Am 05.07.2012 16:02, schrieb Allin Cottrell:
On Thu, 5 Jul 2012, JOSE FRANCISCO PERLES RIBES wrote:
> I'm doing a unit root test ADF with Gretl on a series of tourism market
> share of Spain specified with constant and trend.
> By comparing the results with Eviews or R (package fUnitRoot) I get
> the same
> t-statistic, but although both programs indicate that the critical values
> are McKinnon (1996) MacKinnon, J. G. (1996) "Numerical distribution
> functions for unit root and cointegration tests", Journal of Applied
> Econometrics 11: 601-618.
> p-values of the test are very different in either case .
> Gretl: t = -3.62 p-value 0.02 asymptotic
> Eviews t = -3.62 p-value (one-sided) = 0.04 which is the same value
> obtained in R.
You should find that if you do a non-augmented Dickey-Fuller test (no
lagged differences) the P-values given by gretl agree with those from
R's fUnitRoots package. If you run an augmented test, gretl
automatically gives the asymptotic P-value, while it appears that
fUnitRoots is giving the finite-sample value for the sample size used
(and I suppose Eviews is doing the same). I verified this on some
examples, using MacKinnon's urcdist program.
I believe gretl is doing the right thing here. In his 1996 JAE article
MacKinnon says, "Since the finite-sample P-values are valid only for
non-augmented Dickey-Fuller tests, it is probably wise to ignore them
for ADF tests..."
I'm not sure if the conventional wisdom on this has changed after 1996,
but this looks like a great example of how thoughtful even the details
in gretl are. I very much doubt that R's fUnitRoots has a similar
justification in the background, let alone Eviews, but it would be
interesting to find out -- Jose, if you get an answer from those people,
it would be nice if you could post it here as well.
cheers,
sven