profit and cost efficiencies of conventional banking (cb) and...

Profit and Cost Efficiencies of Conventional Banking (CB) and Islamic Banking..... 63

Profit and Cost Efficiencies of Conventional Banking (CB) and Islamic Banking (IB) using Stochastic

Frontier Approach: A comparative Study

Shamim Ara 1

Abstract

Islamic banking (IB) has been functioning since last three decades while Conventional banking (CB) has been running since long in Bangladesh. IB developed with Islamic law and order contrasts CB operated on normal banking criteria (interest-based). A comparative study of CB and IB has been performed in this study. The data are collected from 19 banks (CB) and 5 banks (IB) from each banks’ annual reports (2004-2008). Cost and profit are used as outputs and deposit, loans /investment, price of fund, price of capital, price of labor, branches, employees, depositors, investors, yrs. of operation are considered as inputs. Using SFA, the overall PE of CB and IB are 0.68 and 0.92 while CEs are 0.88 and 0.75 respectively. It shows that PE for CB and CE for IB are expected to provide significant insights to policy makers and management considered optimal utilization of capacities and resources in Bangladesh.

Keywords: Profit and Cost Efficiencies, Islamic Banks, Conventional Banks.

1. Introduction

Structures of banking industries of Bangladesh have been undergoing changes due to introduction of the development ideas such as technological advent, modern banking mechanism etc. So the efficiencies of past as well as present banking services are very crucial for the creditors/investors, policy makers to take development tasks for the economic development in a country. Moreover, bank management is very much interested to know how efficiency/inefficiency of profit and cost of bank is evolving in the banking industries due to increasing market competition.

1. M.S.S. in Economics in 1994 from National University, Dhaka, Bangladesh and PhD in Economics in 2014 from Jahangir Nagar University, Savar, Dhaka, Bangladesh

Journal of Islamic Economics, Banking and Finance, Vol-12, No. 1, Jan - Mar, 2016 64

Traditionally Conventional Banking system considers that banks get profits by selling their products collecting deposits from the depositors at a lower interest rate, further to reselling those deposits to the borrower comparatively higher interest rate depend on their relatively advantages at collecting information and considering banking risk (santos, 2000). So, Conventional Banking system earns profits from the interest rate spread in between borrowers and depositors. On the other hand, Islamic banking system operates the same intermediary functions but can not pay a predetermined interest to the depositors and does not receive a predetermined interest from clients. However, the profits are based on PLS gathered settlement with the depositors and borrowers. There is service oriented banking that is also similar to the Conventional Banking system. Therefore, Islamic banking may be considered as a different characteristics banking stream where interest is prohibited and it maintains PLS which is based on Quranic commands using Islamic shariah principles ( Ariff, 2006).

Nowadays Conventional Banking system seems to have competitive advantages over Islamic banking system because of long banking history, sustainable banking experience and accepting interest rate which is main source of banks’ profits. Moreover they do not

share losses with borrowers. Islamic banks, on the other, are claimed to be better in terms of banking efficiency than that of Conventional Banks.

This study will focus on the performance of both types of banking in the context of productivity and profitability. The main aim of this paper is that the two banking systems will be compared in terms of profit and cost efficiency of CB and IB during the period 2004-2008 using SFA in Bangladesh.

The remainder of this paper has been divided into four sections namely review of literature, methodology (Data & variables, stochastic frontier analysis, stochastic cost and profit frontiers, formulation of profit and cost function and Model identification), results & discussions and finally conclusion & recommendations.

2. Review of Literature

First Sherman and Gold (1985) studied banking efficiency measurement using frontier approaches. After that, a lot of studies have been conducted using frontier analyses to measure banking efficiency. Some extensive studies of efficiency have been done in the developed countries and majorities of those reflected on Conventional Banking (Berger and Humphrey, 1997; Goddard et al. 2001). Although nowadays Islamic


banking has been established in all over the world especially in Muslim countries, there are very limited studies done in terms of efficiency of Islamic banks. However, some studies have been conducted to evaluate the performance of Islamic banks in terms of profitability and banking characteristics.

All studies in this area have been divided into two groups. In the first group, there are studies which assess the Islamic banking performance using simple financial ratios (e.g., Bashir, 1999; Hassan and bashir, 2003; Bader Ariffi and shams her, 2007). Moreover of those studies, some have been conducted comparing with Conventional Banks. In the second group, there are studies which focused on efficiency of banks using frontier approaches. In addition to these studies are classified into three folders namely i) studies that reflect Islamic banks’ efficiency only (e.g., Yudistira, 2004; Brown Skully, 2005; Hassan, 2005; Bader, Ariff and Taufiq 2007), ii) studies that evaluate efficiency of Conventional Banks ( e.g., Weill, 2004; Bos , 2006 and Barder, 2007) and iii) studies that assess and compare the Conventional Banks’ efficiency with Islamic banks’ efficiency ( e.g., Al-shammari, 2003; Al-jarrah and Molyneux, 2003; Hussain, 2004; Bader, Shamsher and Taufiq, 2007). Despite a lot of studies regarding bank efficiency in the developed economy, a few number of studies have been done in the developing countries ( e.g., Al-Faraj, Alidi and Bu-Bshait, 1993 for Saudi Arabia; Zaim, 1995, Bhattacharya, lavell and sahay, 1997 for india; Isik and Hassan, 2000a,b for Turkey; Dilruba, 2005 and Rahman and Islam, 2011 for Bangladesh ).

