R has another version adf.test {tseries}
which does have "two-sided" alternative
I think somebody can reproduce it in a package
As for me, gretl has excellent correspondence
with most popular textbooks
I use gretl for unit roots even in my R classes
I even do not know where explosive processes
is used even in PhD courses
Oleh
6 листопада 2018, 00:34:59, від "Allin Cottrell" <cottrell(a)wfu.edu>:
On Mon, 5 Nov 2018, Sven Schreiber wrote:
please consider this:
<hansl>
open wgmacro.gdt
adf 0 log(income) --ct # gives pos. test stat
eval urcpval($test, $nobs, 1, 3)
</hansl>
The issue is that the AR coeff is slightly explosive (1.003), which is
not in the rejection region of the one-sided DF test. So the test stat
is positive instead of negative, but the p-value given by Gretl is
strictly <1 (0.9971). I know that philosophically a one-sided test is
actually trickier than we tell the students, so I don't mind whether the
"correct" result is 1 or NA, but I'm pretty sure it shouldn't be
<1.
It seems that Gretl just uses the absolute value of the test stat and
thus doesn't differentiate between the left and the right side.
Summary, from my point of view: We're now clear that gretl is not
ignoring the sign of the test statistic, and is doing what R, Stata
and Eviews also do, namely reporting an estimate of the CDF of the
relevant distribution evaluated at the observed test statistic.
Although I think this convention is too strong to be bucked, I do
think that Sven has a point. It's not specific to ADF tests, but
pertains more generally to p-values for one-sided tests. It's not
clear to me that p-values are well defined for values of the test
statistic that are not at all adverse to the null -- unless there's
unique such value, as in a two-sided test, in which case we say it
has a p-value of 1 (the estimate coincides precisely with the claim
made by the null).
Allin
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