Evaluation of Bank Efficiency with the DEA Approach
The financial system is one of the most significant factors of the economy of all countries around the global. The importance of banking system has led to the necessity of monitoring and evaluation of its efficiency. According to Saidenberg and Schuermann research, the Basel II regulation put barriers in the unlimited undertaking of risk by the financial institutions and focuses on the capital adequacy of financial institutions, especially, in the area of credit risk management. In this way, financial institutions are required to have a risk weight of 8% or less and thus, will be protected in a unexpected loss of capital, by undertaking a potential high risk. Hence, the financial institutions are becoming more efficient and solvent.
Over recent years, the financial sector has rapidly been developed and as a consequence its role became more complex. This phenomenon appears due to the liberalization of banking sector (deregulation) at the end of the year 1970 (initially in USA) and due to the adoption of Euro, which accelerated the competition in financial markets. Other factors are the globalization of financial and banking activities which reinforces the high competitiveness among different financial institutions are: mergers and acquisitions which often take place, volatility in the banking sector, unexpected fluctuations of the interest rates, high risks and rapid advances achieved in information technology (digitalization, e.g. E-banking) which constitute the recent forces that influence the efficiency of the banking sector.
Moreover, the recent financial crisis, which its roots go back to the unlimited mortgage credit expansion in USA loan market, initially influenced its economy. Then, in turn provoked a wider financial crisis which impacted global economy in general. In addition, it worth’s mentioning that Europe was more severely impacted by the crisis.
All the above events indicate the need of building a solid-stable financial system in any country so as every financial institution to maintain or even improve its profits and its efficiency and thus, its general performance. (Varotto, 2009) Ways which contribute to the grow of efficiency and stability of the banking sector and even better extend growth of banks, is the profitability and the effectiveness of its inputs and outputs. According to Wheelock and Wilson (1995), “measuring the efficiency of commercial banks is important for at least two reasons. First, efficiency measures are indicators of success, by which the performance of individual banks, and the industry as a whole, can he gauged. A second reason to investigate the efficiency of commercial banks is the potential impact of government policies on efficiency.”
It is essential for bankers to evaluate the bank’s performance through efficiency analysis. Bankers in order to evaluate bank’s efficiency can use different methods which can be classified in various ways. Such methods are the traditional financial analysis by using financial indicators (e.g. ROE, ROA etc.) based on balance sheet analysis, parametric methods based on the knowledge of production function and non-parametric methods which do not require such knowledge such as the Data Envelopment Analysis (DEA), (Wozniewska G., 2008)
This project will be an attempt to comprehend the non-parametric frontier method – Data Envelopment Analysis (DEA). This method has become increasingly popular in measuring bank efficiency in the countries with developed banking systems. (Wozniewska G., 2008) An additional effort, to assess the efficiency of a sample of 40 top (by assets) European commercial banks through the non-parametric method Data Envelopment Analysis, known as DEA, over the period 2005-2010, will take place. In addition, it is an international comparison of the evolution of the productivity of financial institutions in areas with different legal and institutional frameworks. Furthermore, the analysis will be completed by commenting our findings. The main purpose of this research is to explore the changes in banking efficiency over the period 2005-2010 at a group of European commercial banks that belong to different competitive and regulatory environments.
The significance of this research is indentified through the fact that risk is connected with every operation or process in banking system. The majority of a bank’s operations or processes include a high or low degree of risk e.g. an asset or a loan will become irrecoverable due to outright default. For this reason, an essential prerequisite is to measure the efficiency of the financial institutions and maintain it at a high level, so as the financial institutions are secured against a potential failure or bankruptcy. Moreover, it is quite interesting to explore the efficiency of European financial institutions, before financial agitations and then, the consequences of financial crisis in European bank’s performance. In addition, the evaluation of financial institutions constitutes one of the most interesting studies not only for the researchers interested in such analysis but also, for the financial institutions as well, since such works provide to the Banking Administration useful information concerning the performance of the financial institution. Consequently, the results of this analysis are absolutely essential for the viability of the examined European commercial banks under these unstable conditions.
In the next paragraphs of the Interim report are presented the methodology analysis, the data will be used and its sources, the estimated duration of the research in a timetable and we conclude with the references.
