试析高等学校固定资产的内部控制体系

加强固定资产管理,防止固定资产流失,提高固定资产的使用效率,从而节约资金,是每个高校固定资产管理的目标。从固定资产的内部控制入手,分析了内部控制在固定资产管理中的重要作用,固定资产内部控制所要达到的目标,以及内部控制的措施和手段,并从九个方面构建了固定资产内部控制的管理模式。     

微观与宏观交易费用测量的进展及其关系研究

交易费用测量包括微观和宏观两个层次,微观层次又分为市场型、管理型和政治型交易费用测量。宏观层次即是对一国(或地区)总量交易费用的测量。在总量交易费用测量上,沃利斯和诺思1986年提出的交易行业测量法具有一定的开创性。依据该方法测量总量交易费用会发现,经济越发达,总量交易费用占GNP的比重越大,而每笔交易的交易费用越低。反之则反是。这就提出一个问题,即:总量交易费用和每笔交易的交易费用是否就是这种反比关系?要搞清这二者的关系,关键是必须将理论上的和测量到的总量交易费用两个概念区分开。事实上,理论上的总量交易费用和每笔交易的交易费用并非反比关系。     

Estimation of a Conditional Copula and Association Measures

Abstarct. This paper is concerned with studying the dependence structure between two random variables Y ₁ and Y ₂ conditionally upon a covariate X. The dependence structure is modelled via a copula function, which depends on the given value of the covariate in a general way. Gijbels et al. (Comput. Statist. Data Anal., 55, 2011, 1919) suggested two non‐parametric estimators of the ‘conditional’ copula and investigated their numerical performances. In this paper we establish the asymptotic properties of the proposed estimators as well as conditional association measures derived from them. Practical recommendations for their use are then discussed.     

Pairwise- and marginal-likelihood estimation for the mixed Rasch model with binary data

A marginal–pairwise-likelihood estimation approach is examined in the mixed Rasch model with the binary response and logit link. This method belonging to the broad class of composite likelihood provides estimators with desirable asymptotic properties such as consistency and asymptotic normality. We study the performance of the proposed methodology when the random effect distribution is misspecified. A simulation study was conducted to compare this approach with the maximum marginal likelihood. The different results are also illustrated with an analysis of the real data set from a quality-of-life study.     

Decision Theory Applied to a Linear Panel Data Model

This paper applies some general concepts in decision theory to a linear panel data model. A simple version of the model is an autoregression with a separate intercept for each unit in the cross section, with errors that are independent and identically distributed with a normal distribution. There is a parameter of interest γ and a nuisance parameter τ, a N×K matrix, where N is the cross‐section sample size. The focus is on dealing with the incidental parameters problem created by a potentially high‐dimension nuisance parameter. We adopt a “fixed‐effects” approach that seeks to protect against any sequence of incidental parameters. We transform τ to (δ, ρ, ω), where δ is a J×K matrix of coefficients from the least‐squares projection of τ on a N×J matrix x of strictly exogenous variables, ρ is a K×K symmetric, positive semidefinite matrix obtained from the residual sums of squares and cross‐products in the projection of τ on x, and ω is a (N−J) ×K matrix whose columns are orthogonal and have unit length. The model is invariant under the actions of a group on the sample space and the parameter space, and we find a maximal invariant statistic. The distribution of the maximal invariant statistic does not depend upon ω. There is a unique invariant distribution for ω. We use this invariant distribution as a prior distribution to obtain an integrated likelihood function. It depends upon the observation only through the maximal invariant statistic. We use the maximal invariant statistic to construct a marginal likelihood function, so we can eliminate ω by integration with respect to the invariant prior distribution or by working with the marginal likelihood function. The two approaches coincide. Decision rules based on the invariant distribution for ω have a minimax property. Given a loss function that does not depend upon ω and given a prior distribution for (γ, δ, ρ), we show how to minimize the average—with respect to the prior distribution for (γ, δ, ρ)—of the maximum risk, where the maximum is with respect to ω. There is a family of prior distributions for (δ, ρ) that leads to a simple closed form for the integrated likelihood function. This integrated likelihood function coincides with the likelihood function for a normal, correlated random‐effects model. Under random sampling, the corresponding quasi maximum likelihood estimator is consistent for γ as N→∞, with a standard limiting distribution. The limit results do not require normality or homoskedasticity (conditional on x) assumptions.     

新疆居民消费、固定资产投资与经济增长的动态关系——基于VAR模型的实证分析

利用向量自回归（VAR）模型及其他分析工具,以时间序列数据为基础,探讨新疆居民消费、固定资产投资与经济增长之间的动态关系具有现实意义。实证分析表明：新疆居民消费、固定资产投资与经济增长存在长期稳定的协整关系及单向的因果关系;居民消费、固定资产投资对经济增长呈较大且持续的正向影响;固定资产投资对经济增长贡献最大,随着时间的持续,居民消费的贡献将逐步赶上固定资产投资的贡献;从长期看,固定资产投资对经济增长推动力最大。居民消费对经济增长推动作用较小。因此。若要使其经济得到长远发展,必须采取增加固定资产投资以及提高居民收入以获得更多消费的若干对策。     

俚语新论

"俚语"这一名称产生得较早,历代辞书也有对俚俗词语或说法的收录,现代的某些辞书也对俚语做了解释,但具体什么是俚语,它的性质特点是什么,却没有一个清晰的说法。本文主要讨论了什么是俚语,它与俗语、谚语的区别,俚语的性质和范围。     

河南省产业投资结构现状及优化对策分析

一直以来,中国各地的经济增长受到不合理产业结构的制约,而产业结构的调整和升级可以通过投资结构的优化来实现。本文对河南省近几年来固定资产投资的规模、主体结构及产业结构进行了分析,发现当前河南省的产业投资存在扩大投资规模的难度加大、投资的主体结构不合理、投资的产业结构存在偏差等问题,提出了进一步优化河南省产业投资结构应在扩大投资及调整投资结构上下工夫。     

基于面板数据模型的能耗与固定资产投资关系的实证研究

首先,对我国固定资产投资与能源消费之间的关系进行了机理分析,认为大规模的固定资产投资活动是造成能耗快速增长的主要原因,并且固定资产投资与能源消费之间存在一种循环关系.然后,采用面板数据模型对我国8个主要行业的固定资产投资与能源消费关系进行了实证研究.研究结果表明,固定资产投资是我国能耗增长的格兰杰原因,固定资产投资与能耗增长之间存在显著的正相关性.最后,对遏制我国能耗高速增长给出了相应的政策建议.     

晚唐五代时期士人的生活审美——以《花间集》为中心

五代时期是中国历史上两大封建王朝,即唐和宋的转折和过渡时期.研究这一时期的审美文化,对于辨析唐、宋两代审美风格的差异缘由,以及中国美学史的补充和完善,都具有重要的意义.本文以该时期创作的文学文本《花间集》为中心,探讨了这一历史阶段士人阶层在审美对象、审美能力、审美色彩和审美趣味四个方面呈现出来的特点,将其概括为由外而内、由粗转精、“金”的凸显和醇酒美人.并在此基础上,探讨了其背后的深层社会政治文化原因.