W. Brian Arthur


New Paper

"Complexity Economics: A New Framework for Economic Thought"


Preface to new book: Complexity and the Economy


Complexity In The Economy

Arthur speaking at INET's Bretton Woods Conference 2011






























































Complexity Economics

"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"The neoclassical era in economics has ended and has been replaced by the complexity era."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 about Complexity Economics

Q.   What's going on here?

A.   A major change in happening in economics. For the last two or three decades, economists have felt that their standard approach, neoclassical economics, has become too removed from reality, with its assumptions that people are hyper-rational and make decisions in a static, equilibrium world. So economics has been branching out and looking at more realistic assumptions. Hence we are seeing the coming in of behavioral economics, increasing returns economics, evolutionary game theory. And 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 cars in traffic, and they may react to neighboring cells’ states, or to cars in front or behind them—“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. 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? 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. 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 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.  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; John Holland, computer scientist. Frank Hahn, Arrow, and Tom Sargent were visitors. Out of that a lot of work came. There have been mnay others involved of course, and I'd like to mention in particular Peter Allen, Rob Axtell, Eric Beinhocker, Josh Epstein, Doyne Farmer, Alan Kirman, and Leigh Tesfatsion. Now this approach is thriving and younger people are coming along. But the Santa Fe group was the first coherent effort in this area, and laid down much of the approach.

Q.  Doesn't this nonequilibrium 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. You talk about two great problems in economics. What are they?

A. One is allocation within the economy: how quantities of goods and services and their prices are determined within and across markets. This is represented by the great theories of general equilibrium, international trade, and game-theoretic analysis. The other is formation within the economy: how an economy emerges in the first place, and grows and changes structurally over time. This is represented by ideas about innovation, economic development, structural change, and the role of history, institutions, and governance in the economy. The allocation problem is well understood and highly mathematized, the formation one less well understood and barely mathematized. Complexity economics looks at structures forming in the economy, so it's just as much concerned with formation as with allocation.

Q.  Isn't all this controversial?

A.  No, not any more. Complexity economics is an extension of equilibrium economics to the nonequilibrium case. And since nonequilibrium contains equilibrium it's a widening of economics — a generalization. So that's not controversial, that's inevitable. It's really the beginning of a lot of work to be done.

Q. If it's as important as you say, why are we not seeing more of complexity economics in standard departments?

A.  Well, we are seeing quite a bit. But it takes about a generation or more for any science to change. Rob Axtell is fond of pointing out that game theory took about 40 to 50 years to fully make its way into economics. And behavioral economics which got started in the 1960s is only now fully arriving. By that measure complexity economics still has a good 20 or 30 years to go. The compensation is that it's fun to work on a field that's opening up, and I think this form of economics is only beginning.

Q. You've said that complexity economics is inevitable. Why?

A. It's not a matter of taste. All the sciences are changing from looking at the world as highly ordered, mechanical, predictable, and in some sort of stasis; to looking at is as evolving, organic, not predictable, and in perpetual discovery. Physics, chemistry, mathematics, geology — they've all moved this way. Economics will too, it's slightly behind but it always tracks the Zeitgeist.

Q. Is there a killer app for complexity economics? Something that can't be done without it?

A. I can think of two. One is the increasing-returns work done in the 1980s that shows how network effects lead to lock-in and dominance of one or a few players. This can't be done by equilibrium economics — it's not an equilibrium phenomenon. Now all of Silicon Valley accepts this theory and operates by it.

The other killer app is asset pricing. Complexity doesn't assume there is a (rational-expectations) equilibrium and set out to find it. It assumes investors don't know what the market is doing and must learn for themselves what works — which itself changes the market. The results show phenomena seen in real markets: technical trading, correlations among price and volume, and periods of high volatility followed by low volatility (GARCH behavior). The theory explains real world financial phenomena.