IDEAS home Printed from https://ideas.repec.org/a/ijm/journl/v11y2018i3p78-99.html
   My bibliography  Save this article

Care&WorkMOD: An Australian Microsimulation Model Projecting the Economic Impacts of Early Retirement in Informal Carers

Author

Listed:
  • Rupendra N Shrestha

    (GenIMPACT: Centre for Economic Impacts of Genomic Medicine, Macquarie University, Sydney,)

  • Deborah Schofield

    (GenIMPACT: Centre for Economic Impacts of Genomic Medicine, Macquarie University, Sydney,)

  • Melanie J B Zeppel

    (GenIMPACT: Centre for Economic Impacts of Genomic Medicine, Macquarie University, Sydney,)

  • Michelle M Cunich

    (Faculty of Pharmacy, The University of Sydney, Sydney, Australia.)

  • Robert Tanton

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

  • Simon J Kelly

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

  • Lennert Veerman

    (Cancer Council NSW, Woolloomooloo, Australia and School of Medicine, Griffith University, Queensland, Australia.)

  • Megan E Passey

    (University Centre for Rural Health, The University of Sydney, Lismore, Australia.)

Abstract

We developed a microsimulation model, Care&WorkMOD, to estimate the economic costs of early exit from the labour force, both for informal carers and the government, from 2015 to 2030. In this paper, we describe the methods used to create the model Care&WorkMOD, and the sources of data and model assumptions. Care&WorkMOD is based on the unit record data of people aged 15-64 years in the three Australian Bureau of Statistics (ABS) Surveys of Disability, Ageing and Carers (SDAC) 2003, 2009 and 2012. Population and the labour force projections from the 2015 Intergenerational Report and the outputs of an Australian microsimulation model APPSIM were used for the static aging of the base data to every five years from 2015 to 2030. The 2015 output dataset of another microsimulation model STINMOD was linked with Care&WorkMOD base data using synthetic matching. The matching process has added data on further economic variables from STINMOD into Care&WorkMOD, which are not available in SDACs. Economic data were indexed based on long-term trends on economic variables to capture the projected economic growth from 2015 to 2030. Care&WorkMOD can provide the long-term estimates of the lost labour productivity due to informal caring responsibilities and the related economic burden both at the individual and national level, and has the potential to “fill the gaps” in the current body of evidence on the costs of chronic diseases, particularly related to informal carers

Suggested Citation

  • 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.
  • Handle: RePEc:ijm:journl:v:11:y:2018:i:3:p:78-99
    as

