Mark and Eddy,
Consider the Newey-West estimators if you want something robust to both autocorrelation and heteroskedasticity. You merely have to specify the appropriate lag length in the newey regression procedure.
Regards,
- Bob Yaffee
Robert A. Yaffee, Ph.D.
Senior Research/Statistical Consultant
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----- Original Message -----
From: Mark Schaffer <[email protected]>
Date: Wednesday, October 1, 2003 1:12 pm
Subject: Re: st: -robust- of time series data
> Eddy,
>
> Date sent: Wed, 1 Oct 2003 09:24:12 -0700 (PDT)
> From: Eddy <[email protected]>
> Subject: st: -robust- of time series data
> To: [email protected]
> Send reply to: [email protected]
>
> > A perhaps naive question: Does it make sense to use the -robust-
> > option (sandwitch variance estimate) in a ML estimation of a time
> > series model? What is the variance estimates robust to in this case?
> > Serial correlations? Thanks.
>
> They're still robust to heteroskedasticity but that's it. If you
> want robustness to serial correlation as well, you need something
> like -newey-.
>
> --Mark
>
> > Eddy
> >
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>
> Prof. Mark E. Schaffer
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