We study how large language model (LLM) based recommendations affect evaluations of uncertainty. We elicit certainty equivalents for (i) lotteries that share the same reduced-form winning probability but vary in cognitive demands because they are compound, and (ii) an Ellsberg-style ambiguous lottery. Across all lottery types, valuations from participants who receive LLM-based recommendations before each valuation exhibit second-order stochastic dominance relative to valuations from participants who do not. Hence, LLM-based recommendations leave mean valuations unchanged but compress the distribution, reducing the incidence of extreme valuations. Consistent with this pattern, LLM-based recommendations reduce the intensity of risk, complexity, and ambiguity aversion, while leaving the fraction of participants classified as averse unchanged.

An individual reports subjective beliefs over continuous events using a proper scoring rule, such as the Quadratic Scoring Rule. Under mild additional assumptions, it is known that these reports reflect latent subjective beliefs if the individual is risk neutral. We demonstrate how to fully recover latent subjective beliefs if the individual is known to distort probabilities into decision weights using Rank Dependent Utility theory, and generalize all results for the complete class of proper scoring rules. As an immediate corollary, we can then exactly recover latent subjective beliefs using Expected Utility Theory. Using Bayesian econometric methods, we demonstrate how to recover belief distributions for individuals, and illustrate these results by recovering belief distributions about the “competitiveness” of individuals and the addictiveness of smoking. These results significantly widen the domain of applicability of proper scoring rules for eliciting latent subjective belief distributions.

We design and conduct a real-effort experiment to jointly estimate present bias and sophistication across effort and monetary domains. Unlike prior work (e.g.,Augenblick and Rabin, 2019; Fedyk, 2024), we do not assume that these parameters are identical across domains. We explain and empirically demonstrate how assuming identical sophistication across money and effort domains can bias the estimates of key parameters. In our online experiment, participants chose to (predicted to) complete 14% (10%) fewer tasks on the same day than on a future day, leading to an estimated present bias ($\beta_e$) over effort of 0.70–0.79, and an estimated sophistication ($\widehat{\beta}_e$) of 0.80–0.88. For money, aggregate present bias ($\beta_m$) is near zero, but there is substantial heterogeneity, with roughly equal numbers of participants exhibiting present bias and future bias. At the individual level, roughly three quarters of all participants correctly anticipate the direction of their bias in both domains, even if not its full magnitude.

This study investigates how in-game virtual currencies influence consumer spending behaviour. In an incentivized randomized controlled trial with 753 UK participants, we estimate the willingness-to-pay (WTP) for loot boxes represented as risky and ambiguous lotteries. We test the effects of virtual currencies, money illusion, and cognitive-demanding (non-intuitive) exchange rates, three practices commonly used to sell loot boxes. Our results show that WTP is significantly higher when transactions are conducted in virtual currencies with a 1:1 exchange rate compared to British pounds, contributing to the debate on the neutrality of virtual currencies and experimental currency units. Moreover, participants in our study are affected by money illusion distortions, regardless of the exchange rate’s intuitiveness. However, we find no evidence that non-intuitive exchange rates affect participants’ WTP compared to intuitive exchange rates of comparable size. These findings highlight the behavioural distortions induced by common monetization practices in games and provide empirical support for the European Commission’s call for stricter regulation of virtual currencies in digital environments.

Recent crises have increased price volatility, yet farmers’ adoption of forward contracts, futures, options, and price insurance remains low. Since this appears puzzling from a standard expected utility maximizing perspective, we systematically review the literature on the relation between behavioral factors and price hedging. We distinguish behavioral preferences, formally integrated into choice models, from psychological factors, lacking mathematical formalization. Most of the 101 reviewed studies focus on futures and rely on risk aversion assuming expected utility maximization, with limited evidence on behavioral economic drivers. Considering nonclassical preferences and psychological factors in choice models might better capture farmers’ risk management decisions.

The Multiple Price List (MPL) and Switching Multiple Price List (sMPL) provide a useful framework for estimating preference parameters, most usually risk aversion, from a sample of experimental subjects or survey respondents. In this paper, we consider designs in which more than one sMPL is presented to each subject, allowing more than one preference parameter to be estimated simultanously, and we propose a consistent estimator in this setting – the Multivariate Heterogeneous Preference (MHP) estimator. Focusing on the bivariate case of two sMPLs and two preference parameters, we demonstrate that non-standard econometric techniques, namely Monte Carlo integration with importance sampling, are required to implement the MHP estimator. Via a Monte Carlo exercise, we show that our estimator has good finite-sample properties. Finally, we apply the MHP estimator to a real data set and compare the estimates to those obtained using an inconsistent estimator applied in previous studies.

In various organizational settings, a team member is given the authority to make an investment decision that influences the value of the jointly produced surplus. We experimentally investigate the effect of asymmetric status, investment decisions, and the outcome of these decisions on bargaining behavior and outcomes. Agents’ initial contributions to the surplus are determined by their relative performances in a real-effort task. Three treatments vary in how the final surplus value is determined. We observe that when low-contributors take a risk, they are punished (rewarded) for failure (success), whereas high-contributors receive a fixed share independent of the outcome. Analysis of bargaining process variables, subjects’ communication during bargaining, and third parties’ normative judgments provides further insights into the possible mechanism behind this observation.

