Bayesian functional models for population forecasting

Han Lin Shang, Arkadiusz Wiśniowski, Jakub Bijak, Peter WF Smith, James Raymer

    Research output: Chapter in Book/Report/Conference proceedingChapter


    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 many 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
    EditorsMarco Marsili and Giorgia Capacci
    Place of PublicationRome
    PublisherIstituto Nazionale di Statistica
    ISBN (Print)9788845818103
    Publication statusPublished - 2014


    Dive into the research topics of 'Bayesian functional models for population forecasting'. Together they form a unique fingerprint.

    Cite this