基于SFA和卡尔曼滤波方法的分析

利用随机前沿生产函数模型对中国28个省区1985～2007年的全要素生产率进行了测算和分解,并通过建立状态空间模型测算了全要素生产率各分解成分对中国地区差距的影响程度及变化趋势.研究结果表明,技术效率是导致中国地区经济差距扩大的最主要原因,其次是技术进步的影响,而规模经济性对地区差距的影响非常有限.     

资源约束与贸易开放的技术溢出门槛效应研究——来自我国资源型地区的经验研究

通过构建中间产品种类扩张型的内生增长模型,本文论证了在资源约束条件下,贸易开放的技术溢出效应推动技术进步的作用机理以及技术溢出效应的制约因素。同时,本文还利用我国资源型地区2000~2009年的省际面板数据,实证检验了资源型地区贸易开放的技术溢出门槛效应。研究表明:贸易开放的技术溢出效应对资源型地区技术进步推动作用并不明显,人力资本、贸易开放、能源产业投资额、技术差距对技术溢出皆存在门槛效应,当跨越技术溢出的门槛值,资源型地区能够突破资源约束的瓶颈,实现本地区的技术进步。     

技术进步视角下经济政策不确定性对经济增长的影响研究

文章首次将经济政策不确定性、技术进步和经济增长纳入统一分析框架,在技术进步视角下分析了经济政策不确定性对经济增长的非线性影响.通过利用非线性格兰杰因果检验方法识别出中国经济政策不确定性,技术进步和经济增长之间存在的非线性信息,进一步运用半参数全局向量自回归模型进行实证研究.结果表明:1)经济政策不确定性对技术进步和经济...     

挖掘增长新动能:分级人力资本对我国经济增长的贡献评估

在经历了长时间经济的高速增长后,我国经济进入了向科技创新挖掘动能的新时期。科技创新并非人力资本的简单堆积,而是由高知识储备人才所推动,因此,本文的理论模型建立在知识具有外溢性的理论之上,放松了人力资本同质的假设并细化讨论人力资本对于经济增长的作用机制。实证研究利用个体固定效应模型、双向固定效应模型与混合效应模型分别测算中国东部地区、中部地区、西部地区两个级别人力资本的效率,并计算其相对效率。研究发现,初级教育主要以生产要素的形式参与生产并促进经济增长,高级教育主要以改变技术水平的方式促进经济增长;三大地区对初级人力资本的利用程度均高于高级人力资本,初级人力资本相对效率由东部、中部到西部递增;中西部地区的人力资本弹性为负值,各级人力资本在我国部分地区对产出的贡献并非全为正;社会背景与经济发展程度将明显影响经济体对于人力资本结构需求。     

技术创新影响因素的区域差异:以中国30个省份为例的研究

利用中国30个省(直辖市、自治区)的面板数据,对中国技术创新影响因素的区域差异进行了实证分析,不仅研究了地区研发投入对技术创新的影响,还考虑了财政创新支持、金融创新支持、外商投资的技术溢出、地区经济的转轨情况、地区人力资本禀赋等因素的影响作用.实证结果表明,研发投入是地区技术创新的主要推动因素,各个因素对技术创新影响的区域差异明显.     

基于DEA-Malmquist指数的我国煤炭城市的全要素生产率动态测算

运用1995~2005年中国地级煤炭城市面板数据,采用非参数Malmquist指数方法,实证分析了全要素生产率的变动状况,并将其进一步分解为技术效率和技术进步。研究结果表明:第一,1995~2005年24座地级煤炭城市平均技术效率水平较低,2001年煤炭城市规模效率的下降导致平均技术效率较大幅度下降;第二,1995~2005年间技术效率和技术进步对煤炭城市全要素生产率的影响都有较明显的波动,在这十年间技术效率是全要素生产率增长的动力源泉;第三,东部、中部和西部地区之间和地区内部煤炭城市全要素生产率的变动也存在较显著差异。人力资本和制度因素对全要素生产率、效率提高以及技术进步均有重要的影响。     

中国区域技术效率的随机前沿分析

本文采用1996-2006年全国30个省实际GDP、人力资本和物质资本的面板数据,在随机误差项自相关和异方差的假定下,运用随机前沿分析模型对我国省际技术效率进行测算;同时分东部、中部和西部进行分析,并进行了严格的假设检验。结果表明:我国中部地区的技术效率最高,东部次之,西部最低;且三大地区技术效率均逐年提高,三者之间的技术效率差异呈现收敛趋势。     

我国农业技术扩散环境的评价研究

观察我国大陆地区31个省市(港、澳、台除外)的农业技术扩散环境,从自然环境、社会环境、科技环境、经济环境、政策环境等五个方面建立评价指标体系,运用熵权法与PROMETHEE II方法进行建模与实证分析,并进行了31省市的空间分布分析与分类研究.基于2014年的研究结果表明:农业科技环境、农业经济环境是影响农业技术扩散的重要因素;各省市在5方面农业技术扩散环境指标上有较大差异,总体而言,农业技术扩散环境可分为5种不同等级,北京、浙江、新疆等省市具有较为优越的环境条件,而安徽、山西、甘肃等地的农业技术扩散环境条件较差;全国农业技术扩散环境水平较为均衡,存在局部的区域聚集特征,但梯度转移规律不明显,省际间溢出效应不显著.根据研究结论,为全国以及各省市系统优化农业技术扩散环境提出了对策建议.     

