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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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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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"La première panacée d'une nation mal gouvernée est l'inflation monétaire, la seconde, c'est la guerre. Tous deux apportent une prospérité temporaire, tous deux apportent une ruine permanente. Mais tous deux sont le refuge des opportunistes politiques et économiques"   Hemingway