Cost Efficiency: A comparison of Public and Private Banks in Pakistan

BY Ayaz Shahid M.Phil

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187/FUI/MPHIL (MS) 2009 DEPARTMENT OF MANAGEMENT SCIENCES 2012 Cost Efficiency: A comparison of Public and Private Banks in Pakistan A thesis submitted to the FUIEMS Foundation University, Islamabad In partial fulfillment of the requirements for the DEGREE OF MASTER OF PHILOSOPHY IN MANAGEMENT SCIENCES

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BY

Ayaz ShahidDEPARTMENT OF MANAGEMENT SCIENCES 2012

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APPROVAL SHEET

Approved By

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CERTIFICATE

I have supervised the research Cost Efficiency: A comparison of Public and Private banks in Pakistan by Ayaz Shahid , an M. Phil scholar of Foundation University, Institute of Engineering and Management Sciences (FUIEMS), Islamabad. The work is worth presenting for evaluation.

Qaisar Malik

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DECLARATION

I, Ayaz Shahid, an M. Phil scholar in the subject of management sciences, hereby declare that the matter printed in this thesis titled Cost Efficiency: A comparison of Public and Private Banks in Pakistan is my own work and has not been printed, published and submitted as research work, thesis or publication in any form in any university in Pakistan or abroad.

Signature of Scholar

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ACKNOWLEDGEMENT

First I would like to thank ALMIGHTY ALLAH, THE MOST MERCIFUL THE MOST BENEFICIENT who gave me physical and mental powers to complete my work. I would like to express my sincere thanks to my supervisor, Mr Qaisar Malik whose devotion, knowledge, command over finance added considerably to my research work. He always ready to answer any queries from my side and gave me more than enough time for my research work. I would also like to thank Mr. Amir Gulzar who gave me his precious time to better my work. I would like to give my special thanks to my parents, wife and brother for the love and moral support they provided me throughout the completion of this research work.

Ayaz Shahid

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Table of Contents CHAPTER 1 : INTRODUCTION ...................................................................................... 1 1.1 COST EFFICIENCY IMPORTANCE ..................................................................... 2 1.2 CURRENT TRENDS AND TECHNIQUES ............................................................ 2 1.3 PROBLEM STATEMENT ....................................................................................... 7 1.4 RATIONALE OF STUDY ....................................................................................... 7 1.5 SCOPE OF STUDY .................................................................................................. 8 1.6 SIGNIFICANCE OF STUDY ................................................................................... 8 1.7 LIMITATIONS ......................................................................................................... 8 1.8 OBJECTIVES ........................................................................................................... 9 CHAPTER 2 : LITERATURE REVIEW ......................................................................... 10 CHAPTER 3: METHODOLOGY ................................................................................... 27 CHAPTER 4: DATA ANALYSIS .................................................................................. 37 CHAPTER 5 : CONCLUSION ........................................................................................ 63 RECOMMENDATIONS .............................................................................................. 66 REFERENCES .............................................................................................................. 67

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ABSTRACT

This study compares the public and private sector banks in Pakistan on the count of cost efficiency. In this regard, total cost is used as the dependent variable and six independent variables are used. Using the fixed effects model and DFA,a trans log cost function is used to determine the difference between two groups. Eviews is used to analyze the data. Analysis is made on individual variable basis as well as on the group basis. The public sector was found to be more cost efficient as compared to the private sector banks. All variables have a significant impact on the dependent variable however in case of public banks, price of financial capital and price of physical assets are the most significant variables. In case of private banks, level of investments and level of advances are the most significant variables. In the light of this research, banks can adopt measures to improve on the primary factors affecting the cost efficiency i.e. the variables that are the most significant. New entrants in the industry can take the steps to control the variables that seem to be the most influential. Key Words: Banking Sector, Cost Efficiency, Public and Private Banks.

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CHAPTER 1 : INTRODUCTION

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1.1 COST EFFICIENCY IMPORTANCEIn the present era the resources in the overall economic system are scarce while the competition is putting an enormous pressure on all enterprises to be the most efficient. One of the most discussed dimensions of efficiency is on the cost side whereby the enterprise should use its inputs in the most efficient manner. The cost efficiency is important in an organization in the following manners: The cost efficiency practices can fulfill its needs of increasing profits. Efficiency in costs will mean that the enterprise will produce more output from the same quantity of inputs as compared to what it was doing before. Thus it will lead to increased profits. The enterprise that is implementing successful cost efficiency procedures enjoys a better competitive standing as compared to its competitors. The enterprise that is implementing cost efficiency practices can preserve a good part of its resources that is wasted if the company practices are cost inefficient. A big challenge for most of the enterprises is to increase productivity which is defined as the comparison of inputs to outputs. Running the enterprise in a cost efficient manner means that more output is being produced with the help of lesser inputs which will improve the productivity of the enterprise.

1.2 CURRENT TRENDS AND TECHNIQUESThe recent recessions have forced the companies to look for various ways to fund the growth. One way is to free up costs and divert the resources towards the most profitable growth opportunities.

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Various techniques are used by the enterprises to achieve cost efficiency. Some enterprises cut costs with help of golden handshake schemes in which employees are offered to retire and accept some cash benefits. Some companies save costs by producing different parts in different countries. The company saves its cost by producing the parts in the countries where it costs the least, thus overall assembling is done in a single place by importing all parts to that place. Some people suggest that a change from public to private ownership can also help in cost efficiency. Further the separation of ownership from management will also help. In Pakistan and other third world countries corruption is a persistent problem which does increase the costs. The separation of ownership and management will help in decreasing the corruption thus help decreasing the costs. Controlling the corruption will also stop the misuse of resources thus the enterprise will become more cost efficient. Another aspect of cost efficiency relates to the selection of the type of inputs that the enterprise chooses to use in the production process. In the Sub Continent where population is huge, labor intensive processes are undertaken. On the contrary in countries like Canada the technology driven processes are undertaken. A recent concept is to achieve economies of scale. In that case the main idea is to increase the production of the company to a level where per unit costs of the producer falls as a result of expansion. As far as the banking sector goes, cost efficiency is important as various factors like technology, prices of inputs, perception of service quality have changed drastically in a very short span of time. Banking sector is an important element in the economy by3

facilitating the payment system, mobilizing savings and allocating funds for the most productive uses. Historically the banking sector of Pakistan has been playing an important role in the economic development. The scenario changed significantly in the 1970s with nationalization of Pakistani commercial banks. There is some research on the performance of banking system of Pakistan with respect to cost. The research is also available on other countries like Greece and Italy. There are 35 banks working in the Banking sector of Pakistan including 4 nationalized banks and 4 specialized financial institutions. The government owned institutions constitute a major portion of the banking sector of Pakistan. Public sector dominancy among other factors has led to inefficiency in the banking sector (khan 1995, khan and khan 2007). Various reasons led to low efficiency in the banking sector. The banking sector accommodates for 67.8 % of the total assets in the financial sector of the country. Pakistan is an important example of a country that undertook far reaching financial sector reforms. The reforms have benefitted the country as 80% of the assets of the banking sector are now held by the private sector banks. More professional attitude and better service are seen in the banking sector as a result of privatization of nationalized commercial banks. There are four important constituents of the monetary and fiscal scenario of the country namely regulatory authorities, intermediaries in the form of banks, development finance institution and stock exchanges. Regulation was further divided among three authorities namely State bank of Pakistan, Pakistan Banking council and the corporate Law

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authority. The four major components of the financial sector were divided among these three authorities for regulation. The role of central bank was played by the SBP while the PBC regulated the nationalized commercial banks and the CLA regulated the equity market. Nationalization of banks was undertaken in 1974 to prioritize the availability of credit to the economy according to sectors. This step completely ended the role of the privately owned banks in the financial scenario. The efficiency alongwith performance of the intermediaries was affected by this nationalization process. Since the desired results of nationalization could not be extracted, the government reversed the decision to allow private participation and enhance competition in the banking sector. SBP along with SECP has enhanced its role as a regulator of the financial system of Pakistan. The structure of the banking industry has changed a great deal in the past ten years particularly due to the denationalization of the state managed banks. In the 1990 the sector was dominated by 5 state owned banks. In the same year some amendments were made in the banking Companies ordinance which allowed the privatization of the nationalized banks. Two of the nationalized banks namely Muslim Commercial Bank and Allied Bank were nationalized during 1991 and 1993. The third bank namely United bank limited was privatized in the year 2002 thus ending the national domination in the banking sector. The privatization of nationalized banks has opened the financial sector to domestic as well as foreign competition. With the ever increasing number of banks and other financial institutions, the state bank of Pakistan had enforced an increase in the minimum initial investment of the banks from Rs. 500 million to Rs 6 billion. The ownership and management by the private sectors is one side of the reforms while the other side is the regulatory environment. Private Banks tend to take higher risks in5

