Journal of Risk and Uncertainty最新文献

When faced with a global threat peoples’ perception of risk guides their response. When danger is to the self as well as to others two risk estimates are generated—to the self and to others. Here, we set out to examine how people’s perceptions of health risk to the self and others are related to their psychological well-being and behavioral response. To that end, we surveyed a large representative sample of Americans facing the COVID-19 pandemic at two times (N₁ = 1145, N₂ = 683). We found that people perceived their own risk to be relatively low, while estimating the risk to others as relatively high. These risk estimates were differentially associated with psychological well-being and behavior. In particular, perceived personal but not public risk was associated with people’s happiness, while both were predictive of anxiety. In contrast, the tendency to engage in protective behaviors were predicted by peoples’ estimated risk to the population, but not to themselves. This raises the possibility that people were predominantly engaging in protective behaviors for the benefit of others. The findings can inform public policy aimed at protecting people’s psychological well-being and physical health during global threats.

Intertemporal choice involves outcomes that are received in different moments of time. This paper presents a new framework for analyzing intertemporal choice as a tradeoff between the cumulative payoff of a stream of intertemporal outcomes and its average delay (similar to the mean–variance approach in modelling risk preferences). Ceteris paribus, a decision maker prefers a stream of intertemporal payoffs with a higher cumulative payoff and a lower average delay. A decision maker with such time preferences always dislikes a partial delay in consumption (splitting one payoff into two, one of which is slightly delayed in time). In contrast, many existing models (e.g. discounted utility, quasi-hyperbolic discounting, generalized hyperbolic discounting or liminal discounting) imply a preference for partial delay. Our proposed model is compatible with the common difference effect (corresponding to a horizontal fanning-out of indifference curves) and the absolute magnitude effect (corresponding to a vertical fanning-in of indifference curves). The proposed model is applied to the standard consumption-savings problem with a constant interest rate. A simple experimental test of the proposed model vs. discounted utility and quasi-hyperbolic discounting is presented.

This paper analyzes within-session test/retest data from four different tasks used to elicit risk attitudes. Maximum-likelihood and non-parametric estimations on 16 datasets reveal that, irrespective of the task, measurement error accounts for approximately 50% of the variance of the observed variable capturing risk attitudes. The consequences of this large noise element are evaluated by means of simulations. First, as predicted by theory, the coefficient on the risk measure in univariate OLS regressions is attenuated to approximately half of its true value, irrespective of the sample size. Second, the risk-attitude measure may spuriously appear to be insignificant, especially in small samples. Unlike the measurement error arising from within-individual variability, rounding has little influence on significance and biases. In the last part, we show that instrumental-variable estimation and the ORIV method, developed by Gillen et al. (2019), both of which require test/retest data, can eliminate the attenuation bias, but do not fully solve the insignificance problem in small samples. Increasing the number of observations to N=500 removes most of the insignificance issues.

Little is known about how people's beliefs concerning the Coronavirus Disease 2019 (COVID-19) influence their behavior. To shed light on this, we conduct an online experiment ( $n=3,610$ ) with US and UK residents. Participants are randomly allocated to a control group or to one of two treatment groups. The treatment groups are shown upper- or lower-bound expert estimates of the infectiousness of the virus. We present three main empirical findings. First, individuals dramatically overestimate the dangerousness and infectiousness of COVID-19 relative to expert opinion. Second, providing people with expert information partially corrects their beliefs about the virus. Third, the more infectious people believe that COVID-19 is, the less willing they are to take protective measures, a finding we dub the "fatalism effect". We develop a formal model that can explain the fatalism effect and discuss its implications for optimal policy during the pandemic.

Expected Utility Theory (EUT) provides axioms for maximizing utility in risky choice. The Independence Axiom (IA) is its most demanding axiom: preferences between two options should not change when altering both options equally by mixing them with a common gamble. We tested common consequence (CC) and common ratio (CR) violations of the IA over several months in thousands of stochastic choices using a large variety of binary option sets. Three monkeys showed consistently few outright Preference Reversals (8%) but substantial graded Preference Changes (46%) between the initial preferred gamble and the corresponding altered gamble. Linear Discriminant Analysis (LDA) indicated that gamble probabilities predicted most Preference Changes in CC (72%) and CR (88%) tests. The Akaike Information Criterion indicated that probability weighting within Cumulative Prospect Theory (CPT) explained choices better than models using Expected Value (EV) or EUT. Fitting by utility and probability weighting functions of CPT resulted in nonlinear and non-parallel indifference curves (IC) in the Marschak-Machina triangle and suggested IA non-compliance of models using EV or EUT. Indeed, CPT models predicted Preference Changes better than EV and EUT models. Indifference points in out-of-sample tests were closer to CPT-estimated ICs than EV and EUT ICs. Finally, while the few outright Preference Reversals may reflect the long experience of our monkeys, their more graded Preference Changes corresponded to those reported for humans. In benefitting from the wide testing possibilities in monkeys, our stringent axiomatic tests contribute critical information about risky decision-making and serves as basis for investigating neuronal decision mechanisms.

Supplementary information: The online version contains supplementary material available at 10.1007/s11166-022-09388-7.