Market power and the role of banks as liquidity providers in GCC markets

Al-Khouri, Ritab; Arouri, Houda Article Market power and the role of banks as liquidity providers in GCC markets Cogent Economics & Finance Provided in Cooperation with: Taylor & Francis Group Suggested Citation: Al-Khouri, Ritab; Arouri, Houda (2019) : Market power and the role of banks as liquidity providers in GCC markets, Cogent Economics & Finance, ISSN 2332-2039, Taylor & Francis, Abingdon, Vol. 7, Iss. 1, pp. 1-17, https://doi.org/10.1080/23322039.2019.1639878 This Version is available at: https://hdl.handle.net/10419/245267 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/ Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=oaef20 Cogent Economics & Finance ISSN: (Print) 2332-2039 (Online) Journal homepage: https://www.tandfonline.com/loi/oaef20 Market power and the role of banks as liquidity providers in GCC markets Ritab Al-Khouri & Houda Arouri | To cite this article: Ritab Al-Khouri & Houda Arouri | (2019) Market power and the role of banks as liquidity providers in GCC markets, Cogent Economics & Finance, 7:1, 1639878, DOI: 10.1080/23322039.2019.1639878 To link to this article: https://doi.org/10.1080/23322039.2019.1639878 © 2019 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. Published online: 16 Jul 2019. Submit your article to this journal Article views: 1105 View related articles View Crossmark data GENERAL & APPLIED ECONOMICS | RESEARCH ARTICLE Market power and the role of banks as liquidity providers in GCC markets Ritab Al-Khouri 1 *and Houda Arouri 1 Abstract: Purpose: The study aims to discuss the role of market power and the banks as a liquidity provider, specifically in the twenty-first century. Design: The empirical investigation has evaluated the effects of market power on the ability of GCC banks to provide and transform liquidity. Findings: The banks conveniently perform two significant functions as the financial institution; therefore, they are known to play the role of risk transformers. They have been recognized as the important entities of liquidity creators and providers. The increase in market power increases the ability of GCC banks to create liquidity. There is a negative association between Inflation, growth in GDP, and ability of bank to produce liquidity. Conclusion: The financing impediments are reinforced due to increased competition among different banks. The demand of loans is likely to increase, when the investors possess valuable investment projects during expansion. The study recommends that the future research must involve off-balance-sheet items in the investigation for further clarification. Subjects: Finance; Financial Crisis; Financial Economics; Financial Intermediation; Financial Markets; Ritab Al-Khouri ABOUT THE AUTHOR Ritab Al-Khouri is a full professor of Finance at the Department of Finance and Economics/Qatar University. Holds a Ph.D from the University of Wisconsin at Madison. Her research interests include corporate governance, risk management, portfolio selection, agency issues, earning management, financial systems, and capital structure. Houda Arouri She is a lecturer of Finance at the Department of Finance and Economics/Qatar University since 2012. Before joining College of Business and Economics, Houda served as Head of Investment section in Finance Department at Qatar University. She completed her PhD at FSEG’s university in Tunisia. Her research interests include, asset pricing, credit ratings, liquidity crisis, financial distress, corporate governance, bank performance, and macroeconomic risk factors. This research is part of a series of papers directed toward studying the performance, stability, diversification, asset management and liquidity of the banking sector in the GCC Countries. PUBLIC INTEREST STATEMENT The study aims to discuss the role of market power and the banks' effects of market power on the ability of GCC banks to provide and transform liquidity. The analysis in this study has been conducted by