2. which all transactions and operations are supported by real
economic deals involving tangible assets. This systemic
disparity in business practices between IBs and CBs suggests
that they finance their operations and invest their resources in
different ways. To ensure that IBs comply with sharia (Islamic
laws) principles, every bank has a sharia board made up of
specialists who determine whether an activity is compliant
(Bourkhis & Nabi, 2013; Prima Sakti & Mohamad, 2018).
The growth in IBs has attracted wide attention from scholars
of Islamic finance, especially in terms of financial stability.
Many papers have examined the subject of IBs' riskiness and
stability, finding that IBs have greater financial stability (higher
Z-score) and low risk (particularly during the 2007 financial
crisis) than CBs (Bourkhis & Nabi, 2013; Ghassan &
Guendouz, 2019; Hassan et al., 2021; Kabir & Worthington,
2014; Karim et al., 2018; Prima Sakti & Mohamad, 2018;
Čihák & Hesse, 2010). Čihák and Hesse (2010) measure
financial stability at IBs and CBs in 18 countries using a Z-
score model, findings that small IBs have higher financial
stability than small CBs. Similarly, Bourkhis and Nabi (2013)
explore the impact of the 2007 financial crisis on the financial
stability of IBs and CBs in 16 countries, demonstrating that IBs
maintained financial stability during the 2007 financial crisis.
Similarly, Kabir and Worthington (2017) examine the link
between competition and financial stability at IBs and CBs
using a Z-score model, findings that the market effect on
financial stability is higher at CBs than at IBs. Along the same
lines, using the Z-score method, Prima Sakti and Mohamad
(2018) compare financial stability at IBs and CBs in
Indonesia for the period 2008 to 2012. Their findings indicate
that in Indonesia Islamic banking is more financially stable
than conventional banking. Correspondingly, Ghassan and
Guendouz (2019) measure the financial stability of IBs and
CBs in Saudi Arabia using a Z-score model, showing that IBs
increased financial stability when they diversified their assets.
More recently, Hassan et al. (2021), in a sample of 9 IBs and
23 CBs in Pakistan, show that IBs enjoy higher financial sta-
bility and higher market power than CBs.
Although IBs had high global development with high
financial stability, so far the sukuk market, based on issuance in
2021, has been steady. In the first half of 2021, as the global
economy began to recover from the disruptions due to the
COVID-19 pandemic, the sukuk market was able to adjust. At
the end of 2020 total issuance in the worldwide sukuk market
was USD 174.641 billion, the highest annual sukuk issuance to
date (an improvement of USD 174.641 billion, about 19.86
percent). The major determinants of this growth path were
economic stimulus by governments and a proactive global
economic perspective (IIFM, 2021). Therefore, IBs and sukuk
markets both achieved notable growth. Sukuk markets and IBs
are also experiencing interaction between them, resulting in a
fresh debate among scholars about the effect of sukuk markets
on the Islamic banking sector (Mimouni et al., 2019; Smaoui &
Ghouma, 2020).
Financial markets and the banking sector interact, but the
specific effect of financial markets on the banking sector is an
open question in the literature, and analysis of this issue is still
limited. Therefore, as sukuk markets are financial markets and
Islamic banks are members of the banking sector as a whole,
sukuk markets and IBs interact, sparking a new debate among
researchers regarding the effect of sukuk markets on IBs. Based
on the effect of conventional bond markets on the banking
sector in the literature (competition or complementarity effect),
Mimouni et al. (2019) and Smaoui and Ghouma (2020) state
that the effect of sukuk markets on IBs is also determined by
either the competition effect or the complementarity effect.
Accordingly, despite the rapid rise of IBs and sukuk mar-
kets, little is known about their interaction. For instance, the
link between IBs' financial stability and the sukuk market has
not yet been investigated. This goal of this paper is to fill this
gap in the literature by examining how sukuk market devel-
opment affects the financial stability of IBs.
Given prior conflicting results, this paper examines whether
the effect of sukuk markets on the financial stability of IBs is
positive (complementarity effect) or negative (competition ef-
fect). Hence, the goal of this paper is also to determine whether
the link between sukuk markets and the Islamic banking sector
is characterized by complementarity or competition in terms of
financial stability.
This study contributes to the literature in two main ways.
First, it contributes to the expanding literature on the factors
that influence IB practices. Unlike previous studies that simply
compare the financial stability of CBs and IBs, this paper fo-
cuses on an important exogenous variable, namely, the sukuk
market, which might affect the financial stability of IBs. This
variable has been mostly overlooked so far. This component is
unexpected in that IBs have little regulation of it. Our results
confirm that, to a certain degree, the sukuk market is a sig-
nificant factor that affects IB practices.
Second, unlike previous studies that primarily focus on the
influence of the banking sector, bonds, and equity markets on
economic growth, this paper extends the literature on financial
development by examining the market for Islamic bonds
(sukuk).
These results offer regulators and decision-makers guidance
on the additional aspects to consider as they develop Islamic
finance in the form of IBs and sukuk markets.
The remainder of this paper is organized as follows. The
literature review and the developed hypotheses are discussed in
Section 2. The sample and collected data, variables, and esti-
mation model are addressed in Section 3. The results of the
model, discussion, and robustness check are presented in
Section 4. The conclusion and policy implications are
addressed in Section 5.
2. Literature Review
According to Mimouni et al. (2019) and Smaoui and
Ghouma (2020), the link between financial markets and the
banking sector is determined by complementarity and compe-
tition. The effect of financial markets on the banking sector is
still a topic of debate in the literature, which has little analysis
of sukuk markets and Islamic banking. To the best of our
knowledge, the relationship between IBs' financial stability and
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3. sukuk markets has not yet been investigated. For this reason,
we study whether the link between the sukuk market and IBs is
characterized by complementarity or competition in terms of
financial stability. In so doing, we fill a gap in the literature.
Based on finance theory and empirical studies, sukuk mar-
kets can positively affect IBs by improving their financial
stability and operational management, which confirms the ex-
istence of the complementarity effect.
According to Demirgüç-Kunt and Maksimovic (1996),
because sukuk markets are complementary to IBs, an expan-
sion in stock markets increases corporate debt, which reflects
more banking operations and activities. Similarly, according to
Demerguç-Kunt and Huizinga (2001), the financial system has
no independent influence on banking profitability. Moreover,
Eichengreen and Luengnaruemitchai (2004) show that bond
markets and banks complement each other. According to Song
and Thakor (2010), the relation between banks and capital
markets is frequently interactive, ranging from basic comple-
mentarity to complete collaboration. As a result, banks address
the certification issue by evaluating and assessing the credit
quality of clients whose debts are securitized, decreasing in-
formation asymmetry and enabling the market to provide
funding at lower prices. Because financial market tensions have
decreased, banks can obtain cheaper stocks, increasing their
capital capacity and allowing them to service riskier customers.
