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Study On The Pressures Faced By Financial Markets

Introduction

Rapid globalization and free trade in recent years have created so many significant changes to the world economic environment. Financial markets are also facing big pressures of the globalization process as well as other markets. With effective, fair and stable financial markets, all economies in the world will benefit from and they tend to maintain these characteristics of the markets in their best capacity. However, the recent financial crisis, which started late 2008 in the US banking system, hit the global financial markets severely, especially banking sectors.

“Bank” has becomes a very familiar word with anybody living and working in all over the world. According to the Oxford dictionary of Finance and Banking (2008:34), “Bank is a commercial institution that takes deposits and extends loans. Banks are concerned mainly with making and receiving payments on behalf of their customers, accepting deposits, and making short-term loans to private individuals, companies, and other organizations. However, they also provide money transmission services and in recent years have diversified into many areas of financial services…” Since bank plays such a pivotal role in the economy as a whole and each individual’s life, it is important in “ensuring that the financial system and the economy run smoothly and efficiently” (Mishkin et al. 2009:421). Therefore, the performance as well as operation of it are always the burning issue and draw lots of attentions. In addition, the wake-up call from the recent financial crisis makes reforming and re-regulating the banking sector as well as examining the performance and health of banks, especially commercial banks, have become the main interest of so many researchers, scholars, investors, policy makers etc and the general public.

UK is one of the world financial centers with respectful and successful banks, in particular, commercial banks. Although the numbers of banks in the UK cannot compare with the that of the US, but still the performance of them all contribute to maintaining financial stability in the UK as an essential ingredients for a healthy and successful economy. The efficiency operation of banks has been discussed for decades and it is becoming more and more important due to rapid growth of the financial markets and institutions. The more banks operate efficiently, the more profitable and greater amount of funds they get. In addition, the amount of studies on UK efficiency is still very little while the studies on the US banking efficiency are definitely dominated the literature on the matter which accounts for over 60 percent. Moreover, most of the studies on UK banking system are cross-country studies, which put together the UK with other countries especially European countries. Therefore, with the interest of finding how well the commercial banks in the UK are doing by measuring their efficiency and performance, both before and after the global crisis, I bravely chose this topic with the hope to provide readers a view on this matter.

There are many methods to assess the performance of banks as well as to evaluate the efficiency of them (e.g. non-parametric and parametric frontier methodologies). However, the non-parametric approach is more flexible in compare with the parametric one in examining efficiency bases on multiple inputs and outputs data (Farrell 1957; Charnes et al. 1978; Fare et al. 1994) since it tends to envelop data collected from sampled financial institutions in order to estimate the optimal production or cost level of the whole sample, then scores each institution by comparing its current level with the optimal one (Ngo 2010). Furthermore, the Data Envelopment Analysis (DEA) is by far the most commonly used non-parametric frontier methodology in evaluating the efficiency and performance of banks. For this reason, I use DEA to obtain the efficiency of individual commercial banks in the UK for the period 2004-2009, and then can compare my findings with other studies also using DEA to assess UK commercial banks’ efficiency.

The dissertation with the title “Evaluating the efficiency of commercial banks in the United Kingdom: an application of data envelopment analysis” is divided into several sections and sub-sections with three main chapters. Firstly, I will briefly introduce the definition of commercial banks, the overview of UK banking systems and the review of the literature on the field. Secondly, the methodology and data used in the study will be described. Then, the empirical results and findings will be presented and discussed in chapter three. Last but by no means least, I will summarize all of the key findings together with self-opinion, the limitations of the research process as well as suggest some implications for future research and decision makings. The main contents of this dissertation proceeds as follows:

Introduction

Chapter one: A review of the literature

Chapter two: Methodology and Data

Chapter three: Empirical results and analysis

Conclusion

Recommendations/ Reflections

Chapter I: A review of the literature

1. Overview of UK banking system

The UK financial system includes the Central Bank (Bank of England), commercial banks, investment, development banks and building societies. It main purpose is to bring together savers and investors, i.e. one person's savings are the finance for another person's [1] .

