On Sun, 23 Nov 2008, Sven Schreiber wrote:
Am 23.11.2008 17:15, Allin Cottrell schrieb:
>
> Mean dependent var 4.538837 S.D. dependent var 0.243346
> Sum squared resid 1.617235 S.E. of regression 0.189575
> R-squared 0.430985 Adjusted R-squared 0.405696
> F(2, 45) 17.04203 P-value(F) 3.09e-06
> Log-likelihood 13.26255 Akaike criterion -20.52509
> Schwarz criterion -14.91149 Hannan-Quinn -18.40371
> rho 0.018627 Durbin-Watson 1.960299
>
> (with the last row omitted for non-time series).
>
Why actually have both the rho and the DW stat? (Assuming rho is the
first-order autocorrelation coeff, right?)
Right.
I know there are historical reasons for DW, but hey: change yes we
can
... ;-) Sometimes it seems ridiculous to me that in every econometrics
course you have to talk a lot about the historical DW test just because
it always appears in the standard estimation output.
What I usually teach my students is that DW has just historical importance
and that if you want to test for autocorrelation the LM (Godfrey) test is
a much better tool. So, in principle I agree with you 100%. The only cases
(that I can think of right now) when I may want to actually see the DW
statistic are:
1) as always, for comparison/replication purposes
2) in the context of teaching what a spurious regression is (Granger &
Newbold's famous "rule of thumb")
3) in the context of cointegration tests, but IMHO nowadays Sargan and
Bhargava's idea is quite outdated too.
Hence, I wouldn't miss DW very much personally. If I could have it my way,
I'd show an LM test statistic (with df equal to the dataset's periodicity)
and the associated p-value instead. However, I can also see the case for
keeping DW in for those who prefer a more "traditional" approach.
Next, an unrelated suggestion: What do you think about grouping the
adjusted R-squared and the info criteria together, since conceptually
they are more or less the same thing.
No big objection here; R^2 and adj. R^2 fit together nicely IMHO for OLS,
but we have several estimation methods (eg probit) for which we don't have
the two, so it may make sense to split them. However, the log-likelihood
is the essential ingredient of the information criteria, so I'd like to
keep it where it is now.
And a minor thing that can also be changed later: I think all
information criteria should have the criterion suffix and therefore it
should be "Hannan-Quinn crit.".
Agreed. Once we're at it, I'd like to express my preference for the
"AIC",
"BIC" and "HQC" acronyms, which shouldn't necessarily be
translated.
Riccardo (Jack) Lucchetti
Dipartimento di Economia
Università Politecnica delle Marche
r.lucchetti(a)univpm.it
http://www.econ.univpm.it/lucchetti