As Greedflation Starts to Fade, Wageflation Creeps In

When inflation took off in 2021 in the U.S., so did corporate profits, leading to accusations of “greedflation” and calls in some corners for price controls. This year, Europe is going through the same debate amid soaring food prices.

Judging by recent developments, inflation driven by corporations flexing their power to jack up prices more than costs—greedflation, as some called it—is on its way out. Pretax margins, which widened sharply in 2021 and 2022, were roughly back to pre pandemic levels in the first quarter of 2023, according to revised government data released last week. Margins in six of the S&P 500’s 11 sectors were lower in the second quarter than four years earlier, according to FactSet.

Narrowing profit margins, though, doesn’t necessarily mean an end to inflation. Wages are now growing faster than prices. While that doesn’t provoke the same outrage as soaring profits, it’s just as problematic for getting inflation down.

The circumstances of 2021 and 2022 made for a seller’s paradise. As the economy reopened, newly vaccinated consumers rushed to spend pent-up savings and stimulus cash. That demand collided with supply held down by pandemic disruptions and the inability of meeting so much demand with existing capacity.

The result: pretax margins shot from 15.6% in the fourth quarter of 2019 to 17.9% in the second quarter of 2021. That’s based on the Commerce Department’s measure of total value added by corporate businesses. This measure separates total costs into labor, profits, and non labour costs such as depreciation, interest and excise taxes, while excluding inputs, such as energy.

In the year through the second quarter of 2021, those companies’ prices rose 4.3%. At the same time, the cost of labour per unit of output fell 2.3%, because though wages were rising in that time, output per worker (productivity) was rising faster. Profit per unit of output rose a whopping 40%.

Greedflation is a catchy phrase, but not of much analytical value. Businesses always set prices to maximise profits. Raising them too much risks competitors ramping up supply to take market share.

But in 2021 and most of 2022 many companies couldn’t expand supply because of shortages of materials, labour or transport capacity. In the past when demand for vehicles rose, manufacturers effortlessly boosted output. This time, a shortage of semiconductors curtailed production and manufacturers responded to strong demand by slashing incentives and raising prices. General Motors sold fewer vehicles in both 2021 and 2022 than in 2019 but in both years made about 50% more profit. Companies weren’t the only beneficiaries: so was anyone with a used car to sell.

While greed is timeless, companies conceivably may have more power to translate greed into prices because of declining competition. The Biden administration, for example, blamed soaring meat prices in part on consolidation among meatpackers. But that wouldn’t have translated into such high prices without so much demand from locked-down consumers and the industry enduring production interruptions and labour shortages due to Covid-19, drought, avian flu and shrunken herds.

In recent quarters demand has softened. Adjusted for inflation, consumer spending was flat in three of the past four months. Tyson Foods lost money in the second quarter as soft demand pulled down prices for pork and beef while feed and labour expenses rose.

Supply, meanwhile, seems to be improving, at least for goods. In a report this week, economists at Goldman Sachs said global shipments of automotive semiconductor chips and U.S. auto production in the past few months are finally above pre pandemic levels. As a result, automotive inventories and incentives are both on the rise. In May the average new car buyer paid $410 below sticker price, compared with $637 above a year earlier, according to Cox Automotive.

Demand for services is holding up better than for goods, and services supply is still constrained, in particular by labour shortages. One reason air travel is so expensive is that airline capacity this year is about 14% below pre pandemic trend levels, Delta Air Lines recently told shareholders.

As airlines add flights they stretch staff, aircraft and air-traffic controllers to capacity, leaving them vulnerable to the slightest disruption. After thunderstorms triggered hundreds of flight cancellations in recent weeks, United Airlines said it might reduce flights out of its Newark, N.J. hub to create a buffer.

Airlines also reflect a broader reality: Whatever pricing power business still commands is increasingly eaten up by labor costs. Pilot shortages caused by pandemic retirements have given unions bargaining leverage, with many seeking to replicate a 34%, four-year increase Delta gave its pilots this year.

Workers are slowly recapturing more of the economic pie. In the first quarter of 2023, wages and salaries rose to 49.3% of corporate value added, higher than in 2019. Labor costs per unit of sales rose 6% in the year through the first quarter, ahead of prices, which were up 5.3% in the same period. Profits per unit of output rose just 1.6%.

The trend of wages rising faster than prices has continued in recent months. That’s welcome relief for workers but poses a set of difficult tradeoffs: Either profit margins will have to narrow further, which businesses will resist; high inflation will have to continue, which the Federal Reserve is fighting; or productivity will have to boom, of which there is no sign yet. If none of those things happen, then wageflation, like greedflation, will have to go away.

A sharp technology sell-off has exposed a new anxiety on global markets: whether the enormous borrowing behind the artificial-intelligence infrastructure boom can generate sufficient returns as interest rates rise and Chinese competition intensifies.

The artificial-intelligence investment boom has powered technology shares, semiconductor manufacturers and data-centre operators to extraordinary heights. Last week, investors were given a reminder that much of this expansion is being built with borrowed money.

