3. METHODOLOGY AND DATA
Writer ‘s primary dependant variable is the z-score as a step of single bank hazard. The z-score has become a popular step of bank soundness ( see, e.g. , Boyd and Runkle, 1993 ; and Maechler, Mitra, and Worrell, 2005 ) . Its popularity stems from the fact that it is reciprocally related to the chance of a bank’s insolvency, i.e. , the chance that the value of its assets becomes loauthorr than the value of the debt. The z-score can be summarized as z? ( k+? ) /? , where K is equity capital and militias as per centum of assets, ? is mean return as per centum of assets, and ? is standard divergence of return on assets as a placeholder for return volatility. The z-score measures the figure of standard divergences a return realisation has to fall in order to consume equity, under the premise of normalcy of banks’ returns. A higher z-score corresponds to a loauthorr upper edge of insolvency risk—a higher z-score therefore implies a lower chance of insolvency hazard.
Why does this metric for hazard apply to Islamic Bankss? An of import characteristic of the z-score is that it is a reasonably nonsubjective step of soundness across different groups of fiscal establishments. It is an nonsubjective step because it focuses on the hazard of insolvency, i.e. , on the hazard that a bank ( whether commercial, Islamic, or other ) runs out of capital and militias. The z-score applies every bit to Bankss that use a high risk/high return scheme and those that use allow risk/row return scheme, provided that those schemes lead to the same risk-adjusted returns. If an establishment “chooses” to hold lower risk-adjusted returns, it can still hold the same or higher z-score if it has a higher capitalisation. In this sense, the z-score provides an nonsubjective step of soundness.
A possible unfavorable judgment of the z-score as applied to Islamic Bankss is that the risk-sharing agreements provide an extra protective buffer in sedimentation liabilities, intending that the book values of capital and militias may undervalue fiscal strength of these Bankss. A big part of Islamic banks’ fiscal liabilities consists of investing histories that can be viewed as a signifier of equity investing ( by and large based on the rule of Mudarabah ) . Investing histories are offered in different signifiers, frequently linked to a pre-agreed period of adulthood, which may be from one month upwards, and the financess in the histories can by and large be withdrawn if beforehand notice of one month is given. The net incomes and returns are distributed between the depositors and the bank, harmonizing to a pre-determined ratio, e.g. , 80 per centum to the depositors and 20 per centum to the bank ( Iqbal and Mirakhor, 2007 ) . At the extreme, it could be argued that a bank with merely restricted investing histories would be near to a common fund in footings of its hazard profile, with about all hazard passed to investors. Even with unrestricted investing histories, much of the hazard is in rule borne by investors.
A counterargument against this possible unfavorable judgment is that even conventional Bankss normally have the ability to go through on hazards to their clients, for illustration through their ability to set ( and detain accommodations in ) sedimentation and loan rates. Merely after Islamic banks’ beds of protection have been exhausted and after the bank has started to incur losingss, does a daze have an impact on capital and militias. In other words, these extra beds of protection are finally reflected in the banks’ returns and capital, and thereby in their z-score. Furthermore, the fact that most of the investing histories can be withdrawn in a comparatively short period of clip, every bit good as the fact that the return distribution between the bank and the depositors/investors is pre-determined, diminishes the factual differences in hazard profiles associated with the investing histories, compared with floating-rate sedimentations and other conventional support used by commercial Bankss. So, while the differences between Islamic and conventional Bankss should be born in head, capital and militias are still a sensible placeholder variable to measure the “bottom line” default hazard.
As a preliminary measure in the analysis, writer performs basic statistical trials for the z-scores. Writer compares z-scores in Islamic and commercial Bankss. Because bank size is an of import factor in some of the bing documents on bank soundness, writer besides subdivide Bankss into big and little Islamic Bankss and big and little commercial Bankss ( utilizing entire assets of US $ 1 billion as the cut-off point between little and big Bankss ) , and carry out pair wise comparings of z-scores for these assorted subgroups.
3.1 Arrested development Analysis
The chief portion of our attack is to prove, utilizing arrested developments of z-scores as a map of a figure of variables, whether Muslim Bankss are less or more stable than commercial Bankss. Author estimate a general category of panel theoretical accounts of the signifier
omega B I T T I B T M C D, , , , 1, 1, 1, , 1, 1, , =? +? +? +?? +?? +?? +? +?? +?? +
where the dependant variable is the z-score I J T omega, , for bank I in state J at clip T ; I, J, t?1 B is a vector of bank-specific variables ; J, t?1 I contains time-varying industry-specific variables ; s T and s J, t?1 T I are the type of Bankss and the interaction between the type and some of the industry-specific variables ; J T M, , J C, and T D are vectors of macroeconomic variables, state and annually dummy variables, severally ; eventually, I, J, T ? is the residuary.
