Download Competition-Fragility or Competition

Competition-Fragility or Competition-Stability?
Evidence from the Turkish Banking System
Extended Proposal
04. February. 2010
Elmas Yaldız
Second Year PhD student
CIFREM Doctoral School in Economics and Management
[email protected]
Abstract
There are two hypotheses about the relationship between competition and financial stability in
the banking system: competition-fragility argues that competition makes banks more likely to
take excessive risks, thereby leading to fragility, while competition-stability suggests that higher
interest rates in less competitive environments may cause borrowers to take higher risks,
resulting in higher probability of non-performing loans and a more fragile system. The aim of
this thesis is to understand the impact of competition on Turkish banking system. This
relationship will be analyzed theoretically and empirically with bank fragility being measured
both as bank failures and as banks’ risk-taking. To my knowledge, there are no studies that
examine this relationship using duration analysis for bank failures. The data will be drawn from
bank balance sheets and income statements reported to the Banks Association of Turkey.
1. Introduction
Banking has a distinctive place in Turkish financial system and an important role in achieving
financial stability in Turkey1. Although there has been a recent increase in the number and size of nonbank financial institutions, the system is still dominated by commercial banks.
Between 1990 and 1999 the number of commercial banks grew from 66 to 81. Over the next
decade this number fell sharply and in September 2009, there were only 32 banks operating in the
Turkish banking sector. Therefore a significant change has occurred in the competitive structure of the
Turkish banking system. Abbasoglu et al (2007) provide evidence for a monopolistic competitive
structure in the Turkish banking system from 2001 to 2005.
Turkey has experienced two systemic banking crises over the last 30 years. In 1982 the fiscal
cost of the crisis was 2.4 percent of GDP and the 2000 crisis had an extremely high fiscal cost (32
percent of GDP), which caused a 5.4 percent output loss in GDP (Laeven and Valencia, 2008: 47).
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Total assets of the banking system account for nearly 90 percent of total assets of the financial sector and
commercial banks held 97 percent of the total banking system assets in 2008 (Banks Association of Turkey,
2008).
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Demirguc-Kunt and Kane (2002) report that banking crises are most costly for developing
countries’ economies and 93 different countries had systematic banking crises in 25 years between
1975 and 2000. Lindgren et al (1996) report that two-thirds of IMF member countries had problems
with their banking sectors between 1980 and 1996. Overall, output losses to GDP associated with 43
banking crises from 1977 to 1998 was 16.9 percent and average fiscal cost of banking resolution to
GDP was 18 percent from 1997 to 2003 (Carstens et al, 2004: 9).
The U.S. had also two systemic banking crises over the last 30 years the first 1988, and the
second 2007. According to Greenspan the latter event is referred as a severe crisis as the Great
Depression and “a once-in-a-half-century, probably once-in-a-century type of event."2 Profitability of
U.S. banks declined by 83.5 percent from $35.2 in 2006 to 5.8 billion in 2007 (Laeven and Valencia,
2008: 48) and many big financial institutions failed. Frame and White (2004, 2007) highlight the
increased competition for Fannie Mae and Freddie Mac. They argue that this competition increased
risk-taking behaviors by both enterprises, and reduced their charter value. Both enterprises were taken
over by the U.S. Treasury in September 2008 and were placed under the conservatorship of the
Federal Housing Finance Agency (Lockhart, 2009: 2). Leuvensteijn et al (2007) find that between
1994 and 2004 the U.S. had the most competitive loan market compared to the Eurozone countries,
UK and Japan.
Given these costs of banking crises and the role of competition in the recent U.S. subprime
crisis, determining the reasons for a fragile banking system and the role of the competition on financial
stability are important issues.
There are two main hypotheses in the literature about the relationship between competition and
stability in banking: the competition-fragility and the competition-stability. The competition-fragility
hypothesis argues that smaller banks in more competitive environments are more likely to take
excessive risks and therefore competitive systems are more fragile than less competitive ones. In
contrast, the competition-stability hypothesis suggests that monopoly rents (higher interest rates) in
less competitive environments may encourage firms to take higher risks, which result in a higher
probability of non-performing loan ratios (NPL), and therefore more competitive banking systems are
considered to be more stable. The aim of this thesis is to examine these two hypotheses in relation to
Turkish banking system.
