Boom-bust cycles in real estate markets have been major factors in systemic financial crises and therefore need to be at the forefront of macroprudential policy. The geographically differentiated nature of real estate market fluctuations implies that these policies need to be granular across...

We propose the CoJPoD, a novel framework explicitly linking the cross-sectional and cyclical dimensions of systemic risk. In this framework, banking sector distress in the form of the joint probability of default of financial intermediaries (reflecting contagion from both direct and indirect...

We use financial accounts data at sector level to construct financial networks for individual euro area countries. We then connect the country-level networks to one large “Macro Network”, using information on cross-border linkages between the national banking sectors. We then evaluate the...

A financial stress index for the United States is introduced – an index that was used in real time by the staff of the Federal Reserve Board to monitor the financial crisis of 2008-9 – and the interaction with real activity, inflation and monetary policy is demonstrated using a richly...

In this study, we approximate the financial cycle in Europe by combining potential common and relevant financial indicators. We consider different credit aggregates and asset prices but also incorporate banking sector indicators for 11 European countries. We develop seven different synthetic...

Why did the shadow banking sectors in the US and the euro area expand in the decade before the financial crisis and what are the implications for systemic risk and macro-prudential policy? This paper examines these issues with a model of the financial sector where the size of the shadow banking...

We study the interaction between borrowers' and banks' solvency in a quantitative macroeconomic model with financial frictions in which bank assets are a portfolio of defaultable loans. We show that ex-ante imperfect diversification of bank lending generates bank asset returns with limited...

We develop early warning models for financial crisis prediction by applying machine learning techniques to macrofinancial data for 17 countries over 1870-2016. Most nonlin-ear machine learning models outperform logistic regression in out-of-sample predictions and forecasting. We identify...

The financial crisis has highlighted the need for models that can identify counterparty risk exposures and shock transmission processes at the systemic level. We use the euro area financial accounts (flow of funds) data to construct a sector-level network of bilateral balance sheet exposures and...

This paper analyzes the efficiency of risk-taking decisions in an economy that is prone to systemic risk, captured by financial amplification effects that occur in response to strong adverse shocks. It shows that decentralized agents who have unconstrained access to a complete set of Arrow...