STOCHASTIC COST-VOLUME-PROFIT ANALYSIS WITH A LINEAR DEMAND FUNCTION

In this paper we incorporate a linear demand function to model the price-volume causal relationship into stochastic cost-volume-profit (CVP) analysis. We assume that the objective function is to maximize expected profit; other objective functions are also discussed and compared. A linear stochastic model follows from which probabilistic statements can be easily obtained if the random variables are assumed to be multivariate normal. The basic framework is shown to be a special case of project value maximization where project value is the cash flow of the project discounted for time and risk according to the capital asset pricing model. Moreover, an intertemporal extension that considers inventory is developed. In summary, a new approach to stochastic CVP analysis that incorporates the management decision process in an uncertain environment is developed.     

The declining significance of race among American men during The latter half of the twentieth century

The extent to which racial minority groups face discrimination in the labor market is the subject of considerable debate. Using William J. Wilson's thesis of the declining significance of race as our theoretical context, we provide further empirical evidence about labor market discrimination by investigating wages among African American, American Indian, Chinese American, Hispanic white, Japanese American, and non-Hispanic white men. We find, during the period before the civil rights movement, that a substantively significant wage disadvantage is evident for these minority groups with controls for observed labor force characteristics. In recent data, these net disadvantages are reduced substantially for each of these groups except Hispanics. With the exception of Hispanics, the results support Wilson's thesis.     

控股股东与经营者一体化存在的问题及其治理

文章通过对控股股东与高层管理者的关联性描述,指出了控股股东与经营者的一体化趋势;然后从产权理论、交易费用理论和控制权收益三个角度对这种趋势进行原因分析;最后针对一体化带来的负面影响提出相应的对策。     

Exploitation in Contemporary Capitalism: An Empirical Analysis of the Case of Taiwan

Abstract

Using data for manufacturing firms in Taiwan, we developed a measure of exploitation and analyzed its prevalence in the labor force. Our results indicated that almost two-thirds of the firms in our sample exploit at least some of their workers. For these firms, the average profit rate is 34 percent, but three-fourths of this figure derives from the expropriated wages of their workers. Female and blue-collar workers are the largest groups that are underpaid relative to their productivity (that is, exploited). Managers, professionals, and workers with seniority are not exploited by our definition because our data showed that these groups are paid according to the market value of their productivity, at least on average. Our analysis demonstrates the feasibility of the empirical investigation of exploitation, which should be further considered in future research.     

一类图的优美性

本文考虑Mobius带上格子图的优美性问题，证明了M（n，2）是优美图．     

单顶边星图的优美性

在齿轮图的每个齿的齿顶分别加上一条悬挂边后构成的图称为单顶边星图，本文证明了单顶边星图是优美图，补充了文（２）的结果，从而彻底解决了文（１）的猜想。     

基于技术多样性的专利申请人与审查员的引证行为差异

近年来,专利引文越来越多地被用于技术路径研究、技术会聚、技术扩散等技术领域间的知识活动研究,但并未有效区分申请人引用和审查员引用,现有技术领域层面对申请人和审查员引用差异的对比研究还停留在较为浅显的统计层面。将技术类别间的差异性引入到申请人引用和审查员引用的对比研究中,在技术类别分布基础上,探究专利技术类别多样性视角下申请人引用和审查员引用的知识来源差异,并对其开展相关性分析。研究结果表明:专利申请人引用涉及的技术类别范围更广,而审查员引用则更集中于本技术类别;对大部分技术类别,申请人引用的技术类别多样性要高于审查员引用,但两者呈现出显著的正相关性。     

Estimate of variance of u-statistics

Let g(x₁,… , x_k) be a symmetric function with k arguments. Let U be a U-statistic based on a random sample of size n with kernel function g . In this paper, the problem of estimating var(U) is considered. Several estimators are compared by computer simulations and we conclude that two estimators, one is constructed as a U-statistic and the other is the bootstrap estimator, give good estimates for many U-statistics.     

Likelihood-based cross-validation score for selecting the smoothing parameter in maximum penalized likelihood estimation

Maximum penalized likelihood estimation is applied in non(semi)-para-metric regression problems, and enables us exploratory identification and diagnostics of nonlinear regression relationships. The smoothing parameter A controls trade-off between the smoothness and the goodness-of-fit of a function. The method of cross-validation is used for selecting A, but the generalized cross-validation, which is based on the squared error criterion, shows bad be¬havior in non-normal distribution and can not often select reasonable A. The purpose of this study is to propose a method which gives more suitable A and to evaluate the performance of it.

A method of simple calculation for the delete-one estimates in the likeli¬hood-based cross-validation (LCV) score is described. A score of similar form to the Akaike information criterion (AIC) is also derived. The proposed scores are compared with the ones of standard procedures by using data sets in liter¬atures. Simulations are performed to compare the patterns of selecting A and overall goodness-of-fit and to evaluate the effects of some factors. The LCV-scores by the simple calculation provide good approximation to the exact one if λ is not extremeiy smaii Furthermore the LCV scores by the simple size it possible to select X adaptively They have the effect, of reducing the bias of estimates and provide better performance in the sense of overall goodness-of fit. These scores are useful especially in the case of small sample size and in the case of binary logistic regression.