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

65 Pages Posted: 17 Jun 2020

See all articles by Elena Afanasyeva

Elena Afanasyeva

Board of Governors of the Federal Reserve System

Date Written: June, 2020

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 VAR, Conditional forecast, Credit boom, Credit gap, Early warning, Financial crisis

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

Suggested Citation

Afanasyeva, Elena, Can Forecast Errors Predict Financial Crises? Exploring the Properties of a New Multivariate Credit Gap (June, 2020). FEDS Working Paper No. 2020-045, Available at SSRN: https://ssrn.com/abstract=3628497 or http://dx.doi.org/10.17016/FEDS.2020.045

Elena Afanasyeva (Contact Author)

Board of Governors of the Federal Reserve System ( email )

20th Street and Constitution Avenue NW
Washington, DC 20551
United States

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