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Wald

chi2(6)

34.95

corr(u_i,

X) = 0

(assumed)

Prob

> chi2

0.0000

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Coef.	Std. Err.		z P>\|z\|		[95% Conf.	Interval]
CAP	.199314	.1400128		1.42 0.155		-.0751061	.4737341
NPL	.459672	.5260264		0.87 0.382		-.5713208	1.490665
ROE	.0409049	.0786984		0.52 0.603		-.1133411	.195151
TOA	.003482	.0089416		0.39 0.697		-.0140432	.0210072
GDP	-.3501687	1.293055		-0.27 0.787		-2.88451	2.184173
MIR	-1.264346	.2328949		-5.43 0.000		-1.720812	-.8078806
_cons	.5638247	.1298307		4.34 0.000		.3093612	.8182881
sigma_u	.09798406
sigma_e	.08515644
rho	.56970056	(fraction	of	variance due	to	u_i)

. hausman fe3 re3

Coefficients

(b) fe3	(B) re3	(b-B) Difference	sqrt(diag(V_b-V_B)) S.E.
CAP	.1782048	.199314	-.0211092	.0204572
NPL	.4143958	.459672	-.0452761	.0814177
ROE	.0156434	.0409049	-.0252615	.0115543
TOA	-.0000632	.003482	-.0035452	.0037519
GDP	-.2865151	-.3501687	.0636536	.119679
MIR	-1.281094	-1.264346	-.0167476	.0348707

b = consistent under Ho and Ha; obtained from xtreg B = inconsistent under Ha, efficient under Ho; obtained from xtreg

Test: Ho: difference in coefficients not systematic

chi2(6) = (b-B)'[(V_b-V_B)^(-1)](b-B)

= 6.97

Prob>chi2 = 0.3233

(V_b-V_B is not positive definite)

Phụ Lục 4. Kết quả hồi quy L4 theo Pool OLS, Fix effect, Random effect và kiểm định F-test, Hausman

. regress L4 CAP NPL ROE TOA GDP MIR

Source	SS	df	MS
Model	.907724198	6	.151287366
Residual	7.05140367	227	.031063452
Total	7.95912786	233	.034159347

Number of obs = 234

F( 6, 227) = 4.87

Prob > F = 0.0001

R-squared

=	0.1140
Adj R-squared	=	0.0906
Root MSE	=	.17625

Coef.	Std. Err.	t	P>\|t\|	[95% Conf.	Interval]
CAP	1.165061	.2537781	4.59	0.000	.6649989	1.665123
NPL	1.239809	.9601433	1.29	0.198	-.6521237	3.131742
ROE	.3604252	.1478552	2.44	0.016	.069081	.6517694
TOA	.0251285	.012298	2.04	0.042	.0008957	.0493614
GDP	.1036653	2.605874	0.04	0.968	-5.031129	5.23846
MIR	-.7097228	.4587585	-1.55	0.123	-1.613693	.194247
_cons	.2296651	.2256129	1.02	0.310	-.2148983	.6742284

. xtreg L4 CAP NPL ROE TOA GDP MIR,fe

Fixed-effects (within)

regression	Number	of obs		=	234
Group variable: BANK1				Number	of groups		=	26
R-sq: within	=	0.1401	Obs	per	group:	min	=	9
between	=	0.0329				avg	=	9.0
overall	=	0.0747				max	=	9
				F(6,202)		=		5.49
corr(u_i, Xb)	=	-0.0429		Prob > F		=		0.0000

Coef.	Std. Err.		t P>\|t\|		[95% Conf.	Interval]
CAP	.9533545	.1946556		4.90 0.000		.569537	1.337172
NPL	.6512734	.732252		0.89 0.375		-.7925645	2.095111
ROE	.1061424	.1094231		0.97 0.333		-.1096156	.3219005
TOA	.0008097	.0133396		0.06 0.952		-.025493	.0271124
GDP	.292373	1.786412		0.16 0.870		-3.230033	3.81478
MIR	-.7501403	.3239564		-2.32 0.022		-1.38891	-.1113704
_cons	.5497763	.1835265		3.00 0.003		.1879029	.9116498
sigma_u	.14299926
sigma_e	.11714662
rho	.59840565	(fraction	of	variance due	to	u_i)

F test that all u_i=0: F(25, 202) = 12.47 Prob > F = 0.0000

. xtreg L4 CAP NPL ROE TOA GDP

MIR,re
Random-effects GLS regression	Number of obs	=	234
Group variable: BANK1	Number of groups	=	26
R-sq: within = 0.1388	Obs per group: min	=	9
between = 0.0544	avg	=	9.0
overall = 0.0885	max	=	9
	Wald chi2(6)	=	34.04
corr(u_i, X) = 0 (assumed)	Prob > chi2	=	0.0000

