Measurement of Complexity

This chapter introduces different ways of measuring aspects of complexity. This book is based on the scientific view that measurement enforces precision and links theory to fact. Since complexity is a multidimensional concept, there is no single way to measure it. Many attempts to quantify complexity rely on Shannon entropy from information science, which is explained in detail. How Shannon entropy and other measures can be applied in economics is demonstrated with a number of examples. We can measure the complexity of patterns in data or the complexity of systems. Aspects of system complexity are structural complexity, functional complexity, cyclomatic complexity, and organizational complexity. It is also shown how we can distinguish between objective and subjective complexity and how both contribute to the complexity of a system.