st: Serial Correlation

[Robert Mills <R.Mills@sms.ed.ac.uk>]

Hi all,

I'm performing a panel data regression across six countries and ten  
years in Stata.
I'm a little confused as to which methodology I should use, so far I have:

Run my regression in OLS, then used the Breush-Pagan Lagrange  
Multiplier Test, which rejected the null hypothesis that the variance  
of errors is zero (homoskedastic), thus OLS is inconsistent so I need  
to use Random or Fixed Effects
I've used a Hausman Test in which determined Random effects to be  
inconsistent, so I'm going to use Fixed Effects.
So my errors are heteroskedastic, and I need to correct for this - do  
I simply use robust standard errors in Stata? Or should I use the  
Huber-White Standard Errors? Or are these the same thing?
I've read that using Huber-White Standard Errors requires no serial  
correlation in error terms. To check for this, I need to perform a  
Durbin-Watson Test, and if I find serial correlation, use  
Prais-Winsten (GLS) to correct this.
However, can you use GLS for fixed effects? And if so, how do you do  
this in Stata?
Or, should I use Newey West Standard Errors, which correct for both  
heteroskedasticity and for serial correlation (AR 1). This would seem  
like the best option, but I'm not sure if you can use NW SE's for  
fixed effects? If so, how is this done in stata?
Thanks in advance for any help you may have!

Cheers,

Robert Mills



--
The University of Edinburgh is a charitable body, registered in
Scotland, with registration number SC005336.



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