京津冀节能减排政策措施的差异与协同研究

在对京津冀1981年以来节能减排政策措施进行量化处理的基础上,建立针对节能减排政策措施有效性的计量模型,分析了京津冀节能减排政策措施的演变状况,并探究京津冀节能减排政策措施对其节能减排效果影响的差异性.研究结果表明:京津冀节能减排政策颁布经历了早期各年份相对零散、缺乏连续性到新世纪以来政策颁布数量显著增多、政策总体力度逐渐增大的过程,但三地政策总效力的增加主要是由于节能减排政策颁布数量增多引起的;京津冀三地在政策的制定过程中更多的是趋于实现短期目标,政策整体缺乏系统性和权威性;人事措施、行政措施、引导措施、财税措施、金融措施等不同节能减排政策措施对京津冀节能和减排的有效性具有明显的差异;三地对不同政策措施的使用方式、使用程度方面存在明显的差异,这对京津冀协同推进节能减排的治理工作提出挑战.论文还从京津冀完善单一节能减排政策措施的使用、加强市场手段的应用及京津冀区域协同治理等方面提出了相应政策建议.     

Product partition latent variable model for multiple change-point detection in multivariate data

The product partition model (PPM) is a well-established efficient statistical method for detecting multiple change points in time-evolving univariate data. In this article, we refine the PPM for the purpose of detecting multiple change points in correlated multivariate time-evolving data. Our model detects distributional changes in both the mean and covariance structures of multivariate Gaussian data by exploiting a smaller dimensional representation of correlated multiple time series. The utility of the proposed method is demonstrated through experiments on simulated and real datasets.     

Spatial Distribution of Flood Risk and Quality of Spatial Management: Case Study in Odra Valley,Poland

This article presents methodological solutions aimed at presenting the spatial distribution of flood risk and quality of spatial management (land use), indicating both those areas used reasonably and those requiring modification. The purpose was to identify key risk areas and risk‐free areas from the point of view of human security and activity on the floodplains, based on the examples of the vicinities of Wroclaw and Raciborz in the Odra Valley, Poland. Due to recent climate change, Poland has suffered the effects of severe flooding (e.g., 1997, 2001, 2010). The analyses conducted were motivated by the European Parliament and Council's recently implemented Directive 2007/60/WE, as well as by the demand for studies for local spatial planning. The analysis indicates that reasonably developed areas do not account for the majority of those studied, making up 36% of the Wroclaw area and 15% of the Raciborz area.     

基于碳减排技术的竞争供应链投资均衡策略研究

本文以两条竞争供应链（每条供应链均包含一个制造商和一个零售商）为研究对象，基于其是否采用碳减排技术，构建了两条供应链均不采用碳减排技术（NN情景）、供应链1采用碳减排技术（AN情景），供应链2采用碳减排技术（NA情景），及两条供应链均采用碳减排技术（AA情景）的收益模型，求解出相应的最优解并探讨了竞争供应链投资碳减排技术的均衡策略。研究发现：当碳税较低时，AA情景是竞争供应链的均衡策略；当碳税适中时，生产成本较高的供应链不采用减排技术，而其竞争供应链将采用减排技术以提升竞争力；当碳税较高时，NN情景是竞争供应链的均衡策略。此外，当供应链间竞争强度较弱时，政府可适当提高碳税标准；当供应链间竞争较为激烈时，政府应降低碳税以引导企业采用碳减排技术。     

The boomerang effect of psychological interventions

Research has found that teaching people about psychological biases can help counteract biased behavior. On the other hand, due to the innate need for preservation of a positive self-image, it is likely that teaching people about biases they hold, may cause a boomerang effect in cases where being associated with a specific bias implies negative social connotations. In the three studies below we examine situations in which psychological bias implies negatively associated behavior, and show that teaching people about bias in those contexts can be counterproductive.     

基于家庭策略的贫困代际传递治理

家庭是贫困治理的社会基础,有效阻断贫困的代际传递是贫困治理的重要方式。基于家庭策略的视野,通过对两个贫困家庭在减贫过程中不同减贫方式的分析与比较,探讨家庭策略如何被自主运用来解决贫困问题。研究发现,“反馈模式”的代际关系下,多子女所带来的路径可选择性与关系灵活性让家庭有更大空间采用有效的家庭策略,以“代内合力”和“代际合力”为一部分子女的成长和发展提供更充分的资源及“资源变现”的空间与条件,从而为实现“家庭减贫”创造机会。在巩固脱贫成果和实现乡村振兴进程中,家庭作用的有效发挥能充分激发家庭自我发展的内生动力,从而实现脱贫致富。     

Some notes on robust sure independence screening

Sure independence screening (SIS) proposed by Fan and Lv [4 J. Fan and R. Li, Variable selection via nonconcave penalized likelihood and its oracle properties, J. Amer. Statist. Assoc. 96 (2001), pp. 1348–1360. doi: 10.1198/016214501753382273[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]] uses marginal correlations to select important variables, and has proven to be an efficient method for ultrahigh-dimensional linear models. This paper provides two robust versions of SIS against outliers. The two methods, respectively, replace the sample correlation in SIS with two robust measures, and screen variables by ranking them. Like SIS, the proposed methods are simple and fast. In addition, they are highly robust against a substantial fraction of outliers in the data. These features make them applicable to large datasets which may contain outliers. Simulation results are presented to show their effectiveness.     

Modelling hierarchical clustered censored data with the hierarchical Kendall copula

This article proposes a new model for right‐censored survival data with multi‐level clustering based on the hierarchical Kendall copula model of Brechmann (2014) with Archimedean clusters. This model accommodates clusters of unequal size and multiple clustering levels, without imposing any structural conditions on the parameters or on the copulas used at various levels of the hierarchy. A step‐wise estimation procedure is proposed and shown to yield consistent and asymptotically Gaussian estimates under mild regularity conditions. The model fitting is based on multiple imputation, given that the censoring rate increases with the level of the hierarchy. To check the model assumption of Archimedean dependence, a goodness‐of test is developed. The finite‐sample performance of the proposed estimators and of the goodness‐of‐fit test is investigated through simulations. The new model is applied to data from the study of chronic granulomatous disease. The Canadian Journal of Statistics 47: 182–203; 2019 © 2019 Statistical Society of Canada