Amnon Rapoport made seminal contributions to research on investment decision-making and individual decision-making under risk. To build on his seminal work, this paper explores the impact of social influence on risk-taking. First, to build predictions for experimental testing, we modify a standard expected utility model by introducing a social norm variable. Using a standard 10-decision paired lottery choice task, we report the results from three experiments with different manipulations to test whether social influence information affects subjects’ own lottery choices. In Experiment 1, we find that participants are more likely to switch to choosing the risky option earlier if they are told that a large majority (>75%) of a large group (N = 100) of others have also chosen the risky option in the past. In Experiment 2, we find there is no effect if the social influence prompt is framed as a small group (N = 10) or the choice of one (N = 1) successful lottery participant, but there is an effect when participants are provided information about the consistently risky choices of one (N = 1) person in the past. In Experiment 3, using an in-person subject pool, we find some mixed effects on risk-taking when the social information is framed as a small group (N = 10) of peers (other students). Altogether, this paper demonstrates that social influence can impact risk-taking in line with a socially normed expected utility model.

Alternative disposable dinnerware treatments to per- and polyfluoroalkyl substances (PFAS) are under development. A discrete choice experiment of 1,304 U.S. consumers addressed the market’s response to bio-based alternatives. Information nudges were used to assess the impact of health and environmental information on behavior. Data were analyzed using mixed logit models. Bio-based treated plates generated premiums compared to the PFAS-treated plates. Participants exposed to either environmental or health information were willing to pay a price premium of $2.0-$2.12 for bio-based treatments. Both information nudges generated premiums for the USDA Certified Bio-based products relative to the control.

An abundance of statistics has shown gender disparity in hiring decisions. This paper shows that a previously unexplored factor, the decision-making process utilized by a hiring committee, plays a crucial role. Using a laboratory experiment, we find that gender disparity is eliminated when hiring decisions are made unanimously by a group. By comparison, we find that gender disparity is largest when decisions are made by a leader who volunteers. We do not find evidence of heterogeneity by gender as the results persist regardless of the number of women in the group or the leader’s gender. The experimental design allows us to rule out several possible mechanisms including differences in leadership characteristics and communication styles.

The bonus-malus system (BMS) is a widely recognized and commonly employed risk management tool. A well-designed BMS can match expected insurance payments with estimated claims even in a diverse group of risks. Although there has been abundant research on improving bonus-malus (BM) systems, one important aspect has been overlooked: the stationary probability of a BMS satisfies the monotone likelihood ratio property. The monotone likelihood ratio for stationary probabilities allows us to better understand how riskier policyholders are more likely to remain in higher premium categories, while less risky policyholders are more likely to move toward lower premiums. This study establishes this property for BMSs that are described by an ergodic Markov chain with one possible claim and a transition rule +1/-d. We derive this result from the linear recurrences that characterize the stationary distribution; this represents a novel analytical approach in this domain. We also illustrate the practical implications of our findings: in the BM design problem, the premium scale is automatically monotonic.

We report the results of an experiment on selective exposure to information. A decision maker interested in learning about an uncertain state of the world can acquire information from one of two sources that have opposite biases: when informed on the state, they report it truthfully; when uninformed, they report their favorite state. A Bayesian decision-maker is better off seeking confirmatory information unless the source biased against the prior is sufficiently more reliable. In line with the theory, subjects are more likely to seek confirmatory information when sources are symmetrically reliable. On the other hand, when sources are asymmetrically reliable, subjects are more likely to consult the more reliable source even when prior beliefs are strongly unbalanced and this source is less informative. Our experiment suggests that base rate neglect and simple heuristics (e.g., listen to the most reliable source) are important drivers of the endogenous acquisition of information.

We introduce the “Fork Game,” a graphical interface designed to elicit higher-order risk preferences. In this game, participants connect forked pipes to create a final structure. A ball is then dropped into the top opening of this structure and follows a downward path, randomly turning left or right at each forked joint. This construction is effectively isomorphic to the apportionment of binary-outcome lotteries, allowing participants to construct complex gambles. Furthermore, the game is easily comprehensible, highly modular, and provides a flexible means of assessing risk aversion, prudence, temperance, and even higher-order risk preferences.

Our study contributes to the literature on choice shifts in group decision-making by analyzing how the level of risk-taking within a group is influenced by its gender composition. In particular, we investigate experimentally whether group composition affects how preferences ‘shift’ when comparing individual and group choices. Consistent with hypotheses derived from previous literature, we show that male-dominated groups shift toward riskier decisions in a way that is not explained by any simple preference aggregation mechanism. We discuss potential channels for the observed pattern of choice shifts.

In this paper, we present a flexible approach to estimating parametric cumulative Prospect Theory using Hierarchical Bayesian methods. Bayesian methods allow us to include prior knowledge in estimation and heterogeneity in individual responses. The model employs a generalised parametric specification of the value function allowing each individual to be risk-seeking in low-stakes mixed prospects. In addition, it includes parameters accounting for varying levels of model noise across domains (gain, loss, and mixed) and several aspects of lottery design that can influence respondent behaviour. Our results indicate that enhancing value function flexibility leads to improved model performance. Our analysis reveals that choices within the gain domain tend to be more predictable. This implies that respondents find tasks in the gain domain cognitively less challenging in comparison to making choices within the loss and mixed domains.

