Contingencies Online - July/August 2009

We are irrational in systematic ways. Even if there is

not always a method to our madness, there are at least

repeatable patterns that can be studied scientifically.

Bay, Wis., a citizen of Madison, Wis., might adjust the (known) population of Madison upward and a citizen of Chicago might adjust that city’s population downward. But people tend not to adjust far enough—Madisonians’ guesses will be on average too low, and Chicagoans’ guesses will be on average too high.

Ariely’s experiment demonstrates the surprising fact that people’s judgments and decisions can be anchored even by purely arbitrary numbers. Thaler and Sunstein give another example. They asked their students to add 200 to the last three digits of their phone number and guess the year that Attila the Hun invaded Europe (411). Consistent with Ariely, Thaler and Sunstein found that students with high anchors guessed hundreds of years later than students with low anchors. The phenomenon is surprising and of fundamental importance yet easily repeatable in a classroom setting.

Another interesting aspect of Ariely’s experiment is the finding of “arbitrary coherence.” Despite their susceptibility to completely arbitrary anchors, the students’ preferences were consistent in the sense that each student was willing (for example) to pay more for the bottle of wine than for the box of chocolates. However, the strength of the anchoring effect was such that students with the highest anchors were willing to pay more for the chocolates than students with the lowest anchors were willing to pay for the wine! Such findings give the expression caveat emptor an added meaning.

It is not hard to imagine how anchoring is relevant to the buying and selling of insurance. On the one hand, underwriters use rules of thumb and are susceptible to anchoring effects when setting prices for complex risks. On the other, renewing policyholders’ expectations of their future premium are firmly anchored in their previous term’s premium, regardless of whether their risk profile has changed. It is interesting to speculate on the degree to which even arbitrary anchors might influence the amount people are willing to pay for products like extended-warranty insurance or travel insurance.

Another well-known bias is “loss aversion”: The pleasure (utility) of gaining an item is less intense than the pain ( disutility) of giving it up. A particularly interesting manifestation of loss aversion is a phenomenon that Kahneman and Thaler named the “endowment effect”—people often demand more to part with an object than they would be willing to pay to acquire it. To illustrate the endowment effect, Ariely studied a group of basketball fans, some of whom had won tickets to a big Duke Blue Devils basketball game in a lottery. Ariely found that the

winners were willing to part with their tickets for an average of $2,400, while the losers were willing to pay an average of only $175. Not a single ticket changed hands. Apparently, the mere fact of owning an item—even if that item had been won in a purely random lottery—has a powerful effect on the owner’s sense of its value. Loss aversion and the endowment effect are often invoked to explain why homeowners fail to set realistic prices on their homes in a soft housing market. It might also partially explain why insurers are sometimes reluctant to part with unprofitable segments of their books of business.

The “availability heuristic” is particularly relevant to understanding people’s insurance-buying behavior. Thaler and Sunstein describe it thus: People “assess the likelihood of risks by asking how readily examples come to mind.” For example, homicides are more “cognitively available” than suicides, so