2.
Liste des entreprises CAC 40
|
Accor
|
Sanofi aventis
|
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Air liquide
|
Suez environnement
|
|
Alcatel-lucent
|
Total
|
|
Alstrom
|
Vallorec
|
|
Arcelor mital
|
Veolia environnement
|
|
Bouygues
|
Vinci
|
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Danone
|
Vivendi
|
|
Essilor
|
Gaz de France
|
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France telecom
|
France telecom
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GDZ suez
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AXA
|
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Air France KLM
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DXIA
|
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Carrefour
|
CAP GEMIMI
|
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L'oreal
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Lagardère
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LVMH
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Schneider electric
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Lafarge
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Stimcroelectronics
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|
Michelin
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Unibail -rodamco
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PPR
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Renault
|
|
Peugeot
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sain gobain
|
3: Résultats des
estimations
Etude empirique du modèle 1: Qualité
d'information et normes IFRS
Variable | Obs Mean Std. Dev. Min
Max
-------------+------------------------------------------------------------------
aq | 360 -.04606 .086451
-.88169 .61597
bn | 360 12.42039 2.172793 0
16.91371
Taille | 360 7.38632 .516200 6.173573
8.91791
Croissance | 360 .51401 6.795071 -1.01178
125.2609
Dette | 360 .60248 .3749126 .03415
3.288881
| aq bn ifrs
taille croiss~e dette
-------------+-------------------------------------------------------------------
aq | 1.0000
bn | -0.0117 1.0000
ifrs | 0.1237 0.0487 1.0000
taille | -0.0961 0.3415 0.1020 1.0000
croince | 0.0325 0.0520 -0.0495 0.2120 1.0000
dette | 0.0082 0.1044 -0.0886 0.2231 0.0047
1.0000
Fixed-effects (within) regression Number
of obs = 360
Group variable: id
Number of groups = 36
R-sq: within = 0.4719 Obs
per group: min = 1
between = 0.3721
avg = 9.3
overall = 0.3210
max = 10
F(5,292) = 10.73
corr(u_i, Xb) = 0.0343
Prob > F = 0.0000
-------------------------------------------------------------------------------------
aq | Coef. Std. Err. z P>|z|
[95% Conf. Interval]
-------------+----------------------------------------------------------------------
cronce | .05668 .006461 8.61 .000461 -.0005134
.002254
ifrs | -.036007 .016830 -2.13 .03330
.0067601 .046170
taille | .461891 .052808 8.74 .000012 .049839
-.004714
dette | -.017897 .602504 -0.52 .034323 .013905
.037544
bn | .036942 .020438 0.55 .072076
-.0037697 .005550
_cons | .006739 .005856 1.15 .250923 -.0275929
.279895
Random-effects GLS regression Number of
obs = 360
Group variable: id
Number of groups = 36
R-sq: within = 0.1505 Obs
per group: min = 1
between = 0.2523
avg = 9.3
overall = 0.1731
max = 10
Random effects u_i ~ Gaussian Wald
chi2(5) = 68.46
corr(u_i, X) = 0 (assumed)
Prob > chi2 = 0.0000
--------------------------------------------------------------------------------------
aq | Coef. Std. Err. z
P>|z| [95% Conf. Interval]
-------------+-----------------------------------------------------------------------
croice | .0057900 .000653 8.91 0.0052
-.0006836 .001877
ifrs | -.0242343 .009238 -2.62 0.009
.0061283 .042340
taille | .0112319 .010406 1.08 0.337
-.0421488 -.001355
dette | -.001770 .036266 -.49 0.11
.2000031 .342163
bn | .0009113 .002198 0.41 0.679
-.0033983 .005221
cons | .1019346 .071894 1.42 0.156
-.0389765 .242845
---- Coefficients ----
| (b) (B) (b-B)
sqrt(diag(V_b-V_B))
| eq1 .
Difference S.E.
-------------+----------------------------------------------------------------
croisce | .05668 .00579 .05089
.0256394
bn | .036942 -.0242343 .012713
.0012319
ifrs | -.024234 .0009113 .023323
.0026421
dette | -.017897 -.001770 -.01612
.0101931
------------------------------------------------------------------------------
b = consistent under Ho and Ha;
obtained from xtreg
B = inconsistent under Ha, efficient under Ho;
obtained from xtreg
Test: Ho: difference in coefficients not systematic
chi2(5) = (b-B)'[(V_b-V_B)^(-1)](b-B)
= 9.84
Prob>chi2 = 0.0798
(V_b-V_B is not positive definite)
Breusch and Pagan Lagrangian multiplier test for random
effects
aq[id,t] = Xb + u[id] + e[id,t]
Estimated results:
| Var sd = sqrt(Var)
---------+-----------------------------
aq | .0079685 .0892667
e | .0066036 .0812624
u | 0
0
Test: Var(u) = 0
chi2(1) = 0.16
Prob > chi2 = 0.6927
Etude empirique du modèle 2: Normes IFRS et
gestion du résultat
Variable | Obs Mean Std. Dev.