Literature review
Efficiency is a key concept for financial institutions, and it has long been studied. In recent years, new methodologies have been developed with main aim the analysis of institutions’ efficiency. Due to the recent events in the finance and banking environment, the study of evaluation and measurement of the efficiency of financial institutions has given rise to a growing body of empirical literature.
Specifically, in the year 1997, Berger and Humphrey surveyed 130 studies which were included at least five major techniques of measuring efficiency, which have been applied to financial institutions (Commercial banks, Savings banks, Credit unions and Insurance companies) in at least 21 countries (The most numerous studies were focusing on US financial institutions.) (Cinca et al., 2011). In this survey, there were 69 applications of nonparametric techniques and 60 using parametric approaches. However, some papers used more than one technique to measure the efficiency.
In recent years, the non-parametric DEA method has become the most popular efficiency analysis for the countries with developed banking systems (Grigorian, Manole, 2002). In their paper, by using DEA, they measure the efficiency of banking sector mainly in countries-eastern Europe (in transition economies) which have experienced major transformations throughout the 1990s. This method was developed, in the year 1978, by Charnes, Cooper and Rhodes (Wozniewska, 2008) and, initially, their aim was to be used in the public sector and in non-profits firms. However, nowadays, it is used widely by the financial institutions and firms in order to measure their efficiency levels.
According to the available literature, there are many researches, who examine the efficiency of financial institutions by using parametric or non-parametric methods, focus on the examination of USA countries, such as Elysiani & Mehdian, (1990); Aly et al. (1990); Ferrier & Lowel (1990); (Holló and Nagy, 2006) Rangan et al. (1988-1990, in which year the study was extended to include a sample of bank branches) etc. One more work with U.S. data, is the study of Elyasiani and Mehdian (1995). In this work, the selected years are 1979 and 1986 examining the pre and post-deregulation periods. Through DEA approach, they estimate efficiency levels for examined US banks for these years. (Fernández et al., 2004) Another recent work, on investigating the efficiency of banks is the work of Wezel T. (2010). The purpose of this study is to investigate the efficiency of domestic and foreign banks in the Central American region over the period 2002-2007, by using two main empirical approaches, DEA and Stochastic Frontier Analysis. The results of this research show that the foreign banks are not necessarily more efficient than their domestic rivals.
In addition, the literature includes several researches which are about the efficiency of financial institutions of European countries. In the year 1993, the research of Berg, Forsund et al. took place by using the DEA method and the data from Finland, Norway and Sweden for the year 1990. Another research which is analyzed in the same way with the present research is the paper of B. Casu & P. Moulineux (2003). In this paper, B. Casu & P. Molyneux, focus on the examination of the efficiency of banking system of 5 major European countries since the creation of the Single Internal Market and the deregulation of financial markets by using the DEA method. It was selected 530 banks of the countries France, Germany, Italy, Spain and England, for the examined period 1993-1997. In this study specifies two outputs, total loans and other earning assets and two inputs, total costs (interest expenses, non-interest expenses, personnel expenses) and total customers and short term funding(total deposits). According to their conclusions, “the DEA results show relatively low average efficiency levels; nevertheless, it is possible to detect a slight improvement in the average efficiency scores over the period of analysis for almost all banking systems in the sample, with the exception of Italy. However, the results show that the efficiency gap among countries grew even wider over the period 1993–1997.”
Other recent researches are concerning the examination of efficiency of banking sector of specific countries such as Australia by Sathye (2001) and Sturn & Williams (2004), Polish by Wozniewska G. (2008), India by Attaulah & Le (2006), Indian Saha and Ravisankar (2000), Brazil by Staub et al. (2010), Italy by Resti (1997) and Girandone et al. (2004), Turkey by Arlan and Ergec (2010), Cana Thailand by Chansarn (2008) Japan by Altunbas et al. (2000) and Drake & Hall (2003), Korea by Park & Weber (2006), Portugal by Lazano-Vivas (1998), Taiwan by Huang (2000) and Chen και Yeh (2001), Turkey by Isik & Hassan (2002) and (2003), England by Drake (2001), Ukraine by Mertens & Urga (2001), Greece by Athanasios G. Vasilakis (2005) and the most revently, India by Joshi and Bhalerao(2011). This type of researches are very interesting because they offer not only information about the financial system of every examined countries but also they focus on various subjects which are connected with the efficiency of financial institutions and finally, such researches offer an absolutely comprehensive analysis.
