bank margin

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Bank margin determination:a comparison between Islamic andconventional banks in Indonesia

Erwin G. HutapeaCentral Bank of Indonesia, Jakarta, Indonesia, and

Rahmatina A. Kasri Islamic Economics and Business Center (PEBS)/Department of Economics,

Faculty of Economics, University of Indonesia, Depok, Indonesia

Abstract

Purpose The purpose of this paper is to examine the relationship between Islamic bank margin(BM) and its determinants. It also compares the BM behavior of Islamic and conventional banks in theIndonesian dual banking system.

Design/methodology/approach The paper employs a time series approach under the dealershipframework of Ho and Saunders. The autoregressive distributed lag model is used to inspectcointegration between BM and its determinants for the period of January 1996 to February 2006 of fivesample banks (two Islamic banks and three conventional banks).

Findings The result confirms that there exists a long-running relationship between the Islamic BMand its determinants. In particular, as interest rate volatility increases, Islamic BM respondsnegatively while that of conventional banks responds positively. The findings differ from most of theother studies as they found a positive relationship between BM and interest rate volatility. This paperalso shows that the margin behavior changes as the basis of bank operations changes fromconventional to Islamic principles.

Research limitations/implications The paper uses a relatively small sample of three (out of 150)conventional banks as a comparison to two sample Islamic banks. However, as they come from thesame peer with the Islamic banks, it is believed that the finding is valid. Islamic banks in Indonesiaare not remote from the interest rate volatility in their presence under a dual banking system. It is thedisplaced commercial risk that threatens Islamic banking profitability in a changing market interestrate situation.

Practical implications Under a dual banking system, the stability of interest rates and thefinancial system is of great importance for the policy maker in developing the Islamic bankingindustry in Indonesia. As long as the BM is still a major source of income to the Islamic banks, it isnecessary for Islamic banks to have prudent risk management to mitigate the negative effect ofdisplaced commercial risk and maintain its profitability. Implementation of profit equalizationreserves concept is a possible measure for Islamic banks to shield their operation.

Originality/value This paper is believed to be the first study on Islamic BM behavior in Indonesia.It is expected to provide useful information for policy makers and Islamic bank management to

develop a sound and profitable Islamic banking industry in Indonesia.

Keywords Banks, Risk management, Islam, Indonesia

Paper type Research paper

1. IntroductionThe importance of financial system stability for aggregate economic activity has beenincreasingly emphasized (Kaminsky et al., 1999; Hoggarth and Saporta, 2001; Borio, 2003).

The current issue and full text archive of this journal is available at

www.emeraldinsight.com/1753-8394.htm

Bank margindetermination

65

International Journal of Islamic and

Middle Eastern Finance and

Management

Vol. 3 No. 1, 2010

pp. 65-82

q Emerald Group Publishing Limited

1753-8394

DOI 10.1108/17538391011033870


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This is especially true for a developing economy like Indonesia, where banking sector actsas a dominant source of business financing. Thus, it is important that the intermediaryfunctionof banks be carried outat thelowest possible cost in order to achieve greater socialwelfare. Obviously, lower bank margin (BM) will lead to lower social costs of financial

intermediation (Maudos and de Guevara, 2004, p. 2260).The setting of Indonesian banking system, where Islamic banks operate alongside

and compete with their conventional counterparts, gives a direct motivation to studyIslamic BM. In fact, in the last five years the Islamic banks had been growing at 64percent rate annually, surpassed their counterpart that grew around 30 percentannually (Bank Indonesia, 2007). Thus, we are motivated to examine the determinantsof Islamic BM. In particular, we are interested to investigate the effect of interest ratevolatility on the Islamic BM. For comparative purpose, we also investigate thedeterminants of conventional BM. Given that the Islamic banks have to follow theSharia rules, we expect that the Islamic BM will behave differently with that of theircounterpart.

In efforts to arrive at conclusive findings, we use the extended version of the

dealership approach developed by Ho and Saunders (1981) study and employ theautoregressive distributed lag (ARDL) bounds testing approach to test the existence ofthe relationship between BM and its determinants. The data cover monthly series from1996:01 to 2006:02 of a sample of five Indonesian banks (two Islamic banks and threeconventional banks). As one of the conventional banks converted to an Islamic bank inthe reviewed period, we also inspect the existence of a break in the BM behavior. It isexpected that this study could give a better understanding on the behavior of theIslamic BM in Indonesia as well as enrich Islamic banking literature.

This paper proceeds as follows. In the next section, existing literature and empiricalevidence on BM is discussed. Section 3 describes theoretical setting for Islamic BM andempirical approach of the study, followed by Section 4 which discusses empiricalresults of this study. Section 5 concludes the paper and highlights some relevant policyimplications.

2. Literature review2.1 Definition and models of BMBM is generally defined as the spread between interest revenue on bank assets andinterest expense on bank liabilities, which is presented as a proportion of average bankassets or earning assets (Ho and Saunders, 1981; Angbazo, 1997; Saunders andSchumacher, 2000). As a branch of study on bank behavior, prior to 1981, there was nosignificant development in the literature on bank margins. In its early time, theliterature on BM determination might be traced back to Pyle (1971, as cited inBaltensperger, 1980, pp. 25-9). Afterwards, the literature on bank margins can be

classified into two approaches:(1) the dynamic intermediation or dealership approach (Ho and Saunders, 1981;

Angbazo, 1997; Saunders and Schumacher, 2000; Valverde and Fernandez,2005, 2007); and

(2) the static micro-model of banking firm (Zarruck, 1989; Wong, 1997).

The dealership approach is developed by Ho and Saunders (1981) to study thedeterminants of bank interest margin. According to them, in playing its role as a dealer

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that sets the interest rate on loans and deposits, a bank faces uncertainties and costssince the demand for loans and the supply of deposits are stochastic in the sense thatthey arrive at different times. Thus, it has to hold a long or short position in theshort-term money market to balance this uncertainty that make it exposed to interest

rate risk. This inevitably affects the BM. It is further suggested that greater degree ofrisk aversion, larger size of bank transaction and greater variance of interest rate areassociated with larger bank spread. These imply that even if banking market is highlycompetitive, as long as bank management is risk-averse and faces transactionuncertainties a positive BM will exist as the price of providing deposit-loanimmediacy.

