The impact of liquidity creation on bank profitability empirical evidence from vietnamese commercial banks 2022

MINISTRY OF EDUCATION AND TRAINING STATE BANK OF VIETNAM BANKING UNIVERSITY OF HO CHI MINH CITY  NGUYỄN NGỌC THANH TRÚC THE IMPACT OF LIQUIDITY CREATION ON BANK PROFITABILITY EMPIRICAL EVIDENCE FRO.

MINISTRY OF EDUCATION AND TRAINING STATE BANK OF VIETNAM BANKING UNIVERSITY OF HO CHI MINH CITY - - NGUYỄN NGỌC THANH TRÚC THE IMPACT OF LIQUIDITY CREATION ON BANK PROFITABILITY: EMPIRICAL EVIDENCE FROM VIETNAMESE COMMERCIAL BANKS GRADUATION THESIS MAJOR: FINANCE – BANKING CODE: 7340201 HO CHI MINH CITY, 2022 MINISTRY OF EDUCATION AND TRAINING STATE BANK OF VIETNAM BANKING UNIVERSITY OF HO CHI MINH CITY - - NGUYỄN NGỌC THANH TRÚC THE IMPACT OF LIQUIDITY CREATION ON BANK PROFITABILITY: EMPIRICAL EVIDENCE FROM VIETNAMESE COMMERCIAL BANKS GRADUATION THESIS MAJOR: FINANCE – BANKING CODE: 7340201 SUPERVISOR NGUYỄN DUY LINH, Ph.D HO CHI MINH CITY, 2022 COMMENTS OF THE SUPERVISOR Ho Chi Minh City, …/…/2022 Supervisor Ph.D Nguyễn Duy Linh i ABSTRACT Research data: The final thesis will focus on studying the impact of liquidity creation on the profitability of twenty-three commercial banks in Vietnam in the period from 2009 to 2020 Reliable secondary data are extracted from the financial statements of commercial banks previously disclosed to the public Purpose: To build a regression model to estimate the impact of liquidity creation represented by the “cat fat” measure on bank profitability, the research on the topic aims to investigate and find the impact of liquidity creation on the profitability of commercial banks in Vietnam Several variables represent bank characteristics including bank size, capital ratio, debt ratio, deposit ratio, expense ratio, provision ratio, real GDP growth rate, and treasury bill interest rate In particular, the author performed regressions on the components of liquidity creation and examined each one affected bank profitability Including research variables such as liquidity creation, bank-specific variables, and macro variables Based on the collected data on the factors, the study examines the impact of these factors on the performance of twenty-three commercial banks in Vietnam, including two variables: depends on return on assets (ROA) and return on equity (ROE) Design/methodology/approach: The authors examined how liquidity creation influences the profitability of commercial banks in Vietnam from 2009 to 2020 by constructing regression models for regression analysis The multivariate regression models used are the Pooled Ordinary Least Squares (POLS) method, the Fixed Effects Model (FEM), and the Random Effects Model (REM), respectively Finally, the author uses the Feasible Generalized Least Squares (FGLS) method to overcome the phenomena Findings: Using panel data for the period 2009-2020, the research results show the negative impact of liquidity creation on bank profitability in Viet Nam, for both dependent variables, ROA and ROE In nine independent variables, in each ROA and ROE model, only six variables affect the regression model while the other ii three variables have no significant influence Implications: With the results achieved, it will help banks and other related agencies to evaluate, manage and operate more effectively, as well as contribute to an empirical study for the future Assist them in identifying key variables influencing bank profitability in Vietnam, particularly the influence of liquidity creation The findings will support banks and other associated agencies in better evaluating, managing, and running their businesses and provide an empirical study for future research Keywords: Commercial banks, profitability, ROE, bank size, capital, loans, deposits, loan