Viewpoints

With the U.S. economy growing at a healthy clip and unemployment low, many people ask: Are workers paid appropriately? The rise in stock market valuations, high home prices and the soaring wealth of artificial-intelligence innovators make the question even more urgent. On a topic so central to fairness and living standards, it’s important to use data that carefully measure and evaluate compensation. In particular, the benchmarks we look to need to account for inflation and reflect worker productivity.

In the years prior to Covid, when adjusted for inflation, show that wage compensation—total wages and salaries plus supplements such as employer contributions to pensions and savings plans—closely tracked productivity gains (Chart 1). The 2020s have been a different story. Wages have increased significantly, but persistently high inflation has undercut those gains. Consequently, while real wages have increased, they haven’t kept pace with worker productivity. No wonder surveys show Americans losing confidence in the economy. Persistent inflation is the culprit.

India has confounded expectations, weathering the latest Iran war-induced energy price shock far better than previous crises. Recall 2011–14, when Brent averaged over US$100/bbl for four consecutive years, and 2022, when oil surged to US$123/bbl. Economic growth slowed sharply during both episodes.

This time, despite some moderation in the second quarter, real GDP growth averaged 8.2% YoY in 1H26, up from 6.8% in 1H25. Consumption remains resilient, investment is accelerating and exports have rebounded (Figure 1).

I, and many others, have argued that following the AI buildout, investments in AI will eventually undermine labor's share of income as the declining cost of AI encourages firms aggressively to substitute computers and software for humans in the workforce.

The Bureau of Labor Statistics (BLS) will not release its estimates of third-quarter productivity and costs - including labor's share of Gross Value Added (GVA) - until Thursday of this week. However, if one knows where to look in last week's preliminary estimate of the National Income and Product Accounts for the third quarter, one can calculate the most recent share for the business sector by subtracting from total compensation of employees both the compensation of general government employees and the compensation paid by private households and nonprofit institutions serving households, and then divide the residual by the GVA of the business sector.

The recent history of that calculation is depicted in the chart. Following the introduction of ChatGPT in late 2023 there was no immediate decline in labor's share of income. However, in 2025 that share began slipping, and by the third quarter of 2026 it dropped to 49.1%, the lowest reading recorded in the quarterly data back to 1947.

The US economy saw a significant 3.4% rise in Q3 real GDP. Despite this impressive figure, it falls far short of the expectations set by some "bullish pundits" regarding the AI boom's impact. A surge in business investment helped boost the Q3 economic performance, but it does not represent a sustainable economic boom in its current form. Business investment in equipment, mainly AI technology, rose 20% annualized in Q3. However, the primary factor driving the economy's growth beyond 3% was the 3.8% rise in real consumer spending, with a 4% increase in consumer spending on services. There is limited hard data on services at press time, so revisions are possible. Even if the increase in real PCE is accurate, its sustainability is questionable. Real disposable income advanced only 1.7% annualized in the quarter and 0.8% over the past year. Without stronger income growth, the Q3 consumer spending performance is unlikely to be repeated. Additionally, if AI experts are correct, the rapid investment in AI technology could eliminate thousands, if not millions, of existing jobs, making the outlook for consumer spending concerning at best. (Note: consumer spending accounts for 70% of GDP and business investment in equipment accounts for 7%).

The Federal Reserve, Bank of Canada, European Central Bank and Bank of Japan meet this week against a difficult backdrop. An energy shock has pushed inflation higher just as households and businesses are contending with expensive borrowing. Economic growth has proved resilient, but the question for policymakers is how secure that resilience really is. There is a strong case for caution before tightening monetary policy further.

The immediate dilemma is familiar. Central banks cannot prevent an oil price shock, but they must guard against its spreading into wages, other prices and inflation expectations. At the same time, higher energy bills reduce spending power and raise costs for businesses. Further increases in interest rates could compound that pressure, even as the effects of earlier tightening are still being felt.

