Social Contagion of Risk Perceptions in Environmental Management Networks

An important requisite for improving risk communication practice related to contentious environmental issues is having a better theoretical understanding of how risk perceptions function in real‐world social systems. Our study applied Scherer and Cho's social network contagion theory of risk perception (SNCTRP) to cormorant management (a contentious environmental management issue) in the Great Lakes Basin to: (1) assess contagion effects on cormorant‐related risk perceptions and individual factors believed to influence those perceptions and (2) explore the extent of social contagion in a full network (consisting of interactions between and among experts and laypeople) and three “isolated” models separating different types of interactions from the full network (i.e., expert‐to‐expert, layperson‐to‐layperson, and expert‐to‐layperson). We conducted interviews and administered questionnaires with experts (e.g., natural resource professionals) and laypeople (e.g., recreational and commercial anglers, business owners, bird enthusiasts) engaged in cormorant management in northern Lake Huron (n = 115). Our findings generally support the SNCTRP; however, the scope and scale of social contagion varied considerably based on the variables (e.g., individual risk perception factors), actors (i.e., experts or laypeople), and interactions of interest. Contagion effects were identified more frequently, and were stronger, in the models containing interactions between experts and laypeople than in those models containing only interactions among experts or laypeople.     

基于熵空间交互理论的CRT网络信用风险传染模型

信用风险转移(Credit Risk Transfer,CRT)网络中信用风险传染已逐渐成为学术界和政策制定者关注的热点。本文基于熵空间交互理论,将CRT网络中银行和投资者之间空间距离与非线性耦合、银行的信用风险转移能力与投资者的风险偏好相结合,建立了CRT网络信用风险传染的熵空间模型。通过数值模拟和对参数的敏感性分析发现,模型可以很好地反映银行和投资者之间的空间距离与非线性耦合、银行的信用风险转移能力、信用风险在投资者节点上的集中程度、投资者的风险偏好和风险承受能力对CRT网络信用风险传染效应的影响机制。研究同时发现:CRT网络信用风险传染具有"本地效应"和"关联抑制效应"。     

A Bayesian Approach to Integrated Ecological and Human Health Risk Assessment for the South River,Virginia Mercury‐Contaminated Site

We conducted a regional‐scale integrated ecological and human health risk assessment by applying the relative risk model with Bayesian networks (BN‐RRM) to a case study of the South River, Virginia mercury‐contaminated site. Risk to four ecological services of the South River (human health, water quality, recreation, and the recreational fishery) was evaluated using a multiple stressor–multiple endpoint approach. These four ecological services were selected as endpoints based on stakeholder feedback and prioritized management goals for the river. The BN‐RRM approach allowed for the calculation of relative risk to 14 biotic, human health, recreation, and water quality endpoints from chemical and ecological stressors in five risk regions of the South River. Results indicated that water quality and the recreational fishery were the ecological services at highest risk in the South River. Human health risk for users of the South River was low relative to the risk to other endpoints. Risk to recreation in the South River was moderate with little spatial variability among the five risk regions. Sensitivity and uncertainty analysis identified stressors and other parameters that influence risk for each endpoint in each risk region. This research demonstrates a probabilistic approach to integrated ecological and human health risk assessment that considers the effects of chemical and ecological stressors across the landscape.     

动态尾部金融网络结构与传染性度量

基于Lasso高维分位数回归模型,本文构建了中国金融系统的尾部网络结构,并定义了总体网络以及行业间、行业内和金融机构间等多层金融网络的尾部风险传染度,解构其传染机制与关联特征,评估各机构双向系统重要性(接收端和发射端)。同时,本文提出了一个最优滚动窗宽选择标准方法,以优化滚动样本技术下的动态网络结构。结果表明,所有层级尾部风险传染效应(总体系统、行业间、行业内和机构间)在经济金融极端困境时期,呈现明显增强及剧烈震荡特征,2015年中国股灾期间尤甚。跨行业传染效应日益严峻,银行与保险间表现出较强关联性,房地产机构与其他金融机构间均表现出较高传染性,跨业监管值得关注。接收与发射最多尾部风险传染的金融机构仍然是银行与证券类机构。系统中超过50%的金融机构倾向于接收风险传染,一旦出现系统性冲击,整个金融系统的稳定性将遭受重创,因此,应加强此类机构应对外界冲击的能力。此外,基于新滚动窗宽选择标准法的动态模型的估计性能明显优于传统方法。研究结论有助于理解中国金融系统的网络结构和传染机制,对宏观审慎监管体系的建立提供了依据。     

