“双碳”目标下农业生态效率测度及影响因素分析

农业生态效率是农业经济和生态环保协调发展的重要体现。文章首先引入农业碳汇效应,构建农业生态效率测度指标体系;其次,基于2010—2019年中国31个省市面板数据,运用熵权法改进的超效率SBM测算各地区农业生态效率;然后运用面板Tobit模型探究农业生态效率影响因素。结果发现：2010—2019年中国农业生态效率总体呈现平稳上升态势,空间上呈现东北地区最高、东部次之、西部较低、中部最低的分布格局;财政支农程度、工业化程度、农业自然环境、农业机械密度对农业生态效率产生负向影响;农业环境规制、科技支持力度、农业资源禀赋、农业人力资本和农业生产能力对农业生态效率产生正向影响。最后,提出合理投入农业要素资源;促进农业生产增长;加大农业科技研发和推广力度;提高农业劳动力素质等建议。     

Who Is the Residential Parent? Understanding Discrepancies in Unmarried Parents' Reports

Research examining parental reports of children's living arrangements has often relied on information about legally ordered custody agreements following divorce. This analysis used data from matched pairs of parents (N = 1,156) in the Fragile Families and Child Wellbeing Study who live apart to compare mother and father reports of their child's residence 5 years after a nonmarital birth. The authors found that over one third of unmarried parents disagreed about who their child lived with and that conflicting reports were much more likely when fathers spent nights with the mother (an indicator of part‐time cohabitation) and had overnights with the child on their own. The results further suggest that discrepancies in unmarried parents' reports were more closely associated with the complexity and ambiguity of their living situations than with the quality of their relationships with each other. Implications for measuring children's living arrangements in families formed outside of marriage are discussed.     

人力资源价值计量方法演进路径及发展动态研究

人力资源价值计量方法问题是人力资源管理理论与实践中的一个重要"瓶颈"问题。文章在对相关问题的研究状况进行深入剖析的基础上,对人力资源价值计量方法问题研究的演进路径进行了详细梳理,进而分析了现有研究成果存在的主要问题,并对未来人力资源价值计量方法问题的研究趋势进行了预测,从而为未来合理解决人力资源价值计量方法问题提供了重要的参考与启示。     

微信公众号影响力指数建构与量化评估

作为被广泛使用的社交媒体,微信已经成为热点事件和网络舆情的重要策源地,科学准确评估微信公众号的影响力对于明晰微信信息传播特点,深入挖掘微信传播潜力,进一步规范和指导微信平台的传播行为具有较大的理论和实践意义。在对既有关于微信公众号影响力研究进行梳理和评价的基础上,基于传播效果测量的设计,坚持以受众为中心、由浅入深多层次考察准则,运用德尔菲法和层次分析法建构一套微信公众号影响力指标体系。该指标体系由4个一级指标和9个二级指标构成,并运用线性合成法合成微信公众号影响力指数。     

Uniform in bandwidth consistency for various kernel estimators involving functional data

The paper investigates various nonparametric models including regression, conditional distribution, conditional density and conditional hazard function, when the covariates are infinite dimensional. The main contribution is to prove uniform in bandwidth asymptotic results for kernel estimators of these functional operators. Then, the application issues, involving data-driven bandwidth selection, are discussed.     

公允价值应用研究

我国在2006年新的企业会计准则体系中全面引入了公允价值,这将对会计信息的生成和呈报产生重要影响。论文阐述了公允价值的内涵,分析了公允价值的特征,从公允价值计量的可操作性、公允价值计量的信息质量的可靠性、我国的宏观经济环境、会计人员素质等方面分析了公允价值在应用中存在的问题,最后提出了在我国推行公允价值的建议。     

贫困测量中恩格尔系数的失效及分析

 恩格尔系数在我国的适用性问题是学术界重要议题之一。本文利用对哈尔滨市和沈阳市贫困人口的调查数据,分析了恩格尔系数在我国城市贫困测量中失效的问题及原因。研究者尝试对恩格尔系数的分子、分母进行了重新界定和适当的修正,研究检验表明,从宏观测量和微观测量两个方面,修正恩格尔系数都能更准确的反映我国城市贫困家庭的真实生活水平。     

Estimation in capture–recapture models when covariates are subject to measurement errors and missing data

For capture–recapture models when covariates are subject to measurement errors and missing data, a set of estimating equations is constructed to estimate population size and relevant parameters. These estimating equations can be solved by an algorithm similar to the EM algorithm. The proposed method is also applicable to the situation when covariates with no measurement errors have missing data. Simulation studies are used to assess the performance of the proposed estimator. The estimator is also applied to a capture–recapture experiment on the bird species Prinia flaviventris in Hong Kong. The Canadian Journal of Statistics 37: 645–658; 2009 © 2009 Statistical Society of Canada     

SEMIPARAMETRIC REGRESSION AND GRAPHICAL MODELS

Semiparametric regression models that use spline basis functions with penalization have graphical model representations. This link is more powerful than previously established mixed model representations of semiparametric regression, as a larger class of models can be accommodated. Complications such as missingness and measurement error are more naturally handled within the graphical model architecture. Directed acyclic graphs, also known as Bayesian networks, play a prominent role. Graphical model-based Bayesian 'inference engines', such as bugs and vibes , facilitate fitting and inference. Underlying these are Markov chain Monte Carlo schemes and recent developments in variational approximation theory and methodology.