2
Greenspan’s interview on abc NEWS, Greenspan to Stephanopoulos: This is 'By Far' the Worst Economic
Crisis He's seen in His Career. Available at: http://blogs.abcnews.com/politicalradar/2008/09/greenspan-tost.html
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2. Literature Review
In the literature the competition-fragility and the competition-stability hypotheses have been studied
both theoretically and empirically. This review focuses first on the theoretical issues and then the
empirical studies that analyze the relationship between competition and banking system stability.
2.1. Theoretical Literature
Keeley (1990) was the first study to address the positive relationship between competition and fragility
both theoretically and empirically. In his charter value hypothesis, Keeley (1990) proposes that greater
competition reduces monopoly rents (market power) and the charter value of a bank and makes banks
more likely to take excessive risks and finally they increase their NPL and probability of failure.
Matutes and Vives (1996) extend the famous intermediation theory of Diamond (1984) to
imperfect competition by assuming that banks cannot fully diversify their portfolios and therefore take
on risk and likely to fail. They also extend Diamond and Dybvig’s (1983) bank run model to show that
bank runs can exist in any market structure.
Mishkin (1999) presents dangers and opportunities of financial consolidations in U.S. banking
and argues that under the shelter of regulators’ “too big to fail” policies, bigger banks are more likely
to take excessive risks. Consequently, they threaten the stability because failure of a large institution
exposes the financial system to systemic risk. On the other hand he also underlines that bigger banks
are more likely to have diversified loan portfolios in different locations thanks to their wider branch
network, and this makes bank failures less likely.
Koskela and Stenbecka (2000) show that competition creates lower lending rates and higher
investments and under mean-shifting investment technologies, higher investments do not increase the
bankruptcy risks of borrowers. Therefore, their model implies that the relationship between
competition and financial fragility is ambiguous.
Matutes and Vives (2000) study the effect of competition for deposits (market power on deposit
side) on risk-taking behavior of banks with different assumptions, i.e. the availability of information
on the risks of banks’ portfolios and deposit insurance schemes (flat and risk-based premiums). They
find that under perfect competition and high failure costs, an uninsured market yields excessive
deposit rates, and therefore high asset risk. Flat-rate deposit insurance schemes and perfectly
competitive banks also yield excessive deposit rates even if there is no failure costs, and therefore high
asset risk. In a nutshell, concentrating on the deposit side of the market, they favor the competitionfragility hypothesis.
Using similar scenarios to Matutes and Vives (2000), Cordella and Yeyati (2002) explain the
trade-off relation between competition and stability under the scenarios about the availability of
information regarding banks’ risk level (publicly available or not) and deposit insurance (flat and risk-
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based deposit insurance schemes). Their results indicate that when information about asset quality is
publicly available, banks tend to have less risky portfolios; on the other hand when flat-rate
deposit insurance exists, competition makes banks more risky and welfare is lower compared to
the risk-based deposit insurance.
Caminal and Matutes (2002) explain the relationship between competition -monopoly and
Bertrand competition- and probability of bank failures. A monopoly bank has to monitor firms since it
is the only source of credit. Therefore, a monopoly bank implies higher loan rates, less credit
rationing, and higher probability of failure due to moral hazard. However, competitive banks may be
more likely to fail, if the monitoring costs are so high that banks do not monitor regardless of market
structure. So the relationship between market power and the probability of bank failure depends on
monitoring cost, and therefore it is ambiguous, as the empirical literature indicates.
Although most previous theoretical studies support the competition-fragility hypothesis by
assuming competition in the deposit market, Boyd and De Nicolo (2005) question this and the mixed
results of the empirical studies. They propose their competition-stability hypothesis under the
assumption of competition in both loan and deposit sides of the market. It is true that as competition
declines, banks enjoy monopoly rents by charging lower deposit rates and higher loan rates. Therefore,
these factors are expected to increase profitability and decrease the probability of bank failure, as the
competition-fragility hypothesis suggests. On the other hand, higher loan rates in loan side of the
market would imply lower profits and higher default risk for bank borrowers (firms) according to
Boyd and De Nicolo (2005). Thus the positive relationship between competition and risk is not clear;
indeed, there exists a negative relationship between competition and fragility since competition in the
loan market leads to lower loan interest rates, decreases firms’ default risk and promotes stability of
banking.
Boyd et al (2009) extend Boyd and De Nicolo (2005)’s model by assuming banks holding a
risk-free asset other than giving loans. In this model the relationship between competition and the risk
of bank failure is not certain which doesn’t confirm the previous findings of Boyd and De Nicolo
(2005) and Boyd et al (2009) find that increased competition will generally affect the ratio of loans to
deposits.
