Economists are scientists. They take data. They run statistical tests. Then, they boil down human behavior to elegant mathematical models: G+I+Xn+C =GDP, MRS=-p1/p2 etc. However, as sophisticated as these models may be, they don’t always work in practice.
Several years ago, the returns of two portfolios compiled by a brie eating, Armani wearing analyst at Merrill Lynch and an innocent monkey throwing darts at a page of the Wall-Street Journal were compared, and the differences were negligible. The Subprime mortgage, created by intelligent Ivy League graduates fluent in computer programming and financial modeling, shattered the global economy and literally brought the house down. Your browser may not support display of this image.
What is missing here? Perhaps we are forgetting that the economy is not just a mechanical equation with inputs and outputs, but rather a group of interacting human beings. According to MIT economist Sendhil Mullaithan, traditional economic models assume people have “unbounded willpower, unbounded rationality” when the average American is stereotyped as someone who suffers from uncontrollable donut cravings and dumps pig leavings in Lake Springfield even when he knows he will get in trouble (think Homer Simpson). While economics is certainly an irreplaceable and vital academic field, economic models often sacrifice practical human behavior for mathematical convenience, and thus should be considered with a grain of salt.
In the past few decades, economists have been pondering a strange phenomenon known as the “equity premium puzzle” that’s inexplicable by mathematics: even if one purchases stocks the day before the black Friday stock market crash of the Great Depression, he or she would still earn more money than someone who invested in bonds; yet, most people still prefer bonds because they are less risky in comparison.
As aforementioned, an economy is composed of human beings. Yes, we are highly intelligent, but we also eat, drink, and breathe. We work for food and survival. We value our families above others, and we evolved from so called “lower animals” (no offense to Creationists among us). Maybe biology—the study of life—could give us some answers.
The field of sociobiology deals specifically with explaining complex human social behavior with evolutionary biology. According to evolutionists Charles Darwin and later William James, behavioral traits like risk aversion are passed down from generation to generation just like blue eyes and double-jointed elbows. Natural selection and sexual selection filter traits that increase the fitness of the individual as well as the species.
In 2006, a group of researchers from the Yale School of Management, led by Dr. Keith Chen, conducted an economic experiment (PDF) with brown, adorable Capuchin Monkeys. The monkeys were trained to purchase various delicacies such as grapes and marshmallows with tokens. Several economic principles were tested; the most relevant result, however, was the monkeys’ reactions in a gambling task.
In scenario one, each monkey was given one grape. Then, based on the outcome of a fair coin flip, the monkey either received one or no extra grape. In scenario two, the monkeys were each given two grapes and, based on the coin flip, the experimenter would either leave the monkey alone or confiscate one grape. Note the average outcome of both scenarios is (0.5)(2)+(0.5)(1)=1.5 grapes.
However, despite the equal outcomes of the two scenarios, the monkeys strongly preferred the first scenario. Mathematics tells us that the monkeys should be indifferent, but the second scenario involves losing something the monkey initially owns, adding emotional weight that ultimately tipped the mathematical balance.
Risk aversion also seems to be ingrained in our neural hardware. In Nathalie Camille’s experiment, normal subjects and people with damage in the orbitofrontal area of their brain were asked to rate their emotional states after making a choice that led either to a $50 or $200 win or to a $50 or $200 loss. When normal subjects learned that their choice led to a $50 win while the alternative would have led to a $200 win, they experienced strong negative emotion. After several trials, the subjects began to make choices that maximize the possibility of not incurring a loss, forfeiting possible economic gains in order to prevent the experience of negative emotions. In contrast, orbitofrontal patients reported no regret and did not adjust their behavior to minimize losses.
Aversion to risk is adaptive and selectively advantageous for good reason. If a gopher hiding behind a rock is indecisive about making a run for its hole and the probability of a hawk descending is 50-50, mathematical models says that the gopher should be indifferent in this decision because the chances of safety and danger are equal. However, what’s at stake here is a matter of life and death, and being extra cautious is a worthwhile sacrifice.
The same logic applies to our financial situation. Granting a subprime mortgage is a gigantic leap of faith for both the lender and the borrower. Essentially, a subprime mortgage means lending to someone who does not have the credibility to qualify for a normal loan, thus creating a gold mine for moral hazard problems. For the borrower, taking out a subprime loan means taking out a loan that can only be repaid under the best possible future scenario; unfortunately, luck was not on our side.
Financial crises like this one are not new. In the past 30 years, excessive risk-taking, overconfidence, regulatory forbearance, and reckless financial innovations played leading roles in the S&L crisis, the 2001 tech bubble, the 1980 Scandinavian financial crisis, the 1997 East Asian financial crisis, and many others. The moral of the stories are similar: greed and social contagion overrode our risk-averse nature, and hell broke loose.
Although risk aversion deviates from standard rational economic behavior and may conflict with certain economic objectives, it protects us from economic disasters that result from speculation bubbles the way it protected our ancestors from becoming snacks of saber-tooth tigers. Indeed, mathematical models are useful and power tools, but perhaps it also helps to, humbly, look into our animal instincts once in a while.