Time and space—an introduction

The games of markets including entrepreneur-driven economic development have always taken place on an arena of the combined material and non-material infrastructure. The infrastructure thus constitutes the arena; it is public capital that facilitates and constrains the rapid “games” of buying and selling that economic agents play. Agents perceive the arena as stable because its evolution is so much slower than that of markets for goods and services. Synergetic theory is well equipped to handle such multiple timescales. Its application to economic phenomena enables us to show that competitive equilibrium theory requires prior specification of the infrastructural arena, which consists of public knowledge, space-bridging networks and institutions. Synergetic theory can also help us avoid the pitfalls of conventional macroeconomic theory. In this chapter, we demonstrate how macroeconomic equilibrium depends on the infrastructure. We claim that all goods are durable and are thus instances of capital. This means that historical trajectories, current outcomes, uncertain expectations and changes in spatial accessibility all influence the growth and fluctuations in the value of capital goods. Dynamic non-linear interactions between scientists, inventors and entrepreneurs affect investments. New technological or design ideas spread most easily among spatially proximate firms within communication and transport networks. Such network effects shape processes of spatial clustering, agglomeration and urbanization. Based on causal and various econometric considerations, it has been common for economists to resort to difference equation in their modeling strategies. But if we include dynamic interactions within a system of difference equations—so as to accommodate realistic causal assumptions—it will often result in complex models with chaotic outcomes. However, there are ways out of chaos in economic modeling. The first is to focus on continuous dynamic synergetic models, which implies a careful separation of variables and dynamic processes according to their relevant timescales as well as the collectiveness of their impacts.