Air Pollution Materials Damage: Economics and the Law

Recent concerns about the adverse effects of acid rain have increased the attention given to materials damage effects from air pollution. This article surveys the economics of valuing materials damage effects and relates these methods to the technical aspects of estimating actual damages. The current statutory and regulatory framework within which materials damage effects are considered is also reviewed. The key weaknesses of the relevant sections of the Clean Air Act, in terms of effectively using economic and technical information on materials damage, are identified. The article concludes with several general observations concerning the regulation of materials damage effects.     

Dealing with noncompliance and missing outcomes in a randomized trial using Bayesian technology: Prevention of perinatal sepsis clinical trial,Soweto, South Africa

The success of interventions designed to address important issues in social and medical science is best addressed by randomized experiments. With human beings there are often complications, however, such as noncompliance and missing data. Such complications are often addressed by statistically invalid methods of analysis, in particular, intention-to-treat and per-protocol analyses. Here we address these two complications using a statistically valid approach based on principal stratification with a fully Bayesian analysis. This analysis is applied to a randomized trial of a potentially important intervention designed to reduce the transmission of bacterial colonization between mothers and their infants through vaginal delivery in South Africa: the Prevention of Perinatal Sepsis (PoPs).     

The randomized concentration-controlled trial:mathematical definitions,a dose-adjusting algorithm,and sample size efficiency

A randomized concentration-controlled trial (RCCT) (Peck 1990) is distinguished from a randomized dose-controlled trial (RDCT) by controlling the plasma concentration and allowing the dose to vary, as opposed to controlling the dose and allowing the concentration to vary. Monte Carlo studies have suggested that the RCCT is more efficient (in terms of sample size) than the more traditional dose-controlled trials. This paper presents a general mathematical defminition and investigates the properties of an RCCT. A Bayesian adjustment algorithm used in an RCCT is presented and discussed. Expressions for the sample-size efficiency of the RCCT relative to the RDCT is found for both Gaussian and Bernoulli efficacy variables. The RCCT is found to be at least as efficient in terms of sample size. The RCCT can be considerably more efficient than the RDCT.     

Ecological Community Structure Analyses in the Formulation,Implementation, and Enforcement of Law and Policy

Most of what is currently known about ecosystems derives from two sources: comprehensive studies by classical ecologists and economically motivated studies by resource specialists. The former have traditionally concentrated on natural or long-undisturbed ecosystems, the latter on those few species in managed or polluted ecosystems that are harvested, hunted, or fished. A recent genre of legislation, drafted with insight provided by the scientific community, recognizes the dearth of ecological information on managed or polluted communities (which are becoming far more ubiquitous and important) and dramatically raises the requirements for comprehensive data and data analyses to guide managerial and pollution abatement policies. This paper describes several important current efforts to use ecological community structure analyses to implement and enforce such legislation and some effects of such analyses on environmental policy.     

就业结构、文化教育和城市规模对城镇化质量的影响——基于中国十大城市群的经验分析

中国十大城市群目前正在成为中国经济、科技、文化最发达地区和国民经济的重要支撑点,城镇化质量问题一直是国家高度重视的一个问题,而就业结构、文化教育和城市规模又将对城镇化质量产生一定影响。基于1993—2012年中国十大城市群面板数据,选取城镇化质量为因变量、第三产业产值等为自变量构建面板数据模型,通过回归分析得出固定效应模型,结果表明:自变量大部分对城镇化质量起着正向的作用,因此有必要制定一系列相关政策,全面提高城镇化的质量。     

Assessing the treatment effect in a randomized controlled trial with extensive non‐adherence: the EVOLVE trial

Intention‐to‐treat (ITT) analysis is widely used to establish efficacy in randomized clinical trials. However, in a long‐term outcomes study where non‐adherence to study drug is substantial, the on‐treatment effect of the study drug may be underestimated using the ITT analysis. The analyses presented herein are from the EVOLVE trial, a double‐blind, placebo‐controlled, event‐driven cardiovascular outcomes study conducted to assess whether a treatment regimen including cinacalcet compared with placebo in addition to other conventional therapies reduces the risk of mortality and major cardiovascular events in patients receiving hemodialysis with secondary hyperparathyroidism. Pre‐specified sensitivity analyses were performed to assess the impact of non‐adherence on the estimated effect of cinacalcet. These analyses included lag‐censoring, inverse probability of censoring weights (IPCW), rank preserving structural failure time model (RPSFTM) and iterative parameter estimation (IPE). The relative hazard (cinacalcet versus placebo) of mortality and major cardiovascular events was 0.93 (95% confidence interval 0.85, 1.02) using the ITT analysis; 0.85 (0.76, 0.95) using lag‐censoring analysis; 0.81 (0.70, 0.92) using IPCW; 0.85 (0.66, 1.04) using RPSFTM and 0.85 (0.75, 0.96) using IPE. These analyses, while not providing definitive evidence, suggest that the intervention may have an effect while subjects are receiving treatment. The ITT method remains the established method to evaluate efficacy of a new treatment; however, additional analyses should be considered to assess the on‐treatment effect when substantial non‐adherence to study drug is expected or observed. Copyright © 2015 John Wiley & Sons, Ltd.     

