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From |
"Richard Boylan" <rtboylan@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: suest with large number of fixed effects |

Date |
Wed, 12 Sep 2007 16:44:38 -0500 |

Thanks, but I should have mentioned that a previous post on the statalist discusses how areg cannot be not be used with suest because those estimates are incorrect. So, if I have to assume that you are using an older version of STATA (7 or older) that allows you to use suest with areg. In the newer version of one tries to do that one obtains areg is not supported by suest On 9/12/07, Austin Nichols <austinnichols@gmail.com> wrote: > Richard Boylan-- > Indeed -areg- will mechanically give you an answer when combined with > -suest- but you should be aware that the cluster-robust estimator can > give downward-biased estimates of the true standard deviation of your > estimates, so a smaller p-value after -suest- may be suspect. Also, > just to be clear, -suest- will not give you more precisely estimated > coefficients since it will not change your estimated coefficients. > Under some circumstances it will give you better estimates of the > standard errors, and those circumstances include having a large number > of clusters and observations. How large? That depends... > > webuse abdata > areg ys n w k, a(id) > est sto ys > areg wage n w k, a(id) > est sto wage > suest wage ys, cluster(id) > > On 9/12/07, David Jacobs <jacobs.184@sociology.osu.edu> wrote: > > The command "areg" is designed for this purpose, but I'm not 100% > > sure that it has a score option or that it's matrix isn't equally large. > > > > Dave Jacobs > > > > At 11:11 AM 9/12/2007, you wrote: > > >I would like to estimate several regressions separately, but using > > >suest to obtain more precisely estimate coefficients > > > > > >So, what I would like to do is: > > > > > >xtreg y1 x1, i(id) fe > > >est store eq1 > > >xtreg y2 x2, i(id) fe > > >est store eq2 > > >xtreg y3 x3, i(id) fe > > >est store eq3 > > >suest eq1 eq2 eq3, cluster(id) > > > > > >Given that xtreg does not have a score option, it is discussed in > > >previous postings that one needs to estimate the model using a linear > > >regression with dummy variables. > > > > > >The problem I have is that I have 1000 fixed effects and thus the > > >matrix computed in suest is going to be way too large. > > >* > > >* For searches and help try: > > >* http://www.stata.com/support/faqs/res/findit.html > > >* http://www.stata.com/support/statalist/faq > > >* http://www.ats.ucla.edu/stat/stata/ > > > > > > * > > * For searches and help try: > > * http://www.stata.com/support/faqs/res/findit.html > > * http://www.stata.com/support/statalist/faq > > * http://www.ats.ucla.edu/stat/stata/ > > > * > * For searches and help try: > * http://www.stata.com/support/faqs/res/findit.html > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: suest with large number of fixed effects***From:*"Austin Nichols" <austinnichols@gmail.com>

**References**:**st: suest with large number of fixed effects***From:*"Richard Boylan" <rtboylan@gmail.com>

**Re: st: suest with large number of fixed effects***From:*David Jacobs <jacobs.184@sociology.osu.edu>

**Re: st: suest with large number of fixed effects***From:*"Austin Nichols" <austinnichols@gmail.com>

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