Impact of Internal and Macroeconomic Risks on Financial Performance, Growth, and Stability of Domestic and Foreign Banks in Pakistan

Jamshid ur Rehman1, Abdul Rashid2, and Muhammad Akmal3*

1Department of Management Sciences, Khushal Khan Khattak University, Karak, Pakistan

2International Institute of Islamic Economics, International Islamic University, Islamabad, Pakistan

3MCB Islamic Bank Limited, Lahore, Pakistan

Original Article Open Access
DOI: https://doi.org/10.32350/jfar.61.02

Abstract

The current study aims to scrutinize and compare the effects of internal and macroeconomic risks taken by foreign and domestic banks in Pakistan on their financial performance, growth, and stability. It also compares the substantial impact of both types of risks between foreign and domestic (both Islamic and conventional) banks. Internal risks include liquidity risk, operational risk, credit risk, and capital risk, whereas macroeconomic risks include exchange rate risk, interest rate risk, and inflation rate risk. Using a two-step system GMM with the collapse command, a sample of commercial banks including both Islamic and conventional banks was analyzed over the period 2008-2020. Based on the results, it was determined that both types of banks experience negative exposure to both macroeconomic and internal risks, affecting their financial performance, growth, and stability. However, the impact of both categories of risks was found to be more substantial in the case of domestic banks. Moreover, the results also hold true for both Islamic and conventional banks. The findings recommend that both domestic and foreign Islamic banks are more competent in the practices of risk management, as compared to domestic and foreign conventional banks. The current study has implications for investors, bank management, policymakers, and regulators. In particular, domestic conventional banks should prioritize to enhance their cost management, granting and monitoring of credit, and risk diversification, as well as upgrading their human and technological capital.

Keywords: bank performance, growth, internal risks, macroeconomic risks, profitability, stability, ownership

JEL Codes: G21, G32, C33

*Corresponding author: [email protected]

Published: 27-06-2024

Introduction

The banking industry is a significant pillar of the economy and financial instability in this industry has a pronounced adverse influence on a country's economic stability. Therefore, factors that influence bank performance and stability should be thoroughly investigated. Specifically, since the global financial crisis of 2007-08, banking risks have caused significant distress for policymakers. On the one side, taking too little risk may hinder economic growth. On the other side, taking too much risk may threaten economic stability. Hence, taking excessive risks may lead commercial banks to financial crises and ultimately cause the failure of the entire financial system (Lassoued et al., 2016). Additionally, Abdelaziz et al. (2022) reported that the financial performance of commercial banks is highly elusive due to the increase in liquidity and credit risk. Moreover, excessive risk-taking adversely affects the financial stability of banks.

Bank internal risks including capital risk, liquidity risk, operational risk, funding risk, and credit risk, as well as macroeconomic risks including interest rate risk, inflation rate risk, and others have an adverse impact on their profitability and stability (Alsyahrin et al., 2018; Berríos, 2013; Hakimi & Zaghdoudi, 2017; Hassan, et al., 2019). Moreover, volatility in dynamic macroeconomic variables may lead to a hostile business environment for banks. Likewise, instability in economic variables may deteriorate the business environment from borrowers' perspective and affect their financial power of loan repayment, ultimately decreasing bank liquidity (Singh & Sharma, 2016).

Micco et al. (2007), Lehner et al. (2008), and Shaban and James (2018) argued that bank ownership is an important factor in explaining their risk-taking and performance. Berger et al. (2005) asserted that foreign shareholders have a higher preference for risks than national shareholders. This is because foreigners have a better and easier access to the capital market and a greater ability to diversify risk effectively. In the same way, Lehner et al. (2008) argued that foreign banks have a greater capability to increase capital accumulation, exercise efficient corporate control, provide more profitable investment portfolios, and practice better risk management techniques. Similarly, foreign banks are more capable of absorbing financial shocks arising in the host market by providing important diversification services (De Haas & Van Lelyveld, 2010). In the same manner, these banks have comparatively higher profitability and lower overhead costs (Azam & Siddiqui, 2012). They also possess improved human capital, make better use of advanced technologies, and offer more diverse products and services (Lassoued et al., 2016).

