Where Are Mortgage Delinquencies Rising the Most?
Andrew F. Haughwout, Donghoon Lee, Daniel Mangrum, Joelle W. Scally, and Wilbert van der Klaauw
The Federal Reserve Bank of New York’s Center for Microeconomic Data recently released its Quarterly Report on Household Debt and Credit for the fourth quarter of 2025, revealing continued growth in household debt balances. Aggregate household debt balances rose by $191 billion to reach $18.8 trillion, marking a $4.6 trillion increase since the end of 2019. Mortgage balances grew by $98 billion to $13.2 trillion, while credit card debt increased by $44 billion to $1.28 trillion. Credit card and auto loan delinquency rates appear to have stabilized, albeit at elevated rates. By contrast, the delinquency rate for mortgages—although still near low levels on a longer-term basis—has been steadily increasing over the past few years. Underlying these aggregate figures, however, there are notable differences in mortgage credit performance across places with different income levels and labor and housing market dynamics. This analysis, as well as the Quarterly Report on Household Debt and Credit, are based on anonymous credit report data from Equifax.
Does the Phillips Curve Steepen When Costs Surge?
Simone Lenzu
Inflation does not always respond to cost and demand pressures in the same way. When shocks are small, the mapping from costs to prices is roughly proportional—double the shock, double the inflation response. But when the economy is hit by large shocks, this proportionality breaks down. As the recent surge and subsequent decline of global inflation showed, price growth can accelerate—or decelerate—by more than one-for-one relative to the size of the disturbance. Economists refer to this pattern as nonlinear inflation dynamics. In this post, I discuss what these nonlinearities mean, how they relate to the slope of the Phillips curve discussed in a companion post, and how firm-level data can help us understand the mechanisms behind them.
Anatomy (not Autopsy) of the Phillips Curve
Simone Lenzu
The relationship between inflation and real economic activity has long been central to debates in macroeconomics and monetary policy. At the core of this debate is the Phillips curve (PC), which measures how strongly inflation reacts to movements in economic conditions. The steepness of this curve matters enormously for monetary policy: if the PC is steeper, inflation rises faster during booms and falls faster in recessions, which entails central banks having to act more forcefully if they want to stabilize inflation around their target. Prior analysis found astonishingly small estimates of the slope of the PC, which suggests that the curve is “flat” (or even dead). In this post, I present evidence from coauthored research showing that, contrary to the conventional view, the Phillips curve is alive and steep, and it captures inflation volatility remarkably well once real marginal cost is used instead of standard real economic activity measures.
New York Fed EHIs Reveal Small Business Struggles
Will Aarons and Asani Sarkar
The New York Fed’s Economic Heterogeneity Indicators (EHIs) aim to study macroeconomic outcomes experienced by various groups of people and businesses. We recently added a suite of indicators describing the performance of small businesses to the EHIs—both for the region (defined, for the purpose of this study, as New York, New Jersey, and Connecticut) and nationally. Small businesses are critical to employment generation as they accounted for almost 63 percent of new private sector jobs since 2005 and employed almost 46 percent of all U.S. workers in 2025. Thus, understanding economic trends and impacts for small businesses is important for designing effective monetary policy and aligns with the New York Fed’s mission to support the regional economy. In this post, we highlight some aspects of small business profitability, revenues, employment, and indebtedness since 2019 for firms of different sizes.
A New Dataset for Consumer Spending in the New York Fed EHIs
Rajashri Chakrabarti, Thu Pham, Beck Pierce, and Maxim L. Pinkovskiy
We are enhancing our set of Economic Heterogeneity Indicators (EHIs) by adding a set of metrics on consumer spending with data presented by income, education, race and ethnicity, age, and urban status. The data will help track the evolution of aggregate behavior by analyzing the spending of specific groups in a more timely manner than is possible using public surveys.
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