Hi,
two remarks about the distribution which is used to derive the forecast
confidence intervals. Consider the following forecast:
<hansl>
open denmark
ols LRM 0 LRM(-1 to -2)
dataset addobs 5
fcast 1987:4 1988:4 # --plot=display
</hansl>
In the printout I see:
"For 95% confidence intervals, t(50, 0.025) = 2.009"
And indeed, the width of the confidence intervals seems to be twice the
reported standard error (0.03367 for step h=1) times 2.009.
However, there are several potential issues here I think:
- Gaussian innovations are implicitly assumed AFAICS. This is of course
a widespread assumption but isn't made explicit (and could be wrong).
- The t-distribution for a small estimation sample is quite ad hoc.
Maybe it would be a good idea to give the user an option to switch to a
plain Gaussian.
cheers,
sven