虚拟经济本质与当代金融危机

资本证券化与大众资本的出现,使市场经济继自由竞争市场经济、垄断市场经济后进入第三时代:实体经济与虚拟经济互动的时代,由此形成当代经济的纷纭万象,经济危机通过虚拟经济体系而获得新的形态--由金融危机扩张至整个经济系统.这是当代市场经济结构的最基本特征,而马克思主义是解开其发生机制的理论钥匙.     

英汉壮思维器官跨语言文化比较

思维是人类具有的共同能力之一。不同的民族运用不同的身体器官来思维和表达情感并形成自己独特的民族文化。对这些文化差异的认知,我们可以通过语言层面做具体的分析比较获得。就思维器官跨语言文化比较角度而言,英语民族倾向于用脑智"mind"(脑),汉族倾向于用心智"heart"(心),而壮族则倾向于用喉智"hoz"(throat喉咙,即用喉咙思维和表达情感)。通过跨语言文化比较,可以加深我们对文化差异及文化多样性的认识和理解,更好地进行跨文化交际活动。     

五大发展理念：高校思想政治教育思想引领的新维度

党的十八届五中全会将发展问题置于中国特色社会主义现代化事业的核心地位,提出了五大发展理念——创新、协调、绿色、开放、共享.高校肩负着培养中国特色社会主义事业建设者和接班人的重任,五大发展理念的提出,无疑为高校思想政治教育的思想引领提供了新方向和新的行动指导.以创新发展激发思想政治教育活力,以协调发展提高思想政治教育品质,以绿色发展引领思想政治教育风尚,以开放发展拓展思想政治教育资源,以共享发展提高思想政治教育资源利用率,将五大发展理念渗透到高校思想政治教育中,不断提高思想政治教育的吸引力和说服力.     

数字阅读泛化对大学生学习能力影响分析

随着时代的进步,科技日新月异地发展以及网络的普及化,我们迎来了全新的数字化时代,人们的工作学习生活已经网络化了。阅读作为人们获取知识最基本的手段,强烈地受到了网络新媒体的冲击。在高校中,数字阅读已经成为大学生获取信息、进行交流的主要方式,并呈现出泛化的倾向,这也冲击着大学生的学习能力。文章在观察大学生数字化阅读现状的基础上,分析其利与弊,积极探讨如何更好地利用微信、微博、QQ等信息传播手段,规避弊端,提升学习效果,增强理性阅读能力,丰富自身知识结构。     

国家级新区发展总部经济的扶持政策比较

总部经济是国家级新区竞相培育发展的一种新型经济形态,也是衡量新区区域竞争力的重要指标。以国家级新区总部经济扶持政策为研究对象,重点梳理分析了上海浦东、天津滨海、重庆两江等8个国家级新区扶持总部经济发展的具体政策,总结了新区在总部经济发展扶持政策的通行做法和基本规律,并在此基础上提出新区应加强总部经济规划、总部经济中央商务区建设以及加大优惠扶持政策力度等相关对策建议。     

连片特困区城镇化进程与农民增收效应的空间计量分析——以武陵山片区为例

基于2000—2012年武陵山片区69县市(区)的面板数据,考虑空间异质性,运用空间统计的ESDA法和空间计量等方法,考察了片区农民收入与城镇化进程的空间相关性及其冷热点格局,比较产业城镇化和人口城镇化的农民增收效应。结果表明:(1)武陵山片区各县市(区)农民人均纯收入呈现出高度的空间正相关性,形成以丰都、彭水、武隆、黔江为中心的热点区及洪江、中方和鹤城为中心的次热点区;人口城镇化和产业城镇化空间相关性显著,热点区主要集中在张家界片区,有向周边蔓延趋势;铜仁地区处于"三低"分布的冷点区。(2)进一步的空间模型估计显示,人口城镇化是片区农民增收效应的主要动力,产业城镇化对农民收入增长亦有正效应,但带动能力偏弱。(3)农业技术水平、物质资本投资和经济密度的提高有利于农民增收,相反,片区金融发展的现状对农民增收存在抑制作用。根据以上结论提出了相关政策建议。     

Quantile regression for robust estimation and variable selection in partially linear varying-coefficient models

In this paper, we develop a new estimation procedure based on quantile regression for semiparametric partially linear varying-coefficient models. The proposed estimation approach is empirically shown to be much more efficient than the popular least squares estimation method for non-normal error distributions, and almost not lose any efficiency for normal errors. Asymptotic normalities of the proposed estimators for both the parametric and nonparametric parts are established. To achieve sparsity when there exist irrelevant variables in the model, two variable selection procedures based on adaptive penalty are developed to select important parametric covariates as well as significant nonparametric functions. Moreover, both these two variable selection procedures are demonstrated to enjoy the oracle property under some regularity conditions. Some Monte Carlo simulations are conducted to assess the finite sample performance of the proposed estimators, and a real-data example is used to illustrate the application of the proposed methods.     

Mini-max-risk and mini-mean-risk inferences for a partially piecewise regression

We consider a partially piecewise regression in which the main regression coefficients are constant in all subdomains, but the extraessential regression function is variable in different pieces and is difficult to be estimated. Under this situation, two new regression methodologies are proposed under the criteria of mini-max-risk and mini-mean-risk. The resulting models can describe the regression relations in maximum-risk and mean-risk environments, respectively. A two-stage estimation procedure, together with a composite method, is introduced. The asymptotic normality of the estimators is established, the standard convergence rate and efficiency are achieved. Some unusual features of the new estimators and predictions, and the related variable selection are discussed for a comprehensive comparison. Simulation studies and a real-financial example are given to illustrate the new methodologies.     

Precise large deviations for φ-mixing and UND random variables with long-tailed distributions

In this paper, we investigate the precise large deviations for sums of φ-mixing and UND random variables with long-tailed distributions. The asymptotic relations for non random sum and random sum of random variables with long-tailed distributions are obtained.     

Complete moment convergence of widely orthant dependent random variables

It is known that the dependence structure of widely orthant dependent (WOD) random variables is weaker than those of negatively associated (NA) random variables, negatively superadditive dependent (NSD) random variables, negatively orthant dependent (NOD) random variables, and extended negatively dependent (END) random variables. In this article, the results of complete moment convergence and complete convergence are presented for WOD sequence under the same moment conditions as independent sequence in classical result (Chow 1988 Chow, Y. (1988). On the rate of moment convergence of sample sums and extremes. Bull. Inst. Math. Acad. Sin. 16(3):177–201. [Google Scholar]).