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Borsa Istanbul Review 22-6 (2022) 1251–1259
http://www.elsevier.com/journals/borsa-istanbul-review/2214-8450

Full Length Article

Concentration, capital, and bank stability in emerging and developing

countries
Son Tran a,b,*, Dat Nguyen a,b, Liem Nguyen a,b
a
University of Economics and Law, Ho Chi Minh City, Vietnam
b
Vietnam National University, Ho Chi Minh City, Vietnam
Received 21 April 2022; revised 30 August 2022; accepted 30 August 2022
Available online 6 September 2022

Abstract

This study uses aggregate data from 133 developing and emerging markets from 2002 to 2020 and investigates how market concentration and
capital are related to bank stability. We find that banks operating in more concentrated banking markets tend to be more stable than those operating
in a less concentrated market, which supports the concentration–stability hypothesis. Furthermore, the research reveals that capital significantly
influences banks’ financial stability in developing and emerging markets, highlighting the role of capital as a significant financing source in these
countries. Importantly, evidence shows that market concentration might enhance the positive effect of capital on bank stability. The findings
should be important for policymakers, bank managers, and fund providers for banks to uphold bank stability in the less developed financial
markets. These findings are robust to regression models that include alternative bank stability and market concentration proxies.
Copyright © 2022 Borsa İstanbul Anonim Şirketi. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/).

JEL classification: G21; L22; L25; G33

Keywords: Market concentration; Bank capital; Bank stability; Emerging and developing economies

1. Introduction Furthermore, theories suggest two possible impacts of capital

on bank stability. On the one hand, higher bank capital might
In the context of the increased global integration and in- curtail risky behaviors and help address the moral hazard
ternational and domestic competition among banks, regulations problem associated with deposit insurance, i.e., the equity-at-
could strike a balance between competition and stability for risk effect (Furlong & Keeley, 1990). On the other hand,
banks to grow sustainably (Danisman & Demirel, 2019). more stringent capital requirements could lower banks’ fran-
Following the 2008 global financial crisis, bank regulators chise values, thus encouraging them to take on risky activities
introduced stricter regulatory measures to make the banking (Hellmann et al., 2000).
system more resilient and stable, and capital adequacy re- Besides the complexity of the potential impacts of bank
quirements have been an essential item on the agenda. Even capital, the superior relevance of bank capital in developing
though stricter capital regulation is expected to strengthen the and emerging markets further encourages us to research the
resilience or stability of the banking sector, empirical evidence link between bank capital and stability. First, banks in devel-
tends to be contentious (Klomp & de Haan, 2015). oped markets are less likely to alter loan supply following
changes in monetary policies because they tend to have a wider
variety of financial instruments and financing sources
* Corresponding author. University of Economics and Law, Ho Chi Minh (Sanfilippo–Azofra et al., 2018). In contrast, banks in less
City, Vietnam. developed countries rely heavily on deposits as the chief
E-mail address: sonth@uel.edu.vn (S. Tran). funding source, as they struggle to obtain funds from other
Peer review under responsibility of Borsa İstanbul Anonim Şirketi.

https://doi.org/10.1016/j.bir.2022.08.012
2214-8450/Copyright © 2022 Borsa İstanbul Anonim Şirketi. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://
creativecommons.org/licenses/by-nc-nd/4.0/).
S. Tran, D. Nguyen and L. Nguyen _
Borsa Istanbul Review 22-6 (2022) 1251–1259

