Efficiencies Comparison of Commercial Banks of SAARC Countries

Transcription

1 Journal of Management, Economics and Finance, Vol. 1, Issue 1, July 2011 Efficiencies Comparison of Commercial Banks of SAARC Countries Dr. G.S.K. Niazi Assistant Professor Quaid- e- Azam University, Islamabad Haseeb Shahid Lahore Business School, The University of Lahore Muhammad Akram Naseem Lecturer, Lahore Business School, The University of Lahore Ramiz ur Rehman Assistant Professor, Lahore Business Sc hool, The University of Lahore ; Muhammad Yasir Rafiq Lecturer, Lahore Business School,The University of Lahore ABSTRACT This study investigates the comparison between the efficiency of Commercial banking sector of SAARC Countries (Pakistan, India & Srilanka).For this study, we take sample of all Commercial banks of (Pakistan, India & Srilanka) for the period of ( ). A DEA model is applied to measure the efficiencies of banking sectors under CRS and VRS approach. The results indicate that the TE and P.TE of these Countries are very impressive i.e. (98% & 99%) under CRS and VRS models, as well as SE shows similar pattern. The spearman correlation test shows that choice of inputs/outputs used for this study are closely correlated to each other; however, further studies on similar pattern are required for rest of SAARC Countries. Keywords: Data Envelopment Analysis (DEA), Technical Efficiency (TE),Pure Technical Efficiency (P.TE), Scale Efficiency (SE), Constant Return to Scale (CRS), Variable Return to Scale (VRS) 15 ISSN: London Research Syndicate 2011

2 Journal of Management, Economics & Finance. Vol. 1, Issue 1 July 2011 INTRODUCTION During last two decades, an increasing pace of financial market liberalization has been observed in the developing countries. This resulted in banking markets of different countries becoming highly integrated. This opportunity has allowed foreign banks to set up branches in other countries, and broaden its competitive edge. Such increased competitive pressures would indirectly force the local banks to adapt and operate efficiently in the new environment. Banks that fail to do so will be driven off the market by the highly efficient ones. Therefore, information on bank efficiency when compared across nations is important, as this will enable policy-makers to formulate appropriate and sound policies to direct their banking industry. The role of financial institution in development of any nation is formidable. Economic growth of any nation depends on many factors.but role of financial institutions specially Banks are mandatory.an efficient financial sector is necessary for better usage of financial resources of a nation. Economic development can be achieved only by using the available resources in a better way and hence improving the output performance. Proper utilization of given available resources does indicate the term Efficiency. In order to allocate resources efficiently banks should be sound and efficient. The objective of this research paper is to calculate the commercial banking efficiency of SAARC countries and to understand the results obtained from the study conducted in later sections. But first we need to understand the terms SAARC Countries and Banking efficiency. The term SAARC refers to South Asian Association for Regional Cooperation is composed seven Asian countries i.e. Bangladesh, India, Pakistan, Srilanka, Bhutan, Maldives and Nepal. SAARC is an association based on consciousness of objectives such as, Peace, Freedom, Social Justice and Economic Prosperity are best achieved by fostering mutual understanding, good neighborly relationships and meaningful cooperation among the member states which are bound by ties of history and culture. The idea of creating such association was first mooted in May After consultation foreign secretaries of seven nations meet for the first time in Colombo, which was followed by series of meetings which resulted in First SAARC Summit held in 7-8 December 1985 in Dhaka formally establishing the SAARC. Main objectives of SAARC are welfare of people of South Asia and hence improving their quality of life, accelerate economic growth followed by social progress and cultural development in the region and to provide all individuals the opportunity to live in dignity,promoting and strengthen collective self-reliance among member countries etc.apart from above mentioned objectives SAARC also does follow some set of principles as well which mainly highlights mutual cooperation and strengthening the weak member countries with each other support. The term Efficiency refers to the maximizing of outputs in such a way the input resources are less utilized. Banking efficiency is defined as difference between observed quantity of input and output variables with respect to optimal quantity of input and output variables. The efficient bank can achieve a maximum value of one in comparison to inefficient bank can reduce to level of zero. 16 In the last two decades, the efficiency and productivity analysis of the banking industry has been investigated extensively. The emphasis of this area now spreads widely from scale and scope ISSN: London Research Syndicate 2011

