Foreign Direct Investment and Bank Stability During COVID-19

Topic: Finance
Words: 10312 Pages: 3

Abstract

The question whether foreign direct investment (FDI) can impact bank stability during the coronavirus (COVID-19) pandemic and the global financial crisis (GFC) in countries with dual banking system (Islamic and conventional banks) remains an issue of concerns to academic and professionals alike. Using a sample of Islamic and conventional banks operating in the six GCC (the Cooperative Gulf council region) countries covering the period between 2006 and 2021, our analysis suggests that FDI reduces bank stability, but the presence of Islamic banks weakens the negative effect of FDI on bank stability. We also argue that the COVID-19 and GFC crises strengthen the negative impact of FDI on bank stability; the GFC crisis has a higher influence on reducing the negative impact of FDI on bank stability compared to COVID-19 pandemic crisis. Finally, the impact of FDI on bank stability is found to be heterogeneous across counties. In general, although Islamic banks play a significant role in stabilizing the banking systems in the GCC region, they have less influence in stabilizing the banking system in each individual country. The paper serves as a useful guidance to policymakers, investors and central banks in the region calling for the need for a prudent and cautious approach to supervising the growth in FDI in the GCC countries in order to maintain monetary as well as financial stability.

Introduction

The banking system is one of the main factors that supports the country’ economy. Banks provide the base for the intermediation process that links borrowers and lenders. The stability in the banking system can ensure a continuous strength of the financial sector and financial stability to all key aspects of the economy. Government and central banks always attempt to ensure long term stability of the banking system in order to promote innovation, warrant capital formation, and ultimately, allowing for more economic and welfare development, particularly job opportunities creation (Saif-Alyousfi et al., 2020, 2021). However, although foreign direct investment (FDI as shorter hereafter) has a positive impact on the productivity of local firms and banks due to supporting greater competition and employment, enhancement of economic growth, increase the country’s foreign exchange earnings (Magnus et al., 2006), greater capital formation and diffusion of technology (Alfaro et al., 2009; Bruno and Cipollina, 2014), inward FDI may place pressure on the banking system in the host countries.1 For instance, the inflow of foreign capital into a country may generate higher competition between foreign banks and local banks and higher pressure on bank loans within the lost countries.

The banking system the local markets can benefit from the inflow of FDI. FDI can increase banks performance (Demirguc-Kunt and Levine, 2018) and can foster competition by forcing banks to reduce operating costs and offer more loans, resulting in increased earnings. Another advantage of FDI is that it allows local banks to provide more credit especially to small businesses and other businesses in the private sector because banks strive for a larger market share, and ultimately, lead to higher economic growth. Greater credit offered by local banks would be advantageous to the economy since it allows entrepreneurs to make a greater adoption of best technological practices made available by FDI. However, if credit is not sufficient, more foreign funds will be required by local businesses in order to take advantage of the new knowledge and meet their daily activities. FDI might provide stability during bad economic conditions by offering greater liquidity to the local economy because their parent banks may have access to funding from global financial markets. Thus, the financial sector in the host country will benefit because FDI will not return back quickly to their home countries especially during financial crises, leading to economic and financial stabilization of the developing and emerging markets.

Given the implication of FDI inflow and its role in bank stability in developing and emerging countries, and particularly GCC countries is an important policy concern to academic, regulators and practitioners. As the inward FDI may have an influence on the level of bank stability – bank risk-taking – Islamic banks can be differently influenced by FDI compared to conventional banks due to the differences in the functionality, financial intermediation and operational systems of these two banking systems. As Islamic banks operate based on the rules of Islamic Shariah whereby risk sharing takes place, stakeholders can share profits and losses with prohibition of interest charges. Although conventional banks are largely debt-based institutions and allow for risk transfer, Islamic banks are asset-based institutions with risk sharing endeavor. Because Islamic banks structure investments are based on exchange or ownership of assets, placing such banking system in a step that is closer to the real economy compared to the conventional system can be a differently effected by the level of bank stability.

FDI impacts the stability of banks in a number ways. First, it may affect asset volatility of banks through increasing the cost of capital and systematic risk (Belkhir et al., 2018; Al-Shboul et al., 2020) as well as generating higher fluctuation in banks’ future cash flows. Islamic banks might be less exposed to systemic risk generated by the inflow of FDI than conventional banks do (Kammer et al., 2015; Beck et al., 2013) because the former could attain higher returns than conventional banks due to having distinctive features, such as, better diversification and stronger reputation. Although an increase in FDI may raise the likelihood of default on banks’ loans, Islamic banks may exhibit less probability of default risk and liquidity risk in their loan portfolios because these banks normally enjoy higher deposit growth rates compared to conventional banks (Baele et al., 2014; Belkhir et al., 2018). As Islamic bank normally lend a larger part of their loan portfolio to the consumer sector, they might be less exposed to risk generated by the inflow of FDI compared to conventional banks.

Furthermore, managerial opportunism may increase bank risk taking because managers (if dual board structure exists where board members in Islamic bank’s Shariah supervisory are considered as members in the regular board of directors and/or leading shareholders as well) may expand the bank’s lending strategies in order to receive more personal benefits. If specific type of managers or directors are directly linked to any new FDI inflow, they may act as borrowers who may put more pressure on banks to take large loans at lower borrowing costs. This moral hazard incentive mostly happens because banks face a lack of efficiency in the application of Shariah compliant. Nevertheless, the religious beliefs and the strong loyalty of borrowers may reduce credit risk of Islamic banks, even in periods of greater FDI inflow because they could reduce the risk of competition on loans facilities, the risk of adverse selection and facilitate better understanding of borrowers’ creditworthiness. Due to the religious constraints on accessing interest-based funds from different resources as a last resort facility, Islamic banks might be exposed to more liquidity risk because of lack in money market and tradeable Shariah compliant financial instruments. Higher FDI, where more competition exists, leads banks to adopt restrictive lending strategies and engage highly qualified and reputable members of Shariah scholars in the supervisory board in order to enhance bank’s credibility and legitimacy as well as the efficiency in screening loan quality, and thus, greater stability in Islamic banks (Safiullah and Shamsuddin, 2018). In summary, the inflow of FDI can differently impact the level of risk-taking for Islamic and conventional peers.

The link between foreign direct investment and the banking sector has been examined by the empirical literature. Almost all studies have focused on the impact of FDI on different aspects, such as, bank efficiency, performance, loans and the bank prudent behaviors (Konara, Tan and Johnes, 2019; Hasan and Xie, 2013; Buckley et al., 2018; Alqahtani and Mayes, 2018). However, they have largely ignored the impact of FDI on bank stability and rarely examined such impact on the GCC region during financial and pandemic crises periods. Furthermore, although these studies have tried to reach to establish evidence of the relationship between FDI and banking sector, their results were conflicting and ambiguous across countries and regions. Other studies have examined the impact of FDI on the dual banking systems (Islamic and conventional) as in the GCC banking sector (Saif-Alyousfi, 2020, 2021; Shabir et al., 2022; Tabash, 2018), but they have taken only the impact on bank loans, off-balance sheet items and banking operations without paying an attention to bank stability. Furthermore, one of the main challenges to the previous studies is that there is a lack of studies which examined the presence of the COVID-19 pandemic on the relationship between FDI and bank stability in the dual banking system.

Although the impact of foreign direct investment (FDI) on bank stability is well established, existing studies have left a number of research gaps. First, existing studies have mostly focused on examining the effect of FDI on bank performance and/or profitability, while largely ignored such effect on bank stability, particularly in the dual banking system region (GCC). In addition, it is noticed that there is a lack of studies that differentiate between the impact of FDI on bank stability of conventional and of Islamic banks. Given the presence of COVID-19 crisis as well as the subprime global financial crisis (GFC), there is a noticeable paucity of literature which investigate the impact of FDI on Bank stability. Thus, it is of great interest to examine the impact of FDI on bank stability during the COVID-19 pandemic and the GFC.

The study contributes to the literature in a number of ways. First, it provides a comprehensive analysis to the relationship between FDI and bank stability in countries with dual banking systems (conventional banking and Islamic banking systems). Using a sample of Islamic and conventional banks operating in the six GCC (the Cooperative Gulf council region) countries (Bahrain, Kuwait, Oman, Qatar, Kingdom of Saudi Arabia (KSA), the United Arab Emirates (UAE)) covering the period between 2006 and 2021, a panel data region analysis has been used to examine the relationship between FDI and bank stability. These counties are characterized by the use of the dual banking systems as well as by oil oriented economies. Given the economic downturns generated by the COVID-19 pandemic crisis and the GFC, our paper extends the literature by examining the effect of FDI on bank stability during these two influential periods. Like other countries and region of the world, this region was strongly and negatively affected by both crisis. The GCC region is considered one of the region that allow for heavy foreign direct investment. As FDI may have different influence on bank stability across the GCC countries, our analysis displays an evidence of the effect of FDI on bank stability per countries level during both crises.