Many studies during the 1990s have conducted on estimates of cost efficiency (e.g., Berger, Huster and Timme, 1993; Resti, 1997) avoiding the profit or revenue efficiency of banks’ operations. Indeed, banks might be solvent getting more profit although they incur the highest costs and show highest inefficiencies (e.g., Berger and Humphrey, 1997; Berger and Mester, 1997). Comparing with studies of cost efficiencies, a few number of profit efficiency studies have been done resulting cost efficiency levels are much higher than profit efficiency levels indicating most inefficiencies levels are on the profit side in banks (Maudos et al. 2002).

In maximum studies, profit efficiency is calculated using parametric approach namely works of Deyoung & Nolle (1996), Berger and Mester (1997) and Deyoung & Hasan (1998).

Stochastic Frontier Approach (SFA) is a method that can be used in measuring efficiency of cost and profit in a bank. It has been experimented by a number of researchers. Some of them are Humphrey(1991), Kwan And Eisen beis(1996), Berger and Humphery


(1997), Bhattachayya et al. (1997), Isik (2002), Bedari (2002), Nazirrudin and Elrhman (2003), Hasan (2005). Sarker (1999) observed the growth, structure and performance of Islamic banking in Bangladesh.

Ahmad and Hassan (2007) examined existing legal and regulatory issues of Islamic banking in Bangladesh. Islamic banking system as a viable alternative banking has been judged by them. They prescribed some recommendations for smooth development of Islamic banking. One of those argues that separate monetary policy should be incorporated for developing Islamic money market.

Mohamad et al. (2008) compared Conventional banks and Islamic Banks through measuring cost and profit efficiency using Stochastic Frontier Analysis (SFA). They have taken 80 banks of which 37 Conventional banks and 43 Islamic banks from 21 OIC countries as international evidence. Moreover, it evaluates the efficiency based on their size, age and region. The results showed that the overall efficiency of CB and IB are not different significantly. But, there is a scope to minimize the cost as well as maximize the profit in both systems of banking for betterment of their performance. In addition, comparing between big with old banks, there are no significant differences in their mean efficiency scores. Therefore, it is indicated that age and size did not influence on the performance of both banking streams. However, in fine, the findings of this paper have gone in favor of Islamic banking streams.

Hamiltona et al. (2010) studied cost and profit efficiency of Jordanian banking system during the period 1993-2006 using parametric approach i.e. SFA. There are three efficiency measurement of Jordanian banking sector that have been estimated i.e. cost efficiency, alternative profit efficiency (imperfect competition) and standard profit efficiency (perfect competition) in their study. The results showed firstly the profit efficiency has been considerable below those comparing to cost efficiency in all over the banking system. On the other hand, alternative profit efficiency is less than standard profit efficiency. Moreover, the cost efficiency of Islamic banks is lower than that of investment and commercial banks but profit efficiency (alternative) of those banks more prominent.

Shamsher et al. (2010) measured and compared cost and profit efficiency of 37 Conventional Banks and 43 Islamic banks which are considered from 21 OIC countries respectively. They used SFA for finding efficiency of 80 banks during the period 1990-2005. The results reflected that there are no significance difference in between small versus big banks and old versus new banks in terms of average efficiency scores in both


banking systems. However, the overall findings are in improved of the latest Islamic banking stream.

Kamil et al. (2010) studied profit efficiency consequently causing factors of profit efficiency on Bangladesh banking industry. They used stochastic frontier technique to determine profit efficiency among 20 banks of which NCBs, IBs, FBs and PCBs during the period 2001-2007 considered translog production function. The findings showed that the profit efficiencies have been improved over the years in all type of banking. Moreover, NCBs are significantly less efficient compared to IBs, FBs and PCBs. The average efficiency of banks is 0.664 in a year wise while it is 0.639 group-wise in this study. However AB bank Ltd. is the lowest position (0.35) and Dhaka bank Ltd. is the highest position (0.89) in terms of profit efficiency in this study respectively.

Rahman and Islam (2011) estimated branch-wise cost and profit efficiency of Islami Bank Bangladesh Limited (IBBL) using SFA during the period 2003-2007. Results show that the average profit efficiency was much better than the average cost efficiency during the study period.

