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  • Articles and reports: 11-522-X20020016727
    Description:

    The census data are widely used in the distribution and targeting of resources at national, regional and local levels. In the United Kingdom (UK), a population census is conducted every 10 years. As time elapses, the census data become outdated and less relevant, thus making the distribution of resources less equitable. This paper examines alternative methods in rectifying this.

    A number of small area methods have been developed for producing postcensal estimates, including the Structural Preserving Estimation technique as a result of Purcell and Kish (1980). This paper develops an alternative approach that is based on a linear mixed modelling approach to producing postcensal estimates. The validity of the methodology is tested on simulated data from the Finnish population register and the technique is applied to producing updated estimates for a number of the 1991 UK census variables.

    Release date: 2004-09-13

  • Articles and reports: 12-001-X19980024349
    Description:

    Measurement of gross flows in labour force status is an important objective of the continuing labour force surveys carried out by many national statistics agencies. However, it is well known that estimation of these flows can be complicated by nonresponse, measurement errors, sample rotation and complex design effects. Motivated by nonresponse patterns in household-based surveys, this paper focuses on estimation of labour force gross flows, while simultaneously adjusting for nonignorable nonresponse. Previous model-based approaches to gross flows estimation have assumed nonresponse to be an individual-level process. We propose a class of models that allow for nonignorable household-level nonresponse. A simulation study is used to show, that individual-level labour force gross flows estimates from household-based survey data, may be biased and that estimates using household-level models can offer a reduction in this bias.

    Release date: 1999-01-14
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Articles and reports (2)

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  • Articles and reports: 11-522-X20020016727
    Description:

    The census data are widely used in the distribution and targeting of resources at national, regional and local levels. In the United Kingdom (UK), a population census is conducted every 10 years. As time elapses, the census data become outdated and less relevant, thus making the distribution of resources less equitable. This paper examines alternative methods in rectifying this.

    A number of small area methods have been developed for producing postcensal estimates, including the Structural Preserving Estimation technique as a result of Purcell and Kish (1980). This paper develops an alternative approach that is based on a linear mixed modelling approach to producing postcensal estimates. The validity of the methodology is tested on simulated data from the Finnish population register and the technique is applied to producing updated estimates for a number of the 1991 UK census variables.

    Release date: 2004-09-13

  • Articles and reports: 12-001-X19980024349
    Description:

    Measurement of gross flows in labour force status is an important objective of the continuing labour force surveys carried out by many national statistics agencies. However, it is well known that estimation of these flows can be complicated by nonresponse, measurement errors, sample rotation and complex design effects. Motivated by nonresponse patterns in household-based surveys, this paper focuses on estimation of labour force gross flows, while simultaneously adjusting for nonignorable nonresponse. Previous model-based approaches to gross flows estimation have assumed nonresponse to be an individual-level process. We propose a class of models that allow for nonignorable household-level nonresponse. A simulation study is used to show, that individual-level labour force gross flows estimates from household-based survey data, may be biased and that estimates using household-level models can offer a reduction in this bias.

    Release date: 1999-01-14
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