To make high-quality research more accessible and easier to explore.

Fields:
2 results ✕ Clear filters

Inflation volatility effects on the allocation of bank loans

Journal of Financial Stability 2016 24, 27-39
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.

Analyzing and forecasting China's financial resilience: Measurement techniques and identification of key influencing factors

Journal of Financial Stability 2025 76, 101372
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.