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From | "Imberman, Scott A" <saimberm@central.uh.edu> |
To | "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu> |
Subject | st: RE: RE: testing coefficients across different ivreg models - large dataset with many variables |
Date | Thu, 10 Mar 2011 11:37:07 -0600 |
Thank's Mark. It didn't occur to me to de-mean the data first. That should work much faster. -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Schaffer, Mark E Sent: Thursday, March 10, 2011 11:27 AM To: statalist@hsphsun2.harvard.edu Subject: st: RE: testing coefficients across different ivreg models - large dataset with many variables Scott, You can stack the data as per Austin's posting to Statalist, and use the partial option of -ivreg2- to partial out the RHS fixed effects. Or - probably faster - you can use the within transformation (Ben Jann's -center- command is good for that) to demean your data and then stack. HTH, Mark > -----Original Message----- > From: owner-statalist@hsphsun2.harvard.edu > [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of > Imberman, Scott A > Sent: 10 March 2011 15:23 > To: 'statalist@hsphsun2.harvard.edu' > Subject: st: testing coefficients across different ivreg > models - large dataset with many variables > > Dear Statalisters, > > I'm trying to run the following models on two different subsamples > > ivreg y = (x = z), cluster(k) if j = 1 (model1) ivreg y = (x > = z), cluster(k) if j = 2 (model2) ivreg y = (x = z), > cluster(k) if j = 3 (model3) ivreg y = (x = z), cluster(k) > if j = 4 (model4) > > and I want to test if x(model 1) = x(model 2) = x(model 3) = > x(model 4) > > I know that I can't use suest with ivreg and I can't use > hausman due to the clustering. I'm trying to stack the data > and run a fully interacted model as suggested in this posting > > http://www.stata.com/statalist/archive/2010-04/msg00366.html > > but my dataset is very large and I have many fixed effects > and controls - about 1300 in each model, so 5200 in the fully > interacted model and so it's taking a very long time to run. > Is there any other way to test the coefficients across the > separate models? > > Thanks. > > Scott A. Imberman > Assistant Professor of Economics > University of Houston > 204 McElhinney Hall > Houston, TX 77204-5019 > > 713-743-3839 > simberman@uh.edu > http://class.uh.edu/faculty/simberman > > * > * 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/ > -- Heriot-Watt University is a Scottish charity registered under charity number SC000278. * * 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/