Tác động của chiến lược đa dạng hóa cho vay đến lợi nhuận của các ngân hàng thương mại việt nam

B TR NG GIÁO D C VÀ ÀO T O I H C KINH T TP H CHÍ MINH T NG TH H I HÀ TÁC NG C A CHI N L C A D NG HÓA CHO VAY N L I NHU N C A CÁC NGÂN HÀNG TH NG M I VI T NAM LU N V N TH C S KINH T TP H Chí Minh – N m 2019 B TR NG GIÁO D C VÀ ÀO T O I H C KINH T TP H CHÍ MINH T NG TH H I HÀ TÁC NG C A CHI N L C A D NG HÓA CHO VAY N L I NHU N C A CÁC NGÂN HÀNG TH NG M I VI T NAM Chuyên ngành: Tài – Ngân hàng Mã s : 8340201 LU N V N TH C S KINH T NG IH NG D N KHOA H C: PGS TS NGUY N H U HUY NH T TP H Chí Minh – N m 2019 L I CAM OAN Tôi xin cam đoan lu n v n th c s “Tác đ ng c a chi n l đ n l i nhu n c a ngân hàng th c đa d ng hóa cho vay ng m i Vi t Nam” k t qu c a trình h c t p, nghiên c u khoa h c đ c l p, nghiêm túc c a cá nhân d is h ng d n c a PGS TS Nguy n H u Huy Nh t Các s li u đ c nêu lu n v n đ t th c t , đáng tin c y, đ c trích ngu n rõ rang đ c thu th p c x lý trung th c khách quan K t qu nghiên c u lu n v n trung th c ch a đ c công b b t k cơng trình nghiên c u khác TP.HCM, ngày tháng Tác gi T ng Th H i Hà n m 2019 M CL C TRANG PH BÌA L I CAM OAN M CL C DANH M C CÁC B NG DANH M C CÁC HÌNH DANH M C CÁC T VI T T T TÓM T T - ABSTRACT CH NG GI I THI U NGHIÊN C U 1.1 Lý ch n đ tài 1.2 M c tiêu câu h i nghiên c u 1.2.1 M c tiêu nghiên c u 1.2.2 Câu h i nghiên c u 1.3 Ph m vi đ i t 1.3.1 Ph m vi nghiên c u it 1.3.2 1.4 ng nghiên c u Ph ng nghiên c u ng pháp nghiên c u 1.5 óng góp m i c a lu n v n 1.6 K t c u lu n v n CH NG T NG QUAN LÝ THUY T VÀ NGHIÊN C U TH C NGHI M TR C ÂY 2.1 T ng quan đa d ng hóa cho vay 2.1.1 2.1.2 2.2 Khái ni m ol ng T ng quan lý thuy t liên quan 10 2.2.1 Lý thuy t danh m c đ u t hi n đ i (MPT) 10 2.2.2 Mơ hình chi n l 2.2.3 Lý thuy t ngu n l c 12 2.3 c đa d ng hóa 11 T ng quan nghiên c u tr c 13 2.3.1 Nghiên c u n 2.3.2 Nghiên c u Vi t Nam 21 c 13 K T LU N CH NG 28 CH NG PHÁP VÀ D NG PH LI U NGHIÊN C U 29 3.1 Mơ hình nghiên c u 29 3.2 Gi thuy t nghiên c u 32 3.2.1 Chi n l c đa d ng hóa 32 3.2.2 Ho t đ ng cho vay 33 3.2.3 R i ro tín d ng 34 3.2.4 Hi u qu chi phí 35 3.2.5 Quy mô ngân hàng 36 3.2.6 Thanh kho n ngân hàng 37 3.2.7 T ng tr ng tài s n 37 3.3 D li u nghiên c u 38 3.4 Ph ng pháp nghiên c u 40 K T LU N CH CH NG 43 NG K T QU NGHIÊN C U 44 4.1 Th c tr ng đa d ng hóa cho vay c a ngân hàng 44 4.2 Th ng kê mô t ma tr n t 4.3 Ki m tra ph 4.4 K t qu h i quy 54 ng quan 46 ng sai thay đ i t t ng quan 53 4.4.1 L i nhu n ROA 55 4.4.2 L i nhu n ROE 61 K T LU N CH NG 68 CH NG K T LU N 69 5.1 K t lu n 69 5.2 Hàm ý sách 71 5.3 H n ch đ tài 75 5.4 H ng nghiên c u sau 76 K T LU N CH NG 78 TÀI LI U THAM KH O PH L C DANH M C CÁC B NG B ng 3.1 Mô t bi n 31 B ng 3.2 K v ng d u c a h s h i quy c a bi n đ c l p 38 B ng 3.3 Danh sách ngân hàng TMCP m u nghiên c u 39 B ng 4.1 Mô t th ng kê bi n mơ hình 47 B ng 4.2 T l cho vay bình quân theo lo i hình khách hàng k h n kho n vay c a ngân hàng th B ng 4.3 Ma tr n t ng m i 50 ng quan 52 B ng 4.4 K t qu ki m tra ph ng sai thay đ i Modified Wald 53 B ng 4.5 K t qu ki m tra t t ng quan Wooldridge 54 B ng 4.6 K t qu cl ng tác đ ng c a chi n l c đa d ng hóa cho vay đ n l i nhu n ROA c a ngân hàng 56 B ng 4.7 K t qu cl ng tác