Viewpoints

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.

US voters have not waited for midterm elections—or even a full year—to register their dissatisfaction with Donald Trump’s turbulent return to office. In November last year, Democrats swept key state races in New York, Virginia, and New Jersey. The message from voters was unmistakable: rising living costs and the impact of higher import tariffs are biting hard.

The affordability crisis is already reshaping America’s political landscape. The Financial Times examined the soaring cost of living in New York and the unexpected election of Zohran Mamdani, the 34-year-old Democrat to the office of the mayor. The numbers tell a stark story. Average childcare costs approach US$1,450 per month, yet only 14.5% of New York families can afford them. More than half of renter households spend at least 30% of their income on rent, and between 60,000 and 80,000 New Yorkers sleep in shelters every night.

And New York is far from an outlier.

Recently, a close friend visited us from Boston, and conversation inevitably turned to expenses. Even mundane purchases now come with sticker shock. A simple lunch—sandwiches for two—costs US$30 to US$35. When her German Shepherd needed an X-ray, the bill came to US$1,300; a CT scan was offered for US$3,000. Removing 11 trees from her garden cost US$9,000. She and her husband work in finance and are relatively affluent, so these examples are anecdotal—but they vividly illustrate how sharply costs have risen across the US.

When she insisted on picking up the lunch tab during her visit to the UK, we did not feel too guilty. At £54 with wine (US$71), it was a bargain, even after accounting for the US dollar’s depreciation against sterling.

Both the Financial Times article and these conversations raise important questions. How widespread is the cost-of-living squeeze? How much pressure is Trump under to deliver on his MAGA agenda? And how constrained is the Federal Reserve as it balances rising inflation against already-stretched households?

Income and Spending: A Divided Country

In 2024, the average American took home US$64,426 after taxes, according to data from the Bureau of Economic Analysis (Figure 1). Per capita disposable income exceeded that level in just 18 states. The District of Columbia topped the list at US$92,365, followed by Connecticut at US$80,694. In contrast, residents in 33 states earned less than the national average. Mississippi ranked last at US$47,831, with West Virginia close behind at US$50,444.

If you rely on the GDP estimates from the Federal Reserve Bank of Atlanta's team, the US economy is performing the improbable by growing well beyond its potential, despite two key sectors experiencing no growth and minimal new job creation. The Atlanta Fed's GDPnow estimate suggests that Q4 GDP growth is at an annualized rate of 5.1%. However, that estimate of output growth is at odds with the weak growth picture depicted by data from manufacturing, housing, and employment. That data indicates that GDP growth is occurring at, at best, half the rate.

The US economy is composed of three primary sectors: goods, structures, and services. The Federal Reserve's industrial production metric shows that manufacturing output in Q4 through November is lower than in Q3, suggesting minimal, if any, growth in goods output for Q4.

The structures component includes three sectors: housing, nonresidential, and state and local. Housing starts in October are significantly below the Q3 average, indicating a decrease in residential construction activity. Nonresidential construction has been weak throughout 2025, with data indicating a decline in Q4. Meanwhile, state and local construction spending shows minimal growth. Thus, the structures component is likely to weigh on Q4 GDP.

This leaves the service sector, the largest of the three. The service sector doesn't seem to be expanding rapidly enough to support the GDPNow estimate either. For instance, private sector service job growth amounted to just 112,000 in the three months ending in December.

Moreover, for the GDP output to increase by more than 5%, the income side must show a similar rise. However, the data on jobs, wages, and hours indicate a very modest increase in labor income in Q4. To align with the GDP output growth estimate, there would need to be an extraordinary increase in operating profits to offset the weak labor income. Companies would have to register a record increase in margins to do that, which is unlikely given the price data.

The government shutdown, which lasted over 40 days, affected and delayed several economic reports to such an extent that it's currently very challenging to obtain a reliable assessment of the Q4 economic performance. Nevertheless, if the data on jobs, manufacturing, and housing accurately represent the situation, then GDPnow is more than 50% off.

November was another soft month for state labor markets. No state had a statistically significant change in payroll employment, though the raw increases in California (32,500). New York (17,100), as well as the decline in Illinois (9,700) look to be of some note. However, no state appears to have had a change as large as .2 percent. In the October numbers, the federal cuts were reflected in large, most likely statistically significant, drops in DC, Maryland, and Virginia.

State unemployment rates in November were generally, though not universally, higher in November than in September (there are no unemployment figures for October, due to the federal government shutdown). Delaware and West Virginia’s unemployment rates were .4 percentage points higher in November than in September, and a number of other states saw increases of .3 percentage points. Hawaii’s rate dropped .3 percentage points. The highest unemployment rates were in DC (6.5%), California (5.5%), New Jersey (5.4%), Nevada (5.2%), New Jersey (5.2%), Oregon (5.2%), and Michigan (5.0%). Alabama, Hawaii, North Dakota, South Dakota, and Vermont had unemployment rates under 3.0%, while South Dakota’s 2.1% was the lowest in the nation.

Puerto Rico’s unemployment rate was unchanged at 5.7% (remarkably, there is an October unemployment rate estimate for Puerto Rico) and the island’s job count rose by 1,700.

With the passage of the One Big Beautiful Bill Act (OBBBA) of 2025, already high US federal budget deficits will rise even higher than projected by the Congressional Budget Office (CBO) at the beginning of the year. One element contributing to the rise in the deficits will be interest on the public debt. With the Treasury’s policy of shortening the maturity of the public debt and the politicization of the Fed, I fear that the US government will effectively default on its debt via inflation.

