This paper presents a critique of expected utility theory as a descriptive model of decision making under risk, and develops an alternative model, called prospect theory. Choices among risky prospects exhibit several pervasive effects that are inconsistent with the basic tenets of utility theory. In particular, people underweight outcomes that are merely probable in comparison with outcomes that are obtained with certainty. This tendency, called the certainty effect, contributes to risk aversion in choices involving sure gains and to risk seeking in choices involving sure losses. In addition, people generally discard components that are shared by all prospects under consideration. This tendency, called the isolation effect, leads to inconsistent preferences when the same choice is presented in different forms. An alternative theory of choice is developed, in which value is assigned to gains and losses rather than to final assets and in which probabilities are replaced by decision weights. The value function is normally concave for gains, commonly convex for losses, and is generally steeper for losses than for gains. Decision weights are generally lower than the corresponding probabilities, except in the range of low prob- abilities. Overweighting of low probabilities may contribute to the attractiveness of both insurance and gambling. EXPECTED UTILITY THEORY has dominated the analysis of decision making under risk. It has been generally accepted as a normative model of rational choice (24), and widely applied as a descriptive model of economic behavior, e.g. (15, 4). Thus, it is assumed that all reasonable people would wish to obey the axioms of the theory (47, 36), and that most people actually do, most of the time. The present paper describes several classes of choice problems in which preferences systematically violate the axioms of expected utility theory. In the light of these observations we argue that utility theory, as it is commonly interpreted and applied, is not an adequate descriptive model and we propose an alternative account of choice under risk. 2. CRITIQUE

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Prospect theory: an analysis of decision under risk

This article described three heuristics that are employed in making judgements under uncertainty: (i) representativeness, which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process B; (ii) availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development; and (iii) adjustment from an anchor, which is usually employed in numerical prediction when a relevant value is available. These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors. A better understanding of these heuristics and of the biases to which they lead could improve judgements and decisions in situations of uncertainty.

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Judgment Under Uncertainty: Heuristics and Biases

The psychological principles that govern the perception of decision problems and the evaluation of probabilities and outcomes produce predictable shifts of preference when the same problem is framed in different ways. Reversals of preference are demonstrated in choices regarding monetary outcomes, both hypothetical and real, and in questions pertaining to the loss of human lives. The effects of frames on preferences are compared to the effects of perspectives on perceptual appearance. The dependence of preferences on the formulation of decision problems is a significant concern for the theory of rational choice.

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The Framing of Decisions and the Psychology of Choice

Evidence is reviewed which suggests that there may be little or no direct introspective access to higher order cognitive processes. Subjects are sometimes (a) unaware of the existence of a stimulus that importantly influenced a response, (b) unaware of the existence of the response, and (c) unaware that the stimulus has affected the response. It is proposed that when people attempt to report on their cognitive processes, that is, on the processes mediating the effects of a stimulus on a response, they do not do so on the basis of any true introspection. Instead, their reports are based on a priori, implicit causal theories, or judgments about the extent to which a particular stimulus is a plausible cause of a given response. This suggests that though people may not be able to observe directly their cognitive processes, they will sometimes be able to report accurately about them. Accurate reports will occur when influential stimuli are salient and are plausible causes of the responses they produce, and will not occur when stimuli are not salient or are not plausible causes.

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Telling more than we can know: Verbal reports on mental processes.

Studies of risk perception examine the judgements people make when they are asked to characterize and evaluate hazardous activities and technologies. This research aims to aid risk analysis and policy-making by providing a basis for understanding and anticipating public responses to hazards and improving the communication of risk information among lay people, technical experts, and decision-makers. This work assumes that those who promote and regulate health and safety need to understand how people think about and respond to risk. Without such understanding, well-intended policies may be ineffective.

http://science.sciencemag.org/content/sci/236/4799/280.full.pdf

Perception of risk.

