Working Paper

Can Forecast Errors Predict Financial Crises? Exploring the Properties of a New Multivariate Credit Gap

Abstract: Yes, they can. I propose a new method to detect credit booms and busts from multivariate systems -- monetary Bayesian vector autoregressions. When observed credit is systematically higher than credit forecasts justified by real economic activity variables, a positive credit gap emerges. The methodology is tested for 31 advanced and emerging market economies. The resulting credit gaps fit historical evidence well and detect turning points earlier, outperforming the credit-to-GDP gaps in signaling financial crises, especially at longer horizons. The results survive in real time and can shed light on the drivers of credit booms.

Keywords: Bayesian VARs; conditional forecasts; Credit boom; Credit gap; Early warning; Financial crisis;

JEL Classification: C11; C13; C53; E51; E58;

https://doi.org/10.17016/FEDS.2020.045

Bibliographic Information

Provider: Board of Governors of the Federal Reserve System (U.S.)

Part of Series: Finance and Economics Discussion Series

Publication Date: 2020-06-12

Number: 2020-045