生产函数与成本函数的关系研究

本文给出了生产函数与成本函数之间的一般关系,并证明齐次生产函数与齐次成本函数之间存在着一种齐次对应关系:齐次生产函数在厂商的成本最小化决策下必然产生齐次的成本函数且齐次成本函数必然产生对应于齐次的生产函数。     

高校青年志愿服务的发展路径探析——基于AGIL系统模型

高校青年志愿服务是社会志愿服务中重要的组成部分。高校青年志愿服务事业由四个子系统承担着相应的功能:资源系统发挥适应功能;高校志愿服务组织发挥目标达成功能;共青团发挥整合功能;育人系统发挥模式维持功能。在目前的高校志愿服务工作中,各项功能存在发挥不到位的问题。以AGIL理论分析模型为框架,可以从四个方面促进高校青年志愿服务提供路径支撑:资源系统做好社会化发展、高校志愿服务组织做好项目化管理、共青团做好枢纽化整合、育人系统做好价值化引领,从而发挥有机整体的作用。     

身份与功能交互下的民间信仰景观——以青海西宁湟中县扎麻隆凤凰山为例

改革开放以后,特别是21世纪以来,“文化带动旅游,旅游搞活经济”的模式在全国已经成为常见的经济形态。在这样的大背景下,许多新建的、基于神话和民间信仰打造的旅游景观,与当地居民及海内外香客对民间信仰宗教化的理解,以及国家的宗教政策形成了一种微妙的平衡。作为一处旅游景观,扎麻隆凤凰山的九天圣都筹建于20世纪末,现已成为区域内闻名的民间信仰道场。扎麻隆凤凰山身份与功能的交互与矛盾,以及扎麻隆村权力格局对其影响无疑是值得关注和研究的现象。     

现代汉语框式结构“有X没X”的构式分析

“有X没X”是现代汉语框式结构的一种较为典型的语法构式。当前,学界的研究大多是探究“有X没Y”的句法及语用表现,而对于变项“X”属同一形式的现象尚未涉及。通过外层的形式描写和深层的语义分析,鉴别“有X没X”常规和非常规的用法,指出客观叙述性和主观评价性是区别“有X没X”常规和非常规用法的主要方法。同时,利用句法功能的差异,描绘出现代汉语中“有X没X”所有类型的特点,即“有NP没NP”“有VP没VP”“有一Q没一Q”和“有的没的”4类情况的共性及个性。另外,深入诠释转指性和描述性语义特征的不同是“有X没X”常规和非常规用法区别的关键。     

会计核算软件逆向操作的利弊分析

为了迎合财务会计的需求,软件公司开发了不少带有逆向操作功能的软件,虽然在使用中对更正会计差错、减少系统数据冗余和提高工作质量等起到了一定的作用,但同样也给财务会计系统的安全带来了威胁。这里在简略介绍会计核算软件逆向操作内涵和功能作用的基础上,针对其可能产生的隐患和危害等进行了分析,并针对其弊端和可能的风险提出了防范性完善措施。     

Fused least absolute shrinkage and selection operator for credit scoring

Credit scoring can be defined as the set of statistical models and techniques that help financial institutions in their credit decision makings. In this paper, we consider a coarse classification method based on fused least absolute shrinkage and selection operator (LASSO) penalization. By adopting fused LASSO, one can deal continuous as well as discrete variables in a unified framework. For computational efficiency, we develop a penalization path algorithm. Through numerical examples, we compare the performances of fused LASSO and LASSO with dummy variable coding.     

Moment‐Independent Sensitivity Analysis Using Copula

In risk assessment, the moment‐independent sensitivity analysis (SA) technique for reducing the model uncertainty has attracted a great deal of attention from analysts and practitioners. It aims at measuring the relative importance of an individual input, or a set of inputs, in determining the uncertainty of model output by looking at the entire distribution range of model output. In this article, along the lines of Plischke et al., we point out that the original moment‐independent SA index (also called delta index) can also be interpreted as the dependence measure between model output and input variables, and introduce another moment‐independent SA index (called extended delta index) based on copula. Then, nonparametric methods for estimating the delta and extended delta indices are proposed. Both methods need only a set of samples to compute all the indices; thus, they conquer the problem of the “curse of dimensionality.” At last, an analytical test example, a risk assessment model, and the levelE model are employed for comparing the delta and the extended delta indices and testing the two calculation methods. Results show that the delta and the extended delta indices produce the same importance ranking in these three test examples. It is also shown that these two proposed calculation methods dramatically reduce the computational burden.     

A new generalization of alpha-skew-normal distribution

In this paper, a new generalization of alpha-skew-normal distribution is considered. Some properties of this distribution, which is denoted by GASN(α, λ), including moments, maximum likelihood estimation of parameters, and some other properties are studied. Finally, using a real data set, we show that our new distribution is the best-fitted distribution for the used data among normal, skew normal, alpha-skew-normal, and skew-bimodal-normal distributions.     

全国及省际人力资本水平存量估算

估算全国和省际人力资本水平是经济增长研究所不能回避的问题。当前的研究主要采用教育年限法、物质投入法、生产函数法、人力资本回报法、人力资本特征与收入法和J-F终生收入法等六种方法。多角度比较和判别,可以验证生产函数法测算的各年相对人力资本水平较为可靠。使用生产函数法估算全国和各省的1952-2008年的人力资本存量,可刻画统一单位衡量的全国和各省人力资本水平。总体来说,全国和各省人力资本水平呈增长状态,各省人力资本存量以及增长速度存在明显差异。     

Asymptotic relative efficiency of the linear discriminant function under partial nonrandom classification of the training data

This paper considers the problem where the linear discriminant rule is formed from training data that are only partially classified with respect to the two groups of origin. A further complication is that the data of unknown origin do not constitute an observed random sample from a mixture of the two under- lying groups. Under the assumption of a homoscedastic normal model, the overall error rate of the sample linear discriminant rule formed by maximum likelihood from the partially classified training data is derived up to and including terms of the first order in the case of univariate feature data. This first- order expansion of the sample rule so formed is used to define its asymptotic efficiency relative to the rule formed from a completely classified random training set and also to the rule formed from a completely unclassified random set.