Mémoire économétrie Modèle de Solow

7/24/2019 Mémoire économétrie Modèle de Solow

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S$ 5/7'100,(% PCT $$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$ A-

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3

• l; g 8M6(&8O01 )1 %('?2>,&/ )10 1''1*'0

• l" g 8M6(&8O01 )E8(?(0+/)20&,+,&/

• l A g 8M6(&8O01 )E2:01%+1 )E2*&(+(''/>2&,(%

• l- g 6'/01%+1 (* 2:01%+1 )1 ?*>&,+(>,%/2',&/

• lH g &10& )1 0&2:,>,&/ )10 +(1KK,+,1%&0

.(*' N/',K,1' 9*1 +10 8M6(&8O010 %1 0(%& 620 N,(>/10^ %(*0 6'(+/)1'(%0 ] *%1 :2&&1',1 )1 &10&0 2K,% )1

)/&1'?,%1' >2 6'/01%+1 (* %(% )E8/&/'(0+/)20&,+,&/^ )E2*&(+(''/>2&,(% 1& )1 ?*>&,+(>,%/2',&/ 2,%0, 9*1 >2

%('?2>,&/ )10 1''1*'0 1& >2 0&2:,>,&/ )10 +(1KK,+,1%&0$ U(*0 &,'1'(%0 %(0 +(%+>*0,(%0 *%1 K(,0 9*1 +10 &10&0

01'(%& '/2>,0/0 1& *%1 K(,0 9*1 &(*&10 1''1*'0 '1?1&&2%& 1% +2*01 >1 ?()O>1 10&,?/ 2,1%& /&/ +('',7/10$

! 5/0*>&2&0 2&&1%)*0 g

.2'&2%& )* ?()O>1 )1 F(>(b %(*0 %(*0 2&&1%)(%0 ] +1 9*1 >E,%N10&,001?1%& 1& >2 +'(,002%+1

)/?(7'268,9*1 2,1%& *%1 ,%K>*1%+1 0,7%,K,+2&,N1 0*' >1 .#=$ .2' 2,>>1*'0^ >2 +26,&2>,02&,(% :(*'0,O'1 2,%0, 9*1

>E,%N10&,001?1%& K/)/'2> :'*& )1 )/K1%01 %2&,(%2>1 )(,N1%& 1D6>,9*1' *%1 62'& ,?6('&2%&1 )* '/0,)* )1 F(>(b

+(?6&1 &1%* )1 >2 0&'*+&*'1 )1 >E/+(%(?,1 2?/',+2,%1$

II. 0&"1',-2-%$, )'1 )$,,"'1

4K,% )1 6(*N(,' '/2>,01' >E10&,?2&,(% )1 %(&'1 ?()O>1^ %(*0 2N(%0 '/+(>&/ )10 )(%%/10 0*' >1 0,&1 )1

>2 =2%9*1 B/)/'2>1 )1 F2,%&Z[(*,0$ C1&&1 ,%0&,&*&,(% 2?/',+2,%1 10& 1% 1KK1& >E*%1 )10 6>*0 ] ?\?1 )1 K(*'%,'

)10 )(%%/10 0*' >10 S&2&0ZY%,0 0*KK,02??1%& K,2:>10 1& )2%0 )10 9*2%&,&/0 61'?1&&2%& )1 K2,'1 )10

'/7'100,(%0 9*1 >E(% 61*& `*71' +(''1+&10$ 4K,% )1 72'2%&,' *%1 +1'&2,%1 8(?(7/%/,&/ )2%0 >10 )(%%/10^ >2

&(&2>,&/ )10 )(%%/10 *&,>,0/10 6(*' >2 '/7'100,(% 0(%& &',?10&',1>>10$ S% 1KK1&^ ,> 10& ),KK,+,>1 )E(:&1%,' )10)(%%/10 ?1%0*1>>10 0*' &(*&10 >10 N2',2:>10 /&*),/10 ] >2 K(,0$ [10 )(%%/10 0E/&1%)1%& )* 6'1?,1' &',?10&'1

;L3I 2* )1'%,1' &',?10&'1 "I;I +1 9*, %(*0 K2,& 2* &(&2> "I- (:01'N2&,(%0$

&' ()*+,-)./0/12. 3+0*4156) 7)- 72..,)- 8+6/)-

#' 9+0*4156) 76 :+2761/ ;./,+1)6+ <+6/



@

!' 9+0*4156) 7) =0 >+21--0.>) 7,?23+0*4156)

@' 9+0*4156) 7) =0 A2+?0/12. <+6/) 7) B0*1/0= A1C)

Produit intérieur brut des Etats-Unis de 1960 à 2010

Temps

1 96 3 1 96 6 1 96 9 1 97 2 1 97 5 1 97 8 1 98 1 1 98 4 1 98 7 1 99 0 1 99 3 1 99 6 1 99 9 2 00 2 2 00 5 2 00 80

2500

5000

7500

10000

12500

15000

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

PIB_EU

Population aux Etats-Unis de 1960 à 2010

Temps

1 96 3 1 96 6 1 96 9 1 97 2 1 97 5 1 97 8 1 98 1 1 98 4 1 98 7 1 99 0 1 99 3 1 99 6 1 99 9 2 00 2 2 00 5 2 00 8

180000

200000

220000

240000

260000

280000

300000

320000

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

POPULATION



J

[10 &'(,0 6'1?,1'0 7'268,9*10 +(%+1'%2%& >1 .#=^ >2 K('?2&,(% :'*&1 )1 +26,&2> K,D1^ 1& >2 +'(,002%+1

)/?(7'268,9*1 (%& &(*0 &'(,0 *%1 &'O0 K('&1 +'(,002%+1 )16*,0 >10 2%%/10 ;L3I$ U(*0 (:01'N(%0 *%1

&1%)2%+1 ] >2 82*001 &'O0 ?2'9*/1$ [2 +'(,002%+1 )1 >2 6(6*>2&,(% 61*& 0m1D6>,9*1' 62' >2 K,% )1 >2 F1+(%)1

<*1''1 ?(%),2>1 2N1+ >1 n =2:MZ=((? o$ p*2%& 2* .#= 1& ] >E,%N10&,001?1%&^ ,>0 61*N1%& 0E1D6>,9*1' 62' >2

0,&*2&,(% /+(%(?,9*1 )1 >m/6(9*1 2N1+ >10 Q'1%&1 <>(',1*010$ S% 1KK1&^ 1%&'1 ;L-H 1& ;L@H >10 62M0

)/N1>(66/0 (%& +(%%* *%1 K('&1 +'(,002%+1$ U(*0 2>>(%0 6(*' +1&&1 '2,0(% +81'+81' ] />,?,%1' +1&&1

&1%)2%+1 9*, 6(*''2,& :,2,01' >10 '/0*>&2&0$

D' 9+0*4156) 7) =E1.71>) FG: H"" +0**2+/, 06 :;<

[1 7'268,9*1 +(%+1'%2%& >1 FG. HII 10& :,1% ),KK/'1%& )10 &'(,0 6'/+/)1%&0$ U(*0 (:01'N(%0 )1*D

6/',()10 :,1% )/K,%,10$ W10 2%%/10 ;L3I 2*D 1%N,'(%0 )1 >E2%%/1 ;LJ; >m,%),+1 2 1* *%1 K('&1 &1%)2%+1 ] >2

:2,001$ .*,0 )1 >E2%%/1 ;LJ" 2*D 2%%/10 "III^ ,> +'(_& 6'(7'100,N1?1%&$ [10 HII 7'2%)10 0(+,/&/0 +(&/10 0*'

Investissement aux Etats-Unis de 1960 à 2010

Temps

1 96 3 19 66 19 69 1 97 2 1 975 1 97 8 19 81 1 98 4 1 987 1 99 0 1 99 3 19 96 1 999 2 00 2 2 00 5 20 08

0

100

200

300

400

500

600

700

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00INVESTISSEMENT

Ev olution de l'indice S&P500 rapporté au PIB de 1960 à 2010

Temps

1 96 3 1 96 6 1 96 9 1 97 2 1 97 5 1 97 8 1 98 1 1 98 4 1 98 7 1 99 0 1 99 3 1 99 6 1 99 9 2 00 2 2 00 5 2 00 8

20

40

60

80

100

120

140

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

SP500



L

>10 :(*'010 2?/',+2,%10 0(%& ] %(*N12*D K>(',002%&10$ [m1D1?6>1 )* +(%0&'*+&1*' 2*&(?(:,>1 C8'M0>1' 10&

2001q '16'/01%&2&,K )1 >2 0,&*2&,(% )10 2%%/10 ;LJI$ [10 0(+,/&/0 /&2,1%& 1% K2,>>,&1 ] +1&&1 6/',()1^ 1& 7'i+1 ]

*% +>,?2& )1 +(%+*''1%+1 1& ] )1 %(*N1>>10 ?/&8()10 )m('72%,02&,(% 1>>1 2 '/*00, 2 )(*:>/ 02 6'()*+&,N,&/ )*

&'2N2,>$ W1 %(*N12*D ,%N10&,001*'0 (%& ,%N10&, 2* 01,% )1 >m1%&'16',01 1& 61&,& ] 61&,& >1 FG. HII 2 +'*$

H' 9+0*4156) 7) =0 7,*).-) I,7,+0=) ). 7,I).-) .0/12.0=)

[1 7'268,9*1 )10 )/61%010 1% )/K1%01 %2&,(%2>1 2 *%1 /N(>*&,(% 6>*0 +(?6>1D1$ U(*0 '1?2'9*(%0

9*1 61%)2%& >2 6'1?,O'1 )/+1%%,1 >10 )/61%010 (% 6>*&a& /&/ +(%0&2%&10$ P2,0 ] 62'&,' )10 2%%/10 ;L@"^ >2

