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


From   Kit Baum <baum@bc.edu>
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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