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st: AW: xtivreg2 - Incomplete computation of first stage regression


From   "Martin Weiss" <[email protected]>
To   <[email protected]>
Subject   st: AW: xtivreg2 - Incomplete computation of first stage regression
Date   Sun, 28 Feb 2010 14:55:39 +0100

<> 


-ssc d xtivreg2- managed to provide results only for the endogenous vars in
levels, but not the lagged ones, so I would start my investigation with this
potential problem...



HTH
Martin


-----Ursprüngliche Nachricht-----
Von: [email protected]
[mailto:[email protected]] Im Auftrag von Lim Boon Leong
Gesendet: Sonntag, 28. Februar 2010 09:45
An: [email protected]
Betreff: st: xtivreg2 - Incomplete computation of first stage regression

Dear Statalisters:

 

I have a regression equation which is consisted of 5 suspected endogenous
variables with a list of excluded instrument variables.  I use xtivreg2,
fixed effect, cluster (id) small function to run the regression analysis.

 

Xtivreg2 lsalary ceodual ... (ownexr ownex2r ownex3r L.ldiv L.debt = lrisk
lsale lsale2......), fe cluster(id) small

 

The regression runs smoothly and provides test results such as
underidentification test, weak identification test, and Hansen J statistic.

 

But when I run the first function to get the first stage regression as
below:

 

Xtivreg2 lsalary ceodual ... (ownexr ownex2r ownex3r L.ldiv L.debt = lrisk
lsale lsale2......), fe cluster(id) small first 

 

, it only managed to provide first stage regression results for the first 3
endogenous variables namely ownexr, ownex2r, and ownex3r.

 

And for the fourth first stage regression result it is reported as such:

 

First-stage regression of _000007:

 

..........................

 

_000007 not found 

 

r(111) which implies missing variables.

 

My questions are as follows:

 

1.        If I have 5 endogenous regressors, can I expect to have 5 first
stage regression results for all these endogenous variables?

 

2.       Is there any methods to compute the first stage regression for all
these 5 endogenous regressors?

 

Thank you very much.

 

Best regards,

Lim Boon Leong 

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