The prevalence of false and misleading news has become an issue of great concern in recent years. Academic researchers, policymakers, and social media firms all continue to seek effective solutions to reduce the sharing of misinformation. In this paper, we evaluate the effectiveness of two policies in particular: competition among media firms and fact-checking of published news articles by independent organizations. We first develop a theoretical model that predicts the effect of each policy and then conduct a behavioral experiment to test those predictions. Our experimental findings indicate that media competition is most effective at nipping misinformation in the bud because media firms spend significantly more resources on improving the accuracy of their news when readers obtain news from multiple sources. We also find that fact-checking improves the overall quality of news available to viewers; however, it does not incentivize firms to improve the accuracy of their own news articles. Last, our results from an interaction treatment suggest that under competition, fact-checking adversely affects firms’ investment in news accuracy.

There is existing evidence that many individuals have preferences regarding selection of numbers in lottery games. Lottery data indicate that the percentage of players who choose their numbers, instead of having numbers randomly assigned, varies widely by lottery game. Differences in number selection mechanisms between games and an expected return maximization motive only present for parimutuel games are both reasons that can explain the variation. Differences in the payoff distributions between lottery games could also be contributing to the observed variation, a novel proposition. An experiment is designed to control for differences in number selection mechanisms and remove the expected return maximization motive, to test for the presence of distribution-dependent number preferences. Results indicate that 40% to 50% of subjects may display such preferences. It is therefore possible that distribution-dependent number preferences contribute to the empirical variation in number selection percentages in lottery games.

This paper considers a stationary model of inventory management in a rich setting in which unsold units carry over, in contrast with the full depreciation of unsold units that is implemented in laboratory studies of the news vendor problem. The model permits an array of costs associated with restocking, understocking, depreciation, financing, and holding inventories. The extra dimensions make it possible to hold the optimal inventory constant, while adjusting parameters that change the frequency of stockouts and the risks associated with storage and depreciation. This framework facilitates an investigation of factors that influence the nature and severity of behavioral biases observed in simpler news vendor settings. Optimal inventory decisions are derived and tested with a laboratory experiment. We consider four main questions in the inventory literature: the “pull-to-center” effect, the “recency” effect, the effect of increased up-front costs, and the effect of risk aversion.

How have preventive and curative medical breakthroughs shaped life expectancy and the dispersion of age at death in the United States over the past century? We address this question by developing a life-cycle model in which both health and lifespan are endogenous. The model distinguishes between preventive innovations, which reduce the incidence of disease, and curative advances, which lower mortality risks associated with existing health conditions. Our quantitative analysis shows that while both types of medical innovation have contributed to increased life expectancy since 1935, curative advances have been the primary driver of the decline in the dispersion of age at death. Medical innovations have also improved welfare – measured in terms of a consumption-equivalent metric – by an average of 0.11% per year, with curative advances representing the most significant contribution. These findings are robust across different scenarios and parametrization strategies.

Many important decisions, for example, applying to college, require an individual to simultaneously submit several applications. These decisions are unique as each application is risky because acceptance is uncertain while also being rival as one can only attend a single college. In an influential theoretical analysis of these problems, Chade and Smith (2006) establish the No Safety Schools Theorem which suggests larger portfolios are riskier than single choices. We offer experimental evidence, using several experiments, that this theorem is routinely violated. In fact, the majority of our subjects violate this theorem. However, performance improves with practice, advice, and feedback.

Although compulsory insurance mitigates the negative externalities caused by uninsured individuals, it raises the issue of insurance crowding out prevention. However, at the theoretical level, compulsory insurance and self-insurance (preventive investments dedicated to loss reduction) are know to be substitutes for risk averters but complements for risk lovers. This paper aims to empirically test these opposite predictions through a laboratory experiment using a model-based design. Our experimental results confirm the theoretical predictions: compulsory insurance and self-insurance are complements for risk lovers and substitutes for risk averters. This study strongly supports public policies advocating mandatory insurance implementation as they enhance risk lovers’ self-insurance investments. Therefore, a risk management scheme combining voluntary top-up and compulsory partial insurance guarantees an optimal risk allocation for risk-averters and increases the investments in self-insurance for risk-lovers.

In this paper we study the idea of consequentialism in dynamic games by considering two versions: A commonly used utility-based version stating that the player’s preferences are governed by a utility function on consequences, and a preference-based version which faithfully translates the original idea of consequentialism to restrictions on the player’s preferences. Utility-based consequentialism always implies preference-based consequentialism, but the other direction is not necessarily true, as is shown by means of a counterexample. In this paper we offer conditions under which the two notions are equivalent.

In meritocratic societies, inequality is considered just if it reflects factors within but not outside individuals’ control. However, individuals often benefit differentially from other people’s efforts. Such passive inequality is simultaneously just and unjust by meritocratic standards, confronting meritocrats with a dilemma. We conducted an experiment with a representative US sample to investigate how people deal with this dilemma. In the experiment, impartial spectators redistribute payments between pairs of individuals. We vary whether initial payments result from luck or effort and whether spectators redistribute between individuals who worked themselves or individuals who benefited from the work of real-life friends. We find that spectators treat inequality based on the efforts of individuals’ friends as if individuals had worked themselves, and very different from inequality resulting from differential luck. This indicates that most people accept inequality if it is merited at some stage, which may explain opposition to redistributive policies.

In this paper, we study a two-period optimal insurance problem for a policyholder with mean-variance preferences who purchases proportional insurance at the beginning of each period. The insurance premium is calculated by a variance premium principle with a risk loading that depends on the policyholder’s claim history. We derive the time-consistent optimal insurance strategy in closed form and the optimal constant precommitment strategy in semiclosed form. For the optimal general precommitment strategy, we obtain the solution for the second period semi-explicitly and, then, the solution for the first period numerically via an efficient algorithm. Furthermore, we compare the three types of optimal strategies, highlighting their differences, and we examine the impact of the key model parameters on the optimal strategies and value functions.

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.