J. Doyne Farmer has been a critic of economics for its subjectivity and inaccurate predictions. In his new book, “Making Sense of Chaos,” he proposes a radical alternative to standard economic approaches known as complexity economics. This approach views economies as systems similar to natural ecosystems or Earth’s climate, and uses large-scale computer simulations to model how billions of people interact within the global economy.
Farmer’s path to economics was unconventional, beginning with dropping out of graduate school to build the world’s first wearable computer, which he used to beat the casino at roulette. In the 1990s, he founded Prediction Company, applying similar principles to the stock market. As a pioneer of chaos theory and complex systems, Farmer believes that complexity economics has now reached a point where it can provide reliable predictions about various economic phenomena.
In 2006, economists at the Federal Reserve Bank of New York became concerned about the overheating US housing market. They worried that the bubble might burst and used their best model to predict the potential impact of a 20 per cent drop in house prices. However, surprisingly, their model predicted that not much would happen. Shortly after, house prices plummeted by almost exactly 20 per cent, triggering one of the worst global economic downturns in a century. This event highlights the limitations of standard economic approaches and underscores the need for an alternative approach like complexity economics.