đ ng c a chi n l c đa d ng hóa cho vay đ n l i nhu n ROE c a ngân hàng 63 DANH M C CÁC HÌNH Hình 4.1 Tình hình t l cho vay bình quân c a ngân hàng theo lo i hình khách hàng t n m 2010 đ n n m 2017 44 Hình 4.2 Tình hình t l cho vay bình quân c a ngân hàng theo k h n kho n vay t n m 2010 đ n n m 2017 45 DANH M C CÁC T VI T T T T vi t t t Di n gi i FGLS Feasible Generalized Least Squares ROA Return On Assets ROE Return On Equity MPT Modern Porfolio Theory GLS Generalized Least Squares HHI Herfindahl-Hirschman OLS Ordinary Least Squares GMM Generalized Method of Moments KHCN Khách Hàng Cá Nhân KHDN Khách Hàng Doanh Nghi p TMCP Th ng M i C Ph n TÓM T T Lu n v n tìm hi u nh h ngân hàng th ng c a chi n l ng m i c ph n kinh doanh t i Vi t Nam giai đo n 2010 – 2017 b ng cách ti p c n ph ng pháp c a Lee c ng s (2014) c ng nh m t s nghiên c u khác Trong chi n l d c đa d ng hóa đ n l i nhu n c a 23 c đa d ng hóa nghiên c u đ c ti p c n i khía c nh cho vay, c th nghiên c u t p trung xem li u ngân hàng t p trung vào m t h khách hàng, m t k h n có mang l i cho ngân hàng l i nhu n nhi u h n so v i vi c ngân hàng đa d ng hóa h khách hàng (khách hàng cá nhân khách hàng doanh nghi p) k h n kho n vay (ng n h n, trung h n dài h n) H n th n a, v i vi c s d ng ph ph l ng pháp cl ng FGLS đ kh c ph c v n đ t t ng quan ng sai thay đ i t n t i sai s c a mơ hình, lu n v n tìm th y đ c r ng chi n c đa d ng hóa theo lo i hình khách hàng (khách hàng cá nhân khách hàng doanh nghi p) k h n kho n vay (ng n h n, trung h n dài h n) s làm cho l i nhu n c a ngân hàng suy gi m đáng k M t khác, y u t khác mơ hình nghiên c u quy t đ nh l i nhu n c a ngân hàng c ng có tác đ ng đáng k đ n l i nhu n c a ngân hàng C th , quy mô ngân hàng, ho t đ ng cho vay, chi phí ho t đ ng, kho n t ng tr ng tài s n có t ng quan d ng v i l i nhu n c a ngân hàng K t qu cho th y r ng ngân hàng có quy mô l n, cho vay nhi u, chi tr nhi u chi phí ho t đ ng, n m gi nhi u tài s n kho n, tài s n t ng tr mang đ n nhi u l i nhu n h n cho ngân hàng Ng ng nhanh s c l i, r i ro tín d ng có t ng quan âm v i l i nhu n c a ngân hàng K t qu cho th y r ng ngân hàng có r i ro tín d ng cao s làm gi m l i nhu n mà ngân hàng đ t đ c T khóa: L i nhu n, đa d ng hóa, cho vay, ngân hàng, FGLS Diamond, D W (1984) Financial intermediation and delegated monitoring The review of economic studies, 51(3), 393-414 Diamond, D W (1991) Monitoring and reputation: The choice between bank loans and directly placed debt Journal of political Economy, 99(4), 689-721 Dietrich, A., & Wanzenried, G (2011) Determinants of bank profitability before and during the crisis: Evidence from Switzerland Journal of International Financial Markets, Institutions and Money, 21(3), 307-327 Elsas, R., Hackethal, A., & Holzhäuser, M (2010) The anatomy of bank diversification Journal of Banking & Finance, 34(6), 1274-1287 Fabozzi, F J., Gupta, F., & Markowitz, H M (2002) The legacy of modern portfolio theory The Journal of Investing, 11(3), 7-22 García-Herrero, A., Gavilá, S., & Santabárbara, D (2009) What explains the low profitability of Chinese banks? Journal of Banking & Finance, 33(11), 20802092 Gort, M (1962) Front matter, diversification and integration in American