Min Max
-------------
+--------------------------------------------------------------------
accd_k | 360 -.034426 .122163
-.9808009 .7443
croissance | 360 .569841 6.788301
-.9756227 125.2609
profitabilit | 360 8.634400 20.075860
-.6310300 275.6764
taille | 360 .605896 .419378
.0341552 3.6609
levrage | 360 .602485 .374912
.0034150 3.2888
Cash | 360 11.01967 1.577148
8.212839 19.0123
profitabli~s | 360 4.918336 20.222060 -.631030
275.6764
ifcroiss | 360 .0641394 .448361
-.896317 7.5648
ifrlevrage | 360 .122189 .329340
0 2.7279
| accd_k ifrs croiss~e
profit~t taille levrage cash
-------------+---------------------------------------------------------------------------
accd_k | 1.0000
ifrs | -0.0233 1.0000
croissance | 0.0411 -0.0493 1.0000
profitabilit | -0.0383 0.1491 -0.0115 1.0000
taille | 0.0020 -0.0540 0.0010 -0.1119
1.0000
levrage | 0.0132 -0.0773 0.0031 -0.1240 0.9142
1.0000
cash | 0.0588 0.0762 -0.0165 0.0858 -0.0468
-0.0493 1.0000
profitabli~s | -0.0383 0.2983 -0.0104 0.9621 -0.0962
-0.1098 0.0760
ifcroiss | 0.0148 0.1754 0.0554 0.08721 -0.0875
-0.0769 0.0423
levrage | -0.0102 0.0767 0.0231 0.3350 0.341
1.0000 -0.0643
| profit~s ifcroiss levrage
-------------+---------------------------
profitbli~s | 1.0000
ifcroiss | 0.1178 1.0000
levrage | -0.138 0.068 1.0000
Fixed-effects (within) regression
Number of obs = 360
Group variable: ent
Number of groups = 36
R-sq: within = 0.1780
Obs per group: min = 6
between = 0.1543
avg = 7.4
overall = 0.1413
max = 10
F(9,222) = 0.71
corr(u_i, Xb) = -0.4375
Prob > F = 0.6995
------------------------------------------------------------------------------------------
accd_k | Coef. Std. Err. z
P>|z| [95% Conf. Interval]
-------------+---------------------------------------------------------------------------
ifrs | -.0246726 .0096084 -2.57 0.011
-.0057622 .043583
croisnce | .3140822 .161414 1.95 0.053
-.0040334 .6321977
profitbilit | .0005364 .0014138 0.38 0.704
-.0022346 .0033073
taille | .0144128 .0382839 0.38 0.707
-.0606223 .0894478
cash | -.0049507 .004155 -1.19 0.233
-.0130945 .003193
proabli~s | -.0003029 .0014492 -0.21 0.834
-.0031433 .0025375
ifcros | -.0061978 .0148235 -0.42 0.676
-.0352513 .0228557
levrge | -.0180318 .0429128 -0.42 0.674
-.1021393 .0660757
_cons | .0156289 .048055 0.33 0.745
-.0785573 .109815
Random-effects GLS regression Number of
obs = 360
Group variable: ent
Number of groups = 36
R-sq: within = 0.4901 Obs
per group: min = 10
between = 0.6430
avg = 10.0
overall = 0.5703
max = 10
Random effects u_i ~ Gaussian Wald
chi2(8) = 3.09
corr(u_i, X) = 0 (assumed)
Prob > chi2 = 0.9285
-------------------------------------------------------------------------------------------
accd_k | Coef. Std. Err. z
P>|z| [95% Conf. Interval]
-------------+-----------------------------------------------------------------------------
ifrs | -.058871 .029733 -1.98 0.0941
-4.539062 4.690386
croissance | .000785 .000214 3.66 0.0003
-.0636778 .079189
prtabilit | .0210044 .10871 1.93 0.0532
1.010623 1.070186
taille | .014526 .023881 0.60 0.5434
5.353062 6.713565
levrage | -.017526 .030370 -0.56 0.5701
-7.103724 5.574715
cash | -.0004939 .002698 -1.83 0.0680
-.9585417 .430451
probli~s | -.000313 .000833 -0.37 0.7076
-.0130945 .003193
ifcroiss | -.006267 .009539 -0.65 0.5116
-.6830548 6.402178
ifrvrage | .006453 .032688 1.99 0.0048
.922653 2.863893
_cons | .0149093 .032047 0.46 0.6422
.94024 .718268
---- Coefficients ----
| (b) (B) (b-B)
sqrt(diag(V_b-V_B))
| eq1 .
