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# st: re: how to explain the results of ivendog after -ivreg2-?

 From Kit Baum To statalist@hsphsun2.harvard.edu Subject st: re: how to explain the results of ivendog after -ivreg2-? Date Tue, 4 Aug 2009 10:33:36 -0400

```<>

Rose said

Tests of endogeneity of: x1 x2
H0: Regressors are exogenous
```
Wu-Hausman F test: 5.32266 F(2,1224) P-value = 0.00499 Durbin-Wu-Hausman chi-sq test: 10.70872 Chi-sq(2) P-value = 0.00473
```
Tests of endogeneity of: x1

H0: Regressor is exogenous
```
Wu-Hausman F test: 1.86877 F(1,1225) P-value = 0.17187 Durbin-Wu-Hausman chi-sq test: 1.89181 Chi-sq(1) P-value = 0.16900
```
Tests of endogeneity of: x2
H0: Regressor is exogenous
```
Wu-Hausman F test: 0.59057 F(1,1225) P-value = 0.44235 Durbin-Wu-Hausman chi-sq test: 0.59848 Chi-sq(1) P-value = 0.43916
```

```
and wants to know how these results could be obtained after estimating the model
```
ivreg2 y z1--z8 (x1 x2= z9--z12)

```
Apparently if you ask "is x1 correlated with error" (equivalent to using endog(x1) option on ivreg2) the evidence against the null that it is orthogonal is weak. Likewise for x2. If you ask "can we run the whole thing as OLS" there is sufficient evidence to reject. The result of a joint test cannot be predicted from those of its components; you can
```reg y x1 x2 x3
```
with insignificant t's on x2 and x3 (particularly if their correlation is high) but
```test x2 x3
will strongly reject. Likewise here.
Kit
Kit Baum   |   Boston College Economics & DIW Berlin   |   http://ideas.repec.org/e/pba1.html
```
An Introduction to Stata Programming | http://www.stata-press.com/books/isp.html
```   An Introduction to Modern Econometrics Using Stata  |   http://www.stata-press.com/books/imeus.html

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```

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