• We change the definition of financial distress in CoVaR. • We consider more severe distress events, backtest CoVaR, and improve its consistency. • Our CoVaR and VaR have a weak relation in the ...cross-section and in the time-series. • Depository institutions contribute the most to systemic risk. • Leverage, size, and equity beta are important in explaining systemic risk.
We modify Adrian and Brunnermeier’s (2011) CoVaR, the VaR of the financial system conditional on an institution being in financial distress. We change the definition of financial distress from an institution being exactly at its VaR to being at most at its VaR. This change allows us to consider more severe distress events, to backtest CoVaR, and to improve its consistency (monotonicity) with respect to the dependence parameter. We define the systemic risk contribution of an institution as the change from its CoVaR in its benchmark state (defined as a one-standard deviation event) to its CoVaR under financial distress. We estimate the systemic risk contributions of four financial industry groups consisting of a large number of institutions for the sample period June 2000 to February 2008 and the 12months prior to the beginning of the crisis. We also investigate the link between institutions’ contributions to systemic risk and their characteristics.
Risk aversion (a second-order risk preference) is a time-proven concept in economic models of choice under risk. More recently, the higher order risk preferences of prudence (third-order) and ...temperance (fourth-order) also have been shown to be quite important. While a majority of the population seems to exhibit both risk aversion and these higher order risk preferences, a significant minority does not. We show how both risk-averse and risk-loving behaviors might be generated by a simple type of basic lottery preference for either (1) combining "good" outcomes with "bad" ones, or (2) combining "good with good" and "bad with bad," respectively. We further show that this dichotomy is fairly robust at explaining higher order risk attitudes in the laboratory. In addition to our own experimental evidence, we take a second look at the extant laboratory experiments that measure higher order risk preferences and we find a fair amount of support for this dichotomy. Our own experiment also is the first to look beyond fourth-order risk preferences, and we examine risk attitudes at even higher orders.
Bridging an identified gap between research and practice in the domain of risk and organizational learning with respect to human/organizational factors and organizational behaviour, this book ...highlights the common and recurring threads in contributory factors to accident causation. Based on an extensive research project, it investigates how shipping companies as organizations learn from, filter and give credence/acceptability to differing risk perceptions and how this influences the work culture with special regard to group/team dynamics and individual motivation. The work is presented in the context of the literature regarding conceptual links between risk and the theoretical and operational themes of organizational learning, and in light of interviewees' comments. The themes include processes and structures of knowledge acquisition, information interpretation and distribution, organizational memory and change/adaptation and also levels of learning. The book concludes by discussing some practical implications of the research carried out in various maritime contexts and gives recommendations for the industry and other stakeholders.
Recent studies showed that climate change and socioeconomic trends are expected to increase flood risks in many regions. However, in these studies, human behavior is commonly assumed to be constant, ...which neglects interaction and feedback loops between human and environmental systems. This neglect of human adaptation leads to a misrepresentation of flood risk. This article presents an agent‐based model that incorporates human decision making in flood risk analysis. In particular, household investments in loss‐reducing measures are examined under three economic decision models: (1) expected utility theory, which is the traditional economic model of rational agents; (2) prospect theory, which takes account of bounded rationality; and (3) a prospect theory model, which accounts for changing risk perceptions and social interactions through a process of Bayesian updating. We show that neglecting human behavior in flood risk assessment studies can result in a considerable misestimation of future flood risk, which is in our case study an overestimation of a factor two. Furthermore, we show how behavior models can support flood risk analysis under different behavioral assumptions, illustrating the need to include the dynamic adaptive human behavior of, for instance, households, insurers, and governments. The method presented here provides a solid basis for exploring human behavior and the resulting flood risk with respect to low‐probability/high‐impact risks.
In the face of a novel infectious disease, changing our collective behaviour is critical to saving lives. One determinant of risk perception and risk behaviour that is often overlooked is the degree ...to which we share psychological group membership with others. We outline, and summarize supporting evidence for, a theoretical model that articulates the role of shared group membership in attenuating health risk perception and increasing health risk behaviour. We emphasize the importance of attending to these processes in the context of the ongoing response to COVID‐19 and conclude with three recommendations for how group processes can be harnessed to improve this response.
Cannabis use is common in North America, especially among young people, and is associated with a risk of various acute and chronic adverse health outcomes. Cannabis control regimes are evolving, for ...example toward a national legalization policy in Canada, with the aim to improve public health, and thus require evidence-based interventions. As cannabis-related health outcomes may be influenced by behaviors that are modifiable by the user, evidence-based Lower-Risk Cannabis Use Guidelines (LRCUG)-akin to similar guidelines in other health fields-offer a valuable, targeted prevention tool to improve public health outcomes.
To systematically review, update, and quality-grade evidence on behavioral factors determining adverse health outcomes from cannabis that may be modifiable by the user, and translate this evidence into revised LRCUG as a public health intervention tool based on an expert consensus process.
We used pertinent medical search terms and structured search strategies, to search MEDLINE, EMBASE, PsycINFO, Cochrane Library databases, and reference lists primarily for systematic reviews and meta-analyses, and additional evidence on modifiable risk factors for adverse health outcomes from cannabis use.