Difference S.E.
-------------+----------------------------------------------------------------
ifrs | -.058871 -.0246726 .0588495
.0385626
croince | .000785 .3140822 -.0000806
.0004119
profiilit | .0210044 .0005364 .0008235
.0020131
taille | .014526 .0144128 .0299021
.0813487
levrage | -.017526 -.0180318 -.0681129
.0851662
cash | -.0004939 -.0049507 -.0085122
.0269796
prabli~s | -.000313 -.0003029 -.0012538
.0017414
ifcroiss | -.006267 -.0061978 .0231808
.0395474
------------------------------------------------------------------------------
b = consistent under Ho and Ha;
obtained from xtreg
B = inconsistent under Ha, efficient under Ho;
obtained from xtreg
Test: Ho: difference in coefficients not systematic
chi2(8) = (b-B)'[(V_b-V_B)^(-1)](b-B)
= 9.43
Prob>chi2 = 0.3070
Breusch and Pagan Lagrangian multiplier test for random
effects
accd_k[ent,t] = Xb + u[ent] + e[ent,t]
Estimated results:
| Var sd = sqrt(Var)
---------+-------------------------------
accd_k | .014924 .1221636
e | .0154479 .1242897
u | 0
0
Test: Var(u) = 0
chi2(1) = 11.88
Prob > chi2 = 0.000
Etude empirique du modèle 3: Détermination
de nombre analystes par firme
Variable | Obs Mean Std. Dev.
Min Max
-----------+----------------------------------------------------------------------
rcov | 360 5.613889 2.418205 1
9
taille | 360 .6058965 .419378
.03415 3.6609
roa | 360 4.378594 1.927911
.40764 9.2317
croissce | 360 .5698414 6.788301
-.97562 125.2609
cash | 360 11.01967 1.577148
8.2128 19.0123
| taille cash croissce roa
rcov
--------+---------------------------------------------------------
taille | 1.0000
cash | -0.460 1.0000
croince | 0.0015 -0.165 1.0000
roa | -0.246 0.0960 -0.3822 1.0000
rcov | -0.054 0.3479 0.3514 -0.1121
1.0000
Fixed-effects (within) regression
Number of obs = 360
Group variable: ent
Number of groups = 36
R-sq: within = 0.3485
Obs per group: min = 1
between = 0.2994
avg = 8.2
overall = 0.2001
max = 10
F(4,32) = 9.72
corr(u_i, Xb) = -0.5571
Prob > F = 0.0000
-----------------------------------------------------------------------------------------
rcov | Coef. Std. Err. t
P>|t| [95% Conf. Interval]
-------------+-------------------------------------------------------------------------
taille | -.098447 .5209622 -0.19 0.851
-1.159612 .9627184
cash | 1.053572 .2001723 5.26 0.000
.6458343 1.46131
croince | .0189151 .2915541 0.06 0.949 -.5749612
.6127914
roa | -.084959 .1014965 -0.84 0.409
-.2917006 .1217826
_cons | -7.841406 2.450555 -3.20 0.003 -12.83302
-2.849788
Random-effects GLS regression Number
of obs = 360
Group variable: ent
Number of groups = 36
R-sq: within = 0.6950
Obs per group: min = 1
between = 0.7592
avg = 8.2
overall = 0.5941
max = 10
Random effects u_i ~ Gaussian Wald
chi2(4) = 41.27
corr(u_i, X) = 0 (assumed)
Prob > chi2 = 0.0000
------------------------------------------------------------------------------------------
rcov | Coef. Std. Err. z
P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------------------
cash | .6390153 .1580866 4.04 0.000 .3291714
.9488593
taille | -2.475195 1.075196 -2.30 0.021
-4.58254 -.3678497
croince | -.6266269 .5946893 -1.05 0.292 -1.792196
.5389427
roa | .3182828 .127994 2.49 0.013
.0674191 .5691464
cons | -2.810399 1.690312 -1.66 0.096 -6.12335
.5025514
---- Coefficients ----
| (b) (B) (b-B)
sqrt(diag(V_b-V_B))
| eq1 . Difference
S.E.
