Riskless Choices Research Articles

Transforming Ordinal Riskless Utility into Cardinal Risky Utility: A Comment on Chung, Glimcher, and Tymula (2019)

Chung, Glimcher, and Tymula (2019) observed both consumers’ choices over commodity bundles and choices under risk. They assumed a cardinal riskless utility function V representing consumer choices and a cardinal risky utility function U.The two were inconsistent. This note shows that the two functions can be reconciled if we assume that V is ordinal. Then one utility function U can accommodate both risky and riskless choices. (JEL C91, D12, D81)

Comparing utility functions between risky and riskless choice in rhesus monkeys

Decisions can be risky or riskless, depending on the outcomes of the choice. Expected utility theory describes risky choices as a utility maximization process: we choose the option with the highest subjective value (utility), which we compute considering both the option’s value and its associated risk. According to the random utility maximization framework, riskless choices could also be based on a utility measure. Neuronal mechanisms of utility-based choice may thus be common to both risky and riskless choices. This assumption would require the existence of a utility function that accounts for both risky and riskless decisions. Here, we investigated whether the choice behavior of two macaque monkeys in risky and riskless decisions could be described by a common underlying utility function. We found that the utility functions elicited in the two choice scenarios were different from each other, even after taking into account the contribution of subjective probability weighting. Our results suggest that distinct utility representations exist for risky and riskless choices, which could reflect distinct neuronal representations of the utility quantities, or distinct brain mechanisms for risky and riskless choices. The different utility functions should be taken into account in neuronal investigations of utility-based choice.

Comparing Utility Functions Between Risky and Riskless Choice in Rhesus Monkeys

Decisions can be risky or riskless, depending on the outcomes of the choice. Expected Utility Theory describes risky choices as a utility maximization process: we choose the option with the highest utility, which we compute considering both the value of the option and its associated risk. According to the random utility maximization framework, riskless choices could also be based on a utility measure. Neuronal mechanisms of utility-based choice may thus be common to both risky and riskless choices. This assumption would require the existence of a utility function that accounts for both risky and riskless decisions. Here, we investigated whether the choice behavior of macaque monkeys in riskless and risky decisions could be described by a common underlying utility function. We found that the utility functions elicited in the two choice scenarios were different from each other, even after taking into account the contribution of subjective probability weighting. Our results suggest that distinct utility representations exist for riskless and risky choices, which could reflect distinct neuronal representations of the utility quantities, or distinct brain mechanisms for risky and riskless choices. The different utility functions should be taken into account in neuronal investigations of utility-based choice.

Prior-free auction mechanism for online supplier with risk taking

Auction is a useful trade manner for digital goods procurements in e-market places. In this paper, we present a novel prior-free auction mechanism for supplier that serves online buyers. As the recommended the auction mechanism, the supplier has incomplete knowledge of the distribution of buyers’ valuations and makes a decision to accept or to reject each bid before each buyer leaves. To analyze auction performance without making assumptions about the prior input distribution, the competitive analysis of online algorithmic mechanism is motivated. We extend the original model to present a competitive risk analysis framework by introducing risk and forecast. Moreover, a λ-tolerance algorithmic mechanism and an n-phase λ-tolerance algorithmic mechanism are proposed. They enable a supplier to utilize and exploit forecast under different risk tolerances. Solutions of these risk algorithms yield many insights as follows: a supplier’s risk management performance, i.e., the restricted competitive ratio can be improved by putting reasonable forecasts comparing with the traditional competitive analysis; a supplier can also control his risk behavior even if the forecast is incorrect; this risk framework provides a smooth generalization for a supplier’s riskless choices and risky choices. .

Mathematics self-confidence and the “prepayment effect” in riskless choices

We extend the analysis of a riskless choice experiment reported recently by Hochman et al. (2014). Participants select from among sets of standard playing cards valued by a simple formula. In some sessions, participants are given a prepayment associated with some of the cards, which need not be the earnings-maximizing ones. Hochman et al. (2014) find that participants choose an earnings-maximizing card less frequently when another card is prepaid. We replicate this result under the original instructions, but not with instructions which explain the payment process more explicitly. Participants who state they do not consider themselves good at mathematics make earnings-maximizing choices much less frequently overall, but those who express self-confidence in mathematics drive the treatment effect. The results suggest that even when comparisons among choices require only simple quantitative reasoning steps, market designers and regulators may need to pay close attention to how the terms of offers are expressed, explained, and implemented.

