daniel cassar --
I would prefer -ivreg2- (from SSC) for such a model.
It is impossible to tell from your post whether you have specified
your model correctly, and it cannot be the case that "the standard
errors were completely inflated (they grew very noticeably) so that
almost all of the explanatory variables were significant" since bigger
SEs imply less significance. Perhaps you can specify your question in
terms of a dataset that ships with Stata, or one available to everyone
via the web, e.g.
ssc inst ivreg2, replace
ssc inst estout, replace
use http://fmwww.bc.edu/ec-p/data/hayashi/griliches76.dta, clear
qui reg3 (lw=s expr iq) (iq=s expr med kww age)
est store reg3
qui ivreg2 lw s expr (iq=med kww age)
est store ivreg
qui reg iq med kww age s expr
ren iq was_iq
predict iq
qui reg lw s expr iq
est store byhand
esta reg3 ivreg byhand, eq(1) se mti(reg3 ivreg byhand)
On 4/5/07, daniel cassar <[email protected]> wrote:
Hi,
I have a two-equation system that I solved with
-reg3-. However, when I did the same system "by hand",
the standard errors were completely inflated (they
grew very noticeably) so that almost all of the
explanatory variables were significant. the point
estimates were the same, though.
Any ideas as to why this may happen? Which of the two
ways has the most reliable standard errors?
Note: my system has the following form:
x1=a1 + by1 + by2 + bx2 + e
x2=a2 + bz1 + bz2 + bz3 + e
And I got the weird results only in the second
equation 2. (Note that the dependent variable of the
second equation enters the first equation, but the
dependent variable of the first eq. does not enter the
second eq.)
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