3 Journal of Management, Economics and Finance, Vol. 1, Issue 1, July 2011 economies to the cost and profit efficiency. These studies apply the non-parametric methods such as the data envelopment analysis (DEA) and parametric methods such as the stochastic frontier approach (SFA) to discuss the various issues in the efficiency measurement, for example issues of informing government policy like deregulation, merger and acquisition, problem loans and managerial performance, as well as addressing methodology issues and international comparisons. This cross-country comparison of bank efficiency in SAARC countries is relatively lacking in the literature and there hasn t been any intensive work being done on cross-country efficiency comparisons for banks in the developing countries. This paper aims to analyze the technical efficiency of the SAARC countries Banks through a non parametric linear programming method called Data Envelopment Analysis (DEA) and compare the relative efficiency of banks across countries. These banks are from 3 different countries representing the SAARC countries. They include banks from India, Pakistan, and Sri Lanka. In this research we are going to do a comparative study of Commercial banking sector of SAARC countries. As of current we are choosing Commercial Banks of SAARC countries for time period of ( ). In following parts of current issue we will discuss previous research in the said topic, Data methodology followed by results and hence we draw a conclusion in final section of research. LITERATURE REVIEW In context of prior research regarding banking efficiency review, substantial work has been done on US and European banking markets and similarly in rest of world but work on SAARC countries banking industry is still in its infancy. Our literature review will study two different aspects. 1. Banking efficiency using various methods 2. Cross-Country Banking efficiency comparisons review First we look at individual countries banking efficiency review using various efficiency methods. H Iftekhar and M Katherine (2000) reviewed the Development and Efficiency of Banking sector in a Transitional Economy in context of Hungarian experience. Econometric Frontier Approach (EFA) model has been used to estimate profit and cost inefficiency of 154 banks for the period of ( ).Results indicate that the average bank could improve its cost and profit categories by 21.6 and 29.1 percent respectively, thus matching its performance with best practiced Banks. C Ana and D Jean (2000) reviewed the efficiency of Portuguese banks for the period of ( ). Non-parametric programming technique, Data Envelopment Analysis (DEA) model has been used to estimate efficiency of 20 Banks, which were divided in to segments of Old Commercial banks, Old savings banks and New banks. The results show that over the period of time technological changes as calculated by DEA model proves that efficiency of new banks has been raised by 59% as compared to old banking system. D.A Cavdet et al (2000) examined the Banking efficiency in a pre and post-liberalization environment by studying in context of Turkish experience. Non-parametric programming technique, Data Envelopment Analysis (DEA) model has been used to calculate efficiency changes in Banking sector 17 ISSN: London Research Syndicate 2011

4 Journal of Management, Economics & Finance. Vol. 1, Issue 1 July 2011 w.e.f of liberalization program by ownership or by function for period of ( ) for the Sample banks ranging 29 ( ) to 53 (1991).The results show that total efficiency scores by functionality or ownership suggests, liberalization didn t provide anticipated efficiency gains. No efficiency scores have displayed consistent increase after introduction of new policy. Dr.A. A Reddy (2005) examined the competitiveness of Indian scheduled commercial banks in the deregulated period The data used in this analysis was used from annual reports of reserve bank of India. Efficiency change, scale efficiency and pure technical efficiency change between two periods has been estimated by using data envelopment analysis (DEA) and window analysis. The results indicate that there is an increase in technical efficiency and scale efficiency of most of the banks. Sample size of the study was 80 banks, out of which 27 public sector banks, 21 old private banks, 6 new private banks and 26 foreign banks. B K Sahoo et al (2007) examined the productivity performance trends of the Indian commercial banks for the period: Data Envelopment Analysis (DEA) model was used for the current research. Data set compromises of 100 banks for period of 8 years. Result of the study are indicative in many ways: first, the average annual trends in TE for all ownership groups have improved, indicating an affirmative gesture about the effect of the reform process on the performance of the Indian banking sector, second, foreign banks have a leading edge over both the nationalized banks in both operational and price measures of performance, which indicates that foreign banks are mostly strongly exposed to international markets, and are more sensitive to competitive pressures from outside the country, third, the higher cost efficiency accrual of private banks over the nationalized banks indicate that the nationalized banks though old, do not reflect their learning experience in their cost minimizing behavior due to X-inefficiency factors arising from government ownership. This finding also highlights the possible stronger disciplining role played by the capital market indicating a strong link between market for corporate control and efficiency of private enterprise assumed by property right hypothesis. And, finally, concerning the scale elasticity behavior, the technology- and market-based results differ significantly supporting the empirical distinction between returns to scale and economies of scale, which are most often used interchangeably in the literature. A Qayyum (2007) examined the yearly efficiency scores of 20 banks for period of ( ). Nonparametric programming technique, Data Envelopment Analysis (DEA) model has been used to estimate efficiency of 20 Banks for period ( ). The results show that efficiency score of banking improves from 65% in 1991 to 87.6% in This however indicates banks are able to expand their core business activities, they strengthened their capital base, improved asset quality and profitibilaty during the year 2005.These developments clearly indicate the increased competition among banks and improvement in efficiency of banking sector. 18 E Loukoianova (2008) examined the efficiency and profitability of Japanese banks from ( ). Non-parametric programming technique, Data Envelopment Analysis (DEA) model has been used to estimate efficiency and profitability of city Banks, Trust Banks, Regional Banks and Tier II regional banks of Japanese Banks for ( ).The results show that both groups of regional banks appear to be inefficient both in terms of cost and revenue relative to the city and trust banks. In addition, total factor productivity of both groups of regional banks has been flat over the last six years. However, Trust banks demonstrate highest profitability in terms of return on assets and equity. ISSN: London Research Syndicate 2011