In contrast, the second approach analyzes banking firms in a static setting wheredemand for loans and supply of deposits simultaneously clear both markets. It isdeveloped from the criticisms that the first approach fails to consider some relevantaspects of the banks operation, such as the administrative cost to maintain loan/depositcontracts and the institutional structures of the banking market (Lerner, 1981, p. 601).Zarruck (1989) pioneered the study and found that the risk-averse bank operates with asmaller spread than the risk-neutral bank. This finding was later challenged by Wong(1997) who extended Zarruks work by incorporating credit risk and interest rate riskinto the model. In contrast to Zarruks finding, Wong suggested that the optimal bankinterest margin is larger in the case of risk-averse banks compared to that ofrisk-neutral banks. That is, the spread widens as the banks risk aversion rises.Therefore, as this model leads to different results, most empirical studies on BM use thefirst approach.

2.2 Empirical research on BM determinationBesides developing the theoretical model, Ho and Saunders (1981) examined thevalidity of their model in 53 sample banks in the USA using quarterly series for the

1976:04-1979:04 period. It is reported that the main determinants of the size of actualBM were transaction uncertainty (pure spread) and implicit interest rate. The purespread was smaller in the case of large banks compared to that of the small banks,mainly due to the differences in the US banking market structure rather than riskaversion and transaction size of the banks.

A number of empirical works on BM have employed and extended the originalmodel of Ho and Saunders (1981). Angbazo (1997) incorporated other types of risk,namely credit risk and liquidity risk, to study 286 US commercial banks in the year1989-1993. He found that high BM is associated with high credit risk, interest rate risk,and liquidity risk. Capital base, management quality and opportunity cost of reservesare also significant and positively related to BM. This study is enlarged by Saundersand Schumacher (2000) to cover 614 banks in six selected European countries (UK,

Germany, Switzerland, France, Italy, and Spain) and the USA from 1988 to 1995. Theyfound that BM appears to be equally sensitive to both the short-rate and long-ratevolatility[1]. These results are confirmed by Maudos and de Guevara (2004) whoextended the work of Saunders and Schumacher (2000) by introducing operating cost,degree of market power, and bigger sample size in the period 1993-2000.

A study by Valverde and Fernandez (2005) enrich the BM literature byinvestigating the determinants of BM in banking market of seven European countries(Germany, Spain, France, The Netherlands, Italy, UK, and Sweden) from 1994 to 2001.


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Different from the previous studies, the authors incorporated a broader framework ofBM analysis. In particular, they estimated the determinants of the BM using thetraditional measure of interest margin (the loan to deposit rate spread), a wideraccounting margin (gross income) and a broader BM measure following the New

Empirical Industrial Organization perspective (the Lerner index). They also employedtwo simultaneous equations, i.e. those with level and first-differenced variables. In theinterest margin regression, they reported that the index is not significant, but bothliquidity and interest rate risks are significant. Operating inefficiency and capital toassets ratio are positive and significant. As a proxy to specialization, they found thatthe ratio of loans to total assets is negatively and significantly related to the spread.They suggested that the banks specialized in lending can offer a lower BM due tohigher efficiency (Valverde and Fernandez, 2005, pp. 8-9). A more recent study from thesame authors, Valverde and Fernandez (2007), extended the previous research andfurther investigated the relationship between specialization and BM. Using the samedata set and adding the explanatory variables to include vectors of the pure spreadsdeterminants (risk and market power), other bank-specific factors, bank specializationfactors and regulatory/macroeconomic control variables, they found that both marketpower and risk parameters alter BMs when financial innovations are introduced.In particular, output diversifications permit the banks to increase their revenue andobtain higher market power since revenue from non-traditional business (whichincludes non-interest income) may compensate for lower interest margins that resultfrom stronger competition in the traditional segments (deposits/loans). These resultsexplain, at least in part, the paradoxical coexistence of decreasing interest margins andincreasing market power in European banking sectors which earlier studies havediscovered (Valverde and Fernandez, 2007, p. 15).

As far as study of banks margin is concerned, the literature on bank margins forIslamic banks is hardly available. Although they are not directly related to the study of

BM, some works on Islamic bank performance and profitability are found to be helpfulin laying down the theoretical foundation for the Islamic BM. Haron and Shanmugam(1995) pioneer the empirical study by investigating Bank Islam Malaysia over the year1983-1993. Using autoregressive models to examine the relationship between the ratesof return and the level of deposit in the bank, the study finds that there is an inverserelationship between the variables. This implies that the Islamic bank customers didnot consider returns from the Islamic bank deposit as an incentive to maintain theirfunds with the bank. However, as this result is contrary to the normal behavior ofinvestors, Haron and Ahmad (2000) expand the study to include all funds deposited inIslamic banks in Malaysia from January 1994 to December 1998. The results indicatethat the rates of return have strong positive relationship with the Islamic banksdeposits, while the interest rates have strong negative relationship with it. Therefore, it

is suggested that the Islamic banks customers in Malaysia are attracted to higherreturn and guided by the profit motive. A more recent study by Sukmana and Yusof(2005) which employs a wider data set (January 1994 to October 2004) also confirmconclusions of the previous studies. Accordingly, higher BM is required to attract suchcustomers.