Top 10 facts about UK banking system, according to British Bankers' Association (4/5/2007):

“Banking employs close to half a million people. The wider financial industry employs over 1.1 million and, together with related activities (accountancy, business, computer and legal services, etc), some 3 million people rely on the financial industry for their jobs.

Banks and financial services contribute £70 billion to the UK's national output (6.8% of GDP).

Banks and financial services provide 25% of total corporation tax (£8billion) to the UK Government.

The main retail banks provide over 125 million accounts, clear 7 billion transactions a year and facilitate 2.3 billion cash withdrawals per year from its network of over 30,000 free ATMs.

Banks provide cost-effective banking services to 95% of the UK’s population

In 2005, 24 million personal customers registered to access their bank accounts online, while 42 million are registered to access their accounts by telephone.

Since April 2003, banks have opened a net total of 1.8 million Post Office-accessible basic bank accounts.

Banks in the UK contribute well over £100 million per year to charities and local community initiatives.

Five UK banks are in the top 15 firms listed in the DTI's recent 2006 Value Added Scoreboard of Wealth Creating Companies.

The value of foreign exchange business passed through London every day is £560 billion ($1 trillion)”. [2] 

As seen above, the UK banking sector contributes significantly to the UK and its economy. It not only enjoys one of the most competitive, efficient and secured banking systems in the world, but is one of the cheapest countries in the world to bank. [3] From 1980s onwards, there are a numerous of significant changes and rapid transformation in the UK banking sector. The majority of these changes are structural, in order to improve the sector as well as the financial system as a whole gradually, to adapt with changes in the UK as well as in the world, regarding economy, environment, politics etc. According to Drake (2001), “…This structural change has been associated with: increasing competition, both within and across sectors; deregulation; increased diversification and merger activity and, more recently, the de-mutualisation of segments of both the life assurance and building society industries. These trends have impacted forcefully on the UK banking sector. Following the intensification of competition in both corporate sector lending and international banking in the late 1970s, UK banks began to focus increasingly on domestic retail banking operations in order to maintain their profitability. In 1981, for example, UK banks entered the mortgage market in a significant way and in 1986, following “Big Bang” in the London stock exchange, a number of the large UK clearing banks diversified into investment banking activities. More recently UK banks have diversified into insurance, and particularly into life assurance. In common with banks around the world, UK banks have dramatically increased the contribution to profits emanating from “off' balance sheet” business and fee income”.

During the period of 1994-1997, there were so many building societies convert into banks as following the Building Societies Act 1986 and 1997 that would intensify the competition as well as widen the choices for consumers [4] . Moreover, according to McCauley et al. (1997) and White (1998), from 1991 to 1996, the merger and acquisition activity in the banking sector took place with the number of cases more than any other European country [5] . In addition, new players such as supermarkets, insurance companies and football clubs were allowed to enter the retail financial markets in Britain and are now offering a range of financial services such as credit cards, unit trusts etc (Kosmidou et al. [6] ). All of these above changes created huge challenges to UK banks as they had to operate in a rapidly-changed and more competitive environment, therefore, affected their performance.

After being stable for decades, it had been hit severely at a time when profits were at their peak. The crisis took place since late 2008 brought tears to so many bankers. It is reported that “after the credit crunch, the pre-tax profits of Halifax Bank of Scotland dropped by 72 %, those of Lloyds TSB - with 70 %, at Barclays and HSBC, the slump in profits amounted to 33% and 28%, respectively. The Royal Bank of Scotland had to declare a pre-tax loss of £ 692 million, the first loss in its history” [7] . The government has bailed out so many banks e.g. Northern Rock and offer bank rescue package worth of £ 50 billion (19/1/2009) to provide additional funds for loans [8] . This action also was a necessary and timely decision to soften the chaos-like situation at that time in the financial market. It would be also a chance for banks to learn many precious lessons from this credit crunch and from then on, they can become more cautious in their dealings, more prudent in their transactions, more guaranteed in loans, safer in investments.

