The Real-Time Information Content of Financial Stress and Bank Lending on European Business Cycles

We integrate newly created financial stress indices (FSIs) into an automated real-time recession forecasting procedure for the Euro area and Germany. The FSIs are based on a large number of financial indicators, each of them potentially signaling financial stress. A subset of these indicators is selected in real-time and their stress signal is summarized by principal component analysis (PCA). Besides conventional measures of realized financial stress, such as volatilities, we include variables related to the financial cycle, such as different types of credit growth, for which strong increases may anticipate future financial market stress. Building blocks in our fully automated real-time probit forecasts are then i. the use of a broad set of widely acknowledged macroeconomic and financial variables with predictive power for a real economic downturn, ii. the use of both general-to-specific and specific-to-general approaches for variable and lag selection, and iii. the averaging of different specifications into a composite forecast. As a real-time out-of-sample analysis shows, the inclusion of financial stress leads to an improved recession forecast for the Euro area, while the results for Germany are mixed. Finally, we also evaluate the predictive power of the change in bank lending (credit impulse) and find that it adds little additional information.