
Gaps like this are normal
Carlson's bigger point is that earnings and returns often diverge:
By decade: they moved roughly together in the 1940s, 1960s, 2000s, 2010s and the 2020s so far. In the 1930s earnings did even worse than stocks. In the 1970s earnings far outpaced stocks. In the 1950s, 1980s and 1990s stocks far outpaced earnings.
By year: the average gap between annual earnings growth and annual returns, in either direction, is almost 25 percentage points. The median gap is 17.
Concentrated profits, skeptical prices
This year's profit growth is narrow. The Wall Street Journal found that ten companies produced about two-thirds of it. Two of them, Micron and Nvidia, produced one-third. 5 data show semiconductor profits up nearly 200% while chip stocks are up only a little over 40%. Those stocks are also more than 20% below their highs. The market seems not to trust that these profits will last.
Carlson's conclusion: fundamentals drive stocks over the long run. In the short run, prices also depend on expectations and on what is already "6", and most of the time nobody knows what that is.
Ben Carlson, who writes A Wealth of Common Sense, uses a short post to point out a gap in the 2026 market. Profits at S&P 500 companies have grown almost 30% this year. The index is up only about 12%. In the middle of what he calls the biggest market story "of this decade and probably this century", AI, stocks have become cheaper, not more expensive.
Starting point: forecasting is hard
Carlson opens with humility about forecasts. People make confident calls about how the AI boom and bust will unfold years from now. Professionals, he notes, struggle to forecast even the next 3 to 12 months.
His evidence is the path of the 2026 earnings estimate. When the year began, analysts expected S&P 500 1 of a little more than $310. EPS is the combined profit of the index's companies, scaled to one share of the index. Then several quarterly reporting seasons came in well above expectations, and the full-year estimate is now nearly 20% higher. As a rough illustration, that puts it somewhere in the low-to-mid $300s. Carlson stresses that this wasn't a forecast for three, five or ten years out. It was a forecast for the current calendar year, and it was "not even close."
The two numbers measure different things. The roughly 20% is how far the 2026 estimate has risen since January. The almost-30% is how much earnings have grown this year. The article doesn't spell out exactly how it measured that growth.
How valuations fell during a boom
The 2 ratio is the index price divided by earnings. Forward P/E uses expected earnings for the next 12 months. When earnings rise faster than price, the ratio has to fall.
A worked example with illustrative numbers: suppose the index began the year at a P/E of 22. Prices rise 12% and earnings rise 30%. The new P/E is 22 × 1.12 ÷ 1.30, or about 19, a drop of roughly 14%. Investors are paying less for each dollar of profit than they were in January.
That runs against a common belief that valuations "go vertical" in booms. Carlson includes a chart of the opposite case. If 3 ratios had simply stayed where they started, stock returns around the world would have been "much, much higher." In the arithmetic above, flat multiples plus 30% earnings growth means roughly 30% price gains instead of 12%.
Why the market might be holding back
Carlson offers one explanation without endorsing it. Investors may worry that the AI capital expenditure (4) boom, the huge sums tech companies are spending on data centers and chips, is inflating profits that will "come back down to earth." One company's capex is another company's revenue. If the spending slows, supplier profits could fall sharply. He calls that "possible."
His main argument is broader. A big gap between earnings and returns is simply normal.
The historical record
Carlson shows S&P 500 earnings growth and 5 (price plus dividends) by decade back to the 1930s:
Roughly in line: 1940s, 1960s, 2000s, 2010s and the 2020s so far.
Earnings worse than stocks: the 1930s. Bad as the market was, profits did even worse.
Earnings far ahead of stocks: the 1970s, when high inflation and rising interest rates pushed valuations down. That context is general history, not from the post.
Stocks far ahead of earnings: the 1950s, 1980s and 1990s, all decades when valuations expanded.
Year by year the gaps get larger. Carlson calculates that the average gap between annual earnings growth and annual market return, ignoring direction, is almost 25 percentage points. The median is 17. A few extreme years pull the average up, but even a typical year has a wide gap. On that measure, 2026's gap of about 18 points (30% minus 12%) is ordinary.
Narrow profits, skeptical prices
The gap gets wider when you look at individual companies and sectors. The Wall Street Journal broke down this year's profit growth by company. Ten companies account for about two-thirds of it. Just two, memory-chip maker Micron and AI-chip maker Nvidia, account for about one-third.
6, an economics and markets research firm, highlighted how little the market seems to trust semiconductor earnings. Chip profits are up nearly 200% this year. Chip stocks are up a little over 40% and are now more than 20% below their highs, the usual definition of a bear-market decline. Investors are paying much less for each dollar of chip profit than they were in January. That is consistent with doubts that profits this high will last. Memory chips in particular have a long history of boom-and-bust cycles, which is general industry knowledge rather than a point from the article.
Carlson's conclusion
Fundamentals tell part of the story, Carlson writes, but prices also reflect expectations and what is already "7," and "most of the time no one knows what's priced in." Over the long run, fundamentals drive the market. Over the short run, earnings and prices often move apart.
What the post leaves open
The post is a short argument, not a forecast. It doesn't say whether the falling multiple makes stocks a bargain or reflects a sensible discount on profits that won't last. It doesn't give starting or current P/E levels. It also doesn't say how much of this year's earnings growth comes from outside the AI supply chain. The practical point for a long-term investor is narrower: a year when profits soar and stocks lag, or the reverse, is not a sign that something is broken. It happens often.
Remember
Since 1930, the average yearly gap between S&P 500 earnings growth and returns is almost 25 points; the median is 17.
Just Micron and Nvidia produced about a third of 2026's S&P 500 profit growth.
Chip profits are up nearly 200% this year, but chip stocks only about 40%, a sign investors doubt the profits will last.
