Re: st: Estimating a model allowing for AR(1) in residuals withweights in panel

[Tak-wai Chau <twchau@frontiernet.net>]

Dave,

Thanks!

I have also seen xtgls. Indeed what are the differences between xtpcse? 
Conceptually are there any difference in the adjustment method than xtregar?

Thanks!

Tak Wai Chau

David Jacobs wrote:

> Xtregar fe does allow for aweights (and probably fweights) if you use 
> two of the options for estimating the AR1 term.
>
> Check the help file or the manual.
>
> Probably, however, you will find that xtpcse will better suit your 
> needs if you have a large enough T for this estimator.  Note that Beck 
> and Katz do NOT recommend the PSAR1 option in xtpcse that estimates 
> different ar1 corrections for each case (or state in your study).
>
> Dave Jacobs
>
> At 09:50 AM 4/12/2006, you wrote:
>
> > Hi, Statalist users,
> >
> > I have a question about estimating a model allowing for AR(1) in 
> > residuals with weights.
> >
> > I have a dataset with state-year level data. The model is like this:
> >
> > y_it= a + b*policy_it + c_i + d_t + u_it
> >
> > where i stands for states and t states for year. policy is a policy 
> > implemented at different time in different states. c_i are state 
> > dummies (all states except one), and d_t are year dummies (all year 
> > except one), thus it is a difference in difference model. I also want 
> > to do this regression with state population size as weights.
> >
> > If u_it is serially correlated for each state, and I would like to 
> > allow for AR(1) for this u_it over time for each state to obtain 
> > parameter estimates, what should I do in Stata?
> >
> > I have thought of xtregar, fe, but it does not allow weights.
> >
> > BTW, I think the convention is that we have the autoregressive 
> > parameter the same across all states. I wonder if it is identified if 
> > I allow different autoregressive parameters in different states.
> >
> > Thank you very much in advance!
> >
> > Tak Wai Chau
> >
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