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Housing Stress Today: Estimates for Statistical Local Areas in 2005

Listed author(s):
  • Ben Phillips


    (NATSEM, University of Canberra)

  • S.F. Chin
  • Ann Harding


    (NATSEM, University of Canberra)

This paper presents estimates of housing stress for Statistical Local Areas (SLA) in Victoria, Queensland and the ACT in 2005. The estimates were created by synthesising small-area microdata for measuring housing stress. The technique involves the reweighting of a national ABS sample survey to Census benchmarks for each small area at the SLA level. The reweighting process converts the set of national household weights obtained from the sample survey into sets of household weights for small areas (one set per SLA). This paper defines a household in housing stress as being one that is in the bottom 40 per cent of equivalent household disposable income and whose net spending on housing after subtracting any rent assistance received is more than 30 per cent of their income (i.e. a 'net' rather than 'gross' housing stress measure). Housing stress was found to be more prevalent in the urban areas - especially in the capital cities, followed by other urban centres (especially the fast-growing regions on the eastern seaboard).

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Paper provided by University of Canberra, National Centre for Social and Economic Modelling in its series NATSEM Working Paper Series with number 2006 019.

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Length: 33 pages
Date of creation: Mar 2007
Publication status: Published on the NATSEM web site, December 2006, pages 1-33
Handle: RePEc:cba:wpaper:0619
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University of Canberra, ACT 2601

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  1. Gavin A Wood & Matthew Forbes & Kenneth Gibb, 2005. "Direct subsidies and housing affordability in Australian private rental markets," Environment and Planning C: Government and Policy, Pion Ltd, London, vol. 23(5), pages 759-783, October.
  2. Mark Tranmer & Andrew Pickles & Ed Fieldhouse & Mark Elliot & Angela Dale & Mark Brown & David Martin & David Steel & Chris Gardiner, 2005. "The case for small area microdata," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(1), pages 29-49.
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