Confronting Deep Uncertainties in Risk Analysis

How can risk analysts help to improve policy and decision making when the correct probabilistic relation between alternative acts and their probable consequences is unknown? This practical challenge of risk management with model uncertainty arises in problems from preparing for climate change to managing emerging diseases to operating complex and hazardous facilities safely. We review constructive methods for robust and adaptive risk analysis under deep uncertainty. These methods are not yet as familiar to many risk analysts as older statistical and model‐based methods, such as the paradigm of identifying a single “best‐fitting” model and performing sensitivity analyses for its conclusions. They provide genuine breakthroughs for improving predictions and decisions when the correct model is highly uncertain. We demonstrate their potential by summarizing a variety of practical risk management applications.     

Modeling Uncertainties in Mining Pillar Stability Analysis

Many countries are now facing problems related to their past mining activities. One of the greatest problems concerns the potential surface instability. In areas where a room-and-pillar extraction method was used, deterministic methodologies are generally used to assess the hazard of surface collapses. However, those methodologies suffer from not being able to take into account all the uncertainties inherent in any hazard analysis. Through the practical example of the assessment of a single pillar stability in a very simple mining layout, this article introduces a logical framework that can be used to incorporate the different kinds of uncertainties related to data and models, as well as to specific expert's choices in the hazard or risk analysis process. Practical recommendations and efficient tools are also provided to help engineers and experts in their daily work.     

Analysis of Uncertainties in Interactive Probabilistic Safety Analysis (PSA) Models

Probabilistic safety analysis (PSA) has been used in nuclear, chemical, petrochemical, and several other industries. The probability and/or frequency results of most PSAs are based on average component unavailabilities during the mission of interest. While these average results are useful, they provide no indication of the significance of the facility's current status when one or more components are known to be out of service. Recently, several interactive computational models have been developed for nuclear power plants to allow the user to specify the plant's status at a particular time (i.e., to specify equipment known to be out of service) and then to receive updated PSA information. As with conventional PSA results, there are uncertainties associated with the numerical updated results. These uncertainties stem from a number of sources, including parameter uncertainty (uncertainty in equipment failure rates and human error probabilities). This paper presents an analysis of the impact of parameter uncertainty on updated PSA results.     

An Analysis of the Uncertainties in Estimates of Radon-Induced Lung Cancer

A recent report by the National Academy of Sciences estimates that the radiation dose to the bronchial epithelium, per working level month (WLM) of radon daughter exposure, is about 30% lower for residential exposures than for exposures received in underground mines. Adjusting the previously published BEIR IV radon risk model accordingly, the unit risk for indoor exposures of the general population is about 2.2 x 10(-4) lung cancer deaths (lcd)/WLM. Using results from EPA's National Residential Radon Survey, the average radon level is estimated to be about 1.25 pCi/L, and the annual average exposure about 0.242 WLM. Based on these estimates, 13,600 radon-induced lcd/yr are projected for the United States. A quantitative uncertainty analysis was performed, which considers: statistical uncertainties in the epidemiological studies of radon-exposed miners; the dependence of risk on age at, and time since, exposure; the extrapolation of risk estimates from mines to homes based on comparative dosimetry; and uncertainties in the radon daughter levels in homes and in the average residential occupancy. Based on this assessment of the uncertainties in the unit risk and exposure estimates, an uncertainty range of 7000-30000 lcd/yr is derived.     

Uncertainties in Nuclear Probabilistic Risk Analyses

There are many uncertainties in a probabilistic risk analysis (PRA). We identify the different types of uncertainties and describe their implications. We then summarize the uncertainty analyses which have performed in current PRAs and characterize results which have been obtained. We draw conclusions regarding interpretations of uncertainties, areas having largest uncertainties, and needs which exist in uncertainty analysis. We finally characterize the robustness of various utilizations of PRA results.     

Comparative Risk and Policy Analysis in Environmental Health

There is increasing interest in the integration of quantitative risk analysis with benefit-cost and cost-effectiveness methods to evaluate environmental health policy making and perform comparative analyses. However, the combined use of these methods has revealed deficiencies in the available methods, and the lack of useful analytical frameworks currently constrains the utility of comparative risk and policy analyses. A principal issue in integrating risk and economic analysis is the lack of common performance metrics, particularly when conducting comparative analyses of regulations with disparate health endpoints (e.g., cancer and noncancer effects or risk-benefit analysis) and quantitative estimation of cumulative risk, whether from exposure to single agents with multiple health impacts or from exposure to mixtures. We propose a general quantitative framework and examine assumptions required for performing analyses of health risks and policies. We review existing and proposed risk and health-impact metrics for evaluating policies designed to protect public health from environmental exposures, and identify their strengths and weaknesses with respect to their use in a general comparative risk and policy analysis framework. Case studies are presented to demonstrate applications of this framework with risk-benefit and air pollution risk analyses. Through this analysis, we hope to generate discussions regarding the data requirements, analytical approaches, and assumptions required for general models to be used in comparative risk and policy analysis.     

价格与技术不确定条件下的发电商碳捕获投资模型及分析

碳捕获与储存技术是降低碳排放的有效方法之一。论文针对碳价和碳捕获技术不确定的情况,构建双重不确定条件下的碳捕获技术投资模型,并在模型求解基础上进行了数值仿真分析,其分析结果表明:1)碳价的波动性将延迟碳捕获技术投资,若碳价的波动性足够大,发电商会选择不投资;2)碳捕获技术进步也将延迟投资,但政策性补贴将抵消该投资延迟。     

Analysis of the Market‐Based Adjustable Outsourcing Contract under Uncertainties

The market‐based adjustable contract for customized goods or services has emerged in outsourcing practices. Its objective is to minimize the operational risks inherent in today's volatile environment of operations. Our research reveals several important properties of this contract through a continuous‐time analytical approach. Specifically, we consider the determination of this contract between two risk‐averse firms through a Nash bargaining process. We derive the optimal adjusting mechanism analytically and extensively analyze the application boundary of the market‐based adjustable outsourcing contract. We conclude by discussing implications for practice and research.     

