Modern theories in cognitive psychology and neuroscience indicate that there are two fundamental ways in which human beings comprehend risk. The “analytic system ” uses algorithms and normative rules, such as the probability calculus, formal logic, and risk assessment. It is relatively slow, effortful, and requires conscious control. The “experiential system ” is intuitive, fast, mostly automatic, and not very accessible to conscious awareness. The experiential system enabled human beings to survive during their long period of evolution and remains today the most natural and most common way to respond to risk. It relies on images and associations, linked by experience to emotion and affect (a feeling that something is good or bad). This system represents risk as a feeling that tells us whether it’s safe to walk down this dark street or drink this strange-smelling water. Proponents of formal risk analysis tend to view affective responses to risk as irrational. Current wisdom disputes this view. The rational and the experiential systems operate in parallel and each seems to depend on the other for guidance. Studies have demonstrated that analytic reasoning cannot be effective unless it is guided by emotion and affect. Rational decision making requires proper integration of both modes of

This study investigated the processes that underlie estimates of relative frequency. Ss performed 4 tasks using the same stimuli (squares containing black and white dots); they judged "percentages" of white dots, "percentages " of black dots, "ratios " of black dots to white dots, and "differences " between the number of black and white dots. Results were consistent with the theory that Ss used the instructed operations with the same scale values in all tasks. Despite the use of the correct operation, Ss consistently overestimated small proportions and underestimated large proportions. Variations in the distributions of actual proportions affected the extent to which Ss overestimated small proportions and underestimated large proportions in the direction predicted by range-frequency theory. Results suggest that proportion judgments, and by analogy probability judgments, should not be taken at face value. Many of our real-world decisions are based on subjective probabilities. Whether we bring an umbrella to work depends on our estimate of the chance of rain; whether we buy a lottery ticket depends, in part, on our estimate of the probability of winning; whether we support nuclear power is influenced by our beliefs about the likelihood of disastrous accidents. Subjective probabilities arise from a complex mixture of our perceptions, memories, and reasoning processes. For example, to estimate the probability of rain, we might take into consideration such information as the appearance of the sky, our knowledge of past weather conditions in the area, recent weather reports, and our opinions of the weather forecasters. How such information is retrieved from memory, evaluated, and combined to form an estimate of subjective probability has been the focus of much research (e.g., Birnbaum, 1983;

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Policymaking for posterity employs altruistic preferences to evaluate benefits and costs to distant generations. Contrary to conventional analysis: actions that impose future losses are downgraded; discount rates for the far future fall; greater future wealth may call for more effort in providing amenities.-- Posterity brings great uncertainties. Even massive losses, such as human extinction, however, do not merit infinite negative utility. Given learning, greater uncertainties about damages could increase or decrease the optimal level of current mitigation activities.-- Policies for posterity should anticipate effects on: alternative investments, both public and private; the actions of other nations; and the behaviors of future generations. Such effects may surprise.-- This analysis blends traditional public finance and behavioral economics with a number of hypothetical choice problems. Key words:

The behavioral revolution in economics tells us that human beings often have a difficult time making wise choices. The most widely chronicled difficulties occur in conjunction with decisions made under conditions of uncertainty, decisions that involve significant elements of time, and decisions in complex environments. Unfortunately,

Conceptualizing probability as psychological distance, the authors draw on construal level theory (Y. Trope & N. Liberman, 2003) to propose that decreasing an event’s probability leads individuals to represent the event by its central, abstract, general features (high-level construal) rather than by its peripheral, concrete, specific features (low-level construal). Results indicated that when reported probabilities of events were low rather than high, participants were more broad (Study 1) and inclusive (Study 2) in their categorization of objects, increased their preference for general rather than specific activity descriptions (Study 3), segmented ongoing behavior into fewer units (Study 4), were more successful at abstracting visual information (Study 5), and were less successful at identifying details missing within a coherent visual whole (Study 6). Further, after exposure to low-probability as opposed to high-probability phrases, participants increasingly preferred to identify actions in ends-related rather than means-related terms (Study 7). Implications for probability assessment and choice under uncertainty are discussed.

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This paper examines possible barriers to securitization, focusing on behavioral responses to such novel instruments. These barriers include the difficulties of conveying the associated risks, even to investors who are sophisticated about finance (but still uncertain about model risk and structural uncertainties). Our analyses will draw on results in behavioral decision making and psychology. They will lead to proposals for empirical research and general strategies for making securities design more consonant with investor behavior.

smart people can be so stupid (pp. 124-158). New Haven, CT: Yale

Amos Tversky died in 1996. Tversky’s professional ideas and contributions revolutionized not only his own field of cognitive psychology, but that of economics as well. The purpose of this article is to systematically outline the meaning and potential significance of Tversky’s insights for the study of political science. This discussion centers on three specific foci: judgment under uncertainty; decision-making under risk; and reason-based choice. Two noteworthy points emerge from this review and analysis. First, Tversky’s work stresses the importance of reason-based choice, whereby individuals actively seek to generate, understand, and justify their decisions. Second, Tversky’s work suggests that people do not act even ‘as if ’ they were the value-maximizers they are purported to be by more rationally based theories, such as expected utility. Rather, individuals function as problem-solvers who creatively construct their choices and resolve complex problems which require trade-offs between values and goals. In this way, preferences are