evaluating the annual data on bank variables from the Gulf database including their annual reports. The study is helpful for the financial, banking, and economic professionals because of its relevance with the field. There are positive and effective shifts in the resources because of liquidity creation by the banks. The shift primarily occurs from savings to investments due to the undertaking of short-term liquid liabilities in the form of deposits and creating long-term illiquid credits. The increase in market power increases the ability of GCC banks to create liquidity. Inflation, growth in GDP, and ability of bank to produce liquidity are negatively associated. The study further recommends that future research must involve off-balance-sheet items in the investigation. Al-Khouri & Arouri, Cogent Economics & Finance (2019), 7: 1639878 https://doi.org/10.1080/23322039.2019.1639878 © 2019 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. Received: 13 September 2017 Accepted: 01 July 2019 First Published: 07 July 2019 *Corresponding author: Ritab AlKhouri, Business and Economics, Qatar University, Qatar E-mail: [email protected] Reviewing editor: Professor Caroline Elliott, Aston Business School, Aston University, UK Additional information is available at the end of the article Page 1 of 17 Keywords: Bank; liquidity; Gulf Cooperation Council (GCC); loans; market power 1. Introduction There are positive and effective shifts in the resources as a result of liquidity creation by the banks. The shift primarily occurs from savings to investments due to the undertaking of short-term liquid liabilities in the form of deposits and creation of long-term illiquid credits. This shift performs an important function to facilitate production activities and enable efficient consumption (Levine, 1991). The stock markets accelerate growth by allowing the investors to rely on the diversified portfolios and facilitate trade ownership of different organizations without damaging the productive processes. The leverages of restrictions on entry by branches of foreign banks increased liberalization and market openness in Gulf Cooperation Council (GCC). It raised the question about the role of market power in banking sector and its effects on liquidity, provided by banks for the economy. Liquidity creation plays an important role in commercial banks being a critical financial factor within the economy. It also plays an important role in the establishment of macro-economy by encouraging the production of goods and spur economic growth of the country. It is also possible that banks fail while creating high amounts of liquidity on the balance sheet within a specific time period. This might result in drying up of the liquidity with adverse consequences for the country’s economy (Tu, 2015). The substantial creation of liquidity by the banks leads to pursue the leading policies, which increases fragility of the banking sector. Banks, as financial institutions, conventionally perform two important functions in any economy, which include liquidity creators and providers and risk transformers (Diamond & Dybvig, 2000). The banks facilitate production, investments, and support in economic growth through the transformation in liquidity. Banking sector liquidity is directly associated with the security of fund availability and accessibility of financial resources. Banks can meet their commitments if they are able to borrow or if their assets are quickly transformed into cash with minimum or no losses. However, banks’capital structure might be fragile due to the divergence between banks’assets and liabilities. The banks are able to address liquidity distresses by lending and borrowing from their financial reserves, when that are in excess; thereby increasing the inefficiency of these banks. Therefore, it is claimed that the central bank can reduce these imperfections (Allen & Gale, 2004; Bhattacharya & Fulghieri, 1994). The effects of regulatory-induced competition on banks’risk taking, efficiency, and valuations