Furthermore, in compare with other countries in the world, the UK is one of the most important financial markets as well as the largest single centre for international banking. It accounts for 20% of the world’ cross-border lending, and also has the most open policy -internet and government deregulation- to foreign banks, which accounts for 55% of the total assets of the banking sector (Kosmidou et al. 2006 omega 34).

From all the matters discussed above, examining the performance and effectiveness of the UK banks both before and after the financial crisis is a very interesting and meaningful study, which can contribute to the understanding of the field academically and practically.

2. Commercial banks

According to the Oxford dictionary of Finance and Banking (2008:87), “Commercial bank is a privately owned bank that provides a wide range of financial services, both to the general public and to the firms. The principle activities are operating cheque current accounts, receiving deposits, taking in and paying out notes and coin, and making loans…” As can be seen, commercial banks play a very important role in the financial system of a country in specific and the international financial system as a whole. They raise deposits from general public and loan these funds out to individuals and companies as these are main functions of banks in general. Besides, like other financial institutions as well as other businesses, commercial banks exist to make a profit by minimizing their cost and maximizing their revenue. However, there is a perennial problem that all of commercial banks face, stated by Pilbeam (2005:44), “…the way they raise funds is quite expensive for example, most current accounts are relatively small in size and they are also quite active imposing processing and transaction costs on the banks”.

In recent years, together with the globalization process, the development of technology, the diversity of financial institutions and markets, the commercial banks have also been changed in order to adapt to the changing world economic environment, the increasing competitions as well as to maintain their stability and existence. They tend to widen the range of their services including credit cards, insurance, financial advices, pensions, shares purchase and custody services to customers to diversify their service and improve the profitability of both customers and the banks.

The number of commercial banks accounts for approximately 33% of the UK banking system, with 283 banks (Bankscope 2009). Among them, there are four banks that dominated the industry in question, known as the so-called “Big Four”, namely Barclays Bank Plc (including Woolwich), the Royal Bank of Scotland Plc (including NatWest), HSBC Bank Plc and Lloyds TSB Bank Plc. The four banks have USD 6537,924 million total assets which represent about 50% of the total assets of the UK banking sector and also have listed as the world’s biggest banks, measured by tier-one capital and total assets [9] .

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3. Literature review

The literature on this field, which mostly is empirical, is very huge but not equally distributed on different countries and their banking systems. The studies on the US’s banking efficiency are definitely dominated the literature on the matter which accounts for over 60 percent. However, looking at and researching all of the available articles on the field are a very difficult and challenging, since the ability to access all of the articles is impossible. Rather then, the aim of this section is to critically review the empirical and theoretical literature which uses frontier methodology namely data envelopment analysis (DEA) to assess bank performance of countries around the world from 1985 and onwards. Although the aim is to review the studies on as many countries as possible, the literature in the field just focuses on mainly the US, European countries, some remarkable countries in the Asia. Meanwhile the researches on other countries especially those in the Africa, South America are still not considerably numerous and really need more attention of researchers and scholars in the near future, so that we can have a panorama of world banking systems as well as a comprehensive comparison among these systems.

In fact, there are several outstanding reviews in the field such as Berger et al. (1997), which surveyed 130 studies that apply frontier approaches to examine the efficiency of financial institutions in 21 countries from 1998 and downwards, or Fethi and Pasiouras (2010) provided a comprehensive review of 196 studies on operational research (O.R.) and artificial intelligence (A.I.) over the years 1998-2009. Besides, we cannot talk about this matter without mentioning the study that examined the development of DEA over the last thirty years of Cook et.al (2009) and so many others. I only consider journal articles and some working papers but do not include other types such as dissertations and so on. All of the articles and working papers were searched and obtained from Scopus and Business Source Premier, the two largest abstract and citation databases.

