By Robert D. Atkinson

If there was any possible upside from the destruction stemming from the financial crisis and Great Recession it was that neoclassical economics’ intellectual hegemony began to be more seriously questioned.  As such, the rising interest in complexity theory is a welcome development. Indeed, approaching economic policy from a complexity perspective promises significant improvements.  However, this will only be the case if we avoid a Hayekian passivity grounded in the view that action is too risky given just how complex economic systems are. This would be a significant mistake for the risk of non-action in complex systems is often higher than the risk of action, especially if the latter is informed by a rigorous thinking grounded in robust argumentation.

The flaws of neoclassical economics have long been pointed out, including its belief of the “economy as machine”, where, if policymakers pull a lever they will get an expected result. However, despite what Larry Summers has written, economics is not a science that applies for all times and places. It is a doctrine and as economies evolve so too should doctrines. After the Second World War, when the United States was shifting from what Michael Lind calls the second republic (the post-Civil War governance system) to the third republic (the post-New-Deal, Great Society governance structure), there was an intense intellectual debate about the economic policy path America should take.  In Keynes Hayek: The Clash that Defined Modern Economics, Nicholas Wapshott described this debate between Keynes (a proponent of the third republic), who articulated the need for a larger and more interventionist state, and Hayek (a defender of the second republic), who worried about state over-reach. Today, we are in need of a similar great debate about the future of economic policy for the emerging “fourth republic.”

If we are to develop such an economic doctrine to guide the current socio-technical economic system, then complexity will need to play a foundational role.  But a risk of going down the complexity path is that proponents may substitute one ideology for another.  If today’s policy makers believe that economic systems are relatively simple and that policies generate only first-order effects, policymakers who have embraced complexity may believe that second, third, and fourth order effects are rampant. In other words, the butterfly in Mexico can set off a tornado in Texas. If things are this complex, we are better off following Hayek’s advice to intervene as little as possible. At least with a mechanist view, policymakers felt they could do something and perhaps they got it right. Hayekian complexity risks leading to inaction.

This gets to a second challenge, “group think.”  Many advocates of complexity point to complex financial tools (such as collateralized debt obligations, CDOs) as the cause of the financial crisis.  Regulators simply didn’t have any insight because of the complexity of the instruments.  But these tools were symptoms.  At the heart of crisis, at least in the United States, was mortgage origination fraud.  The even more serious problem was intellectual: virtually all neoclassical economists subscribed to the theory that in an efficient market, all the information that would allow an investor to predict the next price move is already reflected in the current price. If housing prices increase 80 percent in just a few years, then their actual worth increased 80 percent. So any reset of economics has to be based not just on replacing many of the basic tenets of neoclassical economics, it has to be based on replacing a troubling tendency toward group think.  Yet, replacing the former may indeed be harder than the latter.

So where should we go with complexity? I believe that a core component of complexity is and should be evolution.  In an evolutionary view, an economy is an “organism” that is constantly developing new industries, technologies, organizations, occupations, and capabilities while at the same time shedding older ones that new technologies and other evolutionary changes make redundant. This rate of evolutionary change differs over time and space, depending on a variety of factors, including technological advancement, entrepreneurial effort, domestic policies, and the international competitive environment.  To the extent that neoclassical models consider change, it is seen as growth more than evolution. In other words, market transactions maximize static efficiency and consumer welfare. As Alan Blinder writes, “Can economic activities be rearranged so that some people are made better off, but no one is made worse off? If so we have uncovered an inefficiency. If not, the system is efficient.”

In complexity or evolutionary economics, we should be focusing not on static allocative efficiency, but on adaptive efficiency. Douglass North argues that: “Adaptive efficiency…is concerned with the kinds of rules that shape the way an economy evolves through time. It is also concerned with the willingness of a society to acquire knowledge and learning, to induce innovation, to undertake risk and creative activity of all sorts, as well as to resolve problems and bottlenecks of the society through time.” Likewise, Richard Nelson and Sidney G. Winter wrote in their 1982 book An Evolutionary Theory of Economic Change, “The broader connotations of ‘evolutionary’ include a concern with processes of long-term and progressive change.”

This provides a valuable direction. It means that a key focus for economic policy should be to encourage adaptation, experimentation and risk taking. It means supporting policies to intentionally accelerate economic evolution, especially from technological and institutional innovation. This means not only rejecting neo-Ludditism in favor of techno-optimism, it means the embrace of a proactive innovation policy. And it means enabling new experiments in policy, recognizing that many will fail, but that some will succeed and become “dominant species.” Policy and program experimentation will better enable economic policy to support complex adaptive systems.

Originally published at OECD.

2016 October 1