Bank Risks, and Bank Stability: The Moderating Role of State
Ownership in the MENA Region
Ahmed Rashed
1,2 a
and Dexiang Wu
1
1
School of Economics and Management, Beihang University, Beijing, China
2
Faculty of Commerce, Cairo University, Cairo, Egypt
Keywords: Credit Risk, State Ownership, Liquidity Risk, Financial Stability, MENA Region.
Abstract: This paper empirically examines the impact of state ownership on the relationship between bank risks and
financial stability for a sample of 110 banks within the period 2007-2021 with 1650 bank observations listed
in the Middle East and North Africa regions. The findings show that there is no simultaneous link between
credit risk and liquidity risk. Liquidity and credit risks can be managed jointly to affect banking stability. State
banks are more stable, less likely to engage in risky behavior, and more concerned with social welfare. State
banks eliminate the impact of banks' risks on banking stability. Results enhance good governance, economic
development, and employment opportunities, maintain financial safety, and ultimately enhance growth. Our
results are consistent with the present regulatory framework, particularly Basel III, which confirms the
importance of joint management of liquidity and credit risk.
1 INTRODUCTION
The banking sector constitutes a fundamental
component of the financial system, serving as the
foundational financial infrastructure for the economy
of any country, and therefore it is necessary to
contribute to conducting research on financial
stability analysis even in light of a stable
macroeconomic environment. The most significant
financial risks that directly affect what banks do and
why they fail are credit and liquidity risks (Abdelaziz
et al., 2022). Liquidity risk is an opportunity for
depositors to withdraw their deposits suddenly
(Ghenimi et al., 2021; Thakor & Yu, 2024). Credit
risk means the inability of borrowers to repay on time
and constantly changing interest rates (Naili &
Lahrichi, 2022).
This study differs from other previous studies on
the MENA region in four aspects. First, this paper
investigates the effect of bank risks on bank stability
in the MENA region via different statistical methods
like OLS to check the static model, 2SLS to address
the possible endogeneity problem, and GMM to
explore the dynamic results. Second, this study is the
first to provide evidence that state ownership
moderates the relationship between bank risks and
bank stability in large conventional banks in the
a
https://orcid.org/0000-0002-3782-1895
MENA region over the long period of 2007–2021.
Third, we use Merton’s distance to default (DD) and
Z-score as financial stability measures, which Z-score
uses in most literature based on accounting measures,
while Merton’s distance to default (DD) is one of the
most important measures taken into consideration by
investors’ expectations regarding equity. Fourth, we
use a large sample of the MENA region, where these
countries are characterized by common economic,
political, and social features in addition to the same
accounting standards.
Our paper is organized as follows. Section 2
presents the relevant literature review, while Section
3 describes the data and methods. The findings and
robust checks are outlined in Section 4, and the
summary and conclusion are outlined in Section 5.
2 LITERATURE REVIEW
2.1 Credit Risk and Liquidity Risk
According to the traditional theory of financial
intermediation, scholars assert that credit risk and
liquidity risk are positively correlated. For instance,
Cai and Zhang (2017) found a positive association
between credit risk and liquidity risk in Ukrainian
Rashed, A. and Wu, D.
Bank Risks, and Bank Stability: The Moderating Role of State Ownership in the MENA Region.
DOI: 10.5220/0013479300003956
Paper published under CC license (CC BY-NC-ND 4.0)
In Proceedings of the 7th International Conference on Finance, Economics, Management and IT Business (FEMIB 2025), pages 279-286
ISBN: 978-989-758-748-1; ISSN: 2184-5891
Proceedings Copyright © 2025 by SCITEPRESS – Science and Technology Publications, Lda.
279
banks. Some studies emphasize how there is a
negative correlation between credit risks and liquidity
risks (Louati et al., 2015; Hassan et al., 2019; Le &
Pham, 2021). In contrast, some studies show there is
no economically significant reciprocal relationship
between the two risks (Imbierowicz & Rauch, 2014;
Ghenimi et al., 2017). Most research on the reciprocal
relationship is linear, with two studies examining a
nonlinear relationship (Pop et al., 2018; Boussaada et
al., 2022). According to the various points of view
and empirical studies mentioned above, we propose
the following hypothesis:
H
1
: There is an interdependency between credit
risks and liquidity risks.