order to fulfill their capital requirements through investments from other parties. If loss occurs, it is divided disproportionately among the investors. Central bank as a regulator prevents the banks from taking excessive risks. In the supervisory role, specific corporate governance practices have been put in place by the state bank of Pakistan in order to provide safety to the customers. The transformation of nationalized banks into private ones and inclusion of many multinational banks in the Pakistani banking sector has given rise to many challenges. The excessive competition has prompted banks to find new means in order to have an advantage in the industry. One of the issues that is in the spotlight is how to remain cost efficient. The global as well as Pakistani financial environment has been very dynamic in the last decade or so. This dynamism has enhanced the importance of competition and efficiency. Other factors like technological progress, reduced information costs, higher competition among both financial and non-financial intermediaries and ongoing deregulation has led to substantial changes in the banking sector of Pakistan. Banks continue their efforts to cope with new competitive challenges by improving efficiency of their operations. Two streams exist in the literature on banks performance. One focuses purely on productive efficiency of financial institutions and compares the average efficiency of financial institutions relative to the institutions on best- practices cost frontier (Mester, L.J., 1993; Meeusen, W., Van den Broeck, J., 1977 and Mitchell, K. and N.M., Onvural, 1996). The other stream assesses assets quality and capital adequacy as essential determinants of efficiency of financial institutions. These studies investigate the issues of capital adequacy, non-performing loans and agency problems (DemirgucKunt, 1989; Walen, 1991 and Berger and De Young1997).6

Bank efficiency has long been a subject of interest for many researchers. The availability of data has made it possible to conduct research in the Pakistani banking sector and to define the factors that can improve the efficiency of the same. A bank is considered to be efficient if it is producing the outputs at a minimum possible cost as compared to a best practice bank. The efficiency score of the best practice bank will be 100. If a bank has an efficiency score of 75, this means that the bank can decrease its cost by 25% by efficiently using the same proportions of inputs and outputs. In the Pakistani context, minimal research has been done to evaluate the effectiveness of the banking sector. The studies that have been undertaken are done on the sector as a whole thus giving no clue to the reader whether the type of ownership has any impact regarding the better performance or otherwise of the banking sector. Further no comparative research has been undertaken in Pakistan that can give insights about differences among various groups of banks.

1.3 PROBLEM STATEMENTThe study is intended to explore the comparative aspects of the banking sector that still need to be unveiled. The focus is on the comparative aspects regarding the public and private sector banks with respect to cost efficiency by dividing the banking according to the mode of ownership.

1.4 RATIONALE OF STUDYThis study will help find the factors that differentiate the public sector banks from that of the private sector on the count of cost efficiency. The information thus gained will help the policy makers to control the factors that cause the inefficiency in either case. On the

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individual bank level, the study will help the bank to compare itself with the best practice bank so that the flaws thereof can be rectified.

1.5 SCOPE OF STUDYTotal cost will be taken as the dependent variable. Independent variables are total outstanding loans and advances ratio total assets, investments ratio total assets, the nonperforming loans taken as percentile of total assets, price of loan and equity, physical assets and labor inputs. The study will be confined to the banking sector of Pakistan excluding the specialized financial institutions. Further all banks are assumed to be working in the same macroeconomic and regulatory environment.

1.6 SIGNIFICANCE OF STUDYAccording to Ansari (2007) the overall efficiency of the banking sectors stands at 72% suggesting that there is ample room for improvement in the banking scenario of Pakistan. This study utilizes the same model as used by Ansari but examines the comparative aspects of cost efficiency by examining public and private sector banks of Pakistan. The study will further elaborate the reasons that affect the cost efficiency of banks in Pakistan thus letting the higher officials know what steps can be taken towards betterment of situation.

1.7 LIMITATIONSBeing a third world country the overall atmosphere of Pakistan has not been conducive for research. One of the reasons may be the unavailability of the data for the same. This study takes the information from the yearly statements depicting financial position of the banks included in the sample. The data is unbalanced as some of the figures were not available in some balance sheets. In some cases the data was available for less number of

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years. The specialized financial institutions are not included in the study due to the fact that they relate to specific fields like agriculture. Furthermore Islamic banks are also not included.

1.8 OBJECTIVESa. To assess whether there are significant differences between the nationalized and denationalized banks of Pakistan in terms of Cost efficiency in the context of level of advances. b. To assess whether there are significant differences between the nationalized and denationalized banks of Pakistan in terms of Cost efficiency in the context of level of investments. c. To assess whether there are significant differences between the nationalized and denationalized banks of Pakistan in terms of cost efficiency in the context of level of non-performing loans. d. To assess whether there are significant dissimilarities between nationalized and denationalized banks in respect of cost efficiency in the context of prices of financial capital. e. To assess whether there are significant differences between cost efficiency of nationalized and denationalized banks in the context of prices of physical capital. f. To assess whether there are significant differences between cost efficiency of nationalized and denationalized banks in the context of prices of human capital. g. To assess whether there are significant differences between cost efficiency of nationalized and denationalized banks in the context of technological progress.

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CHAPTER 2 : LITERATURE REVIEW

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Janjua (2011) analyzed the cost efficiency of 15 Pakistani commercial banks. Intermediation approach was used to define the cost structure of the banks. To assess the results, free distribution approach has been used. The study found that cost efficiency varies across the intermediary industry. The overall efficiency of the banking sector appeared at 82% which shows that there is enough room for improvement in the banking sector. The non- performing loans were the most important factor contributing to the inefficiency. Other factors like financial prices, advances and investment also contributed towards the inefficiency. Technological up gradation showed healthy impact on the cost effectiveness of banks. Other factors like betterment in HR management, better asset portfolio selection were also found to be helpful in lowering cost inefficiency of the banks. Hanif Akhtar (2010) analyzed Pakistani commercial banks on the count of X efficiency which is defined as the difference between the efficient behavior of firms as implied by the economic theory and their actual behavior in practice. DEA was applied in the study. The authors used the production approach using customer money, human assets and financial assets as inputs while loans and credits, investment and other than interest income are used as products. On the average the banks in Pakistan showed a low efficiency score. Performance of foreign banks working in Pakistan was better than the banks working in Pakistan both nationalized and denationalized. In the context of Pakistan, the private intermediaries are performing better than their public counterparts. The global advantage hypothesis is supported by the results as foreign banks out perform their local counterparts by overcoming cross- border disadvantages. In case of Pakistani commercial banks, the home field advantage hypothesis is not supported where it is11

expected that local banks will perform better than the foreign banks. From a regional perspective, Pakistani banks have a lower average X efficiency score as compared to that of the Indian banks. The banks that were x- efficient were dissimilar regarding stature as depicted by the assets of the bank. The efficient banks were the oldest ones among the sample indicating the learning by doing behavior. Inefficient banks showed an increased NPL to total debts ratio. The public banks had the lowest overall x- efficiency score among all the banks below the private banks while foreign banks stood on top. Subhash Ray (2010) estimated the performance of the Indian banking sector with respect to cost and profit during the period after reforms. Nonparametric DEA approach is used. Banks are being differentiated on the bases of ownership type, size and product mix. A considerable difference in efficiency of banks in terms of profit with different ownership types has been found. Nationalized banks are found to be better performers as compared to denationalized counterparts. Smaller intermediaries are reported as worse performers at the current level of working. Analysis of distribution of efficiency has also been undertaken through kernel density estimates. A positive shift in the distribution is observed over the time which is primarily due to the government owned banks. The differences in efficiency of banks are strongly related to the ownership differences of the banks. Abbas and Malik (2010) assessed the impact of financial liberalization and deregulation on banking sector in Pakistan. The study analyses the market perception about the Pakistani banking sector performance after the deregulation and liberalization measures have been taken by the central bank. The study uses the survey approach. The impact of these reforms have been analyzed on the basis of responses of key stakeholders and cost12

inefficiency scores derived from distribution free approach. Government intervention allowed the political and bureaucratic pressures to be applied on banks. The banks were supervised by the Pakistan banking council side by side with SBP which weakened the supervisory and regulatory capabilities of the SBP. SBP neither had the resources nor the authority to implement a market driven independent monetary policy. The data on key banking indicators exhibited a complete dominance of state owned banks. The nationalized commercial banks were uncompetitive, inefficient and financially vulnerable prior to reforms. The SBP implemented financial deregulation and liberalization measures which included privatization of nationalized banks, removal of caps on leasing and lending rates of banks and removal of restrictions on opening of private banks. The survey results showed that majority of the respondents believed that the reforms program should not be delayed. Some respondents believed that the preliminary work for the reforms has not been undertaken. As far as the nationalized commercial banks were concerned, majority of the respondents believed that years of operation under government supervision was the primary reason behind the inefficiency, uncompetitiveness and financial vulnerability. According to the majority, privatization of state owned banks was the primary correction of the flaws of the banking sector. The survey results also indicate a significant improvement in the key indicators of banks after major reforms had been undertaken. As the consequences of the reforms the ownership structure of the banks changed with less intervention by the government in the overall functions of the banks. The SBP turned towards a more market based monetary policy. The interest rates were liberalized by the SBP. The banking spread i.e. the gap between the lending and deposit rates was narrowed. The non- performing loans were higher.13

