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Interconnectedness, uncertainty and innovation – Brian Arthur on economic complexity

2014/08/02

The other day, Charles Consult on Twitter drew attention to a fascinating paper by W. Brian Arthur on Complexity Economics.

At a time of never-ending financial crises and lasting imbalances when people are becoming increasingly aware of the shortcomings of traditional economics with its focus on equilibrium as the natural state of an economy, Brian Arthur presents a different approach, a nonequilibrium view of economic processes and structures. In his paper, in acting and interacting firms, consumers, investors and other economic agents collectively create an outcome and then adjust their strategy in response to what they see they have created. The result of these adjustments is another outcome which causes them anew to make revisions – and so forth.

As a consequence, the economy is constantly in motion. It is not “something given and existing but forming from a constantly developing set of technological innovations, institutions, and arrangements that draw forth further innovations, institutions and arrangements.” In this scenario, equilibrium is the exception, not the rule. As the author notes: “For highly interconnected systems, equilibrium and closed form solutions are not the default outcomes; if they exist they require justification.”

Complexity economics is a field of research which developed at the Santa Fe Institute in the late 1980s and which has won many followers worldwide ever since. As the author emphasizes it is not just an extension of standard economics but an entirely different way of seeing the economy. Agents “buy and sell, speculate trade, oversee, bring products into being, offer services, invest in companies, strategize, explore, forecast, compete, learn, innovate, and adapt. In modern parlance we would say it is a massively parallel system of concurrent behavior [my emphasis]. And from all this concurrent behavior markets form, prices form, trading arrangements form, institutions and industries form. Aggregate patterns form.”

“Complexity is about formation—the formation of structures—and how this formation affects the objects causing it.”

Arthur contrasts this view with traditional economics asking not “how agents’ behaviors would react to the aggregate patterns these created, but what behaviors (actions, strategies, expectations) would be upheld by—would be consistent with—the aggregate patterns these caused. It asked in other words what patterns would call for no changes in micro-behavior, and would therefore be in stasis, or equilibrium.”

He gives three examples:

General equilibrium theory is asking what prices and quantities of goods produced and consumed would be consistent with—would pose no incentives for change to—the overall pattern of prices and quantities in the economy’s markets.

Classical game theory asks what strategies, moves, or allocations would be consistent with—would be the best course of action for an agent (under some criterion)—given the strategies,moves, allocations his rivals might choose.

Rational expectations economics asks what expectations would be consistent with—would on average be validated by—the outcomes these expectations together created.

The advantage of the traditional approach is, as Arthur notes, that it is more amenable to mathematical analysis. He admires it for its finesse and mathematical elegance, but “the construct is too pure, too brittle—too bled of reality.” He argues:

“If we assume equilibrium we place a very strong filter on what we can see in the economy. Under equilibrium by definition there is no scope for improvement or further adjustment, no scope for exploration, no scope for creation, no scope for transitory phenomena, so anything in the economy that takes adjustment—adaptation, innovation,structural change, history itself—must be bypassed or dropped from theory. The result may be a beautiful structure, but it is one that lacks authenticity, aliveness, and creation.”
As agents interact, and in interacting create patterns, and then in turn react to the patterns they created together, nonequilibrium arises endogenously in the economy and is not the result of an exogenous disturbance from outside such as a natural disaster after which the economy tends to return to a state of equilibrium again. Arthur gives two main reasons for endogeneity. One is fundamental uncertainty, the other is technological innovation. Both trigger self-reinforcing processes which hinder the economy to come to rest:

Fundamental (or Knightian) uncertainty arises from the fact that “all problems of choice in the economy involve something that takes place in the future, perhaps almost immediately, perhaps at some distance of time.Therefore they involve some degree of not knowing. In some cases agents are well informed, or can put realistic probability distributions over events that might happen; but in many other cases—in fact in most cases—they have no basis to do this, they simply do not know. I may be choosing to put venture capital into a new technology, but my startup may simply not know how well the technology will work, how the public will receive it, how the government will choose to regulate it, or who will enter the space with a competing product. I must make a move but I have genuine not-knowingness—fundamental uncertainty. There is no “optimal” move. Things worsen when other agents are involved; such uncertainly then becomes self-reinforcing. If I cannot know exactly what the situation is, I can take it that other agents cannot know either. Not only will I have to form subjective beliefs, but I will have to form subjective beliefs about subjective beliefs. And other agents must do the same.Uncertainty engenders further uncertainty.”

Technological change is the other driver that hinders the economy from coming to a standstill. Arthur refers to Schumpeter and his view of technology as a source of energy. But he regards this force as even more disruptive:

“Novel technologies call forth further novel technologies: when computers arrive, they call forth or “demand” the further technologies of data storage, computer languages, computational algorithms, and solid-state switching devices. And novel technologies make possible other novel technologies: when the vacuum tube arrives, it makes possible or “supplies” the further technologies of radio transmission and receiving, broadcasting, relay circuits, early computation, and radar. And these novel technologies in turn demand and supply yet further technologies. It follows that a novel technology is not just a one-time disruption to equilibrium, it is a permanent ongoing generator and demander of further technologies that themselves generate and demand still further technologies … Notice again theself-reinforcing nature of this process. The result is not occasional disruption but ongoing waves of disruption causing disruptions, acting in parallel across the economy and at all scales within the economy. Technology change breeds further change endogenously and continually, and this throws the economy into a permanent state of disruption.”

The result of interconnectedness, uncertainty and innovation is complexity:

“A picture is now emerging of the economy different from the standard equilibrium one. To the degree that uncertainty and technological changes are present in the economy—and certainly both are pervasive at all levels—agents must explore their way forward, must “learn” about the decision problem they are in, must respond to the opportunities confronting them. We are in a world where beliefs, strategies, and actions of agents are being “tested” for survival within a situation or outcome or “ecology” that these beliefs, strategies and actions together create. Further, and more subtly, these very explorations alter the economy itself and the situation agents encounter. So agents are not just reacting to a problem they are trying to make sense of; their very actions in doing so collectively re-form the current outcome, which requires them to adjust afresh. We are, in other words, in a world of complexity, a complexity closely associated with nonequilibrium.”

The main part of the paper deals with the implications of this view for theorizing which are truly challenging. But read for yourself …

W. Brian Arthur: Complexity Economics: A Different Framework for Economic Thought,Institute for New Economic Thinking (INET) Research Note #033‚ March 2013.

From → Markets

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