Application of In-direct Estimation for Small Area Statistics

소지역 통계 생산을 위한 추정방법

  • Kim, Young-Won (Department of Statistics, Sookmyung Women's University) ;
  • Sung, Na-Young (Department of Statistics, Sookmyung Women's University)
  • 김영원 (숙명여자대학교 통계학과) ;
  • 성나영 (숙명여자대학교 통계학과 대학원)
  • Published : 2000.04.30

Abstract

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.

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