Grouped functional time series forecasting: An application to age-specific mortality rates

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dc.contributor.authorShang, Hanlin
dc.contributor.authorHyndman, Rob
dc.date.accessioned2020-01-07T06:02:53Z
dc.date.issued2017
dc.date.updated2019-08-18T08:16:28Z
dc.description.abstractAge-specific mortality rates are often disaggregated by different attributes, such as sex, state and ethnicity. Forecasting age-specific mortality rates at the national and sub-national levels plays an important role in developing social policy. However, independent forecasts at the sub-national levels may not add up to the forecasts at the national level. To address this issue, we consider reconciling forecasts of age-specific mortality rates, extending the methods of Hyndman et al. (2011) to functional time series, where age is considered as a continuum. The grouped functional time series methods are used to produce point forecasts of mortality rates that are aggregated appropriately across different disaggregation factors. For evaluating forecast uncertainty, we propose a bootstrap method for reconciling interval forecasts. Using the regional age-specific mortality rates in Japan, obtained from the Japanese Mortality Database, we investigate the one- to ten-step-ahead point and interval forecast accuracies between the independent and grouped functional time series forecasting methods. The proposed methods are shown to be useful for reconciling forecasts of age-specific mortality rates at the national and sub-national levels. They also enjoy improved forecast accuracy averaged over different disaggregation factors. Supplemental materials for the article are available online.en_AU
dc.description.sponsorshipThis research is funded by a research school grant from the Australian National University.en_AU
dc.format.mimetypeapplication/pdfen_AU
dc.identifier.issn1061-8600en_AU
dc.identifier.urihttp://hdl.handle.net/1885/196572
dc.language.isoen_AUen_AU
dc.publisherAmerican Statistical Associationen_AU
dc.rights© 2017 American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North Americaen_AU
dc.sourceJournal of Computational and Graphical Statisticsen_AU
dc.titleGrouped functional time series forecasting: An application to age-specific mortality ratesen_AU
dc.typeJournal articleen_AU
local.bibliographicCitation.issue2en_AU
local.bibliographicCitation.lastpage343en_AU
local.bibliographicCitation.startpage330en_AU
local.contributor.affiliationShang, Hanlin, College of Business and Economics, ANUen_AU
local.contributor.affiliationHyndman, Rob, Monash Universityen_AU
local.contributor.authoremailu5506744@anu.edu.auen_AU
local.contributor.authoruidShang, Hanlin, u5506744en_AU
local.description.embargo2037-12-31
local.description.notesImported from ARIESen_AU
local.identifier.absfor010401 - Applied Statisticsen_AU
local.identifier.absseo970116 - Expanding Knowledge through Studies of Human Societyen_AU
local.identifier.ariespublicationu1027566xPUB17en_AU
local.identifier.citationvolume26en_AU
local.identifier.doi10.1080/10618600.2016.1237877en_AU
local.identifier.scopusID2-s2.0-85018210758
local.identifier.thomsonID000400182800010
local.identifier.uidSubmittedByu1027566en_AU
local.publisher.urlhttps://www.routledge.com/en_AU
local.type.statusPublished Versionen_AU

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