Emotions,Trust, and Perceived Risk: Affective and Cognitive Routes to Flood Preparedness Behavior

Despite the prognoses of the effects of global warming (e.g., rising sea levels, increasing river discharges), few international studies have addressed how flood preparedness should be stimulated among private citizens. This article aims to predict Dutch citizens’ flood preparedness intentions by testing a path model, including previous flood hazard experiences, trust in public flood protection, and flood risk perceptions (both affective and cognitive components). Data were collected through questionnaire surveys in two coastal communities (n= 169, n= 244) and in one river area community (n= 658). Causal relations were tested by means of structural equation modeling (SEM). Overall, the results indicate that both cognitive and affective mechanisms influence citizens’ preparedness intentions. First, a higher level of trust reduces citizens’ perceptions of flood likelihood, which in turn hampers their flood preparedness intentions (cognitive route). Second, trust also lessens the amount of dread evoked by flood risk, which in turn impedes flood preparedness intentions (affective route). Moreover, the affective route showed that levels of dread were especially influenced by citizens’ negative and positive emotions related to their previous flood hazard experiences. Negative emotions most often reflected fear and powerlessness, while positive emotions most frequently reflected feelings of solidarity. The results are consistent with the affect heuristic and the historical context of Dutch flood risk management. The great challenge for flood risk management is the accommodation of both cognitive and affective mechanisms in risk communications, especially when most people lack an emotional basis stemming from previous flood hazard events.     

消费者对转基因食品感知风险影响因素分析

采用西安市区消费者的调研数据,分析消费者对转基因食品感知风险的认知程度,并利用结构方程模型研究了影响感知风险的主要因素。结果表明:不同人口特征在转基因食品感知风险上存在显著差异,消费者对转基因技术的态度、转基因食品知识、社会信任与感知风险呈显著负向关系,对健康的关心与感知风险呈显著正向关系。最后根据研究结果,提出政策建议。     

基因编辑的刑法规制 ——兼论非法植入基因编辑、克隆胚胎罪中的“情节严重”

CRISPR-Cas9基因编辑技术的主要特点在于操作简便、准确性高以及可遗传等,该技术在造福人类的同时也催生了基因编辑的风险。按照基因编辑的目的,可将基因编辑分为治疗型、预防型和增效型三种。增效型基因编辑以及将人类胚胎植入动物体内或将动物胚胎植入人体内的行为,严重违背医学伦理且造成人类毁灭危险,应属于刑法非法植入基因编辑、克隆胚胎罪中的情节严重。其他基因编辑行为也应视情况构成毁坏财物罪、侵犯公民个人信息罪、盗窃罪等。此外,为实现罪责刑相适应,需在相关行政法规中制定明确的技术标准,出现重伤或死亡结果时,根据行为人主观罪过视情况认定为非法植入基因编辑、克隆胚胎罪,故意伤害致人死亡或故意杀人罪。     

对中国电力企业全面风险管理的认识

本文通过对企业风险、企业全面风险管理的阐述,企业风险因素与企业组织结构管理之间的关联性的描述,以及企业风险管理部门与企业内其他部门的关系介绍,指出当前电力企业的风险管理意识暂时停留在危机管理的意识状态上,提出变革时期的电力行业,影响企业战略制定最主要的风险因素是来自于企业外部的政策、环境风险。     

影子银行、地方政府债务及金融发展动态关系研究——基于省级面板VAR模型

基于2004—2017年中国省级面板数据,运用面板向量自回归(PVAR)模型,使用系统GMM估计、脉冲响应函数、方差分解以及格兰杰因果关系检验等方法分析了影子银行、地方政府债务及金融发展之间的动态关系.结果表明:影子银行、地方政府债务与金融发展水平三者之间存在动态耦合关系.在地方政府融资能力受到约束的情况下,影子银行为地方政府提供了多元的融资方式,在增加政府融资能力的同时提升了政府债务水平;而地方政府债务需求显著推动了影子银行规模的快速发展.同时,影子银行过度扩张危害了金融市场的健康发展,降低金融发展水平,继而使地方政府的融资渠道受到约束.但金融发展并不能有效约束影子银行规模,原因在于,政府融资需求是影子银行的主要动力,若不能控制地方政府的借贷行为则无法从源头解决问题.监管机构在去杠杆的过程中,应该综合考虑影子银行与地方政府债务、金融发展之间的动态关系,如此才能够实现预期的政策效果.     