The major reforms taken by the central bank of Pakistan remain a good aid in the correction of flaws in the banking scenario of Pakistan. The inefficiency scores of banks also indicate that the performance of Pakistani banks has increased. Manlagnit (2010) examined the efficiency with respect to cost of commercial banks in Philippines. The intermediation approach has been applied with regard to specification of bank inputs and outputs. Stochastic frontier approach has been used. Risk and resource quality aspects have been added in the analysis. Human capital, financial capital and other funds have been used as inputs. Outputs include total debts, investments and other accounts. The findings show inefficiencies in the banking sector. Uncertainty and resource quality also have an impact on the efficiency of banks. Some costs have been connected to the 1997 financial crisis. The rehabilitation processes put in place thereafter also had an adverse effect on the sector. Although the reforms enhanced the antagonism in the banking arena, they put pressure on the banks to incur more costs to cope with newer regulations. It is found that bank efficiency is correlated to risk and asset quality. Wang, Faiq and Humera (2009) assessed the technical attainment of banking arena of Pakistan. Technical efficiency comprises of pure technical efficiency and level efficiency. Banks are divided according to their ownership types i.e. government owned, local private and away owned intermediaries. Away owned intermediaries are found to be at the top regarding efficiency followed by the nationalized and denationalized local banks. It is also found that pure technical efficiency results in better technical performance and intermediaries are facing severe scale problems. Overall technical bad performance appears to be a major consequence of scale inefficiency. The authors found a developing

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trend in the pure technical performance while the scale efficiency shows an opposite trend over the study period. Elina (2008) assessed the performance of Japanese banks. DEA approach was applied. Steady improvement in the banking sector has been noticed in Japan. Regional banks are found less efficient in terms of cost and revenue as compared to city and trust banks. Japanese bank profitability is found to be low as compared to other advanced nations. Debashish (2006) applied the DEA model for studying comparative performance of Indian intermediaries for 1998-2004. The efficiency of away banks was known to be greater as compared to their domestic rivals. Medium sized banks were found to be the least efficient as compared to large and small sized banks. Gulati (2006) used non- parametric analysis to measure efficiency of Indian banking sector. Only 9 out of 51 intermediaries were examined to be higher performers. Inefficiency with respect to management is the major cause of total wastefulness. Private sector banks play a vital part in forming of efficient frontier. Statistical significance of efficiency differences between the two groups could not be found. The most influential factors on the technical efficiency were profitability and off balance sheet items. Su Wu (2006) assessed the impact of deregulation on the Australian banking sector. DEA with moving window has been used. In order to assess the efficiency of Australian banking sector, Malmquist indices are used. The second stage regression is conducted. Considerable impact of deregulation on the overall Australian banking sector has been found.

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Berger, Hasan and Zhou (2006) analyzed the gain and cost performance of the intermediaries comprising a major chunk of commercial banking resources in China. The difference of majority and minority ownership structure was also considered. Log transformation has been used. The four nationalized intermediaries were found to be the most inefficient. Banks having minority away ownership show improved efficiency. Steps that allow the away intermediaries to have a larger part in the intermediation sector are likely to improve the performance of the same. Nocera and Sironi (2006) compared the performance and risk for one hundred and eighty one big banks from fifteen European states and evaluated impact of different ownership models. Regression analysis is used. It is found that mutual and government banks exhibit poor profitability than denationalized banks. Poor debt quality and more bankruptcy risk are shown by nationalized banks. Ownership concentration does not impact a banks performance. Ownership concentration results in better debt quality, lower asset vulnerability and lower bankruptcy risk. Fiorentino (2006) compared SFA and DEA methods to investigate consistency of efficiency scores.34192 observations are sampled to be analyzed against 5 criteria namely stages, grades, identification of best members, stability with respect to time and application of standard accounting principles. Non- parametric methods show more sensitivity to outliers and errors. The differences among commercial, cooperative and savings intermediaries should be considered. In short run, efficiency scores are stable but not in the long run.

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Adika Kiani (2005) compared local and foreign banks applying the stochastic frontier Approach. The study investigated the relative technical performance of Pakistani and away intermediaries working in Pakistan. Using the stochastic frontier method, the study compared the banks. The study showed how variable was efficient cost among banks and how actual cost departed from efficient cost. The study concentrated on technical efficiency assuming the allocatively efficient banks. Since the management practices of Pakistani and foreign banks are different, separate methods for these two subsets are constructed to compare comparative efficiencies of commercial intermediaries in their respective subsets. The results show that banks with foreign ownership working in Pakistan are comparatively better performers than the domestic intermediaries. Average efficiencies of banks have been obtained and banks have been ranked accordingly. This provides a true picture of the extremes on the count of efficiency. Within the samples, separate average efficiency points were also calculated to obtain the most and least efficient intermediaries. In case of Pakistani banks the distance between the efficiency score of the most efficient and the least efficient banks was not very huge however the best banks were still far from the overall efficient frontier. The banks choose inefficient allocation frontier and resources are allocated more easily in line with the political pressures. The role of the state was suggested to be minimized in the banking sector. Das (2005) investigated the impact of financial regulations on the performance of the Indian commercial intermediaries using non parametric data envelopment approach. Different input and output combinations are used in intermediation, value added and operating approach. Various variables like number of branches, whether it is public or private, capital adequacy ratio, non- performing debts and human resource quality are17

used to analyze the variation in in calculated efficiencies. The medium sized banks are found to be reasonable performers and are performing at higher level of efficiency. The soundness of banks as calculated by the capital adequacy ratio of the banks is found to be closely related to the efficiency. The efficient banks tend to have lower non- performing loans on the average. Ataullah, Cockerill and Le (2004) studied the comparative aspects of the banking scenarios of India and Pakistan on the count of evolution of technical efficiency in both countries. The authors try to know the impact of financial reforms on intermediary performance. DEA is used with two different input- output combinations to evaluate technical performance and to break it into its components namely pure technical efficiency and level of operations efficiency. The consistency of efficiency scores is also examined by evaluating their relationship with three non- frontier measures of bank performance. In this regard RoA, TC/TA and TC/TR are used. Two complementary models are used by the authors. One model takes loans as final product of the banks while other model uses income as the final product of the banks. The banking industry of both the countries shows very low overall efficiency scores. The sector in both countries also shows very little improvement until 1995. In both the countries, the reason of low overall technical efficiency was poor scale efficiency which is in turn attributed to the intervention of government in banking industry. Yielding assets model shows higher efficiency as compared to the income model. This difference is attributable to the nonperforming loans in the asset combination of banks in the two countries. Casolaro and Gobbi (2004) used micro data from 600 Italian banks in order to analyze the impact of investment in information technology in the Italian banking scenario.18

Stochastic frontier approach has been used for both cost and profit. Both cost and gain frontier movements have been found to be strongly related with IT capital addition. Efficiency of banks adopting IT related techniques is higher. Qayyum and Sajawal (2004) studied the x- efficiency, scale economies, technological innovation and competitiveness in the Pakistani banking scenario. Efficiency comparisons between domestic, foreign and big banks are also made. Panel data is used and stochastic econometric frontier approach is used. In order to estimate the xefficiency, distribution free method is used. The results show that the efficiency for local banks is lower than the overall mean of all banks. The same figure is higher for the foreign banks. The smallest domestic banks are the least efficient. Pakistani domestic banks are less efficient than those of other countries. The contribution of technological advances in reducing the average costs has been notable. This has been slower for the domestic intermediaries as compared to the foreign intermediaries. The larger banks have lower economies of scale as compared to all banks for all periods while the foreign banks are more scale efficient. The SBP must encourage mergers among banks so that the instability issue in the financial sector can be addressed. Atsushi Iimi (2004) assessed the Economies of level of production, scope and cost complementarities in the light of banking sector of Pakistan. The author investigated the ways to improve the scale efficiency of Pakistani banks through working specialization and diversification and size extension. Using the intermediation approach, outputs are given as four kinds of debts and two types of investments. The input prices are specified as salaries for human assets, rent for physical assets and markups paid on money received. For calculation of costs, duality theory has been used. Although the banking19

