Optimizing Credit Gaps for Predicting Financial Crises: Modelling Choices and Tradeoffs

40 Pages Posted: 23 Apr 2021

See all articles by Daniel O. Beltran

Daniel O. Beltran

Board of Governors of the Federal Reserve System

Mohammad R. Jahan-Parvar

Board of Governors of the Federal Reserve System

Fiona Paine

MIT Sloan Finance Group

Multiple version iconThere are 2 versions of this paper

Date Written: January 6, 2021

Abstract

Credit gaps are good predictors for financial crises, and banking regulators recommend using them to inform countercyclical capital buffers for banks. Researchers typically create credit gap measures using trend-cycle decomposition methods, which require many modelling choices, such as the method used, and the smoothness of the underlying trend. Other choices hinge on the tradeoffs implicit in how gaps are used as early warning indicators (EWIs) for predicting crises, such as the preference over false positives and false negatives. We evaluate how the performance of credit-gap-based EWIs for predicting crises is influenced by these modelling choices. 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. We also show that out-of sample performance 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

Beltran, Daniel O. and Jahan-Parvar, Mohammad R. and Paine, Fiona, Optimizing Credit Gaps for Predicting Financial Crises: Modelling Choices and Tradeoffs (January 6, 2021). Available at SSRN: https://ssrn.com/abstract=3832811 or http://dx.doi.org/10.2139/ssrn.3832811

Daniel O. Beltran (Contact Author)

Board of Governors of the Federal Reserve System ( email )

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Mohammad R. Jahan-Parvar

Board of Governors of the Federal Reserve System ( email )

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

HOME PAGE: http://sites.google.com/site/mrjahan/

Fiona Paine

MIT Sloan Finance Group ( email )

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