Re: [Gretl-users] Restrictions on cointegration vectors
Riccardo (Jack) Lucchetti wrote:
We'd like to have some feedback from you cointegration junkies out there
(Sven, are you there? ;-)). One of the things we're currently uncertain
on is: when the restriction are applied, should the restricted model
estimated in full? On one hand, this seems a bit overkill: especially if
the restrictions are rejected, it makes little sense to compute the
short-run parameters and all the rest. On the other hand, if we don't
estimate the model, you don't get a covariance matrix for the restricted
\betas, since you need the residuals for that. [footnote: It must be
said, though, that I'm not sure at the moment whether the formulae for
the asymptotic covariance matrix for \beta still hold under linear
restictions.].
Well it's nice to hear that you guys are still active in the
cointegration area!
For a native implementation I'd say that the full model should be made
available. Not only because of the residuals, but also for forecasting
and possibly other stuff. After all, restricting a model is often not an
end in itself. I say "native" because my own py4gretl functions don't do
that either, because I'd say that's beyond the limits of the function
package thing (but the background python-numpy vecm class can do it of
course).
Re the covar matrix: which formula is used right now?
/sven