Model-based small area estimation with application to unemployment estimates

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Abstract

The problem of Small Area Estimation (SAE) is complex because of various information sources and insufficient data. In this paper, an approach for SAE is presented for decision-making at national, regional and local level. We propose an Empirical Best Linear Unbiased Predictor (EBLUP) as an estimator in order to combine several information sources to evaluate various indicators. First, we present the urban audit project and its environmental, social and economic indicators. Secondly, we propose an approach for decision making in order to estimate indicators. An application is used to validate the theoretical proposal. Finally, a decision support system is presented based on open-source environment.
Original languageEnglish
Pages (from-to)10-17
JournalWorld Academy of Science, Engineering and Technology
Volume3
Issue number1
Publication statusPublished - 2009

Keywords

  • decision-making
  • sampling
  • Small area estimation
  • statistical method
  • empirical best linear unbiased predictor (EBLUP)

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