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Les déterminants de la croissance économique au Sénégal.

( Télécharger le fichier original )
par Oumar DIOUF
Université Cheikh Anta Diop de Dakar - Master 2 en Méthodes Statistiques et Econométriques 2013
  

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Extinction Rebellion

ANNEXE 4 : TEST DE COINTEGRATION

Pesaran/Shin/Smith (2001) Bounds Test

H0: no levels relationship F = 22.193

t = -10.124

Critical Values (0.1-0.01). F-statistic. Case 3

| [I_0] [I_1] | [I_0] [I_1] | [I_0] [I_1] | [I_0] [I_1]

| L_1 L_1 | L_05 L_05 | L_025 L_025 | L_01 L_01

+ + + +

k_4 | 2.45 3.52 | 2.86 4.01 | 3.25 4.49 | 3.74 5.06
accept if F < critical value for I(0) regressors reject if F > critical value for I(1) regressors

Critical Values (0.1-0.01). t-statistic. Case 3

| [I_0] [I_1] | [I_0] [I_1] | [I_0] [I_1] | [I_0] [I_1]

| L_1 L_1 | L_05 L_05 | L_025 L_025 | L_01 L_01

+ + + +

k_4 | -2.57 -3.66 | -2.86 -3.99 | -3.13 -4.26 | -3.43 -4.60
accept if t > critical value for I(0) regressors reject if t < critical value for I(1) regressors

k: # of non-deterministic regressors in long-run relationship

ARDL regression

Model: ec

Sample: 1984

- 2013

Number of obs

=

30

Log likelihood

=

101.62521

R-squared

=

.94088214

Adj R-squared

=

.85713183

Root MSE

=

.01292877

 

D.TXCPIB

|

Coef.

Std. Err.

t

P>|t|

[95% Conf.

Interval]

 
 

+

 
 
 
 
 
 

ADJ

 

|

 
 
 
 
 
 
 

TXCPIB

|

 
 
 
 
 
 
 

L1.

|

-1.583608

.1564146

-10.12

0.000

-1.924406

-1.24281

LR

 

|

 
 
 
 
 
 
 

INF

|

.054779

.0571065

0.96

0.356

-.0696453

.1792032

 

FBCFPIB

|

.3233638

.1152641

2.81

0.016

.072225

.5745027

 

PGF

|

.5470513

.2499841

2.19

0.049

.0023826

1.09172

 

TXCOUV

|

-.0544007

.0705531

-0.77

0.456

-.2081228

.0993214

SR |

INF |

 
 
 
 
 
 

D1. |

-.3472959

.1228519

-2.83

0.015

-.6149673

-.0796246

LD. |

-.0879927

.0948526

-0.93

0.372

-.2946587

.1186734

L2D. |

-.20351

.0880118

-2.31

0.039

-.3952713

-.0117488

FBCFPIB |

 
 
 
 
 
 

D1. |

-.2841138

.2148174

-1.32

0.211

-.7521607

.1839332

LD. |

-.4225409

.2064124

-2.05

0.063

-.8722749

.027193

L2D. |

-.3082085

.1709053

-1.80

0.096

-.6805793

.0641622

PGF |

 
 
 
 
 
 

D1. |

.0574075

.3134522

0.18

0.858

-.6255461

.7403612

LD. |

.2590554

.181011

1.43

0.178

-.1353336

.6534445

TXCOUV |

 
 
 
 
 
 

D1. |

-.230772

.0978875

-2.36

0.036

-.4440505

-.0174935

LD. |

-.0336988

.0891296

-0.38

0.712

-.2278956

.1604979

L2D. |

-.1254537

.0711391

-1.76

0.103

-.2804524

.0295451

L3D. |

.0810834

.0705573

1.15

0.273

-.0726478

.2348147

_cons |

.0253874

.1220764

0.21

0.839

-.2405943

.2913692

Page 85

ANNEXE 5 : RESULTATS DE LA REGRESSION DU MODELE ARDL

Page 86

Source

 

|

SS

df MS

 

Number of obs

= 30

+

 
 
 
 

F( 17, 12)

= 11.23

Model

|

.031923631

17 .001877861

 

Prob > F

= 0.0001

Residual

|

.002005838

12 .000167153

 

R-squared

= 0.9409

+

 
 
 
 

Adj R-squared

= 0.8571

Total

|

.033929469

29 .001169982

 

Root MSE

= .01293

D,TXCPIB

|

Coef.

Std, Err. t

P>|t|

[95% Conf.

Interval]

TXCPIB

|

 
 
 
 
 

L1.

|

-1.583608

.1564146 -10.12

0.000

-1.924406

-1.24281

INF

|

.0867484

.0892418 0.97

0.350

-.1076928

.2811895

FBCFPIB

|

.5120815

.1833017 2.79

0.016

.1127015

.9114616

PGF

|

.8663146

.4215746 2.05

0.062

-.0522176

1.784847

TXCOUV

|

-.0861494

.1134583 -0.76

0.462

-.3333537

.161055

INF

|

 
 
 
 
 

D1.

|

-.3472959

.1228519 -2.83

0.015

-.6149673

-.0796246

LD.

|

-.0879927

.0948526 -0.93

0.372

-.2946587

.1186734

L2D.

|

-.20351

.0880118 -2.31

0.039

-.3952713

-.0117488

FBCFPIB

|

 
 
 
 
 

D1.

|

-.2841138

.2148174 -1.32

0.211

-.7521607

.1839332

LD.

|

-.4225409

.2064124 -2.05

0.063

-.8722749

.027193

L2D.

|

-.3082085

.1709053 -1.80

0.096

-.6805793

.0641622

PGF

|

 
 
 
 
 

D1.

|

.0574075

.3134522 0.18

0.858

-.6255461

.7403612

LD.

|

.2590554

.181011 1.43

0.178

-.1353336

.6534445

TXCOUV

|

 
 
 
 
 

D1.

|

-.230772

.0978875 -2.36

0.036

-.4440505

-.0174935

LD.

|

-.0336988

.0891296 -0.38

0.712

-.2278956

.1604979

L2. |

 

-.1254537

.0711391 -1.76

0.103

-.2804524

.0295451

L3D.

|

.0810834

.0705573 1.15

0.273

-.0726478

.2348147

_cons

|

.0253874

.1220764 0.21

0.839

-.2405943

.2913692

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

Variables: fitted values of D.TXCPIB

chi2(1) = 1.13

Prob > chi2 = 0.2874

LM test for autoregressive conditional heteroskedasticity (ARCH)

lags(p) | chi2 df Prob > chi2

+

1 | 1.171 1 0.2793

H0: no ARCH effects vs, H1: ARCH(p) disturbance

Breusch-Godfrey LM test for autocorrelation

lags(p) | chi2 df Prob > chi2

+

1 | 1.057 1 0.3039

H0: no serial correlation

Page 87

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