ANNEXES
ESTIMATIONS DES MODELES
CHAPITRE 2 :
ESTIMATIONS DE LA REGLE TRADITIONNELLE DE TAYLOR
POUR LA BEAC
PERIODE 1993 :1 A 2008 :4
Long terme
Dependent Variable: TIAO Method: Least Squares
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Date: 09/30/10 Time: 11:51
Sample: 1993:1 2008:4
Included observations: 64 TIAO=C(1)+C(2)*OPG+C(3)*EICEMAC
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Coefficient
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Std. Error t-Statistic
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Prob.
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C(1)
C(2)
C(3)
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7.122491
0.005874
0.072304
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0.238819 29.82381
0.037526 0.156529
0.089728 0.805815
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0.0000
0.8761
0.4235
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R-squared
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0.011320
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Mean dependent var
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7.000516
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Adjusted R-squared
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-0.021096
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S.D. dependent var
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1.466314
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S.E. of regression
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1.481699
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Akaike info criterion
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3.669997
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Sum squared resid
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133.9214
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Schwarz criterion
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3.771195
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Log likelihood
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-114.4399
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F-statistic
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0.349219
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Durbin-Watson stat
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0.121209
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Prob(F-statistic)
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0.706639
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Court terme
Dependent Variable: TIAO1
Method: Least Squares
Date: 09/30/10 Time: 12:24
Sample(adjusted): 1993:2 2008:4
Included observations: 63 after adjusting endpoints
TIAO1=C(1)*OPG1+C(2)*EICEMAC1+C(3)*YT
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Coefficient
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Std. Error t-Statistic
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Prob.
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C(1)
C(2)
C(3)
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0.012109 -0.323498 -0.021494
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0.014723 0.822438
0.036647 -8.827363
0.026528 -0.810258
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0.4141
0.0000
0.4210
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R-squared
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0.595016
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Mean dependent var
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-0.091270
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Adjusted R-squared
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0.581516
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S.D. dependent var
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0.441671
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S.E. of regression
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0.285718
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Akaike info criterion
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0.378828
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Sum squared resid
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4.898100
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Schwarz criterion
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0.480882
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Log likelihood
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-8.933073
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F-statistic
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44.07696
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Durbin-Watson stat
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2.019975
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Prob(F-statistic)
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0.000000
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PERIODE 1999 :1 A 2008 :4
Long
terme
Dependent Variable: TIAO Method: Least Squares
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Date: 09/30/10 Time: 14:35
Sample: 1999:1 2008:4
Included observations: 40 TIAO=C(1)+C(2)*OPG+C(3)*EICEMAC
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Coefficient
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Std. Error t-Statistic
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Prob.
|
C(1)
C(2)
C(3)
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4.200843 0.010501 -0.841308
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0.582909 7.206686
0.021864 0.480262
0.247321 -3.401681
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0.0000
0.6339
0.0016
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R-squared
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0.245683
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Mean dependent var
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6.151250
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Adjusted R-squared
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0.204909
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S.D. dependent var
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0.761670
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S.E. of regression
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0.679165
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Akaike info criterion
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2.136132
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Sum squared resid
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17.06680
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Schwarz criterion
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2.262798
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Log likelihood
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-39.72265
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F-statistic
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6.025493
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Durbin-Watson stat
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0.107989
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Prob(F-statistic)
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0.005429
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TEST DE STATIONNARITE DU RESIDU (ET) ISSU DE
L'ESTIMATION DE LONG TERME
ADF Test Statistic -2.878557 1% Critical Value* -4.2242
5% Critical Value -3.5348
10% Critical Value -3.1988
*MacKinnon critical values for rejection of hypothesis of a unit
root.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(ET)
Method: Least Squares
Date: 09/30/10 Time: 14:40
Sample(adjusted): 1999:4 2008:4
Included observations: 37 after adjusting endpoints
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Variable
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Coefficient
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Std. Error t-Statistic
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Prob.
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ET(-1)
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-0.322501
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0.112036 -2.878557
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0.0071
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D(ET(-1))
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0.434122
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0.176984 2.452896
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0.0198
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D(ET(-2))
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0.304418
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0.180334 1.688082
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0.1011
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C
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0.284605
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0.146485 1.942889
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0.0609
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@TREND(1999:1)
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-0.014816
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0.006825 -2.170807
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0.0375
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R-squared
|
0.300283
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Mean dependent var
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-0.031037
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Adjusted R-squared
|
0.212818
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S.D. dependent var
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0.212073
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S.E. of regression
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0.188158
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Akaike info criterion
|
-0.377980
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Sum squared resid
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1.132911
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Schwarz criterion
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-0.160288
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Log likelihood
|
11.99263
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F-statistic
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3.433192
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Durbin-Watson stat
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1.920704
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Prob(F-statistic)
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0.019166
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Le résidu n'étant pas stationnaire, on
s'arrête ici et il n'est pas question de tester le court terme.
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