An Experimental Comparison of Risky and Riskless Choice—Limitations of Prospect Theory and Expected Utility Theory

Prospect theory, used descriptively for decisions under both risk and certainty, presumes concave utility over gains and convex utility over losses; a pattern widely seen in lottery tasks. Although such discontinuous gain-loss reference-dependence is also used to model riskless choices, only limited empirical evidence supports this use. In incentive-compatible experiments, we find that gain-loss reflection effects are not observed under riskless choice as predicted by prospect theory, even while in the same subjects gain-loss reflection effects are observed under risk. Our empirical results challenge the application of choice models across both risky and riskless domains. (JEL C91, D12, D81)

Predecisional Information Distortion and the Self-Fulfilling Prophecy of Early Preferences in Choice

When a decision maker begins to favor a particular choice option, this tentative preference often shifts the evaluation of subsequent information in a manner that benefits the early leader. This ubiquitous bias, called predecisional information distortion, can create a form of self-fulfilling prophecy in which the decision maker is especially likely to choose the initially preferred option. Recent evidence has indicated that information distortion occurs in risky choices as well as riskless choices, that distortion also occurs in choices with more than two options, and that distortion can both enhance the leading option and degrade the trailing option(s). The effects of information distortion on choice and related variables are often sizable and cannot be attributed to individual differences in people’s “undistorted” assessments of the information. Although several issues are not yet resolved, incorporating information distortion into theories and models of the choice process should be a high priority for decision science.

Canonical Riskless Choice Over Bundles: Aint No Reference Point Here

Prospect Theory (Kahneman and Tversky 1979), one of the most prominent models for valuation of goods and money, presumes that people have convex utility over gains and concave utility over losses; a discontinuity at something like the current wealth level or reference point. This reflects a behavioral pattern confirmed in hundreds of experimental studies where in lottery tasks people show decreasing marginal utility over gains (risk aversion) and increasing marginal utility (risk seeking) over losses relative to this ?reference?. Although it is widely assumed that a reference point is also required to describe riskless choices made over bundles of goods, there is less empirical evidence for this claim. In this paper, using incentive-compatible experimental methods, we challenge the generality of this assumption. We find that in riskless choice over bundles of goods in a canonical budget set experiment, gain-loss asymmetries are not observed even while in interleaved lottery tasks the reference point is observed, in the same subjects. Our results suggest a discontinuity between the value functions inferred from choices over standard lotteries and the utility functions inferred from indifference curves in riskless choice.

The combined role of task, child’s age and individual differences in understanding decision processes

AbstractIt is important to understand the impact of individual differences in decision making from childhood to adulthood. This cohort-based study extends our knowledge by comparing decision making of children across the age range of 8 to 17 years and their parents. Based on prior research and theory focusing on different types of framing effects, we uncover several key differences across ages, including levels of risk taking and sensitivity to expected value differences between risky and riskless choices. Furthermore, we find that measures such as Numeracy and Surgency help explain both age-related and individual differences on our tasks, especially for decisions involving risk. We discuss the role of diverse task measures in understanding how individual difference factors affect different aspects of decision making, including the ability and effort to process numerical information and the ability to suppress affective reactions to stimulus labels.

Keeping your gains close but your money closer: The prepayment effect in riskless choices

Although research on loss aversion now spans more than three decades, researchers are still debating whether (or in which cases) the finding holds true for money. We contribute to this debate by exploring how prepayment affects financial decisions. In one set of experiments, we show that when faced with a tradeoff between post- and prepayment, participants overvalue prepaid money, and sometimes even prefer it over objectively higher gains. Importantly, this effect was more pronounced when prepayment was more distant from its pure representation in dollars and cents (Experiment 1A), as well as when potential losses were directly linked to specific options (Experiment 1B). As far as the processes involved, our results suggest that prepayment leads to increased personal commitment to prepaid options (Experiment 1C). In a second set of experiments, we show that even when the tradeoff element is eliminated, participants are more motivated and engaged in a task that is prepaid rather than post-paid (Experiments 2A and 2B). Based on our findings, we discuss how firms can use prepayment mechanisms to get more out of their agents, and how individuals can be motivated to better utilize their money.