sources (Hou & Wang, 2013). Claessens and Yurtoglu (2013) direct measure of market conduct (Calice et al., 2021; Leon,
also argue that firms in less developed countries suffer from 2015; Schaeck & Cihak, 2012).
poor access to financing and problematic corporate governance Until now, few studies have investigated the interaction effect
(highly concentrated ownership structures and low institutional of competition and capital on bank stability (Agoraki et al., 2011;
ownership) that cannot effectively support the supervision of Beck et al., 2013; Danisman et al., 2019; Mateev et al., 2022).
firm management, thwarting firms' ability to obtain external Still, no studies have focused on the interaction of concentration
financing. Moreover, Klomp and de Haan (2015) document and capital on bank stability, while the nature of concentration is
that, among the regulations imposed, only capital-related re- not the same as that of competition in the banking markets.
quirements can reduce bank risk in 94 developing and Studying this link on a sample of developing and emerging
emerging markets. These effectively prove bank capital's markets is highly relevant since banks in these markets are
importance and relevance to bank stability in less developed financially constrained, and capital is essential for financial sta-
countries. bility. Meanwhile, concentration might affect stability differently
In addition to capital-related requirements and capital build- in less developed markets due to varying governance, institutional
ups among banks, consolidations and mergers have led to quality, and regulatory monitoring (Claessens & Yurtoglu, 2013).
higher concentration ratios across many countries in the last As concentration can reduce risk and improve profitability, banks
decade. Theoretically, two contrasting views exist regarding with higher capital are incentivized to protect their equity by
the impact of market concentration on bank stability: (i) the taking less risk. Furthermore, higher concentration and capital
concentration–stability and (ii) the concentration–fragility build-ups might effectively establish entry barriers for market
views. The concentration–stability hypothesis argues that a participants, further improving the profitability of the incumbent
high concentration level in the banking sector reduces banks’ banks. Therefore, we argue that the interaction between market
incentives to take on excessive risk. According to this view, concentration and capital may consolidate bank stability, which
larger banks in more concentrated areas can attain more market remains an interesting research hypothesis to be tested for a
power and healthier profitability, discouraging banks from sample of developing and emerging markets.
engaging in more risky operations and improving financial Our study adds to the existing literature from many per-
stability (Allen & Gale, 2004; Keely, 1990). Conversely, the spectives. First, we use the latest recent aggregate dataset,
concentration–fragility theory claims that greater concentration covering a sample of 133 developing and emerging countries
leads to higher market power, enabling banks to raise lending from 2002 to 2020, with the country classification scheme of
rates and, as a result, making the banking sector riskier (Boyd IMF based on a combination of income, financial market, and
& De Nicolo, 2005; Kasman & Kasman, 2015; Schaeck et al., intermediation development (Nielsen, 2011). Using this
2009; Uhde & Heimeshoff, 2009). Interestingly, Khan et al. aggregate data enables the generalizability and relevance of the
(2017) offer some evidence on the quiet-life hypothesis, research findings to emerging and developing markets. Second
which states that banks in concentrated markets lack incentives and importantly, according to our literature review, this is the
to operate efficiently. first study investigating the role of market structure and capital
Unfortunately, the empirical literature provides indecisive and their interaction toward bank stability, at least for a large
evidence on this. Beck et al. (2006) suggest that higher con- sample of developing and emerging countries. As mentioned
centration leads to banks adopting a diversification strategy, earlier, we cannot generalize from previous research on the link
increasing sector stability. As banks are larger and more between competition, capital, and bank stability as market
diversified, they could have more incentives to engage in risky concentration tends to be a poor proxy of competition. Our
activities (Boyd et al., 2005). In addition, larger banks could findings would be valuable and relevant to policymakers since
suffer from internal inefficiencies and operations-related risks banking systems in less developed markets are generally less
(Laeven & Levine, 2007). stable. Surprisingly, no studies have exploited this context.
Many studies examine bank competition or its effect on Third, this is a response to the call for more studies on the link
different aspects of bank operations and stability (Agoraki between market concentration and bank stability by Calice
et al., 2011; Beck et al., 2013; Danisman & Demirel, 2019; et al. (2021); conversely, voluminous content exists on the
Khan et al., 2016; Mateev et al., 2022). Still, as Calice et al. nexus between competition and bank stability. Fourth, we use
(2021) emphasized, even though numerous studies have both proxies of capital (equity and capital risk-weighted asset)
examined the relationship between competition and bank sta- and both types of risks (Z-score and nonperforming loan) to
bility, the effect of concentration on stability has received much ascertain our findings. Finally and practically, as both bank
less attention. Previous studies that associate concentration concentration and capital requirements are the current trends, it
with competition might be subject to fundamental flaws, as is imperative and relevant to investigate the interaction of these
concentration is a poor measure of market competition (Beck two factors on bank stability.
et al., 2006; Calice et al., 2021; Leon, 2015). Etudaiye- The remainder of our study is as follows. Section 2 presents
Muhtar and Abdul-Baki (2021) find that concentration and relevant theories and studies, and Section 3 presents the
Lerner index (a widely used proxy of competition) have research methodology, covering estimation methods, models,
different impacts on African bank capital. Competition and and variable construction. Section 4 provides the estimation
concentration are not the same concepts since concentration is results and robustness checks, and Section 5 concludes the
meant to gage market structure, while competition is a more study.
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Borsa Istanbul Review 22-6 (2022) 1251–1259

