Các yếu tố ảnh hưởng đến khả năng sinh lời và chấp nhận rủi ro tại các ngân hàng thương mại cổ phần Việt Nam - 10


Trần Việt Dũng (2014), “Xác định các nhân tố tác động tới khả năng sinh lời của các NHTM Việt Nam”, Tạp chí Ngân hàng, no.16 (tháng 08/2014, trang 2-11).


Tài liệu tiếng Anh


Alessandri, P., & Nelson, B. D. (2015). Simple banking: Profitability and the yield curve. Journal of Money, Credit and Banking, 47(1), 143–175.

Altunbas, Y., Gambacorta, L., & MarquesIbanez, D. (2010). Does monetary policy affect bank risktaking? ECB Working Paper

Bikker, J. A., & Hu, H. (2002). Cyclical patterns in profits, provisioning and lending of banks and procyclicality of the New Basel Capital requirements. Banca Nazionale del Lavoro Quarterly Review, 55(221), 143–175.

Bikker, J. A., & Vervliet, T. M. (2017). Bank profitability and risktaking under low interest rates. DNB Working Paper No. 560, De Nederlandsche Bank, Amsterdam.

Bolt, W., de Haan, L., Hoeberichts, M., Van Oordt, M. R. C., & Swank, J. (2012). Bank profitability during recessions. Journal of Banking & Finance, 36(9), 2552–2564.

Borio, C., Gambacorta, L., & Hofmann, B. (2015). The influence of monetary policy on bank profitability. BIS Working Paper.

Don Hofstrand (2009). Understanding Profitability - Ag Decisions Makers: 2 (2009): C3-24.

Eissa A. Al-Homaidi, Mosab I. Tabash, Najib H. S. Farhanand Faozi A. Almaqtari(2018), Bank specific and macro-economic determinants of profitability of Indian commercial bank: A panel data approach, Journal Cogent Economics & Finance,Volume 6, 2018.

Fakhri J. Hasanov, Nigar Bayramliand Nayef Al-Musehel (2018), Bank- Specific and Macroeconomic Determinants of Bank Profitability: Evidence


from an Oil-Dependent Economy, International Journal of Financial Studies.

Genay, H., & Podjasek, R. (2014). What is the impact of a low interest rate environment on bank profitability?. Chicago Fed Letter.

James Ayodele Owoputi, (2014), Bank specific, industry specific and macroeconomic determinants of bank profitability in nigeria. European Scientific Journal September 2014 edition vol.10, No.25.

Maddaloni, A., & Peydró, J. L. (2011). Bank risktaking, securitization, supervision, and low interest rates: Evidence from the Euroarea and the United State lending standards. Review of Financial Studies, 24(6), 2121– 2165.

Mehmet Sabri Topak và Nimet Hulya Talu (2017), Bank Specific and Macroeconomic Determinants of Bank Profitability: Evidence from Turkey, International Journal of Economics and Financial, Issues ISSN: 2146-4138.

Shehzad, C. T., De Haan, J., & Scholtens, B. (2013). The relationship between size, growth and profitability of commercial banks. Applied Economics, 45(13), 1751–1765.

Susan Moraa Onuonga (2014),The Analysis of Profitability of Kenya`s Top Six Commercial Banks: Internal Factor Analysis, American International Journal of Social Science, Vol. 3, No. 5; October 2014.


PHỤ LỤC ĐỊNH LƯỢNG


Phụ lục 1: Thống kê mô tả


Variable

Obs

Mean

Std. Dev.

Min

Max

nim

160

2.821169

1.135517

.3692929

7.421874

profit

160

1.581935

2.11208

-.83456

10.9967

roa

160

.7604937

.5130707

.0111122

2.538122

roe

160

8.998523

6.09364

.0753253

26.82345

pcl

158

.0231585

.0135977

.0020391

.0881

size

160

32.33569

1.071629

30.16692

34.723

cap

160

9.083807

3.433291

4.06177

25.53888

loanta

160

.5249948

.1249096

.1910427

.7233553

nita

160

.0056089

.0043615

-.0058772

.0275189

inf

160

.0656375

.0547065

.006

.1813

gdp

160

.060775

.005196

.0525

.0678

irl

160

.0870888

.0221123

.05559

.119

irs

160

.0737855

.0318276

.04035

.1351088

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Phụ lục 2: Ma trận tương quan



