Credit growth, the yield curve and financial crisis prediction: Evidence from a machine learning approach - Kristina Bluwstein; Marcus Buckmann; Andreas Joseph; Sujit Kapadia; Özgür Şimşek (European Central Bank (ECB), 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: C40; C53; E44; F30; G01; 330; machine learning; financial stability; financial crises; credit growth; yield curve; Shapley values