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Loss Aversion
Kahneman and Tversky’s most important contribution is
called prospect theory, which describes individual behavior in
the face of risky situations where there are prospects of gains
and losses. In general, financial economists such as Harry
Markowitz constructed models where individuals made
decisions based on the likely effect of those choices on the
person’s final wealth. Prospect theory challenges that
assumption. People’s choices are motivated instead by the
values they assign to gains and losses. Losses are considered
far more undesirable than equivalent gains are desirable.
Moreover, the language used to present the possible gains and
losses will influence the final decision that is made. In
psychological terms, this is known as “how the choice is
framed.”
For example, you are told that a fair coin will be flipped
and that if it comes up heads you will be given $100. If the
coin comes up tails, however, you must pay $100. Would
you accept such a gamble? Most people would say no, even
though the gamble is a fair one in the sense that in repeated
trials you would end up even. Half the time you would gain
$100 and half the time you would lose $100. In mathematical
terms, the gamble has an “expected value” of zero, calculated
as follows:
Probability of heads payoff if heads + probability of tails
payoff if tails Expected value.
Expected value ½($100) + ½ (–$100) 0.
Kahneman and Tversky then tried this experiment with
many different subjects, varying the amount of the positive
payoff to test what it would take to induce people to accept
the gamble. They found that the positive payoff had to be
about $250. Note that the expected value of the gain from
such a gamble is $75, so this is a very favorable bet.
Expected value ½($250) + ½ (–$100) $75.
Kahneman and Tversky concluded that losses were 2½
times as undesirable as equivalent gains were desirable. In
other words, a dollar loss is 2½ times as painful as a dollar
gain is pleasurable. People exhibit extreme loss aversion, even
though a change of $100 of wealth would hardly be noticed
for most people with substantial assets. We’ll see later how
loss aversion leads many investors to make costly mistakes.
Interestingly, however, when individuals faced a situation
where sure losses were involved, the psychologists found
that they were overwhelmingly likely to take the gamble.
Consider the following two alternatives:
1. A sure loss of $750.
2. A 75% chance to lose $1,000 and a 25% chance to lose
nothing.
Note that the expected values of the two alternatives are
the same—that is, a loss of $750. But almost 90 percent of
the subjects tested chose alternative (2), the gamble. In the
face of sure losses, people seem to exhibit risk-seeking
behavior.
Kahneman and Tversky also discovered a related and
important “framing” effect. The way choices are framed to
the decision maker can lead to quite different outcomes. They
posed the following problem.
Imagine that 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.
Note first that the expected value of the number of people
saved is the same 200 in both programs. But according to
prospect theory, people are risk-averse when considering
possible gains from the two programs, and, as expected,
about two-thirds of the respondents to this question picked
Program A as the more desirable.
But suppose we framed the problem differently.
If Program A* is adopted, 400 people will die.
If Program B* is adopted, there is a one-third
probability that nobody will die and a two-thirds
probability that 600 people will die.
Note that the options A and A* as well as B and B* are
identical. But the presentation in the second problem is in
terms of the risks of people’s dying. When the problem was
framed in this way, over 75 percent of the subjects chose
Program B*. This illustrated the effect of “framing” as well as
risk-seeking preferences in the domain of losses. When
doctors are faced with decisions regarding treatment options
for people with cancer, different choices tend to be made if
the problem is stated in terms of survival probabilities rather
than mortality probabilities.
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