We revisit the recently introduced concept of return risk measures (RRMs) and extend it by incorporating risk management via multiple so-called eligible assets. The resulting new class of risk measures, termed multi-asset return risk measures (MARRMs), introduces a novel economic model for multiplicative risk sharing. We point out the connection between MARRMs and the well-known concept of multi-asset risk measures (MARMs). Then, we conduct a case study, based on an insurance dataset, in which we use typical continuous-time financial markets and different notions of acceptability of losses to compare RRMs, MARMs, and MARRMs and draw conclusions about the cost of risk mitigation. Moreover, we analyze theoretical properties of MARRMs. In particular, we prove that a positively homogeneous MARRM is quasi-convex if and only if it is convex, and we provide conditions to avoid inconsistent risk evaluations. Finally, the representation of MARRMs via MARMs is used to obtain various dual representations.

Narrow bracketers who are myopic in specific decisions would fail to consider preexisting risks in investment and neglect hedging opportunities. Growing evidence has demonstrated the relevance of narrow bracketing. We take a step further in empirical investigation and study individual heterogeneity in narrow bracketing. Specifically, we use a lab experiment in investment and hedging that elicits subjects’ preferences on rich occasions to uncover the individual degree of narrow bracketing without imposing distributional assumptions. Combining prospect theory and narrow bracketing can explain our findings: Subjects who invest more also insure more, and subjects insure significantly less in the loss domain than in the gain domain. More importantly, we show that the distribution of the individual degree of narrow bracketing is skewed at two extremes, yet with a substantial share of people in the middle who partially suffer from narrow bracketing. Neglecting this aspect, we would overestimate the severity of narrow bracketing and misinterpret its relation with individual characteristics.

Risk was incorporated into monetary aggregation over thirty-five years ago, using a stochastic version of the workhorse money-in-the-utility-function model. Nevertheless, the mathematical foundations of this stochastic model remain shaky. To firm the foundations, this paper employs richer probability concepts than Borel-measurability, enabling me to prove the existence of a well-behaved solution and to derive stochastic Euler equations. This measurability approach is less common in economics, possibly because the derivation of stochastic Euler equations is new. Importantly, the problem’s economics are not restricted by the approach. The results provide firm footing for the growing monetary aggregation under risk literature, which integrates monetary and finance theory. As crypto-currencies and stable coins garner attention, solidifying the foundations of risky money becomes more critical. The method also supports deriving stochastic Euler equations for any dynamic economics problem that features contemporaneous uncertainty about prices, including asset pricing models like capital asset pricing models and stochastic consumer choice models.

We investigate the role of visual attention in risky choice in a rich experimental dataset that includes eye-tracking data. We first show that attention is not reducible to individual and contextual variables, which explain only 20% of attentional variation. We then decompose attentional variation into individual average attention and trial-wise deviations of attention to capture different cognitive processes. Individual average attention varies by individual, and can proxy for individual preferences or goals (as in models of “rational inattention” or goal-directed attention). Trial-wise deviations of attention vary within subjects and depend on contextual factors (as in models of “salience” or stimulus-driven attention). We find that both types of attention predict behavior: average individual attention patterns are correlated with individual levels of loss aversion and capture part of this individual heterogeneity. Adding trial-wise deviations of attention further improves model fit. Our results show that a decomposition of attention into individual average attention and trial-wise deviations of attention can capture separable cognitive components of decision making and provides a useful tool for economists and researchers from related fields interested in decision-making and attention.

This paper reports a series of experiments designed to evaluate how the advertised participation payment impacts participation rates in laboratory experiments. Our initial goal was to generate variation in the participation rate as a means to control for selection bias when evaluating treatment effects in common laboratory experiments. Initially, we varied the advertised participation payment to 1734 people from $\mathrm{\$}5$ to $\mathrm{\$}15$ using standard email recruitment procedures, but found no statistical evidence this impacted the participation rate. A second study increased the advertised payment up to $\mathrm{\$}100$. Here, we find marginally significant statistical evidence that the advertised participation payment affects the participation rate when payments are large. To combat skepticism of our results, we also conducted a third study in which verbal offers were made. Here, we found no statistically significant increase in participation rates when the participation payment increased from $\mathrm{\$}5$ to $\mathrm{\$}10$. Finally, we conducted an experiment similar to the first one at a separate university. We found no statistically significant increase in participation rates when the participation payment increased from $\mathrm{\$}7$ to $\mathrm{\$}15$. The combined results from our four experiments suggest moderate variation in the advertised participation payment from standard levels has little impact on participation rates in typical laboratory experiments. Rather, generating useful variation in participation rates likely requires much larger participation payments and/or larger potential subject pools than are common in laboratory experiments.