5 Journal of Management, Economics and Finance, Vol. 1, Issue 1, July 2011 While both groups of regional banks perform worse than city and trust banks. But on the whole Japanese banks have steadily improved since S.L Seelanatha (2008) examined determinants of technical efficiency in the intermediation and in the assets transformation functions using 16-year (1989 to 2003) unbalanced penal data set from banking industry in Sri Lanka. Technical efficiency scores are estimated using the input-oriented constant return to scale (CRS) data envelopment analysis model (DEA model). Tobit regression model has been used for identifying the significance of the influence of various factors on technical efficiency. Variables representing profitability, liquidity and newness (new vs. old) have shown positive relationships with TE (I) and negative relationships with TE (A). On the one hand, size and inflation have indicated a negative relationship with TE (I) and positive relationships with TE(A). This finding showed that profitability and liquidity enhance the intermediary process of the banking industry giving incentives to managers for their effective decision making capability. S.L Seelanatha (2008) examined impact of reforms in the financial services sector in Sri Lanka in efficiency and productivity improvements in the assets transformation function of banks during the period of 1996 to Input-oriented data envelopment analysis (DEA) model is used to estimate efficiency and productivity improvements in banks in Sri Lanka. The study found reduction of efficiency gap between state-owned and privately-owned banks during the study period. Further to that the commercial banks have improved their productivity mainly on technological changes. Overall, this study found mixed evidence on impact of reforms in efficiency and productivity improvements. Burki & Niazi (2009) had explored that financial reforms in Pakistan Banking Industry had a significant impact on state-owned, private and foreign banks efficiency. M Dash and C Charles (2009) investigated the technical efficiency of Indian banks, segmented in terms of ownership. The data envelopment analysis (DEA) model was used with five input variables (viz. borrowings, deposits, fixed assets, net worth, and operating expenses) and four output variables (advances & loans, investments, net interest income, and non-interest income), and the efficiency scores were calculated for a sample of forty-nine major banks operating in India. D Canakci (2009) examined the effect of banking crises on performance of banking efficiency through testing on Turkish experience before and after crises. Ratio analysis and non-parametric programming technique,data Envelopment Analysis (DEA) model have been used to estimate the effect of banking crises on performance of Banking efficiency through testing on Turkish experience before and after crises for the period of ( ) which were divided in to two sections i.e., (precrises) which holds the years (1991,1992 and 1993) for 1994 crises and post-crises period of (1995,1996 and 1997).Similarly for crises pre-crises period was (1997,1998 and 1999) and post-crises period was (2004,2005 and 2006).The results indicates the efficiency changes during 1994 and crises measured different results for ROA and ROE during post and pre crises sessions. However, results of ratio analysis regarding measuring ratios other than profitability (costs and risk) seem to be not significantly different in post crises period in This could be attributed to difference in handling 1994 and in terms of banking sector. The results of DEA model also suggests that post crises period has resulted in higher overall mean efficiency of Turkish commercial banks. We found evidence that business cycle theory holds in Turkish crises experience. 19 ISSN: London Research Syndicate 2011

6 Journal of Management, Economics & Finance. Vol. 1, Issue 1 July 2011 The efficiency increase was quite significant in case of crises because after 1994 crises there were not restricting efforts for the banking sector. D P Gajurel (2010) examined the structure-performance hypotheses in the context of Nepalese banking industry for the period of ( ) under the Berger and Hannan (1993) empirical framework. Berger and Hannan approach is used to study the commercial banks in operation for the sample period of nine years from (2001 to 2009). Results suggest that traditional structure conductperformance hypothesis and quit life hypothesis are at work in explaining concentration-profitability relation and there are weak supports for efficiency structure hypotheses. The results of this study hold significant policy and managerial implications. Nobuyoshi et al (2010) examined the technical efficiency of Japanese trust banks. Stochastic distance function approach have been used for the study, which is suitable for analyzing complex trust banks but was never applied for Japanese trust banks. The sample in this study compromises traditional domestic trust banks, foreign-owned trust banks, trust subsidiaries and a fewer financial institutions but it excludes the commercial banks for the period of ( ). The empirical results indicates that traditional domestic trust banks have experienced superior technical efficiency as compared with foreign-owned trust banks and trust subsidiaries.however, mean efficiency value of traditional domestic trust banks also tends to decrease after consolidation.as a result of study Authors drew that entry barriers in the Japanese trust banking has had no significant effect on the technical efficiency of new entrants. This can be possibly attributed to the inequality in the conditions of competition, such as the permitted range of trust banking business, which has benefitted the incumbent traditional domestic trust banks. In other words, although entry barriers were gradually relaxed, the complete liberalization of business areas was not necessarily implemented. Seelanatha (2010) examined structure-performance relation for banking industry in SriLanka. Under the Berger and Hannan approach, the study used four hypotheses. The author found that traditional structure conduct performance argument is not held in the banking industry in Sri Lanka and the banks performance does not depend on either market concentration or market power of individual firms but on the level of efficiency of the banking units. Now we look at how banking efficiency analysis works on cross-country comparisons. Berg et al(1993) surveys 130 studies that apply frontier efficiency analysis to financial institutions in 21 countries. The primary goals are to summarize and critically review empirical estimates of financial institution efficiency and to attempt to arrive at a consensus view. Results indicates that the various efficiency methods do not necessarily yield consistent results and suggest some ways that these methods might be improved to bring about findings that are more consistent, accurate, and useful. Secondary goals are to address the implications of efficiency results for financial institutions in the areas of government policy, research, and managerial performance. Areas needing additional research are also outlined. 20 Allen, L. & Rai, A. (1996) estimate cost and profit efficiency of a global cost function for international banks to test for both input and output inefficiencies using SFA & DFA approach. Results indicate that for ( ) banks in 15 countries, the prevalence of input X-inefficiencies far outweighs that of output inefficiencies (as measured by economies of scale and scope). Moreover, the distribution-free model overestimates the magnitude of X-inefficiencies relative to the stochastic ISSN: London Research Syndicate 2011