In the case of Indonesia, using time series analysis for 1994-2002 data, Mangkuto(2004) confirmed that the deposits outstanding of Bank Muamalat Indonesia werenegatively responsive to the market interest rate. That is, as interest rates increase,

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depositors take their fund from the Islamic bank and move it to the conventionalbanks, thus reducing the Islamic banks deposit outstanding. He therefore suggestedthat the Islamic banks depositors were mainly rational depositors who were drivenby profit motive in using the banks services. Scope of the study is later widened by

Kasri (2008) to cover data of all Islamic banks in Indonesia from March 2000 to August2007. Using vector autoregressive model model, she revealed that the mudharaba[2]investment deposit in the Islamic banks are cointegrated with return of the Islamicdeposit, interest rate of the conventional banks deposit, number of Islamic banksbranches, and national income in the long-run. She also reported that rate of return andinterest rate move in tandem, indicating that Islamic banks in Indonesia are exposed tobenchmark risk and rate of return risk. Further, as the level of Islamic depositdecreased when interest rate increased, she suggested that the banks are also exposedto displaced commercial risk. In Islamic banking literature, the displaced commercialrisk occurs due to market pressure that Islamic bank pays a return that exceeds therate that has been earned on assets financed by investment account holders whenthe return on assets is under-performing as compared with competitors rates[3]. This

result, hence, confirms the previous finding of Mangkuto (2004). Taken together, theseresults suggest that the Islamic banks are exposed to various banking risks which willinevitably affect the BM.

3. Empirical approach3.1 Islamic BM: theoretical setting and empirical specificationThe nature of Islamic BM is determined by the nature of its component. Islamic banksnever have a predetermined-commitment to pay the return or profit to depositors,neither in nominal sum nor in rate, since this violates the Sharia rules regarding riba.Thus, deposit or financing rates of Islamic banks debt-based products[4] are knownex ante, while those of the equity-based products[5] are known ex post. Taken together,

as the deposit rate and financing rate of the equity-based products of Islamic bankswill be known at the end of period, it follows that the Islamic BM is ex postin nature[6].Conversely, the deposit rate of conventional banks is a predetermined-commitmentby the name of interest rate. Since the deposit and lending rates are predeterminedas interest rate commitment, the net interest margin of conventional banks is knownex ante.

As financial intermediaries, Islamic and conventional banks normally face the sameproblems in their operation. Among others, they have to face asymmetrical arrival timeof financing demand and deposit supply, interest rate volatility, default risk onfinancings, and liquidity risk. In light of the original model of the dealership approach(Ho and Saunders, 1981) and its extended versions (Angbazo, 1997; Maudos and deGuevara, 2004), the relationship between the Islamic BM and its determinants can be

stated as follow:

BMt FSt; Xt; 1t 1

where BMt is the reported Islamic BM at time t, St is a vector of the determinants of thepure spread (interest rate volatility and default risk on financings), Xt is a vector ofbank-specific control variables (liquidity risk, capital base, implicit return todepositors, opportunity cost of bank reserves, and management quality), and 1t isresidual term.


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Following discussion in the previous sections, we argue that there are seven factorscritical in determining the BM, namely interest rate volatility, default risk, liquidityrisk, capital base, management quality, implicit return to depositors, and opportunitycost of bank reserves. With respect to interest rate volatility, theories and empirical

evidences show that conventional banks would ask for a higher margin ascompensation when interest rate risk increases. In contrast, we argue that Islamic BMreacts negatively to interest rate volatility. That is, as market interest rate volatilityincreases, ceteris paribus, Islamic banks need to increase their deposit rate or todecrease their financing rate. In the deposit market, as market interest rate increases, itis possible that Islamic banks customer withdrawn their fund and transfer it tothe conventional counterpart, a risk known as displaced commercial risk[2]. In thefinancing (credit market), however, demand for Islamic banks financing will alsoincrease when market interest rates increase, as their prices are normally lower ascompared to the credit interest rate of the conventional banks. Hence, as the marketinterest rate swings, no matter whether it increases or decreases, Islamic banks areexposed to a certain degree of risk, which possibly comes from the movement of eithertheir depositors or users of funds. Thus, the higher the volatility of market interest rate,the bigger the displaced commercial risks faced by Islamic banks such that the banksneed to increase their deposit rate or to decrease their financing rate or operate at alower margin.

Default risk (of financing) is the risk of non-repayment on financing due to theinability of the funds users to fulfill their obligations to banks. Both Islamic andconventional banks have to face this risk in their operation. Since financing is the majorsource of income for both banks, deterioration of financing quality will affect the banksprofitability and subsequently the banks viability. As default risk increases, Islamicbanks will put a higher risk premium on financing, then the financing price will increaseand, ceteris paribus, the BM will increase. Thus, the BM relates positively to the default

risk. In a similar way, liquidity risk or the risk of not having sufficient cash or borrowingcapacity to meet deposit withdrawals or new financing demand could force banks toresort to emergency funds at a higher cost. As liquidity risk of a bank increases, it willask for a higher risk premium, which might be done through increasing financing rate.As a result, ceteris paribus, the Islamic BM will increase. Hence, the Islamic BM respondspositively to the liquidity risk.

In the cost of capital perspective, higher portion of equity in the capital structurewill lead to higher cost of capital as the cost of equity is higher than the cost of debt.Following the earlier literature, an increase in the capital base may increase theaverage cost of capital and, to compensate for the cost, the bank will ask for a higherfinancing rate. As a result, ceteris paribus, the Islamic BM will increase or, in otherwords, Islamic BM would respond positively to the capital ratio. Likewise, implicit

return to depositor that reflects extra payments to depositors through service chargeremission or other types of transfers is positively related to the Islamic BM, ceterisparibus. As the implicit return to depositors is a component of the operation costs of thebanks, a higher financing rate will be asked to cover the higher costs.

Akin to conventional banks, Islamic banks have to fulfill reserve requirementregulation which reduces the banks opportunity to give financing. Previous literaturessuggest that the banks will request a higher financing rate as the reserves increase incompensation for opportunity forgone. Thus, ceteris paribus, we argue that the Islamic

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BM responds positively to the opportunity cost of bank reserves. Finally, managementquality reflecting the ability of management to minimize costs at a given level ofincome or to maximize income at a reasonable level of cost would would reactnegatively to Islamic BM. That is, as efficiency of Islamic banks improves, the banks

would be able to reduce their costs and thus will ask for a relatively lower margin thanthat of the inefficient banks.

