Thanks, this is useful.
-sven
On 07/10/2012 09:14 AM, JOSE FRANCISCO PERLES RIBES wrote:
Dear Gretl list
Finally I put my question on the differences observed in the p-value in
the Gretl ADF test, in Eviews and R package fUnitRoots forums
(r-sig-finance).
From Eviews team I have obtained the following answer, that I put on the
list (on the advice of Sven) if interest for the whole list
"Your reading of MacKinnon's comment about finite sample ADF values is
generally correct, though there is no evidence presented that they are
better or worse than the asymptotic values for the t-stat. I will point
out that the one case (z-stat) where MacKinnon strongly cautions against
using the finite sample values is not a test statistic that EVIews
produces for the ADF (though we do report related tests in the
cointegration context -- perhaps in this case we shouldn't...). I think
that the jury is still out on whether the t-statistic finite sample or
asymptotic values are better.
To provide some context, the basic idea is that that the finite sample
critical values are based on a set of simulations for which MacKinnon
did not employ ADF regressions. Were he to have run some with ADF
corrections he might very well have found that the finite sample DF
results were closer than the asymptotic results in some cases (but
understandably he did not run those simulations as the number of
simulations that he did run is already quite large and it is not clear
the best way to set up the correlation structure for evaluating the test
statistics).
The most compelling argument for continuing to use the finite sample
values for the ADF is, I think, one of comparability. One concern with
switching over to the asymptotic values for ADF tests is that if you
were to run a DF test for a smallish sample and then add a single ADF
lag, you are more likely to get quite different results if we were to
switch to using the asymptotic values--and in the absence of simulation
results it is not clear whether this is a good or a bad thing. It would
then be difficult to evaluate whether the difference in results is the
result of the autocorrelation correction or the result of different
critical values (or both). With either the finite sample or asymptotic
choice, one is in a bit of a bind in the absence of finite sample
simulations. By sticking with the finite sample values we are at least
holding one thing somewhat constant...this may or may not be better...
As I write this, it occurs to me that one possibility would be to report
both values. That has it's own set of issues but would then allow users
to pick what they want to evaluate. I'll put it on a list of things to
consider."
From the forum fUnitRoots still awaiting a response...
To be continued...
José F. Perles
University of Alicante (Spain)
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