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Small-area estimation with spatial similarity

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  • Nicholas Longford

Abstract

A class of composite estimators of small area quantities that exploit spatial (distancerelated) similarity is derived. It is based on a distribution-free model for the areas, but the estimators are aimed to have optimal design-based properties. Composition is applied also to estimate some of the global parameters on which the small area estimators depend. It is shown that the commonly adopted assumption of random effects is not necessary for exploiting the similarity of the districts (borrowing strength across the districts). The methods are applied in the estimation of the mean household sizes and the proportions of single-member households in the counties (comarcas) of Catalonia. The simplest version of the estimators is more efficient than the established alternatives, even though the extent of spatial similarity is quite modest.

Suggested Citation

  • Nicholas Longford, 2008. "Small-area estimation with spatial similarity," Economics Working Papers 1105, Department of Economics and Business, Universitat Pompeu Fabra, revised Sep 2009.
    • Handle: RePEc:upf:upfgen:1105
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    References listed on IDEAS

    as
    1. Paul Elliott & Jon Wakefield, 2001. "Disease clusters: should they be investigated, and, if so, when and how?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 164(1), pages 3-12.
    2. N. T. Longford, 1999. "Multivariate shrinkage estimation of small area means and proportions," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 162(2), pages 227-245.
    3. Peter Congdon, 2004. "Modelling Trends and Inequality in Small Area Mortality," Journal of Applied Statistics, Taylor & Francis Journals, vol. 31(6), pages 603-622.
    4. Nicholas T. Longford, 2004. "Missing data and small area estimation in the UK Labour Force Survey," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 167(2), pages 341-373, May.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Auxiliary information; composite estimation; design-based estimator; exploiting similarity; model-based estimator; multivariate shrinkage; small-area estimation; spatial similarity;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods

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