+(*':1 +'(_& )1 K2r(% 1D6(%1%&,1>>1$ U(*0 6(*N(%0 /N(9*1' >1 +(%&1D&1 )1 <*1''1 B'(,)1 +(??1 '2,0(% (*

1%+('1 >10 ),KK/'1%&10 7*1''10 )1 >m/6(9*1^ +1>>1 )* R,\Z U2? 1& >2 7*1''1 )* <(>K1$ S% 1KK1&^ >10 S&2&0ZY%,0

(%& )s '1%K('+1' >1*'0 )/61%010 1% 2'?1?1%& 6(*' K2,'1 K2+1 ] &(*&10 >10 2&&29*10 ?,>,&2,'10 )1 >m/6(9*1$ [16,+ ] 62'&,' )1 "II; )(%%1 0*,&1 2*D 2&&29*10 &1''(',0&10 )* ;; 016&1?:'1 2N1+ >E,%N20,(% )1 >E4K782%,0&2%^

0*,N,1 )1 +1>>1 )1 >E#'2j$

<' &.0=J-) 6.1K0+1,) 7)- 72..,)-

C1&&1 01+&,(% 10& +(%02+'/1 >2 )10+',6&,(% )10 '/0*>&2&0 (:&1%*0 7'i+1 ] >2 6'(+/)*'1 '-%./"%/0 1

0(*0 F4F$ S>>1 61'?1& )E(:&1%,' >10 ?(?1%&0 )1 +829*1 0/',1$ [10 0/',10 '16'/01%&/10 ,+, 0(%& &(*&10

0&2&,(%%2,'10$ U(*0 2N(%0 *%1 N2>1*' ?2%9*2%&1 +1 9*, '2?O%1 >1 %(?:'1 )1 %(0 (:01'N2&,(%0 ] "IA$

#' &.0=J-) 7)->+1*/1K) 76 :;< ). 71II,+).>) *+)?1L+)

Variable : d_PIB_EU

Moments

N 203 Somme des poids 203

Moyenne 0.01645318 Somme des observations 3.33999464

Dépenses en défense nationale de 1960 à 2010

Temps

19 63 1 96 6 1 96 9 1 97 2 1 97 5 1 97 8 1 98 1 1 98 4 1 98 7 1 99 0 1 99 3 1 99 6 1 99 9 2 00 2 2 00 5 2 00 8

0

20

40

60

80

100

120

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

DGI



;I

Moments

Ecart-type 0.00968895 Variance 0.00009388

Skewness 0.35483156 Kurtosis 2.4990803

Somme des carrés noncorrigée

0.07391641 Somme des carréscorrigée

0.0189629

Coeff Variation 58.8880145 Std Error Mean 0.00068003

!' &.0=J-) 7)->+1*/1K) 7) =0 *2*6=0/12. ). 71II,+).>) *+)?1L+)

Variable : d_POP

Moments



Ecart-type 0.00053223 Variance 2.8327E-7

Skewness 0.8716372 Kurtosis 0.61313418

Somme des carrés non

corrigée

0.00154323 Somme des carrés

corrigée

0.00005722


@' &.0=J-) 7)->+1*/1K) 7) =E1.71>) FG: H"" ). 71II,+).>) *+)?1L+)

Variable : d_SP500

Moments


Moyenne -0.0013556 Somme des observations -0.2751948


Skewness -0.8929976 Kurtosis 3.16699157



;;

Moments



0.79507087

Coeff Variation -4627.8907 Std Error Mean 0.00440331

D' &.0=J-) 7)->+1*/1K) 7) =0 7,*).-) ). 7,I).-) .0/12.0=) ). 71II,+).>)

*+)?1L+)

Variable : d_DGI

Moments







1.42759973


H' &.0=J-) 7)->+1*/1K) 7) =E1.71>) FG: H"" ). 71II,+).>) *+)?1L+)

Variable : d_FBCF

Moments







0.09224599




;"

<>(:2>1?1%& >10 0&2&,0&,9*10 *%,N2',/10 )1 +829*1 0/',1 1% ),KK/'1%+1 6'1?,O'1 )(%%1%& )10

?(M1%%10 6'(+810 1& )10 /+2'&0 t&M610 &'O0 6'(+810 )1 I$ C1>2 6'(*N1 9*1 %(0 0/',10 0(%& :,1% 0&2&,(%%2,'10

1& )(%+ ,%&/7'/10 ] >E(')'1 ;$ [2 01*>1 N2>1*' 9*, ?(%&'1 )1 7'2%)10 ),062',&/0 10& +1>>1 )* +(1KK,+,1%& )1

N2',2&,(% 9*, 01 +2>+*>1 +(??1 0*,& g

C1 +(1KK,+,1%& ?10*'1 >2 ),061'0,(% '1>2&,N1 62' '266('& ] >2 ?(M1%%1$ #> 10& &'O0 />1N/ 6(*' >10

N2',2:>10 FG. HII 2,%0, 9*1 >2 K('?2&,(% :'*&1 )1 +26,&2> K,D1 1& >E,%N10&,001?1%& 1% 2'?1?1%&$ F(,& ^ >10

N2',2:>10 9*, 0(%& >1 6>*0 0(*?,010 ] )10 K>*+&*2&,(%0 2>/2&(,'10$

B' M0/+1>) 7)- >2++,=0/12.-

Coefficients de corrélation de Pearson, N = 203Proba > |r| sous H0: Rho=0

d_PIB_EU d_POP d_SP500 d_DGI d_FBCF

d_PIB_EU1.00000 -0.11637

0.0982

0.02219

0.7534

0.16319

0.0200

0.72884

<.0001

d_POP-0.11637

0.0982

1.00000 0.04246

0.5475

-0.13649

0.0522

0.00703

0.9207

d_SP5000.02219

0.7534

0.04246

0.5475

1.00000 -0.08917

0.2058

0.10053

0.1536

d_DGI0.16319

0.0200

-0.13649

0.0522

-0.08917

0.2058

1.00000 0.29434

<.0001

d_FBCF0.72884

<.0001

0.00703

0.9207

0.10053

0.1536

0.29434

<.0001

1.00000



;A

[2 ?2&',+1 )10 +(''/>2&,(%0 ?(%&'1 9*1 >10 N2',2:>10 0&2&,(%%2,'10 0(%& 61* +(''/>/10 1%&'1 1>>10$

C1+, 61*& 02%0 )(*&1 0E1D6>,9*1' 62' >E2:01%+1 )1 &1%)2%+1 )2%0 >10 0/',10 )* K2,& )1 >2 0&2&,(%%2',&/^ )1 +1

K2,& 1>>10 01?:>1%& 9*20,?1%& ,%)/61%)2%&10 >10 *%10 )10 2*&'10$ U(*0 6(*N(%0 )/0('?2,0 %(*0 +(%02+'1' ]

>E10&,?2&,(% )1 %(&'1 ?()O>1$ P2,0 2N2%& )E2'',N1' ] +1&&1 /&261 %(*0 )/&2,>>1'(%0 )2%0 >2 01+&,(% 0*,N2%&1

>E1%01?:>1 )10 ?/&8()10 *&,>,0/10 2K,% )1 72'2%&,' >2 N2>,),&/ )1 >E10&,?2&,(% 62' >10 PCT$

III. !"-3$)'1 '- -'1-1 /-%4%1"1

&' N)-/- 7) -/0/12..0+1/, )/ -/0/12..0+1-0/12. 7)- -,+1)-

4K,% )1 6(*N(,' 266>,9*1' >2 ?/&8()1 )10 ?(,%)'10 +2''/0 ] %(&'1 ?()O>1 %(*0 2N(%0 )2%0 *%

6'1?,1' &1?60 6'(+/)1' 2*D &10&0 )1 W,+j1M B*>>1' 1& )2%0 +1'&2,%0 +20 ] +1>*, )* W,+j1M B*>>1' 4*7?1%&/$ C1

&10& +(%0,0&1 )2%0 *% 6'1?,1' &1?60 ] 62'&,' )E*%1 06/+,K,+2&,(% 7>(:2>^ 0(,& *% ?()O>1 2N1+ +(%0&2%&1 1&

&1%)2%+1 1& *%1 ),KK/'1%+1 6'1?,O'1 6(*' >1 W,+j1M B*>>1' 0,?6>1 1& >2 ?\?1 06/+,K,+2&,(% 2N1+ )10 '1&2')0

0*66>/?1%&2,'10 6(*' >1 W,+j1M B*>>1' 2*7?1%&/$ [10 06/+,K,+2&,(%0 6(00,:>10 6(*' >1 W,+j1M B*>>1' 0,?6>10

0(%& >10 0*,N2%&10 g

[1 +8(,D 1%&'1 +10 &'(,0 06/+,K,+2&,(%0 01 K2,& 1% K(%+&,(% )1 >2 0,7%,K,+2&,N,&/ )1 >2 &1%)2%+1 1& )1 >2 +(%0&2%&1

62' '266('& ] >2 .ZN2>*1 c0, >2 &Z0&2& 10& ,%K/',1*'1 2* 01*,> )1 Hu (% '1`1&&1 >E8M6(&8O01 %*>>1 )1 %(%

0,7%,K,+2&,N,&/d$ S% 7/%/'2>^ +E10& >2 )1*D,O?1 06/+,K,+2&,(% 9*, 10& '1&1%*1 c?()O>1 2N1+ +(%0&2%&1 02%0

&1%)2%+1d$ #> K2*& 1%0*,&1 '/+*6/'1' >10 '/0,)*0 )1 >2 '/7'100,(% 1& >10 &10&1' 6(*' 02N(,' 0, +1 0(%& )10 :'*,&0

