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Working Paper
Mapping Heat in the U.S. Financial System
Palumbo, Michael G.; Lee, Seung Jung; Warusawitharana, Missaka; Aikman, David; Kiley, Michael T. (2015-06-24)
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 ...
Finance and Economics Discussion Series , Paper 2015-59

Working Paper
Sentiment in Bank Examination Reports and Bank Outcomes
Cowhey, Maureen; Lee, Seung Jung; Popeck Spiller, Thomas; Vojtech, Cindy M. (2022-11-17)
We investigate whether the bank examination process provides useful insight into bank future outcomes. We do this by conducting textual analysis on about 5,500 small to medium-sized commercial bank examination reports from 2004 to 2016. These confidential examination reports provide textual context to the components of supervisory ratings: capital adequacy, asset quality, management, earnings, and liquidity. Each component is given a categorical rating, and each bank is assigned an overall composite rating, which are used to determine the safety and soundness of banks. We find that, ...
Finance and Economics Discussion Series , Paper 2022-077

Working Paper
Financial Stability Implications of Generative AI: Taming the Animal Spirits
Lundgaard Hansen, Anne; Lee, Seung Jung (2025-09-26)
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 ...
Finance and Economics Discussion Series , Paper 2025-090

Working Paper
Estimating changes in supervisory standards and their economic effects
Spiller, Thomas W.; Lee, Seung Jung; Bassett, William F. (2012)
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). ...
Finance and Economics Discussion Series , Paper 2012-55

Working Paper
Sowing the Seeds of Financial Imbalances: The Role of Macroeconomic Performance
Afanasyeva, Elena; Modugno, Michele; Lee, Seung Jung; Jerow, Sam (2020-04-07)
The seeds of financial imbalances are sown in times of buoyant economic growth. We study the link between macroeconomic performance and financial imbalances, focusing on the experience of the United States since the 1960s. We first follow a narrative approach to review historical episodes of significant financial imbalances and find that the onset of financial disturbances typically occurs when the economy is running hot. We then look for evidence of a statistical link between measures of macroeconomic conditions and financial imbalances. In our in-sample analysis, we find that strong ...
Finance and Economics Discussion Series , Paper 2020-028

Working Paper
Identifying Financial Crises Using Machine Learning on Textual Data
Chen, Mary; DeHaven, Matthew; Kitschelt, Isabel; Lee, Seung Jung; Sicilian, Martin (2023-03-31)
We use machine learning techniques on textual data to identify financial crises. The onset of a crisis and its duration have implications for real economic activity, and as such can be valuable inputs into macroprudential, monetary, and fiscal policy. The academic literature and the policy realm rely mostly on expert judgment to determine crises, often with a lag. Consequently, crisis durations and the buildup phases of vulnerabilities are usually determined only with the benefit of hindsight. Although we can identify and forecast a portion of crises worldwide to various degrees with ...
International Finance Discussion Papers , Paper 1374

Journal Article
Profits and balance sheet developments at U.S. commercial banks in 2009
Rose, Jonathan D.; Lee, Seung Jung (2010-05)
Reviews recent developments in the balance sheets and in the profitability of U.S. commercial banks. The article discusses how developments in the U.S. banking industry in 2009 and early 2010 were related to changes in financial markets and in the broader economy.
Federal Reserve Bulletin , Volume 96 , Issue May , Pages A1-37

Working Paper
Bank capital ratios and the structure of nonfinancial industries
Stebunovs, Viktors; Lee, Seung Jung (2012)
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 ...
Finance and Economics Discussion Series , Paper 2012-53

Working Paper
The U.S. Syndicated Loan Market: Matching Data
Sicilian, Martin; Shaton, Maya; Hayes, William; Friedrichs, Melanie; Gupta, Kamran; Mislang, Nathan; Lee, Seung Jung; Cohen, Gregory J.; Marsh, W. Blake (2018-12-03)
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 ...
Research Working Paper , Paper RWP 18-9

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