2. Literature review proxy for competition (Beck et al., 2006; Calice et al., 2021;
Leon, 2015).
2.1. Market concentration and bank stability
2.2. Bank capital and bank stability
Two perspectives exist regarding the potential relationships
between market concentration and bank stability: Stricter capital requirements are essential in ensuring that
concentration–stability and concentration–fragility (Uhde & banks can obtain adequate liquidity and sustain unplanned
Heimeshoff, 2009). losses. Theoretical studies emphasize the significance of moral
Advocates of the concentration–stability viewpoint argue hazard issues in lending and investing activities; higher capital
that larger banks in concentrated banking sectors can amelio- leads banks to adopt less risky activities because risk-shifting
rate financial fragility through several channels. (i) It is more incentives are minimized (Calomiris & Kahn, 1991; Freixas
effective for larger banks to enjoy higher profitability and & Rochet, 2008). Higher capitalization necessitates more effi-
market power, allowing healthier “capital buffers,” thus mak- cient loan monitoring and better credit risk management (Coval
ing them less vulnerable to liquidity and macroeconomic & Thakor, 2005; Allen et al., 2011; Mehran & Thakor, 2011).
shocks. (ii) Larger banks may have more conditions to boost Increased capital allows banks to build buffers, thus reducing
their charter value, dissuading bank executives from taking the risk of contagious defaults caused by systemic risks/mac-
excessive risks. (iii) It is easier to supervise fewer larger banks roeconomic shocks (Kaufman & Scott, 2003).
in a highly concentrated market, resulting in an effective Laeven et al. (2016) examine the role of bank capital toward
intervention by supervisory authorities and, as a result, a lower systemic risk during the 2007–2009 global recession, finding
danger of system-wide contagion. (iv) Larger banks can that systemic risk and bank capital are inversely related. Berger
diversify loan-portfolio risks more economically and and Bouwman (2013) show that capitalization enhances the
geographically through cross-border activity due to greater survival chances of banks in the US. Godlewski (2005), Lee
economies of scale and scope. and Hsieh (2013), Tan and Floros (2013), Hua (2011), Maji
Using data from 69 countries from 1980 to 1997, Beck et al. and Hazarika (2016), Ding and Sickles (2018), and Jiang
(2006) offer compelling evidence suggesting that financial et al. (2020) also find an inverse relationship between risk
crises occur less often in a concentrated banking sector. and bank capital.
Hellmann et al. (2000) show that market power helps banks In contrast, increasing capital may reduce the stability of
maintain their brand value, become more conservative, and banking systems. More capital can increase investment risk and
involve less risk-taking. Market power is beneficial since it instability (Koehn & Santomero, 1980). Besanko and Kanatas
lowers informational asymmetries and enhances the credit (1996) argue that insiders decrease management effort when
rating of bank loans (Petersen & Rajan, 1995). According to their ownership is diluted as capital increases. Empirically,
Allen and Gale (2004), banks’ capacity to benefit from Jokipii and Milne (2011), Athanasoglou (2011), and Teply and
increased revenues makes capital degradation unlikely and Matejašák (2007) support a positive relationship between bank
strengthens the financial system. risk and capital. More recently, Ugwuanyi (2015) documented
Conversely, proponents of the concentration–fragility a positive correlation between risk and capital in Nigeria in the
viewpoint contend that larger banks in a concentrated market post-crisis period, and Mateev et al. (2022) found a positive
undermine stability through three channels. (i) Larger banks are link between capital and risk in the Middle East and North
considered “too-big-to-fail” organizations likely to receive Africa (MENA) region.
government bailouts, creating conditions for moral hazard is-
sues. (ii) Due to enhanced power associated with larger market 2.3. Association between market concentration, capital,
shares, larger banks can impose exorbitant loan interest rates, and bank stability
which may lead to borrowers undertaking risky investments to
afford such rates, resulting in greater default risks (Mirzaei Etudaiye-Muhtar and Abdul-Baki (2021) and Schaeck and
et al., 2013). (iii) Operating efficiency may deteriorate due to Cihak (2012) support the findings of Allen et al. (2011), con-
an enlarged operating scale, resulting in high operational risk. firming that a competitive environment increases banks’
Nicoló et al. (2004) consistently find that higher concen- incentive to maintain higher bank capital, which in turn in-
tration is connected with banking sector instability in their creases bank stability. Danisman and Demirel (2019) find that
analysis of financial corporations and banks in 90 countries. in developed countries, capital decreases bank risk, especially
Uhde and Heimeshoff (2009) document similar results for for banks with higher market power. Danisman and Demirel
banks in Europe. Fu et al. (2014) and Kasman and Kasman (2019) argue that banks with higher power can afford not to
(2015) also find that a more concentrated market is more vol- take on more risks to satisfy the increased capital requirements.
atile for banks in 14 Asian-Pacific economies and Turkey, As concentration can reduce risk and improve profitability,
respectively. banks with higher capital have more incentive to protect their
Even though numerous papers investigate the link between equity by operating at lower risk levels. Although concentra-
competition and bank stability, the results should not be tion is not a decent measure of competition, a higher concen-
considered comparable to that between concentration and sta- tration can, to some extent, infer higher market power and less
bility because concentration is not supposed to be a decent competition; thus, banks do not have to keep high capital. As
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capital increases, banks in a concentrated market should have lnZscorei,t = β + β1 lnZscorei,t−1 + β2 MSi,t + β3 MSi,t *Capitali,t
more incentives to protect the capital and involve fewer risk-
+ β4 Control variablesi,t
taking activities (equity-at-risk effect).
Furthermore, higher concentration and capital might effec- (2)
tively establish barriers for new entries, further improving the 3.2.1. lnZscore
profitability and lowering the risk-taking activities of the The natural logarithm of the Z-score taken from the Global
incumbent banks. Higher concentration might allow better and Financial Development Database, is used to gage bank stabil-
more efficient monitoring of bank operations, which might ity, in line with previous studies (Lepetit et al., 2008; Stiroh &
prove convenient and meaningful in developing countries Rumble, 2006). A higher lnZscore indicates greater financial
without adequate institutions. Furthermore, bank capital is an stability and lower bank risk. The natural logarithm of the Z-
essential source of financing in less developed markets, so score is used to smooth the values of the otherwise significantly
banks in such markets should be more concerned about pro- skewed raw Z-score.
tecting this funding source. Therefore, we expect that with
more monitoring and bank CEOs’ incentives to protect capital 3.2.2. Market structure (MS)
in emerging and developing countries, the interaction between Market structure (MS) is employed to proxy for the market
the two factors should significantly reduce bank risk or enhance concentration (Berger et al., 2004; Calice et al., 2021; Mirzaei
bank stability. et al., 2013). In line with Cihak et al. (2012), we use CR3 (the
proportion of total assets of the three largest banks divided by
3. Data and research methodology total assets of all commercial banks in a country) from Global
Financial Development Database. A higher CR3 indicates a
3.1. Data higher banking market concentration.

