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Article
Small area estimation combining information from several sources
Survey Methodology
  • Jae Kwang Kim, Iowa State University
  • Seunghwan Park, Seoul National University
  • Seo-young Kim, Statistics Korea
Document Type
Article
Publication Version
Published Version
Publication Date
6-1-2015
Abstract

An area-level model approach to combining information from several sources is considered in the context of small area estimation. At each small area, several estimates are computed and linked through a system of structural error models. The best linear unbiased predictor of the small area parameter can be computed by the general least squares method. Parameters in the structural error models are estimated using the theory of measurement error models. Estimation of mean squared errors is also discussed. The proposed method is applied to the real problem of labor force surveys in Korea.

Comments

This article is published as Kim, Jae-kwang, Seunghwan Park, and Seo-young Kim. "Small area estimation combining information from several sources." Survey Methodology 41 (2015). Posted with permission.

Rights
Source: Statistics Canada; Survey Methodology; June 2015. Reproduced and distributed on an "as is" basis with the permission of Statistics Canada.
Copyright Owner
Minister of Industry
Language
en
File Format
application/pdf
Citation Information
Jae Kwang Kim, Seunghwan Park and Seo-young Kim. "Small area estimation combining information from several sources" Survey Methodology Vol. 41 Iss. 1 (2015) p. 21 - 36
Available at: http://works.bepress.com/jae-kwang-kim/36/