OPTIMAL INVESTMENT OF A LIFE INTEREST

We consider the problem of a trustee faced with investing a sum of money, the interest from which will be received by one party (the life-tenant) during his lifetime while the capital will go to another party (the survivor) on the death of the life-tenant. We assume mat there are n + 1 assets in which the trustee may invest— n risky assets of geometric Brownian motion type and one nonrisky asset. Under assumptions as to the utility functions of the two parties, we find the collection of Pareto optimal investment strategies for the trustee together with the corresponding payoffs. We do this by optimizing the payoff of the Lagrangian for the problem. We go on to present the Nash optimal solution for the trustee.     

一种高性能CMOS带隙基准电压源的设计

本文提出了一种采用0.25μm CMOS工艺的高性能的带隙基准参考源。该电路结构简单,性能较好。用模拟软件进行仿真,在tt模型下,其温度系数为9.6 ppm/℃,电源抑制比(PSRR)为-56 dB,电压拉偏特性为384 ppm/V。而在其它模型下,也有较低的温度系数和较高的电源抑制比。     

Joining a Queue or Staying Out: Effects of Information Structure and Service Time on Arrival and Staying Out Decisions

We study a class of single-server queueing systems with a finite population size, FIFO queue discipline, and no balking or reneging. In contrast to the predominant assumptions of queueing theory of exogenously determined arrivals and steady state behavior, we investigate queueing systems with endogenously determined arrival times and focus on transient rather than steady state behavior. When arrival times are endogenous, the resulting interactive decision process is modeled as a non-cooperative n-person game with complete information. Assuming discrete strategy spaces, the mixed-strategy equilibrium solution for groups of n = 20 agents is computed using a Markov chain method. Using a 2 × 2 between-subject design (private vs. public information by short vs. long service time), arrival and staying out decisions are presented and compared to the equilibrium predictions. The results indicate that players generate replicable patterns of behavior that are accounted for remarkably well on the aggregate, but not individual, level by the mixed-strategy equilibrium solution unless congestion is unavoidable and information about group behavior is not provided.JEL Classification: C71, C92, D81     

我国出口国(区)别分布及出口增长的影响因素

本文基于1997-2008年我国对25个主要贸易伙伴出口额等面板数据建立了6个贸易引力模型,筛选出了两国首都(城市)之间贸易平均里程等10个影响贸易流量及出口增长的因素,通过对比研究,发现不同因素对我国出口流量的国别分布以及出口增长有着不同程度的影响。同时,本文给出了某一年份我国对不同贸易伙伴的名义和实际出口增长潜力的测算方法。     

我国天然气发电存在问题及对策建议

天然气发电具有能源利用效率高、环境影响小、启停灵活等优势,积极发展,有利于提高能源利用效率、保护大气环境、优化电源结构、满足电力系统调峰要求等。对我国天然气发电存在的主要问题进行了分析,提出了我国天然气发电健康有序发展的对策和措施建议。     

十二五期间中国军人保险制度发展研究

探讨十二五期间中国军人保险制度的发展,首先要明确军人保险制度发展的出发点,在此基础上明确军人保险制度发展的目标和任务,并紧紧围绕完善军人保险制度的目标任务,立足于军人保险现实情况,统筹兼顾,循序渐进,从不同层面、不同角度完善军人保险制度。具体包括：建立大病医疗保险与基本医疗保障相结合的新型军人医疗保险制度,建立军人分类养老保险制度,完善军人伤亡保险制度,建立军人互助保险等。     

The moderating effect of average wage and number of stores on private label market share: A hierarchical linear model analysis

Existing research on private label market share is primarily in the context of the Western market. The Chinese market context research is scarce, although private labels are developing rapidly in the past several years. This study investigates how the average wage and number of stores affect the Chinese market's private label market share. More importantly, this paper examines the moderating effect of the average wage and the number of stores on the relationship between the private label market share and product assortment as well as the relationship between the private label market share and pricing. Data collected from a Chinese supply chain dyad is analyzed to study category management using hierarchical linear models. The results reveal that the average wage and the number of stores positively affect the private label market share. Furthermore, the average wage enhances the negative effect of the number of brands, weakens the negative effect of the private label price, weakens the positive effect of national brand price. Meanwhile, the number of stores enhances the positive effect of the SKU proliferation of private label, enhances the negative effects of the number of brands, and enhances the negative effect of the private label price. This study contributes to category management. Furthermore, the findings will be valuable to domestic and international grocery marketers and retailers operating private labels in China.     

新一代车险“理赔难”

保险作为现代服务行业之一,服务质量问题始终贯穿其中。其中,“理赔难”的现象层出不穷。从1929年11月在中国上海成立第一家保险公司太平保险,到目前保险行业已发展90余年,中国的车险理赔还难吗?依然难,只是难点变了,老矛盾得到部分解决,新矛盾层出不穷,唯独对理赔服务质量的评价参差不齐是永恒的。     

Estimating the potential impact of requiring a stand-alone board-level risk committee

Motivated by the requirement under the Dodd-Frank Act that all large bank holding companies create a stand-alone, board-level risk committee, this paper investigates the association between such a committee and regulatory risk both before and during the financial crisis. I focus the analysis on the set of banks that did not have a risk committee in place prior to the Dodd-Frank Act, as these are the banks that were most affected by the regulation. I find that matched control banks with a risk committee in place had higher capital ratios during the financial crisis, but lower capital ratios during more stable economic conditions relative to the banks without a risk committee. This paper contributes to the literature by narrowly investigating the effects a board-level risk committee, by focusing on a risk measure that is of interest to the regulators who implemented the new regulation, and by documenting that this association changes over time which highlights the importance of estimating the effects of new regulations across different economic conditions.     

Using machine learning and big data for efficient forecasting of hotel booking cancellations

Cancellations are a key aspect of hotel revenue management because of their impact on room reservation systems. In fact, very little is known about the reasons that lead customers to cancel, or how it can be avoided. The aim of this paper is to propose a means of enabling the forecasting of hotel booking cancellations using only 13 independent variables, a reduced number in comparison with related research in the area, which in addition coincide with those that are most often requested by customers when they place a reservation. For this matter, machine-learning techniques, among other artificial neural networks optimised with genetic algorithms were applied achieving a cancellation rate of up to 98%. The proposed methodology allows us not only to know about cancellation rates, but also to identify which customer is likely to cancel. This approach would mean organisations could strengthen their action protocols regarding tourist arrivals.