Sampling Strategies for Toxic Air Contaminants

Annual concentrations of toxic air contaminants are of primary concern from the perspective of chronic human exposure assessment and risk analysis. Despite recent advances in air quality monitoring technology, resource and technical constraints often impose limitations on the availability of a sufficient number of ambient concentration measurements for performing environmental risk analysis. Therefore, sample size limitations, representativeness of data, and uncertainties in the estimated annual mean concentration must be examined before performing quantitative risk analysis. In this paper, we discuss several factors that need to be considered in designing field-sampling programs for toxic air contaminants and in verifying compliance with environmental regulations. Specifically, we examine the behavior of SO2, TSP, and CO data as surrogates for toxic air contaminants and as examples of point source, area source, and line source-dominated pollutants, respectively, from the standpoint of sampling design. We demonstrate the use of bootstrap resampling method and normal theory in estimating the annual mean concentration and its 95% confidence bounds from limited sampling data, and illustrate the application of operating characteristic (OC) curves to determine optimum sample size and other sampling strategies. We also outline a statistical procedure, based on a one-sided t-test, that utilizes the sampled concentration data for evaluating whether a sampling site is compliance with relevant ambient guideline concentrations for toxic air contaminants.     

上市公司ESG信息强制性披露：制度优势、法理基础与实现路径

随着ESG投资的兴起,上市公司ESG信息应否强制性披露成为全球主要资本市场的重要议题。ESG信息强制性披露有降低信息成本和提高信息质量的制度优势,但我国选择该模式并将其制度化的法理基础及实现路径还有待探讨。社会系统论视角下风险规制的需要和证券法中信息“重大性”标准的适用可成为ESG信息强制性披露的正当性基础。ESG信息强制性披露制度的构建,可在将重要ESG信息解释为证券法框架下重大信息的基础上,通过证监会制定基本原则、证券交易所设计具体规则形成结构化披露规则体系;宜区分以满足投资者决策需要为中心的ESG理念和以关照利益相关者诉求为核心的公司社会责任理念,分两步建立ESG信息披露框架和标准;充分考虑上市公司合规成本,推行渐进式实现方案。     

Causal inference for recurrent events data with all-or-none compliance

ABSTRACT

In this article, causal inference in randomized studies with recurrent events data and all-or-none compliance is considered. We use the counting process to analyze the recurrent events data and propose a causal proportional intensity model. The maximum likelihood approach is adopted to estimate the parameters of the proposed causal model. To overcome the computational difficulties created by the mixture structure of the problem, we develop an expectation-maximization (EM) algorithm. The resulting estimators are shown to be consistent and asymptotically normal. We further estimate the complier average causal effect (CACE), which is defined as the difference of the average numbers of recurrence between treatment and control groups within the complier class. The corresponding inferential procedures are established. Some simulation studies are conducted to assess the finite sample performance of the proposed approach.     

A meta-analysis of the pique technique of compliance

A random-effects meta-analysis was undertaken to examine the effectiveness of the pique technique of compliance-gaining. Results indicated an overall significant effect of the pique technique on increased compliance rate across 17 comparisons (r = .27). Moderator analyses showed the technique worked significantly better than controls in gaining compliance when a smaller amount was requested, when the reason for the request was included, and when the technique was used in France. In addition, the pique technique was more successful than control requests in terms of the total amount of money or time given by participants and the percentage of participants inquiring about the requests. Theoretical and practical implications for the success of pique technique are discussed for future research.     

Reciprocal relationships in tax compliance decisions

Reciprocity considerations are important to the tax compliance problem as they may explain the global dynamics of tax evasion, beyond individual tax evasion decisions, toward a downward or upward spiral. To provide evidence on reciprocity in tax compliance decisions, we have conducted a laboratory experiment in which we introduced two types of inequities. The first type of inequity is called vertical, because it refers to inequities introduced by the government when it sets different fiscal parameters for identical taxpayers, while the second type of inequity is called horizontal because it refers to the fact that taxpayers may differ in tax compliance decisions. In this setting, taxpayers may react to a disadvantageous or advantageous inequity through negative or positive reciprocal behaviors, respectively. Our results support the existence of negative and positive reciprocity in both vertical and horizontal cases. When both inequities come into play and may induce reciprocal behaviors in opposite directions, the horizontal always dominates the vertical.     

The surprising effectiveness of earliest operation due-date sequencing

In make-to order production, schedule reliability is very important but still not sufficiently accomplished in industrial practice by the vast majority of companies. It has been known for long that processing the orders at a workstation in the order of their operation due-dates can compensate for lateness in the arrival at the workstation within certain boundaries. The paper analyses the effectiveness of earliest operation due date (EODD) sequencing by comparing it to an optimistic theoretical boundary. The surprising result is that EODD can nearly fully exploit the theoretical potential. It should therefore be used in practice whenever schedule reliability is important, with only few exceptions. Its effectiveness though is increasing with the workstation’s WIP level and thus is in conflict with the objective to reduce WIP levels and throughput times. A simple forecasting model allows to assess the extent to which lateness can be compensated by EODD sequencing and which schedule compliance can be achieved.     

流程、合规与操作风险管理

商业银行风险管理研究中“违规活动—操作风险—信用风险”风险链条尚未得到足够重视． 巴塞尔委员会全面风险管理框架下的众多风险是分层次的,最底层是合规与操作风险,合规与操作风险做到位能极大降低其他风险发生的概率． 以往由于缺少数据支撑,信用风险的合规与操作风险动因无法建立,本文基于“流程—节点—风险点—控制措施—违规事件”关联模型,建立了合规与操作风险的动因库和损失数据库,并在理论上对风险链条上的风险传递关系进行初步探索． 首先基于流程对合规与操作风险动因进行解析,寻找深层次的人员违规和操作风险动因; 其次,探讨了金融机构如何通过业务流程再造改善合规与操作风险管理; 最后是基于流程的操作风险量化建模． 基于实践,总结提炼了“三位一体”的金融机构合规与操作风险管理模式,包含理论基础、信息系统和保障机制,该模式在诸多金融机构中得到运用,并取得显著成效．     

企业会计准则强制实施制度效率的二元分析

将会计准则强制实施制度与会计准则执行行为直接联结,以期望效用理论和前景理论为指导,从会计准则强制实施制度对企业会计准则执行效用和遵从心理影响两个角度,分析强制实施制度威慑风险下企业会计准则的执行决策,剖析强制实施制度的作用机理和局限性;采用比较分析和调查研究方法分析了我国强制实施制度低效率的原因。最后,提出完善我国企业会计准则强制实施机制的建议。