A Review of Spatial Microsimulation Methods

    Research output: Contribution to journalArticle

    Abstract

    This paper outlines a framework for spatial microsimulation models, gives some reasons why someone may want to use a spatial microsimulation model, describes the development of spatial microsimulation over the last 30 years, summarises the different methods currently used for spatial microsimulation, and outlines how the models can be validated. In reviewing the reasons and methods for spatial microsimulation, we conclude that spatial microsimulation provides an alternative to other small area estimation methods, providing flexibility by allowing cross-tabulations to be built, and an ability to link to other models, and derive projections. Spatial microsimulation models also allow demographic changes, like births and deaths, to be included in a dynamic microsimulation model. This also allows 'what if' scenarios to be modelled, for example, what would happen if the birth rate increased over time. Validation of the spatial microsimulation models shows that they are now at the stage where they can provide reliable results.
    Original languageEnglish
    Pages (from-to)4-25
    Number of pages22
    JournalInternational Journal of Microsimulation
    Volume7
    Issue number1
    Publication statusPublished - 2014

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    Microsimulation
    Model
    Small Area Estimation
    Review
    Dynamic models
    Flexibility
    Projection
    Scenarios

    Cite this

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    title = "A Review of Spatial Microsimulation Methods",
    abstract = "This paper outlines a framework for spatial microsimulation models, gives some reasons why someone may want to use a spatial microsimulation model, describes the development of spatial microsimulation over the last 30 years, summarises the different methods currently used for spatial microsimulation, and outlines how the models can be validated. In reviewing the reasons and methods for spatial microsimulation, we conclude that spatial microsimulation provides an alternative to other small area estimation methods, providing flexibility by allowing cross-tabulations to be built, and an ability to link to other models, and derive projections. Spatial microsimulation models also allow demographic changes, like births and deaths, to be included in a dynamic microsimulation model. This also allows 'what if' scenarios to be modelled, for example, what would happen if the birth rate increased over time. Validation of the spatial microsimulation models shows that they are now at the stage where they can provide reliable results.",
    keywords = "Small area estimation, Spatial microsimulation",
    author = "Robert TANTON",
    year = "2014",
    language = "English",
    volume = "7",
    pages = "4--25",
    journal = "International Journal of Microsimulation",
    issn = "1747-5864",
    publisher = "International Microsimulation Association",
    number = "1",

    }

    A Review of Spatial Microsimulation Methods. / TANTON, Robert.

    In: International Journal of Microsimulation, Vol. 7, No. 1, 2014, p. 4-25.

    Research output: Contribution to journalArticle

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    AB - This paper outlines a framework for spatial microsimulation models, gives some reasons why someone may want to use a spatial microsimulation model, describes the development of spatial microsimulation over the last 30 years, summarises the different methods currently used for spatial microsimulation, and outlines how the models can be validated. In reviewing the reasons and methods for spatial microsimulation, we conclude that spatial microsimulation provides an alternative to other small area estimation methods, providing flexibility by allowing cross-tabulations to be built, and an ability to link to other models, and derive projections. Spatial microsimulation models also allow demographic changes, like births and deaths, to be included in a dynamic microsimulation model. This also allows 'what if' scenarios to be modelled, for example, what would happen if the birth rate increased over time. Validation of the spatial microsimulation models shows that they are now at the stage where they can provide reliable results.

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