收入分配、产权保护与社会冲突: 现代经济学视角下的冲突管理与和谐社会构建

以群体性事件为代表的社会冲突现象越来越成为当下社会聚焦的问题。在现代经济学的视角下详解冲突的发生机制和化解方法,通过将精英和社会大众这两个阶层之间的冲突行为纳入到以博弈论为基础的分析框架内构建模型分析,进而发现,产权保护的加强和收入分配的改善都会减少群体性冲突行为的发生,反之,两者同时恶化往往是冲突爆发的重要潜在原因。在一定范围内,精英通过改善收入分配可以同时改善双方的收入情况,以达到帕累托改进,这在一定程度上为政府打开了施政的空间。从长远看,产权保护的加强和收入分配的改善不仅是构建完善的社会稳定机制的微观基础,也是社会大众实现中国梦的保障。     

A Latent Process Model for Temporal Extremes

This paper presents a hierarchical approach to modelling extremes of a stationary time series. The procedure comprises two stages. In the first stage, exceedances over a high threshold are modelled through a generalized Pareto distribution, which is represented as a mixture of an exponential variable with a Gamma distributed rate parameter. In the second stage, a latent Gamma process is embedded inside the exponential distribution in order to induce temporal dependence among exceedances. Unlike other hierarchical extreme‐value models, this version has marginal distributions that belong to the generalized Pareto family, so that the classical extreme‐value paradigm is respected. In addition, analytical developments show that different choices of the underlying Gamma process can lead to different degrees of temporal dependence of extremes, including asymptotic independence. The model is tested through a simulation study in a Markov chain setting and used for the analysis of two datasets, one environmental and one financial. In both cases, a good flexibility in capturing different types of tail behaviour is obtained.     

基于马尔可夫链的间歇性购买个体客户终生价值预测模型

随着市场竞争的日益激烈,客户的购买行为呈现出个体化和间歇性的特征,如何对此类间歇性购买个体客户的赢利性进行预测进而合理分配营销资源是当前亟待解决的一个重要问题.首先根据马尔可夫链的理论构造了间歇性购买个体客户的购买马尔可夫链,并利用马尔可夫链的转移矩阵得出该类客户全部剩余终生价值预测公式;其次,对终生价值预测公式中的参数(如个体客户在未来时间活跃度、个体客户在未来时间购买概率、个体客户在未来时间购买次数、个体客户在未来时间购买量等)进行了确定;最后,利用Matlab程序对济南市某IT分销商的客户交易数据进行了实证分析,从而证明了本预测模型的有效性和实用性.     

Confidence intervals based on L-moments for quantiles of the GP and GEV distributions with application to market-opening asset prices data

In a ground-breaking paper published in 1990 by the Journal of the Royal Statistical Society, J.R.M. Hosking defined the L-moment of a random variable as an expectation of certain linear combinations of order statistics. L-moments are an alternative to conventional moments and recently they have been used often in inferential statistics. L-moments have several advantages over the conventional moments, including robustness to the the presence of outliers, which may lead to more accurate estimates in some cases as the characteristics of distributions. In this contribution, asymptotic theory and L-moments are used to derive confidence intervals of the population parameters and quantiles of the three-parametric generalized Pareto and extreme-value distributions. Computer simulations are performed to determine the performance of confidence intervals for the population quantiles based on L-moments and to compare them to those obtained by traditional estimation techniques. The results obtained show that they perform well in comparison to the moments and maximum likelihood methods when the interest is in higher quantiles, or even best. L-moments are especially recommended when the tail of the distribution is rather heavier and the sample size is small. The derived intervals are applied to real economic data, and specifically to market-opening asset prices.     