Ownership is an important determinant associated with the financial performance of banks. In this regard, banks with a higher proportion of foreign shareholders have higher capital, higher profit, low overhead cost, low financial instability, and high operational efficiency. Further, foreign banks have better regulation and supervision, advanced technology, superior management practices, and better techniques and tools to diversify risks effectively (Rahman & Reja, 2015; Noor & Mohamed, 2019). On the other side, Shaban and James (2018) asserted that public sector banks are less profitable and more vulnerable to risks than foreign and private banks.

There are divergent views about bank performance and risk-taking. Some studies reported that foreign banks are highly profitable and exposed to lower risk, while others reported contrasting views. Thus, the lack of empirical studies that provide a clear understanding regarding the nexus between risks, financial performance, and stability with reference to bank ownership types motivated this study. Hence, it attempts to explore whether bank internal and macroeconomic risks differently affect the growth, financial performance, and stability of foreign and domestic banks. Moreover, the study also determines whether the impact of both types of risks is different across domestic versus foreign (Islamic and conventional) banks. The outcomes revealed that both sets of risks reduce the financial performance, growth, and stability of both foreign and domestic banks. However, the growth, financial performance, and stability of domestic banks (including both Islamic and conventional banks) are more sensitive to all risks. This supports the view that banks with a majority of foreign shareholders are more cost-efficient, more profitable, have better supervision and risk management, higher capital, lower financial instability, and better operational efficiency.

The rest of the paper is arranged as follows: Section 2 reviews the literature, Section 3 describes the research methodology, Section 4 details the estimation results, and Section 5 states the conclusion.

Literature Review

Banks are exposed to several types of risks including market risk, insolvency risk, credit risk, off-balance sheet risk, liquidity risk, interest rate risk, country risk, foreign exchange risk, operational risk, and technology risk due to their dynamic structure as well as the complex nature of the economic and business environment in which they operate. These risks have extensive and adverse effects on their market value, profitability, equity, and liability. Thus, bank management is essentially required to monitor and control these risks effectively because they may lead to bank default (Ekinci & Poyraz, 2019; Kakar et al., 2021). For the period 2004-2015, Abdelaziz et al. (2022) observed the empirical link among liquidity risk, credit risk, and profitability of conventional banks operating in the MENA region. Their findings revealed that the profitability of banks is extremely sensitive to both kinds of risks, resulting in a substantial decrease as these risks increase. Likewise, Wood and McConney (2018) reported that interest rate risk, credit risk, operational risk, capital risk, and liquidity risk had a significant and negative effect on the performance of commercial banks in Barbados. Similarly, Al-Tamimi et al. (2015) reported a negative association between capital and operational risks and Islamic banks' performance.

Lassoued et al. (2016) analyzed the effect of foreign and state ownership on the risk-taking behavior of banks in the MENA region during the period 2006-2012. They reported that higher foreign ownership is associated with decreased risk-taking, while state ownership in banks encourages higher risk-taking. Likewise, Al-Tamimi and Al-Mazrooei (2007) compared foreign and UAE national banks with respect to risk management. They found that foreign banks are more competent in the practices of risk management. Further, Berger et al. (2009) argued that Chinese banks with a large number of foreign shareholders are more profit-proficient and cost-effective as compared to others. Similarly, Kalluru (2009) examined the risks and performance of Indian commercial banks in relation to ownership structure. The study aimed to determine if there were significant differences in relation with risks and performance between foreign banks and domestic (private and state-owned) banks. The study concluded that foreign banks exhibited higher profit and risk-taking than domestic banks.

Kamau (2009) analyzed the data of Kenya's banks for the period 1997-2006. The results suggested that domestic banks with a higher proportion of foreign shareholders showed greater performance. Further, the study showed that foreign banks have better technical capacity and more know-how, in general. Moreover, foreign banks obtain liquidity resources from their parent banks and have access to the international financial market, thus increase competition for local banks. Likewise, the empirical study of Sufian and Habibullah (2010) evaluated the impact of the entrance of foreign banks on the performance of domestic Islamic banks. They argued that domestic Islamic banks are relatively less profitable than their domestic conventional counterparts. Rahman and Reja (2015) investigated the impact of the various forms of ownership structure (family, government, insider, foreign, and institutional ownership) on banking performance in Malaysia over the period 2000-2011. Based on the findings, the study concluded that the performance of banks varies depending on the types of ownership structure. The banks with a higher proportion of foreign shareholders are more competent in their operations because they have sufficient and efficient financial, human, and technical resources and lower overhead costs. Further, they are more cost-efficient and offer good services (Lensink & Naaborg, 2007). Along the same lines, foreign banks have a larger capital adequacy ratio, liquidity, asset quality, and size than domestic banks (Matthew & Esther, 2012), are efficient in risk mitigation, hold better technology, implement high governance standards, and also specialize in taking advantage from specific tax breaks (Al-Harbi, 2019).

