Index

Abstract

This study investigates the effects of environmental characteristics, namely the quality of country-level governance and domestic risk on Islamic banking capital decisions. To do so, this study selects 29 listed Islamic banks operating in Arab markets for the wide range between the 2003-2018 period by performing the System-GMM dynamic panel technique. The results underscore that higher country-level governance quality is linked with higher capital ratios and Islamic banks increase capital ratios specifically by improving methods of anti-corruption, political stability, government effectiveness, and legal systems. Moreover, the results reveal that Islamic banks increase capital ratios by the rise of a country’s vulnerability, particularly by increasing financial and economic risks. However, the results suggest that decreasing political risk also corresponds with higher capital ratios. Overall, the results confirm that environmental characteristics have a pivotal role in determining Islamic bank capital ratios. The results are robust and the findings of this study are likely to open new discussions in the banking literature.

Keywords: Capital ratios, Country-level governance, Domestic risk, Islamic banks.

JEL Classification: G10; G15; G21.

Received: 30 March 2022 / Revised: 26 May 2022 / Accepted: 10 May 2022/ Published: 28 June 2022

Contribution/ Originality

This study specifically contributes by examining the effect of environmental characteristics, namely country risk and governance quality on capital decisions of Islamic banks operating in Arab markets.

1. INTRODUCTION

Bank capital is considered the most significant factor in the performance of the banking sector, given the fact that it represents the strength of banks against risk (Kalifa & Bektaş, 2018). The works of Berger and Herring (1995) and Francis and Osborne (2010) argued that banks hold minimum amounts of capital since it acts as a buffer to absorb unexpected losses or unforeseen fluctuations in order to prevent any possible bank failure. Remarkably, since the sub-prime mortgage crisis in 2007 and 2008, bank capital has become a popular subject for regulatory bodies (e.g., Basel Committee on Banking Supervision) and has considerably triggered the interest of many researchers. For instance, the work of Barrios and Blanco (2003) showed that market discipline is the crucial factor that impacts capital ratios. Ariff (2008) suggested that profitability and size impact a bank’s capital ratio positively and negatively, respectively. Octavia and Brown (2010) found that macroeconomic factors significantly impact bank capital structures, particularly in emerging countries. Cohen and Scatigna (2016) and Valencia (2016) showed that banks’ capital ratios increased gradually after the financial crisis1 and higher uncertainty causes banks to keep the higher capital ratios to reduce the riskiness of their portfolios. Recently, a study by Anginer, Demirguc-Kunt, Huizinga, and Ma (2016) revealed that corporate governance plays a significant role in determining bank capital decisions. Bitar, Hassan, and Hippler (2018) also showed that improvements in the financial and economic environments and market discipline is linked with higher bank capitalization. Few studies have focused, however, on investigating the determinants of shariah-principles banks’ capital ratios (e.g., (Bitar et al., 2018; Chazi & Syed, 2010; Kalifa & Bektaş, 2018)). The Islamic financial industry has significantly grown in the last three decades, with a 15–20% annual growth rate in both Muslim and non-Muslim countries (Smolo & Hassan, 2010), and is expected to reach $6.5 trillion by 2020 (Mollah, Hassan, Al Farooque, & Mobarek, 2017). As approved by the Organization of Islamic Conference (OIC), Islamic banks are defined as a “financial institution whose status, rules and procedures expressly state its commitment to the principle of Islamic sharia and the abolishing of the receipt and payment of interest on any of its operations” (Ali & Sarkar, 1995). Farook, Kabir, and Lanis (2011) described Islamic banks as a financial intermediary that works under the controls of Islamic laws and shariah principles.

Islamic banks are a particular type of financial institution that operate differently and have unique micro-operating fundamentals by employing sharia principles and Islamic laws. Unlike the conventional banks’ interest-bearing modes, Islamic banks base investment and financing decisions on profit and loss sharing (PLS) and return-bearing contracts. Also, Islamic banks offer investment accounts based on partnership-basis contracts (e.g., Mudarabah) for whom investment depositors are considered quasi-equity holders. Islamic banks also develop different capital ratio guidelines concerning their nature and characteristics. Over time, regulatory organizations such as Accounting and Auditing Organization for Islamic Financial Institutions (AAOIFI) and the Islamic Financial Services Board (IFSB) have proposed different capital adequacy frameworks to increase the credibility and soundness of the Islamic financial system worldwide. 

