  When generating social policies and pricing annuity at national and
subnational levels, it is essential both to forecast mortality accurately and
ensure that forecasts at the subnational level add up to the forecasts at the
national level. This has motivated recent developments in forecasting
functional time series in a group structure, where static principal component
analysis is used. In the presence of moderate to strong temporal dependence,
static principal component analysis designed for independent and identically
distributed functional data may be inadequate. Thus, through using the dynamic
functional principal component analysis, we consider a functional time series
forecasting method with static and dynamic principal component regression to
forecast each series in a group structure. Through using the regional
age-specific mortality rates in Japan obtained from the Japanese Mortality
Database (2019), we investigate the point and interval forecast accuracies of
our proposed extension, and subsequently make recommendations.
