An Empirical Study of Seasonal Unit Roots in Forecasting

We assess the usefulness of pre-testing for seasonal roots, based on the HEGY approach, for outof-sample forecasting. We show that if there are shifts in the deterministic seasonal components then the imposition of unit roots can partially robustify sequences of rolling forecasts, yielding improved forecast accuracy. We illustrate with two empirical examples where more accurate forecasts can be obtained by imposing more roots than is warranted by HEGY. We address the issue of assessing forecast accuracy when predictions of any one of a number of linear transformations may be of interest.