We included studies if they focused on potentially modifiable behavior-based factors for risks or harms for health from cannabis use, and excluded studies if cannabis use was assessed for therapeutic purposes.
We screened the titles and abstracts of all studies identified by the search strategy and assessed the full texts of all potentially eligible studies for inclusion; 2 of the authors independently extracted the data of all studies included in this review. We created Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow-charts for each of the topical searches. Subsequently, we summarized the evidence by behavioral factor topic, quality-graded it by following standard (Grading of Recommendations Assessment, Development, and Evaluation; GRADE) criteria, and translated it into the LRCUG recommendations by the author expert collective on the basis of an iterative consensus process.
For most recommendations, there was at least "substantial" (i.e., good-quality) evidence. We developed 10 major recommendations for lower-risk use: (1) the most effective way to avoid cannabis use-related health risks is abstinence, (2) avoid early age initiation of cannabis use (i.e., definitively before the age of 16 years), (3) choose low-potency tetrahydrocannabinol (THC) or balanced THC-to-cannabidiol (CBD)-ratio cannabis products, (4) abstain from using synthetic cannabinoids, (5) avoid combusted cannabis inhalation and give preference to nonsmoking use methods, (6) avoid deep or other risky inhalation practices, (7) avoid high-frequency (e.g., daily or near-daily) cannabis use, (8) abstain from cannabis-impaired driving, (9) populations at higher risk for cannabis use-related health problems should avoid use altogether, and (10) avoid combining previously mentioned risk behaviors (e.g., early initiation and high-frequency use).
Evidence indicates that a substantial extent of the risk of adverse health outcomes from cannabis use may be reduced by informed behavioral choices among users. The evidence-based LRCUG serve as a population-level education and intervention tool to inform such user choices toward improved public health outcomes. However, the LRCUG ought to be systematically communicated and supported by key regulation measures (e.g., cannabis product labeling, content regulation) to be effective. All of these measures are concretely possible under emerging legalization regimes, and should be actively implemented by regulatory authorities. The population-level impact of the LRCUG toward reducing cannabis use-related health risks should be evaluated. Public health implications. Cannabis control regimes are evolving, including legalization in North America, with uncertain impacts on public health. Evidence-based LRCUG offer a potentially valuable population-level tool to reduce the risk of adverse health outcomes from cannabis use among (especially young) users in legalization contexts, and hence to contribute to improved public health outcomes.
As residents living in hazard‐prone areas face on‐going environmental threats, the actions they take to mitigate such risks are likely motivated by various factors. Whereas risk perception has been ...considered a key determinant of related behavioral responses, little is known about how risk mitigation actions influence subsequent perceived risk. In other words, do actions to prevent or mitigate risk reduce risk perception? This longitudinal study considers the dynamic relationships between risk perception and risk‐mitigating behavior in the context of forest disturbance in north‐central Colorado. Based on panel survey data collected in 2007 and 2018, the results provide a first look at changes in perceived forest risks as they relate to individual and community actions in response to an extensive mountain pine beetle outbreak. Analysis revealed that the perception of direct forest risks (forest fire and falling trees) increased, whereas indirect forest risk perception (concern on broader threats to local community) decreased across the two study phases. Higher individual or community activeness (level of actions) was associated with subsequent reductions in perceived forest fire risk, smaller increases in direct risk perception, and larger decreases in indirect risk perception. These findings contribute insights into the complex risk reappraisal process in forest hazard contexts, with direct implications for risk communication and management strategies.
In recent years, there has been a gradual increase in research literature on the challenges of interconnected, compound, interacting, and cascading risks. These concepts are becoming ever more ...central to the resilience debate. They aggregate elements of climate change adaptation, critical infrastructure protection, and societal resilience in the face of complex, high‐impact events. However, despite the potential of these concepts to link together diverse disciplines, scholars and practitioners need to avoid treating them in a superficial or ambiguous manner. Overlapping uses and definitions could generate confusion and lead to the duplication of research effort. This article gives an overview of the state of the art regarding compound, interconnected, interacting, and cascading risks. It is intended to help build a coherent basis for the implementation of the Sendai Framework for Disaster Risk Reduction (SFDRR). The main objective is to propose a holistic framework that highlights the complementarities of the four kinds of complex risk in a manner that is designed to support the work of researchers and policymakers. This article suggests how compound, interconnected, interacting, and cascading risks could be used, with little or no redundancy, as inputs to new analyses and decisional tools designed to support the implementation of the SFDRR. The findings can be used to improve policy recommendations and support tools for emergency and crisis management, such as scenario building and impact trees, thus contributing to the achievement of a system‐wide approach to resilience.
In this paper we study both market risks and nonmarket risks, without complete markets assumption, and discuss methods of measurement of these risks. We present and justify a set of four desirable ...properties for measures of risk, and call the measures satisfying these properties “coherent.” We examine the measures of risk provided and the related actions required by SPAN, by the SEC/NASD rules, and by quantile‐based methods. We demonstrate the universality of scenario‐based methods for providing coherent measures. We offer suggestions concerning the SEC method. We also suggest a method to repair the failure of subadditivity of quantile‐based methods.
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