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Estimating small-area Indigenous cultural participation from synthetic survey data

Author

Listed:
  • Yogi Vidyattama
  • Robert Tanton
  • Nicholas Biddle

Abstract

Lack of data on the spatial distribution of the social conditions of Australia's Indigenous peoples has created difficulties in the allocation of government and community programs. Small-area estimation methods can overcome this lack of data, but typically require access to a unit record file. However, strict confidentiality rules applied to these unit record files may hinder the development of these models. In Australia, unit record data for the Indigenous population is analysable only using Australian Bureau of Statistics servers remotely. This study looks specifically at this issue and offers a solution to the problem of confidentiality restrictions by using a synthetic database. The results show that reasonable small-area estimates of social conditions for Indigenous Australians can be derived from a small-area estimation (spatial microsimulation) model using a synthetic database. While this application is for Australia, the method developed can be used for any small-area model requiring unit record data that are not available due to confidentiality restrictions.

Suggested Citation

  • Yogi Vidyattama & Robert Tanton & Nicholas Biddle, 2015. "Estimating small-area Indigenous cultural participation from synthetic survey data," Environment and Planning A, , vol. 47(5), pages 1211-1228, May.
    • Handle: RePEc:sae:envira:v:47:y:2015:i:5:p:1211-1228
    DOI: 10.1177/0308518X15592314
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    References listed on IDEAS

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    1. 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.
    2. Yogi Vidyattama & Rebecca Cassells & Ann Harding & Justine Mcnamara, 2013. "Rich or Poor in Retirement? A Small Area Analysis of Australian Private Superannuation Savings in 2006 Using Spatial Microsimulation," Regional Studies, Taylor & Francis Journals, vol. 47(5), pages 722-739, May.
    3. Monica Pratesi & Nicola Salvati, 2008. "Small area estimation: the EBLUP estimator based on spatially correlated random area effects," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 17(1), pages 113-141, February.
    4. Enrico Fabrizi & Caterina Giusti & Nicola Salvati & Nikos Tzavidis, 2014. "Mapping average equivalized income using robust small area methods," Papers in Regional Science, Wiley Blackwell, vol. 93(3), pages 685-701, August.
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    Cited by:

    1. Vidyattama, Yogi & Tanton, Robert & Nakanishi, Hitomi, 2021. "Investigating Australian households’ vehicle ownership and its relationship with emission tax policy options," Transport Policy, Elsevier, vol. 114(C), pages 196-205.

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