研究生导师队伍建设的重要环节——学术论文量化评估

本文从研究生导师队伍科研成果的结构入手 ,认为对导师科研工作评估重点应是对学术论文的量化 ,并提出学术论文量化评估的指标设置、权重系数及其数学模型。     

指数分析中多种方法的结合运用

指数分析法在经济分析的各个领域里已得到广泛的应用。但只用单一方法分析问题往往不够全面、深入。本文以工业劳动生产率的分析为例,从三个方面,多角度、多层次、比较系统地阐述了指数分析中独具特色的分析手法。     

Applicability of a Neuroprobabilistic Integral Risk Index for the Environmental Management of Polluted Areas: A Case Study

Recently, we developed a GIS-Integrated Integral Risk Index (IRI) to assess human health risks in areas with presence of environmental pollutants. Contaminants were previously ranked by applying a self-organizing map (SOM) to their characteristics of persistence, bioaccumulation, and toxicity in order to obtain the Hazard Index (HI). In the present study, the original IRI was substantially improved by allowing the entrance of probabilistic data. A neuroprobabilistic HI was developed by combining SOM and Monte Carlo analysis. In general terms, the deterministic and probabilistic HIs followed a similar pattern: polychlorinated biphenyls (PCBs) and light polycyclic aromatic hydrocarbons (PAHs) were the pollutants showing the highest and lowest values of HI, respectively. However, the bioaccumulation value of heavy metals notably increased after considering a probability density function to explain the bioaccumulation factor. To check its applicability, a case study was investigated. The probabilistic integral risk was calculated in the chemical/petrochemical industrial area of Tarragona (Catalonia, Spain), where an environmental program has been carried out since 2002. The risk change between 2002 and 2005 was evaluated on the basis of probabilistic data of the levels of various pollutants in soils. The results indicated that the risk of the chemicals under study did not follow a homogeneous tendency. However, the current levels of pollution do not mean a relevant source of health risks for the local population. Moreover, the neuroprobabilistic HI seems to be an adequate tool to be taken into account in risk assessment processes.     

投资者信心和中国宏观经济波动——基于MIDAS混频模型

将投资者信心指数引入MIDAS混频模型之中,可以考察新冠疫情背景下投资者信心对于中国宏观经济波动的影响。基于投资者信心指数和“三驾马车”对我国季度GDP增长率进行预测,通过实证发现:引入投资者信心指数的MIDAS混频模型在预测精准度方面和基准模型进行比较,预测精准度高于未加入投资者信心的模型,均方根残差比值更小;在多元MIDAS混频模型之中,加入投资者信心指数的回归模型对我国GDP的实时预报和短期预测结果更加稳定,可为决策者提供更加精确的参考区间;宏观经济的波动对投资者信心指数变化反应,和投资、消费和进出口相比是最灵敏的。这为定量追踪宏观经济波动提供了一个新的视角。     

客户价值评价指标体系设计

客户关系管理是目前管理研究的热点,企业对客户价值的评估是其基础问题之一。如何设计一套实用的客户价值评价指标体系仍是尚未解决的问题。针对这种情况,在客户全生命周期管理的指导下,本文设计了一套分别针对最终客户和中间客户的评价指标体系,详细阐述了其管理应用,并进行了具体案例分析,证实了该指标体系的有效性。     

基于GARCH族模型的深证成指波动特征实证分析

采用GARCH族模型对深证成指总体及分阶段收益率的波动性进行统计拟合分析,指出深证成指的波动具有集聚性、持久性、显著的非对称性效应及阶段性特征。以深证成指价格达到最高点的时间点为分界,将整个样本分成两个阶段:在第一阶段,“利好消息”对深证成指的冲击比同等程度的“利空消息”大;在第二阶段,“利空消息”的冲击比同等程度的“利好消息”大。这说明深证市场具有杠杆效应。     

金融市场收益率方向预测模型研究———基于文本大数据方法

金融市场的发展关系着一国的经济命脉,而股票市场作为金融市场的重要组成部分,对其收益率的研究也一直都是学术界的热点。财经新闻常被认为蕴含着丰富的信息,其中所包含的情感信息作为影响投资者投资决策的重要因素之一,对股票收益率也具有一定的影响。故本文构建了适用于金融投资领域的财经新闻情感词典来对财经新闻进行文本分析,同时构造了新的预测模型:将财经新闻文本中所含的情感量化为情绪指数并与时变密度函数相结合,得到时变加权密度模型。并在此基础上以模型评分为权重组合多个预测模型构建出评分加权模型用于股票收益率预测。结果显示,加入情绪指数能有效提高模型预测能力,而评分加权模型的预测能力则在此基础上更进一步,在准确率以及评分规则上基本达到双重最优。     

The Construction of College Students＇ Employment Competitiveness Evaluation Index System

随着大学生就业呈现竞争化、多元化趋势，对高校就业情况的衡量标准也应由“就业率”评价向“就业竞争力”评价转变。大学生就业竞争力评价指标体系主要包括主观就业竞争力与客观就业竞争力。硬实力和软实力构成主观就业竞争力，其中软实力包括基本职业人格、学习创新能力、团队组织能力、职业知识结构四方面，客观就业竞争力包含就业机会、就业成本、就业效率和就业质量等方面。     

中国省际人口流动与 人力资本流动差异性分析

人力资本流动与人口流动相关却不相同,本文采用2010-2016年全国流动人口动态监测数据,从流动方向和流动强度两方面对我国省际人口流动引致的人力资本流动现象加以研究。结果表明从流动方向分析,各省人口净流动方向基本呈现时间一致性并且流入流出区域具有稳定性。在调查期间人口净流出省份为16个,人口净流入省份为15个,没有明显变化。人力资本净流向与人口净流向完全一致,但省际人口净流向与高级人力资本净流向并不完全一致,山西、广西、重庆等省市的高级人力资本净流向始终与总人力资本净流向相反。本文采用流出流入比率和迁移选择中心两种指标测算人力资本流动强度,结果基本一致。人力资本流动中心与人口流动中心分布均较为固定。2010年人力资本流动强度最大的省份在2016年的流动强度也更强,流动强度在省际呈现惯性和马太效应。人力资本流入最强地区包括北京、天津、上海三个直辖市,人力资本流出最强省份始终包括安徽、四川、河南等省份。以人力资本流出弹性衡量人力资本流出强度与人口流出强度的相对强弱,东部地区、东北地区省份人力资本的流出强度始终大于人口流出强度,西部地区省份差异较大。考虑各省近五年经济增长状况,人口流动或者人力资本流动对经济增长的影响是非线性的。     

Risk and diversification of nonprofit revenue portfolios: Applying modern portfolio theory to nonprofit revenue management

This study uses modern portfolio theory (MPT) to estimate the risk of nonprofit revenue portfolios and examines to what degree the revenue concentration measure based on Herfindahl–Hirschman Index is associated with the portfolio risk measure based on MPT. The findings suggest that nonprofits with greater revenue concentration have lower revenue portfolio risk in the whole sample analysis. However, it is plausible that this result is dominated by organizations reliant on commercial income, which comprise over half of the sample. In fact, when examined separately, the relationship varies by an organization's primary funding structure. While higher revenue concentration is positively associated with portfolio risk for organizations relying on donations or those without a consistent primary funding source, it appears to associate with a lower portfolio risk for commercial organizations and those relying on government grants. This study reflects on the concept of diversification derived from portfolio theory and calls attention to a more nuanced approach to nonprofit revenue strategy.