基于Markov区制转换模型的极值风险度量研究

将马尔科夫区制转换模型与极值理论相结合研究金融风险度量问题.首先用SWARCH-t模型捕捉收益率序列的剧烈波动和结构变换特征,然后将收益序列转化为标准残差序列,在此基础上通过SWARCH-t模型与极值理论相结合拟合标准残差的尾部分布,进而构建基于SWARCH- t- EVT的动态VaR模型,最后对模型的有效性进行检验.研究表明,SWARCH-t-EVT模型能够有效识别上证综指的波动区制特征,且能有效合理地测度上证综指收益风险,尤其在高的置信水平下表现更好.     

Integrating Family Resilience and Family Stress Theory

The construct, family resilience, has been defined and applied very differently by those who are primarily clinical practitioners and those who are primarily researchers in the family field. In thisarticle, the family resilience perspective is integrated with conceptual definitions from family stress theory using the Family Adjustment and Adaptation Response (FAAR) Model in an effort to clarify distinctions between family resiliency as capacity and family resilience as a process. The family resilience process is discussed in terms of (a) the meaning of significant risk exposure (vs. the normal challenges of family life) and (b) the importance of making conceptual and operational distinctions between family system outcomes and family protective processes. Recommendations for future family resilience research are discussed.     

Intertemporal choice under timing risk: An experimental approach

This paper investigates how individuals evaluate delayed outcomes with risky realization times. Under the discounted expected utility (DEU) model, such evaluations depend only on intertemporal preferences. We obtain several testable hypotheses using the DEU model as a benchmark and test these hypotheses in three experiments. In general, our results show that the DEU model is a poor predictor of intertemporal choice behavior under timing risk. We found that individuals are averse to timing risk and that they evaluate timing lotteries in a rank-dependent fashion. The main driver of timing risk aversion is nothing but probabilistic risk aversion that stems from the nonlinear treatment of probabilities.     

我国股票市场的流动性风险溢价研究

我国股票预期回报率中包含显著的非流动性补偿和流动性风险溢价,而且非流动性补偿和流动性风险溢价更为显著地出现在流动性较差或者说价格冲击弹性较高的股票上.由于流动性水平和流动性风险在股票横截面上存在强相关性,使得代理流动性水平的非流动性指标能够抓住流动性风险的溢价效应.经典资本资产定价模型的价格风险敏感度对股票回报率缺乏解释力,意味着股票的风险溢价更多地来自对流动性风险的补偿,而非来自对单纯的价格风险的补偿.     

A Data‐Driven Approach to Assessing Supply Inadequacy Risks Due to Climate‐Induced Shifts in Electricity Demand

The U.S. electric power system is increasingly vulnerable to the adverse impacts of extreme climate events. Supply inadequacy risk can result from climate‐induced shifts in electricity demand and/or damaged physical assets due to hydro‐meteorological hazards and climate change. In this article, we focus on the risks associated with the unanticipated climate‐induced demand shifts and propose a data‐driven approach to identify risk factors that render the electricity sector vulnerable in the face of future climate variability and change. More specifically, we have leveraged advanced supervised learning theory to identify the key predictors of climate‐sensitive demand in the residential, commercial, and industrial sectors. Our analysis indicates that variations in mean dew point temperature is the common major risk factor across all the three sectors. We have also conducted a statistical sensitivity analysis to assess the variability in the projected demand as a function of the key climate risk factor. We then propose the use of scenario‐based heat maps as a tool to communicate the inadequacy risks to stakeholders and decisionmakers. While we use the state of Ohio as a case study, our proposed approach is equally applicable to all other states.