st: Panel data: Mixture of persistent and non-persistent errors.

["Steven Proud" <steven_proud@hotmail.com>]

Dear all,

I was wondering if anyone could help me.

I am trying to estimate a model in a panel, with time t and cross sectional 
variable s

F(st)=F(s)+e(st)+u(st)
where e(st)=p*e(st-1)+a(st)
where u(st) and a(st) are random error terms, and e(st) is a persistent
error of AR(1)
and F(s) is some underlying fixed effect.

Obviously if there wasn't a persistent term, then it would be easy to 
estimate as simply a fixed effect model, and similarly, if there wasn't a 
random shock term, I could simply estimate it using xtregar.  However, I'm 
slightly confused as to how to go about estimating it as it is.  I 
considered mixed models, but couldn't see how I could use these to estimate 
the model.

Any help would be very gratefully received.

Thanks in advance,

Steven Proud

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