10 posts from "February 2026"
February 25, 2026
The Post‑Pandemic Global R*
In this post we provide a measure of “global” r* using data on short- and long-term yields and inflation for several countries with the approach developed in “Global Trends in Interest Rates” (Del Negro, Giannone, Giannoni, and Tambalotti). After declining significantly from the 1990s to before the COVID-19 pandemic, global r* has risen but remains well below its pre-1990s level. These conclusions are based on an econometric model called “trendy VAR” that extracts common trends across a multitude of variables. Specifically, the common trend in real rates across all the countries in the sample is what we call global r*. The post is based on the discussion of an insightful paper by Lukasz Rachel on the drivers of r* presented at the Brookings Papers on Economic Activity Fall 2025 conference.
February 24, 2026
Estimating the Term Structure of Corporate Bond Risk Premia
Understanding how short- and long-term assets are priced is one of the fundamental questions in finance. The term structure of risk premia allows us to perform net present value calculations, test asset pricing models, and potentially explain the sources of many cross-sectional asset pricing anomalies. In this post, I construct a forward-looking estimate of the term structure of risk premia in the corporate bond market following Jankauskas (2024). The U.S. corporate bond market is an ideal laboratory for studying the relationship between risk premia and maturity because of its large size (standing at roughly $16 trillion as of the end of 2024) and because the maturities are well defined (in contrast to equities).
February 19, 2026
What Workplace Composition Are Job Candidates Looking For?
Why do workers still segregate by sex across occupations, industries, and firms? Recent research has focused on how preferences for job amenities, like flexibility, may differ by sex. However, one “amenity” that has received relatively little attention is the sex composition of a job itself. In a recent paper, I conducted a survey experiment to estimate men’s and women’s preferences for sex composition in the workplace. One result is that women and young single men prefer jobs with at least half female coworkers.
February 17, 2026
Seeing Through the Shutdown’s Missing Inflation Data
Data releases for inflation have been scarce over the past four months due to the government shutdown. As a result, until January 22 no personal consumer expenditures (PCE) data were available beyond September and the consumer price index (CPI) had many missing entries for the one-month changes for October and November. In this post, we use an extended version of the New York Fed’s Multivariate Core Trend (MCT) inflation model to examine changes in underlying inflation over this period. The MCT model is well-suited to do so because it decomposes sectoral inflation rates into a trend (“persistent”) and a transitory component. In contrast to core (ex-food and energy) inflation, its aim is to remove all transitory factors, thus identifying the underlying trend. In addition, since the model can handle missing data—like for October—it can produce values for trend inflation for months where little or no data were released. Our findings suggest caution: while the fragmented data from November initially signaled a deceleration in price pressures, the integration of December data indicates that these reductions were largely transitory. Once the full data set is used, the aggregate trend for December stands at 2.83 percent, an increase from 2.55 percent in September.
February 12, 2026
Who Is Paying for the 2025 U.S. Tariffs?
Over the course of 2025, the average tariff rate on U.S. imports increased from 2.6 to 13 percent. In this blog post, we ask how much of the tariffs were paid by the U.S., using import data through November 2025. We find that nearly 90 percent of the tariffs’ economic burden fell on U.S. firms and consumers.
February 10, 2026
Where Are Mortgage Delinquencies Rising the Most?
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.
February 5, 2026
Does the Phillips Curve Steepen When Costs Surge?
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.
February 4, 2026
Anatomy (not Autopsy) of the Phillips Curve
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.
February 3, 2026
New York Fed EHIs Reveal Small Business Struggles
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.
Posted at 10:01 am in Employment, New Jersey, New York, Regional Analysis | Permalink | Comments (0)
A New Dataset for Consumer Spending in the New York Fed EHIs
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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