-------------+----------------------------------------------------------------
taille | -.098447 -2.475195 2.376748
.154578
cash | 1.053572 .6390153 .4145566
.1227909
crance | .0189151 -.6266269 .645542
.004578
roa | -.084959 .3182828 -.4032418
.201548
------------------------------------------------------------------------------
b = consistent under Ho and Ha;
obtained from xtreg
B = inconsistent under Ha, efficient under Ho;
obtained from xtreg
Test: Ho: difference in coefficients not systematic
chi2(4) = (b-B)'[(V_b-V_B)^(-1)](b-B)
= -95.73 chi2<0 ==> model
fitted on these
data fails to meet the
asymptotic
assumptions of the
Hausman test;
see suest for a
generalized test Estimated results:
| Var sd = sqrt(Var)
---------+-----------------------------
rcov | 3.754878 1.937751
e | .3682473 .6068338
u | 0 0
Test: Var(u) = 0
chi2(1) = 25.90
Prob > chi2 = 0.0000
Etude empirique du modèle 4: Présence des
analystes et gestion du résultat
Variable | Obs Mean Std. Dev. Min
Max
-------------+-------------------------------------------------------------
accd_k | 360 .0823296 .0965164 .0000897
.9808
taill | 360 -.0344268 .1221636 -.9808009
.7443
croissace | 360 .5698414 6.788301 -.9756227
125.2609
casvolatile | 360 10.02006 1.590379 7.204885
18.5226
taille | 360 .6058965 .419378 .0341552
3.6609
| accd_k taille croissce cash
roa
-----------+--------------------------------------------------------
accd_k | 1.0000
taille | -0.0975 1.0000
croissce | -0.0272 0.0010 1.0000
cash | 0.0252 -0.0468 -0.0165 1.0000
roa | 0.0213 -0.2471 -0.0390 0.1161
1.0000
Fixed-effects (within) regression Number of
obs = 360
Group variable: ent
Number of groups = 36
R-sq: within = 0.350 Obs
per group: min = 10
between = 0.277
avg = 10.0
overall = 0.290
max = 10
F(4,320) = 0.28
corr(u_i, Xb) = -0.0589
Prob > F = 0.8904
-----------------------------------------------------------------------------------------
accd_k | Coef. Std. Err. t P>|t|
[95% Conf. Interval]
-------------+|--------------------------------------------------------------------------
resid| -.000180 .00339 -4.14 0.0000
-.0563903 .0763608
roa| -.0000856 .0014517 -0.27 0.0090
-.0032416 .0024704
croisse | -.0003361 .0007685 -0.44 0.6621
-.001848 .0011758
cash | .0049878 .0108671 0.46 0.6472
-.0163923 .0263678
taille | -.0147646 .0187175 -0.79 0.0443
-.0515895 .0220603
_cons | .0386739 .1209548 0.32 0.7495
-.1992931 .2766409
Random-effects GLS regression
Number of obs = 360
Group variable: ent
Number of groups = 36
R-sq: within = 0.531
Obs per group: min = 10
Between = 0.618
avg = 10.0
Overall = 0.571
max = 10
Random effects u_i ~ Gaussian
Wald chi2(4) = 2.84
corr(u_i, X) = 0 (assumed)
Prob > chi2 = 0.5848
---------------------------------------------------------------------------------------
accd_k | Coef. Std. Err. z P>|z|
[95% Conf. Interval]
-------------+------------------------------------------------------------------------
resid| -.00018 .00339 -4.14 0.0001
-.0563903 .0763608
roa | -.000014 .00214 -3.09 0.0009
-.0029102 .0019695
croissce | -.000371 .000754 -0.49 0.6234
-.0018230 .0010878
cash | .062101 .030756 2.01 0.0442
-.0062750 .0094527
taille | -.020837 .012547 -1.66 0.0977
-.0485797 .0057565
_cons | .0386739 .12095 0.32 0.3495
-.1992931 .2766409
---- Coefficients ----
| (b) (B) (b-B)
sqrt(diag(V_b-V_B))
| eq1 .
Difference S.E.
-----------+-------------------------------------------------------------------------
roa | -.0003856 -.0004703 .0000848
.0007468
croisce | -.0003361 -.0003676 .0000315
.000198
cash | .0049878 .0015889 .0033989
.0100993
taille | -.0147646 -.0214116 .006647
.0125778
b = consistent under Ho and Ha;
obtained from xtreg
B = inconsistent under Ha, efficient under Ho;
obtained from xtreg
Test: Ho: difference in coefficients not systematic
chi2(4) = (b-B)'[(V_b-V_B)^(-1)](b-B)
= 0.55
Prob>chi2 = 0.9688
Breusch and Pagan Lagrangian multiplier test for random
effects
accd_k[ent,t] = Xb + u[ent] + e[ent,t]
Estimated results:
| Var sd = sqrt(Var)
---------+-----------------------------
accd_k | .0093154 .0965164
e | .00883 .0939682
u | .0006461 .0254188
Test: Var(u) = 0
chi2(1) = 3.97
Prob > chi2 = 0.046
| 