In view of the above, in this paper, we directly estimate the relationship between theIslamic BM and its determinants in the following model:

BM Fdefault risk; interest rate volatility;

liquidity risk; capital ratio; implicit return;

bank reserve; management quality

2

This empirical model also serves as our hypothesis in studying the behavior of theIslamic BM. The data and empirical variables as proxies to the theoretical variables arediscussed in the next section.

3.2 Data and empirical variablesIn this paper, we use monthly data of banks publication reports covering 1996:01 to2006:02 (122 observations) from the Bank Indonesia database. We use a sample of fivebanks: two Islamic banks, namely Bank Muamalat and Bank Syariah Mandiri(henceforth BM and BSM, respectively), and three conventional banks, namely BankBumiputera, Bank Ekonomi Rahardja, and Bank Agroniaga (henceforth BB, BER, andBA, respectively). In order to get a comparable picture of the margin behavior ofIslamic and conventional banks, we select the conventional banks of the same assetsize as the Islamic banks[7].

It is important to note that in this paper, we define Islamic BM as the ratio of

net-financing income to average earning assets. Net-financing income equals income offinancing minus income distributed to depositors. As our study compares the marginbehavior of Islamic banks with that of the conventional banks, the Islamic BM is acomparable variable to the net interest margin of conventional banks. Meanwhile, netinterest margin is the ratio of net interest income to average earning assets. Definitionand measure for each determinant of the conventional bank (CB) and Islamic bank (IB)margin as well as expected relationship between the variables are summarized inTable I.

3.3 Econometric proceduresBased on the empirical specifications and variables discussed in the previous section,the regression model is specified as follows:

BMt a b1DEFt b2MKTt b3LIQt b4SOLVt

b5IMPLt b6OCBRt b7QMt nt3

where all variables are as previously defined, a is intercept and bi (for i 1, 2, . . . , 7)are slope coefficients.

In testing the existence of the relationship between the Islamic BM and itsdeterminants (equation (3)), we apply the recently developed cointegration analysis


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based on the ARDL framework, namely the bounds F-test[8]. The statistic used is thefamiliar Wald or F-statistic, which is used to test the joint significance of lagged levelvariables in a conditional unrestricted equilibrium correction model (UECM) presentedin the ARDL format[9]. If the computed Wald or F-statistic is bigger than the upperbound, we reject the null of no cointegration between variables, vice versa. However, ifthe Wald or F-statistic falls inside these bounds , i.e. bigger than the lower bound but

smaller than the upper bound inference about cointegration is inconclusive andknowledge of the order of the integration of the underlying variables is required beforeconclusive inferences can be drawn (Pesaran et al., 2001, p. 11). This approach hasadvantages, as it does not involve pre-testing the integration property of the variablesunder study[10] and can be applied to small samples.

Before conducting the F-test for cointegration, we need to form the UECM forIslamic BM equation and select the optimal lag length[11]. Based on the dealershipmodel, the UECM of the Islamic BM equation is as follows:

Expected

BM and its relationship

determinants Definition and measure CB IB

BM Ratio of net-financing income to average earningassets

Default risk of financings(DEF)

Ratio of allowances for financing losses to totalfinancing:[(allowance for financing losses/total financing) 100 percent]

Market interest ratevolatility (MKT)

Standard deviation of market interest rate:

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiXr2 r2=n2 1

q 2

Liquidity risk (LIQ) Ratio of liquid assets to liabilities:

[(liquid assets/liabilities) 100 percent]

Capital base or solvencyratio (SOLV)

Ratio of core equity to assets:[(core equity/assets) 100 percent]

Implicit return to thedepositors (IMPL)

Ratio of non funding-related expenses minusnon financing-related revenues to averageearning assets:[(net nonfunding related expenses/average earning assets) 100 percent]

Opportunity cost of bankreserves (OCBR)

Ratio of cash and balance of the deposit with thecentral bank to total assets:[(cash balance at CB/total assets) 100 percent]

Management quality (QM) Ratio of operating cost to operating income:[operating costs/operating incomes) 100 percent]

Table I.BMand its determinants

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DBMt a0 Xnp1

lpDBMt2p Xnp0

gpDDEFt2p Xnp0

wpDMKTt2p

Xnp0

fpDLIQt2p Xnp0

upDSOLVt2p Xnp0

dpDIMPLt2p

Xnp0

cpDOCBRt2p Xnp0

qpDQMt2p p1BMt21 p2DEFt21

p3MKTt21 p4LIQt21 p5SOLVt21 p6IMPLt21

p7OCBRt21 p8QMt21 1t

4

where all variables are as previously defined, D is the first difference operator, n is theorder of UECM model [ARDL(n, n, . . . , n )], and p1 (for i 1, 2, . . . , 8) is the slope

coefficients of lagged levels variables.The null hypothesis of the bounds testing for our model is that there exists nocointegration between the Islamic BM and its determinants. Given that there exists acointegration between the Islamic BM and its determinants, for the sake of parsimony,we adopt the general-to-specific approach of Hendry (1977) to select a parsimoniousspecification for the dynamic of the Islamic BM[12], then we are able to establish thelong-run relationships of the Islamic BM through normalizing coefficients ofregressions of the UECM.

4. Empirical results and discussion4.1 The bounds testing for cointegrationTable II presents the F-statistics for testing the existence of cointegration between BM

and its determinants. In general, the results suggest that there is evidence ofcointegration between the BM and its determinants for each sample bank. In particular,for BM, we reject the null hypothesis of no cointegration between variables at lags 1-4and 6 but we fail to reject the null at lags 5, 7, and 8. For BSM, we reject the nullhypothesis at all lag lengths. Meanwhile, for BB and BER, we find evidence of

Lag order BM BSM BB BER BA

1 4.516 * 12.447 * 6.994 * 4.833 * 3.730 * *

2 6.344 * 8.855 * 4.495 * 5.352 * 3.307 * * *

3 4.499 * 7.888 * 5.521 * 5.685 * 4.640 *

4 3.626 * * 4.965 * 3.695 * * 5.523 * 2.090

5 2.915 9.637 * 3.517 * * 4.834 * 3.705 * *6 3.323 * * * 6.553 * 2.295 1.429 3.681 * *

7 1.957 3.158 * * * 1.804 1.763 3.602 * *

8 2.211 8.308 * 1.482 1.382 2.238

Notes: Statistic is significant at: *0.01, * *0.05, and * * *0.10 levels, respectively; critical values for theF-test are taken from Narayan (2004) with number of observations T 80 and number of regressorsk 7; lower and upper bounds for 0.01, 0.05, and 0.10 levels are 3.021-4.350, 2.336-3.458, and 2.017-3.052, respectively

Table II.F-statistic for testing theexistence of a levels bank

margin equation


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cointegration at lags 1-5 but we do not find it at a higher lag. Lastly, for BA, we rejectthe hypothesis of no cointegration except for lags 4 and 8.

