This study examined the effects of age and income temporal discounting (i.e. the decrease in the subjective value of a reward as the delay to its receipt increases). The value of delayed hypothetical monetary rewards was discounted at similar rates by adults of different ages but similar income levels, but at different rates by adults of similar age but different income levels. Specifically, lower income older adults showed a greater degree of temporal discounting than did either upper income older adults or upper income younger adults, but there were no age differences in discounting between the upper income groups. Comparison of these findings with those of a previous study (Green, Fry, & Myerson, 1994) suggests that impulsivity in decision making declines rapidly in young adulthood, reaching stable levels in the 30s. Further, age and income appear to interact in determining the impulsivity of decision making by adults.

It has been suggested that older adults are more variable in their performance because they are more prone to lapses of either attention or intention. In the present experiment, 9 young and 9 older adults each performed nearly 2,000 trials of a same‐different judgment task. As expected, older adults were slower and more variable than young adults. When the age‐related difference in speed was taken into account, however, the older adults were, if anything, less variable than the young adults. When younger and older adults' RT distributions were analyzed using quantile—quantile plots and by fitting ex‐Gaussian and Weibull functions, there was no consistent evidence that older adults' distributions were more skewed than young adults', as would be predicted by age‐related increases in lapses of attention or intention. Importantly, there was a positive, linear relation between RT and intraindividual variability, and the same relation was observed both within subjects (practice increased speed and reduced variability) as well as between subjects (regardless of age, slower individuals were more variable). Thus, the present results suggest that there may be a general law governing the relation between average RT and variability, and that the greater performance variability of older adults primarily reflects their greater average RTs.

The present study with college students examined the effect of amount on the discounting of probabilistic monetary rewards. A hyperboloid function accurately described the discounting of hypothetical rewards ranging in amount from $20 to $10,000,000. The degree of discounting increased continuously with amount of probabilistic reward. This effect of amount was not due to changes in the rate parameter of the discounting function, but rather was due to increases in the exponent. These results stand in contrast to those observed with the discounting of delayed monetary rewards, in which the degree of discounting decreases with reward amount due to amount-dependent decreases in the rate parameter. Taken together, this pattern of results suggests that delay and probability discounting reflect different underlying mechanisms. That is, the fact that the exponent in the delay discounting function is independent of amount is consistent with a psychophysical scaling interpretation, whereas the finding that the exponent of the probability-discounting function is amount-dependent is inconsistent with such an interpretation. Instead, the present results are consistent with the idea that the probability-discounting function is itself the product of a value function and a weighting function. This idea was first suggested by Kahneman and Tversky (1979), although their prospect theory does not predict amount effects like those observed. The effect of amount on probability discounting was parsimoniously incorporated into our hyperboloid discounting function by assuming that the exponent was proportional to the amount raised to a power. The amount-dependent exponent of the probability-discounting function may be viewed as reflecting the effect of amount on the weighting of the probability with which the reward will be received.

Despite its avowed goal of understanding individual behavior, the field of behavior analysis has largely ignored the determinants of consistent differences in level of performance among individuals. The present article discusses major findings in the study of individual differences in intelligence from the conceptual framework of a functional analysis of behavior. In addition to general intelligence, we discuss three other major aspects of behavior in which individuals differ: speed of processing, working memory, and the learning of three‐term contingencies. Despite recent progress in our understanding of the relations among these aspects of behavior, numerous issues remain unresolved. Researchers need to determine which learning tasks predict individual differences in intelligence and which do not, and then identify the specific characteristics of these tasks that make such prediction possible.