Viewpoints: January 2026

Yet again, the Federal Reserve Bank of Philadelphia’s state coincident indexes in December were generally soft. In the one-month changes, Kentucky and Missouri were the only states with increases above .50 percent. 16 were down, with West Virginia off by more than one percent. Over the three months ending in December, Missouri was the only state with an increase higher than 1 percent (Idaho was up .99 percent), while eight fell, with Delaware off more than 1 percent and West Virginia down more than two percent. Over the last twelve months, four states were down (Delaware by more than two percent), and seven others saw increases of less than one percent. Seven states saw increases of 3 percent or more, with Alabama’s 3.91 percent at the top.

The independently estimated national estimates of growth over the last three and twelve months were, respectively, .38 and 1.84 percent. The three-month reading seems to be in line with what the state numbers would have suggested, while the twelve-month one appears to be lower.

Excess, innovation and why this boom may still have room to run

Recent weeks have seen financial markets gripped by a shifting mix of narratives. A weaker US dollar, rising rate volatility and renewed geopolitical uncertainty have revived talk of a tentative “sell America” trade, as investors reassess US exceptionalism after several years of outperformance. At the same time, global equity markets have remained remarkably resilient, supported in large part by continued optimism around artificial intelligence and the powerful investment cycle it has unleashed.

Against this unsettled backdrop, a familiar question has returned to the centre of market debate: are prices being driven by fundamentals, or by faith? With artificial intelligence, that conversation has clearly arrived. Equity markets — particularly in the United States — have surged on the back of a relatively small group of AI-exposed firms that now account for a striking share of index gains. Valuations increasingly rest on the assumption that AI will deliver a sustained uplift to productivity, profits and long-run growth. Investors are no longer debating whether AI will transform the economy; instead, they are debating how quickly — and how completely — those gains will materialise.

Lessons From History

History offers a useful starting point. Truly transformative technologies almost always arrive alongside periods of financial excess. Railroads, electricity, telecoms and the internet all produced extraordinary investment booms that ultimately reshaped economic structures, even as they destroyed large amounts of capital along the way. The presence of a bubble never meant the technology was flawed. It meant expectations moved faster than cash flows, infrastructure deployment and balance-sheet reality. AI fits this historical pattern uncomfortably well.

In this environment, narrative often dominates near-term profitability, and that is typically how transformative technologies diffuse rapidly across the economy. But where bubbles become truly dangerous is not via investor enthusiasm itself, but in the financing structures that accompany large infrastructure build-outs. Equity investment in diversified firms with strong balance sheets is fundamentally different from debt-financed bets on long-lived assets whose viability depends on uncertain demand and rapidly evolving technology. Yet we are already seeing significant capital being channelled into data centres, energy infrastructure and specialised AI facilities, increasingly funded through project-level vehicles and long-dated financing. These investments rest on assumptions about sustained utilisation, manageable energy costs and technological continuity — assumptions that inevitably carry risk.

This should feel familiar. The late-1990s telecoms boom was not undone because fibre optics were useless, but because capacity was financed almost entirely with leverage long before revenues caught up. When pricing power collapsed, investors absorbed enormous losses, even as the infrastructure went on to support the digital economy that followed.

The Macro Dimension

However, there is also a macro dimension in this debate that deserves more attention, and this is where today’s AI boom still looks somewhat different from past excesses. The chart below contrasts private non-residential investment in the US with the financial balance of non-financial corporations. During the dot-com era, corporate investment surged at the same time as the corporate sector moved deep into financial deficit. Firms were spending far beyond internal cash flows, and increasingly reliant on external financing — particularly debt — to fund speculative expansion. That combination of soaring investment and widening financial imbalances was a classic Minsky-style warning sign.

State labor markets were again soft in December. No state had a statistically significant change in payroll employment; the largest absolute gain was a 19,700 increase in Texas, which was barely .1 percent.

Six states saw statistically significant increases in their unemployment rates (Delaware, Florida, Illinois, Minnesota, Oklahoma, and Washington)—Delaware’s was up .3 percentage points. The highest unemployment rates were in DC (6.7%), California (5.5%), New Jersey (5.4%), Delaware (5.2%), Nevada (5.2%), Oregon (5.2%), and Michigan (5.0%). Alabama, Hawaii, North Dakota, South Dakota, and Vermont had unemployment rates below 3.0%, with Hawaii and South Dakota’s the lowest, both at 2.2%.

Puerto Rico’s unemployment rate was again unchanged at 5.7% and the island’s job count rose by 3,600.

U.S. economic growth has remained solid through most of 2025, driven by healthy gains in consumption and strong business fixed investment, particularly for the buildout of AI. This has defied the pessimists’ worries about President Trump’s misguided tariffs, clampdown on immigration and cuts in research grants to universities. The only real laggard in 2025 was the housing sector, which suffered from continuous declines in construction and improvements. But that was last year and we should not expect any let up in erratic tariff policies and anti-immigrant initiatives in 2026.

Despite these obstacles, the outlook for sustained expansion in 2026 looks favorable, and the probability for recession is low. Current conditions are inconsistent with onsets of recession in the past. Consider the following two items that will support aggregate demand: 1) three Fed interest rate cuts in September-December 2025 lowered the real Fed funds rate below the Fed’s estimate of the longer-run real rate of interest consistent with its dual mandate of 2% inflation and maximum employment, and the Federal Reserve Bank of Chicago’s Financial Conditions Index signals loose financial conditions, and 2) fiscal policy is stimulative, as the OBBBA of 2025 extended the 2017 tax cuts and added some additional cuts (eliminating tax on income from tips, expensing of outlays for research and development) that will boost tax refunds in Spring 2026 by approximately 0.6% of disposable personal income. In this environment, 3) business inventories are relatively low and 4) employment is well-aligned with output (GDP). Accordingly, any slump in aggregate demand will not force businesses to cut output and/or employment in a meaningful way.