are assessed by Goetz, Laeven, and Levine (2016). Risks are linked with illiquidity, which might increase due to the differences between cash flow that comes from principal and interest associated with assets, liabilities, and off-balance-sheet. The main reason for the fragility of banks is their functions in transforming maturity and offering protection with respect to creditors’ expected needs for liquidity (Diamond & Dybvig, 2000). The literature has cited two contrary views concerning the effects of banks’market power on their capacity to create liquidity. The first view is related to the fact that increased competition (i.e. low market power) might reduce bank profitability, leading to an increase in bank fragility (Jimenez, Lopez, &Saurina,2013). The solvency of particular institutions threatened by the standard principle of banking supervision allows excessive competition among the banks. Therefore, banks would try to limit the amount of credit granted and reduce the volume of deposits accepted that would reduce the liquidity created by banks. The second view suggested that high competition or low market power would lead to a reduction in loan rates and an increase in deposit rates, which increases the demand for loans and deposits (Boot & Thakor, 2000). In this scenario, small banks appear to provide no significant buffer to the investments (Kashyap & Stein, 1995). Therefore, bank liquidity creation is expected to increase through the bank pricing channel (Love & Peria, 2015). Endogeneity can occur when there is reverse causality, since the market power and liquidity are jointly determined. It is possible that banks with high market power provide more liquidity to the Al-Khouri & Arouri, Cogent Economics & Finance (2019), 7: 1639878 https://doi.org/10.1080/23322039.2019.1639878 Page 2 of 17 market or to other banks in need of liquidity. In this situation, banks can achieve higher market power. On the other hand, banks with high liquidity have the chance to expand or merge with other banks, leading to increased market power. Davidson and MacKinnon (1993) suggested that test is done for endogeneity using an augmented regression Durbin Wu-Hausman test. The banking sectors of GCC countries are domestically owned by providing financial leniencies to the foreign banks. Such banks are usually not allowed to enter the GCC market; however, they are allowed to open a restricted number of branches. The development of financial markets is the primary aim of the Gulf countries. Moreover, the economic conditions in GCC markets are resilient corresponding to the global financial crisis. The financial developments suffer because of low market liquidity, funding issues, and large price swings. Therefore, the present study has discussed the role of market power and the banks as a liquidity provider in the twenty-first century. It empirically investigates the effects of market power on the ability of GCC banks to provide and transform liquidity. The study has conducted the analysis by evaluating the annual data on bank variables from the Gulf database including the annual reports of 69 Islamic and conventional banks established in 6 GCC countries. Table 1has shown the percentage of foreign banks to total number of banks in the sample. It further shows the concentration of the banking industry in the GCC. 2. Materials and methods 2.1. Data source The study has included annual data on bank variables taken from Gulf Base database, and the annual reports of 69 conventional and Islamic banks located in six GCC countries during the 2002–2014 period. The database offered complete information for the years 2002 till 2014. Therefore, the banks having complete data available for these years were included in the study. Data were collected on macroeconomicvariablesasthegrowthinrealGDPandinflation obtained from the World Development Indicators (WDI). The stock market capitalization data were taken from Gulf-Base database. The present study has used the two-step Generalized Method of Moments (GMM) to evaluate and compare the outcomes of the coefficient vectors from two models, similar to Arellano and Bond (1991). Among the two models, one treats market power as endogenous; while, the other treats market power as exogenous. The GMM methodology reduces the problem of endogeneity between variables. The GMM optimally assisted in dealing with the dependent and independent variables (Arellano & Bond, 1991). 