Small-area estimates using model-based methods

Abstract

In small areas, the number of sample plots is usually small, and the classical estimators have a large variance. Information from nearby areas can be utilized to improve the subarea estimates using either nonparametric or parametric models. In this study, a number of model-based estimators for small-area estimation are presented. To illustrate the presented methods a numerical example in a real inventory situation is given. The auxiliary information used in this study is pure coordinate information, but the methods are applicable also for other kinds of auxiliary information. The object of this study is to compare the features of the presented small-area estimation methods and to discuss the applicability of these methods in different situations.