These days spatial microsimulation modelling plays a vital role in policy analysis for small areas. Most developed countries are utilising these tools in more effective 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 estimating small area housing stress in Australia. It also establishes new ways to test the statistical significance of the model estimates.
|Title of host publication||Statistics|
|Subtitle of host publication||A key to Innovation in a Data-Centric World|
|Place of Publication||Alexandira, USA|
|Number of pages||15|
|Publication status||Published - 2010|
|Event||Joint Statistical Meetings by American Statistical Association (ASA) - Vancouver, British Columbia., Canada|
Duration: 01 Jan 2010 → …
|Conference||Joint Statistical Meetings by American Statistical Association (ASA)|
|Period||01/01/10 → …|
Harding, A., Liu, S., Tanton, R., & Rahman, A. (2010). Simulating the Characteristics of Populations at the Small-Area Level: New Validation Techniques for a Spatial Microsimulation Model in Australia. In Statistics: A key to Innovation in a Data-Centric World (pp. 2022-2036). ASA.