Individual-Level Loss Aversion in Riskless and Risky Choices

Loss aversion can occur in riskless and risky choices. Yet, there is no evidence whether people who are loss averse in riskless choices are also loss averse in risky choices. We measure individual-level loss aversion in riskless choices in an endowment effect experiment by eliciting both WTA and WTP from each of our 360 subjects (randomly selected customers of a car manufacturer). All subjects also participate in a simple lottery choice task which arguably measures loss aversion in risky choices. We find substantial heterogeneity in both measures of loss aversion. Loss aversion in the riskless choice task and loss aversion in the risky choice task are highly significantly and strongly positively correlated. We find that in both choice tasks loss aversion increases in age, income, and wealth, and decreases in education.

The Neural Basis of Financial Risk Taking

Investors systematically deviate from rationality when making financial decisions, yet the mechanisms responsible for these deviations have not been identified. Using event-related fMRI, we examined whether anticipatory neural activity would predict optimal and suboptimal choices in a financial decision-making task. We characterized two types of deviations from the optimal investment strategy of a rational risk-neutral agent as risk-seeking mistakes and risk-aversion mistakes. Nucleus accumbens activation preceded risky choices as well as risk-seeking mistakes, while anterior insula activation preceded riskless choices as well as risk-aversion mistakes. These findings suggest that distinct neural circuits linked to anticipatory affect promote different types of financial choices and indicate that excessive activation of these circuits may lead to investing mistakes. Thus, consideration of anticipatory neural mechanisms may add predictive power to the rational actor model of economic decision making.

Aversion to risk and guilt

AbstractMuch research has shown that cognitive processes are largely guided by individuals' states of mind (Mancini & Gangemi, 2002a, in press; Smeets, de Jong, & Mayer, 2000). In this paper, we specifically consider a state of mind characterized by guilt for having acted irresponsibly. This state is currently considered the breeding ground for the obsessive–compulsive disorder (Rachman, 2002; Salkovskis & Forrester, 2002). Our aim is to examine the impact of this state of mind on decision under risk. We hypothesize that individuals' choices (risk seeking/risk aversion) depend on how they evaluate themselves, as guilty or as victims of a wrong, and thus on moral values. People who evaluate them‐selves as guilty are expected to show a risk‐averse preference. People who evaluate themselves as victims are expected to show a risk‐seeking preference. In two different experiments, we demonstrated that non‐clinical participants' aversion to risky choices and preference for risky choices vary as a function of their moral role (guilty/victim). As predicted, in both the experiments, participants experienced intolerance for risk, making more riskless choices, in the context of guilt. Thus, aversion to risk‐taking is actually affected by a mental state of guilt. Copyright © 2004 John Wiley & Sons, Ltd.

An Essay on Cardinal Utility

The analysis of choice in situations involving uncertainty has always occupied an important place in economic research. This is especially true of the period following the publication of J. von Neumann's and Morgenstern's monumental treatise on game theory. In this work, the writers not only developed a systematic theory of rational behavior, but also introduced a cardinal utility theory of risk preference into modern economic literature. Subsequently there ensued an extended controversy over the relative merits of ordinal and cardinal theories of utility. Although a consensus has not yet been attained, it seems that professional opinion has reached a point of stability. Most economists now agree that an ordinal preference theory is sufficient for the prediction of riskless choices. On the other hand, many hold that in the study of choices involving risks (stochastic situations), a cardinal measure of utility is more serviceable.

The theory of decision making.

This literature review of decision making (how people make choices among desirable alternatives), culled from the disciplines of psychology, economics, and mathematics, covers the theory of riskless choices, the application of the theory of riskless choices to welfare economics, the theory of risky choices, transitivity of choices, and the theory of games and statistical decision functions. The theories surveyed assume rational behavior: individuals have transitive preferences (“… if A is preferred to B, and B is preferred to C, then A is preferred to C.”), choosing from among alternatives in order to “… maximize utility or expected utility.” 209-item bibliography. (PsycINFO Database Record (c) 2006 APA, all rights reserved)