A mixed integer linear programming model for optimal sovereign debt issuance

Governments borrow funds to finance the excess of cash payments or interest payments over receipts, usually by issuing fixed income debt and index-linked debt. The goal of this work is to propose a stochastic optimization-based approach to determine the composition of the portfolio issued over a series of government auctions for the fixed income debt, to minimize the cost of servicing debt while controlling risk and maintaining market liquidity. We show that this debt issuance problem can be modeled as a mixed integer linear programming problem with a receding horizon. The stochastic model for the interest rates is calibrated using a Kalman filter and the future interest rates are represented using a recombining trinomial lattice for the purpose of scenario-based optimization. The use of a latent factor interest rate model and a recombining lattice provides us with a realistic, yet very tractable scenario generator and allows us to do a multi-stage stochastic optimization involving integer variables on an ordinary desktop in a matter of seconds. This, in turn, facilitates frequent re-calibration of the interest rate model and re-optimization of the issuance throughout the budgetary year allows us to respond to the changes in the interest rate environment. We successfully demonstrate the utility of our approach by out-of-sample back-testing on the UK debt issuance data.     

A flexible multicriteria decision-making methodology to support the strategic management of Science,Technology and Innovation research funding programs

Research funding programs are a policy instrument utilized by governments to influence the innovation process. They are usually elaborated, launched and managed by research funding agencies. In order to select the most adequate research projects, agencies often rely on the peer review process.This paper introduces a methodology to support funding decisions based on the peer review process. The methodology involves the use of a multicriteria decision model to support the assessment, evaluation, prioritization and selection of applications, under a multi-step decision-making process, which fits into a strategic management cycle within the agency. The Multiattribute Value Theory, being considered under a Value Focused Thinking approach, provides a basis for the construction of the multicriteria decision model. The good practices in peer review and also a logical framework for program management are considered by the methodology.A pilot study, presented in the paper, involved a retrospective implementation of a peer review process in the context of a program launched by the Ministry for Science, Technology, Innovations and Communications and the National Council of Technological and Scientific Development, in Brazil. The methodology allowed a clear distinction of roles. The agency staff in the role of decision-makers was responsible for making value judgments on behalf of the agency. The experts, in the role of committee members and ad hoc reviewers, contributed with their expertise by providing objective assessments. Such assessments served as a basis for evaluating the applications, characterizing the possible portfolios, and can be considered as data in future program evaluation studies.     

后发企业突破低端锁定的三方演化博弈分析

后发企业突破低端锁定是中国产业迈向全球价值链(GVC)中高端的必经之路。论文构建了一个包含后发企业、领先企业和后发企业所在国政府的三方演化博弈模型,分析后发企业策略选择的影响因素,并对博弈模型进行数值模拟分析。结果表明:复制动态系统存在{突破,封锁,消极}和{不突破,封锁,积极}两个可能的演化稳定策略组合(ESS),系统趋向哪个ESS主要由企业核心能力决定。后发企业的核心能力越强,突破收益越大,越倾向于选择“突破”策略。无论后发企业采用哪种策略,领先企业都会选择“封锁”策略。政府策略选择有机会主义倾向,但政策扶持有利于阻止本国后发企业滑向“不突破”稳定均衡,是促进企业挣脱价值链低端锁定的重要外部力量。     

平台参与下网络食品安全政府监管策略研究

针对“互联网+食品”新兴业态产生的更为严峻的食品安全问题,本文研究政府对网络食品安全实施直接监管下的最优监管策略,以及在网络平台参与监管时政府的最优间接监管策略,并考虑了网络平台与食品企业合谋对监管效率的影响。结果表明,在食品安全问题被发现的概率越大或食品安全问题发生对政府影响较大时,选择直接监管策略会更优;但监管成本的增加会降低政府直接监管的动因,促使政府选择间接监管策略;比较两种策略可知,间接监管模式更能抑制平台与企业的合谋行为。此外,研究还表明在直接监管策略下,由于提高食品企业的惩罚力度会降低政府的监管强度,因此加大惩罚并不总能提高政府的效益;而在间接监管策略下,加大对网络平台的惩罚会使网络平台加大监管力度,从而提高政府的效益。     

基于博弈论视角的稀土矿区环境治理及监管策略研究

针对稀土矿区环境治理的复杂性,本文通过建立地方政府和稀土企业之间的动态演化博弈模型,分析了博弈双方在不同情形下的演化稳定策略及其影响因素,并利用matlab对其进行数值仿真。研究表明,地方政府的监管成本、执行环境规制时对稀土企业的奖惩政策、稀土企业的治污成本以及非法开采时的额外收益都会影响地方政府与稀土企业的演化稳定策略,降低地方政府的监管成本、稀土企业的治污成本等都会引导博弈双方的演化稳定策略趋向于{严格监管,合法开采},从而促进矿区环境的可持续性发展。     

