Knowledge that Transforms

We develop a credit-risk based framework for macroprudential policy that treats systemic risk as the credit exposure of a policymaker to a portfolio of supervised banks. Using a structural credit model estimated from Credit Default Swap (CDS) prices, we derive the socially optimal capital buffers per bank by balancing the benefits of lower systemic risk against the economic costs of higher capital requirements through reduced credit supply. Applying this framework to Europe’s systemic banks, we find that the market-based optimal buffers are substantially higher than those currently in use and vary significantly across institutions. Conditional on current country averages, within-country buffers are aligned close to optimally; suboptimality mostly arises from substantial differences between country averages.

We develop a new way to measure evolving production networks in real time using financial news. Combining artificial intelligence with a structural propagation framework, we extract firm-level production linkages and study how changes in network architecture relate to future output. We show that economies with centralized production structures experience slow subsequent growth, while dense and dispersed structures are associated with stronger performance. The framework yields firm-level measures of systemic importance that can be used by regulators to monitor macroeconomic risks. Our results show that the architecture of the production network is a measurable and economically meaningful determinant of aggregate dynamics.

This study extends Acharya and Naqvi’s (2012) theory of liquidity-driven risk-taking to digital asset markets by examining the relationship between U.S. and Chinese excess-liquidity conditions and cryptocurrency returns. Using monthly panel data for ten major cryptocurrencies from 2019 to 2024, and defining excess liquidity and economic policy uncertainty (EPU) as binary state indicators, the baseline results show that periods of U.S. excess liquidity are associated with a 12.1 percentage-point increase in average monthly cryptocurrency returns. This liquidity-return premium is reduced by approximately 54% during episodes of rising U.S. EPU. Chinese excess-liquidity regimes are associated with a 9.3 percentage-point increase in monthly returns, but this positive association is more than offset under rising Chinese policy uncertainty, as indicated by a −13.8 percentage-point interaction effect. These findings are consistent with the interpretation that surplus-liquidity conditions coincide with stronger cryptocurrency returns, in line with risk-taking and stablecoin-based arbitrage channels, whereas rising-EPU regimes weaken the liquidity-return relationship by increasing risk aversion and reducing arbitrage efficiency. The results highlight a macro-financial channel through which liquidity conditions are linked to digital asset markets and suggest that regulators should monitor stablecoin issuance, leverage, funding conditions, and liquidity-driven speculative pressure in the crypto market.

This study examines how the introduction of China's deposit insurance system affects bank risk-taking, using panel data on 117 commercial banks from 2010 to 2023. Employing a theoretical framework together with system GMM and difference-in-differences estimations, we find that deposit insurance does not uniformly enhance stability; instead, it may increase idiosyncratic risk by weakening market discipline. The effect is concentrated among local commercial banks, with large commercial banks showing comparatively limited responses. Corporate governance and financial leverage serve as important transmission channels: banks with more concentrated ownership or higher leverage exhibit stronger moral hazard incentives following the reform. Robustness tests using the provision coverage ratio confirm these patterns. Overall, the results highlight the heterogeneous impact of deposit insurance across bank types and underscore the importance of governance quality and capital structure in mitigating risk-taking incentives under explicit insurance schemes.

Publisher Copyright: © 2026 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license. http://creativecommons.org/licenses/by/4.0/