Optimizing Credit Gaps for Predicting Financial Crises: Modelling Choices and Tradeoffs
39 Pages Posted: 6 Feb 2019 Last revised: 22 Dec 2020
Date Written: January 1, 2019
Credit gaps are often used as early warning indicators (EWIs) for financial crises. We evaluate how the performance of credit-gap-based EWIs is influenced by the various modelling choices inherent in their design. For the most common trend-cycle decomposition methods used to recover credit gaps, we find that optimally smoothing the trend enhances out-of-sample prediction. Out-of-sample prediction improves further when we consider a preference for robustness of the credit gap estimates to the arrival of new information, which is important as any EWI should work in real-time. We offer several practical implications.
Keywords: Credit, Credit Gap, Optimization, Predictive Power, Robustness, Trend-Cycle Decomposition
JEL Classification: C22, E39, G28
Suggested Citation: Suggested Citation