9 posts from "September 2025"
September 30, 2025
Calming the Panic: Investor Risk Perceptions and the Fed’s Emergency Lending during the 2023 Bank Run
In a companion post, we showed that during the bank run of spring 2023 investors were seemingly not concerned about bank risk broadly but rather became sensitized to the risk of only about a third of all publicly traded banks. In this post, we investigate how the Federal Reserve’s liquidity support affected investor risk perceptions during the run. We find that the announcement of the Fed’s novel Bank Term Funding Program (BTFP), and subsequent borrowings from the program, substantially reduced investor risk perceptions. However, borrowings from the Fed’s traditional discount window (DW) had no such effect.
Reading the Panic: How Investors Perceived Bank Risk During the 2023 Bank Run
The bank run that started in March 2023 in the U.S. occurred at an unusually rapid pace, suggesting that depositors were surprised by these events. Given that public data revealed bank vulnerabilities as early as 2022:Q1, were other market participants also surprised? In this post, based on a recent paper, we develop a new, high-frequency measure of bank balance sheet risk to examine how stock market investors’ risk sensitivity evolved around the run. We find that stock market investors only became attentive to bank risk after the run and only to the risk of a limited number (less than one-third) of publicly traded banks. Surprisingly, investors seem to have mostly focused on media exposure and not fundamentals when evaluating bank risk. In a companion post, we examine how the Federal Reserve’s liquidity support affected investor risk perceptions.
September 24, 2025
The Financial Stability Implications of Tokenized Investment Funds
In a previous post, we provided background information about the emergence of tokenized investment funds and their use cases. These use cases are currently limited to the digital asset ecosystem. However, the recent approval of cryptocurrency exchange-traded funds (ETFs) and the passage of the GENIUS Act raise concerns about the impact of these tokenized investment fund to the broader financial system. In this post, we assess this impact by considering three economic mechanisms based in part on market participants’ investment strategies and liquidity needs. They include: liquidity transformation, interconnections between the digital asset and the traditional financial system, and transaction settlement. Through these mechanisms, tokenization of investment funds can bring about financial stability benefits in the form of reduced redemption pressures and additional sources of liquidity for fund issuances, but may also increase interconnectedness between the traditional financial system and digital asset ecosystem, thereby amplifying existing financial stability risks.
The Emergence of Tokenized Investment Funds and Their Use Cases
A blockchain is a distributed database where independent computers across the world maintain identical copies of a transaction record, updating it only when the network reaches consensus on new transactions—making the history transparent and extraordinarily difficult to alter. Historically, bonds have traded almost entirely in over-the-counter (OTC) markets, while equities and money market fund shares have largely settled through centralized infrastructures such as stock exchanges and central securities depositories. In both settings, each institution maintains its own records, and post-trade steps like confirmation, clearing, and settlement require multiple intermediaries and repeated reconciliation.
September 22, 2025
Financial Intermediaries and Pressures on International Capital Flows
Global factors, like monetary policy rates from advanced economies and risk conditions, drive fluctuations in volumes of international capital flows and put pressure on exchange rates. The components of international capital flows that are described as global liquidity—consisting of cross-border bank lending and financing of issuance of international debt securities—have sensitivities to risk conditions that have evolved considerably over time. This risk sensitivity has been driven, in part, by the composition and business models of the financial institutions involved in funding. In this post, we ask whether these same features have led to changes in the pressures on currency values as risk conditions evolve. Using the Goldberg and Krogstrup (2023) Exchange Market Pressure (EMP) country indices, we show that the features of financial institutions in the source countries for international capital do influence how destination countries experience currency pressures when risk conditions change. Better shock-absorbing capacity in financial institutions moderates the pressures toward depreciation of currencies during adverse global risk events.
Posted at 7:00 am in Bank Capital, Exchange Rates, Financial Institutions, International Economics, Systemic Risk | Permalink | Comments (0)
September 19, 2025
The New York Fed DSGE Model Forecast—September 2025
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 June 2025. To summarize, the model expects growth in 2025 to be stronger, and inflation lower, than in June. Moreover, the model’s predictions for the short-run real natural rate of interest (r*) have increased relative to June throughout the forecast horizon, partly reflecting the strength in the economy and the buoyant financial conditions.
September 4, 2025
Are Businesses Scaling Back Hiring Due to AI?
The swift advancement of artificial intelligence (AI) has sparked significant concern that this new technology will replace jobs and stifle hiring. To explore the effects of AI on employment, our August regional business surveys asked firms about their adoption of AI and if they had made any corresponding adjustments to their workforces. Businesses reported a notable increase in AI use over the past year, yet very few firms reported AI-induced layoffs. Indeed, for those already employed, our results indicate AI is more likely to result in retraining than job loss, similar to our findings from last year. That said, AI is influencing recruiting, with some firms scaling back hiring due to AI and some firms adding workers proficient in its use. Looking ahead, however, layoffs and reductions in hiring plans due to AI use are expected to increase, especially for workers with a college degree.
September 3, 2025
Economic Capital: A New Measure of Bank Solvency
Bank supervisors, industry analysts, and academic researchers rely on a range of metrics to track the health of both individual banks and the banking system as a whole. Many of these metrics focus on bank solvency—the likelihood that a bank will be able to repay its obligations and thus retain its funding and continue to supply services to consumers, businesses, and other financial institutions. We draw on our recent research to describe a new solvency metric that is more forward-looking, more timely, and more comprehensive in its assessment of solvency than many current measures.
Posted at 7:00 am in Bank Capital | Permalink
September 2, 2025
What Is Natural Disaster Clustering—and Why Does It Matter for the Economy?
Understanding the economic and financial consequences of natural disasters is a major concern for researchers and policymakers. The way in which overlapping natural disaster systems interact, as exemplified by the recent fires in Los Angeles being exacerbated by strong winds, is a major area of study in environmental science but has received comparatively little attention in the economics literature. Examining these potential interactions would likely be important for financial institutions, since such assessments would, in many instances, increase the estimated financial impact of a given natural disaster. In our recent Staff Report, we develop a method of identifying disaster systems in natural disaster data, such as the Spatial Hazard Events and Loss Database (SHELDUS), and use it to argue that the economics and finance literatures may have overlooked some sources of systemic risk.
Posted at 7:00 am in Macroeconomics | Permalink
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