The paper develops an early-warning model for predicting vulnerabilities leading to distress in European banks using both bank and country-level data. As outright bank failures have been rare in Europe, the paper introduces a novel dataset that complements bankruptcies and defaults with state...

We estimate a multivariate early-warning model to assess the usefulness of private credit and other macro-financial variables in predicting banking sector vulnerabilities. Using data for 23 European countries, we find that global variables and in particular global credit growth are strong...

This paper presents a new database for financial crises in European countries, which serves as an important step towards establishing a common ground for macroprudential oversight and policymaking in the EU. The database focuses on providing precise chronological definitions of crisis periods to...

We develop an integrated Early Warning Global Vector Autoregressive (EW-GVAR) model to quantify the costs and benefits of capital-based macroprudential policy measures. Our findings illustrate that capital-based measures are transmitted both via their impact on the banking system's resilience...

We estimate a multivariate early-warning model to assess the usefulness of private credit and other macro-financial variables in predicting banking sector vulnerabilities. Using data for 23 European countries, we find that global variables and in particular global credit growth are strong...

This paper proposes a framework for deriving early-warning models with optimal out-of-sample forecasting properties and applies it to predicting distress in European banks. The main contributions of the paper are threefold. First, the paper introduces a conceptual framework to guide the process...