To separate the impact of bank type on the z-score, writer include a dummy variable that takes the value of 1 if the bank in inquiry is an Islamic bank, and 0 otherwise ( i.e. , if it is a commercial bank ) . For illustration, if Muslim Bankss are comparatively weaker than commercial Bankss, the silent person variable would hold a negative mark in the arrested development explicating z-scores.
At the systemic ( state ) degree, writer wants to analyze the Islamic banks’ impact on other Bankss and the hypothesis that the presence of Islamic Bankss lowers systemic stableness. For this ground, writer has calculated the market portion of Islamic Bankss by assets for each twelvemonth and state and interact it with Islamic and commercial bank silent persons. For illustration, a negative mark for the interaction of the Islamic banks’ market portion and the Islamic bank silent person would bespeak that a higher portion of Islamic Bankss reduces their soundness ( reduces their z-scores ) .
In add-on to the above key variables of involvement, the arrested development includes a figure of other control variables, both at the single bank degree and the state level.8 To command for bank-level differences in size, plus composing, and cost efficiency, writer include the bank’s plus size in U.S. dollars billion, loans over assets, and the cost-income ratio. Besides, to command for differences in the construction of the bank’s income, writer calculate a step of income diverseness that follows Laeven and Levine ( 2005 ) .9 This variable captures the grade to which Bankss diversify from traditional loaning activities ( those bring forthing net involvement income ) to other activities. For Muslim Bankss, the net involvement income is by and large defined as the amount of the positive and negative income flows associated with the PLS agreements ( see, e.g. , International Monetary Fund, 2004 ) . To farther gaining control differences of Muslim Bankss in their concern orientation, writer interact the income diverseness variable with the Islamic bank silent person. Controling for these variables is of import because there are differences in these variables between Islamic Bankss and the other groups.
At the state degree, writer includes a figure of variables that take on the same value for all Bankss in a given state. In peculiar, author adjusts for the impact of the macroeconomic rhythm by including three macroeconomic variables ( GDP growing rate, rising prices rate, and exchange rate depreciation ) . To account for cross-country fluctuation in fiscal stableness caused by differences in market concentration, writer includes the Herfindahl index, defined as the amount of squared market portions ( in footings of entire assets ) of all Bankss in the state. The index can hold values from 0 to 10,000 ( for a system with merely one bank ) .
Author besides account for the impact of administration on stableness by utilizing the administration index that was compiled by Kaufmann, Kraay, and Mastruzzi ( 2005 ) . Author mean the 6 administration steps of voice and answerability, political stableness, authorities effectivity, regulative quality, regulation of jurisprudence, and control of corruptness across the available old ages 2004, 2002, 2000, 1998, and 1996 into a individual index per state. The administration index gaining controls crosscountry differences in institutional developments that might hold an consequence on banking hazard.
All bank-specific and macroeconomic variables, the Herfindahl index, and the Islamic banks’ market portion and its interaction with the Islamic and commercial bank silent persons are lagged to capture the possible past effects of these variables on the banks’ single hazard. Author besides tests for the hardiness of the lagged effects by curtailing the explanatory variables to contemporary effects.
Author start the arrested development analysis by the pooled ordinary least squares ( OLS ) technique. Given that our sample includes outliers, writer usage a robust appraisal technique as an of import appraisal method. Hamilton ( 2002 ) provides a elaborate description of the technique. In a nutshell, it assigns, through an iterative procedure, lower weights to observations with big remainders, doing the appraisal less sensitive to outliers. Standard mistakes are calculated utilizing the pseudovalues approach ( Street, Carroll, and Ruppert, 1988 ) . To prove the sensitiveness of the consequences with regard to the appraisal method, writer besides estimates fixed effects and average least squares arrested developments. The average least squares regressor minimizes the average square of remainders instead than the mean and therefore reduces the consequence of outliers.
Author besides assesses the hardiness of the consequences with regard to the selected sample. To make that, writer estimation the same arrested developments for different bank sizes. Specifically, writer estimation the arrested developments individually for sub-samples of big Bankss ( those with entire assets of more than US $ 1 billion ) and little Bankss ( all others ) .