污染产业转移下府际间合作治理大气污染的演化博弈分析

大气污染具有跨区域性,府际间合作治理是大气污染防治的必由之路,合作治理中存在“搭治污便车”的困境。由于府际间大气污染治理博弈的具有长期性和动态性,由此建立了多人两策略的演化博弈模型。分别研究,无约束机制和有约束机制两种情况下地方政府演化稳定策略及其影响因素。考虑到政府间污染产业转移,建立了污染产业转移政府对承接方政府治污补偿机制下的演化博弈模型,分别研究无约束和有约束两种情形下(补偿,治理)策略成为演化稳定均衡状态的条件。研究表明:府际间的合作治理策略选择不会受到外部效应的影响,大气污染治理成本、治理时污染物减排量、不治理时污染物排放增加量、中央政府对治理的奖励和对不治理的惩罚力度是影响地方政府决策的重要因素。将大气质量作为政绩考核的重要指标,提高其权重系数,可有效促使地方政府策略向参与合作治理演化。无约束下自主选择时,最优策略(补偿,治理)不会成为稳定均衡策略,引入中央政府约束后,当经济惩罚在一定范围内,(补偿,治理)成为稳定均衡策略。     

An integrated model for screening cargo containers

This paper focuses on detecting nuclear weapons on cargo containers using port security screening methods, where the nuclear weapons would presumably be used to attack a target within the United States. This paper provides a linear programming model that simultaneously identifies optimal primary and secondary screening policies in a prescreening-based paradigm, where incoming cargo containers are classified according to their perceived risk. The proposed linear programming model determines how to utilize primary and secondary screening resources in a cargo container screening system given a screening budget, prescreening classifications, and different device costs. Structural properties of the model are examined to shed light on the optimal screening policies. The model is illustrated with a computational example. Sensitivity analysis is performed on the ability of the prescreening in correctly identifying prescreening classifications and secondary screening costs. Results reveal that there are fewer practical differences between the screening policies of the prescreening groups when prescreening is inaccurate. Moreover, devices that can better detect shielded nuclear material have the potential to substantially improve the system’s detection capabilities.     

不同补贴对象下闭环供应链信息共享价值研究

在一个制造商和一个零售商组成的二级闭环供应链中,为研究政府补贴下供应链需求信息共享对决策的影响及共享价值,针对两种补贴对象,构建并求解无信息共享和信息共享博弈模型,并进行仿真验证.研究表明:1)两种补贴对象下,制造商均能从信息共享中获益,零售商仅在绿色成本和回收成本较低时才会从信息共享中获益;绿色成本和回收成本稍高时,设计基于谈判势力的信息补偿机制能有效促进零售商共享信息.2)产品绿色度和回收率随预测需求量的提高而提高,批发价和零售价仅在回收成本较低时,才会随预测需求量的提高而提高.3)在仅补贴一方情况下,当补贴对象为低补贴一方时,两个主体所获的信息共享价值大;若对两者的补贴均较低,两个主体均希望补贴对象为零售商;若对两者的补贴均较高,零售商不愿共享需求信息.     

政府监管下的医院医疗信息分享演化博弈分析

在分析政府监管下医院间医疗信息分享特征的基础上,结合我国当前正在推行的医联体医院间信息分享运作模式,引入梅特卡夫定律并考虑患者评价的影响,分析了监管部门与医院各自的利益组成,建立了监管部门与医院两者之间的演化博弈模型,并采用复制动态方程研究了不同情形下医院间信息分享的演化博弈轨迹。研究表明,政府通过监管并建立激励惩罚机制等引导措施对医院最终达到的演化稳定态具有极大影响;降低医院主体信息分享的风险成本、规范提高医院分享信息的质量、引导患者增强对医院信息分享的关注、制定有吸引力和威慑力的奖惩政策,是促进医院医疗信息分享的关键。研究结果可为政府监管部门预测医院间的信息分享趋势和制定精准化政策以促进分享提供参考。     

Opportunistic timing and manipulation in Australian Federal Elections

In many parliamentary systems, election timing is an important decision made by governments in order to maximize their expected remaining life in power. Governments can also introduce policy or economic actions to enhance their popular standing and thus their chance of being re-elected. On the other hand, an oppositions’ natural objective is to gain power, and they will also apply controls through their own policies to reduce the governments’ chance of being re-elected. In this paper we employ a dynamic programming approach to determine the optimal timing for governments and oppositions to best utilize their limited resources. At each decision branch, the optimal control is interpreted as a Nash–Cournot equilibrium of a zero-sum political game which, in certain states, admits mixed strategy solutions. We perform a case study on the Australian Federal Election for House of Representatives.