2.2 Credit, Liquidity Risks and
Stability
Bank stability is necessary to ensure the smooth
functioning of financial activities in emerging
economies. Banks are subject to several risks, like
liquidity risk and credit risk. Imbierowicz and Rauch
(2014) show that both credit and liquidity risks jointly
influence the possibility of bank failure. Ghenimi et
al. (2017) found that the existence of an individual
and joint influence for both liquidity and credit risks
on banking stability. Hassan et al. (2019) concluded
that both liquidity risks and credit risks adversely
affect financial stability. Lachaab (2023) concluded
that credit and liquidity hurt bank stability in Islamic
banks. Some of the literature argues that credit risk is
the most important part of determining bank stability,
while generally liquidity risk is ignored (Lachaab,
2023; Ben Lahouel et al., 2024).
On the other hand, some of the literature
concludes that the interaction between liquidity and
credit risk leads to higher bank failure risk through a
decrease in market liquidity due to an increase in risk
premium (He & Xiong, 2012). Some studies indicated
that non-traditional banking activities increase risks,
whereas adequate funding liquidity positively affects
stability, reinforcing the need for effective risk
management (Habib et al., 2022).
Chai et al. (2022) found that bank-specific risks,
including credit and liquidity, negatively impact bank
stability in Pakistan. According to theoretical and
empirical research, liquidity and credit risks can
affect bank stability, and interacting between both
credit and liquidity risks may reduce the likelihood of
bank failure and thus improve banking stability.
Based on the aforementioned discussion, we propose
that:
H
2
: Liquidity risk and credit risk jointly support
banking stability.
2.3 State Ownership and Stability
Theoretical perspectives support government
ownership as a tool to secure capital to fund projects
with high social and political returns but might have
high risk and low financial returns (Boulanouar et al.,
2021).State ownership is viewed from two
perspectives. According to the first perspective,
ownership structures foster good governance,
economic development, financial safety, and growth
by attracting employment opportunities through
various financing methods, even without private
financing (Lassoued et al., 2016; Boulanouar et al.,
2021). State-owned banks are less likely to engage in
risky behavior and are more concerned with social
welfare. The second perspective is associated with the
conflict between the agent (managers) and principal
(owners), hence raising agency problems in state
ownership compared to private bank. Managers may
achieve their own goals regardless of the interests of
the ultimate owners due to bureaucracy and the
inefficiency of capital market. State ownership enjoys
governmental protection, which may push more risky
decisions because losses and excess costs are
constantly being paid by the government. The lending
practices of state banks may prioritize social goals
over financial ones through their unprofitable projects
to achieve their social objectives. Politicians
essentially control state-owned banks by achieving
their own goals instead of their social ones and by
having the ability to transfer resources to their
backers. Soft budget constraints in state banks are
related to excessive risk-taking behavior and resource
allocation. Empirical results support two perspectives
related to state ownership and bank stability. The first
perspective argued that state ownership is associated
with increased efficiency and lower risk-taking
(Boubakri et al., 2020).On the other hand, the second
preservative supports the role of state ownership in
raising risk-taking and insolvency risk and decreasing
financial stability. State ownership plays a positive
role in the face of cyclical fluctuations, preventing
private banks from generating credit bubbles.
Restricting loan granting during boom periods is
crucial for banking stability. Boulanouar et al. (2021)
found that state-owned banks are more stable than
privately owned banks within 14 years for 76 GCC
markets. Mateev et al. (2023) argued that ownership
structure has a significant impact on shaping risk
behavior in the MENA region. Hunjra et al. (2020)
found that state banks have more risk-taking behavior
compared to foreign banks in emerging markets.
Based on the theoretical and empirical arguments, we
formulate the third hypothesis as follows:
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H
3
: State ownership is positively related to bank
stability in the MENA region.
2.4 Moderating Role of State
Ownership
Some of the literature argues that government
ownership increases risk-taking (Shleifer & Vishny,
1997; Laeven & Levine, 2009; Haque & Shahid,
2016), while other studies suggest decreased risk-
taking (Iannotta et al., 2007; Haddad et al., 2020;
Alshammari, 2022).
Shleifer and Vishny (1997) believe that
government ownership leads to inefficiency because
of conflicts between political and social goals,
bureaucracy and corruption, and politics among
interest groups. Haddad et al. (2020) concluded that
ownership structure had a significant positive impact
on conventional banks' performance but not on
Islamic banks.
