• Elizabeth Jane Casabianca | Promoteia, Università Politecnica delle Marche
• Michele Catalano | Prometeia, IIASA
• Lorenzo Forni | Prometeia, Department of Economics and Management of the University of Padua
• Elena Giarda | Prometeia, Università degli Studi di Modena e Reggio Emilia
• Simone Passeri | Prometeia

Machine learning is employed to rank the determinants of banking crises over time and across countries.

In this paper, the authors have carried out an analysis on 100 countries, advanced and emerging, from 1970 to 2017.

Their result show that US 10 yr Treasury interest rate and world growth play a key role in anticipating crises and that these variables explain a growing share of the results over time for all countries.

Read their "Journal of International Money and Finance" article here