Labor market and personal income dynamics. One key trend to keep an eye on is real wage and salary incomes, a key indicator of labor market conditions and measure of consumer purchasing power. Growth in personal income from wages and salaries has decelerated to 3.8% in the year ending November 2025 (Chart 1). That’s down from a 5.5% rise in the prior year. At the same time, CPI inflation was 2.7% in the last two years ending November 2025. According, the year-over-year growth in real personal disposable income from wage and salaries has receded to 1.1% in the year ending November 2025, significantly slower than its 2.8% rise in the prior year.

This deceleration in real wages and salaries reflects primarily a combination of moderating gains in average hourly earnings (AHE) and weakness in employment. As shown in Chart 2, AHE have moderated to 3.5% year-over-year growth from 4.1% a year earlier. The yr/yr rise in AHE will decline further in the January and February 2026 readings as the high monthly increases in Jan-Feb 2025 roll off. At the same time, establishment payroll gains have flattened significantly. In the six months July-December 2025, employment rose a net 87,000, an average of 14k per month; in the prior six months jobs rose 497k, an average monthly rise of 82k (Chart 3). In the prior year ending December 2024, employment rose over 2 million.

State real GDP growth rates in 2025:3 ranged from 0.4% in North Dakota to 6.5% in Kansas. North Dakota’s performance was a major outlier (Minnesota was the next weakest state, with a 2.7% real growth rate) and appears largely attributable to a major, but localized, contraction in agricultural output. The vast majority of states had growth rates above 3.3% (in Massachusetts). Among larger states, Pennsylvania and North Carolina stood out with 5.6% growth rates (Michigan and Ohio were also above 5%0, while Florida’s rate was 3.5%. Manufacturing and finance were major contributors to growth, and states in the Midwest, as well as New York, benefitted from those.

Personal income growth rates ranged from 6.3% in Kansas to 0.1% in Louisiana. The weakness in Louisiana was due to an aberrant sharp contraction in transfer payments following very strong growth in the second quarter. On the flip side, gains in transfers played an outside role in New York’s 4.2% . Earnings growth was unusually high in Iowa and South Dakota; unusually low in Oklahoma.

The GDPNow model has several shortcomings, and here's an example. After the Census Bureau released October's construction spending data, the GDPNow model increased its Q4 GDP estimate to 5.4%, up from the previous 5.3%. However, a closer look at the detailed construction data suggests that the Q4 GDP estimate should have been revised downward, not upward. The GDPNow estimate for Q4 residential investment was adjusted from -5.7% to -1.0%. Yet, October's construction data indicates spending declines in new single and multi-family construction, alongside an increase in reported spending on remodeling and improvements. The latter relies on a survey that the BEA does not incorporate into its GDP calculations. Instead, the BEA uses retail spending data from building materials and hardware stores to estimate home modeling. In October, consumer spending in that retail category decreased by 1.3%.

In summary, GDPnow estimates have several shortcomings and should not be considered a definitive measure of economic activity.

Because the federal government was shut down in October the Bureau of Labor Statistics (BLS) did not conduct a survey of consumer prices that month but then reported two-month changes (for September-November) in prices with the following release of the Consumer Price Index (CPI). At the time I, in a commentary here (“A Dodgy CPI Rent Reading for November,” December 20, 2025), and others viewed the reported sharp two-month deceleration in the shelter component of the CPI with suspicion. Subsequent methodological clarifications from the BLS confirmed those concerns.

In October, for price levels not surveyed, the BLS assumed (unreported) changes of zero from September to October. In principle, with price levels then correctly measured in November, the two-month changes reported for September-November are correct. It is as if (implied) price increases in November include catch up effects, but with one important exception: rent.

The BLS stratifies its full panel of housing units into six subpanels that are surveyed in rotation. Each month the BLS assumes the monthly change in the shelter component of the CPI equals the sixth root of the six-month change in rent reported for the currently surveyed subpanel. Since a survey was not conducted during the shutdown, the BLS assumed that the rent for the subpanel that would have been surveyed in October was the same as in April when that subpanel was last surveyed. Because in October the six-month change in rent was thus assumed to be zero so, also, was the one-month change (i.e., the sixth root of zero).

The Federal Reserve Bank of Philadelphia’s state coincident indexes in November continued to be generally soft. In the one-month changes, Hawaii, Missouri, and Nevada had increases above .50 percent, but 12 were down, with West Virginia off by more than one percent. Over the three months ending in November, four states (Hawaii, Missouri, Iowa, and Alabama) had increases of 1.00 percent or more, while eight fell, with Montana and West Virginia seeing declines of more than one percent. Over the last twelve months, three states were down (Delaware by nearly 1 ½ percent), and seven others saw increases of less than one percent. Nine states saw increases of 3 percent or more, with Alabama’s 3.89 percent at the top.

The independently estimated national estimates of growth over the last three and twelve months were, respectively, .44 and 2.15 percent. The three=month reading seems to be in line with what the state numbers would have suggested, while the twelve-month one appears to be a bit lower.

Due to the absence of state unemployment rates for October, the indexes were computed using a modified method.