消费品生命周期隐患识别与风险评价的三维矩阵方法

面对近年我国产品质量安全事故频发、消费者人身安全与健康遭受不同程度的威胁以及出口产品不时被召回或退回的问题,给出了一种基于消费品生命周期和事故致因的隐患识别及表征方法,有助于提升人们对消费品危害规律的认知水平并为消费品风险评价奠定基础. 考虑到事故伤害受体的能力和行为会对消费品缺陷或隐患演化及事故伤害后果产生重要影响,在常规风险评价二维矩阵的基础上,加入风险受体的脆弱性要素,提出了消费品风险评价的三维矩阵方法,能够更好地表征消费者能力与行为等主观要素对消费品隐患事故及危害的影响作用. 以家用电器风险评价为例,基于欧盟非食品类消费品快速预警系统（RAPEX）对中国消费品通报信息分析和专家评价打分,形成了消费品评价三维风险矩阵,分析了家用电器的风险规律,为消费品的风险评价提供了新思路、新方法.     

基于效用的公司证券定价与资本结构选择

考虑到市场的不完备性,本文基于效用无差别定价原理,研究公司证券主观价值,分析最优资本结构,计算最优破产触发水平. 本文发现：1)对于给定的债券发行量,随着非系统风险增加,股权主观价值逐渐减小,财务杠杆逐渐增大,这一结果与完备市场相反;2) 与完备市场下资本结构相比,非完备市场下最优财务杠杆较小,债权的收益率溢价较大;3)股权的系统风险和非系统风险溢价随着公司收益流增加而减少;4) 投资者的风险态度和非系统风险对破产选择、股权和债权的主观价值有显著影响.     

探析新产品开发中影响因素的作用大小——论技术创新度的调节作用

从企业内部可控因素出发,具体从企业管理层行为、跨部门协同行为以及各部门具体操作行为等三个层次探讨高级管理层支持、跨部门目标一致性以及各部门早期参与对新产品开发的积极作用。并分析在不同技术创新程度对这三大积极因素作用效果的影响。结果表明,在创新程度高的情况下,高级管理层支持对新产品开发的促进作用减弱,跨部门目标一致性和各部门早期参与对其的积极作用增强。本文在此基础上提出6个命题,构建了概念模型。     

南开大学生物实验教学中心实验技术队伍的现状与建设

实验室是知识创新和高层次人才培养的基地，而实验技术人员队伍建设是实验室建设和提高实验教学质量的保证。高素质、稳定的实验室技术队伍也是当前教育事业发展的要求。通过对南开大学生物实验教学中心的现状与实验技术队伍的分析，来探讨关于实验技术队伍的建设问题。     

多米诺骨牌理论中的人为失误与风险管理(英文)

通过介绍多米诺骨牌理论在风险管理中的作用原理,提出海事风险管理应主要以控制人为失误为主的观点,深入分析人为失误的原因,提出控制人为失误的方法,总结多米诺骨牌理论的优缺点.     

产学研协同发展、知识积累与技术创新效率——基于动态面板门限机理实证分析

基于产学研耦合协调度测度模型、数据包络分析模型以及动态面板门限回归模型,运用2013～2017年中国30个省市的面板数据,研究以知识积累为门限变量时,产学研协同发展水平对区域技术创新效率产生的影响.实证结果表明:当以知识积累水平为门限变量时,产学研协同发展水平与技术创新效率间存在明显的双门限效应;随着知识积累水平的提升...     

Forecasting with Micro Panels: The Case of Health Care Costs

Micro panels characterized by large numbers of individuals observed over a short time period provide a rich source of information, but as yet there is only limited experience in using such data for forecasting. Existing simulation evidence supports the use of a fixed‐effects approach when forecasting but it is not based on a truly micro panel set‐up. In this study, we exploit the linkage of a representative survey of more than 250,000 Australians aged 45 and over to 4 years of hospital, medical and pharmaceutical records. The availability of panel health cost data allows the use of predictors based on fixed‐effects estimates designed to guard against possible omitted variable biases associated with unobservable individual specific effects. We demonstrate the preference towards fixed‐effects‐based predictors is unlikely to hold in many practical situations, including our models of health care costs. Simulation evidence with a micro panel set‐up adds support and additional insights to the results obtained in the application. These results are supportive of the use of the ordinary least squares predictor in a wide range of circumstances. Copyright © 2016 John Wiley & Sons, Ltd.     

The US Dollar/Euro Exchange Rate: Structural Modeling and Forecasting During the Recent Financial Crises

The paper investigates the determinants of the US dollar/euro within the framework of the asset pricing theory of exchange rate determination, which posits that current exchange rate fluctuations are determined by the entire path of current and future revisions in expectations about fundamentals. In this perspective, we innovate by conditioning on Fama–French and Carhart risk factors, which directly measures changing market expectations about the economic outlook, on new financial condition indexes and macroeconomic variables. The macro‐finance augmented econometric model has a remarkable in‐sample and out‐of‐sample predictive ability, largely outperforming a standard autoregressive specification. We also document a stable relationship between the US dollar/euro Carhart momentum conditional correlation (CCW) and the euro area business cycle. CCW signals a progressive weakening in economic conditions since June 2014, consistent with the scattered recovery from the sovereign debt crisis and the new Greek solvency crisis exploded in late spring/early summer 2015. Copyright © 2016 John Wiley & Sons, Ltd.     

Forward Rates,Monetary Policy and the Economic Cycle

The short end of the yield curve incorporates essential information to forecast central banks' decisions, but in a biased manner. This article proposes a new method to forecast the Fed and the European Central Bank's decision rate by correcting the swap rates for their cyclical economic premium, using an affine term structure model. The corrected yields offer a higher out‐of‐sample forecasting power than the yields themselves. They also deliver forecasts that are either comparable or better than those obtained with a factor‐augmented vector autoregressive model, underlining the fact that yields are likely to contain at least as much information regarding monetary policy as a dataset composed of economic data series. Copyright © 2015 John Wiley & Sons, Ltd.