ratio, deposit ratio, GDP growth, treasury bill rates, liquidity creation iii COMMITMENT My graduation thesis titled "The impact of liquidity creation on bank profitability: Empirical evidence from Vietnamese commercial banks" is my research work in the past time The article is made with the guidance and dedicated help of Ph.D Nguyen Duy Linh The topic is my result after studying and accumulating knowledge at Banking university of Ho Chi Minh City The author's research work and the research results are honest The reference part of the thesis clearly states the material and data used in the research work The substance of the thesis, as well as the results and software program, are done honestly and plainly and have never been published before Ho Chi Minh City, …/…/2022 Author Nguyễn Ngọc Thanh Trúc iv ACKNOWLEDGEMENTS To complete this final thesis, I would like to thank the lecturers of Banking University of Ho Chi Minh City Especially the teachers who majored in Finance and Banking during the years of studying here have taught me valuable knowledge as a foundation for my career and later life I would like to express my sincere thanks to Ph.D Nguyen Duy Linh, who has always accompanied and supported me during my research work Thanks to that, the research was completed on schedule and completed my graduation thesis most conveniently In addition, I would also like to share my joy and express my gratitude to my family and friends who have always supported and encouraged me throughout the process of writing this thesis In the process of implementing the thesis, due to the limitations of knowledge, shortcomings are inevitable I look forward to receiving suggestions from teachers, and friends to improve the topic At the same time, it creates a better premise and a direction for future research Finally, I would like to wish the lecturers always have good health, and happiness and always achieve much success in their work as well as in their lives Sincerely thanks! Ho Chi Minh City, …/…/2022 Author Nguyễn Ngọc Thanh Trúc v TABLE OF CONTENTS ABSTRACT i COMMITMENT iii ACKNOWLEDGEMENTS iv TABLE OF CONTENTS .v LIST OF ABBREVIATIONS ix LIST OF FIGURES x LIST OF TABLES xi CHAPTER 1: INTRODUCTION 1.1 BACKGROUND OF THE RESEARCH 1.2 OBJECTIVES OF THE RESEARCH .4 1.2.1 General objectives 1.2.2 Specific objectives 1.3 RESEARCH QUESTIONS 1.4 RESEARCH SUBJECTS AND SCOPE 1.4.1 Research subject .4 1.4.2 Research scope .5 1.5 RESEARCH METHODOLOGY .5 1.6 CONTRIBUTION OF THE RESEARCH 1.6.1 Literature gap 1.6.2 New contributions 1.7 STRUCTURE OF THE RESEARCH .7 CONCLUSION CHAPTER 93 empirical evidence from European banking sector Journal of Financial Reporting and Accounting, 14(1), 86–115 https://doi.org/10.1108/JFRA-05-2015-0060 50 Mergaerts, F., & Vander Vennet, R (2016) Business models and bank performance: A long-term perspective Journal of Financial Stability, 22, 57–75 https://doi.org/10.1016/J.JFS.2015.12.002 51 Muriithi, J G., Robert, D., & Muigai, G (2017) Quantitative analysis of Operational Risk and Profitability of Kenyan Commercial Banks using Cost Income Ratio IOSR Journal of Economics and Finance, 8(3), 76–83 https://doi.org/10.9790/5933-0803047683 52 Pasiouras, F., & Kosmidou, K (2007a) Factors influencing the profitability of domestic and foreign commercial banks in the European Union Research in International Business and Finance, 21(2), 222–237 https://doi.org/10.1016/j.ribaf.2006.03.007 53 Pasiouras, F., & Kosmidou, K (2007b) Factors influencing the profitability of domestic and foreign commercial banks in the European Union Research in International Business and Finance, 21(2), 222–237 https://doi.org/10.1016/J.RIBAF.2006.03.007 54 Petria, N., Capraru, B., Ihnatov, I (2015) Determinants