By considering the unique characteristics of Islamic banks and the significant gap in research in the related literature, this study aims to answer the following questions:

- What are the main determinants of capital ratios in the shariah-based banks?
- How do the environmental characteristics impact Islamic bank capital decisions across countries?

To do so, 29 listed Islamic banks operating in Arab markets were selected for the wide range between the 2003-2018 period. This study sheds light on the following gaps by investigating the impact of bank-level variables (size, profitability, financial risk, credit risk, and default risk) on capital ratios. For testing the effect of environmental characteristics, this study considers the effect of country-level governance quality and its dimensions, namely corruption, government effectiveness, political stability, regulatory quality, rule of law, voice and accountability, and also domestic risk and its sub-indices, mainly financial, economic, and political risks. The findings of this study are likely to open new discussions in the banking literature.

The article is organized as follows. Section 2 describes data and methodology. Section 3 explains the results and discussions. Section 4 concludes the article.

2. DATA AND METHODOLOGY

2.1. Data and Descriptive Statistics

This study initially focuses on listed banks operating in Morgan Stanley Capital International (MSCI) Arabian Market Index countries (Saudi Arabia, Bahrain, Qatar, Kuwait, United Arabic Emirates, Egypt, Jordan, Morocco, Tunisia, and Lebanon). However, the countries of Morocco, Tunisia, and Lebanon are excluded as they do not offer Islamic banking systems, leaving the final sample list limits at 29 listed Islamic banks between the 2003- 2018 period.

Some studies revealed that bank-specific variables such as size, profitability, and risk (e.g., financial, credit) impact capital ratios significantly (e.g., (Anginer et al., 2016; Bitar & Tarazi, 2019; Mahdi & Abbes, 2018)). This study selected similar financial factors, and the annual data was collected from the Bankscope and the respective banks’ websites.

The findings of previous studies showed that the traditional macroeconomic determinants (e.g., inflation, GDP, exchange rate) and institutional development determinants (e.g., rule of law, regulatory efficiency, financial development) impact bank capital decisions (e.g., (Bitar et al., 2018; Bitar & Tarazi, 2019; Kalifa & Bektaş, 2018; Mili, Sahut, Trimeche, & Teulon, 2017)). Following the work of Athari, Shaeri, Kirikkaleli, Ertugrul, and Ozun (2020), this study employs the novel country-risk composite index scores2 from Political Risk Services Group 3, which include a set of 22 components that are grouped into three subcategories of financial, economic, and political risks. Likewise, this study uses the proxy of country-level governance index scores from the Worldwide Governance Indicators (WGI), as has previously been used by Bitar and Tarazi (2019), for measuring country-level governance. The WGI constructs a country-level governance index by using the aggregate six dimensions, including control of corruption, government effectiveness, political stability and absence of violence (terrorism), regulatory quality, rule of law, and voice and accountability.

Table 1 reports the country-specific descriptive summary of the investigated variables. As shown in panel (A), Egypt displays the lowest capital adequacy and equity to asset ratios with a mean of 0.173 and 0.096. In contrast, Jordan had the highest capital adequacy with a mean of 0.376, and Saudi Arabia had the highest equity to asset ratio with a mean of 0.488. Egypt, with a mean of 0.909 and 1.908 has the highest financial and default risks. Panel (B) also shows the average country-level governance and its dimensions scores. As shown, Egypt and Saudi Arabia, with a mean of -0.705 and -0.337, have the lowest country-level governance scores. However, the United Arab Emirates and Qatar have the highest scores with a mean of 0.544 and 0.492, respectively. Moreover, panel (C) shows the average domestic risk and sub-indices scores and indicates that the United Arab Emirates and Kuwait, with a mean score of 81.803 and 81.181, have the least vulnerable environments, respectively.