FIRM DEFAULT AND AGGREGATE FLUCTUATIONS

This paper studies the relationship between macroeconomic fluctuations and corporate defaults while conditioning on industry affiliation and an extensive set of firm‐specific factors. By using a panel data set for virtually all incorporated Swedish businesses over 1990–2009, a period which includes a full‐scale banking crisis, we find strong evidence for a substantial and stable impact from aggregate fluctuations on business defaults. A standard logit model with financial ratios augmented with macroeconomic factors can account surprisingly well for the outburst in business defaults during the banking crisis, as well as the subsequent fluctuations in default frequencies. Moreover, the effects of macroeconomic variables differ across industries in an economically intuitive way. Out‐of‐sample evaluations show that our approach is superior to models that exclude macro information and standard well‐fitting time‐series models. Our analysis shows that firm‐specific factors are useful in ranking firms’ relative riskiness, but that macroeconomic factors are necessary to understand fluctuations in the absolute risk level.     

考虑在险价值的中小企业成长性评价研究——基于沪深中小上市公司的实证

评价分析中小企业的成长性有助于中小企业的发展,越来越多的研究从各个角度来评价其成长能力。本文以中小上市公司为样本,在已有的较为成熟的指标体系中加入市场风险的在险价值因素,并通过实证研究对考虑市场风险因素与未考虑市场风险因素两个排名作有效性检验及比较分析,得出考虑市场风险因素的排名结果更为有效。以不同公司作为样本对成长性排名与市场风险做回归分析,发现对总体样本而言,成长性排名与市场风险呈显著负相关关系。     

Some Limitations of “Risk = Threat × Vulnerability × Consequence” for Risk Analysis of Terrorist Attacks

Several important risk analysis methods now used in setting priorities for protecting U.S. infrastructures against terrorist attacks are based on the formula: Risk=Threat×Vulnerability×Consequence. This article identifies potential limitations in such methods that can undermine their ability to guide resource allocations to effectively optimize risk reductions. After considering specific examples for the Risk Analysis and Management for Critical Asset Protection (RAMCAP?) framework used by the Department of Homeland Security, we address more fundamental limitations of the product formula. These include its failure to adjust for correlations among its components, nonadditivity of risks estimated using the formula, inability to use risk‐scoring results to optimally allocate defensive resources, and intrinsic subjectivity and ambiguity of Threat, Vulnerability, and Consequence numbers. Trying to directly assess probabilities for the actions of intelligent antagonists instead of modeling how they adaptively pursue their goals in light of available information and experience can produce ambiguous or mistaken risk estimates. Recent work demonstrates that two‐level (or few‐level) hierarchical optimization models can provide a useful alternative to Risk=Threat×Vulnerability×Consequence scoring rules, and also to probabilistic risk assessment (PRA) techniques that ignore rational planning and adaptation. In such two‐level optimization models, defender predicts attacker's best response to defender's own actions, and then chooses his or her own actions taking into account these best responses. Such models appear valuable as practical approaches to antiterrorism risk analysis.     

A Bayesian Method to Mine Spatial Data Sets to Evaluate the Vulnerability of Human Beings to Catastrophic Risk

Vulnerability of human beings exposed to a catastrophic disaster is affected by multiple factors that include hazard intensity, environment, and individual characteristics. The traditional approach to vulnerability assessment, based on the aggregate‐area method and unsupervised learning, cannot incorporate spatial information; thus, vulnerability can be only roughly assessed. In this article, we propose Bayesian network (BN) and spatial analysis techniques to mine spatial data sets to evaluate the vulnerability of human beings. In our approach, spatial analysis is leveraged to preprocess the data; for example, kernel density analysis (KDA) and accumulative road cost surface modeling (ARCSM) are employed to quantify the influence of geofeatures on vulnerability and relate such influence to spatial distance. The knowledge‐ and data‐based BN provides a consistent platform to integrate a variety of factors, including those extracted by KDA and ARCSM to model vulnerability uncertainty. We also consider the model's uncertainty and use the Bayesian model average and Occam's Window to average the multiple models obtained by our approach to robust prediction of the risk and vulnerability. We compare our approach with other probabilistic models in the case study of seismic risk and conclude that our approach is a good means to mining spatial data sets for evaluating vulnerability.     

