Mortgage Rate Intelligence & Market Updates

We recently updated the suite of indicators describing the performance of small businesses in the Second District (defined, for the purpose of this study, as New York, New Jersey, and Connecticut) and nationally with data from the 2025 edition of the Small Business Credit Survey (SBCS). In this post, we find that regional small businesses reported severe declines in employment and revenue growth in 2025 and became more pessimistic about growth in 2026. In contrast, small firms in the rest of the nation enjoyed stable revenues and employment in 2025 and, while they also had lower expectations of future growth, the decline was smaller in magnitude. Given the importance of small businesses in employment generation, analyzing such data helps to inform the design of effective monetary policy and to understand trends in the regional economy.

Youth unemployment has risen dramatically since the pandemic—as has the prevalence of remote work. Our analysis suggests that these trends are related, with remote work making it more difficult for managers to train and mentor new employees. Accordingly, companies may be reluctant to hire less-experienced workers in distributed work arrangements. We estimate that remote work can explain 64 percent of the recent increase in unemployment among young college graduates. Further, the timing of this surge suggests that remote work—not generative AI—explains the bulk of the rise in youth unemployment.

In this post, we use the inaugural release of our regional consumer spending indicators to ask whether these patterns hold for a significant portion of the Second District, and how regional spending patterns by income have been similar to or different from the national patterns we documented earlier. We find similar K‑shaped patterns in both retail and gas spending in our region as we do in the nation, with the K‑shaped pattern in gasoline in response to the recent gas price shock being more pronounced in the region.

Current discussions regarding a bifurcated U.S. economy highlight the increasing economic divide between lower- and higher-income Americans in spending and earnings growth and wealth accumulation. While many households are doing fine and economic activity overall has been expanding at a solid pace, large segments of the population are facing high levels of economic insecurity and financial strain, and consumer sentiment on the whole has dropped to low levels. In this post, we use newly collected data from the Survey of Consumer Expectations (SCE) to update our 2020 analysis of disproportionate financial hardship experienced during the early pandemic and to investigate recent changes in food insecurity and broader economic strains. We then examine how food insecurity relates to the increase in consumer pessimism. We find a remarkable increase in food insecurity, particularly among lower-educated and lower-income households and households with young children. We document a contemporaneous increase in pessimism among the same groups, along with a sharp decline in job-finding expectations.

Economists often look at nominal wage growth to gauge labor market imbalances, price pressures, and households’ spending ability. But to use wage growth for these purposes, it is important to look through short-run fluctuations and retrieve underlying wage inflation. In this post, we use our own measure of wage growth persistence—called Trend Wage Inflation (TWIn in short)—to summarize what we learned from wage growth behavior in the past years and draw conclusions for what may lie ahead. Since peaking in late 2021, TWIn has been on a steady decline, reaching levels near those of the 2017-19 period. In the past few months, however, this decline seems to have lost momentum. Our analysis shows that most of the decline in TWIn between 2022 and 2025 was common across industries. Recently, however, a few sectors have shown a decoupling of wage growth dynamics.

In the third quarter of 2025, America’s largest tech firms for the first time spent more on capital investment than they earned from operations. The implication is that AI, a technology with the potential to make the economy more productive, is, for now, absorbing resources faster than it is generating returns. This post discusses how the tension between AI’s long-run promise and its short-run costs affects the outlooks for inflation, real activity, and financial stability.

The global corporate nonfinancial bond market is both a large investment asset class and a vital source of funding for nonfinancial firms. With $19 trillion outstanding at the end of 2024, a broad portfolio of corporate bonds would be expected to be well diversified. Yet, in 37 percent of months between 1998 and 2024, more than 80 percent of bonds in the ICE Global Bond Indices—a portfolio with over 10,000 constituents spanning diverse industries, credit ratings, and regions—moved in the same direction, suggesting a large degree of synchronization. In this post, we introduce the global credit factor, which proxies for the global price of risk in international corporate bond markets. The global credit factor creates a global credit cycle in bond risk premia and generates predictable comovement in bond prices.

Foreign holdings of U.S. financial assets are immense, with official estimates putting their current market value at $69 trillion. U.S. holdings of foreign assets are also impressive but much smaller, at $41 trillion. The shortfall in U.S. foreign assets relative to foreign liabilities has been mounting for decades. Yet U.S. investment income receipts—in profits, dividends, and interest—comfortably exceeded income payments until recently. We show that the fading of the net investment income surplus stems from the upward shift in interest rates in the aftermath of the pandemic along with the continued net sales of U.S. assets to foreign investors.

As generative AI tools become more widely used, a key issue is the technology’s impact on labor demand. Where might we find evidence of that impact? In this post, we examine whether early evidence of AI’s effect on the labor market appears in firms’ job postings. We combine an occupational measure of AI exposure with detailed U.S. job-posting data from Lightcast, which aggregates listings from company career pages, national and local job boards, and job-listing aggregators. Using this data, we test whether postings for AI-exposed occupations declined disproportionately since the release of ChatGPT in late 2022. We find that, while overall hiring has slowed since then, the evidence from job postings provides little indication of a distinct AI-driven decline in labor demand.