Figure 1 demonstrates the domestic risk and the country-specific sub-indices scores for the examined period of 2003-2018. As shown in Figure 1, Egypt has the least stable environment relative to other countries. Overall, Figure 1 shows that domestic risk has a negative trend, and countries experienced domestic instability between 2003-2018.

Table 1. Descriptive summary (2003-2018).
Panel (A): Average bank-specific variables
Sample country
Sample listed
Capital adequacy
Size
Profitability
Financial risk
Credit risk
Default risk
Equity to
assets
Saudi Arabia
5
0.221
24.435
0.028
0.512
0.535
1.565
0.488
Bahrain
6
0.242
20.462
0.022
0.593
0.455
1.392
0.406
Qatar
3
0.203
23.664
0.034
0.813
0.657
1.636
0.183
Kuwait
6
0.195
21.163
0.012
0.827
0.551
1.661
0.167
United Arabic Emirates
4
0.212
22.958
0.019
0.769
0.512
1.618
0.288
Egypt
3
0.173
22.773
0.013
0.909
0.488
1.908
0.096
Jordan
2
0.374
20.018
0.025
0.728
0.346
1.611
0.255
Panel (B): Average country-level governance and its dimensions scores
Sample country
Corruption
Government
effectiveness
Political stability
Regulatory quality
Rule of
law
Voice and
accountability
Governance
score
Saudi Arabia
-0.009
-0.029
-0.416
0.060
0.106
-1.735
-0.337
Bahrain
0.207
0.440
-0.542
0.663
0.464
-1.058
0.029
Qatar
0.919
0.726
1.033
0.514
0.722
-0.960
0.492
Kuwait
0.143
0.027
0.241
0.124
0.387
-0.554
0.061
United Arabic Emirates
1.061
1.076
0.818
0.726
0.536
-0.951
0.544
Egypt
-0.639
-0.540
-1.073
-0.532
-0.324
-1.125
-0.705
Jordan
0.201
0.120
-0.419
0.192
0.330
-0.713
-0.048
Total
0.269
0.260
-0.051
0.249
0.317
-1.014
0.005
Panel (C): Average domestic risk and sub-indices scores
Sample country
Financial risk Index
Economic risk Index
Political risk Index
Domestic risk Index
Saudi Arabia
46.083
41.964
67.307
77.677
Bahrain
40.539
40.565
68.909
75.006
Qatar
39.396
46.349
72.534
79.139
Kuwait
45.513
45.018
71.831
81.181
United Arabic Emirates
41.075
44.807
77.724
81.803
Egypt
39.120
31.047
55.552
62.859
Jordan
39.203
32.794
66.305
69.151
Total
41.561
40.363
68.594
75.260
Note: Table 1 shows the country-specific descriptive summary of the investigated variables.
Figure 1. Time series plot of domestic risk index and its sub-indices for investigated countries.

Table 2 shows the pooled statistics (Panel (A)) and Pearson correlation matrix and Variance Inflation Factors (VIF) (Panel (B)) for the studied variables. Panel (A) shows that the median value of capital adequacy and equity to assets ratios are 0.196 and 0.142, respectively. Panel (B) further indicates that multicollinearity is unlikely to be a severe problem in the panel estimations.

2.2. Model Specifications and Methodology

Following the studies by Bitar et al. (2018) and Kalifa and Bektaş (2018) this study uses two proxies of capital adequacy (Tier 1 plus Tier 2 capital, divided by risk-weighted assets) and equity-to-assets for measuring bank capital ratio. Equations.1 and 2 are performed in order to investigate the effects of bank-specific, domestic risk, and country-level governance on Islamic banks’ capital ratios.

