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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 16:23:14 +0000

On Tue, Jan 15, 2013 at 4:18 PM, Austin Nichols <> wrote:
> Nick--
> Also "both T and N are
> large" so there is some confusion on the part of the OP.
> T is the # of time periods, and N is the number of panels AKA clusters
> for this case.
> On Tue, Jan 15, 2013 at 10:48 AM, Nick Cox <> wrote:
>> But Vasja said that he has just one panel...
>> Nick
>> On Tue, Jan 15, 2013 at 3:32 PM, Austin Nichols <> wrote:
>>> wasis dat <>:
>>> -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.
>>> or
>>> or
>>> or
>>> 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 <> 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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