Islamic Banks and Financial Stability: An Empirical Analysis

Abstract

The relative financial strength of Islamic banks is assessed empirically based on evidence covering individual Islamic and commercial banks in 19 banking systems with a substantial presence of Islamic banking. We find that (a) small Islamic banks tend to be financially stronger than small commercial banks; (b) large commercial banks tend to be financially stronger than large Islamic banks; and (c) small Islamic banks tend to be financially stronger than large Islamic banks, which may reflect challenges of credit risk management in large Islamic banks. We also find that the market share of Islamic banks does not have a significant impact on the financial strength of other banks.

Appendix II: data issues

Our initial sample covered banks in the following 20 countries and jurisdictions (alphabetically ordered): Bahrain, Bangladesh, Brunei, Egypt, Gambia, Indonesia, Iran, Jordan, Kuwait, Lebanon, Malaysia, Mauritania, Pakistan, Qatar, Saudi Arabia, Sudan, Tunisia, United Arab Emirates, West Bank and Gaza, and Yemen.

Our calculations are based on individual bank data drawn from the BankScope database, provided by Bureau van Dijk. We use annual data on all Islamic and commercial banks in the database from the above 20 countries. In total, we have up to 520 observations for 77 Islamic banks (and 3,248 observations for 397 comparable commercial banks) over a period of 1993 to 2004. However, BankScope does not have a sufficient number of observations for Islamic banks for Lebanon , so these countries are excluded from the regression analysis, bringing the number of countries on which the aggregate results are based from 20 to 19. Even after the exclusions, Islamic banks included in the panel have total assets of US$253 billion as of 2004, which is in line with the “about US$250 billion” estimated worldwide assets of Islamic banks (see, e.g., El Qorchi 2005).

We use consolidated data when available, but when consolidated data are not available for a bank, we use unconsolidated data instead.

To classify whether a bank is commercial or Islamic, we have used the BankScope classification as a starting point. BankScope defines as Islamic banks that are members of the “International Association of Islamic Banks” plus 20 non-member banks that are considered to be “Islamic” by FitchRatings. However, we have found that in several cases, BankScope misclassifies Islamic banks as commercial, and vice versa. Therefore, we have cross-checked the BankScope classification with the information available from the FSAP exercises in the relevant countries, the information available on the respective banks’ websites, and the list of Islamic banks provided by the Institute of Islamic Banking and Insurance at http://www.islamic-banking.com/ibanking/ifi_list.php and by IBF.net at http://islamic-finance.net/bank.html.

In all calculations, large banks are defined as those with total assets of more thanUS$1 billion. All other banks are classified as small banks.

The table on the following two pages describes the individual variables used in the paper and their sources.

Variable	Description	Source
Z-score	Defined as ${\hbox{z}} \equiv \left( {k + \mu } \right)/\sigma$, where k is equity capital as percent of assets, μ is average return as percent of assets, and σ is standard deviation of return on assets as a proxy for return volatility. Measures the number of standard deviations a return realization has to fall in order to deplete equity, under the assumption of normality of banks’ returns.	Authors’ calculations based on BankScope data.
Assets_bln	Total assets of a bank (In U.S. dollars billion).	BankScope.
Loans_assets	Ratio of loans to assets (percent).	BankScope.
Cost_income	Ratio of cost to income (percent).	BankScope.
Income diversity	$1 - \left| {\frac{{\left( {Net\;{\rm int} erest\;income - Other\;operating\;income} \right)}}{{Total\;operating\;income}}} \right|$	Authors’ calculations based on Laeven and Levine (2007) and BankScope.
Income diversity* Islamic bank dummy	Interaction of income diversity and Islamic bank dummy.	Authors’ calculations based on BankScope.
Herfindahl index	Sum of squared market shares of banks in the system.	Authors’ calculations based on BankScope.
GDP growth	Growth rate of nominal GDP, adjusted for inflation (in local currency).	IMF (International Financial Statistics).
Inflation	Year-on-year change of the CPI index (percent).	IMF (International Financial Statistics).
Exch. rate depreciation	Year-on-year change in the nominal exchange rate, local currency per U.S. dollars (percent).	IMF (International Financial Statistics).
Islamic bank dummy	Equals 1 for Islamic banks; 0 otherwise.	Authors’ calculations based on BankScope.
Share of Islamic banks	Market share of Islamic banks in a country per year.	Authors’ calculations based on BankScope.
Share of Islamic banks * Islamic bank dummy	Interaction of share of Islamic banks and the Islamic bank dummy.	Authors’ calculations based on BankScope.
Share of Islamic Banks * commercial bank dummy	Interaction of share of Islamic banks and the commercial bank dummy.	Authors’ calculations based on BankScope.
Governance	Average of the six governance measures- voice & accountability, political stability, government effectiveness, regulatory quality, rule of law and control of corruption- across the available years 2004, 2002, 2000, 1998 and 1996 into one single index per country.	Authors’ calculations based on Kaufmann et al. (2005).