SAE Manual Sections 1 to 4_1 (May 06).pdf - National Statistical ...

A Guide to Small Area Estimation - Version 1.1 05/05/2006
4.2 The Modelling Framework
Figure 4.1 presents a schematic representation of the small area modeling framework
followed in this manual. Figure 4.2 complements Figure 4.1 by providing a list of key
questions the purpose of which is to aid the decision making process of small area
modeling in a reasonably systematic approach. The objective of these questions is to
help the modeller/analyst better understand the modeling framework (Figure 4.1) and
hence be able to choose the most appropriate technique for a given set of data. This,
however, does not mean these are the only questions that need to be raised in this kind
of exercise.
The left-hand-side of Figure 4.1 shows the simplest small area methods, these being the
Direct and Broad Area Ratio estimators, which are frequently used in the absence of
good quality auxiliary data. The answer to question 1 of Figure 4.2 is important as good
quality auxiliary data is a key requisite in order to proceed to the regression-based small
area estimators. We take good auxiliary data to mean area-level and/or unit-level data
that are potentially correlated (both theoretically and empirically) with the variable of
interest. Section 3.5 discusses some of the ways the quality of auxiliary data can be
determined. The quality of the auxiliary data, therefore, has a large bearing on the
reliability of model predictions for the variable of interest. In other words, when good
quality auxiliary data is available one can choose among a number of regression-based
estimators that “borrow strength” from the relationship between the variable of interest
and the auxiliary data; thereby improving the quality of small area estimates/predictions.
Australian Bureau of Statistics 28