nim

profit

roa

roe

pcl

size

cap

loanta

nita

inf

gdp irl irs

nim

1.0000











profit

0.1320

1.0000










roa

0.6470

0.3568

1.0000









roe

0.4076

0.5382

0.8012

1.0000








pcl

-0.0513

-0.2360

-0.2723

-0.3710

1.0000







size

-0.1072

0.7383

0.0382

0.4543

-0.1906

1.0000






cap

0.3636

-0.3127

0.2595

-0.2869

0.1727

-0.7068

1.0000





loanta

0.3287

0.3410

0.1211

0.1359

-0.1087

0.2838

-0.0320

1.0000




nita

0.0003

0.4558

0.2324

0.2879

0.0729

0.3249

-0.0623

0.0255

1.0000



inf

0.1367

-0.1518

0.4435

0.3662

-0.0796

-0.1955

0.1497

-0.3188

-0.2028

1.0000


gdp

-0.1415

0.0862

0.0684

0.1559

-0.3493

0.0595

-0.1349

0.1762

0.0932

-0.1305

1.0000

irl

0.1312

-0.2554

0.3838

0.2684

0.0245

-0.2658

0.2398

-0.4049

-0.2245

0.8561

-0.3022 1.0000

irs

0.1570

-0.2030

0.4349

0.3357

-0.0397

-0.2337

0.2002

-0.3646

-0.2333

0.9661

-0.1976 0.9506 1.0000


.


Source

SS

df

MS

Model

74.8243333

8

9.35304166

Residual

130.190114

151

.862186186

Total

205.014447

159

1.28939904

Number of obs

=

160

F( 8, 151)

=

10.85

Prob > F

=

0.0000

R-squared

=

0.3650

Adj R-squared

=

0.3313

Root MSE

=

.92854



nim

Coef.

Std. Err.

t

P>|t|

[95% Conf.

Interval]

size

.0510833

.1185617

0.43

0.667

-.1831708

.2853374

cap

.1155701

.0345175

3.35

0.001

.0473705

.1837696

loanta

3.856928

.7159899

5.39

0.000

2.442276

5.27158

nita

24.37131

19.79782

1.23

0.220

-14.7452

63.48782

inf

-19.02866

8.469571

-2.25

0.026

-35.76283

-2.294492

gdp

-40.12135

16.02321

-2.50

0.013

-71.77999

-8.462714

irl

-46.36093

18.21427

-2.55

0.012

-82.34867

-10.37319

irs

70.88276

24.56568

2.89

0.004

22.34592

119.4196

_cons

.4527397

4.249053

0.11

0.915

-7.942534

8.848014


. vif


Variable

VIF

1/VIF

irs

112.74

0.008870

inf

39.59

0.025258

irl

29.91

0.033428

size

2.98

0.335912

cap

2.59

0.386105

loanta

1.48

0.677951

nita

1.37

0.727278

gdp

1.28

0.782297

Mean VIF

23.99


.


Fixed-effects (within) regression

Number of obs

=

160

Group variable: id

Number of groups

=

20

R-sq: within

=

0.3723

Obs

per

group:

min

=

8

between

=

0.0827




avg

=

8.0

overall

=

0.1495




max

=

8




F(8,132)

=

9.78

corr(u_i, Xb)

=

-0.6358

Prob > F

=

0.0000


nim

Coef.

Std. Err.


t P>|t|


[95% Conf.

Interval]

size

.841085

.3417197


2.46 0.015


.1651297

1.51704

cap

.1318238

.0354376

3.72 0.000

.0617248

.2019228

nita

-3.510473

19.79954

-0.18 0.860

-42.67592

35.65497

loanta

5.754727

1.042886

5.52 0.000

3.691794

7.817659

gdp

-30.56994

13.61452

-2.25 0.026

-57.50081

-3.639071

irs

-15.41317

29.15961

-0.53 0.598

-73.09375

42.26741

irs2

110.6579

123.1538

0.90 0.371

-132.9525

354.2682

irl

19.70127

17.20715

1.14 0.254

-14.33616

53.73871

_cons

-28.00932

12.09922

-2.31 0.022

-51.94278

-4.075869

sigma_u

1.0528656







sigma_e

.7486767






rho

.66416868

(fraction

of

variance due

to

u_i)

F test that all u_i=0: F(19, 132) = 5.65 Prob > F = 0.0000


Fixed-effects (within)

regression

Number

of

obs

=

160

Group variable: id


Number

of

groups

=

20

R-sq: within

=

0.4647

Obs

per

group:

min

=

8

between

=

0.7693




avg

=

8.0

overall

=

0.6718




max

=

8




F(8,132)

=

14.33

corr(u_i, Xb)

=

-0.2043

Prob > F

=

0.0000


profit

Coef.

Std. Err.


t P>|t|


[95% Conf.

