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Ho: All panels contain unit roots Number of panels = 679

Ha: At least one panel is stationary Number of periods = 6


AR parameter: Panel-specific Asymptotics: T -> Infinity Panel means: Included

Time trend: Not included

Drift term: Not included ADF regressions: 0 lags Statistic p-value

Inverse chi-squared(1358) P 2440.3078 0.0000

Inverse normal Z -25.2995 0.0000

Inverse logit t(3399) L* -23.2152 0.0000

Modified inv. chi-squared Pm 20.7676 0.0000


P statistic requires number of panels to be finite.

Other statistics are suitable for finite or infinite number of panels.



Fisher-type unit-root test for GDP Based on augmented Dickey-Fuller tests

Ho: All panels contain unit roots Number of panels = 679

Ha: At least one panel is stationary Number of periods = 6


AR parameter: Panel-specific Asymptotics: T -> Infinity Panel means: Included

Time trend: Not included

Drift term: Not included ADF regressions: 0 lags Statistic p-value

Inverse chi-squared(1358) P 1427.5060 0.0927

Inverse normal Z -10.0740 0.0000

Inverse logit t(3399) L* -8.9247 0.0000

Modified inv. chi-squared Pm 1.3337 0.0912


P statistic requires number of panels to be finite.

Other statistics are suitable for finite or infinite number of panels.



Fisher-type unit-root test for beta Based on augmented Dickey-Fuller tests

Ho: All panels contain unit roots Number of panels = 678

Ha: At least one panel is stationary Avg. number of periods = 5.83


AR parameter: Panel-specific Asymptotics: T -> Infinity Panel means: Included

Time trend: Not included

Drift term: Not included ADF regressions: 0 lags Statistic p-value

Inverse chi-squared(1356) P 4673.1588 0.0000

Inverse normal Z -28.5176 0.0000

Inverse logit t(3364) L* -41.2925 0.0000

Modified inv. chi-squared Pm 63.6974 0.0000


P statistic requires number of panels to be finite.

Other statistics are suitable for finite or infinite number of panels.



Fisher-type unit-root test for Risk Based on augmented Dickey-Fuller tests

Ho: All panels contain unit roots Number of panels = 678

Ha: At least one panel is stationary Avg. number of periods = 5.83


AR parameter: Panel-specific Asymptotics: T -> Infinity Panel means: Included

Time trend: Not included

Drift term: Not included ADF regressions: 0 lags Statistic p-value

Inverse chi-squared(1356) P 3694.6771 0.0000

Inverse normal Z -18.5029 0.0000

Inverse logit t(3374) L* -27.8531 0.0000

Modified inv. chi-squared Pm 44.9082 0.0000


P statistic requires number of panels to be finite.

Other statistics are suitable for finite or infinite number of panels.



Fisher-type unit-root test for SR Based on augmented Dickey-Fuller tests

Ho: All panels contain unit roots Number of panels = 678

Ha: At least one panel is stationary Avg. number of periods = 5.83


AR parameter: Panel-specific Asymptotics: T -> Infinity Panel means: Included

Time trend: Not included

Drift term: Not included ADF regressions: 0 lags Statistic p-value

Inverse chi-squared(1356) P 2629.6505 0.0000

Inverse normal Z -21.6360 0.0000

Inverse logit t(3374) L* -23.0217 0.0000

Modified inv. chi-squared Pm 24.4571 0.0000


P statistic requires number of panels to be finite.

Other statistics are suitable for finite or infinite number of panels.



Fisher-type unit-root test for ILLIQ Based on augmented Dickey-Fuller tests

Ho: All panels contain unit roots Number of panels = 678

Ha: At least one panel is stationary Avg. number of periods = 5.83


AR parameter: Panel-specific Asymptotics: T -> Infinity Panel means: Included

Time trend: Not included

Drift term: Not included ADF regressions: 0 lags Statistic p-value

Inverse chi-squared(1356) P 3359.5797 0.0000

Inverse normal Z -9.0853 0.0000

Inverse logit t(3359) L* -20.0516 0.0000

Modified inv. chi-squared Pm 38.4735 0.0000


P statistic requires number of panels to be finite.

Other statistics are suitable for finite or infinite number of panels.



