  We study the importance of group structure in grouped functional time series.
Due to the non-uniqueness of group structure, we investigate different
disaggregation structures in grouped functional time series. We address a
practical question on whether or not the group structure can affect forecast
accuracy. Using a dynamic multivariate functional time series method, we
consider joint modeling and forecasting multiple series. Illustrated by
Japanese sub-national age-specific mortality rates from 1975 to 2016, we
investigate one- to 15-step-ahead point and interval forecast accuracies for
the two group structures.