高管团队风险偏好、失败再创新行为与再创新绩效——基于我国医药制造业上市企业的实证研究

本文以2011—2019年我国医药制造业上市企业为样本,考察了高管团队风险偏好、失败再创新行为与再创新绩效间的关系。研究表明,高管团队风险偏好正向影响失败后技术开发阶段再创新绩效,但负向影响失败后成果转化阶段再创新绩效。失败后全新创新在高管团队风险偏好与失败后两阶段再创新绩效间皆存在中介作用,而失败后追加创新未见中介作用。同时,高管团队风险偏好对失败后两阶段再创新绩效的影响较对成功后两阶段再创新绩效更显著,且失败后全新创新较成功后全新创新的中介作用更显著。本文旨在为企业构建合理的高管团队、改善其失败再创新行为、提高再创新绩 效提供理论依据和决策借鉴。     

金砖国家经济增长源泉的异质性及强度研究——基于互联网、金融发展和法治水平的视角

国家的异质性导致了各国经济增长源泉具有较强的差异性。运用2003年至2013年金砖国家经济发展数据,构建面板数据门槛回归模型,研究互联网、金融发展及法治水平对金砖国家经济增长的影响。实证结果表明:互联网对金砖国家经济增长促进作用并不显著,现阶段金融发展对经济增长推动作用有限。但随着法治水平的提高,金融发展对经济增长的推动作用呈J字型增长,法治水平的提高有利于推动金砖国家金融发展。加强互联网、金融及法治建设将为金砖国家经济增长注入新的动力。     

应对入世挑战 推进依法统计

一、进一步确立依法统计的观念统计部门应对入世挑战 ,首先应当更新思想观念。而牢固确立依法行政、依法统计的观念 ,实现统计工作的组织管理由以行政手段为主向以法制手段为主的转变 ,具有全局意义和战略意义。世界贸易组织的最大特点之一 ,就是为各成员制定各自的国际贸易政策提供了一套法律框架 ,即ＷＴＯ规则 ,被称为“国际行政法典”。由于国际贸易壁垒都由政府设立 ,ＷＴＯ协议及其所有规则首先都是针对政府的 ,ＷＴＯ协议规范了每一个成员方政府对国际贸易的管理 ,几乎影响到成员方行政管理的各个层面。因此 ,入世 ,首先是政府的入世…     

从成交量统计看大势的变化(下)--市场顶部的确认

在上期文章中我们从成交量的缩量中找到了市场底部确认的一个重要指标。通过对股票市场的统计分析，我们同样发现成交量的变化直接标示着市场顶部的来临。 对整个市场而言，成交量的变化更直接地反映了市场顶部的特征。在上一期的文章中，我们已经谈到：市场底部的确认要有两次缩量的过程，即缩量——小幅放量——再缩量，盘整并且确认底部；然后是成交量迅速放大，市场快速脱离底部，进入一个上升通道；其间尽管有调整，但是成交量不会有明显的放大，维持在一个上升的大趋势之中；然后市场会进入一个疯涨的时期，此时成交量会再次明显的…     

中国十大城市群城市流强度的比较分析

运用城市流强度定量分析方法,对中国十大城市群99座城市的外向型功能量、城市流强度和城市流倾向度进行计算,并汇总求出各城市群的上述指标,进而对城市群间城市流强度、各城市群核心城市及各城市群内部城市的城市流强度相关指标进行分析,分析结果显示：城市群问外向型功能量和城市流强度存在巨大差距,并存在从东南沿海到西部地区逐渐减小的态势,京津唐、长三角、珠三角为三大高城市流强度的辐射中心;东部地区城市群从业人员中为城市区域以外的地区服务的人员比例普遍较低,其中长三角最低仅为11％;核心城市的外向型功能量和城市流强度变化趋势与城市群一致,对城市群影响巨大,北京、深圳和上海三座城市综合实力和外向型服务能力最强,北京服务型产业在全国也有着超强的辐射功能;城市群内城市的城市流强度差巨大,核心城市的总体实力、城市流强度均较高,但元一例外的其GDP’i值大于其K’i,表明进一步提升其综合服务能力十分必要,非核心城市则更应着眼于综合实力的提升。     