Fisher-type unit-root test for LM12 Based on augmented Dickey-Fuller tests

Ho: All panels contain unit roots Number of panels = 678

Ha: At least one panel is stationary Avg. number of periods = 5.83


AR parameter: Panel-specific Asymptotics: T -> Infinity Panel means: Included

Time trend: Not included

Drift term: Not included ADF regressions: 0 lags


Statistic p-value


Inverse chi-squared(1354) P 3551.3661 0.0000

Inverse normal Z -9.9328 0.0000

Inverse logit t(3319) L* -22.4074 0.0000

Modified inv. chi-squared Pm 42.2258 0.0000


P statistic requires number of panels to be finite.

Other statistics are suitable for finite or infinite number of panels.



2. Kiểm định lựa chọn phương pháp ước lượng


Breusch-Pagan / Cook-Weisberg test for heteroskedasticity Ho: Constant variance

Variables: fitted values of ILLIQ


chi2(1) = 44.01

Prob > chi2 = 0.0000

Breusch-Pagan / Cook-Weisberg test for heteroskedasticity Ho: Constant variance

Variables: fitted values of LM12

chi2(1) = 775.23

Prob > chi2 = 0.0000

Breusch and Pagan Lagrangian multiplier test for random effects

ILLIQ[MCT,t] = Xb + u[MCT] + e[MCT,t]

Estimated results:


Var sd = sqrt(Var

ILLIQ

11.17137

3.34236

e

.9965541

.9982756

u

.5755179

.7586289

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Nhân tố tác động đến tính thanh khoản của cổ phiếu niêm yết trên thị trường chứng khoán Việt Nam - 25

)



Breusch and Pagan Lagrangian multiplier test for random effects


LM12[MCT,t] = Xb + u[MCT] + e[MCT,t]


Estimated results:


Var sd = sqrt(Var

LM12

36.90356

6.07483

e

12.56068

3.544104

u

1.689307

1.299733

)



Kiểm định Hausman ILLIQ


Coefficients


(b)

FE

(B)

RE

(b-B)

Difference

sqrt(diag(V_b-V_B))

S.E.

FreeFloat

State Pcs TYPE

2

3

4

VSGR

Size LnKLGD RATE GDP

Risk SR

-.305856

-.3726164

.0667604

.0567137

.3225965

.4132013

-.0906049

.1028446

-.9364938

-1.18511

.2486162

.1312761

-.204158

-.1854926

-.0186653

.0263128

.0399402

.1678641

-.1279239

.0258197

.1145283

.2117491

-.0972208

.0267844

-.6166677

-.8060923

.1894247

.0592336

-.7401627

-.4858657

-.254297

.0345353

-.7316247

-.7634801

.0318553

.0111645

26.584

28.04689

-1.462889

1.361199

35.16469

29.554

5.610688

1.6

64.9011

66.29407

-1.392977

.8975799

-.7443141

-.911902

.1675879

.0425386

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

= 89.94

Prob>chi2 = 0.0000

(V_b-V_B is not positive definite)


Kiểm định Hausman LM12


Coefficients


(b)

FE

(B)

RE

(b-B)

Difference

sqrt(diag(V_b-V_B))

S.E.

FreeFloat

State Pcs TYPE

2

3

4

VSGR

Size LnKLGD RATE GDP

Risk SR

.4220762

-.8600593

1.282135

.2801379

-.2816066

.4312225

-.7128291

.4543007

.7335827

.5285105

.2050722

.6473038

-.116078

-.3701347

.2540568

.1487015

.3161347

.2821655

.0339692

.1373923

.450912

.2830778

.1678342

.1457183

1.564758

1.537565

.0271931

.3043893

-.3889255

-.2117035

-.177222

.1402665

-1.022576

-1.426764

.4041876

.0494113

-26.90213

-84.5433

57.64117

7.181545

-133.0993

-193.2497

60.15036

8.460689

51.9173

69.86196

-17.94465

4.668824

-2.851489

-4.105063

1.253574

.2725221

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

= 86.29

Prob>chi2 = 0.0000

(V_b-V_B is not positive definite)


