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Low insurance take‐up in low‐income populations is not easily explained by the standard single‐period expected utility model of insurance that overlooks the relevance of time preference when liquidity is constrained. We design field survey instruments to elicit quasi‐hyperbolic time preferences, as well as prospect theory risk preferences, and use them to examine whether time preferences explain health insurance behavior of low‐income Filipinos. Consistent with theory, those with stronger parameterized time preference are less likely to insure and the partial association is most pronounced at low wealth where liquidity is most likely to be constrained. Among those with better understanding of insurance, lower take‐up is also associated with present bias. We do not find that insurance is significantly associated with risk preferences. [ABSTRACT FROM AUTHOR]

Prevention efforts, such as quitting smoking, flu vaccination, and exercising, are of crucial importance in health policy, but people tend to undertake too few of them. The main reason is that most prevention efforts only reduce but do not completely eliminate the risk of poor health. This makes it harder for people to assess the benefits of prevention, because they tend to misperceive and transform probabilities. In "When Risk Perception Gets in the Way: Probability Weighting and Underprevention," Baillon et al. introduce psychological insights (probability weighting) in a model of optimal decision making and show that most people undertake too little prevention when the risk of poor health is between 10% and 80%. The paper discusses several policy measures to make people spend more on prevention. Personal decisions about health hazards are the main cause of impaired health and premature death. People smoke and eat too much, and they exercise too little. The lack of preventive efforts is surprising given their proven effectiveness. In the early 1960s, Arrow suggested that moral hazard might be a reason for underprevention, but this explanation was later challenged. In this paper, we show that underprevention might be caused by misperceived probabilities. We derive when and how probability weighting gets in the way of prevention by blurring its benefits. We use a general model of prevention, encompassing several special cases from the literature. We also show how perceived ambiguity makes the problem of underprevention even worse by amplifying the effect of probability weighting. [ABSTRACT FROM AUTHOR]

Facing several decisions, people may consider each one in isolation or integrate them into a single optimization problem. Isolation and integration may yield different choices, for instance, if uncertainty is involved, and only one randomly selected decision is implemented. We investigate whether the random incentive system in experiments that measure ambiguity aversion provides a hedge against ambiguity, making ambiguity‐averse subjects who integrate behave as if they were ambiguity neutral. Our results suggest that about half of the ambiguity averse subjects integrated their choices in the experiment into a single problem, whereas the other half isolated. Our design further enables us to disentangle properties of the integrating subjects' preferences over compound objects induced by the random incentive system and the choice problems in the experiment. [ABSTRACT FROM AUTHOR]

This paper introduces two simple betting mechanisms—top‐flop and threshold betting—to elicit unverifiable information from crowds. Agents are offered bets on the rating of an item about which they received a private signal versus that of a random item. We characterize conditions for the chosen bet to reveal the agents' private signal even if the underlying ratings are biased. We further provide microeconomic foundations of the ratings, which are endogenously determined by the actions of other agents in a game setting. Our mechanisms relax standard assumptions of the literature, such as common prior, and homogeneous and risk neutral agents. [ABSTRACT FROM AUTHOR]

Although reference dependence plays a central role in explaining behavior, little is known about the way that reference points are selected. This paper identifies empirically which reference point people use in decision under risk. We assume a comprehensive reference-dependent model that nests the main reference-dependent theories, including prospect theory, and that allows for isolating the reference point rule from other behavioral parameters. Our experiment involved high stakes with payoffs up to a week's salary. We used an optimal design to select the choices in the experiment and Bayesian hierarchical modeling for estimation. The most common reference points were the status quo and a security level (the maximum of the minimal outcomes of the prospects in a choice). We found little support for the use of expectations-based reference points. This paper was accepted by David Simchi-Levi, decision analysis. [ABSTRACT FROM AUTHOR]

Cybersecurity cannot be ensured with mere technical solutions. Hackers often use fraudulent emails to simply ask people for their password to breach into organizations. This technique, called phishing, is a major threat for many organizations. A typical prevention measure is to inform employees but is there a better way to reduce phishing risks? Experience and feedback have often been claimed to be effective in helping people make better decisions. In a large field experiment involving more than 10,000 employees of a Dutch ministry, we tested the effect of information provision, simulated experience, and their combination to reduce the risks of falling into a phishing attack. Both approaches substantially reduced the proportion of employees giving away their password. Combining both interventions did not have a larger impact. [ABSTRACT FROM AUTHOR]

Two events are exchangeable for an agent when she is indifferent to permutations of their outcomes. Such events are thus revealed to be equally likely. If they are complementary, the subjective probability associated with each event should be 1/2 (assuming the additivity of the probability measure). This paper reports the results of an experiment that elicits probabilities through exchangeable events. The experiment shows that this method does not suffer from source dependence, i.e., the preference for betting on some events based on knowledge about the mechanism that generates them. However, it also highlights how additivity might be violated. This paper deduces the practical implications of these results. [ABSTRACT FROM AUTHOR]

Language use differs between truthful and deceptive statements, but not all differences are consistent across people and contexts, complicating the identification of deceit in individuals. By relying on fact-checked tweets, we showed in three studies (Study 1: 469 tweets; Study 2: 484 tweets; Study 3: 24 models) how well personalized linguistic deception detection performs by developing the first deception model tailored to an individual: the 45th U.S. president. First, we found substantial linguistic differences between factually correct and factually incorrect tweets. We developed a quantitative model and achieved 73% overall accuracy. Second, we tested out-of-sample prediction and achieved 74% overall accuracy. Third, we compared our personalized model with linguistic models previously reported in the literature. Our model outperformed existing models by 5 percentage points, demonstrating the added value of personalized linguistic analysis in real-world settings. Our results indicate that factually incorrect tweets by the U.S. president are not random mistakes of the sender. [ABSTRACT FROM AUTHOR]