This procedure motivates banks to enhance their evaluation
technologies on a constant basis, reducing the certification
issue even further. Finally, these enhancing repercussions from
banks to capital markets and the opposite benefit their overall
growth. This link is described by Song and Thakor (2010) as
coevolution, in which banks and capital markets both develop
at the same time. In line with the coevolution relationship,
Smaoui et al. (2017) examine the link between CBs and the
sukuk market and demonstrate that sukuk markets and the
banking sector are substitutes.
Anand et al. (2012) investigate the implications of covered
bonds issued by banks on financial stability. Their findings
demonstrate that covered bonds enhance the financial stability
of banks. Likewise, Neyer and Sterzel (2017) investigate
whether a bank's government bond holdings improve banking
system financial stability during sovereign debt crises, and their
results demonstrate that government bonds improve the
banking system's shock-absorbing proficiency and hence
financial stability. In a recent study, based on international
evidence, Park et al. (2021) demonstrate that bond markets of
local currencies and bank loans improve financial stability.
Furthermore, and more directly, the financial stability of IBs
could be enhanced more directly by issuing sukuk, which are
classified as Tier 1 capital. This kind of sukuk is even more
desirable and less expensive than ordinary stocks, which suffer
from negative signaling and underpricing. Simulating Basel III
capitalization to increase stability and capital at financial in-
stitutions, in December 2013 the IFSB (2013) established
sukuk, which are regarded as capital according to IFSB-15.
According to the IFSB (2013), issuing Tier 1 sukuk can help
IBs to improve their financial stability. According to the Basel
Committee, bank capitalization comprises Tier 1 capital (core
capital at any bank), which includes equity capital, permanent
loans, and declared reserves (Cobanoglo, 2015). Simulating
Basel III, IFSB-15 establishes common equity as Tier 1 capital
to the sukuk issued, called “Tier 1 sukuk.” Thus, to qualify
sukuk as Tier 1 capital, the sukuk issuance must operate in
accordance with the Basel Accord requirements (Cobanoglo,
2015).
As stated by the IFSB (2013), Tier 1 sukuk have a high level
of loss absorbency, in particular, mudharabah (profit sharing
agreement), wakala (agency agreement), and musharaka
(partnership agreement). In practice, several IBs have issued
sukuk regarded as additional Tier 1 capital (ijarah (leasing
agreement) and mudarabah Tier 1), which can contribute to the
development of sukuk markets and increase the IBs’ financial
stability (IFSB, 2013; IIFM, 2021). According to a report by
the IIFM (2021), in 2020, the Saudi National Bank issued USD
1.12 billion in mudharabah Tier 1; the Dubai Islamic Bank
issued USD 1.0 billion in mudharabah Tier 1; and the National
Commercial Bank also issued USD 1.25 billion in additional
Tier 1 sukuk. These examples of sukuk issuance indicate that
developed sukuk markets would enhance IBs' capacity to ac-
cess adequate investment opportunities and strengthen their
financial stability. Based on these arguments, we posit that:
Hypothesis 1. The development of the sukuk market has a
positive effect on IBs' financial stability.
Although these arguments support a favorable link between
sukuk market development and IBs’ financial stability, finance
theory suggests the opposite. The stream of literature on
financial intermediation indicates the presence of a competition
effect between capital markets and the banking sector, in which
the growth of one source of financing must unavoidably come
at the expense of the other (Allen & Gale, 1997; Song &
Thakor, 2010). In a notable study, Rajan and Zingales (2003)
argue that, under the theoretical context of an “interest
group,” the banking sector resists the development of financial
markets as a direct risk to itself, particularly if it is concen-
trated. Dickie and Fan (2005) empirically demonstrate this
based on a sample of 30 countries from 1989 to 2002 in which
the banking sector competes with the capital markets. Based on
these arguments, the link between IBs and sukuk markets is
determined by competition.
However, sukuk markets can negatively affect IBs by reducing
their financial stability, resulting in high risk for assets, which
confirms the existence of the competition effect. Mimouni et al.
(2019) investigate the effect of sukuk markets on the profit
ratio of IBs and CBs. Their results reveal that sukuk markets
decrease IBs' profitability resulting from high risk-taking,
which demonstrates that sukuk markets are competitive with
IBs.
Correspondingly, Smaoui and Ghouma (2020) study the effect
of sukuk markets on the capitalization of IBs. Their empirical
results demonstrate that sukuk markets are competitive with
IBs in terms of capitalization. In addition, firms and other
economic players obtain direct and probably less expensive
financing via the sukuk market. The existence of a sophisti-
cated sukuk market can diminish banks' market share and
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4. increase competition among them. Sukuk markets are preferred
and largely relied on by the public and big firms (supposedly
less risky firms) in their funding and investment operations
(Mimouni et al., 2019; Smaoui & Ghouma, 2020). As a result,
banks mostly deal with younger private firms (apparently the
riskiest in the market), which frequently have limited access to
capital markets because of their size, resources, or age. As
indicated by Mimouni et al. (2019) and Smaoui and Ghouma
(2020), banks adopt more assertive lending strategies, result-
ing in worse credit quality, and increase the risky assets of their
financial statements. As a result IBs' financial stability declines.
Keeley (1990) and Jiménez et al. (2013) state that greater
competition among US banks led to higher risk-taking. In re-
ality, when the level of competition is high, banks are more
likely to take risks because competition decreases their profit-
ability, resulting in low financial stability.