DEA application in banking systems all over the world

I reviewed 39 studies on using DEA to assess bank performance and efficiency of European Union countries (Belgium, France, Germany, Italy, Luxembourg, the Netherlands, Denmark, Ireland, United Kingdom, Greece, Portugal, Spain, Austria, Finland, Sweden, Cyprus, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Malta, Poland, Slovakia, Slovenia, Bulgaria, and Romania), the US, Asian and African countries. The reason for choosing the US and EU countries as the main focuses of the literature review for this study is that they have big and well-developed banking systems. In addition, the EU has developed a single market and created a common currency – yet not all of member states adopted the Euro – so it is understandable to show interests in the performance of the members in this Union. Also, the UK has a really close relationship with this Union, both geographical and economical as well as political relations. Besides, there will be a special review on studies which only examine the UK banks’ performance so that we can have a clear comparison between studies on the UK with other countries and studies on UK only. For all of the above targets, a large number of articles of nearly 70 were used.

The scope and samples of each study are also different on the number of countries, the number of banks, the number of variables used etc. The simple summary of the studies on 32 countries’ bank efficiency is presented in Table 1 below.

Table 1: 39 studies using DEA to measure bank efficiency in 32 countries

Author (date)

Countries

Period

Sample

Method

Average annual efficiency estimate

Casu et al. (2003)

France

Germany

Italy

Spain

UK

1993-1997

750 banks

DEA

0.62

0.72

0.54

0.57

0.78

Canhoto et al. (2003)

Portugal

1990-1995

20 banks

DEA

0.59

Lozano et al. (2002)

Belgium Denmark

France

Germany

Italy

Luxembourg Netherlands

Portugal

Spain

UK

1993

612 banks

DEA

0.77

0.71

0.36

0.49

0.85

0.54

0.71

0.78

0.81

0.55

Casu et al. (2006)

Austria

Belgium

Denmark

Finland

France

Germany

Greece

Ireland

Italy

Luxembourg

Netherlands

Portugal

Spain

Sweden

UK

1997-2003

11,000 observations

DEA

0.79

0.74

0.75

0.86

0.67

0.68

0.88

0.81

0.69

0.64

0.82

0.87

0.79

0.74

0.75

Tortosa (2002)

Spain

1985-1997

104 banks

DEA

0.89

Pasiouras et al. (2008)

Greece

2000-2005

10 banks

DEA

0.95

Maudos et al. (2002)

Spain

1985-1996

1666 observations

DEA

n.a.

Maudos et al. (2003)

Spain

1985-1996

50-77 savings 75-98 national

DEA

0.87

Pastor (2002)

Spain

Italy

France

Germany

1988-1994

2598 observations

DEA

SFA

0.74

Bergendahl (1998)

Denmark

Finland

Norway

Sweden

1992-1993

48 banks

DEA

n.a.

Delis et al. (2009)

Bulgaria

Czech Rep

Estonia

Hungary

Latvia

Lithuania

Poland

Romania

Slovakia

Slovenia

1994-2005

364 banks 4368 observations

DEA

0.71

0.51

0.77

0.63

0.64

0.65

0.57

0.75

0.70

0.66

Pastor (1999)

Spain

1985-1992

n.a.

DEA

n.a.

Beccalli et al. (2006)

France

Germany

Italy

Spain

UK

1999-2000

90 banks

DEA

SFA

0.72-0.84

0.90- 0.84

0.79-0.89

0.91-0.86

0.83-0.80

Havrylchyk (2006)

Poland

1997-2001

n.a.

DEA

0.53 -0.73

Delis et al. (2009)

Greece

1993-2005

14-23 banks 224 observations

DEA

SFA

0.64

0.81

Hauner (2005)

Austria

Germany

1995-1999

97 banks

485 observations

DEA

0.97

0.96

Casu et al. (2004)

France

Germany

Italy

Spain

UK

1993-1997

2363 observations

DEA

SFA

0.85->0.86

Weill (2004)

France

Germany

Italy

Spain

Switzerland

1992-1998

688 banks

DEA

SFA

0.4-0.71

0.71-0.83

0.68-0.84

0.78-0.78

0.65-0.66

Guzman et al. (2008)

Spain

2000-2004

14 banks

DEA

n.a.