4.2 The long-run equation for bank margin

4.2.1 Long-run equation of Islamic banks. The evidence of cointegration betweenIslamic BM and its determinants for BM and BSM serves as an empirical ground forexistence of the Islamic BM equation and allow us to proceed and estimate thecoefficient of the Islamic BM equations. The long-run coefficients of the BM equationfor the respective sample bank are reported in Table III.

The relationship between the Islamic BM and its determinants for BM, as reflectedin the long-run equation, is generally as expected. The coefficients of variousdeterminants, namely default risk of financing, interest rate volatility, liquidity risk,solvency ratio, implicit cost, and opportunity cost of bank reserves carry the expectedsigns. In particular, the Islamic BM positively responds to the default risk, solvencyratio, implicit costs, and opportunity cost of bank reserves. Conversely, it negativelyreacts to interest rate volatility and liquidity risk. However, the coefficient ofmanagement quality carries a negative sign, which is not as expected. As describedearlier, the management quality is measured by efficiency ratio, whereby a higher ratioreflects a lower efficiency, thus we expected that inefficient management would bereflected in the higher margin. This finding suggests that the efficiency ratio might notbe the best proxy to the management quality; otherwise, it becomes a puzzle in themargin behavior of Islamic banks.

Of special interest is the coefficient of interest rate volatility. The finding of negativesign on interest rate volatilitys coefficient for BM reinforces the theoretical foundationfor the Islamic BM behavior described earlier. Moreover, with regard to the size of itsimpact on the Islamic BM, the interest rate volatility stands in second place after theimplicit cost (with coefficient of20.0195). This finding implies that as the volatility of

interest rates (measured by its standard deviation) increases by 1 percentage point,ceteris paribus, the Islamic BM will decrease by 0.02 percentage point. Furtherimplication of this relationship is that the performance of Islamic banks will deteriorate

BSMBM (1,0,0,0,0,0,0,5) BB BER BA

Variables (6,3,4,2,5,6,5,5) 96:01-99:10 99:12-06:02 (1,5,5,4,0,0,4,5) (2,5,1,4,0,2,0,0) (1,0,0,0,3,0,0,3)

DEFt 0.0040 20.0076 0.0034 0.0622 0.0021 20.0025MKTt 20.0195 0.0021 20.0064 0.0110 0.0048 0.0385LIQt 20.0003 20.0070 20.0036 20.0057 20.0018 20.0004

SOLVt 0.0153 0.0236 0.0109 0.0046 0.0048 0.0010IMPLt 0.0371 0.2805 0.4499 0.4315 0.5374 0.7266OCBRt 0.0149 20.0511 0.0362 0.0034 0.0022 20.0193QMt 20.0143 20.0176 20.0080 20.0251 20.0040 20.0098

Notes: The regression is based on the conditional UECM[9], using an ARDL(n1, n2, . . ., n8)specification, which is appropriate for each sample bank, with dependent variable BMt estimated over1996:01-2006:02; for BSM, it is estimated in 1996:01-1999:10 and 1999:12-2006:02 due to its conversionto be an Islamic bank in 1999:11

Table III.A comparison of long-runequation of BM

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as the volatility of interest rates increases, given the fact that the BM is still the majorsource of income for the Indonesian Islamic banks.

As mentioned earlier, the second Islamic bank of our sample banks, BSM, hadoperated under a conventional framework prior to its conversion into an Islamic bank.

In fact, this setting benefits us in observing the existence of switching behavior in theBM of BSM in the period under consideration. Since BSM was converted into anIslamic bank in November 1999, we perform the Chow Break test to check the existenceof switching behavior with 1999:11 as the break point. Having the F-statistic equal to23.95, we reject the null hypothesis of no break in the model at the 0.01 level ofsignificance. This finding motivates us to break the observation into 1996:01-1999-10as the conventional period and 1999:12-2006:02 as the Islamic period, and then estimatethe BM equation for each period.

In general, we find that the BM equation of BSM in the Islamic period is as expectedand thus strengthens the abovementioned empirical evidence of BM. All coefficients ofthe Islamic BM determinants of BSM carry the expected signs. With respect to interestrate volatility, however, the size of its coefficient is only20.0064, which is far below thatofBMof20.0195. Moreover, based on its effect on the Islamic BM, for BSM, interest ratevolatility stands in fifth position, following the implicit costs, opportunity cost of bankreserve, solvency ratio and management quality.

Comparing the BM equation of BSM in its conventional and Islamic periods, weobserve some differences in the coefficient sign of some determinants. For instance, thecoefficient sign of default risk of financing changes from negative to positive and thecoefficient sign of opportunity cost of bank reserve changes in the same way.Interestingly, the coefficient sign of interest rate volatility changes from previouslypositive in the conventional period to be negative in the Islamic period. This revealsthat, as interest rate volatility increases, conventional banks will ask for a highermargin to compensate for the interest rate risk (reinvestment or refinancing risks),

while Islamic banks have to increase their deposit rate or decrease their financing rate(thus the margin decrease) to protect their operation from increasing magnitude ofdisplacement risk. With respect to the banks response to the interest rate movement,this finding implies that the margin behavior changes as the basis of the banksoperation switches from conventional practices, where it faces interest rate risk, to theIslamic principles where it faces the displaced commercial risk.