7 Journal of Management, Economics and Finance, Vol. 1, Issue 1, July 2011 cost frontier approach. Large banks in separated banking countries (that prohibit the functional integration of commercial and investment banking) had the largest measure of input inefficiency amounting to 27.5 percent of total costs as well as significant levels of diseconomies of scale. All other banks have X-inefficiency levels ranging in the area of fifteen percent of total costs with slight economies of scale for small banks. Dietsch and Lozano-Vivas (2000) investigates the influence the environmental conditions have on the cost-efficiency of French and Spanish banking industries. A new methodology for cross-country comparisons of efficiency using a parametric approach. In particular, the specific environmental conditions of each country play an important role in the definition and specification of the common frontier of different countries. Results suggest that, without environmental variables, the costefficiency scores of Spanish banks are quite low compared to those of the French banks. However, when environmental variables are included in the model, the differences between both banking industries are reduced substantially. Overall, results demonstrate that environmental variables contribute significantly to the difference in efficiency scores between the two countries. Altunbas, et al (2001) extends the established literature on modelling the cost characteristics of banking markets by applying the flexible Fourier functional form and stochastic cost frontier methodologies to estimate scale economies, X-inefficiencies and technical change for a large sample of European banks between 1989 and The results reveal that scale economies are widespread for smallest banks and those in the ECU 1 billion to ECU 5 billion assets size range. Typically, scale economies are found to range between 5% and 7%, while X-inefficiency measures appear to be much larger, between 20% and 25%. X-inefficiencies also appear to vary to a greater extent across different markets, bank sizes and over time. This however suggests that banks of all sizes can obtain greater cost savings through reducing managerial and other inefficiencies. Apart from that technical progress has had a similar influence across European banking markets between 1989 and 1997, reducing total costs by around 3% per annum. The impact of technical progress in reducing bank costs is also shown to systematically increase with bank size. Overall, these results indicate that Europe's largest banks benefit most from technical progress although they do not appear to have scale economy advantages over their smaller counterparts. D stavarek (2003) examined the commercial banks efficiency in the Vise grad region before joining the EU and also to consider differences in efficiency across the countries. Non-parametric programming technique, Data Envelopment Analysis (DEA) model has been used to estimate efficiency of different banks for period of ( ).The Sample sets for every year were different in context of study as,59 banks in 1999, 72 in 2000, 70 in 2001 and 62 in 2002 respectively. The results show that average efficiency of banking intermediation in 2002, the V4 banking industries can be distinguished as more and less efficient. Czech and Hungarian banking sectors were on average evaluated as the most efficient followed with a, non-marginal distance, by the Polish banking sector. Only Slovak banking sector stands apart with a substaintional gap in efficiency scores. A Ataullah and H Le (2004) examined comparative analysis of evolution of technical efficiency in commercial banking industry in India and Pakistan during , a period characterized by farreaching changes in financial sector brought about by financial liberalization. Data Envelopment Analysis is applied to two alternative input-output specifications to measure technical efficiency, and 21 ISSN: London Research Syndicate 2011

