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st: Serial Correlation


From   Robert Mills <R.Mills@sms.ed.ac.uk>
To   statalist@hsphsun2.harvard.edu
Subject   st: Serial Correlation
Date   Fri, 04 Feb 2011 15:46:39 +0000

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



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