A number of motivations behind conducting this study. First, given the negative impact of oil price fluctuations on the banking sector in the GCC as an oil-oriented region, examining the link between FDI and bank stability is an important issue of investigation. Although the GCC economies have witnessed greater growth over years, the oil-revenue and oil reserves in such countries are declining over time, diminishing GCC governments’ revenues, and ultimately, impacted the level of bank stability in the region. Allowing foreign capital and encouraging more foreign investment to exist in the GCC markets especially after 2006 is the other motive to examine such topic. There has been a significant increase in the foreign ownership in the GCC maerkets since 2006 (Almfraji and Almsafir, 2014). According to the UNCTAD annual World Investment Report (WIR)2, released on Jun, 09th 2022, the inflow of FDI has risen on average from 4918.2USD million in 2010 to 7407.3USD million in 2021, increased by 51%. The rise in the FDI is mostly happens in UAE, KSA and Oman. Buckley et al. (2018) stated that the banking sector is ranked the second in foreign direct investment flows after the services sector in the region, particularly in the UAE.3 Mosteanu (2019) argued that the UAE is the leading country of FDI not only in the GCC region but also in the entire world. The UAE attracts a whopping 14.3% FDIs from across the world. As achieving sustainability as a first priority of the GCC countries where they require more import of technology and greater FDI inflow, the level of bank risk taking may be highly affected by such priority. The other motive is that the GCC countries are generally characterized by the attractiveness of FDI as they have highly advanced infrastructure in the banking system and have many energy sources. The other motive is the presence of the dual banking system in the CGG region and the region has become highly developed since years and attractive to more incoming foreign capital.

The paper reaches to the following findings. First, the presence of FDI reduces bank stability in the GCC region. However, the existence of Islamic banks weakens the negative effect of FDI on bank stability, meaning that the existence of Islamic bank system play a significant role in the GCC banking system. The presence of the COVID-19 pandemic and the GFC outbreaks strengthen the negative impact of FDI on bank stability; the GFC crisis has a higher impact on the negative relationship between FDI on bank stability compared to the impact of the COVID-19 pandemic. Finally, the impact of FDI on bank stability is found to be heterogeneous across counties. Although Islamic banks play a significant role in stabilizing the banking systems in the GCC region, their influence in stabilizing the banking system in each individual country is different across countries. A prudent and cautious approach to supervising the growth in FDI in the GCC countries is needed in order to maintain monetary as well as financial stability.

The remainder of the study is structured as follows. Section 2 addresses the literature review. Section 3 explains the methodology and data used in the study while the analysis and the results are discussed in Section 4. In section 5, the conclusion is addressed.

Literature review

A growing body of literature examining the link between foreign direct investment and the banking sector has been noticed in recent years. However, these studies have not provided conclusive evidence or/and even a clear direction of the relationship between FDI and bank stability. According to Dunning (1973, 1980) and Hymer (1976, 1955), FDI is an important component of economic development in all counties, especially in the developing countries. However, this theory was contradicted by a number of empirical studies which found a complex relationship between FDI and economic development. A group of studies found this relationship is positive (Blomstrom and Kokko; Smarzynska, 2002; Borensztein et al., 1998; Antwi et al., 2013; Soumaré, 2015; Musah et al., 2018), while other studies they found it negative (Greenwood, 2002; Hanson, 2001; Hassen and Anis, 2012). Another study by Asiedu and Lien (2011) showed that FDI represented by foreign capital is the main contributor to economic growth. Although the impact of FDI on the economic growth has been discussed by different theories and empirical studies, the link between FDI and the banking sector remains significantly understudied.

Most recently however, it has been observed that an immense number of empirical studies have been directed towards the importance of FDI during normal and distressed market conditions. Sauvant et al. (2010) stated that during the global financial crisis (GFC), where a harsh impact was on the economic stability, FDI acted as an economic boost to the developing countries. According to Tabash (2018), international investment in Islamic banks went through turmoil when the price of crude oil fluctuated the global crisis because countries in the GCC was heavily involved in regional politics and in current events of international importance (Al Samman, 2018). Buchanan, Le and Rishi (2012) stated that in Saudi Arabia foreign funds may enter the economy either indirectly through local banks that have access to investment funds abroad or directly through equity investment and foreign direct investment.

Another group of studies have examined the impact of FDI on bank’s efficiency. For instance, Degryse et al. (2012) stated that banks accessing international funding markets could enjoy a lower cost of efficiency due to their superior reputation. Hasan and Xie (2013) found that the presence of foreign participation in the Chinese banking industry has a positive impact on the prudent behavior of Chinese banks. However, Buckley et al. (2018) argued that, after the Arab revolution, many international investors left, but banks remained efficient throughout the continuous increase in share prices in the United Arab Emirates (UAE). Alqahtani and Mayes (2018) stated that the presence of FDI in the banking sector is one of the most attractive investments due to its long-term nature, but because of the highly volatility of bank capital flows, and the direction were reversed during the 2008 crisis.

In a comparison between oil-exporting and oil-importing countries, Elheddad (2018) argued that the decline in foreign direct investment in the banking system was compensated by the increasing importance of portfolio inflows for oil-exporting countries, banking inflows for oil-importing countries, and a large part of these inflows. Almfraji and Almsafir (2014) stated that in Saudi Arabia opening the stock market to non-resident investors allowed foreigners to buy shares through barter arrangements through licensed brokers. Pao and Tsai (2011) argued that capital inflows brought significant benefits to countries by facilitating smoothing consumption fluctuations and risk diversification, along with investment financing. Similarly, Buchanan, Le and Rishi (2012) stated that banks are directly affected by the FDI in the host countries. Ramasamy, Yeung and Laforet (2012) pointed out that banks are responsible for the conversion of the earned income in the host country and they are reluctant to take risks. Konara, Tan and Johnes (2019) argued that the presence of foreign banks increases overall technical and scale efficiency of banking, but do not have an effect on pure technical efficiency, cost efficiency and revenue efficiency.

Ajide (2020) pointed out that the outflows in FDI have seen major growth during the COVID-19 pandemic. This means that when a country fails to perform well and then results in a loss for the investors, such countries pulled out their investment from the economy to reduce the amount of loss they will eventually suffer from due to the poor performing economy. As the COVID-19 cases were increasing and the death toll was increasing at a rapid pace, investors were becoming more uncertain about their investments due to more FDI flow to the GCC countries. Another study on Islamic banks (Casey, 2021) argued that changes in the policies regularly can attract more FDIs and along with the FDI it can attract the inflow of the technologies into their country and improve their infrastructure while boosting their economy. Therefore, the governments of the GCC region regulate their banking policies at regular intervals so that the investors feel safe and secure with their investments.

By examining the impact of the off-balance sheet items of in the dual banking systems (conventional and Islamic) in GCC countries, Saif-Alyousfi (2020) found that FDI inflow is negatively associated with the off-balance sheet items in GCC banks and indicated that the off-balance sheet items from conventional banks were more affected by FDI than those from Islamic banks. In another study, Alyousfi (2021) argued that FDI inflow adversely impact bank loans in the GCC region via the increase FDI-related liquidity, business activity or excessive competition in the banking market. They also argued that bank lending in conventional banks were more affected by FDI inflow than the same in Islamic banks. Shabir et al. (2022) stated that FDI net inflows have a significant influence on the banking operations in the GCC region where banks enjoy the support of the central bank and the federal government during any financial crises. Increase in FDI allows the banks to raise more funds in order to loan it out to other organizations for their development.

Altogether, the above-referenced studies have attempted to provide evidence of the impact of the FDI on bank stability. However, they have failed to a clear-cut evidence or even a right direction to the impact of FDI and bank stability. The vast majority of existing studies have mostly focused on the link between FDI and economic growth or the performance of the banking sector, but ignored the impact of FDI on bank risk taking particularly during the COVID-19 crisis. Furthermore, it is noticed that the bulk of the literature inflow has been directed towards only a limited number of countries or region while overlooked the GCC region. The existing studies have rarely examined such a topic using the comparison between conventional and Islamic banks.

Description of Variables

Dependent variable

The dependent variable in our analysis is the bank risk which is measured by the following three proxies: insolvency risk, liquidity risk, and the leverage risk. Due to the limited space in the paper these three measure are only used.

