hausman检验的问题

1、F检验，可以检验到底是pooled ols还是fixed model

2、xttest0 是检验到底是pooled ols还是random model

3、hausman是检验到底是fixed model还是random model，

其H0：是不可观测效应与X是不相关的，应采用random effect模型估计；

H1：不可观测效应与X是相关的，应采用fixed effect模型估计

蓝色:谢谢您。偶还有几个特殊的问题在上面呢。您回答的是一般原则啊。

以下是引用YUZCP在2007-2-6 22:16:00的发言：

如果根据HAUSMAN检验选择模型不符合经济涵义呢？这时应该根据经济涵义来选择模型吗？谢谢斑竹能够回答。如果这个显著性水平往往是人为定的，如果正好是5%左右，而两个模型都有经济含义，只是回归系数大小略有不同，应该如果选择模型呢？

在加入一个解释变量后，一个模型的解释力即R2明显上升了，而这个模型又不是符合LM和HAUSMAN检验的 ，这时应该根据哪个标准来选择？

是否符合经济含义，不是统计检验决定的。

在你建立模型以前，就应该确定那些变量是应该放入的。

那和检验无关。

xtreg lnjishu lnjingfei jiaoyi,fe

Fixed-effects (within) regression Number of obs = 23
Group variable (i): diqu Number of groups = 12

R-sq: within = 0.6373 Obs per group: min = 1
between = 0.9329 avg = 1.9
overall = 0.8944 max = 2

F(2,9) = 7.91
corr(u_i, Xb) = 0.3553 Prob > F = 0.0104

------------------------------------------------------------------------------
lnjishu | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
lnjingfei | .6619254 .1903613 3.48 0.007 .2312982 1.092553
jiaoyi | .899726 .6327677 1.42 0.189 -.5316939 2.331146
_cons | -.2279501 .9540045 -0.24 0.817 -2.386058 1.930158
-------------+----------------------------------------------------------------
sigma_u | .46090868
sigma_e | .447694
rho | .51454089 (fraction of variance due to u_i)
------------------------------------------------------------------------------
F test that all u_i=0: F(11, 9) = 0.96 Prob > F = 0.5313

. xtreg lnjishu lnjingfei jiaoyi,re

Random-effects GLS regression Number of obs = 23
Group variable (i): diqu Number of groups = 12

R-sq: within = 0.6222 Obs per group: min = 1
between = 0.9643 avg = 1.9
overall = 0.9134 max = 2

Random effects u_i ~ Gaussian Wald chi2(2) = 210.94
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000

------------------------------------------------------------------------------
lnjishu | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
lnjingfei | .9236558 .1024741 9.01 0.000 .7228101 1.124501
jiaoyi | .6860679 .1667696 4.11 0.000 .3592055 1.01293
_cons | -1.373571 .4579633 -3.00 0.003 -2.271162 -.4759794
-------------+----------------------------------------------------------------
sigma_u | 0
sigma_e | .447694
rho | 0 (fraction of variance due to u_i)
------------------------------------------------------------------------------

.
. xttest0

Breusch and Pagan Lagrangian multiplier test for random effects:

lnjishu[diqu,t] = Xb + u[diqu] + e[diqu,t]

Estimated results:
| Var sd = sqrt(Var)
---------+-----------------------------
lnjishu | 2.061713 1.435867
e | .2004299 .447694
u | 0 0

Test: Var(u) = 0
chi2(1) = 0.47
Prob > chi2 = 0.4918

. xthausman
Estimate of sigma_u = 0, random-effects estimator has degenerated to pooled
OLS and the Wald test from xthausman may not be appropriate. See [R] hausman
for a more general implementation of the Hausman test.
r(459);

这种情况下应该选择FE？如果选择FE，那么回归系数不符合偶的经济学涵义。谢谢。

xthaus 拒绝执行hausman test 当矩阵没有正定解(positive definite), 因此STATA推荐常用的hausman 命令。

stata8以后hausman检验是用hausman命令

xtreg y x, fe

est store fixed

xtreg y x,re

est store random

hausman fixed

蜻蜓点水与蓝色：谢谢二位为偶答疑解惑。

xtreg lnchanzhi lnziben lnrenshu jiaoyi,fe

Fixed-effects (within) regression Number of obs = 38
Group variable (i): diqu Number of groups = 19

R-sq: within = 0.9315 Obs per group: min = 2
between = 0.9600 avg = 2.0
overall = 0.9530 max = 2

F(3,16) = 72.51
corr(u_i, Xb) = -0.9314 Prob > F = 0.0000

------------------------------------------------------------------------------
lnchanzhi | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
lnziben | .4143423 .1174352 3.53 0.003 .1653907 .6632939
lnrenshu | 1.646248 .4142596 3.97 0.001 .768057 2.524439
jiaoyi | -.4148017 .32936 -1.26 0.226 -1.113014 .2834102
_cons | -3.140117 1.040475 -3.02 0.008 -5.345826 -.9344083
-------------+----------------------------------------------------------------
sigma_u | .75801058
sigma_e | .11302602
rho | .97825015 (fraction of variance due to u_i)
------------------------------------------------------------------------------
F test that all u_i=0: F(18, 16) = 7.24 Prob > F = 0.0001

.
.
. xtreg lnchanzhi lnziben lnrenshu jiaoyi,re

Random-effects GLS regression Number of obs = 38
Group variable (i): diqu Number of groups = 19

R-sq: within = 0.8981 Obs per group: min = 2
between = 0.9707 avg = 2.0
overall = 0.9669 max = 2

Random effects u_i ~ Gaussian Wald chi2(3) = 695.96
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000

------------------------------------------------------------------------------
lnchanzhi | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
lnziben | .6139068 .0849526 7.23 0.000 .4474027 .7804109
lnrenshu | .7080905 .1067483 6.63 0.000 .4988676 .9173133
jiaoyi | .1667369 .2205208 0.76 0.450 -.2654759 .5989498
_cons | -.5485092 .3959151 -1.39 0.166 -1.324488 .2274701
-------------+----------------------------------------------------------------
sigma_u | .1722379
sigma_e | .11302602
rho | .69899511 (fraction of variance due to u_i)
------------------------------------------------------------------------------

. xttest0

Breusch and Pagan Lagrangian multiplier test for random effects:

lnchanzhi[diqu,t] = Xb + u[diqu] + e[diqu,t]

Estimated results:
| Var sd = sqrt(Var)
---------+-----------------------------
lnchanzhi | 1.691057 1.300406
e | .0127749 .113026
u | .0296659 .1722379

Test: Var(u) = 0
chi2(1) = 4.29
Prob > chi2 = 0.0382

. xthausman
(Warning: xthausman is no longer a supported command; use -hausman-. For
instructions, see help hausman.)

Hausman specification test

---- Coefficients ----
| Fixed Random
lnchanzhi | Effects Effects Difference
-------------+-----------------------------------------
lnziben | .4143423 .6139068 -.1995645
lnrenshu | 1.646248 .7080905 .9381576
jiaoyi | -.4148017 .1667369 -.5815386

Test: Ho: difference in coefficients not systematic

chi2( 3) = (b-B)'[S^(-1)](b-B), S = (S_fe - S_re)
= 12.84
Prob>chi2 = 0.0050

根据检验应选择固定效应模型，但是，固定效应中的jiaoyi变量的回归系数为负，不符合经济学解释，而在随机效应中为正，正是偶需要的模型。应该怎么选择呢？谢谢。

反正那个变量也不显著，可以不用管啊

再问：当hausman检验时选择固定效应模型，而如果选择随机效应可决系数提高了，变量也显著了。应该怎么办？谢谢