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From |
Austin Nichols <austinnichols@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: Re: st: Bootstrap with xtregar fails |

Date |
Tue, 15 Jan 2013 11:18:46 -0500 |

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 <njcoxstata@gmail.com> wrote: > But Vasja said that he has just one panel... > > Nick > > On Tue, Jan 15, 2013 at 3:32 PM, Austin Nichols <austinnichols@gmail.com> wrote: >> wasis dat <vasja.sivec@gmail.com>: >> -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 <vasja.sivec@gmail.com> 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 * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: Re: st: Bootstrap with xtregar fails***From:*Nick Cox <njcoxstata@gmail.com>

**References**:**Re: Re: st: Bootstrap with xtregar fails***From:*wasis dat <vasja.sivec@gmail.com>

**Re: Re: st: Bootstrap with xtregar fails***From:*Austin Nichols <austinnichols@gmail.com>

**Re: Re: st: Bootstrap with xtregar fails***From:*Nick Cox <njcoxstata@gmail.com>

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