of Banks’ Profitability: Evidence from EU 27 Banking Systems Procedia Economics and Finance, 20, 518–524 https://doi.org/10.1016/S2212-5671(15)00104-5 55 Pradhan, R S (2017) Impact of Capital Adequacy and Cost Income Ratio on Performance of Nepalese Commercial Banks Pratikshya Parajuli International Journal of Management Research, 8(1) 56 Ramlan, H., & Adnan, M S (2016) The Profitability of Islamic and Conventional Bank: Case Study in Malaysia Procedia Economics and Finance, 35, 359–367 https://doi.org/10.1016/S2212-5671(16)00044-7 57 Roman, A., Şargu, A C (2013) Analysing the Financial Soundness of the Commercial Banks in Romania: An Approach based on the Camels Framework Procedia Economics and Finance, 6, 703–712 https://doi.org/10.1016/S2212- 94 5671(13)00192-5 58 Rose, P S (2002) Commercial bank management (5th ed.) 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Retrieved June 6, 2022, from https://www.ceicdata.com/en/vietnam/treasurybill-and-government-securities-rates-quarterly 71 Yen, N H., & Chau, L N M (2021) Impact of Liquidity Transformation to Vietnamese Commercial Banks Adequacy Ratio Tạp Chí Khoa Học & Đào Tạo Ngân Hàng, 229(12–26) 72 Yusgiantoro, I., Soedarmono, W., & Tarazi, A (2019) Bank consolidation and financial stability in Indonesia International Economics, 159, 94–104 https://doi.org/10.1016/J.INTECO.2019.06.002 96 APPENDIX Appendix 1: List of 23 commercial banks Bank name An Binh Commercial Joint Stock Bank Asia Commercial Joint Stock Bank Commercial Bank for Investment And Development of Vietnam BaoViet Joint Stock Commercial Bank Vietnam Joint Stock Commercial Bank For Industry and Trade Viet nam Export Import Commercial Joint Stock Bank Ho Chi Minh City Development Joint Stock Commercial Bank Kien Long Commercial Joint Stock Bank Military Commercial Joint Stock Bank Vietnam Maritime Commercial Joint Stock 10 Bank 11 Nam A Commercial Joint Stock Bank 12 Nam Viet Commercial Joint Stock Bank Petrolimex Group Commercial Joint Stock 13 Bank Saigon Thuong Tin Commercial Joint Stock 14 Bank Bank code ABB ACB Name ABBANK ACB BID BIDV BVB BAOVIET Bank CTG VietinBank EIB Eximbank HDB HDBank KLB MBB KienLongBank Military Bank MSB MSB NAB NVB Nam A Bank Navibank PGB PGB SCB Sacombank 15 Saigon Bank For Industry And Trade SGB Saigonbank 16 Saigon – Hanoi Joint Stock Bank SHB SHB STB STB TCB (TCB) TPB TPBank VAB VAB VCB Vietcombank VIB VIB VPB VPBank Sai Gon Thuong Tin Commercial Joint Stock Bank Vietnam Technological and Commercial Joint 18 Stock Bank 19 Tien Phong Commercial Joint Stock Bank 17 20 21 22 23 Vietnam - Asia Joint Stock Bank JointStock Commercial Bank For Foreign Trade Of Vietnam Vietnam International Commercial Joint Stock Bank Vietnam Prosperity Joint Stock Commercial Bank 97 Appendix 2: Descriptive statistic Variable Obs Mean ROA ROE LC LCA LCL 276 276 276 276 276 0108844 1282076 0962539 -.1181477 2364105 LCOBS SIZE CAP LOANS DEP 276 276 276 276 276 COST LLP GDP TB 276 276 276 276 Std Dev Min Max 0081081 0879546 1754961 0664714 1010992 -.0055299 -.0822716 -.5891604 -.2682699 -.1594039 0524355 3582474 8596061 1966422 404108 -.0203469 32.28961 0950797 5773058 6273683 1342934 1.241807 0448682 1193391 1430873 -.6468172 28.83398 0262139 1697196 1309261 9868994 34.9553 3323917 8207877 8937174 5305924 0153098 0593625 0552645 3752775 0143788 0109214 0282727 -.5322074 0024349 02906 01887 2.327052 1554985 07076 11335 corr ROA ROE Appendix LC LCA LCL LCOBS3:SIZE CAP LOANS DEP COST LLP GDP TB Correlation matrix (obs=276) ROA ROE LC LCA LCL LCOBS SIZE CAP LOANS DEP COST LLP GDP TB ROA ROE LC LCA LCL LCOBS SIZE CAP LOANS DEP 1.0000 0.8035 -0.1445 -0.1940 -0.2646 0.1234 0.0389 0.3430 0.0787 -0.1561 -0.4903 -0.0359 -0.0866 0.2317 1.0000 -0.0993 -0.2609 -0.0635 0.0560 0.3732 -0.1695 0.1302 -0.0414 -0.5032 -0.0232 -0.0442 0.1156 1.0000 0.4778 0.5267 0.6671 0.1670 -0.1176 0.3858 0.5335 -0.0027 -0.0741 -0.0083 -0.0713 1.0000 0.2165 -0.0506 0.0387 0.0283 0.4534 0.3141 0.2188 -0.0256 -0.0170 -0.2196 1.0000 -0.1400 0.3844 -0.3411 0.5503 0.9036 0.0927 -0.0616 0.0614 -0.5186 1.0000 -0.1139 0.1145 -0.1322 -0.1332 -0.1830 -0.0334 -0.0441 0.4037 1.0000 -0.6675 0.3195 0.3531 -0.2352 0.0370 0.0005 -0.3598 1.0000 -0.0536 -0.1978 0.0131 -0.0142 -0.0575 0.2672 1.0000 0.6079 0.0361 -0.1044 -0.0100 -0.4473 1.0000 0.0362 -0.0795 -0.0099 -0.5182 COST LLP GDP TB 1.0000 -0.0962 1.0000 0.0712 -0.0887 1.0000 -0.2307 0.1200 0.0455 1.0000 98 Appendix 4: Model regression using Pooled OLS, FEM and REM method of models POOLED OLS Model (1) reg ROA LC SIZE CAP LOANS DEP COST LLP GDP TB Source SS df MS Model Residual 008682267 009396487 266 000964696 000035325 Total 018078754 275 000065741 ROA Coef LC SIZE CAP LOANS DEP COST LLP GDP TB _cons -.0067872 0022963 0907041 0143177 -.0081053 -.0083568 -.0578167 -.035052 0455896 -.0695331 Std Err .0025736 0004583 011452 0040821 0038747 0010761 0254575 0332485 0173333 0156398 t -2.64 5.01 7.92 3.51 -2.09 -7.77 -2.27 -1.05 2.63 -4.45 Number of obs F(9, 266) Prob > F R-squared Adj R-squared Root MSE P>|t| 0.009 0.000 0.000 0.001 0.037 0.000 0.024 0.293 0.009 0.000 = = = = = = 276 27.31 0.0000 0.4802 0.4627 00594 [95% Conf Interval] -.0118544 001394 0681561 0062805 -.0157343 -.0104755 -.1079406 -.1005157 0114617 -.1003268 -.0017201 0031986 1132522 022355 -.0004764 -.0062381 -.0076927 0304117 0797176 -.0387395 FEM Model (1) ssc install estout, replace Fixed-effects (within) regression Group variable: bank1 Number of obs Number of groups R-sq: Obs per group: within = 0.4992 between = 0.2937 overall = 0.3983 corr(u_i, Xb) = = 276 23 = avg = max = 12 12.0 12 = = 27.02 0.0000 F(9,244) Prob > F = -0.3504 ROA Coef Std Err LC SIZE CAP LOANS DEP COST LLP GDP TB _cons -.0051379 0040929 0816182 0276921 -.0121745 -.0075124 -.0551857 -.0438148 0957266 -.1347468 0026968 0008998 0117678 0050153 0041013 0011983 024173 0285691 0213475 0304858 sigma_u sigma_e rho 00445809 00507121 43592472 (fraction of variance due to u_i) F test that all u_i=0: F(22, 244) = 5.52 t -1.91 4.55 6.94 5.52 -2.97 -6.27 -2.28 -1.53 4.48 -4.42 P>|t| 0.058 0.000 0.000 0.000 0.003 0.000 0.023 0.126 0.000 0.000 [95% Conf Interval] -.01045 0023205 0584388 0178132 -.020253 -.0098728 -.1028001 -.1000884 0536776 -.1947957 0001741 0058653 1047977 0375709 -.004096 -.005152 -.0075712 0124588 1377755 -.0746979 Prob > F = 0.0000 99 REM Model (1) xtreg ROA LC SIZE CAP LOANS DEP COST LLP GDP TB, re Random-effects GLS regression Group variable: bank1 Number of obs Number of groups R-sq: Obs per group: within = 0.4923 between = 0.4017 overall = 0.4587 corr(u_i, X) = = 276 23 = avg = max = 12 12.0 12 = = 250.11 0.0000 Wald chi2(9) Prob > chi2 = (assumed) ROA Coef Std Err z LC SIZE CAP LOANS DEP COST LLP GDP TB _cons -.0062326 0028021 082056 0236713 -.0115919 -.007697 -.0546297 -.0403564 0679327 -.089629 0025825 0006364 0113473 0046127 0039392 0011391 0237773 0286501 0181219 0216408 sigma_u sigma_e rho 00338994 00507121 30884392 (fraction of variance due to u_i) -2.41 4.40 7.23 5.13 -2.94 -6.76 -2.30 -1.41 3.75 -4.14 P>|z| 0.016 0.000 0.000 0.000 0.003 0.000 0.022 0.159 0.000 0.000 [95% Conf Interval] -.0112942 0015549 0598157 0146306 -.0193125 -.0099295 -.1012324 -.0965096 0324144 -.1320443 -.0011711 0040494 1042963 032712 -.0038712 -.0054645 -.008027 0157969 103451 -.0472138 reg ROA LCA LCL LCOBS SIZE CAP LOANS COST LLP GDP TB POOLED OLS Model (2) Source SS df MS Model Residual 009056185 009022569 10 265 000905618 000034047 Total 018078754 275 000065741 ROA Coef LCA LCL LCOBS SIZE CAP LOANS COST LLP GDP TB _cons -.023749 -.0208049 -.0008367 0021495 0846303 0190772 -.0074567 -.0467852 -.0243741 0317485 -.0711206 Std Err .0061382 0047463 0029175 0004496 0114903 0042347 0010813 0251258 0328418 0172043 0153654 t -3.87 -4.38 -0.29 4.78 7.37 4.50 -6.90 -1.86 -0.74 1.85 -4.63 Number of obs F(10, 265) Prob > F R-squared Adj R-squared Root MSE P>|t| 0.000 0.000 0.775 0.000 0.000 0.000 0.000 0.064 0.459 0.066 0.000 = = = = = = 276 26.60 0.0000 0.5009 0.4821 00584 [95% Conf Interval] -.0358348 -.0301503 -.0065812 0012642 0620064 0107392 -.0095857 -.0962568 -.0890382 -.0021261 -.1013744 -.0116632 -.0114596 0049078 0030348 1072541 0274152 -.0053277 0026864 0402899 0656231 -.0408669 100 FEM Model (2) xtreg ROA LCA LCL LCOBS SIZE CAP LOANS COST LLP GDP TB, fe Fixed-effects (within) regression Group variable: bank1 Number of obs Number of groups R-sq: Obs per group: within = 0.4945 between = 0.3278 overall = 0.3990 corr(u_i, Xb) ROA Coef LCA LCL LCOBS SIZE CAP LOANS COST LLP GDP TB _cons -.0148056 -.0193573 -.0027877 0043205 0783898 0286143 -.0072637 -.0491757 -.0345226 098671 -.1486219 00801 0049633 0030162 0009199 0129033 0053174 0012095 024579 0289679 0213516 0314302 sigma_u sigma_e rho 00454247 00510515 44187417 (fraction of variance due to u_i) Std Err t -1.85 -3.90 -0.92 4.70 6.08 5.38 -6.01 -2.00 -1.19 4.62 -4.73 P>|t| = avg = max = 12 12.0 12 = = 23.77 0.0000 0.066 0.000 0.356 0.000 0.000 0.000 0.000 0.047 0.235 0.000 0.000 [95% Conf Interval] -.0305836 -.0291339 -.008729 0025084 0529733 0181402 -.0096462 -.0975907 -.0915827 0566132 -.2105323 F test that all u_i=0: F(22, 243) = 4.69 0009723 -.0095807 0031535 0061326 1038063 0390884 -.0048812 -.0007606 0225376 1407288 -.0867115 Prob > F = 0.0000 LCOBS SIZE CAP LOANS COST LLP GDP TB, re Random-effects GLS regression Group variable: bank1 Number of obs Number of groups R-sq: Obs per group: within = 0.4810 between = 0.5026 overall = 0.4852 corr(u_i, X) 276 23 F(10,243) Prob > F = -0.4099 REM (2)LCL xtregModel ROA LCA = = = = 276 23 = avg = max = 12 12.0 12 = = 246.61 0.0000 Wald chi2(10) Prob > chi2 = (assumed) ROA Coef Std Err z LCA LCL LCOBS SIZE CAP LOANS COST LLP GDP TB _cons -.0178526 -.0209701 -.0033563 0025431 0784259 0239144 -.0073907 -.0470873 -.0292408 0576079 -.0865195 0070885 0047737 002897 0005886 0120512 004773 0011422 0242492 0294783 0178163 02013 sigma_u sigma_e rho 00257603 00510515 20294258 (fraction of variance due to u_i) -2.52 -4.39 -1.16 4.32 6.51 5.01 -6.47 -1.94 -0.99 3.23 -4.30 P>|z| 0.012 0.000 0.247 0.000 0.000 0.000 0.000 0.052 0.321 0.001 0.000 [95% Conf Interval] -.0317459 -.0303264 -.0090344 0013895 0548059 0145594 -.0096294 -.0946148 -.0870172 0226886 -.1259736 -.0039594 -.0116138 0023218 0036967 1020458 0332694 -.005152 0004402 0285356 0925272 -.0470654 101 reg ROE LC SIZE CAP LOANS DEP COST LLP GDP TB POOLED OLS Model (3) Source SS df MS Model Residual 872294037 1.25510675 266 09692156 004718446 Total 2.12740079 275 007736003 ROE Coef LC SIZE CAP LOANS DEP COST LLP GDP TB _cons -.1007014 0225847 -.0822881 1939241 -.0588801 -.0915392 -.5979017 -.3023182 6800187 -.6204509 Std Err .0297436 0052964 1323544 0471777 0447811 0124367 2942213 3842637 2003268 1807549 t -3.39 4.26 -0.62 4.11 -1.31 -7.36 -2.03 -0.79 3.39 -3.43 Number of obs F(9, 266) Prob > F R-squared Adj R-squared Root MSE P>|t| 0.001 0.000 0.535 0.000 0.190 0.000 0.043 0.432 0.001 0.001 = = = = = = 276 20.54 0.0000 0.4100 0.3901 06869 [95% Conf Interval] -.1592643 0121565 -.3428836 1010349 -.1470507 -.116026 -1.177201 -1.058903 2855907 -.9763431 -.0421385 0330128 1783074 2868133 0292904 -.0670524 -.0186027 4542672 1.074447 -.2645586 FEM Model (3) xtreg ROE LC SIZE CAP LOANS DEP COST LLP GDP TB, fe Fixed-effects (within) regression Group variable: bank1 Number of obs Number of groups