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These days it's hard to have a conversation about real estate without hearing the term "housing bubble." As this ScienCentral News video reports, a geophysicist says he predicted the current U.S. housing bubble — and when it would burst.
Predicting Catastrophe
Those who live in earthquake zones know their houses could one day come crashing down. But UCLA geophysicist Didier Sornette says he used the same theory that can help predict earthquakes, to pinpoint when the U.S. housing market would crumble. He says the warning signs have been building for a few years.
As reported in Discover magazine, Sornette studies what's known as "complexity theory" to try to predict how a system will behave in the future. He uses physics and statistical analysis to look at the organization of the dynamic parts of a complex system, and how these parts interact to cause something major to happen. For example, when a multitude of physical changes affect the organization of the earth's crust to produce an earthquake.
"It emphasizes the whole more than the parts, it emphasizes the interactions and what we call the feedback," he says.
image: Zhou and Sornette
The interplay of the elements is affected by both positive and negative feedback. Negative feedback is often obvious. For example, when real estate prices are inflated many people decide to sell with the hope of making a nice profit. Eventually more houses are available for sale than there are buyers, so the prices start to drop back to normal. "Positive feedback is exactly the opposite. A high price pushes the price still higher," explains Sornette. "This is the expectation of people that lead [people] to buy houses at prices that they would never have bought otherwise and taking supposedly big risks… first buyers, for example — you're a young couple relatively at the early stage of your life and you think, 'Well if I don't buy now… .'"
Applying complexity theory to the interplay within the real estate business, Sornette saw that a housing bubble has been building in 22 states, mostly in the northeast and western U.S., since 2003 — and has now reached bursting point. In 2005 he predicted that in the first half of 2006 prices would level out or return to normal rather than crash.
"It's absolutely non-sustainable," he says. "This bubble is basically ending now, and has, has ended in some cases… and now the market is transitioning into a more stable kind of plateau."
Sornette defines a housing bubble as a situation when house prices climb continually and unexplainably fast — faster than exponential growth — resulting in market prices that are vastly inflated from the fundamental value of the house. "The fundamental value of a house, well this is the value, the price, that takes into account all the services, all the income you should get from this house," he explains. "For example we get service from it, of course you profit from it by living in it, or you could rent the house — this would give you a flow of income."But even in a bubble people keep rushing to buy. Sornette says there's one thing that keeps people buying — what he calls "the greater fool" theory. "The faith that you'll be able to sell it in the future to a greater fool than yourself for an even higher price."
Not everyone accepts Sornette's theory. University of Houston econo-physicist Joseph McCauley says although the idea of a housing bubble still hasn’t been precisely defined, , Sornette has developed a very interesting model, but it includes too many factors to be fully provable.
"The bottom line is that his model has too many parameters in it. That's not, what we call in physics, falsifiable. If you have too many parameters in a model, you can always fit it to the data, and the data can never tell you what's wrong with the model," says McCauley, who is a senior fellow with the Computable and Behavioural Research Axis (COBERA), in the department of Economics at the National University of Ireland, Galway. "I'd like to see him or someone else go back and get rid of the freedom in this model, constrain it… so that it really could be considered hard science."
He adds that, "True complexity is based on surprises, and we don't really have any mathematical way of dealing with surprises at this stage."
Sornette agrees his is only one way of defining a bubble. But he says his method has been successfully tested in many other systems — from extreme weather phenomena to stock market crashes.
Sornette hopes continued testing of his theory will improve people's trust in it, and offer better understanding of how complex systems work.
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