Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
We present a new dataset on the dynamics of non-performing loans (NPLs) during 92 banking crises since 1990. The data show similarities across crises in NPL buildup but much heterogeneity in the pace of NPL resolution. We document how high and unresolved NPLs deepen post-crisis recessions and use a machine learning approach to establish pre-crisis predictors of NPL problems. These predictors—a set of weak macroeconomic, institutional, corporate, and banking sector conditions—help shed light on post-COVID-19 NPL vulnerabilities.