Trang chủ / Ngoại Hối

Hồi Quy Ols Cho Mô Hình Nghiên Cứu

Source

SS

df

MS

Model

.043320719

1

.043320719

Residual

.011104798

49

.000226629

Total

.054425517

50

.00108851

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Ước lượng mức dự trữ ngoại hối tối ưu của Việt Nam - 33

. reg cost l.cost


Number of

obs =

51

F( 1,

49) =

191.15

Prob > F

=

0.0000

R-squared

=

0.7960

Adj R-squared = 0.7918 Root MSE = .01505


cost

Coef.

Std. Err.

t

P>|t|

[95% Conf.

Interval]

cost







L1.

.9030884

.065319

13.83

0.000

.7718249

1.034352

_cons

.0100442

.0075232

1.34

0.188

-.0050742

.0251627


. estat ic


Akaike's information criterion and Bayesian information criterion


Model

Obs

ll(null)

ll(model)

df

AIC

BIC

.

51

102.1242

142.6553

2

-281.3107

-277.447

Note: N=Obs used in calculating BIC; see [R] BIC note



. reg cost l.cost l2.cost


Source

SS

df

MS

Model

.045331617

2

.022665808

Residual

.009092683

47

.000193461

Total

.0544243

49

.0011107


Number of

obs =

50

F( 2,

47) =

117.16

Prob > F

=

0.0000

R-squared

=

0.8329

Adj R-squared = 0.8258 Root MSE = .01391


cost

Coef.

Std. Err.

t

P>|t|

[95% Conf.

Interval]

cost







L1.

1.281594

.1319906

9.71

0.000

1.016063

1.547125

L2.

-.4320384

.1340024

-3.22

0.002

-.7016165

-.1624603

_cons

.0162652

.0072242

2.25

0.029

.0017321

.0307984


. estat ic


Akaike's information criterion and Bayesian information criterion


Model

Obs

ll(null)

ll(model)

df

AIC

BIC

.

50

99.62726

144.3608

3

-282.7216

-276.9855

Note: N=Obs used in calculating BIC; see [R] BIC note

. reg cost l.cost l2.cost l3.cost

Source

SS

df

MS

Model

.046889345

3

.015629782

Residual

.007534154

45

.000167426

Total

.054423499

48

.001133823

Number of obs = 49

F( 3, 45) = 93.35

Prob > F = 0.0000

R-squared = 0.8616 Adj R-squared = 0.8523 Root MSE = .01294


cost

Coef.

Std. Err.

t

P>|t|

[95% Conf.

Interval]

cost







L1.

1.458033

.1357822

10.74

0.000

1.184553

1.731512

L2.

-.9578067

.2129244

-4.50

0.000

-1.386658

-.528955

L3.

.4211508

.1381895

3.05

0.004

.1428228

.6994788

_cons

.0080295

.0072454

1.11

0.274

-.0065635

.0226225


. estat ic


Akaike's information criterion and Bayesian information criterion


Model

Obs

ll(null)

ll(model)

df

AIC

BIC

.

49

97.14011

145.5852

4

-283.1703

-275.6031

Note: N=Obs used in calculating BIC; see [R] BIC note


. reg cost l.cost l2.cost l3.cost l4.cost


Source

SS

df

MS

Model

.047165602

4

.011791401

Residual

.007246068

43

.000168513

Total

.05441167

47

.001157695

Number of obs = 48

F( 4, 43) = 69.97

Prob > F = 0.0000

R-squared = 0.8668 Adj R-squared = 0.8544 Root MSE = .01298


cost

Coef.

Std. Err.

t

P>|t|

[95% Conf.

Interval]

cost







L1.

1.537404

.1495558

10.28

0.000

1.235796

1.839012

L2.

-1.142776

.2571721

-4.44

0.000

-1.661413

-.6241395

L3.

.7018101

.2572245

2.73

0.009

.1830675

1.220553

L4.

-.1975783

.152627

-1.29

0.202

-.50538

.1102234

_cons

.0106471

.0075649

1.41

0.166

-.0046091

.0259032


. estat ic


Akaike's information criterion and Bayesian information criterion


Model

Obs

ll(null)

ll(model)

df

AIC

BIC

.