2.2. Hypothesis Development H1: Increase in market power affect the ability of GCC banks to create liquidity. H0: Increase in market power does not affect the ability of GCC banks to create liquidity. Table 1. Characteristics of banks in the GCC Countries Top 3 banks Government ownership F No. of domestic banks (%) No. of conventional banks No. of Islamic banks Bahrain 71.27% 1.37% 22.61% 48 (13) 7 6 Kuwait 67.84% 12.17% 2.31% 10 (10) 8 2 Oman 77.31% 5.45% 11.62% 9 (7) 5 2 Qatar 72.92% 21.75% 0.00% 11 (8) 7 1 Saudi Arabia 46.04% 13.43% 11.04% 12 (12) 6 6 UAE. 53.12% 19.25% 8.69% 21 (19) 15 4 Source: author’s calculations and country authorities. Al-Khouri & Arouri, Cogent Economics & Finance (2019), 7: 1639878 https://doi.org/10.1080/23322039.2019.1639878 Page 3 of 17 H2: Increase in competition among the banks decreases their ability to provide liquidity. H0: Increase in competition among the banks increases their ability to provide liquidity. 2.3. Research methodology The impact of market power and competition variables on GCC banks were evaluated to analyse liquidity of banks through certain attributes and macro-economic indicators. The model was evaluated as Liqi;j;t¼fMP i;j;t;BSi;j;t;MEj;t  (1) where Liq i,j,t measures of liquidity creation of bank i, in country jand time t. MP i,j,t is the proxy for market power of bank i, in country jand time t. BS i,j,t reflects a vector of bank ispecific characteristics, in country jand time t. ME j,t is a vector of macroeconomic variables for each single country, over time t. The study has used cross-sectional and time series data to obtain information on liquidity created by the banking system over time. The component of time in a dynamic panel is expected to assess the consequences of continuous changes in institutional characteristics on bank liquidity creation. Therefore, the dynamic model to be implemented suggests that the current level of liquidity will eventually be affected by past liquidity levels. The equation takes the following form: LIQijt ¼/ 0þβ1BSijt þβ2MEijt þvijt vijt ¼2 iþμtþρijt (2) where LIQ ijt is the Liquidity creation measure (i.e., dependent variable) for bank iin country jand at time t. BS jit is a vector of specific characteristics of bank i, in country jand at time t. ME jit refers to the vector of macro-economic and financial structure indicators of country j, and time t. ß 1 and ß 2 are vectors of coefficients estimated. νijt is an error-term. 2.4. Liquidity creation variable (LIQ) Liquidity creation was measured as the difference between liquid assets and liquid liabilities, divided by total bank assets. A higher value indicated a better ability of a bank to create liquidity. The definition of liquidity creation implemented revealed the liquidity of assets and liabilities of the banks’balance sheet. The study concentrated on the following measure: LIQ = (Liquid liability-Liquid Assets)/Gross total assets The measure of liquid liability included all entries in the balance sheets that have maturity of one year or less. In addition to money market deposits, demand deposits, foreign deposits, and any other borrowed resources were included that have a maturity of one year or less. The measures of Al-Khouri & Arouri, Cogent Economics & Finance (2019), 7: 1639878 https://doi.org/10.1080/23322039.2019.1639878 Page 4 of 17 liquid assets include cash, acceptances (either governmental or non-governmental securities), and loans that have a maturity not exceeding one year. 2.5. Market power (MP) Herfindahl-Hirschman index (HHI) is a measure of concentration, which is calculated as the sum of