Inference on Causal Effects in a Generalized Regression Kink Design

We consider nonparametric identification and estimation in a nonseparable model where a continuous regressor of interest is a known, deterministic, but kinked function of an observed assignment variable. We characterize a broad class of models in which a sharp “Regression Kink Design” (RKD or RK Design) identifies a readily interpretable treatment‐on‐the‐treated parameter (Florens, Heckman, Meghir, and Vytlacil (2008)). We also introduce a “fuzzy regression kink design” generalization that allows for omitted variables in the assignment rule, noncompliance, and certain types of measurement errors in the observed values of the assignment variable and the policy variable. Our identifying assumptions give rise to testable restrictions on the distributions of the assignment variable and predetermined covariates around the kink point, similar to the restrictions delivered by Lee (2008) for the regression discontinuity design. Using a kink in the unemployment benefit formula, we apply a fuzzy RKD to empirically estimate the effect of benefit rates on unemployment durations in Austria.     

中国是否拥有原油的国际定价权？——基于油价间独立性与传导性视角

在目前国际原油以期货市场定价的格局下,如何判别中国原油期货价格是否已经拥有了国际定价权是一个亟待解决的理论和现实问题。本文基于多变量单方向因果测度统计分析方法,聚焦原油期货市场定价的独立性与传导性,以上海国际能源交易中心的原油期货价格（INE）为例进行实证分析。研究发现：第一,INE在短、中期内未受到WTI、Brent等原油期货价格的因果影响,具有价格发现功能,但是尚不具备长期独立性;第二,在本文的样本区间与美元兑人民币汇率条件下,上海原油期货采用人民币计价可以增强其对WTI、Brent的影响力,同时减弱二者的影响力,彰显出人民币计价的双重定价优势;第三,WTI和Brent油价作为基准油价指标,INE作为非基准油价指标满足本文所创建的国际基准油价之间应长期相互独立、基准油价对非基准油价应具有传导性的研判标准,反映了该标准的科学性。     

贸易开放对中国水环境污染影响的实证研究

文章基于2004-2013年中国31个省市的面板数据,采用动态面板模型和差分GMM估计方法,分别选取化学需氧量排放和氨氮排放作为水环境污染的有机污染物和无机污染物的排放指标,对贸易开放的结构效应引致的中国水环境污染排放进行了实证研究.研究结果表明,经济增长的规模和技术效应是影响水环境污染排放的主要因素,直接结构效应对中国水污染排放的影响不显著,贸易开放的结构效应也在一定程度上加剧了中国水环境污染的排放.通过引入贸易开放的相关交叉项进一步对决定贸易结构效应的比较优势来源进行识别,结果发现,对于中国水环境污染排放并不存在所谓的“污染天堂效应”和“要素禀赋效应”.贸易的结构效应会导致西部经济欠发达地区的水污染排放降低,而对中东部经济相对发达地区,贸易的结构效应会引致其水污染排放量的增大和排放强度的加剧.     

农村居民大病保险经济补偿能力及效果

经济补偿是农村居民大病保险的基本职责,经济补偿能力是履行该职责的前提和基础,经济补偿效果是履行该职责的具体体现。利用江苏省5个样本地区的实地调研数据,从横向和纵向两个维度评估了各地大病保险的经济补偿能力,从大病保险的受益面、患者个人自付比例、大病保险基金使用率等指标综合衡量各地大病保险的经济补偿效果。研究发现,医疗费用、筹资机制、政策设计等多种主客观因素共同约束着大病保险经济补偿能力和补偿效果的发挥,亟需从补偿主体的衔接、大病费用的控制、筹资机制的建设、大病保险的服务等方面进行改进。     

创业板公司风险投资对财务治理效率影响研究

风险投资在投资目的、方式、收回等方面与传统投资有很大区别,研究此投资框架下各项财务治理行为对企业财务治理效率的影响,能够有针对性地指导企业完善治理措施,提高治理效率。创业板是我国风险投资参与面最广的上市公司板块,以创业板2009—2013年期间IPO上市公司为研究对象,采用实证研究方法,分析风险投资对上市公司财务治理效率的作用及其形式。结果显示,风投方持股比例越高,参与时间越长,在董事会、监事会高管中拥有席位越多,财务治理效率就越高,但创业板中的联合投资存在“搭便车”现象。上市公司应努力完善并调整企业相关制度和治理结构,风险投资机构加强合作,以最终实现高效的财务治理。     

中国由ICT渠道获取的国际R&D溢出门槛效应

采用2003-2012年中国除西藏外30个省市自治区的面板数据,考察信息通信技术渠道国际R & D溢出效应。运用面板单位根检验、协整检验、相关性分析、格兰杰因果检验、随机效应模型等计量方法,研究中国通过信息通信技术渠道获得的国际R & D溢出与当地全要素生产率之间的关系;建立Hansen非动态面板门槛模型,采用稳健标准差回归,检验各省份由信息通信技术渠道获得的国际R & D溢出门槛效应,并从产业转型升级和信息化建设角度分析存在门槛效应的原因。结果表明,中国大部分省份通过信息通信技术渠道获取的国际R & D溢出与全要素生产率有正相关关系;通过信息通信技术渠道获得的国际R & D溢出对当地技术进步的影响存在明显的地区差异和门槛效应。     