8 Journal of Management, Economics & Finance. Vol. 1, Issue 1 July 2011 to decompose technical efficiency into its two components, pure technical efficiency and scale efficiency, furthermore analysis of consistency of estimated efficiency scores by examining their relationship with three traditional non-frontier measures of bank performance. Result indicates that: (1) technical efficiency of overall commercial banking industry improved in both the countries; (2) public sector banks in India witnessed improvement in both pure technical efficiency and scale efficiency, (3) public sector banks in Pakistan witnessed improvement in scale efficiency only; (4) pure technical efficiency and scale efficiency of private sector banks, foreign and domestic, in both the countries improved after liberalization; (5) due to high non-performing loans, banks are more efficient in generating loans and advances than in generating income from these assets, and (6) importance of size has declined after the implementation of financial liberalization. Fries and Taci (2004) examine the cost efficiency of 289 banks in 15 East European countries. Fforeign-owned banks have a larger share of total assets have lower costs and that the association between a country_s progress in banking reform and cost efficiency is non-linear. Early stages of reform are associated with cost reductions, while costs tend to rise at more advanced stages. Private banks are more efficient than state-owned banks, but there are differences among private banks. Privatised banks with majority foreign ownership are the most efficient and those with domestic ownership are the least. Carvallo and Kasman (2005) estimate cost and profit efficiency for Latin American and the Caribbean banking sectors. Using a model proposed by Battese and Coelli (1995), a common cost and profit frontiers with country specific environmental variables have been estimated for a panel of 427 banking firms from sixteen countries. The empirical analysis reveals the importance of the environmental variables in explaining the efficiency differences among countries. The results show that profit efficiency levels are well below those corresponding to cost efficiency, implying that the most important inefficiency is on the revenue side. The results further indicate that on average foreign banks are more efficient than domestic banks. Kasman and Yildirim (2006) examine the cost and profit efficiencies in commercial banking in the eight Central and Eastern European countries that became new members to the European Union. Common stochastic cost and profit frontiers with country-specific variables are employed in order to take into account macro-economic and financial sector conditions that vary over time and across countries. The impact of foreign ownership on performance is also examined. The results indicate a wide range of cost and profit inefficiency scores across countries and across different size groups. All banking systems in the sample display significant levels of cost and profit inefficiency and there does not seem to be any continuous improvement in performance over time. There is also some evidence that foreign banks perform, on average, better than domestic banks. 22 S Pereira et al (2007) examined the cost efficiency performance of 111 commercial banks in Bangladesh, India, Pakistan and Sri Lanka over The primary focus is to assess whether bank size, state ownership and stock exchange listing have significant effects on South Asian banks' efficiency performance. To this end, a Tran s log-form composite-error cost efficiency model, which allows for exogenous environmental influences, is estimated. The results indicate that the overall efficiency of South Asian banks declined over Larger banks and banks with widespread ownership through stock exchange listings were found to be relatively more cost efficient. In contrast, state-owned banks were less efficient. ISSN: London Research Syndicate 2011

9 Journal of Management, Economics and Finance, Vol. 1, Issue 1, July 2011 W Laurent (2008) examined the convergence in banking efficiency for European Union countries. Stochastic frontier approach has been used on banking efficiency measures for the period of ( ). The results show that significant reduction of the gap between the least and the most efficient banking sector between 1994 and 2005, i.e., in 1991 efficiency means range from 61% in Portugal to 78.90% in France, whereas it ranges from 80.32% in Spain up to 90.88% in Luxembourg in 2005.On the whole results suggests that overall improvement in banking efficiency for all investigated EU countries and thus impact a positive image on banking efficiency. METHODOLOGY AND MODEL SPECIFICATION Efficiency Measurement Efficiency of banks can be calculated by various methods. First we will have a short review of one of commonly used Banking efficiency tools. Berger and Humphrey (1997) provide an extensive account of 130 studies that used different frontier efficiency analysis for 21 countries. The tradional method of approaching the efficiency measurement issue is the financial ratio analysis. But there is a lack of agreement on the relative importance of various types of input or output under this method.moreover this method also doesn t consider the value of management actions and investment decisions that will effect future as opposed to current performance. It is a thus a short run measure and may be inappropriate for describing the actual efficiency of a bank for a long run. In addition to that, there are parametric and non-parametric frontier analyses used in measuring x-efficiency of financial sector firms. The parametric approach includes stochastic frontier analysis, the free disposal hull, while the nonparametric is the data envelopment analysis (DEA). Data Envelopment Analysis (DEA Model) The (DEA) approach refers to the ability of banks to control cost and generate revenues and was developed by Charnes, Cooper and Rhoades (1978).The (DEA) is a linear programming based technique for measuring relative efficiency and management performance of firms where presence of multiple inputs and outputs makes comparison difficult.it uses observed values of inputs and outputs and attempts to find which of the firms in the given sample determine an envelopment analysis. In (DEA) most efficient bank (with the score of 1) doesn t necessarily generate maximum output level but it does indicate that it has tendency of generating best practice outputs among the rest of firms in the given sample. Firms lying on the surface of are deemed to be the efficient and receive value of unity whereas; firms falling below surface level are deemed as inefficient and capture the value less than unity. Hence, all deviations from the estimated frontier represent inefficiency. The (DEA) measure compares each of firm in the sample with the best practice ones known as peers or role model. DEA serves as an alternative approach to regression technique. Since regression is based on central tendencies, while DEA is based on extreme observations. Moreover, the merit with the DEA is that unlike regression analysis, it doesn t require a prior assumption about the analytical form of the 23 ISSN: London Research Syndicate 2011

