. sysuse auto, clear
(1978 Automobile Data)
. generate wgt=weight/100
.
. reg mpg wgt price if foreign==0
Source | SS df MS Number of obs = 52
-------------+------------------------------ F( 2, 49) = 87.05
Model | 895.435922 2 447.717961 Prob > F = 0.0000
Residual | 252.006385 49 5.14298745 R-squared = 0.7804
-------------+------------------------------ Adj R-squared = 0.7714
Total | 1147.44231 51 22.4988688 Root MSE = 2.2678
------------------------------------------------------------------------------
mpg | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
wgt | -.6684313 .0616974 -10.83 0.000 -.7924169 -.5444456
price | .0002368 .0001385 1.71 0.094 -.0000416 .0005152
_cons | 40.56149 1.637025 24.78 0.000 37.27177 43.85122
------------------------------------------------------------------------------
. est store a
. reg mpg wgt price if foreign==1
Source | SS df MS Number of obs = 22
-------------+------------------------------ F( 2, 19) = 8.41
Model | 431.002738 2 215.501369 Prob > F = 0.0024
Residual | 486.860898 19 25.6242578 R-squared = 0.4696
-------------+------------------------------ Adj R-squared = 0.4137
Total | 917.863636 21 43.7077922 Root MSE = 5.062
------------------------------------------------------------------------------
mpg | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
wgt | -.875872 .5491112 -1.60 0.127 -2.025175 .273431
price | -.0003109 .0009068 -0.34 0.735 -.002209 .0015871
_cons | 47.04234 8.124348 5.79 0.000 30.03788 64.04679
------------------------------------------------------------------------------
. est store b
.
. suest a b
Simultaneous results for a, b
Number of obs = 74
------------------------------------------------------------------------------
| Robust
| Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
a_mean |
wgt | -.6684313 .0660396 -10.12 0.000 -.7978665 -.538996
price | .0002368 .0002078 1.14 0.254 -.0001704 .0006441
_cons | 40.56149 1.642392 24.70 0.000 37.34246 43.78052
-------------+----------------------------------------------------------------
a_lnvar |
_cons | 1.637634 .2941351 5.57 0.000 1.06114 2.214128
-------------+----------------------------------------------------------------
b_mean |
wgt | -.875872 .4376178 -2.00 0.045 -1.733587 -.0181569
price | -.0003109 .0007267 -0.43 0.669 -.0017352 .0011133
_cons | 47.04234 6.477927 7.26 0.000 34.34583 59.73884
-------------+----------------------------------------------------------------
b_lnvar |
_cons | 3.243539 .3206506 10.12 0.000 2.615076 3.872003
------------------------------------------------------------------------------
. test [a_mean]wgt-[a_mean]price = [b_mean]wgt-[b_mean]price
( 1) [a_mean]wgt - [a_mean]price - [b_mean]wgt + [b_mean]price = 0
chi2( 1) = 0.22
Prob > chi2 = 0.6407
那个是 suest里面的保存的变量
看suest的结果就知道了。
不同 回归那个是不一样的。
论坛币就不用了。
我可不发收费的帖子啊


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