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Using Composite Estimators to Improve both Domain and Total Area Estimation

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Author Info
Àlex Costa
Albert Satorra ()
Eva Ventura ()

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Abstract

In this article we propose using small area estimators to improve the estimates of both the small and large area parameters. When the objective is to estimate parameters at both levels accurately, optimality is achieved by a mixed sample design of fixed and proportional allocations. In the mixed sample design, once a sample size has been determined, one fraction of it is distributed proportionally among the different small areas while the rest is evenly distributed among them. We use Monte Carlo simulations to assess the performance of the direct estimator and two composite covariant-free small area estimators, for different sample sizes and different sample distributions. Performance is measured in terms of Mean Squared Errors (MSE) of both small and large area parameters. It is found that the adoption of small area composite estimators open the possibility of 1) reducing sample size when precision is given, or 2) improving precision for a given sample size.

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Publisher Info
Paper provided by Department of Economics and Business, Universitat Pompeu Fabra in its series Economics Working Papers with number 731.

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Date of creation: Dec 2003
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Handle: RePEc:upf:upfgen:731

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Related research
Keywords: Regional statistics; small areas; mean square error; direct and composite;

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Find related papers by JEL classification:
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing
J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Alex Costa & Albert Satorra & Eva Ventura, 2003. "An Empirical Evaluation of Five Small Area Estimators," General Economics and Teaching 0312003, EconWPA. [Downloadable!]
  2. Àlex Costa & Albert Satorra & Eva Ventura, 2003. "An Empirical Evaluation of Small Area Estimators," Economics Working Papers 674, Department of Economics and Business, Universitat Pompeu Fabra, revised Jun 2003. [Downloadable!]
  3. 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.
  4. 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.
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(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. 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. [Downloadable!]
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