Testing Wagner's Law in India: A cointegration and causality analysis

The present study empirically analyzes the validity of Wagner's Law for Indian economy. With the use of annual time series data from 1970–71 to 2013–14, all the six versions of Wagner's Law have been analyzed to test the relationship between government expenditure and gross domestic product. Wagner's Law states that the economic growth is the causative factor of the growth of the public expenditure. The study applied the unit root test and cointegration test to find the long-run relationship between government expenditure and gross domestic product. The present study employed the various econometric techniques such as unit root test, cointegration, and causality analysis for empirical analysis. The empirical analysis under study inferred mixed results of Wagner's Law for Indian economy, where four versions, namely Peacock, Gupta, Guffman, and Musgrave, found valid for Indian economy. The study concluded that the Wagner's Law is valid for the Indian economy except the Pryor and Mann Versions of the Wagner's Law.     

Pearl'S Law and the Growth of the Scottish National Party

An examination of the percentage of the total Soottish poll gained by the SNP at general elections between 1951 and 1974 inclusive suggested that a stable, sigmoidal growth process might be identified if elections were regarded as occurring at unit intervals in time. The resulting time service was extremely well-fitted by Pearl's Law, a theoretical growth curve possessing a signoidal trend, and a theoretical upper limit to growth. On the basis of this model, estimated of, and confidence intervals for, both this theoretical upper limit, and of the party's performance in the next general election were obtained.     

Sample size and the probability of a successful trial

This paper describes the distinction between the concept of statistical power and the probability of getting a successful trial. While one can choose a very high statistical power to detect a certain treatment effect, the high statistical power does not necessarily translate to a high success probability if the treatment effect to detect is based on the perceived ability of the drug candidate. The crucial factor hinges on our knowledge of the drug's ability to deliver the effect used to power the study. The paper discusses a framework to calculate the 'average success probability' and demonstrates how uncertainty about the treatment effect could affect the average success probability for a confirmatory trial. It complements an earlier work by O'Hagan et al. (Pharmaceutical Statistics 2005; 4:187-201) published in this journal. Computer codes to calculate the average success probability are included.     

PREDICT-1 (CNA106030): the first powered, prospective trial of pharmacogenetic screening to reduce drug adverse events

Pharmacogenetics (PGx) – the study of DNA variation in the human genome and the way this impacts the efficacy and safety of medicines – is becoming an increasingly important research tool as physicians, patients, regulatory authorities and payers look for innovative ways to improve the risk:benefit ratio of medicines. While scientific knowledge about PGx is rapidly increasing, implementation of PGx findings to patient care has yet to be fully achieved. One area where significant progress has been made is in the identification of PGx markers associated with variable response to antiretroviral medicines. For example, the major histocompatibility complex HLA‐B*5701 allele has been associated with hypersensitivity to abacavir (ABC) by several independent researchers. While PGx associations have been identified largely through retrospective examination, the clinical utility of these PGx markers in patient care has not been prospectively determined in a randomized study. This paper outlines the design of a study to evaluate the utility of prospective screening for HLA‐B*5701 to reduce the incidence of ABC hypersensitivity in an ABC‐naïve population of HIV‐infected subjects. This represents the first fully powered, randomized, blinded, prospective study to determine the clinical utility of PGx screening to reduce drug‐associated adverse events in any patient population. This type of trial design may have utility for other important medicines which have treatment‐limiting side effects. Copyright © 2007 John Wiley & Sons, Ltd.     

Optimizing trial design in pharmacogenetics research: comparing a fixed parallel group,group sequential,and adaptive selection design on sample size requirements

Two‐stage clinical trial designs may be efficient in pharmacogenetics research when there is some but inconclusive evidence of effect modification by a genomic marker. Two‐stage designs allow to stop early for efficacy or futility and can offer the additional opportunity to enrich the study population to a specific patient subgroup after an interim analysis. This study compared sample size requirements for fixed parallel group, group sequential, and adaptive selection designs with equal overall power and control of the family‐wise type I error rate. The designs were evaluated across scenarios that defined the effect sizes in the marker positive and marker negative subgroups and the prevalence of marker positive patients in the overall study population. Effect sizes were chosen to reflect realistic planning scenarios, where at least some effect is present in the marker negative subgroup. In addition, scenarios were considered in which the assumed ‘true’ subgroup effects (i.e., the postulated effects) differed from those hypothesized at the planning stage. As expected, both two‐stage designs generally required fewer patients than a fixed parallel group design, and the advantage increased as the difference between subgroups increased. The adaptive selection design added little further reduction in sample size, as compared with the group sequential design, when the postulated effect sizes were equal to those hypothesized at the planning stage. However, when the postulated effects deviated strongly in favor of enrichment, the comparative advantage of the adaptive selection design increased, which precisely reflects the adaptive nature of the design. Copyright © 2013 John Wiley & Sons, Ltd.