:>2%+0 c)2%0 +1 +20 >10 &Z0&2& )(,N1%& \&'1 0*6/',1*'10 2* 01*,> )1 Hu 6(*' 6(*N(,' +(%+>*'1 >E2:01%+1

)E2*&(+(''/>2&,(% )10 '/0,)*0d$ WO0 >('0 9*E,> M 2 )1 >E2*&(+(''/>2&,(% )2%0 >10 '/0,)*0^ ,> K2*& *&,>,01' >1 &10& )*

W,+j1M B*>>1' 4*7?1%&/ 2K,% )1 >10 :>2%+8,'^ 1% ,%&/7'2%& 2* K*' 1& ] ?10*'1 )10 '1&2')0$ Y%1 K(,0 >10 '/0,)*0

:>2%+8,0 9*1 +1 0(,& )2%0 *% &10& WB 0,?6>1 (* *% &10& 4WB^ ,> K2*& +(?62'1' >2 0&Z0&2& +(1KK,+,1%& ! )1 >2

N2',2:>1 1% ),KK/'1%+1 6'1?,O'1 ] >2 &2:>1 )1 W,+j1MZB*>>1' (* ] >2 &2:>1 )1 P2+v,%%(% 9*, 10& :12*+(*6 6>*0

6'/+,01$ F, >2 &Z0&2& (:01'N/1 10& ,%K/',1*'1 2* 01*,> +',&,9*1 (% 1% )/)*,& 9*1 >1 ?()O>1 10& 0&2&,(%%2,'1$ T%

&10&1 1%0*,&1 1% ),KK/'1%+1 )1*D,O?1 6(*' +(%K,'?1' +1 '/0*>&2&$ F, >2 0/',1 10& 0&2&,(%%2,'1 1% ),KK/'1%+1

)1*D,O?1^ (% 1% )/)*,& 9*1 >2 N2',2:>1 10& ,%&/7'/1 ] >E(')'1 ;$

U(*0 2N(%0 &10&/ >E1%01?:>1 )1 %(0 N2',2:>10 9*E1>>10 0(,1%& 1D6>,+2&,N10 (* 1D6>,9*/1^ 1& 2N(%0

2:(*&, 2* ?\?1 +(%0&2& 6(*' +82+*%1 )E1%&'1 1>>10$ Q(*&10 >10 N2',2:>10 0(%& ,%&/7'/10 ] >E(')'1 ;^ +E10& Z]Z



;-

),'1 9*E,> K2*& ),KK/'1%+,1' *%1 K(,0 >2 0/',1 6(*' >2 '1%)'1 0&2&,(%%2,'1$ cCK 2%%1D1 +()10 +(??1%&/0 6(*' >2

0&2&,(%%2',02&,(% )10 0/',10$

<' N)-/ 7) >21./,3+0/12.

[1 &10& )1 +(,%&/7'2&,(% 10& &(*& +(??1 >10 &10&0 )1 0&2&,(%%2',&/^ *% 6'/Z'19*,0 6(*' 266>,9*1' >2?/&8()1 )10 PCT 0*' >10 N2',2:>10 +(%0,)/'/10$ [1 &10& )ES%7>1 1& <'2%71' +(%0,0&1 ] '/7'1001' >10 N2',2:>10

1D6>,+2&,N10 :'*&10 0*' >2 N2',2:>1 1D6>,9*/1 :'*&1 1& '/+*6/'1' >1 '/0,)* 2K,% )1 &10&1' 02 0&2&,(%%2',&/$ [1

&10& 0E1KK1+&*1 0(,& 2N1+ *% W,+j1MZB*>>1' 0,?6>1 (* *% W,+j1M B*>>1' 2*7?1%&/ ?2,0 *%,9*1?1%& 2N1+ >2

06/+,K,+2&,(% ;^ 0(,& *% ?()O>1 02%0 +(%0&2%&1 %, &1%)2%+1$ F1*>1?1%& +(%&'2,'1?1%&^ 2*D &10&0 )1 W,+j1M

B*>>1'^ (% %1 +(?62'1 620 >1 +(1KK,+,1%& ] >2 &2:>1 )1 W,+j1MZB*>>1' ?2,0 ] +1>>1 )ES%7>1Zk(($ [2 'O7>1 )1

)/+,0,(% '10&1 >2 ?\?1 1& >1 6'(+100*0 +(%K,'?2&(,'1 2*00,$ C161%)2%&^ )2%0 >1 +2)'1 )1 +1 &10& 0, >1

+(1KK,+,1%& ! 10& 0&2&,(%%2,'1 ,> M 2 6'/01%+1 )1 +(,%&/7'2&,(%^ +1>2 0,7%,K,1 9*E,> 1D,0&1 ] >2 K(,0 )2%0 >1

?()O>1 *%1 '1>2&,(% )1 +(*'& &1'?1 1& *%1 '1>2&,(% )1 >(%7 &1'?1 1%&'1 >10 ),KK/'1%&10 N2',2:>10$ .(*'

'1?/),1' ] +1 6'(:>O?1 ,> K2*& )(%+ K2,'1 *%1 10&,?2&,(% )E*% ?()O>1 ] +(''1+&,(% )E1''1*'$ W2%0 >1 +20

+(%&'2,'1^ 0(,& >E2:01%+1 )1 +(,%&/7'2&,(% ,> K2*& 6'(+/)1' ] *%1 10&,?2&,(% )* ?()O>1 1% ),KK/'1%+1

6'1?,O'1$

U(*0 2N(%0 6'(+/)/ ] +1 &10& 2N1+ >10 N2>1*'0 :'*&10 1% >(7 1& %(*0 0(??10 62'N1%*10 ] >2

+(%+>*0,(% )E*%1 2:01%+1 )1 +(,%&/7'2&,(%$cCK$ 2%%1D1 +()10 +(??1%&/0 +(,%&/7'2&,(%d$ W1 +1 K2,& %(*0

2N(%0 6'(+/)/ ] >E10&,?2&,(% )1 %(&'1 ?()O>1 1% ),KK/'1%+1 6'1?,O'1 1& 2N(%0 (:&1%* >10 '/0*>&2&0 9*1 %(*0

1D6(01'(%0 1& +(??1%&1'(%0 )2%0 >2 01+&,(% 0*,N2%&1$

IV. 51-%#2-%$, )/ #$)64'

&' (,-6=/0/- 7) =E)-/1?0/12. *0+ =)- MBO

C(?6&1 &1%* )10 &10&0 '/2>,0/0^ %(*0 2N(%0 (:&1%* >1 ?()O>1 0*,N2%& g

!!"!! ! !! !!!!"!! ! !!!!"#$!! ! !!!

!"!! ! !!!!"#!! ! !!

U(*0 2N(%0 (:&1%*0 >10 '/0*>&2&0 0*,N2%&0 +(%+1'%2%& >E10&,?2&,(% 62' >2 ?/&8()1 )10 ?(,%)'10 +2''/0

('),%2,'10 6(*' >10 +(1KK,+,1%&0 )E10&,?2&,(%$

Valeurs estimées des paramètres

Variable DDL Valeur estiméedes paramètres

Erreurtype

Valeurdu test t

Pr > |t|

Intercept 1 0.01774 0.00242 7.32 <.0001

d_POP 1 -2.37945 0.87327 -2.72 0.0070



;H



Erreurtype

Valeurdu test t

Pr > |t|

d_SP500 1 -0.00866 0.00743 -1.17 0.2448

d_DGI 1 -0.00960 0.00583 -1.65 0.1008

d_FBCF 1 0.34455 0.02274 15.15 <.0001

<' N)-/- 7) =0 -13.1I1>0/1K1/, 7)- *0+0?L/+)-

#' N)-/ 7) =0 -13.1I1>0/1K1/, 7)- *0+0?L/+)-

4K,% )1 )/?(%&'1' >2 61'&,%1%+1 )1 %(&'1 ?()O>1 %(*0 &10&(%0 >2 0,7%,K,+2&,N,&/ )10 62'2?O&'10 ] >E2,)1 )1 >2

.ZR2>*1$

123*045$($ 6

!! ! ! ! !

!!! ! ! !

! [2 'O7>1 )1 )/+,0,(% 10& >2 0*,N2%&1 g

F, >2 .ZR2>*1 10& ,%K/',1*'1 2* 01*,> )1 Hu (% '1`1&&1 >E8M6(&8O01 %*>>1^ )(%+ >2 N2',2:>1 10& 0,7%,K,+2&,N1$F, >2 .ZR2>*1 10& 0*6/',1*'1 2* 01*,> )1 Hu (% '1`1&&1 >E8M6(&8O01 %*>>1^ )(%+ >2 N2',2:>1 %E10& 620

0,7%,K,+2&,N1$

W2%0 >1 +20 6'/01%& >10 .ZR2>*1 )10 +(1KK,+,1%&0 !! @ !! 1& ! '16'/01%&2%& '1061+&,N1?1%& >2 6(6*>2&,(%^

>2 K('?2&,(% :'*&1 )1 +26,&2> K,D1 2,%0, 9*1 >2 +(%0&2%&1 0(%& >10 &'(,0 62'2?O&'10 0,7%,K,+2&,K0 )E26'O0 >2

?/&8()1 )1 &10& /%(%+/1 6'/+/)1??1%&$ C1>2 ,?6>,9*1 9*1 >10 )1*D 62'2?O&'10 '10&2%&0^ >E,%),+1 FG. HII

'266('&/ 2* .#= 2,%0, 9*1 >10 )/61%010 K/)/'2>10 1% )/K1%01 %2&,(%2>1 %1 >1 0(%& 620^ (' +1 0(%& >10 )1*D

N2',2:>10 9*, (%& /&/ 2`(*&/10 2* ?()O>1 6(*' 1D6>,9*1' >1 '/0,)* )1 F(>(b$ U(*0 2>>(%0 )(%+ 6'(+/)1' 2*

&10& )1 0,7%,K,+2&,N,&/ )1 B,081' 7>(:2>$

!' N)-/ 7) -13.1I1>0/1K1/, 3=280= 7)- *0+0?L/+)-

123*045$($ 6

!! ! !! ! !! ! !! ! !! ! !

