供应链企业间战略共识如何影响技术创新绩效——知识共享与供应链协同的作用

在动态复杂的市场环境中，企业不仅要重视内部创新力量，同时需要依托外部力量，充分发挥外部知识资源在创新过程中的作用。基于认知行为理论，采用多元层次回归和Bootstrap方法，分析供应链企业间战略共识、知识共享和供应链协同对企业技术创新绩效的作用。结果发现：供应链企业间战略共识对知识共享和企业技术创新绩效具有促进作用；知识共享在供应链企业间战略共识与技术创新绩效间起中介作用；供应链协同正向调节供应链企业间战略共识与知识共享的关系，并正向调节知识共享的中介作用。     

高技术产业国家价值链网络结构与省域增加值分解——来自电子信息产业的证据

为破解我国在高技术产业全球价值链中面临的低端锁定困境，需要构建并完善国家价值链分工体系。构建中国高技术产业国家价值链内生增值传导网络结构分析框架，并以电子信息产业为例，对省域国内增加值进行分解。结果表明，现阶段中国电子信息产业上游技术研发能力较弱，整体增值能力不强；下游间接关联产业部门数量及关联系数值仍待提高；除中游外，上下游出口国内增加值偏低，国际竞争力较弱；东、中部省域国内完全增加值占据优势，内生增值能力方面各有所长，东北、西部省域国内完全增加值及其内生增值能力均较弱。同时，中国省域国际垂直专业化程度未表现出显著地理地区特征，即使同一地域的省域之间也存在不同程度差异。     

长江经济带人才集聚水平测度及时空演变研究——基于价值链视角

基于价值链视角，构建涵盖人才资源在区域空间层面集聚生成、地区配置、效能产出3个维度在内的区域人才集聚水平评价指标体系，采用专家咨询AHP-信息熵组合赋权法构建综合评价模型和耦合协调度模型，对2010—2018年长江经济带沿线省市人才集聚水平进行测度与时空演化特征分析。结果表明，就长江经济带整体而言，考察期内地区人才集聚水平总体呈现逐年上升态势，但仍处于低水平状态；沿线省市人才集聚水平差异显著，缩小趋势渐缓，整体呈现局部高水平、全局低效率的不利境况；各省市人才集聚水平关键维度的耦合协调度整体呈显著波动递增态势，但内部耦合协调度存在不平衡发展问题，影响地区人才集聚水平整体提升。为提升长江经济带人才集聚水平，推进沿线地区协调发展，需强化区域人才合作机制，采取差别化精准策略破解沿线地区人才集聚低水平、不协调的短板因素。     

Error analysis of finite difference and Markov chain approximations for option pricing

Mijatovi? and Pistorius proposed an efficient Markov chain approximation method for pricing European and barrier options in general one‐dimensional Markovian models. However, sharp convergence rates of this method for realistic financial payoffs, which are nonsmooth, are rarely available. In this paper, we solve this problem for general one‐dimensional diffusion models, which play a fundamental role in financial applications. For such models, the Markov chain approximation method is equivalent to the method of lines using the central difference. Our analysis is based on the spectral representation of the exact solution and the approximate solution. By establishing the convergence rate for the eigenvalues and the eigenfunctions, we obtain sharp convergence rates for the transition density and the price of options with nonsmooth payoffs. In particular, we show that for call‐/put‐type payoffs, convergence is second order, while for digital‐type payoffs, convergence is generally only first order. Furthermore, we provide theoretical justification for two well‐known smoothing techniques that can restore second‐order convergence for digital‐type payoffs and explain oscillations observed in the convergence for options with nonsmooth payoffs. As an extension, we also establish sharp convergence rates for European options for a rich class of Markovian jump models constructed from diffusions via subordination. The theoretical estimates are confirmed using numerical examples.     