The authors argue that state ownership moderates
the relationship between bank risks and bank stability
from two perspectives: Firstly, state ownership
creates governmental protection caused by increased
risk-taking behavior and thus decreases bank
stability. In countries with inadequate legal and
regulatory frameworks, agency disputes related to
state control are more prevalent and thus increase
risk-taking. Secondly, state ownership is related to
good governance and economic development, which
maintains financial safety and ultimately enhances
bank stability. The government seeks to achieve its
different social and political goals through its
participation in banks. State-owned banks are less
likely to engage in risky behavior and are more
concerned with social welfare compared to non-state
banks. Based on the above explanation, the authors
suggest that state ownership may moderate the
relationship between bank risks and stability in the
MENA region, and thus we formulate both the fourth
and fifth hypotheses as follows:
H
4
: State ownership inversely impacts the
relationship between credit risk and bank stability in
the MENA region.
H
5
: State ownership inversely impacts the
relationship between liquidity risk and bank stability
in the MENA region.
Consequently, this paper addresses the
subsequent research questions. First, Is there a causal
relationship between liquidity risk and credit risk?
Second, how do the joint of credit risks and liquidity
risks affect the banking stability? Finally, does state
ownership moderate the relationship between bank
risks and banking stability?
The proposed model is illustrated in Figure (1).
Figure 1: The proposed research model.
3 RESEARCH DESIGN
3.1 Sample and Data
Our sample consists of 110 commercial banks from
16 MENA countries from 2007 to 2021, excluding
unstable countries and Islamic banks. The final
sample included 1650 bank-year observations. The
sample excluded Islamic banks due to potential
differences in bank risks. The study examines the
long-term impact of bank risks on bank stability from
2007 to 2021, encompassing economic uncertainty
events like the global financial crisis in 2008, Arab
Spring in 2010, and US presidential election in 2020,
and the prolonged uncertainty around Brexit, and
other events, the research period encompassed the
majority of economic uncertainty occurrences. Data
is gathered from Bankscope while macroeconomic
variables are obtained from the World Bank. Table
(1) reveals that state ownership accounted for 66% of
banks, while non-state ownership was 34%.
Table 1: Sample distribution.
Ownership structure Freq %
State
b
anks 1089 66
Non-State
b
anks 561 34
Total 1650 100
3.2 Empirical Models
This study explores the causal link between credit and
liquidity risk in the MENA region using two-stage
least squares (2SLS) and panel vector autoregressive
(PVAR). Also, we explore the impact of state
ownership on the relationship between bank risks and
bank stability. According to the simultaneous
equation (2SLS), the formula is as follows:
Bank Risks, and Bank Stability: The Moderating Role of State Ownership in the MENA Region
281
𝐶𝑅
,
=𝛼
+𝛽
𝐶𝑅
,
+𝛽
𝐿𝑅
,
+𝛽
𝐵𝑎𝑛𝑘
,
+𝛽
𝑀𝑎𝑐𝑟𝑜
,
+𝜂
,
(1)
𝐿𝑅
,
=𝛼
+𝛽
𝐿𝑅
,
+𝛽
𝐶𝑅
,
+𝛽
𝐵𝑎𝑛𝑘
,
+𝛽
𝑀𝑎𝑐𝑟𝑜
,
+𝜂
,
(2)
CR
k,t
refers to credit risk. LR
k,t
expresses liquidity
risk. Bank
k, t,
and Bank
g
k.t
refer to bank-specific
variables: BS, CAR, and GFC. Macro
m
k, t,
and Macro
n
k, t
refer to the INF and GDP.
Panel vector autoregressive (PVAR) explores the
causal relationship between credit and liquidity risk.
By introducing fixed effects (π
k, t
), PVAR accounts
for individual bank specificity at the level of the
variables as follows:
𝑌
,
=𝜋
,
+µ (𝐿)𝑌
,
+𝜂
,
(3)
Where Y
k,t
is a vector of variables and µ (L)
denotes the lag operator.
The research model to explore the impact of
ownership structure on the relationship between risk
and bank stability Whereby the formula is as follows:
ZSC
it
= α
+ β
CR
+ β
LR
+ β
CR
∗
LR
+ β
OWN
+ β
OWN
∗CR
+ β
OWN
∗LR
+β
BS
+ β
CAR
+ β
INF
+
β
GDP
+ β
GFC
+ ϵ
(4)
We measured bank stability through the Z-score
(Ghenimi et al., 2017; Naili & Lahrichi, 2022), which
considers profitability, leverage, and return volatility.
It measures return on assets (ROA) and return on
equity (ROE). A higher Z-score indicates increased
stability and a decrease in bankruptcy probability.