Yahya et al. (2012) compared Islamic banks and Conventional banks in terms of efficiency level of Malaysian banks. They used Data Envelopment Analysis (DEA) considered three years. The findings showed that the efficiency levels of both bankings are not statistically difference though the foreign banks inclusion might be disturbs that results because of foreign banks’ different capital structures. This paper showed that though Islamic banking operation is new advent in the banking system, they have been performing their activities like conventional ones.

Rahim et al. (2013) measured efficiency of Islamic banks using DEA (Intermediation approach) taking 63 Islamic banks during the period 2006 to 2009 for comparing MENA and Asian countries in their study. The study identified the causes of technical inefficiency of the Islamic banks as scale of operations to their banking. However, in general, pure technical efficiency achieved high scores; the Islamic banks tackled their management and costs properly through scale effects on the operations of the banking. Finally, findings showed that the Islamic banks of Asian countries are more efficient compared to MENA countries. Interestingly, maximum banks have been found better performance in terms of efficiency in Gulf Cooperation Countries (GCC). In this study, it is also found that the main determinants for their efficiencies are country’s economic condition. So, identifying the utilizing resources is taken to use for achieving their healthy efficiency and confirm increasing growth in their Islamic banks.


Kamarudin et al. (2014) compared performance of 73 banks in terms of various efficiencies where 47 CBs and 27 IBs in Gulf Cooperation Council (GCC) countries during the period 2007 to 2011. Using DEA method with intermediation approach, the profit, revenue and cost efficiencies were measured where IBs’ efficiencies are found lower levels compared to those of CBs’. This study also exhibited that revenue efficiency is the main cause which leads the profit efficiency of these banks. Moreover, the determinants have been identified that could increase the revenue as well as improve the profit efficiency levels using Multiple Regression Analysis (MRA) in GCC Islamic banks. The results showed that four banks have specific factors (asset and management quality, liquidity and non-traditional operations) to cause improve the revenue efficiency. As a consequently, the improvement of the performance of GCC IBs was also affected by the macro indicator inflation and concentration ratio of the three banks which dominants the other banks. Therefore, this study has contributed the valuable knowledge to enhance the properly operating into both CBs and IBs and also suggested that banks’ management and policy makers simultaneously have to work for optimum utilization of resources and more works have to be needed in this purposes.

In this study, SFA has been used because of service oriented banking business applying Battese & Coelli (1995 ) model.

3. Methodology

Data and Variables

The panel data is used in this analysis. The study period is 2004-2008. Out of 41 Commercial Conventional Banks 19 banks and out of 7 Islamic banks 5 banks are taken on the basis of 80% asset of total Conventional and Islamic banks respectively. For this study secondary data are collected from the annual reports of their selective banks.

There are several variables included for finding profit efficiency and cost efficiency using SFA in this study. The dependent variables are total cost and total Profit (pre-tax) and independent variables are total deposit, total asset, and total loans/investment, price of fund, price of capital, and price of labor. Moreover in SFA, some inefficient variables are considered namely number of branches, number of employees, number of depositors, number of investors and years of operation. The dummy variables are introduced to evaluate the technological change due to introduction of IT system and banker-customer awareness of their business activities i.e. customers’ counseling in the banking business.


Stochastic Frontier Analysis (Parametric) Every farm functions its own characteristics which is associated with coordination, hierarchy, incomplete contracts and monitoring with management costs etc. hence, this indicates that different form of farms need to evaluate to their performances. As a result Leibenstein (1966, 1976, 1978 and 1987) thought that production is always limited to be inefficient because of motivation, information, observation and institution problems with in the farm. This is considered to as X-inefficiency. But De Alessi (1983) criticized the above argument specified an incomplete model caused for the failure to optimize. So, from the previous literature indicate that the Stochastic Frontier Analysis (SFA) is a useful model if it could be used to the practical results on the theoretical issues raised.

The development of SFA (Koopmans, Debvecd and Shephard 1950s) was the theoretical efficiency which means a producer is technically efficient, if and only if, it is impossible to produce more of any output without producing less of some other output or losing more of some input.

Farrell (1957) provided first to evaluate productive efficiency empirically using the linear programming techniques. After his continuing of this study, he was influenced by Charnes, Cooper and Rhody (1978) who used DEA (non-parametric efficiency technique). Now, it is very useful method in the area of management science and other appropriate fields.

However, the work of development of SFA by Farrall (1957) was very remarkable which influenced on Aigner and Chu (1968), Seitz (1971), Timmer (1971), Afriat (1974) and Richmand (1974) works. Later on, all of these contributions had a great influence on the development of SFA.

Frontier defines to a boundary function. There are many boundary functions in microeconomic theory, namely production function which is indicated in a given set of inputs that considers the maximum output of the production.

Profit function gives maximal profit in a given input and output prices and cost function represents minimum cost, given input prices and output and so on.