Coef.	Std. Err.		z P>\|z\|		[95% Conf.	Interval]
CAP	.9769671	.1920973		5.09 0.000		.6004632	1.353471
NPL	.6580931	.7217232		0.91 0.362		-.7564583	2.072645
ROE	.1384669	.1079712		1.28 0.200		-.0731528	.3500866
TOA	.0068517	.0122904		0.56 0.577		-.017237	.0309403
GDP	.1274603	1.773684		0.07 0.943		-3.348896	3.603817
MIR	-.7083918	.3195162		-2.22 0.027		-1.334632	-.0821516
_cons	.4833583	.1783063		2.71 0.007		.1338843	.8328323
sigma_u	.13703493
sigma_e	.11714662
rho	.5777684	(fraction	of	variance due	to	u_i)

. hausman fe4 re4

Coefficients

(b) fe4	(B) re4	(b-B) Difference	sqrt(diag(V_b-V_B)) S.E.
CAP	.9533545	.9769671	-.0236125	.0314551
NPL	.6512734	.6580931	-.0068197	.123728
ROE	.1061424	.1384669	-.0323245	.0177662
TOA	.0008097	.0068517	-.006042	.0051857
GDP	.292373	.1274603	.1649127	.2128693
MIR	-.7501403	-.7083918	-.0417485	.0534521

b = consistent under Ho and Ha; obtained from xtreg B = inconsistent under Ha, efficient under Ho; obtained from xtreg

Test: Ho: difference in coefficients not systematic

chi2(6) = (b-B)'[(V_b-V_B)^(-1)](b-B)

= 3.70

Prob>chi2 = 0.7171

Phụ Lục 5.Kiểm định đa cộng tuyến

. collin CAP NPL ROE TOA GDP MIR

(obs=234)

Collinearity Diagnostics

SQRT R-

Variable VIF VIF Tolerance Squared

---------------------------------------------------- CAP 1.89 1.37 0.5294 0.4706

NPL 1.13 1.06 0.8860 0.1140

ROE 1.18 1.08 0.8510 0.1490

TOA 2.03 1.42 0.4932 0.5068

GDP 1.17 1.08 0.8540 0.1460

MIR 1.23 1.11 0.8162 0.1838

---------------------------------------------------- Mean VIF 1.44

Phụ Lục 6. Kiểm định tự tương quan

. xtserial L1 CAP NPL ROE TOA GDP MIR

Wooldridge test for autocorrelation in panel data H0: no first-order autocorrelation

F( 1, 25) = 18.914

Prob > F = 0.0002

. xtserial L2 CAP NPL ROE TOA GDP MIR

Wooldridge test for autocorrelation in panel data H0: no first-order autocorrelation

F( 1, 25) = 12.457

Prob > F = 0.0016

. xtserial L3 CAP NPL ROE TOA GDP MIR

Wooldridge test for autocorrelation in panel data H0: no first-order autocorrelation

F( 1, 25) = 62.055

Prob > F = 0.0000

. xtserial L4 CAP NPL ROE TOA GDP MIR

Wooldridge test for autocorrelation in panel data H0: no first-order autocorrelation

F( 1, 25) = 16.194

Prob > F = 0.0005

. xttest0

Phụ Lục 7. Kiểm định phương sai tha đổi

Breusch and Pagan Lagrangian multiplier test for random effects

L1[BANK1,t] = Xb + u[BANK1] + e[BANK1,t]

Estimated results:

Var sd = sqrt(Var)

L1 .0113308 .106446

e .0052377 .0723721

u .00433 .0658031

Test: Var(u) = 0

chibar2(01) = 169.58 Prob > chibar2 = 0.0000

. xttest0

Breusch and Pagan Lagrangian multiplier test for random effects

L2[BANK1,t] = Xb + u[BANK1] + e[BANK1,t]

Estimated results:

Var sd = sqrt(Var)

L2 .0222918 .1493044

e .0100214 .1001072

u .0063243 .0795254

Test: Var(u) = 0

chibar2(01) = 121.67 Prob > chibar2 = 0.0000

. xttest0

Breusch and Pagan Lagrangian multiplier test for random effects

L3[BANK1,t] = Xb + u[BANK1] + e[BANK1,t]

Estimated results:

Var sd = sqrt(Var)

L3 .0181084 .1345674

e .0072516 .0851564

u .0096009 .0979841

Test: Var(u) = 0

chibar2(01) = 273.40 Prob > chibar2 = 0.0000

Breusch and Pagan Lagrangian multiplier test for random effects

L4[BANK1,t] = Xb + u[BANK1] + e[BANK1,t]

