Loss aversion and ‘thinking’ about the house price collapse (in Ireland and further afield)
There has been a dramatic collapse in house prices in many parts of the world, including Ireland, which has seen prices come down by 40% or so on average since the peak a few years ago (and more to come, according to some economists). The market is now very slow-moving, and probably as bad as it ever has been. And given past patterns, will probably take a decade to recover. Jonah Lehrer has a fantastic post on the pervasive phenomenon of loss aversion in human cognition which must underpin at least some of the problems in the market, because of the aversion and indeed pain caused by recognising losses quickly.
Key quote: “The pain of a loss was approximately twice as potent as the pleasure generated by a gain. Furthermore, our decisions seemed to be determined by these feelings. As Kahneman and Tversky put it, “In human decision making, losses loom larger than gains.”
[Blog reproduced in full]
The Real Estate Collapse By Jonah Lehrer
The news on the housing front is bleak and getting bleaker. The New York Times posts a graph that captures the trend:
Obviously, a stew of forces are at work here. There is the end of the federal tax credit, and the crappy employment news, and the shadow inventory of foreclosed homes. But I think the dismal housing data also reflects a systematic human bias: loss aversion. The phenomenon was first identified by Daniel Kahneman and Amos Tversky in the mid-70s, after they gave their students at Hebrew University a simple survey asking them whether or not they’d accept a variety of different bets. The psychologists noticed that, when people were offered a gamble on the toss of a coin in which they might lose $20, they demanded an average payoff of at least $40 if they won. The pain of a loss was approximately twice as potent as the pleasure generated by a gain. Furthermore, our decisions seemed to be determined by these feelings. As Kahneman and Tversky put it, “In human decision making, losses loom larger than gains.”
Consider this scenario:
The U.S. is preparing for the outbreak of an unusual Asian disease, which is expected to kill 600 people. Two alternative programs to combat the disease have been proposed. Assume that the exact scientific estimates of the consequences of the programs are as follows: If program A is adopted, 200 people will be saved. If program B is adopted, there is a one-third probability that 600 people will be saved and a two-thirds probability that no people will be saved. Which of the two programs would you favor?
When this question was put to a large sample of physicians, 72 percent chose option A, the safe-and-sure strategy, and only 28 percent chose program B, the risky strategy. In other words, physicians would rather save a certain number of people for sure than risk the possibility that everyone might die. But what about this scenario:
The U.S. is preparing for the outbreak of an unusual Asian disease, which is expected to kill 600 people. Two alternative programs to combat the disease have been proposed. Assume that the exact scientific estimates of the consequences of the programs are as follows: If program C is adopted, 400 people will die. If program D is adopted, there is a one-third probability that nobody will dies and a two-thirds probability that 600 people will die. Which of the two programs would you favor?
When the scenario was described in terms of deaths instead of survivors, physicians reversed their previous decision. Only 22 percent voted for option C, while 78 percent of them opted for option D, the risky strategy. Most doctors were now acting just like Frank: they were rejecting a guaranteed gain in order to partake in a questionable gamble.
Of course, this is a ridiculous shift in preference. The two different questions examine identical dilemmas; saving one third of the population is the same as losing two thirds. And yet, doctors reacted very differently depending on how the question was framed. When the possible outcomes were stated in terms of deaths – this is the “loss frame” – physicians were suddenly eager to take chances. They were so determined to avoid any alternative associated with a loss that they were willing to risk losing everything.
The same irrational quirk is now playing out in the U.S. housing market. Look, for instance, a 2001 paper by the economists Christopher Mayer and David Genesove. They studied the Boston condominium market of the early 1990s, which was one of the most spectacular real estate busts in recent decades. Between 1989 and 1992, Boston condo prices fell by nearly 40 percent. This meant that, for the vast majority of condo owners, they could only sell their home at a steep loss.
Classical economics assumes that people will adjust to the new reality. They’ll realize that the market has changed, and that they made a costly mistake. But that’s not what happened. In their paper, “Loss Aversion and Seller Behavior: Evidence From the Housing Market,” Mayer and Genesove found that, for essentially identical condos, people who had bought at the peak of the market (between 1989-1992) listed their properties for nearly 35 percent more than those who had bought after the collapse. Why? Because they couldn’t bear to take a loss.
The end result, of course, is that these overpriced properties just sat there, piling up like unwanted inventory. According to the economists, less than 25 percent of the properties bought during the condo bubble sold in less than 180 days.
I’d argue that the same thing is happening right now, except on a nationwide scale. The housing market will only recover when we get over our collective bias, and realize that home prices have fallen and aren’t coming back (at least not anytime soon). Our irrationality got us into this mess – we binged on credit cards and took out unreasonable loans and mistook a bubble for a boom – and the only way we’re going to get out of it is to see through a new set of irrational quirks, which prevent us from fully equilibrating to our new financial reality. Sometimes, the wisest thing to do is cut our losses and run.