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Incompatibility of estimation and policy objectives. An example from small-area estimation

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  • Nicholas Longford

Abstract

We show on an application to small-area statistics that efficient estimation is not always conducive to good policy decisions, because the established inferential procedures have no capacity to incorporate the priorities and preferences of the policy makers and the related consequences of incorrect decisions. A method that addresses these deficiencies is described. We argue that elicitation of the perspectives of the client (sponsor) and their quantification are essential elements of the analysis, because different estimators (decisions) are appropriate for different perspectives. An example of planning an intervention in a country’s districts with high rate of illiteracy is described. In the problem, the established small-area estimators perform poorly because the minimum mean squared error is an inappropriate criterion.

Suggested Citation

  • Nicholas Longford, 2014. "Incompatibility of estimation and policy objectives. An example from small-area estimation," Economics Working Papers 1447, Department of Economics and Business, Universitat Pompeu Fabra.
  • Handle: RePEc:upf:upfgen:1447
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    References listed on IDEAS

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    1. Chris Elbers & Jean O. Lanjouw & Peter Lanjouw, 2003. "Micro--Level Estimation of Poverty and Inequality," Econometrica, Econometric Society, vol. 71(1), pages 355-364, January.
    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. 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.
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    Keywords

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