Table 2. Pool descriptive statistics and Pearson correlation.
Panel (A):
Variables
Observations
Mean
Median
Std. Dev.
Minimum
Maximum
Capital adequacy
464
0.233
0.196
0.142
0.051
0.913
Size
464
22.187
21.282
1.736
17.052
25.221
Profitability
464
0.024
0.031
0.033
-0.197
0.177
Financial risk
464
0.727
0.741
0.697
-10.122
0.873
Credit risk
464
0.521
0.573
0.310
0.131
0.945
Default risk
464
1.592
1.577
0.652
-0.695
3.780
Equity to assets
464
0.179
0.142
0.117
0.031
0.615
Panel (B): Pearson correlation matrix
Explanatory variables
Size
PROF
FRISK
CRISK
DFRISK
DCRISK
CG
VIF
Size
1.000
1.30
Profitability (PROF)
0.257*
1.000
1.18
Financial risk (FRISK)
0.306*
0.163*
1.000
1.37
Credit risk (CRISK)
0.157*
0.256*
0.103***
1.000
1.12
Default risk (DFRISK)
0.161*
0.007
0.104
0.043
1.000
1.04
Domestic risk (DCRISK)
0.039
0.194*
0.151*
0.137**
-0.089
1.000
1.28
Governance score (CG)
-0.134**
-0.124**
-0.045
0.067
-1.101
0.347*
1.000
1.14
Note: ***, **, and * are statistically significant at 1%, 5%, and 10%, respectively.

Before estimating the equations, the panel data are winsorized at the 1% level for each year to remove the impact of outliers on the estimation. Use of Ordinary Least Squares (OLS) was avoided as the estimation models suffer from the correlation between the lagged dependent variable and error term, thereby yielding inconsistent and biased coefficient estimates (Baltagi, 2005; Roodman, 2009). Instead, dynamic panel regression provided more consistent and unbiased results in the presence of endogeneity problems and unobserved country fixed effects.

As such, this study used the generalized method of moments (GMM) approach to estimate the equations since the number of cross‐sections (i=29) was higher than the number of time units (t=16) in the present study. Specifically, this study used the System-GMM (Arellano & Bover, 1995; Blundell & Bond, 1998) methodology to estimate equations because the System‐GMM estimator contains both the levels and the first difference equations and outperforms the Difference‐GMM methodology proposed by Arellano and Bover (1995). Therefore, to perform System-GMM estimations, this study applied the xtabond2 package, as suggested by Roodman (2009), and was executed in Stata Software. In testing the validity of the estimated models and robustness of results, the Hansen and serial correlation diagnostic tests are conducted.

Table 3. The impact of banks-specific risks, domestic risk, and governance on Islamic banks’ capital ratios.
Independent variables
Model 1: Capital adequacy ratio
Model 2:  Total equity to assets
Coefficient
Z-value
P-value
Coefficient
Z-value
P-value
Lag capital adequacy
0.833*
3.74
0.000
---
---
---
Lag equity to assets
---
---
---
0.153*
3.82
0.000
Bank-specific variables
 
Size
-0.065***
-1.67
0.086
-0.015*
-2.77
0.001
Profitability
0.107*
2.67
0.001
0.023***
1.67
0.077
Financial risk
1.316*
2.86
0.004
0.155*
2.94
0.000
Credit risk
0.234**
2.07
0.033
0.039*
6.40
0.000
Default risk
-1.180*
-3.38
0.001
-0.114*
-2.73
0.003
Country variables
 
Domestic risk
-0.066**
-2.04
0.036
-0.077*
-5.53
0.000
Governance score
1.682**
2.07
0.038
0.089**
2.04
0.025
Constant
-0.534
-0.20
0.985
0.628
1.50
0.134
Diagnostic checking
P-value
P-value
AR(2)
0.472
0.423
Hansen test
0.431
0.502
Note: ***, **, and * are statistically significant at 1%, 5%, and 10%, respectively.