industry In Diversification and integration in American Industry (pp 22-0) Greenwood Press Guillén, J., Rengifo, E W., & Ozsoz, E (2014) Relative power and efficiency as a main determinant of banks' profitability in Latin America Borsa Istanbul Review, 14(2), 119-125 Gurbuz, A O., Yanik, S., & Ayturk, Y (2013) Income diversification and bank performance: Evidence from Turkish banking sector Journal of BRSA Banking and Financial markets, 7(1), 9-29 Guru, B K., Staunton, J., & Balashanmugam, B (2002) Determinants of commercial bank profitability in Malaysia Journal of Money, Credit, and Banking, 17(1), 69-82 Hoskisson, R E., & Hitt, M A (1990) Antecedents and performance outcomes of diversification: A review and critique of theoretical perspectives Journal of management, 16(2), 461-509 Ismail, A., Hanif, R., Choudhary, S., & Nisar, A (2015) Income-diversification in banking sector of Pakistan: a'Blessing'or'Curse'? The Journal of Commerce, 7(1), 11 Khan, A., & Hildreth, W B (Eds.) (2002) Budget theory in the public sector Greenwood Publishing Group Lee, C C., Yang, S J., & Chang, C H (2014) Non-interest income, profitability, and risk in banking industry: A cross-country analysis The North American Journal of Economics and Finance, 27, 48-67 Lepetit, L., Nys, E., Rous, P., & Tarazi, A (2008) Bank income structure and risk: An empirical analysis of European banks Journal of banking & finance, 32(8), 1452-1467 Liu, H., & Wilson, J O (2010) The profitability of banks in Japan Applied Financial Economics, 20(24), 1851-1866 Maksimovic, V., & Phillips, G (2002) Do conglomerate firms allocate resources inefficiently across industries? Theory and evidence The Journal of Finance, 57(2), 721-767 Markowitz, H (1952) Portfolio selection The journal of finance, 7(1), 77-91 Mercieca, S., Schaeck, K., & Wolfe, S (2007) Small European banks: Benefits from diversification? Journal of Banking & Finance, 31(7), 1975-1998 Meslier, C., Tacneng, R., & Tarazi, A (2014) Is bank income diversification beneficial? Evidence from an emerging economy Journal of International Financial Markets, Institutions and Money, 31, 97-126 Miller, S M., & Noulas, A G (1997) Portfolio mix and large-bank profitability in the USA Applied Economics, 29(4), 505-512 Montgomery, C A (1994) Corporate Diversificaton Journal of economic perspectives, 8(3), 163-178 Naceur, S B (2003) The determinants of the Tunisian banking industry profitability: Panel evidence Universite Libre de Tunis working papers, 11(3), 317319 Nisar, S., Peng, K., Wang, S., & Ashraf, B (2018) The impact of revenue diversification on bank profitability and stability: Empirical evidence from South Asian countries International Journal of Financial Studies, 6(2), 40 Pasiouras, F., & Kosmidou, K (2007) Factors influencing the profitability of domestic and foreign commercial banks in the European Union Research in International Business and Finance, 21(2), 222-237 Pasiouras, F., & Kosmidou, K (2007) Factors influencing the profitability of domestic and foreign commercial banks in the European Union Research in International Business and Finance, 21(2), 222-237 Rajan, R G (1992) Insiders and outsiders: The choice between informed and arm's length