Các yếu tố ảnh hưởng đến tính thanh khoản của các ngân hàng thương mại cổ phần Việt Nam - 11



Wald

chi2(6)

=

34.95

corr(u_i,

X) = 0

(assumed)

Prob

> chi2

=

0.0000

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Các yếu tố ảnh hưởng đến tính thanh khoản của các ngân hàng thương mại cổ phần Việt Nam - 11



L3

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



L4

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



L4

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



L4

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



L1

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



L2

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



L3

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



L4

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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