投保人与保险人博弈关系分析

博弈论是研究信息不对称问题的一种有效方法 ,其广泛应用于军事、政治、经济等领域。保险业作为信息不对称最为集中的行业 ,投保人与保险人之间的信息不对称现象尤为突出 ,道德风险也极易发生。如何用博弈理论与方法分析这些信息不对称问题 ,并据此提出切实可行的解决方法 ,已成为保险界日益关注的问题。     

道德的成本收益分析

利益为道德本质的内容 ,趋利行为是道德行为发生的机制。守德成本与收益 ,既有有形和无形的 ,也有个体和社会的。守德行为是其成本与收益关系权衡的结果。进行道德成本收益分析的目的在于建立有效的国家或社会、公民的道德机制。     

优化教育环境 发挥德育功能

德育与环境之间存在着紧密的联系,环境对于激发和形成个人的行为方式有很大影响.学校应不断建设、创造良好的教育环境,使德育教育收到更大的成效.     

存款保险法律制度利弊之研究

存款保险法律制度是直接针对银行挤兑和破产倒闭而设计的,目的在于保护存款人的利益,增强公众对银行体系的信心,减少挤兑的可能性。我国建立该制度,将有利于维护金融安全,营造公平竞争的市场环境,完善银行的退出机制,从而提高金融业的效率。     

Genetic risk and value

A conceptual truth about risks is that they involve a possible and future adverse effect or a negative value of some kind. The genetic risks that individuals may face in the health care setting differ in some crucial respects to other kind of risks. The aims of this paper are to analyse the notion of value in the context of genetic risk in the setting of health care, and to suggest a conception of the evaluative aspect of genetic risk that is fruitful for genetic risk information. Two influential and relevant approaches to value, preferentialism and the capability approach, are discussed in the light of certain distinctive features of genetic risk and a third, a sensibility theory of value is suggested. According to this view, the concept of risk is a so-called ‘thick’ evaluative concept that has both a world-guiding function as well as an action-guiding or normative function. It is argued that this provides a more promising way to think about genetic risks in the clinical setting.     

多重委托代理下医生最优激励模型设计探究

"过度医疗"即指超过疾病实际需求的诊断和治疗的行为。医疗服务的特殊性,使患者、医生、监督方之间存在信息不对称和多重委托代理关系。鉴于此,从政府的第三方监督职能出发,将政府和患者作为共同委托人,避免政府与医院之间道德风险的发生,构建医生作为代理人的最优激励模型,并得出相关结论与启示。     

试析德沃金对司法能动主义的批判——宪法解释视角

德沃金的法律解释学说是本世纪重要的法律学说,其宪法的道德解释是不同于司法能动主义支持者解释路径,通过对原意主义批判和宪法道德解释证成两个方面对司法能动主义进行批判。     

Repeated moral hazard and recursive Lagrangeans

This paper shows how to solve dynamic agency models by extending recursive Lagrangean techniques à la Marcet and Marimon (2011) to problems with hidden actions. The method has many advantages with respect to the promised utilities approach (Abreu et al., 1990): it is a significant improvement in terms of simplicity, tractability and computational speed. Solutions can be easily computed for hidden actions models with several endogenous state variables and several agents, while the promised utilities approach becomes extremely difficult and computationally intensive even with just one state variable or two agents.