Additionally, Cole et al. (1995), Hellmann et al. (2000), and
Kane (1989) indicate that when banks encounter intense
competition from capital markets, banks prefer to take risks and
gamble through investing in risky portfolios with high returns
if they succeed but leaves depositors worse off if the gamble is
unsuccessful. Moreover, Hellmann et al. (2000) state that su-
pervisors who are aware of this practice often employ capital
requirements to push banks to put a large portion of their
capital at high risk to internalize the ineffectiveness of such
gambles. As a result, banks respond and act intelligently in a
manner that decreases their exposed capital, rendering capital
adequacy standards ineffective in strengthening financial sta-
bility. Accordingly, several studies support this viewpoint,
arguing that competition tends to increase banks' risk-taking
behavior, reducing bank financial stability (Allen & Gale,
2004; Hellmann et al., 2000). The influence of competition
on the behavior of IBs can reduce financial stability, reflecting
the competition effect of sukuk markets on IBs. Based on the
reasoning in this paper, the development of sukuk markets
increases competition among IBs, pushing them to increase
their portfolio risk or reduce their financial stability to a min-
imum. In light of this, this study proposes the following
hypothesis:
Hypothesis 2. The development of the sukuk market has a
negative effect on IBs' financial stability.
According to the two different views of the link between sukuk
markets and IBs in the literature, sukuk markets can affect IBs
positively, creating a complementary effect, or it can affect IBs
negatively, creating a competition effect. Nevertheless, to the
best of our knowledge, no prior studies have gone beyond the
paradigm of IBs’ riskiness to investigate additional variables
for IBs' financial stability, in contrast to the plethora of studies
on CBs' financial stability. Which variables influence IBs'
financial stability remains an open question. Therefore, the
adoption of sukuk markets as a significant variable influencing
IBs' financial stability is primarily due to the recent rapid
development in sukuk markets. So, the goal of this paper is to
fill this gap in the literature by exploring the effect of sukuk
market development on the IBs' financial stability in terms of
the complementary effect hypothesis (H1) and competition
effect hypothesis (H2).
3. Research Methodology
3.1. Sample and data collection
3.1.1. Sample countries
According to the International Islamic Financial Market
(IIFM, 2021) sukuk database, global sukuk issuance increased
19.84 percent in 2020 (from USD 145.702 billion in 2019 to
USD 174.641 billion in 2020), and the volume in 2020 was
primarily due to the domestic sukuk market, which represent
about 75.80 percent (USD 132.233 billion) of the total. Although
Indonesia, Saudi Arabia, Turkey, Brunei, and the United Arab
Emirates all increased their share of the sukuk market, in 2020
the global sukuk market was dominated by Malaysia, as indi-
cated in Table 1. This database shows that Malaysia, Saudi
Arabia, Indonesia, Turkey, Bahrain, Brunei, United Arab
Emirates, and Oman are the major domestic sukuk-issuing
countries for financing projects, providing liquidity, meeting
financial commitments, and other business requirements, as
shown in Table 1.
IFSB (2021) reported that, in 2020, IBs in Malaysia,
Indonesia, Saudi Arabia, Turkey, and Brunei expanded their
assets and market share of the local banking sector. Malaysia and
Indonesia increased their assets because of a favorable regula-
tory framework and extensive government assistance. Malaysia
remained the largest market of Islamic banking in Southeast
Asia, with a market value of USD 210.0 billion and 28.9 percent
of the Malaysian banking system's market at the end of 2020Q3
(28.4% in 2019Q3). At the end of 2020Q3, Indonesia's IBs were
valued at USD 37.7 billion and represented 6.1 percent of the
market, an increase from 5.8 percent in 2019. Brunei had an
acceptable rate in IBs' assets in 2020 b y holding to 4.8 percent
from 7.5 percent in 2019. In Saudi Arabia, IBs expanded by 17.0
percent year over year, compared to 10.6 percent in 2019Q3, and
the IBs' asset share was 68.0 percent at the end of 2020Q3
(69.0% in 2019Q3). At the end of 2020Q3, Saudi Arabia had the
largest Islamic banking system, with total assets of USD 522.3
Table 1
Major domestic sukuk-issuing countries, 2001–2020.
Country Domestic sukuk
issuance
(USD millions)
Market share of the
global domestic
sukuk market (%)
2001–2020 2020 2001–2020 2020
Malaysia 714,311 53,747 65.50% 40.65%
Saudi Arabia 109,258 18,727 10.02% 14.16%
Indonesia 103,755 23,550 9.51% 17.81%
Turkey 49,998 23,399 4.58% 17.70%
Bahrain 23,807 2502 2.18% 1.89%
Brunei 11,830 881 1.08% 0.67%
United Arab Emirates 8631 307 0.79% 0.23%
Oman 3103 1134 0.28% 0.86%
Source: IIFM (2021).
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5. billion. In Turkey, the share of IBs increased, with assets valued
at USD 54.98 billion at the end of 2020Q3 (USD 45.57 billion in
2019Q3), accounting for 7.10 percent of total local banking as-
sets (6.3% in 2019Q3).
Based on the available data from the IFSB database, we
cover a sample of Islamic banking and sukuk markets in
Malaysia (16 IBs), Saudi Arabia (8 IBs), Indonesia (14 IBs),
Brunei (2 IBs), and Turkey (6 IBs).
3.1.2. Data collection
For the empirical investigation, this paper uses a balanced
panel data from 2013Q4 until 2019Q4; this avoids the period of
the Covid-19 pandemic, which created great global uncertainty
and low investor appetite in Islamic banking and sukuk markets,
as shown in a report by DinarStandard (2021). Because the IFSB
is the most comprehensive, global database of official financial
statements and reports on IBs, sukuk markets, and other Islamic
financial institutions (IFSB, 2021; Rosman & Abdul Rahman,
2015; Ullah et al., 2018), the data on sukuk and IBs were gath-
ered from quarterly statistics in this database on all the working
Islamic financial institutions in the sample countries.
The data on macroeconomic factors are collected from the
database of the International Monetary Fund (IMF). Since all
countries have varied currencies, this study converts each
quarter's financial value to the US dollar using the average ex-
change rate for each quarter extracted from the IMF database.
3.2. Variables
3.2.1. Financial stability as a dependent variable
Many studies support the effectiveness of using the Z-score
model by Altman (1968) for measuring and evaluating the
financial stability, soundness, bankruptcy risk, and solvency in
the banking sector. According to Bourkhis and Nabi (2013)
and Khalil (2021), the Z-score is a distance-to-default metric
that compares the market value of a bank's assets to its book
value of liabilities. Thus, this study employs the Z-score model
for the best assessment of IBs' financial stability: the higher the
Z-score, the lower the potential for a bank's bankruptcy, and
thus the more stable the bank is. This study calculates the Z-
score based on the equation by Boyd et al. (2006) as follows:
Z − score =
ROA + Equity
Assets
σ(ROA)
(1)
where the Z-score is calculated based on the ratio of the sum of
return on assets (ROA) and equity divided by assets to the ratio
of the standard deviation of ROA. This equation is used in
several notable studies to assess the financial stability of con-
ventional banking (Demirgüç-Kunt & Huizinga, 2010;
Fiordelisi & Mare, 2014; González et al., 2017; Turk Ariss,
2010). In addition, this equation is commonly used in empir-
ical studies to assess the financial stability of IBs, as shown in
Table 2. Following Bourkhis and Nabi (2013), Karim et al.