Stochastic Profit and Cost FrontiersThere are many studies using SFA in evaluating banking efficiency (Kumbhakar et al. 2001; Berger and master, 2003; Bikkar and Bos, 2004; Koetter, 2005), Specially profit and cost efficiency (Kraft and tirtiroglu, 1998; Hassan and marton, 2003; bonin et al. 2005; Fries and taci, 2005; Bos and kool, 2006; and Kwan, 2006).


The characteristic virtues of SFA are that it includes both the random errors, e.g., due to well-known measurement problems and systematic differences between banks in the sample due to heterogeneity across banks (kumbhakar and lovell, 2000). From their study the important features considered a relative comparison of remarkably different banks. For instance, Conventional Banks versus Islamic banks, Foreign banks versus domestic banks etc. Therefore, explicitly allowing for both environmental factors and random errors are important.

The profit and cost stochastic frontiers are given below:

Qit = Xit ijβ + aUit + Vit and

Uit = Zit jδ + Wit

i) Where Qit is cost or profit (depending on the model; a =1 or -1 depending on cost or profit function). If a= 1 its meant cost function and if a = -1 it indicates profit function;

ii) Xit is the set of relevant independent variables;

iii) Uit is the value of efficiency to extract and is determined by a set of variables Zit and assumed by a half-normal distribution;

iv) Vit is a white noise i.e., N( 0,σ² ) error terms and so is Wit N(0,σ²);

v) i indicates bank and t represents time values of the bank;

vi) For cost function , Uit ≥ 0, 0 for the most cost efficient bank ( best practitioner) and increasing values imply more inefficient, If function is in natural log, then the most cost-efficient bank has a value of 1, the further the value from 1 the more cost inefficient.

vii) For profit function, Uit ≤ 0, 0 for highest profit. In logarithm, the values are ranged between 0 and 1, 0 for bank with the highest profit.

viii) These two models are simultaneously estimated by using maximum likelihood estimation; the methodology was advanced by Battese and Coelli( 1995), and the software, front 4.1, was produced by Coelli(1995).

Formulation of the Stochastic Profit and Cost Frontier

Deyoung and Nolle (1996) illustrated that cost-based function might misinterpret the nature of banking parameters and also impact on inefficiency models in banks. For example, banks may earn more revenue by decreasing cost efficiency. This revenue efficiency might accelerate to cost efficiency. So, if revenue efficiency takeover cost inefficiency, banks would be more profitable. Many studies like Berger and Master


(1999) and Berger and Deyoung (2001) suggested that profit optimization is better than cost minimization for the study firm performance because it is more complex to identify the economic developments of firms and their owners. For that reason, they will consciously take revenue account as well as cost account. Profit efficiency ability to achieve maximum profits for a given set of output which require the economic goal in a firm. Profit efficiency requires the same figure of managerial target to increase a managerial taka of revenues as to decrease a managerial taka of costs. At that sense profit efficiency comparatively better measurement at any efficiency gains.

There are two ways to measure the profit efficiency, alternative profit function and standard profit function. The standard profit function is generalized in terms of output prices and input prices. While the alternative profit function is recognized in terms of output qualities and input prices. In this analysis, the alternative profit function approach has been taken because the right hand side of the profit function is same as the cost function. The same functional computation form has also been used in cost function only sign change; Berger and master (1997, 1999) saw alternative profit and cost function which are closer to reality because some standard assumptions of perfect competition markets do not satisfy, for instance questionable pricing of products or different production quality among the banks. So, they thought that the alternative profit/cost function is the best measurement. Moreover, they identified four causes that give better information using alternative profit/cost efficiency. They are i) questionable quality of banking services ii) banks can not classify every output scale and mixed product iii) financial markets are imperfect iv) output prices are not accurately measure.

Berger and Deyoung (2001) used alternative profit function to calculate bank efficiencies in terms of geographical of bank expansion when better profit explanation and availability of data were there. They justified that output prices are not easy to measure for banks and also these prices vary bank to bank. So, in this study, we conduct the alternative profit function and cost function.

The translog production function has been used to calculate the profit and cost function which is given below:

Full-form of cost /profit function:


Where, Qit represents the output variables ( cost/profit) of the selected CB and IB; i = 1, 2,……19 for CB and i = 1,2,…… 5 for IB and t = time period ( 2004-2008).

1y = total deposit, 2y = Total loans/investment, 1p = price of fund, 2p = price of capital, 3p = price of labor, ijβ = Co-efficient of independent variables, a = Plus for cost function and Minus for profit function, ln = natural logarithm, And Where,

ititititititit wDDZZZZZu ++++++++= 2716.55.44.33.22.110 δδδδδδδδ

0δ = intercept term, jδ ( j = 1, 2, 3, 4, 5, 6, 7) is the co-efficient of delta explanatory variables. itZ .1 = Number of branches, itZ .2 = Number of employee, itZ .3 = Number of depositors, itZ .4 = number of investor, itZ .5 = years of bank operation, 1D = computerized or not, 2D = bank counseling or not and itw = error terms

If function is profit function then dependent variable is considered Qit is pre-tax profit and the other elements remained the same like cost function.

