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An Empirical Evaluation of Five Small Area Estimators

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Author Info

  • 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.

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Bibliographic Info

Paper provided by EconWPA in its series General Economics and Teaching with number 0312003.

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Length: 23 pages
Date of creation: 15 Dec 2003
Date of revision:
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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Web page: http://128.118.178.162

Related research

Keywords: Regional statistics; small areas; root mean square error; direct; indirect and composite estimators.;

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References

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  1. Isaki, Cary T, 1990. "Small-Area Estimation of Economic Statistics," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(4), pages 435-41, October.
  2. 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 101-8, January.
  3. 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.
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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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