On Sat, 7 Feb 2009, Riccardo (Jack) Lucchetti wrote:
On Sat, 7 Feb 2009, Sven Schreiber wrote:
> On 07.02.2009 20:35, Allin Cottrell wrote:
>> On that basis, we calculate
>>
>> se(k) = sqrt(k*s2)
>>
>> where k = 1,2,...n is the forecast step and s2 is the square of
>> the Standard Error of the Regression.
>>
>> If this is rubbish -- or if there is a clearly better way to
>> proceed -- I hope Jack or Sven will tell me so!
>>
> Indeed it seems to me that this is not entirely correct in general; with
> this formula the forecast uncertainty grows linearly (and thus w/o
> bounds) irrespective of the property of the considered variable. But for
> a mean-stationary variable the long-run forecast is just its mean, and
> the associated confidence interval is finite...
The key is "mean-stationary" . Remember we're talking about the
forecasts on the level, while the statistical model is in
differences...
I think I'm with Jack on this: if the user doesn't believe the
forecast error should grow without limit (as it does under the
approach I outlined) then he/she shouldn't be estimating a model
in differences?
Allin.