  • The insolvency risk measure is used in order to minimize the risk of bank’s destruction. If the foreign direct investment makes up a large part of the bank’s money, it is at risk of insolvency. It is necessary to analyze cash investments and build its strategy for development constantly. It is also essential to consider that when the FDI is abolished, the risk of the bank falling into the insolvency zone develops faster. Many factors may be the reasons for cancellation, starting from the planned shutdown or unforeseen circumstances. Therefore, it is necessary to have a minimum reserve of finances to guarantee that the bank will work.
  • The liquidity risk measure is used to characterize the asset side of the bank. To be specific, a higher value of liquid assets to total assets ratio is the less portfolio of investment securities, the higher the bank stability. This measure is also a source of income of the bank (Al-Shboul et al., 2020; Saif-Alyousfi, 2021). In this case, the amount of money the FDI pours in needs to be calculated carefully. Excessive investment in foreign finance can change the value of assets and affect the overall market trend. Thus, foreign re-financing and assistance to the bank with different payouts can significantly influence the domestic banking system and the depositors’ investments in other stocks and securities. It is also essential to understand that despite the price regulation, it may not have any effect on the payouts because the value of the assets can compensate for the money that foreign investments are implementing.
  • Leverage risk This risk is associated with when the bank’s loss, namely the payments to customers, prevails postponement of money from the same customers. That is why it is essential to keep careful records of the finances deposited and brought to the bank by the depositors. The FDI is designed to regulate this amount and not allow this risk to happen. But you have to understand that this regulation mechanism is not permanent, and the money from foreign investments must also be returned. This method only temporarily influences the situation when the bank cannot pay its clients. However, it cannot fully compensate for the whole problem but works at most as a mechanism of stabilization.

Independent variables

The independent variables used in our study to explain bank stability are based on the theory and literature review. The main independent variable is the proxy for the foreign direct investment inflow (FDI). This variable is connected with the estimated value of a foreign direct investment, as produced by a non-resident actor’s work. As this value rises, so does the strength of the FDI in question.

Foreign direct investment (FDIS) then, is the process of companies being acquired, controlled, and managed by, outside-the-country influences. FDI’s are an important part of the economy’s growth, providing it with the necessary monetary backing, and attracting innovation. Knowledge technology and skills are often brought into a nation along with foreign direct investment.

Control variables

Islamic (islam) refers to the presence and activity of Islamic banks in the economy. Their existence is likely to influence the stability of FDI’s and affect how risky the market environment is, affecting the foundation of the whole banking industry as a result.

  • Bank size (size): The bank size is an important issue that affects the FDI and bank stability. Large banks have more resources and a wider capacity to influence the economy, while also being capable to benefit from outside investment. The size of a bank also significantly affects its stability, with larger banks becoming less capable of maintaining a steady presence in an economy.
  • Net loan to assets (NLTA): Determines the liquidity of a bank and its capacity for risks.
  • Capital adequacy ratio (CAR) : The value is indicative of how much capital a bank has available, which can be influenced by FDI investments. With the flow of capital, it is possible for banks to make the ratio better. Furthermore, a higher CAR indicates a more economically successful bank, and a more stable one.
  • Cost-to-income (CTI): The cost to income ratio signifies an ability of the bank to cover its expenses while actively making profits. FDI’s can be considered as part of the cost for a bank’s operation, which would then have to be justified by an increase in income. The value is crucial to determine the profitability of a bank and its capacity for long-term operation. The better the value, the more capable the bank is for stable continued operation.
  • Return on assets (ROA): Return on assets signifies how effectively monetary, human and technological resources are used by a bank. For FDI’s investors, it is a key measure to understand the value of their economic support. By examining a business’s return on assets, it is possible to understand how likely it is to keep making profits in the future, and whether investment is worthwhile.
  • Liquid asset-to-assets (LATA): The liquid asset to assets ratio determines the liquidity of the bank, and its ability to quickly generate liquid capital. It is indicative of the ability of banks to pay for short term obligations and realize their other possible financial needs. Therefore, it is another indicator of a bank’s financial health and wellbeing on the market. Better LATA ratios are positively correlated with both FDI’s and bank stability.
  • Corruption (CORR): Corruption constitutes the level of potential financial liabilities or risks that come with organized businesses. Higher levels of corruption present instability, as they affect the income of a company, jeopardize its ability to accurately report its status and participate in the economy. For FDI’s corruption is also a source of worry, and can often be a deciding factor in not investing into a business.
  • Economic freedom (ECFR): Economic freedom can be considered as the ability of organizations to work, perform their duties and continue the pursuit of profit and development. It is also indicative of the level of free market’s development. Freer markets produce more companies, creating competition and economic growth, which then creates instability. At the same time, economic freedom is also a source of interest for many investors.
  • Inflation (INF): Inflation affects the purchasing power of individuals, and destabilizes the economy. It has the capacity to negatively affect FDI’s as it devalues money considerably and requires adjustment. Banks also have to consider appropriate countermeasures to inflation, influencing their long term growth strategies and outcomes.
  • Gross domestic product (GDP): GDP can be seen as an overall indication of an economy’s health, and the prospects for profit in a particular market. Economies with high GDP values are able to facilitate their businesses to prosper, attract more FDI’s and provide more opportunities for business growth.
  • Global Financial Crisis (GFC): The global financial crisis is extremely detrimental to the stability of the banking industry. During the crisis time, the population’s purchasing power drops considerably, affecting bank profits and returns on investment. During the times of financial crisis, it is possible for banks to be destabilized in losing their source of income. FDI’s similarly, have a limited capacity to invest.
  • COVID-19 pandemic (COVID): The COVID-19 pandemic affects supply chains and global connections between organizations and individuals. Furthermore, it exists as a source of worry and economic, political and social instability. Its presence is detrimental to the long term success of banks, which need the participation of their clients and investment from other sources, and FDI’s, which require clear and accessible pathways for investment.

Table 1 presents the description of the variables used in the paper.

Table 1: Description of variables
Variable Description Source
Panel A: Dependent variables – z-score bank stability measures
Insolvency risk The natural logarithm of [1 + (return on assets per bank + equity to total assets per bank)/standard deviation of the return on assets per bank]. The standard deviation is calculated as a three-year rolling-window standard deviation. A higher value designates higher bank stability and vice versa. authors’ calculation and Orbis databases
Liquidity risk The natural logarithm of the ratio of liquid assets to total assets per bank. A higher value indicates a higher bank liquidity stability and vice versa. authors’ calculation and Orbis databases
Leverage risk The natural logarithm of [Equity to assets ratio/ standard deviation of the return on assets per bank]. The standard deviation is calculated as a three-year rolling-window standard deviation. A higher value indicates the higher the bank leverage stability and vice versa. authors’ calculation and Orbis databases
Panel B: Main independent variables – Foreign direct investment
Foreign direct investment (FDI) The natural logarithm of ratio of foreign direction investment to GDP World Bank and authors’ calculation
Foreign direct investment (FDIS) This is the inward Foreign Direct Investment (FDI) stocks by country. It is the end of year total level of direct investment in the reporting country based on source countries. It is the value of equity in and net loans received by enterprises resident in the subject country from foreign investors resident in the source country. World Bank and authors’ calculation
Panel C: Control variables
Islamic (islam) A dummy variable representing Islamic banks which takes a value of 1 if the bank is an Islamic bank, or zero otherwise. authors’ calculation
Bank size (size) The natural logarithm of the average total assets authors’ calculation and Orbis databases
Net loan to assets (NLTA) The ratio of net loan to total assets. authors’ calculation and Orbis databases
Capital adequacy ratio (CAR) The percentage of the sum of Tier 1 capital and Tier 2 capital on the risk-weighted assets. authors’ calculation and Orbis databases
Cost-to-income (CTI) The ratio of operating costs including salaries, technology, administrative expenses, and others on total operating income. authors’ calculation and Orbis databases
Return on assets (ROA) Return on assets. The percentage of net profit after tax on total assets authors’ calculation and Orbis databases
Liquid asset-to-assets (∆LATA) The percentage changes in the ratio liquidity assets on total assets authors’ calculation and Orbis databases
Corruption (CORR) Estimate to Control of Corruption per country ranging between approximately -2.5 to 2.5. World bank
Economic freedom (ECFR) The economic freedom index which measures the independency of banking industry from government control and intervention. The index ranges between 0 to 100. The higher values denotes more freedom economic freedom. The Heritage Foundation
Inflation (INF) The percentage change in the rate of inflation per country. World Bank and authors’ calculation
Gross domestic product (GDP) The percentage change in the natural logarithm of annual GDP per capita. World Bank and authors’ calculation
COVID-19 pandemic (COVID) A dummy variable representing the COVID-19 pandemic crisis which takes a value of 1 for the years 2020 and 2021, or zero otherwise. Authors’ calculation
Global Financial Crisis (GFC) A dummy variable representing the subprime global financial crisis which takes a value of 1 for the years 2008 and 2009, or zero otherwise. Authors’ calculation
Note: This table provides the definitions and description of variables used in the study.

Methodology and Data

Data

The sample data of this paper contains the banks (Islamic and conventional) operating the GCC markets (Bahrain, Kuwait, Oman, Qatar, Saudi Arabia (KSA) and in the United Arab Emirates (UAE)) covering the period between 2006 and 2021. The yearly data is used and extracted from ORBIS, World Bank and the Heritage Foundation databases. Table 2 shows that the percentage of Islamic banks reaches around 64% of total banks whereas the percentage of the conventional banks reaches to 54% of total banks. This indicates that the GCC region is a bank-oriented, and more specifically, it is an Islamic bank-oriented region. The largest number of Islamic banks is in Bahrain while the lowest number of Islamic banks is in Oman.

