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st: testing coefficients across different ivreg models - large dataset with many variables
From
"Imberman, Scott A" <[email protected]>
To
"'[email protected]'" <[email protected]>
Subject
st: testing coefficients across different ivreg models - large dataset with many variables
Date
Thu, 10 Mar 2011 09:23:20 -0600
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
[email protected]
http://class.uh.edu/faculty/simberman
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