Neoclassical economics, both its assumptions and its ability to forecast future economic activity, has been taking a bit of a panning recently. Back near the start of this most recent economic downturn, Jean-Philippe Bouchard argued that neoclassical economists need to develop more pragmatic and realistic representations of what actually happens in ‘wild’ and messy free markets. And at the start of this year I highlighted how Niall Ferguson has stressed the importance of considering history in economic markets and decision-making. In both cases the criticism is that some economists have been blinded by the beauty of their elegant models and have failed to see where their assumptions and idealizations fail to match what’s happening in the real world. Most recently, Paul Krugman argued that ‘flaws-and-frictions economics’ (emphasizing imperfect decision-making and rejecting ideas of a perfectly free ‘friction-less’ market) must become more important. Krugman (‘friend’ of Niall Ferguson) suggests that mainstream economics needs to become more ‘behavioural’, and follow the lead of the behavioural economists that incorporate social, cognitive and emotional factors into their analyses of human decision-making.
The view from the Nature editors on all this is that in the future agent-based modelling will be an important tool to inform economic policy. In many ways agent-based modelling is very well suited to build more ‘behaviour’ into economics. For example, agent-based modelling provides the ability to represent several types of agent each with their own rules for decision-making, potentially based on their own life-histories and circumstances (this in contrast to the single perfectly rational ‘representative agent’ of neoclassical economics). Farmer and Foley, in their opinon piece of the same issue of Nature, are keen:
“Agent-based models potentially present a way to model the financial economy as a complex system, as Keynes attempted to do, while taking human adaptation and learning into account, as Lucas advocated. Such models allow for the creation of a kind of virtual universe, in which many players can act in complex — and realistic — ways. … To make agent-based modelling useful we must proceed systematically, avoiding arbitrary assumptions, carefully grounding and testing each piece of the model against reality and introducing additional complexity only when it is needed. Done right, the agent-based method can provide an unprecedented understanding of the emergent properties of interacting parts in complex circumstances where intuition fails.”
At the very least, our agent-based models need to improve upon the homogenizing assumptions of neoclassical economics. It takes all sorts to make a world — we need to do a better job of accounting for those different sorts in our models of it.