Two perspectives on bank liquidity and interest rate sensitivity
Two papers published in June 2025 provide complementary insights into how interest rates affect bank stability through different liquidity channels. Bräuning and Ivashina examine the asset side, showing that higher rates reduce credit line drawdowns and stabilize banks, while Blickle, Li, Lu, and Ma focus on the liability side, demonstrating that higher rates can destabilize banks by triggering deposit runs, especially following quantitative easing (QE). Together, these studies reveal the complex, bidirectional effects of monetary policy on banking sector stability.
Paper 1 (Bräuning & Ivashina) asks: How does interest rate sensitivity affect revolving credit line utilization during periods of banking sector stress? The authors focus on the “asset side” of bank liquidity, examining how firms’ decisions to draw down credit lines respond to interest rate changes.
Paper 2 (Blickle et al.) investigates: How does deposit flightiness vary over time and what are its implications for bank runs and monetary policy? This study examines the “liability side,” analyzing how depositor behavior and sensitivity to interest rates evolve over time and affect financial stability.
Data sources and sample periods
Bräuning & Ivashina utilize the FR Y-14Q supervisory dataset (data collected by the Federal Reserve for stress testing purposes, as mandated by the
2010 Dodd-Frank Act) covering facility-level data on commercial and industrial (C&I) loans from 2011-2023, with primary focus on the COVID period (2019q4-2020q4). This dataset covers approximately 70% of all C&I loans in the United States and provides detailed information on committed and utilized credit line exposures.
Blickle et al. employ multiple complementary datasets: Call Reports data (2000-2023), the Complex Institution Liquidity Monitoring Report (FR2052) for deposit counterparty analysis, and novel transaction-level data from over 1,400 U.S. banks. This comprehensive approach allows them to examine deposit dynamics across different time periods and depositor types.
Identification Strategies
Bräuning & Ivashina use a Regression Kink Design (RKD) that exploits interest rate floors in credit line contracts. When LIBOR falls below contractual floors, the applicable rate becomes insensitive to further LIBOR changes, creating a “kink” that provides exogenous variation for identifying interest rate sensitivity. This approach is particularly innovative because it doesn’t require interest rates themselves to be exogenous.
Blickle et al. implement rolling window instrumental variable regressions using fixed costs and salary expenses per unit of assets as supply-side instruments for deposit rates. The authors estimate deposit flow sensitivities over 8-quarter windows to capture how depositor responsiveness to rate changes evolves over time.
Empirical models
Bräuning & Ivashina estimate piecewise regressions around the interest rate floor kink:
– For facilities above the floor: utilization responds to rate changes
– For facilities at the floor: utilization insensitive to rate changes
– The difference in slopes identifies the causal effect of rates on credit line usage
Blickle et al. estimate time-varying deposit flow sensitivities through:
– Bank-level deposit flows regressed on instrumented deposit rates
– Rolling window estimation to capture temporal variation
– Cross-sectional analysis of depositor heterogeneity using transaction-level data
Key Findings
Credit line sensitivity (Bräuning & Ivashina)
The most striking finding is that credit line utilization is highly sensitive to interest rates. The authors document that a 1 percentage point increase in interest rates leads to an 8.2 percentage point decrease in line utilization (their conservative estimate during COVID). Outside the COVID period, they find even larger effects of up to 30 percentage points.
This sensitivity operates through a cost channel: higher interest rates increase the cost of precautionary drawdowns, making firms less likely to draw on credit lines preemptively. During COVID, firms initially drew heavily on credit lines in March 2020 due to uncertainty, then repaid these drawdowns in subsequent quarters as conditions stabilized.
Deposit flightiness dynamics (Blickle et al.)
The second paper reveals that deposit flightiness varies dramatically over time, reaching unprecedented levels before the 2022 rate hike cycle. Key findings include:
– Deposit flow sensitivities increased sharply after 2008, fell around 2015, then surged to historical highs in early 2020
– QE attracts flightier depositors: Reserve expansions draw investors who value deposit convenience less and are more rate-sensitive
– Heterogeneous deposit types: Corporate deposits are more volatile than retail deposits; non-operational accounts more volatile than operational accounts
The authors develop a dynamic model showing that when flightier depositors enter the banking system (as during QE), the marginal depositor becomes more rate-sensitive, amplifying run risk during subsequent rate hikes.
The papers identify opposing forces during monetary policy changes:
- Stabilizing force (Bräuning & Ivashina): Higher rates reduce credit line utilization by making precautionary drawdowns more expensive, reducing liquidity pressure on banks.
- Destabilizing force (Blickle et al.): Higher rates trigger deposit outflows, especially from flighty depositors attracted during QE periods, increasing liquidity pressure on banks.
These findings help explain the 2023 banking crisis: while high rates helped banks by reducing credit line risk, they simultaneously hurt banks by triggering deposit runs, with the net effect varying across institutions. Blickle et al. provide novel insights on policy implementation speed: gradual rate hikes are less destabilizing than sharp increases. Gradual increases allow flightier depositors to exit gradually, leaving more stable depositors in the banking system. This finding has important implications for Fed communication and policy sequencing.
Conclusion
The key insight is that the net effect depends on the composition of bank depositors and borrowers, which is endogenously determined by previous monetary policy actions. This suggests that policymakers must consider both sides of bank balance sheets and the path-dependent effects of previous policy interventions when designing monetary policy strategies.
(From Bräuning and Ivashina)
(From Blickle et al.)
Bank Runs and Interest Rates: A Revolving Lines Perspective
Authors: Falk Bräuning, Victoria Ivashina
From: Federal Reserve Bank of Boston, Harvard University
The Dynamics of Deposit Flightiness and its Impact on Financial Stability
Authors: Kristian Blickle, Jian Li, Xu Lu, Yiming Ma
From: Federal Reserve Bank of New York, Columbia University, University of Washington
