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Is Chaos the Key to Better Economics?
The chaos theorist Doyne Farmer has led an eventful life. He and fellow schemers beat the casinos by inventing a concealable computer that could predict (albeit with low accuracy) where a roulette ball would land. He got a doctorate in physics in …
The chaos theorist Doyne Farmer has led an eventful life. He and fellow schemers beat the casinos by inventing a concealable computer that could predict (albeit with low accuracy) where a roulette ball would land. He got a doctorate in physics in 1981 and took a job at the nuclear weapons laboratory in Los Alamos, N.M., where he did “nonlinear studies,” not weapons research. He co-founded a successful quantitative trading firm, the Prediction Co. And, of course, he worked on chaos theory. Now 72, with an ample white beard, he splits his time between Oxford University and his 46-foot sloop.
This is not a look back on Farmer’s illustrious career, because he is as busy as ever. He recently co-founded a company called Macrocosm that’s using insights from chaos theory and a field called complexity economics to fight climate change and other knotty problems. He also just wrote a book, “Making Sense of Chaos: A Better Economics for a Better World.”
Farmer is the director of complexity economics at the Institute for New Economic Thinking at Oxford’s Martin School, which operates separately from the U.S.-based institute of the same name. Both have received major funding from the financier and philanthropist George Soros.
In “Making Sense of Chaos,” Farmer writes that in mainstream models, the economy always tends toward equilibrium, like a rocking horse that rocks when it’s whacked with a stick but eventually settles down (to use the analogy of the Swedish economist Knut Wicksell, who died in 1926).
In fact, Farmer argues, a lot of the economy’s ups and downs come from internal forces, not external ones. As a result, the economy never settles down into a quiet equilibrium. It behaves chaotically.
Chaos to Farmer isn’t a messy sock drawer. It has two qualities: sensitive dependence on initial conditions, such that a tiny change in how things start off can lead to dramatic differences in what happens later; and endogenous motion — the notion that the system never settles because it generates its own churning.
