enseignement de base au niger :quel bilan - CONFEMEN
enseignement de base au niger :quel bilan - CONFEMEN
enseignement de base au niger :quel bilan - CONFEMEN
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REDAN2 | 1.08 0.925486<br />
ENFTCONFIE | 1.06 0.939053<br />
FILLE | 1.06 0.942242<br />
-------------+----------------------<br />
Mean VIF | 1.36<br />
Il ressort du modèle qu’à ancienneté comparable, ce sont les contractuels non formés qui font<br />
le moins progresser les élèves.<br />
Nous avons vu qu’il y a une corrélation entre les variables <strong>de</strong> formation professionnelle,<br />
d’ancienneté et <strong>de</strong> statut. Dans le modèle précé<strong>de</strong>nt, remplaçons le statut successivement par<br />
la formation professionnelle initiale et l’ancienneté.<br />
i) formation professionnelle<br />
Modèle IV.13<br />
. reg STFIN2FM STINI2FM FILLE AGEPLUS ENFTCONFIE NIVEAUVIE3 REDAN2 LIV_FR LIV_MT<br />
MAITRFEM FPI1ANPL FPI1AN DIPCYCLB NIVCYCLB MTMOBILE MTPRECENS MTAUTREACT<br />
MTRESTENS MTCONCOUR ABSMT DOUBLFLX BANCO UTILIVRFR UTILIVMT APEACTIV CONSULCOLL<br />
INSPECTEUR CONSPEDAG MTCHANGECO DIRENSEIG RURAL if SERVICE < 10, cluster(NUMECOLE)<br />
Regression with robust standard errors Number of obs = 1178<br />
F( 30, 97) = 19.76<br />
Prob > F = 0.0000<br />
R-squared = 0.4522<br />
Number of clusters (NUMECOLE) = 98 Root MSE = .75825<br />
------------------------------------------------------------------------------<br />
| Robust<br />
STFIN2FM | Coef. Std. Err. t P>|t| [95% Conf. Interval]<br />
-------------+----------------------------------------------------------------<br />
STINI2FM | .4929054 .0386588 12.75 0.000 .4161784 .5696324<br />
FILLE | -.0601545 .0459042 -1.31 0.193 -.1512617 .0309526<br />
AGEPLUS | -.0749859 .0832938 -0.90 0.370 -.240301 .0903293<br />
ENFTCONFIE | -.0617004 .0681852 -0.90 0.368 -.1970292 .0736285<br />
NIVEAUVIE3 | .1018503 .0891374 1.14 0.256 -.0750627 .2787633<br />
REDAN2 | -.1797012 .0709476 -2.53 0.013 -.3205124 -.0388899<br />
LIV_FR | .2808516 .0638875 4.40 0.000 .1540527 .4076506<br />
LIV_MT | .0685099 .0618186 1.11 0.270 -.054183 .1912028<br />
MAITRFEM | -.1217096 .1554094 -0.78 0.435 -.4301543 .1867351<br />
FPI1ANPL | .3201731 .1165931 2.75 0.007 .0887682 .5515781<br />
FPI1AN | .0470198 .1910045 0.25 0.806 -.3320712 .4261108<br />
DIPCYCLB | -.0959702 .1465111 -0.66 0.514 -.3867541 .1948137<br />
NIVCYCLB | .1997001 .137797 1.45 0.150 -.0737888 .473189<br />
MTMOBILE | -.3124457 .1929663 -1.62 0.109 -.6954303 .0705389<br />
MTPRECENS | .1374475 .0997781 1.38 0.172 -.0605845 .3354795<br />
MTAUTREACT | -.0994398 .1102932 -0.90 0.370 -.3183413 .1194617<br />
MTRESTENS | -.1620044 .1181746 -1.37 0.174 -.3965482 .0725394<br />
MTCONCOUR | .2987793 .1350161 2.21 0.029 .0308098 .5667488<br />
ABSMT | .0056622 .0146634 0.39 0.700 -.0234406 .0347651<br />
DOUBLFLX | -.4605032 .1668576 -2.76 0.007 -.7916692 -.1293371<br />
BANCO | .0060927 .1156318 0.05 0.958 -.2234044 .2355897<br />
UTILIVRFR | .2033017 .1262773 1.61 0.111 -.0473238 .4539272<br />
UTILIVMT | -.3530074 .1307146 -2.70 0.008 -.6124396 -.0935751<br />
APEACTIV | -.128873 .1024943 -1.26 0.212 -.3322959 .0745499<br />
CONSULCOLL | .0114102 .0990445 0.12 0.909 -.1851657 .2079861<br />
INSPECTEUR | -.2772142 .1445652 -1.92 0.058 -.564136 .0097077<br />
CONSPEDAG | .1886545 .1278696 1.48 0.143 -.0651313 .4424402<br />
MTCHANGECO | -.0383473 .1126736 -0.34 0.734 -.2619732 .1852786<br />
DIRENSEIG | .4433941 .1202414 3.69 0.000 .2047481 .6820401<br />
RURAL | -.3646469 .1390936 -2.62 0.010 -.6407093 -.0885845<br />
_cons | -.319882 .3283763 -0.97 0.332 -.971618 .331854<br />
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