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Re: Re: st: Bootstrap with xtregar fails

From   Nick Cox <>
Subject   Re: Re: st: Bootstrap with xtregar fails
Date   Tue, 15 Jan 2013 15:07:12 +0000

Thanks for the explication.

I do not address the fact that your variables are generated.

Naturally I sympathise with your wanting sensible standard errors, but
I remain unconvinced on general grounds that -bootstrap- can provide
what you want when there is a dependence structure. You haven't given
me any reason to suppose that it would.

Also, as a frequent reviewer of papers and FWIW a journal editor too,
I can say that I never give credit for people doing the wrong thing
for the right reason.

What seems to be indicated is that you simulate a variety of outcomes
using a generating process similar to that you postulate when using
-xtregar- and get an idea of variability that way. That would imply
some custom programming but commands like -simulate- exist to make
things easier.


On Tue, Jan 15, 2013 at 2:45 PM, wasis dat <> 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).
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