Plotted in the chart below are fiscal year (FY) ratios of federal net interest payments on the public debt to federal net revenues (blue bars) along with end-of-quarter 3-month Treasury bill rates and 10-year Treasury yields. In FY 2025, the ratio of net interest on the public debt to federal net revenues was 5.4, the lowest in the post-WWII era and the lowest since FY 1991, when interest rates were almost twice the level they are now. You can think of the ratio of net interest to net revenues as similar to a corporation’s interest coverage. The CBO forecasts that with the passage of OBBBA, net interest will increase by $4.7 trillion starting in FY 2026 through FY 2029. Unless there is a Festivus miracle resulting in a commensurate increase in federal net revenues, the federal government’s interest coverage will fall below that of an already low FY 2025’s.

On December 18 the Bureau of Labor Statistics (BLS) released the Consumer Price Index (CPI) for November. In October, when the federal government was partially shut down, BLS did not conduct its survey of prices, leaving most of them unrecorded for that month. Therefore, rather than reporting the usual 1-month percent changes in prices for November, BLS reported 2-month percent changes instead. For example, from September to November, the core CPI advanced at a 1% annualized rate – a surprisingly benign reading that, if accurate, significantly improves the current narrative on inflation and strengthens the case for easier monetary policy.

Unfortunately, the potential impact of the shutdown on both the quality and timing of the November survey raises legitimate concerns about the reliability of its results. One particularly dodgy-looking element of the report was a quite sharp deceleration in the CPI for shelter, the 2-month annualized percent change of which dropped from 3.9% in September to just 1.1% in November (gold line in chart). An erroneous reading here could be of considerable importance given that shelter costs comprise nearly 18% of “core” personal consumption expenditures.

The CPI-shelter reflects rents on tenant- and owner-occupied housing units. Imputed rents on owner-occupied units are inferred from observed rents on nearby comparable tenant-occupied units. Because shelter costs reflect average rents, they are highly inertial, lagging well behind current (i.e., marginal) market conditions for two reasons. First, rental contracts typically are for one year, requiring twelve months for all contracts to reflect a change in market conditions. Second, the BLS rotates through a panel of renters over a period of six months, adding another half year to the lag between marginal and average rents.

However, these lags allow one empirically to relate the CPI-shelter to current and past new rental contracts. I did so by estimating a model that explains the CPI-shelter with current and lagged values of Zillow indices of observed newly contracted rents. These indices are available monthly through November. I then used that model to forecast the shelter costs for the months of October and November. The resulting projection of the 2-month change in the CPI-shelter is shown in the blue line in the chart.

The model suggests that from September through November the CPI-shelter grew at an annualized rate of 2.9%, 1.8 percentage points faster than the number published by BLS. To me, the projection seems more believable than the reported figure. Replacing the latter with the former raises the 2-month annualized change in the core CPI by approximately 0.3 percentage points, to 1.3% - still a good reading, but not as good. And, of course, all this makes one wonder about the reliability of estimates of other prices in the report. So, before concluding prematurely that inflation is quiescent, it makes sense for one to await additional months of readings.

For all the talk of a weakening labor market, the wage bill for private nonfarm employees (private nonfarm employees times their average weekly earnings) has risen at annualized rates of 5.85% and 5.91% in October and November, respectively, compared to the median increase of 5.75% in the eleven moths of 2025. If these data are valid, it would seem that labor market earnings are growing relatively fast, especially in light of all the talk of a weak labor market. Why would employers be increasing the labor wage bill so rapidly if labor demand were weak? Perhaps because the labor supply is shrinking.

We have been overweight Korean equities this year—and it has paid off, handsomely. The allocation decision was anchored in the business-cycle framework: three of five key indicators pointed clearly toward expansion at the start of the year. The cost of capital was supportive, the credit cycle was in a firm upswing, and money-supply growth was accelerating. The corporate profit cycle, though still technically in downturn, was already showing improvement thanks to strong balance sheets. The major drag was the investment cycle, which continued to lag.

What has surprised us is the speed of the profit-cycle recovery, especially against the year’s backdrop. From Trump’s tariff war to domestic political turbulence following the impeachment of President Yoon Suk-yeol and the snap elections in June, one would have expected a more cautious rebound. Instead, the listed sector delivered a solid performance. Return on equity averaged 7% in the first three quarters, up from 5.6% a year earlier and nearly back to the seven-year average of 7.3%. EBITDA cash flow per share, free cash flow per share, and retained earnings all advanced. EBITDA rose almost 20% year-on-year, cash flow per share climbed 29%, and free cash flow per share swung decisively into positive territory.

Central-bank data paint a similarly encouraging picture. Profitability and interest-coverage ratios have improved markedly for large corporates, even as debt-to-capital ratios inched higher. SMEs have seen some deterioration, but the stress is neither systemic nor alarming at this stage.

And yet, despite these solid fundamentals, Korea Inc has continued to err on the side of caution (Figure 1). Companies tightened spending this year and delayed new investment plans. As a result, the investment cycle slid deeper into downturn: real spending on both facilities and construction has contracted for six consecutive quarters. Rather than expand capacity, firms have chosen to run down inventories and utilise existing manufacturing facilities more intensively. Operating rates have increased, allowing companies to meet rising shipments without committing fresh capital.