R-sq: Obs per group: within = 0.3382 between = 0.4852 overall = 0.3802 corr(u_i, Xb) = = 276 23 = avg = max = 12 12.0 12 = = 13.85 0.0000 F(9,244) Prob > F = -0.3599 ROE Coef Std Err LC SIZE CAP LOANS DEP COST LLP GDP TB _cons -.0832384 0363529 -.204959 2862391 -.0931039 -.0755808 -.7431002 -.429828 1.101886 -1.108851 0315189 0105163 1375348 058616 0479336 0140053 2825196 3338985 2494967 3562992 sigma_u sigma_e rho 04481186 05926914 3637253 (fraction of variance due to u_i) F test that all u_i=0: F(22, 244) = 5.15 t -2.64 3.46 -1.49 4.88 -1.94 -5.40 -2.63 -1.29 4.42 -3.11 P>|t| 0.009 0.001 0.137 0.000 0.053 0.000 0.009 0.199 0.000 0.002 [95% Conf Interval] -.1453222 0156385 -.4758659 1707812 -.1875203 -.1031675 -1.299589 -1.087519 6104436 -1.810665 -.0211546 0570672 0659479 4016971 0013125 -.0479941 -.1866116 2278631 1.593328 -.4070359 Prob > F = 0.0000 102 xtreg ROE LC SIZE CAP LOANS DEP COST LLP GDP TB, re Random-effects GLS regression Group variable: bank1 Number of obs Number of groups R-sq: Obs per group: within = 0.3345 between = 0.5097 overall = 0.3985 corr(u_i, X) = = 276 23 = avg = max = 12 12.0 12 = = 142.05 0.0000 Wald chi2(9) Prob > chi2 = (assumed) ROE Coef Std Err z P>|z| LC SIZE CAP LOANS DEP COST LLP GDP TB _cons -.0922003 0266105 -.1902038 2580893 -.0873069 -.0793599 -.7077911 -.3904201 88532 -.771107 0299551 0074125 1316074 0535511 0456922 0132156 2756673 3320182 2104742 2520634 sigma_u sigma_e rho 04017801 05926914 31485079 (fraction of variance due to u_i) -3.08 3.59 -1.45 4.82 -1.91 -6.01 -2.57 -1.18 4.21 -3.06 [95% Conf Interval] 0.002 0.000 0.148 0.000 0.056 0.000 0.010 0.240 0.000 0.002 -.1509112 0120823 -.4481497 1531311 -.1768619 -.105262 -1.248089 -1.041164 4727982 -1.265142 -.0334894 0411388 067742 3630475 0022482 -.0534578 -.1674932 2603236 1.297842 -.2770717 REM Model (3) est sto REM4 OLS Model (4) POOLED FEM Model (4) reg ROE LCA LCL LCOBS SIZE CAP LOANS COST LLP GDP TB Source SS df MS Model Residual 94298277 1.18441802 10 265 094298277 004469502 Total 2.12740079 275 007736003 ROE Coef LCA LCL LCOBS SIZE CAP LOANS COST LLP GDP TB _cons -.3665195 -.1941633 -.0225519 0209014 -.1185333 2616944 -.0791693 -.4571993 -.216829 517488 -.6510805 Std Err .0703276 0543809 0334275 0051517 1316491 0485193 0123887 2878772 3762828 1971176 1760479 t -5.21 -3.57 -0.67 4.06 -0.90 5.39 -6.39 -1.59 -0.58 2.63 -3.70 Number of obs F(10, 265) Prob > F R-squared Adj R-squared Root MSE P>|t| 0.000 0.000 0.500 0.000 0.369 0.000 0.000 0.113 0.565 0.009 0.000 = = = = = = 276 21.10 0.0000 0.4433 0.4222 06685 [95% Conf Interval] -.5049914 -.301237 -.0883693 010758 -.3777446 1661619 -.1035621 -1.024017 -.9577135 1293722 -.997711 -.2280476 -.0870897 0432655 0310448 1406779 3572268 -.0547765 1096183 5240555 9056039 -.30445 103 xtreg ROE LCA LCL LCOBS SIZE CAP LOANS COST LLP GDP TB, fe Fixed-effects (within) regression Group variable: bank1 Number of obs Number of groups R-sq: Obs per group: within = 0.3333 between = 0.5151 overall = 0.3864 corr(u_i, Xb) = = 276 23 = avg = max = 12 12.0 12 = = 12.15 0.0000 F(10,243) Prob > F = -0.4141 ROE Coef Std Err t LCA LCL LCOBS SIZE CAP LOANS COST LLP GDP TB _cons -.1462214 -.1960837 -.0603661 0380159 -.2378925 2921857 -.074077 -.6912232 -.3490077 1.111021 -1.208316 093524 0579507 035217 0107411 1506567 0620854 0141223 2869806 3382244 2492977 3669744 sigma_u sigma_e rho 04494653 059607 36248398 (fraction of variance due to u_i) -1.56 -3.38 -1.71 3.54 -1.58 4.71 -5.25 -2.41 -1.03 4.46 -3.29 P>|t| 0.119 0.001 0.088 0.000 0.116 0.000 0.000 0.017 0.303 0.000 0.001 [95% Conf Interval] -.3304426 -.3102336 -.1297356 0168583 -.5346522 1698914 -.1018947 -1.25651 -1.015233 6199609 -1.931172 F test that all u_i=0: F(22, 243) = 4.11 0379999 -.0819338 0090034 0591735 