Exchange-Rate Volatility and Financial Stability in the Banking Sector: Distributional Evidence from G7 and High-Income European Economies

The present study examined how volatility in exchange rates shapes banking-sector financial stability across the G7 and six high-income European countries, consisting of 13 developed economies. The study analyses the time period from 2000 to 2023. To measure volatility, the present study employed the GARCH(1,1) conditional variance of monthly real effective exchange rates. Stability is measured through the following two supporting indicators: Bank Z-score (solvency) and Non-Performing Loan (NPL) ratio (credit quality). Our analysis combines the Fully Modified OLS and two-step System GMM for analysing long-run and dynamic effects. To assess distributional heterogeneity, Method of Moments Quantile Regression (MMQR) is employed, while Dumitrescu–Hurlin tests are used for examining causality. The results show that volatility in exchange rates significantly reduces bank solvency and elevates credit risk. These effects are highly uneven: the adverse impact falls on the most fragile banking systems—those in the lower quantiles of the Z-score distribution and the upper quantiles of the NPL distribution. Causality runs unidirectionally, moving from volatility to instability. Institutional quality, which is proxied by the rule of law and regulatory quality, is seen to significantly decrease the credit-risk channel but not the solvency channel. Our findings provide implications for developed economies and support targeted, fragility-sensitive macro-prudential policy.