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Volatilité et accumulation du capital dans les économies subsahariennes

( Télécharger le fichier original )
par Arthur CHOPKENG AWOUNANG
Université de Yaoundé II - Nouveau Programme de Troisième Cycle Inter universitaire (NPTCI ) - Diplôme d'études approfondies (DEA ) en sciences économiques 2012
  

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Extinction Rebellion

Annexe 5 : Résultats des modèles GARCH (1,1) pour tous les indices de volatilité

ARCH family regression

Sample: 1981 - 2010, but with gaps Number of obs = 540

Distribution: Gaussian Wald chi2(2) = 9388.05

Log likelihood = -2231.773 Prob > chi2 = 0.0000

 

|

TDE | Coef.

OPG
Std. Err.

z

P>|z|

[95% Conf.

Interval]

TDE

 
 
 
 
 
 
 
 

annee

| -.1358252

.0335987

-4.04

0.000

-.2016774

-.069973

 

TDE

|

 
 
 
 
 
 
 

L1.

| .8625697

.0109956

78.45

0.000

.8410188

.8841206

 

_cons

| 284.6143

67.80582

4.20

0.000

151.7173

417.5112

ARCH

arch

|
|

 
 
 
 
 
 
 

L1. garch

|

| 1.14178

.0968774

11.79

0.000

.951904

1.331656

 

L1.

| .3763153

.0315607

11.92

0.000

.3144576

.4381731

 

_cons

| 5.921532

1.629067

3.63

0.000

2.72862

9.114445

ARCH family regression

 
 
 
 

Sample: 1981 - 2010, but with gaps

 

Number of obs =

540

Distribution: Gaussian

 
 

Wald chi2(2) =

96.66

Log likelihood = -2055.258

 
 

Prob >

chi2 =

0.0000

 

|

OPG

 
 
 
 
 

INF | Coef.

Std. Err.

z

P>|z|

[95% Conf.

Interval]

INF

 
 
 
 
 
 
 
 

annee

| -.2280001

.0321262

-7.10

0.000

-.2909663

-.1650339

 

INF

|

 
 
 
 
 
 
 

L1.

| .2336108

.037691

6.20

0.000

.1597379

.3074838

 

_cons

| 460.6296

64.08571

7.19

0.000

335.0239

586.2352

ARCH

arch

|
|

 
 
 
 
 
 
 

L1. garch

|

| .5608286

.0687763

8.15

0.000

.4260295

.6956277

 

L1.

| .5848858

.0295384

19.80

0.000

.5269916

.64278

 

_cons

| 3.764139

1.477751

2.55

0.011

.8677997

6.660478

ARCH family regression

 
 
 

Sample: 1981 - 2010, but with gaps

Number of obs

=

540

Distribution: Gaussian

Wald chi2(2)

=

114.21

Log likelihood = -1482.27

Prob > chi2

=

0.0000

 

|

CPIB | Coef.

OPG
Std. Err.

z

P>|z|

[95% Conf.

Interval]

CPIB

 
 
 
 
 
 
 
 

annee

| .0491861

.0125781

3.91

0.000

.0245334

.0738388

 

CPIB

|

 
 
 
 
 
 
 

L1.

| .3394635

.0400378

8.48

0.000

.2609909

.4179362

 

_cons

| -97.74281

25.13419

-3.89

0.000

-147.0049

-48.48071

ARCH

arch

|
|

 
 
 
 
 
 
 

L1. garch

|

| .3195382

.0340149

9.39

0.000

.2528703

.3862061

 

L1.

| .7007803

.0190067

36.87

0.000

.6635278

.7380328

 

_cons

| .1409633

.1598976

0.88

0.378

-.1724303

.4543569

ARCH family regression

 
 
 
 

Sample: 1981 - 2010, but with gaps

 

Number of obs =

270

Distribution: Gaussian

 
 

Wald chi2(2) =

1872.27

Log likelihood = -1138.185

 
 

Prob >

chi2 =

0.0000

 

|

OPG

 
 
 
 
 

TCER | Coef.

Std. Err.

z

P>|z|

[95% Conf.

Interval]

TCER

 
 
 
 
 
 
 
 

annee

| .471836

.0663061

7.12

0.000

.3418783

.6017936

 

TCER

|

 
 
 
 
 
 
 

L1.

| .7042655

.0169368

41.58

0.000

.67107

.7374611

 

_cons

| -915.8871

133.3239

-6.87

0.000

-1177.197

-654.5771

ARCH

arch

|
|

 
 
 
 
 
 
 

L1. garch

|

| 1.391145

.1202265

11.57

0.000

1.155505

1.626784

 

L1.

| .0506607

.0193407

2.62

0.009

.0127535

.0885679

 

_cons

| 18.37266

3.809408

4.82

0.000

10.90636

25.83896

Annexe 6 : résultats des tests d'autocorrélation sur les modèles

. xtserial CK ASP lnTG lnOC FDI PFI STI CPIB VTCER VPIB VCTDE VINF

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

F( 1, 17) = 28.947

Prob > F = 0.0000

. xtserial H CPIB lnTG lnOC FERT lnSTI VINF VCTDE VPIB VTCER

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

F( 1, 16) = 300.599

Prob > F = 0.0000

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