社会资本对居民生活垃圾分类行为的影响机理分析

社会资本与环境保护合作行为的逻辑关系已经成为环境管理的一个重要研究方向。基于219户城镇居民调查数据的实证研究发现,除了年龄、受教育年限和中共党员身份外,以社会网络、社会规范和社会信任为要素的社会资本,对提高居民生活垃圾分类水平有显著的正向影响。具体而言,社会网络能够降低居民机会主义和“搭便车”的行为倾向;社会规范能够提高居民行为的可预测性,增强居民投资环境保护集体行动的信心;社会信任则通过降低交易成本,促进居民生活垃圾分类的自主合作行为。为从源头上化解我国生态环境管理面临的“垃圾围城”困境,政府应积极促进居民间的网络互动,完善互惠共享的社会规范,提升居民间的普遍信任,同时加大对生活垃圾分类知识和技巧的宣传力度、发挥党员在遵守社会规范中的带头作用,通过社会资本发展促进公众的自主环境保护合作行为。     

A win ratio approach to comparing continuous non‐normal outcomes in clinical trials

Clinical trials are often designed to compare continuous non‐normal outcomes. The conventional statistical method for such a comparison is a non‐parametric Mann–Whitney test, which provides a P‐value for testing the hypothesis that the distributions of both treatment groups are identical, but does not provide a simple and straightforward estimate of treatment effect. For that, Hodges and Lehmann proposed estimating the shift parameter between two populations and its confidence interval (CI). However, such a shift parameter does not have a straightforward interpretation, and its CI contains zero in some cases when Mann–Whitney test produces a significant result. To overcome the aforementioned problems, we introduce the use of the win ratio for analysing such data. Patients in the new and control treatment are formed into all possible pairs. For each pair, the new treatment patient is labelled a ‘winner’ or a ‘loser’ if it is known who had the more favourable outcome. The win ratio is the total number of winners divided by the total numbers of losers. A 95% CI for the win ratio can be obtained using the bootstrap method. Statistical properties of the win ratio statistic are investigated using two real trial data sets and six simulation studies. Results show that the win ratio method has about the same power as the Mann–Whitney method. We recommend the use of the win ratio method for estimating the treatment effect (and CI) and the Mann–Whitney method for calculating the P‐value for comparing continuous non‐Normal outcomes when the amount of tied pairs is small. Copyright © 2016 John Wiley & Sons, Ltd.     

A visualization method measuring the performance of biomarkers for guiding treatment decisions

Biomarkers that predict efficacy and safety for a given drug therapy become increasingly important for treatment strategy and drug evaluation in personalized medicine. Methodology for appropriately identifying and validating such biomarkers is critically needed, although it is very challenging to develop, especially in trials of terminal diseases with survival endpoints. The marker‐by‐treatment predictiveness curve serves this need by visualizing the treatment effect on survival as a function of biomarker for each treatment. In this article, we propose the weighted predictiveness curve (WPC). Based on the nature of the data, it generates predictiveness curves by utilizing either parametric or nonparametric approaches. Especially for nonparametric predictiveness curves, by incorporating local assessment techniques, it requires minimum model assumptions and provides great flexibility to visualize the marker‐by‐treatment relationship. WPC can be used to compare biomarkers and identify the one with the highest potential impact. Equally important, by simultaneously viewing several treatment‐specific predictiveness curves across the biomarker range, WPC can also guide the biomarker‐based treatment regimens. Simulations representing various scenarios are employed to evaluate the performance of WPC. Application on a well‐known liver cirrhosis trial sheds new light on the data and leads to discovery of novel patterns of treatment biomarker interactions. Copyright © 2015 John Wiley & Sons, Ltd.     

Group sequential monitoring based on the weighted log‐rank test statistic with the Fleming–Harrington class of weights in cancer vaccine studies

In recent years, immunological science has evolved, and cancer vaccines are now approved and available for treating existing cancers. Because cancer vaccines require time to elicit an immune response, a delayed treatment effect is expected and is actually observed in drug approval studies. Accordingly, we propose the evaluation of survival endpoints by weighted log‐rank tests with the Fleming–Harrington class of weights. We consider group sequential monitoring, which allows early efficacy stopping, and determine a semiparametric information fraction for the Fleming–Harrington family of weights, which is necessary for the error spending function. Moreover, we give a flexible survival model in cancer vaccine studies that considers not only the delayed treatment effect but also the long‐term survivors. In a Monte Carlo simulation study, we illustrate that when the primary analysis is a weighted log‐rank test emphasizing the late differences, the proposed information fraction can be a useful alternative to the surrogate information fraction, which is proportional to the number of events. Copyright © 2016 John Wiley & Sons, Ltd.