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