People are often overconfident in evaluating the correctness of their knowledge. The present studies investigated the possibility that assessment of confidence is biased by attempts to justify one's chosen answer. These attempts include selectively focusing on evidence supporting the chosen answer and disregarding evidence contradicting it. Experiment 1 presented subjects with two-alternative questions and required them to list reasons for and against each of the alternatives prior to choosing an answer and assessing the probability of its being correct. This procedure produced a marked improvement in the appropriateness of confidence judgments. Experiment 2 simplified the manipulation by asking subjects first to choose an answer and then to list (a) one reason supporting that choice, (b) one reason contradicting it, or (c) one reason supporting and one reason contradicting. Only the listing of contradicting reasons improved the appropriateness of confidence. Correlational analyses of the data of Experiment 1 strongly suggested that the confidence depends on the amount and strength of the evidence supporting the answer chosen.

Journal of Experimental Psychology: Human Learning and Memory

One of the fundamental questions addressed by risk-benefit analysis is “How safe is safe enough?” Chauncey Starr has proposed that economic data be used to reveal patterns of acceptable risk-benefit tradeoffs. The present study investigates an alternative technique, in which psychometric procedures were used to elicit quantitative judgments of perceived risk, acceptable risk, and perceived benefit for each of 30 activities and technologies. The participants were seventy-six members of the League of Women Voters. The results indicated little systematic relationship between perceived existing risks and benefits of the 30 risk items. Current risk levels were generally viewed as unacceptably high. When current risk levels were adjusted to what would be considered acceptable risk levels, however, risk was found to correlate with benefit. Nine descriptive attributes of risk were also studied. These nine attributes seemed to tap two basic dimensions of risk. These dimensions proved to be effective predictors of the tradeoff between acceptable risk and perceived benefit. The limitations of the present study and the relationship between this technique and Starr's technique are discussed, along with the implications of the findings for policy decisions.

How safe is safe enough? a psychometric study of attitudes towards technological risks and benefits

https://files.eric.ed.gov/fulltext/ED045723.pdf

Comparison of Bayesian and Regression Approaches to the Study of Information Processing in Judgment.

From the subjectivist point of view (de Finetti, 1937/1964), a probability is a degree of belief in a proposition. It expresses a purely internal state; there is no “right,” “correct,” or “objective” probability residing somewhere “in reality” against which one's degree of belief can be compared. In many circumstances, however, it may become possible to verify the truth or falsity of the proposition to which a probability was attached. Today, one assesses the probability of the proposition “it will rain tomorrow.” Tomorrow, one looks at the rain gauge to see whether or not it has rained. When possible, such verification can be used to determine the adequacy of probability assessments. Winkler and Murphy (1968b) have identified two kinds of “goodness” in probability assessments: normative goodness, which reflects the degree to which assessments express the assessor's true beliefs and conform to the axioms of probability theory, and substantive goodness, which reflects the amount of knowledge of the topic area contained in the assessments. This chapter reviews the literature concerning yet another aspect of goodness, called calibration. If a person assesses the probability of a proposition being true as .7 and later finds that the proposition is false, that in itself does not invalidate the assessment. However, if a judge assigns .7 to 10,000 independent propositions, only 25 of which subsequently are found to be true, there is something wrong with these assessments.

Calibration of probabilities: the state of the art to 1980

: This report provides a critical overview to work, its applicability and directions for further research. As might be expected with a burgeoning, multi-disciplinary field, it is difficult to keep track of all that is done and to draw the implications of research done in one discipline for research done in another. This report surveys the entire field asking, (1) what is known. (2) what good is it. and (3) what else must we learn. Particular attention is given to work integrating research describing how people do make decisions with normative work that prescribes how people should make decisions.

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Sarah Lichtenstein

Papers

Journal of Experimental Psychology: Human Learning and Memory

How safe is safe enough? a psychometric study of attitudes towards technological risks and benefits

Comparison of Bayesian and Regression Approaches to the Study of Information Processing in Judgment.

Calibration of probabilities: the state of the art to 1980

Behavioral Decision Theory