sector of Pakistan shows both scale and scope economies, the same diminishes as the size of the banks increases. With the exception of Demand deposits, when the size of all other operational categories is increased, it resulted in costs saving. Due to the existence of cost complementarities in majority of product pairs, banks can have a cost advantage in providing several services at the same time. Non- performing debts are found to be a big issue in the Pakistani banking scenario. The denationalized banks are found to be working with higher scale economies but lower scope economies as compared to the government sector banks. Privatized banks are reported to be the most efficient amongst all the categories studied. Saathye (2003) measured the productive performance of the banking industry in India. The banking sector was divided into publicly owned, foreign owned and privately owned banks. Data envelopment analysis is undertaken to obtain efficiency scores. The mean efficiency scores of the denationalized Indian banks are less than that of nationalized away intermediaries. However the mean scores of the Indian banking sector compare well with the global efficiency scores. The study showed that the non- performing assets of the banks should be reduced. Further the rationalization of staff and branches should be continued to make the Indian banking sector globally competitive. Maryam and Shaban (2003) investigated the evolution of the banking sectors of postcommunist new EU member countries. The efficiency frontiers were estimated using various parametric, non- parametric and semi parametric techniques. The results show that the methodology used affects the efficiency estimators. However the determinants of efficiency remain consistent which ever methodology is followed. This consistency will help the managers to determine the efficiency or otherwise in their enterprise. The study20

also finds that aggressive lending policy generates lower profits. Before transformation, the non- performing loans were high for the banks. Kumbhakar and Sarkar (2003) calculated increase in the total factor productivity to know the impact of financial liberalization. 23 government owned banks and 27 counterpart banks were used. They found that there is over employment in the Indian banks. No results were found in support of liberalization enhancing the productivity of banks. Government sector banks were found to be too dominant in the Indian banking sector. Glaveli (2003) assessed the cost efficiency of fifty eight branches of a bank in six major cities of Greece. Data envelopment Analysis approach has been used. The impact of stature on cost efficiency is also observed. The results suggest that the overall efficiency of the banking sector can be improved. Rural branches tend to be better performers than the urban ones. Dyson and Camanho (2003) discussed the measurement of cost efficiency when input price information tends to change overtime. The prices may be exactly known at each decision making unit (DMU) or the information may not be complete. The upper and lower bounds of cost efficiency are developed in the case of price uncertainty. These bounds are developed by considering the most favorable and the most unfavorable price scenarios. DEA model is used. The results show that estimates from DEA are robust even in case of price uncertainty. Joaquin Maudos (2002) examined two aspects of efficiency in the European banking sector i.e. cost and profit. Alternative techniques have been used to calculate the efficiency on both aspects. Lower profit efficiency levels have been observed as21

compared to cost efficiency. Some factors like differences in size, specialization, other bank characteristics and market characteristics are also examined as the possible sources of differences in efficiency. Gregarion and Manole (2002) analyzed the factors affecting commercial bank performance in change using the data envelopment analysis. As far as the bank production is concerned, the value added approach has been applied in which the output characteristics of both assets and liabilities are considered. Only those characteristics that have substantial value added are considered as outputs. The choice of value added approach also made it possible to classify inputs and outputs based on their specific characteristics. The inputs used are labor, fixed assets and interest expenditures. Two sets of output are defined, one comprises of revenues, net debts and cashable assets while the other includes deposits, net debts and cashable assets. The first set of outputs puts emphasis on profit generation while the second set of output emphasizes service provision as a goal. The overall analysis suggests that foreign ownership enhances bank performance provided that they are given controlling power and enterprise restructuring. If the Central bank tightens the policies, the effects will differ depending upon the prudential norms of the country. The efficiency of the banks will improve as a result of consolidation. Emili Auslina (2002) compared the efficiency scores when different output specifications are used. Non- parametric methods using the kernel smoothing are used. Assets and deposits are used as outputs in two different approaches. The efficiency scores thus calculated vary greatly.

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Ashton (2001) investigated the features of British retail banks on the count of cost efficiency. Both production and intermediation approaches were used. The DFA was used to estimate the cost efficiencies. The scale, scope and cost complementarities were also estimated. The results showed that the economies of scale were increasing and the British banks were not far apart from each other on the count of cost efficiency. Low financed retail banks were found to be more efficient than the higher financed ones. Hardy and Patti (2001) used distribution free approach to know whether the 33 Pakistani banks included are efficient on the ground of the cost and revenue. Costs and revenues were found to be increasing in the post liberalization period. The benefits from increase in efficiency in terms of income were delivered to the customers. Banks charged higher rates of interest on their debts but did not deliver them to their customers. Altunbas et al. (1999) used the SFA to calculate the effect of technical diversification on the costs of European intermediaries. The study used the dataset of around four thousand intermediaries based in fifteen European countries for the year 1989 1996. Three components of technical change have been assessed viz. pure, scale and non- neutral components. The bank size strongly affects the decrease in cost attributable to technical change. Chen and Yeh (1998) investigated the operational performance of thirty three intermediaries in Taiwan. DEA approach was applied in the study. Variables like debt services, portfolio management, markup and non markup incomes of the banks were used as outputs of banks. HR strength, bank assets, the strength of branch network, operational costs and deposits were used as inputs.

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Bhattacharya (1998) examined the 70 Indian commercial banks on the count of productive efficiency. Data envelopment analysis is applied to evaluate efficiency scores. Temporal component, ownership component and a random noise component are considered as sources of the efficiency scores calculated. Stochastic frontier approach is used to relate the efficiency level to the above three components. Government owned Indian intermediaries are found to be the best followed by the foreign intermediaries and the private banks. As time passes, the performance of foreign owned banks has improved while the performance of the private Indian banks remained constant. The performance of government banks declined as the time passed by. These patterns of time driven performance are described in the light of governments regulatory policies. Chang (1998) compared the US owned multinational banks with foreign multinational banks working in US for the years 1984-1989. The analysis was done using translog stochastic cost frontier approach. The inefficiency score of US multinational banks was found to be significantly lower than foreign owned multinational banks. The banks that had foreign ownership more than 50% were found to be the least efficient. The foreign portion in ownership was inversely proportion to the efficiency of banks. Resti (1997) compared two approaches towards bank efficiency namely econometric studies and DEA. A common panel of 270 banks was observed for comparison of these two methods. If the conceptual framework is the same, these two methods do not differ dramatically. Differences arise due to the built in differences in the models. Efficiency scores show high variance. A direct relationship exists between productive efficiency and asset quality

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Favero and Papi (1995) evaluated the performance of the Italian banking sector. A comparison of parametric and non- parametric techniques was made on 174 Italian banks for the year 1991. High variability in both profit and cost was found in the Italian banking sector. Zardkoohi and Kolari (1994) assessed the scale and scope economies for 615 bank branches in Finland for the year 1988. Estimates of scale and scope economies were obtained using a standard translog cost analysis. Economies of scale were found to exist for individual branch offices. Aly et al. (1990) assessed the various aspects of bank efficiency in the united states. Technical, scale and price efficiency have been discussed. Non parametric techniques have been applied to estimate overall performance of the banks. They assessed 322 banks in the year 1986 and found an overall low level of performance. The banks were found to be scale efficient. There was a negative correlation between product diversity and technical performance and a positive correlation between technical efficiency and extent of urbanization. Ferrier and Lovell (1990) studied the banking scenario of the US on the count of cost efficiency. Linear programming and econometric techniques were compared to unleash the structure of cost efficiency of the banking sector. They found that technical inefficiency accounted for a 9 % increase in the overall cost while the price inefficiency accounted for a 17% increase in cost. Technical inefficiency showed a decrease as the bank size increases.

25

Qayyum assessed the effect of financial sector reforms on the performance of banking sector in Pakistan. As far as the banking aspect is concerned, intermediation approach has been used. DEA approach was applied. Both input based and output based versions of the DEA have been applied. Financial sector reforms have diversified the ownership structure of banks in Pakistan. Whatever methodology is used, the scale efficiency dominates the pure technical efficiency. Only 20% of the banks were enjoying economies of scale which were all private sector banks. Financial sector changes have improved the efficiency of commercial banks as an intermediary. In this regard, pure technical efficiency has increased more as compared to the scale efficiency. The study revealed that 60% of the banks were on the best practice frontier out of which only 1 was a public sector bank. Sturn and Williams assessed the impact of foreign bank entry on the performance of intermediaries in Australia. Both DEA and Stochastic frontier approaches were used. Away banks were found to be more efficient as compared to their domestic counterparts. A barrier to entry of the new banks was bank size. Throughout Australia there was a positive impact of deregulation and competition via new entry in the banking sector. From the above literature review, it is evident that some evidence on the banking sector of Pakistan is available in the literature. However the gap lies at the comparative aspects of the sector whereby the banking sector can be segregated on some base. This study will try and fill this gap by segregating the banking sector on the basis of ownership. Furthermore this study uses a comprehensive model that inculcates the variables that have been used in isolation by various authors.

