Ula Šveikauskaitė
In 2006, economists at the Federal Reserve Bank of New York started to worry about the overheating US housing market. Concerned that the bubble might burst, they used their best model to predict what would happen if house prices dropped by 20 per cent. Not much, was the answer it churned out. Soon after, house prices fell by almost exactly this amount, leading to probably the worst period of global economic decline in a century.
Economics is often lambasted for being a pseudoscience, with dense mathematical formulae that belie its subjectivity and a poor track record of making accurate predictions. J. Doyne Farmer thinks we can do better. In his new book, Making Sense of Chaos, he unpicks why standard economic approaches often fail – and presents a radical alternative. Complexity economics, as it is called, treats economies as systems akin to natural ecosystems or Earth’s climate. Giant computer simulations based on these ideas offer a better representation of how billions of people interact within the global economy.
Farmer currently holds posts at the University of Oxford and the Santa Fe Institute in New Mexico, but his journey into economics has been unconventional. It began when he dropped out of graduate school, built the world’s first wearable computer and used it to beat the casino at roulette. In the 1990s, he set up Prediction Company, where he applied similar principles to the stock market. A pioneer of chaos theory and complex systems, he believes that complexity economics has recently come into its own, making reliable predictions about the…
