invested in risky investments. Some of these studies have found that the proportion actually increases until about age 65, when it begins to decrease (Jianakoplos and Bernasek, 1998; Riley and Chow, 1992; Schooley and Worden, 1999). One study of university employees found that hypothetical asset allocations became more conservative with age (Dulebohn, 2002), whereas another study using a different sample of university employees found that, with age, people described themselves as more tolerant of risk in their financial decisions (Grable, 2000). A survey of high-level managers at Dutch bank and insurance companies revealed that older managers’ business decisions were more aggressive than younger managers’ decisions (Brouthers, Brouthers, and Werner, 2000). Conflicting results such as these may be due to factors confounded with age, such as wealth and the time horizon of the investment goals. Certainly the studies that show an inverse u-shaped function, with risk tolerance increasing in midlife and then decreasing after retirement (Jianakoplos and Bernasek, 1998; Riley and Chow, 1992; Schooley and Worden, 1999), suggest that asset allocation decisions are more influenced by changes in life circumstances than by age-related changes in information-processing strategies. Given the available evidence, we cannot rule out the possibility that younger adults would make similar financial decisions as older adults if they had the same amount of wealth and similar investment time horizons.

Gambling is a popular activity among older adults. A survey of activity directors at residential and assisted-care facilities and other senior centers revealed that bingo is the activity most participated in on-site, and that casino gambling is the most highly attended type of day-trip social activity (McNeilly and Burke, 2001). Playing bingo or the slots every so often is unlikely to cause serious financial or social problems, but gambling has its risks, especially if it becomes an addiction. Nationwide surveys indicate that rates of pathological gambling in the general population are lower for older adults than younger adults (National Opinion Research Center, 1999). However, this age effect is no longer significant when race, socioeconomic status, and gender are accounted for (Welte, Barnes, Wieczorek, Tidwell, and Parker, 2001). This finding suggests that when other factors are taken into account, age in itself does not predict rates of pathological gambling. For example, gender is one confound when looking at age trends, since a lower proportion of the older population is male and proportionately more males are pathological gamblers. Furthermore, the prevalence of gambling among older adults may not accurately reflect risk aversion because the gambling may instead serve as a social activity for older adults.

Evidence from experiments comparing individual decision-making strategies among younger and older adults provides even less support for the stereotype of cautious older adults. Two studies found no significant age differences in whether people selected cards from high-reward/high-risk



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