Rest of World’s Growth Is at Trump’s Mercy

Donald Trump will retake office in a global economy substantially transformed from eight years ago—one much more reliant on the U.S.

It means that the president-elect’s plans, including across the board tariffs , could pack an even greater wallop on other countries than the first round of “America First” economic policy. It also gives Trump much more leverage in negotiations over trade policy.

Strong growth since the pandemic has expanded the U.S.’s weight in the global economy. Its share of output among the Group of Seven wealthy nations is higher than at any point since at least the 1980s, International Monetary Fund data shows.

Growth in China, the world’s second-largest economy, has slowed. Germany, the largest European economy, is contracting. Many poorer economies are buckling under the weight of high debt.

U.S. gains in global output partly reflect the strong dollar, which pushes up the value of American output relative to that of foreign economies. But they also result from substantial increases in U.S. productivity compared with the rest of the world.

The changes in the global economy have made America, not China, the premier destination for foreign direct investment, enlarging the exposure that foreign companies have to the U.S. economy and changes in government policy. A booming U.S. stock market has attracted huge flows of investment dollars.

“The fact that much of the rest of the world is now struggling to generate demand on its own provides more reason for countries to try to reach some sort of accommodation with Trump,” said Brad Setser, a senior fellow at the Council on Foreign Relations.

Trump started imposing tariffs in 2018, primarily on China but also on Europe and other allies. Those tariffs fractured global trade, weighing on large exporting economies in Asia and Europe, while not obviously hurting the U.S., which is less reliant on foreign demand than its trading partners. Trump campaigned on a promise to impose at least a 60% tariff on China, and an across the board tariff of 10% to 20% on everywhere else.

America’s superior economic performance has been driven in part by energy independence and massive government spending, said Neil Shearing , chief economist at Capital Economics in London. Since the U.S. now exports more energy than it imports—including millions of barrels of oil each month to China—the nation as a whole benefits when energy prices rise, unlike for net importers such as China and Europe.

The upshot: America’s traditional role as the centre of gravity in the global economy has become even more pronounced in the years after Trump’s first-term tariffs, the pandemic, and Russia’s full-scale invasion of Ukraine.

U.S. influence over Europe’s economy is a case in point. The U.S. has cemented its position as Europe’s largest export market as trans-Atlantic trade surged in recent years and China’s imports from Europe stalled. The U.S. has replaced Russia as Europe’s major source of imported energy. Europe runs big trade surpluses with the U.S. but big trade deficits with China.

The result is access to the U.S. market is far more important for Europe than access to European markets for the U.S. That asymmetry will give Trump leverage in trade negotiations with Europe, according to economists.

Germany exports around 7% of its entire manufacturing value-added to the U.S., but Germany imports only around 0.8% of value-added in U.S. manufacturing, according to a September paper by researchers at Germany’s Ifo Institute for Economic Research.

“German business is vulnerable to Trump,” said Marcel Fratzscher , president of the Berlin-based economic research institute DIW Berlin.

Parts of Asia have benefited from the changes in supply chains sparked by Trump’s initial trade war with China. Many manufacturers, including Chinese ones, moved factories to places such as Vietnam and Cambodia. For the past two quarters, Southeast Asia’s exports to the U.S. have exceeded those to China.

But that now leaves them more exposed to across the board tariffs, a policy that Trump advisers say will be necessary to force manufacturing back to the U.S.

To be sure, Trump’s policies could create countervailing forces. Tariffs would decrease imports and potentially weigh on productivity, but tax cuts would drive up household and business spending, including, inevitably, on imports. Other countries could retaliate by placing tariffs on U.S. goods.

Meanwhile, a tight U.S. labor market has pushed up wages, which is good for those workers. But it could pressure employers to raise prices, in turn making them vulnerable to foreign competition.

Many economists are girding for a different type of trade war from Trump 1.0, when trade fell between the U.S. and China but was diverted elsewhere.

“As long as protectionism refers only to one country, China, the world can live with this,” said Joerg Kraemer , chief economist at Commerzbank. “The thing becomes difficult or dangerous if you implement tariffs on all countries. This would be a new era in global trade.”

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