Boyd and De Nicolo (2005) and Boyd et al (2009) assume that the default risk of borrowers
(firms) is highly correlated with bank failures. On the other hand, Martinez-Miera and Repullo (2009)
argue that this may not necessarily be true. Since competition reduces the interest income over
performing loans, the lack of correlation between firm and bank failures questions the validity of Boyd
and De Nicolo’s (2005) results. Thus in addition to Boyd and De Nicolo’s (2005) risk shifting effect,
Martinez-Miera and Repullo (2009) present a margin effect that goes in the opposite direction. For
competitive markets, the margin effect dominates risk shifting effect so any additional entry would
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increase the risk of bank failure. Therefore, as competition increases, fragility also increases, but not
necessarily vice versa; that is to say in less competitive loan markets the effect is ambiguous.
The main conclusion of this review of theoretical literature is that although most papers support
the competition-fragility hypothesis, there is no consensus about the relationship between competition
and stability in banking systems. It is also clear that the results of the studies differ according to their
assumptions. The studies that consider fragility from the viewpoint of banks’ risk-taking, and
concentrate on competition on the deposit side, generally provide support for the competition-fragility.
In contrast, the studies that consider moral hazard and adverse selection problems and evaluate
stability as bank failures generally favor the competition-stability hypothesis.
2.2. Empirical Literature
Using q as a measure of market power in banking, Keeley (1990) examines the relationship between
competition and financial stability3. He estimates the effect of q on banks’ default risk and finds that
U.S. banks with greater market power had lower risks of default between 1970 and 1986. This study is
a micro-based study of the relationship between competition and financial stability that provides
empirical evidence for the competition–fragility hypothesis. Bordo et al (1993) compare the Canadian
and the U.S. banking systems between 1920 and 1980 and report that the Canadian banks failed less
often than the U.S. banks, due to the oligopolistic structure of the Canadian banking system.
Demsetz et al (1996) examine the role of franchise value on risk-taking behavior of U.S. banks
between 1986 and 1994. In their study, the franchise value refers to the expected present value of the
future profits, and therefore it is considered an indicator of market power and, following Keeley
(1990) they measure it with Tobin’s q. By finding a negative relationship between franchise value and
risk, they provide empirical evidence for the competition-fragility hypothesis.
Staikouras and Wood (2000) compare the banking systems in the Spain and Greece. Comparing
the structure and sources of profitability for the 1980s and 1990s they infer that Spanish banks are
more profitable and stable than Greek banks, which have a less competitive structure. Therefore,
Staikouras and Wood (2000) provide evidence in favor of the competition-stability hypothesis.
Based on cross-country data of 69 countries from 1980 to 1997, Beck et al (2006) investigate
the impact of bank concentration on the likelihood of a systemic banking crisis. They measure bank
concentration by the share of the three largest banks in total banking assets, which is the most standard
way of computing concentration, and find that more competition decreases the probability of systemic
banking crises.
Boyd et al (2006) also examine the relationship between competition and financial fragility
using a cross-sectional sample of about 2,500 U.S. banks in 2003 and a panel data set of about 2,600
3
This measure q is defined as the market value of assets (calculated as the sum of the market value of common
equity-price per share times number of shares and the book value of liabilities) divided by the book value of
assets.
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banks in 134 nonindustrialized economies from 1993 to 2004. They find consistent results for both
samples and provide empirical support for theoretical study of Boyd et al (2005): a positive relation
between concentration and risk-taking of bank failures and a negative relationship between
competition, (as measured by the Herfihndahl-Hirschmann Index (HHI)), and risk-taking behavior of
banks as measured by the inverse Z-index.
Using the Panzar and Rosse H-Statistic and the averaged proportion of the total assets held by
three largest banks in the country, Schaeck et al (2006) examine banking system fragility as the
probability of systemic banking crises. Schaeck et al (2006) employ both logit and duration analysis
for 38 countries from 1980 to 2003 and present evidence that in a more competitive environment the
survival of the banking systems are longer and systemic crises are rare events in such an environment.
They provide further evidence for the competition-stability hypothesis.