48

94.66801

143.0549

5

-276.1098

-266.7538

Note: N=Obs used in calculating BIC; see [R] BIC note

. reg cost l.cost l2.cost l3.cost l4.cost l5.cost


Source

SS

df

MS

Model

.047328224

5

.009465645

Residual

.007079462

41

.00017267

Total

.054407686

46

.001182776

Number of obs = 47

F( 5, 41) = 54.82

Prob > F = 0.0000

R-squared = 0.8699 Adj R-squared = 0.8540 Root MSE = .01314


cost

Coef.

Std. Err.

t

P>|t|

[95% Conf.

Interval]

cost







L1.

1.567168

.154394

10.15

0.000

1.255363

1.878973

L2.

-1.247718

.2815103

-4.43

0.000

-1.81624

-.6791968

L3.

.8744444

.3146184

2.78

0.008

.2390596

1.509829

L4.

-.4283708

.282122

-1.52

0.137

-.9981277

.141386

L5.

.1542249

.1579521

0.98

0.335

-.1647659

.4732157

_cons

.0082277

.0080676

1.02

0.314

-.0080652

.0245205


. estat ic


Akaike's information criterion and Bayesian information criterion


Model

Obs

ll(null)

ll(model)

df

AIC

BIC

.

47

92.20273

140.1265

6

-268.2529

-257.152

Note: N=Obs used in calculating BIC; see [R] BIC note



. dfuller cost, lags(3) drift reg


Augmented Dickey-Fuller test for unit root Number of obs = 48

Z(t) has t-distribution

Test 1% Critical 5% Critical 10% Critical Statistic Value Value Value

Z(t) -1.547 -2.416 -1.681 -1.302

p-value for Z(t) = 0.0647


D.cost

Coef.

Std. Err.

t

P>|t|

[95% Conf.

Interval]

cost







L1.

-.1011409

.0653979

-1.55

0.129

-.2330284

.0307467

LD.

.6385447

.1520228

4.20

0.000

.3319614

.9451279

L2D.

-.5042318

.1527156

-3.30

0.002

-.8122122

-.1962514

L3D.

.1975783

.152627

1.29

0.202

-.1102234

.50538

_cons

.0106471

.0075649

1.41

0.166

-.0046091

.0259032


Nguồn : Tác giả xử lý và copy từ phần mềm Stata 13.0

Phụ lục 2.6. Hồi quy OLS cho mô hình nghiên cứu



. tsset stt

Phụ lục 2.6.1. HỒI QUY OLS MÔ HÌNH NGHIÊN CỨU

time variable: stt, 1 to 52

delta: 1 unit


. reg lnres lngdp open expv fpi erv cost


Source

SS

df

MS

Model

10.0969164

6

1.68281941

Residual

1.30201976

45

.028933772

Total

11.3989362

51

.223508553

Number of obs = 52

F( 6, 45) = 58.16

Prob > F = 0.0000

R-squared = 0.8858 Adj R-squared = 0.8705 Root MSE = .1701


lnres

Coef.

Std. Err.

t

P>|t|

[95% Conf.

Interval]

lngdp

.8249641

.1032783

7.99

0.000

.616951

1.032977

open

.364676

.2299461

1.59

0.120

-.0984592

.8278111

expv

-1.704014

.5339296

-3.19

0.003

-2.779404

-.628625

fpi

1.595866

.3065724

5.21

0.000

.9783978

2.213335

erv

1.836711

.4616052

3.98

0.000

.9069907

2.766432

cost

-5.381188

.9778078

-5.50

0.000

-7.350594

-3.411782

_cons

3.658205

2.625193

1.39

0.170

-1.629206

8.945616


Nguồn : Tác giả xử lý và copy từ phần mềm Stata 13.0


Phụ lục 2.6.2. HỒI QUY OLS MÔ HÌNH NGHIÊN CỨU (LOẠI BIẾN open)


Source

SS

df

MS

Model

10.0241439

5

2.00482879

Residual

1.37479227

46

.029886788

Total

11.3989362

51

.223508553

. reg lnres lngdp expv fpi erv cost


Number of

obs =

52

F( 5,

46) =

67.08

Prob > F

=

0.0000

R-squared

=

0.8794

Adj R-squared = 0.8663 Root MSE = .17288


lnres

Coef.