Interval]

size

1.929417

.4344507


4.44 0.000


1.070031

2.788804

cap

.1910795

.0450541


4.24 0.000


.1019581

.280201

nita

94.52009

25.17246


3.75 0.000


44.72648

144.3137

loanta

.1911197

1.32589


0.14 0.886


-2.431622

2.813861

gdp

5.06578

17.30904


0.29 0.770


-29.17321

39.30477

irs

10.97826

37.07253


0.30 0.768


-62.35486

84.31138

irs2

48.59718

156.5735


0.31 0.757


-261.1207

358.3151

irl

-27.51587

21.87658


-1.26 0.211


-70.7899

15.75816

_cons

-62.20841

15.38254


-4.04 0.000


-92.63658

-31.78023

sigma_u

.88152799







sigma_e

.95184193







rho

.46170404

(fraction

of

variance due

to

u_i)


F test that all u_i=0: F(19, 132) = 6.20 Prob > F = 0.0000


Fixed-effects (within) regression

Number of obs

=

160

Group variable: id

Number of groups

=

20


R-sq: within


=


0.5733


Obs


per


group:


min


=


8

between

=

0.1550




avg

=

8.0

overall

=

0.2242




max

=

8





F(8,132)


=


22.17

corr(u_i, Xb)

=

-0.8051

Prob > F

=

0.0000



roa


Coef.


Std. Err.



t P>|t|



[95% Conf.


Interval]


size


.6520611


.1374507



4.74 0.000



.3801701


.9239521

cap

.0554063

.0142541


3.89 0.000


.0272103

.0836024

nita

38.12664

7.964012


4.79 0.000


22.37304

53.88025

loanta

1.387442

.4194825


3.31 0.001


.5576642

2.21722

gdp

18.36785

5.476199


3.35 0.001


7.535385

29.20031

irs

-4.946654

11.72893


-0.42 0.674


-28.14764

18.25433

irs2

47.05503

49.53642


0.95 0.344


-50.9329

145.043

irl

17.47954

6.921268


2.53 0.013


3.78859

31.1705

_cons

-24.34704

4.866696


-5.00 0.000


-33.97385

-14.72023


sigma_u


.61913187







sigma_e

.30114187







rho

.80868274

(fraction

of

variance due

to

u_i)



F test that all u_i=0: F(19, 132) = 5.34 Prob > F = 0.0000


Fixed-effects (within)

regression

Number

of obs

=

160

Group variable: id


Number

of groups

=

20

R-sq: within

=

0.5205

Obs

per

group:

min

=

8

between

=

0.5968




avg

=

8.0

overall

=

0.4639




max

=

8




F(8,132)

=

17.91

corr(u_i, Xb)

=

-0.8333

Prob > F

=

0.0000


roe

Coef.

Std. Err.


t P>|t|


[95% Conf.

Interval]

size

6.929966

1.541395


4.50 0.000


3.880933

9.978998

cap

-.2385228

.1598482


-1.49 0.138


-.5547184

.0776728

nita

413.4238

89.3098


4.63 0.000


236.7602

590.0874

loanta

11.59051

4.704149


2.46 0.015


2.285237

20.89578

gdp

251.8214

61.41104


4.10 0.000


130.3443

373.2985

irs

-3.028304

131.5303


-0.02 0.982


-263.2082

257.1515

irs2

313.901

555.5099


0.57 0.573


-784.9525

1412.754

irl

168.3233

77.61629


2.17 0.032


14.79059

321.856

_cons

-253.0889

54.57597


-4.64 0.000


-361.0455

-145.1322

sigma_u

5.9771846







sigma_e

3.3770566







rho

.75802653

(fraction

of

variance due

to

u_i)


F test that all u_i=0: F(19, 132) = 5.28 Prob > F = 0.0000


max

=

8

F(8,130)


=

4.30

Prob > F


=

0.0001

overall = 0.1521


corr(u_i, Xb) = -0.0973


pcl

Coef.

Std. Err.


t P>|t|


[95% Conf.

Interval]

size

.000969

.0054355


0.18 0.859


-.0097845

.0117225

cap

.000697

.0005623


1.24 0.217


-.0004154

.0018094

nita

.4586366

.3153577


1.45 0.148


-.1652608

1.082534

loanta

-.0119909

.0166174


-0.72 0.472


-.0448665

.0208847

gdp

-.8576864

.2163068


-3.97 0.000


-1.285624

-.4297493

irs

.0918362

.4721237


0.19 0.846


-.8422041

1.025876

irs2

-.8669959

1.987052


-0.44 0.663


-4.798141

3.064149

irl

.0029198

.2765102


0.01 0.992


-.5441226

.5499622

_cons

.0398636

.192382


0.21 0.836


-.3407411

.4204683

sigma_u

.00646512







sigma_e

.01187155







rho

.22873881

(fraction

of

variance due

to

u_i)


F test that all u_i=0: F(19, 130) = 1.85 Prob > F = 0.0239


Phụ lục 5: Kiểm định Pooled REM



Random-effects GLS regression

Number

of

obs

=

160

Group variable: id

Number

of

groups

=

20

R-sq: within

=

0.3506

Obs

per

group:

min

=

8

between

=

0.3116




avg

=

8.0

overall

=

0.3286




max

=

8




Wald chi2(8)

=

79.24

corr(u_i, X)

=

0 (assumed)

Prob > chi2

=

0.0000


nim

Coef.

