为什么eviews和stata处理同样数据,结果相差那么多呢?
stata处理的tobit面板模型
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tfp | Coef. Std. Err. z P>|z| [95% Conf. Interval]
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lsmj | .0044849 .0070289 0.64 0.523 -.0092915 .0182613
ncwl | -.0075873 .0090699 -0.84 0.403 -.0253639 .0101893
rkmd | .0119272 .0074545 1.60 0.110 -.0026833 .0265376
rjsr | .0174592 .0268869 0.65 0.516 -.0352381 .0701565
gllc | .0005724 .0129959 0.04 0.965 -.0248991 .026044
_cons | .8691216 .2082339 4.17 0.000 .4609908 1.277253
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/sigma_u | .027406 .0063981 4.28 0.000 .014866 .0399461
/sigma_e | .0509929 .0034154 14.93 0.000 .0442988 .057687
-------------+----------------------------------------------------------------
rho | .224115 .0890028 .0899091 .4303734
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eviews处理的
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Variable | Coefficient | Std. Error | z-Statistic | Prob. |
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RETAILPROVINCE | -0.017801 | 0.005642 | -3.155168 | 0.0016 |
NCWLPROVINCE | -0.006351 | 0.007600 | -0.835605 | 0.4034 |
RJMJPROVINCE | 0.013256 | 0.006160 | 2.151961 | 0.0314 |
INCOMEPROVINCE | 0.117655 | 0.011567 | 10.17127 | 0.0000 |
HIGHWAYPROVINCE | 0.031164 | 0.010048 | 3.101562 | 0.0019 |
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| Error Distribution | | |
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SCALE:C(6) | 0.062743 | 0.003750 | 16.73328 | 0.0000 |
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Mean dependent var | 1.020729 | S.D. dependent var | 0.061190 |
S.E. of regression | 0.063894 | Akaike info criterion | -2.613837 |