Std. Err.

t

P>|t|

[95% Conf.

Interval]

lngdp

.7826921

.1014094

7.72

0.000

.5785656

.9868186

expv

-1.822864

.5372799

-3.39

0.001

-2.904352

-.7413752

fpi

1.930064

.2263035

8.53

0.000

1.474539

2.38559

erv

1.777098

.4675877

3.80

0.000

.8358932

2.718303

cost

-6.102439

.8797495

-6.94

0.000

-7.873283

-4.331595

_cons

4.985764

2.528801

1.97

0.055

-.1044481

10.07598


.


Nguồn : Tác giả xử lý và copy từ phần mềm Stata 13.0

Phụ lục 2.7. Kiểm định các khuyết tật của mô hình


Phụ lục 2.7.1. KIỂM ĐỊNH HIỆN TƯỢNG ĐA CỘNG TUYẾN


. estat vif



Variable

VIF

1/VIF

lngdp

4.49

0.222531

erv

4.40

0.227017

cost

1.41

0.709473

fpi

1.41

0.711092

expv

1.14

0.878248

Mean VIF

2.57


Nguồn : Tác giả xử lý và copy từ phần mềm Stata 13.0


Phụ lục 2.7.2. KIỂM ĐỊNH HIỆN TƯỢNG PHƯƠNG SAI THAY ĐỔI


. estat hettest


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

Variables: fitted values of lnres


chi2(1) = 0.91

Prob > chi2 = 0.3389


.


Nguồn : Tác giả xử lý và copy từ phần mềm Stata 13.0

Phụ lục 2.7.3. KIỂM ĐỊNH HIỆN TƯỢNG TỰ TƯƠNG QUAN


. estat bgodfrey, lags(1/12)


Breusch-Godfrey LM test for autocorrelation


lags(p)

chi2

df

Prob > chi2

1

10.100

1

0.0015

2

10.939

2

0.0042

3

10.992

3

0.0118

4

12.754

4

0.0125

5

13.204

5

0.0215

6

15.133

6

0.0192

7

17.323

7

0.0154

8

17.367

8

0.0265

9

17.466

9

0.0419

10

17.595

10

0.0622

11

17.919

11

0.0835

12

18.025

12

0.1149

H0: no serial correlation


. newey lnres lngdp expv fpi erv cost, lag(24)


Regression with Newey-West standard errors Number of obs = 52

maximum lag: 24 F( 5, 46) = 353.43

Prob > F = 0.0000



lnres


Coef.

Newey-West Std. Err.


t


P>|t|


[95% Conf.


Interval]

lngdp

.7826921

.1084186

7.22

0.000

.5644568

1.000927

expv

-1.822864

.1931758

-9.44

0.000

-2.211706

-1.434021

fpi

1.930064

.1339318

14.41

0.000

1.660474

2.199655

erv

1.777098

.4443071

4.00

0.000

.8827545

2.671442

cost

-6.102439

1.23278

-4.95

0.000

-8.583896

-3.620982

_cons

4.985764

2.778685

1.79

0.079

-.6074383

10.57897


.


Nguồn : Tác giả xử lý và copy từ phần mềm Stata 13.0

Phụ lục 2.8. Mức dự trữ ngoại hối tối ưu và thực tế

MỨC DỰ TRỮ NGOẠI HỐI TỐI ƯU VÀ THỰC TẾ GIAI ĐOẠN 2005 - 2017


QUÝ

DTNH THỰC TẾ (USD)

DTNH TỐI ƯU

(USD)

