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From |
László Sándor <sandorl@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: AW: how to get slopes by clusters in a linear regression |

Date |
Tue, 25 Aug 2009 13:51:25 -0400 |

Austin, thanks for the code. I meant the latter approach, or even simpler, as you don't need interactions if you will estimate it cluster by cluster. In your code (without collecting the coefficients): qui reg mvalue kstock predict m2, res qui reg t kstock predict t2, res sortby c: reg m2 t2 The last can be made more useful with statsby, as Martin suggested. Thanks, Laszlo On Tue, Aug 25, 2009 at 1:31 PM, Austin Nichols<austinnichols@gmail.com> wrote: > László Sándor <sandorl@gmail.com>: > Using the FWL thm is the fastest way to go, probably, but I am not > clear on what you are actually doing. Is it something like one of the > approaches below? Or are you trying to get the individual-specific > coefs on the treatment dummy (harder, but can be done in Mata without > making any really big matrices)? > > webuse grunfeld, clear > set seed 1 > ren company c > keep if c<5 > qui ta c, g(d_) > g byte t=uniform()>.5 > forv i=1/4 { > g byte td_`i'=d_`i'*t > } > drop d_1 > reg mvalue kstock d_* td_* > est sto reg1 > egen double m1=mean(mvalue), by(c t) > g double mres=mvalue-m1 > egen double k1=mean(kstock), by(c t) > g double kres=kstock-k1 > areg mres kres, a(c) > est sto reg2 > egen c2=group(t c) > areg mvalue kstock, a(c2) > est sto reg3 > est table reg? > > Or are you doing something like: > > qui reg mvalue td_2 td_3 td_4 d_* kstock > predict m2, res > qui reg td_1 td_2 td_3 td_4 d_* kstock > predict t2, res > reg m2 t2 > > which still needs big matrices as the problem gets big? Make sure you > are getting the right answer in a small subsample before you go too > far... > > 2009/8/25 László Sándor <sandorl@gmail.com>: >> Thank you, Martin! >> >> I don't see how this could be used to estimate the model in a single >> command -- statsby still seem to break down the regression by >> clusters, without the intercluster restrictions on the >> controls/covariates. >> >> However, this led me to try to apply the Frisch-Waugh-Lowell theorem: >> I estimate the univariate regression of outcome on treatment by each >> cluster, I must only use the residuals for both after regressing them >> on the set of controls. >> >> If there is no other way, this seems to be doable. >> >> Thanks again! >> >> Laszlo >> >> On Tue, Aug 25, 2009 at 11:23 AM, Martin Weiss<martin.weiss1@gmx.de> wrote: >>> >>> <> >>> >>> >>> ****** >>> h statsby >>> ****** >>> >>> >>> HTH >>> Martin >>> >>> >>> -----Ursprüngliche Nachricht----- >>> Von: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von László Sándor >>> Gesendet: Dienstag, 25. August 2009 17:20 >>> An: statalist@hsphsun2.harvard.edu >>> Betreff: st: how to get slopes by clusters in a linear regression >>> >>> Dear Fellow Statalisters, >>> >>> I want to extend a fixed-effects-type model to allow for different >>> coefficients on a variable (actually a treatment dummy) by each >>> cluster I have. The richness of my data would allow for that. However, >>> I did not find a way to do it in Stata that would report (and collect) >>> the coefficients themselves. -xtmixed- doesn't seem to do so. I would >>> like to restrict the coefficients on controls to be equal across >>> clusters, so estimation by cluster is not a solution either. >>> >>> If there were a way that could collect the slopes to a single new >>> variable (with the same value for observations in the same cluster, >>> naturally), that would be the best. It would be great if I did not >>> need to introduce all the 1438 cluster-indicator variables and >>> interactions myself, and collect the coefficients. >>> >>> Thank you for any guidance in advance! >>> >>> Laszlo > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: AW: how to get slopes by clusters in a linear regression***From:*Austin Nichols <austinnichols@gmail.com>

**References**:**st: how to get slopes by clusters in a linear regression***From:*László Sándor <sandorl@gmail.com>

**Re: st: AW: how to get slopes by clusters in a linear regression***From:*László Sándor <sandorl@gmail.com>

**Re: st: AW: how to get slopes by clusters in a linear regression***From:*Austin Nichols <austinnichols@gmail.com>

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