26

CHAPTER 3: METHODOLOGY

27

Various approaches have been applied by the researchers to analyze the cost efficiency of the banking sector. Financial Ratio analysis is often used for this purpose. The main problem with the financial ratios analysis is that it does not provide any clue of the long term performance of the firm. The basic framework for measuring inefficiency was introduced by Farrell (1957) who defined inefficiency as a deviation from an optimum behavior. It is important to calculate the cost efficiency of most efficient banks first and then to calculate the relative efficiencies of other banks. In the current study, some of the distributional assumptions of stochastic frontier approach have been released and Distribution free approach will be implemented. The data available and the research objectives usually decide which approach will be used. When the inferences are drawn directly from population, fixed effects model is used. In this study the data is taken directly from banks included in the population so fixed effect model is an appropriate choice. The Non Parametric method is more vulnerable to outliers while parametric approaches are generally more robust. In the production method banks use financial and human resources as inputs to produce the outputs. Number of deposits and loan accounts are used as a measure of banks product while mean account size is used as a measure to analyze the quality of product. Under the intermediation method, banks take money and purchase funds from other sources and generate earning assets as loans using them. This approach uses earning

resources as an alternate to banks output while labor, financial assets and deposits are used as inputs. This study applies the DFA for calculating the relative efficiency of public and private banks in Pakistan from 2003 2010. In DFA calculated efficiencies are thought to be28

consistent over time while random errors average out. Since panel data allows the application of certain random and fixed effects models without prior assumptions, I will use the fixed effects model in this study. As stated above, the study will use the intermediation approach of banks inputs and outputs. In the upcoming lines I operationalize the variables under consideration by providing the evidence of past research that used the same variables. Total cost The dependent variable in my study is the Total cost. The figure of total cost/ total assets (TC/TA) has been used as a proxy to represent the total cost of the banks. Author Ataullah Country Pakistan and India Variable Total Assets Findings cost/Total Overall low levels of efficiency banking

This study prompted me to use the figure of total cost/total assets as my dependent variable. I will investigate whether the public and private banks in Pakistan are different with respect to the cost efficiency. Y1 (Ratio of total outstanding loans and advances to total assets) Author Janjua Country Pakistan Variable Advances Findings variable cost

29

efficiency

across

banking sector Attaullah India and Pakistan Loans Overall low levels of efficiency Chen and yeh Taiwan Loans Banks with higher amount outstanding of loans banking

had lower efficiency The above studies used either loans or advances to evaluate the cost efficiency in various countries. In the light of these studies, I use the ratio of total outstanding loans and advances to total assets as independent variable. I will investigate whether public and private banks in Pakistan are different with respect to the effect of loans and advances on the cost efficiency of the banks. The related hypothesis will be as under: H01: There is no distinction between public and private banks in Pakistan with respect to the impact of the ratio of total outstanding loans and advances to total assets on cost efficiency. Y2 (Ratio of total investment to total assets) Author Janjua Country Pakistan Variable Investments Findings Variable efficiency cost across

banking sector

30

The above study prompted me to see the effect of investments on the total cost of banks in Pakistan. I use the ratio of total investment to total assets as independent variable. I will investigate whether public and private banks in Pakistan differ with respect to the impact of level of investments on the cost efficiency. The related hypothesis will be as under: H02: There is no difference between public and private banks in Pakistan with respect to the impact of the ratio of total investments to total assets on cost efficiency. W1 (Price of financial capital) Author Gregarion Manole and Country Variable Interest expenses Findings Foreign enhances performance ownership bank

Janjua

Pakistan

Financial prices

Overall

low

efficiency of the banking sector.The above studies prompted me to check the effect of price of financial capital on the efficiency of the banks. I use the ratio of total interest expense to total deposits and financial borrowings as independent variable. I will investigate whether the public and private banks in Pakistan differ with respect to the effect of price of financial capital on the cost efficiency of banks. The related hypothesis will be as under:

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H03: There is no difference between public and private banks in Pakistan with respect to the impact of the ratio of total interest expense to total deposits and financial borrowings on cost efficiency. W2 (Price of physical assets) Author Gregarion manole and Country Variable Operating assets Findings fixed Foreign enhances performance. Manlagnit Philippines Capital ownership bank

The above studies prompted me to evaluate the impact of prices of physical capital on the cost efficiency of banks. I use the ratio of depreciation cost to total operating fixed assets as an independent variable. I will investigate whether public and private banks in Pakistan differ with respect to the impact of price of physical assets on their cost efficiency. The related hypothesis will be as under: H04: There is no difference between public and private banks in Pakistan with respect to the impact of the ratio of total depreciation expense to total operating fixed assets on cost efficiency. W3 (price of labor) Author Hanif Akhtar Manlagnit Country Pakistan Phillippines Variable Labor Labor Findings

32

Gregarion Manole

and

Labor

Foreign enhances

ownership bank

performance. The above studies prompted me to evaluate the impact of price of labor on the cost efficiency of banks. I use the ratio of total salary expense to the total HR strength in the bank as an independent variable. I will investigate whether the public and private banks in Pakistan differ with respect to the impact of price of labor on the cost efficiency of banks. The related hypothesis will be as under: H05: There is no difference between public and private banks in Pakistan with respect to the impact of the ratio of total salary expenses to the total HR strength on cost efficiency. NPL (non performing loans) Author Das Country India Variable NPLs Findings

The above study prompted me to evaluate the impact of non performing loans on the cost efficiency of banks. I use the percentage of NPL to total assets as an independent variable. I will investigate whether public and private banks in Pakistan differ with respect to the impact of NPLs on their cost efficiency. The related hypothesis will be as under: H06: There is no difference between public and private banks in Pakistan with respect to the impact of the NPLs on cost efficiency.

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SAMPLEThis study uses unbalanced panel data of 15 banks. 3 banks are public and remaining 12 are private banks. The study does not include the specialized banks like ADBP. The study involves the annual data of the banks from 2003-2010.

ESTIMATION PROCEDUREUsing the intermediation approach, the cost of a bank can be calculated through a vector of outputs, a combination of its input prices, random error and the level of inefficiency as in the following equation

C = f(Y, W) + u + vWhere c represents the accumulated costs, Y shows the combination of output, W represents the combination of input prices, u represents the random error and v represents the level of inefficiency of the banks. Both u and v together form the residual term of the model. There might be a problem of isolating the inefficiency and random error of the banks. To overcome this problem, fixed effects model is used in this study. Banks specific constant includes the inefficiency associated with that specific bank. The below written econometric equality represents the general form of the model

Cit = + Xit + ui + vitWhere I = 1,2,3.N indices while t = 1,2,. T indexes the time span from 2003 to 2010. The term Cit represents the cost estimate of ith bank at time t. vit represents the random34

error of ith bank at time t. ui shows inefficiency level of the ith bank which is assumed to remain constant over time. Following assumptions should be considered while considering error and efficiency terms.

The vit term is uncorrelated with the regressors Xit such that corr(Xitvd) = 0 The inefficiency of the best practice bank Is assumed to be zero at the given time. Uis are assumed to follow identical independent distribution with mean u and Variance S2

Corr(ui,vi)=0

By using the FEM, the impact of all outside variables on the efficiency of individual banks is assumed to be same. This assumption also covers the fact that all banks are acting under same general economic conditions, legal regulations, implemented fiscal restrictions and other effects. The general form of the model can be modified as under.

Cit = ( + ui ) + Xit + vitWhere i = ( + ui ) so

Cit = i + Xit + vitThe trans log cost function of the ith bank can be represented in the following equation

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TC = total cost (administrative cost plus interest expenses) to total asset ratio Y1 = ratio of total advances to total assets Y2 = ratio of total investments to total assets NPL/ Assets = percentage ratio of NPL to assets W1 = Price of financial capital calculated as the ratio of total interest expenses to total deposits and financial borrowings

W2 = Price of physical assets calculated as the ratio of depreciation cost to total operating fixed assets

W3 = Price of labor inputs calculated as the ratio of salary expenses to total number of employees

I = index of banks t = time subscript indicating the respective year where t = 1.. 12 T = time variable quantifies the impact of technological progress upon cost

DATA COLLECTIONThe data for this study will be gathered from the annual balance sheets of the banks. Figures like interest expenses will not be available for some banks which do not pay or earn interest.36

CHAPTER 4: DATA ANALYSIS

37

Two approaches have been suggested in the literature to evaluate the performance of the banking sector. Parametric and non-parametric approaches. Parametric approaches encompass distribution free method, thick frontier method etc. Non-parametric approaches include data envelopment analysis and total factor productivity measures. Panel data models are better as compared to the time series analysis. Since the financial institutions are heterogeneous in their internal determinants and factors. Time series analysis runs the risk of biased results due to the problem of heterogeneity. Panel data allows for more information, less collinearity among the variables, more degrees of freedom and more efficiency. Thus this study uses the panel data analysis to overcome the same problem. In the research on the banking sector, appropriate choice of inputs and outputs has always been a serious problem. Two methods exist in the literature for examining the banking system. Intermediation approach and production approach. The production approach uses the traditional sources of production i.e. land, labor and capital to provide services to depositors and borrowers. The intermediation approach sees banks as financial helpers who use labor and physical assets to change deposits and other available resources into advances. A model has been developed to calculate the cost efficiency of the banking sector. Distribution free approach has been undertaken. The efficiency has been calculated with the help of software named Eviews 5.0.

