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Small Area Estimation Techniques Based on Logistic Model to Estimate Unemployment Rate

Authors
김영원최형아
Issue Date
Dec-2004
Publisher
한국통계학회
Keywords
composite estimator; hierarchical generalized linear model; logistic regression. unemployment rate; composite estimator; hierarchical generalized linear model; logistic regression. unemployment rate
Citation
Communications for Statistical Applications and Methods, v.11, no.3, pp 583 - 595
Pages
13
Journal Title
Communications for Statistical Applications and Methods
Volume
11
Number
3
Start Page
583
End Page
595
URI
https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/15958
ISSN
2287-7843
Abstract
For the Korean Economically Active Population Survey(EAPS), we consider the composite estimator based on logistic regression model to estimate the unemployment rate for small areas(Si/Gun). Also, small area estimation technique based on hierarchical generalized linear model is proposed to include the random effect which reflect the characteristic of the small areas. The proposed estimation techniques are applied to real domestic data which is from the Korean EAPS of Choongbuk. The MSE of these estimators are estimated by Jackknife method, and the efficiencies of small area estimators are evaluated by the RRMSE. As a result, the composite estimator based on logistic model is much more efficient than others and it turns out that the composite estimator can produce the reliable estimates under the current EAPS system.
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