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Datum: Mon, 25 Apr 2011 17:21:17 -0400 (EDT)
Von: Allin Cottrell <cottrell(a)wfu.edu>
An: Gretl list <gretl-users(a)lists.wfu.edu>
Betreff: Re: [Gretl-users] Activating HAC does not work
On Mon, 25 Apr 2011, Artur Tarassow wrote:
> I am just estimating some VAR models and would like to use robust
> standard errors. I am using the following lines to set up HAC...
You're right, these won't work to produce HAC for a VAR. It's not
exactly a bug, but a semi-deliberate decision ;-)
That is, some time ago we replaced equation-by-equation estimation
of VARs by a matrix method that does the whole thing in one go. At
that time I rebuilt the HC variance estimator for the new method
but I didn't bother rebuilding the HAC estimator. The reason
(other than laziness) was that you'd generally expect a VAR to
include enough lags to make HAC redundant. (Stock and Watson, for
example, include several VARS in their undergraduate textbook and
they always use a robust variance estimator, but they never use
HAC for VARs: I asked them why not, and that's the answer they
gave me.)
Anyway, it's easy enough to re-enable HAC for VARs if anyone
really wants it. But if I do so, what should the default be?
Should VARs be treated like regular models on time-series data
with regard to the --robust option (that is, HAC unless you "set
force_hc on")? Or vice versa (with a new VAR-specific "set"
variable, "force_hac")?
What do people think?
I tend to think it should be _possible_ to use HAC with VARs for demonstration purposes,
even if it may not be wise to use them for real applications.
The robust default should probably be the "wise" one, i.e. HC but not HAC.
However, there may also be a case to treat all time-series models alike, as you mention.
fwiw,
sven