Simulating the characteristics of populations at the small area level: New validation techniques for a spatial microsimulation model in Australia

Azizur RAHMAN, Ann HARDING, Robert TANTON, Shuangzhe LIU

    Research output: Contribution to journalArticle

    11 Citations (Scopus)

    Abstract

    Abstract: 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.
    Original languageEnglish
    Pages (from-to)149-165
    Number of pages17
    JournalComputational Statistics Data Analysis
    Volume57
    Issue number1
    DOIs
    Publication statusPublished - 2013

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    Microsimulation
    Statistical Significance
    Estimate
    Output
    Model
    Testing
    Modeling
    Demonstrate
    Policy

    Cite this

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    abstract = "Abstract: 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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    author = "Azizur RAHMAN and Ann HARDING and Robert TANTON and Shuangzhe LIU",
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    AU - HARDING, Ann

    AU - TANTON, Robert

    AU - LIU, Shuangzhe

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    AB - Abstract: 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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