绿色新政：欧洲走出危机的长期性、可持续计划

欧洲绿党所倡导的“绿色新政”,其目的在于实现在地球自然限制内带来经济繁荣、社会正义和生活幸福的经济社会的全面转型,而实现路径则依赖于对基础设施、工业产业、教育创新、社会聚合与自然环境等进行投资。由欧洲议会绿党党团委托支持、绿色智库“重构”完成的这一研究报告,试图构建一个相对不利环境下如何达到改变欧洲经济与社会状况的投资水平的金融体制。它认为,欧盟每年需将GDP的2%投资到2020年时实现CO2排放减少30%目标的工作中,并建议财源的主体应是私人投资,同时国家创造必需的激励和支持以吸引这些私人投资。     

迈向精细化的乡村治理——以一个陇西移民村的治理实践为例

自党的十八届五中全会提出"加强和创新社会治理,推进社会治理精细化,构建全民共建共享的社会治理格局"的总目标以来,"精细化治理"成为推进国家治理能力和治理体系现代化的重要议题。以一个移民村的治理实践为例,分别从政策执行的精细化、村干部权责的精细化以及村民日常生活的精细化三个维度阐释D村乡村治理中的精细化趋向及其背后的运作机制与内在逻辑。研究发现:在国家的精细化治理要求下,细致的政策制定构建了精细的乡村治理组织体系,从而进一步明晰了村干部的权责匹配,由此形成了自上而下的精细化乡村治理路径;同时,村民在日常生活中的精准需求助推了乡村治理评价体系的细化,又自下而上地倒逼着乡村治理朝向精细化发展。但迈向精细化的乡村治理仍然存在若干现实问题,如何能在这一路径下实现乡村治理有效,还有待进一步的理论探讨与实践探索。     

农产品贸易对农业碳排放的影响——兼议数字乡村发展的门槛效应

基于1999—2019年中国省际面板数据,运用普通面板模型、空间面板模型与面板门槛模型实证分析了农产品贸易对农业碳排放的影响及其空间溢出效应与数字乡村发展门槛效应。研究发现：（1）农产品贸易对农业碳排放具有显著的抑制作用,并且相较于东部地区、粮食主产区以及贸易顺差区间,这种抑制作用在中西部地区、非粮食主产区以及贸易逆差区间更为显著; （2）在三种空间权重矩阵设定下,农产品贸易对本地区和“毗邻地区”农业碳排放均具有显著抑制作用,存在空间溢出效应,且相较于农产品出口贸易,农产品进口贸易抑制农业碳排放的空间溢出效应更为显著;（3）农产品贸易影响农业碳排放的过程中存在数字乡村发展双重门槛,即随着跨越数字乡村发展两道“门槛”,农产品贸易对农业碳排放的抑制作用呈现出边际递增的特征。由此,提出推动农产品贸易深度开放、构建农产品贸易交流协调机制以及增强数字乡村建设力度等政策建议。     

论工程造价的有效控制

建筑安装工程造价的有效控制,应该以优秀的工程设计为前提,工程招投标为核心,施工管理为重要环节,竣工结算为关键,“以人为本”是基础。工程造价的控制是贯穿于项目建设全过程的控制,即在投资决策阶段、设计阶段、建设项目发包阶段和建设实施阶段,将工程造价控制在批准的造价限额以内。     

使用词汇化句干对二语语用能力的影响

大多数语言中均普遍存在相当数量的词汇化句干，此类语言信息块的使用能够缩短使用者话语输出的编码时间，提高理解语言输入的解码效率。故此，二语学习者需要增强对目标语语块信息的注意力，将之内化进而提高二语语用能力。词汇化句干对中介语发展的实证研究表明，词汇化句干的使用将促进中介语的发展。     

Effect of Health on Retirement of Older Americans: a Competing Risks Study

Retirement is an important event in the life of an individual. The decision to retire or exit from full-time employment may be motivated by several factors, including health. This paper explores the effect of both subjective and relatively more objective physical and mental health conditions on the probability of exit from full-time employment. Using longitudinal data on older Americans from ten waves of the Health and Retirement Study (1992–2010), eight health indices are created from a wide range of health measures by principal component analysis. The effect of these health indices on the time until exit from full-time employment is empirically examined in a proportional hazard model. Single and competing risk specifications are estimated that allow for multiple spells of full-time employment and control for unobserved heterogeneity. The main results suggest that better self-reported health decreases the likelihood of exit from full- time employment, while poor physical health (functional limitations factor) increases the likelihood of exit from full-time employment via complete retirement and disability. For mental health, I find that depression increases the likelihood of exit via complete retirement, part-time work and unemployment while cognitive disorders lead to an increase in likelihood of exit via the disability exit route. Hence, physical and mental health problems are both impediments to continued work. These results have implications for public policies targeted towards retaining older workers within the labor market.     

A likelihood based estimator for vector autoregressive processes

A onestep estimator, which is an approximation to the unconditional maximum likelihood estimator (MLE) of the coefficient matrices of a Gaussian vector autoregressive process is presented. The onestep estimator is easy to compute and can be computed using standard software. Unlike the computation of the unconditional MLE, the computation of the onestep estimator does not require any iterative optimization and the computation is numerically stable. In finite samples the onestep estimator generally has smaller mean square error than the ordinary least squares estimator. In a simple model, where the unconditional MLE can be computed, numerical investigation shows that the onestep estimator is slightly worse than the unconditional MLE in terms of mean square error but superior to the ordinary least squares estimator. The limiting distribution of the onestep estimator for processes with some unit roots is derived.     

A robust QTL mapping procedure

In quantitative trait linkage studies using experimental crosses, the conventional normal location-shift model or other parameterizations may be unnecessarily restrictive. We generalize the mapping problem to a genuine nonparametric setup and provide a robust estimation procedure for the situation where the underlying phenotype distributions are completely unspecified. Classical Wilcoxon–Mann–Whitney statistics are employed for point and interval estimation of QTL positions and effects.     

Classification rules for triply multivariate data with an AR(1) correlation structure on the repeated measures over time

In this article we study the problem of classification of three-level multivariate data, where multiple q$q$-variate observations are measured on u$u$-sites and over p$p$-time points, under the assumption of multivariate normality. The new classification rules with certain structured and unstructured mean vectors and covariance structures are very efficient in small sample scenario, when the number of observations is not adequate to estimate the unknown variance–covariance matrix. These classification rules successfully model the correlation structure on successive repeated measurements over time. Computation algorithms for maximum likelihood estimates of the unknown population parameters are presented. Simulation results show that the introduction of sites in the classification rules improves their performance over the existing classification rules without the sites.