debt The Journal of finance, 47(4), 1367-1400 Rajan, R G., & Zingales, L (2000) The governance of the new enterprise (No w7958) National Bureau of Economic Research Ramanujam, V., & Varadarajan, P (1989) Research on corporate diversification: A synthesis Strategic management journal, 10(6), 523-551 Sanya, S., & Wolfe, S (2011) Can banks in emerging economies benefit from revenue diversification? Journal of Financial Services Research, 40(1-2), 79-101 Short, B K (1979) The relation between commercial bank profit rates and banking concentration in Canada, Western Europe, and Japan Journal of Banking & Finance, 3(3), 209-219 Smirlock, M (1985) Evidence on the (non) relationship between concentration and profitability in banking Journal of money, credit and Banking, 17(1), 69-83 Stein, J C (2002) Information production and capital allocation: Decentralized versus hierarchical firms The journal of finance, 57(5), 1891-1921 Sufian, F., & Chong, R R (2008) Determinants of bank profitability in a developing economy: empirical evidence from the Philippines Asian Academy of Management Journal of Accounting & Finance, 4(2) Sufian, F., & Habibullah, M S (2009) Bank specific and macroeconomic determinants of bank profitability: Empirical evidence from the China banking sector Frontiers of Economics in China, 4(2), 274-291 Tabak, B M., Fazio, D M., & Cajueiro, D O (2011) The effects of loan portfolio concentration on Brazilian banks’ return and risk Journal of Banking & Finance, 35(11), 3065-3076 Weersainghe, V E I W., & Perera, T R (2013) Determinants of profitability of commercial banks in Sri Lanka International Journal of Arts and commerce, 2(10), 141-170 TÀI LI U THAM KH O TI NG VI T oàn Anh Tu n (2016) Tác đ ng c a đa d ng hoá thu nh p đ i v i hi u qu ho t đ ng c a ngân hàng th ng m i Vi t Nam T p chí Qu n lý kinh t , 75, trang 14 – 26 H Th H ng Minh, Nguy n Th Cành (2015) a d ng hoá thu nh p y u t tác đ ng đ n kh n ng sinh l i c a ngân hàng th ng m i Vi t Nam T p chí Cơng ngh Ngân hàng, 106 – 107, trang 13 -24 Tr nh Th Thúy H ng, Nguy n Hoàng Phong, Lê Ti n Thành (2018) Tác đ ng c a đa d ng hóa thu nh p đ n hi u qu ho t đ ng c a ngân hàng th ng m i Vi t Nam T p chí tài http://tapchitaichinh.vn/tai-chinh-kinh-doanh/tac-dong-cua-dadang-hoa-thu-nhap-den-hieu-qua-hoat-dong-cua-cac-ngan-hang-thuong-mai-viet-nam140677.html Võ Xuân Vinh, Tr n Th Ph hoá thu nh p c a ngân hàng th 54 – 70 ng Mai (2015) L i nhu n r i ro t đa d ng ng m i Vi t Nam T p chí phát tri n kinh t , 8, trang PH L C variable mean roa roe size liq loan cost cr growth div1 div2 div3 div4 0076563 0863444 32.173 3801198 8610793 0164706 0060149 2162285 6047416 5793702 4324524 9521005 sd p50 max 0060823 -.0134102 0622354 -.1288367 1.110901 30.16295 115138 1747214 2118318 3718736 0052365 0058254 0047691 -.004846 2544345 -.4164141 1005585 5001392 1140263 2053547 0751374 3338047 1074098 5712094 0068913 0771826 32.25434 3802375 8414302 0157486 0050168 1767916 5696962 6217332 4221628 9610416 0475236 2682345 34.723 7492896 1.805003 0320248 0288064 1.171405 9007951 693008 7049904 1.097906 bank khcn khdn nh th dh ABB ACB BID CTG EIB HDB KLB MBB MSB NAB NASB NVB PGB SEAB SGB SHB STB TCB TPB VAB VCB VIB VPB 3251506 