Doyne Farmer

Sante Fe Institute

J. Doyne Farmer is a professor at the Santa Fe Institute. He has broad interests in complex systems, and has done research in dynamical systems theory, time series analysis and theoretical biology. At present his main interest is in developing quantitative theories for social evolution, in particular for financial markets (which provide an accurate record of decision making in a complex environment) and the evolution of technologies (whose performance through time provides a quantitative record of one component of progress). He was a founder of Prediction Company, a quantitative trading firm that was recently sold to the United Bank of Switzerland, and was their chief scientist from 1991 - 1999. During the eighties he worked at Los Alamos National Laboratory, where he was an Oppenheimer Fellow, founding the Complex Systems Group in the theoretical division. He began his career as part of the U.C. Santa Cruz Dynamical Systems Collective, a group of physics graduate students who did early research in what later came to be called "chaos theory". In his spare time during graduate school he led a group that designed and built the first wearable digital computers (which were used to beat the game of roulette). For popular press see The Newtonian Casino by Thomas Bass, Chaos by Jim Gleick, Complexity by Mitch Waldrup, and The Predictors by Thomas Bass.

My Video Content

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The Inaugural Conference @ King's, Institute for New Economic Thinking, Day 2 – Lunch: Networks and Systemic Risks

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J. Doyne Farmer, professor at the Santa Fe Institute, notes that data sets in economics research are not nearly as complicated as those generated in other sciences. Interviewed by Peter Leyden at King's College, April 2010.

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J. Doyne Farmer, professor at the Santa Fe Institute, says that the core ideas in economics will shift entirely within 25 years. And this can already be seen: economists, he says, are even now studying issues like "what makes people happy." Interviewed by Peter Leyden at King's College, April 2010.

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Much of today’s economics is based on abstract modeling of complex systems – but a lot of the theories behind the models are overly simplistic, and do not have predictive capabilities. The economics field can do much, much more, according to J. Doyne Farmer, professor at the Santa Fe Institute.

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About the Interview

In 2006, the Fed asked its macroeconometric model what would happen if house prices dropped by 20%. The model projected the past into the future and said: "Not much." Well, the financial crisis proved it wrong. Meanwhile, DSGE models, the main alternative up to this date, do not feature financial institutions; "They are not even good enough to be wrong," says Doyne Farmer. That's why Farmer and his team are developing an agent-based model, of the housing market first and of the entire economy next, to mimic the current financial crisis. The team collects data on actual people to calibrate a rich model with millions of interacting agents. This is a bottom-up approach to macroeconomics -- this is new economic thinking.

My Grants

Doyne Farmer of the Santa Fe Institute, Robert Axtell, John Geanakoplos, and Peter Howitt were awarded a grant by the Institute for New Economic Thinking to create a computational model of the current financial crisis.