(2018), and Khalil (2021), the financial stability variable of
IBs for the selected sample countries is determined by the Z-
score as shown in Fig. 1.
According to the International Monetary Fund (IMF), the
strength, soundness, and stability of banks can be detected from
several indicators, such as profitability, which is measured by
ROA; asset quality, which is measured by the ratio of nonper-
forming loans (NPLs) to total loans; and capitalization, which is
measured by the capital adequacy ratio (Avlokulov, 2016;
Kasselaki & Tagkalakis, 2014; Nugroho et al., 2020; Pointer &
Khoi, 2019; Rahayu et al., 2018; Čihák & Hesse, 2010). For a
robustness test, this study uses profitability, which is measured
by ROA, as an indicator of financial stability.
3.2.2. Sukuk market development as an independent
variable
Following Ledhem (2020), Yıldırım et al. (2020), and
Ledhem and Mekidiche (2021), this paper uses the total sukuk
holdings as a variable for sukuk market development.
3.2.3. Bank-level factors
To avoid the issue of bias in the estimated model because of
omitted bank-level variables, which could affect IBs’ financial
stability, this section uses the bank level as a control variable
Table 2
Summary of notable literature on financial stability assessment in IBs.
Study Method Contribution
Čihák and Hesse (2010) Z-score Measures the financial stability of IBs and CBs using the Z-score model in 18 banking systems
Bourkhis and Nabi (2013) Z-score Explores the impact of the 2007 financial crisis on the financial stability of Islamic and conventional
banking in 16 countries
Fakhrunnas and Ramly (2017) Z-score Calculates the bankruptcy risk in IBs for examining the link among sharia supervisory and directors
board and risk-taking in Southeast Asia
Karim et al. (2018) CAMELS
model and Z-
score
Measures the bank stability for local IBs and CBs in Malaysia from 1999 to 2015
Prima Sakti and Mohamad (2018) Z-score Compares the financial stability of IBs and CBs in Indonesia (2008–2012)
Ghassan and Guendouz (2019) Z-score Measures the financial stability of IBs and CBs in Saudi Arabia
Qasim (2020) Z-score Examines the Islamic banking performance and bankruptcy in Jordan from 2010 to 2016
Khalil (2021) CAMELS
model and Z-
score
Investigates the effect of sharia and directors board on the financial soundness of IBs
Hassan et al. (2021) Z-score Assesses the financial stability of 9 IBs and 23 CBs in Pakistan
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6. and their predicted impact on the financial stability of IBs.
These control variables are extensively employed in studies on
IBs' financial stability.
3.2.3.1. Capital adequacy ratio. This study employs the cap-
ital adequacy ratio (CAR) to measure the IBs' capitalization.
According to Ledhem and Mekidiche (2020), CAR is calcu-
lated by dividing the total Tier 1 and Tier 2 capital by the risk-
weighted assets. A higher CAR indicates that IBs are well
capitalized regarding their risk level, guaranteeing their
soundness (Karim et al., 2018; Ledhem & Mekidiche, 2020).
As a result, the effect of CAR on IBs’ financial stability is
expected to be positive.
3.2.3.2. Asset quality. As Ledhem and Mekidiche (2020)
stated, asset quality (AQ) is a factor in IBs' financial stabil-
ity, in which good asset quality leads to high profitability and
good financial stability. Therefore, following Ledhem and
Mekidiche (2020), this study employs AQ, which is the ratio
of gross nonperforming financing to total financing. The effect
of AQ on IBs’ financial stability is expected to be positive.
3.2.3.3. Management efficiency ratio. According to Ledhem
and Mekidiche (2020), IBs' financial stability is determined
by the management efficiency ratio. However, Sun et al. (2017)
state that proficient management has a negative influence on
banking profitability, which reduces financial stability. Hence,
following Ledhem and Mekidiche (2020), this study employs
the management efficiency ratio (MER) by dividing total
operating costs by gross income to show the effect of MER on
IBs’ financial stability and is expected to be negative.
3.2.3.4. Liquidity. According to Sun et al. (2017), liquidity risk
can negatively affect banking stability because it motivates
banks to select larger bank intermediation margins as a pre-
mium, particularly when banks are cash strapped and might
accrue debt fees from other banks or financial markets. Hence,
the effect of LIQ on IBs’ financial stability is expected to be
negative. Following Ledhem and Mekidiche (2020), LIQ is
calculated by the ratio of liquid assets to total assets.
3.2.3.5. Riskiness. Following Klepczarek (2015), this paper
employs the ratio of risk-weighted assets to total assets as a
proxy for the riskiness of IBs. To compensate for their risk
tolerance, risk-averse CBs establish larger intermediation
profits (Mimouni et al., 2019). As a result, the effect of RISK
on IBs’ financial stability is expected to be positive.
3.2.3.6. Size. The impact of bank size on financial stability
ratios varies (Kasman et al., 2010). On the one hand, a bigger
bank's fixed expenses can be distributed across a larger asset
base, reducing average expenses and resulting in higher earn-
ings through economies of scale (Regehr & Sengupta, 2016).
On the other hand, small banks can build deeper ties with local
consumers and businesses than big banks, giving them access
to important information that can be used to improve credit
rating and contract conditions (Athanasoglou et al., 2008).
Thus, small banks might be able to achieve better earnings and
more stability than bigger banks as a result of this information
and price advantages, offsetting any loss from economies of
scale. As a result, the influence of bank size on bank earnings
and stability is ambiguous, and therefore so is the effect of
bank size on the financial stability of IBs. Following the IFSB
(2021), IB size is calculated by total assets.
3.2.4. Macroeconomic factors
This paper employs four country-level factors to control for
the impacts of macroeconomic factors on IBs’ financial stability.
Fig. 1. Financial stability assessment in IBs for the selected sample countries.