0588672 4144799 -.0462593 -.125936 317218 1.602081 -.4854589 Prob > F = 0.0000 REM Model (4) xtreg ROE LCA LCL LCOBS SIZE CAP LOANS COST LLP GDP TB, re Random-effects GLS regression Group variable: bank1 Number of obs Number of groups R-sq: Obs per group: within = 0.3206 between = 0.6058 overall = 0.4301 corr(u_i, X) = = 276 23 = avg = max = 12 12.0 12 = = 151.96 0.0000 Wald chi2(10) Prob > chi2 = (assumed) ROE Coef Std Err z LCA LCL LCOBS SIZE CAP LOANS COST LLP GDP TB _cons -.2492995 -.2018219 -.0558317 0240014 -.1913288 2723623 -.0776221 -.5870983 -.2799385 741383 -.7428899 0808462 0551521 0334883 0065608 1386363 0545547 0131435 2810994 3435842 2041253 2243691 sigma_u sigma_e rho 02663892 059607 16647765 (fraction of variance due to u_i) -3.08 -3.66 -1.67 3.66 -1.38 4.99 -5.91 -2.09 -0.81 3.63 -3.31 P>|z| 0.002 0.000 0.095 0.000 0.168 0.000 0.000 0.037 0.415 0.000 0.001 [95% Conf Interval] -.4077551 -.3099181 -.1214676 0111424 -.4630509 165437 -.1033829 -1.138043 -.9533511 3413047 -1.182645 -.0908439 -.0937258 0098041 0368603 0803933 3792876 -.0518613 -.0361536 3934741 1.141461 -.3031346 104 Appendix 5: Model selection Heteroskedasticity diagnostics Model 1(ROA) test Autcorrelation diagnostics xttest0 Breusch and Pagan Lagrangian multiplier test for random effects ROA[bank1,t] = Xb + u[bank1] + e[bank1,t] Estimated results: Var ROA e u Test: sd = sqrt(Var) 0000657 0000257 0000115 0081081 0050712 0033899 Var(u) = chibar2(01) = Prob > chibar2 = 78.90 0.0000 xtserial ROA LC SIZE CAP LOANS DEP COST LLP GDP TB Wooldridge test for autocorrelation in panel data H0: no first-order autocorrelation F( 1, 22) = 14.243 Prob > F = 0.0010 Model (ROA) xttest3 Modified Wald test for groupwise heteroskedasticity in fixed effect regression model H0: sigma(i)^2 = sigma^2 for all i chi2 (23) = Prob>chi2 = 377.03 0.0000 xtserial ROA LCA LCL LCOBS SIZE CAP LOANS COST LLP GDP TB Wooldridge test for autocorrelation in panel data H0: no first-order autocorrelation F( 1, 22) = 14.250 Prob > F = 0.0010 and 105 Model (ROE) Breusch and Pagan Lagrangian multiplier test for random effects ROE[bank1,t] = Xb + u[bank1] + e[bank1,t] Estimated results: Var ROE e u Test: sd = sqrt(Var) 007736 0035128 0016143 0879546 0592691 040178 Var(u) = chibar2(01) = Prob > chibar2 = 80.89 0.0000 xtserial ROE LC SIZE CAP LOANS DEP COST LLP GDP TB Wooldridge test for autocorrelation in panel data H0: no first-order autocorrelation F( 1, 22) = 29.965 Prob > F = 0.0000 Model (ROE) xttest3 Modified Wald test for groupwise heteroskedasticity in fixed effect regression model H0: sigma(i)^2 = sigma^2 for all i chi2 (23) = Prob>chi2 = 482.83 0.0000 xtserial ROE LCA LCL LCOBS SIZE CAP LOANS COST LLP GDP TB Wooldridge test for autocorrelation in panel data H0: no first-order autocorrelation F( 1, 22) = 30.316 Prob > F = 0.0000 106 Appendix 5: xtgls ROA LC SIZE CAP LOANS DEP COST LLP GDP TB, panels(h) corr(ar1) Est im ate d FG LS mo del (1) Cross-sectional time-series FGLS regression Coefficients: Panels: Correlation: generalized least squares heteroskedastic common AR(1) coefficient for all panels Estimated covariances = Estimated autocorrelations = Estimated coefficients = ROA Coef LC SIZE CAP LOANS DEP COST LLP GDP TB _cons -.0049665 0016972 0782178 0025015 -.0000777 -.0056801 -.0332666 -.0095957 0441724 -.0504161 23 10 Number of obs Number of groups Time periods Wald chi2(9) Prob > chi2 Std Err .0022705 0004599 011461 0037376 0030668 0008952 0145297 019736 015625 0152647 (0.6067) z -2.19 3.69 6.82 0.67 -0.03 -6.35 -2.29 -0.49 2.83 -3.30 P>|z| 0.029 0.000 0.000 0.503 0.980 0.000 0.022 0.627 0.005 0.001 = = = = = 276 23 12 128.57 0.0000 [95% Conf Interval] -.0094167 0007958 0557547 -.0048241 -.0060885 -.0074347 -.0617443 -.0482775 0135481 -.0803344 -.0005163 