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Health&WealthMOD2030: A Microsimulation Model of the Long Term Economic Impacts of Disease Leading to Premature Retirements of Australians Aged 45-64 Years Old

Author

Listed:
  • Deborah Schofield

    (NHMRC Clinical Trials Centre, Sydney Medical School, The University of Sydney)

  • Rupendra Shrestha

    (NHMRC Clinical Trials Centre, Sydney Medical School, The University of Sydney)

  • Simon Kelly

    (National Centre for Social and Economic Modelling, The University of Canberra)

  • Lennert Veerman

    (School of Population Health, Faulty of Medicine and Biomedical Sciences, The University of Queensland)

  • Robert Tanton

    (National Centre for Social and Economic Modelling, The University of Canberra)

  • Megan Passey

    (University Centre for Rural Health, North Coast, School of Public Health, Sydney Medical School, The University of Sydney)

  • Theo Vos

    (School of Population Health, Faulty of Medicine and Biomedical Sciences, The University of Queensland)

  • Michelle Cunich

    (NHMRC Clinical Trials Centre, Sydney Medical School, The University of Sydney)

  • Emily Callander

    (NHMRC Clinical Trials Centre, Sydney Medical School, The University of Sydney)

Abstract

Policymakers in Australia, like in most OECD countries, have recognised the importance of early retirement due to ill health on individuals and families, as well as on the budget balance when planning for the health needs of an ageing population. In order to understand these effects, a unique microsimulation model, called Health&WealthMOD2030, was built to estimate the impacts of early retirement due to ill health on labour force participation, personal and household income, economic hardship (poverty), and government taxation revenue, spending and GDP in the years 2010, 2015, 2020, 2025 and 2030. This paper describes the construction of Health&WealthMOD2030. The model captures the long term projections of demographic change, changing labour force participation patterns, real wages growth and trends in major illnesses affecting the older working age population. The base population of Health&WealthMOD2030 are the individuals aged 45-64 years with information on their work force status and health from the Australian Bureau of Statistics Surveys of Disability, Ageing and Carers (SDAC) 2003 and 2009. Projected estimates of income, taxation, income support payments, savings and superannuation from the National Centre for Social and Economic Modelling (NATSEMs) dynamic microsimulation model Australian Population and Policy Simulation Model (APPSIM) were synthetically matched with the base population. Health&WealthMOD2030 project forward the economic impacts of early retirement from ill health to 2030. This will fill substantial gaps in the current Australian evidence of health conditions that will keep older working age Australians out of the labour market over the long-term.

Suggested Citation

  • Deborah Schofield & Rupendra Shrestha & Simon Kelly & Lennert Veerman & Robert Tanton & Megan Passey & Theo Vos & Michelle Cunich & Emily Callander, 2014. "Health&WealthMOD2030: A Microsimulation Model of the Long Term Economic Impacts of Disease Leading to Premature Retirements of Australians Aged 45-64 Years Old," International Journal of Microsimulation, International Microsimulation Association, vol. 7(2), pages 94-118.
    • Handle: RePEc:ijm:journl:v:7:y:2014:i:2:p:94-118
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    References listed on IDEAS

    as
    1. Kulish Mariano & Kent Christopher & Smith Kathryn, 2010. "Aging, Retirement, and Savings: A General Equilibrium Analysis," The B.E. Journal of Macroeconomics, De Gruyter, vol. 10(1), pages 1-32, July.
    2. Deborah Schofield & Megan Passey & Arul Earnest & Richard Percival & Simon Kelly & Rupendra Shrestha & Susan Fletcher, 2009. "Case Studies - Health&WealthMOD: a microsimulation model of the economic impacts of diseases on older workers," International Journal of Microsimulation, International Microsimulation Association, vol. 2(2), pages 58-63.
    3. Productivity Commission, 2005. "Economic Implications of an Ageing Australia," Labor and Demography 0506001, University Library of Munich, Germany.
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    7. Deborah Schofield & Rupendra Shrestha & Emily Callander & Richard Pervical & Simon Kelly & Megan Passey & Susan Fletcher, 2011. "Modelling the cost of ill health in Health&WealthMOD (Version II): lost labour force participation, income and taxation, and the impact of disease prevention," International Journal of Microsimulation, International Microsimulation Association, vol. 4(3), pages 32-36.
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    Cited by:

    1. Cathal O'Donoghue & Gijs Dekkers, 2018. "Increasing the Impact of Dynamic Microsimulation Modelling," International Journal of Microsimulation, International Microsimulation Association, vol. 11(1), pages 61-96.
    2. Sharyn Lymer & Deborah Schofield & Crystal M Y Lee & Stephen Colagiuri, 2016. "NCDMod: A Microsimulation Model Projecting Chronic Disease and Risk Factors for Australian Adults," International Journal of Microsimulation, International Microsimulation Association, vol. 9(3), pages 103-139.
    3. Rupendra N Shrestha & Deborah Schofield & Melanie J B Zeppel & Michelle M Cunich & Robert Tanton & Simon J Kelly & Lennert Veerman & Megan E Passey, 2018. "Care&WorkMOD: An Australian Microsimulation Model Projecting the Economic Impacts of Early Retirement in Informal Carers," International Journal of Microsimulation, International Microsimulation Association, vol. 11(3), pages 78-99.

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    More about this item

    Keywords

    Chronic conditions; Early retirement; Economic impacts; Ageing; Synthetic matching;
    All these keywords.

    JEL classification:

    • I15 - Health, Education, and Welfare - - Health - - - Health and Economic Development
    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • J26 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Retirement; Retirement Policies

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