企业家社交关系对关联信用风险传染影响的研究——基于双层网络视角

关联信用风险是指某些企业违约,导致与其存在关联关系的企业违约或违约可能性增大的这类信用风险。企业家的社交关系会影响企业之间关联信用风险的传染效应。本文利用双层网络刻画企业家和企业所形成的耦合网络,分析企业家的社交关系对关联信用风险传染的影响路径,构建双层网络中关联信用风险的传染模型,并考察企业家社交网络和双层网络的结构等因素对关联信用风险传染效应的影响。研究结果表明：企业家的社交关系是影响关联信用风险传染的重要因素;企业家社交-企业关联双层网络的拓扑结构也会影响关联信用风险的传染效应;提高双层网络的相似度,可以抑制关联信用风险在关联企业网络中的传染。本文的研究进一步拓展了信用风险的研究视角,为银行等金融机构对信用风险的提供科学的决策依据。     

FINANCIAL CONTAGION THROUGH CAPITAL CONNECTIONS: A MODEL OF THE ORIGIN AND SPREAD OF BANK PANICS

Financial contagion is modeled as an equilibrium phenomenon in a dynamic setting with incomplete information and multiple banks. The equilibrium probability of bank failure is uniquely determined. We explore how the cross‐holding of deposits motivated by imperfectly correlated regional liquidity shocks can lead to contagious effects conditional on the failure of a financial institution. We show that contagious bank failure occurs with positive probability in the unique equilibrium of the economy and demonstrate that the presence of such contagion risk can prevent banks from perfectly insuring each other against liquidity shocks via the cross‐holding of deposits. (JEL: G2, C7)     

From Entrepreneurial Orientation and Learning Orientation to Business Performance: Analysing the Mediating Role of Organizational Learning and the Moderating Effects of Organizational Size

Following the organizational learning theory and the knowledge‐based view approach, this contribution aims to study the influence of entrepreneurial orientation and learning orientation on organizational learning, considering the latter as a mediating variable in the relationships between both antecedent cultural values and business performance. We also analyse the moderating role of organizational size on these previous relationships. The hypotheses proposed in our research model are tested on a sample of 140 Spanish industrial companies, applying variance‐based structural equation modelling: partial least squares. In order to assess the moderating effects of organizational size, we adopt a multi‐group approach using two subsamples with large firms and small and medium‐sized enterprises (SMEs). Our findings indicate that organizational learning partially mediates the relationship between entrepreneurial orientation and performance and fully mediates the link between learning orientation and performance. Likewise, the results reveal that the relationship established between entrepreneurial orientation and organizational learning is more intense for the group of large firms than for the group of SMEs. Moreover, the influence of learning orientation on organizational learning is greater in SMEs than in large firms.     

“These Power Lines Make Me Ill”: A Typology of Residents’ Health Responses to a New High‐Voltage Power Line

Little attention has been devoted to the potential diversity in residents’ health responses when exposed to an uncertain environmental health risk. The present study explores whether subgroups of residents respond differently to a new high‐voltage power line (HVPL) being put into operation. We used a quasi‐experimental prospective field study design with two pretests during the construction of a new HVPL, and two posttests after it was put into operation. Residents living nearby (0–300 m, n = 229) filled out questionnaires about their health and their perception of the environment. We applied latent class growth models to investigate heterogeneity in the belief that health complaints were caused by a power line. Classes were compared on a wide range of variables relating to negative‐oriented personality traits, perceived physical and mental health, and perceptions of the environment. We identified five distinct classes of residents, of which the largest (49%) could be described as emotionally stable and healthy with weak responses to the introduction of a new power line. A considerable minority (9%) responded more strongly to the new line being activated. Residents in this class had heard more about the health effects of power lines beforehand, were more aware of the activation of the new line, and reported a decrease in perceived health afterwards. Based on our findings we can conclude that there is a considerable heterogeneity in health responses to a new HVPL. Health risk perceptions appear to play an important role in this typology, which has implications for risk management.     