!!! !! ! ! !

F(,& F * >2 0&2&,0&,9*1 )1 &10& g



;3

A g %(?:'1 )1 N2',2:>10 1D6>,+2&,N10w -

7 g %(?:'1 )E(:01'N2&,(%0 w"IA

?B

g +(1KK,+,1%& )1 )/&1'?,%2&,(%$

Root MSE 0.00653 R carré 0.5542

Moyenne dépendante 0.01645 R car. ajust. 0.5452

Coeff Var 39.71228

733+%8/0%*- -'9#"%:'( 6

Bxw;^H3L$ ;IZAy LH ^@ cN2>1*' &2:*>/1 )* v8,Z)1*D 2* 01*,> Hu 1& ;LJ )17'/0 )1 >,:1'&/d

4,%0,^ %(*0 6(*N(%0 1% )/)*,'1 9*1 >1 ?()O>1 %E10& 620 7>(:2>1?1%& 0,7%,K,+2&,K$ .2' 2,>>1*'0 %(*0

6(*N(%0 +(%0&2&1' 9*1 >1 5" %1 )/62001 620 >2 :2''1 )10 @Iu^ 0(,& >2 N2>1*' )* 5

" 6(*' *%1 10&,?2&,(%

+(''1+&1 %(*0 6(*N(%0 1% )/)*,'1 9*E,> ?2%9*1 +1'&2,%1?1%& )10 N2',2:>10 1D6>,+2&,N10 )2%0 >1 ?()O>1$ #>

K2*& &(*& )1 ?\?1 2N2%& )1 01 >2%+1' )2%0 *%1 ,%&1'6'/&2&,(%^ N/',K,1' 9*1 &(*&10 >10 +(%),&,(%0 %/+1002,'10

] >2 N2>,),&/ )1 >2 '/7'100,(% 62' >10 PCT 2,1%& :,1% /&/ '1?6>,10$

B' N)-/- 7)- 4J*2/4L-)- 7) K0=171/, 7) =0 ?,/427) 7)- MBO

#' N)-/ 7) P2+?0=1/, 7)- )++)6+-

Tests de normalité

Test Statistique p-Value

Shapiro-Wilk W 0.961029 Pr < W <0.0001

Kolmogorov-Smirnov D 0.084178 Pr > D <0.0100

Cramer-von Mises W-Sq 0.393055 Pr > W-Sq <0.0050

Anderson-Darling A-Sq 2.193296 Pr > A-Sq <0.0050

#+,^ 9*1> 9*1 0(,& >1 &10& )E2`*0&1?1%& ] >2 >(, %('?2>1 '1&1%*1^ >10 .ZR2>*1 0(%& &(*&10 ,%K/',1*'10 2*

01*,> )1 Hu$ U(*0 6(*N(%0 2>('0 1% )/)*,'1 9*1 >10 1''1*'0 0(%& %('?2>10$ W1 +1 K2,&^ >2 6'1?,O'1 8M6(&8O01



;@

)10 PCT N/',K,/1^ +1 9*, 61'?1& 6(*' >E,%0&2%& )1 N2>,)1' >10 '/0*>&2&0 6'/+/)1%&0 %(&2??1%& +1>*, )* &10&

)1 0,7%,K,+2&,N,&/ 7>(:2>1 )1 B,081'$

!' N)-/ 7E42?2->,70-/1>1/, 7) Q41/)

S&2%& )(%%/ 9*1 >2 6'1?,O'1 8M6(&8O01 )1 >2 ?/&8()1 )10 ?(,%)'10 +2''/0 ('),%2,'10 10& N/',K,/1$U(*0 &10&(%0 >2 )1*D,O?1 9*, '16(01 0*' >E8(?(0+/)20&,+,&/ )10 1''1*'0$ S% '/2>,02%& >1 &10& 0(*0 F4F^ %(*0

(:&1%(%0 >1 '/0*>&2& 0*,N2%& g

Variable dépendante : d_PIB_EU

Test d'indication du Premieret du Second

DDL Khi-2 Pr > Khi-2

14 12.59 0.5589

F(*0 >E8M6(&8O01 %*>>1 >2 0&2&,0&,9*1 )1 &10& 0*,& *%1 >(, )* v8,Z)1*D^ ?2,0 >2 'O7>1 )1 )/+,0,(%

1?6>(M/1 ,+, 10& >2 .Z N2>*1$ [10 '/0*>&2&0 )* &10& )E8/&/'(0+/)20&,+,&/ )1 V8,&1 ?1&&1%& 1% /N,)1%+1

>E8(?(7/%/,&/ )10 &1'?10 )E1''1*'0$ U(*0 (:01'N(%0 9*1 >2 .$ N2>*1 10& )1 I$HHJLz I$IH^ 2>('0 (%

%1 '1`1&&1 620 lI$ W(%+ >E8M6(&8O01 )E8(?(0+/)20&,+,&/ )1 >2 N2',2%+1 10& N/',K,/1$ U(*0 6200(%0 )(%+ 2* &10& )E2*&(+(''/>2&,(%^ >1 &10& )1 W*':,%ZV2&0(% 10& 266'(6',/ ] %(&'1 ?()O>1

+2' ,> %1 +(%&,1%& 2*+*%1 N2',2:>1 2*&('/7'100,N1$

@' N)-/ 7) =E08-).>) 7E06/2>2++,=0/12.

#> M 2 6'/01%+1 )E2*&(+(''/>2&,(% )2%0 *% ?()O>1 )/K,%, +(??1 0*,& g

!! ! ! ! ! !! ! !! >('09*1 !! ! !!!!! ! !!

! [1 &10& )1 W*':,%ZV2&0(% 61'?1& 1% >E(++*''1%+1 )1 &10&1' >E2*&(+(''/>2&,(% ] >E(')'1 ;$ .(*' >10

)17'/0 6>*0 />1N/0 %(*0 K1'(%0 2661> 2* &10& )1 ='1*0+8Z<()K'1M$

Variable dépendante : d_PIB_EU

Durbin-Watson D 1.885

Nombre d'observations 203

Autocorrélation de 1er ordre 0.051

123*045$($ 6

!! ! ! ! !

!!! ! ! !



;J

;5<+( &( &#8%$%*- &' 0($0 &( ='">%-?@/0$*- 6

W2%0 %(&'1 +20^ )E26'O0 >2 &2:>1 )1 W*':,%ZV2&0(%

• ); w ;^@A

• )" w ;^J;

• - t )"w"^;L

• - t );w "^"@

WE26'O0 >1 &10& 1KK1+&*/ 0(*0 F4F >2 0&2&,0&,9*1 )1 WVw ;$JJH^ (% 2 2>('0 CBD'EDBF [2 0&2&,09*1 01 0,&*1

)2%0 >2 q(%1 )1 %(% '1`1& )1 >E8M6(&8O01 %*>>1$ #> M 2 )(%+ )1 >E2*&(+(''/>2&,(% ] >E(')'1 ; )2%0 >10 '/0,)*0$

.200(%0 2>('0 2* &10& )1 ='1*0+8Z<()K'1M 2K,% )1 )/+1>1' >2 6'/01%+1 )E2*&'10 )17'/0 0*6/',1*'0

)E2*&(+(''/>2&,(%$

! [1 &10& )1 ='1*0+8Z<()K'1M

[1 &10& )1 ='1*0+8Z<()K'1M 10& *% &10& )* ?*>&,6>,+2&1*' )1 [27'2%71 9*, 61'?1& +(%&'2,'1?1%& 2* &10& )1

W*':,%ZV2&0(% )1 '1+81'+81' >10 '1>2&,(%0 1%&'1 >10 1''1*'0 !! 0ABCDED

U(*0 0*66(0(%0 9*1 >1 &1'?1 )E1''1*' !! )* ?()O>1 )1 '/7'100,(% 0,?6>1 0*,& *% 6'(+100*0 2*&('/7'100,K

)E(')'1 6 cTf !!

10& *% :'*,& :>2%+d g

!! ! !!!!!! !!!!!!! !!!!!!!!! ! !!

123*045$($ 6

!! ! !! ! !! ! ! ! !! ! !

!!! !! ! ! !

Test de corrélation en sériede Godfrey

Alternatif LM Pr > LM

! ! !

51`1& )1

lI

" - t )" - t ); )" ); -I

51`1& )1

lI

! ! !

! ! !