Foreign ownership in banks is significantly associated with high returns and low financial instability. Foreign banks are known for superior management practices, use of advanced technology, efficient risk management, high operational efficiency, and higher profitability (Micco et al., 2007). Similarly, foreign banks have technical advantages as compared to local banks in their host country. They also have increased economies of scale due to functioning in more than one country at a time. Further, they are not often affected by interest rate volatility. For example, when interest rates go higher in their home countries than the interest rate in their host countries, they just decrease their loans and advances in the host country and increase loans and advances in the home country and vice versa (Aburime, 2008). Moreover, foreign shareholders and investors play a significant role in the implementation of a transparent corporate governance system, managing moral hazards, leading to good relationships among stakeholders, and reducing information asymmetries. These steps reduce the risks taken (Oh et al., 2011).

On the other hand, some empirical studies such as De Nicolò and Loukoianova (2007), San et al. (2011), Dogan (2013), and Mungly et al. (2016) reported better performance of domestic banks than foreign banks. For example, De Nicolò and Loukoianova (2007) asserted that banks with majority foreign shareholders possess higher risk profiles than domestic banks. Similarly, the study conducted by San et al. (2011) demonstrated that Malaysian domestic banks exhibit greater efficiency and managerial competence as compared to foreign banks. Additionally, Dogan (2013) reported the outperformance of Turkish domestic banks in terms of return on equity, asset quality, management effectiveness, and total assets than foreign banks. Further, Mungly et al. (2016) found that the profitability of banks decreases with the increase in foreign ownership.

H1: Banks' internal and macroeconomic risks have differential negative effects on the financial performance, growth, and stability of foreign and domestic banks.

H2: Bank's ownership moderates the negative impact of bank's internal and macroeconomic risks on financial performance, growth and stability of both Islamic and conventional banks.

Methodology

Sampling and Data Collection

The population of the study included 33 scheduled commercial banks operating in Pakistan over the period 2008-2020. Purposive sampling technique was used to select 22 commercial banks as sample. The remaining banks were excluded because of the absence of data for the sampling period. The sample included both full-fledged Islamic banks (IBs) and conventional banks (CBs). Islamic branches and windows of CBs were excluded because of the unavailability of data regarding ownership types. The bank-level data regarding bank ownership, internal risks, and other bank-related control variables was collected from the financial reports of each concerned bank. Further, data concerning macroeconomic risks and other macro-level associated and control variables was obtained from publications and economic surveys issued by the State Bank of Pakistan (SBP).

Description of Variables

Table 1 displays variables and their measurement proxies. To measure growth, an index consisting of three proxies namely asset growth, deposit growth, and loan/financing growth was utilized. Similarly, for profitability, an index comprising the return on assets (RoA) ratio, return on equity (RoE) ratio, and net interest/markup margin (NIMM) ratio was developed. Likewise, indexes to measure banks' internal risks (BIR) and macroeconomic risks (MER) were also developed for this research. BIR comprises respective ratios of credit risk, capital risk, liquidity risk, and operational risk, while MER includes foreign exchange rate risk, inflation rate risk, and interest rate risk. Additionally, credit risk, liquidity risk, and operational risk were measured by using an index comprising its respective ratios, as shown in Table 1. All indexes were developed by using the principle component analysis (PCA) technique.

Table 1

Study Variables

Variables

Measurement Proxies

Dependent Variables

Growth

1. Deposit growth = Deposits in current year minus deposits in the previous year divided by deposits in the previous year.

