Journal of Risk and Uncertainty最新文献

As health care becomes increasingly personalized to the needs and values of individual patients, informational interventions that aim to inform and debias consumer decision-making are likely to become important tools. In a randomized controlled experiment, we explore the effects of providing participants with published fact boxes on the benefits and harms of common cancer screening procedures. Female participants were surveyed about breast cancer screening by mammography, while male participants were surveyed about prostate cancer screening by prostate-specific antigen (PSA) testing. For these screening procedures, we expect consumers to have overly optimistic prior beliefs about the benefits and harms. We find that participants update their beliefs about the net benefits of screening modestly, but we observe little change in their stated preferences to seek screening. Participants who scored higher on a numeracy test updated their beliefs about screening benefits more in response to the fact boxes than did participants who scored lower on the numeracy test.

An important societal problem is that people underinsure against risks that are unlikely or occur in the far future, such as natural disasters and long-term care needs. One explanation is that uncertainty about the risk of non-reimbursement induces ambiguity averse and risk prudent decision makers to take out less insurance. We set up an insurance experiment to test this explanation. Consistent with the theoretical predictions, we find that the demand for insurance is lower when the nonperformance risk is ambiguous than when it is known and when decision makers are risk prudent. We cannot attribute the lower take-up of insurance to our measure of ambiguity aversion, probably because ambiguity attitudes are richer than aversion alone.

Supplementary information: The online version contains supplementary material available at 10.1007/s11166-021-09364-7.

While much literature has focused on preferences regarding risk, preferences over skewness also have significant economic implications. An important and understudied aspect of skewness preferences is how they affect risk taking. In this paper, we design a novel laboratory experiment that elicits certainty equivalents over lotteries where the variance and skewness of the outcomes are orthogonal to each other. This design enables us to cleanly measure both skewness seeking/avoiding and risk taking behavior, and their interaction, without needing to make parametric assumptions. Our experiment includes both left- and right-skewed lotteries. The results reveal that the majority of subjects are skewness avoiding risk takers who correspondingly also take more risk when facing less skewed lotteries. Our second contribution is to link these choices to individual rank-dependent utility preference parameters estimated using a separate lottery choice protocol. Using a latent-class model, we are able to identify two classes of subjects: skewness avoiders with the classic inverse s-shaped probability weighting function and skewness neutral subjects that do not have an inverse s-shaped probability weighting function. Our results thus demonstrate the link between probability distortion and skewness seeking/avoidance choices. They also highlight the importance of accounting for individual heterogeneity.

Supplementary information: The online version contains supplementary material available at 10.1007/s11166-021-09345-w.

The Centers for Disease Control and Prevention (CDC) deem large indoor gatherings without social distancing the "highest risk" activity for COVID-19 contagion. On June 20, 2020, President Donald J. Trump held his first mass campaign rally following the US coronavirus outbreak at the indoor Bank of Oklahoma arena. In the weeks following the event, numerous high-profile national news outlets reported that the Trump rally was "more than likely" the cause of a coronavirus surge in Tulsa County based on time series data. This study is the first to rigorously explore the impacts of this event on social distancing and COVID-19 spread. First, using data from SafeGraph Inc, we show that while non-resident visits to census block groups hosting the Trump event grew by approximately 25 percent, there was no decline in net stay-at-home behavior in Tulsa County, reflecting important offsetting behavioral effects. Then, using data on COVID-19 cases from the CDC and a synthetic control design, we find little evidence that COVID-19 grew more rapidly in Tulsa County, its border counties, or in the state of Oklahoma than each's estimated counterfactual during the five-week post-treatment period we observe. Difference-in-differences estimates further provide no evidence that COVID-19 rates grew faster in counties that drew relatively larger shares of residents to the event. We conclude that offsetting risk-related behavioral responses to the rally-including voluntary closures of restaurants and bars in downtown Tulsa, increases in stay-at-home behavior, displacement of usual activities of weekend inflows, and smaller-than-expected crowd attendance-may be important mechanisms.

Supplementary information: The online version contains supplementary material available at 10.1007/s11166-021-09359-4.

Economic theory suggests that the deterrence of deviant behavior is driven by a combination of severity and certainty of punishment. This paper presents the first controlled experiment to study a third important factor that has been mainly overlooked: the swiftness of formal sanctions. We consider two dimensions: the timing at which the uncertainty about whether one will be punished is dissolved and the timing at which the punishment is actually imposed, as well as the combination thereof. By varying these dimensions of delay systematically, we find a surprising non-monotonic relation with deterrence: either no delay (immediate resolution and immediate punishment) or maximum delay (both resolution and punishment as much as possible delayed) emerge as most effective at deterring deviant behavior and recidivism. Our results yield implications for the design of institutional policies aimed at mitigating misconduct and reducing recidivism.

Supplementary information: The online version contains supplementary material available at doi:10.1007/s11166-021-09352-x.