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An Empirical Evaluation of Five Small Area Estimators

Author

Listed:
  • Alex Costa

    (Idescat)

  • Albert Satorra

    (UPF)

  • Eva Ventura

    (UPF)

Abstract

This paper compares five small area estimators. We use Monte Carlo simulation in the context of both artificial and real populations. In addition to the direct and indirect estimators, we consider the optimal composite estimator with population weights, and two composite estimators with estimated weights: one that assumes homogeneity of within area variance and squared bias and one that uses area-specific estimates of variance and squared bias. In the study with real population, we found that among the feasible estimators, the best choice is the one that uses area-specific estimates of variance and squared bias.

Suggested Citation

  • Alex Costa & Albert Satorra & Eva Ventura, 2003. "An Empirical Evaluation of Five Small Area Estimators," General Economics and Teaching 0312003, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpgt:0312003
    Note: Type of Document - pdf; prepared on Win2000; to print on Hewlett Packard Laserjet; pages: 23; figures: 7
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    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/get/papers/0312/0312003.pdf
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    References listed on IDEAS

    as
    1. Farrell, Patrick J & MacGibbon, Brenda & Tomberlin, Thomas J, 1997. "Empirical Bayes Small-Area Estimation Using Logistic Regression Models and Summary Statistics," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(1), pages 101-108, January.
    2. Pfeffermann, Danny & Barnard, Charles H, 1991. "Some New Estimators for Small-Area Means with Application to the Assessment of Farmland Values," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(1), pages 73-84, January.
    3. Isaki, Cary T, 1990. "Small-Area Estimation of Economic Statistics," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(4), pages 435-441, October.
    4. A. C. Singh & D. M. Stukel & D. Pfeffermann, 1998. "Bayesian versus frequentist measures of error in small area estimation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 60(2), pages 377-396.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Àlex Costa & Albert Satorra & Eva Ventura, 2003. "Using composite estimators to improve both domain and total area estimation," Economics Working Papers 731, Department of Economics and Business, Universitat Pompeu Fabra.
    2. Albert Satorra & Eva Ventura & Alex Costa, 2006. "Improving small area estimation by combining surveys: new perspectives in regional statistics," Economics Working Papers 969, Department of Economics and Business, Universitat Pompeu Fabra.

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    More about this item

    Keywords

    Regional statistics; small areas; root mean square error; direct; indirect and composite estimators.;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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