The sample consists of 133 developing and emerging 3.2.3. Capital

countries from 2002 to 2020. We collect our data at the We use two ratios to proxy for bank capital, including the
aggregate level from several sources. The aggregate data on non-risk-based capital ratio (total equity to total assets [EQ-
banking system characteristics and macroeconomic variables UITY]) and bank regulatory capital to risk-weighted assets
are retrieved from Global Financial Development Database (CAR). The variables are in line with many studies (Abbas
(Cihak et al., 2012) and the World Development Indicator et al., 2021; Anginer et al., 2021; Ashraf et al., 2020; Jiang
dataset (World Bank, 2021). We select the period under et al., 2020; Mateev et al., 2022; Schaeck & Cihak, 2012).
investigation based on data availability.
3.3. Control variables
3.2. Methodology
NonII accounts for the income diversification impact,
calculated as the ratio of non-interest income to total income
The generalized method of moments (GMM) estimator is
(Le, 2021; Stiroh & Rumble, 2006).
used to deal with the two primary problems of heterogeneity
We utilize the costs-to-income ratio to account for bank
and endogeneity (Arellano, 2002). Notably, the GMM esti-
efficiency (EFFICIENCY), following Khediri and Khedhiri
mator produces consistent estimates in the presence of the
(2009) and Dietrich and Wanzenried (2011).
unobserved heterogeneity and the dynamics of the dependent
A commercial bank's net interest margin (NIM) is used to
variable. The System GMM estimator employs lagged values
control the effect of profitability on lending and investing
of explained variables and potentially endogenous regressors to
(Wang & Lin, 2021).
tackle endogeneity. Autocorrelation (AR) tests and the over-
The ratio of bank liquid reserves to bank assets calculates
identifying constraints test ensure the validity of the in-
liquidity (LIQ), which refers to the bank's capacity to meet short-
struments used (Hansen, 1982).
term financial obligations without selling its assets at a loss. Due
We propose the following dynamic model of bank financial
to a liquidity shortfall, some financial institutions failed during
stability to test hypotheses about the individual effects of
the financial crisis. According to Cole and White (2012), Berger
market concentration (MS) and bank capital on bank stability:
and Bouwman (2013), and DeYoung and Torna (2013), banks
lnZscorei,t = α + α1 lnZscorei,t−1 + α2 MSi,t + α3 Capitali,t with higher liquid assets are less prone to collapses.
Gross domestic product (GDP) growth rates account for the
+ α4 Control variablesi,t (1) influence of economic growth on bank stability. The inflation
After that, we further introduce the interaction term rate (INF) is used to control the impact of inflation.
(MS*Capital) to investigate the role of the interaction between
market structure and bank capital toward bank stability:1 4. Empirical results

