Risk preference is an important construct for understanding individual differences in risk taking throughout the behavioral sciences. An active stream of research has focused on better understanding ...risk preference through its connection to other psychological constructs, in particular, cognitive abilities. Here, we examine two large-scale multimethod data sets and demonstrate that the method used to measure risk preference is an important moderator. In self-report measures, we found small but consistent positive correlations between working memory capacity/numeracy, facets of cognitive abilities, and risk tolerance. In behavioral measures, we found, on average, no correlation and large intermethod heterogeneity. This heterogeneity can be explained by the choice architecture that is created in behavioral methods-in particular, the relation between risk and reward and the impact of decision error in a task. Consequently, investigating how risk preference relates to psychological constructs such as cognitive abilities require a profound understanding of the choice architecture in measurements of risk preference and in the real world.
When deciding for others based on explicitly described odds and outcomes, people often have different risk preferences for others than for themselves. In two pre-registered experiments, we examine ...risk preference for others where people learn about the odds and outcomes by experiencing them through sampling. In both experiments, on average, people were more risk averse for others than for themselves, but only when the risky option had a higher expected value. Furthermore, based on a separate set of choices, we classified people as pro- or anti-social. Only those people classified as anti-social were more risk averse for others, whereas those classified as prosocial chose similarly for themselves and others. When the uncertainty was removed, however, all participants exhibited less anti-social behavior. Together, these results suggest that anti-social motives contribute to the observed limited risk taking for others and that outcome uncertainty facilitates the expression of these motives.
•When learning from experience, cognitive limits cause uncertainty and increase risk.•Two studies show that people have a metacognitive awareness of their imprecision.•Decision makers adapt their ...risk taking to their own cognitive limitations.•A newly developed Bayesian model can account for the experimental data.•Modeling decisions from experience should take cognitive imprecision into account.
In a fundamentally uncertain world, sound information processing is a prerequisite for effective behavior. Given that information processing is subject to inevitable cognitive imprecision, decision makers should adapt to this imprecision and to the resulting epistemic uncertainty when taking risks. We tested this metacognitive ability in two experiments in which participants estimated the expected value of different number distributions from sequential samples and then bet on their own estimation accuracy. Results show that estimates were imprecise, and this imprecision increased with higher distributional standard deviations. Importantly, participants adapted their risk-taking behavior to this imprecision and hence deviated from the predictions of Bayesian models of uncertainty that assume perfect integration of information. To explain these results, we developed a computational model that combines Bayesian updating with a metacognitive awareness of cognitive imprecision in the integration of information. Modeling results were robust to the inclusion of an empirical measure of participants’ perceived variability. In sum, we show that cognitive imprecision is crucial to understanding risk taking in decisions from experience. The results further demonstrate the importance of metacognitive awareness as a cognitive building block for adaptive behavior under (partial) uncertainty.
Quick decision making under risk is ubiquitous in modern times, yet its consequences are not fully understood. Time pressure might change people's risk preferences, lead to less consistent choices, ...or change people's decision strategy. With the present work, we make the novel contribution of testing all hypotheses against each other in a unifying hierarchical Bayesian model. In two studies, participants decided repeatedly between two risky gambles either with or without high time pressure. We found a significant increase in risky choices under time pressure. With modeling, we show that time pressure decreased choice consistency but did not systematically affect people's risk preferences. In addition, the number of participants using simple, noncompensatory strategies increased slightly under time pressure. Finally, participants did not systematically choose easier gambles more often under time pressure. Thus, a reliable analysis of the effect of time pressure on preferential choice requires a model framework that allows for the distinction between the various effects time pressure can have.
State-ownership of commercial companies exists around the world, and it is important to understand its effect on financing and investment decisions. Empirically, firms that are partially state-owned ...(SOE) usually profit from easier access to capital. We propose a novel explanation for this: investors’ social preferences can affect capital allocation if SOEs are perceived as socially beneficial. In support of this we found that people attribute social benefits more to SOEs than to private firms, and their propensity to invest depends on this attitude. Further, in an incentivized modified stochastic public goods game, participants invested in risky options with positive externalities even when the aggregate of private return and externality was lower than the return of an investment option with only private returns. For the case of the EU, we discuss alternative explanations such as state guarantees and political lending in the light of regulations of state aid. We conclude that even if these regulations prohibit direct or indirect state aid for SOEs, state-ownership can affect capital allocation through investors’ social preferences.
