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Working Paper
Financial Stability Implications of Generative AI: Taming the Animal Spirits
This paper investigates the impact of the adoption of generative AI on financial stability. We conduct laboratory-style experiments using large language models to replicate classic studies on herd behavior in investment decisions. Our results show that AI agents make more rational decisions than humans, relying predominantly on private information over market trends. Increased reliance on AI-powered investment advice could therefore potentially lead to fewer asset price bubbles arising from animal spirits that trade by following the herd. However, exploring variations in the experimental ...
Working Paper
Cyber Vulnerabilities at Large US Financial Institutions and Their Third-Party Service Providers
This paper examines cyber vulnerabilities across the 100 largest US banks, non-bank financial institutions (NBFIs), and their third-party service providers. Our analysis, based on a proprietary cyber risk analytics model, shows NBFIs exhibit greater cyber vulnerabilities than banks, though banks face larger relative losses from routine incidents. We identify third-party service providers as a hidden cyber fault line in the financial system, often having greater vulnerabilities than the institutions they serve and creating systemic risks. Scenario analyses of catastrophic cyber events ...
Working Paper
LLM on a Budget: Active Knowledge Distillation for Efficient Classification of Large Text Corpora
Large Language Models (LLMs) are highly accurate in classification tasks, however, substantial computational and financial costs hinder their large-scale deployment in dynamic environments. Knowledge Distillation (KD) where a LLM ""teacher"" trains a smaller and more efficient ""student"" model, offers a promising solution to this problem. However, the distillation process itself often remains costly for large datasets, since it requires the teacher to label a vast number of samples while incurring significant token consumption. To alleviate this challenge, in this work we explore the ...
Working Paper
Do Anecdotes Matter? Exploring the Beige Book through Textual Analysis from 1970 to 2025
We apply various natural language processing tools to see if the Beige Book is helpful in understanding economic activity. The Beige Book is a gathering of anecdotal compilations of current economic conditions from each Federal Reserve Bank, which is released to the public prior to FOMC meetings. We find that even controlling for lagged GDP growth and other metrics, the Beige Book sentiment provides meaningful explanatory power in nowcasting GDP growth and forecasting recessions, even more so than the yield spread or other news sentiment measures. The results on economic activity even hold in ...
Working Paper
The Credit Crunch and Fall in Employment during the Great Recession
We study the existence and economic significance of bank lending channels that affect employment in U.S. manufacturing industries. In particular, we address the question of how a dramatic worsening of firm and consumer access to bank credit, such as the one observed over the Great Recession, translates into job losses in these industries. To identify these channels, we rely on differences in the degree of external finance dependence and of asset tangibility across manufacturing industries and in the sensitivity of these industries' output to changes in the supply of consumer credit. We show ...
Working Paper
Risk Taking and Low Longer-term Interest Rates: Evidence from the U.S. Syndicated Loan Market
We use supervisory data to investigate risk taking in the U.S. syndicated loan market at a time when longer-term interest rates are exceptionally low, and we study the ex-ante credit risk of loans acquired by different types of lenders, including banks and shadow banks. We find that insurance companies, pension funds, and, in particular, structured-finance vehicles take higher credit risk when investors expect interest rates to remain low. Banks originate riskier loans that they tend to divest shortly after origination, thus appearing to accommodate other lenders' investment choices. These ...
Working Paper
Mapping Heat in the U.S. Financial System
We provide a framework for assessing the build-up of vulnerabilities in the U.S. financial system. We collect forty-four indicators of financial and balance-sheet conditions, cutting across measures of valuation pressures, nonfinancial borrowing, and financial-sector health. We place the data in economic categories, track their evolution, and develop an algorithmic approach to monitoring vulnerabilities that can complement the more judgmental approach of most official-sector organizations. Our approach picks up rising imbalances in the U.S. financial system through the mid-2000s, presaging ...
Working Paper
Bank capital ratios and the structure of nonfinancial industries
We exploit variation in commercial bank capital ratios across states to identify the impact of commercial bank balance sheet pressures manifested through changes in capital ratios on employment in the manufacturing sector. For industries dependent on external finance, we find that an increase in the capital ratio has no statistically significant effect on net firm creation, but has an economically significant impact on average firm size, as measured in the number of employees. Our findings indicate a lack of substitutes for bank funding both in the short and long run. This lack of substitutes ...
Working Paper
Estimating changes in supervisory standards and their economic effects
The disappointingly slow recovery in the U.S. from the recent recession and financial crisis has once again focused attention on the relationship between financial frictions and economic growth. With bank loans having only recently started growing and still sluggish, some bankers and borrowers have suggested that unnecessarily tight supervisory policies have been a constraint on new lending that is hindering recovery. This paper explores one specific aspect of supervisory policy: whether the standards used to assign commercial bank CAMELS ratings have changed materially over time (1991-2011). ...
Working Paper
The U.S. Syndicated Loan Market : Matching Data
We introduce a new software package for determining linkages between datasets without common identifiers. We apply these methods to three datasets commonly used in academic research on syndicated lending: Refinitiv LPC DealScan, the Shared National Credit Database, and S&P Global Market Intelligence Compustat. We benchmark the results of our match using results from the literature and previously matched files that are publicly available. We find that the company level matching is enhanced by careful cleaning of the data and considering hierarchical relationships. For loan level matching, a ...