Following Keeley’s (1990) approach, Jimenez et al (2007) provide more recent evidence for the
role of competition on banks’ risk-taking behavior for Spain from 1988 to 2003. Using the NPL ratio
as dependent variable to measure banks’ distress and controlling for macroeconomic conditions as
well as bank characteristics, they find that standard concentration measures do not affect bank NPL
ratios. On the contrary, using a Lerner index, based on bank-specific interest rates on loan and deposit
products, they find a negative relationship between competition and bank risk; that is, as market power
increases, bank NPL ratios decrease.
Berger et al (2009) is another micro-based study that considers banking fragility as the risktaking behavior of the banks. Using alternative measures of competition -the Lerner and HHI- and of
risks -NPL and Z-index- for 8,235 banks in 23 developed countries, they provide conflicting evidence
that provide support both hypotheses. In other words different techniques can lead to different results.
Fungacova and Weill (2009) consider fragility of bank failures from a micro point of view for
Russian banks over the period 2001-2007. They employ the Lerner index as a measure of bank
competition and panel logit analysis to see the effect of competition on bank failures. Their findings
support the competition-fragility view which implies that a more intense competition undermines the
financial stability.
Table 1 summarizes the results of the empirical studies. One can infer from this review of the
empirical literature three main conclusions. First, studies consider the fragility issue from different
points of view. Some studies consider banking fragility from a macro perspective and take into
account systemic banking crisis (e.g. Beck et al, 2006 and Schaeck et al, 2006). Other studies consider
bank fragility from a micro or managerial perspective and by defining it as the failure of an individual
bank (e.g. Fungacova and Weill, 2009; Bordo et al, 1993) or by considering fragility as the risk-taking
behavior of banks and use the Z-index4 (e.g. Boyd et al, 2006; Berger et al, 2009) or the NPL ratio to
4
The Z-index is the sum of capital-asset ratio and return on assets, weighted by the standard deviation of return
on assests.
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measure risk (Jimenez et al, 2008). Macro studies provide evidence mainly for the competitionstability hypothesis while micro-based studies generally support the competition-fragility hypothesis.
The second conclusion is that there is no consensus about the measurement of competition. Some
studies simply take the concentration ratios, while others use indices such as HHI, Lerner, Tobin’s q,
and Panzar-Rosse. Third, the empirical literature does not provide conclusive evidence in favor of one
of the two hypothesis and the results of the individual studies are highly sensitive to the definition of
stability.
Table 1: Summary of the Empirical Literature
Study
Approach
Keeley (1990)
Micro
Bordo et al
(1993)
Mixed
Demsetz et al
(1996)
Micro
Staikouras and
Wood (2000)
Mixed
Beck et al
(2006)
Macro
Boyd et al
(2006)
Schaeck et al
(2006)
Micro
Macro
Measure of
fragility
Banks’ default
risk(a)
Competition
Sample
Method
Tobin’s q
The U.S.
1970-1986
Pooled regression
Bank failures,
ROA, ROE
Number of banks
Canada and the
U.S.
1920-1980
Descriptive
statistics
All-in risk(b)
Tobin’s q
The U.S.
1986-1994
Random-effects
and fixed-effects
panel data models
Std concentration
measures
Greece and Spain
1980s and 1990s
Descriptive
statistics
Std concentration
measures
69 countries
1980-1997
Two sample:
a.2,500 U.S. banks
in 2003 b. 2,600
banks in 134 nonindustrialized
countries
1993-2004.
Output
fluctuations,
inflation and
profitability of
banks.
Systemic
banking crises
Logit
Result
Competitionfragility
The U.S.
Banking is less
stable and less
competitive
Competitionfragility
Competitionstability
Competitionstability
Z-index
HHI as
competition
measure and std
concentration
measure
Systemic
banking crises
Panzar and Rosse
H Stat and std
concentration
measure
Spain 1988-2003
Logit
No relationship
and
Competitionfragility
38 countries
1980–2003
Various Panel data
estimation
techniques.
Logit and duration
Competitionstability
Competitionstability
Jimenez et al
(2008)
Micro
NPL ratio
Lerner index and
std measures of
concentration
Berger et al
(2009)
Micro
Both NPL and
Z-index
Both Lerner and
HHI
23 developed
countries
1999–2005
GMM regression
analysis
Mixed results
Fungacova and
Weill (2009)
Micro
Bank failures
Lerner index
Russia 2001-2007
Panel logit
Competitionfragility
(a) Banks’ default risk is calculated as the market-value capital-to-asset ratio and the interest cost on large,
uninsured deposits.
