The impact of financial reform and the global financial crisis on bank
competition in MENA countries
Abstract
The financial reforms In the Middle Eastern and North African (MENA) countries
touch several aspects of the financial system. State banks are going through a
privatization and restructuring process. Foreign-owned banks and new private
banks were allowed entry. All that had impacted bank competition in these
countries. The global financial crisis has affected market power. The main
objective of this paper is to examine the dynamics of the bank competition in the
MENA countries, to provide an up-to-date assessment of market power, to
examine the impact of financial reform on bank competition in these countries,
and to explore the evolution of market power in MENA countries during the
global financial crisis.
The Beta and sigma convergence tests were applied to check whether a
convergence in bank competition has taken place in the banking markets of the
MENA countries.
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I.
Introduction
In the last decade, most of the MENA countries implemented financial reforms to
improve the business environment and promote financial development. The
financial markets of many Middle Eastern countries have shown dramatic
changes. Turkey emerged as powerful regional leader with strong economy and
more developed financial system. The economies of the Golf Arab countries have
experience tremendous growth and the financial system has experienced
significant reforms. The Wall Street Journal (May 4, 2014) reports that the
classification of the UAE and Qatar had been upgraded from “frontier” markets
status to “emerging” markets.
The financial reforms in the MENA countries touch several aspects of the financial
system. The World Bank reports that “most countries in the region have reduced
the share of state banks through restructuring and privatization and allowed the
entry of new private banks, including foreign banks.”
In addition, the global financial crisis has impacted the financial systems around
the world, although the impact on MENA countries was less significant since the
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financial system in these countries is less integrated than the financial systems in
the rest of the world.
One the main objective of this study is to examine the dynamics of the bank
competition in the MENA countries.
Although research on bank competition was conducted for developed and
emerging markets, little research was done for MENA countries. This work intends
to fill this gap.
This paper will add to the literature in the following way:
First, it provides an up-to-date assessment of market power in MENA countries.
Second, it examines the impact of financial reform on bank competition in these
countries.
Third, it explores the evolution of market power in MENA countries during the
global financial crisis in order to study the impact of the crisis on bank
competition in these countries.
Fourth, the Beta and sigma convergence tests are applied to check whether a
convergence in bank competition has taken place in the banking markets of the
MENA countries.
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Literature review
i.
Structural and non-structural approaches
Examining the competitiveness in the banking sector of the MENA countries is of
considerable interest and that is due, first, to the reforms that are taking place in
many MENA countries and the need for policy makers for theoretical and
empirical research, and, second, there is large body of literature that find a strong
correlation between competition and bank performance, efficiency and stability.
Research on bank competition is focused on two major directions: the structural
and the non- structural approaches.
The structural approaches:
Two paradigms are covered under the structural approach: the Structureconduct- performance (SCP) and the efficient-structure. (Efthyvoulou el al 2014)
defines the SCP paradigm” when concentration in a market increases, firms with
greater monopoly power can charge higher prices and thereby achieve profits”.
(Berger et al 2003) argue that “bank concentration and other impediments to
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competition create an environment that affects bank conduct and performance in
unfavorable ways from social points”. The SCP hypothesis was tested using
measure of concentration such as Herfindahl-Hirschman Index (HHI) and n-firm
concentration ratio (CRn).
(Berger and Hannan, 1998) tests the “Quiet life” hypothesis by examining
whether firms that have market power in concentrated markets can ignore
minimizing costs without risking an exit of the industry.
The authors show that when firm is not under pressure to minimize costs it cost
efficiency will be reduced.
Hannan 1991 assessing the relationship between bank behavior and market
power, measured by the HHI and the CRn, finds that firms exercising market
power increase the rate charged for loans, while decrease the rate offered for
these loans.
Both results are consistent with the SCP hypothesis.
In contrast to the SCP hypothesis, (Smirlock, Gillian, and Marshal, 1984) suggest
the “efficient structure” hypothesis, which provides different interpretation. The
authors argue that market power emerges from competition and competition
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occurs when firms have comparative advantage, using which they can be more
efficient and thus earn economic rent. The authors find that the efficient
structure hypothesis better describes the relationship between market structure
and firm conduct. (Rhoades 1985, Shepherd 1986, and Smirlock 1985) find results
that provide support for the efficient structure hypothesis.
The non- structural approach:
In contrast to the structural approach, the non-structural approach suggests that
market power does not exclude competition if firms are consumer’s centered.