4511914 1917081 1917175 3778536 4804039 7552157 2045852 1749814 3381466 7590808 3377437 2088487 1737002 529404 2466709 436994 390256 3634255 2586644 1753422 4982235 5754723 6748494 5488086 8082919 8082825 6221465 5195961 2447843 7954148 8250186 6618534 2409192 6622563 7911513 8262999 470596 7533291 563006 609744 6365745 7413356 8246578 5017765 4245277 5428617 5048046 5591573 5883247 5544383 5993676 5852646 6175479 416422 5853178 5895978 4779816 6241493 2526435 7229147 5126207 4977307 4375695 5497941 3911815 5925936 472206 4483731 1954283 1741648 1272774 1026936 1312718 2274606 3145514 1824507 273553 2592662 2701629 2504267 1962328 35785 1254769 2514403 3158336 2918217 2434601 2963554 1092856 2367677 3577395 2617099 3210306 3135653 3089817 3142899 1731718 100184 2000015 310025 155416 1402393 2715917 1796179 3895065 1516083 2359391 1864357 2706088 2067459 3124631 2981208 2910263 1938874 Total 3671643 6328357 527081 2300422 2428768 roa roe size liq loan cost cr growth div1 div2 div3 div4 Ph roa roe size liq loan cost cr growth div1 div2 div3 1.0000 0.7608 -0.0047 -0.1186 0.3857 0.1799 0.1320 0.1592 0.0128 -0.0123 0.2797 -0.2909 1.0000 0.4700 -0.0073 0.2767 -0.0227 0.1136 0.2371 0.1040 -0.1026 0.0928 -0.1051 1.0000 -0.0281 -0.0406 -0.1700 0.1944 -0.0602 0.1781 -0.1776 -0.3168 0.2933 1.0000 -0.4883 -0.3371 -0.2899 0.2383 0.1776 -0.1881 -0.1343 0.1568 1.0000 0.0840 0.1338 0.1027 -0.0225 0.0324 0.3121 -0.3308 1.0000 0.4686 -0.4349 -0.3601 0.3566 0.0322 -0.0433 1.0000 -0.3035 -0.0902 0.0880 -0.0081 0.0142 1.0000 0.0606 -0.0596 0.1910 -0.1828 1.0000 -0.9989 0.0492 -0.0672 1.0000 -0.0428 0.0599 1.0000 -0.9937 ng trình ROA + DIV1 Modified Wald test for groupwise heteroskedasticity in fixed effect regression model H0: sigma(i)^2 = sigma^2 for all i chi2 (23) = Prob>chi2 = 10909.48 0.0000 Wooldridge test for autocorrelation in panel data H0: no first-order autocorrelation F( 1, 22) = 26.878 Prob > F = 0.0000 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 size liq loan cost cr growth div1 _cons 0006537 0076307 0086153 3826134 -.1660805 0035329 0055246 -.0336517 23 Std Err .0003412 0036387 001627 082988 0730498 0011797 0032479 0119365 (0.4175) Number of obs Number of groups Time periods Wald chi2(7) Prob > chi2 z 1.92 2.10 5.30 4.61 -2.27 2.99 1.70 -2.82 P>|z| 0.055 0.036 0.000 0.000 0.023 0.003 0.089 0.005 = = = = = 184 23 56.68 0.0000 [95% Conf Interval] -.0000151 000499 0054264 2199598 -.3092556 0012206 -.0008411 -.0570468 0013225 0147624 0118041 5452669 -.0229054 0058451 0118904 -.0102567 Ph ng trình ROA + DIV2 Modified Wald test for groupwise heteroskedasticity in fixed effect regression model H0: sigma(i)^2 = sigma^2 for all i chi2 (23) = Prob>chi2 = 11061.78 0.0000 Wooldridge test for autocorrelation in panel data H0: no first-order autocorrelation F( 1, 22) = 27.177 Prob > F = 0.0000 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 size liq loan cost cr growth div2 _cons 0005965 0073117 0097588 3888453 -.1774463 0039413 -.0050331 -.0265696 23 Std Err .0003434 0035529 0016558 081737 0773709 0011927 0026659 0125393 (5.4509) Number of obs Number of groups Time periods Wald chi2(7) Prob > chi2 z 1.74 2.06 5.89 4.76 -2.29 3.30 -1.89 -2.12 P>|z| 0.082 0.040 