Cost function indicates cost minimizing whereas profit function means profit maximizing in the models.

Cost Efficiency: The cost efficiency exhibits a measure to close a bank’s cost to the best practice bank’s cost that produces the same bundle of output under the same conditions.

Profit Efficiency: The profit efficiency is observed by how to close a bank comes to earning maximum profit given its output level.

Model Identification

Before going to estimate of profit and cost efficiencies using SFA, it should be clarified what production function and associated variables are appropriate to play in this analysis.

So, the following hypotheses are important to be tested with generalized likelihood ratio statistics to decide that whether the stochastic production function is represented by the Cobb-Douglas production function or translog production function and also the inefficiency variables’ effects are not present in the model. There are four null hypotheses that are to be tested in this regard,

H0: ijβ = 0


The Cobb-Douglas stochastic frontier production function can be established to a translog SFPF.

H0: 0ˆ =γ

In every level, the inefficiencies variables are absent in the model.

H0: 076543210 ======== δδδδδδδδ

The stochastic technical inefficiency ( 2σ ) is not satisfied in the model.

H0: 07654321 ======= δδδδδδδ

There are no technical inefficiencies in the model.

The above hypotheses requires testing with the generalized likelihood ratio test statistic is established by,

LR =)ln(

)ln(2

1

0

HH−

= -2 ln( H0-H1) which follows the 2χ distribution.

Where, LR = Likelihood Ratio

In our analysis we apply translog profit and cost function frontier to estimate the frontier models because of the above first hypothesis rejected (Appendix: table-1 showed). However, the Cobb-Douglas functional form has been used widely in many studies. This simplicity, perhaps, is involved with a number of restrictive properties. One is important that the elasticity of substitution for the Cobb-Douglas function is equal to one. The other two restrictions on (C-D) function are constant input elasticity and return to scale. In the banking industries, because of complexity of banking variables, it is better to use the alternative functional form i.e. translog profit and cost function. The most popular alternative form, the translog form is used by Greene (1980b) to remove the Cobb-Douglas function’s restrictions. However, some drawbacks, i.e. multi-co linearity and degrees of freedom problems are associated in the translog functional form. There are so many studies attributed to estimate efficiencies using both Cobb-Douglas production function and translog functional form. However, in this case, it should be tested the null hypotheses that the Cobb-Douglas form is an adequate representation of the data, given the specification of the translog model. This can be tested by using the generalized likelihood ratio test.


To estimate profit and cost efficiency, the frontier version 4.1 (computer software) developed by Coelli (1995) has been used with the maximum likelihood estimation of parameters.

4 Results and discussions

Estimation of profit and cost efficiency using translog production function

The translog profit and cost function are estimated with 27 independent variables of that 7 inefficient delta variables. Table1 shows the MLE estimation of profit and cost function.

In profit function, out of 27 regresses (including inefficient variables) 23 variables are statistically significant. Of them loans, price of capital, square of loan, combined deposit and loan, square of price of fund, square of price of capital, combined price of fund and price of labor, combined price of capital and price of labor, combined deposit and price of capital and combined loan and price of labor are positively significant with profit function and only one inefficient variable named number of depositors is negatively related with profit function. However, Out of 23 variables 7 variables are negatively significant with profit function namely deposit, price of labor, square of deposit, square of price of labor, combined deposit and price of labor, combined loan and price of fund, combined loan and price of capital . These suggest that all the positive and non-positive influence variables significantly related to the profit function which was very much reasonable. Moreover, in the context of price of labor suggesting that the negative influence of the labor cost to the profit function of a bank are to be likely. Alone loan was positive and significant in relation to the profit function. Whenever it combines to the price of fund and price of capital the scenario of result show opposite but significant with the profit function. This is also countable for the banking business because their activities of modes are running to the opposite direction into business.

In cost function, there are some significant variables that showed in the same table 1. Of 27 regresses, 11 variables are statistically significant of cost function. There are 6 variables namely deposit, loans, price of capital, price of labor, combined deposit and loan, combined price of capital and price of labor and combined loan and price of fund which are positively significant with cost function. However, 5 variables are negatively significant with cost function mentioning price of labor, square of price of labor, combined deposit and price of capital and combined loans and price of labor. The all inefficient delta variables are statistically insignificant in cost function.