How do people make preferential choices in situations where their cognitive capacities are limited? Many studies link the manipulation of cognitive resources to qualitative changes in preferences. ...However, there is a widely overlooked alternative hypothesis, namely, that a reduction in cognitive capacities leads to an increase in choice inconsistency. We developed a mathematical model and followed a hierarchical Bayesian estimation approach to test to what extent a reduction in cognitive capacities leads to a shift in preference or an increase in choice inconsistency. Using a within-subject n-back task to manipulate cognitive load, we conducted three experiments across different choice domains: risky choice, temporal discounting, and strategic interaction. Across all three domains, results show that a reduction in cognitive capacities predominantly affected participants' level of choice consistency rather than their respective preference. These results hold on an individual and a group level. In sum, our approach and the mathematical model we used provide a rigorous and general test of how reduced cognitive capacities affect people's decision-making.
Personal experiences can impact investors’ risk taking, and this can explain market phenomena such as time-varying risk premia, asset price bubbles or wage–price spirals. Establishing the link from ...individual experiences to market outcomes is challenging, as together with experiences, several decision-relevant factors simultaneously change. The present work investigates the impact of prior experiences on subsequent investments in a laboratory experiment without confounds, which allows for the control of various factors that usually are correlated with experience. The results show that high (low) previously experienced outcomes lead to more (less) investment in a risky asset, even in a condition where experiences do not provide new information and should be ignored. A reinforcement learning model captures the observed individual behavior and allows us to explain market price dynamics. The experience effect on risk taking informs behavioral theories of markets and provides a cognitive explanation for trend-following and self-enforcing market dynamics.
Do people's attitudes toward the (a)symmetry of an outcome distribution affect their choices? Financial investors seek return distributions with frequent small returns but few large ones, consistent ...with leading models of choice in economics and finance that assume right-skewed preferences. In contrast, many experiments in which decision-makers learn about choice options through experience find the opposite choice tendency, in favor of left-skewed options. To reconcile these seemingly contradicting findings, the present work investigates the effect of skewness on choices in experience-based decisions. Across seven studies, we show that apparent preferences for left-skewed outcome distributions are a consequence of those distributions having a higher value in most direct outcome comparisons, a "frequent-winner effect." By manipulating which option is the frequent winner, we show that choice tendencies for frequent winners can be obtained even with identical outcome distributions. Moreover, systematic choice tendencies in favor of right- or left-skewed options can be obtained by manipulating which option is experienced as the frequent winner. We also find evidence for an intrinsic preference for right-skewed outcome distributions. The frequent-winner phenomenon is robust to variations in outcome distributions and experimental paradigms. These findings are confirmed by computational analyses in which a reinforcement-learning model capturing frequent winning and intrinsic skewness preferences provides the best account of the data. Our work reconciles conflicting findings of aggregated behavior in financial markets and experiments and highlights the need for theories of decision-making sensitive to joint outcome distributions of the available options.
In many important real-world decision domains, such as finance, the environment, and health, behavior is strongly influenced by experience. Renewed interest in studying this influence led to ...important advancements in the understanding of these decisions from experience (DfE) in the last 20 years. Building on this literature, we suggest ways the standard experimental design should be extended to better approach important real-world DfE. These extensions include, for example, introducing more complex choice situations, delaying feedback, and including social interactions. When acting upon experiences in these richer and more complicated environments, extensive cognitive processes go into making a decision. Therefore, we argue for integrating cognitive processes more explicitly into experimental research in DfE. These cognitive processes include attention to and perception of numeric and nonnumeric experiences, the influence of episodic and semantic memory, and the mental models involved in learning processes. Understanding these basic cognitive processes can advance the modeling, understanding and prediction of DfE in the laboratory and in the real world. We highlight the potential of experimental research in DfE for theory integration across the behavioral, decision, and cognitive sciences. Furthermore, this research could lead to new methodology that better informs decision-making and policy interventions.
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