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st: Re: Two step estimation and standard error computation


From   "Rodrigo A. Alfaro" <raalfaroa@gmail.com>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: Re: Two step estimation and standard error computation
Date   Sun, 19 Aug 2007 12:55:10 -0400

Georgios,

I don't have access to the article that you mentioned. My suggestion is
to use the matrices e(b) and e(V) to construct the required std. error.
You could check -_robust- command in Programming manual.

Rodrigo.

----- Original Message ----- From: <gmc107@york.ac.uk>
To: <statalist@hsphsun2.harvard.edu>
Sent: Saturday, August 18, 2007 6:41 PM
Subject: st: Two step estimation and standard error computation



Dear statalisters ,
I was wondering whether somebody knows how to implement in Stata Vella and
Verbeek's covariance matrix estimation practical impementation which is
given in (p.259-260: Appendix A) in their Journal of econometrics (1999
article:) "2 step estimation of panel data models with censored endogenous
variables and selection bias".
The only thing that's readily available in Stata for linear models is the
hc3 (heteroskedasticity) robust standard errors option but this doesn't
allow for the endogeneity correction terms and in the event the two terms
are jointly statistically significant then the standard errors will be
deflated and significance lebels overstated. Would simply going for say 500
boostrap replications that would be sufficient or would that be a very na´ve
approach? I have seen some papers that argue that this should be
sufficient+avoids the computational perplexities.
Would be most grateful of any help.

Georgios


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