Table 2: Number of banks per type
Country All banks Conventional banks Islamic banks
Bahrain (BAH) 32 11 21
Kuwait (KW) 21 6 15
Oman (OM) 12 9 3
Qatar (QAT) 11 6 5
Saudi Arabia (KSA) 15 9 6
United Arab Emirates (UAE) 37 28 9
Total 128 69 59
% Total 100% 54% 46%

Methodology

A panel data regression model is used to examine the impact of FDI on bank stability is implemented.

Formula

where the symbols i, j, and t refers to bank, country, and time, respectively.

  •  Stability(ijt) represents the bank stability measures based on insolvency, leverage and liquidity risks.
  • FDIjt refers to the main independent variable that measures country foreign direct investment as defined by the World Bank data.
  • Islam is a dummy variable representing the presence of Islamic banks.
  • COVIDJT is a dummy variable which represents the presence of the COVID-19 pandemic crisis and
  • GFCjt refers to the proxy for the subprime 2008-2009 global financial crisis.

Symbol

is a number of bank-level variables which represent the bank characteristics (size, capital adequacy, cost-to-income ratio, ROA, net loans to assets, and liquid asset ratio).

Symbol

is a vector of time-varying country-level variables representing the macroeconomic conditions and the institutional environment. The disturbance term,

  • εit is the error term assumed to be normally distributed εit~iid N(0, σ2).

To examine the impact of the pandemic and financial crises on the impact of FDI on bank stability, we specify the following model.

Formula

Results and analysis

Univariate analysis

Table 3 presents the summary descriptive statistics for the variables used in the study. It is clear that the mean value of bank stability measures (insolvency, leverage and liquidity) are: 4.638, 4.544, and 4.756, respectively. On average, the mean value of FDI as a percentage of GDP is approximately equal to 0.55. The Islamic banks variable is found to be positively correlated with bank stability while negatively correlated with FDI. This means that the presence of Islamic banks would lead to an increase in bank stability and the at the same time would reduce the negative impact of FDI on the overall banking system in the GCC region.

Table 3. Descriptive statistics.
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (16) (16)
Insolvency Leverage Liquidity FDI FDIS ISLAMIC SIZE NLTA CAR ROA CTI CORR ECFR LATA INF GDP
count 2043 2043 2043 1939 2048 2048 2047 2047 2047 2047 2047 2032 2048 2047 2048 1920
mean 4.6380 4.5441 4.7565 0.5499 3.2891 0.4688 15.0302 51.9801 33.19 0.7135 56.46 0.4652 68.4011 31.138 2.6237 0.0185
p25 2.8324 2.7975 2.8552 -0.2811 2.8859 0 13.6241 40.1845 15.39 0.2483 35.049 0.0406 63.1000 17.475 1.0058 -0.0655
p75 4.7384 4.6529 5.1448 1.3822 3.8226 1 16.4979 68.2142 23.3200 1.9932 64.732 1.0135 72.6000 40.099 3.3000 0.0653
sd 5.4356 5.4540 5.5659 1.2055 0.8313 0.4991 2.0759 22.8176 361.54 5.4231 296.03 0.5028 5.1991 19.707 3.3630 0.1408
min -0.1284 -1.6747 -2.2955 -2.3685 -0.2744 0 7.9638 -1.8973 -6.970 -66.021 -12870.8 -0.3297 59.6000 0.0000 -4.8633 -0.2846
max 39.7710 39.7297 40.6849 2.7569 4.4407 1 19.4560 97.6247 16320.0 44.7656 2068.5 1.5672 77.7000 98.28 15.0501 0.4774
Note: The table reports the descriptive statistics of the variables used in the study.
Table 4. Correlation coefficients’ matrix
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (16) (16)
Insolvency Leverage Liquidity FDI FDIS ISLAMIC SIZE NLTA CAR ROA CTI CORR ECFR LATA INF GDP
Insolvency 1
Leverage 0.9995* 1
Liquidity 0.9826* 0.9821* 1
FDI 0.0890* 0.0897* 0.0983* 1
FDIS -0.0685* -0.0713* -0.0599* 0.4011* 1
ISLAMIC 0.0561* 0.0576* 0.0288 0.1395* 0.0082 1
SIZE 0.0781* 0.0722* 0.1711* -0.0212 -0.1307* -0.1241* 1
NLTA 0.1146* 0.1108* 0.1051* 0.0497* -0.0403 -0.1119* 0.1344* 1
CAR 0.006 0.006 0.004 -0.001 -0.001 -0.027 -0.007 0.0226 1
ROA -0.0489* -0.0602* -0.0667* -0.0620* -0.1164* -0.1151* 0.1316* 0.1077* 0.0067 1
CTI -0.005 -0.004 -0.012 -0.004 -0.005 0.029 -0.0770* -0.0665* 0.0006 -0.0880* 1
CORR 0.004 0.004 0.016 0.1262* -0.0575* -0.1248* 0.1457* 0.1819* -0.0207 0.0530* -0.0067 1
ECFR 0.018 0.021 0.027 0.1167* 0.1459* -0.007 -0.0974* 0.0267 -0.0002 -0.1032* -0.0274 0.3916* 1
LATA -0.0930* -0.0919* -0.0482* 0.029 0.031 -0.017 -0.1389* -0.1108* 0.0029 -0.0296 0.0327 -0.1307* -0.0301 1
INF 0.0518* 0.0503* 0.0579* 0.0809* -0.2959* -0.007 0.0001 -0.0827* -0.0105 0.0770* 0.0095 0.0021 -0.1363* 0.0984* 1
GDP 0.002 0.0041 0.0039 -0.1469* -0.0584* 0.0162 0.0095 0.0238 -0.0095 -0.0403 0.0213 -0.0465* -0.0361 -0.0302 -0.1162* 1
Note: The table reports the correlation coefficients’ matrix of the variables used in the study.

Table 4 reveals the correlation coefficients among the variables used in the study. It shows that there is a strong positive correlation between the three bank stability measures and FDI. We expect that FDI increases bank stability in the GCC region. A number of bank characteristics variables, including, net loan to total assets, bank size, capital adequacy ratio are positively correlated with bank stability, while we see that other variables are negatively correlated with bank stability, such as, the cost to income ratio, long term debt to total assets ratio and the return on assets. In light of the macroeconomic variables, we expect that corruption, economic freedom, inflation and GDP increase bank stability.

Multivariate analysis

Results of the main model

The results of the relationship between FDI and bank stability are reported in Table 5. The model estimations are obtained by using the two-step GMM system panel regression methods. The coefficients in columns (1-3) are those estimated using xtabond, while the coefficients of the columns (4-6) are obtained from using the xtdpdsys. We see that FDI significantly and positively associated with bank stability. However, the presence of Islamic banks in the GCC economies has weakened the negative impact of FDI on the bank stability of the overall banking system in the GCC markets. This suggests that Islamic banks plays a significant role on the relationship between FDI and bank stability in the region.

The other issue found in Table 6 is that the presence of the COVID-19 pandemic crisis (COVID-1) and the global financial crisis (GFC) decrease bank stability. Interestingly, based on the value of the coefficients of GFC, we argue that the presence of GFC has a higher impact on reducing bank stability compared to COVID-19 crisis. Looking at the bank characteristics variables, such as bank size (SIZE), net loans to total assets (NATA) and return on assets (ROA), it is clear that these variables are positively and significantly associated with banks stability. This means that banks with higher profitability, size and long-term debt would involve less risk tolerance. However, other bank characteristics variables, such as, the percentage change in the ratio of liquid assets to total assets (∆LATA), capital adequacy ratio (CAR) and cost to income ratio (CTI) are negatively and significantly associated with banks stability – increasing bank risk tolerance.

