The first are simple systems which are characterized by only a few variables or agents, and which can be described by perhaps a handful of equations (or even one).
The second are systems which are characterized by disorganized complexity. These may consist of huge numbers of agents or variables, and their interactions cannot be described by simple equations; yet the overall system is well-described statistically through averages and can be described as being stochastic. Such systems are typically characterized by a stable equilibrium, provided there are no external shocks to the system. They are incapable of generating internal shocks or surprises. For example, you might consider the distribution of air molecules in a room. You may not be able to predict the motion of any particular air molecule, but you can be reasonable certain that the global population won’t do anything unexpected (like all move into one side of the room leaving a vacuum on the other side).
The third type of system is characterized by organized complexity. As the systems above, one may consist of many variables or agents, each of which is simple, but the system’s behaviour does not lend itself to statistical description because instead of the activities of each component dissolving into a background equilibrium, large-scale (even global scale) structure “emerges” instead of seething chaos. Along with these “emergent properties”, common features of such a system include multiple equilibria, adaptive behaviour, and feedbacks. There is no simple way to describe its behaviour, as much of the system’s history is bound up in its behaviour (what economists call “long memory”).
Complex systems, for all their unpredictability are remarkably resilient. The resilience arises from the way in which this type of system interacts with its environment–through the individual actions of its simple components, the system is able to gather information about its environment and modify its operations to adapt. Yet this adaptation and evolution all occur in the absence of central control.
The above descriptions–and characterizations of three types of systems–go back to 1948. Unfortunately it appears that Dr. Weaver was too optimistic when he recommended science develop an understanding of the third type of system “over the next 50 years”. Here we are 65 years later and we have made only basic improvements in our understanding of such systems.
What has gone wrong? I think it is partly due to the limitations of the Newtonian paradigm on which science has rested over the past few hundred years.
Back to Weaver. He asks,
How can currency be wisely and effectively stabilized? To what extent is it safe to depend on the free interplay of such forces as supply and demand? To what extent must systems of economic control be employed to prevent the wide swings from prosperity to depression? These are also obviously complex problems, and they too involve analyzing systems which are organic wholes, with their parts in close interrelation.
The Fed has answered.
Sixty-five years ago, economics was known to be a complex, organized system. Yet today, the Fed continues to set policy as if the economy were a stochastic system that could be sledgehammered into whatever equilibrium state is deemed politically expedient. I would further argue that the Fed has not managed to succeed even in hammering the economy into a desirable equilibrium, but rather has mastered the ability to create artificial statistics to “justify” its actions.
The system is doomed to fail, because the resilience of natural complex systems requires freedom of action for its individual components. We do not observe resilient complex systems with central control. Yet central control is the dominant ideology of our present political and economic systems. Total control, with a vanishingly thin veneer of democracy, ephemeral as the morning dew.