For now, there is little evidence that higher energy prices are feeding into broader inflation. The foundations of demand also deserve closer scrutiny. Government borrowing, rising asset values and investment based on expectations of future returns have all supported spending. Those supports may be less durable than the headline growth figures suggest.

The danger is that policymakers mistake this spending for lasting economic strength. Until productivity gains translate into broader income growth, further tightening risks undermining both today’s demand and the revenues needed to justify tomorrow’s investment. That does not mean central banks should overlook persistent inflation. It does mean they should weigh the evidence for it against the fragility of the growth they are seeking to restrain.

The evidence on inflation Latest data for September show that core CPI inflation, which strips out food and energy, is 2.6 per cent in the United States, 2.5 per cent in the euro area and 2.4 per cent in Japan. None has moved materially higher over the past six months, and the American and Japanese measures are lower than a year ago. So far, the rise in headline US inflation to nearly 4 per cent has not been accompanied by a comparable increase in core inflation.

The Federal Reserve Bank of Philadelphia’s state coincident indexes in September showed moderate growth. In the one-month changes, three states, located in three corners of the nation--had increases greater than .5 percent (South Carolina, Nevada, and New Hampshire). However, 10 saw declines. Over the three months ending in September Nevada’s index rose more than 2 percent, and South Carolina’s was up more than 1.5 percent. Alabama and Hawaii saw declines. Over the last twelve months Nevada’s index rose a marked 4.77 percent, South Carolina was also up more than 4 percent, and 9 other states saw increases of over 3 percent. Of the remaining states, 34 had increases of at least 1 percent, while Hawaii, Alabama, and Connecticut registered small declines.no state saw an increase of 4 percent or more—Nevada’s 3.76 percent was the highest (six other states had increases above 3 percent). Alabama and Connecticut were down, and six others saw increases of less than one percent. r percent (Idaho was up 3.62 percent), and six others were at or higher than three percent.

The independently estimated national estimates of growth over the last three and twelve (respectively, .45 and 1.91 percent) appear to be a bit lower than what the state numbers would have suggested.

The AI boom faces a problem beyond the technology itself: its prospective customers must be able to afford it. Investment in computing capacity is adding to demand for power, equipment and capital before comparable productivity gains have spread across the economy. If those pressures weaken customers’ spending power, they may also constrain the revenues needed to justify the build-out. AI can fulfil its technical promise while disappointing those who finance it.

This helps explain why weakness outside technology should concern technology investors. The immediate beneficiaries of infrastructure spending are easy to identify. The eventual returns depend on a much broader group of businesses earning enough from AI to pay for its services. Those two stages need not proceed at the same pace.

The costs arrive first Every investment boom creates demand before it creates productive capacity. For AI, the timing matters because several essential inputs are slow to expand. Power stations, grid connections and transformers take years to deliver. A well-funded buyer can secure priority without increasing what is immediately available to everyone else.

Electricity makes the constraint tangible. Data centres add demand to networks already serving competing needs. Fuel prices, weather and available generating capacity also matter, so rising power costs cannot simply be attributed to AI. Nevertheless, the build-out can intensify local shortages. For other users, the consequences include higher operating expenses and delays to investment, even if they have yet to adopt the technology.

State labor markets were little-changed in September. New Jersey and South Carolina recorded statistically significant increases in jobs, while Wisconsin saw a decline (though the Brewers sweeping the Dodgers is likely providing great solace). Five states saw significant drops in their unemployment rates (Florida, Maryland, Nevada, New Hampshire, and Pennsylvania), though none was larger than .2 percentage points. The highest unemployment rates were in DC (5.6%), Oregon (5.1%), California (5.1%), Oregon (5.0%), and Michigan (5.0%). However, Oregon’s rate was not regarded as statistically higher than the nation’s 4.2%.Nebraska, New Hampshire, Hawaii, Vermont, North Dakota, and South Dakota had unemployment rates under 3.0%, while South Dakota’s 2.0% was the lowest in the nation.

Puerto Rico’s unemployment rate increased to 6.2%, reflecting another marked increase in the island’s labor force (July saw a .8% rise), while the island’s job count fell 1,500.