This paper examines the distortionary effects of inflation volatility on the allocation of bank loans. We argue that inflation volatility would render bank managers to behave more conservatively in issuing new loans. In contrast, when inflation volatility is low, bank managers would have the latitude to lend more idiosyncratically. Using a large panel of commercial bank data gathered from 15 countries, we provide support for our hypothesis by demonstrating a strong negative relation between inflation volatility and the dispersion of loans-to-assets ratio. Similar results are obtained when we split the sample between EU and non-EU country groups. The robustness of our findings is confirmed by a battery of sensitivity checks.

This paper measures China's financial resilience from the perspective of external risk shocks and analyzes its influencing factors for forecasting. First, we introduce an innovative financial resilience model comprising three submodels: the dynamic factor model, the TVP-VAR model, and a resilience characteristic measurement model that captures resistance and recoverability through absorption intensity and absorption duration. The results show a clear inverse relationship between absorption intensity and absorption duration, with resilience fluctuations exhibiting distinct phase characteristics. Notably, intervals of low resilience often correspond to specific risk events. Second, we apply the Lasso-logistic model for recursive estimation and forecasting financial resilience, while comparing its performance to that of the Logistic regression model. The results indicate that the Lasso-logistic model achieves, on average, a 10 % higher forecasting accuracy than the Logistic model does. Among the most important features identified by the model are macroeconomic and public expectation variables. The analysis shows that the stability of economic fundamentals and market participants' confidence in the future play pivotal roles in strengthening financial resilience and ensuring the stability of the financial system.

Using experimental data, we document that the impact of professional norms on the risk-taking of bank employees depends on their expectations of peers’ risk preferences. When the professional identity of bank employees is made salient, those who expect colleagues to take more risk than themselves increase risky investments by 5.2% points in a mock investment task, while others do not statistically change their risk-taking behaviors. Data from placebo experiments with non-bank employees do not exhibit such empirical patterns. The results are consistent with peer effects and social identity theories, and challenge the existing evidence that professional norms in the banking industry decrease risk-taking.

We derive the default cascade model and the fire-sale spillover model in a unified interdependent framework. The interactions among banks include not only direct cross-holding, but also indirect dependency by holding mutual assets outside the banking system. Using data extracted from the European Banking Authority, we present the interdependency network composed of 48 banks and 21 asset classes. For the robustness, we employ three methods, called Anan, Hała and Maxe, to reconstruct the asset/liability cross-holding network. Then we combine the external portfolio holdings of each bank to compute the interdependency matrix. The interdependency network is much denser than the direct cross-holding network, showing the complex latent interaction among banks. Finally, we perform macroprudential stress tests for the European banking system, using the adverse scenario in EBA stress test as the initial shock. For different reconstructed networks, we illustrate the hierarchical cascades and show that the failure hierarchies are roughly the same except for a few banks, reflecting the overlapping portfolio holding accounts for the majority of defaults. We also calculate systemic vulnerability and individual vulnerability, which provide important information for supervision and relevant management actions.

Despite the significance of social networks in influencing firm behavior, research on their impact on corporate tax behavior is limited. In this paper, we construct social networks of CFOs from U.S. companies based on their employment history, education, and non-professional activities. We find that firms with more socially connected CFOs have lower effective tax rates (ETR) compared to firms with less socially connected CFOs. This effect is more pronounced when corporate governance is weaker and managers have higher incentives. Furthermore, a firm's ETR decreases as CFO centrality increases. We do not observe similar results regarding the connectedness of boards of directors. Additionally, firm pairs exhibit similar ETRs when their CFOs are socially connected, suggesting an exchange of tax-related information among CFOs through their social networks. We also find that the past ETRs of firms with central CFOs predict the ETRs of firms with non-central CFOs. This indicates that less socially connected CFOs tend to follow the tax planning strategies of their more socially connected counterparts. Overall, our findings indicate that more socially connected CFOs possess more relevant information and resources regarding tax planning, leading to the adoption of more aggressive tax strategies compared to their less socially connected counterparts.