Other papers focus on a comparison of the efficiency among domestic and foreign financial institutions, such as the researches of Mahajan et al. (1996), Sabi (1996), Havrylchyk (2006), Kraft et al. (2006) and Sensarma R. (2006). In other studies the researchers choose the way to compare and contrast different methods in order to measure the efficiency of the examined institutions, such as Bauer et al. (1998) and Weil (2004).
Furthermore, F. Pasiouras (2006) in his study uses the DEA in order to evaluate the efficiency of the Greek commercial banking industry throughout the period 2000-2004. In addition, he compares the traditional intermediation approach with the recently proposed profit-oriented approach. Moreover, he compares the banks which are limited in domestic market and the ones which have expanded their operations in foreign markets. Based on the results, banks which have expanded their operations in foreign markets are more efficient than the ones operating only in the domestic market.
Some other studies which use DEA techniques to evaluate financial institutions’ efficiency and productivity are Athanassopoulos (1997), Pastor et al (1997), Seiford and Zhu (1999), Dekker and Post (2001), , Kuosmanen and Post (2001), Hartman et al (2001), Luo (2003), Wheelock and Wilson (2006) (Cinca, 2011) and Gobbi (1995) on Italian banks and Drake and Howcroft (1994) for UK building societies (Altunbas et al., 2001)
Other researchers use this non-parametric approach and investigate inefficiencies among bank branches. Specifically, this approach gives how much total productivity in the banking sector could be improved, and ranks the efficiency scores of individual banks. Empirical studies of Rangan et al. (1988), and Berger and Humphrey (1990) ranked banlung firms, while Sherman and Gold [1985], Parkan [1987], and Oral and Yolalan [I9901 analyzes bank branches. (Tser-Yieth and Tser-Lien(2000)
Also, few recent studies provide cross-country evidence such Field (1990) who applied the DEA method to a cross-section of 71 UK building societies in 1981. Most of them examine banks from the large EU banking sectors (Pastor, 2002; Casu and Molyneux, 2003; Beccalli et al., 2006). Lozano-Vivas et al. (2002) examine ten EU countries, Bergendahl (1998) focuses on Nordic countries, while Pasiouras (2008a) examines an international dataset.
As it is presented by the studies mentioning before, the evaluation of commercial bank efficiency/performance has been approached from various standpoints. Recent DEA studies have examined almost all the banking sectors around the global. However, it is obvious the necessity of continuing evaluating of bank efficiency due to the volatility in financial markets, the high undertaken risks by banks, the high competitive environment in which the banks operate etc. Under such conditions, the present study tend to add in the bibliography examining the efficiency of European banking sector.
Methodology
The efficiency of the banking sector has been one of the major issues in the recent studies. The efficiency and competitiveness of financial institutions cannot easily be measured, since their products and services are intangible. However, many researchers have attempted to develop ways to estimate the efficiency levels of the banking institutions by using outputs, costs, efficiency and performance. (Kosmidou and Zopounidis, 2008)
According to the available literature, there are many ways on banking evaluation. One way which have been proposed for the estimation of banks’ efficiency is the Uniform Financial Institutions Rating System (UFIRS). This system is mainly used by the Regulators in order to evaluate banks’ efficiency. Another way is the Uniform Bank Performance Reports (UBPR) which is an evaluation that concerns the American banks of USA. In addition, another way to measure and rank the financial institutions based on how efficiency are is the credit rating agency. The three major credit rating agencies are Moody’s, Standard & Poor’s and Fitch Ratings. Also, the methods of the Multicriteria Decision Aid (MCDA) are used widely. However, many researchers choose the way of financial analysis, through financial indicators, by using the financial data of Balance sheets and Income statements for the examined years. (ΓΚΟΡΓΚΟΛΗΣ, 2007)
In this study we will measure the efficiency of x top banks (ranked by assets) from the European banking system over the period 2005-2010, through the method of Data Envelopment Analysis (DEA). Specifically, this non-parametric frontier analysis (DEA) will be applied to estimate the relative efficiency of commercial banks of different geographical areas.
As it is referred before, in the year 1978, the non-parametric DEA method was first introduced by Charnes, Cooper and Rhodes, known as “CCR model”. Nowadays, this method has become widely known in measuring efficiency of developed banking systems (Grigorian, Manole, 2002; Wozniewska2008).