CHÊNH LỆCH GIỮA DTNHTT VÀ TU

Q1.2005

8,067,889,609

7,161,605,324

906,284,285

Q2.2005

8,008,941,800

7,954,471,020

54,470,780

Q3.2005

8,752,768,928

9,049,723,123

-296,954,195

Q4.2005

9,216,467,261

11,596,857,579

-2,380,390,318

Q1.2006

10,907,963,064

9,951,608,168

956,354,896

Q2.2006

11,458,391,867

11,973,958,457

-515,566,590

Q3.2006

12,068,741,898

12,289,363,880

-220,621,982

Q4.2006

13,590,986,809

14,065,629,017

-474,642,208

Q1.2007

18,533,442,260

14,610,408,170

3,923,034,090

Q2.2007

21,001,961,710

18,610,653,081

2,391,308,629

Q3.2007

22,813,103,339

22,936,606,309

-123,502,970

Q4.2007

23,747,734,370

27,214,071,200

-3,466,336,830

Q1.2008

26,743,982,118

31,147,505,540

-4,403,523,422

Q2.2008

22,559,770,745

19,100,875,335

3,458,895,410

Q3.2008

24,135,804,456

15,025,280,709

9,110,523,747

Q4.2008

24,175,912,526

19,292,842,323

4,883,070,203

Q1.2009

23,308,237,839

23,213,503,646

94,734,193

Q2.2009

20,565,930,669

22,731,103,004

-2,165,172,335

Q3.2009

19,091,125,421

22,303,289,149

-3,212,163,728

Q4.2009

16,803,158,161

16,179,324,522

623,833,639

Q1.2010

14,214,886,167

15,206,670,238

-991,784,071

Q2.2010

14,523,730,028

19,139,115,313

-4,615,385,285

Q3.2010

14,537,105,505

18,315,252,141

-3,778,146,636

Q4.2010

12,926,169,011

21,151,993,641

-8,225,824,630

Q1.2011

12,681,708,961

16,539,213,930

-3,857,504,969

Q2.2011

15,723,825,677

15,405,647,501

318,178,176

Q3.2011

15,873,716,575

14,493,991,193

1,379,725,382

Q4.2011

14,045,561,449

18,480,833,408

-4,435,271,959

Q1.2012

18,340,324,556

16,705,435,793

1,634,888,763

Q2.2012

20,623,332,502

19,506,235,098

1,117,097,404

Q3.2012

22,244,353,172

21,839,803,707

404,549,465

Q4.2012

26,112,815,991

25,964,602,369

148,213,622

Q1.2013

28,867,374,222

23,399,956,492

5,467,417,730

Q2.2013

25,296,578,364

27,460,103,324

-2,163,524,960

Q3.2013

24,858,376,566

28,268,105,729

-3,409,729,163

Q4.2013

26,287,179,896

30,408,864,553

-4,121,684,657

Q1.2014

34,175,088,881

28,042,863,055

6,132,225,826

Q2.2014

36,228,183,481

32,031,960,278

4,196,223,203

Q3.2014

37,217,799,550

31,397,684,968

5,820,114,582

Q4.2014

34,575,170,166

33,741,689,942

833,480,224

Q1.2015

37,296,744,236

32,256,970,617

5,039,773,619

DTNH THỰC TẾ

(USD)

DTNH TỐI ƯU

(USD)

CHÊNH LỆCH GIỮA

DTNHTT VÀ TU

Q2.2015

37,686,617,675

32,941,529,713

4,745,087,962

Q3.2015

31,024,749,237

33,640,616,558

-2,615,867,321

Q4.2015

28,615,884,805

35,294,747,720

-6,678,862,915

Q1.2016

32,016,963,829

32,777,233,148

-760,269,319

Q2.2016

35,415,985,640

32,096,088,305

3,319,897,335

Q3.2016

38,054,895,541

36,369,632,812

1,685,262,729

Q4.2016

36,905,580,573

37,514,749,028

-609,168,455

Q1.2017

38,232,435,679

34,769,277,384

3,463,158,295

Q2.2017

39,601,245,068

38,967,741,509

633,503,559

Q3.2017

41,775,108,127

38,196,128,528

3,578,979,599

Q4.2017

49,497,307,812

45,455,515,348

4,041,792,464

QUÝ


Nguồn : International Financial Statistics – IFS (2018) và tác giả tính toán

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