I want to compare how well different statistical methods (e.g. "ordinary" linear growth exponentially weighted regression as opposed to robust versions like Huber, Tukey) cope with problems in time series such as outliers, heavy tails, shift.

Which measures can I look at apart from standard error of the forecast or MSE?
How else can I compare the efficency of the different methods?

Any ideas would be much appreciated!
Thanks!