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Re: Re: st: Bootstrap with xtregar fails
From
Austin Nichols <[email protected]>
To
[email protected]
Subject
Re: Re: st: Bootstrap with xtregar fails
Date
Tue, 15 Jan 2013 10:32:30 -0500
wasis dat <[email protected]>:
-bootstrap- does acknowledge the error dependence if you resample
clusters instead of obs, but you need to tell -xtregar- what to do
about resampled clusters. See e.g.
http://www.stata.com/statalist/archive/2006-11/msg00025.html or
http://www.stata.com/statalist/archive/2007-08/msg01135.html or
http://www.stata.com/statalist/archive/2011-04/msg01348.html or
http://www.stata.com/statalist/archive/2009-08/msg01584.html or
hundreds of other posts on the topic. In any case, the cluster-robust
SE implemented by -xtreg, robust- will deal with serially correlated
errors in a more robust way, so I don't see what you hope to gain from
-xtregar- (which gives you different estimates, ostensibly more
efficient, but tends to perform worse in simulations).
webuse grunfeld, clear
xtset company time
cap prog drop bsxtar
prog bsxtar, eclass
xtset i time
xtregar invest mvalue kstock
end
bs, cluster(company ) idcluster(i):bsxtar
On Tue, Jan 15, 2013 at 9:45 AM, wasis dat <[email protected]> wrote:
> Dear Jay V. and Nick C.,
>
> Thank you for your kind responses!
>
> I understand that bootstrap doesn't acknowledge the dependence
> structure in the panel data. I do not have a clear cluster structure,
> just a big panel. The reason why I would still like to use bootstrap
> is because my y and x are generated regressors (both T and N are
> large), and when y and x are generated regressors they can be
> imprecisely estimated. The usual formulas for standard errors do not
> account for this. This is why I attempted to bootstrap the standard
> errors. Let me say that when ignoring autocorrelation in the residuals
> and estimating a FE regression the bootstraped and the calculated
> standard errors are practically equal. Of course I have residual
> autocorrelation, so I wish to estimate with model with -xtregar. I get
> results that are in accordance with my theory, but when presenting a
> paper somebody might object that my y and x are generated and so my
> standard errors and significance tests are not valid. I wish to avoid
> this objection by rather estimating the standard errors using
> bootstrap.
>
> I hope that the above explanation is clear and makes sense. I would be
> grateful If you could point me in the right direction (if there is on
> of course).
>
> Kind regards,
> Vasja
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