We separate for the first time the roles of cognitive and motivational factors in shaping age differences in decision making under risk. Younger and older adults completed gain, loss, and mixed-domain choice problems as well as measures of cognitive functioning and affect. The older adults’ decision quality was lower than the younger adults’ in the loss domain, and this age difference was attributable to the older adults’ lower cognitive abilities. In addition, the older adults chose the more risky option more often than the younger adults in the gain and mixed domains; this difference in risk aversion was attributable to less pronounced negative affect among the older adults. Computational modeling with a hierarchical Bayesian implementation of cumulative prospect theory revealed that the older adults had higher response noise and more optimistic decision weights for gains than did the younger adults. Moreover, the older adults showed no loss aversion, a finding that supports a positivity-focus (rather than a loss-prevention) view of motivational reorientation in older age.

When people have access to information sources such as newspaper weather forecasts, drug-package inserts, and mutual-fund brochures, all of which provide convenient descriptions of risky prospects, they can make decisions from description. When people must decide whether to back up their computer's hard drive, cross a busy street, or go out on a date, however, they typically do not have any summary description of the possible outcomes or their likelihoods. For such decisions, people can call only on their own encounters with such prospects, making decisions from experience. Decisions from experience and decisions from description can lead to dramatically different choice behavior. In the case of decisions from description, people make choices as if they overweight the probability of rare events, as described by prospect theory. We found that in the case of decisions from experience, in contrast, people make choices as if they underweight the probability of rare events, and we explored the impact of two possible causes of this underweighting—reliance on relatively small samples of information and overweighting of recently sampled information. We conclude with a call for two different theories of risky choice.