3. EMPIRICAL RESULTS

The estimated results in Table 3 reveal that the lagged coefficient of CA and ETA is positive and significant, implying that Islamic banks follow a partial adjustment towards the target capital ratios. Size is also shown to impact capital ratios negatively, which supports the trade-off theory and is consistent with the prior studies (e.g., (Bitar et al., 2018; Bitar & Tarazi, 2019; Gropp & Heider, 2010; Kalifa & Bektaş, 2018)), and implies that larger Islamic banks hold lower capital ratios as they have asset portfolios that are relatively better diversified, less volatile earnings, and better access to capital markets. These results are in line with the pecking-order theory as well as prior studies (e.g.,(Anginer et al., 2016; Bitar & Tarazi, 2019; Brewer Iii, Kaufman, & Wall, 2008)) and reveal that profitability impacts capital ratios positively, though this contradicts with several other studies (e.g., (Ahmad, Ariff, & Skully, 2008; Yu, 2000)).

Furthermore, results show that higher bank-specific risks correspond with higher capital ratios. This is consistent with prior studies (e.g., (Ahmad et al., 2008; Kalifa & Bektaş, 2018; Mili et al., 2017)) and showed that higher leverage and loan ratios are more likely to expose banks to higher risks and trigger them to increase capital ratios as a buffer to withstand potential bank failure. The work of Ahmad et al. (2008) highlighted that a bank engaging with higher risk-taking behavior prefers to increase capital ratios.

Moreover, Table 3 shows that the increases in domestic risks and country-level governance are associated with higher capital ratios. This is in line with prior studies (Ayuso, Pérez, & Saurina, 2004; Jokipii & Milne, 2008; Stolz & Wedow, 2005), and implies that higher a country’s vulnerability triggers Islamic banks to increase capital ratios as a buffer to minimize unexpected losses. Results also support the study by Bitar and Tarazi (2019), which found that the stronger country-level governance corresponds with higher capital ratios, and Islamic banks in the presence of a strong institutional environment are more capable of raising equity than debt.

Table 4 and Table 5 present the impacts of governance dimensions and domestic risk sub-indices on capital ratios. Results of panel (A) support the study by Bitar et al. (2018) that shows how the improvements in corruption, political stability, government effectiveness, and legal systems within a country correspond with higher capital ratios. Likewise, the results of the panel (B) are in line with prior studies (e.g., (Cohen & Scatigna, 2016; Francis & Osborne, 2010; Kalifa & Bektaş, 2018)) and show that banks’ capital ratios increase with the rise of financial and economic risks. However, results indicate that decreasing political risk is also linked with higher capital ratios.

Table 4. The impacts of governance dimensions and domestic risk sub-indices on capital adequacy ratio.
Model 1: Capital adequacy ratio
Panel (A): Governance dimensions scores
Independent variables
Corruption
Government effectiveness
Political stability
Regulatory quality
Rule of
Law
Voice and
accountability
Lag capital adequacy
0.823*
(4.89)
0.829*
(3.11)
0.816*
(4.12)
0.848**
(2.08)
0.826*
(3.12)
0.802*
(3.18)
Governance score
1.562**
(2.00)
1.002
(0.72)
2.589*
(3.60)
3.570*
(2.70)
1.386*
(3.55)
1.802**
(2.04)
Domestic risk
-0.230
(-0.94)
-0.349*
(-5.69)
-1.475**
(-2.07)
-0.836
(-0.81)
-1.266
(-0.75)
-0.624
(-0.58)
Bank-specific
Yes
Yes
Yes
Yes
Yes
Yes
AR(2)
0.368
0.353
0.389
0.393
0.370
0.426
Hansen test
0.354
0.388
0.375
0.525
0.543
0.361
Panel (B): Domestic risk sub-indices scores
Independent variables
Financial risk index
Economic risk index
Political risk index
Lag capital adequacy
0.769*
(4.49)
0.834*
(5.71)
0.664*
(3.34)
Governance score
1.346*
(3.41)
1.184**
(2.06)
2.159*
(4.71)
Domestic risk
-0.096**
(-2.02)
-0.057*
(-3.90)
0.649*
(3.75)
Bank-specific
Yes
Yes
Yes
AR (2)
0.315
0.380
0.688
Hansen test
0.419
0.399
0.498

Note: Table 4 shows the effects of governance dimensions (Panel A) and domestic risk sub-indices (Panel B) on capital adequacy ratio. The symbols * and ** indicate statistical significance at the 1% and 5% levels, respectively.