Multicollinearity38

Y1 Y1 Y2 W1 W2 W3 NPL 1 0.75810 0.00455 -0.02637 0.06279 0.68997

Y2 0.75810 1 -0.01830 -0.06663 -0.01111 0.62163

W1 0.00455 -0.01830 1 -0.04266 0.113076 0.00652

W2 -0.02637 -0.06663 -0.04266 1 0.077963 0.00736

W3 0.06279 -0.01111 0.113076 0.077963 1 0.39277

NPL 0.68997 0.62163 0.00652 0.00736 0.39277 1

Multicollinearity refers to a situation where the correlations between the independent variables are significant. This is especially important in cases where researcher wishes to compare two sets of data on some common variables. As we can see in the above table, in case of variable Y1, the problematic figures are the correlations with Y2 and NPL. This means that while observing the relationship between total cost and Y1, the change in Y1 will also affect the variables Y2 and NPL. In case of the variable Y2, the problematic figures are those of Y1 and NPL. The variables W1 and W2 have no problematic figure when observed with respect to multicollinearity. The variable W3 has somewhat problematic figure with NPL. In case of NPL, Y1, Y2 and W3 are problematic. The log transformation has been applied on the data. R squared for the private sector is calculated at 0.8675 which means that the independent variables define 86.75% variation in the dependent variable. Further analysis shows that for both nationalized and denationalized banks, the same figure for the public sector is calculated at 0.979 which means that the independent variables define 97.9% variation in the dependent variable.

39

As far as the individual variables are concerned, in case of private sector banks, Y1 and Y2 are the most significant variables and in case of public sector banks. Y2 and W1 are the most significant variables. The values are calculated at 95% confidence interval. Among the input prices, in the public sector banks, the price of financial capital and the price of labor have a considerable effect on the total cost of the banks. In the group of private sector banks, price of financial capital and price of physical assets are found to have a considerable effect on the cost of banks. Due to political interference the non performing loans have turned out to be a huge problem for the public sector banks. Parallel to this notion the unhealthy loans have a greater impact on the costs of nationalized banks as compared to the private sector banks. In case of private sector banks, the NPL variable does not have an important impact on cost. In the case of private banks, 1% change in NPL will bring a 4% change in the total cost. In the case of government sector banks 1% change in NPL will bring a 52% change in the total cost. This figure depicts the vulnerability of the government sector banks to the NPLs. The technological impact has been significant on both the groups. However the private sector banks have been found to have better use of the available technology as compared to their public counterparts. Main aspects of technological progress include automation of banking transactions. The technological progress has reduced the cost of banking considerably. As far as the group comparison is concerned, the government sector is found to have more efficiency as compared to the private sector banks.

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Dependent Variable: TC_? Method: Pooled Least Squares Date: 02/24/12 Time: 20:40 Sample: 2003 2010 Included observations: 8 Cross-sections included: 3 Total pool (unbalanced) observations: 22 Variable NPL_? R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood Coefficient 0.826229 0.752408 0.752408 1.847827 71.70378 44.21316 Std. Error 0.223264 t-Statistic 3.700682 Prob. 0.0013 1.877471 1.395866 4.110287 4.159880 0.705602

Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion Durbin-Watson stat

In the individual analysis, the above table depicts the relationship between total cost and NPL. There is a positive relationship between the two said variables. As the probability figure lies at 0.0013, this depicts a significant impact of NPL on the total cost. The figure under the head coefficient shows that a unit change in NPL will bring 82.62% change in the total cost. This fact makes it necessary for all the banks to keep a close eye on NPLs.

41

Dependent Variable: TC_? Method: Pooled Least Squares Date: 02/24/12 Time: 23:07 Sample: 2003 2010 Included observations: 8 Cross-sections included: 3 Total pool (balanced) observations: 24 Variable C Y1_? Fixed Effects (Cross) NBP--C BOK--C FWBL--C Coefficient -1.717822 0.968855 -1.121563 0.851933 0.269629 Effects Specification Cross-section fixed (dummy variables) R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood Durbin-Watson stat 0.572184 0.508011 0.970274 18.82862 -31.14242 1.242555 Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion F-statistic Prob(F-statistic) -1.985708 1.383301 2.928535 3.124877 8.916343 0.000594 Std. Error 0.209065 0.242123 t-Statistic -8.216694 4.001492 Prob. 0.0000 0.0007

In the individual analysis, the above table depicts the relationship between total cost and Y1. There is a positive relationship between the two said variables. As the probability figure lies at 0.0007, this depicts a significant impact of Y1 on the total cost. The figure under the head coefficient shows that a unit change in Y1 will bring 96.88% change in the total cost. As the effect of change in the variable on total cost is very strong, the banks should keep a close check on the variations of the variable.

42

Dependent Variable: TC_? Method: Pooled Least Squares Date: 02/24/12 Time: 23:10 Sample: 2003 2010 Included observations: 8 Cross-sections included: 3 Total pool (balanced) observations: 24 Variable C Y2_? Fixed Effects (Cross) NBP--C BOK--C FWBL--C Coefficient -1.163540 1.011197 -0.293348 0.579400 -0.286051 Effects Specification Cross-section fixed (dummy variables) R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood Durbin-Watson stat 0.799020 0.768873 0.665031 8.845334 -22.07656 1.247948 Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion F-statistic Prob(F-statistic) -1.985708 1.383301 2.173047 2.369389 26.50411 0.000000 Std. Error 0.174237 0.174197 t-Statistic -6.677912 7.527072 Prob. 0.0000 0.0000

In the individual analysis, the above table depicts the relationship between total cost and Y2. There is a positive relationship between the two said variables. As the probability figure lies at 0.0000, this depicts a highly significant impact of Y2 on the total cost. The figure under the head coefficient shows that a unit change in Y2 will bring more than 100% change in the total cost. As the effect of change in the variable on total cost is very strong, the banks should keep a close check on the variations of the variable.

43

Dependent Variable: TC_? Method: Pooled Least Squares Date: 02/24/12 Time: 23:11 Sample: 2003 2010 Included observations: 8 Cross-sections included: 3 Total pool (balanced) observations: 24 Variable C W1_? Fixed Effects (Cross) NBP--C BOK--C FWBL--C Coefficient 0.073738 0.751226 -0.221851 -0.373223 0.595074 Effects Specification Cross-section fixed (dummy variables) R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood Durbin-Watson stat 0.684497 0.637171 0.833235 13.88561 -27.48811 1.716671 Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion F-statistic Prob(F-statistic) -1.985708 1.383301 2.624009 2.820352 14.46360 0.000031 Std. Error 0.419566 0.139906 t-Statistic 0.175748 5.369498 Prob. 0.8623 0.0000

In the individual analysis, the above table depicts the relationship between total cost and W1. There is a positive relationship between the two said variables. As the probability figure lies at 0.000031, this depicts a highly significant impact of W1 on the total cost. The figure under the head coefficient shows that a unit change in W1 will bring 75.12% change in the total cost. As the effect of change in the variable on total cost is very strong, the banks should keep a close check on the variations of the variable.

44

Dependent Variable: TC_? Method: Pooled Least Squares Date: 02/24/12 Time: 23:12 Sample: 2003 2010 Included observations: 8 Cross-sections included: 3 Total pool (balanced) observations: 24 Variable C W2_? Fixed Effects (Cross) NBP--C BOK--C FWBL--C Coefficient -1.155819 0.417383 -0.495447 0.382467 0.112980 Effects Specification Cross-section fixed (dummy variables) R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood Durbin-Watson stat 0.365107 0.269873 1.181996 27.94228 -35.87957 1.254638 Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion F-statistic Prob(F-statistic) -1.985708 1.383301 3.323298 3.519640 3.833786 0.05558 Std. Error 0.468664 0.202074 t-Statistic -2.466200 2.065497 Prob. 0.0228 0.0521

In the individual analysis, the above table depicts the relationship between total cost and W2. There is a positive relationship between the two said variables. As the probability figure lies at 0.0521, this depicts a significant impact of W2 on the total cost. The figure under the head coefficient shows that a unit change in W2 will bring 41.73% change in the total cost. As the effect of change in the variable on total cost is very strong, the banks should keep a close check on the variations of the variable.