10 Journal of Management, Economics & Finance. Vol. 1, Issue 1 July 2011 production function, instead it derives the best production function solely on the basis of observed values making it impossible to miss-specify the production technique. The DEA model allows for the treatment of constant as well as variable returns to scale. The constant return to the scale (CRS) is advantageous as it allows for comparison between small and larger firms/banks in a situation where frequency distribution is skewed due to the presence of small and large banks in the sample. In such case the use of variable returns to the scale (VRS) raise the possibility that larger banks would appear as efficient n the sample for the simple reason that there are no truly efficient banks (Berg et al., 1991). This study will use both CRS and VRS for the analysis. Data and Input/output Specification The selection of variables is extremely important in the process of measuring efficiency.. It s commonly acknowledged that the choice of variables in efficiency studies significantly affects the results. (Favero and Pappi, 1995; Hunter and Timme, 1995). This is further amplified when unnecessary variables clutters the modeling, adding more variables not only inflates DEA efficiency scores but it also potentially conceals the actual magnitude of inefficiency. So the burden is on the study to tediously justify the selection process. During recent years, the issue of the sensitivity and stability of Data Envelopment Analysis results on the combination of variables has been extensively studied. The first DEA sensitivity analysis paper by Charnes et. al., (1985), examined the change in a single output. This was followed by a series of sensitivity analysis articles by Charnes and Neralic (1990). The variable selection for most DEA banking efficiency study relied mainly on the classical banking theory which depends on the approach selected i.e. intermediation or production. The data source for the research has been mainly the Banking Statistics Department for Commercial Banks of respected SAARC countries for the period of ( ). In order to allow the crosscountry comparison, All the financial data used for analysis converted to US dollar using Purchasing Power Parity exchange rate (PPP) with inflation adjusted are in terms of Us (in thousands). See Table 1 (Annexure). All financial figures are used in terms of Dollars (in Thousands). The efficiency of the banks can be measured either by using the operating approach or the intermediate approach. Under formal approach, the bank is perceived to be the producer of services for its account holders and is known as the cost/revenue management perspective. The intermediate approach however, consider bank as entities, which convert and transfer financial assets between surplus and deficient units acting as an intermediary better called a mechanical perspective. This study uses the intermediation approach as it enables financial institute like bank to be prescribed as a manufacturing units, converting inputs into outputs e.g. deposits in to loans and investments. In this paper the input output combination utilized are based on Mester (1996), applying the intermediation approach where deposit and asset are treated as inputs while loans and interest income will represent the outputs. Table 2 (Annexure) summarized the dependent and independent variables in this study. 24 In justification of the input-output variable selection, a sensitivity analysis is carried out with these three alternative input-output models. The initial model selection process was done through ISSN: London Research Syndicate 2011

11 Journal of Management, Economics and Finance, Vol. 1, Issue 1, July 2011 Spearman Rank Correlation.The result of the Spearman Rank Correlation is presented in Table 3-a,3-b & 3-c ( Annexure) From the results (see Annexure), it s found that the efficiency score for model 3 s combination of inputs and outputs are highly correlated with those of model 1 as compared to model 2 and its combinations. This indicates that the choice of deposit and asset as inputs and loan and interest income would best represent the efficiency scores of the sample set. EFFICIENCY ANALYSIS The descriptive statistics of the financial variables of the SAARC countries banks studied are shown in (See Table 4 Annexure). Among the SAARC countries, banks from Srilanka & Pakistan have the biggest number of average bank assets among the neighboring SAARC countries banks while India has been on lower side in terms of average bank asset ranking. However, for average deposits and loans Pakistan & India leads Srilanka. (See Table-4 Annexure) Utilizing Model 3, the technical efficiency (CRS) and the pure technical efficiency (VRS) levels of these SAARC countries banks are computed. Due to lack of space the focus of the analysis will be on the Central banking groups in each country at an overall industry level rather than the individual banks. The aggregated results are presented as in (See Table 5-a & 5-b Annexure). In terms of overall technical efficiency measures defined by CRS frontier (See Table 5-a Annexure), the results indicate that banking groups from India & Maldives followed by had the highest average score while the rest of SAARC countries had the lowest scores. Similar results were also found when the frontier was defined by VRS. In terms of the range of the efficiency scores obtained by the banking groups of each country, Srilanka & Bhutan appears to have the widest disparity, suggesting that some of its banks could be extremely efficient in allocating its resources while others are not that efficient in doing so. The finding also indicates that the overall technical efficiency of SAARC countries banks is around 98 percent (CRS) &99 percent (VRS) with a level of 2 percent (CRS) & 1 percent (VRS) room for improvement on average respectively. Besides that, the spread of the efficiency score is be found to be on similar pattern among these SAARC countries banks (approximate 3 percent (CRS) & 1 percent (VRS) respectively). This explains that these SAARC countries perform well in comparison with each other. The nature of technical inefficiencies may be due to the ineffective implementation of the production plan in converting inputs to outputs (pure technical inefficiency) and/or to the divergence of the DMU from the most productive scale size (scale inefficiency). Decomposing technical efficiency (TE) into pure technical efficiency (PTE) and scale efficiency (SE) allows an insight into the source of inefficiencies. The VRS model scores are regarded as the pure technical efficiency scores while the scale efficiency is computed by dividing the VRS scores with the CRS scores. The results of the decomposition are as in Table-6 (See Annexure). 25 ISSN: London Research Syndicate 2011

