The use of auxiliary information in design-based estimation for domains

In the final paper of this special issue, Estevao and Särndal consider two types of design-based estimators used for domain estimation. The first, a linear prediction estimator, is built on the principle of model fitting, requires known auxiliary information at the domain level, and results in weights that depend on the domain to be estimated. The second, a uni-weight estimator, has weights which are independent of the domain being estimated and has the clear advantage that it does not require the calculation of different weight systems for each different domain of interest. These estimators are compared and situations under which one is preferred over the other are identified.