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Journal of Financial Services Research

Erschienen in:

01.12.2010

Islamic Banks and Financial Stability: An Empirical Analysis

verfasst von: Martin Čihák, Heiko Hesse

Erschienen in: Journal of Financial Services Research | Ausgabe 2-3/2010

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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.

Vorheriger Artikel Funding Modes of German Banks: Structural Changes and their Implications

Nächster Artikel Internationalization, Performance and Volatility: The World Largest Financial Groups

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The term “country” as used in this paper covers also territorial entities that are not states as understood by international law and practice, but for which separate data are maintained.

Among the exceptions is the IMF (2009) which finds that Islamic banks in the Middle East were less affected in the first phase of the financial crisis in 2008 but also suffered strong profitability declines in 2009 especially in countries with high exposure to real estate and construction sectors.

For example, a recent Financial Sector Stability Assessment for Bahrain (IMF 2006) included stress tests for both commercial banks and Islamic banks.

For an overview of the basic characteristics and concepts in Islamic Finance, see Errico and Farrahbaksh (1998) and El-Hawary et al. (2004).

For convenience, the term “commercial banks” is used to refer to non-Islamic banks.

It would also be possible to examine Islamic banks compared with cooperative banks, savings banks, or investment banks. However, given the dominance of commercial banks in most financial systems in the world, commercial banks are a convenient comparator. Hesse and Čihák (2007) provide an analysis of the role of cooperative, savings, and commercial banks in financial stability in a range of advanced economies and emerging markets, using a methodology similar to that applied in this paper.

For banks that are listed in liquid equity markets, a popular version of the z-score is distance to default, which uses the stock price data to estimate the volatility in the economic capital of the bank (see e.g., Danmark Nationalbank, 2004). However, given the lack of reliable market price data on Islamic banks, this paper relies on the specification of the z-score that uses accounting data.

We have discussed these arguments and counterarguments with various experts, including at the conferences and seminars mentioned in the acknowledgement. On balance, the arguments in favor of the z-score seem stronger. In addition to the arguments mentioned above, some experts noted that Islamic banks can protect investment account holders and shift risks to shareholders (so-called displaced commercial risk), and for competitive reasons, they can hold back profits in good years and pay out in bad years.

Appendix II provides a description of the variables, and Table 2 provides summary statistics for the key bank-by-bank explanatory variables.

The income diversity measure is defined as \( 1 - \left| {\frac{{\left( {Net\;{\rm int} erest\;income - Other\;operating\;income} \right)}}{{Total\;operating\;income}}} \right| \) . Higher values of the variable correspond to a higher degree of diversification.

We do not have a strong prior on the impact of the Herfindahl index, because the existing literature contains two contrasting views on the relationship between concentration and stability. For example, Allen and Gale (2004) put forth arguments why more concentrated markets are likely to be more stable, while, for example, Mishkin (1999) suggests that more concentrated systems are characterized by increased risk-taking by banks.

To ensure sufficiently comprehensive coverage of Islamic banks, we have cross-checked the BankScope data on Islamic banks against 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.

Also, large Islamic banks have significantly lower z-scores than small Islamic banks (at 1% level), and large commercial banks have significantly higher z-scores than small commercial banks (at 1% level).

To examine the skewness of the z-score distribution, we also calculate the median for the z-score. While there is some evidence for skewness, this is more pronounced for the Islamic banks indicating the expected heterogeneity of Islamic banks across the sample as well as the fact that commercial banks are likely to be better captured with BankScope data.

For example, Moktar et al. (2006) found that Islamic banks are less efficient than commercial banks in Malaysia, even though they also find that the gap has been declining over time.

The difference reflects the relatively higher concentration among commercial banks. There is a small number of very large commercial banks, but their impact on the (unweighted) average for all large banks is limited.

To further assess the robustness of our findings, we have also looked at other measures of financial soundness that are alternative to the z-scores. Measures such as nonperforming loans are not a viable alternative, since they focus on only one of the risks faced by banks and by themselves do not fully capture a bank’s soundness. An obvious alternative to z-scores are credit ratings by rating agencies, which also aim to be a comprehensive measure of a bank’s soundness. However, the sample of credit ratings for Islamic banks is rather small to allow for a meaningful analysis of the statistical distribution of the ratings. To perform an econometric analysis, we therefore focus on the z-scores.

As mentioned earlier, we have also estimated fixed effects and median least squares regressions. The median least squares regressor minimizes the median square of residuals rather than the average and thus reduces the effect of outliers. These regressions yielded results that were consistent with those presented here.

As an additional robustness check, we included a variable for private sector credit growth as well as an interest rate proxying for the monetary policy stance. The results did not change.

The results are available from the authors upon request. We have also tried, as an additional check, to distinguish majority government-owned and other banks, and the distinction appears to have no impact on our result. However, this last result needs to be taken with a grain of salt, given the limited availability of cross-country data on ultimate ownership of Islamic banks (BankScope distinguishes a category of government-owned banks, but it only includes commercial banks).

Ainley M, Mashayekhi A, Hicks R, Rahman A, Ravalia A (2007) Islamic finance in the UK: regulation and challenges. Financial Services Authority, London

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Hesse H, Čihák M (2007) Cooperative banks and financial stability. IMF Working Paper No. 07/02. International Monetary Fund, Washington

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Titel: Islamic Banks and Financial Stability: An Empirical Analysis
verfasst von: Martin Čihák
Heiko Hesse
Publikationsdatum: 01.12.2010
Verlag: Springer US
Erschienen in: Journal of Financial Services Research / Ausgabe 2-3/2010
Print ISSN: 0920-8550
Elektronische ISSN: 1573-0735
DOI: https://doi.org/10.1007/s10693-010-0089-0

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