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Demographic change and the needs-based planning of government services: projecting small area populations using spatial microsimulation

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Abstract

Changing patterns of longevity, fertility and migration in Australia have driven substantial changes in population age structure and household size and composition. Of the various dimensions of population change, population ageing is expected to present major challenges to the financing and sustainability of welfare state programs in industrialized countries. One key issue for many of these countries will be assessing where particular services will be required in the future. This paper outlines the application of new forecasting techniques that age a spatial microdataset to 2027. Two illustrative examples are provided to highlight the potential capacities of the new modelling approach for government service delivery planners. For many older people, ageing in place is important, but is more difficult when the person is single: and so the first illustrative application focuses on where aged single people will be living in 2027. The second application examines where future childcare places will be required given the projected growth in the number of children aged 3–4 years living in families where all parents are working. This information will be important for Government planners in deciding the best location for childcare places. The creation of synthetic small-area household microdata for future years offers great potential for a number of purposes, such as analysis of the likely future sociodemographic characteristics of individuals and families at the local level and assessment of the future geographic effect of alternative scenarios such as changes in labour force participation or fertility rates.

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Notes

  1. At the time of writing this paper new population projections had just been released and there was extensive debate about whether the growth in projected population was desirable and achievable.

  2. Unit record data (alternatively termed microdata) usually consist of thousands of individual records of persons, families or households in a computer readable format. Such microdata are the essential building blocks for microsimulation models, which in the past two decades have revolutionized the quality of information available to policy makers about the likely distributional effect of policy reforms that they are contemplating (Harding and Gupta 2007).

  3. Simply reweighting the small area dataset to future population projections and holding many of the characteristics of the individuals within the model constant, such as their marital status.

  4. It should be noted that we are still exploring opportunities to use the output from APPSIM to inform the ageing approach used with the SpatialMSM database. For example, APPSIM will provide information about the possible national growth in wealth for households with different characteristics and this could be used to help simulate future growth in wealth at the small-area level.

  5. Note that unemployed people are not considered in this analysis.

  6. Comparable maps for Sydney, Brisbane and the ACT can be requested from the authors.

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Acknowledgments

This research has been funded by a Linkage Grant from the Australian Research Council (LP775396), with our research partners on this grant being the NSW Department of Community Services; the Australian Bureau of Statistics; the ACT Chief Minister’s Department; the Queensland Department of Premier and Cabinet; Queensland Treasury; the Victorian Departments of Education and Early Childhood and Planning and Community Development; and Paul Williamson, University of Liverpool, UK. We gratefully acknowledge the support provided by these agencies and individuals. We would also like to thank Marcia Keegan for research assistance and to acknowledge the helpful comments of two anonymous referees.

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  1. National Centre for Social and Economic Modelling, University of Canberra, University Drive South, Canberra, ACT, 2601, Australia

    Ann Harding, Yogi Vidyattama & Robert Tanton

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  1. Ann Harding
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  2. Yogi Vidyattama
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Correspondence to Ann Harding.

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Harding, A., Vidyattama, Y. & Tanton, R. Demographic change and the needs-based planning of government services: projecting small area populations using spatial microsimulation. J Pop Research 28, 203–224 (2011). https://doi.org/10.1007/s12546-011-9061-6

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