The log of the Z-score is used due to its asymmetry
and high skewness (Ahamed & Mallick, 2017). In the
robustness check, we employ DD as an alternate
metric of stability. We measure credit risk based on
non-performing loans divided by total loans (Natsir et
al., 2019; Naili & Lahrichi, 2022). The higher value
of credit risk means higher loan losses, and the bank
should change its credit policy to be able to manage
its loans. Liquidity risk is measured by the sum of
liquid assets to total assets (Ghenimi et al., 2017;
Hassan et al., 2019). Liquid assets are the sum of
demand deposits, transaction deposits, and contingent
liabilities within a fiscal year. A positive score
indicates insufficient liquid assets for short-term
obligations, necessitating funding from other sources,
while a negative score indicates more liquid assets
than short-term liabilities.We measure ownership
structure with a dummy variable equal to 1 if the bank
is a state and 0 otherwise (Boulanouar et al., 2021).
We account for several bank-specific variables that
are frequently associated with bank stability, such as
bank size, which is determined by the natural
logarithm of total assets. We also take into
consideration other bank-specific variables, such as
the capital adequacy ratio (CAR), which measures the
equity-to-asset ratio. Financial crisis period measured
by the dummy variable 1 if the year is 2007, 2008,
2009, and 0 otherwise. It is necessary to use both
country and year-fixed effects as control variables.
This study also considers the yearly growth rate of the
gross domestic product (GDP), as well as inflation,
which is measured by the inflation rate (Hassan et al.,
2019).
4 RESULTS
4.1 Descriptive Statistics
Table 2 presents the mean of both credit and liquidity
risks is about 0.635 and 0.294, respectively, which
implies high credit and liquidity risks, while the
average BS and CAR are about 6.842 and 17.599,
respectively, which denotes a high bank size and
capital adequacy ratio. Indeed, the averages of both
INF and GDP are about 3.548 and 3.442,
respectively, which indicates high inflation and gross
domestic product. According to financial stability, the
averages of Z
ROA
, Z
ROE
, and DD are about 3.855,
3.323, and 3.703, respectively, which denotes high
financial stability in the MENA region.
Table 2: Descriptive Statistics.
Var N Mean SDV Min Max
Z
ROA
1650 3.855 0.267 3.483 4.162
Z
ROE
1650 3.323 0.452 2.637 4.286
DD 1650 3.703 0.348 3.105 4.265
CR 1650 .635 0.414 0.2 1.4
LR 1650 .294 .023 .256 .329
BS 1650 6.842 0.735 5.7 8
CAR 1650 17.599 4.712 9.16 24.67
INF 1650 3.548 2.699 0.693 9.42
GDP 1650 3.442 1.482 1.1 6.4
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4.2 Causality Test
Table 3 shows the causality between credit risk and
liquidity risk using 2SLS. The null hypothesis of the
Durbin-Wu-Hausman test is rejected, and the Hansen
test confirms the over-identifying restriction null
hypothesis. We find no meaningful reciprocal
relationship between credit and liquidity concerns,
consistent with the literature (Imbierowicz & Rauch,
2014; Ghenimi et al., 2017). This result shows that
there is a unidirectional causal relationship between
credit and liquidity risks.
Table 3: Credit and liquidity risks using 2SLS.
Var CR LR
CR -0.484***
LR -.393
BS .006*** .0062**
CAR .061*** 0.030
INF .001*** .001***
GDP 0.001 -.0022**
GFC -.005* 0.000
_cons 1.753*** 1.075
AR (1) 0.000 0.000
AR (2) 0.232 0.193
Hansen J –test 0.343 0.435
DWH test 0.000 0.000
Note: ***p < 0.01; **p < 0.05; *p < 0.1.
Robustness check using panel vector
autoregression (PVAR) and Granger causality in both
tables 4 and 5 show that there is no economically
significant patterns of causal links between credit and
liquidity risks.
Table 4: panel vector autoregression (PVAR).
VAR Coef. St. Err.
Ŷ
P>z
CR
CR
t
-1 0.607 0.146 4.14 0.000
LR
t
-1 2.743 1.993 1.38 0.169
LR CR
t
-1 0.033 .016 2.02 0.044
LR
t
-1 .382 .208 1.84 0.066
Results show that credit and liquidity concerns
have a unidirectional causal link using a lot of
different methods like 2SLS, PVAR, and Granger
causality. Therefore, we rejected the first hypothesis
H
1
.
