中国货币政策的利率规则——基于金融状况指数的分析

为检验中国中央银行是否已将金融市场状况纳入货币政策的框架,采用HTVPVAR模型的脉冲响应构建中国金融市场状况指数,检验结果显示:以金融市场状况指数为转换变量的STR模型形式的利率规则能较好地拟合实际数据,政策利率对通货膨胀缺口的变动存在非线性调整,且金融市场的景气（不景气）将增强（减弱）货币政策对通货膨胀缺口的反应程度。     

中国语境下主流媒体传播力评估模型及指标体系的构建

在对中国语境下主流媒体的内涵、主流媒体传播力解析的基础上,构建了一个主流媒体传播力的评估模型,并依据此模型,提出基于传播基础、传播能力、传播生态和媒介技术四个影响因素的主流媒体传播力的评估指标体系.     

浅埋大跨黄土隧道下穿公路方案比选

以大跨黄土隧道下穿公路安全施工为背景,对隧道下穿公路的安全施工方案进行研究。基于公路路面破损指数与下穿公路施工风险事件引起路面最大沉降之间的关系确定了隧道下穿施工可能引起的路面最大允许沉降量,并据此制定出施工管理基准,对比分析了CRD和CD法引起的隧道拱顶沉降、地表最大沉降、支护受力和隧道周边地层塑性区特征,建议采用CD法进行下穿施工。下穿孙辛路施工监测结果表明,采用CD法保证了隧道施工安全和孙辛路的正常通行。     

A股上市公司变相财务操纵对行业估值的影响

关于上市公司利润操控的相关研究主要是将净利润作为一个事关操控的敏感指标,但在监管与被监管双方努力的博弈下,其可被操纵的潜力已被充分挖掘。从实证角度关注上市公司财务操纵的其他可操作途径,其中就包括一些看似合理的变相财务操纵手段。按照2001年中国证监会公布的《上市公司行业分类指引》,把我国上市企业分为13个行业,对不同行业内企业2003—2013年部分主观可操控的财务指标与其所在行业的平均市盈率进行格兰杰因果检验和回归分析,结果表明,一些行业内企业的部分财务指标与其所在行业的平均市盈率存在领先与滞后关系,并且影响作用显著。     

基于因子分析的株洲各县市区 综合经济实力评价

市区经济发展离不开本市各个县市区经济的贡献,而本市各县市区发展之间的差异会影响整个市区的经济发展。株洲市近几年来发展迅速,但各县市区的发展却有很大差异。通过因子分析方法研究株洲市各县市区的综合经济实力问题,并根据株洲统计年鉴提出了14个反映城市综合经济实力的指标。研究结果反映了株洲市各县市区的经济发展之间差异,为株洲市经济发展提供了参考。     

Studying Complexity of Model-based Clustering

Cluster analysis is a popular statistics and computer science technique commonly used in various areas of research. In this article, we investigate factors that can influence clustering performance in the model-based clustering framework. The four factors considered are the level of overlap, number of clusters, number of dimensions, and sample size. Through a comprehensive simulation study, we investigate model-based clustering in different settings. As a measure of clustering performance, we employ three popular classification indices capable of reflecting the degree of agreement in two partitioning vectors, thus making the comparison between the true and estimated classification vectors possible. In addition to studying clustering complexity, the performance of the three classification measures is evaluated.     

Conditional VAR and Expected Shortfall: A New Functional Approach

We estimate two well-known risk measures, the value-at-risk (VAR) and the expected shortfall, conditionally to a functional variable (i.e., a random variable valued in some semi(pseudo)-metric space). We use nonparametric kernel estimation for constructing estimators of these quantities, under general dependence conditions. Theoretical properties are stated whereas practical aspects are illustrated on simulated data: nonlinear functional and GARCH(1,1) models. Some ideas on bandwidth selection using bootstrap are introduced. Finally, an empirical example is given through data of the S&P 500 time series.     

Functional Partial Linear Single‐index Model

This paper deals with the problem of predicting the real‐valued response variable using explanatory variables containing both multivariate random variable and random curve. The proposed functional partial linear single‐index model treats the multivariate random variable as linear part and the random curve as functional single‐index part, respectively. To estimate the non‐parametric link function, the functional single‐index and the parameters in the linear part, a two‐stage estimation procedure is proposed. Compared with existing semi‐parametric methods, the proposed approach requires no initial estimation and iteration. Asymptotical properties are established for both the parameters in the linear part and the functional single‐index. The convergence rate for the non‐parametric link function is also given. In addition, asymptotical normality of the error variance is obtained that facilitates the construction of confidence region and hypothesis testing for the unknown parameter. Numerical experiments including simulation studies and a real‐data analysis are conducted to evaluate the empirical performance of the proposed method.     

煤炭大数据指数编制及经验模态分解模型研究

基于开放性数据源、连续观测昨多变量数据编制的大数据指数,与传统的统计调查指数存在的差异不仅在于数据本身的无限扩张,而且在于编制方法以及分解研究的规则、模型方面的差异。在大数据背景下,率先尝试性地提出大数据指数的定义和数据假设,将"互联网大数据指数"引入煤炭交易价格指数综合编制太原煤炭交易大数据指数,从而反映煤炭价格的变动趋势;导入经验模态分解模型,对所编制的煤炭大数据指数进行分解研究,尝试比较与传统的统计调查指数的差异。研究表明:新编制的煤炭价格大数据指数要比太原煤炭交易价格指数更为敏感和迅速,能更好地反映煤炭价格的变动趋势。随着"互联网+"和大数据战略的逐渐普及,基于互联网大数据编制的综合指数会影响到更多领域,将成为经济管理和社会发展各个领域的晴雨表和指示器;与传统统计调查指数逐步融合、互补或者升级,成为宏观经济大数据指数的重要组成部分。