squared market share of each bank in the system used to measure concentration in the theoretical literature. The HHI, as the concentration ratio, ignores the importance of smaller banks in the industry. More concentration is placed on the Boone index, instead of using the concentration measures for market power. Boone index provides a direct measure of market power based on the recent empirical literature related to industrial organization. The study has attempted to search for an alternative marginal cost proxy through the introduction of fuller marginal cost proxy. The study has measured the level of competition by using the Boone indicator, which assumes that firms operating in a highly competitive industry would suffer if they operate inefficiently (Boone, 2008). The level of competition is measured by estimating the elasticity of revenues to marginal cost. It is measured by assessing the following regression: LogVROAit ¼αþβtLogMcjj þij;t(3) where Log VROA it : Log of bank variable revenue (the ratio of operating revenue of bank ito its total assets). Log Mcij: is measured by taking the natural logarithm of the marginal cost of bank i. βt: is the time-varying parameter where the absolute value of this coefficient (i.e. Boone Index), measures the level of competition. A rise in βtsuggests a decline in competitive behaviour of the banking system. 2.6. Banks’capital (EQTA) Bank capital is measured by book value of equity as a Percentage of Total Assets (EQTA). High share of equity to total assets indicates a lower amount of risk and higher bank stability. High capital requirement indicates a more secure banking system. This ratio illustrated the degree at which banks’assets value may drop before risking the position of its creditors and depositors. The higher the liquidity produced by the bank, the larger the potential losses are associated with the nature of illiquid assets to encounter the high demand of liquidity by depositors. Furthermore, Coval and Thakor (2005) emphasized the role of bank capital in absorbing risks and increasing risk tolerance. Therefore, high capital may allow banks to create a higher level of liquidity. 2.7. Credit risk (σROA) The credit risk was measured as the standard deviation of return on assets (σROA). The default risk in repayment loans is related to the creation of bank liquidity, since the increase in default risk is likely to strengthen over time; thus, the expected relationship is also positive. 2.8. Profitability (ROA) Profitable banks are able to transfer funds by providing more loans and a higher level of investment. The evaluation of profitability is important as there is a positive association between profitability and the ability of banks to provide liquidity. 2.9. Size: ln (TA) The bank size has been measured by the natural log of total assets. This variable was added to capture possible side effects; for example, bank complexity and risk management. Al-Khouri & Arouri, Cogent Economics & Finance (2019), 7: 1639878 https://doi.org/10.1080/23322039.2019.1639878 Page 5 of 17 2.10. Government ownership (GO) The model included in this study comprises two types of ownership indicators; government ownership (GO) and the other is foreign ownership (F). The banks with high government and semigovernment ownership are more capable of providing liquidity. The government is expected to work as insurance for the depositors in the case of adverse shocks. Foreign ownership reflects different type of regulations that are imposed on the banking sector reflecting the degree of freedom given to the banking sector. The banks with high government and semi-government ownership are more capable of providing liquidity. In the case of adverse shocks, the government was expected to work as insurance for the depositors. 2.11. Nonperforming loans to total assets (NPLTA) A percentage of total assets was measured on the basis of non-accruing loans. This ratio is used to determine the quality of output, banks’investments in assets with high risk, and liquidity produced by the banks. However, negative relationship is expected for NPLTA. 