Table 5: Granger causality test.
Granger Equation Excluded chi2 Df Prob
Wald
tests
CR LR 1.895 1 0.169
LR CR 4.067 1 0.044
4.3 OLS &GMM Test
Table 6 presents the results from pooled OLS and
dynamic GMM. The GMM specification test AR (2)
is valid for testing bank serial correlation, indicating
the empirical model's accuracy. Hansen J-statistic
tests show higher than 0.1, valid over-identifying
limits, and accurate model formulation. Positive and
significant Z
ROAt-1
and Z
ROEt-1
indicate GMM's
dynamic fit. The study reveals that credit risk
increases, and bank stability declines due to higher
loan rates. Liquidity risk significantly affects banking
stability, as stable banks are more liquid. Ineffective
handling of liquidity risk by banks and regulators can
lead to a liquidity crisis, threatening stability and
highlighting the importance of maintaining stability.
The study reveals a negative and significant
interaction between credit and liquidity risk on
banking stability at a level of 5%, with high credit risk
leading to increased liquidity risk and vice versa.
Banks with higher credit risk face reduced
liquidity risk and higher charges for stability, despite
maintaining stability with sufficient funding. Our
findings suggest that a combined rise in liquidity and
credit risk reduces stability. Our findings are
consistent with the literature supporting the combined
rise of bank risks on stability. The negative
coefficient of liquidity and credit risk reduces bank
stability during crises, leading to higher loan rates and
credit risks, resulting in bank defaults, and affecting
banks differently. This result is consistent with
(Ghenimi et al., 2017; Merton & Thakor, 2022).
These findings suggest that both liquidity and
credit issues play an important role in influencing
banking stability in the MENA region. These findings
support our hypothesis H
2
. State banks have a
statistically significant impact on the two financial
stability models. State banks have the most
substantial positive influence on bank stability with
1% and 5% significance levels in OLS and GMM,
respectively. This demonstrates how state ownership
contributes to financial stability in the MENA region.
Therefore, we accepted hypothesis H
3
. This result
highlights good governance, economic development,
and employment opportunities, maintains financial
safety, and ultimately enhances growth. Our findings
are consistent with the literature supporting the
impact of ownership structure on banking stability
(Lassoued et al., 2016; Boulanouar et al., 2021). State
ownership is less likely to be risky behavior, and
more concerned with social welfare compared to
private-owned banks, which are more likely to be
related to profit maximization and more probably
risky behavior. Bank size significantly enhances
Bank Risks, and Bank Stability: The Moderating Role of State Ownership in the MENA Region
283
banking stability in OLS and GMM models at 1%
level, as it diversifies portfolios and improves risk
management. Capital adequacy ratio (CAR) also
enhances financial stability, acting as a safety net
during crises. Financial crises, GDP growth, and
inflation rate all impact banking stability in the
MENA region, with the latter having a positive effect.
Table 6: The effect of bank risks on stability.
Va r
Z
ROA
Z
ROE
OLS GMM OLS GMM
Z
ROA t-1
.557***
Z
ROE
t
-1
.384***
CR -.043* -.0896** -.115** -.118**
LR -.629* -2.140** -1.872** -2.98**
CR*LR -.144* -.290*** -.2159* -.212**
OWN .079** .537*** .0459* .437*
BS .055*** .206*** .098*** .108***
CAR .005*** .021*** .0364*** .025***
INF .011* .029* -.007 -.006
GDP -.007 -.011* -.011 -.024*
GFC -.141* -.003* -.062 -.019
Country FE Yes Yes Yes Yes
Yea r F E Yes Ye s Yes Yes
Constant 3.175*** 2.654 2.602*** 1.961
Obs 1650 1650 1650 1650
F 16.00 *** 42.10 ***
Adjust R
2
.25 .48
Breusch T
Prob
3.44
0.063
1.12
0.290
Ramsey F
Prob
0.46
0.709
3.22
0.103
Durbin T 1.904 1.960
Levin-Lin 0.000 0.000
AR (1) (p) 0.000 0.00
AR (2) (p) 0.096 0.109
Sargan (p) 0.466 0.332
Hansen (p) 0.757 0.557
Note: ***p < 0.01; **p < 0.05; *p < 0.1.
4.4 Main Effects Test
Table 7 shows that state ownership plays an important
role in mitigating the association between credit risk
and financial stability, in addition to the association
between liquidity risk and financial stability in the
MENA region. Therefore, we accepted both
hypotheses H
4
and H
5
.