(Baumol 1982) argues that when there is completely free entry and exit,
monopolists can prevent new entry if they provide the consumers with a
competitive product. Lack of efforts to produce such a product make the firms
“vulnerable to hit-and-run entry”. (Besnco and Thakor 1992) confirm Baumol’s
result by finding that competition is driven by the threat of new entry. ( Baumol,
Panzar, and Willig 1982) show that the market power in not the only indicator of
competitiveness. And (Claessen and Laeven, 2004) argue that testing for
competition requires a structural, contestability approach. Banking market power
is not the only factor that impacts bank conduct. It is important, they argue, to
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take into account other factors like “entry barriers, including on foreign
ownership, and the severity of activity restrictions”.
These results are of considerable interest for policy makers in the MENA
countries who are undertaking series of reform to better shape the banking
system and promote economic growth.
ii.
The dynamics of bank competition
If early research were limited to the local U. S. banking markets, the new
literature have international orientation that include developed as well as
developing countries.
Number of more recent studies focus on the European banking markets and
examine the dynamics of bank competition, the evolution of the banking system
in Europe and the impact of deregulation and large scale consolidation on
competition.
( Angelini and Cetorelli, 2003) analyze the evolution of competitive conditions in
the Italian banking industry . They find evidence consistent with hypothesis that
deregulation contributed to the improvement of bank competition.
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Unlike other studies that rely on one indicator to determine the degree of
competition in banking markets ( Carbo et al 2009) use five indicators of
competition- net interest margin, Lerner index, return on assets, H-statistic, and
HHI market concentration. The authors show that “the comparison of the five
indicators gives conflicting predictions of competitive behavior across countries,
within countries, and over time”. The authors suggest that research should take
into account country-specific factors when examining banking market
competition. (Bolt and Humphrey 2010) provided an alternative indicator to the
Lerner index by applying a competition frontier to a panel of 11 European
countries over the period 1987-2006. European countries were ranked by their
dispersion from the competition efficiency frontier. The authors find “there is
lower levels of competition in no-interest income generating activities, while
there is higher level of competition in the activities that generate spread income”.
(Weil 2013) analyze the evolution and convergence in bank competition in the EU
over the period 2002-2010 .he uses the Lerner index and the Rosse-Panzar model
to estimate bank competition measures for all EU countries. He applies the Beta
and sigma convergence tests.
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The author finds an increase in bank competition during the 2000s. He also finds
evidence that clearly support the view of a convergence in bank competition
across European countries.
iii.
variability of bank competition:
Recent studies examine the factors impacting the variability of bank competition
and its dynamics.
(Fernandez de Guevara et al 2005) study the evolution of competition in the
banking industries of five big European countries - Germany, France, Italy, Spain,
and the United Kingdom using the Lerner Index for the sample period is 19921999. The authors find that concentration is still persisting in European banks
despite the implementation of deregulation. They explain that by the low level of
banks integration.
(Fernandez de Guevara and Maudos 2007) analyze the explanatory factors of
market power in the Spanish banking system in the period 1986-2002.
Their results show an increase of market power from the mid-1990s. The authors
find that “size, efficiency and specialization significantly impact market power”.
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This result allows them to conclude that “economic policy decisions to accept or
refuse a bank merger process based on its effects on market concentration are
without solid foundation”.
iv.
impact of foreign banks participation on bank competition
More recent literature focuses on the impact of foreign banks participation on
competition. This body of work is of particular interest to the research on MENA
countries, since these countries are in the process of restructuring the banking
system and allowing the entry of foreign banks.
(Gelos, Roldos 2004) apply the Panzar and Rosse methodology in a sample of
eight emerging countries. They find that, although bank consolidation led to a
decrease of the number of banks, nonetheless concentration did not increase as a
result of this decline. The reason for that is that those countries had allowed the
participation of foreign bank and lower barriers to entry.
(Fungacova, solanko , and weill 2010) analyze Russian banking sector for the
period 2001-2006. The authors did not find a persistence of competiveness of
foreign-owned banks over state owned banks.
v.
Bank ownership and market power
Recently the research focuses on the sources of market power and whether bank
ownership impacts market power.
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(Stijn Claessens and Neeltje van Horen 2012) document the following finding
about foreign banks: the performance of foreign banks improves over time, as
they adjust to the new environment, and is” better when the home country is
geographical or cultural (but not institutional) close to the host country”.
