我国商业银行马尔奎斯特生产力指数的实证分析

利用马尔奎斯特生产力指数测度方法测算了我国商业银行整体生产力增长率,发现我国商业银行生产力变化主要来自劳动密集型的数量扩张而非技术效率的改善。在外部竞争日益激烈的条件下,提高商业银行技术效率,促进技术创新是提升我国银行业竞争力与可持续发展能力的必然途径,也应当是我国商业银行下一步改革的重要目标。     

Estimation of non-parametric regression for dasometric measures

The aim of this paper is to describe a simulation procedure to compare parametric regression against a non-parametric regression method, for different functions and sets of information. The proposed methodology improves lack of fit at the edges of the regression curves, and an acceptable result is obtained for the no-parametric estimation in all studied cases. Larger differences appear at the edges of the estimation. The results are applied to the study of dasometric variables, which do not fulfil the normality hypothesis needed for parametric estimation. The kernel regression shows the relationship between the studied variables, which would not be detected with more rigid parametric models.     

A class of partially linear single‐index survival models

The authors define a class of “partially linear single‐index” survival models that are more flexible than the classical proportional hazards regression models in their treatment of covariates. The latter enter the proposed model either via a parametric linear form or a nonparametric single‐index form. It is then possible to model both linear and functional effects of covariates on the logarithm of the hazard function and if necessary, to reduce the dimensionality of multiple covariates via the single‐index component. The partially linear hazards model and the single‐index hazards model are special cases of the proposed model. The authors develop a likelihood‐based inference to estimate the model components via an iterative algorithm. They establish an asymptotic distribution theory for the proposed estimators, examine their finite‐sample behaviour through simulation, and use a set of real data to illustrate their approach.     

A robust prediction error criterion for pareto modelling of upper tails

Estimation of the Pareto tail index from extreme order statistics is an important problem in many settings. The upper tail of the distribution, where data are sparse, is typically fitted with a model, such as the Pareto model, from which quantities such as probabilities associated with extreme events are deduced. The success of this procedure relies heavily not only on the choice of the estimator for the Pareto tail index but also on the procedure used to determine the number k of extreme order statistics that are used for the estimation. The authors develop a robust prediction error criterion for choosing k and estimating the Pareto index. A Monte Carlo study shows the good performance of the new estimator and the analysis of real data sets illustrates that a robust procedure for selection, and not just for estimation, is needed.     

产出与经济效益的相应关系研究

在文献[1～4]的基础上,进一步提出产出-完全经济效益传递系数、贡献系数和受益系数,以揭示产出与经济效益的相互联系和数量关系,并在此基础上提出了提高各部门经济效益的主要途径。     

狱内行刑社会化的价值及其实现

行刑社会化的含义虽十分广泛,但狱内行刑社会化因较集中体现了自由刑与社会化的冲突而具有代表性.纯粹理性意义上的自由刑的本质应当仅仅限于将犯罪人限制在特定的活动空间里,但在实际执行时却必然产生种种负价值.行刑社会化作为执行自由刑宽和化的措施必然有利于消减这些负价值.累进处遇居于行刑社会化中心地位.我国狱内行刑社会化的横向分类重点在对监内罪犯的再次分类,建议以自然标准、犯罪标准和人格标准逐渐推进.纵向分级建议取消特严管理甚至一般严管并加大宽管的力度,其特宽管理可以考虑建立开放式监狱和半自由刑制度.操作上主要包括设立省级和狱内分类中心、将监狱分隔为普通管区、宽管区和特宽管区三部分以及实现罪犯的区际流动.     

基于模糊层次综合评判方法的企业投资财务评价

企业投资管理的财务评价包括数量评价和质量评价两个方面,其中投资管理的数量评价是与企业战略发展结构的贯彻、核心能力的强化以及管理控制的跟进息息相关的;投资管理的质量评价则建立在时间价值和现金流量的考量之上。鉴于企业财务信息的模糊性特征,建立基于模糊层次综合方法的企业投资管理的财务评价方法,无疑为企业投资管理的财务评价开辟了一种新的思路。     

Regularization and variable selection via the elastic net

Summary.  We propose the elastic net, a new regularization and variable selection method. Real world data and a simulation study show that the elastic net often outperforms the lasso, while enjoying a similar sparsity of representation. In addition, the elastic net encourages a grouping effect, where strongly correlated predictors tend to be in or out of the model together. The elastic net is particularly useful when the number of predictors ( p ) is much bigger than the number of observations ( n ). By contrast, the lasso is not a very satisfactory variable selection method in the p ≫ n case. An algorithm called LARS-EN is proposed for computing elastic net regularization paths efficiently, much like algorithm LARS does for the lasso.     

我国财务分析的局限性及其完善

文章针对我国财务分析中存在的问题,提出了加强现金流量表分析,强化专题分析,增加非单纯的财务分析和新产品研发分析等建议,以正确分析企业的经济活动.     

特别声明

从技术进步的角度出发对增长极理论模型化进行了探索,给出了运用增长极模式的一个必要条件——增长极的选择规模限度,说明了新增投资比例与采用增长极模式的预期开发效果(扩散效应)、增长极的极化效应强度以及极化效应完成的时间长短之间的关系,并实证探讨了增长极理论在西部开发中应用的可行性。