12 Journal of Management, Economics & Finance. Vol. 1, Issue 1 July 2011 Apart from Efficiency analysis, Graphical representations for Efficiency levels (TE and SE) are attached in Annexure as well. See Annexure for details. CONCLUDING REMARKS Efficient and healthy financial system is a vital and necessary component for faster economic development. If a financial system is efficient, then it should show profitability improvements, increased funds intermediation, better prices for financial products and quality services for consumers. If the financial system is under tight regulation, financial markets would not function efficiently and the use of resources would not provide desired outcomes. It should also be noted that reforms in other sectors have less impact on the overall economic development if the financial sector is under control. Most of the leading international financial markets including the United States, Great Britain, Japan, Australia and other European countries have introduced financial reforms in order to improve financial market efficiencies and competitiveness and to provide a better service to consumers. An input-oriented DEA model was used for estimating overall technical, scale and pure technical, efficiencies of the SAARC Countries Financial Sector Review for the period of ( ). The variables used in this study are deposits and asset as inputs while loans and interest income as outputs. This selection of variables was done through a sensitivity analysis (Spearman Correlation) via combination of 3 different models. A comprehensive analysis of efficiency among the cross country found that on average of 2 percent of inefficiency exists among these banks using CRS (Constant Returns to Scale) which signals there is room for further improvement still exists. Banking groups from India & Pakistan show the highest level of overall and pure technical efficiency while banking groups from Srilanka indicates the lowest level of technical and scale efficiency under CRS analysis, followed by similar results VRS analysis as well. So these smaller banks should take steps in ensuring they are relatively large enough to stay competitive among the other top SAARC Countries banks. A financial sector reform has been introduced in South Asia in early 1980s and still is a continuing process. Sri Lanka was the pioneering country among SAARC countries to introduce such reforms in the region. In recent time SAARC countries have also been focusing on reforming the financial sector as an integrated system. The formation of SAARCFINANCE (a discussion group of central bankers and other officials in the South Asian countries) has long term objectives such as possible economic union, possible single regulatory structure, possible single payment system and a possibility of introducing a single currency for the region ( Among South Asian countries, Sri Lanka has dynamic and vibrant financial markets. While the financial sector reform programme is going on for a number years, there appears to be no significant studies done for the country to examine the effect of such a reform programme. 26 However, Lack of research on policy implications may not only hinder further reforms in the country but also may deprive benefits to consumers by way of not implementing further reforms due to the uncertainty of effects. ISSN: London Research Syndicate 2011

13 Journal of Management, Economics and Finance, Vol. 1, Issue 1, July 2011 In total, this findings signals that banking efficiency has becomes critically important and it should be constantly compared with their counterparts in other countries to help bankers make better decisions regarding the direction of their banking industry and adapt to gain a competitive edge. The findings also may provide useful insights to government regulators and policy makers to enhance decision-making and policy formulation. REFERENCE 1) Allen, L. & Rai, A. 1996/5, "Operational efficiency in banking: An international comparison", Journal of Banking & Finance, vol. 20, no. 4, pp ) Altunbaş, Y., Gardener, E.P.M., Molyneux, P. & Moore, B. 2001, "Efficiency in European banking", European Economic Review, vol. 45, pp ) A Canhoto, and J Dermine (2000), A Non-Parametric Evaluation of Banking Efficiency in Portugal, New vs. Old Banks, Social Science Research Network (SSRN-id221168). 4) Burki, A.A. & Niazi, G.S.K, Impact of Financial Reforms on Efficiency of State-Owned, Private & Foreign Banks in Pakistan, Applied Economics, 42:24, First published on :9th April ) Berger, A.N. & Humphrey, D.B. 1997, "Efficiency of financial institutions: International survey an directions for future research", European Journal of Operational Research, vol. 98,pp ) Carvallo, O. & Kasman, A. 2005/1, "Cost efficiency in the Latin American and Caribbean banking systems", Journal of International Financial Markets, Institutions and Money, vol. 15, no. 1, pp ) I Hasan and K Marton (2000), Development and Efficiency of the Banking Sector in a Transitional Economy: Hungarian Experience, Bofit Discussion Papers (7/2000). 8) C.A. Denizer,M Dinc, and M Tarimcilar (2000), Measuring Banking Efficiency in the Preand Post-Liberalization Environment:Evidence from the Turkish Banking System, Social Science Research Network (SSRN-id632546). 9) D Stavarek (2003), Banking Efficiency in Visegrad Countries Before Joining the European Union, Social Science Research Network (SSRN-id671644). 10) M Dietsch, & Lozano-Vivas, A. 2000, "How the environment determines banking efficiency: A comparison between French and Spanish industries", Journal of Banking and Finance, vol. 24, no. 6, pp ) Fries, S. & Taci, A. 2005, "Cost efficiency of banks in transition: Evidence from 289 banks in 15 post-communist countries", Journal of Banking and Finance, vol. 29, no. 1 SPEC. ISS., pp ) Kasman, A. & Yildirim, C. 2006, "Cost and profit efficiencies in transition banking: The case of new EU members", Applied Economics, vol. 38, no. 9, pp ) A Ataullah and H Le (2004), Financial Liberalization and Bank Efficiency: A Comparative Analysis of India and Pakistan, Social Science Research Network (SSRN-id ). 14) Dr.A.A Reddy (2005), Technical Efficiency and Its Decomposition in Indian Banks in Post Liberalization, Social Science Research Network (SSRN-id870745). 15) A Qayyum (2007), Financial Sector Reforms and the Efficiency of Banking in Pakistan, South Asian Network of Economic research Institutes (SANEI B K Sahoo, J K. Sengupta and A 27 ISSN: London Research Syndicate 2011

