Constructing a banking fragility index for Islamic banks: definition impact on the predictive power of an early warning system

ABSTRACT

This study aims to construct a banking sector fragility index for Islamic banks that gives substantial predictive power results. We develop various banking sector fragility indices using different combinations of proxies for credit, liquidity and market risk factors. Apart from the existing literature, we add profitability risk factor into fragility indices. Our results show that the predictive power of an Early Warning System (EWS) is highly sensitive to the proxies and combinations of the risk factors and, profitability risk has a positive impact on the predictive power results for Islamic banks.

KEYWORDS:

• Early warning systems
• banking crises
• Islamic banking
• banking fragility

JEL CLASSIFICATION:

• G21
• C51

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ Bahrain, Bangladesh, Brunei Darussalam, Indonesia, Jordan, Kuwait, Malaysia, Pakistan, Qatar, Saudi Arabia, Turkey, UAE. The country set was selected based on the criteria of having the highest ‘share of global Islamic banking assets ratio’ among the countries that provide Islamic banking services. Accordingly, the main factor for a country to be included in the dataset was to have a minimum 10% share of Islamic banking assets in its total domestic banking sector assets. For the share of global Islamic banking assets ratio, Islamic Financial Services Industry Stability Report (2019) of Islamic Financial Services Board was utilized. However, due to data availability problem, we had to exclude some countries even if they matched with our criteria (i.e. Iran and Oman). The banks are selected considering data availability and, the banks that stopped their activities before 2018 are excluded from the dataset.

² μ and σ is the mean and standard deviation of the proxies.

³ We rely on Hausman test results where we reject the null hypothesis of there is a no correlation between the error terms and the regressors in the model and, employ fixed effects in order to remedy unobserved heterogeneity among different countries.

⁴ As Faizulayev, Bektas, and Ismail (2020) mentioned CAR measures the resilience of banks in case of unexpected risks and losses and this ratio reveals the importance of underlying stability of banks.