    Download full text from publisher

    File URL: https://www.microsimulation.org/IJM/V11_3/IJM_11_3_3.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Nguyen, Ha Trong & Connelly, Luke Brian, 2014. "The effect of unpaid caregiving intensity on labour force participation: Results from a multinomial endogenous treatment model," Social Science & Medicine, Elsevier, vol. 100(C), pages 115-122.
    3. Matthew Gray & Ben Edwards, 2009. "Determinants of the Labour Force Status of Female Carers," Australian Journal of Labour Economics (AJLE), Bankwest Curtin Economics Centre (BCEC), Curtin Business School, vol. 12(1), pages 5-20.
    4. Binod Nepal & Laurie Brown & Simon Kelly & Richard Percival & Phil Anderson & Ruth Hancock & Geetha Ranmuthugala, 2011. "Projecting the Need for Formal and Informal Aged Care in Australia: A Dynamic Microsimulation Approach," NATSEM Working Paper Series 11/07, University of Canberra, National Centre for Social and Economic Modelling.
    5. Laurie Brown & Ann Harding, 2002. "Social Modelling and Public Policy: Application of Microsimulation Modelling in Australia," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 5(4), pages 1-6.
    6. Sharyn Lymer & Laurie Brown & Ann Harding & Mandy Yap, 2009. "Predicting the need for aged care services at the small area level: the CAREMOD spatial microsimulation model," International Journal of Microsimulation, International Microsimulation Association, vol. 2(2), pages 27-42.
    7. Sanjay Basu & Hilary Seligman & Jay Bhattacharya, 2013. "Nutritional Policy Changes in the Supplemental Nutrition Assistance Program," Medical Decision Making, , vol. 33(7), pages 937-948, October.
    8. Robert Tanton & Yogi Vidyattama & Binod Nepal & Justine McNamara, 2011. "Small area estimation using a reweighting algorithm," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 174(4), pages 931-951, October.
    9. Jinjing Li & Cathal O'Donoghue, 2013. "A survey of dynamic microsimulation models: uses, model structure and methodology," International Journal of Microsimulation, International Microsimulation Association, vol. 6(2), pages 3-55.
    10. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jinjing Li & Yogi Vidyattama, 2019. "Projecting spatial population and labour force growth in Australian districts," Journal of Population Research, Springer, vol. 36(3), pages 205-232, September.
    2. Robert Tanton, 2018. "Spatial Microsimulation: Developments and Potential Future Directions," International Journal of Microsimulation, International Microsimulation Association, vol. 11(1), pages 143-161.
    3. Ann Harding & Robert Tanton, 2014. "Policy and people at the small-area level: using micro-simulation to create synthetic spatial data," Chapters, in: Robert Stimson (ed.), Handbook of Research Methods and Applications in Spatially Integrated Social Science, chapter 25, pages 560-586, Edward Elgar Publishing.
    4. Frederik Priem & Philip Stessens & Frank Canters, 2020. "Microsimulation of Residential Activity for Alternative Urban Development Scenarios: A Case Study on Brussels and Flemish Brabant," Sustainability, MDPI, vol. 12(6), pages 1-28, March.
    5. M. Esteban Muñoz H. & Ivan Dochev & Hannes Seller & Irene Peters, 2016. "Constructing a Synthetic City for Estimating Spatially Disaggregated Heat Demand," International Journal of Microsimulation, International Microsimulation Association, vol. 9(3), pages 66-88.
    6. 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.
    7. Cathal O'Donoghue & Karyn Morrissey & John Lennon, 2014. "Spatial Microsimulation Modelling: a Review of Applications and Methodological Choices," International Journal of Microsimulation, International Microsimulation Association, vol. 7(1), pages 26-75.
    8. Yogi Vidyattama & Riyana Miranti & Justine McNamara & Robert Tanton & Ann Harding, 2013. "The Challenges of Combining Two Databases in Small-Area Estimation: An Example Using Spatial Microsimulation of Child Poverty," Environment and Planning A, , vol. 45(2), pages 344-361, February.
    9. María Priscila Ramos & Estefanía Custodio & Sofía Jiménez & Alfredo J. Mainar-Causapé & Pierre Boulanger & Emanuele Ferrari, 2022. "Do agri-food market incentives improve food security and nutrition indicators? a microsimulation evaluation for Kenya," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 14(1), pages 209-227, February.
    10. Maheshwar Rao & Robert Tanton & Yogi Vidyattama, 2013. "‘A Systems Approach to Analyse the Impacts of Water Policy Reform in the Murray-Darling Basin: a conceptual and an analytical framework’," NATSEM Working Paper Series 13/22, University of Canberra, National Centre for Social and Economic Modelling.
    11. Giordana, Gastón A. & Pi Alperin, María Noel, 2023. "Old age takes its toll: Long-run projections of health-related public expenditure in Luxembourg," Economics & Human Biology, Elsevier, vol. 50(C).
    12. Holger Bonin & Karsten Reuss & Holger Stichnoth, 2015. "Life-Cycle Incidence of Family Policy Measures in Germany: Evidence from a Dynamic Microsimulation Model," SOEPpapers on Multidisciplinary Panel Data Research 770, DIW Berlin, The German Socio-Economic Panel (SOEP).
    13. Heger, Dörte & Korfhage, Thorben, 2017. "Does the negative effect of caregiving on work persist over time?," Ruhr Economic Papers 703, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    14. Eugenio Zucchelli & Andrew M Jones & Nigel Rice, 2012. "The evaluation of health policies through dynamic microsimulation methods," International Journal of Microsimulation, International Microsimulation Association, vol. 5(1), pages 2-20.
    15. Rolf Aaberge & Ugo Colombino, 2014. "Labour Supply Models," Contributions to Economic Analysis, in: Handbook of Microsimulation Modelling, volume 127, pages 167-221, Emerald Group Publishing Limited.
    16. Loughrey, Jason & O’Donoghue, Cathal & Meredith, David & Murphy, Ger & Shanahan, Ultan & Miller, Corina, 2018. "The Local Impact of Cattle Farming," 166th Seminar, August 30-31, 2018, Galway, West of Ireland 276231, European Association of Agricultural Economists.
    17. Templ, Matthias & Meindl, Bernhard & Kowarik, Alexander & Dupriez, Olivier, 2017. "Simulation of Synthetic Complex Data: The R Package simPop," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 79(i10).
    18. Matteo Richiardi & Ross E. Richardson, 2017. "JAS-mine: A new platform for microsimulation and agent-based modelling," International Journal of Microsimulation, International Microsimulation Association, vol. 10(1), pages 106-134.
    19. GENEVOIS Anne-Sophie & LIEGEOIS Philippe & PI ALPERIN Maria Noel, 2019. "DyMH_LU: a simple tool for modelling and simulating the health status of the Luxembourgish elderly in the longer run," LISER Working Paper Series 2019-06, Luxembourg Institute of Socio-Economic Research (LISER).
    20. Kamila Hynek & Aslaug Gotehus & Fredrik Methi & Ragnhild Bang Nes & Vegard Skirbekk & Thomas Hansen, 2023. "Caregiving + Migrant Background = Double Jeopardy? Associations between Caregiving and Physical and Psychological Health According to Migrant Backgrounds in Norway," IJERPH, MDPI, vol. 20(10), pages 1-13, May.

    More about this item

    Keywords

    INFORMAL CARERS; LOST PRODUCTIVE LIFE YEARS; EARLY RETIREMENT; ECONOMIC IMPACTS;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • J26 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Retirement; Retirement Policies
    • J17 - Labor and Demographic Economics - - Demographic Economics - - - Value of Life; Foregone Income

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ijm:journl:v:11:y:2018:i:3:p:78-99. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Jinjing Li (email available below). General contact details of provider: http://www.microsimulation.org/ijm/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.