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


From   Tak-wai Chau <[email protected]>
To   [email protected]
Subject   Re: st: Estimating a model allowing for AR(1) in residuals withweights in panel
Date   Wed, 12 Apr 2006 14:00:56 -0400

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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