中国省际工业企业创新效率及其收敛性研究

本文运用基于DEA的Malmquist指数方法测度了2002-2009年中国30个省(自治区、直辖市)大中型企业的创新技术效率、技术进步指数及Malmquist指数,发现省际大中型企业普遍存在创新技术无效率,技术效率指数年均下降0.2%,而技术进步指数与全要素生产率指数年均增长率分别为0.8%和0.6%。分地区的大中型企业创新全要素生产率的增长也主要是来自于技术进步指数增长;地区大中型企业Malmquist指数东部最高,中部地区次之,西部地区最低;省际大中型企业生产率的收敛分析均表现出收敛和"俱乐部收敛"趋势.     

环境约束下中国地区物流业全要素生产率重估及收敛性研究

利用基于方向距离函数的Malmquist-Luenberger(ML)生产率指数方法对环境约束下中国1997-2009年30个省级地区物流业全要素生产率增长及其成分进行了重新估算,并通过技术创新者研究,分析了推动生产可能性边界外移的地区.研究发现:忽视非期望产出的传统Malmquist指数方法会低估物流业技术效率水平、高估物流业技术进步指数和全要素生产率指数.环境约束下我国物流业ML生产率指数年均增长率呈现下降趋势,下降的原因一方面是由于技术效率偏低阻碍了生产率的增长,另一方面是我国物流业技术进步的动力不足所致,物流环境技术创新主要集中于东部和西部地区个别省份,中部地区技术创新水平较低.收敛性检验表明,研究样本期内,全国以及三大地区物流业全要素生产率均存在显著的收敛趋势.     

Linear bilevel multi-follower programming with independent followers

This paper considers a particular case of linear bilevel programming problems with one leader and multiple followers. In this model, the followers are independent, meaning that the objective function and the set of constraints of each follower only include the leader’s variables and his own variables. We prove that this problem can be reformulated into a linear bilevel problem with one leader and one follower by defining an adequate second level objective function and constraint region. In the second part of the paper we show that the results on the optimality of the linear bilevel problem with multiple independent followers presented in Shi et al. [The kth-best approach for linear bilevel multi-follower programming, J. Global Optim. 33, 563–578 (2005)] are based on a misconstruction of the inducible region.     

Phenomena in Inverse Stackelberg Games,Part 1: Static Problems

Games are considered in which the role of the players is a hierarchical one. Some players behave as leaders, others as followers. Such games are named after Stackelberg. In the current paper, a special type of these games is considered, known in the literature as inverse Stackelberg games. In such games, the leader (or: leaders) announces his strategy as a mapping from the follower (or: followers) decision space into his own decision space. Arguments for studying such problems are given. The routine way of analysis, leading to a study of composed functions, is not very fruitful. Other approaches are given, mainly by studying specific examples. Phenomena in problems with more than one leader and/or follower are studied within the context of the inverse Stackelberg concept. As a side issue, expressions like “two captains on a ship” and “divide and conquer” are given a mathematical foundation.     

基于动机的联合风险投资收益分配契约设计(A2016-0158)

从联合风险投资的领导者采取联合投资的动机出发,考虑分配给跟随者的收益份额是否能达到目的,运用优化理论建立了联合投资双方的收益分配模型,提出了联合风险投资机构之间的收益分配契约设计的一种可供参考的方法,并用实例说明了模型方法的应用。研究还表明,潜在的市场竞争可能对领导者造成的损失越大,领导者越愿意给予跟随者更多的收益份额;当项目质量信息的不确定性越高,单独投资将存在较大风险的时候,为了获得项目质量信息的补充,也使得领导者愿意给予跟随者更多的收益份额。     

The existence of monotonic solutions of a nonlinear car-following equation

A leader-follower pair of cars whose motion is subject to a nonlinear car-following equation are travelling with the same positive constant velocity when the leader begins to change his velocity in a monotonic way to a different non-negative value. Conditions are found for the headway between leader and follower to tend monotonically to a positive value. The results are extended to a system of a leader and two followers.     

Parallel splitting augmented Lagrangian methods for monotone structured variational inequalities

The typical structured variational inequalities can be interpreted as a system of equilibrium problems with a leader and two cooperative followers. Assume that, based on the instruction given by the leader, each follower can solve the individual equilibrium sub-problems in his own way. The responsibility of the leader is to give a more reasonable instruction for the next iteration loop based on the feedback information from the followers. This consideration leads us to present a parallel splitting augmented Lagrangian method (abbreviated to PSALM). The proposed method can be extended to solve the system of equilibrium problems with three separable operators. Finally, it is explained why we cannot use the same technique to develop similar methods for problems with more than three separable operators.     