4.1. Descriptive statistics

1
Nonetheless, when estimating Eq. (2), we must remove Capital variable due
to the multicollinearity problem (evident through the Variance Inflation Factor Table 1 presents descriptive statistics of the model's vari-
test [not tabulated here]). ables. The mean of bank stability (lnZSCORE) is 2.601.
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Table 1 with better stability in the financial sector, providing support to

Descriptive statistics. the concentration–stability view. This finding is consistent with
Variable Proxy Obs Mean Std. Dev. Min Max previous studies, including Beck et al. (2006), Maudos and De
lnZscore Bank stability 2138 2.601 0.623 0.527 3.806 Guevara (2004), Schaeck et al. (2009), and Hamid (2017);
CR3 Market concentration 2158 70.074 20.269 23.452 100 however, this finding contradicts Saif–Alyousfi et al. (2020) in
CR5 Market concentration 1777 80.375 16.179 34.403 100 six Gulf Cooperation Council nations, Fu et al. (2014) in the
EQUITY Total equity to total 1276 11.330 3.878 1.490 30.352
assets
Asia Pacific, and Kasman and Kasman (2015) in Turkey. As
CAR Bank regulatory 1330 17.690 5.426 1.754 46.820 our sample focuses on emerging and developing markets, our
capital to results support the positive attributes of banking concentration
risk-weighted assets for those countries: better monitoring and higher charter value
NonII Income 2097 37.088 13.478 10.119 78.898 that reduce the incentives to take unnecessary risks.
diversification
EFFICIENCY Bank operating 2096 55.699 14.208 18.468 96.622
Concerning bank capital, we document a statistically sig-
efficiency nificant and positive relationship between bank capitalization
NIM Bank profitability 2077 5.413 2.729 0.619 15.355 and lnZscore. The result agrees with the moral hazard hy-
LIQ Bank liquidity 2130 36.741 19.189 6.706 148.501 pothesis and previous studies (Coval & Thakor, 2005; Allen
GDP Economic growth 2508 18.374 10.353 0.36 34.78 et al., 2011; Jiang et al., 2020; Lee & Hsieh, 2013; Mehran
INF Inflation 2508 15.894 9.928 0.36 31.79
& Thakor, 2011) while contradicting Mateev et al. (2022) in
Note(s): All variables have been winsorized at the 1% and 99% levels (except the MENA region.
for macroeconomic variables).
Columns (2) and (4) of Table 3 show that the interaction terms
between market concentration and capital are positive and sig-
Furthermore, the average values of CR3 and CR5 are 70.07 and nificant, suggesting that a more concentrated market facilitates a
80.37 percent, respectively. These values are relatively high, more positive impact of capital on bank stability in developing
indicating high levels of bank concentration in developing and and emerging countries. This supports the view that, as con-
emerging markets. EQUITY and CAR variables have average centration can increase banks' market power, reduce risk and
values of 11.33 and 11.69 percent, respectively, indicating that improve profitability, banks with higher capital have more
bank capital is about one-tenth of total assets. incentive to protect their capital by taking less risk. Furthermore,
Table 2 displays pair-wise correlation coefficients. Market higher concentration and capital might make it more difficult for
concentration is positively related to bank stability, and bank newcomers to enter the market, thus enhancing profitability and
capital is negatively associated with bank stability. lowering the risk-taking activities of the incumbent banks. For
developing and emerging markets, monitoring bank operations
4.2. Results and discussion and capital should be two critical factors to enhance bank sta-
bility. All of the above arguments point to a significantly positive
Table 3 presents the estimation results. The lagged depen- interaction term coefficient in our case. In Columns (5) and (6),
dent variable (lnZscoret−1) has significant coefficients in all we also control for the global financial crisis by including year
models, indicating that the use of dynamic models is appro- dummies for 2007, 2008, and 2009. The sign and significance of
priate. Furthermore, the p-values of both autocorrelation and the interaction term remain unchanged. Interestingly, our study's
overidentification tests are larger than five percent, indicating findings are consistent with the results for banks from 37 African
that the validity of the set of instruments and the estimates are countries found in Oduor et al. (2017); higher capital re-
reliable. quirements tend to benefit only large banks.
Market concentration (CR3) is positively correlated with The results for the control variables are in line with our
lnZscore, implying that increased concentration is associated expectations. Income diversification (NonII) positively impacts

