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

Elena Afanasyeva

No 2020-045, Finance and Economics Discussion Series from Board of Governors of the Federal Reserve System (U.S.)

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 (search for similar items in EconPapers)
JEL-codes: C11 C13 C53 E51 E58 (search for similar items in EconPapers)
Pages: 65 p.
Date: 2020-06-12
New Economics Papers: this item is included in nep-mac
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:fip:fedgfe:2020-45

DOI: 10.17016/FEDS.2020.045

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