Nash bargaining and leader–follower models in water allocation: Application to the Zarrinehrud River basin,Iran

Mathematical models for conflict resolution are very important in integrated water resources and environmental management. This study proposes a new methodology to resolve conflicts among different water users and water suppliers while considering environmental requirements and the system’s constraints. A two-level leader–follower model is applied to maximize the net benefit with the Iran Water Resources Management Company as the leader and agricultural, domestic, and industrial users as followers subject to the system’s constraints. As a comparison, the Nash bargaining solution is also used to find a solution when simultaneous moves are assumed by the participants. The suggested method is then applied to the real case of the Zarrinehrud River basin that is one of the areas facing water shortages in Iran. For the actual optimization, Genetic Algorithm is used in order to avoid local optimum. As the contribution of this study, the results show that benefits for the leader in the leader–follower model increased in comparison with the Nash bargaining solutions.     

Controlled predatory pricing in a multiperiod Stackelberg game: an MPEC approach

We analyze a multiperiod oligopolistic market where each period is a Stackelberg game between a leader firm and multiple follower firms. The leader chooses his production level first, taking into account the reaction of the followers. Then, the follower firms decide their production levels after observing the leader’s decision. The difference between the proposed model and other models discussed in literature is that the leader firm has the power to force the follower firms out of business by preventing them from achieving a target sales level in a given time period. The leader firm has an incentive to lower the market prices possibly lower than the Stackelberg equilibrium in order to push the followers to sell less and eventually go out of business. Intentionally lowering the market prices to force competitors to fail is known as predatory pricing, and is illegal under antitrust laws since it negatively affects consumer welfare. In this work, we show that there exists a predatory pricing strategy where the market price is above the average cost and consumer welfare is preserved. We develop a mixed integer nonlinear problem (MINLP) that models the multiperiod Stackelberg game. The MINLP problem is transformed to a mixed integer linear problem (MILP) by using binary variables and piecewise linearization. A cutting plane algorithm is used to solve the resulting MILP. The results show that firms can engage in predatory pricing even if the average market price is forced to remain higher than the average cost. Furthermore, we show that in order to protect the consumers, antitrust laws can control predatory pricing by setting rules on consumer welfare.     

Phenomena in Inverse Stackelberg Games,Part 2: Dynamic Problems

Games are considered in which the role of the players is a hierarchical one. Some players behave as leaders, others as followers. Such games are named after Stackelberg. In the current paper, a special type of these games is considered, known in the literature as inverse Stackelberg games. In such games, the leader (or: leaders) announces his strategy as a mapping from the follower (or: followers) decision space into his own decision space. Arguments for studying such problems are given. The routine way of analysis, leading to a study of composed functions, is not very fruitful. Other approaches are given, mainly by studying specific examples. Phenomena in problems with more than one leader and/or follower are studied within the context of the inverse Stackelberg concept. As a side issue, expressions like “two captains on a ship” and “divide and conquer” are given a mathematical foundation.     

Fuzzy bilevel programming with multiple objectives and cooperative multiple followers

Classic bilevel programming deals with two level hierarchical optimization problems in which the leader attempts to optimize his/her objective, subject to a set of constraints and his/her follower’s solution. In modelling a real-world bilevel decision problem, some uncertain coefficients often appear in the objective functions and/or constraints of the leader and/or the follower. Also, the leader and the follower may have multiple conflicting objectives that should be optimized simultaneously. Furthermore, multiple followers may be involved in a decision problem and work cooperatively according to each of the possible decisions made by the leader, but with different objectives and/or constraints. Following our previous work, this study proposes a set of models to describe such fuzzy multi-objective, multi-follower (cooperative) bilevel programming problems. We then develop an approximation Kth-best algorithm to solve the problems.     

A robust model for a leader–follower competitive facility location problem in a discrete space

This paper aims at determining the optimal locations for the leader’s new facilities under the condition that the number of the follower’s new facilities is unknown for the leader. The leader and the follower have some facilities in advance. The first competitor, the leader, opens p new facilities in order to increase her own market share. On the other hand, she knows that her competitor, the follower, will react to her action and locate his new facilities as well. The number of the follower’s new facilities is unknown for the leader but it is assumed that the leader knows the probability of opening different numbers of the follower’s new facilities. The leader aims at maximizing her own market share after the follower’s new facilities entry. The follower’s objective is also to maximize his own market share. Since the number of the follower’s new facilities is unknown for leader, “Robust Optimization” is used for maximizing the leader’s market share and making the obtained results “robust” in various scenarios in terms of different numbers of the follower’s new facilities. The optimal locations for new facilities of both the leader and the follower are chosen among pre-determined potential locations. It is assumed that the demand is inelastic. The customers probabilistically meet their demands from all different facilities and the demand level which is met by each facility is computed by Huff rule. The computational experiments have been applied to evaluate the efficiency of the proposed model.