What predicts financial (in)stability? A Bayesian approach

This paper contributes to the literature on early warning indicators by applying a Bayesian model averaging approach. Our analysis, based on Austrian data, is carried out in two steps: First, we construct a quarterly financial stress index (AFSI) quantifying the level of stress in the Austrian financial system. Second, we examine the predictive power of various indicators, as measured by their ability to forecast the AFSI. Our approach allows us to investigate a large number of indicators. The results show that excessive credit growth and high returns of banks' stocks are the best early warning indicators. Unstable funding (as measured by the loan to deposit ratio) also has a high predictive power.