If your series is nonstationary, why do you think ARMA(1,1)
is a plausible model? Am I missing something?
Nick
[email protected]
Alexander Gelber wrote
> Thank you, this was quite helpful.
>
> However, I understand that conditional MLE is inappropriate for a
> nonstationary series, so that it would not be a good idea to use the
> "condition" option. If my series is nonstationary, what alternatives
> would I have for estimating an ARMA(1,1) with multiple panels?
>
> Best,
>
> Alex
>
> On Tue, 22 Aug 2006, Vince Wiggins, StataCorp wrote:
>
> > Many thanks for this extremely helpful suggestion!
> >
> > Regarding the conditional ML estimator for -arima- models,
> Alexander Gelber
> > <[email protected]> goes on to ask,
> >
> > > When you say that the "conditional estimator is conditional on
> > > simple rules for starting the process at the beginning of the
> > > sample," what simple rules or assumptions, in particular, are you
> > > referring to? I have had trouble finding the answer using Stata
> > > help.
> >
> > Primarily that e_t=0 and u_t=0 in first periods before they
> can be estimated
> > from the data, see [TS] arima and the associated references
> for details.
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