U(% '1`1& )1 lI

{(%1

)E,%+1'&,&*)1

{(%1

)E,%+1'&,&*)1



;L

Test de corrélation en sériede Godfrey

Alternatif LM Pr > LM

AR(1) 0.5511 0.4579

AR(2) 8.1836 0.0167

AR(3) 13.9035 0.0030

AR(4) 17.9326 0.0013

U(*0 +(?62'(%0 >10 .ZR2>*1 2* 01*,> )1 Hu 1& 01*> >1 6'1?,1' '1&2') %(*0 61'?1& )1 '1`1&1'

>E8M6(&8O01 %*>>1 )E2:01%+1 )E2*&(+(''/>2&,(%$ U(*0 0(??10 )(%+ 1% 6'/01%+1 )E2*&(+(''/>2&,(% 2*D (')'10"^ A 1& -$ C1 9*, 1D6>,9*1 )/0('?2,0 >2 %/+100,&/ )E266>,9*1' *%1 +(''1+&,(% 6(*' >10 10&,?2&1*'0 PCT

+(%01'N1%& >1*'0 6'(6',/&/0 9*, 0(%& >10 0*,N2%&10 g

- S0&,?2&1*'0 >,%/2,'10

- S0&,?2&1*'0 02%0 :,2,0

- S0&,?2&1*'0 )1 N2',2%+1 ?,%,?2>1

4*&'1?1%& ),&^ ,>0 )(,N1%& +(%01'N1' >1*' 2661>>2&,(% )E10&,?2&1*'0 FGHI 56,7& 8(%,9' :%)(9(7,; 07&(29&$'<=

! 4%2>M01 )1 >2 %2&*'1 )1 >E2*&(+(''/>2&,(%

Durbin-Watson D 1.885

Pr < DW 0.1784

Pr > DW 0.8216

Nombre d'observations 203

Autocorrélation de 1er ordre 0.051

[2 0&2&,0&,9*1 .'yWV 61'?1& )1 &10&1' >2 6'/01%+1 )E2*&(+(''/>2&,(% 6(0,&,N1 2>('0 9*1 >2 0&2&,0&,9*1

.'zWV 61'?1& )1 &10&1' >2 6'/01%+1 )E2*&(+(''/>2&,(% %/72&,N1$ G@HIJKLG@GM )(%+ (% %1 '1`1&&1 620

>E8M6(&8O01 %*>>1^ 62' +(%0/9*1%& >1 ?()O>1 %E10& 620 +2'2+&/',0/ 62' >2 6'/01%+1 )E2*&(+(''/>2&,(% 6(0,&,N1$

U(*0 2N(%0 1%0*,&1 I^J";3zI^IH (% '1`1&&1 >E8M6(&8O01 %*>>1 1& >10 1''1*'0 )* ?()O>1 )1 '/7'100,(% 0(%&

+2'2+&/',0/10 62' >2 6'/01%+1 )E2*&(+(''/>2&,(% %/72&,N1$

#> K2*& )/0('?2,0 +('',71' >10 1''1*'0 2K,% )1 6(*N(,' '1061+&1' >10 8M6(&8O010 )1 >2 ?/&8()1 )10

?(,%)'10 +2''/0 ('),%2,'10 1% >10 '1%)2%& '(:*0&10 2*D 6'(:>O?10 )E2*&(+(''/>2&,(%$ .(*' +1^ %(*0



"I

*&,>,01'(%0 >2 +(''1+&,(% )1 U1b1MZV10&^ 9*, 1>>1 +('',71 ] >2 K(,0 >E2*&(+(''/>2&,(% 1& /N1%&*1>>1?1%&

>E8/&/'(0+/)20&,+,&/$

! C(''1+&,(% )1 U1b1MZV10&

[10 '/0*>&2&0 )1 >2 %(*N1>>1 '/7'100,(% K,7*'1%& )2%0 >2 +(>(%%1 )1 )'(,&1 )* &2:>12* 0*,N2%& g


Variable DDL Valeurestimée

desparamètres

Erreurtype

Valeurdu

test t

Pr >|t|

Cohérent avecl'hétéroscédasticité

Erreurtype

Valeurdu test

t

Pr > |t|

Intercept 1 0.01774 0.00242 7.32 <.0001 0.00244 7.27 <.0001

d_POP 1 -2.37945 0.87327 -2.72 0.0070 0.88789 -2.68 0.0080

d_SP500 1 -0.00866 0.00743 -1.17 0.2448 0.00898 -0.96 0.3358

d_DGI 1 -0.00960 0.00583 -1.65 0.1008 0.00824 -1.17 0.2450

d_FBCF 1 0.34455 0.02274 15.15 <.0001 0.02949 11.69 <.0001

WE26'O0 >10 '/0*>&2&0 (:&1%*0 0(*0 F4F >10 +(%+>*0,(%0 &,'/10 >('0 )1 >2 6'1?,O'1 '/7'100,(% )1?1*'1%&,%+82%7/10$ S% 1KK1&^ >10 /+2'&0Z&M610 0(%& 6>*0 />1N/0 9*E2*62'2N2%& 1& 2*+*%1 N2>1*' %(% 0,7%,K,+2&,N1 2N2%&

>2 +(''1+&,(% %1 >E10& )1N1%*1 26'O0$ U(*0 6(*N(%0 )(%+ +(%+>*'1 9*1 >1 ?()O>1 '1061+&1 >10 8M6(&8O010

)10 ?(,%)'10 +2''/0 ('),%2,'10^ +161%)2%& 6(*' 2?/>,('1' 0(% 6(*N(,' 1D6>,+2&,K ,> +(%N,1%)'2,& )E2`(*&1' )10

N2',2:>10 1D6>,+2&,N10 2* ?()O>1$

D' N)-/ 7) *+,-).>) 26 7E08-).>) 7) ?6=/1>2=1.,0+1/,

U(*0 &10&(%0 >2 ?*>&,+(>,%/2',&/ 2K,% )1 N/',K,1' )E*%1 62'& 0, >10 +(%),&,(%0 )1 N2>,),&/ )1 >2 ?/&8()1 )10

PCT 0(%& :,1% '1?6>,10 1& )E2*&'1 62'& 62'+1 9*E1>>1 2 6>*0,1*'0 1KK1&0$ W10 1KK1&00*' >10 N2',2%+10 1&

+(N2',2%+10 )10 +(1KK,+,1%&0 PCT ?2,0 /72>1?1%& 0*' >2 01%0,:,>,&/ )10 +(1KK,+,1%&0 PCT 0*' >10 N2',2&,(%0

)* %(?:'1 )E(:01'N2&,(%0$ U(*0 *&,>,01'(%0 ,+, >1 +',&O'1 R#B ̂ 0(,& >E,%K>2&,(% )1 >2 N2',2%+1$

! ;5<+( &( &#8%$%*- 6

S% 6'2&,9*1 6(*' *% Qw;II g

- F, R#B y ;I 620 )1 6'(:>O?1 )1 ?*>&,+(>,%/2',&/

- F, R#B z;I (% 2 *% 6'(:>O?1 )1 ?*>&,+(>,%/2',&/



";



Erreurtype

Valeurdu test t

Pr > |t| Inflationde variance

Intercept 1 0.01774 0.00242 7.32 <.0001 0

d_POP 1 -2.37945 0.87327 -2.72 0.0070 1.02213

d_SP500 1 -0.00866 0.00743 -1.17 0.2448 1.02682

d_DGI 1 -0.00960 0.00583 -1.65 0.1008 1.13476

d_FBCF 1 0.34455 0.02274 15.15 <.0001 1.11701

U(*0 ),06(0(%0 )1 "II N2>1*'0 %(&'1 01*,> +',&,9*1 %1 0E/>ON1 )(%+ 620 ] ;I ?2,0 ] "I$ #+,^ >1 R#B

)E2*+*%1 N2',2:>1 %1 )/62001 ;I 1%+('1 ?(,%0 "I$ U(*0 1% )/)*,0(%0 9*E,> %EM 620 )1 ?*>&,+(>,%/2',&/ )2%0

>1 ?()O>1$

H' N)-/ 7) -/081=1/, 7)- >2)II1>1)./-

[E(:`1+&,K )1 +1 &10& 10& >E/N2>*2&,(% )1 >2 '(:*0&1001 )* ?()O>1 10&,?/$ S% 1KK1&^ ,> 61*& \&'1 0(*?,0

] )10 +82%71?1%&0 0&'*+&*'1>0 )2%0 >2 '1>2&,(% 1%&'1 >2 N2',2:>1 1D6>,9*/1 1& >10 N2',2:>10 1D6>,+2&,N10$ 4K,%

)1 )/&1'?,%1' 0, >1 ?()O>1 10&,?/ 10& 0&2:>1 (* %(%^ %(*0 2*'(%0 '1+(*'0 1* &10& )1 0&2:,>,&/ )1 C8(b$

[2 0&2&,0&,9*1 )1 &10& 0*,& *%1 >(, )1 B,081'$ F, >2 0&2&,0&,9*1 +2>+*>/1 10& 0*6/',1*'1 ] >2 0&2&,0&,9*1 &2:*>/1^

0(,& !<"N<ON/0 L !#"PON/0 (% '1`1&&1 >E8M6(&8O01 %*>>1 )1 0&2:,>,&/ )10 +(1KK,+,1%&0$ W2%0 +1 +20 )1 K,7*'1^ %(*0

6(*N(%0 )/)*,'1 )1 >E2:01%+1 )1 +82%71?1%& 0&'*+&*'1>$ W2%0 >1 +20 +(%&'2,'1^ 0(,& !<"N<ON/0 D !#"PON/0 (% %1

'1`1&&1 620 >E8M6(&8O01 %*>>1 )1 0&2:,>,&/ )10 +(1KK,+,1%&0$ #> M 2 )(%+ 6'/01%+1 )E*% +82%71?1%& 0&'*+&*'1>$

Test de changement de structure

Test Point de rupture DDL Num. DDL Res. Valeur F Pr > F

Chow 102 5 193 8.48 <.0001

[2 N2>1*' &2:*>/1 )1 >2 >(, )1 B,081' Bcj|;^ QZ"cj|;d (f j 10& >1 %(?:'1 )1 N2',2:>10 8('0 +(%0&2%&1^ Q >1

%(?:'1 )E(:01'N2&,(%0$ wz BcH^;LAdw "^";H

!<"N<ON/0w J^-Jz !#"PON/0 w"^";H



""

T% '1`1&&1 >E8M6(&8O01 %*>>1 )1 0&2:,>,&/ )10 +(1KK,+,1%&0 1& %(*0 6(*N(%0 )/)*,'1 )1 >E2:01%+1 )1

+82%71?1%& 0&'*+&*'1> )2%0 >1 ?()O>1 10&,?/$

.78 .,-'&9&"-2-%$, )'1 &"1/4-2-14 >2 0*,&1 )1 >2 '/7'100,(%^ %(*0 2N(%0 +

V. :,,';'

&' 9+0*4156)- 7)- 72..,)- 8+6/)- -6+ (&NFxxxxC(??2%)10 7'268,9*1 ,%N10&,001?1%&xxxx