2.12. Real GDP growth (GGDP) Real GDP growth is directly associated with the amount of liquidity created by banks. A high correlation between oil revenues and real GDP growth is expected as oil is the main source of income among the GCC countries. 2.13. Inflation (INF) There is a positive relation between the level of inflation and the performance of banks. The high inflation indicates an increase in the expected interest rates on loans, a high level of income, and high liquidity. On the other hand, the level of inflation and the bank costs rises, when inflation is unanticipated. This in return have an inverse effect on bank profitability and their ability to provide liquidity, given that banks are incapable of adapting appropriately. 2.14. Stock market capitalization as a percentage of GDP (MCGDP) Stock market capitalization as a percentage of GDP is used to measure the degree of stock market development and its significance in providing adequate funding to economic activities. DemirgucKunt and Huizinga (1999) stated that the ratio of market capitalization to GDP is inversely associated to margins. The study advocated that financing by the banks can be replaced by a well-developed stock market. Consequently, there is strong effect of stock market on the positive impact of market capitalization on liquidity in providing financing to companies. 2.15. Statistical analysis It is assumed that bank liquidity and growth in real GDP are the endogenously determined variables; whereas, capital and liquidity creation are jointly determined (Berger & Udell, 1994). The data would create biased coefficients as the potential endogeneity problem implies to the application of ordinary least squares (OLS). The GMM system utilizes differences of the regression equation to eliminate the expected correlation between the lagged dependent variable and the error term. Apart from the operation of regression, the data have also been analysed with the employment of descriptive statistics and correlation matrix to develop authentic association between the dependent and independent variables. 3. Results and discussion 3.1. Descriptive statistics for the variables Table 2has revealed that on average GCC banks produced a high degree of liquidity. The mean liquidity gap across all banks in the six countries is approximately 85%. Therefore, banks are able to convert approximately 85% of their liquid deposits into illiquid assets. The result is contrary to the results found for US banks, where the liquidity gap was approximately 20% (Deep & Schaefer, 2004). Majority of the US banks have managed to use deposits to invest to bring higher profits, as compared to GCC banks. Beta or market power has an average of 1.5 for the whole sample that is Al-Khouri & Arouri, Cogent Economics & Finance (2019), 7: 1639878 https://doi.org/10.1080/23322039.2019.1639878 Page 6 of 17 Table 2. Summary statistics for the variables of interest Complete sample Conventional banks Islamic banks Variable Mean Std. Min Max Mean Std. Min Max Mean Std. Min Max LIQ −0.840 0.1545 −1−0.2054 −0.848 0.124 −1−0.3454 −0.821 0.2154 −1 0.2053 EQTA 0.2372 0.226 0.0077 0.9892 0.1580 0.1084 0.0294 0.9600 0.3276 0.1251 0.0760 0.9980 ROA 0.020 0.0324 −0.3803 0.1843 0.021 0.027 −0.98 0.139 0.0187 0.0434 −0.284 0.1843 σROA 0.016 0.0247 0 0.1548 0.014 0.21 0 0.137 0.0204 0.0317 0 0.1548 MP 1.491 1.4501 0 6.1652 1.316 1.257 0 2.952 1.8908 1.7533 0 0.1652 Ln(TA) 8.866 1.3726 4.0121 11.8022 8.852 1.4 4.012 11.802 8.9052 1.297 4.898 11.3139 (lnTA) 2 80.487 23.5961 16.0971 139.292 80.307 24.047 16.097 139.292 80.977 22.3662 23.99 128.0058 GO 0.1209 0.185 0 0.9988 0.114 0.167 0 0.698 0.1366 0.225 0 0.9988 Finance (F) 0.1289 0.2204 0 0.9451 0.131 0.211 0 0.945 0.1243 0.2422 0 0.8906 NPLTA 0.014 0.025 0 0.2421 0.014 0.027 0 0.242 0.0128 0.0194 0 0.1025 CON 0.6287 0.133 0.4473 0.9002 0.631 0.13 0.447 0.9 0.6237 0.1394 0.45 0.9002 HHI 0.1923 0.0815 0 0.4448 0.129 0.081 0 0.445 0.1925 