Modeling Uncertainties in Workforce Disruptions from Influenza Pandemics Using Dynamic Input‐Output Analysis

Influenza pandemic is a serious disaster that can pose significant disruptions to the workforce and associated economic sectors. This article examines the impact of influenza pandemic on workforce availability within an interdependent set of economic sectors. We introduce a simulation model based on the dynamic input‐output model to capture the propagation of pandemic consequences through the National Capital Region (NCR). The analysis conducted in this article is based on the 2009 H1N1 pandemic data. Two metrics were used to assess the impacts of the influenza pandemic on the economic sectors: (i) inoperability, which measures the percentage gap between the as‐planned output and the actual output of a sector, and (ii) economic loss, which quantifies the associated monetary value of the degraded output. The inoperability and economic loss metrics generate two different rankings of the critical economic sectors. Results show that most of the critical sectors in terms of inoperability are sectors that are related to hospitals and health‐care providers. On the other hand, most of the sectors that are critically ranked in terms of economic loss are sectors with significant total production outputs in the NCR such as federal government agencies. Therefore, policy recommendations relating to potential mitigation and recovery strategies should take into account the balance between the inoperability and economic loss metrics.     

日本环境政策分析

日本在环境保护方面是一个富有特色的国家,它曾创造了经济的奇迹,又在短时期内摆脱了"公害大国"的形象,并长期保持环境保护和经济发展"双赢"的局面,可以说也创造了环境保护的"奇迹".从日本环境政策的调整过程入手,简要分析了其主要内容以及各种管理手段等.     

Jordan's Public Policy Response to COVID-19 Pandemic: Insight and Policy Analysis

The aim of this study was to gain an understanding of how the Jordanian government has responded and continues to respond to the COVID-19 pandemic. It utilizes the interpretive policy analysis approach through document analysis. The analysis showed that Jordan created social protection policies to assist people who lost their jobs or whose work was suspended due to the coronavirus. The economic policies build solidarity and facilitate the private sector’s recovery. The health care measures firmly applied included lockdown, wearing masks, and restrictions on gatherings and public events. Jordan uses hard power and imposes sanctions on any violation that threatens the lives of others.

     

采购价格柔性策略与供应链利润风险分析

面对原材料市场价格的大幅波动,供应链节点企业需要采用相应策略来规避价格波动带来的风险。本文通过设计价格柔性合同,分析供应链企业通过采购价格柔性策略来缓解采购价格波动给企业利润带来的风险。采用Stackelberg主从博弈模型研究得出了制造商的最优采购数量和供应商的最优价格柔性系数,并分别分析了各最优结果随采购价格柔性合同参数的变化趋势。利用供应链各主体的利润方差度量各自承担的利润风险,分析了供应商和制造商的利润风险随采购价格柔性合同参数的变化规律。     

The Science of Policy Analysis in a Political and Ethical Perspective

Public Organization Review -     

中国宏观经济政策的效果分析

在当前中国的经济发展中,由于住房、医疗、教育等领域的改革和资金净流入的大量增加,存在着两个显著的变化,即货币需求的大幅增加和国际收支中资本项目的大量盈余,而这两个变化同时对我国财政政策和货币政策的实施产生了较大的影响,基于这两个变化,通过对IS－LM模型的修正,对我国当前宏观经济政策的效果进行分析。     

Modeling Correlated Discrete Uncertainties in Event Trees with Copulas

Modeling the dependence between uncertainties in decision and risk analyses is an important part of the problem structuring process. We focus on situations where correlated uncertainties are discrete, and extend the concept of the copula‐based approach for modeling correlated continuous uncertainties to the representation of correlated discrete uncertainties. This approach reduces the required number of probability assessments significantly compared to approaches requiring direct estimates of conditional probabilities. It also allows the use of multiple dependence measures, including product moment correlation, rank order correlation and tail dependence, and parametric families of copulas such as normal copulas, t‐copulas, and Archimedean copulas. This approach can be extended to model the dependence between discrete and continuous uncertainties in the same event tree.     

分段的延期支付条件下临时订货策略分析

商业活动中供应商时常会给采购商短期的价格折扣,目的是使采购商进行临时的大量采购;供应商为了鼓励采购商订货,会针对采购规模给予其不同的延期支付期限;而当价格恢复到定常时,延期支付的期限则为供求双方事先规定的常值,采购商按照允许延期支付的EOQ模型订货。将延期支付基本EOQ模型中存在的门槛式延期支付规则(只有当采购量大于特定值才可以延期支付货款)应用并推广到这种临时采购中:延期支付期限是临时采购量的分段函数。由于采购商可以采取按低价追加订货或者放弃这个机会,基于这2种策略年度成本差异最大化,分析了采购商最优的追加订货批量如何确定的问题,拓宽了允许延期支付的EOQ模型应用范围。     

规则性与相机选择性货币政策的作用机制分析

使用狭义货币存量(增长率)和银行同业拆借利率等作为货币政策的状态指标,能够分析货币政策可预期(不可预期)扩张性(紧缩性)冲击对实际产出的作用机制,并检验货币政策作用机制的非对称性。实证结果表明,我国货币政策中无论是规则性的可预期冲击,还是相机选择形成的不可预期冲击,都对实际产出的波动形成了显著作用。货币政策在短期内即具有影响价格的名义作用,也存在影响实际产出的实际作用。我国货币政策具有内生性和短期非中性等特征。