0.000 0.000 0.022 0.001 0.059 0.034 = = = = = 184 23 77.38 0.0000 [95% Conf Interval] -.0000767 0003482 0065135 2286437 -.3290906 0016036 -.0102582 -.0511461 0012696 0142752 0130042 5490469 -.0258021 0062789 0001921 -.001993 Ph ng trình ROA + DIV3 Modified Wald test for groupwise heteroskedasticity in fixed effect regression model H0: sigma(i)^2 = sigma^2 for all i chi2 (23) = Prob>chi2 = 4878.56 0.0000 Wooldridge test for autocorrelation in panel data H0: no first-order autocorrelation F( 1, 22) = 30.124 Prob > F = 0.0000 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 size liq loan cost cr growth div3 _cons 0008721 0075414 0080281 3493501 -.1742768 0029947 0146549 -.042327 23 Std Err .0003304 0034929 001606 0783937 0712955 0011572 0049217 0119754 (0.4156) Number of obs Number of groups Time periods Wald chi2(7) Prob > chi2 z 2.64 2.16 5.00 4.46 -2.44 2.59 2.98 -3.53 P>|z| 0.008 0.031 0.000 0.000 0.015 0.010 0.003 0.000 = = = = = 184 23 68.47 0.0000 [95% Conf Interval] 0002245 0006955 0048804 1957013 -.3140135 0007266 0050086 -.0657985 0015197 0143873 0111758 502999 -.0345402 0052628 0243012 -.0188556 Ph ng trình ROA + DIV4 Modified Wald test for groupwise heteroskedasticity in fixed effect regression model H0: sigma(i)^2 = sigma^2 for all i chi2 (23) = Prob>chi2 = 4626.08 0.0000 Wooldridge test for autocorrelation in panel data H0: no first-order autocorrelation F( 1, 22) = 30.579 Prob > F = 0.0000 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 size liq loan cost cr growth div4 _cons 0009043 0072591 0076487 3307754 -.1745481 0034616 -.0139606 -.0231131 23 Std Err .0003014 0032854 0016001 0738314 070818 0011434 0034542 0113623 (5.4188) Number of obs Number of groups Time periods Wald chi2(7) Prob > chi2 z 3.00 2.21 4.78 4.48 -2.46 3.03 -4.04 -2.03 P>|z| 0.003 0.027 0.000 0.000 0.014 0.002 0.000 0.042 = = = = = 184 23 112.92 0.0000 [95% Conf Interval] 0003136 0008199 0045125 1860684 -.3133487 0012207 -.0207308 -.0453828 001495 0136983 0107849 4754823 -.0357474 0057026 -.0071904 -.0008434 Ph ng trình ROE + DIV1 Modified Wald test for groupwise heteroskedasticity in fixed effect regression model H0: sigma(i)^2 = sigma^2 for all i chi2 (23) = Prob>chi2 = 886.54 0.0000 Wooldridge test for autocorrelation in panel data H0: no first-order autocorrelation F( 1, 22) = 25.499 Prob > F = 0.0000 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 size liq loan cost cr growth div1 _cons 0313875 0775025 0849025 4.019755 -2.477647 059931 0696764 -1.136285 23 Std Err .0031407 0360075 0168108 7709908 835693 0141028 0331507 109805 (5.3908) Number of obs Number of groups Time periods Wald chi2(7) Prob > chi2 z 9.99 2.15 5.05 5.21 -2.96 4.25 2.10 -10.35 P>|z| 0.000 0.031 0.000 0.000 0.003 0.000 0.036 0.000 = = = = = 184 23 184.44 0.0000 [95% Conf Interval] 0252318 0069291 0519539 2.508641 -4.115575 0322899 0047023 -1.351499 0375432 148076 1178512 5.530869 -.839719 087572 1346505 -.9210717 Ph ng trình ROE+ DIV2 Modified Wald test for groupwise heteroskedasticity in fixed effect regression model H0: sigma(i)^2 = sigma^2 for all i chi2 (23) = Prob>chi2 = 878.10 0.0000 Wooldridge test for autocorrelation in panel data H0: no first-order autocorrelation F( 1, 