According to, Duygun-Fethi και Pasiouras (2009) the obvious advantages of DEA approach are that:
It implies succefully with small samples.
It does not require to undertake any assumptions concerning the distribution of inefficiency.
It does not require a specific type of data in order to determine the most efficient banks.
However, in the same research it is mentioned that there are two well-known limitations of this method. The first is that “DEA assumes data to be free of measurement error and the second one, that it is sensitive to outliers.”
In this approach the units which convert the inputs to outputs are referred as Decision Making Units (DMUs). In addition, the DEA efficiency value for a Decision-Making Unit (DMU) is not determined by a specific level, but it is determined in comparison to the other DMUs of the examined sample. That characteristic differentiates the DEA approach from the parametric approaches, which require particular functional form. Casu & Molyneux (2003).
Based on Duygun-Fethi και Pasiouras (2009), “DEA is a mathematical programming technique for the development of production frontiers and the measurement of efficiency relative to these frontiers.” So, every unit in the effective frontier is considered to be efficient, which means that the examined unit uses the suitable sources and it is not possible to increase the production of certain goods, while its efficiency is equal to 1. On the other hand, the units below the efficient frontier line present efficiency less than 1. Consequently, for each unit is considered as efficiency score a value from 0 to 1. (Wozniewska, 2008). So, in our case, “each bank, with higher scores indicating a more efficient bank, relatively to other banks in the sample.” Duygun-Fethi και Pasiouras (2009).
Based on the relevant theory the implementation of the DEA approach requires the choice one of the two approaches. The first is the Profit Approach and the second one is the Intermediation Approach. According to Intermediation Approach, as outputs, we consider the total loans and other earning assets but as inputs, the expenses and in Profit approach we consider as outputs, the total income and as inputs, the total operating expenses and interest expenses.
In addition, we have to set:
the outputs and inputs of the model according to the examined DMUs
the collection of the data
the solve of our regression model and
the interpretation of the results
Furthermore, it follows the implementation of the multi-criteria Promethee method in order to evaluate the performance and then, classify the sample of European commercial banks. “The Promethee method can be considered as an extension of the CAMEL rating system, which is widely used in the assessment of banking performance. The advantage of the Promethee method is that it does not assume a linear evaluation model and it can easily be used with qualitative data. Compared to other performance assessment methodologies, such as data envelopment analysis (DEA), PROMETHEE is easier to implement and it does not require the specification of inputs and outputs, which may not always be easy to identify.” This approach was initially, proposed by Brans (1982). (Kosmidou and Zopounidis, 2008)
The main source of literature will be collected from the electronic databases of Wiley Online library, Science Direct-Elsevier, Taylor and Francis group and Oxford Journals through VPN connection and the library of Portsmouth University and TEI of Crete. Firstly, based on the available relevant literature, we will attempt to give a brief description of the function of the European financial system in order to understand the main financial institutions and its operations. Additionally, it will follow a historical examination of European banking system, while we will mention the factors that they constituted in its transformation up to gets its current form. Then, the main part will contain the presentation of the background of DEA approach, which will be used for the evaluation of commercial banks of the sample. Moreover, it will take place, a presentation of the Multicriteria method Promethee which will be used in order to classify the examined financial institutions. Furthermore, we will illustrate the data that will be used and the sample of the examined financial institutions. Then, we will give a detailed description of the results which will be raised from the implementation of the DEA approach and Promethee method in the investigated sample, over the examined period of time. In addition, we will mention a more comprehensive analysis of the results in order to be comprehended clearly. In conclusion, we will summarize conclusions which are exported from the present research relatively with the operation of banking institutions and some issues for further research.
The necessary resources for the efficiency analysis will be mainly the Internet through the Bankscope database, which will be the provider of the bank’s annual reports and the software xxx. For the efficiency analysis will be used a financial data of Balance sheets and Income statements for the years 2005-2010. The (no of examined banks) top (by assets) European commercial banks that will be chosen are:
xxx
Then, we will summarize the results on tables. Hence, we will be able to observe the fluctuation of the results throughout the years. In conclusion, we are going to write a report in order to comment on our findings and add our predictions about the tendency of European banking sector the next years.
Timetable
The estimated duration of the research is presented in the following timetable:
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