Coordination of Supply Chains with Risk‐Averse Agents

The extant supply chain management literature has not addressed the issue of coordination in supply chains involving risk‐averse agents. We take up this issue and begin with defining a coordinating contract as one that results in a Pareto‐optimal solution acceptable to each agent. Our definition generalizes the standard one in the risk‐neutral case. We then develop coordinating contracts in three specific cases: (i) the supplier is risk neutral and the retailer maximizes his expected profit subject to a downside risk constraint; (ii) the supplier and the retailer each maximizes his own mean‐variance trade‐off; and (iii) the supplier and the retailer each maximizes his own expected utility. Moreover, in case (iii), we show that our contract yields the Nash Bargaining solution. In each case, we show how we can find the set of Pareto‐optimal solutions, and then design a contract to achieve the solutions. We also exhibit a case in which we obtain Pareto‐optimal sharing rules explicitly, and outline a procedure to obtain Pareto‐optimal solutions.     

“剩女”婚配困境的生成、限度及突破：一种博弈视角

当代“剩女”队伍不断壮大,越来越引发众多学者的关注,女性在职业复出与婚姻回归之间的心理纠结,加剧了女性婚恋的紧张。文章从博弈视角切入,得出女性依据传统婚配机制与诉求取向进行婚配博弈,形成一种婚配困境的纳什均衡。婚配帕累托改进可以在“剩女”数量激增与婚配市场失效的情况下实现,可以从婚配梯度与错位中转变,促使两性交往方式与取向进行调整。     

Mitigating the U.S. Drug Shortages Through Pareto‐Improving Contracts

Drug shortages have been a major challenge facing the US pharmaceutical industry and government in recent years. Although the problem has drawn tremendous attention from the government and media, limited academic research has been devoted to this problem, and few solutions have been proposed based on rigorous research. This study addresses the drug shortage problem from a supply chain perspective, a key aspect missing in the literature, and proposes to mitigate shortages through drug purchase contracts. By modeling the drug supply chain, we capture the objectives of various supply chain parties, and investigate Pareto‐improving contracts that mitigate drug shortages, improve drug manufacturer's and group purchasing organization (GPO)'s profits, and cut government spending and healthcare providers’ costs. We explore structural properties of key supply chain decisions and the Pareto‐improving contracts, and conduct scenario analysis with realistic industry data to evaluate shortage mitigation solutions. Our analysis shows that increasing drug prices only, a solution advocated by many, is not very effective in shortage mitigation. Price increases must be paired with strengthened failure‐to‐supply clauses (called the IPS approach) to achieve consistent and significant shortage reduction as well as Pareto improvement. Across all scenarios tested, a 30% price increase under IPS can lead to a minimum, average, and maximum shortage reduction of 25%, 53%, and 70%, respectively. Our analysis also shows the impacts of IPS on different parties in the supply chain and the impacts of various model parameters on shortage mitigation. The IPS approach rewards reliability of drug supply, which is in line with the FDA's strategic plan to reward quality, but is easier to achieve in this regulation‐based industry. Interactions with the government and industry practitioners indicate that IPS also challenges the current mindset in pharmaceutical contracting.     

Improving extreme quantile estimation via a folding procedure

In many applications (geosciences, insurance, etc.), the peaks-over-thresholds (POT) approach is one of the most widely used methodology for extreme quantile inference. It mainly consists of approximating the distribution of exceedances above a high threshold by a generalized Pareto distribution (GPD). The number of exceedances which is used in the POT inference is often quite small and this leads typically to a high volatility of the estimates. Inspired by perfect sampling techniques used in simulation studies, we define a folding procedure that connects the lower and upper parts of a distribution. A new extreme quantile estimator motivated by this theoretical folding scheme is proposed and studied. Although the asymptotic behaviour of our new estimate is the same as the classical (non-folded) one, our folding procedure reduces significantly the mean squared error of the extreme quantile estimates for small and moderate samples. This is illustrated in the simulation study. We also apply our method to an insurance dataset.     

耕地抛荒与农地流转的经济学解读——农民土地权益保护的制度寻求

探讨了耕地抛荒何以是一种理性人思维。在此基础上,指出耕地抛荒与农地流转都是在特定条件下农民追求资源配置的帕累托改进的理性选择。基于帕累托改进的原理,提出在完善以政府的农地流转服务链为制度保障的基础上重构城乡相互哺育的良性关系的制度寻求方案。