Table 2
The correlation matrix of variables.
lnZscore CR3 CR5 EQUITY CAR NonII EFFICIENCY NIM LIQ GDP INF
lnZscore 1.000
CR3 0.034 1.000
CR5 0.047 0.946 1.000
EQUITY −0.069 0.008 0.016 1.000
CAR −0.104 0.082 0.107 0.698 1.000
NonII −0.216 0.016 −0.008 0.155 0.169 1.000
EFFICIENCY −0.141 0.027 −0.015 0.107 0.094 0.333 1.000
NIM −0.033 0.070 0.073 0.373 0.344 −0.048 0.279 1.000
LIQ −0.058 0.020 −0.008 0.168 0.288 0.325 0.168 0.146 1.000
GDP −0.014 −0.056 −0.078 −0.035 −0.002 −0.009 −0.035 0.040 0.007 1.000
INF −0.030 −0.012 −0.003 −0.068 −0.022 0.012 0.074 0.149 0.044 0.064 1.000
Source: author's calculation from research dataset.

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Table 3
Regression estimates.
π lnZSCORE (1) lnZSCORE (2) lnZSCORE (3) lnZSCORE (4) lnZSCORE (5) lnZSCORE (6)
πt−1 0.412*** (0.037) 0.361*** (0.011) 0.785*** (0.050) 0.266*** (0.011) 0.039*** (0.012) 0.284*** (0.020)
CR3 0.002* (0.001) 0.002*** (0.001) 0.001* (0.001) 0.001* (0.000) 0.003*** (0.001) 0.002*** (0.001)
EQUITY 0.035*** (0.006)
CAR 0.006** (0.002)
CR3*EQUITY 0.000*** (0.000) 0.000*** (0.000)
CR3*CAR 0.000*** (0.000) 0.000** (0.000)
NonII 0.004*** (0.001) 0.003*** (0.001) 0.008*** (0.001) 0.003*** (0.000) 0.002*** (0.001) 0.003*** (0.000)
EFFICIENCY −0.008** (0.001) −0.006** (0.000) −0.010*** (0.001) −0.007*** (0.000) −0.007*** (0.000) −0.008*** (0.000)
NIM 0.042*** (0.005) 0.030*** (0.002) 0.069*** (0.005) 0.039*** (0.002) 0.031*** (0.002) 0.037*** (0.002)
LIQUIDITY −0.001 (0.001) −0.001** (0.000) 0.002*** (0.000) −0.001*** (0.000) −0.001*** (0.000) −0.003*** (0.000)
GDP −0.000 (0.000) −0.000 (0.000) −0.000 (0.000) −0.000 (0.000) −0.000 (0.000) −0.000 (0.000)
INF 0.000 (0.001) −0.000 (0.000) −0.000 (0.000) −0.000 (0.000) −0.000 (0.000) −0.000 (0.000)
Constant 1.224*** (0.190) 1.570*** (0.063) 0.258 (0.168) 1.989*** (0.070) 1.581*** (0.053) 1.926*** (0.076)
CRISIS YEAR DUMMY YES YES
No of Obs 1090 1090 1145 1145 1090 1145
No of Groups 88 88 90 90 88 90
AR1 test (p-value) 0.010 0.015 0.013 0.021 0.014 0.019
AR2 test (p-value) 0.143 0.124 0.295 0.146 0.121 0.165
Hansen test (p-value) 0.413 0.466 0.472 0.143 0.315 0.344
Note: Numbers in parentheses are standard errors. *, **, and *** indicate significance at 10%, 5%, and 1%.

