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st: Re: STATA heteroscedasticity test

From   Kit Baum <>
To   Svetlana Jefimova <>
Subject   st: Re: STATA heteroscedasticity test
Date   Mon, 16 Mar 2009 08:55:39 -0400

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 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   |
An Introduction to Stata Programming   |
An Introduction to Modern Econometrics Using Stata   |

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

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