软预算约束与国企改革：从要素投入的视角分析

论文运用动态模型对软预算约束的形成路径进行了理论研究,并对中国国有企业改革的路径选择进行实证研究。研究结果表明软预算约束起源于企业要素投入与生产模式的匹配模式,而中国国有企业改革路径选择的结果是使要素投入和生产模式满足弱匹配条件。     

供应链中具有产能限制的竞争企业中的信息共享研究

本文研究由一个供货商和两个制造商组成的二级供应链中，制造商之间的横向信息共享策略和供应商的定价问题。在模型中，上游供应商同时为下游两家制造商提供价格相同的原材料，下游制造商生产具有替代性的商品进行数量竞争，并受到相同的产能限制。以Cournot博弈为研究手段，求解了制造商的均衡订货决策和信息共享策略，分析比较了在不同的信息共享策略下制造商的利润、供应商的利润和批发价格。本文在研究制造商的信息共享策略时考虑了上游供应商的批发价格的影响。研究表明，当均衡解受到产能约束时，制造商的信息共享策略会反向。在某些情况下，完全信息共享和完全信息不共享都可能成为博弈的占优策略。上游供应商通过调整批发价格可以影响制造商的信息共享决策。该模型为上游供应商提供了一种最优定价策略，也为下游制造商提供了求解自身最优订货量和信息共享决策的方法。     

Performance of TOC based finite capacity material requirement planning system for a multi-stage assembly factory

This paper aims to develop a finite capacity material requirement planning (FCMRP) system based on TOC philosophy (TOC-MRP) for multi-stage assembly factory that has some bottleneck stations. The proposed TOC-MRP system tries to load and schedule operations on bottleneck stations in a manner that they are free of idle time and overtime. The schedules on non-bottleneck stations will be arranged until they are not conflicting with those on the bottleneck stations. The non-bottleneck stations are allowed to have idle time and overtime if necessary. To analyse whether TOC-MRP is effective, it is compared with a FCMRP method that does not adopt TOC philosophy. The experimental results reveal that the TOC-MRP outperforms the FCMRP without TOC philosophy.     

Establishing decision tree-based short-term default credit risk assessment models

ABSTRACT

Traditional credit risk assessment models do not consider the time factor; they only think of whether a customer will default, but not the when to default. The result cannot provide a manager to make the profit-maximum decision. Actually, even if a customer defaults, the financial institution still can gain profit in some conditions. Nowadays, most research applied the Cox proportional hazards model into their credit scoring models, predicting the time when a customer is most likely to default, to solve the credit risk assessment problem. However, in order to fully utilize the fully dynamic capability of the Cox proportional hazards model, time-varying macroeconomic variables are required which involve more advanced data collection. Since short-term default cases are the ones that bring a great loss for a financial institution, instead of predicting when a loan will default, a loan manager is more interested in identifying those applications which may default within a short period of time when approving loan applications. This paper proposes a decision tree-based short-term default credit risk assessment model to assess the credit risk. The goal is to use the decision tree to filter the short-term default to produce a highly accurate model that could distinguish default lending. This paper integrates bootstrap aggregating (Bagging) with a synthetic minority over-sampling technique (SMOTE) into the credit risk model to improve the decision tree stability and its performance on unbalanced data. Finally, a real case of small and medium enterprise loan data that has been drawn from a local financial institution located in Taiwan is presented to further illustrate the proposed approach. After comparing the result that was obtained from the proposed approach with the logistic regression and Cox proportional hazards models, it was found that the classifying recall rate and precision rate of the proposed model was obviously superior to the logistic regression and Cox proportional hazards models.     

A Discrete Variable Chain Graph for Applicants for Credit

A bank offering unsecured personal loans may be interested in several related outcome variables, including defaulting on the repayments, early repayment or failing to take up an offered loan. Current predictive models used by banks typically consider such variables individually. However, the fact that they are related to each other, and to many interrelated potential predictor variables, suggests that graphical models may provide an attractive alternative solution. We developed such a model for a data set of 15 variables measured on a set of 14 000 applications for unsecured personal loans. The resulting global model of behaviour enabled us to identify several previously unsuspected relationships of considerable interest to the bank. For example, we discovered important but obscure relationships between taking out insurance, prior delinquency with a credit card and delinquency with the loan.     

递阶双因素模型估计信用组合一致性风险

当信用组合内资产个数较少时，基于Gordy提出的粒度调节方法计算的组合风险量度VaR将严重被低估，从而高估一致性风险量度预期短缺ES。本文利用Taylor展开式改进粒度调节方法，提高估计ES的准确性；并且假设行业因素是宏观经济因素的线性函数，由此保证了组合不变性的条件，从而扩展单因素模型为递阶双因素模型，提高相关性估计准确性，解决了单因素模型高估经济资本的问题。模拟结果显示递阶双因素模型的优越性，特别是组合内资产规模较小时，改进的效果更明显。     

东道国主权信用与中国对外直接投资——基于中国与全球ODI国别面板数据的实证比较

基于2003-2012年中国与全球在42国对外直接投资ODI面板数据,分别研究发达与发展中东道国主权信用对中国ODI的影响,并与全球ODI所受影响相比较得出结论：因主权信用下降、遭遇全球ODI流出的发达国家反而越来越吸引中国ODI,对发达地区市场与战略资产的寻求驱动我国企业在此时增持资产;中国与全球ODI均规避主权信用下降的发展中国家, 我国企业也并不偏好主权信用下降的自然资源丰富国。     

碳排放约束与农业全要素生产率增长及分解

针对传统ML指数不具有传递性特征并且面临潜在线性规划无解的问题,将Global Malmquist－Luenberger生产率指数引入到农业全要素生产率的分析框架中,并利用中国31个省市1993—2013年的面板数据测算了碳排放约束条件下农业全要素生产率的增长及其分解。研究表明：是否考虑农业碳排放因素会对农业全要素生产率的测算产生较大影响,忽略碳排放约束会高估区域农业全要素生产率,测算结果可能导致政策偏误;在碳排放约束条件下,中国农业发展普遍存在效率恶化与技术进步并存的局面,农业全要素生产率增长主要由技术进步贡献,农业技术效率不增反减;中国农业全要素生产率增长存在显著的区域差异,东部地区要明显优于其他地区;中国农业大省在碳排放约束条件下未能表现出特别明显的农业优势,农业大省并非农业强省。     

问题驱动还是方法驱动——对政治科学研究中一些重要理论问题的反思

政治学的发展过程中存在许多导致学科落后的严重理论问题。作为一门并非成熟学科的政治学,要取得长足发展,首先应该正确认识政治学服务于和谐秩序构建与稳定之目的与功能,正确认识本学科的学科特性,在此基础上,选择问题驱动的研究思路,和以权力及其约束为主题的研究内容,并向外拓展,正确处理好各个理论派别与各级理论问题在纵向与横向上的关系,在各个理论孤岛之间建立起相互沟通的桥梁,互相提供理论支持,同时摒弃依赖从其他学科借用研究方法的做法,提出自己的作为成熟学科标志的核心研究方法,建构一个完整的理论体系。     

我国信用卡的现状及其发展

信用卡是一种消费信用工具 ,具有方便消费者的特点。我国的银行信用卡业务起步虽然较晚 ,但伴随着我国改革开放事业的稳步推进和国民经济的快速发展 ,我国银行信用卡业务的发展可谓突飞猛进 ,已形成较大规模 ,并发挥着一定作用。然而随着业务发展的不断深入 ,很多问题和矛盾也日益显得突出 ,迫切需要解决