中国城镇居民消费差距的动态演进及分类决定

论文将测量个人收入分配差距的基尼系数方法引入到城镇居民消费差距的测定中。采用1992-2008年我国城镇居民各收入分组的消费数据,计算了食品、衣着、家庭设备用品及服务、医疗保健、交通通讯、文教娱乐、居住七类消费分项指标的差距及其对总消费差距的贡献,并通过反事实方法模拟分析分项指标对总体消费差异的影响。研究发现:第一,城镇居民消费差距与收入差距保持同步的发展趋势,但消费基尼系数一般小于同期收入基尼系数;第二,尽管恩格尔系数的持续下降一直成为平抑居民消费差距的最重要因素,但其对总体差距的贡献程度呈逐步弱化态势;第三,交通通讯和文教娱乐消费,尤其是前者,已逐步成为影响居民总体消费差距的重要力量;第四,虽然居民家庭设备消费差距一直高居不下,但是其对总体消费差距影响程度呈现出逐步弱化趋向。     

服务产品价格的范围与振荡收敛性研究

服务提供商占有服务创造的价值的问题必然涉及到对服务产品的定价。通过使用价格和服务量共同来描述服务价值的创造与分配,用服务产品的价格的确定来实现价值的分配,用不同的价格决定权和博弈顺序来确定服务产品的价格范围,然后寻求一种服务产品价格的振荡系统,使得服务产品的价格最终收敛于总价值创造最高的价格。     

代理人间具有竞争关系的薪酬激励机制设计

销售系统中存在着典型的信息不对称情况:委托人(公司)对代理人(销售人员)的努力程度具有不对称信息,委托人不能观测到代理人努力程度,因而常根据销售业绩来制定薪酬激励机制.本文研究销售系统中具有多个代理人且代理人之间存在竞争关系的委托代理问题.在假设市场最终需求对努力水平敏感,且某代理人努力水平提高时,他可以在开拓市场的同时,吸引对方顾客的条件下,建立了具有多代理人且代理人间存在竞争的委托代理模型.得到当努力成本、风险规避度、产出不确定性越大,代理人的风险分担越小,利润提成越低,越倾向于取得固定工资;竞争程度越高,代理人的努力程度也随之提高;利用代理人之间的竞争可以使委托人获利等结论.     

Copula函数选择对投资组合压力测试的影响分析

将在刻画变量之间相关性方面具有优势的Copula函数与能够准确评估市场极端情况的压力测试两种方法相结合,通过度量市场危机发生的期望等待时间,实证检验不同Dopula函数对投资组合压力测试结果的影响.在实证过程中,首先选择上证A股、深成A股两个市场指数作为研究样本,构造能反映单变量极值的广义帕累托边际分布,然后采用不同形式的Copula函数刻画变量之间的相关性结构,利用压力测试的方法考察Copula函数的选择对刻画投资组合风险的影响.实证检验表明,在度量两个市场同时出现危机情况的等待时间时,拟合效果较好与拟合效果较差的两种Copula函数对风险的估计存在显著的差别.这一结论表明,在压力测试的应用中引入Copula函数为组合投资风险管理指出了一个新的方向,但仍需要在描述相关性过程中慎重考虑Copula函数的选择.     

供应商管理库存环境下的分销网络连续近似模型

本文在现有连续近似(CA)模型的基础上,从供应商管理库存(VMI)角度出发,引入了PowerofTwo(POT)周期配送策略,构建了VMI环境下分销网络设计的CA模型。该模型的目标函数不仅包括了分销中心的建设 运营费用、运输费用,而且引进了实际中关注的存储费和订货费;该模型在确定分销网络结构的同时,也确定了各分销中心的库存策略和对其客户的配送策略。文中给出了模型的解法,利用此解法对算例进行求解,并分析了求解的结果,得出各参数变化对解的影响。     

生存分析与股指涨跌的概率推断

通过研究上证指数连涨连跌的收益率,发现其服从伽玛分布,并且可得出股指涨跌的条件概率,以及极值时的情况,进一步研究了成交量的影响,从而说明了技术分析特别是价量分析为何在实际中仍然被广泛运用.可认为随机游动假说是一种粗糙的近似,本研究也有助于加深对市场有效性理论的认识.     

数据驱动下收货方质量偏好与电商配送服务质量优化

针对"互联网+大数据"优化电商配送服务质量问题,明确不同收货方的质量需求稳定性,引导电商根据收货方不同质量敏感性提供相对精准服务,提升配送服务质量。模拟投票结果的形成过程聚类得到收货方对服务质量偏好的记忆性特征：（1）"无记忆"型收货方;（2）"记忆"型收货方;（3）"不确定"型收货方;（4）收货方总体。进一步推导不同规划类型求解空间,设计得到"无记忆"型收货方动态规划精确求解方法,及其他三种类型近似求解粒子群算法。研究过程中,配送资源质量感知度被嵌入到模型约束;"无记忆"型收货方的质量需求规划问题转化为零库存策略最优解问题,进而证明存在精确解;"记忆"型收货方呈现出对质量感知的累积;"不确定"型收货方模型通过赋值即可得总体收货方表达式。结果表明：数据驱动研究框架借助大数据资源,使得电商更易通过收货方的质量偏好设计更加匹配的配送方案;不确定服务需求得到有效满足,投入成本的利用率更高;通过特征分类的方式,尽可能地抽取能够精确最优化的部分,缩小NP范围,提高整体求解的精确度。     

Understanding changes in Māori incomes and income inequality 1997–2003

This paper examines recent changes in weekly income levels and dispersion for Māori, New Zealand’s indigenous ethnic group. Changes in the Māori income distribution between 1997 and 2003 reflect rapid increases in economic growth and employment rate. A reduced proportion of people had zero or benefit-level incomes and a higher proportion had high incomes. Income inequality declined for working-aged Māori and was stable for employed Māori. The average income gap between Māori and Europeans declined. The increased Māori employment rate during this period was the single most important driver of changes in the Māori income distribution.

Designing and integrating composite networks for monitoring multivariate gaussian pollution fields

Networks of ambient monitoring stations are used to monitor environmental pollution fields such as those for acid rain and air pollution. Such stations provide regular measurements of pollutant concentrations. The networks are established for a variety of purposes at various times so often several stations measuring different subsets of pollutant concentrations can be found in compact geographical regions. The problem of statistically combining these disparate information sources into a single 'network' then arises. Capitalizing on the efficiencies so achieved can then lead to the secondary problem of extending this network. The subject of this paper is a set of 31 air pollution monitoring stations in southern Ontario. Each of these regularly measures a particular subset of ionic sulphate, sulphite, nitrite and ozone. However, this subset varies from station to station. For example only two stations measure all four. Some measure just one. We describe a Bayesian framework for integrating the measurements of these stations to yield a spatial predictive distribution for unmonitored sites and unmeasured concentrations at existing stations. Furthermore we show how this network can be extended by using an entropy maximization criterion. The methods assume that the multivariate response field being measured has a joint Gaussian distribution conditional on its mean and covariance function. A conjugate prior is used for these parameters, some of its hyperparameters being fitted empirically.     

Analysis of Competing Risks by Using Bayesian Smoothing

We consider the competing risks set-up. In many practical situations, the conditional probability of the cause of failure given the failure time is of direct interest. We propose to model the competing risks by the overall hazard rate and the conditional probabilities rather than the cause-specific hazards. We adopt a Bayesian smoothing approach for both quantities of interest. Illustrations are given at the end.