Mortgage Rate Intelligence & Market Updates

This post presents an update of the economic forecasts generated by the Federal Reserve Bank of New York’s dynamic stochastic general equilibrium (DSGE) model. We describe very briefly our forecast and its change since March 2026. To summarize, inflation forecasts are higher in 2026 than predicted in March. Projections for the short-run real natural rate of interest (r*) increased slightly relative to March.

Several states have recently capped consumer loan rates with the stated purpose of protecting borrowers. In a recent Staff Report, we study how these interventions have played out in three states. In our first post about that study, we showed that rate caps lead riskier borrowers to face rationing in the credit market. One question that naturally arises is what lenders do with the credit they used to provide to high-risk borrowers before the caps were imposed. Lenders that lend exclusively to high-risk borrowers (at rates above the cap) may decide to stop lending to high-risk borrowers in that state. Others, however, may try to change their “credit box” by lending more to somewhat safer borrowers. In this post, we will try to understand how lenders reallocate credit after usury limits are implemented.

In imperial China, 3 percent was the maximum legal monthly loan rate; charging more was punishable by 40 to 100 blows with the “light cane.” (Rockoff 2003) Centuries later, many U.S. states are imposing the same cap (without corporal penalties) on alternative credit providers, such as payday, installment, and auto-title lenders, with the goal of lowering credit costs and delinquency for the high-risk borrowers that rely on these funding sources. A concern, however, is that lenders will simply refuse to lend to these borrowers at lower interest rates. Our recent Staff Report studies how interest rate caps have played out in several states that recently adopted them. Using household-level data from a major credit bureau, we find that loan balances for the riskiest borrowers declined substantially relative to counterparts in states without caps. Despite taking on less debt, these borrowers did not experience an improvement in delinquencies.

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.