0025986 1006809 0098271 0059331 -.0039256 -.0047889 0290861 0747968 -.0204978 Est imated FGLS model (2) Cross-sectional time-series FGLS regression Coefficients: Panels: Correlation: generalized least squares heteroskedastic common AR(1) coefficient for all panels Estimated covariances = Estimated autocorrelations = Estimated coefficients = ROA Coef LCA LCL LCOBS SIZE CAP LOANS COST LLP GDP TB _cons -.0151628 -.0077896 -.0002436 0018357 0806953 0042296 -.0054986 -.0310784 -.0063622 034011 -.0563962 23 11 Std Err .0048585 0034767 0027305 0004478 011371 003699 0008736 0148369 0200967 0153216 014864 (0.5735) Number of obs Number of groups Time periods Wald chi2(10) Prob > chi2 z -3.12 -2.24 -0.09 4.10 7.10 1.14 -6.29 -2.09 -0.32 2.22 -3.79 P>|z| 0.002 0.025 0.929 0.000 0.000 0.253 0.000 0.036 0.752 0.026 0.000 = = = = = 276 23 12 149.70 0.0000 [95% Conf Interval] -.0246852 -.0146038 -.0055952 000958 0584085 -.0030204 -.0072109 -.0601582 -.045751 0039812 -.0855292 -.0056404 -.0009753 005108 0027134 1029821 0114796 -.0037863 -.0019985 0330265 0640409 -.0272633 107 xtgls ROE LC SIZE CAP LOANS DEP COST LLP GDP TB, panels(h) corr(ar1) Cross-sectional time-series FGLS regression Coefficients: Panels: Correlation: generalized least squares heteroskedastic common AR(1) coefficient for all panels Estimated covariances = Estimated autocorrelations = Estimated coefficients = ROE Coef LC SIZE CAP LOANS DEP COST LLP GDP TB _cons -.0571173 0199691 -.1151855 0866603 0014627 -.0587552 -.420238 -.0333327 6786404 -.5483077 23 10 Number of obs Number of groups Time periods Wald chi2(9) Prob > chi2 Std Err .0270311 0053721 1185974 0428082 0364515 0102049 1792003 2394135 1919227 180639 (0.5962) z -2.11 3.72 -0.97 2.02 0.04 -5.76 -2.35 -0.14 3.54 -3.04 P>|z| 0.035 0.000 0.331 0.043 0.968 0.000 0.019 0.889 0.000 0.002 = = = = = 276 23 12 103.19 0.0000 [95% Conf Interval] -.1100972 0094399 -.3476323 0027577 -.0699809 -.0787565 -.7714642 -.5025744 3024789 -.9023536 -.0041374 0304983 1172612 1705629 0729064 -.0387539 -.0690119 4359091 1.054802 -.1942618 Estimated FGLS model (3) Estimated FGLS model (4) xtgls ROE LCA LCL LCOBS SIZE CAP LOANS COST LLP GDP TB, panels(h) corr(ar1) Cross-sectional time-series FGLS regression Coefficients: Panels: Correlation: generalized least squares heteroskedastic common AR(1) coefficient for all panels Estimated covariances = Estimated autocorrelations = Estimated coefficients = ROE Coef LCA LCL LCOBS SIZE CAP LOANS COST LLP GDP TB _cons -.156218 -.0832647 -.0125182 0201016 -.0998046 1169122 -.0570069 -.4017593 0016303 5948611 -.5742216 23 11 Std Err .0577216 0440384 0336534 0052107 1219084 0438779 0101082 1842778 2434849 1885484 174874 (0.5580) Number of obs Number of groups Time periods Wald chi2(10) Prob > chi2 z -2.71 -1.89 -0.37 3.86 -0.82 2.66 -5.64 -2.18 0.01 3.15 -3.28 P>|z| 0.007 0.059 0.710 0.000 0.413 0.008 0.000 0.029 0.995 0.002 0.001 = = = = = 276 23 12 119.96 0.0000 [95% Conf Interval] -.2693502 -.1695785 -.0784775 0098888 -.3387406 0309131 -.0768186 -.7629371 -.4755913 225313 -.9169684 -.0430857 0030491 0534412 0303143 1391314 2029113 -.0371951 -.0405815 4788519 9644091 -.2314749 ... on the issue of the impact of liquidity creation on the profitability of commercial banks The author will refer to several studies on the impact of liquidity creation on commercial banks' profits,... decided to explore the issue of the "Impact of liquidity creation on the profit of Vietnamese commercial banks" A brief overview of the research process on liquidity creation of banks is presented... the impact of liquidity creation represented by the “cat fat” measure on bank profitability, the research on the topic aims to investigate and find the impact of liquidity creation on the profitability