Having seen that the coefficient of interest rate volatility is negative in sign for bothBM and BSM, we further investigate the empirical justifications of the finding.Specifically, we examine the behavior of the Islamic BM components, namely price offinancing products (financing rate) and rate of return to depositors (deposit rate), underdifferent trends of market interest rate. Indeed, with the purpose of properly analyzingthe behavior of the components under a different tendency of market interest rate, we

break the observation into increasing and decreasing periods of market interestrate[13]. Afterwards, for the respective periods, we calculate the correlation coefficientbetween market interest rate and financing rate, measured as a ratio of financingincome to financing outstanding. We also calculate the correlation coefficient betweenmarke t int eres t rat e and d ep osit rat e, m easu re d as a rat io of profitdistributed-to-depositors to deposits outstanding. The results are reported in Table IV.

Some interesting findings could be highlighted from our investigation. In theincreasing interest rate period, we observe that the financing rates of Islamic banks


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(BM and after-conversion-BSM) move opposite to the market interest rate, as supportedby the correlation coefficient of20.66 and20.43. In contrast, the deposit rates changein a similar direction to the market interest rate, as suggested by the correlationcoefficient of 0.61 and 0.24. These results imply that, as the market interest rateincreases, the Islamic banks are unable to adjust instantaneously their financing rate,since upwardly adjusting the financing rate will violate the Sharia rule regardingthe alteration of selling price[14] once it was agreed up-front. On the other hand, as themarket interest rate increases, to dissuade their depositors from withdrawing theirfunds (displaced commercial risk), the Islamic banks have to increase their deposit rate.In fact, these two contrary effects will bring down the Islamic BM in periods ofincreasing interest rates. This evidence restates our finding on the negative sign of theinterest rate volatilitys coefficient for BM and BSM.

In the period of decreasing market interest rates, we verify that both the financingand deposit rates move in tandem with the market interest rate. For BM and BSM, thecorrelation coefficients of financing rate-market interest rate are 0.55 and 0.55, whilethe correlation coefficients of deposit rate-market interest rate are 0.91 and 0.81.However, to this point we are unable to explain why the Islamic BM respondsnegatively to the market interest rate in the decreasing period. Thus, we estimate theeffect of market interest rate on the financing and deposit rates of Islamic banks[15].The result reveals that as the interest rate decreases by 1 percentage point, ceterisparibus, the deposit rates of BM and BSM will decrease by 0.03 and 0.07 percentagepoints, respectively, while the financing rate of the two banks will decrease by 0.008and 0.04 percentage points, respectively. Thus, we can verify that the deposit andfinancing rates respond disproportionately to the market interest rate. As the marketinterest rate shrinks, the deposit rates decrease by a bigger percentage point comparedto that of the financing rate. This evidence is found in the regressions of both BM andBSM, with the evidence of BM being more apparent. In fact, this is the reason why theIslamic BM does not decrease in the period of decreasing market interest rates. Again,this finding reinforces the negative sign of interest rate volatilitys coefficient in theIslamic BM equation.

Another interesting finding in the decreasing rate period would be the fact that thefinancing price is able to adjust to the market interest rate in the decreasing period,

Correlation

Increasingregime

(96:01-98:08)

Decreasingregime

(98:08-00:02)a

Increasingregime

(00:02-02:01)

Decreasingregime

(02:01-05:03)

BMFinancing rate-market rate 20.6624 0.5521 Deposit rate-market rate 0.6082 0.9118

BSMFinancing rate-market rate 0.7006 0.2417 20.4334 0.5497Deposit rate-market rate 0.5386 0.3101 0.2423 0.8062

Notes: Financing and deposit rates are measured as ratios of financing incomes (equivalent to interestincomes) to total financings outstanding and ratio of profit distributed-to-depositors (equivalent tointerest costs) to total deposits outstanding, respectively;

afor the BSM, this period is set to 1998:08-

1999:10 in order to avoid the effect of conversion of its operation from conventional bank into Islamicbank on 1999:11

Table IV.Correlation betweenfinancing and depositrate with market rate

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but not in the increasing period. As argued earlier, any alteration of selling price in thefixed-price mode of financing will breach the contract as it violates the Sharia rule.That is, in light of the Islamic principles, it is prohibited to make any increase to theselling price, i.e. adding the mark-up as interest rate increases or for whatever reasons,

as this is unjust and will increase the burden of the customers. However, giving adiscount or rebate under the name of the banks kindness without altering the sellingprice is permissible as long as the rebate is not contracted and should be at the banksdiscretion[16]. In fact, to protect their operation from the displaced commercial risk offinancing in the decreasing period, in which the customers re-finance their financingin the Islamic banks with that of conventional banks since now the market interest rateis lower, it is a common practice for the Islamic banks to give a discount or rebate totheir customers.

It is also worth to note that when the financing rates of both of the banks decreaseonly by 0.008 and 0.04 percent, their deposit rates decrease by a bigger magnitude,i.e. 0.03 and 0.07 percent, respectively, while the deposit contract is based on theprofit-loss-sharing (PLS) contract. Recall that there are two factors working here inreducing the deposit rates to a bigger extent as compared to the financing rates.The first factor is the decrease in the financing rate itself as discussed previously, whilethe other factor is the movement of depositors from conventional banks to Islamicbanks since now the return of the first is lower than that of the second, ceteris paribus.This deposits movement will bring down further the rate of return to depositors as nowthe denominator (amount of deposits) increases while the numerator (profit distributedto depositors) is relatively slow to adjust[17]. The deposits movement will continueuntil the difference of deposit rates between the Islamic and conventional banks is notsignificant enough to invite arbitrage opportunity action.

