Parametric aggregation in ordered weighted averaging

Incorporating further information into the ordered weighted averaging (OWA) operator weights is investigated in this paper. We first prove that for a constant orness the minimax disparity model [13] has unique optimal solution while the modified minimax disparity model [16] has alternative optimal OWA weights. Multiple optimal solutions in modified minimax disparity model provide us opportunity to define a parametric aggregation OWA which gives flexibility to decision makers in the process of aggregation and selecting the best alternative. Finally, the usefulness of the proposed parametric aggregation method is illustrated with an application in metasearch engine.     

OPTIMAL HARVEST FEEDBACK RULE ACCOUNTING FOR THE FISHING‐UP EFFECT AND SIZE‐DEPENDENT PRICING

Abstract Fishing leads to truncation of a population's age and size structure. However, large‐sized fish are usually more valuable per unit weight than small ones. Nevertheless, these size‐related factors have mostly been ignored in bioeconomic modeling. Here, we present a simple extension to the Gordon–Schaefer model that accounts for variations in mean individual catch weight, and derive the feedback rule for optimal harvest in this setting. As the Gordon–Schaefer model has no population structure, size effects have to be accounted for indirectly. Here we assume a simple negative relationship between fishing effort and mean individual weight, and a positive relationship between mean catch weight and price. The aim is to emulate alterations of size structure in fish populations due to fishing and the influence of size on price per weight unit and eventually, net revenues. This demonstrates, on a general level, how such size‐dependent effects change the patterns of optimal harvest paths and sustainable revenue in single fish stocks. The model shows clear shifts toward lower levels of optimal effort and yield compared to classical models without size effects. This suggests that ignoring body size could lead to misleading assumptions and policies, potentially causing rent dissipation and suboptimal utilization of renewable resources.     

能源节约型技术进步下碳关税对中国经济与环境的影响——基于动态递归可计算一般均衡模型

将动态递归的可计算一般均衡方法应用于碳关税征收影响的研究,建立了测算美国征收碳关税对中国经济与环境影响的动态递归可计算一般均衡模型,并在模型中引入技术进步参数以刻画能源节约型技术进步.模型以2007年作为基年,包含37个生产部门和7个国内国外账户.应用该模型模拟了2020年起美国征收碳关税,在税率从20美元每吨碳排放到80美元每吨碳排放的13种情景下,到2030年期间对我国碳排放和经济发展的不同影响,进而测算在不同的能源节约型技术进步条件下,碳关税对我国经济与环境影响的变动.     

基于未确知测度理论的工业企业经济效益评价

介绍了工业企业经济效益评价的经济指标,建立了基于未确知测度理论的多属性综合评价方法.在确定各评价对象的属性权重时,采用熵值法这一客观性方法来确定.通过实例,将这种方法应用于具体的工业企业经济效益的评价,为评价企业经济效益提供了一种量化处理的方法,从而能够更直观、更合理地分析评价企业的经济效益状况.     

甘肃省物流业与经济发展的协调性评价分析

介绍了甘肃省物流业的实际状况,其次建立了甘肃省经济发展和甘肃省物流业发展的二级评价指标体系,运用基于方差加权法与熵值法相结合的综合赋权法的非线性评价模型分别对甘肃省经济发展的综合实力和物流业发展的综合实力进行评价.最后基于回归和隶属度函数相结合的方法,运用物流业和经济发展的综合实力评价结果分析计算甘肃省物流系统与经济系统的协调测度,根据计算的测度绘制散点图,对甘肃省物流系统与经济系统的协调度进行分析评价.     

中智自由贸易协定全面实施对双方经济影响研究:基于GTAP模型仿真

基于GTAP模型,结合Walmsley等递归动态法,就《中智自由贸易协定》全面实施对双方在贸易规模、贸易结构、双边贸易、GDP、生产格局和福利水平等方面产生的经济效应进行仿真.研究结果显示,双方贸易规模及产出水平明显扩大;国内资源分配格局有所改变,贸易结构处于较快的变动中;两国GDP有所增长,双边贸易显著增强,社会福利明显改善;中国贸易条件相对恶化,农产品所受负面冲击有限,高级化服务业发展迅速;智利制造业受益匪浅,产业结构趋于相对平衡;双方利益让渡不一致,福利所得分配不等,智利所受的经济影响要明显大于中国,而中国的动态比较利益会使其福利所得明显高于智利.     

中国区域就业结构与区域收入差异的实证研究—基于panel-data模型

运用面板数据模型(Panel-data Model)分析了直辖市、东中西部三大产业的就业结构对区域收入差异的影响,不同区域的就业结构对区域的收入差异影响不同,针对不同区域情况,提出了协调发展产业,调整产业就业结构.促使区域差异缩小的政策建议.     

A point‐input,point‐output forest as a microprototype for capital accounting

The point‐input, point‐output, plantation forest was first studied by Martin Faustmann in the mid‐19th century. The exploitation of a Faustmannian forest involves decisions concerning investments and receipts over time that are qualitatively different from the smooth, convex flows that are usually studied in the economics of accounting. The simple, well understood analysis of the forest has implications for the concept of income in forestry as well as in other industries that are typified by nonconvex decisions. A forest is a salient example of the importance of discrete, irreversible investment, and of the role of price effects (capital gains) in income accounting and, more fundamentally, of perceptions of the “right prices” in economic analysis.     

The maximum surplus in a finite‐time interval for a discrete‐time risk model with exchangeable,dependent claim occurrences

This paper investigates a discrete‐time risk model that involves exchangeable dependent loss generating claim occurrences and compound binomially distributed aggregate loss amounts. First, a general framework is presented to derive the distribution of a surplus sequence using the model. This framework is then applied to obtain the distribution of any function of a surplus sequence in a finite‐time interval. Specifically, the distribution of the maximum surplus is obtained under nonruin conditions. Based on this distribution, the computation of the minimum surplus distribution is given. Asset and risk management–oriented implications are discussed for the obtained distributions based on numerical evaluations. In addition, comparisons are made involving the corresponding results of the classical discrete‐time compound binomial risk model, for which claim occurrences are independent and identically distributed.     

Random field Ising model and community structure in complex networks

We propose a method to determine the community structure of a complex network. In this method the ground state problem of a ferromagnetic random field Ising model is considered on the network with the magnetic field B_s = +∞, B_t = -∞, and B_i≠s,t=0 for a node pair s and t. The ground state problem is equivalent to the so-called maximum flow problem, which can be solved exactly numerically with the help of a combinatorial optimization algorithm. The community structure is then identified from the ground state Ising spin domains for all pairs of s and t. Our method provides a criterion for the existence of the community structure, and is applicable equally well to unweighted and weighted networks. We demonstrate the performance of the method by applying it to the Barabási-Albert network, Zachary karate club network, the scientific collaboration network, and the stock price correlation network. (Ising, Potts, etc.)