Table 5: Estimation of the effect of FDI on bank stability
(1) (2) (3) (1) (2) (3)
Insolvency leverage liquidity Insolvency leverage liquidity
Cons -1.4740*** -2.2171*** 1.3721*** -0.9447*** -0.4585*** 4.0826***
(-16.25) (-17.09) (10.70) (-7.79) (-3.23) (32.01)
L.Insolvency 0.7951*** 0.6923***
(640.09) (542.61)
L.leverage 0.7875*** 0.6846***
(444.83) (578.76)
L.liquidity 0.7974*** 0.6912***
(409.53) (712.76)
FDI -0.0277*** -0.0092* -0.0276***
(-5.70) (-1.73) (-6.74)
L.FDI*ISLAM -0.0823*** -0.0646*** -0.0223**
(-8.15) (-7.78) (-2.43)
FDIS -0.2990*** -0.5876*** -0.8401***
(-9.04) (-15.71) (-27.60)
L.FDIS*ISLAM -0.0755*** -0.0449*** -0.1279***
(-5.78) (-2.73) (-8.38)
COVID -0.6147*** -0.6261*** -0.6132*** -0.3872*** -0.4155*** -0.3783***
(-55.06) (-66.32) (-39.73) (-52.97) (-49.98) (-40.60)
GFC -0.9054*** -0.8089*** -0.8130*** -0.5104*** -0.4658*** -0.5550***
(-72.92) (-51.17) (-50.01) (-31.33) (-43.99) (-49.21)
L.ROA 0.0493*** 0.0311*** 0.0103*** 0.0336*** 0.0179*** 0.0006
(27.78) (18.17) (7.32) (24.76) (13.47) (0.48)
L.SIZE 0.2485*** 0.3029*** 0.0756*** 0.2472*** 0.2837*** 0.0778***
(44.56) (37.18) (8.98) (24.78) (30.16) (6.75)
NLTA -0.0228*** -0.0237*** -0.0265*** -0.0086*** -0.0106*** -0.0184***
(-28.62) (-20.86) (-24.79) (-10.00) (-12.17) (-15.75)
L2.CAR -0.0074*** -0.0082*** -0.0099*** -0.0001*** -0.0001*** -0.0001***
(-10.04) (-10.95) (-10.86) (-22.92) (-17.36) (-14.14)
L.CTI -0.0001*** -0.0000*** -0.0000** -0.0002*** -0.0002*** -0.0001***
(-33.69) (-20.81) (-2.22) (-73.75) (-42.36) (-24.13)
∆.CORR -1.0622*** -1.0735*** -1.1359*** -1.1821*** -1.2331*** -1.3033***
(-25.75) (-17.25) (-24.27) (-29.43) (-27.30) (-31.61)
∆.ECFR 0.1204*** 0.1169*** 0.1196*** 0.0623*** 0.0646*** 0.0654***
(45.98) (42.07) (45.11) (51.12) (47.73) (36.62)
∆.LATA 0.0085*** 0.0066*** 0.0345*** 0.0101*** 0.0087*** 0.0338***
(20.95) (14.56) (76.50) (28.87) (22.89) (73.65)
∆.INF -0.0326*** -0.0341*** -0.0451*** -0.1000*** -0.1079*** -0.1171***
(-28.82) (-31.55) (-34.47) (-73.66) (-63.33) (-48.38)
∆.ln.GDP 2.9090*** 2.8175*** 2.9967*** 1.9430*** 2.1457*** 2.1893***
(76.19) (88.32) (69.77) (89.61) (68.80) (77.35)
Country YES YES YES YES YES YES
Year YES YES YES YES YES YES
N 1599 1599 1599 1648 1648 1648
AR(1) Arellano-Bond -2.3319 -2.3454 -2.2558 -2.3742 -2.3892 -2.2995
p-value 0.0197 0.019 0.0241 0.0176 0.0169 0.0215
AR(2) Arellano-Bond -0.76376 -0.74639 -0.96331 -0.68744 -0.60052 -0.81265
p-value 0.445 0.4554 0.3354 0.4918 0.5482 0.4164
Sargan-Hansen 112.9217 109.4934 110.0107 124.5712 123.762 120.9955
p-value 0.2586 0.3371 0.3245 0.2687 0.2987 0.2816
Wald test (F-statistic) 8148.91 9080.59 8309.84 13789.36 15230.01 18230.1
1-3 estimated using two-step GMM System dynamic panel-data estimation of Arellano-Bond dynamic panel-data estimation. 4-6 using Arellano-Bover/Blundell-Bond system estimator using two-step GMM System dynamic panel-data estimation of xtdpdsys

To take a look at the impact of FDI on bank stability with respect to the difference in bank size, we make use of another estimation for large and small sized banks. The coefficients of the main model are re-estimated by dividing out the banks into two groups (small and large banks) in order to examines whether large and small banks differently impact the relationship between FDI and bank stability. These sizes measures are determined by based on the average total assets of each bank in each year. If the bank’s total assets more than the average total assets, the bank in that year is considered large, and is considered small if its total assets in that year is less than the average of the total assets of banks. The results of the difference in the impact of FDI on bank stability on large and small banks are reported Table 6. surprisingly, Table 6 shows interesting results. We notice that increases the stability of large banks while reduces the stability of small bank. In addition, we see that large Islamic banks increase the positive effect of FDI on bank stability, suggesting that the existence large Islamic banks strengthens the stability of the banking system in the GCC region, while the presence of small Islamic banks weakens the negative impact of FDI on bank stability in the banking industry in the region. Thus, the presence of small and large Islamic banks leads to more bank stability in the GCC region.

Table 6: Estimation of the effect of FDI on bank stability per bank type
Large banks Small
(1) (2) (3) (1) (2) (3)
Insolvency leverage liquidity Insolvency leverage liquidity
Cons 3.5924*** 4.5823*** 4.0729*** -3.0736*** -4.1771*** 1.4312***
(3.38) (4.43) (4.33) (-14.65) (-26.49) (3.27)
L.insolv 0.8209*** 0.8587***
(18.09) (324.13)
L.leverage 0.8151*** 0.8548***
(19.19) (493.97)
L.liquidity 0.8693*** 0.8472***
(24.41) (362.09)
FDI 0.4749*** 0.4501*** 0.4617*** -0.1510*** -0.1523*** -0.1961***
(8.98) (9.01) (5.76) (-18.10) (-30.02) (-26.19)
FDI*ISLAM 0.8977*** 0.9189*** 0.8129*** -0.1174*** -0.1125*** -0.0611***
(5.51) (5.64) (4.53) (-11.51) (-13.47) (-4.55)
L.COVID -1.1521*** -1.1551*** -1.3225*** -0.5169*** -0.5210*** -0.5828***
(-12.45) (-9.33) (-14.99) (-36.81) (-36.64) (-24.03)
L2.GFC -0.9292*** -0.6799*** -0.5778*** -0.9241*** -0.8775*** -0.7182***
(-4.72) (-2.80) (-3.37) (-36.50) (-38.35) (-19.62)
ROA 0.0371** 0.0964** 0.1024** 0.0374*** 0.0204*** 0.0201**
(1.99) (1.89) (2.34) (14.63) (8.96) (2.03)
SIZE 0.3161*** 0.4020*** 0.2547 0.3462*** 0.452*** 0.205***
(23.11) (40.17) (1.55) (26.11) (45.17) (2.45)
L.NLTA -0.0094 -0.0125 -0.0072 -0.0248*** -0.0296*** -0.0287***
(-0.66) (-0.89) (-0.55) (-25.92) (-31.06) (-25.76)
L.CAR 0.0000*** 0.0001*** 0.0000*** 0.0008** 0.0000** -0.0043**
(2.64) (2.87) (6.92) (2.30) (2.05) (-2.38)
L.CTI -0.0411*** -0.0504*** -0.0477*** -0.0002*** -0.0001*** -0.0001***
(-3.38) (-4.79) (-4.79) (-21.41) (-12.30) (-13.15)
∆.CORR -1.6848*** -2.2414*** -2.2428*** -2.1283*** -2.0447*** -2.0113***
(-3.13) (-3.33) (-3.64) (-24.50) (-31.38) (-26.35)
∆.ECFR 0.0993*** 0.1079*** 0.0770*** 0.1798*** 0.1800*** 0.1873***
(4.47) (4.70) (3.26) (56.44) (42.33) (53.54)
∆.LATA 0.0210** 0.0079 0.0350*** 0.0034*** 0.0225*** 0.0329***
(2.43) (0.79) (3.55) (3.39) (14.26) (21.26)
∆.INF -0.0742*** -0.0685*** -0.0382** -0.0460*** -0.0465*** -0.0622***
(-5.69) (-4.80) (-2.47) (-24.26) (-37.02) (-22.89)
∆.ln.GDP -0.7446** -0.3067 -0.3346 2.8185*** 2.8238*** 2.8273***
(-2.36) (-0.83) (-0.99) (39.16) (44.88) (26.73)
N 371 371 371 1183 1183 1183
Country YES YES YES YES YES YES
Year YES YES YES YES YES YES
AR(1) Arellano-Bond -1.2955 -1.2585 -1.3085 -2.8153 -2.7922 -2.7593
p-value 0.1951 0.2082 0.1907 0.0049 0.0052 0.0058
AR(2) Arellano-Bond 0.23162 .48862 .04127 -1.2642 -.55716 -.58936
p-value 0.8168 0.6251 0.9671 0.2062 0.5774 0.5556
Sargan-Hansen 85.0850 85.43843 84.75737 96.25941 95.94516 96.40046
p-value 0.7389 0.7366 0.7376 0.9194 0.9229 0.9178
Wald test (F-statistic) 1495.08 5477.75 12025.19 730699.45 4.67e+06 2.17e+06
*, **, and *** present the level of significance: 10%, 5% and 1%, respectively. The numbers between parentheses are the value of the appropriate test (t-statistic).