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Dependent Variable: TC_? Method: Pooled Least Squares Date: 02/24/12 Time: 23:15 Sample: 2003 2010 Included observations: 8 Cross-sections included: 3 Total pool (unbalanced) observations: 23 Variable C W3_? Fixed Effects (Cross) NBP--C BOK--C FWBL--C Coefficient -1.534440 0.122550 -0.784114 0.636546 0.049554 Effects Specification Cross-section fixed (dummy variables) R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood Durbin-Watson stat 0.352990 0.250831 1.209613 27.80011 -34.81536 0.877509 Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion F-statistic Prob(F-statistic) -2.029195 1.397515 3.375249 3.572726 3.455292 0.037105 Std. Error 0.477809 0.100519 t-Statistic -3.211410 -1.219166 Prob. 0.0046 0.0377

In the individual analysis, the above table depicts the relationship between total cost and W3. There is a positive relationship between the two said variables. As the probability figure lies at 0.0377, this depicts a significant impact of W3 on the total cost. The figure under the head coefficient shows that a unit change in W3 will bring more than 100% change in the total cost. As the effect of change in the variable on total cost is very strong, the banks should keep a close check on the variations of the variable.

46

Method: Pooled Least Squares Date: 01/01/12 Time: 10:01 Sample: 2003 2010 Included observations: 8 Cross-sections included: 3 Total pool (unbalanced) observations: 21 Variable C Y1_? Y2_? W1_? W2_? W3_? NPL_? Fixed Effects (Cross) NBPC BOKC FWBLC Coefficient Std. Error 0.028144 0.124343 1.258662 0.501143 0.023220 0.213181 0.527480 -0.037643 -0.053886 0.077413 Effects Specification Cross-section fixed (dummy variables) R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood Durbin-Watson stat 0.979171 0.965285 0.263771 0.834902 4.064407 2.259584 Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion F-statistic Prob(F-statistic) -1.919946 1.415694 0.470056 0.917709 70.51530 0.045352 0.138804 0.117701 0.178979 0.072248 0.064062 0.053414 0.129496 t-Statistic 0.202763 1.056431 7.032445 6.936393 -0.362463 3.991132 -4.073337 Prob. 0.8427 0.0007 0.0000 0.0000 0.0233 0.0018 0.0015

The above table depicts the overall impact of all variables on total cost. In the public bank group, almost all variables seem to have a considerable impact on total cost. In cases of this group, the most important variables are Y2 and W1. These figures show that the banks should keep a close look on these two variables. NPL also shows a significant effect on the total cost. Further if the total cost of any bank rises abruptly, initially these three variables can be looked upon. The figure named R squared shows that the independent variables show 97.9% variation in the dependent variable. The probability47

figure of 0.045352 shows a significant relationship between independent and dependent variables.

48

Dependent Variable: TC_? Method: Pooled Least Squares Date: 02/24/12 Time: 23:28 Sample: 2003 2010 Included observations: 8 Cross-sections included: 12 Total pool (unbalanced) observations: 85 Variable C NPL_? Fixed Effects (Cross) ABL--C ASK--C BAL--C FAYSAL--C HBL--C HMB--C JS--C MCB--C MEE--C NIB--C SON--C UBL--C Coefficient 2.161863 0.699695 -0.346409 0.239710 1.108488 0.447366 1.445977 -1.558793 -0.782747 -0.043595 -0.075147 0.014123 0.227166 -0.327406 Effects Specification Cross-section fixed (dummy variables) R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood Durbin-Watson stat 0.207394 0.075293 1.470753 155.7442 -146.3462 1.426971 Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion F-statistic Prob(F-statistic) -2.226836 1.529458 3.749323 4.122905 1.569964 0.120105 Std. Error 0.222582 0.167160 t-Statistic -9.712653 -0.418575 Prob. 0.0000 0.0676

In the individual analysis, the above table depicts the relationship between total cost and NPL for the private sector banks. There is a positive relationship between the two said variables. As the probability figure lies at 0.0677, this depicts a significant impact of

49

NPL on the total cost. The figure under the head coefficient shows that a unit change in NPL will bring 70% change in the total cost, the same figure for the public sector is 82.62% which depicts a considerable difference between the two groups. The Ho7 is thus rejected. As the effect of change in the variable on total cost is relatively strong, the banks should keep a close check on the variations of the variable.

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Dependent Variable: TC_? Method: Pooled Least Squares Date: 02/24/12 Time: 23:31 Sample: 2003 2010 Included observations: 8 Cross-sections included: 12 Total pool (unbalanced) observations: 88 Variable C Y1_? Fixed Effects (Cross) ABL--C ASK--C BAL--C FAYSAL--C HBL--C HMB--C JS--C MCB--C MEE--C NIB--C SON--C UBL--C Coefficient 1.820597 1.197283 -0.113591 0.424622 0.248964 0.562829 -0.282994 -0.799440 0.062961 -0.479918 0.075429 0.231843 0.443094 -0.151121 Effects Specification Cross-section fixed (dummy variables) R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood Durbin-Watson stat 0.525647 0.449751 1.123329 94.64018 -128.0674 1.730035 Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion F-statistic Prob(F-statistic) -2.259357 1.514354 3.206077 3.572047 6.925842 0.002000 Std. Error 0.133134 0.158772 t-Statistic 13.67487 7.540912 Prob. 0.0000 0.0000

In the individual analysis, the above table depicts the relationship between total cost and Y1 for the private sector banks. There is a positive relationship between the two said variables. As the probability figure lies at 0.0000, this depicts a highly significant

51

impact of Y1 on the total cost. The figure under the head coefficient is 1.1972 while the same figure for the public sector lies at 0.9688 which depicts a considerable difference between the two groups. The H01 is rejected. As the effect of change in the variable on total cost is very strong, the banks should keep a close check on the variations of the variable.

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Dependent Variable: TC_? Method: Pooled Least Squares Date: 02/24/12 Time: 23:32 Sample: 2003 2010 Included observations: 8 Cross-sections included: 12 Total pool (unbalanced) observations: 88 Variable C Y2_? Fixed Effects (Cross) ABL--C ASK--C BAL--C FAYSAL--C HBL--C HMB--C JS--C MCB--C MEE--C NIB--C SON--C UBL--C Coefficient -1.120160 1.144132 -0.076482 0.724203 0.016942 0.272311 -0.206979 -1.505265 -0.601863 -0.460442 0.657020 0.557308 0.380537 0.114865 Effects Specification Cross-section fixed (dummy variables) R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood Durbin-Watson stat 0.651508 0.595749 0.962838 69.52921 -114.5006 1.944928 Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion F-statistic Prob(F-statistic) -2.259357 1.514354 2.897742 3.263712 11.68439 0.000000 Std. Error 0.151509 0.111928 t-Statistic -7.393378 10.22201 Prob. 0.0000 0.0000

In the individual analysis, the above table depicts the relationship between total cost and Y2 for the private sector banks. There is a positive relationship between the two said variables. As the probability figure lies at 0.0000, this depicts a highly significant

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impact of Y2 on the total cost. The figure under the head coefficient lies at 1.4413 for private banks while the same figure for the public sector banks is 1.011 showing a considerable difference between two groups. Thus H02 is rejected. As the effect of change in the variable on total cost is very strong, the banks should keep a close check on the variations of the variable.

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Dependent Variable: TC_? Method: Pooled Least Squares Date: 02/24/12 Time: 23:33 Sample: 2003 2010 Included observations: 8 Cross-sections included: 12 Total pool (unbalanced) observations: 82 Variable C W1_? Fixed Effects (Cross) ABL--C ASK--C BAL--C FAYSAL--C HBL--C HMB--C JS--C MCB--C MEE--C NIB--C SON--C UBL--C Coefficient -0.005771 0.743104 -0.410371 0.094610 0.825761 0.174726 0.518672 0.005771 -0.584676 0.230802 -0.044674 -0.383934 -0.419180 -0.262137 Effects Specification Cross-section fixed (dummy variables) R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood Durbin-Watson stat 0.637738 0.574735 0.951221 62.43263 -105.1751 1.528824 Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion F-statistic Prob(F-statistic) -2.109811 1.458652 2.882319 3.263872 10.12247 0.000000 Std. Error 0.238009 0.075430 t-Statistic -0.024248 9.851548 Prob. 0.9807 0.0000

In the individual analysis, the above table depicts the relationship between total cost and W1 for the private sector banks. There is a positive relationship between the two said variables. As the probability figure lies at 0.0000, this depicts a highly significant

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impact of W1 on the total cost. The figure under the head coefficient lies at 0.6431for the private sector banks while the same figure for the public sector banks lies at 0.7512 depicting a considerable difference between the two groups. Thus H03 is rejected. As the effect of change in the variable on total cost is very strong, the banks should keep a close check on the variations of the variable.