Estimated results:

Var sd = sqrt(Var)

L4 .0341593 .1848225

e .0137233 .1171466

u .0187786 .1370349

Test: Var(u) = 0

chibar2(01) = 270.29 Prob > chibar2 = 0.0000

Phụ Lục 8. Kết quả hồi quy GLS

. xtgls L1 CAP NPL ROE TOA GDP MIR, panels(correlated)

Cross-sectional time-series FGLS regression

Coefficients: generalized least squares

Panels: heteroskedastic with cross-sectional correlation Correlation: no autocorrelation

Estimated

covariances	=	351	Number of obs	=	234
Estimated	autocorrelations	=	0	Number of groups	=	26
Estimated	coefficients	=	7	Time periods	=	9
				Wald chi2(6)	=	103.37
				Prob > chi2	=	0.0000

Coef.	Std. Err.	z	P>\|z\|	[95% Conf.	Interval]
CAP	-.1336323	.0899655	-1.49	0.137	-.3099614	.0426968
NPL	-1.048426	.5116941	-2.05	0.040	-2.051328	-.0455238
ROE	.085451	.0766803	1.11	0.265	-.0648396	.2357416
TOA	-.0095086	.0033038	-2.88	0.004	-.0159839	-.0030333
GDP	-3.428545	1.226006	-2.80	0.005	-5.831473	-1.025617
MIR	1.512976	.2332956	6.49	0.000	1.055725	1.970227
_cons	.4278216	.0860633	4.97	0.000	.2591406	.5965026

Estimated

covariances	=	351	Number of obs	=	234
Estimated	autocorrelations	=	0	Number of groups	=	26
Estimated	coefficients	=	7	Time periods	=	9
				Wald chi2(6)	=	59.02
				Prob > chi2	=	0.0000

Coef.	Std. Err.	z	P>\|z\|	[95% Conf.	Interval]
CAP	.2194927	.1567015	1.40	0.161	-.0876367	.5266221
NPL	-1.632101	.5313774	-3.07	0.002	-2.673581	-.5906199
ROE	.1645354	.1086949	1.51	0.130	-.0485028	.3775735
TOA	-.0131394	.0071267	-1.84	0.065	-.0271076	.0008287
GDP	-3.702348	3.488315	-1.06	0.289	-10.53932	3.134623
MIR	2.631954	.630906	4.17	0.000	1.395401	3.868508
_cons	.4145577	.2428879	1.71	0.088	-.0614938	.8906092

. xtgls L3 CAP NPL ROE TOA GDP MIR, panels(correlated)

Cross-sectional time-series FGLS regression

Coefficients: generalized least squares

Panels: heteroskedastic with cross-sectional correlation Correlation: no autocorrelation

Estimated

covariances	=	351	Number of obs	=	234
Estimated	autocorrelations	=	0	Number of groups	=	26
Estimated	coefficients	=	7	Time periods	=	9
				Wald chi2(6)	=	56.56
				Prob > chi2	=	0.0000

Coef.	Std. Err.	z	P>\|z\|	[95% Conf.	Interval]
CAP	.4457578	.1290483	3.45	0.001	.1928278	.6986878
NPL	.8880482	.4796989	1.85	0.064	-.0521443	1.828241
ROE	.1591352	.0786932	2.02	0.043	.0048994	.313371
TOA	.0146403	.0079836	1.83	0.067	-.0010073	.0302878
GDP	-.1597238	1.18727	-0.13	0.893	-2.48673	2.167282
MIR	-1.148338	.2238594	-5.13	0.000	-1.587094	-.7095816
_cons	.3724828	.1245873	2.99	0.003	.1282961	.6166695

Estimated

covariances	=	351	Number of obs	=	234
Estimated	autocorrelations	=	0	Number of groups	=	26
Estimated	coefficients	=	7	Time periods	=	9
				Wald chi2(6)	=	64.30
				Prob > chi2	=	0.0000

Coef.	Std. Err.	z	P>\|z\|	[95% Conf.	Interval]
CAP	.9821538	.1438706	6.83	0.000	.7001726	1.264135
NPL	1.029679	.6387252	1.61	0.107	-.2221991	2.281558
ROE	.2161293	.0700813	3.08	0.002	.0787725	.3534861
TOA	.0226033	.005206	4.34	0.000	.0123997	.0328069
GDP	.0167516	1.804386	0.01	0.993	-3.51978	3.553283
MIR	-.5775459	.3009248	-1.92	0.055	-1.167348	.0122559
_cons	.290608	.1354857	2.14	0.032	.025061	.5561551

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