C4[SUW45 ;L3IgI; -

4[[ "I;IgI-

T.SU W4Q4 }Cg~Y01'0~B2•?2~W(+*?1%&0~4&1>,1' )m/+(%(?/&',1~<'268,9*10~B=CB$D>0}

W4Q4cBT5P4Qw€[F^T5<wCT[YPUFd #%N10&,001?1%&

0?6>

<54.lcFQk[Sw[#US^TRS5[4kw[#US^lS4WS5w}#%N10&,001?1%& 2*D S&2&0ZY%,0 )1 ;L3I ] "I;I}^l[4=S[wmQ1?60m^j1Mw*6>d ;

‚ #URSFQ#FFSPSUQ

xxxxC(??2%)10 7'268,9*1 .(6*>2&,(%xxxx

C4[SUW45 ;L3IgI; -4[[ "I;IgI-

T.SU W4Q4 }Cg~Y01'0~B2•?2~W(+*?1%&0~4&1>,1' )m/+(%(?/&',1~<'268,9*10~.T.$D>0}

W4Q4cBT5P4Qw€[F^T5<wCT[YPUFd .(6*>2&,(%

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<' &.0=J-) 6.1K0+1,) 7)- 72..,)- -/0/12..01+)-****Création d'une table constituée des différences premières***; *** Création d'une bibliothèque ***; libname sauve "C:\Users\Faïma\Documents\Atelier d'économétrie" ;run ;****importation des données brutes***; PROC IMPORT OUT= sauve.donneesbrDATAFILE ="C:\Users\Faïma\Documents\Atelier d'économétrie\Données_brutes.xls" DBMS=xls

REPLACE;GETNAMES=YES;

****Création des variables: différences****;

data sauve.donneesbr2;set sauve.donneesbr;l_PIB_EU=log(PIB_EU);d_PIB_EU=dif(l_PIB_EU);l_FBCF=log(FBCF);d_FBCF=dif(l_FBCF);l_DGI=log(DGI);d_DGI=dif(l_DGI);l_POP=log(POP);d_POP=dif(l_POP);l_SP500=log(SP500);d_SP500=dif(l_SP500);run;

***Analyse univariée des variables stationnaire¨***; PROC UNIVARIATE DATA = sauve.donneesbr2; /*UNIVARIE*/ VAR d_PIB_EU d_POP d_SP500 d_DGI d_FBCF;RUN; QUIT;*****CORRELATION entre les variables*****; PROC CORR DATA = sauve.donneesbr2; /*CORRELATION*/ var d_PIB_EU d_POP d_SP500 d_DGI d_FBCF;RUN; QUIT;

B' N)-/- F/0/12..0+1/, 7)- K0+108=)-



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#' F/0/12..0+1/, :;<

*** Création d'une bibliothèque ***; libname sauve "C:\Users\Faïma\Documents\Atelier d'économétrie" ;run ;****Importation des données sur le PIB****;

filename PIB_EU "C:\Users\Faïma\Documents\Atelier d'économétrie\GDP envolume.txt" ;data PIB_EU ;infile PIB_EU dlm = '09'x dsd missover firstobs = 2;input PIB_EU ;run;****Création des variables: différences, retards et tendance****; data PIB_EU;set PIB_EU;l_GDP=log(PIB_EU);d_GDP=dif(l_GDP);lag1_GDP=lag(l_GDP);lag1_d_GDP= lag(d_GDP);

lag2_d_GDP= lag2(d_GDP);lag3_d_GDP= lag3(d_GDP);trend=_n_;run;****Test de Dickey Fuller simple*****;

proc reg data=PIB_EU ;model d_GDP = lag1_GDP trend;output out=sauve.resPIB r=residus_DF3;run ; quit;*Test de bruit blanc sur les résidus*;

proc arima data = sauve.resPIB;identify var = residus_DF3;run; quit;

** Les résidus sont autocorrélés dans ce cas pas de bruit blanc, nous passonsalors au test ADF******Test ADF avec constante et trend(cf modele complet)***;

proc reg data=PIB_EU ;model d_GDP = trend lag1_GDP lag1_d_GDP;output out=sauve.resPIB r=residus_ADF3;run ; quit;***Test ADF avec constante(cf modele 2) méthode ascendante avec 1 retard***;

proc reg data=PIB_EU ;model d_GDP = lag1_GDP lag1_d_GDP;output out=sauve.resPIB r=residus_ADF2;run ; quit;***Test du bruit blanc****;

proc arima data = sauve.resPIB;identify var = residus_ADF2;run; quit;*** Les résidus sont toujours autocorrélés, nous ajoutons un retard afin de lesblanchir*******Test ADF avec constante(cf modele 2) méthode ascendante avec 2 retards***;

proc reg data=PIB_EU ;model d_GDP = lag1_GDP lag1_d_GDP lag2_d_GDP;output out=sauve.resPIB r=residus_ADF2_2;run ; quit;***Test du bruit blanc****;

proc arima data = sauve.resPIB;



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identify var = residus_ADF2_2;run; quit;*** Le test du bruit blanc nous permet rejeter H0: les résidus sont autocoréléscar laP-value est supérieure au seuil de 5%******Création des différences deuxièmes****;

data PIB_EU ; set PIB_EU ;d2_GDP = dif(d_GDP);lag1_d2_GDP= lag(d2_GDP);lag2_d2_GDP= lag2(d2_GDP);lag3_d2_GDP= lag3(d2_GDP);trend=_n_;run;***Vérification de la stationnarité avec la différence deuxième********Test de Dickey Fuller simple diff 2eme *****;

proc reg data=PIB_EU ;model d2_GDP = lag1_d_GDP trend;output out= sauve.resPIB r=residus_DDF3;run ; quit;

***Test du bruit blanc****; proc arima data = sauve.resPIB;identify var = residus_DDF3;run; quit;***D'après le test les résidus sont un bruit blanc********On a bruit blanc**********Comparaison des T-stats aux seuils critiques de la table d'ADF: -9,75<-2,88HO:non statio, H1: sattio: ici on rejette H0 donc la sérieen diff 2eme est statio=> notre série est intégrée à l'odre 1!!!!

!' F/0/12..0+1/, FG:H""

*** Création d'une bibliothèque ***; libname sauve "C:\Users\Faïma\Documents\Atelier d'économétrie" ;run ;****Importation des données sur le S&P500****; filename SP_EU "C:\Users\Faïma\Documents\Atelier d'économétrie\Indice_S&P500.txt" ;data SP_EU ;infile SP_EU dlm = '09'x dsd missover firstobs = 2;input SP_EU ;run;****Création des variables: différences, retards et tendance****; data SP_EU;set SP_EU;l_SP=log(SP_EU);d_SP=dif(l_SP);lag1_SP=lag(l_SP);lag1_d_SP= lag(d_SP);lag2_d_SP= lag2(d_SP);lag3_d_SP= lag3(d_SP);trend=_n_;run;****Test de Dickey Fuller simple avec constante et tendance*****;

proc reg data=SP_EU ;model d_SP = lag1_SP trend;output out=sauve.resSP r=residus_DF3;



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run ; quit;****Test de Dickey Fuller simple avec constante*****;

proc reg data=SP_EU ;model d_SP = lag1_SP;output out=sauve.resSP r=residus_DF2;run ; quit;

*Test de bruit blanc sur les résidus*; proc arima data = sauve.resSP;identify var = residus_DF2;run; quit;**Les résidus sont autocorrélés donc on a pas de bruit blanc, on passe alorsau test ADF en ajoutant des retards****Test ADF avec constante et trend(cf modele complet)***;

proc reg data=SP_EU ;model d_SP = trend lag1_SP lag1_d_SP;output out=sauve.resSP r=residus_ADF3;run ; quit;*** La tendance n'est pas significative******Test ADF modèle avec constante***;

proc reg data=SP_EU ;model d_SP = lag1_SP lag1_d_SP;output out=sauve.resSP r=residus_ADF2;run ; quit;*Test de bruit blanc sur les résidus*;

proc arima data = sauve.resSP;identify var = residus_ADF2;run; quit;***0.8835>0.05 les résidus ne sont pas autocorrélés on a un bruit blanc mais lelag n'est pas significatif*; ****Passage en différence deuxième*******Création des différences deuxièmes****; data PIB_EU ; set PIB_EU ;d2_SP = dif(d_SP);lag1_d2_SP= lag(d2_SP);lag2_d2_SP= lag2(d2_SP);lag3_d2_SP= lag3(d2_SP);trend=_n_;****Test de Dickey Fuller simple modèle avec constante et trend*****;

proc reg data=SP_EU ;model d2_SP = lag1_d_SP trend;output out=sauve.resSP r=residus_DDF3;run ; quit;****Test de Dickey Fuller simple modèle avec constante*****;

proc reg data=SP_EU ;model d2_SP = lag1_d_SP;output out=sauve.resSP r=residus_DDF2;run ; quit;*Le trend n'est pas significatif on passe alors au modèle avec constante**Test de bruit blanc sur les résidus*;

proc arima data = sauve.resSP;identify var = residus_DDF2;run; quit;***Le test de White sur les résidus montre qu'ils ne sont pas autocorrélés, ilsn'est pas utilede les blanchir en ajoutant avec le test ADF. On a un bruit blanc, d'après lesrésultats du modèle 2



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série est stationnaire car -9.93<-2.88 (ou -3.367 seuil calculé à partir de latable de MacKinnon)***Ainsi notre série est stationnaire et intégrée à l'odre 1***

