This paper aims at providing policymakers with a set of early warning indicators helpful in guiding decisions on when to activate macroprudential tools targeting excessive credit growth and leverage. To robustly select the key indicators we apply the “Random Forest” method, which bootstraps...

Can the upturns and downturns in financial variables serve as early warning indicators of banking crises? Using data from 59 advanced and emerging economies, we show that financial overheating can be detected in real time. Equity prices and output gap are the best leading indicators in advanced...

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 technical note examines the macroprudential policy framework in the Czech Republic. The Czech National Bank (CNB) has been actively developing its macroprudential policy framework for some time, including most recently the establishment of a separate Financial Stability Department. The...

Successful implementation of macroprudential policy is contingent on the ability to identify and estimate systemic risk in real time. In this paper, systemic risk is defined as the conditional probability of a systemic banking crisis and this conditional probability is modeled in a fixed effect...

In recent years, machine learning techniques have assumed an increasingly central role in many areas of research, from computer science to medicine, including finance. In the current study, we applied it to financial literacy to test its accuracy, compared to a standard parametric model, in the...