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Dependent Variable: TC_? Method: Pooled Least Squares Date: 02/24/12 Time: 23:34 Sample: 2003 2010 Included observations: 8 Cross-sections included: 12 Total pool (unbalanced) observations: 87 Variable C W2_? Fixed Effects (Cross) ABL--C ASK--C BAL--C FAYSAL--C HBL--C HMB--C JS--C MCB--C MEE--C NIB--C SON--C UBL--C Coefficient -0.414836 0.767885 0.460805 0.175737 0.933182 0.136115 0.242606 -1.641377 0.225174 0.086669 0.015776 -0.257466 -0.184914 -0.408682 Effects Specification Cross-section fixed (dummy variables) R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood Durbin-Watson stat 0.586758 0.519746 1.055519 82.44486 -121.1083 1.472642 Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion F-statistic Prob(F-statistic) -2.258429 1.523108 3.082949 3.451418 8.756001 0.000000 Std. Error 0.240656 0.088464 t-Statistic -1.723771 8.680235 Prob. 0.0889 0.0000

In the individual analysis, the above table depicts the relationship between total cost and W2 for the private sector banks. There is a positive relationship between the two said variables. As the

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probability figure lies at 0.0000, this depicts a highly significant impact of W2 on the total cost. The figure under the head coefficient lies at 0.7678 while the same figure for the public sector banks lies at 0.4173 depicting a significant difference between the two groups. Thus H04 is rejected. As the effect of change in the variable on total cost is very strong, the banks should keep a close check on the variations of the variable.

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Dependent Variable: TC_? Method: Pooled Least Squares Date: 02/24/12 Time: 23:34 Sample: 2003 2010 Included observations: 8 Cross-sections included: 12 Total pool (unbalanced) observations: 81 Variable C W3_? Fixed Effects (Cross) ABL--C ASK--C BAL--C FAYSAL--C HBL--C HMB--C JS--C MCB--C MEE--C NIB--C SON--C UBL--C Coefficient 0.482532 0.840426 -0.331158 0.265442 0.069769 0.601327 1.442750 -1.447929 0.325132 0.005328 -0.004521 -0.002456 0.054244 -0.291826 Effects Specification Cross-section fixed (dummy variables) R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood Durbin-Watson stat 0.544023 0.463557 1.023372 71.21575 -109.7202 1.249426 Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion F-statistic Prob(F-statistic) -2.138030 1.397242 3.030130 3.414424 6.760870 0.052300 Std. Error 0.271743 0.050752 t-Statistic 1.775692 6.707606 Prob. 0.0803 0.0000

In the individual analysis, the above table depicts the relationship between total cost and W3 for the private sector banks. There is a positive relationship between the two said variables. As the probability figure lies at 0.0000, this depicts a highly significant

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impact of W3 on the total cost. The figure under the head coefficient lies at 0.8404 while the same figure for the public sector banks lies at 0.1225 depicting a considerable difference between the two groups. Thus H05 is rejected. As the effect of change in the variable on total cost is very strong, the banks should keep a close check on the variations of the variable.

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Dependent Variable: TC_? Method: Pooled Least Squares Date: 01/01/12 Time: 06:49 Sample: 2003 2010 Included observations: 8 Cross-sections included: 12 Total pool (unbalanced) observations: 75 Variable C Y1_? Y2_? W1_? W2_? W3_? NPL_? Fixed Effects (Cross) ABLC ASKC BALC FAYSALC HBLC HMBC JSC MCBC MEEC NIBC SONC UBLC Coefficient Std. Error -0.089320 0.431181 0.566873 0.179123 0.152285 0.071080 0.047814 -0.086518 0.352967 -0.154161 0.203813 -0.132672 0.089320 0.283869 -0.427792 0.164585 0.105396 -0.050643 -0.153511 Effects Specification Cross-section fixed (dummy variables) R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood Durbin-Watson stat 0.898026 0.867613 0.473893 12.80075 -40.12097 1.840818 Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion F-statistic Prob(F-statistic) -1.964820 1.302437 1.549892 2.106090 29.52736 0.000000 0.135781 0.133092 0.109617 0.092777 0.077030 0.045221 0.070291 t-Statistic -0.657821 3.239721 5.171391 1.930678 1.976942 -1.571846 -0.680230 Prob. 0.5133 0.0020 0.0000 0.0000 0.0000 0.0523 0.4991

The above table depicts the overall impact of all variables on the total cost in case of private banks. Except for NPL, all other variables seem to have important effects on the total cost. The figure against R squared shows that the independent variables account for61

89.8% of the variation in total cost. The probability figure at 0.0000 shows a highly significant impact on the total cost. As far as the management is concerned, it has to keep a close look on Y2, W1 and W2. If the cost of any bank or the banking sector as a whole changes abruptly, the management should focus on these variables to rectify the situation. This opinion is further strengthened by the figures under the head coefficients. In case of Y2, W1 and W2, a unit change will bring a huge change in the total cost. Thus it will be beneficial for the management to keep a close look on these variables.

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CHAPTER 5 : CONCLUSION

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This research has applied the distribution free approach to compare the private and public sector banks in Pakistan. An unbalanced panel of 15 banks including 3 public and 12 private sector banks has been used. Both sectors differ significantly on the variables used. If we see the individual variables, all variables show different coefficient values against total cost. In case of NPL the coefficient for public sector is 0.8262 while the same figure for the private sector is 0.6996 depicting a considerable difference between the two sets. Next is the variable Y1(total advances/total assets) where the figure related to the public sector is 0.9688 while the same figure for private sector is 1.1972 depicting a clear difference between the two groups. In case of the variable Y2 (total investment/total assets) the figure for public sector is 1.0111 while the same figure for the private sector banks is 1.4413 thus depicting considerable difference between the groups. In case of price of financial capital i.e. W1 the figure for public sector banks is 0.7512 while the same figure for private sector banks is 0.6431depicting a considerable difference between the two groups. In case of W2 (price of physical assets) the value for the public sector banks is 0.4173 while the same figure for the private sector banks is 0.7678 depicting a considerable difference between the two groups. The last variable is W3 (price of human capital) whereby the figure for the public sector banks is 0.1225 while the same figure for the private sector banks is 0.8404 depicting a considerable difference between the two groups. Public sector banks have been found more efficient as opposed to the private sector banks. The major variables that affect both the sectors however differ. NPLs however are a point of concern for the public sector banks. In case of the private sector banks, the ratio of total investments to total assets is the major variable of concern. The

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technological progress has made a significant impact. Technological progress has come in the form of lesser transaction time and automated teller machines. As far as the policy implications of the study are concerned, the various variables and their impact can be taken as a signal as to which things are to be controlled in order to control the overall cost of the bank. Further the cost structure of the bank can be re assessed and decomposed so that the managers can assess and improve the situation for the banks. SBP can impose or relax its statutory role relative to the factors affecting cost efficiency i.e. if a variable has a significant impact on cost, SBP can impose strict regulations regarding the same. It can relax the banks in case of the variable that does not affect the cost significantly. The regulatory authorities can make the regulations that can result in cost minimization for the banks. In this regard, the SBP can impose regulations keeping in view the variables that affect the respective groups. From the future perspective, this research can provide ground for analyzing the differences within groups i.e. the researchers may be interested to know which banks cause the overall group performance to weaken or strengthen. Further this research can help the researchers to find out overtime whether factors affecting the cost efficiency have changed or remained constant. This aspect specially relates to the technological aspects whereby it remains to be seen whether technological impact increases or decreases overtime. Another aspect relates to the ever changing economic and geopolitical situation of the world. Being a third world country, Pakistan is especially vulnerable to any change in the economic and political situation in the world. Thus a researcher may be interested to see if the results of the research remain the same in changed economic and political situations.65

RECOMMENDATIONSThis study will help the state bank of Pakistan to determine the various factors that can affect the cost efficiency of a bank in general and the overall banking sector in particular. While making policies, it can focus on the most significant variables that affect the cost efficiency of the sector. NPLs affect the efficiency of the banks adversely especially in the case of nationalized banks. This reflects the political and bureaucratic influence on the public sector banks to issue loans. This practice should be curbed. Technological aspects should be improved in case of public sector banks. On the individual bank level, the cost structure of the bank may be re assessed to evaluate the effects of various variables upon banks.

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REFERENCESMuhammad Sadiq Ansari (2007). An empirical investigation of cost efficiency in the banking sector of Pakistan SBP Research bulletin volume 3 number 2 2. Usman, Wang, Mehmood and Humaira (2009). Scale efficiency in banking sector of Pakistan International journal of Business and management 3. Weill (1999). Measuring cost efficiency in European banking 4. Ataullah, Cockerill and Le (2004). Financial liberalization and bank efficiency: a comparative analysis of India and Pakistan Journal of Applied Economics 36, 1915-1924 5. Maudos and Past