As pointed out in the Introduction, a macro economy consists of many micro agents. These agents are not independent of each other, but form networks, i.e., they have relationships among each other. An understanding of their interactions is crucial for an understanding of a macro economy.

This chapter explains the basic concepts and techniques for understanding the structure of economic networks, and then applies them to economic networks. Economic networks are not random nor regular, but exhibit fat-tailed distributions for the numbers and weights of relationships. They also form densely knit groups that are only loosely connected with each other, called clusters or communities.

Basic tools cover

We will show that one can retrieve interesting information and implications by applying network analyses to these applications.

Basic Tools

Graph search and simple applications

Computational algorithms for simulation on a network are often based on graph-search algorithms and their modifications. Graph search refers to a way of visiting nodes and/or edges exhaustively by putting “marks” on them in a systematic manner. It is analogous to the well-known Greek tale about the hero, Theseus, who successfully escaped from a labyrinth of Minotaur by following Ariadne's thread, but is far more elaborate.