COVID-19 and the effect of FDI on bank stability

To examine the impact of FDI on bank stability during COVID-19 crisis period as well as during the GFC crisis period, the main model is re-estimated using the two-step panel GMM system of equation. Table 7 provides the estimated coefficients of the effect of the crises on the relationship between FDI and bank stability for the full sample period and all banks. Our results in columns (1-3) show that the presence of both crises strengthen the negative effect of FDI of bank stability. This means that the decrease in bank stability caused by FDI rose during both crises periods – there is a higher negative impact of FDI on bank stability during the crisis compared to normal period. Interestingly, we notice that the COVID-19 crisis led to a higher negative impact on the relationship between FDI and bank stability compared to the GFC crisis.

For robustness check, we re-estimate our main model by using an alternative proxy for FDI which is the foreign direct investment stocks proxy (FDIS). Our results show qualitatively similar findings of those reported in the same Table in columns (1-3). The FDIs reduces bank stability and the role of crises increase the native impact of FDIS on bank stability. The estimated models are well-fitted and the diagnostic testing results are strongly appropriate.

Table 7: The effect of crises on the impact of FDI on bank stability – Full sample
(1) (2) (3) (1) (2) (3)
Insolvency leverage liquidity Insolvency leverage liquidity
Cons 0.0422 -0.5711*** 2.8997***
(0.35) (-4.38) (20.93)
L.Insolvency 0.7771***
(589.63)
L.leverage 0.7718***
(747.54)
L.liquidity 0.7822***
(495.49)
FDI -0.0675*** -0.0560*** -0.0603***
(-14.33) (-10.32) (-14.17)
COVID*FDI 0.3607*** 0.3478*** 0.3461***
(23.88) (23.78) (18.31)
L.GFC*FDI 0.0566*** 0.0756*** 0.0337**
(5.59) (5.93) (2.50)
L.ROA 0.0558*** 0.0367*** 0.0150***
(27.90) (27.01) (10.31)
L.SIZE 0.1389*** 0.1874*** -0.0251**
(21.17) (27.75) (-2.57)
NLTA -0.0241*** -0.0255*** -0.0297***
(-30.65) (-27.94) (-42.27)
L2.CAR -0.0057*** -0.0067*** -0.0085***
(-10.68) (-9.35) (-11.48)
L.CTI 0.0001*** 0.0000*** -0.0000**
(21.47) (9.16) (-2.02)
∆.CORR -0.5556*** -0.5983*** -0.6515***
(-13.80) (-14.71) (-18.85)
∆.ECFR 0.0948*** 0.0916*** 0.1010***
(35.59) (24.25) (39.01)
∆.LATA 0.0063*** 0.0047*** 0.0324***
(14.62) (10.37) (93.22)
∆.INF -0.0333*** -0.0329*** -0.0439***
(-23.49) (-20.75) (-28.22)
∆.ln.GDP 1.9256*** 1.9229*** 2.0103***
(83.06) (86.70) (70.89)
Country YES YES YES
Year YES YES YES
N 1599 1599 1599
AR(1) Arellano-Bond -3.2567 -3.2845 -3.3118
p-value 0.0011 0.0010 0.0009
AR(2) Arellano-Bond -1.0701 -.85457 -1.9258
p-value 0.2846 0.3928 0.0541
Sargan-Hansen 123.5527 123.65 121.6651
p-value 0.3213 0.3191 0.3653
Wald test (F-statistic) 1.64e+07 2.35e+07 4.71e+06
*, **, and *** present the level of significance: 10%, 5% and 1%, respectively. The numbers between parentheses are the value of the appropriate test (t-statistic).

Another analysis is conducted in this study covering the effect of crises on the relationship between FDI and bank stability across both types of banks. This analysis is performed to examine whether the presence of crises can differently influence the relationships between FDI and Islamic banks’ stability and conversational banks stability. The results are reported in Table 8. Generally, our results show a negative impact of FDI on bank stability of each type of banks, meaning that FDI reduces bank stability of both banking systems. FDI has a greater negative impact on bank stability of conventional bank compared to its impact on bank stability of Islamic banks.

In light of the crises, our results show that the presence of both crises strengthen the negative impact of FDI on bank stability on both banking systems. This suggest that the COVID-19 pandemic and the GFC event leads to FDI to cause a greater reduction in bank stability in both banking systems compared to the normal market conditions. However, if a comparison of the FDI and bank stability of each system during both crises is taken, interesting results are shown in Table 8. For instance, our results reveals that during both crises, FDI has a greater negative impact on the stability of conventional banks more than for the stability of Islamic banks. This negative impact is higher during the GFC than during the COVID-19 crisis.

Table 8: The effect of crises on the impact of FDI on bank stability per bank type
Conventional banks Islamic banks
(1) (2) (3) (1) (2) (3)
Insolvency leverage liquidity Insolvency leverage liquidity
Cons 3.5441*** 2.7849*** 5.6402*** -1.9866*** -5.9078*** 0.4189
(5.68) (5.14) (8.19) (-6.33) (-7.71) (0.69)
L.insolv 0.6519*** 0.8062***
(87.76) (332.33)
L.leverage 0.6588*** 0.8032***
(112.08) (253.09)
L.liquidity 0.5985*** 0.8169***
(81.73) (381.61)
FDI -0.0689*** -0.0868*** -0.0914*** -0.0662*** -0.0716*** -0.0789***
(-3.00) (-4.45) (-3.26) (-4.40) (-6.72) (-8.80)
COVID*FDI 0.1934*** 0.1922*** 0.2898*** 0.0380 0.0556* 0.1728***
(4.03) (4.39) (6.33) (0.76) (1.68) (5.21)
GFC*FDI 0.8572*** 0.8973*** 0.9276*** 0.8364*** 0.8536*** 0.8576***
(10.55) (14.55) (14.11) (26.03) (27.69) (21.96)
L.ROA 0.0813*** 0.0625*** 0.0263*** 0.0211*** 0.0049* -0.0039
(10.55) (7.04) (3.86) (9.42) (1.72) (-1.17)
L.SIZE -0.1553*** -0.0855** -0.1756*** 0.2167*** 0.4842*** 0.0949**
(-3.42) (-1.99) (-3.66) (9.18) (10.07) (2.32)
NLTA 0.0090** 0.0043 -0.0124*** -0.0285*** -0.0273*** -0.0372***
(2.36) (1.26) (-3.98) (-13.31) (-5.00) (-14.60)
L2.CAR -0.0021 -0.0042*** -0.0030 0.0313*** 0.0305*** 0.0163***
(-1.61) (-3.46) (-1.17) (13.32) (13.21) (8.00)
L.CTI -0.0074*** -0.0080*** -0.0108*** 0.0001*** 0.0000*** 0.0000**
(-6.80) (-6.99) (-10.20) (5.83) (5.91) (2.21)
∆.CORR -1.2429*** -1.1242*** -1.2615*** -1.7213*** -1.6661*** -1.5654***
(-7.33) (-9.42) (-6.25) (-12.17) (-17.19) (-11.85)
∆.ECFR 0.0167*** 0.0195*** 0.0183** 0.0449*** 0.0412*** 0.0448***
(3.02) (3.23) (2.23) (5.55) (9.80) (6.65)
∆.LATA 0.0086*** 0.0071*** 0.0254*** 0.0112*** 0.0088*** 0.0373***
(3.58) (3.81) (13.36) (11.17) (5.00) (32.49)
∆.INF -0.0139*** -0.0152*** -0.0209*** -0.0627*** -0.0751*** -0.0913***
(-3.74) (-4.04) (-6.20) (-13.68) (-18.89) (-20.60)
∆.ln.GDP 1.1157*** 1.2709*** 1.2764*** 3.0177*** 3.2597*** 3.2661***
(13.13) (25.84) (15.65) (21.89) (21.76) (20.39)
Country YES YES YES YES YES YES
Year YES YES YES YES YES YES
N 883 883 883 837 739 739
AR(1) Arellano-Bond -1.8003 -1.8708 -1.7815 -2.8396 -2.8454 -2.8678
p-value 0.0718 0.0614 0.0748 0.0045 0.0044 0.0041
AR(2) Arellano-Bond -1.2524 -1.082 -1.2854 .07374 .29103 -1.1216
p-value 0.2104 0.2792 0.1987 0.9412 0.7710 0.2620
Sargan-Hansen 99.73912 98.87498 90.55404 95.39713 95.37762 95.73284
p-value 0.7540 0.7498 0.7564 0.7731 0.7545 0.7762
Wald test (F-statistic) 349326.84 421340.84 87607.20 493847.22 1.14e+06 1.10e+06
*, **, and *** present the level of significance: 10%, 5% and 1%, respectively. The numbers between parentheses are the value of the appropriate test (t-statistic).

