ABSTRACT
This chapter moves decidedly into the area of statistical estimation. Using the rate of unemployment as an example, it discusses step-by-step the construction of abstract notions and explains how their final form is the result of an interplay between theoretical purities and empirical considerations. A stylized example is then used to demonstrate the decisions made along the way, and how we actually construct some of our most well-known statistics. In the process, it shows that invariably several related concepts also emerge and are measured, such as underemployment or the participation ratio. The discussion moves into empirical research and provides a framework for how theories drive the construction of indicators and how data analysis feeds back to theories. It then extends to the process of creating abstract notions in general and discusses the example of the gross domestic product as a proxy for the notion of output. Fact-checking tips emphasize the need to know the makeup of key indicators and what they purport to measure, as well as how at times our mental creations may elude our estimation prowess.
