楼主: nkzhh
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如何使用hasuman检验内生性问题? [推广有奖]

11
nkzhh 发表于 2006-4-19 21:02:00
以下是引用bigdog_1在2006-4-19 7:54:00的发言:

Stata can do Hausman test for panel data. Following is stata 8.0 code for hausman test to compare random effect model and fixed effect model.

(If there are some variables are endogeneous, FEM is better than REM )

 . xtreg dependentvar independentvar1 independentvar2 independentvar3 ... , fe
. estimates store fixed
. xtreg dependentvar independentvar1 independentvar2 independentvar3 ... , re
. estimates store random
. hausman fixed random

When you use "panel" in Limdep, it will report the results of Hausman test.

SAS/IML can do everything. I have SAS/IML code for panel data and Hausman test. If you want it,please let me know, i will send you a copy.

你说的是检验面板模型是固定还是随机效应的hausman,我说的是hausman test,用莱检验内生性问题的

12
bigdog_1 发表于 2006-4-20 04:58:00

Actually, there is not big difference. The basic theory is exactlly same. When you use hausman test to compare FEM and REM in panel data, the null hypothesis is that no variables are endogeneous--x'* ε=0 , the alternative hypothesis is x`*ε≠0.

Generally, if you want to test the null hypothesis that the error terms are uncorrelated with all the regressors against the alternative that they are correlated with some of the regressors(endogenity), you can use DWH(Durbin Wu Hausman) test.

At first, run OLS and IV estimator.

Under H1, the IV estimator is consistent, but OLS estimator is not.

Under H0, Both are consistent, and OLS are more efficient.

Thus, plim(BIV-BOLS)=0 under null and nonzero under the alternative.

. reg dependentvar independentvar1 independentvar2 independentvar3 ... (OLS)
. estimates store OLS
. reg dependentvar independentvar1 independentvar2 independentvar3 ... , (IV)
(or ivreg ----------)

. estimates store IV
. hausman IV OLS

[此贴子已经被作者于2006-4-20 11:11:24编辑过]

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13
蓝色 发表于 2006-4-25 08:41:00

hausman有好几个检验:

1、内生性检验

2、过渡识别检验

3、模型选择检验

所以不要混了啊,

14
thinky 发表于 2008-9-10 16:06:00

我也出现这个问题,在做内生行检验的时候,用ivreg做,然后ivendog ,overid都可以

可是用ivreg2做的时候,就不行了。出现下面的问题

Warning - collinearities detected
Vars dropped:      road field 

equation not identified; must have at least as many instruments not in
the regression as there are instrumented variables

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