Am 01.05.2008 14:03, Riccardo (Jack) Lucchetti schrieb:
On Thu, 1 May 2008, Sven Schreiber wrote:
> Am 01.05.2008 12:54, Riccardo (Jack) Lucchetti schrieb:
>
>>
>> Moreover, we have a slight inconsistency in the way we compute
>> things: $sigma uses the asymptotic formula (ie, E'E over T), while in
>> the displayed equations we use degrees-of-freedom corrected figures
>> for standard errors. I'm not overly bothered by this, but some may.
>
> What about $sigma in other contexts, is that asymptotic or
> dof-corrected? I think that should be made consistent.
I'm all for consistency in general, but this case is difficult. In OLS
estimation, for example, SSR/T and SSR/(T-k) are both consistent, but
the latter has the additional small advantage of being unbiased under
certain conditions, so that's traditionally what people use. I
personally think it's rather silly to worry about this when you have a
decent sample size; if you don't, well, I doubt very much you should be
doing inference _at all_.
In other contexts, Tobit models for example, you simply don't have a
choice. In my view, the really important thing is that you know which
formula is used in each case, so that if you feel like re-computing
$sigma to your taste, you have the tools to do it.
I just meant "consistent definition" across the various contexts of
$sigma, not consistent in the statistical sense. So if you are saying
$sigma for Tobit models is w/o dof correction out of necessity but for
OLS it currently is dof-corrected, then I would suggest the rule:
"$sigma has a dof correction if at all feasible". That would mean dof
correction for the VAR/VECM $sigma. BTW, I remember we had a discussion
in the context of the vcv of the betas in the VECM, but I don't remember
the result. Is there a dof correction there in the end? (I know I know
it's probably in the manual...)
cheers,
sven