Oxford University professor Doyne Farmer traces his research exposing risks in the financial system to the roulette wheels of Las Vegas.
In the 1970s, Farmer and two fellow physics students at the University of California at Santa Cruz built a computer small enough to hide in a shoe that helped them predict roughly where roulette balls would land. At casinos in Vegas, they communicated with toe-controlled switches and transmitters, also in their shoes, about what bets to make. The gadget was legal, but they feared their winnings—about a 20% return on their wagers—would lead to trouble. So they quit after a couple of years.
“We were nervous about getting our kneecaps broken,” he explains.
Today, in a more bucolic setting—the Institute for New Economic Thinking at the Oxford Martin School—Farmer is drawing on decades of complexity research that began with roulette. After winning acclaim as a pioneer of chaos theory, which helps explain the unpredictability of complex systems such as the weather, he jumped into markets, co-founding one of the early quantitative investment firms in the 1990s. Now, Farmer and a band of central bank researchers are focusing on the tangled web of global finance, using a tool of the natural sciences called agent-based models to find dangers lurking in the system and uncover ways to avoid them.
Agent-based models, used in fields from biology to sociology, are bottom-up, simulating the messy interactions of hundreds and even millions of agents—human cells or attitudes or financial firms—to explain the behavior of a complex system. The nonlinear interplay can produce unexpected phenomena, such as economic booms and busts, providing insights into the causes of events and the best responses. Epidemiologists have successfully deployed the models for years to test strategies to control everything from obesity to the spread of infectious diseases, including the flu.
Central banks worldwide began experimenting with the agent-based approach after macroeconomists and their standard models were blindsided by the 2008 financial crisis. The European Central Bank, where Farmer is a consultant, as well as central banks in Canada, Germany, South Africa, and the U.K. have taken the lead in building the models to research financial risk. The U.S. Federal Reserve’s regulatory staff is also exploring their use.
Today, central banks mostly stress-test financial firms individually. But agent-based models are giving regulators a better read by accounting for the systemwide impact of shocks. In the simulations, a shock to a single firm cascades through the network of banks and asset managers, creating feedback loops that significantly amplify the initial losses. It’s the kind of contagion that a decade ago spread from the U.S. subprime mortgage market through lenders, money managers, and insurers, creating a liquidity crisis that doomed Lehman Brothers Holdings Inc. and infected the global economy.
“There are efforts at central banks to integrate systemic stress testing,” says Co-Pierre Georg, a research economist at Germany’s central bank (but he doesn’t speak for it). “The banks are highly interconnected and highly leveraged. We now know from Lehman that if something happens to one big bank it can be devastating to the entire economy.”
Farmer, 67, a gray-bearded scientist whose papers have garnered more than 34,500 citations, can be a provocateur. He sees central banks as a beachhead for a bigger challenge to mainstream economics. In a coming book, he says economists in academia resist new approaches such as agent-based models.
It’s a sentiment shared by Bank of England Chief Economist Andrew Haldane, who’s helping lead the push for alternative research. In 2017, Haldane called his profession “insular” for its subpar track record in citing work from other disciplines in its academic journal papers. Farmer says the prestigious top five economic journals rarely if ever publish worthy agent-based model papers, including his own. The American Economic Review says papers are evaluated on their merits without bias.
Many macroeconomists shrug off Farmer’s criticism. He’s a physicist, they say, not an economist, and agent-based models have yet to provide real-world verifiable results.
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October - November 2019