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Australia's uncertain demographic future

Author

Listed:
  • Tom Wilson

    (Independent researcher)

  • Martin Bell

    (University of Queensland)

Abstract

The techniques of probabilistic population forecasting are increasingly being recognised as a profitable means of overcoming many of the limitations of conventional deterministic variant population forecasts. This paper applies these techniques to present the first comprehensive set of probabilistic population forecasts for Australia. We stress the disadvantages of directly inputting net migration into the cohort component model in probabilistic forecasting, and propose a gross migration flows model which distinguishes between permanent and non-permanent immigration and emigration. Our forecasts suggest that there is a two thirds probability of Australia’s population being between 23.0 and 25.8 million by 2026 and between 24.4 and 31.8 million by 2051. Comparisons with the latest official population projections of the Australian Bureau of Statistics are made.

Suggested Citation

  • Tom Wilson & Martin Bell, 2004. "Australia's uncertain demographic future," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 11(8), pages 195-234.
    • Handle: RePEc:dem:demres:v:11:y:2004:i:8
    DOI: 10.4054/DemRes.2004.11.8
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    References listed on IDEAS

    as
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    Cited by:

    1. Booth, Heather, 2006. "Demographic forecasting: 1980 to 2005 in review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 547-581.
    2. Demirel, Duygun Fatih & Basak, Melek, 2019. "A fuzzy bi-level method for modeling age-specific migration," Socio-Economic Planning Sciences, Elsevier, vol. 68(C).
    3. Alho, Juha, 2008. "Aggregation across countries in stochastic population forecasts," International Journal of Forecasting, Elsevier, vol. 24(3), pages 343-353.
    4. Hyndman, Rob J. & Booth, Heather, 2008. "Stochastic population forecasts using functional data models for mortality, fertility and migration," International Journal of Forecasting, Elsevier, vol. 24(3), pages 323-342.
    5. Nasibeh Esmaeili & Mohammad Jalal Abbasi-Shavazi, 2024. "Forecasting number of births and sex ratio at birth in Iran using deep neural network and ARIMA: implications for policy evaluations," Journal of Population Research, Springer, vol. 41(4), pages 1-21, December.

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    More about this item

    Keywords

    population forecasting; Australia; migration; uncertainty; migration forecasts;
    All these keywords.

    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • Z0 - Other Special Topics - - General

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