the lnZscore, meaning that more income diversification enables 4.3.2. Alternative proxy of market concentration
greater bank stability or lower bank risk. The finding is We use the 5-market concentration (CR5) variable (the
consistent with Markowitz (1968)'s Portfolio theory. The concentration of assets held by the five largest banks for each
expense-to-income ratio (EFFICIENCY) is significant and country) to test whether market concentration shapes bank
negatively affects lnZscore, meaning that a higher bank stability in developing and emerging countries (Table 5). The
expense-to-income ratio is linked to lower profitability and less findings are consistent as the variables of interest remain sig-
stable banking (Hamid, 2017). The association between NIM nificant and maintain their signs. The CR5 and capital variables
and lnZscore is strong and positive, implying that as com- show a positive association with bank stability, in line with the
mercial bank profitability rises, so does bank stability (Wang & above results (in Table 3), suggesting that a less competitive
Lin, 2021). Furthermore, LIQUIDITY negatively affects market and higher capital can facilitate the banking sector's
lnZscore, suggesting that the higher the liquidity ratio, the stability in developing and emerging countries. Importantly,
bigger the risks the bank faces (Le, 2021). Columns (2) and (4) of Table 5 show that the coefficients of
interaction terms between market concentration and capital are
4.3. Robustness check positive and significant; thus, it supports our abovementioned
results.
4.3.1. Alternative proxy of bank stability
Additional assessments are performed to ensure the 5. Conclusion
robustness of our findings concerning the relationship between
market concentration, capital, and bank stability. We use the Following turbulences in banking systems and increased
nonperforming loans ratio to total loans (NPL) as an additional competition from the unavoidable global integration, several
proxy of bank stability. This proxy measures asset quality and regulatory capital-related requirements and mergers and ac-
higher values suggest a higher level of risk. quisitions have emerged, leading to more market concentration
Table 4 shows that MS and bank capital are negatively to enhance the resilience of banks across the globe. It is highly
linked to bank risk. Additionally, the coefficients of the inter- relevant to examine the roles of capital and concentration on
action between MS and capital are significant and negative, the stability of banks as intended, especially in developing and
suggesting that a more concentrated market produces a stronger emerging markets. This is because banks in less developed
incentive for banks to reduce risk when capital increases. In markets have few financing options; they lack efficient
Columns (5) and (6), we also control for the global financial corporate governance mechanisms, and low institutional qual-
crisis by including year dummies for 2007, 2008, and 2009. ities might further hinder financial development in these mar-
The sign and significance of the interaction term remain un- kets, endangering banking stability. It is also essential to
changed. Therefore, the results are highly consistent with those investigate the combined effect of these two factors as they are
in Table 3. occurring simultaneously; however, no studies have examined
In summary, through robustness analysis, the NPL model this link, at least for developing and emerging countries.
provides additional support to the findings of our lnZscore This study uses aggregate data of banking systems in 133
model. developing and emerging markets from 2002 to 2020 to
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Table 4
Robustness test using the nonperforming loans (NPL) as a dependent variable.
π NPL (1) NPL (2) NPL (3) NPL (4) NPL (5) NPL (6)
πt−1 0.593*** (0.034) 0.644*** (0.037) 0.736*** (0.005) 0.723*** (0.025) 0.752*** (0.013) 0.691*** (0.025)
CR3 −0.100*** (0.027) −0.069** (0.032) −0.015*** (0.002) 0.015 (0.017) 0.005 (0.011) 0.021 (0.019)
EQUITY −0.380*** (0.132)
CAR −0.097*** (0.012)
CR3*EQUITY −0.002* (0.001) −0.002* (0.001)
CR3*CAR −0.002*** (0.001) −0.003*** (0.001)
NonII 0.035 (0.027) 0.053*** (0.017) −0.001 (0.003) 0.008 (0.013) −0.050*** (0.000) 0.007 (0.014)
EFFICIENCY −0.067* (0.037) −0.040*** (0.015) 0.006** (0.003) −0.065*** (0.013) 0.012 (0.012) −0.075*** (0.014)
NIM 0.610*** (0.169) 0.886*** (0.134) −0.057** (0.021) 0.214** (0.086) −0.062 (0.075) 0.239*** (0.091)
LIQUIDITY −0.032 (0.020) −0.012 (0.010) −0.028*** (0.004) −0.032** (0.015) −0.004 (0.007) −0.026 (0.016)
GDP −0.000*** (0.000) −0.000*** (0.000) −0.000*** (0.000) −0.000*** (0.000) −0.000*** (0.000) −0.000*** (0.000)
INF −0.000** (0.000) −0.000*** (0.000) −0.000*** (0.000) −0.000 (0.000) −0.000* (0.000) −0.000 (0.000)
Constant 14.631*** (3.534) 5.948*** (1.590) 6.127*** (0.236) 7.585*** (1.318) 4.323*** (0.693) 7.643*** (1.357)
CRISIS YEAR DUMMY YES YES
No. of Obs 1051 1051 1102 1102 1051 1102
No. of Groups 88 88 90 90 88 90
AR1 test (p-value) 0.026 0.010 0.033 0.026 0.029 0.026
AR2 test (p-value) 0.219 0.232 0.051 0.060 0.100 0.102
Hansen test (p-value) 0.452 0.596 0.956 0.579 0.436 0.551
Note: Numbers in parentheses are standard errors. *, **, and *** indicate significance at 10%, 5%, and 1%.

