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Old, Single and Poor: Using Microsimulation and Microdata to Analyse Poverty and the Impact of Policy Change among Older Australians

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  • Robert Tanton
  • Yogi Vidyattama
  • Justine McNamara
  • Quoc Ngu Vu
  • Ann Harding

Abstract

In recent months in Australia there has been extended debate about whether the age pension, particularly with regard to single pensioners, is sufficiently high to allow older Australians to attain an acceptable standard of living. This is an important policy consideration given Australia’s rapidly ageing population. By using microdata and microsimulation models, this paper examines the national and spatial impacts on the distribution of poverty among older single people of an increase in the single age‐pension rate. This paper shows that the cost of increasing the single age‐pension to 66 per cent of the couple‐age pension rate would be about $A1.3 billion and would benefit about 824,000 single age‐pensioners. Further, it is estimated that such an increase would reduce poverty rates for lone older persons from 46.5 per cent to 36.5 per cent, a 10‐percentage point reduction. Looking at the spatial distribution of such benefits, the effect of the policy change seems to be generally stronger in capital cities, and in bands of rural areas in New South Wales and Victoria.

Suggested Citation

  • Robert Tanton & Yogi Vidyattama & Justine McNamara & Quoc Ngu Vu & Ann Harding, 2009. "Old, Single and Poor: Using Microsimulation and Microdata to Analyse Poverty and the Impact of Policy Change among Older Australians," Economic Papers, The Economic Society of Australia, vol. 28(2), pages 102-120, June.
    • Handle: RePEc:bla:econpa:v:28:y:2009:i:2:p:102-120
    DOI: 10.1111/j.1759-3441.2009.00022.x
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    References listed on IDEAS

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    Cited by:

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    2. Robert Tanton & Paul Williamson & Ann Harding, 2014. "Comparing Two Methods of Reweighting a Survey File to Small Area Data," International Journal of Microsimulation, International Microsimulation Association, vol. 7(1), pages 76-99.
    3. 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.
    4. Yogi Vidyattama & Maheshwar Rao & Itismita Mohanty & Robert Tanton, 2014. "Modelling the impact of declining Australian terms of trade on the spatial distribution of income," International Journal of Microsimulation, International Microsimulation Association, vol. 7(1), pages 100-126.
    5. Karyn Morrissey & Cathal O'donoghue & Niall Farrell, 2014. "The Local Impact of the Marine Sector in Ireland: A Spatial Microsimulation Analysis," Spatial Economic Analysis, Taylor & Francis Journals, vol. 9(1), pages 31-50, March.
    6. Deborah Schofield & Michelle Cunich & Simon Kelly & Megan E Passey & Rupendra Shrestha & Emily Callander & Robert Tanton & Lennert Veerman, 2015. "The Impact of Diabetes on the Labour Force Participation, Savings and Retirement Income of Workers Aged 45-64 Years in Australia," PLOS ONE, Public Library of Science, vol. 10(2), pages 1-10, February.
    7. Robert Tanton, 2018. "Spatial Microsimulation: Developments and Potential Future Directions," International Journal of Microsimulation, International Microsimulation Association, vol. 11(1), pages 143-161.
    8. Rahman, Azizur & Harding, Ann & Tanton, Robert & Liu, Shuangzhe, 2013. "Simulating the characteristics of populations at the small area level: New validation techniques for a spatial microsimulation model in Australia," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 149-165.
    9. 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.
    10. 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.
    11. Ricardo Crespo & Ignacio Hernandez, 2020. "On the spatially explicit Gini coefficient: the case study of Chile—a high-income developing country," Letters in Spatial and Resource Sciences, Springer, vol. 13(1), pages 37-47, April.
    12. Itismita Mohanty & Robert Tanton & Yogi Vidyattama & Marcia Keegan & Robert Cummins, 2013. "‘Small area estimates of Subjective Wellbeing: Spatial Microsimulation on the Australian Unity Wellbeing Index Survey’," NATSEM Working Paper Series 13/23, University of Canberra, National Centre for Social and Economic Modelling.
    13. Robert Tanton, 2014. "A Review of Spatial Microsimulation Methods," International Journal of Microsimulation, International Microsimulation Association, vol. 7(1), pages 4-25.
    14. Tim Goedemé & Karel Van den Bosch & Lina Salanauskaite & Gerlinde Verbist, 2013. "Testing the Statistical Significance of Microsimulation Results: Often Easier than You Think. A Technical Note," ImPRovE Working Papers 13/10, Herman Deleeck Centre for Social Policy, University of Antwerp.
    15. Xiong Linping & Zhang Lulu & Tang Weidong & Liu Hong, 2010. "Evaluating Sustainability of Medical Insurance Scheme for Urban Employed Individuals in China," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 35(4), pages 600-625, October.

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