(b) All-in risk is calculated as the annualized standard deviation of weekly stock returns.
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3. Research Question
The aim of this thesis is to understand whether competition promotes stability or fragility in the
Turkish banking system. This question is particularly important for the Turkish banking system since
it has experienced intensive regulation processes which have led to a sharp decline in the number of
banks and, possibly to changes in the competitive structure.
The thesis will be organized in three chapters: the first will analyze the issue theoretically. The
subsequent chapters will examine the issues empirically, but will conceptualize the stability of the
banking system in different ways. The second chapter will employ duration and discrete choice
models of the failures of Turkish commercial banks as the indicator of financial fragility. The third
chapter will analyze the effect of competition on bank’s risk-taking behavior using the NPL and Zindex.
To date, no study has examined the role of the competition on the stability of Turkish banking
system. One aim of this thesis will be to rectify this gap. Moreover the second chapter of this thesis
will provide the first country-specific study to examine the effect of competition on bank failures
using duration analysis.
4. Data and Methodology
The data will be drawn from bank balance sheets and income statements as reported to the Banks
Association of Turkey (BAT). In the first empirical part, the lifetime of a bank is assumed to start at
the date of issue of the license and to end at the point that its banking license is withdrawn by Saving
Deposit Insurance Fund (SDIF). The general empirical model for the both parts of the study will be
Financial fragility = f(Competition, Control variables)
As the empirical literature shows, there are various ways of considering financial stability and
measuring the competitive power of a bank. In the following sections, competition measurement
methods and then the financial fragility proxies will be introduced.
4.1. Competition
Many studies considered competition as a structural phenomenon and employ concentration to
measure competition. These studies argue that greater concentration creates a less competitive banking
environment and leads to higher profitability (Fungacova and Weill, 2009: 12-13). Accordingly,
competition can be measured by concentration indices such as the market share of the largest banks or
by the HHI, which is defined as the sum of the squares of the market shares of the largest banks. The
HHI varies between 1/N and 1, where N is the number of the banks. It becomes one, when there is
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only one bank - i.e. the case of monopoly- and it approaches zero in limit as competition increases
(Bikker and Haaf, 2000:7). However, studies show that a concentrated banking system can be more
competitive than a less concentrated one or a less concentrated banking system can be less
competitive than a concentrated system (Claessens and Laeven, 2003; Abbasoglu et al, 2007).
Panzar and Rosse’s (1987) H-statistic avoids this criticism since it calculates competition as the
sum of the elasticities of the reduced form revenues with respect to the input prices. If the H-statistic is
less than zero, the market structure is considered to be monopolistic; if H-statistic is between zero and
one, it is considered as monopolistic competition; and if H-statistic is equal to one it is considered to
be perfect competition. Therefore, an increase in H-statistic reflects an increase of the degree of
competition in the market.
The Lerner Index is one of the earliest and most popular indices for measuring competitive
power as the difference between price and marginal cost over the price (Jimenez et al, 2008; Hainz et
al, 2008; Fungacova and Weill, 2009). The disadvantage of this index is that the information on price
is limited and the marginal cost function needs to be estimated.
Bolt and Humphrey (2009) employ the three standard measures explained above – the HHI, the
H-statistic and the Lerner index- to measure the competition of the European banking system and find
a very weak correlation among the measures. As competition decreases, banks generally enjoy higher
profits. Therefore, some studies use profitability ratios as the easiest proxy for measuring competitive
power. In addition to the HHI, the H-statistic and the Lerner index, Carbo et al (2009) employ net
interest margin/total asset and Return on Asset (ROA) ratio as measures of competition and also find
that these competition measures give different and even conflicting results for European banks.
Therefore, the use of different indices can lead to different inferences about banking competition.
Consequently, Bolt and Humphrey (2008) emphasize the importance of developing another indirect
measure rather than these four indices.
All of the indices explained above measure competition of the aggregate banking industry.
Boone (2008) proposes a new measure that calculates competition in separate product markets, such as
loan markets and for specific types of banks, such as commercial and investment banks. This new
measure depends on relative profit differences among banks and does not require more data than the
indices based on price-cost margin such as the Lerner Index (Boone, 2008: 1259).
Based on the literature on competition measurement in banking, this thesis will calculate the
competition with various techniques explained above in order to obtain robust results for the
competitive power of Turkish banks.
4.2. Financial Fragility
In this study, financial fragility of Turkish banks will be considered in two dimensions: banks’ risktaking and failure.