2. Assets growth = Assets in the current year minus assets in the previous year divided by assets in the previous year.

3. Loan/financing = Loan/financing for the current year minus loan/financing for the previous year divided by loan/financing for the previous year. The term "loan" for conventional banks while "financing" for Islamic banks.

Profitability

1. RoA = net income divided by total assets

2. RoE = net income divided by total equity

3. NIMM = net interest/mark-up earned minus interest/mark-up expense to total assets

Stability

Ζ= ((RoA)it+(Ε/A)it)/δ(RoA)it, Ζit , Signify stability, denote individual bank at time t, represent standard deviation of return on total asset, denote capital to asset ratio.

Independent Variables

Credit risk

1.   Non-performing loan (NPL) to gross advances ratio

2.     Ratio of Provision against loans to gross loans

3.     NPL write-off divided by total provision against advances

Liquidity risk

1.     Current assets divided by total deposits

2.     current assets divided by total assets

Operational risk

1.     total Admin expense divided by non-interest/mark-up-up income

2.     Non-interest/mark-up expense divided by total income

3.     Total Admin expense divided by profit before interest and tax

Capital risk

Total equity to total assets ratio

Inflation rate risk

monthly standard deviation of inflation rate

Interest rate risk

Monthly standard deviation of lending interest rate

Exchange rate risk

monthly standard deviation of real effective exchange rate

Control Variables

Bank size

log of total bank^' assets

Tax ratio

tax paid divided by profit before tax

Cost efficiency ratio

total expense/total assets ratio

Deposits

total deposits divided by total assets

Savings

total savings in relation to GDP

Assets structure ratio

total loan divided by total assets

Financial development

credit provided to private sector as percent of GDP

Moderating variable

Bank ownership

Take value 1 if the bank is foreign and 0 otherwise. A bank will be categorized as foreign if foreigners own 50% or more of its shares; otherwise, it will be classified as domestic.

Econometric Model

A total of six (06) dynamic panel data models were estimated in this study. The first three models denoted in equations (1), (2), and (3) below were established to perceive the effects of BIR and MER across domestic versus foreign banks.

growthit= β0+ Χit β1+ β2 BIRit ×DiDom+ β3 BIRit × DiFor4 MERt × DiDom+ β5 MERt × DiForit (1)

Profitabilityit= β0+ Yit β1+ β2 BIRit ×DiDom+ β3 BIRit × DiFor4 MERt × DiDom+ β5 MERt × DiForit (2)

Stabilityit= β0+ Zit β1+ β2 BIRit ×DiDom+ β3 BIRit × DiFor4 MERt × DiDom+ β5 MERt × DiForit (3)

In the above equations, denotes banks' internal risks at time for bank, where BIR is the index developed from the ratios of credit risk, capital risk, operational risk, and liquidity risk. denotes the macroeconomic risks at time , which includes exchange rate risk, inflation rate risk, and interest rate risk. is the vector of control variables in the growth model which include bank size, tax ratio, and cost efficiency. denotes control variables in the profitability model namely bank size, savings, and deposits. Moreover, represents the control variables in the stability model which include bank size, financial development, and asset structure. Further, is the dummy for domestic banks, assuming the value of 0 for domestic and 1 for foreign banks. Similarly, is the dummy for foreign banks, assuming the value of 1 for foreign banks and 0 for domestic banks. In all equations, are the coefficients denoting the responsiveness of growth, profitability, and stability of domestic and foreign banks with respect to each unit change in bank' internal risks and macroeconomic risks. Whereas, is the error term.

In order to observe the differential influences of both sets of risks across foreign versus domestic banks (including CBs and IBs), estimation models were employed. These models are displayed in equations (4), (5), and (6). In these equations, four dummies for domestic IBs, foreign IBs, domestic CBs, and foreign CBs with BIR and MER were used for interaction.

growthit= β0+Xit β12 BIRit×DiDomIB3 BIRit ×DiForIB4 BIRit×DiDomCB+ β5 BIRit×DiForCB+β6 MERt× DiDomIB+ β7 MERt× DiForIB8 MERt× DiDomCB+ β9 MERt×DiForCB+µit (4)