0.082 0 0.4448 GDPG 0.0594 0.0550 −0.0710 0.262 MCGDP 0.386 0.4537 0.204 2.12 INF 0.0309 0.0325 −0.0486 0.1681 Al-Khouri & Arouri, Cogent Economics & Finance (2019), 7: 1639878 https://doi.org/10.1080/23322039.2019.1639878 Page 7 of 17 Table 7. Regression results of the impact of market power on liquidity creation for the complete model, for conventional banks and for Islamic banks with and without crisis intercept Dep. Var./LIQ Complete Model Model (1) Conventional Banks Model (2) Islamic Banks Model (3) Independent variables Without crisis intercept (p-value) With crisis intercept (p-value) Without crisis intercept (p-value) With crisis intercept (p-value) Without crisis intercept (p-value) With crisis intercept (p-value) L.LIQ 0.4340 (0.0156)* 0.4020 (0.0169)* 0.4680 (0.0177)* 0.4830 (0.0280)* 0.2420 (0.0894)** 0.2420 (0.0889)** CON 0.3620 (0.0207)* 0.3980 (0.0263)* 0.1640 (0.0437)* 0.1610 (0.0488)* −0.6190 (0.1370) −0.6730 (0.1390) ROA −0.0676 (0.0235)* −0.0962 (0.0192)* 0.0617 (0.0347)* 0.1050 (0.0286)* −0.2350 (0.1330) −0.2430 (0.1340) σROA −5.5320 (0.8160) −6.0300 (0.7670) −2.1440 (1.5890) (1.0240) (1.8130) 4.9660 (1.4070) 4.7850 (1.4070) EQTA 0.0314 (0.0850)** 0.02944 (0.0820)** 0.0897 (0.0001)* 0.0979 (0.0001)* −0.06137 (0.5880) −0.0820 (0.4820) lnTA 0.1890 (0.0242)* 0.2140 (0.0234)* 0.1030 (0.0337)* 0.0715 (0.0301)* 0.3810 (0.1090)** 0.325 (0.1110) (LnTA)2 −0.0112 (0.0014)* −0.0127 (0.00138)* −0.00658 (0.00184)* −0.00503 (0.00168)* −0.0226 (0.0062)* −0.0193 (0.0063)* GO −0.0363 (0.0244)* −0.0499 (0.0276)* −0.0048 (0.0134)* 0.00672 (0.0124)* −0.1690 (0.1170) −0.1440 (0.1160) F 0.0487 (0.0089)* 0.0513 (0.0138)* −0.0343 (0.00523)* −0.02710 (0.0275)* 0.3990 (0.0899)** 0.3770 (0.0904)** INF −0.0044 (0.00086)* −0.0029 (0.00074)* −0.0042 (0.00112)* −0.0025 (0.0017)* −0.0088 (0.0055)* −0.0062 (0.0056)* NPLTA −0.0811 (0.0342)* −0.1271 (0.0383)* −0.1270 (0.0501)* −0.2197 (0.0551)* −0.398 (0.3790) −0.381 (0.3770) GDPG −0.0008 (0.0002)* −0.0015 (0.00016)* −0.00044 (0.00017)* −0.0009 (0.00023)* −0.0013 (0.0014)* −0.0022 (0.0014)* MCGDP 0.0168 (0.0038)* 0.0211 (0.0355)* 0.0137 (0.0055)* 0.00998 (0.0064)* −0.0252 (0.0281)* −0.022 (0.0281)* DCRISIS −0.0191 (0.0019)* −0.0218 (0.0030)* −0.0309 (0.0185)* (CON* DCRISIS) −0.0017 (0.0088)* −0.0041 (0.0016)* −0.0017 (0.0079)* Constant −0.6300 (0.1140) −0.7430 (0.0947)** −0.0760 (0.1750) −0.0739 (0.1500) −1.5280 (0.4880) −1.322 (0.4940) Sargan Test (Prob >chi2) 56.104 (0.9578) 59.273 (0.9216) 37.631 (0.9999) 36.06943 (0.999) 96.127 (0.998) 89.772 (0.9337) AR (1) −2.5210 (0.0013)* −2.5497 (0.0012)* −2.6860 (0.0063)* −2.5562 (0.0013)* −2.3432 (0.0221)* −2.6534 (0.0318)* AR(2) 0.3424 (0.81270) 0.5479 (0.8710)| 0.7869 (0.6791) 0.8854 (0.7232) 0.7650 (0.8180) 0.9675 (0.9271) *Significant at the 5% level. Al-Khouri & Arouri, Cogent Economics & Finance (2019), 7: 1639878 https://doi.org/10.1080/23322039.2019.1639878 Page 14 of 17 Table 8. Regression results of the impact of HHI on liquidity creation for the complete model, for conventional banks and for Islamic banks with and without crisis intercept Complete model Conventional banks Islamic banks VARIABLES Without crisis intercept (p-value) With crisis intercept (p-value) Without crisis intercept (p-value) With crisis intercept (p-value) Without crisis intercept (p-value) With crisis intercept (p-value) L.LIQ 0.5020 (0.0106)* 0.484 (0.0127)* 0.5050 (0.0278)* 0.4960 (0.0305)* 0.3920 (0.0914)** 0.3990 (0.0908)** HHI 0.2690 (0.0249)* 0.2460 (0.0314)* 0.1460 (0.0319)* 0.1410 (0.0344)* 0.4910 (0.2170) 0.5200 (0.2180) ROA 0.0603 (0.0223)* 0.0841 (0.0236)* 0.1212 (0.0389)* 0.0952 (0.0384)* −0.198 (0.1430) −0.207 (0.1420) σROA 4.1200 (0.5990) 4.3110 (0.5570) 2.2120 (1.0390) 1.6420 (1.4360) 4.4820 (1.5030) 4.3240 (1.5020) EQTA .01607 (0.0490)* .03088 (0.1390) .06890 (0.0080)* 0.0981 (0.0020)* −0.1858 (0.1170) −0.1860 (0.1340) lnTA 0.2200 (0.0154)* 0.2370 (0.0197)* 0.1140 (0.0358)* 0.1110 (0.0350)* 0.2600 (0.1130) 0.2090 (0.1150) (LnTA)2 −0.0134 (0.0089)* −0.0145 (0.0011)* −0.0075 (0.0021)* −0.0074 (0.0020)* −0.0166 (0.0064)* −0.0137 (0.0066)* GO 0.0824 (0.0200)** 0.0982 (0.0242)** 0.0143 (0.0133)* 0.0065 (0.0155)* 0.1050 (0.1240) 0.0875 (0.1240) F 0.0679 (0.0103)* 0.0806 (0.0105)* −0.0220 (0.0055)* −0.0276 (0.0262)* 0.4640 (0.0920)** 0.4530 (0.0920)** NPLTA −0.0928 (0.0509)* −0.1720 (0.0428)* −0.1040 (0.0430)* −0.1530 (0.0613)** −0.3500 (0.4080) −0.3490 (0.4060) INF −0.0063 (0.0088)* −0.0036 (0.0012)* −0.0042 (0.0014)* −0.0015 (0.0016)* −0.0082 (0.0059)* −0.0061 (0.0059)* GDPG −0.0007 (0.0013)* −0.0012 (0.0014)* −0.00034 (0.0018)* −0.0083 (0.0002)* −0.0013 (0.0015)* −0.0020 (0.0015)* MCGDP 0.0181 (0.0051)* 0.0228 (0.0045)* 0.00796 (0.0062)* 0.00796 (0.0060)* −0.0140 (0.0299)* −0.0104 (0.0300)* (HHI* DCRISIS) 0.0148 (0.0017)* −0.0084 (0.0016)* 0.0045 (0.0084)* Constant −0.5980 (0.0684)** −0.6560 (0.0957)** −0.0555 (0.1390) −0.0336 (0.1370) −0.7590 (0.4860) −0.5490 (0.4970) Sargan Test (Prob >chi2) 56.56841 (0.9535) 54.2923 (0.9718) 37.85822 (0.9999) 35.19722 (1.0000) 102.1366 (0.9980) 98.15952 (0.9999) AR (1) −3.2355 (0.0012)* −3.234 (0.0014)* −2.4654 (0.0106)* −2.4560 (0.0058)* −2.7540 (0.0144)* −2.7548 (0.0135)* AR(2) 0.3369 (0.8080) 0.2030 (0.9011) 0.3754 (0.6907) 0.7443 (0.7409) 0.8554 (0.8611) 0.7871 (0.9911) *Significant at the 5% level, **Significant at the 10% level. Al-Khouri & Arouri, Cogent Economics & Finance (2019), 7: 1639878 https://doi.org/10.1080/23322039.2019.1639878 Page 15 of 17 competition) increases the ability of GCC banks to create liquidity using all other measures of market power and different liquidity measures. There is negative and significant relationship between the variables of inflation and growth in GDP, and the banks’ability to provide liquidity. Thus, the banks, which want to satisfy the increased demand for loans, might not be able to cope up with it resulting in decreased ability to provide liquidity. The results showed a slightly significant (at 10% significance level) difference in business between Islamic and conventional banks in the regression of market power and macro-economic factors on the ability of banks to provide liquidity. It was also suggested that increased competition among banks tend to reduce bank profitability and increases the non-performing loans, which results in reduction of the bank incentives to provide liquidity. Moreover, there is significant impact of market liquidity on the asset side of bank balance sheet resulting in active management of the portfolios. There is significant impact of liquidity on the market having potential implication on the level of bank competition. There is no difference in the ability of b conventional and Islamic banks to provide liquidity. It is recommended that banks in GCC should be focused for providing more detailed information about off balance sheet items and be more transparent that would help researchers to develop a better measure of liquidity creation. Future studies need to be based on off-balance-sheet items investigation along with analysing specific products and the business lines provided by the Islamic banks. Funding The authors received no direct funding for this research. Conflict of Interest This research holds no conflict of interest and is not funded through any source. Author details Ritab Al-Khouri 1 E-mail: [email protected] ORCID ID: http://orcid.org/0000-0002-0095-7270 Houda Arouri 1 E-mail: [email protected] 1 College of Business and Economics, Qatar University, 2713, Al Hala St, Doha, Qatar. Citation information Cite this article as: Market power and the role of banks as liquidity providers in GCC markets, Ritab Al-Khouri & Houda Arouri, Cogent Economics & Finance (2019), 7: 1639878. References Allen, F., & Gale, D. (2004). Financial intermediaries and markets. Econometrica,72, 1023–1061. doi:10.1111/ j.1468-0262.2004.00525.x Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. The review of economic studies,58, 277–297. doi:10.2307/2297968 Bawazira, H., Degl’innocentia, M., & Wolfea, S. 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