Macro-Economic Factors in Credit Risk Calculations: Including Time-Varying Covariates in Mixture Cure Models

The prediction of the time of default in a credit risk setting via survival analysis needs to take a high censoring rate into account. This rate is because default does not occur for the majority of debtors. Mixture cure models allow the part of the loan population that is unsusceptible to default to be modeled, distinct from time of default for the susceptible population. In this article, we extend the mixture cure model to include time-varying covariates. We illustrate the method via simulations and by incorporating macro-economic factors as predictors for an actual bank dataset.     

Systemic risk statistics with scenario analysis

In this paper, we introduce two new classes of risk statistics, named convex and positively homogeneous systemic risk statistics, respectively. Structural decomposition results and representation results for them are provided. These new risk statistics can be considered as a kind of systemic risk extension of risk statistics introduced by Kou, Peng, and Heyde, and also empirical versions of system risk measures introduced by Cehn, Iyengar, and Mollemi and Kromer, Overbeck, and Zich. Finally, some examples are also given.     

Safe-by-Design: Stakeholders’ Perceptions and Expectations of How to Deal with Uncertain Risks of Emerging Biotechnologies in the Netherlands

Advanced gene editing techniques such as Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)/Cas have increased the pace of developments in the field of industrial biotechnology. Such techniques imply new possibilities when working with living organisms, possibly leading to uncertain risks. In the Netherlands, current policy fails to address these uncertain risks because risk classification is determined process-wise (i.e., genetically modified organism [GMO] and non-GMO), there is a strong focus on quantifiable risks, and the linearity within current governance (science–policy–society) hinders iterative communication between stakeholders, leaving limited room to anticipate uncertainties at an early stage of development. A suggested concept to overcome these shortcomings is the Safe-by-Design (SbD) approach, which, theoretically, allows stakeholders to iteratively incorporate safety measures throughout a technology's development process, creating a dynamic environment for the anticipation of uncertain risks. Although this concept originates from chemical engineering and is already widely applied in nanotechnology, for the field of biotechnology, there is no agreed upon definition yet. To explore the possibilities of SbD for future governance of biotechnology, we should gain insight in how various stakeholders perceive notions of risk, safety, and inherent safety, and what this implies for the applicability of SbD for risk governance concerning industrial biotechnology. Our empirical research reveals three main themes: (1) diverging expectations with regard to safety and risks, and to establish an acceptable level of risk; (2) different applications of SbD and inherent safety, namely, product- and process-wise; and (3) unclarity in allocating responsibilities to stakeholders in the development process of a biotechnology and within society.     

Probabilistic Analysis of Dam Accidents Worldwide: Risk Assessment for Dams of Different Purposes in OECD and Non-OECD Countries with Focus on Time Trend Analysis

This study presents probabilistic analysis of dam accidents worldwide in the period 1911–2016. The accidents are classified by the dam purpose and by the country cluster, where they occurred, distinguishing between the countries of the Organization for Economic Cooperation and Development (OECD) and nonmember countries (non-OECD without China). A Bayesian hierarchical approach is used to model distributions of frequency and severity for accidents. This approach treats accident data as a multilevel system with subsets sharing specific characteristics. To model accident probabilities for a particular dam characteristic, this approach samples data from the entire data set, borrowing the strength across data set and enabling to model distributions even for subsets with scarce data. The modelled frequencies and severities are combined in frequency-consequence curves, showing that accidents for all dam purposes are more frequent in non-OECD (without China) and their maximum consequences are larger than in OECD countries. Multipurpose dams also have higher frequencies and maximum consequences than single-purpose dams. In addition, the developed methodology explicitly models time dependence to identify trends in accident frequencies over the analyzed period. Downward trends are found for almost all dam purposes confirming that technological development and implementation of safety measures are likely to have a positive impact on dam safety. The results of the analysis provide insights for dam risk management and decision-making processes by identifying key risk factors related to country groups and dam purposes as well as changes over time.     

Risk and Quantification: A Linguistic Study

In risk analysis and research, the concept of risk is often understood quantitatively. For example, risk is commonly defined as the probability of an unwanted event or as its probability multiplied by its consequences. This article addresses (1) to what extent and (2) how the noun risk is actually used quantitatively. Uses of the noun risk are analyzed in four linguistic corpora, both Swedish and English (mostly American English). In total, over 16,000 uses of the noun risk are studied in 14 random (n = 500) or complete samples (where n ranges from 173 to 5,144) of, for example, news and magazine articles, fiction, and websites of government agencies. In contrast to the widespread definition of risk as a quantity, a main finding is that the noun risk is mostly used nonquantitatively. Furthermore, when used quantitatively, the quantification is seldom numerical, instead relying on less precise expressions of quantification, such as high risk and increased risk. The relatively low frequency of quantification in a wide range of language material suggests a quantification bias in many areas of risk theory, that is, overestimation of the importance of quantification in defining the concept of risk. The findings are also discussed in relation to fuzzy‐trace theory. Findings of this study confirm, as suggested by fuzzy‐trace theory, that vague representations are prominent in quantification of risk. The application of the terminology of fuzzy‐trace theory for explaining the patterns of language use are discussed.     

