The U.S. Economy’s Secret Weapon: Seniors With Money to Spend

Why has consumer spending proven so resilient as the Federal Reserve has raised interest rates? An important and little-appreciated reason: Consumers are getting older.

In August, 17.7% of the population was 65 or older, according to the Census Bureau, the highest on record going back to 1920 and up sharply from 13% in 2010. The elderly aren’t just more numerous: Their finances are relatively healthy and they have less need to borrow, such as to buy a house, and are less at risk of layoffs than other consumers.

This has made the elderly a spending force to be reckoned with. Americans age 65 and up accounted for 22% of spending last year, the highest share since records began in 1972 and up from 15% in 2010, according to the Labor Department’s survey of consumer expenditures released in September.

“These are the consumers that will matter over the coming year,” said Susan Sterne, chief economist at Economic Analysis Associates.

“Our large share of older consumers provides a consumption base in times like today when job growth slows, interest rates rise and student-debt loan repayments begin again,” she said.

Seniors’ high spending propensities reflect health, wealth and perhaps lingering psychological effects of the pandemic.

“All my life it was, save for this, save for that,” said Maureen Green, 66, of Cape Cod, Mass. “Now there’s money in the bank and I’m spending in ways that bring me closer to friends and family than I did before.”

Green, a real-estate agent with four grown children living across the country, estimated she is spending 25% more and twice as much time traveling now compared with 2019. She recently traveled to Syracuse, N.Y., to catch a photo exhibit with friends, and toured Rhode Island with her son and his girlfriend.

“The one million Americans who didn’t survive Covid—that’s part of it. That taught me not to let time go by because before I know it, that time won’t be there anymore,” she said.

Living better, longer—and larger

“The lifestyle of the senior has changed dramatically—they’re more active than ever,” said Marshal Cohen, chief retail adviser of Circana, a research firm specialising in consumer behavior. That has expanded the menu of recreation on which to spend, he said. “They’re riding e-bikes, they’re hiking, they’re traveling. And they’re doing these things for longer than they’ve ever been done.”

The average household led by someone age 65 and older spent 2.7% more last year than in 2021, adjusted for inflation, according to the Labor Department, compared with 0.7% for under-65 households. Spending by older households is up 34.5% from 1982, compared with 16.5% for younger households.

Comparable data isn’t available for 2023. However, consumers older than 60 reported spending 7.9% more in August than a year earlier, compared with a 5.1% increase among those age 40 to 60 and a 4.6% gain for younger consumers, according to a survey by the New York Fed. The data aren’t adjusted for inflation.

The growing yen to spend by the elderly is amplified by their sheer numbers. The unusually large cohort of baby boomers, the youngest of which are 59, are reaching their retirement years en masse.

American Cruise Lines, which gears its cruises toward older consumers, said it is seeing double-digit sales growth this year, driven largely by boomers. The Guilford, Conn., company this year added three ships to its fleet and expanded its season by a month for some popular routes.

“River cruising has traditionally attracted an older audience, and with more boomers retiring each year, we see both a rapid rate of growth and demand for longer experiences,” said Charles B. Robertson, the company’s president and chief executive.

The economy’s silver bullet

Another factor in the elderly’s favor: relatively strong finances. Americans age 70 and older now hold nearly 26% of household wealth, the highest since records began in 1989, according to the Federal Reserve.

While economists still see a relatively high probability of recession in the coming year, Ed Yardeni, president and chief investment strategist of Yardeni Research, isn’t one of them. An important reason: By the Fed’s reckoning, baby boomers alone have now amassed $77.1 trillion in wealth. “There’s a $77 trillion-wide hole in the theory that consumers’ running out of pandemic savings will sink the economy,” he said.

They have less consumer debt, minimal student debt and are more likely to own their homes outright. Many of those who have mortgages refinanced at the unprecedented low in mortgage rates after the pandemic hit. They are also less likely to need to move due to an expanding family or a new job than Gen Z and Millennials, shielding them from the impact of rising housing costs.

Retirees also received an 8.7% cost-of-living-adjustment bump to Social Security payments in January, the largest single-year increase since 1981, and an automatic adjustment to offset last year’s 9.1% inflation peak.

These factors have cushioned seniors from the twin scourges of inflation and high interest rates. And since most of them are retired, seniors’ spending is less vulnerable to the rise in unemployment that many economists anticipate in coming quarters.

Subscription demand for the Cincinnati Opera’s summer festival this year was surprisingly strong and driven by older patrons, said Todd Bezold, director of marketing.

“Despite the multiyear trend in subscriptions going down, down, down in every art form, we went up this year—by 3%,” he said. That jump in demand came despite a sharp rise in ticket prices to account for several years of inflation. “The vast majority of our subscribers are baby boomers; we know that much.”

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