Retizis (2006)

Greece

1982-1997

6 banks

DEA

0.91

Favero et al. (1995)

Italy

1991

174 banks

DEA

0.88-0.91-0.79-0.84

Pastor et al. (2006)

Austria

Belgium

Denmark

France

Germany

Greece

Italy

Luxembourg

Spain

1992-1998

540 banks 3780 observations

DEA

0.4->0.48

0.66->0.72

Tsionas et al. (2003)

Greece

1993-1998

19 banks

DEA

0.96

Bhattacharyya et al. (1997)

India

1986-1991

70 banks

DEA

0.86-0.75-0.79

Fukuyama (1993)

Japan

1990

143 banks

DEA

0.86

Fukuyama (1995)

Japan

1989-1991

155 banks (1989) and 154 banks (1990)

DEA

0.46-0.46-0.44

Taylor et al. (1997)

Mexico

1989-1991

11 banks

DEA

0.75-0.72-0.69

Berg et al. (1992)

Norway

1980-1989

346 banks (1980) and 178 banks (1989)

DEA

n.a

Zaim (1995)

Turkey

1981

1990

42 banks

56 banks

DEA

0.83-0.94

Aly et al. (1990)

US

1986

322 banks

DEA

0.75-0.81

Charnes et al. (1990)

US

1980-1985

48 banks

DEA

n.a

Elyasiani et al. (1992)

US

1988

160 banks

DEA

0.89

Elyasiani et al. (1995)

US

1979

1986

150 banks

DEA

0.97-0.95-0.95-0.96

Elyasiani et al. (1994)

US

1983-1987

203 banks

DEA

0.86-0.83

English et al. (1993)

US

1982

442 observations

DEA

0.75-0.76

Ferrier et al. (1993)

US

1984

468 banks

DEA

0.69-0.60

Ferrier et al. (1990)

US

1984

575 banks

DEA

SFA

0.83

0.79

Grabowski et al. (1993)

US

1989

240 banks, 522 observations

DEA

0.72

Thompson et al. (1997)

US

1986-1991

100 banks

DEA

0.81-0.69-0.59-0.59-0.54-0.62

More than half of these above studies research one country, mostly the US, Greece and Spain. Besides, the other studies focus more on more than 4 countries, such that Casu et al. (2004) with 5 countries; Weill et al. (2004) with 5 countries, even studies assess more than 10 countries namely, Delis et al. (2009) and Lozano et al. (2002) with 10 countries each, Casu et al. (2006) with 15 countries. All of these statistics can be found in Table 1 above. The study with the biggest number of countries in investigation is Pasiouras (2008a) with the sample of banks from 95 countries.

To start up with the model, researcher tends to start with addressing the objective of the research, end then choosing the model, collecting the data, running the model to find the results from the data collected and explain the implied meaning as well as the significance of the results. The way to carry out the research can similar and even they can come up with the similar conclusions or findings, but there are still big differences in each phase of the process and even contrast results. For example, Greece is the subject of 5 studies with differences in choosing the variables, inputs, outputs, even the objectives of the research but still can have the average efficiency score at above 0.90 as found out in Casu et al. (2006), Pasiouras et al. (2008), Delis et al. (2009), Retizis (2006), Tsionas et al. (2003). Besides, the US banking sector is also examined in 11 studies during the period of 1980-1990, yet, with different efficiency scores ranging from 0.54 to 0.97, as can be obtained in Aly et al. (1990); Charnes et al. (1990); Elyasiani et al. (1992), (1994), (1995); English et al. (1993); Ferrier et al. (1990), (1993); Grabowski et al. (1993); Thompson et al. (1997). To understand the meaning of the efficiency results obtained, for example, 0.79 score or 79%, Berger et al. (1997) explained: “Efficiency results are typically reported in either of two ways. The 0.79 efficiency figure means that if the average firm were producing on the frontier instead of at its current location, then only 79% of the resources currently being used would be necessary to produce the same output (or meet the same objectives). The 27% inefficiency [(1-0.79)/0.79] figure means that the average firm requires 27% more resources to produce the same output (or meet the same objectives) as an efficient firm on the frontier (the relationship is 0.79 = 1/(1+0.27) or 0.27 = (1-0.79)/0.79)”.

