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.

There are two means of changing the expected value of a risk: changing the probability of a reward or changing the reward. Theoretically, the former produces a greater change in expected utility for risk averse agents. This paper uses two formats of a risk preference elicitation mechanism under two decision frames to test this hypothesis. After controlling for decision error, probability weighting, and order effects, subjects, on average, are slightly risk averse and prefer an increase in the expected value of a risk due to increasing the probability over a compensated increase in the reward. There is substantial across-format inconsistency but very little within-format inconsistency at the individual level.

Time pressure is a central aspect of economic decision making nowadays. It is therefore natural to ask how time pressure affects decisions, and how to detect individual heterogeneity in the ability to successfully cope with time pressure. In the context of risky decisions, we ask whether a person’s performance under time pressure can be predicted by measurable behavior and traits, and whether such measurement itself may be affected by selection issues. We find that the ability to cope with time pressure varies significantly across decision makers, leading to selected subgroups that differ in terms of their observed behaviors and personal traits. Moreover, measures of cognitive ability and intellectual efficiency jointly predict individuals’ decision quality and ability to keep their decision strategy under time pressure.

We present evidence of a direct social context effect on decision-making under uncertainty: the gender composition of those in the room when making individual risky decisions significantly alters choices even when the actions or presence of others are not payoff relevant. In our environment, decision makers do not know the choices made by others, nor can they be inferred from the experiment. We find that women become more risk taking as the proportion of men in the room increases, but the behavior of men is unaffected by who is present. We discuss some potential mechanisms for this result and conjecture it is driven by women being aware of the social context and imitating the expected behavior of others. Our results imply that the environment in which individual decisions are made can change expressed preferences and that aggregate behavior may be context dependent.

Accountability—the expectation on the side of the decision maker that she may have to justify her decisions in front of somebody else—has been found by psychologists to strongly influence decision-making processes. The awareness of this issue remains however limited amongst economists, who tend to focus on the motivational effects of financial incentives. Accountability and incentives may provide different motivations for decision makers, and disentangling their effects is thus important for understanding real-world situations in which both are present. Separating accountability and incentives, I find different effects. Accountability is found to reduce preference reversals between frames, for which incentives have no effect. Incentives on the other hand are found to reduce risk seeking for losses, where accountability has no effect. In a choice task between simple and compound events, accountability increases the preference for the normatively superior simple event, while incentives have a weaker effect going in the opposite direction.

A standard method to elicit certainty equivalents is the Becker-DeGroot- Marschak (BDM) procedure. We compare the standard BDM procedure and a BDM procedure with a restricted range of minimum selling prices that an individual can state. We find that elicited prices are systematically affected by the range of feasible minimum selling prices. Expected utility theory cannot explain these results. Nonexpected utility theories can only explain the results if subjects consider compound lotteries generated by the BDM procedure. We present an alternative explanation where subjects sequentially compare the lottery to monetary amounts in order to determine their minimum selling price. The model offers a formal explanation for range effects and for the underweighting of small and the overweighting of large probabilities.

Decisions to trust in strategic situations involve ambiguity (unknown probabilities). Despite many theoretical studies on ambiguity in game theory, empirical studies have lagged behind due to a lack of measurement methods, where separating ambiguity attitudes from beliefs is crucial. Baillon et al. (Econometrica, 2018b) introduced a method that allows for such a separation for individual choice. We extend this method to strategic situations and apply it to the trust game, providing new insights. People’s ambiguity attitudes and beliefs both matter for their trust decisions. People who are more ambiguity averse decide to trust less, and people with more optimistic beliefs about others’ trustworthiness decide to trust more. However, people who are more a-insensitive (insufficient discrimination between different likelihood levels) are less likely to act upon their beliefs. Our measurement of beliefs, free from contamination by ambiguity attitudes, shows that traditional introspective trust survey measures capture trust in the commonly accepted sense of belief in trustworthiness of others. Further, trustworthy people also decide to trust more due to their beliefs that others are similar to themselves. This paper shows that applications of ambiguity theories to game theory can bring useful new empirical insights.

I study the effect of task difficulty on workers’ effort. I find that task difficulty has an inverse-U effect on effort and that this effect is quantitatively large, especially when compared to the effect of conditional monetary rewards. Difficulty acts as a mediator of monetary rewards: conditional rewards are most effective at the intermediate or high levels of difficulty. The inverse-U pattern of effort response to difficulty is inconsistent with many popular models in the literature, including the Expected Utility models with the additively separable cost of effort. I propose an alternative mechanism for the observed behavior based on non-linear probability weighting. I structurally estimate the proposed model and find that it successfully captures the behavioral patterns observed in the data. I discuss the implications of my findings for the design of optimal incentive schemes for workers and for the models of effort provision.

The COVID-19 pandemic presents a remarkable opportunity to put to work all of the research that has been undertaken in past decades on the elicitation and structural estimation of subjective belief distributions as well as preferences over atemporal risk, patience, and intertemporal risk. As contributors to elements of that research in laboratories and the field, we drew together those methods and applied them to an online, incentivized experiment in the United States. We have two major findings. First, the atemporal risk premium during the COVID-19 pandemic appeared to change significantly compared to before the pandemic, consistent with theoretical results of the effect of increased background risk on foreground risk attitudes. Second, subjective beliefs about the cumulative level of deaths evolved dramatically over the period between May and November 2020, a volatile one in terms of the background evolution of the pandemic.

We investigate how people make choices when they are unsure about the value of the options they face and have to decide whether to choose now or wait and acquire more information first. In an experiment, we find that participants deviate from optimal information acquisition in a systematic manner. They acquire too much information (when they should only collect little) or not enough (when they should collect a lot). We show that this pattern can be explained as naturally emerging from Fechner cognitive errors. Over time participants tend to learn to approximate the optimal strategy when information is relatively costly.