Re: [Gretl-devel] some 'coint' interface details (and questions)
Am 13.11.2018 um 18:55 schrieb Allin Cottrell:
On Mon, 12 Nov 2018, Sven Schreiber wrote:
I may have "misspoken" in my original message on this in 2013. What we
actually did at that time, or not long thereafter, was to replace use
of the t-statistic as the (only) test-down criterion with a choice of
AIC, BIC or t-statistic, with AIC as the default. However, the
Modified AIC and BIC are specific to the ADF-GLS method. So, for
example, if you specify --test-down=BIC then MBIC is used with GLS,
plain BIC otherwise (and similarly for AIC).
OK
That's now rectified in git. I've also added a verbose switch.
...
OK, done in git.
Excellent, thanks!
> - adf and coint2 have a --seasonals option, but 'coint'
doesn't,
> according to the doc and the missing GUI item. Any particular reason
> why?
I guess not. But if we enabled it for "coint" would we want to include
the seasonals in the final regression (ADF test on uhat from the
cointegrating regression)? Or only in the initial ADF tests?
Well, I haven't talked about the initial ADF tests, because in my view
they are not part of the Engle-Granger test which presupposes I(1)
variables I'd say. (BTW Jack, take note how there is an almost
officially endorsed pre-testing problem here, when you wanted to get rid
of something much weaker in the BoxCoxFuncForm package ;-)
What I meant was in the same place where all other deterministics
appear, in the cointegrating regression. (And by implication then also
in the previous ADF tests, if selected, I guess.) Definitely not also in
the final residual test regression.
As an imaginary example, suppose you wanted to test a Fisher-type
relationship for cointegration. So you have a nominal interest rate
which is not seasonal, and then you have inflation which is seasonal.
(And for the various good reasons out there you don't want to use
seasonally adjusted data.) If you ran the Engle-Granger 1st stage
regression without seasonal dummies, your residuals inherit the seasonal
pattern. If you run the 2nd stage on them, chances are that that pattern
is mistaken for mean reversion -> potentially spurious cointegration.
(Yes, with enough lags the pattern could implicitly be modelled as
seasonal quasi-unit roots. But it would still be misspecified.)
thanks,
sven
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