Profitabilityit= β0+Yit β12 BIRit×DiDomIB3 BIRit×DiForIB4 BIRit×DiDomCB+ β5 BIRit×DiForCB+β6 MERt× DiDomIB7 MERt × DiForIB8 MERt×DiDomCB+ β9 MERt×DiForCBit(5)

Stabilitit= β0+Zit β12 BIRit×DiDomIB3 BIRit×DiForIB4 BIRit×DiDomCB+ β5 BIRit×DiForCB+β6 MERt×DiDomIB+ β7 MERt×DiForIB8 MERt×DiDomCB+ β9 MERt×DiForCBit (6)

represents the interaction term between the index of BIR and the dummy of domestic IBs, while denotes the interaction term between the index of BIR and the dummy of foreign IBs. Further, denotes the interaction term expressing BIR for domestic CBs, whereas shows BIR for foreign CBs. The interaction term shows MERs for domestic IBs. Likewise, the term represents MERs for foreign IBs. Further, is the interaction term between MERs and the dummy of domestic CBs. Similarly, is the interaction term between MERs and the dummy of foreign CBs.

Estimation Techniques

The current study scrutinizes the dynamic panel data set for the sample period 2008-2020. The regressions of a dynamic panel data set may contain the problems of autocorrelation, heterogeneity, and endogeneity. Thus, the use of conventional econometric techniques such as OLS and GLS would be unfair and biased. The reason is that conventional techniques do not provide a solution for the problem of autocorrelation, heterogeneity, and endogeneity. To overcome the problems of traditional econometric techniques, two-step system GMM known as dynamic panel data estimator was employed to examine the effects of BIR and MER. The GMM estimator is the standard estimation technique for estimating parameters in dynamic econometric models. It was initially developed by Arellano-Bond (1991) and later modified and fully refined by Arellano and Bover (1995) and Blundell and Bond (1998). Recently, this estimator has emerged in the empirical literature as the most popular and dynamic panel data estimator among academicians and researchers (Ali et al., 2019; Ghenimi et al., 2017; Shair et al., 2019).

Estimation Techniques

The current study scrutinizes the dynamic panel data set for the sample period 2008-2020. The regressions of a dynamic panel data set may contain the problems of autocorrelation, heterogeneity, and endogeneity. Thus, the use of conventional econometric techniques such as OLS and GLS would be unfair and biased. The reason is that conventional techniques do not provide a solution for the problem of autocorrelation, heterogeneity, and endogeneity. To overcome the problems of traditional econometric techniques, two-step system GMM known as dynamic panel data estimator was employed to examine the effects of BIR and MER. The GMM estimator is the standard estimation technique for estimating parameters in dynamic econometric models. It was initially developed by Arellano-Bond (1991) and later modified and fully refined by Arellano and Bover (1995) and Blundell and Bond (1998). Recently, this estimator has emerged in the empirical literature as the most popular and dynamic panel data estimator among academicians and researchers (Ali et al., 2019; Ghenimi et al., 2017; Shair et al., 2019).

Table 3

Estimation Results

Regressors

Growth Model

Profitability Model

Stability Model

Coefficient

(SE)

Coefficient

(SE)

Coefficient

(SE)

Panel A

Lagged growthDom

0.976***

(0.151)

 

 

 

 

Lagged growthFor

0. 074*

(0.038)

 

 

 

 

Lagged profitabilityDom

 

 

0. .668***

(0.082)

 

 

Lagged profitabilityFor

 

 

0.77***

(0.053)

 

 

Lagged stabilityDom

 

 

 

 

1.035***

(0.172)

Lagged stability For

 

 

 

 

1.118***

(0.201)

BIR-Domestic

-0.507***

(0.163)

-0. 664***

(0.178)

-0.168**

(0.087)

BIR-Foreign

-0.418***

(0.011)

-0.393***

(0.106)

-0.132***

(0.01)

MER-Domestic

-0. 409**

(0.16)

-0. 245*

(0.245)

-0.132*

(0.011)

MER-Foreign

-0.092*

(0.052)

-0.142**

(0.253)

-0.022 ***

(0.005)

Bank size

0. 494***

(0.074)

1.722*

(0.883)

0.06***

(0.02)

Tax ratio

-1.177**

(0.577)

 

 

 

 

Cost efficiency ratio

0. 143***

(0.041)