22) = 25.788 Prob > F = 0.0000 Cross-sectional time-series FGLS regression Coefficients: Panels: Correlation: generalized least squares heteroskedastic panel-specific AR(1) Estimated covariances = Estimated autocorrelations = Estimated coefficients = roe Coef size liq loan cost cr growth div2 _cons 0321658 1008802 100818 4.454433 -1.553535 0737616 -.0429137 -1.132726 23 23 Std Err .0026152 0309889 0161609 6411825 712012 0134711 0249298 0969435 Number of obs Number of groups Time periods Wald chi2(7) Prob > chi2 z 12.30 3.26 6.24 6.95 -2.18 5.48 -1.72 -11.68 P>|z| 0.000 0.001 0.000 0.000 0.029 0.000 0.085 0.000 = = = = = 184 23 280.47 0.0000 [95% Conf Interval] 0270401 040143 0691433 3.197738 -2.949053 0473587 -.0917751 -1.322731 0372915 1616173 1324927 5.711127 -.1580168 1001645 0059478 -.9427201 Ph ng trình ROE+ DIV3 Modified Wald test for groupwise heteroskedasticity in fixed effect regression model H0: sigma(i)^2 = sigma^2 for all i chi2 (23) = Prob>chi2 = 1509.92 0.0000 Wooldridge test for autocorrelation in panel data H0: no first-order autocorrelation F( 1, 22) = 28.034 Prob > F = 0.0000 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 size liq loan cost cr growth div3 _cons 0347854 0977698 0948744 4.173715 -1.768523 0615875 141614 -1.288133 23 Std Err .0026489 0298979 0157818 60437 7118718 0133644 0415218 0977259 (0.0509) Number of obs Number of groups Time periods Wald chi2(7) Prob > chi2 z 13.13 3.27 6.01 6.91 -2.48 4.61 3.41 -13.18 P>|z| 0.000 0.001 0.000 0.000 0.013 0.000 0.001 0.000 = = = = = 184 23 289.54 0.0000 [95% Conf Interval] 0295936 0391709 0639426 2.989172 -3.163766 0353937 0602328 -1.479672 0399771 1563686 1258061 5.358259 -.37328 0877813 2229952 -1.096594 Ph ng trình ROE+ DIV4 Modified Wald test for groupwise heteroskedasticity in fixed effect regression model H0: sigma(i)^2 = sigma^2 for all i chi2 (23) = Prob>chi2 = 1502.77 0.0000 Wooldridge test for autocorrelation in panel data H0: no first-order autocorrelation F( 1, 22) = 28.277 Prob > F = 0.0000 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 size liq loan cost cr growth div4 _cons 0333706 0769447 0690983 3.179225 -2.375437 0354624 -.0776959 -1.048712 23 Std Err .0033697 0366585 0162107 7625919 7424698 0125602 0322696 1186883 (0.4846) Number of obs Number of groups Time periods Wald chi2(7) Prob > chi2 z 9.90 2.10 4.26 4.17 -3.20 2.82 -2.41 -8.84 P>|z| 0.000 0.036 0.000 0.000 0.001 0.005 0.016 0.000 = = = = = 184 23 126.48 0.0000 [95% Conf Interval] 0267661 0050954 0373259 1.684572 -3.830651 0108449 -.1409432 -1.281336 0399751 148794 1008707 4.673877 -.9202232 0600798 -.0144486 -.8160868 ... a ngân hàng Berger c ng sách đa d ng hóa V i t t c khía c nh c a sách đa s (2010) c a ngân hàng bao g m d ng hóa, ngân hàng đa d ng hóa đa d ng hóa cho vay, đa s làm gi m l i nhu n c a ngân hàng. .. ng r i ro c a ngân hàng Theo tác gi , ngân hàng đa d ng hóa chi n l c cho vay s làm gi m thi u hi u qu giám sát kho n vay c a ngân hàng ngân hàng khó giám sát kho n vay c a khách hàng h n ng th... nghiên c u này, tác gi s d ng ch s HHI đ đo l gi i quy t m c tiêu ng sách đa d ng hóa c a ngân hàng bao g m đa d ng hóa cho vay, đa d ng hóa ti n g i, đa d ng hóa tài s n đa d ng hóa đ a bàn M