(Buch, Koch, Koetter 2013) using the Lerner index, study the impact
internationalization on market power and find that “Large, internationally active
banks have substantial market power”.
(Efthyvoulou and Yildrim 2014) examine how the global financial crisis has
affected market power by studying Central and Eastern European banking
markets. The authors find that “there is some convergence in country-level
market power during the pre-crisis period, and the onset of the global crisis put
an end this process”.
B. Methodology
The Reform in the banking system has a significant impact on bank competition.
And the global financial crisis has affected, to various degrees, all the MENA
countries. So the purpose of this study is to evaluate the evolution of the bank
competition in MENA. We apply two methodologies; in the first we follow (Weill
2011),(Fernandez de Guevara, Maudos and Perez 2005) and( Carbo, Humphry,
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Maudos, and Molyneux, 2009) to estimate the learner index; and in the second
step, we follow (Weill 2011) to apply  and  convergence tests to check
whether convergence in bank competition has taken place in the banking system
of MENA countries.
The source of data is Bankscope.
I.
The Learner index
The learner index is defined as the difference between price and marginal cost,
divided by price.
The cost function is specified as follows
2
w
w
w
w
TC
1
1  w 
ln(
)   0   1 ln y   2 (ln y ) 2   3 ln( 1 )   4 ln( 2 )   5 ln( 1 ) ln( 2 )   6  ln( 1 )  
w3
2
w3
w3
w3
w3
2  w3 
2
n
w
w
1  w 
  7  ln( 2 )    8 ln y ln( 1 )   9 ln y ln( 2 )   Countryi
2  w3 
w3
w3
i 1
Where TC denotes total costs, y total assets, w1 the price of labor( the ratio of
personal expenses to total assets), w2 the price of physical capital ( the ratio of
other non-interest expenses to total assets), w3 the price of the borrowed funds (
the ratio of paid interests to all funding), Countryi dummy variable for the country
i. Total costs are the sum of personnel expenses, other non-interest expenses and
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paid interests. The estimated coefficients of the cost function are then used to
compute the marginal cost.
II.
Test of convergence
There are two concepts of convergence developed by (Barro and Sala-i-Martin
1991) the  and  convergences.
As (Weill 2011) explains, “the  convergence test aims to regress the growth
rate on the initial level for any variable. The  convergence aims to investigate
the evolution of the dispersion of a cross-section. The  convergence captures
how quickly each country’s level is converging to the average level of the group of
countries”.
The  convergence test is performed through the estimation of the following
equation:
n
ln Competitioni ,t  ln Competitioni ,t 1     ln Competitioni ,t 1   Countryi   i ,t
i 1
Where Competitioni ,t is the measure of bank competition of country i in year t,
Competitioni ,t 1
is the measure of bank competition of country i in year t-1,
Countryi is country dummies,  i,t is the error term, and  ..and .. are the
parameters to be estimated.
“There is  convergence if the coefficient Beta of the initial level in negative”.
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The  convergence test is performed through the estimation of the following
equation following the specification for panel data used notably by Parish and
Shibata (2004):
n
Wi ,t    Wi ,t 1   Countryi   i ,t
i 1
Where ln Competitioni ,t the logarithm of the mean competition measure of banks of
county i in year t MCompetitiont the mean of ln Competitioni ,t for each period,
Wi ,t  ln Competitioni ,t  MCompetitiont
Wi ,t  Wi ,t  Wi ,t 1
Countryi is country dummies,  i,t is the error term, and  ..and .. are the
parameters to be estimated.
“There is then a   convergence if the coefficient  of the initial level is negative”.
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Model’s Descriptive Statistics
Definition
Variables
TC
Total costs
y
Total assets
W(1)
Price of labor( the ratio of personal expenses to total assets)
W(2)
Price of physical capital ( the ratio of other non-interest expenses to total assets)
W(3)
Price of the borrowed funds ( the ratio of paid interests to all funding)
Country(i)
Dummy variable for the country i
Total costs
Sum of personnel expenses, other non-interest expenses and paid interests
Beta
Beta convergence
Sigma
Sigma convergence
Competition(I,t)
Measure of bank competition of country i in year t
Competition(I,t-1) Measure of bank competition of country i in year t-1
Epsilon(I,T)
Error term
Lncompetition(I,t) Logarithm of the mean competition measure of banks of county i in year t
Mcompetition(t)
Mean of lncompetition(I,t)
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