 

 

 

 

Total Deposit

 

 

1.711*

(0.989)

 

 

Total Saving

 

 

- 9.498***

(2.737)

 

 

Asset structure ratio

 

 

 

 

0.757***

(0.266)

Financial Development

 

 

 

 

0.371*

(0.209)

constant

6.087***

(1.011)

10.298***

(3.659)

0.14**

(0.29)

Panel B

No of Observations                                286                                   286                             286

No. of Banks                                             22                                      22                              22

No. of Instruments                                    19                                      21                              18

AR (1)                                                     0.037                                 0.007                          0.016

AR (2)                                                     0.596                                 0.156                          0.312

p-value                                                    0.933                                 0.864                          0.838

J-state                                                      9.41                                   4.08                            7.48

p-value                                                    0.668                                 0.253                          0.486

Note. *** p<0.01. ** p<0.05. * p<0.1.

The estimates of BIR and MER display significantly negative coefficients, which suggests that banks exposed to higher risks would have lower growth and be less profitable and stable. However, the coefficients of both categories of risks exhibit high values in the case of domestic banks. Such as a one unit increase in banks' internal risks leads to 0.50 unit, 0.66 unit, and 0.16 unit decrease in domestic banks' growth, financial performance, and stability, respectively. On the other side, a one unit increase in banks' internal risks leads to 0.41 unit, 0.39 unit, and 0.13 unit decrease in the growth, profitability, and stability of foreign banks, respectively. In the case of macroeconomic risks, a one unit increase causes a greater decrease in the growth, profitability, and stability of domestic banks than foreign banks. This suggests that domestic banks are exposed to more bank internal and macroeconomic risks than foreign banks.

The estimates in Table 4 signify the significant and negative coefficients of all risks in all models. However, the coefficient of both types of risks in the case of domestic IBs and CBs are higher than foreign IBs and CBs. Additionally, the coefficient of both types of risks are less in the case of domestic and foreign IBs as compared to domestic and foreign CBs. The results recommend that both categories of risks exhibit a large but adverse influence in the case of both domestic IBs and CBs, as compared to foreign IBs and CBs. The suggested results are in line with the studies of Oh et al. (2011), Rahman et al. (2012), Rehman and Rejab (2015), Shaban and James (2018), and Noor and Mohamed (2019). Their results suggested that foreign banks usually are more profitable, have the ability to increase liquid funds or capital easily from the international market, and have higher operational efficiency. Additionally, foreign banks have better regulation and supervision, advanced technology, superior management practices, and better techniques and tools to mitigate and diversify risks effectively. Moreover, foreign shareholders play a significant role in monitoring the moral hazards of managers and forcing them to develop transparent corporate governance, which leads to better relationships among stakeholders and mitigates informational asymmetries.

The estimates in Table 4 also provide evidence that both domestic and foreign IBs are less affected by both types of risks than domestic and foreign CBs. The reason behind this may be that Islamic banks are based on risk-sharing principles and Islamic law prohibits investment in risky products, such as the selling of loans and derivatives.

Table 4

Estimation Results

Regressors

Growth Model

Profitability Model

Stability Model

Coefficient

(SE)

Coefficient

(SE)

Coefficient

(SE)

Panel A

Lagged growthCBs

0.380***

(0.516)

 

 

 

 

Lagged growthIBs

0.932***

(1.029)

 

 

 

 

Lagged profitabilityCBs

 

 

0.395***

(0.114)

 

 

Lagged profitabilityIBs

 

 

0.143**

(0.193)

 

 

Lagged stabilityCBs

 

 

 

 

1.209***

(0.297)

Lagged stabilityIBs

 

 

 

 

1.590***

(0.312)

BIR-DCBs

-0.555**

(0.098)

-0.664***

(0.284)

-0.087**

(0.081)

BIR-FCBs

-0.402**

(0.102)

-0.322**

(0.077)

-0.032**

(0.030)

BIR-DIBs

-0.452*

(0.083)

-0.110***

(0.370)

-0.049***

(0.013)

BIR-FIBs

-0.334**

(0.061)

-0.227***

(0.179)

-0.017**

(0.010)

MER-DCBs

-0.488**

(0.211)

-0.423*

(0.218)

