Bayesian functional models in population forecasting

Han Lin Shang*, Arkadiusz Wisniowski, Jakub Bijak, Peter Smith, James Raymer

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

Abstract

We explore the functional modelling approach to population forecasting within the wider context of Bayesian predictions and model uncertainty. The functional modelling approach can be used to analyse and forecast different age- and time-specific components for fertility, mortality and migration. For each of these demographic processes, we perform Bayesian model averaging across the outcomes of two functional models to take into account model uncertainty. We illustrate the method with a population forecast for the United Kingdom for 2010-2030. We conclude that regularities in age profiles of demographic processes, where available, provide important information for the forecasts and as such should be included in the forecasting process.
Original languageEnglish
Title of host publicationProceedings of the Sixth Eurostat/Unece Work Session on Demographic Projections
Place of PublicationRoma
PublisherIstituto nazionale di statistica
Pages313-325
Number of pages13
ISBN (Electronic)9788845818103
ISBN (Print)9788845818110
Publication statusPublished - 2014
Externally publishedYes
EventSixth Eurostat/Unece Work Session on Demographic Projections - Rome, Italy
Duration: 29 Oct 201331 Oct 2013

Conference

ConferenceSixth Eurostat/Unece Work Session on Demographic Projections
CountryItaly
CityRome
Period29/10/1331/10/13

Keywords

  • Age schedules
  • Bayesian model selection
  • Functional models
  • LeeCarter model
  • Model uncertainty
  • Population forecasting

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