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7. 3.2.4.1. Economic growth. According to the “demand-
following hypothesis” of Robinson (1952) and the literature on
the link between banking and economic growth, increased
economic growth leads to high demand for banking services
and, therefore, increases bank activity. The consequent increase
in loans and client deposits might have a beneficial effect on
banking stability and profitability (Sufian & Chong, 2008). As
a result, this study supports the concept that economic growth
and IBs’ financial stability are positively correlated. Following
Ledhem (2020), this study uses the gross domestic product
(GDP) to measure economic growth.
3.2.4.2. Inflation. According to the IB literature, inflation
benefits IBs' financial stability because a bigger share of their
income comes from service charges on their financial prod-
ucts and trade deals, as shown and empirically proved by
Asutay and Izhar (2007). Additionally, Bashir (2003) states
that inflation improves IBs' financial stability when a larger
amount of IBs' earnings come from direct investment, equity,
and other commercial activities. Their outcomes show that,
with inflation, bank earnings increase more than their costs.
Thus, IBs predict inflation and subsequently modify their
earnings to exceed expenses, and then, increase their finan-
cial stability (Chowdhury & Rasid, 2015; Trad et al., 2017).
For these reasons, we expect inflation to have a positive
effect on IBs’ financial stability. This paper employs the
consumer price index as a measure of inflation (Zarrouk
et al., 2016).
3.2.4.3. Trade openness. This study adopts trade openness to
control its possible effect on IBs' financial stability. Trade
openness stimulates demand and motivates economies to
implement financial liberalization policies that improve
competition in the banking sector (Adeel-Farooq et al., 2017).
According to Rashid et al. (2017), increased competition is
expected to strengthen IBs' financial stability. In light of this,
this study expects trade openness to have a positive effect on
IBs’ financial stability. Following Ledhem (2020), trade
openness is calculated by dividing total exports and imports of
goods and services by GDP.
3.2.4.4. Investment. Many studies state that investment has a
positive effect on banking stability because it increases prof-
itability of CBs (Almazari, 2014). As well, Zarrouk et al.
(2016) demonstrate empirically that higher levels of invest-
ment have a positive effect on profitability of IBs, which re-
inforces the IBs' financial stability. Therefore, this paper
expects investments to have a positive influence on IBs’
financial stability. Following Ledhem and Mekidiche (2021),
this paper employs gross fixed capital formation (GFCF) as a
measurement of investment. Table 3 defines all the variables
and gives the expected sign of their effect.
3.3. Estimation model
This paper adopts empirical modeling proposed by Ho and
Saunders (1981) and its expansion in terms of banking
Table 3
Definition of the variables and the expected sign of their effect.
Variables Description Variable label Expected sign
Dependent
Financial stability Financial stability is measured by the Z-score:
Z − score =
ROA +
Equity
Assets
σ(ROA)
Z-score
Return on assets For the robustness test, financial stability is measured by profitability:
ROA =
Net income
Total assets
ROA
Independent
Sukuk market development Sukuk market development is measured by total sukuk issued SUKUK +
Bank-level factors
Capital adequacy ratio
CAR =
Total Tier 1 and Tier 2 capital
risk − weighted assets
CAR +
Asset quality
AQ =
Gross nonperforming financing
Total financing
AQ +
Management efficiency ratio
MER =
Total operating costs
Gross income
MER –
Liquidity
LIQ =
Share of liquid assets
Total assets
LIQ –
Riskiness
RISK =
Risk − weighted assets to
Total assets
RISK +
Size SIZE = Total assets SIZE +/−
Macroeconomic factors
economic growth GDP is the proxy for economic growth GDP +
Inflation Inflation is measured by the CPI CPI +
Trade Openness
TRADE =
Total imports + exports
GDP
TRADE +
Investment Gross fixed capital formation represents the investment GFCF +
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8. determinants. However, the estimated model might have
endogeneity problems because of the potential unobserved
individual effects. As a result, panel regression with fixed/
random effects is inappropriate for estimation and can generate
biased estimations and inaccurate results (Baltagi & Kao,
2001). In this case, IB factors that determine financial stabil-
ity, such as riskiness and liquidity, capital, and management
affect sukuk markets (Khoutem, 2014; Said & Grassa, 2013;
Smaoui & Khawaja, 2017). Thus, endogeneity problems might
arise because of the potential effect of the dependent variable
(IB's financial stability) on sukuk market development. To
avoid this problem, Blundell and Bond (1998) develop dy-
namic panel system–generalized method of moments (GMM),
which is an approach developed to determine the first-
difference panel regression, created by Arellano and Bond
(1991). Unlike the approach of Arellano and Bond (1991),
which includes weak instruments with lagged levels, the dy-
namic panel system-GMM has robust instruments at lagged
levels and differences. Therefore, using Stata software, which
provides accurate panel data analysis, particularly for system-
GMM, as stated by Roodman (2009), this study applies the
dynamic panel one-step system-GMM method of Blundell and
Bond (1998), which can eliminate the unobserved individual
effect and then mitigate the possible endogeneity issue, serial
correlation, and heteroskedasticity in residuals as stated by
Bond (2002) and Roodman (2009). Based on this evidence and
following the approach typically employed in the empirical
research on banking stability at both IBs and CBs
(Athanasoglou et al., 2008; Demirgüç-Kunt & Huizinga, 1999;
Ghassan & Guendouz, 2019; Prima Sakti & Mohamad, 2018;
Smaoui et al., 2017; Stavárek & Polouček, 2004), the empirical
model based on the dynamic panel data (including a lagged
variable of the dependent variable lagged Z-score) is defined as
follows:
Yit = α0 + ∂Yi,t−1 + αiPit + βiXit + ζiMit + ξit⋅ ∀⋅ξit = vi + μit
(2)
where for country i at time t, Yit is financial stability (Z.score),
Yi,t−1 is the Z. score lagged one-quarter, and ∂ is the coefficient
of equilibrium speed. Pit is sukuk market development
(SUKUK), Xit denotes bank-level factors (CAR, AQ, MER,
LIQ, RISK, and SIZE), Mit represents macroeconomic vari-
ables (GDP, CPI, TRADE, and GFCF), α0 is a constant, and αi,
βi, and ζi are regression parameters. ξit is an error term in which
vi is the unobserved effect of SUKUK, and μit is individual
error.
4. Results and discussion
4.1. Descriptive statistics
The descriptive statistics for the variables are measured
using Stata software, as shown in Table 4. Each variable has
125 observations for 5 countries, except for 5 missing values of
the bank-level factor LIQ (the missing values are for Saudi
Arabia from 2013Q4 to 2014Q4). Because only a few values of
LIQ are missing, Stata converts the total dataset into balanced
panel data for running the panel regression with dynamic panel
one-step system-GMM. Focusing on the statistics of the main
variables, Table 4 shows that the Z-score for the average
financial stability of IBs in the sample is 49.38, which indicates
the presence of high financial stability and low risk by IBs.
