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

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

Thanks a lot!

David Jacobs wrote:
> Check out the cites to the articles by Beck and Katz in the manual 
> entry on xtpcse.  They claim that xtgls shouldn't be used because its 
> estimates of the standard errors are far to optimistic.  And I've 
> certainly found comparatively enormous t-values when I've used xtgls, 
> so I suspect B & K are right.
>
> By the way, at least xtpcse and xtgls assume that you have at least 
> ten to twelve time periods.  I don't remember if there are similar 
> strictures on xtregar.
>
> Dave Jacobs
>
> At 02:00 PM 4/12/2006, you wrote:
>
> > 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
> > > >
> > > > *
> > > > *   For searches and help try:
> > > > *   http://www.stata.com/support/faqs/res/findit.html
> > > > *   http://www.stata.com/support/statalist/faq
> > > > *   http://www.ats.ucla.edu/stat/stata/
> > >
> > > *
> > > *   For searches and help try:
> > > *   http://www.stata.com/support/faqs/res/findit.html
> > > *   http://www.stata.com/support/statalist/faq
> > > *   http://www.ats.ucla.edu/stat/stata/
> >
> > *
> > *   For searches and help try:
> > *   http://www.stata.com/support/faqs/res/findit.html
> > *   http://www.stata.com/support/statalist/faq
> > *   http://www.ats.ucla.edu/stat/stata/
>
> *
> *   For searches and help try:
> *   http://www.stata.com/support/faqs/res/findit.html
> *   http://www.stata.com/support/statalist/faq
> *   http://www.ats.ucla.edu/stat/stata/

*
*   For searches and help try:
*   http://www.stata.com/support/faqs/res/findit.html
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/