Table 5. The impacts of governance dimensions and domestic risk sub-indices on total equity to assets.
Model 2: Total equity to assets
Panel (A): Governance dimensions scores
Independent variables
Corruption
Government effectiveness
Political stability
Regulatory quality
Rule of
law
Voice and
accountability
Lag equity to assets
0.140*
(3.38)
0.138*
(3.13)
0.146**
(2.04)
0.127*
(4.46)
0.131*
(3.19)
0.137**
(2.06)
Governance score
0.998***
(1.79)
0.422**
(2.01)
0.824*
(2.67)
0.995
(0.65)
1.050***
(1.67)
0.615
(0.80)
Domestic risk
-0.080*
(-5.48)
-0.032***
(-1.67)
-0.067
(-0.62)
-0.081
(-0.28)
-0.077*
(-4.84)
-0.074
(-0.68)
Bank-specific
Yes
Yes
Yes
Yes
Yes
Yes
AR (2)
0.430
0.426
0.355
0.367
0.315
0.352
Hansen test
0.695
0.485
0.556
0.441
0.489
0.625
Panel (B): Domestic risk sub-indices scores
Independent variables
Financial risk index
Economic risk index
Political risk index
Lag equity to assets
0.169***
(1.80)
0.132*
(4.42)
0.125**
(2.04)
Governance score
0.951*
(4.81)
0.782*
(6.56)
0.353
(1.26)
Domestic risk
-0.038*
(-2.80)
-0.040*
(-3.64)
0.082*
(3.75)
Bank-specific
Yes
Yes
Yes
AR(2)
0.365
0.581
0.553
Hansen test
0.443
0.372
0.428
Note: Table 5 shows the effects of governance dimensions (Panel A) and domestic risk sub-indices (Panel B) on total equity to assets. The symbols *, **, and *** indicate statistical significance at the 1%, 5%, and 10% levels, respectively.

4. CONCLUSIONS

Although several studies have investigated the determinants of Islamic bank capital ratios, few studies found to examine the dynamic effect of environmental characteristics on Islamic bank capital ratios. This study fills the research gap by examining comparatively the impact of country-level governance quality and domestic risk on capital decisions of Islamic banks operating in Arab markets by performing the System-GMM dynamic panel technique.

The results underscore that stronger country-level governance is linked with higher capital ratios, and banks can increase capital, particularly by improving corruption, political stability, government effectiveness, and legal systems. Results also reveal that banks’ capital ratios increase with the rise of a country’s vulnerability, specifically in response to rises in financial and economic risks. However, the results show that decreasing political risks also corresponds with higher capital ratios. Overall, the results confirm that environmental characteristics have a pivotal role in setting Islamic bank capital ratios. The results are robust, and the findings of this study are likely to open up new channels in the banking literature. Also, the results have significant implications and suggest to policymakers to prepare for a more financially and economically stable environment, which helps banks to reduce capital buffers and allocate their capital more effectively. Also, the results imply that regulators enhance country-level governance quality specifically by reforming new policies to control risk at both the bank and country levels. Although this study provides strong empirical findings for the Arab markets, further studies can contribute to the research by considering the corporate governance factor and testing its effect on capital ratios of Islamic banks for individuals or groups of Islamic countries.

Funding: This study received no specific financial support.  

Competing Interests: The author declares that there are no conflicts of interests regarding the publication of this paper.

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Footnotes:

1. For instance, the capital adequacy for larger banks increased from 5.7% in 2009 to 9.2% in 2012 while for smaller banks increased from 7.8% to 9.4% over the same period. Also, the capital ratios for US commercial banks increased from 11.3% in 2009 to 11.8% in 2012 (www.federalreserve.gov/releases/h8/current/default.htm).

2. The domestic risk score is between the 0-100 range and a high score means low country risk.

4. A higher Z-score means a lower probability of default risk.