Table 1 MLE Results (Stochastic Frontier Approach) of the Translog Profit and Cost Function for the Combined Banks (CB and IB) (2004-2008)

Number of VariablesProfit Cost

Co-efficient t-value Co-efficient t-value Constant -11.998 -17.225 -18.746 -5.931.Deposit -1.723 -14.292 5.686 5.5082.Loan/Investment 7.265 25.938 1.812 2.726

3.Price of fund -1.202 -1.448 1.825 1.123

4.Price of capital 4.402 7.214 3.513 2.942

5.Price of labor -9.552 -12.738 5.28 -2.408

6.Deposit*Deposit -0.11 -5.644 0.033 6.8

7.Loans*Loans 0.135 6.829 -0.003 -0.633

8.Deposit*Loans 0.747 9.762 0.749 3.726

9.Price of fund* Price of fund 0.336 9.909 0.288 1.242

10.Price of capital* Price of capital 1.426 9.759 1.278 1.274

11.Price of labor* Price of labor -0.458 -9.525 -0.629 -5.88212.Price of fund* Price of capital -0.46 -0.898 -0.145 -0.19913.Price of fund* Price of labor 0.995 2.206 -0.19 -0.209

14.Price of capital* Price of labor 1.132 11.083 1.498 2.298

15. Deposit*Price of fund 3.239 8.846 -0.6 -0.49916. Deposit*Price of capital 3.111 5.793 -2.945 -3.32517. Deposit*Price of labor -5.724 -17.428 2.209 1.90818. Loans* Price of fund -3.198 -10.754 0.335 0.31319. Loans* Price of capital -3.981 -7.574 2.305 2.35820. Loans*Price of labor 7.543 17.257 -1.142 -1.073

Inefficient Model

Constant -2.503 -2.838 1.365 2.178No. of Branches 1.395 2.547 0.105 0.478

No. of employees 1.122 1.434 -0.463 -1.312

No. of depositors -1.581 -3.46 0.147 0.694

No. of Investors 0.997 1.798 -0.165 -0.948Yrs. of operation 0.412 0.569 -0.218 -1.549Computerized or not( Dummy) -2.416 -9.208 -0.025 -0.284Counseling or not(Dummy) -1.016 -5.279 0.051 0.461

Variance Parameters

Sigma-squared 0.926 17.443 0.029 6.429

Gamma 0.999 6962718 0.256 1.682

Log likelihood value 7.439 53.449

Note: MLE= Maximum Likelihood Estimator, CB = Conventional Bank, IB = Islamic Bank


In the cost function, it is expecting that all input prices are related to cost positively. But our surprising results of cost function show that the price of fund is insignificant. On the other hand, price of capital is positively significant and price of labor is negatively significant with cost function respectively. However, the elasticity of price of capital is greater than the elasticity of the price of labor. This indicates that bank can emphasis more personnel expenditure rather than profit operation when price increase. Moreover the price of capital is often under the registered inflation rate in this study. So, positive relationship with cost function is logical.

Table 2 Bank-wise (CB and IB) Profit and Cost efficiency using Stochastic Frontier Approach (2004-2008)

Banks 2004 2005 2006 2007 2008Profit Cost Profit Cost Profit Cost Profit Cost Profit Cost

Islamic BankIBBL 0.56 0.98 0.61 0.98 0.71 0.99 0.88 0.99 0.93 0.99SIBL 0.35 0.96 0.30 0.96 0.54 0.94 0.99 0.92 0.97 0.85AIBL 0.77 0.86 0.96 0.86 0.81 0.91 0.66 0.95 0.96 0.85EXIM 0.73 0.74 0.73 0.74 0.81 0.85 0.87 0.88 0.75 0.92Shahjalal 0.13 0.69 0.84 0.69 0.96 0.68 0.99 0.70 0.84 0.83Mean 0.51 0.85 0.69 0.85 0.77 0.87 0.88 0.89 0.89 0.89Conventional BankAgrani 0.05 0.99 0.04 0.99 0.44 0.99 0.40 0.99 0.50 0.99Sonali 0.18 0.99 0.15 0.99 0.05 0.99 0.05 0.99 0.36 0.99Janata 0.05 0.99 0.44 0.99 0.05 0.99 0.43 0.99 0.99 0.99Rupali 0.27 0.99 0.45 0.98 0.29 0.97 0.09 0.97 0.63 0.97Pubali 0.33 0.98 0.72 0.97 0.71 0.90 0.62 0.97 0.86 0.97NBL 0.47 0.98 0.62 0.95 0.82 0.96 0.98 0.96 0.87 0.96The city 0.79 0.97 0.94 0.94 0.75 0.95 0.97 0.96 0.77 0.98AB 0.35 0.96 0.57 0.95 0.44 0.95 0.98 0.96 0.99 0.96IFIC 0.28 0.95 0.35 0.95 0.65 0.92 0.82 0.95 0.72 0.97EBL 0.78 0.97 0.99 0.86 0.97 0.77 0.86 0.93 0.99 0.94Uttara 0.76 0.86 0.85 0.93 0.88 0.96 0.94 0.97 0.77 0.97

