Real-Time Signals Anticipating Credit Booms in Euro-Area Countries

Abstract

This paper identifies credit booms in 11 Euro Area countries by tracking private loans from the banking sector. The events are associated with both financial crises and specific macro fluctuations, but the standard identification through threshold methods does not allow to catch credit booms in real time data. Thus, an early warning model is employed to predict the explosive dynamics of credit through several macro-financial indicators. The model catches a large part of the in-sample events and signals correctly both the global financial crisis and the sovereign debt crisis in an out-of-sample setting by issuing signals in real-time data. Moreover, while tranquil booms are driven by global dynamics, crisis-booms are related to the resilience of domestic banking systems to adverse financial shocks. The results suggest an ex-ante policy intervention can avoid dangerous credit booms by focusing on the solvency of the domestic banking system and financial market's overheating.