Average financial stability of IBs, measured by ROA, is 1.46
percent. Table 4 further reveals that the financial stability of
IBs of the sample varies widely, with a standard deviation of
30.94 for the Z-score, and 0.58 percent for ROA. In addition,
the average sukuk market development for the countries stud-
ied is USD 7.03 billion for total sukuk holdings issued over the
study period, with a standard deviation of USD 8.56 billion.
Table 5 shows the correlation coefficients of the variables
used for regression. The Z-score is highly positively correlated
with SUKUK, SIZE, and TRADE over a range from 0.784 to
0.918, and ROA is highly positively correlated with CAR. In
addition, the financial stability ratios (Z-score and ROA) are
negatively correlated with AQ, MER, GDP, CPI, and GFCF.
4.2. Empirical results
In this section, we perform a panel regression with dynamic
panel one-step system-GMM using Stata to obtain adjusted
balanced panel data with 116 observations over the period
2013Q4–2019Q4, as shown in Table 6.
Table 6 shows that the effect of sukuk market development
on financial stability (Z-score) of IBs is significantly positive at
the 5 percent level ( p-value of SUKUK = 0.023 < 0.05),
which indicates that sukuk market development improves
complementarity between IBs, helping them to maintain sta-
bility. This finding is consistent with the conclusion of Anand
et al. (2012), who demonstrate that covered bonds improve the
financial stability of CBs, and it is compatible with the findings
of Neyer and Sterzel (2017) that government bonds improve
CBs' shock-absorbing proficiency and financial stability. Also,
Table 4
Summary of descriptive statistics.
Variable N Mean Std. Dev Min. Max.
Dependent variables
Z-score 125 49.38017 30.94437 19.53098 107.2002
ROA 125 0.0146216 0.0058118 0.0039464 0.0327846
Independent variable
SUKUK 125 7034.867 8562.796 74.58109 31,424.05
Bank-level factors
CAR 125 0.180049 0.02647 0.1386601 0.2313424
AQ 125 0.0329021 0.0190574 0.0084121 0.0847224
MER 125 0.5341304 0.1863644 0.2809293 0.9512756
LIQ 120 0.306361 0.1774829 −0.0001496 0.7237573
RISK 125 0.6552348 0.1032558 0.4629566 0.8155739
SIZE 125 299,847.9 236,626.9 7869.331 794,649.8
Macroeconomic factors
GDP 125 142,793.5 89,643.63 2756.005 289,104.6
CPI 125 129.0856 30.41448 98.25291 245.3924
TRADE 125 0.780495 0.3330159 0.3456053 1.426386
GFCF 125 40,890.42 28,213.21 762.7048 97,731.01
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9. this finding is in line with the evidence by Park et al. (2021)
that bond markets improve financial stability. Because the
positive link of complementarity is demonstrated only between
capital markets and CBs, this finding is the first to reveal a
complementary effect between the two main sectors of the
Islamic finance industry (IBs and sukuk markets) in terms of
financial stability.
As a result, this finding confirms H1, so it rejects H2, which
is compatible with the conclusion by Mimouni et al. (2019) and
Smaoui and Ghouma (2020) that sukuk market development
negatively affects IBs by creating more competition among
them.
Concerning the effect of a lagged Z-score on financial sta-
bility, it is positively significant at the 1 percent level as shown
in Table 6 ( p-value of lagged Z-score = 0.000 < 0.01), which
means that IBs’ financial stability in the sample countries is
adjusted to equilibrium at a speed of 96.90 percent. This in-
dicates that IBs in the sample countries are strongly stable in
the face of external shocks.
Regarding the effect of bank-level factors on financial sta-
bility, Table 6 shows that the CAR affects financial stability
positively at the 1 percent significance level ( p-value of
CAR = 0.001 < 0.01). This finding is confirmed by Karim
et al. (2018) and Ledhem and Mekidiche (2020), who state
that well-capitalized IBs are financially stable. The asset quality
has a positive influence on IBs' financial stability but is not
statistically significant, as shown in Table 6 ( p-value of
AQ = 0.065 > 0.05), which indicates that the asset quality is
not sufficient to enhance the IBs' financial stability in the
sample countries. Moreover, Table 6 shows that the MER
negatively affects the IBs' financial stability but is not statis-
tically significant ( p-value of MER = 0.169 > 0.05). However,
the effect of liquidity on IBs' financial stability is statistically
negative at the 5 percent level ( p-value of
LIQ = 0.045 < 0.05), which indicates that liquidity risk re-
duces IBs' financial stability in the sample countries. Because
liquidity risk may negatively affect CBs stability because of the
high margin intermediation, as stated by Sun et al. (2017) with
respect to IBs, this negative effect can occur when liquidity risk
motivates IBs to pick larger bank intermediation margins as a
premium and may increase debt fees for other IBs or sukuk
markets. Concerning the riskiness factor, Table 6 shows that
riskiness has a positive effect on IBs' financial stability at the 1
percent significance level ( p-value of RISK = 0.000 < 0.01),
which leads to the conclusion that the riskiness stimulates IBs
to augment the profit margins to compensate for the predicted
risk, in line with the evidence by Klepczarek (2015) on this
effect at CBs. Regarding the size effect on IBs’ financial sta-
bility, Table 6 shows that it is positive but not statistically
significant ( p-value of SIZE = 0.867 > 0.05), which indicates
that employed assets at IBs are not adequate to improve their
financial stability in the sample countries.
Concerning the effect of macroeconomic factors on IBs'
financial stability in the sample countries, Table 6 shows that
GDP, which is an economic growth proxy, affects the IBs'
Table 5
Correlation matrix.
