At the New York Fed, our mission is to make the U.S. economy stronger and the financial system more stable for all segments of society. We do this by executing monetary policy, providing financial services, supervising banks and conducting research and providing expertise on issues that impact the nation and communities we serve.
Can bank failures be predicted before they happen? In a previous post, we established three facts about failing banks that indicated that failing banks experience deteriorating fundamentals many years ahead of their failure and across a broad range of institutional settings. In this post, we document that bank failures are remarkably predictable based on simple accounting metrics from publicly available financial statements that measure a bank’s insolvency risk and funding vulnerabilities.
Why do banks fail? In a new working paper, we study more than 5,000 bank failures in the U.S. from 1865 to the present to understand whether failures are primarily caused by bank runs or by deteriorating solvency. In this first of three posts, we document that failing banks are characterized by rising asset losses, deteriorating solvency, and an increasing reliance on expensive noncore funding. Further, we find that problems in failing banks are often the consequence of rapid asset growth in the preceding decade.
Letters of recommendation from faculty advisors play a critical role in the job market for Ph.D. economists. At their best, they can convey important qualitative information about a candidate, including the candidate’s potential to generate impactful research. But at their worst, these letters offer a subjective view of the candidate that can be susceptible to conscious or unconscious bias. There may also be similarity or affinity bias, a particularly difficult issue for the economics profession, where most faculty members are white men. In this post, we draw on our recent working paper to describe how recommendation letters differ by the gender, race, or ethnicity of the job candidate and how these differences are related to early career outcomes.
Rapid GDP growth, due in part to high rates of investment and capital accumulation, has raised China out of poverty and into middle-income status. But progress in raising living standards has lagged, as a side-effect of policies favoring investment over consumption. At present, consumption per capita stands some 40 percent below what might be expected given China’s income level. We quantify China’s consumption prospects via the lens of the neoclassical growth model. We find that shifting the country’s production mix toward consumption would raise both current and future living standards, with the latter result owing to diminishing returns to capital accumulation. Chinese policy, however, appears to be moving in the opposite direction, to reemphasize investment-led growth.
U.S. household debt balances grew by $147 billion (0.8 percent) over the third quarter, according to the latest Quarterly Report on Household Debt and Credit from the New York Fed’s Center for Microeconomic Data. Balances on all loan products recorded moderate increases, led by mortgages (up $75 billion), credit cards (up $24 billion), and auto loans (up $18 billion). Meanwhile, delinquency rates have also risen over the past two years, returning to roughly pre-pandemic levels (and exceeding them in the case of credit cards and auto loans), though there are some signs of stabilization this quarter. Are rising aggregate debt burdens sustainable? Or is this expansion to be expected given increases in aggregate income and population size? In this post, we take a look at debt balances scaled by income, tracking the evolution of this ratio over the past twenty-five years.
After a period of relative stability, a series of bank failures in 2023 renewed questions about the fragility of the banking system. As in previous years, we provide in this post an update of four analytical models aimed at capturing different aspects of the vulnerability of the U.S. banking system using data through 2024:Q2 and discuss how these measures have changed since last year.
A central use of reserves held at Federal Reserve Banks (FRBs) is for the settlement of interbank obligations. These obligations are substantial—the average daily total reserves used on two main settlement systems, Fedwire Funds and Fedwire Securities, exceeds $6.5 trillion. The total amount of reserves needed to efficiently settle these obligations is an active area of debate, especially as the Federal Reserve’s current quantitative tightening (QT) policy seeks to drain reserves from the financial system. To better understand the use of reserves, in this post we examine the intraday flows of reserves over Fedwire Funds and Fedwire Securities and show that the mechanics of each settlement system result in starkly different intraday demands on reserves and differing sensitivities of those intraday demands to the total amount of reserves in the financial system.
As central banks shrink their balance sheets to restore price stability and phase out expansionary programs, gauging the ampleness of reserves has become a central topic to policymakers and academics alike. The reason is that the ampleness of reserves informs when to slow and then stop quantitative tightening (QT). The Federal Reserve, for example, implements monetary policy in a regime of ample reserves, whereby the quantity of reserves in the banking system needs to be large enough such that everyday changes in reserves do not cause large variations in short-term rates. The goal is therefore to implement QT while ensuring that reserves remain sufficiently ample. In this post, we review how to gauge the ampleness of reserves using the new Reserve Demand Elasticity (RDE) measure, which will be published monthly on the public website of the Federal Reserve Bank of New York as a standalone product.
While policies to combat climate change are designed to address a global problem, they are generally implemented at the national level. Nevertheless, the impact of domestic climate policies may spill over internationally given countries’ economic and financial interdependence. For example, a carbon tax charged to domestic firms for their use of fossil fuels may lead the firms to charge higher prices to their domestic and foreign customers; given the importance of global value chains in modern economies, the impact of that carbon tax may propagate across multiple layers of cross-border production linkages. In this post, we quantify the spillover effects of climate policies on forward-looking asset prices globally by estimating the impact of carbon price shocks in the European Union’s Emissions Trading System (EU ETS) on stock prices across a broad set of country-industry pairs. In other words, we measure how asset markets evaluate the impact of changes to the carbon price on growth and profitability prospects of the firms.
A key question in economic policy is how labor market tightness affects wage inflation and ultimately prices. In this post, we highlight the importance of two measures of tightness in determining wage growth: the quits rate, and vacancies per searcher (V/S)—where searchers include both employed and non-employed job seekers. Amongst a broad set of indicators, we find that these two measures are independently the most strongly correlated with wage inflation. We construct a new index, called the Heise-Pearce-Weber (HPW) Tightness Index, which is a composite of quits and vacancies per searcher, and show that it performs best of all in explaining U.S. wage growth, including over the COVID pandemic and recovery.
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