Hello Greg,
you include your trend as a (Nx1) matrix and use this for 'dumvar'. The matrix
'dumvar' is just added to the VECM as deterministic regressors and while you
are referring to case 5, this is basically what you are after, if I am not
mistaken. But we aware that this implies a quadratic trend for the levels.
Best,
Bernhard
________________________________
Von: Grzegorz Konat [mailto:[email protected]]
Gesendet: Mittwoch, 30. März 2011 20:50
An: Pfaff, Bernhard Dr.; [email protected]
Betreff: Re: [R] VECM with UNRESTRICTED TREND
Hello Bernhard,
Thank You very much. Unfortunately I'm still not really sure how should
I use dummy vars in this context...
If I have a system of three variables (x, y, z), lag order = 2 and 1
cointegrating relation, what should I do? I mean, what kind of 'pattern' should
be used to create those dummy variables, what should they represent and how
many of them do I need?
Many thanks in advance!
Best,
Greg
2011/3/30 Pfaff, Bernhard Dr. <[email protected]>
Hello Greg,
you can exploit the argument 'dumvar' for this. See ?ca.jo
Best,
Bernhard
> -----Ursprüngliche Nachricht-----
> Von: [email protected]
> [mailto:[email protected]] Im Auftrag von Grzegorz
Konat
> Gesendet: Mittwoch, 30. März 2011 16:46
> An: [email protected]
> Betreff: [R] VECM with UNRESTRICTED TREND
>
> Dear All,
>
> My question is:
>
> how can I estimate VECM system with "unrestricted trend" (aka
> "case 5") option as a deterministic term?
>
> As far as I know, ca.jo in urca package allows for
"restricted trend"
> only [vecm
> <- ca.jo(data, type = "trace"/"eigen", ecdet = "trend", K =
> n, spec = "transitory"/"longrun")].
> Obviously, I don't have to do this in urca, so if another
> package gives the possibility, please let me know too!
>
> Thanks in advance!
>
> Greg
>
> [[alternative HTML version deleted]]
>
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