When it comes to experiments with multiple-round decisions under risk, the current payoff mechanisms are incentive compatible with either outcome weighting theories or probability weighting theories, but not both. In this paper, I introduce a new payoff mechanism, the Accumulative Best Choice (“ABC”) mechanism that is incentive compatible for all rational risk preferences. I also identify three necessary and sufficient conditions for a payoff mechanism to be incentive compatible for all models of decision under risk with complete and transitive preferences. I show that ABC is the unique incentive compatible mechanism for rational risk preferences in a multiple-task setting. In addition, I test empirical validity of the ABC mechanism in the lab. The results from both a choice pattern experiment and a preference (structural) estimation experiment show that individual choices under the ABC mechanism are statistically not different from those observed with the one-round task experimental design. The ABC mechanism supports unbiased elicitation of both outcome and probability transformations as well as testing alternative decision models that do or do not include the independence axiom.

Recent research argues “betrayal aversion” leads many people to avoid risk more when a person, rather than nature, determines the outcome of uncertainty. However, past studies indicate that factors unrelated to betrayal aversion, such as loss aversion, could contribute to differences between treatments. Using a novel experiment design to isolate betrayal aversion, one that varies how strategic uncertainty is resolved, we provide rigorous evidence supporting the detrimental impact of betrayal aversion. The impact is substantial: holding fixed the probability of betrayal, the possibility of knowing that one has been betrayed reduces investment by about one-third. We suggest emotion-regulation underlies these results and helps to explain the importance of impersonal, institution-mediated exchange in promoting economic efficiency.

This study develops a theoretical, and experimental analysis addressing the issue of premium variations on the demand for insurance. Accounting for risk attitudes, our contribution disentangles the decision to buy insurance from the conditional demand (the non-null demand for insurance). Partially validating our theoretical predictions, our experimental results show that, when it has an effect, a non-massive increase in the premium (either in the unit price or the fixed cost) exclusively results in an exit from the insurance market (the risk lovers first, then the risk averters). Moreover, our study highlights a key feature of risk-seeking agents' behavior; they exhibit behavior consistent with gambling and opportunism rather than a lack of interest in insurance.

This paper investigates whether and to what extent group identity plays a role in peer effects on risk behaviour. We run a laboratory experiment in which different levels of group identity are induced through different matching protocols (random or based on individual painting preferences) and the possibility to interact with group members via an online chat in a group task. Risk behaviour is measured by using the Bomb Risk Elicitation Task and peer influence is introduced by giving subjects feedback regarding group members’ previous decisions. We find that subjects are affected by their peers when taking decisions and that group identity influences the magnitude of peer effects: painting preferences matching significantly reduces the heterogeneity in risk behaviour compared with random matching. On the other hand, introducing a group task has no significant effect on behaviour, possibly because interaction does not always contribute to enhancing group identity. Finally, relative riskiness within the group matters and individuals whose peers are riskier than they are take on average riskier decisions, even when controlling for regression to the mean.

A recent strand of the literature on decision-making under uncertainty has pointed to an intriguing behavioral gap between decisions made from description and decisions made from experience. This study reinvestigates this description-experience gap to understand the impact that sampling experience has on decisions under risk. Our study adopts a complete sampling paradigm to address the lack of control over experienced probabilities by requiring complete sampling without replacement. We also address the roles of utilities and ambiguity, which are central in most current decision models in economics. Thus, our experiment identifies the deviations from expected utility due to over- (or under-) weighting of probabilities. Our results confirm the existence of the behavioral gap, but they provide no evidence for the underweighting of small probabilities within the complete sampling treatment. We find that sampling experience attenuates rather than reverses the inverse S-shaped probability weighting under risk.

We demonstrate how the standard usage of the random incentive system in ambiguity experiments eliciting certainty and probability equivalents might not be incentive compatible if the decision-maker is ambiguity averse. We propose a slight modification of the procedure in which the randomization takes place before decisions are made and the state is realized, and prove that if subjects evaluate the experimental environment in that way (first-risk, second-uncertainty), incentive compatibility may be restored.

Eliciting the level of risk aversion of experimental subjects is of crucial concern to experimenters. In the literature there are a variety of methods used for such elicitation; the concern of the experiment reported in this paper is to compare them. The methods we investigate are the following: Holt–Laury price lists; pairwise choices, the Becker–DeGroot–Marschak method; allocation questions. Clearly their relative efficiency in measuring risk aversion depends upon the numbers of questions asked; but the method itself may well influence the estimated risk-aversion. While it is impossible to determine a ‘best’ method (as the truth is unknown) we can look at the differences between the different methods. We carried out an experiment in four parts, corresponding to the four different methods, with 96 subjects. In analysing the data our methodology involves fitting preference functionals; we use four, Expected Utility and Rank-Dependent Expected Utility, each combined with either a CRRA or a CARA utility function. Our results show that the inferred level of risk aversion is more sensitive to the elicitation method than to the assumed-true preference functional. Experimenters should worry most about context.