Bad News Has Wings: Dread Risk Mediates Social Amplification in Risk Communication

Social diffusion of information amplifies risk through processes of birth, death, and distortion of message content. Dread risk—involving uncontrollable, fatal, involuntary, and catastrophic outcomes (e.g., terrorist attacks and nuclear accidents)—may be particularly susceptible to amplification because of the psychological biases inherent in dread risk avoidance. To test this, initially balanced information about high or low dread topics was given to a set of individuals who then communicated this information through diffusion chains, each person passing a message to the next. A subset of these chains were also reexposed to the original information. We measured prior knowledge, perceived risk before and after transmission, and, at each link, number of positive and negative statements. Results showed that the more a message was transmitted the more negative statements it contained. This was highest for the high dread topic. Increased perceived risk and production of negative messages was closely related to the amount of negative information that was received, with domain knowledge mitigating this effect. Reexposure to the initial information was ineffectual in reducing bias, demonstrating the enhanced danger of socially transmitted information.     

感知风险对在线旅游产品购买意愿的影响分析

旅游电子商务发展迅猛,互联网购物平台的虚拟性和远程性强化了消费者感知风险,它也成为影响旅游电子商务发展的重要因素之一.文章聚焦消费者感知风险,运用SPSS 19.0及AMOS 21.0软件,构建以5个维度的感知风险为自变量、购买意愿为因变量、信任为调节变量的结构方程模型,探讨变量间相关关系.结果发现:感知风险对信任的影响差异较大,仅经济风险感知与信任呈显著负相关;感知风险对购买意愿总效应皆呈负相关;信任作为中介变量存在明显的调节作用,有效地降低了感知风险对购买意愿的负向影响.     

A qualitative investigation of risk and protective factors for interpersonal violence in adults on the autism spectrum

Abstract

Individuals on the autism spectrum are at an increased risk of experiencing violence. This study sought to understand the opinions of adults on the spectrum regarding potential risk and protective factors for interpersonal violence. Twenty-two adults (12 men; 18 to 53 years of age) participated in semi-structured qualitative interviews. Interviews were recorded, transcribed, and analysed. The results of the qualitative analysis identified individual and contextual risk and protective factors. Protective themes focused on individual needs (awareness of the self and the environment, interpersonal knowledge/skills, skill building strategies) and supportive contexts (benefits of a trusted person, advocates, fostering acceptance and inclusion). There is a need for strategies to decrease the vulnerability to, and the impact of, interpersonal violence. Individuals on the spectrum have the capacity to provide important information regarding safety promotion and risk factors for interpersonal violence, and their expertise should play a role in guiding efforts that promote safety.     

#BlackLivesMatter: Innovative Black Resistance

Since 2013, extrajudicial police killings of black people have captured the attention of U.S. and international media, substantially because of the work of leaders in the Black Lives Matter (#BLM) movement. #BLM is simultaneously a group of localized organizations and a broad online social movement. In this article, we examine the #BLM movement in detail, with particular emphasis on the following aspects of the movement: (1) its innovative organizational practices and social media use; (2) its accent on black perspectives (counterframing) of systemic racial oppression, heteronormativity, and capitalism; and (3) its broad emphasis on oppressed Americans, including black women and LGBTQ people. We also situate the #BLM movement within the surrounding system of racial oppression, including the historical role of racialized policing in maintaining social control of blacks. We detail the long tradition of black social movements, especially black feminist organizing, against systemic racial oppression. In doing so, we intend to contribute social movement theorizing that more fully considers powerful counterframed perspectives of black activists in U.S. social movements. Although the #BLM movement reflects black feminism and past civil rights movement struggles, it is a uniquely twenty‐first‐century social movement that uses new technologies for innovative social protest.     

Joint models for mixed categorical outcomes: a study of HIV risk perception and disease status in Mozambique

Two types of bivariate models for categorical response variables are introduced to deal with special categories such as ‘unsure’ or ‘unknown’ in combination with other ordinal categories, while taking additional hierarchical data structures into account. The latter is achieved by the use of different covariance structures for a trivariate random effect. The models are applied to data from the INSIDA survey, where interest goes to the effect of covariates on the association between HIV risk perception (quadrinomial with an ‘unknown risk’ category) and HIV infection status (binary). The final model combines continuation-ratio with cumulative link logits for the risk perception, together with partly correlated and partly shared trivariate random effects for the household level. The results indicate that only age has a significant effect on the association between HIV risk perception and infection status. The proposed models may be useful in various fields of application such as social and biomedical sciences, epidemiology and public health.