The technology-heavy Nasdaq Composite fell 4.5 per cent over the week ended October 16, its weakest performance since late June. Semiconductor shares suffered an even deeper correction, with the Philadelphia Semiconductor Index losing about 11.4 per cent.

The selling spread quickly through global markets. Micron Technology fell 14.6 per cent over the week, while South Korea’s Samsung Electronics and SK Hynix dropped approximately 18 per cent and 24 per cent respectively.

This was more than a routine bout of profit-taking. Investors were reassessing three interconnected risks: higher interest rates, the rapidly expanding debt burden attached to AI infrastructure and the prospect of stronger competition from Chinese memory-chip manufacturers.

The debt behind the AI build-out

Artificial intelligence requires a physical infrastructure network of enormous scale. Data centres must be built, advanced processors purchased, power supplies secured and cooling systems installed before customers begin generating meaningful revenue from them.

Technology companies are increasingly supplementing their own cash with corporate bonds, syndicated loans, equipment leases, private credit and project-level financing.

JPMorgan describes the emerging funding model as a combination of conventional corporate borrowing and project finance tied to individual data-centre assets. In Australia, the Reserve Bank estimates that syndicated loans accounted for approximately three-quarters of data-centre financing during 2025 and 2026 to date.

The numbers are becoming large enough to affect broader credit markets. The Federal Reserve Bank of Dallas has cited Wall Street estimates suggesting AI-related investment-grade bond issuance could approach US$300 billion in 2026 alone.

That borrowing is not automatically problematic. Debt can be an efficient way to finance long-lived infrastructure when future revenue is sufficiently predictable. The concern is that AI technology, customer demand and computing economics are changing much faster than the repayment schedules attached to the assets.

A data centre financed today may carry debt for years. Investors must therefore make assumptions about future utilisation rates, electricity prices, chip performance, customer concentration and the amount businesses will ultimately pay for AI computing.

When interest rates rise, those assumptions become less forgiving.

Inflation changes the calculation

September’s US inflation data intensified the pressure. Consumer prices increased 3.7 per cent over the year, ahead of market expectations and up from 3.4 per cent in August.

The hotter reading reduced confidence that interest rates would fall quickly and pushed bond yields higher. That matters particularly for companies whose valuations depend on profits expected well into the future, as well as highly leveraged infrastructure operators that may need to refinance.

CoreWeave has emerged as a closely watched test case. The specialist cloud-computing company has accumulated substantial debt and lease obligations to build AI capacity, while relying on a concentrated group of large technology customers.

Its shares fell sharply during the sell-off, while the cost of insuring its debt against default climbed. CoreWeave has argued that its contracted backlog more than covers its obligations and that financial markets do not always understand its business model. Nevertheless, its securities have become a proxy for investor confidence in debt-funded AI infrastructure.

Oracle, another major investor in AI computing capacity, fell 8.8 per cent in Friday trading, while CoreWeave dropped 15.5 per cent.

The question is shifting from how much AI infrastructure can be built to how profitably it can be operated.

China adds another source of pressure

Interest rates were not the only catalyst. Reports of advances by Chinese memory-chip producer ChangXin Memory Technologies raised concerns that lower-cost Chinese products could increase competition across the global semiconductor industry.

Memory chips are essential to AI systems, but the industry is historically cyclical. Periods of tight supply and high pricing can encourage rapid investment, eventually producing oversupply and falling margins.

The prospect of a well-funded Chinese competitor expanding its technological capabilities unsettled investors in Samsung, SK Hynix and Micron. It also demonstrated that AI-related demand does not insulate chipmakers from conventional competitive pressures.

That combination—slower rate cuts, more expensive financing and potentially cheaper supply—challenged the assumption that every company exposed to AI would enjoy continually expanding margins.

A reset rather than the end of the boom

The sell-off does not establish that the AI boom is ending. Demand for computing power remains strong, the largest technology companies continue to generate formidable cash flows and many infrastructure projects are backed by long-term customer contracts.

What has changed is the market’s willingness to overlook the price and financing structure of that growth.

The most resilient companies are likely to be those able to fund investment from operating cash flow, secure long-duration customers and demonstrate that new capacity will earn returns comfortably above its financing costs.

More speculative operators may face greater scrutiny, particularly where debt is expensive, customers are concentrated or expected revenue depends on demand that has not yet materialised.

For Australian investors, the lesson extends beyond US technology shares. Local data-centre operators, infrastructure funds, electricity suppliers and property groups are increasingly exposed to the same investment cycle.

Artificial intelligence may remain one of the defining growth themes of the decade. But last week’s correction showed that enthusiasm for the technology does not eliminate financial discipline.

The next stage of the AI boom will be judged not only by computing power, model performance or demand for chips, but by something more traditional: whether the assets being financed can generate enough cash to repay the money borrowed to build them.

Fact box

Nasdaq Composite: Down 4.5 per cent for the week ended October 16, 2026

Philadelphia Semiconductor Index: Down approximately 11.4 per cent

Micron Technology: Down approximately 14.6 per cent

Samsung Electronics: Down approximately 18 per cent

SK Hynix: Down approximately 24 per cent

US September inflation: 3.7 per cent annually

Estimated 2026 AI-related investment-grade issuance: Approximately US$300 billion