--- sara borelli <[email protected]> wrote:
> I am estimating the following regression:
>
> y1= ax + by2 + u
> where y2 is endogenous and I am using some varaible z as identifying
> instrument
>
> y1, x, z are osberved for the whole sample, but y2 is missing for 30%
> of observations.
> If I use ivreg, stata estimates the model only on the non-missing
> observations. But I need to estimate the model on the whole sample.
> Therefore I explicitly performed the two steps separately,
> predicting y2 in the first stage for the whole sample and inserting
> it into the second stage. But I know the standard errors may be
> biased. Does anyone know a way to estimate this correctly?
I don't think that your procedure is going to solve your problem: This
way your predictions of y2 are still based on the sample without
missing data. A more principled approach is to use -ice-, see the
articles below:
Royston, P. 2004. Multiple imputation of missing values. Stata Journal
4(3): 227�241.
Royston, P. 2005. Multiple imputation of missing values: update. Stata
Journal 5(2): 188�201.
Royston, P. 2005. Multiple imputation of missing values: Update of ice.
Stata Journal 5(4): 527-536.
Royston, P. 2007. Multiple imputation of missing values: further update
of ice, with an emphasis on interval censoring. Stata Journal 7(4):
445-464.
You can find these articles here:
http://www.stata-journal.com/archives.html
Hope this helps,
Maarten
-----------------------------------------
Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands
visiting address:
Buitenveldertselaan 3 (Metropolitan), room Z434
+31 20 5986715
http://home.fsw.vu.nl/m.buis/
-----------------------------------------
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