Std. Err.


z P>|z|


[95% Conf.

Interval]

size

.1758769

.1653621


1.06 0.288


-.148227

.4999807

cap

.1189482

.0335345

3.55 0.000

.0532217

.1846747

nita

.2310588

19.00558

0.01 0.990

-37.0192

37.48131

loanta

4.605336

.8767404

5.25 0.000

2.886956

6.323716

gdp

-36.89143

13.35931

-2.76 0.006

-63.07519

-10.70766

irs

-7.89864

29.21344

-0.27 0.787

-65.15593

49.35865

irs2

106.0221

123.8818

0.86 0.392

-136.7817

348.826

irl

-.4102359

15.25619

-0.03 0.979

-30.31182

29.49135

_cons

-4.188844

5.861917

-0.71 0.475

-15.67799

7.300301

sigma_u

.61271453







sigma_e

.7486767






rho

.40111625

(fraction

of

variance due

to

u_i)


.

. xttest0


Breusch and Pagan Lagrangian multiplier test for random effects


nim[id,t] = Xb + u[id] + e[id,t]


Estimated results:

Var sd = sqrt(Var)


nim 1.289399 1.135517

e .5605168 .7486767

u .3754191 .6127145


Test: Var(u) = 0

chibar2(01) = 59.99

Prob > chibar2 = 0.0000



profit


Coef.


Std. Err.



z P>|z|



[95% Conf.


Interval]


size


1.760836


.2173793



8.10 0.000



1.33478


2.186892

cap

.1914495

.0421465


4.54 0.000


.108844

.2740551

nita

92.06687

23.88163


3.86 0.000


45.25973

138.874

loanta

.4856155

1.117169


0.43 0.664


-1.703996

2.675227

gdp

2.928612

16.68772


0.18 0.861


-29.77871

35.63593

irs

9.462939

36.46984


0.26 0.795


-62.01664

80.94252

irs2

60.12931

154.6227


0.39 0.697


-242.9256

363.1842

irl

-29.79423

19.14118


-1.56 0.120


-67.31027

7.721799

_cons

-56.53571

7.702574


-7.34 0.000


-71.63248

-41.43895


sigma_u


.86234134







sigma_e

.95184193







rho

.45078596

(fraction

of

variance due

to

u_i)




.

. xttest0


Breusch and Pagan Lagrangian multiplier test for random effects


profit[id,t] = Xb + u[id] + e[id,t]


Estimated results:

Var sd = sqrt(Var)


profit 4.460883 2.11208

e .9060031 .9518419

u .7436326 .8623413


Test: Var(u) = 0

chibar2(01) = 83.15

Prob > chibar2 = 0.0000


Random-effects GLS regression

Number of obs

=

160

Group variable: id

Number of groups

=

20

R-sq: within

=

0.5300

Obs

per

group:

min

=

8

between

=

0.3737




avg

=

8.0

overall

=

0.4749




max

=

8




Wald chi2(8)

=

160.62

corr(u_i, X)

=

0 (assumed)

Prob > chi2

=

0.0000


roa

Coef.

Std. Err.


z P>|z|


[95% Conf.

Interval]

size

.176779

.0649027


2.72 0.006


.049572

.3039861

cap

.0475117

.0137908

3.45 0.001

.0204823

.0745411

nita

35.39277

7.817256

4.53 0.000

20.07123

50.71431

loanta

.9907363

.354775

2.79 0.005

.2953901

1.686082

gdp

13.56155

5.536414

2.45 0.014

2.710377

24.41272

irs

-1.767719

12.11356

-0.15 0.884

-25.50987

21.97443

irs2

51.1495

51.37891

1.00 0.319

-49.55132

151.8503

irl

5.096069

6.294904

0.81 0.418

-7.241717

17.43385

_cons

-7.573558

2.302193

-3.29 0.001

-12.08577

-3.061342

sigma_u

.22042026







sigma_e

.30114187






rho

.3488516

(fraction

of

variance due

to

u_i)


.

. xttest0


Breusch and Pagan Lagrangian multiplier test for random effects


roa[id,t] = Xb + u[id] + e[id,t]


Estimated results:

Var sd = sqrt(Var)


roa .2632416 .5130707

e .0906864 .3011419

u .0485851 .2204203


Test: Var(u) = 0

chibar2(01) = 38.13

Prob > chibar2 = 0.0000

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