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

18218 8 98845 3 303560 document 98845 jimf-2022.pdf application/pdf 4f4747c98635fd5bdaedc898f63c8dfb MD5 1400620 2022-09-13 13:59:37 https://pure.iiasa.ac.at/id/eprint/18218/1/jimf-2022.pdf 18218 1 1 application/pdf text en public cc_by_nc_nd_4

jimf-2022.pdf

2024-09-07 accepted 98846 2 303566 document 98846 lightbox.jpg image/png 7e724e2251f6b1292d7cf9774e0df0e8 MD5 30598 2022-09-13 14:09:49 https://pure.iiasa.ac.at/id/eprint/18218/2/lightbox.jpg 18218 2 2 image/png other Thumbnails conversion from text to thumbnail_lightbox en staffonly

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/98845 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/98845 http://eprints.org/relation/isIndexCodesVersionOf https://pure.iiasa.ac.at/id/document/98845 archive 353 disk0/00/01/82/18 2022-09-13 14:02:02 2024-09-07 03:00:04 2022-09-13 14:02:02 article show Jane Casabianca E. Catalano M. 2355 Forni L. Giarda E. Passeri S. A machine learning approach to rank the determinants of banking crises over time and across countries pub ASA EM banking crises; predictive models; machine learning 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 10yr 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 present also extensions of the model, which confirm and add to the main results of the baseline model. 2022-09-07 published Elsevier doi:10.1016/j.jimonfin.2022.102739 3405 public Journal of International Money and Finance 129 e102739 TRUE 0261-5606 no info:eu-repo/semantics/article