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Re: st: RE: bootstrapping standard errors with several estimated regressors


From   "Erasmo Giambona" <e.giambona@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: RE: bootstrapping standard errors with several estimated regressors
Date   Mon, 9 Jul 2007 11:25:02 +0200

Thanks Maarten. Unfortunately, I have not been able to find any good
reference on the issue. Anyone suggestions would be appreciated,
Erasmo

On 7/6/07, Maarten Buis <M.Buis@fsw.vu.nl> wrote:
I have no direct answer for you, except that in the example below exactly the opposite happens. Not that I claim that this should be generally true.

*------------- begin example ---------------
sysuse auto, clear
factor wei length headroom trunk, factors(1)
predict si
reg mpg si foreign

drop si
capture program drop boo
program define boo, rclass
       factor wei length headroom trunk, factors(1)
       predict si
       reg mpg si foreign
       return scalar si = _b[si]
       return scalar for = _b[foreign]
end

bootstrap si=r(si) for=r(for), reps(1000): boo
*------------- end example --------------

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/
-----------------------------------------

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu]On Behalf Of Erasmo Giambona
Sent: vrijdag 6 juli 2007 19:46
To: statalist
Subject: st: bootstrapping standard errors with several estimated regressors

Dear Statalist users,
 I am estimating a model which includes several estimated regressors
and two observed regressors. Therefore, I am bootstrapping the
standard errors. I had thought that bootstrapping would cause
statistical significance for all regressors to go down. However, I
noticed that statistical significance goes down for the estimated
regressors go down while it actually goes up for the 2 observed
regressors.
Is this what the theory predicts. Is there a good reference that
addresses this issue?
Any help would be appreciated.
Thanks very much,
Erasmo
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