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

Deborah Schofield, Rupendra Shrestha (), Simon Kelly, Lennert Veerman (), Robert Tanton (), Megan Passey (), Theo Vos (), Michelle Cunich () and Emily Callander ()
Additional contact information
Rupendra Shrestha: NHMRC Clinical Trials Centre, Sydney Medical School, The University of Sydney
Lennert Veerman: School of Population Health, Faulty of Medicine and Biomedical Sciences, The University of Queensland
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

International Journal of Microsimulation, 2014, vol. 7, issue 2, 94-118

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.

Keywords: Chronic conditions; Early retirement; Economic impacts; Ageing; Synthetic matching (search for similar items in EconPapers)
JEL-codes: I15 J21 J26 (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (3)

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