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Re: st: bootstrap and XTIVREG2


From   "Erasmo Giambona" <e.giambona@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: bootstrap and XTIVREG2
Date   Fri, 14 Sep 2007 14:35:58 -0400

Dear Stas,
As you expected most of my results are unchanged. However, one of the
variable looses significance. The number of cluster that I have is
quite large (about 1600). Can it be bootstrapping is eliminating the
effect of some outliers?
Thanks for any suggestions,
Erasmo

On 8/29/07, Stas Kolenikov <skolenik@gmail.com> wrote:
> On 8/29/07, Austin Nichols <austinnichols@gmail.com> wrote:
> > Erasmo--
> > At a minimum, you probably need the cluster() and idcluster() options
> > on -bootstrap- (see -help bootstrap-) so you are not resampling from N
> > obs, but M clusters (each panel) and there is a new id variable to
> > supply to your cluster() option on -xtivreg2-.  Something like:
> >
> > bootstrap, r(1000) cl(gvkey) id(g): xtivreg2 `v', first cl(g) fe i(g)
> >
> > might work.
> > As no doubt Stas Kolenikov will point out, -bootstrap- is not
> > guaranteed to solve your problems.
>
> I'll just sob in despair...
>
> Well for this one it may not be that terribly bad, as this is still
> some sort of M-estimation/estimating equations setup, and the
> regularity conditions such as smooth derivatives may be reasonably
> easy to establish, but then I'd be surprised if the bootstrap would
> give a result substantially different from -xtivreg2-'s original
> sandwich estimator. If it did, then it means the asymptotics is not
> there yet for the sample size you have at hand, and then neither is a
> satisfactory answer. E.g. if you had 15 clusters then your estimation
> procedure is pretty much guaranteed to go astray either way no matter
> how many observations you have in each cluster.
>
> --
> Stas Kolenikov, also found at http://stas.kolenikov.name
> Small print: Please do not reply to my Gmail address as I don't check
> it regularly.
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