Pub. online:4 Jan 2022Type:Statistical Data ScienceOpen Access
Journal:Journal of Data Science
Volume 20, Issue 3 (2022): Special Issue: Data Science Meets Social Sciences, pp. 303–324
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.