Table 7: Moderating role via OLS.
Va r Z
ROA
Z
ROE
CR -.045* -.106***
LR -.946** -.967*
OWN .110*** .232** .099*** .506***
CR*OWN -.153* -.355**
LR*OWN -.523* -1.500***
BS .053*** .051*** .106*** .091***
CAR .005** .006*** .038*** .037***
INF .011* .010* -.006 -.006
GDP -.007 -.008 .009 .009
GFC .140*** .099** -.064 -.115**
Country FE Yes Yes Yes Yes
Ye ar FE Ye s Yes Ye s Yes
_cons 3.360*** 3.031*** 1.924** 2.209***
N 1650 1650 1650 1650
R
2
.266 .265 .487 .489
Adjust R
2
.250 .249 .476 .478
F-Test 16.28*** 16.19*** 42.67*** 42.98***
Breusch
Prob
1.89
(0.169)
1.94
(0.113)
0.45
(0.504)
3.06
(0.08)
Ramsey F
Prob
0.11
(0.954)
0.32
(0.807)
2.09
(0.112)
1.85
(0.09)
Durbin T 1.907 1.905 1.959 1.956
Note: ***p < 0.01; **p < 0.05; *p < 0.1.
4.5 Robustness Test
We follow two-stage robustness checks. Firstly, we
used the distance-to-default (DD) as an alternative
measure of financial stability to explore the impact of
state ownership on the relationship between bank
risks and bank stability. The default is measured by
subtracting the face value of the bank's debt from its
predicted market value and dividing the spread by the
bank's expected volatility. We used three models to
check the impact of state banks on the association
between bank risks and stability using OLS, 2SLS,
and GMM methods. Table 8 confirms the findings
that state banks positively impact financial stability in
the MENA region, while state ownership negatively
affects the association between bank risks and
stability, highlighting its crucial role in enhancing
stability.
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284
Table 8: Robustness check.
Var OLS GMM
CR
it
-.185*** -.014**
OWN
it
.100*** .057** 5.34*** 2.029**
CR
it
*OWN -.231*** -.018*
LR
it
-3.94** -.717*
LR
i
t
*OWN -.270*** -1.52***
Control
i
t
Yes Yes Yes Yes
Country FE Yes Yes Yes Yes
Year FE Yes Yes Yes Yes
_cons 3.709*** 4.906*** 3.331** 4.672***
N 1650 1650 1650 1650
R
2
.68 0.71
F-Test 96.41*** 110.87***
Wald chi2 1842.7*** 1737.5***
Breusch Chi2
Prob
0.38
(0.53)
0.56
(0.21)
Ramsey Prob
1.35
(0.08)
1.69
(0.07)
Durbin T 2.258 2.255
AR(1) (p) .000 0.009
AR (2) (p) 0.117 0.324
Sargan (p) 0.791 0.643
Hansen (p) 0.211 0.124
Note: ***p < 0.01; **p < 0.05; *p < 0.1.
5 CONCLUSIONS
This paper investigates the impact of credit and
liquidity risk on banking stability using a panel
dataset of 110 banks listed in the MENA region from
2007 to 2021. Moreover, our analysis indicated that
credit risk and liquidity risk do not exhibit
economically significant reciprocal
contemporaneous, even though each risk category has
a major impact on financial stability. Additionally, we
found that the interaction between the two risk
categories profoundly affects financial stability.
Consequently, the findings of the estimation revealed
the pivotal role of credit and liquidity risks in shaping
banking stability in the MENA region. We found that
state-owned banks are more stable. State ownership
is less likely to risky behavior, is more concerned
with social welfare, and has increased efficiency
compared to non-state ownership, which is associated
with more likely risky behavior.
State ownership plays an important role in the
association between bank risks (credit and liquidity
risks) and financial stability. Our results have several
policy implications that are worth considering. First,
these findings offer some recommendations for bank
management and supervisors in the MENA region.
The financial crisis demonstrated that bank
failures caused by credit risk in their portfolios might
result in a liquidity market freeze. These findings
provide regulators, policymakers, and bank
management bodies with a better understanding of
bank stability and efficiency, as well as their behavior
toward credit and liquidity risk. Our findings suggest
that joint liquidity and credit risk management could
significantly affect banking stability. Finally, our
findings back up current regulatory initiatives,
particularly Basel III, which highlight the critical
importance of joint management of liquidity risk and
credit risk.
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