Systemic Risk Diagnostics

A macro-prudential policy maker can manage risks to financial stability only if current and future risks can be reliably assessed. We propose a novel framework to assess financial system risk. Using a dynamic factor framework based on state-space methods, we model latent macro-financial and credit risk components for a large data set comprising the U.S., the EU-27 area, and the rest of the world. Controlling for global, region-specific, and industry effects, we construct coincident measures ("thermometers") and forward looking indicators of financial distress and the likelihood of financial meltdown. We find that credit risk conditions can significantly and persistently de-couple from macro-financial fundamentals. Such decoupling can serve as an early warning signal for macro-prudential policy.