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Predicting bank insolvency in the Middle East and North Africa

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  • Calice, Pietro

Abstract

This paper uses a panel of annual observations for 198 banks in 19 Middle East and North Africa countries over 2001-12 to develop an early warning system for forecasting bank insolvency based on a multivariate logistic regression framework. The results show that the traditional CAMEL indicators are significant predictors of bank insolvency in the region. The predictive power of the model, both in-sample and out-of-sample, is reasonably good, as measured by the receiver operating characteristic curve. The findings of the paper suggest that banking supervision in the Middle East and North Africa could be strengthened by introducing a fundamentals-based, off-site monitoring system to assess the soundness of financial institutions.

Suggested Citation

  • Calice, Pietro, 2014. "Predicting bank insolvency in the Middle East and North Africa," Policy Research Working Paper Series 6969, The World Bank.
    • Handle: RePEc:wbk:wbrwps:6969
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    References listed on IDEAS

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    2. Anggraeni, Anggraeni & Mongid, Abdul & Suhartono,, 2020. "Prediction Models for Bank Failure: ASEAN Countries," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 54(2), pages 41-51.
    3. Chebbi, Ali & Hedhli, Amel, 2022. "Revisiting the accuracy of standard VaR methods for risk assessment: Using the Copula–EVT multidimensional approach for stock markets in the MENA region," The Quarterly Review of Economics and Finance, Elsevier, vol. 84(C), pages 430-445.

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    Keywords

    Banks&Banking Reform; Bankruptcy and Resolution of Financial Distress; Access to Finance; Financial Crisis Management&Restructuring; Debt Markets;
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