Z-score ROA SUKUK CAR AQ MER LIQ RISK SIZE GDP CPI TRADE GFCF
Z-score 1.000
ROA −0.012 1.000
SUKUK 0.918 −0.034 1.000
CAR −0.105 0.698 −0.148 1.000
AQ −0.762 −0.26 −0.729 0.055 1.000
MER −0.450 −0.319 −0.377 −0.208 0.245 1.000
LIQ −0.495 0.199 −0.464 0.232 0.496 −0.498 1.0000
RISK −0.489 0.370 −0.479 0.149 0.093 0.189 0.310 1.000
SIZE 0.813 0.156 0.854 0.007 −0.856 −0.152 −0.572 −0.162 1.00
GDP −0.308 −0.119 −0.133 −0.290 −0.087 0.640 −0.283 0.373 0.145 1.000
CPI −0.312 −0.198 −0.149 −0.283 0.102 0.111 0.208 0.065 −0.065 0.610 1.000
TRADE 0.784 −0.056 0.644 −0.022 −0.358 −0.639 −0.148 −0.650 0.3483 −0.762 −0.469 1.000
GFCF −0.397 −0.204 −0.249 −0.326 0.031 0.730 −0.295 0.319 0.012 0.976 0.590 −0.784 1.000
Table 6
Dynamic panel one-step system-GMM results.
Number of observations = 116 Number of groups = 5
Wald chi2 (12) = 283.17 Prob > chi2 = 0.000
Variables Coefficients Robust Standard Error z-stat P> |z|
Lagged Z-score 0.9690645 0.038986 24.86 0.000**
SUKUK 0.0000703 0.0000309 2.27 0.023**
CAR 17.54935 5.326526 3.29 0.001**
AQ 27.30758 14.78297 1.85 0.065
MER −5.414993 3.936945 −1.38 0.169
LIQ −9.462373 4.714133 −2.01 0.045*
RISK 7.834279 1.111991 7.05 0.000**
SIZE 7.10e-07 4.25e-06 0.17 0.867
GDP −0.0000332 0.0000177 −1.88 0.060
CPI 0.0239379 0.0088635 2.70 0.007**
TRADE 1.62157 1.218684 1.33 0.183
GFCF 0.0000961 0.0000344 2.80 0.005**
Constant −6.14944 4.5922 −1.34 0.181
Tests of serial correlation
Arellano–Bond test for AR (1) z-stat = −1.82 P> |z| = 0.069
Arellano–Bond test for AR (2) z-stat = 0.67 P> |z| = 0.504
Instruments' total validity test
Sargan test Chi2 (68) = 69.19 Pr > chi2 = 0.437
Robustness test
Hansen test Chi2 (52) = 0.00 Pr > chi2 = 1.000
Note: * 0.05 significance, ** 0.01 significance.
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10. financial stability negatively but is not statistically significant
( p-value of GDP = 0.060 > 0.05). Inflation has a positive
effect on IBs' financial stability at the 1 percent significance
level ( p-value of CPI = 0.007 < 0.01), as revealed in Table 6.
This finding is in line with Bashir (2003), who determines that
inflation improves financial stability at IB′ when they achieve
high earnings from direct investment, equity, and other com-
mercial activities that are stimulated by inflation. The effect of
trade on IBs' financial stability is positive but not statistically
significant ( p-value of TRADE = 0.183 > 0.05), as revealed in
Table 6. However, the effect of investment on IBs' financial
stability is positively significant at the 1 percent level ( p-value
of GFCF = 0.005 < 0.01), as revealed in Table 6. This finding
specifies that investment in the selected countries enhances IBs'
financial stability because higher investment fuels earning at
IBs, which reinforce their financial stability, consistent with the
empirical evidence of Zarrouk et al. (2016) on this effect. The
constant is statistically insignificant, which indicates that IBs’
financial stability in this model is not affected by other omitted
variables.
Regarding the diagnostics of dynamic panel system-GMM,
Table 6 shows that the instruments’ total validity is significant,
which indicates that all instruments are exogenous ( p-value is
insignificant: Pr > chi2 = 0.437) and so is the Sargan test of
overidentifying restrictions. Therefore, based on the recom-
mendations by Arellano and Bond (1991), all GMM in-
struments are valid. In addition, Table 6 shows the absence of
panel serial correlation on the first-order AR (1)
(Pr > Z = 0.069) and second-order AR (2) (Pr > Z = 0.504)
based on the Arellano–Bond test. The results in Table 6 show
that the p-value of the Hansen test is highly insignificant
(Pr > Chi2 = 1.00), which indicates that the estimation model
is robust and unbiased, as stated by Roodman (2009).
Because the estimation model is free of serial correlation,
and all instruments in the GMM estimation are robustly valid,
the empirical outcomes are robustly unbiased and accurate.
Consequently, the empirical study is precise, accurate, and
robustly unbiased.
4.3. Robustness test
To check the robustness of the empirical results in Table 6,
we perform another regression. To do so, we focus on the
profitability indicator, which is measured by ROA as an
alternative measure of financial stability. Therefore, Table 7 is
replicated using ROA for investigating whether a structural
change occurred in the effect of sukuk market development on
financial stability (Z-score) of IBs.
The empirical results in Table 7 show that the robustness
test generates results that are similar to the original results in
Table 6. The ROA estimations confirm the original estimated
results about the effect of sukuk market development on the
financial stability of IBs. Table 7 reveals that the effect of
sukuk market development on IBs’ financial stability (ROA) is
significantly positive at the 1 percent level ( p-value of
SUKUK = 0.007 < 0.01), which confirms H1. This finding
confirms the result of Anand et al. (2012), Neyer and Sterzel
(2017), and Park et al. (2021)—that bond markets are com-
plementary to CBs in terms of financial stability. This finding is
in line with the evidence of Smaoui et al. (2017) that sukuk
markets are complementary to the CB sector.
Also, Table 7 reveals that the effect of lagged ROA on
financial stability is positively significant at the 1 percent sig-
nificance level ( p-value of lagged ROA = 0.003 < 0.01). This
estimated result indicates that IBs' financial stability is adjusted
to equilibrium at a speed of 18.16 percent if lagged ROA is
used. Therefore, this finding confirms the original estimated
result in Table 6 that IBs’ financial stability achieves equilib-
rium if the lagged Z-score is used, which confirms that IBs in
the sample countries are strongly stable in the face of external
shocks.
Additionally, the robustness test demonstrates that the effect
of bank-level and macroeconomic variables on the financial
stability of IBs has the same signs and statistical significance
levels for the majority of variables. The bank-level variables in
Table 7 maintain their signs or become statistically insignifi-
cant, with some exceptions to the earlier results. In particular,
the effect of AQ on the financial stability of IBs becomes
negative and loses statistical significance ( p-value of
AQ = 0.780 > 0.05), implying that asset quality is not suffi-
cient for maintaining IBs’ financial stability, measured by
profitability. Additionally, the effect of SIZE on the financial
stability of IBs also becomes negative and has statistical sig-
nificance ( p-value of SIZE = 0.016 < 0.05), implying that
the asset growth decreases profitability, leading to a decline in
the financial stability of IBs. This finding is consistent with
Table 7
Dynamic panel one-step system-GMM results using ROA as the variable.