Most of the studies focus on the technical efficiency of banks rather than the allocative efficiency (e.g. Canhoto et al. 2003; Lozano et al. 2002; Pasiouras 2008; Rezitis 2006). This efficiency measures the ability of a firm to obtain maximal output from a given set of inputs. However, as Fethi et al. (2010) says, “When price data for the inputs and/or outputs are available one can also estimate cost and/or profit efficiency measures”. Cost efficiency can be seen in a large number of studies such as Hauner (2005), Tortosa (2002; Maudos et al. 2002), and so on. According to Fethi et al. (2009), cost efficiency is the product of technical and allocative efficiency, therefore, it will tell us which banks provide services without wasting its resources. Estimating profit efficiency with DEA is quite limited in the literature and can only be found in Maudos et al. (2003), which show the existence of profit efficient levels well below those corresponding to cost efficiency. The reason may be it is difficult to collect reliable and transparent information for output prices. (Fethi et al. 2010).

In order to implement DEA, we can assume either constant returns to scale (CRS) or variable returns to scale (VRS). According to Pasiouras et al. (2008), “in their seminal study, Charnes et al. (1978) proposed a model that had an input orientation and assumed CRS”. They also mentioned, “Banker et al. (1984) suggested the use of variable returns to scale (VRS) that decomposes overall technical efficiency into product of two components, pure technical efficiency (PTE) and scale efficiency (SE)”. The majority of the studies using the assumption of VRS and CRS (e.g. Canhoto et al. 2003, Pastor 1999; Hauner 2005), however, there are still studies that in favor of CRS (e.g. Guzman et al. 2008) and VRS (e.g. Casu et al. 2003). There are many views on which assumption should be used and one of the arguments support for VRS is that CRS is only appropriate when all firms are operating at an optimal scale (Fethi et al. 2010).

There are two approaches for examining technical efficiency: input-oriented or output-oriented approach. As Coelli et al. (2005) point out, the input-oriented technical efficiency measures address the question: “By how much can input quantities be proportionally reduced without changing the output quantities produced?”. In contrast the output-oriented measures of technical efficiency address the question: “By how much can output quantities be proportionally expanded without altering the input quantities used?”. The majority of studies in the field obtain the efficiency estimates under the input-oriented approach for the assumption that the inputs can be controlled more easily and efficiently than outputs.

Regarding to input/output choosing, this is a matter that can be seen clearly in the studies with both common and different inputs/outputs. There is an ongoing discussion in the banking literature regarding the proper definition of inputs and outputs (Fethi et al. 2010). Therefore, there is no particularly true for banks as there is no such agreement on appropriate inputs and outputs in banking. The inputs can be labour, capital, cost of supplies, loanable funds, purchased funds, total operating expenses, actual loan losses, interest expenses, deposits, non-interest expenses etc. The outputs can be number of transactions, loans, deposits, and some other especial outputs like number of branches as an additional output under the assumption that it represents an additional value for retail customers (Canhoto et al. 2003), non-interest income or off-balance-sheet items as additional outputs (Havrylchyk 2006).

The variables that can be taken into account in assessing the efficiency of banks mentioned in these studies are environmental variables. As Fried et al. (1999) in Casu et al. (2003) suggested, “In this context, the term ‘environment’ is used to describe factors that could influence the efficiency of a firm, where such factors are not traditional inputs and are not under the control of management”. Such factors can include, for example, ownership differences (private/public), location characteristics and government regulations. Coelli et al. (2005) also shared the same views about this and suggested that environmental variables can include government regulations, location characteristics, labour union power and ownership differences.

