Nonparametric test for the homogeneity of the overall variability

In this paper, we propose a nonparametric test for homogeneity of overall variabilities for two multi-dimensional populations. Comparisons between the proposed nonparametric procedure and the asymptotic parametric procedure and a permutation test based on standardized generalized variances are made when the underlying populations are multivariate normal. We also study the performance of these test procedures when the underlying populations are non-normal. We observe that the nonparametric procedure and the permutation test based on standardized generalized variances are not as powerful as the asymptotic parametric test under normality. However, they are reliable and powerful tests for comparing overall variability under other multivariate distributions such as the multivariate Cauchy, the multivariate Pareto and the multivariate exponential distributions, even with small sample sizes. A Monte Carlo simulation study is used to evaluate the performance of the proposed procedures. An example from an educational study is used to illustrate the proposed nonparametric test.     

以帕累托最优为标准的效率与公平问题的分析

以帕累托标准为基础的关于效率与公平的理论是西方经济学重要的理论。帕累托标准不过是为资本主义生产资料私有制和资产阶级统治披上合理的外衣,表明资本主义私有制的经济制度和阶级差别是公平与效率矛盾问题的根源。只有消除阶级差别和权利差别,以人民的利益为根本出发点,才能实现效率与公平的统一。     

国际气候基金的资金筹集与资金分配的理论探索——兼顾全球帕累托最优与财政收支平衡分析

通过构建数理模型，文章分析了国际气候基金应该如何筹集和分配资金，才能同时实现全球气候治理的帕累托最优与自身的财政收支平衡。为此，首先，构建全球气候治理的帕累托最优模型与市场均衡模型，并分别求得帕累托最优实现条件和市场均衡条件；其次，比较二者，求得使市场均衡结果实现全球帕累托最优的唯一的价格条件；紧接着，在该价格条件的基础上，纳入财政收支平衡的考虑，进而推导出兼顾全球帕累托最优与财政收支平衡下的国际气候基金的资金筹集与资金分配所需要遵循的唯一规则；在此基础上，给出了兼顾全球帕累托最优与财政收支平衡下的国际气候基金的资金筹集与资金分配的全部可选方案；最后，提出了逐步推进国际气候基金建设的政策建议。文章的创新有两点：对Baumol和Oates构建的公共外部性模型的假设条件进行修正，从而使本文的结论更加适合于全球气候治理分析；推导得出同时实现全球帕累托最优和国际气候基金收支平衡的唯一价格条件。     

市场失灵：传统分析与现代解释

经济学家在肯定市场制度的效率的同时,从未停止过对“市场失灵”问题的关注。对有关“市场失灵”的传统理论和现代思想进行比较分析,从中可看出现代经济学在理论范式和政策范式上的一些变化,对中国市场经济的发展不无启示。     

基于Pareto Optimality的PPP项目三大主参与方效用探讨

在PPP项目的众多参与方中,选取项目发起人、SPC和贷款银行三个最主要的参与方,通过分析项目发起人与SPC、SPC与贷款银行和贷款银行与项目发起人之间的内在联系,在Pareto Optimality理论分析的基础上,得到三者之间两两优势互补的埃奇沃思方框图,并根据瓦尔拉斯均衡理论得出PPP项目能够实现帕累托最优,实现项目效用的最大化,最后拟画出PPP项目三大主参与方的效用可能性曲线。     

基于产品卖方市场的劳工标准移植研究

市场竞争促使越来越多发展中国家企业成为劳工认证供应链的一部分。劳工标准借助于贸易平台移植到中国,对中国劳工条件甚至劳工法律制度都产生一定影响,但对现实情况的分析发现其影响还处于初级阶段。基于产品卖方主导型市场结构,采用信号模型研究中国劳工标准移植的微观机理时发现,供应商的劳工标准趋于最低要求水平是供应商借助卖方市场势力帕累托改进的结果;当公司类型的概率分布函数为凹函数时,劳工标准会收敛到最低点均衡,而非高于最低点。发展中国家处于卖方主导型市场的企业要利用劳工标准移植契机,内在提高劳工条件,让劳工信号带动产品质量提高,为更多采购商和消费者接受,以获得更大的市场势力。     

最优司法判决结果的博弈解读——兼及法律方法的可操作性

最优判决结果应为司法活动永恒的最高追求.从博弈论的视角解读,最优的司法判决结果应当是一个合法的、具有可接受性的而且实现了利益最大化的判决结果,亦即纳什均衡基础之上帕累托最优的实现.为达到这一目标,法官在视角选择时应站在"局内的局外人"的立场,而在实际操作时采取"无为的独裁者"的策略.通过这一问题的分析还表明,法律方法应具有可操作性,并且应将其作为法律方法研究进一步深入拓展的突破点与基本目标之一.     

Bayesian Inference Using Artificial Augmenting Regressions

In this article, it is shown that many intractable problems of Bayesian inference can be cast in a form called “artificial augmenting regression” in which application of Markov Chain Monte Carlo techniques, especially Gibbs sampling with data augmentation, is rather convenient. The new techniques are illustrated using several challenging statistical problems and numerical results are presented.     

Shared frailty models with baseline generalized Pareto distribution

Abstract

In this article, we have considered three different shared frailty models under the assumption of generalized Pareto Distribution as baseline distribution. Frailty models have been used in the survival analysis to account for the unobserved heterogeneity in an individual risks to disease and death. These three frailty models are with gamma frailty, inverse Gaussian frailty and positive stable frailty. Then we introduce the Bayesian estimation procedure using Markov chain Monte Carlo (MCMC) technique to estimate the parameters. We applied these three models to a kidney infection data and find the best fitted model for kidney infection data. We present a simulation study to compare true value of the parameters with the estimated values. Model comparison is made using Bayesian model selection criterion and a well-fitted model is suggested for the kidney infection data.     

Choice experiments for estimating main effects and interactions

Choice-based conjoint experiments are used when choice alternatives can be described in terms of attributes. The objective is to infer the value that respondents attach to attribute levels. This method involves the design of profiles on the basis of attributes specified at certain levels. Respondents are presented sets of profiles and asked to select the one they consider best. However if choice sets have too many profiles, they may be difficult to implement. In this paper we provide strategies for reducing the number of profiles in choice sets. We consider situations where only a subset of interactions is of interest, and we obtain connected main effect plans with smaller choice sets that are capable of estimating subsets of two-factor and three-factor interactions in 2ⁿ and 3ⁿ plans. We also provide connected main effect plans for mixed level designs.