@' F/0/12..0+1/, A<BA

*** Création d'une bibliothèque ***; libname sauve "C:\Users\Faïma\Documents\Atelier d'économétrie" ;run ;****Importation des données sur le PIB****; filename INV_EU "C:\Users\Faïma\Documents\Atelier d'économétrie\FBCF envolume.txt" ;data INV_EU ;infile INV_EU dlm = '09'x dsd missover firstobs = 2;input INV_EU ;run;****Création des variables: différences, retards et tendance****; data INV_EU;

set INV_EU;l_FBCF=log(INV_EU);d_FBCF=dif(l_FBCF);lag1_FBCF=lag(l_FBCF);lag1_d_FBCF= lag(d_FBCF);lag2_d_FBCF= lag2(d_FBCF);lag3_d_FBCF= lag3(d_FBCF);trend=_n_;run;****Test de Dickey Fuller simple*****;

proc reg data=INV_EU ;model d_FBCF = lag1_FBCF trend;output out=sauve.res r=residus_DF3;

run ; quit;*Le trend est significatif on accepte HO, et on a une spécification de type 3 etdonc on teste les résisdus afin de voir si c'est un bb **Test de bruit blanc sur les résidus*;

proc arima data = sauve.res;identify var = residus_DF3;run; quit;*** Le résidus sont autocc, ce n'sst pas un bb on passe au modèle ADF***

****Test ADF******** Test du modèle 3*******Test ADF avec constante et trend(cf modele complet)***;

proc reg data=INV_EU ;

model d_FBCF = trend lag1_FBCF lag1_d_FBCF;output out=sauve.res r=residus_ADF3;run ; quit;*** On enlève le trend qui n'est pas significatif****;

proc reg data=INV_EU ;model d_FBCF = lag1_FBCF lag1_d_FBCF;output out=sauve.res r=residus_ADF2;run ; quit;***La constante est significative le modèle 2 est adéquat***; *Test de bruit blanc sur les résidus*;

proc arima data = sauve.res;identify var = residus_ADF2;



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run; quit;*** On ne rejette pas H0 les résidus ne sont plus autocc , c'est un bruitblanc******-2,1>-2?88 on accpete HO et la série est snon stattionnaire et au moinsintégrée à l'odre 1****** Différence 2eme****;

data INV_EU ; set INV_EU ;d2_FBCF = dif(d_FBCF);lag1_d2_FBCF= lag(d2_FBCF);lag2_d2_FBCF= lag2(d2_FBCF);lag3_d2_FBCF= lag3(d2_FBCF);trend=_n_;run;****Test de Dickey Fuller simple diff 2eme *****;

proc reg data=INV_EU ;model d2_FBCF = lag1_d_FBCF trend;output out= sauve.res r=residus_DDF;run ; quit;**** Le trend est significatif***;

proc arima data = sauve.res;identify var = residus_DDF;run; quit;*** On ne rejette pas H0 les résidus ne sont pas autocc c'est un bruit blanc***; ***-8.56<-3.43 on rejette HO la série en diff 2eme est statio donc la série estintégrée à l'ordre 1*****

D' F/0/12..0+1/, R9;

*** Création d'une bibliothèque ***; libname sauve "C:\Users\Faïma\Documents\Atelier d'économétrie" ;run ;

****Importation des données sur la défense nationale DGI****; filename DGI_EU "C:\Users\Faïma\Documents\Atelier d'économétrie\DGI envolume.txt" ;data DGI_EU ;infile DGI_EU dlm = '09'x dsd missover firstobs = 2;input DGI_EU ;run;****Création des variables: différences, retards et tendance****; data DGI_EU;set DGI_EU;l_DGI=log(DGI_EU);d_DGI=dif(l_DGI);lag1_DGI=lag(l_DGI);

lag1_d_DGI= lag(d_DGI);lag2_d_DGI= lag2(d_DGI);lag3_d_DGI= lag3(d_DGI);trend=_n_;run;****Test de Dickey Fuller simple*****;

proc reg data=DGI_EU ;model d_DGI = lag1_DGI trend;output out=sauve.resDGI r=residus_DF3;run ; quit;**Le modèle retenu est la spécification 3 car ici la tendance est significative.



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Testons les résidus de cette régression afin de déterminer si ce sont des bruitsblancs****Test de bruit blanc sur les résidus*;

proc arima data = sauve.resDGI;identify var = residus_DF3;run; quit;

*** Les résidus sont autocorrélés, on passe alors au test ADF afin de lesblanchir***; ***Test ADF avec constante et tendance**;

proc reg data=DGI_EU ;model d_DGI = trend lag1_DGI lag1_d_DGI;output out=sauve.resDGI r=residus_ADF3;run ; quit;*** Ici la tendance n'est pas significative on pass à la spécification 2******Test ADF avec constante et tendance**;

proc reg data=DGI_EU ;model d_DGI = lag1_DGI lag1_d_DGI;output out=sauve.resDGI r=residus_ADF3_1;run ; quit;

***Test de bruit blanc sur les résidus*; proc arima data = sauve.resDGI;identify var = residus_ADF3_1;run; quit;***Les résidus ne sont pas blanchis, on ajoute un retard****** Test ADF sur modèle avec constante et deux retards***;

proc reg data=DGI_EU ;model d_DGI = lag1_DGI lag1_d_DGI lag2_d_DGI;output out=sauve.resDGI r=residus_ADF3_2;run ; quit;***Test de bruit blanc sur les résidus*;

proc arima data = sauve.resDGI;identify var = residus_ADF3_2;run; quit;*** Test ADF sur modèle avec constante et trois retards***;

proc reg data=DGI_EU ;model d_DGI = lag1_DGI lag1_d_DGI lag2_d_DGI lag3_d_DGI;output out=sauve.resDGI r=residus_ADF3_3;run ; quit;****Test de bruit blanc sur les résidus*;

proc arima data = sauve.resDGI;identify var = residus_ADF3_3;run; quit;** Le 3e retard n'est pas significatif nous retiendrons alors la spécificationprécédenteavec 2 retards puisqu'il ne blanchit pas les résidus d'après le test du bruitblanc***

***Passage en différence Deuxième*****Création des différences deuxièmes****; data DGI_EU ; set DGI_EU ;d2_DGI = dif(d_DGI);lag1_d2_DGI= lag(d2_DGI);lag2_d2_DGI= lag2(d2_DGI);lag3_d2_DGI= lag3(d2_DGI);trend=_n_;run;



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****Test de Dickey Fuller simple en différence 2eme modèle avec constante ettendance*****;

proc reg data=DGI_EU ;model d2_DGI = lag1_d_DGI trend;output out= sauve.resDGI r=residus_DDF3;run ; quit;

*** La tendance n'est pas significative on passe alors à la spécification 2***; proc reg data=DGI_EU ;model d2_DGI = lag1_d_DGI ;output out= sauve.resDGI r=residus_DDF2;run ; quit;*** Test du bruit blanc***;

proc arima data = sauve.resDGI;identify var = residus_DDF2;run; quit;*** On a -17.81<-2.88 on peut ainsi en conclure que la série est stationnaire etqu'elle estintégrée à l'odre 1****;

H' F/0/12..0+1/, :2*6=0/12.

*** Création d'une bibliothèque ***; libname sauve "C:\Users\Faïma\Documents\Atelier d'économétrie" ;run ;****Importation des données sur la POPULATION****; filename POP_EU "C:\Users\Faïma\Documents\Atelier d'économétrie\POP envolume.txt" ;data POP_EU ;infile POP_EU dlm = '09'x dsd missover firstobs = 2;input POP_EU ;run;

****Création des variables: différences, retards et tendance****; data POP_EU;set POP_EU;l_POP=log(POP_EU);d_POP=dif(l_POP);lag1_POP=lag(l_POP);lag1_d_POP= lag(d_POP);lag2_d_POP= lag2(d_POP);lag3_d_POP= lag3(d_POP);trend=_n_;run;****Test de Dickey Fuller simple*****;

proc reg data=POP_EU ;

model d_POP = lag1_POP trend;output out=sauve.resPOP r=residus_DF3;run ; quit;*Le trend est significatif on accepte HO, et on a une spécification de type 3 etdonc on teste les résisdus afin de voir si c'est un bb **Test de bruit blanc sur les résidus*;

proc arima data = sauve.resPOP;identify var = residus_DF3;run; quit;*** Le test du bruit blanc sur les résidus nous montre qu'ils sont autocorrélés,il faut donc ajouter des retards pour les blanchir******Test ADF sur le modèle avec constante et trend et un retard***;



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proc reg data=POP_EU ;model d_POP = lag1_POP lag1_d_POP trend;output out=sauve.resPOP r=residus_ADF3_1;run ; quit;***Test du bruit blanc****;

proc arima data = sauve.resPOP;

identify var = residus_ADF3_1;run; quit;***Test ADF sur le modèle avec constante et trend et deux retards***;

proc reg data=POP_EU ;model d_POP = lag1_POP lag1_d_POP lag2_d_POP trend;output out=sauve.resPOP r=residus_ADF3_2;run ; quit;***Test du bruit blanc****;

proc arima data = sauve.resPOP;identify var = residus_ADF3_2;run; quit;***Test ADF sur le modèle avec constante et trend et trois retards***;

proc reg data=POP_EU ;

model d_POP = lag1_POP lag1_d_POP lag2_d_POP lag3_d_POP trend;output out=sauve.resPOP r=residus_ADF3_3;run ; quit;***Test du bruit blanc****;

proc arima data = sauve.resPOP;identify var = residus_ADF3_3;run; quit;**** Suite à l'ajout de 3 retards les résidus ne sont toujours pas blanchis, pourcette raison nous***** Différence deuxième*********Création des différences deuxièmes****; data POP_EU ; set POP_EU ;d2_POP = dif(d_POP);lag1_d2_POP= lag(d2_POP);lag2_d2_POP= lag2(d2_POP);lag3_d2_POP= lag3(d2_POP);lag4_d2_POP= lag4(d2_POP);trend=_n_;run;***Test de Dickey Fuller simple diff 2eme spécification 3*****;

proc reg data=POP_EU ;model d2_POP = lag1_d_POP trend;output out= sauve.resPOP r=residus_DDF3;run ; quit;***Test du bruit blanc****;

proc arima data = sauve.resPOP;identify var = residus_DDF3;run; quit;*** La constante et le trend sont siginificatifs, nous passons donc au test ADFpuisque les résidus sont autocorrélés******Test de Dickey Fuller simple diff 2eme spécification 3*****;

proc reg data=POP_EU ;model d2_POP = lag1_d_POP lag1_d2_POP trend;output out= sauve.resPOP r=residus_DADF3;run ; quit;**Test du bruit blanc****;

proc arima data = sauve.resPOP;identify var = residus_DADF3;