14 Journal of Management, Economics & Finance. Vol. 1, Issue 1 July 2011 Mandal (2007), Productive Performance Evaluation of the Banking Sector in India Using Data Envelopment Analysis, Social Science Research Network (SSRN-id956812). 16) S Perera, M T. Skully and J. Wickramanayake (2007), Cost Efficiency in South Asian Banking: The Impact of Bank Size, State Ownership and Stock Exchange Listings, Social Science Research Network (SSRN-id ). 17) E Loukoianova (2008), Analysis of the Efficiency and Profitability of the Japanese Banking System, Social Science Research Network (SSRN-id ). 18) L Weill (2008), Convergence in Banking Efficiency across European, Social Science Research Network (SSRN-id ). 19) S L Seelanatha (2008), Determinants of Technical Efficiency of Banks in Sri Lanka, Social Science Research Network (SSRN-id ). 20) S L Seelanatha (2008) Did Reforms in Financial Services Sector in Sri Lanka Affect to the Improvement in Productivity and Efficiency in the Banking Industry?, Social Science Research Network (SSRN-id ). 21) M Dash and C Charles (2009), A STUDY OF TECHNICAL EFFICIENCY OF BANKS IN INDIA, Social Science Research Network (SSRN-id ). 22) D Canakci (2009), A case Study on Business Cycle, Bank Efficiency and Banking Crises, Social Science Research Network (SSRN-id ). 23) N Yamori and K Harimaya (2010), Efficiency in the Japanese trust banking industry:a stochastic distance function approach, Social Science Research Network (SSRN-id ). 24) D P Gajurel (2010), Structure-Performance Relation in Nepalese Banking Industry, Social Science Research Network (SSRN-id ). 25) S L Seelanatha (2010), Market Structure, Efficiency and Performance of Banking Industry in SriLanka, Banks and Bank System, vol. 5, pp ISSN: London Research Syndicate 2011

15 Journal of Management, Economics and Finance, Vol. 1, Issue 1, July 2011 Annexure Table-1 PPP exchange rate for the SAARC Countries (National Currency per current International Dollar ) Country Pakistan India SriLanka Source : International Monetary Fund, World Economic Outlook Database, April 2009 Table-2 Model Selection Model Inputs Outputs Serial Deposits Assets Loans Interest Income 1 Yes Yes Yes - 2 Yes Yes - Yes 3 Yes Yes Yes Yes 29 ISSN: London Research Syndicate 2011

16 Journal of Management, Economics & Finance. Vol. 1, Issue 1 July 2011 Table-3-a (Model-1 Spearman Test) Correlations Deposits Assets Loans Spearman's rho Deposits Correlation Coefficient Sig. (2-tailed) N Assets Correlation Coefficient Sig. (2-tailed) N 3 3 Loans Correlation Coefficient Sig. (2-tailed) N **. Correlation is significant at the 0.01 level (2-tailed). Table 3-b (Spearman Test Model-2) Correlations Deposits Assets Interest.Income Spearman's rho Deposits Correlation Coefficient Sig. (2-tailed) N Assets Correlation Coefficient Interest.Income Sig. (2-tailed) N Correlation ISSN: London Research Syndicate 2011

17 Journal of Management, Economics and Finance, Vol. 1, Issue 1, July 2011 Coefficient Sig. (2-tailed) N **. Correlation is significant at the 0.01 level (2-tailed). (Table 3-c Spearman Test Model-3 ) Correlations Deposits Assets Interest.Income Loans Spearman's rho Deposits Correlation Coefficient Sig. (2- tailed) N Assets Correlation Coefficient Sig. (2- tailed) N Interest.Income Correlation Coefficient Sig. (2- tailed) N Loans Correlation Coefficient Sig. (2- tailed) N **. Correlation is significant at the 0.01 level (2-tailed). 31 ISSN: London Research Syndicate 2011

18 Journal of Management, Economics & Finance. Vol. 1, Issue 1 July 2011 Table 4 (Average Price Values) Ammount in Million (usd) ( ) Serial SAARC Countries Average Assets Average Loan Average Deposits Average Interest Income 1 Pakistan 1,113, , ,350 44,736 2 India 250,763 8,006,855 10,915, ,842 3 Srilanka 279, , ,934 28,146 Table 5-a (CRS Efficiency Score) SAARC Banks Technical Efficiency Score (CRS) Banks Of Geometric Average Min Max Spread Pakistan India Srilanka Geometric Average ISSN: London Research Syndicate 2011