Comparison of seasonal estimation methods in multi-item short-term forecasting

This paper addresses the issue of estimating seasonal indices for multi-item, short-term forecasting, based upon both individual time series estimates and groups of similar time series. This development of the joint use of individual and group seasonal estimation is extended in two directions. One class of methods is derived from the procedures developed for combining forecasts. The second employs the general class of Stein Rules to obtain shrinkage estimates of seasonal components. A comparative evaluation has been undertaken of several versions of these methods, based upon a sample of retail sales data. The results favour these newly developed methods and provide some interesting insights for practical implementation.