3. Kiểm định đa cộng tuyến


Variable

VIF

1/VIF

GDP

5.25

0.190566

RATE

5.04

0.198250

Size

2.30

0.434538

LnKLGD

2.17

0.460255

SR

1.44

0.695704

FreeFloat

1.32

0.757250

Risk

1.23

0.810649

Pcs

1.22

0.817118

State

1.22

0.821940

VSGR

1.10

0.910226

Mean VIF

2.23


Hệ số VIF sau khi loại biến GDP


Variable

VIF

1/VIF

Size

2.29

0.436733

LnKLGD

2.17

0.460532

FreeFloat

1.32

0.757619

Risk

1.23

0.814723

Pcs

1.22

0.817519

State

1.20

0.830704

VSGR

1.09

0.914353

SR

1.08

0.928560

RATE

1.05

0.952745

Mean VIF

1.41


4. Kiểm định tự tương quan ILLIQ

Wooldridge test for autocorrelation in panel data

H0: no first-order autocorrelation F( 1, 671) = 65.560

Prob > F = 0.0000


LM12

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

F( 1, 670) = 99.543

Prob > F = 0.0000


5. Kiểm định phương sai sai số thay đổi


ILLIQ

Modified Wald test for groupwise heteroskedasticity in fixed effect regression model


H0: sigma(i)^2 = sigma^2 for all i


chi2 (676) = 3.0e+05

Prob>chi2 = 0.0000


LM12

Modified Wald test for groupwise heteroskedasticity in fixed effect regression model


H0: sigma(i)^2 = sigma^2 for all i


chi2 (675) = 2.2e+06

Prob>chi2 = 0.0000


6. Kết quả kiểm định mô hình sau khắc phục phương sai không đồng nhất với 2 phương pháp FGLS và sai số chuẩn vững cho biến phụ thuộc ILLIQ

FGLS

Cross-sectional time-series FGLS regression


Coefficients: generalized least squares Panels: heteroskedastic Correlation: no autocorrelation


Estimated

covariances

=

676

Number of obs

=

3,862

Estimated

autocorrelations

=

0

Number of groups

=

676

Estimated

coefficients

=

13

Obs per group:

min


=


1


avg

=

5.713018

max

=

6

Wald chi2(12)

=

48518.53

Prob > chi2

=

0.0000


ILLIQ

Coef.

Std. Err.

z

P>|z|

[95% Conf.

Interval]

FreeFloat

State

Pcs


TYPE KH KO TM


VSGR

size LnKLGD

RATE

Risk

SR

_cons

-.1761028

.0651542

-2.70

0.007

-.3038027

-.0484028

.2780143

.0577087

4.82

0.000

.1649073

.3911212

-2.682732

.1251439

-21.44

0.000

-2.92801

-2.437455


-.1499061


.0702227


-2.13


0.033


-.2875401


-.0122721

.4669767

.0579328

8.06

0.000

.3534304

.5805229

.4656505

.0612538

7.60

0.000

.3455953

.5857056

-1.509277

.1067997

-14.13

0.000

-1.7186

-1.299953

-.2327736

.0116269

-20.02

0.000

-.2555619

-.2099853

-.8760416

.007783

-112.56

0.000

-.891296

-.8607871

10.82147

4.071565

2.66

0.008

2.84135

18.80159

69.29304

1.433481

48.34

0.000

66.48347

72.10261

-1.453919

.2161769

-6.73

0.000

-1.877618

-1.03022

6.038824

.3276778

18.43

0.000

5.396587

6.681061


Sai số chuẩn vững


Fixed-effects (within)

regression

Number

of obs

=

3,862

Group variable: MCT


Number

of groups

=

676

R-sq:


within


=


0.5411

Obs

per

group:


min


=


1


between

=

0.9106




avg

=

5.7


overall

=

0.8525




max

=

6



F(12,675)

=

111.75

corr(u_i, Xb)

= 0.0280

Prob > F

=

0.0000


(Std. Err. adjusted for 676 clusters in MCT)



ILLIQ


Coef.

Robust Std. Err.


t P>|t|



[95% Conf.


