A machine learning approach to rank the determinants of banking crises over time and across countries-Reference-Cited by-同舟云学术

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

Published:2022-12 Issue: Volume:129 Page:102739
ISSN:0261-5606
Container-title:Journal of International Money and Finance
language:en
Short-container-title:Journal of International Money and Finance

Author:

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

Funder

Università di Bologna

Publisher

Elsevier BV

Subject

Economics and Econometrics,Finance

Reference61 articles.

1. Quasi real time early warning indicators for costly asset price boom/bust cycles: a role for global liquidity;Alessi;Eur. J. Polit. Econ.,2011

2. Identifying excessive credit growth and leverage;Alessi;J. Financ. Stabil.,2018

3. Bankruptcy forecasting: an empirical comparison of AdaBoost and neural networks;Alfaro;Decis. Support Syst.,2008

4. Predicting bankruptcy of local government: a machine learning approach;Antulov-Fantulin;J. Econ. Behav. Organ.,2021

5. Arteta, C., Eichengreen, B., 2000. Banking crises in emerging markets: presumptions and evidence. Center for International and Development Economics Research (CIDER) Working Papers, C00-115, August.

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