Predicting the Likelihood of Systematic Banking Crises in Selected Developing Countries (An Approach from the Multinomial Logit Model)

Document Type : Research Paper

Authors

1 Department of Economics, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran.

2 Associate Professor of Economics, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran

Abstract

The purpose of this article is to predict the likelihood of systematic banking crises in selected developing countries, so that economic policymakers can study and deal with this crisis and reduce the likelihood of its occurrence. For this purpose, 37 developing countries were selected and the probability of a banking crisis for the selected countries during the years 1994-2018 was estimated using the binary and multinomial logit model. The results showed that in the multinomial logit model, the percentage of correctly predicted critical periods is higher than in the binary logit model, and the multinomial logit model is more appropriate. The results of the multinomial logit model indicate the ineffectiveness of exchange rate deviation and the positive effect of inflation, real interest rate and trade relations on the probability of a banking crisis in the countries under study. Economic growth rate, per capita production and capital flow, and the ratio of the ratio of bank redits to private sector to production have had a negative effect on the likelihood of a banking crisis in the countries under study. The results also showed that the ratio of private sector credit to production was not a good predictor of the possibility of a banking crisis in the countries under study

Keywords

References

1. Abu Nouri, A, Mehregan, N, Safari, N, (2018), Identifying the factors affecting the probability of crises in the banking system of selected countries using the logit panel model, Economic Research and Policies, 26, 88, 38-7. (In Persain)
2. Ahmadian, A., Kianvand, M., (2014), The effect of banking regulations on bank profit margins (integration data approach), 1, 21, 15-28. (In Persain)
3. Bussiere, M. Fratzscher, M.(2006). Towards a new early warning system of financial crises.journal of International Money and Finance,25(6),953-973.
4. Bordo, M., Meissner, C. M. (2012). Does inequality lead to a financial crisis?. Journal of International Money and Finance, 31(8), 2147-2161.
5. Berg, A., Pattillo, C.(1999). Predicting Currency Crises: The Indicators Approach and an Alternative. Journal of International Money and Finance 18, 561–586.
6. Caggiano, G., Calice, P., Leonida, L. (2014). Early warning systems and systemic banking crises in low income countries: A multinomial logit approach. Journal of Banking & Finance, 47, 258-269.
7. Catao, L., Milessi-Ferretti, G.,(2013). External liabilities and crisis risk, IMF Working Paper No. 13/113.
8. Caprio, G., Klingebiel, D. (1996). Bank insolvency: bad luck, bad policy, or bad banking?.In Annual World Bank conference on development economics.
9. Cheong, C. W, Ramasamy, S.(2019). Bank Failure: A New Approach to Prediction and Supervision.
10. Cihák, M. M., Schaeck, K. (2007). Banking competition and capital ratios (No. 7-216). International Monetary Fund.
11. Calomiris, C., Mason, J. (2004). How to Restructure Failed Banking Systems: Lessons from the United States in the 1930s and Japan in the 1990s. In Governance, Regulation, and Privatization in the Asia-Pacific Region, 375-424.
12. Calomiris, C., Kahn, C. (1991). The role of demandable debt in structuring optimal banking arrangements. The American Economic Review, 497-513.
13. Claessens, S., & Kose, M. M. A. (2013). Financial crises explanations, types, and implications (No. 13-28). International Monetary Fund.
14. Davis, E. P., Karim, D. (2008). Comparing early warning systems for banking crises. Journal of Financial stability, 4(2), 89-120.
15. Demirgüç-Kunt, A., Detragiache, E.(2000).Monitoring banking sector fragility: a multivariate logit approach. The World Bank Economic Review, 14, 287-307.
16. Demirguc, A., Detragiache, E. (1998). The Determinants of Banking Crises inDeveloping and Developed Countries. IMF Staff Paper 45, 1.
17. Drehmann, M., Borio, C. E., Tsatsaronis, K. (2011). Anchoring countercyclical capital buffers: the role of credit aggregates.
8. Eijffinger, S. C, & Karatas, B. (2019). Together or apart? The
relationship between currency and banking crises. Journal of Banking &
Finance, 105631.
19. Fuertes, A., Kalotychou, E.(2007). Optimal Design of Early Warning Systems for Sovereign Debt Crises, International Journal of Forecasting, 23(1), 85-100.
20. Hahm, J. H., Shin, H. S., & Shin, K. (2013). Noncore bank liabilities and financial vulnerability. Journal of Money, Credit and Banking, 45(s1), 3-36.
21. Hamdaoui, M. (2016). Are systemic banking crises in developed and developing countries predictable?. Journal of Multinational Financial Management, 37, 114-138.
22. Kaminsky, G., (1998). Currency and Banking Crises: The Early Warnings ofDistress.International Finance Discussion Paper,629.
23. Laeven, L. and F. Valencia.(2012). Systemic Banking Crises Database: An Update.Washington: International Monetary Fund.
24. Moshiri, S., Nadali, M.,(2014), Identification of effective factors in the occurrence of banking crisis in the Iranian economy, Economic Research Journal, 13, 48, 27-1. (In Persain)
25. Minoiu, C., Reyes, J. A. (2011). A network analysis of global banking: 1978-2009. IMF Working Papers, 1-41.
 26. Musdholifah, M., Hartono, U., Wulandari, Y. (2020).  Banking Crisis Prediction: Emerging Crisis Determinants in Indonesian Banks. International Journal of Economics and Financial Issues, 2020, 10(2), 124-131.
27. Sarzaim, A., (2017), Typology of financial crises with emphasis on banking crises, Fiscal and Economic Policies, 5, 18, 208-187. (In Persain)
28. Shajari, P., Mohebikhah, B, (2010), Predicting Banking Crises and Balance Sheets Using the KLR Marking Method (Case Study: Iran), Money and Economics, 2, 4, 152-115. (In Persain)
29. The World Bank Annual Report 2012.
30. Von Hagen, J., Ho, T. K. (2007). Money market pressure and the determinants of banking crises. Journal of Money, Credit and Banking, 39(5), 1037-1066.
31. Zarei, J., Komijani, A., (2015), Identifying and Predicting Banking Crises in Iran, Economic Modeling, 9, 1, 29, 23-1. (In Persain)
Quarterly Journal of Applied Theories of Economics
Volume 7, Issue 4 - Serial Number 27
February 2021
Pages 117-138

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