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‘Small area estimates of Subjective Wellbeing: Spatial Microsimulation on the Australian Unity Wellbeing Index Survey’

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Author Info

  • Itismita Mohanty

    ()
    (NATSEM, University of Canberra)

  • Robert Tanton

    ()
    (NATSEM, University of Canberra)

  • Yogi Vidyattama

    ()
    (NATSEM, University of Canberra)

  • Marcia Keegan

    ()
    (NATSEM, University of Canberra)

  • Robert Cummins

    ()
    (Deakin University)

Abstract

Subjective wellbeing is an indicator of how satisfied a person is with their life. It is becoming accepted as an indicator of happiness and overall wellbeing. This paper uses spatial microsimulation methods to estimate small area subjective wellbeing (SWB) in Australia. The procedure uses the Australian Unity Wellbeing Index survey and the 2011 Census data to derive small area estimates of SWB. Validation of the results shows that high and normal levels of SWB compare well to another source of SWB for small areas in the Murray Darling Basin, but levels of low SWB are not predicted as well, possibly due to the effect of local factors not available for the modelling on reducing SWB. Aggregate estimates compare well to HILDA estimates of SWB at a State level. These estimates are now available from the Australian Urban Research Infrastructure Network (AURIN) at the University of Melbourne..

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File URL: http://www.natsem.canberra.edu.au/files/download?id=1175
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Bibliographic Info

Paper provided by University of Canberra, National Centre for Social and Economic Modelling in its series NATSEM Working Paper Series with number 13/23.

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Length: 35 pages
Date of creation: Dec 2013
Date of revision:
Publication status: Published as a NATSEM Working Paper series
Handle: RePEc:cba:wpaper:wp1123

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Postal: University of Canberra, ACT 2601
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Web page: http://www.natsem.canberra.edu.au/
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Keywords: Wellbeing; Regional welfare; Spatial Microsimulation;

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  1. Paul Dolan & Richard Layard & Robert Metcalfe, 2011. "Measuring subjective well-being for public policy," LSE Research Online Documents on Economics 35420, London School of Economics and Political Science, LSE Library.
  2. 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, Interational Microsimulation Association, vol. 2(2), pages 27-42.
  3. 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, 06.
  4. Robert Cummins, 2003. "Normative Life Satisfaction: Measurement Issues and a Homeostatic Model," Social Indicators Research, Springer, vol. 64(2), pages 225-256, November.
  5. P Williamson & M Birkin & P H Rees, 1998. "The estimation of population microdata by using data from small area statistics and samples of anonymised records," Environment and Planning A, Pion Ltd, London, vol. 30(5), pages 785-816, May.
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