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Policy-related small-area estimation

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  • Nicholas Longford

Abstract

A method of small-area estimation with a utility function is developed. The utility characterises a policy planned to be implemented in each area, based on the area's estimate of a key quantity. It is shown by simulations that the commonly applied composite and empirical Bayes estimators are inefficient for a wide range of asymmetric utility functions. Adaptations for limited budget to implement the policy are explored. An argument is presented for a closer integration of estimation and (regional) policy making because no single small- area estimator is suitable for a wide range of purposes.

Suggested Citation

  • Nicholas Longford, 2014. "Policy-related small-area estimation," Economics Working Papers 1427, Department of Economics and Business, Universitat Pompeu Fabra.
    • Handle: RePEc:upf:upfgen:1427
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    References listed on IDEAS

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    1. Garthwaite, Paul H. & Kadane, Joseph B. & O'Hagan, Anthony, 2005. "Statistical Methods for Eliciting Probability Distributions," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 680-701, June.
    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 Hall & Tapabrata Maiti, 2006. "On parametric bootstrap methods for small area prediction," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 68(2), pages 221-238, April.
    4. Longford, Nicholas T., 2010. "Bayesian Decision Making About Small Binomial Rates With Uncertainty About the Prior," The American Statistician, American Statistical Association, vol. 64(2), pages 164-169.
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    Keywords

    Composition; empirical Bayes; expected loss; borrowing strength; exploiting similarity; small-area estimation; utility function.;
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