The other issue of analysis taken in our paper is the examination of the relationship between FDI and bank stability for each individual banking system at each individual country. By looking at the

Table 9: The impact of FDI on bank stability per country – Full sample
(1) (2) (3) (4) (5) (6)
Insolvency Insolvency Insolvency Insolvency Insolvency Insolvency
Cons -3.2355*** -3.7899*** -3.3091*** -2.8354*** -2.9348*** -3.1526***
(-12.84) (-14.01) (-14.32) (-9.95) (-12.78) (-12.52)
L.insolv 0.7841*** 0.7803*** 0.7853*** 0.7810*** 0.7866*** 0.7823***
(369.07) (359.17) (358.14) (351.28) (523.10) (351.81)
FDI -0.0953*** -0.0454*** -0.0626*** -0.0687*** -0.1025*** -0.0568***
(-14.33) (-6.78) (-9.60) (-9.36) (-16.06) (-8.28)
L.Bahrain*FDI 0.0974***
(8.96)
L.Kuwait*FDI 0.2846***
(4.11)
L.UAE*FDI 0.1446***
(8.26)
L.OMAN*FDI 1.6827***
(24.60)
L.QATAR*FDI 0.3464***
(8.32)
L.KSA*FDI 0.0697***
(3.49)
covid -0.4615*** -0.3551*** -0.4475*** -0.5601*** -0.3970*** -0.4131***
(-40.34) (-41.03) (-44.08) (-55.85) (-35.33) (-30.33)
gfc -0.4195*** -0.3632*** -0.3557*** -0.4184*** -0.3946*** -0.3596***
(-18.65) (-13.63) (-17.97) (-18.32) (-16.85) (-15.29)
L.roa 0.0520*** 0.0542*** 0.0537*** 0.0506*** 0.0523*** 0.0529***
(20.00) (21.08) (22.04) (17.64) (19.01) (19.47)
L.size 0.3610*** 0.3990*** 0.3651*** 0.3242*** 0.3439*** 0.3579***
(21.31) (23.51) (23.09) (17.27) (22.38) (22.65)
NLTA -0.0227*** -0.0228*** -0.0234*** -0.0229*** -0.0231*** -0.0232***
(-16.76) (-16.97) (-15.00) (-19.49) (-15.79) (-12.89)
L2.CAR -0.0071*** -0.0074*** -0.0077*** -0.0077*** -0.0084*** -0.0079***
(-5.38) (-7.46) (-8.02) (-8.87) (-8.19) (-6.68)
L.CTI -0.0001*** -0.0001*** -0.0001*** -0.0001*** -0.0001*** -0.0001***
(-27.68) (-19.62) (-27.74) (-28.94) (-22.95) (-23.08)
∆.corr -0.3983*** -0.5072*** -0.4935*** -0.7834*** -0.3157*** -0.4329***
(-7.10) (-9.43) (-8.91) (-14.76) (-6.03) (-7.58)
∆.eco_free 0.0966*** 0.0948*** 0.0978*** 0.0960*** 0.0917*** 0.0942***
(39.57) (31.26) (35.00) (32.22) (28.25) (33.49)
∆.LATA 0.0077*** 0.0065*** 0.0067*** 0.0077*** 0.0069*** 0.0068***
(11.00) (10.50) (11.02) (11.61) (10.41) (11.25)
∆.inf -0.0654*** -0.0619*** -0.0654*** -0.0673*** -0.0641*** -0.0610***
(-34.95) (-30.35) (-37.08) (-42.99) (-34.25) (-35.36)
∆.gdp 2.7502*** 2.5013*** 2.6869*** 2.7500*** 2.5503*** 2.6221***
(49.99) (60.02) (67.83) (75.11) (62.87) (67.21)
Year YES YES YES YES YES YES
N 1428 1428 1428 1428 1428 1428
AR(1) Arellano-Bond -3.2669 -3.269 -3.2666 -3.2604 -3.2626 -3.266
p-value 0.0011*** 0.0011*** 0.0011*** 0.0011*** 0.0011*** 0.0011***
AR(2) Arellano-Bond -1.1389 -1.1446 -1.0664 -.9299 -1.1196 -1.1533
p-value 0.2547 0.2524 0.2862 0.3524 0.2629 0.2488
Sargan-Hansen 119.6529 117.9892 118.6854 119.8803 118.4569 118.6537
p-value 0.1253 0.1484 0.1384 0.1224 0.1416 0.1388
Wald test (F-statistic) 525009.07*** 553867.62*** 1.37e+06*** 338980.28*** 955261.87*** 680572.56***
Table 10: The impact of FDI on bank stability per country – Conventional banks
(1) (2) (3) (4) (5) (6)
Insolvency Insolvency Insolvency Insolvency Insolvency Insolvency
Cons 2.7379*** 2.3741** 3.3464*** 3.7798*** 2.6377*** 2.2761***
(3.62) (2.39) (5.15) (6.68) (2.58) (3.04)
L.insolv 0.6532*** 0.6549*** 0.6603*** 0.6502*** 0.6574*** 0.6561***
(100.31) (224.21) (120.29) (157.89) (182.18) (94.53)
FDI 0.1412*** 0.1662*** 0.1668*** 0.1389*** 0.1072*** 0.1338***
(9.41) (10.31) (12.10) (9.49) (6.46) (8.57)
L.Bahrain*FDI 0.0609**
(2.56)
L.Kuwait*FDI 0.0486
(0.23)
L.UAE*FDI 0.4192***
(11.45)
L.OMAN*FDI 0.9712***
(6.58)
L.QATAR*FDI 0.6016***
(3.69)
L.KSA*FDI 0.4478***
(4.10)
covid -0.5380*** -0.4735*** -0.6075*** -0.6470*** -0.4961*** -0.4508***
(-15.06) (-11.84) (-15.48) (-17.20) (-11.26) (-15.29)
gfc -0.0360 -0.0549** 0.0251 0.0129 -0.0441* -0.1127***
(-0.83) (-2.06) (0.83) (0.46) (-1.78) (-2.97)
L.roa 0.0523*** 0.0478*** 0.0579*** 0.0576*** 0.0489*** 0.0519***
(7.85) (8.31) (8.28) (12.63) (10.64) (8.52)
L.size -0.0636 -0.0444 -0.1240*** -0.1328*** -0.0500 -0.0434
(-1.33) (-0.69) (-2.97) (-3.66) (-0.78) (-0.92)
NLTA -0.0004 0.0020 0.0022 -0.0015 -0.0017 0.0007
(-0.12) (0.73) (0.60) (-0.44) (-0.62) (0.27)
L2.CAR -0.0043** -0.0085*** -0.0037 -0.0062*** -0.0058*** -0.0042**
(-2.33) (-3.34) (-1.43) (-5.33) (-2.81) (-2.42)
L.CTI -0.0062*** -0.0058*** -0.0076*** -0.0062*** -0.0062*** -0.0054***
(-6.02) (-4.77) (-8.59) (-5.65) (-6.13) (-4.39)
∆.corr -0.1776** -0.1814*** -0.4200*** -0.3747*** 0.0205 -0.1400*
(-1.99) (-3.11) (-3.48) (-2.81) (0.18) (-1.67)
∆.eco_free 0.0466*** 0.0551*** 0.0549*** 0.0408*** 0.0488*** 0.0315***
(7.66) (8.38) (8.14) (6.52) (11.02) (4.84)
∆.LATA 0.0030 0.0055*** 0.0041* 0.0024 0.0038** 0.0022
(1.61) (4.31) (1.70) (1.13) (2.27) (1.09)
∆.inf -0.0083** -0.0119** -0.0206*** -0.0123*** -0.0080* -0.0058
(-2.21) (-2.57) (-4.74) (-3.00) (-1.92) (-1.53)
∆.gdp 0.6631*** 0.5764*** 1.1287*** 0.6562*** 0.5206*** 0.7536***
(9.76) (7.03) (12.12) (7.80) (6.16) (10.41)
Year YES YES YES YES YES YES
N 856 883 856 856 856 856
AR(1) Arellano-Bond -1.7163 -1.7361 -1.729 -1.7019 -1.7089 -1.7131
p-value 0.0861* 0.0825* 0.0838* 0.0888* 0.0875* 0.0867*
AR(2) Arellano-Bond -1.2889 -1.2835 -1.3334 -1.2409 -1.2763 -1.289
p-value 0.1974 0.1993 0.1824 0.2146 0.2019 0.1974
Sargan-Hansen 156.541 160.050 162.491 155.611 157.252 157.440
p-value 0.4523 0.4672 0.4589 0.5986 0.5874 0.6201
Wald test (F-statistic) 298120.86*** 79189.19*** 175758.62*** 112838.80*** 105639.99*** 71259.74***
Table 11: The impact of FDI on bank stability per country – Islamic Banks
(1) (2) (3) (4) (5) (6)
Insolvency Insolvency Insolvency Insolvency Insolvency Insolvency
Cons -1.9213*** -1.9237*** -1.2966*** -2.9086*** -1.6159*** -1.0842*
(-3.95) (-3.68) (-3.03) (-4.53) (-3.11) (-1.70)
L.insolv 0.7730*** 0.7681*** 0.7786*** 0.7713*** 0.7762*** 0.7734***
(334.99) (344.83) (277.08) (326.68) (176.20) (301.02)
FDI -0.0959*** -0.0441*** -0.1115*** -0.0698*** -0.1028*** -0.0667***
(-9.09) (-5.42) (-8.09) (-5.44) (-6.51) (-4.94)
L.Bahrain*FDI 0.1419***
(10.33)
L.Kuwait*FDI 0.1341
(0.82)
L.UAE*FDI -1.3286***
(-10.94)
L.OMAN*FDI 1.8656***
(3.67)
L.QATAR*FDI 0.7430**
(2.09)
L.KSA*FDI 0.1656**
(2.09)
Covid -0.7630*** -0.5669*** -0.4439*** -0.7083*** -0.6275*** -0.6506***
(-43.92) (-29.16) (-11.18) (-39.88) (-23.34) (-26.05)
Gfc -0.3529*** -0.1832** -0.4780*** -0.1816** -0.3272*** -0.3070***
(-3.73) (-2.14) (-6.52) (-2.44) (-4.05) (-3.39)
L.roa 0.0270*** 0.0292*** 0.0258*** 0.0229*** 0.0273*** 0.0261***
(7.05) (7.99) (9.06) (6.59) (8.78) (9.30)
L.size 0.3020*** 0.3199*** 0.2862*** 0.3749*** 0.2950*** 0.2468***
(7.74) (8.20) (8.70) (7.63) (8.24) (5.42)
NLTA -0.0344*** -0.0387*** -0.0367*** -0.0391*** -0.0373*** -0.0348***
(-10.72) (-12.46) (-10.59) (-9.93) (-15.25) (-13.67)
L2.CAR 0.0008 -0.0013 -0.0023 0.0016 -0.0015 0.0001
(0.70) (-0.67) (-1.39) (0.66) (-0.95) (0.05)
L.CTI -0.0002*** -0.0002*** -0.0002*** -0.0002*** -0.0002*** -0.0002***
(-7.64) (-13.88) (-9.65) (-10.21) (-10.09) (-9.47)
∆.corr -1.0023*** -1.1338*** -0.5085*** -1.4416*** -1.1472*** -0.8968***
(-11.14) (-8.36) (-3.53) (-8.39) (-8.54) (-6.09)
∆.eco_free 0.1582*** 0.1540*** 0.1350*** 0.1496*** 0.1388*** 0.1502***
(18.91) (13.84) (16.37) (23.51) (16.22) (22.86)
∆.LATA 0.0114*** 0.0097*** 0.0110*** 0.0114*** 0.0122*** 0.0118***
(10.63) (11.07) (3.29) (9.91) (10.71) (9.99)
∆.inf -0.0730*** -0.0647*** -0.0623*** -0.0730*** -0.0773*** -0.0632***
(-10.48) (-11.42) (-9.35) (-14.60) (-10.81) (-10.13)
∆.gdp 3.3727*** 2.8705*** 2.8115*** 3.0278*** 2.9754*** 3.1683***
(22.94) (22.57) (20.99) (18.32) (16.02) (20.37)
Year YES YES YES YES YES YES
N 740 740 740 740 740 740
AR(1) Arellano-Bond -2.8218*** -2.8042*** -2.7978*** -2.8078*** -2.8039*** -2.8101***
p-value 0.0048 0.0050 0.0051 0.0050 0.0050 0.0050
AR(2) Arellano-Bond 0.72673 0.64112 0.09318 0.82574 0.63012 0.57249
p-value 0.4674 0.5214 0.9258 0.4090 0.5286 0.5670
Sargan-Hansen 115.704 115.762 114.201 116.125 114.886 112.712
p-value 0.6502 0.6621 0.6702 0.5621 0.5596 0.5879
Wald test (F-statistic) 1.41e+06*** 1.02e+06*** 1.14e+06*** 1.62e+06*** 4.00e+06*** 1.37e+06***