When reviewing the articles in the field, I found out that nearly all of them attempt to investigate the determinants of efficiency. Some studies found out that bank-specific factors such as size, profitability, capitalization, loans to assets influence the efficiency (e.g. Casu et al. 2003). Others suggest country-specific factors include market concentration, presence of foreign banks, and GDP growth as the determinants (e.g. Hauner 2005, Maudos et al. 2002). Besides, there are studies that attempts to find out the effect of stock returns on efficiency (Pasiouras et al. 2008; Beccalli et al. 2006; Guzman et al. 2008). For example, Becalli et al. (2006) provides a positive relationship between stock returns and efficiency changes in the five principal EU banking sectors. Moreover, the bank ownership also is considered an influence in Havrylchyk (2006) or Hauner (2005). There are even studies that attempt to find whether there is a link between bank performance and bank personnel’s profile, e.g. educational qualifications, age etc as in Isik et als (2003a), Canhoto et al. (2003).

Besides the interests in finding the factors determine bank performance, there are also concerns about the links between efficiency and stock returns, bank ownership, corporate events and regulatory reforms. These are the key matters directly relate to the operation of any financial institutions. Firstly, regarding stock returns and efficiency, this relationship gains lot of attention in the finance and accounting literature. The studies on it usually try to find out whether the information in stock prices is reflected in earnings. The results in most cases are positive and can be seen in the case of Autralia (Kirkwood et al. 2006), Spain (Guzman et al. 2008), Singapore (Chu et al. 1998), Turkey (Erdem et al. 2008), Greece (Pasiouras et al. 2008), and Malaysia (Sufian et al. 2006). Secondly, different ownership can affect bank efficiency to some extent. For example, some studies suggested that foreign banks are more efficient than domestic banks in Poland (Havrylchyk 2006), Australia (Sturm et al. 2004), and Turkey (Isik et al. 2003a). Furthermore, there is also the difference between state-owned banks and privately-owned banks in which the former are less efficient in Spanish banks (Garcia et al. 2008), China (Ariff et al. 2008) etc. However, in other studies, the contrary results were found that the latter is lower in Turkey (Isik et al. 2003a), India (Sathye 2003), and Austria and Germany (Hauner 2005). As mentioned above, since the samples as well as the period, inputs/outputs chose in different studies are dissimilar, therefore, the findings for the same countries might slightly different, even opposite. Thirdly, corporate events such as mergers and acquisition, bankruptcy and so on were also found out to be linked with efficiency. Overall, the findings suggested that merged banks are more technically efficient than non-merged banks, therefore, they had higher productivity growth (Avkiran 1999; Al-Sharkas et al. 2008; Hahn 2007a). However, the after-merger efficient period does not last long and still need more researches. Last but not least, a number of scholars and researchers examined the effect of regulatory reforms or deregulations on the efficiency of banks. Their studies indicate a positive relationship in countries, namely, Korea (Gilbert et al. 1998), Australia (Sturm et al. 2004), etc.

DEA application on measuring efficiency of banking system in the UK

Chapter II: Methodology and data

1. DEA theory

The term Data envelopment analysis (DEA) was first used by Charnes, Cooper and Rhodes in 1978 in their study of “Measuring the efficiency of decision-making units”. Since then, there are a large number of studies that use and develop this methodology. DEA is a mathematical programming technique for the development of production frontiers and the measurement of efficiency relative to these frontiers. Each bank is assigned an efficiency score between 0 and 1, with higher scores indicating a more efficient bank, relatively to other banks in the sample. (Fethi et al. 2010:190). DEA is known to work well with small samples and does not require a specific functional form. The efficiency can be measured as follows: when a decision-making unit (DMU) utilizes one input to produce one output, the efficiency =. When a DMU produces more than one output by using one or more inputs, the efficiency = Weighted sum of outputs/Weighted sum inputs. Normally, the efficiency of a firm consists of two components, namely, technical efficiency and allocative efficiency and together they combine to provide a measure of total economic efficiency. (Farrell 1957).

However, DEA is also subject to some limitations and problems especially, the two best well-known shortcomings are that DEA assumes data to be free of measurement error, and that it is sensitive to outliers (Fethi et al. 2010). Despite these facts, DEA is still in favor of researchers in examining the efficiency of banking sectors all over the world.

2. Methodology

3. Data

Chapter III: Empirical results and analysis

1.

2.

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In addition to the example literature review above we also have a range of free study materials to help you with your own dissertation: