Exploring the bearing of liquidity risk in the Middle East and North Africa (MENA) banks

Khalaf, Bashar Abu; Awad, Antoine B. Article Exploring the bearing of liquidity risk in the Middle East and North Africa (MENA) banks Cogent Economics & Finance Provided in Cooperation with: Taylor & Francis Group Suggested Citation: Khalaf, Bashar Abu; Awad, Antoine B. (2024) : Exploring the bearing of liquidity risk in the Middle East and North Africa (MENA) banks, Cogent Economics & Finance, ISSN 2332-2039, Taylor & Francis, Abingdon, Vol. 12, Iss. 1, pp. 1-16, https://doi.org/10.1080/23322039.2024.2330840 This Version is available at: https://hdl.handle.net/10419/321462 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Cogent Economics & Finance ISSN: 2332-2039 (Online) Journal homepage: www.tandfonline.com/journals/oaef20 Exploring the bearing of liquidity risk in the Middle East and North Africa (MENA) banks Bashar Abu Khalaf & Antoine B. Awad To cite this article: Bashar Abu Khalaf & Antoine B. Awad (2024) Exploring the bearing of liquidity risk in the Middle East and North Africa (MENA) banks, Cogent Economics & Finance, 12:1, 2330840, DOI: 10.1080/23322039.2024.2330840 To link to this article: https://doi.org/10.1080/23322039.2024.2330840 © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group Published online: 24 Mar 2024. Submit your article to this journal Article views: 2105 View related articles View Crossmark data Citing articles: 12 View citing articles Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=oaef20 FINANCIAL ECONOMICS | RESEARCH ARTICLE Exploring the bearing of liquidity risk in the Middle East and North Africa (MENA) banks Bashar Abu Khalaf and Antoine B. Awad College of Business, Accounting & Finance Department, University of Doha for Science and Technology, Doha, Qatar ABSTRACT The paper examines how liquidity risk affects the Middle East and North Africa (MENA) bank profitability. Banks need profitability to survive, but liquidity risk measures long-term company health. Through Refinitiv Eikon, quantitative data was collected over 11 years from 2012 to 2022 for 71 MENA banks to support the theoretical study. Return on Equity (ROE), a profitability indicator, is the dependent variable, whereas liquidity risk is the independent variable and controlling for size, loan quality, inflation, gross domestic product, income diversification, operational efficiency, capital adequacy, and growth. This study estimates the impact of liquidity risk on MENA bank profitability using OLS and panel regression (fixed and random effects). Several results were found, such as that bank size, operational efficiency, and non-performing loans negatively affect profitability, suggesting that large banks have higher operating costs and may weaken profitability in MENA. Besides, additional non-performing loans increase the bank’s costs and thus diminish profitability. Also, if the bank has no control over the operational expenses, then this will lead to reduce profitability. Liquidity risk, capital adequacy, income diversification, and growth have a positive significant impact on ROE implying that banks with higher growth opportunities, better capital adequacy ratio, more income sources, and liquidity risk will result in higher profitability as explained by the risk-reward theory. The results are robust and this has been confirmed by applying the Generalized Method of Moments (GMM). IMPACT STATEMENT This study aims to investigate the influence of liquidity risk on the profitability of banks in the Middle East and North Africa (MENA) region over the period of 2012 to 2022 for a total of 71 banks. The analysis employs Ordinary Least Squares (OLS) and panel regression techniques, including fixed and random effects models. The results are robust and this has been verified by implementing the Generalized Method of Moments (GMM). Multiple findings indicate that factors such as bank size, operational efficiency, and non-performing loans have a negative impact on profitability. Besides, Liquidity risk, income diversification, growth, capital adequacy and gross domestic product have positive impact on profitability. This study provides valuable insights into the complex relationship between liquidity risk and profitability in the banking sector of the Middle East and North Africa (MENA) region. The study's conclusions not only contribute to academic knowledge but also have practical consequences for banking professionals, regulators, and investors, highlighting its broad influence across various sectors. ARTICLE HISTORY Received 25 June 2023 Revised 8 March 2024 Accepted 12 March 2024 KEYWORDS Liquidity risk; banks; return on equity; MENA region; panel regression REVIEWING EDITOR David McMillan, University of Stirling, United Kingdom SUBJECTS Economics; Finance; Business, Management and Accounting JEL G15; G20; G33 1. Introduction In countries of the Middle East and North Africa (MENA), banks are the main providers of financial services, as the economies have bank-based financial systems (Uzunkaya, 2012). Therefore, having vibrant banks is crucial for the MENA region as ill-performing banks or a failing banking sector impact the economy adversely. Furthermore, sound banks are considered to support the economy in unfavorable CONTACT Dr. Bashar Abu Khalaf [email protected] College of Business, Accounting & Finance Department, University of Doha for Science and Technology, Doha, Qatar ß2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. COGENT ECONOMICS & FINANCE 2024, VOL. 12, NO. 1, 2330840 https://doi.org/10.1080/23322039.2024.2330840 conditions and crises (Rdaydeh et al., 2017). Technological innovation, globalization, and a competitive market environment challenge the profitability of banks globally and in the MENA region. However, little is known about the factors that contribute to vibrant and profitable banks in this region. Our paper fills this research gap by studying bank and country-specific impact factors on banks’profitability using a sample of 71 MENA banks for the years 2012 to 2022. Liquidity risk can be defined as an arising risk when a bank is unable to meet its obligations at the time of due in the absence of incurring undesirable losses (Ismail & Ahmed, 2023). Therefore, this risk can have an adverse impact on the financial institutions’capital and earnings. The bank’s management should ensure that there are sufficient funds available to fulfill future requests from lenders and borrowers at reasonable rates. Similarly, Hacini et al. (2021) defined liquidity risk as the possibility for an institution to lose money if it is unable to pay its bills on time or fund asset growth when it becomes necessary without incurring unacceptably high costs or losses. Another definition of liquidity risk is the danger of being unable to quickly and affordably liquidate a position. The influence of the liquidity situation on the management of banks and other economic units has always been attractive and compelling. In the literature over the years, there seems to have been an endless debate on the functions, significance, and factors that affect liquidity risk. The goal of liquidity management is to ensure that an asset may be rapidly and reliably converted back into funds (cash or income) anytime the asset holder desires (Khalaf & Alajlani, 2021; Saleh et al., 2020). A liquid financial institution is when it has enough cash and liquid assets on hand, in addition to the capability to quickly raise funds through additional sources aiming to satisfy its financial commitments and respect deadlines for payments (Ouma, 2015). Furthermore, this empirical paper investigates the impact of liquidity risk on banks’profitability in the MENA region. This empirical paper is structured in five sections. Section 2 provides a summary of selected previous studies and Section 3 explains the methodology and the model development. Section 4 highlights the results and discussion. Section 5 shows the conclusion of this paper. 2. Literature review Bourke (1989) examined the drivers of return on assets and found that institutions with superior liquidity generate better earnings. Banks typically have excessive profitability if they have excessive liquidity, according to Kosmidou’s(2008) observation. Moreover, Rahman et al. (2015) also researched liquidity risk and profits by analyzing the results of a selected sample of 25 Bangladeshi financial institutions between the years of 2003 and 2006. The findings indicate a link between both liquidity risk and bank profitability, indicating that institutions require greater liquidity to run more effectively. Liquidity, according to Islam & Nishiyama (2016), contributes to the profitability of banks but does not significantly do so. Chen et al. (2018) used panel data from 12 developed economies from 1994 till 2006 to identify factors driving Liquidity risk as well as its relationship to financial institutions profitability. The findings demonstrated a basic and adverse relationship between liquidity risk and profitability as projected through the funding gap. As predicted by ROA and ROE, a better financing gap (greater liquidity) lowers financial institution revenue. These facts lead to a conclusion stating that the profitability of financial institutions is significantly impacted by liquidity risk. The impact of liquidity risk on the profitability of financial institutions, as determined by the return on equity in the Eurozone region, was discussed by Toutou and Xiaodong in 2011. Regression analysis was used to analyze secondary data that was gathered from financial reports for 12 banks in the Eurozone region between the years 2005 and 2010. The findings showed that liquidity risk has a favorable effect on ROE in the Eurozone region. Similar findings were made by Ruziqa (2013), who used secondary data gathered from 23 traditional banks between 2007 and 2011 to examine such a relationship in Indonesia and found that there was a positive significant relationship. Liquidity was highlighted as one of the elements affecting profitability by Berr ıos (2013) in research aiming to identify the determinants of profitability in commercial financial institutions in Kenya. The research involved 35 financial institutions with the data for 5 years. The study estimated the factors influencing commercial banks’profitability using descriptive statistics and multiple regression analysis. The study concluded that liquid assets considerably influence the profitability of commercial banks, 2 B. ABU KHALAF AND A. B. AWAD particularly during the time of political chaos following elections. The results also showed that both the insider holdings in addition to the tenure of the CEO impact negatively the bank’s performance. Rahman et al. (2015) examined the relationship between liquidity risk and Bangladeshi financial institutions’profitability as determined by return on equity. The outcome was determined through the analysis of secondary data gathered from 6 banks out of which 3 banks were Islamic institutions and 3 other conventional commercial banks between 2007 and 2011. The results of the study revealed that the bank’s regulatory capital, size, liquidity, and loan intensity are positively influencing its profitability. Besides, other variables such as the bank’s cost efficiency and off-balance sheet activities in addition to the inflation rate are negatively influencing its profitability. Similarly, Saeed discovered this by analyzing 27 commercial Malaysian financial institutions using secondary data from the years 2005 to 2013 and the final results confirmed the positive impact of the bank’s liquidity on its profitability. Ouma (2015) investigated the effect of liquidity risk on profitability. It was found out that if liquidity issues are left unchecked, they can negatively affect a financial organization’s capital, profitability, and, in extreme cases, even cause the institution to fail. In addition, a financial institution having liquidity issues might additionally experience problems in satisfying the demands of customers, although this liquidity risk can be avoided by keeping appropriate cash on hand, increasing the deposit base, and improving the commercial banks’profitability. A financial institution’s dependency on the financial markets would be less just with enough cash holdings; thus, minimizing the cost of overnight borrowing. Such issues must be directly sermonized and instantaneous measures need to be considered to evade the outcomes of illiquidity. To have a better understanding of liquidity risk and ROA, Salim & Bilal (2016) also investigated this connection in the Middle Eastern country Oman. The data was gathered from the annual reports of 4 Omani financial institutions for the period 2010-2014. Using the multiple regression analysis, the authors proved that the loan-to-total assets ratio and the liquid assets-to-total deposits are significantly influencing the bank’s ROA. Besides, this study failed to identify a significant relationship between the bank’s liquidity position and its net interest margin. Malik et al. (2016) additionally discovered a mere relationship between liquidity and profitability in the private sector banks of Pakistan. The dataset was collected from 22 private Pakistani banks for the period 2009-2013. The study utilized the ordinary least square regression to prove statistically that the liquidity position of the Pakistani banks influences the bank’s return on assets. Consequently, the same study failed to identify a significant relation between the bank’s liquidity and its return on equity. Lastly, the authors advised the banks to formulate their future strategies in a way to properly manage their liquidity position. Additionally, Chowdhury et al. (2018) sought to clarify the relationship between liquidity risk and ROE in light of the fact that Bangladesh’s banking sector was experiencing a liquidity crisis. Six Islamic banks’ information was gathered from 2012 to 2016. The findings revealed a non-significant link between liquidity measures and ROE. Berrios (2013), however, did not discover a similar relationship when examining information gathered from 5 Islamic banks between 2001 and 2011 in Bangladesh. This could be due to the fact that research periods in the two cases were different in terms of the number of years. The period 2010-2014 also demonstrated the essential positive influence of liquidity risk on the return on equity, in Oman by using secondary information accumulated from four commercial banks by Salim & Bilal (2016). Addou & Bensghir (2021) article investigated the primary factors influencing the liquidity risk faced in the United Arab Emirates (UAE) by Islamic financial institutions. The research focused on 4 Islamic entities in the UAE using annual data extracted from their annual reports. The researchers used six variables such as size, return on equity, non-performing loans, return on assets, and capital adequacy ratio for data analysis using linear regression analysis. The results of the model demonstrate that both the return on assets and non-performing loans have a negative effect on the Emirati banks’liquidity risk. Abbas et al. (2021) examined how funding liquidity risk affects banks’propensity to take risks is the driving force behind this research. They used data from US commercial banks between 2002 and 2018 and the two-stage system GMM method to examine the hypotheses. Their research shows that US commercial banks are more willing to take risks when they have access to liquid finance. In addition, there is COGENT ECONOMICS & FINANCE 3 less oversight of bank managers’risky behavior and fewer funding shortages for banks with bigger deposits. Widyarti et al. (2022) conducted research on the impact of non-performing loans, return on assets, return on equity, and bank size on the liquidity risk of Indonesian banks. The study encompassed 40 state-owned and private banks with a dataset extracted for the period 2016-2020. The authors utilized the OLS regression to prove that the bank’s return on assets and return on equity are positively influencing the bank’s liquidity risk in Indonesia. Subsequently, the results also revealed that the non-performing loans along with the bank size do not impact the liquidity risk. AstudybySaif-Alyousfi(2022) involving 2,446 banks aimed to identify the determinants of bank profitability in 47 Asian countries. The author compiled 41,582 observations to create a dataset for the period 19952017. Using the Generalized Methods of Moments (GMM) estimation technique, the results of the research proved that the liquidity risk, capital adequacy ratio, loan-to-total assets, bank size, GDP growth, and inflation rate are positively associated with the bank’s return on assets. Besides, other variables such as cost-to-income, non-performing loans, and loan loss provisions are negatively impacting bank profitability. Using a dynamic GMM panel approach, Shoaib Ali et al. (2022) propose to examine the effect of banking-sector concentration on the liquidity creation of banks in GCC nations from 2012 to 2018. The findings point to a decrease in liquidity creation by banks throughout the GCC nations as a result of greater banking rivalry. The results of the study corroborate the ‘financial fragility hypothesis’, which states that when market competition is fierce, banks will cut back on lending. Another study by Ismail & Ahmed (2023) created a panel dataset for the period 2016-2021 to examine the impact of liquidity risk, credit risk, and operational risk on the financial stability of Jordanian banks. The scholar selected all conventional commercial banks listed in the Amman Stock Exchange and utilized the panel regression technique to prove that both credit risk and COVID-19 have negatively affected the bank’s stability. The study also showed that liquidity risk, operational risk, and bank size do not have any significant influence over the Jordanian’s bank stability. Rubbaniy et al. (2023) found empirical evidence that the Business Cycle (BC) has a nonlinear effect on liquidity generation using a panel smooth transition regression framework using US bank holding company quarterly data from 1993Q1 to 2020Q1, as well as a new proxy of the business cycle index. They discover that the BC has a positive and statistically significant nonlinear impact on liquidity generation, lending credence to the idea that liquidity creation is pro-cyclical and leading to an improvement in liquidity creation estimation when compared to earlier research. 3. Methodology 3.1. Sample used In this research paper, the main market focus will be the MENA region’s banking sector with data extracted from the Refinitiv Eikon platform for the period 2012-2022. This paper comprised data for 11 countries, that is 7 countries from the Middle East and 4 other countries from North Africa, as this will help in better understanding the different financial environments. As stated in Table 1, the population Table 1. Sample of the study. Country Population Final Sample Country Population Final Sample Panel A: Middle East Panel C: Full Sample Bahrain 9 4 Bahrain 9 4 Jordan 14 8 Egypt 10 6 Kuwait 11 7 Jordan 14 8 Oman 7 4 Kuwait 11 7 Qatar 9 6 Libya 14 8 Saudi Arabia 10 7 Morocco 6 4 UAE 18 9 Oman 7 4 Panel B: North Africa Qatar 9 6 Egypt 10 6 Saudi Arabia 10 7 Libya 14 8 Tunisia 11 8 Morocco 6 4 UAE 18 9 Tunisia 11 8 Total 119 71 Source: Authors’Analysis. 4 B. ABU KHALAF AND A. B. AWAD and the final sample where any bank with missing data for more than 3 years was excluded from our sample. The selection of banks is based on the availability of data aiming to achieve reliable and accurate results. In addition, before excluding the bank, any missing data were searched for in the annual reports of the reflective banks or the stock market exchange related to that specific market. 3.2. Model development 3.2.1. Dependent variable: return on equity Return on equity is a ratio calculated as net income divided by average shareholders’equity (Noraini, 2012; Seissian et al., 2018). According to Farhi & Hacini (2021), the return on equity is considered a crucial financial metric that shows if the bank is properly utilizing its resources. Another study by Berrani & Hacini (2021) pinpointed the importance of the return on equity in showing how much the bank is earning from its total equity. Different conclusions were reached after looking into the impact of liquidity risk on ROE in several studies. Syafi’i & Rusliati (2016) and Mwangi (2014) discovered a significant affirmative effect of liquidity risk on ROE while others such as Hacini et al. (2021) discovered a significant negative relationship. Though, other studies similar to Badawi (2017) have discovered a non-significant relationship between the bank’s liquidity risk and its ROE. 3.2.2. Independent variables 3.2.2.1. Liquidity risk. Liquidity, as defined by the Basel Committee on Banking Supervision in 2008, is a bank’s capacity to finance asset growth and pay commitments when they become due without triggering impermissible losses (Ojo, 2010). According to the committee, a financial institution becomes vulnerable to liquidity risk when it fulfills the fundamental function of maturing short-term deposits into long-term loans, both on an institution-specific level and in a way that impacts the market as a whole. A bank can fulfill its irregular cash flow obligations which are impacted by external events and the activities of other agents by effectively managing its liquidity risk (Badawi, 2017). Through the use of a panel data set of commercial banks from industrialized economies, Chung et al. studied the causes of liquidity risk in their study Bank Liquidity Risk and Performance. It was discovered that dependency on outside finance and liquid assets are the main contributors to liquidity risk. Due to the increased cost of funds, liquidity risk reduces bank profitability but boosts net interest margin. The findings demonstrated that, in a financial system based on markets, liquidity risk has a negative relationship with bank ROA and ROE. Other studies such as Hacini et al. (2021) confirmed that liquidity risk has a significant negative impact on the bank’s profitability. Hence, we hypothesize: H 1 : The liquidity risk has a negative impact on the profitability of banks. 3.2.2.2. Size. The Size of the bank is calculated using the natural logarithm of total assets (Awad et al., 2022; Khalaf et al., 2023a). This measure for the bank size is generally used as a measure of economies of scale in the banking industry according to Widyarti et al. (2022). Large financial institutions typically have the potential to raise capital at a lower cost and display higher profitability. Bank profitability is positively correlated with large capitalization. According to Mester (2010), the profitability and size of the bank are immensely related. Enlarging the bank size will enlarge the profitability of financial institutions by allowing them to recognize the economic scale. An illustration, enlarging size lets financial institutions increase fixed expenses over a greater asset base, thereby decreasing common expenses. Enlarging financial institutions’asset size can also bring down risk by branching out operations across regions and sectors. Another study by Aladwan (2015) including Jordanian banks concluded that bank size has a significant effect on profitability. The study proved that small and medium-sized banks have a better financial performance implying a higher profitability in comparison to larger banks; thus, concluding a negative relation between profitability and size. Other studies by Yuen et al. (2022) and Phan et al. (2020) found that the size factor has a significant positive relationship with profitability. Given the mixed results in the literature, we hypothesize: COGENT ECONOMICS & FINANCE 5 H 2 : The size has a positive impact on the profitability of banks. 3.2.2.3. Loan quality. Loans offered by banks not paid off in due time go on to become non-performing loans in the banking sector. This causes unfavorable impacts on the banking sector, specifically in terms of profitability. The impact spreads onto related banks, central government budgets, and various other sectors (Koten, 2021). Lending money to people is one of the main functions of commercial banks, and their main revenue streams. Alternatively, loans are considered among the assets that will provide a high yield to the bank. According to Abreu and Mendes, it can be understood undeniably that the more loans commercial banks provide to the public, the more monetary value is created in the economy. However, banks must be cautious when expanding their loan portfolios as doing so exposes them to default and liquidity risks that negatively impact their capacity to generate income and survive. A study by Husni (2011) shows that the interest obtained on bank loans is a significant driver of profitability and has a positive association with the profitability of financial institutions. This was also discussed in research by Vong and Chan who demonstrated the relationship between profitability and loan quality suggesting to use the bank’s non-performing loans as a gauge of loan quality. Another study by Alnabulsi et al. (2022), reveals that bank profitability is inversely related to non-performing loans in the MENA region. This implies that banks with less non-performing loans report more profitability figures unlike the results acquired in North African Countries. Other studies by Yuen et al. (2022), Widyarti et al. (2022), and Badawi (2017) revealed that the bank’s non-performing loans level does not impact statistically its profitability. Still, a study by Syafi’i & Rusliati (2016) in Indonesia confirmed a significant negative association between the bank’s non-performing loans and its return on assets. Thus, we hypothesize: H 3 : The loan quality has a negative impact on the profitability of banks. 3.2.2.4. Growth. According to Fama & French (1992), the growth of a firm is estimated based on the anticipated figures of profits and cash flows. Firms with higher growth rates are anticipated to have higher profitability; and thus, higher returns for investors (Hasanudin, 2023). The price-to-book ratio measures how market participants value the equity of the firms in relation to its book value. The priceto-book is estimated by dividing the market price of the firm’s share by its book value per share (Doblas et al., 2020; La Torre et al., 2021). Various studies have examined the relationship between the firm’s price-to-book and its profitability. For instance, Fama & French (2007), Block (1995), and Fama & French (1992) considered that low price-to-book firms can beat high price-to-book firms since this reflects underpricing and high potential for future growth; thus, increasing profits and cash flows. Similar studies by Jensen et al. (1997) and Asness et al. (2013) proved that high price-to-book firms have also a future growth potential which can be achieved via innovation and new projects. H 4 : The growth has a positive impact on the profitability of banks. 3.2.2.5. Income diversification. The relationship between income diversity and return on equity (ROE) in banks is a significant area of focus in finance (Abu Khalaf et al., 2024). It investigates how banks might maximize their income streams to improve profitability and shareholder value. Income diversification involves banks broadening their income streams beyond conventional interest-based operations, such as loans, to encompass non-interest revenue sources such as fees, commissions, trading, and investment income. Diversifying revenue sources mostly reduces risk. Banks can reduce the instability linked to a single revenue stream by depending on various sources of income. During times of low-interest rates, interest revenue from loans may decrease, while income from fees and commissions may stay steady or rise. Reducing this risk can result in a more stable and potentially increased Return on Equity (ROE) for the bank, as it becomes less vulnerable to changes in any individual revenue stream. This study will use the ratio of non-interest income to total income as the measure of income diversification. This measure offers a thorough assessment of the significance of non-interest revenue within a bank’s total income profile. H 5 : The income diversification has a positive impact on the profitability of banks. 6 B. ABU KHALAF AND A. B. AWAD 3.2.2.6. Operational efficiency. Organizations must sustain operational efficiency in their activities. Bank profitability is influenced by the operational efficiency of the bank, which is assessed by the total operating expenditure divided by total assets, mostly interest expense (Kundu & Banerjee, 2022). Bank operational efficiency involves managing interest expense to a minimum through asset and liabilities management (Altaf et al., 2022). The bank management consistently works to optimize bank operations, particularly by minimizing interest payments paid to clients, in order to enhance bank profitability (Boamah et al., 2022). The focus on interest expenses is not intended for banks to minimize the interest paid, as the interest rates on deposits offered to clients by banks must be competitive (Hidayat et al., 2021). It can increase interest expenses by using bank services to acquire funds from customers for daily transactions. Increasing the number of service facilities available to clients can lead to more cash collected, in addition to savings accounts and customer deposits. H 6 : The operational efficiency has a negative impact on the profitability of banks. 3.2.2.7. Capital adequacy (CapAd). The ratio represents the proportion of a bank’s capital in relation to its weighted assets (Baldwin et al., 2019). A higher Capital Adequacy Ratio (CAR) may indicate a lower risk profile because the bank is allocating a greater part of its deposits to loans. This has the potential to increase liquidity and improve the financial performance of financial institutions (Abu Khalaf et al., 2024). According to Ajayi et al. (2019), a high Capital Adequacy Ratio (CAR) shows a bank’s greater ability to meet its financial commitments and depositor demands, as it represents a bigger safety buffer (Baldwin et al., 2019). A high Capital Adequacy Ratio (CAR) among banks in a given market suggests a strong and stable financial system there (Almazari et al., 2022). H 7 : The capital adequacy has a positive impact on the profitability of banks. 3.2.2.8. Gross domestic product (GDP). Many researchers included the GDP as one of the macroeconomic variables to control for the relationship between liquidity risk and banks profitability, for example, Golubeva et al. (2019) and Nguyen et al. In addition, GDP is an essential indicator of a country’s economic health since it represents the worth of all products and services generated within its boundaries. Businesses tend to thrive as GDP grows, resulting in increased economic activity and increasing demand for financial services such as loans and investments (Klein & Weill, 2022). This rise in economic activity helps banks to increase their lending behavior. In contrast, during economic contractions, GDP tends to contract, affecting both firms and individuals. More specifically, banks may experience difficulties in such periods as loan defaults might rise and this, as a result, shall affect the profitability of banks (Lopez et al., 2020). H 8 : This paper expects that there is a positive relation between GDP and profitability. 3.2.2.9. Inflation (INF). Several empirical papers investigated the impact of inflation on the profitability of banks. According to Jeevitha et al., inflation and bank profitability have a complex relationship in many ways. They argued that the general rise in prices can affect Banks’bottom lines. In other words, banks tend to find ways and benefit from inflation through more borrowing, lending, and investments. Conversely, banks may face challenges due to high or unanticipated inflation which diminishes the buying power of money and impacts the value of assets (Tan & Floros, 2012). In addition, interest rates could be impacted by inflation uncertainty, which makes it challenging for banks to set reasonable prices for their financial products. H 9 : This paper expects that there is a positive relationship between inflation and banks profitability. 3.3. Model Based on the previous section, the following model has been developed to investigate the impact of liquidity risk on banks’profitability in the MENA region. COGENT ECONOMICS & FINANCE 7 Alhassan, A. L., & Tetteh, M. L. (2017). Non-interest income and bank efficiency in Ghana: A two-stage DEA bootstrapping approach. Journal of African Business,18(1), 124–142. https://doi.org/10.1080/15228916.2016.1227668 Al-Matari, E. M. 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