Conclusion

The paper examined the impact of foreign direct investment (FDI) on bank stability in the context of dual banking systems (Islamic and conventional) region (the Gulf Cooperative Council (GCC)) with respect to COVID-19 pandemic and the global financial crisis (GFC). A sample of banks operating in the six countries covering the period between 2006 and 2021 was used. Using a panel data analysis, our analysis suggests that FDI reduces bank stability in the GCC region. However, the presence of Islamic banks in this region reduces the negative impact of FDI on bank stability. FDI increases bank stability of Islamic banks whereas decreases bank stability of conventional banks. We also argue that COVID-19 and GFC increases the negative impact of FDI on bank stability; the COVID-19 pandemic strengthens on the negative impact of FDI on bank stability more than GFC does. When treating such effect in each individual country, it is clear that FDI weakens bank stability of Islamic banks by a higher magnitude than the strengthens increase in the positive impact of FDI on bank stability of conventional banks. This suggests that although Islamic banks play a significant role in stabilizing the banking systems in the GCC region, they have less influence in stabilizing the banking system in each individual country.

What are the contributions of the study to the theory and empirical studies?

We need here a policy implication paragraph and how these implications have contributed to the research community The findings of our paper has a number of important policy implications. First, our findings can help policymakers in GCC countries identify the attractive foreign capital inflow that support the non-oil sectors, such as, the banking sector in order to achieve more diversification in their economies. For instance, attracting foreign technologies to the banking sectors can be one of the best ways to improve economies. Furthermore, the GCC authorities can entice more foreign capital in green finance technologies in order to reduce carbon gas emission and continue with sustainability in the banking sectors.

Based on the findings of our paper, we could draw a number of recommendations. The GCC authorities have to adopt more regulatory policy in order to compete with other nations in attracting more foreign capital inflow. This would make the GCC region more competitive at the global level. These regulatory policies such as creating more transparent and clear legal systems to protect property rights, especially when importing high technology are used in the banking systems. The authorities in the GCC countries are recommended to always improve infrastructure (electricity, telecommunications and roads) and allow for the labor market liberalization. In addition, they are advised to adopt investment promotion strategy to attract more foreign investments, especially those can lead to increase in export.

Our findings offer a number of interesting policy implications. First it provides evidence of the systemic importance of FDI inflows on bank stability in the GCC region. Given that management of liquidity and investment within the financial system is certainly one of the main concerns of regulators (central banks), understanding such systemic importance by regulators and policymakers is vital in this occasion. Furthermore, as bank stability has become one of the key agendas of central banks, the attractiveness of the GCC economies to foreign investment, both through FDI and in the stock market, has to be monitored by regulators and authorities in order to avoid mismanagement of liquidity and unexpected losses in banks.

Investors in the banking sector of the GCC region are can benefit from our paper’s results. As local banks in the GCC countries are operating in a highly competitive environment with their foreign peers and might lose out their reliable customers as well as non-fund-based business to foreign banks operating in the GCC region, investors have to control their portfolio investment risk profiles, technological dominance and management expertise. High competition would lead local banks to offer higher interest rates on deposit as well as on lending to maintain their customers’ market share. These higher interest rates would lead to more costs, potential economic stress as well as trigger large defaults in the lending portfolios of local banks. Thus, banks in the GCC region have to support domestic banks and let them focus on capacity building initiatives and technology upgrade and to significantly improve their operational efficiency to face competitive pressure.

In any case, a close look at fund-based as well as non-fund-based activities of foreign banks should be ruled by the central banks in the region. Both government and the regulators of the financial systems of the GCC economies can benefit from our findings by balancing the need to promote FDI and maintain the safety and soundness of the financial system. Finally, the findings of this paper attests to the importance of bank stability of both types of banking systems and emphasizes the need for a prudent and cautious approach to supervising the growth in FDI in the GCC countries in order to maintain monetary as well as financial stability. Monetary authorities may re-examine the definitions of liquidity indicators; that is, they need to account for unused OBS commitments to identify the amount of total liquidity, and hence to redefine the monetary aggregates. However, such actions need to be validated by further research. Future research work can be conducted in this topic where the difference in the impact of different types of FDI on bank stability could be examined in a new sample period of the GCC region. On the GCC countries, a research attempt might be taken to explore the specific channels through which FDI affects bank stability.

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Footnotes

  1. The inward foreign direct investment (FDI) can be in different forms such as the entry of multinational corporations and banks to the host country as well as the presence of a composite bundle of capital stock and technology in the host economy. Thangavelu and Narjoko (2014) indicated that FDI is the flow of capital, transfer of new technologies, marketing techniques and management skills into the host economy, and thus potentially increasing its competitiveness and productivity and stimulates economic growth.
  2. Web.
  3. A number of studies examined the determinants of FDI in the UAE and other countries (see, Alqahtani and Mayes, 2018; Buckley et al., 2018; Mosteanu, 2019).