Simulating the characteristics of populations at the small area level: New validation techniques for a spatial microsimulation model in Australia
These days spatial microsimulation modelling plays a vital role in policy analysis for small areas. Most developed countries are using these tools in ways to make knowledgeable decisions on major policy issues at local levels. However, building an appropriate model is very difficult for many reasons. For example, the creation of reliable spatial microdata is still challenging. In addition there has not been much research on testing statistical significance of the model outputs yet, and deriving estimates of how reliable these outputs may be. This paper deals with the spatial microsimulation model building procedure for simulating synthetic spatial microdata, and then estimating small area housing stress in Australia. Geographic maps for small area housing stress estimates are illustrated. The research also demonstrates a new system to test the statistical significance of the model estimates.
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Volume (Year): 57 (2013)
Issue (Month): 1 ()
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- Azizur Rahman & Ann Harding & Robert Tanton & Shuangzhe Liu, 2010. "Methodological Issues in Spatial Microsimulation Modelling for Small Area Estimation," International Journal of Microsimulation, International Microsimulation Association, vol. 3(2), pages 3-22.
- Stephen Hynes & Karyn Morrissey & Cathal O’Donoghue, 2005.
"Building a Static Farm Level Spatial Microsimulation Model: Statistically Matching the Irish National Farm Survey to the Irish Census of Agriculture,"
0506, Rural Economy and Development Programme,Teagasc.
- Stephen Hynes & Karyn Morrissey & Cathal O'donoghue, 2006. "Building a Static Farm Level Spatial Microsimulation Model: Statistically Matching the Irish National Farm Survey to the Irish Census of Agriculture," ERSA conference papers ersa06p431, European Regional Science Association.
- 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.
- Robert Tanton & Yogi Vidyattama, 2010. "Pushing It To The Edge: Extending Generalised Regression As A Spatial Microsimulation Method," International Journal of Microsimulation, International Microsimulation Association, vol. 3(2), pages 23-33.
- 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.
- Edwards, Kimberley L. & Clarke, Graham P., 2009. "The design and validation of a spatial microsimulation model of obesogenic environments for children in Leeds, UK: SimObesity," Social Science & Medicine, Elsevier, vol. 69(7), pages 1127-1134, October. Full references (including those not matched with items on IDEAS)
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