An Empirical Investigation of the Determinants of Banking Crises in the WAEMU using the BMA Approach

International Journal of Economics and Management Studies

© 2022 by SSRG - IJEMS Journal

Volume 9 Issue 3

Year of Publication : 2022

Authors : Kodjo W. Baoula

10.14445/23939125/IJEMS-V9I3P108

How to Cite?

Kodjo W. Baoula, "An Empirical Investigation of the Determinants of Banking Crises in the WAEMU using the BMA Approach," SSRG International Journal of Economics and Management Studies, vol. 9,  no. 3, pp. 60-70, 2022. Crossref, https://doi.org/10.14445/23939125/IJEMS-V9I3P108

Abstract:

The economic literature on methods for identifying the determinants of crisis risk in the banking sector presents important divergences; due to uncertainty regarding the choice of model and indicators. The objective of this paper is twofold: first, to identify the factors that expose the WAEMU banking sector to the risk of crises and second, to determine for these factors the critical threshold at which they become a source of triggering banking crises. To do this, we adopt an empirical approach based respectively on the Bayesian selection method (BMA) following Babecky et al. (2013) and a threshold effect model based on the Panel Threshold Regression (PTR) method of Hansen (1999), on a panel of seven WAEMU countries covering the period from 2000 to 2016. Our results show that the size of bank assets, foreign ownership, capital inflows and credit market regulation are factors that reduce the probability of a banking crisis; on the other hand, rates of private sector lending, public sector lending, delinquency and the level of corruption control are factors that contribute to the increased probability of banking crises in the WAEMU. Furthermore, our results reveal that among the eight indicators selected by the BMA method, three admit a critical threshold at which they become a source of triggering a banking crisis in WAEMU countries. These include the share of foreign capital, the rate of credit to the public sector and the corruption control index, for which we find a critical threshold of 80.83%, 6.27% and - 0.96, respectively.

Keywords:

Banking crises, Bayesian model, WAEMU.

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