Dutch 0.42 0.97 0.61 0.85 0.73 0.86 0.76 0.81 0.99 0.82

South 0.48 0.85 0.7 0.94 0.99 0.92 0.99 0.93 0.99 0.94Prime 0.7 0.91 0.64 0.94 0.75 0.94 0.87 0.96 0.87 0.96Dhaka 0.63 0.93 0.75 0.91 0.65 0.94 0.74 0.90 0.74 0.94Mercantile 0.63 0.90 0.81 0.79 0.89 0.87 0.80 0.91 0.81 0.85Bank Asia 0.94 0.51 0.74 0.80 0.85 0.74 0.99 0.86 0.80 0.92SCB 0.90 0.83 0.86 0.95 0.99 0.96 0.90 0.96 0.99 0.95CITI 0.99 0.46 0.96 0.56 0.98 0.70 0.81 0.76 0.80 0.82Mean 0.53 0.89 0.64 0.91 0.68 0.91 0.74 0.93 0.81 0.94Combined 0.69 0.91 Mean

Note: CB = Conventional Bank, IB = Islamic Bank


Table 2 shows the stochastic profit and cost efficiency estimations of CB and IB during the years 2004-2008. The overall mean of profit efficiencies of CB and IB are about 68 and 75 percent during the period 2004-2008 respectively. The mean of profit efficiency of combined bank (CB & IB) is around 69 percent. The above profit efficiencies indicate that about 68 percent profit is generated in CB while 75 percent is generated for their potential profits on an average in IB. The results imply that the profit efficiency of IB is better than that of CB even it is greater than generating profit in combined banks. Finally, it seems that the profit efficiency of Islamic bank is relatively not bad compare to CB as well as combined banks. For instance, on an average, it is showed that around 64 percent in U.S banks (Berger and Humphrey, 1997) and about 72 percent in Spanish banks (Lozano, 1995) were profit efficiencies.

The inter-temporal comparisons within CB the profit efficiencies are varied from year to year (2004-2008). Although the profit efficiencies of CB and IB are more or less stable during the periods of 2006 to 2008 they fell down moderately during the year 2004 to 2005. Results also indicate that profit efficiencies of both banks in 2004 and 2005 are much less than that of 2005, 2006, 2007 and 2008 respectively. However the all profit efficiencies show that those are gradually increasing year to year i.e. 2004-2008.

The overall cost efficiency of combined banks is about 91 percent and it is far better than profit efficiency (0.69) of combined of that banks. The individual system of banks i.e. CB and IB, the cost efficiencies reported that they are about 92 percent in CB. Here the cost efficiency of CB is better than that of IB.

On the other hand, the inter-temporal comparison of the cost efficiencies of CB and IB suggests that they are more or less stable within the study period. However, few banks show the below 80 percent cost efficiency in this regards.

Finally, the overall comparison of profit and cost efficiencies in between CB and IB, the profit efficiency of IB is better than that of CB. On the other hand, the cost efficiency of CB is improved compared to that of IB during the years.


Table 3 Frequency Distribution of Profit and Cost efficiencies measure of CB and IB using Stochastic Frontier Approach (2004-2008)

Efficiency% Profit Cost

CB % IB % CB % IB %<20 9 9.47 1 4.00 0 0.00 0 0.0021-25 0 0.00 0 0.00 0 0.00 0 0.0026-30 3 3.16 1 4.00 0 0.00 0 0.0031-35 3 3.16 1 4.00 0 0.00 0 0.0036-40 2 2.11 0 0.00 0 0.00 0 0.0041-45 6 6.32 0 0.00 0 0.00 0 0.0046-50 3 3.16 0 0.00 1 1.05 0 0.0051-55 0 0.00 1 4.00 1 1.05 0 0.0056-60 1 1.05 1 4.00 1 1.05 0 0.0061-65 9 9.47 1 4.00 0 0.00 0 0.0066-70 2 2.11 1 4.00 1 1.05 4 16.0071-75 10 10.53 4 16.00 1 1.05 1 4.0076-80 9 9.47 1 4.00 5 5.26 0 0.0081-85 7 7.37 4 16.00 7 7.37 6 24.0086-90 10 10.53 0 0.00 8 8.42 2 8.0091-95 3 3.16 1 4.00 26 27.37 5 20.0096-100 18 18.95 8 32.00 44 46.32 7 28.00All 95 100 25 100 95 100 25 100Mean 0.68 0.75 0.92 0.88Max. 0.99 0.99 0.99 0.99

Min. 0.04 0.13 0.46 0.68


Table 3 reports that the frequency distribution of profit and cost efficiencies during the year (2004-2008). In CB more or less 40 percent banks are on the profit efficiency scores i.e. 71-75, 86-90 and 96-100 ranges respectively. The rest of the banks of CB are frequently distributed on the other profit efficiency scores, although around 10 percent banks are on the lowest profit efficiencies scores i.e. <20. On the other hand, in IB, about 64 percent banks are on 71-75, 81-85, and 96-100 profit efficiencies scores respectively. The rest of the IB is frequently distributed on the other profit efficiencies scores.