-0.056*

(0.023)

MER-FCBs

-0.347**

(0.111)

-0.140*

(0.103)

-0.042 **

(0.011)

MER-DIBs

-0.404*

(0.171)

-0.282**

(0.239)

-0.046**

(0.019)

MER-FIBs

-0.170***

(0.629)

0.109***

(0.105)

-0.031***

(0.010)

Bank size

0.634*

(0.886)

1.641*

(0.901)

0.053**

(0.042)

Tax ratio

-0.359**

(0.148)

 

 

 

 

Cost efficiency ratio

0.764*

(0.281)

 

 

 

 

Total Deposit

 

 

0.903*

(0.388)

 

 

Total Saving

 

 

- 0.133**

(0.702)

 

 

Asset structure ratio

 

 

 

 

0.795*

(0.277)

Financial development

 

 

 

 

0.406**

(0.178)

Constant

4.067***

(0.287)

3.021**

(1.367)

0.621***

(0.087)

Panel B

No. of Observations                                 286                                    286                              286

No. of Banks                                             22                                      22                                22

No. of Instruments                                    19                                      18                                21

AR (1)                                                      0.068                                 0.010                           0.022

AR (2)                                                      0.732                                 0.782                           0.415

p-value                                                    0.301                                 0.397                           0.981

J-state                                                      7.46                                   6.83                             8.050

p-value                                                    0.487                                 0.981                           0.709

Note. *** p<0.01. ** p<0.05. * p<0.1.

While examining the coefficients of control variables in all models in both tables, it was found that bank size is positively associated with the growth, profitability, and stability of banks. It shows that big banks (in terms of assets) experience higher growth in their deposits, assets, and loan/financing. Further, big banks remain highly profitable and stable. They take advantage of the economies of scale, where banks reduce their average cost by spreading fixed costs over a greater assets base. Furthermore, bank size reduces risks by diversifying operations across various product lines, regions, and sectors.

Unlikely, the coefficient of tax ratio has a negative effect on bank growth. This result suggests that a high tax rate diminishes the assets, deposits, and loan growth of banks. The reason may be that the tax burden is fully shifted to commission and interest rates on loans. Consequently, it increases the cost of loans for households as compared to firms. On the other hand, the coefficient of cost efficiency remains positive, which implies that effective management of cost boosts bank growth. While examining the estimated coefficient of deposits, it was determined that total deposits have a positive impact on the overall profitability of banks. This result indicates that banks with greater deposits would be more profitable. On the other hand, the coefficient of savings remains negative, which suggests that an increasing amount of savings (as a percentage of GDP) decreases bank profitability. Moreover, in the stability model, the coefficients of asset structure ratio and financial development ratio remain significantly positive. This suggests that a high portion of loan/financing in total assets increases the stability of banks because banks earn more return on the granting of loan/financing. Similarly, the provision of an increased amount of credit to the private sector leads to greater stability for banks.

Conclusion

In this study, the effects of risks on financial performance, growth, and stability of banks with respect to their ownership types (based on foreign and domestic shareholdings) were examined and compared. Additionally, the impacts of risks across foreign and domestic IBs and CBs were also compared. It was found that the index of banks' internal risks as well as the index of macroeconomic risks adversely affected their financial performance, growth, and stability. Furthermore, it was also determined that domestic banks, including both domestic IBs and CBs, are more affected by both types of risks than foreign IBs and CBs. Moreover, the results suggested that foreign and domestic IBs are less exposed to risks than foreign and domestic CBs.

Implications and Future Directions

The study provides a clear understanding of the adverse impacts of various types of risks on the operations and performance of banks. Hence, there is a strong need for the management and regulators of both types of banks, particularly domestic banks, to improve banking supervision, operational management, cost efficiency, mechanism of credit granting, and risk diversification. Further studies may be conducted to compare risks across various ownership types, such as institutional ownership, family ownership, and state ownership. Additionally, similar studies may be conducted at the regional level or to make comparisons among different countries.

Conflict of Interest

The author of the manuscript has no financial or non-financial conflict of interest in the subject matter or materials discussed in this manuscript.

Data Availability Statement

The data associated with this study will be provided by the corresponding author upon reasonable request.

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