Dear Sven,
To reproduce the best GUI option
with a script, use
open wgmacro.gdt
y = log(income)
maxlag = 12*(nobs(y)/100)^0.25
adf maxlag y --c --ct --test-down
# now no signs of explosion
Oleh
5 листопада 2018, 18:09:59, від "Sven Schreiber" <svetosch(a)gmx.net>:
Am 05.11.18 um 16:53 schrieb Allin Cottrell:
On Mon, 5 Nov 2018, Sven Schreiber wrote:
>>
> Well, is a p-value a probability?
I think it's best described as: the probability, conditional on H0
being true, of obtaining a test statistic as unfavorable to the null
as the one actually observed, or more so.
I'm not against it. (As I said from the beginning, p-values can be
philosophically tricky, and one-sided tests, too.)
However, this still leaves the wrong result of urcpval(0,0,1...). I
think your definition also says it should be 1. Or to put it
differently: The current output can only be justified with your
definition if at the same time you consider explosive values (possibly
far away from 1) as _less_ unfavorable to the unit root H0 than the H0
value of 1 itself. I don't think we'd want that.
One could argue that if the test statistic is not even prima facie
unfavorable to the null (on the wrong side of the distribution), the
antecedent is not fulfilled and the p-value is therefore undefined.
Right. I think that's an important difference with one-sided tests,
where we cannot just focus on the null and forget about the rest.
I mean, one _could_ do the whole thing as a two-sided test, also
allowing explosion under the null. Obviously the null distribution would
be asymmetric. But that would also affect the critical values to the
left (stationary) side, because a part of the prob mass of the rejection
region would have to be shifted to the right.
(I'm not sure in the end / right now what gretl is actually doing
effectively.)
But before changing gretl's behavior I'd want to take a look
at what
other software does in this sort of case.
That is certainly wise.
thanks,
sven
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