Dear Kit
Thanks. When I tried -xtivreg2- the following is what
I got (note I have not got stata 10; I am using Stata
9.2):
.xtivreg2 pay yen (b4a2 = dhat) mek2 e1 a2-a1a5
e1-e5 e1 d2 a2 aa3 a2 e31 e33 e34 d1 zp2-zp6 rark2
ns1-ns4 ns6-ns12 fn1-fn6 fno1-fno6 ratwrk2 ahow1
kpr2-kpr4 inu1 ct1, re
unrecognized command: xtivreg2
r(199);
When I tried -xtivreg- I got as you know (but I do not
have anywhere near 2000 variables and option ( I also
tried issuing -preserve-; I still get the same error
message:
. xtivreg pay yen (b4a2 = dhat) mek2 e1 a2-a1a5
e1-e5 e1 d2 a2 aa3 a2 e31 e33 e34 d1 zp2-zp6 rark2
ns1-ns4 ns6-ns12 fn1-fn6 fno1-fno6 ratwrk2 ahow1
kpr2-kpr4 inu1 ct1
no room to add more variables
An attempt was made to add a variable that would
have resulted in more than 2048 or 2047 variables
(Stata reserves one variable for its own use).
You have the following alternatives:
1. Drop some variables; see help drop.
2. If you are using Stata/SE, increase maxvar;
see help maxvar.
r(900);
I cannot drop any variables as they are all needed and
I have only about 60 variables not > 2047 variables.
Any help will be greatly appreciated.
Thank you
Kit Baum wrote:
(1) Try the estimation using xtivreg2. If you have
anywhere near 2000 variables in the dataset,
-preserve- and drop some of those that are not in the
equation to be estimated.
(2) "Hausman test easily rejects the fixed effects
GLS." A Hausman test rejects when the "efficient"
estimator is found to be inconsistent. In the RE/FE
setup, RE is "efficient" under the null that X \perp u
and inconsistent otherwise. If the Hausman test is
rejecting anything, it is rejecting that the random
effects estimator is consistent.
It is not surprising that you could reject reject
pooled OLS, which ignores unit-level heterogeneity, in
favor of a FE model which incorporates it. But whether
you can assert that X \perp u in that model is another
issue.
Kit
Kit Baum, Boston College Economics and DIW Berlin
http://ideas.repec.org/e/pba1.html
An Introduction to Modern Econometrics Using Stata:
http://www.stata-press.com/books/imeus.html
On Feb 21, 2008, at 02:33 , statalist-digest wrote:
Thank you. As I mentioned I used -xtreg- for the
original equation as I believed that random-effects
GLS is a less biased estimator than OLS, since the
data are grouped across workplaces (Moulton, 1987). A
Hausman test easily rejects the fixed effects GLS.
I tried to perform the Hausman test by estimating the
model with -xtivreg- using re. But this is what I got:
. xtivreg pay yrsed (b4a2 = dhat) mnedwk2 e1a1
p1a2-p1a5 v2a1-v2a5 v14a1 dis2 h2a2 h2a3 h4a2 h3a1
h3a3 h3a4 f1a1 z2-z6 ratiopk2 n1-n4 n6-n12
fnonmana1-fn6 fno1-fno6 ratiofk2 aga1 k2-k4 in1 c1,
re
no room to add more variables
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