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Previous empirical studies have mostly used NPL, ROA, Return on Equity (ROE) ratios and the
Z-index to measure the risk-taking behavior of banks. NPL, ROA and ROE are the standard financial
ratios and the Z-index can be computed as Z = (ROA+ EA) /σ(ROA) , where EA is the equity to assets
ratio and σ(ROA) is the standard deviation of the return on assets. The Z-index goes up as profitability
and capitalization increase, and decreases as the variability of earnings increases. Thus, there is a trade
off between Z-index and a bank’s probability of failure (Berger et al, 2009: 106).
Bank failures are modeled with different empirical techniques. Some studies use simple ratios,
especially capital ratios and establish thresholds for bank failure (Beaver, 1966; Estrella et al, 2000),
while others employ discriminant analysis to predict bank failures (Gibson et al 1991; Canbaş et al,
2005). Another group of studies employ Artificial Neural Networks to predict bank failures (Atiya,
2001; Zhang et al, 2009).
My thesis will employ econometrics and focus on duration analysis (Whalen, 1991; Wheelock
and Wilson, 1994; Bennett and Loucks, 1996; Wheelock and Wilson, 2000; De Young, 2000; Molina,
2002; Carree, 2003; Dabos and Escudero, 2004; Podpiera and Podpiera, 2005; Buehler et al, 2005;
Gonzalez and Kiefer, 2006;Konstandina, 2006; Cole and Wu, 2009) and limited dependent variable
models (Martin, 1977; Pantolone and Plat, 1987; Thomson, 1992; Barr et al, 1994; Lanine and Vennet,
2006; Fungacova and Weill, 2009) to predict and identify determinants of bank failures.
The limited dependent variable or so-called discrete choice models mainly consist of the linear
probability, logit, and probit models. The aim of building a limited dependent variable model is to
predict the probability of failure. The parameter estimates in these models indicate whether an increase
in the independent variable will decrease or increase the probability of failure. Both probit and logit
produce probability estimates between zero and one, while linear probability models can not. Thus
logit and probit are mostly used in studies on bank failures and only determine the variables that affect
the failure probability of a bank with a given set of explanatory variables.
Duration models, on the other hand, are able to predict the timing of failure. The duration
function specification depends on the conditional probabilities, while limited dependent variable
model specification depends on unconditional probabilities (Kiefer, 1988: 649). In limited dependent
variable models, all failed banks are regarded the same as surviving banks. For example, a bank that
fails on the first day of the data interval is regarded as equal to a bank that fails on the last day, and a
bank that survives the interval but fails one day after that period ends is treated the same as a bank that
survives an additional ten years. Duration models contain much more information and more efficient
parameter estimates (Wheelock and Wilson, 1994: 64). The prediction abilities of the duration and
limited dependent variable models are compared by Lee and Urrutia (1996). According to this study,
duration models identify more significant variables than the limited dependent variable models.
Recently, Cole and Wu (2009) have demonstrated that a simple dynamic hazard model can
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significantly improve the out-of-sample forecasting accuracy of bank failures relative to a static probit
model.
Duration methodology is a useful tool for many different fields of studies including
unemployment duration (Lancaster, 1979; Sider, 1985, Kiefer, 1988; Holmas, 2002; Campolieti,
2009), lifetimes of firms (Santarelli, 1998; Mata and Portugal, 1994; Audretsch and Mahmood 1995),
durations of wars and conflicts (Akdede and Oğuş, 2006), the survival of theatre productions (Akdede
and Oğuş, 2006) and smoking habit duration (Madden, 2002). The dependent variables are cross
sections of durations, t1, t2, …tn and the parameter estimates in duration models indicate whether an
increase in the independent variable will decrease or increase the expected time until failure.
5. Conclusion
Given the high costs of banking crises and the role of competition in the recent subprime crisis
in the U.S., determining the reasons for a fragile banking system and the role of competition on
financial stability are important issues. However, there is no consensus about the sign of the
relationship between competition and fragility both theoretically and empirically. Moreover, there is
also no consensus about how to measure stability and competition. In order to obtain robust results,
this thesis will employ various measurement methods of competition and consider financial fragility in
two different ways: as banks’ risk-taking and bank failures. Since there is no study that examines this
relationship using duration analysis, this thesis will provide a methodological advancement in studying
the problem. Furthermore, there has been no study that examines the role of competition on the
stability of Turkish banking system.
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16