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run; quit;*** Les résidus ne sont toujours pas blanchis on ajoute alors un retard*******Test de Dickey Fuller simple diff 2eme spécification 3*****;

proc reg data=POP_EU ;model d2_POP = lag1_d_POP lag1_d2_POP lag2_d2_POP trend;output out= sauve.resPOP r=residus_DADF3_2;

run ; quit;**Test du bruit blanc****; proc arima data = sauve.resPOP;identify var = residus_DADF3_2;run; quit;***Test de Dickey Fuller simple diff 2eme spécification 3*****;

proc reg data=POP_EU ;model d2_POP = lag1_d_POP lag1_d2_POP lag2_d2_POP lag3_d2_POP trend;output out= sauve.resPOP r=residus_DADF3_3;run ; quit;*Test du bruit blanc****;

proc arima data = sauve.resPOP;identify var = residus_DADF3_3;

run; quit;**Test de Dickey Fuller simple diff 2eme spécification 3*****; proc reg data=POP_EU ;model d2_POP = lag1_d_POP lag1_d2_POP lag2_d2_POP lag3_d2_POP lag4_d2_POP trend;output out= sauve.resPOP r=residus_DADF3_4;run ; quit;*Test du bruit blanc****;

proc arima data = sauve.resPOP;identify var = residus_DADF3_4;run; quit;**** A la suite des tests sur les variables en différence deuxième on rejettel'hypothèse H0 de non stationnarité car on a -3.95<-3.45ainsi notre série en différence deuxième est stationnaire et intégrée à l'ordre1.***

R' N)-/ 7) B21./,3+0/12.

/*******TEST DE COINTEGRATION D'ENGLE et GRANGER****/ *** Création d'une bibliothèque ***; libname sauve "C:\Users\Faïma\Documents\Atelier d'économétrie" ;run ;****importation des données brutes***; PROC IMPORT OUT= sauve.donneesbrDATAFILE ="C:\Users\Faïma\Documents\Atelier d'économétrie\Données_brutes.xls" DBMS=xls


RUN; QUIT;***Définition des données****; data sauve.donneesbr2;set sauve.donneesbr;

PIB =log(PIB_EU);l_POP = log(POP);l_FBCF = log(FBCF);l_DGI = log(DGI);

l_SP500 = log(SP500);run; quit;



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**** Régression sur les données brutes en log****; proc reg data=sauve.donneesbr2;model PIB = l_POP l_FBCF l_DGI l_SP500;output out=sauve.res_coint r=residus_reg;run;quit;

***Création de variables dans la table des résidus pour évaluer la relation delong terme entre elles***; data sauve.res2;set sauve.res_coint;

lres = lag(residus_reg);dres = dif(residus_reg);t+1;dl1res = lag(dres);dl2res = lag2(dres);dl3res = lag3(dres);dl4res = lag4(dres);dl5res = lag5(dres);dl6res = lag6(dres);

dl7res = lag7(dres);dl8res = lag8(dres);dl9res = lag9(dres);dl10res = lag10(dres);dl11res = lag11(dres);dl12res = lag12(dres);dl13res = lag13(dres);dl14res = lag14(dres);dl15res = lag15(dres);dl16res = lag16(dres);dl17res = lag17(dres);dl18res = lag18(dres);dl19res = lag19(dres);dl20res = lag20(dres);dl21res = lag21(dres);dl22res = lag22(dres);dl23res = lag23(dres);dl24res = lag24(dres);dl25res = lag25(dres);dl26res = lag26(dres);dl27res = lag27(dres);dl28res = lag28(dres);dl29res = lag29(dres);dl30res = lag30(dres);dl31res = lag31(dres);

run;quit;***Dickey Fuller simple spécification 1****;

proc reg data=sauve.res2;model dres = lres /noint;output out=sauve.resDF1 r=residus_DF1;

run; quit;***Test du bruit blanc sur les résidus***;

proc arima data = sauve.resDF1;identify var = residus_DF1;run; quit;

***Régression pour test ADF sur les résidus afin de déterminer si ils sontstationnaires***;



A-

proc reg data=sauve.res2;model dres = lres dl1res dl2res/noint;output out=sauve.res2 r=residus_ADF1_2;

run; quit;****Test du bruit blanc sur les résidus***;

proc arima data = sauve.res2;

identify var = residus_ADF1_2;run; quit;*** Suite aux tests DF et ADF et le test du bruit blanc sur les résidus, ondéduit qu'ils ne sont pas autoccorrélés on a donc un bruit blanc.On comparae aux seuil critique de la table d'Engle and Yoo pour 4 variables et200 données -2.10>-4.13On en déduit l'absence de cointégration.On peut donc estimer le modèle endifférence première.

S' (,3+)--12. MBO

****Création d'une table constituée des différences premières***; *** Création d'une bibliothèque ***; libname sauve "C:\Users\Faïma\Documents\Atelier d'économétrie" ;run ;****importation des données brutes***; PROC IMPORT OUT= sauve.donneesbrDATAFILE ="C:\Users\Faïma\Documents\Atelier d'économétrie\Données_brutes.xls" DBMS=xls


****Création des variables: différences****; data sauve.donneesbr2;set sauve.donneesbr;l_PIB_EU=log(PIB_EU);d_PIB_EU=dif(l_PIB_EU);l_FBCF=log(FBCF);d_FBCF=dif(l_FBCF);l_DGI=log(DGI);d_DGI=dif(l_DGI);l_POP=log(POP);d_POP=dif(l_POP);l_SP500=log(SP500);d_SP500=dif(l_SP500);

run;

/*****************************************/ /* ESTIMATION MCO */

/*****************************************/ *****Estimation du modèle par les MCO; PROC REG DATA = sauve.donneesbr2; /*Estimation*/ model d_PIB_EU = d_POP d_SP500 d_DGI d_FBCF;RUN; QUIT;

A' N)-/- 7)- 4J*2/4L-)- MBO

/*********************************************/ /* Validation des hypothèses MCO */ /*********************************************/



AH

****Hypothèse 1: normalité des erreurs********; ***TEST DE NORMALITE*****;

proc univariate DATA= sauve.donneesbr2 normal; /*normalité de l'erreur JARQUEBERA*/ var d_PIB_EU d_POP d_SP500 d_DGI d_FBCF ;

run;QUIT;***H1 est vérifiée.; *******Hypothèse 2: homoscédasticité ********; PROC REG DATA = sauve.donneesbr2; /*test de White*/ MODEL d_PIB_EU = d_POP d_SP500 d_DGI d_FBCF / SPEC;run; quit;*¨**** H2 est vérifiée.; *******Hypothèse 3: absence d'autocorrélation ********; PROC REG DATA = sauve.donneesbr2; /*regression*/ MODEL d_PIB_EU = d_POP d_SP500 d_DGI d_FBCF /DW r;RUN; QUIT;****H3 n'est pas vérifiée il faut tester aux ordres supérieurs et apporter descorrections.***;

***Test d'autocorrélation aux ordres supérieurs***; proc autoreg data = sauve.donneesbr2 ;model d_PIB_EU = d_POP d_SP500 d_DGI d_FBCF / GF ;run ; quit ;****Analyse de la nature de l'autocorrélation****; PROC REG DATA = sauve.donneesbr2;MODEL d_PIB_EU = d_POP d_SP500 d_DGI d_FBCF / DWPROB ;RUN; QUIT;*****Correction de Newey-West****; PROC REG DATA = sauve.donneesbr2; /*correction de Newey-west*/ MODEL d_PIB_EU = d_POP d_SP500 d_DGI d_FBCF / ACOV;TEST intercept=0;RUN; QUIT;****Les résultats obtenus avec la correction de Newey West n'apporte aucunemodificationles écarts-types ont même augmenté****

*****Hypothèse 4: absence de multicolinéarité****; proc reg data = sauve.donneesbr2 ;MODEL d_PIB_EU = d_POP d_SP500 d_DGI d_FBCF / VIF ;run ; quit ;****Deuxième test*****;

proc reg data = sauve.donneesbr2 ;MODEL d_PIB_EU = d_POP d_SP500 d_DGI d_FBCF / collin ;run ; quit ;**** D'apres les VIF des coefficients estimés il n'y a pas de multicolinéaritédans la matrice variables explicatives***

****Hypothèse 5: stabilité des coefficients****; ***Test de CHOW ****; PROC AUTOREG DATA = sauve.donneesbr2;MODEL d_PIB_EU = d_POP d_SP500 d_DGI d_FBCF / chow = 4 ;RUN; QUIT;***Dans ce test la P-Value est inférieure à 5% on rejette l'hypothèse nulle destabilité du modèleil n'y pas eu de changement structurel****;



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