Table 5
Robustness test using the alternative of bank concentration.
π lnZSCORE (1) lnZSCORE (2) lnZSCORE (3) lnZSCORE (4)
πt−1 0.433*** (0.104) 0.365*** (0.015) 0.931*** (0.019) 0.973*** (0.021)
CR5 0.004* (0.002) 0.001*** (0.000) 0.003*** (0.000) 0.002*** (0.000)
EQUITY 0.037*** (0.011)
CAR 0.002* (0.001)
CR5*EQUITY 0.000*** (0.000)
CR5*CAR 0.000*** (0.000)
NonII 0.001 (0.002) 0.001*** (0.000) 0.005** (0.000) 0.006*** (0.000)
EFFICIENCY −0.009*** (0.002) −0.010*** (0.000) −0.006*** (0.000) −0.006*** (0.000)
NIM 0.004 (0.013) 0.035*** (0.001) 0.031*** (0.002) 0.030*** (0.002)
LIQUIDITY −0.002 (0.001) 0.001 (0.000) 0.000** (0.000) −0.000 (0.000)
GDP 0.000 (0.000) 0.000 (0.000) 0.000*** (0.000) 0.000*** (0.000)
INF 0.000* (0.000) −0.000** (0.000) 0.000*** (0.000) 0.000*** (0.000)
Constant 1.272*** (0.413) 1.845*** (0.066) −0.146* (0.081) −0.252*** (0.068)
No. of Obs 983 983 1035 1035
No. of Groups 81 81 82 82
AR1 test (p-value) 0.020 0.030 0.013 0.013
AR2 test (p-value) 0.244 0.104 0.201 0.206
Hansen test (p-value) 0.705 0.492 0.495 0.219
Note: Numbers in parentheses are standard errors. *, **, and *** indicate significance at 10%, 5%, and 1%.

empirically examine how market concentration and capital are models that include alternative stability and market concen-
related to a bank's financial stability. tration proxies.
First, the results show that bank stability is related to market Our findings offer several important implications for stake-
concentration. The findings support the concentration–stability holders on bank stability. For providers of funding for banks, it
hypothesis, suggesting that banks operating in a more is suggested that banks with higher capital have fewer incentives
concentrated banking market tend to be more stable. Second, to shirk or engage with asset substitution; this should make it
we find that bank capital significantly and positively impacts safer to lend to those banks. For bank managers, if their banks
bank stability in developing and emerging markets, empha- operate in a more concentrated market, this might allow them to
sizing the role of equity as a valuable funding source in the earn healthy profit with low risk, with no need to engage in
context of limited access to capital markets. Third, we argue unnecessary risk-taking activities. Notably, the incentive to
that market concentration and capital jointly affect bank sta- reduce risk and ensure the banking system's stability is stronger
bility. The findings reveal that a more concentrated market when both factors exist simultaneously. Therefore, policymakers
produces a more beneficial influence of capital on the bank's could leverage the evidence provided in this paper on matters
financial stability. These findings are robust to regression related to the combined effect of the two factors.

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Borsa Istanbul Review 22-6 (2022) 1251–1259

Our study could benefit from future research covering Boyd, J. H., & De Nicolo, G. (2005). The theory of bank risk taking and
developed and less developed markets when examining the competition revisited. The Journal of Finance, 60(3), 1329–1343. https://
doi.org/10.1111/j.1540-6261.2005.00763.x
same link. Future studies can uncover the specific regulatory Calice, P., Leonida, L., & Muzzupappa, E. (2021). Concentration-stability vs
requirements or institutional qualities to explain differences in concentration-fragility. New cross-country evidence. Journal of Interna-
the same link between developed and less developed markets; tional Financial Markets, Institutions and Money, 74, Article 101411.
this would significantly extend the literature and offer consid- https://doi.org/10.1016/j.intfin.2021.101411
erable implications for the relevant stakeholders. Calomiris, C. W., & Kahn, C. M. (1991). The role of demandable debt in
structuring optimal banking arrangements. The American Economic Re-
view, 497–513.
Funding Cihak, M., Demirgüç-Kunt, A., Feyen, E., & Levine, R. (2012). Benchmarking
financial systems around the world. The World Bank.
The research is funded by the University of Economics and Claessens, S., & Yurtoglu, B. (2013). Corporate governance in emerging
Law, Vietnam National University, Ho Chi Minh City, markets: A survey. Emerging Markets Review, 15(C), 1–33.
Cole, R. A., & White, L. J. (2012). Déjà vu all over again: The causes of US
Vietnam. commercial bank failures this time around. Journal of Financial Services
Research, 42(1–2), 5–29. https://doi.org/10.1007/s10693-011-0116-9
Conflict of interest Coval, J. D., & Thakor, A. V. (2005). Financial intermediation as a beliefs-
bridge between optimists and pessimists. Journal of Financial Eco-
None. nomics, 75(3), 535–569. https://doi.org/10.1016/j.jfineco.2004.02.005
Danisman, G. O., & Demirel, P. (2019). Bank risk-taking in developed coun-
tries: The influence of market power and bank regulations. Journal of In-
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