An Assessment of Change in Risk Perception and Optimistic Bias for Hurricanes Among Gulf Coast Residents

This study focuses on levels of concern for hurricanes among individuals living along the Gulf Coast during the quiescent two‐year period following the exceptionally destructive 2005 hurricane season. A small study of risk perception and optimistic bias was conducted immediately following Hurricanes Katrina and Rita. Two years later, a follow‐up was done in which respondents were recontacted. This provided an opportunity to examine changes, and potential causal ordering, in risk perception and optimistic bias. The analysis uses 201 panel respondents who were matched across the two mail surveys. Measures included hurricane risk perception, optimistic bias for hurricane evacuation, past hurricane experience, and a small set of demographic variables (age, sex, income, and education). Paired t‐tests were used to compare scores across time. Hurricane risk perception declined and optimistic bias increased. Cross‐lagged correlations were used to test the potential causal ordering between risk perception and optimistic bias, with a weak effect suggesting the former affects the latter. Additional cross‐lagged analysis using structural equation modeling was used to look more closely at the components of optimistic bias (risk to self vs. risk to others). A significant and stronger potentially causal effect from risk perception to optimistic bias was found. Analysis of the experience and demographic variables’ effects on risk perception and optimistic bias, and their change, provided mixed results. The lessening of risk perception and increase in optimistic bias over the period of quiescence suggest that risk communicators and emergency managers should direct attention toward reversing these trends to increase disaster preparedness.     

基于欧洲主权债务危机背景下的金融传染分析

运用向量自回归方法(VAR)和时变多元GARCH模型(DCC-MGARCH),检验欧洲主权债务危机期间的金融传染效应。研究市场包括希腊、西班牙、爱尔兰、英国、法国、德国、美国、日本以及中国的股票市场。实证结果表明,欧洲债务危机期间各国金融市场间相关性显著上升,市场间影响程度更大、影响时间更长,存在金融传染效应;希腊是此次危机的传染源,欧洲其他国家之间的传染效应不明显;蔓延期中国股票市场也与欧洲市场存在联动性,但影响较为滞后。此外,研究发现直至2009年4月,美国次债危机的影响才基本消退。分析表明历年巨额的财政支出和较差的经济自愈能力是欧洲主权债务危机发生的主要原因。     

考虑风险总关联的项目风险应对策略选择方法

本文针对考虑风险总关联的项目风险应对策略选择问题,首先结合MACBETH方法以及DEMATEL方法分析项目风险总关联;然后,在考虑项目管理者风险态度的基础上,以最大化项目管理者期望效用为目标构建考虑风险总关联的项目风险应对策略选择优化模型;最后,通过实际案例分析验证所提方法和模型的可行性与有效性,并比较分析了不同关联作用对风险应对决策的影响。结果表明：1）存在使项目管理者期望效用达到最大的最优项目风险应对预算;2）项目管理者的风险态度和对风险关联的关注程度对风险应对策略的选择和项目管理者的期望效用均有影响,在实际项目风险应对决策中均应予以考虑;3）在项目风险应对策略选择过程中,项目管理者不仅要考虑风险之间的直接关联还要重视风险之间的间接关联,而风险之间的积极关联则可以忽略。     

On “Black Swans” and “Perfect Storms”: Risk Analysis and Management When Statistics Are Not Enough

Two images, “black swans” and “perfect storms,” have struck the public's imagination and are used—at times indiscriminately—to describe the unthinkable or the extremely unlikely. These metaphors have been used as excuses to wait for an accident to happen before taking risk management measures, both in industry and government. These two images represent two distinct types of uncertainties (epistemic and aleatory). Existing statistics are often insufficient to support risk management because the sample may be too small and the system may have changed. Rationality as defined by the von Neumann axioms leads to a combination of both types of uncertainties into a single probability measure—Bayesian probability—and accounts only for risk aversion. Yet, the decisionmaker may also want to be ambiguity averse. This article presents an engineering risk analysis perspective on the problem, using all available information in support of proactive risk management decisions and considering both types of uncertainty. These measures involve monitoring of signals, precursors, and near‐misses, as well as reinforcement of the system and a thoughtful response strategy. It also involves careful examination of organizational factors such as the incentive system, which shape human performance and affect the risk of errors. In all cases, including rare events, risk quantification does not allow “prediction” of accidents and catastrophes. Instead, it is meant to support effective risk management rather than simply reacting to the latest events and headlines.     

