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re:st: R: RE: Quick doubt about the 2-way clustering option used in


From   Christopher Baum <[email protected]>
To   <[email protected]>
Subject   re:st: R: RE: Quick doubt about the 2-way clustering option used in
Date   Mon, 10 Jan 2011 08:48:35 -0500

<>
I didn't explain right, sorry me.  The problem is the second stage regression.
I am using -ivreg2-for the GMM estimation and in the first-stage F-stat is not missing like this:

. ivreg2 y t p c d (x w = h l m n o ) if sampleCM==1, gmm2s endog (x w) cluster (id deal )

2-Step GMM estimation
---------------------
Estimates efficient for arbitrary heteroskedasticity and clustering on id and deal
Statistics robust to heteroskedasticity and clustering on id and deal
Number of clusters (id) =         2903                Number of obs =     8194
Number of clusters (deal) =     6512                F( 51,  2902) =     1.90
                                                                         Prob > F      =   0.0001
Total (centered) SS     =   84.6613152             Centered R2   =  -0.3689
Total (uncentered) SS   =  85.85567541           Uncentered R2 =  -0.3499
Residual SS             =  115.8950279                Root MSE      =    .1189

All the tests show that my regressors are not endogenous and that my instruments are valid. 
And so, I back to my OLS regression results that had produced good estimations (and unbiased too).

You can use ivreg2 to estimate OLS models with 2-way clustering. Just remove the parens and put in x,w as exogenous variables, and drop the excluded instruments. 

Kit



Kit Baum   |   Boston College Economics & DIW Berlin   |   http://ideas.repec.org/e/pba1.html
                              An Introduction to Stata Programming  |   http://www.stata-press.com/books/isp.html
   An Introduction to Modern Econometrics Using Stata  |   http://www.stata-press.com/books/imeus.html


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