Interval]

FreeFloat

State

Pcs


TYPE KH KO TM


VSGR

size LnKLGD

RATE

Risk

SR

_cons

-.2681394

.1411452

-1.90 0.058


-.5452759

.0089971

.3939544

.1807519

2.18 0.030


.0390509

.7488579

-1.58905

.2592527

-6.13 0.000


-2.098089

-1.080011


-.2231687


.0955838


-2.33 0.020



-.410846


-.0354914

.2691636

.090209

2.98 0.003


.0920397

.4462875

.3093153

.0943438

3.28 0.001


.1240726

.4945579

-.9809227

.1929855

-5.08 0.000


-1.359847

-.6019987

-.3753317

.0736349

-5.10 0.000


-.5199128

-.2307506

-.7973166

.0403364

-19.77 0.000


-.8765166

-.7181166

-.9164651

5.528004

-0.17 0.868


-11.77062

9.937685

68.98475

3.641777

18.94 0.000


61.83417

76.13532

-1.296813

.2400364

-5.40 0.000


-1.768121

-.8255055

7.621156

1.225611

6.22 0.000


5.214687

10.02763

sigma_u

.91489744






sigma_e

.99827556






rho

.45650155

(fraction

of variance due

to

u_i)



7. Kết quả kiểm định mô hình sau khắc phục phương sai không đồng nhất với 2 phương pháp FGLS và sai số chuẩn vững cho biến phụ thuộc LM12

FGLS


Cross-sectional time-series FGLS regression


Coefficients: generalized least squares Panels: heteroskedastic Correlation: no autocorrelation


Estimated

covariances =

675

Number of obs =

3,867

Estimated

autocorrelations =

0

Number of groups =

675

Estimated

coefficients =

13

Obs per group:



min =

1

avg =

5.728889

max =

6

Wald chi2(12) =

15552.96

Prob > chi2 =

0.0000


LM12

Coef.

Std. Err.

z

P>|z|

[95% Conf.

Interval]

FreeFloat

State Pcs


TYPE KH KO TM


VSGR

size LnKLGD RATE

Risk SR

_cons

-.9509185

.1465459

-6.49

0.000

-1.238143

-.6636939

.555532

.1306254

4.25

0.000

.2995109

.8115531

-.548436

.3070055

-1.79

0.074

-1.150156

.0532838


-.0273054


.1808488


-0.15


0.880


-.3817626


.3271518

.4672182

.1491957

3.13

0.002

.1748

.7596365

.4120609

.1543212

2.67

0.008

.1095969

.7145248

-.0112841

.2261357

-0.05

0.960

-.4545019

.4319338

-.426423

.0265349

-16.07

0.000

-.4784305

-.3744155

-1.233048

.0199231

-61.89

0.000

-1.272096

-1.193999

59.1296

9.51115

6.22

0.000

40.48809

77.77111

51.04191

3.085199

16.54

0.000

44.99503

57.08879

-2.145199

.538953

-3.98

0.000

-3.201528

-1.088871

20.30068

.7501532

27.06

0.000

18.8304

21.77095


Sai số chuẩn vững

Fixed-effects (within) regression Number of obs = 3,867 Group variable: MCT Number of groups = 675


R-sq: Obs per group:

within = 0.1364 min = 1

between = 0.6576 avg = 5.7

overall = 0.4908 max = 6

F(12,674) = 28.72

corr(u_i, Xb) = -0.4307 Prob > F = 0.0000

(Std. Err. adjusted for 675 clusters in MCT)


LM12


Coef.

Robust Std. Err.


t P>|t|



[95% Conf.


Interval]

FreeFloat

State Pcs


TYPE KH KO TM


VSGR

size LnKLGD RATE

Risk SR

_cons

.3270895

.4337509

0.75 0.451


-.5245759

1.178755

.0296492

.5026876

0.06 0.953


-.9573729

1.016671

-.3627253

.8405965

-0.43 0.666


-2.013228

1.287778


-.0973078


.4010406


-0.24 0.808



-.884747


.6901314

.2588029

.3533257

0.73 0.464


-.4349486

.9525544

.4498795

.3513792

1.28 0.201


-.2400501

1.139809

1.02592

.4684135

2.19 0.029


.1061947

1.945645

-2.033738

.2641675

-7.70 0.000


-2.552429

-1.515048

-.9187104

.0654848

-14.03 0.000


-1.047289

-.7901316

60.19603

17.67605

3.41 0.001


25.48929

94.90276

49.10434

9.240407

5.31 0.000


30.96089

67.24778

-1.298942

1.068146

-1.22 0.224


-3.396235

.7983519

36.22329

4.026001

9.00 0.000


28.31828

44.1283

sigma_u

3.2505771






sigma_e

3.5532219






rho

.45560611

(fraction

of variance due

to

u_i)


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