“The field of economics is going through its most profound change in over a hundred years.”
— E. Beinhocker, The Origin of Wealth: Evolution, Complexity and the Radical Remaking of Economics (2006)
“The neoclassical era in economics has ended and has been replaced by the complexity era.”
— R.P. Holt, J.B. Rosser, and D. Colander, “The Complexity Era in Economics,” (2010)
Some Q & A
Q. What’s going on here?
A. A major change in happening in economics, one that’s long overdue in my opinion. For the last two or three decades, economists have felt that their standard approach — neoclassical economics — has become too unrealistic, too far from reality, with its assumptions that people are hyper-rational and make decisions in a static, equilibrium world. So economics has been slowly groping toward a more realistic picture of the economy. And since the financial crisis there’s a feeling that economics has failed, that the standard approach has delivered much, but is surprised by bubbles and crashes, That it leaves out history, process, and institutions, that it doesn’t deal with real human behavior. Hence we are seeing the coming in of behavioral economics, information economics, increasing returns economics, evolutionary game theory, and various forms of generative economics. One of these is complexity economics.
Q. So what is complexity economics?
A. Well, it’s really a different way of looking at the economy. Complexity isn’t so much a subject as a movement across all the sciences. Complex systems are ones with multiple elements adapting or reacting to the pattern these elements create. The elements might be cells in a cellular automaton, or cells in an immune system, and they may react to neighboring cells’ states, or concentrations of B and T cells—“elements” and the “patterns” they respond to vary from one context to another. But the elements adapt to the world—the aggregate pattern—they co-create. Time enters naturally here via adjustment and change: as the elements react, the aggregate changes, as the aggregate changes, elements react anew.
Complex systems arise naturally in the economy. Economic agents, whether they are banks, consumers, firms, or investors, continually adjust their market moves, buying decisions, prices, and forecasts to the situation these moves or decisions or prices or forecasts together create. So complexity’s a natural way to look at the economy, and in a way it’s been around for 200 years in economics. It’s really an economics of things coming into being and it focuses on patterns forming, structures changing, innovation, and the consequences of permanent disruption.
Q. Is there a logical basis for the complexity view?
A. There is. As I said, the players in the economy continually adjust their market decisions, strategies, and forecasts to the situation these moves or decisions or strategies or forecasts together create. So it might be natural in such a setting for economic theorists to study the unfolding of patterns that economic agents create. But this obviously is complicated. And so to seek analytical solutions, historically economics chose to simplify its questions. It asked instead what behavior caused an outcome or pattern that leads to no incentive to change that behavior. In other words, it asked what patterns in the economy would look like if they were at equilibrium—were consistent with the micro-behavior (actions, strategies, expectations) that creates them. Thus, for example, general equilibrium theory asks: What prices and quantities of goods produced and consumed are 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 are consistent with—would be the best course of action for an agent (under some criterion)—
given the strategies, moves, allocations his rivals might choose? Partial-equilibrium economics—say in international trade theory—asks: what local behaviors would produce larger patterns that would support (be consistent with) those local behaviors. This was a natural way to approach the economy, but one that has run into diminishing returns.
It is natural to go beyond this equilibrium approach and ask how agents’ behavior might not just be consistent with the aggregate pattern it creates, but how actions, strategies, or expectations might in general react to—might endogenously change with—the patterns they create. In other words, it is natural to ask how the economy behaves when it is not at a steady state—when it is out of equilibrium. That is complexity economics. At this more general level, we can surmise that economic patterns might settle down over sufficient time to a simple, homogeneous equilibrium. Or, that they might not: they might show ever-changing, perpetually novel behavior. We might also surmise they might show new phenomena that do not appear in steady state.
Q. So complexity economics and nonequilibrium economics are closely related?
A. They are. In fact, I’d prefer to think of nonequilibrium economics. I cooked up the label “complexity economics” when I did a piece on this for Science in 1999. The editor asked me to name this approach and so I called it “complexity economics.” I regret this slightly. Nonequilibrium emphasizes disruption — the constant disruption that comes from agents adjusting to a situation that’s always changing. Complexity emphasizes agents reacting to changes that other agents make. The two concepts are indeed closely related.
Q. Complexity and uncertainty are related too, aren’t they?
A. Yes. In the complexity approach, you can’t assume that all problems that agents face are well defined. This is because agents simply don’t know how other agents might react. They don’t know how others see the same problem. Therefore there is real Knightian uncertainty. This means that agents need to cognitively structure their problems — the have to “make sense” of them, as much as solve them. So this brings us into the world of cognition, and of behavioral economics.
Q. Doesn’t this non-equilibrium and complexity view go back a long way in economics?
A. There’s indeed a long history of this line of thinking in economics. Many of the themes we are exploring — innovation, disruption, deciding under real uncertainty — occur in Schumpeter, Veblen, Hayek, Shackle, and others. They aren’t exactly new in economics. What’s changed is that we can now investigate them rigorously. We have far more tools at our disposal, including much more sophisticated probablity theory and the possibility of doing carefully controlled computer experiments.
Q. How did you get into this area?
A. Throughout the 1980s I’d been working on increasing returns economics — now very much a branch of complexity. I was at Stanford, and in 1987 Kenneth Arrow invited me to the Santa Fe Institute, then just starting. I was brought back a year later to direct a research program on “The Economy as an Evolving Complex System.” This turned out to be SFI’s first research program. We began to ask: what would it be like to do economics out of equilibrium. I had excellent people: David Lane, probability theorist; Richard Palmer, physicist; Stu Kauffman, theoretical biologist; and others. Frank Hahn, Arrow, and Tom Sargent were visitors. Out of that a lot of work came. There have been others involved in parallel efforts or course, and now this is thriving. But the Santa Fe group was certainly one of the first, and laid down much of the approach.
Q. Is complexity economics a fad? Do you think it’s here to stay?
A. It’s only a fad if you think that looking at structures forming in the economy and the consequences of disruption are fads. We badly need an economics that does this. We need an economics based on realistic assumptions, and on living realities, not on hyper-rationality and static equilibria.