新时代防控金融风险跨市场交叉网络传染机制研究

文章基于习近平新时代中国特色社会主义金融思想与大数据时代背景,探讨了防控金融风险跨市场交叉网络传染机制。通过模型的理论推演及数值仿真模拟分析,研究结果表明：防控金融风险跨市场交叉传染主要取决于R₀,其值越大,金融风险跨市场交叉传染越容易形成蔓延趋势;金融风险在各个金融子市场之间交叉传染蔓延趋势主要取决于β、δ、α、μ、γ等因素;仅采取事前防御措施或事后防控化解的金融风险防范措施都将缺乏效率,应从事前防御与事后化解两个层面统筹采取金融风险防范措施以提升防范金融风险跨市场交叉传染能力;在此基础上从三个层面提出了防控金融风险跨市场交叉网络传染机制,为构建金融风险救助机制预案以阻隔金融风险在各个金融子市场之间进一步交叉传染蔓延,实现新时代增强金融风险跨市场交叉传染防范与控制能力,更好的防范与化解系统性金融风险以助力打好防范化解重大风险攻坚战、维护国家金融安全的目标提供一定的借鉴与参考。     

中国股市与国际股市的极值风险传导效应研究

本文针对股市中具有的部分典型事实构造股市指数损失的标准残差序列,并运用EVT对其极值尾部建模进而估计出股市指数的动态极值风险,然后基于Granger-Causality检验方法分析中国股市与国际上主要股市之间的极值风险传导效应。结果表明,在过去相当长时间内,中国大陆沪市与其它三个国际股市不存在风险传导效应而处于分割状态,但自2007年起,中国大陆沪市可以通过香港市场与其它国际股市进行极值风险传导;日本东京股市极值风险单向传导给香港股市,香港股市又单向传导给美国纽约股市;日本东京股市和美国纽约股市的极值风险存在明显的双向传导关系。     

Overcoming institutional voids as a pathway to becoming ambidextrous: The case of China's Sichuan Telecom

The paper examines how firms develop supply chain financing model to help overcome institutional voids (IVs) and become ambidextrous. This study presents a case analysis of a novel supply chain financing model instigated and implemented by China's Sichuan Telecom (ST) to help supply chain partners overcome IVs in their environments. We identified three unique stages in the evolution of the supply chain ambidextrous financing model: drivers for change (including identifying suppliers' problems and constraints), designing and implementing the supply chain ambidextrous financing model, and the tripartite performance effects. The analysis demonstrated how ST utilized its market power, resources and network ties to harness expertise and competences of small and medium-sized enterprises (SMEs) to overcome IVs and become ambidextrous. Sichuan Telecom aided the SMEs in solving the financing problem through order-based supply chain financing. Based on the analysis, we outline implications of this case for theory and policy.     

Estimating Benchmark Exposure for Air Particulate Matter Using Latent Class Models

We performed benchmark exposure (BME) calculations for particulate matter when multiple dichotomous outcome variables are involved using latent class modeling techniques and generated separate results for both the extra risk and additional risk. The use of latent class models in this study is advantageous because it combined several outcomes into just two classes (namely, a high‐risk class and a low‐risk class) and compared these two classes to obtain the BME levels. This novel approach addresses a key problem in risk estimation—namely, the multiple comparisons problem, where separate regression models are fitted for each outcome variable and the reference exposure will rely on the results of the best‐fitting model. Because of the complex nature of the estimation process, the bootstrap approach was used to estimate the reference exposure level, thereby reducing uncertainty in the obtained values. The methodology developed in this article was applied to environmental data by identifying unmeasured class membership (e.g., morbidity vs. no morbidity class) among infants in utero using observed characteristics that included low birth weight, preterm birth, and small for gestational age.