Number of observations = 116 Number of groups = 5
Wald chi2 (12) = 341.38 Prob > chi2 = 0.000
Variables Coefficients Robust Standard Error z-stat P> |z|
Lagged ROA 0.1816199 0.061339 2.96 0.003**
SUKUK 5.72e-07 2.14e-07 2.68 0.007**
CAR 0.1131861 0.0204863 5.52 0.000**
AQ −0.0137377 0.0491483 −0.28 0.780
MER −0.0362544 0.0060652 −5.98 0.000**
LIQ −0.0366064 0.0070102 −5.22 0.000**
RISK 0.0404596 0.0063171 6.40 0.000**
SIZE −2.04e-08 8.48e-09 −2.41 0.016*
GDP −5.07e-08 2.72e-08 −1.86 0.062
CPI 0.0000429 0.0000152 2.83 0.005**
TRADE −0.011057 0.0058737 −1.88 0.060
GFCF 9.64e-08 8.70e-08 1.11 0.268
Constant 0.0043675 0.0074142 0.59 0.556
Tests of serial correlation
Arellano–Bond test for AR
(1)
z-stat = −1.42 P> |z| = 0.156
Arellano–Bond test for AR
(2)
z-stat = 0.83 P> |z| = 0.405
Instruments' total validity test
Sargan test Chi2 (58) = 52.92 Pr > chi2 = 0.664
Robustness test
Hansen test Chi2 (58) = 0.00 Pr > chi2 = 1.000
Note: * 0.05 significance, ** 0.01 significance.
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11. Athanasoglou et al. (2008), who state that larger banks do not
achieve higher earnings and more stability than small banks.
Although in Table 7 the macroeconomic variables retain the
same signs, except for the effect of TRADE on the financial
stability of IBs, which turns negative and lacks statistical sig-
nificance, whereas in Table 6 it was positive with no statistical
significance. Following the above-mentioned analysis by
Adeel-Farooq et al. (2017) and Rashid et al. (2017) about trade
openness and financial stability, the empirical results of the
robustness test indicate that trade openness is not sufficient for
maintaining financial liberalization policies, which improve
competition in the IB sector, leading greater financial stability.
Moreover, Table 7 shows that the estimation model for the
robustness check is free of serial correlation (first-order AR (1)
with Pr > Z = 0.156, and second-order AR (2) with
Pr > Z = 0.405). Also, all instruments in the GMM estimation
are robust, valid, and exogenous ( p-value is insignificant:
Pr > chi2 = 0.664), whereas the Hansen test p-value is highly
insignificant (Pr > Chi2 = 1.00), which shows that the esti-
mation model is robust and unbiased. Consequently, the
empirical outcomes in the robustness check are robustly un-
biased and accurate.
In general, the estimated results from the robustness test
show the absence of structural change from the majority of the
earlier empirical results based on using the Z-score as an in-
dicator of the financial stability of IBs. Thus, the robustness test
confirms H1.
5. Conclusion
This paper empirically investigates the effect of sukuk
market development on IBs' financial stability, based on a
sample of the Islamic financial institutions operating in
Malaysia, Saudi Arabia, Indonesia, Turkey, and Brunei over the
period 2013Q4–2019Q4. We posit two opposing hypotheses.
H1 predicts a positive link between sukuk market development
on IBs' financial stability, whereas H2 expects a negative link.
Using dynamic panel one-step system-GMM estimation, the
estimated results support H1, which states that the development
of the sukuk markets has a positive effect on IBs’ financial
stability. The empirical results show that the sukuk markets are
complementary to the IBs and maintain financial stability
among IBs, which results in decreasing risk-taking by these
banks. Moreover, to the best of our knowledge, of all the
existing studies on the link between IBs and sukuk market
development, this paper is the first that finds a complementarity
effect of sukuk market development on IBs. Therefore, this
study contributes to the literature with new evidence.
The conclusions of this study are critical for financial
regulators and policy makers. Policy makers and authorities in
developing economies are unquestionably committed to
developing their finance and banking systems and making
them more resilient to external shocks. Developed sukuk
markets are becoming more widely recognized as an impor-
tant component of stable financial systems. Accordingly, this
study demonstrates that sukuk market development is com-
plementary to IBs and promotes stability and reduces riskiness
at IBs. Consequently, IBs support sukuk market development.
Financial regulators and policy makers in emerging econo-
mies should look for measures to encourage the growth of
sukuk markets, while also supporting cooperation that in-
creases complementary between the main sectors in the Is-
lamic finance industry: sukuk markets and IBs.
This paper has significant implications for IBs managers,
regulators, and investors. Based on the existence of the
complementarity effect of sukuk market development on IBs'
financial stability, this paper recommends that regulators
facilitate the issuance of sukuk by IBs to contribute to the
development of the sukuk market in the framework of a
complementarity link. In addition, this paper suggests that
regulators allow IBs to issue sukuk, especially Tier 1 sukuk
with loss-absorption features to enable IBs to engage in riskier
activities, which usually have larger profits, strengthening
financial stability. Additionally, simulating Basel III capitali-
zation to enhance the financial stability of financial institutions,
IBs' financial stability could be improved more directly by
issuing Tier 1 sukuk, which is reclassified by IFSB-15 as
desirable and less expensive than ordinary sukuk. Therefore, a
practical implication is that in line with the recommendation of
the IFSB (2013), which mirrors the Basel III requirements, IBs
should expand the issuance of Tier 1 sukuk capital, especially
ijarah and mudarabah Tier 1, which contribute to the devel-
opment of sukuk markets and enhance IBs' capacity to access
investment opportunities and strengthen their financial stabil-
ity, as stated by IFSB (2013) and IIFM (2021). Moreover, this
study recommends that investors invest in sukuk issued by IBs,
particularly Tier 1 sukuk, because of their high level of loss
absorbency with a desirable capital adequacy rate.
Funding
We declare that no funds, grants, or other support were
received to carry out this study.
Conflict of interest
None.
Acknowledgments
We are thankful to Prof. Dr. Warda Moussaoui for her
valuable information and continuous encouragement. We are
grateful to the editor, Professor Ali Kutan, and anonymous
referees for their valuable comments. All errors remain our
responsibility.
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