• The Korean Journal of Applied Statistics
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• v.23 no.5
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• pp.891-908
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• 2010

In Korea, the small area estimation method is currently unpopular in generating o cial statistics. Because it may be difficult to determine the reliability for small area estimation, although small area estimation ha a sufficiently good advantage to generate small area statistics for Korea. This paper inspects the method of making small area unemployment through the small area estimation method. To estimate small area unemployment we used an EBLUP-type estimator based on a logistic linear mixed model. To evaluate the EBLUP-type estimator we accomplished the real data analysis and simulation experiment from the population and housing census data. In addition, small area estimates are compared to large sample survey estimates. We found the provided method in this paper is highly recommendable to generate small area unemployment as the official statistics.

• Journal of the Korean Data and Information Science Society
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• v.11 no.1
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• pp.111-126
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• 2000

Small area estimation is becoming important in survey sampling due to a growing demand for reliable small area statistics. In estimating means, totals, and other parameters for small areas of a finite population, samplie sizes for small areas are typically small because the overall sample size is usually determined to provide specific accuracy at a much higher level of aggregation than that of small area. The usual direct estimators that use the only information which is gotten from the sample in a given small area provide unreliable estimates. However, indirect estimators utilize the information from the areas related with a given small area, that is, borrow strength from other related areas, and so give more accurate estimates than direct estimators. In this paper we investigate small area estimation methods such as synthetic, composite and empirical best linear unbiased prediction estimator, and apply them to real domestic data which is from the Survey of Hotels and Restaurants in In-Chon as of 1996 and then evaluate the performance of these methods by measuring average squared errors. This evaluation shows that indirect estimators, which are small area estimation methods, are more efficient than direct estimator.