Finally, should we look at the correlation coefficient of BSM in itsconventional period,some interesting findings are noticeable. We verify that, in the conventional period, the

financing rate behaves in a different manner relative to that in its Islamic period. Indeed,the dissimilarity is found in the sign of correlation coefficient of the financing rate andmarket interest rate. As discussed earlier, after it became an Islamic bank, this coefficientis found to be negative in the period of increasing interest rates. However, the coefficientis always positive in the conventional period irrespective of whether it is in the period ofincreasing or decreasing interest rates. That is, as conventional banks have noconstraints in adjusting their credit rate to follow the market rate, the correlationcoefficient is always positive in the different tendency of market interest rate.

4.2.2 Long-run equation of conventional banks: a comparison. Some comparisons ofthe long-run BM behavior of Islamic and conventional banks could be pointed out fromTable III results. In general, both banks share similar behavior in the relationshipbetween the BM and majority of its determinants, namely default risk of financing,

liquidity risk, solvency ratio, implicit cost, opportunity cost of bank reserves andmanagement quality. In particular, although the coefficients of those determinantsvary in size, they show similar signs for all sample banks, irrespective of whether theyare conventional or Islamic banks[18]. This evidence reinforces the validity of Ho andSaunders (1981) dealership model and its extended versions. With respect to theinterest rate volatility, while its coefficient shows a negative sign for the Islamic banks,it is positive for the conventional banks. These findings reveal that the conventionalbanks have no constraint in adjusting their credit (financing) and deposit rates to


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follow the market interest rate movement, regardless of whether it is in the period ofincreasing or decreasing interest rates. However, as discussed earlier, the Islamicbanks are unable to adjust their financing price in the period of increasing interestrates, since this will violate the very central principle in their operations, namely the

Sharia rule.

5. Conclusion and policy recommendationWe have examined the behavior of the BM in Indonesia using monthly data over theperiod of 1996:01-2006:02. Applying a relatively new cointegration technique, namelythe bounds testing approach within the ARDL framework, we specifically identify along-run relationship between the Islamic BM and its determinants, namely defaultrisk of financing, interest rate volatility, liquidity risk, solvency ratio, implicit cost,opportunity cost of bank reserves, and management quality.

In particular, this paper confirms the Ho and Saunders dealership approach and itsextended versions in BM determination. In the theoretical setting, we argued that

Islamic banks in Indonesia are not remote from the interest rate volatility in theirpresence under a dual banking system. It is the displaced commercial risk, rather thanreinvestment and refinancing risk, that threatens Islamic banking operations in achanging market interest rate situation. For Islamic banks case, our finding differsfrom Angbazo (1997) and Valverde and Fernandez (2005, 2007). Indeed we find anegative relationship between Islamic BM and interest rate volatility. This is in linewith the finding of Kasri (2008) as well as our empirical evidence that the Islamic BMbehaves differently relative to that of conventional banks, i.e. with respect to theirresponse to the market interest rate movement. Moreover, we documented that BMbehavior switched as the underlying operational principles of the bank changed fromconventional to Islamic principles. It is an opportunity for future research to compareour finding with BM behavior in other dual banking system such as Malaysia, Bahrain,

and Pakistan. As we make use of time series approach, it will also be interesting toemploy different methodology like two-step approach and a pool-data analysis toinvestigate the issue.

Our finding has particular relevance to the formulation of banking policy indeveloping Islamic banks in Indonesia. As far as the Islamic banks are concerned,knowing that the Islamic BM responds negatively to the volatility of the marketinterest rate implies that the stability of market interest rates becomes of great concernin developing the Islamic banking industry. As long as the BM is still a major source ofincome to the Islamic banks, the instability of the market interest rates will have anegative impact on the profitability and thus sustainability of the Islamic banks,regardless its share to the Indonesian banking system currently. In light of thisunderstanding, Bank Indonesia as the monetary authority as well as the banking

authority (at least at the present time) should take into consideration the impact ofmarket interest rate volatility on the Islamic banks, in designing its monetary policy. Itis also necessary for Islamic banks to have prudent risk management to mitigate thenegative effect of displaced commercial risk and maintain its profitability. As such, theprofit equalization reserve (PER) concept introduced by Islamic Financial ServicesBoard (IFSB) is a possible solution that could be adopted by Islamic banks inIndonesia. The PER is the amount set aside by the Islamic financial institutions out oftheir gross income in order to maintain a certain level of rate of return for their

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depositors (IFSB, 2005). The concept is in line with the finding and suggestion ofValverde and Fernandez (2007) in which (Islamic) banks could enlarge their range ofproducts and services in attempts to increase the revenue from non-traditionalbusiness (which includes non-financing income) which may compensate for lower BM

due to stronger competition in the traditional segment.

Notes

1. The short-run rate is defined as the annual standard deviation of weekly interest rate onthree-month securities while the long-rate volatility is defined as that of the one-yearsecurities. An 1 percent increase in the volatility of interest rates increased BM by about 0.2percent.

2. Mudharaba is a type of time deposit based on profit-loss sharing contract offered by Islamicbanks in Indonesia.

3. Further, according to IFSB, displaced commercial risk is defined as an exposure when theIslamic banks are under market pressure to pay a return that exceeds the rate that has been

earned on assets financed or when the return on assets is under-performing as comparedwith competitors rates. As such, the Islamic banks may decide to waive their rights to partor their entire mudarib share of profits in order to satisfy and retain their fund providers anddissuade them from withdrawing their funds (IFSB, 2005, Guiding Principles of Risk

Management for Islamic Financial Institution, p. 23).

4. Products of Islamic banks can be classified into debt- and equity-based products. Thedebt-based (fixed-return) products are commonly based on the sale (trading) and lease oftangible assets with delayed payment, among others murabahah (mark-up sale), ijarah(leasing), istisna (sale to manufacture transaction) and salam (sale with future delivery).

5. The variable-return products employ PLS contracts such as mudarabah (trust financing) andmusharakah (joint financing).

6. Although in the extreme case, where all financing products are fixed-return (debt-based) and

thus the financing rate is known ex ante, notice that the Islamic BM remains ex postsince thedeposit rate is unknown ex ante.

