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A machine learning approach to rank the determinants of banking crises over time and across countries

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  • Casabianca, Elizabeth Jane
  • Catalano, Michele
  • Forni, Lorenzo
  • Giarda, Elena
  • Passeri, Simone

Abstract

We use a machine learning approach, namely AdaBoost, to rank the determinants of banking crises over time and across countries. We cover a total of 100 countries, advanced and emerging, over the years from 1970 to 2017. The paper first shows that AdaBoost has a better predictive performance than the logit model, both in-sample and out-of-sample; then, it employs AdaBoost to classify the major macroeconomic factors leading to banking crises. The baseline analysis reveals that the US 10 yr Treasury interest rate and world growth play a key role in anticipating a crisis, and that these two variables explain a growing share of the results over time, for both country groups. Other variables, which have been highlighted as important in the literature on crises - such as inflation, current account, public and external debt and credit - are relevant in the lead up to banking crises, but their role has been decreasing over time compared to the aforementioned variables. We also present extensions of the model, which confirm and add to the main results of the baseline model.

Suggested Citation

  • Casabianca, Elizabeth Jane & Catalano, Michele & Forni, Lorenzo & Giarda, Elena & Passeri, Simone, 2022. "A machine learning approach to rank the determinants of banking crises over time and across countries," Journal of International Money and Finance, Elsevier, vol. 129(C).
  • Handle: RePEc:eee:jimfin:v:129:y:2022:i:c:s0261560622001425
    DOI: 10.1016/j.jimonfin.2022.102739
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    Cited by:

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    More about this item

    Keywords

    Banking crises; Predictive models; Machine learning;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G01 - Financial Economics - - General - - - Financial Crises
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

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