3.2 Data Analysis
To capture the importance of bank size on stableness in Islamic and commercial Bankss, writer present some of the consequences individually for sub-samples of big Bankss ( assets over US $ 1 billion ) and little Bankss ( all others ) , utilizing the same threshold for both Islamic and commercial Bankss. The threshold is arbitrary, but it has been used in old research on little Bankss ( e.g. , Mercieca, Schaeck, and Wolfe, 2007 ) , and, more significantly, the chief consequences of our analysis are non sensitive with regard to chair alterations in the threshold. About 49 per centum of the Islamic Bankss and about 62 per centum of the commercial Bankss fall into the big bank class.
Several general issues associating to the BankScope informations demand to be mentioned. First, to be able to analyse Islamic banks’ impact on systemic stableness, writer has focused on states where Muslim Bankss have a higher than negligible portion of the fiscal system. El Qorchi ( 2005 ) notes that Islamic establishments operate in 75 states, yet in most of those states, Islamic Bankss have a really little market portion. Writer has included all the systems where Muslim Bankss harmonizing to the BankScope informations accounted for more than 1 per centum of the entire assets in at least one twelvemonth in the period under observation ( 1993-2005 ) . The exclusion of the Islamic Bankss from the other states does non look stuff, since our sample still has a good worldwide coverage of Islamic Bankss. This is confirmed by the fact that Islamic Bankss covered in our get downing sample have entire assets of US $ 253 billion as of 2004, which is in line with the estimation of “about US $ 250 billion” world-wide assets of Muslim Bankss quoted for illustration by El Qorchi, 2005.
Second, our empirical analysis relies to a big extent on unconsolidated bank statements. Ideally, writer would hold opted for utilizing merely amalgamate statements for all fiscal establishments. However, merely about 1/3 of the relevant observations in BankScope are based on amalgamate informations ; the remainder are unconsolidated informations. This scarceness of amalgamate informations bounds their utility for econometric analysis. Author hence use amalgamate informations when available, but when amalgamate informations are non available for a bank, writer usage unconsolidated informations alternatively.
Third, BankScope, while being the most comprehensive commercially available database of banking sector informations, is non thorough. Coverage varies from state to state ; for most states in author’s sample, the BankScope informations cover 80-90 per centum of the banking systems in footings of entire assets. Furthermore, writer had to except 2 states from our analysis because of informations jobs, conveying the figure of states on which the sum consequences are based from 20 to 18. For Lebanon and Kuwait, BankScope does non hold unconsolidated observations for Islamic Bankss, so these states are excluded from the arrested development analysis. The coverage of this paper, while less than 100 per centum, is still higher than that for most banking surveies ( and in peculiar surveies that focus on Bankss with peculiar characteristics, such as big Bankss or Bankss that are listed on the stock market ) . Even after the exclusions, entire assets of the Islamic Bankss included in the panel are about the same as the estimated entire assets of Muslim Bankss in the universe reported in earlier literature ( see above ) . Author’s sample should hence be big plenty to supply dependable illations.
Fourth, writer mostly relies on BankScope for informations quality. There are a figure of of import issues associating to definitions of fiscal indexs for Islamic Bankss, for illustration what to include in capital, or how to mensurate ( the equivalent of ) involvement income. The issue of fiscal soundness indexs in Islamic Bankss is discussed in more item for case in International Monetary Fund ( 2004 ) . For the intents of this paper, writer have mostly relied on BankScope’s definitions of the cardinal variables, even though writer have done basic crosschecking and besides excluded outliers, some of which may be the consequence of divergences from common definitions.
Fifth, some commercial Bankss ( including several major planetary participants ) have opened dedicated Islamic Windowss or Islamic subdivisions carry oning concern harmonizing to Islamic banking rules. However, the available fiscal informations do non let writer to separate the fiscal public presentation ( and importance ) of these Windowss or subdivisions and analyze their separate impact on fiscal stableness. Author therefore focuses merely on the comparing of fully-fledged Islamic Bankss and commercial Bankss.
Sixth, information restrictions prevent writer from taking to the full into history all facets of Islamic fiscal contracts, for illustration, by commanding for type of Islamic instruments, separating between PLS and other investings, separating the different types of investing histories, and return equalisation financess. In add-on to the bank-by-bank informations, writer besides uses a figure of macroeconomic and other system-wide indexs. Those are described in more item in Appendix II.