In respect of cost efficiency, most of the CB and IB i.e. 74 percent and 48 percent are on the 91-95 and 96-100 efficiency scores respectively. The results show that the cost efficiencies of CB are better than that of IB. Below 45 percent ranges, there are no CB and IB laid down in order to cost efficiencies.


In fine, the illustration of Table 4 reflects that the profit efficiency (0.75) of IB is in good position compared to that of CB (0.68). On the contrary, the opposite result showed that the cost efficiencies 0.92 and 0.88 are in CB and IB respectively.

Eventually, it is concluded that regarding profit and cost efficiencies of the two banking systems that the more generating profit and the less controlling cost are attributed in IB but it is opposite in CB.

Table 4 Summary Statistics for the Stochastic Profit and Cost efficiencies of CB and IB (2004-2008)

YearsProfit

EfficiencyCost

Efficiency

Mean(IB) S.D Mean(CB) S.D Mean(IB) S.D Mean(CB) S.D2004 0.51 0.27 0.53 0.29 0.85 0.13 0.89 0.152005 0.69 0.25 0.64 0.26 0.85 0.13 0.91 0.102006 0.77 0.15 0.68 0.30 0.87 0.12 0.91 0.092007 0.88 0.13 0.74 0.29 0.89 0.11 0.93 0.062008 0.89 0.09 0.81 0.18 0.89 0.07 0.94 0.05


Figure 1 Line diagrams of Profit Efficiencies of CB and IB


Figure 2 Line diagrams of Cost Efficiencies of CB and IB

Table 4 shows that the mean and standard deviation of profit and cost efficiencies of CB and IB during 2004-2008. Columns of Table 4 are depicted in figures 1 and 2.The profit efficiencies of both banking system are gradually increasing from 2004 to 2008. On the other hand the cost efficiencies of CB and IB are steadily increasing from 2004 to 2008. However, comparing the profit and cost efficiencies of both banking system, it can be said that the profit efficiencies of IB is better than that of CB and the cost efficiencies of CB is better than that of IB.

5 Conclusion and Recommendations The two banking systems, i.e. Conventional Banking (CB) and Islamic Banking (IB) are performing simultaneously in Bangladesh. The former has been o p e r a t i n g since long while the latter has been functioning for two to three decades only. In this paper, the profit and cost efficiency of CB and IB are calculated using SFA. The panel data are collected from 19 CBs selected from 42 CBs and 5 IBs selected from 7 IBs for the period from 2004to 2008. The translog production function has been used as it has been identified to be the adequate functional form. The overall profit efficiency of IBs (0.75) is better than that of CBs (0.68). On the other hand, the overall cost efficiency of CBs (0.92) is slightly higher compared to that of IBs (0.88). However, profit and cost efficiencies are exhibiting up-ward trends with respective period. It indicates that the overall banking performance is improving in terms of profit and cost efficiency. However performance of IBs is comparatively better than that of CBs.


The competition of Islamic banks with Conventional banks is expected to increase further in the future due to globalization. The findings from Stochastic Frontier Analysis (SFA) in this study, profit efficiencies for Conventional banks and cost efficiencies for Islamic banks in Bangladesh, are expected to provide significant insights to policy makers and management with respect to the optimal utilization of capacities and resources allocations respectively. It is also expected that the results will open further avenues for research works in the banking area.

Appendix

Table I Likelihood ratio test of different hypotheses for profit/cost function of the banks

Null HypothesesLikelihood ratio test

Critical value of Chi-square e*

Decision

βij = 0

0=γ076543210 ======== δδδδδδδδ

07654321 ======= δδδδδδδ

111.73180.26212.16101.45

24.38(15)5.41(1)20.97(9)17.76(7)

Reject H0

Reject H0

Reject H0

Reject H0

Note: Critical values of chi-square are taken from Kodde & palm (1986) of Table 1 and * indicates the critical value of chi-square at 1% level of significant. Parentheses figures are represented the degrees of freedom.

Table II Brief Description of the Variables for Combined Banks (CB & IB)Variables

Description

CostProfit paid on deposit, operational expenses, salary allowances and others.

Profit/Loss Total Profit or loss of the banks

Total Deposit Total amount of deposit ( demand deposit, term deposit)

Total Asset Total amount of asset

Total Loans or Investment Total amount of loans or investment of bank

Price of Fund Total profit and non-profit expenses/total deposit

Price of Capital Non-profit expenses/average assets

Price of Labor Total salary expenses/total asset

Number of Branches Total number of branches of bank

Number of Employee Total number of Executives, Officers and sub-staffs

Number of Depositors Total deposit clients

Number of investors Total investment clients

Years of operation Years of Operation up to 31 December, 2008

Computerized or not (Dummy Variable) Bank computerized or not

Counseling or not ( Dummy Variable) Client counseling or not


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