Credit Growth, the Yield Curve and Financial Crisis Prediction: Evidence from a Machine Learning Approach
65 Pages Posted: 23 Nov 2021
Date Written: November 1, 2021
We develop early warning models for financial crisis prediction by applying machine learning techniques to macrofinancial data for 17 countries over 1870–2016. Most nonlin-ear machine learning models outperform logistic regression in out-of-sample predictions and forecasting. We identify economic drivers of our machine learning models using a novel framework based on Shapley values, uncovering nonlinear relationships between the predic-tors and crisis risk. Throughout, the most important predictors are credit growth and the slope of the yield curve, both domestically and globally. A flat or inverted yield curve is of most concern when nominal interest rates are low and credit growth is high.
Keywords: credit growth, machine learning, Shapley values, yield curve, ﬁnancial crises, ﬁnancial stability
JEL Classification: C40, C53, E44, F30, G01
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