Thank You very much again, and I feel terrible to disturb You with
one more question (hopefully last one), but what could we do to amke
the model homoscedastic? Or can we still use results obtained as
unbiased?
2009/3/16 Kit Baum <[email protected]>
Here is the Stata Tip, which should explain the interpretation of
these stats...
Kit Baum | Boston College Economics and 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
On Mar 16, 2009, at 12:40 , Svetlana Jefimova wrote:
Dear Mr Baum,
Thank You for a promt reply, which we found very useful!
However, we would like to ask again for a favour, as we have no
available funds to aquire Your work, we would like to ask if You
could send it to us(Stata Tip 38), or just help to interpret the
results we aquire from the robvar test :
W0 = 2.0786285 df(47, 165) Pr > F = .00038932
W50 = .88411755 df(47, 165) Pr > F = .68287619
W10 = 2.0786285 df(47, 165) Pr > F = .00038932
Does it mean we have heteroscedasticity or not?
Again, sorry for disturbunce!
Irina and Svetlana
p.s. We wrote to statalist, however, we have not received any reply
yet!
2009/3/16 Kit Baum <[email protected]>
<>
I am not aware of any test specifically for xtreg, re, but you could
certainly use robvar to test for groupwise heteroskedasticity:
webuse grunfeld
xtreg invest mvalue kstock
predict double eps, e
robvar eps, by(company)
Please see http://ideas.repec.org/a/tsj/stataj/
v6y2006i4p590-592.html for details.
With regard to collinearity, as the regressors do not change when
using fe vs. re vs. OLS, you could use any collinearity diagnostics
from pooled OLS to consider this. The one thing they would not pick
up is potential collinearity between the Xs and the dummy variables
implicit in the within transformation. High pairwise correlations
imply collinearity, but not vice versa. I would recommand
considering variance inflation factors (estat vif) for this purpose.
It is a good idea to address questions like this to Statalist, where
I and many others knowledgeable in the subject may answer.
Kit Baum | Boston College Economics and 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
On Mar 16, 2009, at 08:16 , Svetlana Jefimova wrote:
Dear Mr F Baum,
We are Svetlana Jefimova and Irina Beinarovica and we are writing to
You from Stockholm School of Economics in Riga (Latvia). We are
writing a bachelor thesis on the topic of FDI into Turkey. We are
researching the determinants affecting FDI inflow using gravity
model. Consequently, our approach is very similar to the work of
Ludo Cuyvers, Joseph Plasmans, Reth Soeng & Daniël Van den Bulcke
"Determinants of Foreign Direct Investment in Cambodia: Country-
Specific Factor Differentials", whom You advised on some STATA
commands. Therefore, we would like to ask for Your advice on several
issues on STATA commands for random effects model.
1) Is there any test for heteroscedasticity in the random effects
model? Wald statistics seems applicable just for fixed effects or
can be applicable as well?
2) Is there any test for multicollinearity in random effects model?
Or just "corr" is enough?
We would really appreciate Your help, as we do not know whom else to
approach!
Best reagrds,
Irina and Svetlana
