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118 Decision making under uncertainty
we could either ask the decision maker how much he would be prepared
to pay to buy the lottery ticket or, assuming that he already owns the
ticket, how much he would accept to sell it. Research suggests that people
tend to offer a lower price to buy the ticket than they would accept to
sell it. There is thus a propensity to prefer the status quo, so that people
are generally happier to retain a given risk than to take the same risk
on (see also Thaler 6 ). Finally, the context in which the questions were
framed was found to have an effect on responses. For example, Hershey
et al. 5 refer to an earlier experiment when the same choice was posed in
different ways, the first involving an insurance decision and the second
a gamble as shown below:
Insurance formulation
Situation A: You stand a one out of a thousand chance of losing $1000.
Situation B: You can buy insurance for $10 to protect you from this loss.
Gamble formulation
Situation A: You stand a one out of a thousand chance of losing $1000.
Situation B: You will lose $10 with certainty.
It was found that 81% of subjects preferred B in the insurance formulation,
while only 56% preferred B in the gamble formulation.
Tversky and Kahneman 7 provide further evidence that the way in
which the choice is framed affects the decision maker’s response. They
found that choices involving statements about gains tend to produce
risk-averse responses, while those involving losses are often risk seeking.
For example, in an experiment subjects were asked to choose a program
to combat a disease which was otherwise expected to kill 600 people.
One group was told that Program A would certainly save 200 lives
while Program B offered a 1/3 probability of saving all 600 people and a
2/3 probability of saving nobody. Most subjects preferred A. A second
group were offered the equivalent choice, but this time the statements
referred to the number of deaths, rather than lives saved. They were
therefore told that the first program would lead to 400 deaths while the
second would offer a 1/3 probability of no deaths and a 2/3 probability
of 600 deaths. Most subjects in this group preferred the second program,
which clearly carries the higher risk. Further experimental evidence that
different assessment methods lead to different utilities can be found in a
paper by Johnson and Schkade. 8
What are the implications of this research for utility assessment? First,
it is clear that utility assessment requires effort and commitment from
the decision maker. This suggests that, before the actual elicitation takes
place, there should be a pre-analysis phase in which the importance of