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...

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...

Over the recent decades researchers in academia and central banks have developed early warning systems (EWS) designed to warn policy makers of potential future economic and financial crises. These EWS are based on diverse approaches and empirical models. In this paper we compare the performance...

Building on the literature on systemic risk and financial contagion, the pa- per introduces estimated network linkages into an early-warning model to predict bank distress among European banks. We use multivariate extreme value theory to estimate equity-based tail-dependence networks, whose...