7. Please see the Appendix for the detailed comparison of the banks.

8. In empirical studies of time series, estimation of relationship in levels such as equation (3) isjustified as long as variables appearing in the equation are stationary. Should some variablesin the system or all of them be non-stationary, then they should be cointegrated. Otherwise,we will face the problem of spurious regression. Notice that in the presence of non-stationaryvariables, Granger and Newbold (1974) suggest that there might be a spurious regressionwith high R2 and t-statistics that appear to be significant, but the results has no economicmeaning (in Enders, 1995, p. 216). Thus, it is important in the first place to verify thecointegration properties of the variables under study. In general, this analysis is based onthe use of two main approaches in the cointegration analysis have been widely used, namely

the two-step residual-based test as developed by Engle and Granger (1987) and themaximum likelihood-based test as developed by Johansen (1988) and Johansen and Juselius(1990). However, those approaches require a pre-testing integration order of the studiedvariables. Otherwise, pre-testing bias problem could happen. In light of those problems,Pesaran and Shin (1997) and Pesaran et al. (2001) developed a new technique based on

F-statistic in the autoregressive distributed lag specification (henceforth ARDL) framework.

9. There are two sets of critical values for the F-test, which assumes all the regressors are, onthe one hand, purely I(1) and these are referred to as the upper bound critical values, and, onthe other hand, purely I(0) and these are referred to as the lower bound critical values.


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10. In particular,the cointegration testis directlyapplicable irrespectiveof whether the underlyingregressors are purely I(0), purely I(1) or mixture ofI(0) and I(1) (Pesaran et al., 2001, p. 1).

11. We make use of the information criteria, namely, Akaikes information criterion (AIC) orSchwarzs information criterion (SC). However, as emphasized by Pesaran et al. (2001), it is

important to note that the assumption of serially uncorrelated errors is essential for thevalidity of the bounds tests. Therefore, this concern must be incorporated in determining theappropriate lag length of the UECM. In this paper, we calculate the AIC, SC, and F-statisticby imposing the same lag length for all first differenced variables in equation (4).

12. In particular, we start from the base model as suggested by AIC or SC, then sequentiallyreduce the insignificant lag-length for each of the lagged first-differenced variables until thelast-lag is significant.

13. It seems easier for us to understand the response of the deposit rate and financing rate underthe increasing or decreasing interest rate era rather than under increasing or decreasinginterest volatility. In fact, the finding of coefficient correlation between the interest rate andits volatility (standard deviation) equal to 0.66 serves as a basis for us to proceed.

14. This argument is reliable, as the dominant contract in financing product is murabahah

(fixed-price financing). Even if the contributions of mudarabah and musharakah (PLSfinancing) in the assets portfolio of Islamic banks are significant, this argument is stillworkable on the basis that the business sector generally performs poorer in an increasinginterest rate period. Hence, the financing income of the Islamic bank will remain constant ormight decrease as the profit of the business sector deteriorates.

15. Note that before we proceed, we have tested whether the market interest rate causes inthe Granger sense the deposit rate and financing rate or not to provide basis for theinvestigation. From the Granger test, we find that the market interest rate Granger-causesthe deposit rate and financing rate of BM at 0.01 levels, respectively. For BSM, we find thesame result at 0.01 and 0.10 levels, respectively.

16. At least for the practice of Islamic banks in Indonesia as it is allowed by the Fatwa ofNational Sharia Council No. 46, February 22, 2005.

17. It has been known in the banking practices that there is a lag between the times the bankreceives deposits and the times the bank lend out the money. This happens to conventionalbanks and Islamic banks as well.

18. An exception is given to BA since this bank shows a peculiar sign in the coefficients ofdefault risk of financing and opportunity cost of bank reserves. However, the other fiveregressors have similar sign with those of remaining conventional banks.

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Granger, C.W.J. and Newbold, P. (1974), Spurious regressions in econometrics, Journal ofEconometrics, Vol. 2, pp. 111-20.

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Hendry, D.F. (1977), On the time series approach to econometric model building,in Sims, C.A. (Ed.), New Methods in Business Cycle Research, Minneapolis, MN, FederalReserve Bank of Minneapolis, pp. 183-202, reprinted in Hendry, D.F. (1993),Econometrics: Alchemy or Science?, Blackwell Publishers, Oxford, 2000.

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Kasri, R.A. (2008), The dynamics of Islamic banking growth determinants: the Indonesiaexperience, paper presented at the International Accounting Conference (INTAC) IV,

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Sukmana, R. and Yusof, R.M. (2005), Are funds deposited in Islamic banks guided by profitmotive? An empirical analysis on Malaysia, paper presented at the 4th Global Conferenceon Business and Economics, Oxford University, Oxford, 26-28 June.

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Further reading

Bahmani-Oskooee, M. and Chi, W.N.R. (2002), Long-run demand for money in Hong Kong:

an application of the ARDL model, International Journal of Business and Economics,Vol. 1 No. 2, pp. 147-55.

Gujarati, D.N. (2005), Basic Econometrics, 4th ed., McGraw-Hill, East Windsor, NJ.

Appendix

Corresponding authorRahmatina A. Kasri can be contacted at: [email protected]

Name of bank BM BSMa BB BER BA

Description b

Assets 2,028 3,011 1,816 5,229 918Financings 1,589 2,186 1,186 1,673 706

Earning assets 1,738 2,678 1,510 3,688 848Deposits 1,523 2,354 1,394 4,074 666Core equity 226 460 183 251 120Variables c

BM 0.502 0.697 0.474 0.502 0.471DEF 5.577 6.425 2.411 7.694 4.696MKT 2.799 2.799 2.799 2.799 2.799SOLV 14.264 32.865 12.849 4.656 18.409LIQ 19.815 74.819 40.713 57.325 28.278IMPL 0.675 0.551 0.375 0.322 0.264OCBR 7.590 5.014 4.653 4.536 3.965QM 100.41 87.08 93.78 89.39 91.95Number of observation 122 75 122 122 122

Notes:

aAll figures for BSM are after it converted to be an Islamic bank (1999:11 to 2006:02); ballfigures in this section are in billions of IDR; call variables are in percentage

Table AI.Description of sample

banks and variablesmean

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