Tourism,terrorism and political violence in Tunisia: Evidence from Markov-switching models

This study investigates the impact of terrorist attacks and political violence on the number of tourist arrivals and overnight stays in Tunisia. The dataset employed consists of monthly data that covers the period from January 2000 to September 2016, which includes several political and terrorist attacks in Tunisia and the region. Empirically, we investigate the true data generating process (DGP) of these two proxies of tourism activity by accounting for four statistical properties that characterize these series: (1) seasonality, (2) unit roots, (3) breaks, and (4) long memory behavior.Our empirical findings show strong evidence of stationarity, five breaks in the tourist arrival time series and spurious long memory behavior. By estimating a 3-state Markov switching model consisting of the mean, trend, and variance, we find that the Tunisian Jasmine revolution and two recent terrorist attacks, one at the Bardo National Museum on March 18, 2015 and the other at the tourist resort at Port El Kantaoui, Sousse on June 26, 2015, played an important role in influencing the tourism activity of the country. Our empirical findings show also that local shocks have a more important impact than international shocks in influencing tourism activity. Interestingly, we find that the effects of terrorist shocks have a long duration compared to political violence shocks. Several security, marketing, and economic policies have been proposed and discussed in the paper.     

Bayesian selection of technology assumptions for the transformation from supply-use to input–output tables

ABSTRACT

In the construction of input–output models from supply-use tables, technology assumptions disambiguate how an industry uses inputs in the production recipe of multiple outputs. This paper uses Bayes' theorem to select technology assumptions, taking into account empirical observations. The paper presents a formulation to explore hybrids between product and industry technology assumptions in product-by-product tables. We then present Markov chain Monte-Carlo techniques to implement the Bayesian method for selecting technology assumptions. We apply the method in a case study using Eurostat supply-use tables of 2004 and 2005, exhibiting a volume of secondary products of less than 13%, and 59 products and industries per country. The results show that the choice of technology is not important, given that there is no strong evidence in favour of any of them.     

三维价值链视阈下科技成果转化知识供给体系研究

科技成果转化知识供给是指知识沿价值链不同维度，经过耦合与交流，形成知识供给体系，对其探索可推动知识的精准供给和有序流动。基于全程价值链视角，从3个维度剖析科技成果转化知识供给体系的特征与机理。在纵向维度中，知识供给纵贯创意→设计→实验→中试→量产→销售等价值环节，并经历知识分化、加工、增值、包装与应用；在横向维度中，科技成果转化知识供给内含于各价值模块中，具有半自律化特征；在网络维度中，知识供给嵌于价值网络中，具有开放组合性、跨领域交叉性与跨疆界性。     

Leverage effect on stochastic volatility for option pricing in Hong Kong: A simulation and empirical study

This paper explores the importance of incorporating the financial leverage effect in the stochastic volatility models when pricing options. For the illustrative purpose, we first conduct the simulation experiment by using the Markov Chain Monte Carlo (MCMC) sampling method. We then make an empirical analysis by applying the volatility models to the real return data of the Hang Seng index during the period from January 1, 2013 to December 31, 2017. Our results highlight the accuracy of the stochastic volatility models with leverage in option pricing when leverage is high. In addition, the leverage effect becomes more significant as the maturity of options increases. Moreover, leverage affects the pricing of in-the-money options more than that of at-the-money and out-of-money options. Our study is therefore useful for both asset pricing and portfolio investment in the Hong Kong market where volatility is an inherent nature of the economy.     

价值链视角下中心城市创新首位度评价与比较研究——以南京为例

基于创新价值链理论，构建创新首位度的理论内涵与评价体系，对南京和其它中心城市的创新首位度进行评价与比较。研究结果显示：①在总体首位度方面，南京位列省域中心城市排名下游，落后于西安、成都、武汉、郑州、广州等国家中心城市，自2008年以来一直落后于深圳、杭州、合肥、苏州等对标竞争城市且差距较大；②在分项首位度方面，南京的研发创新、产业创新首位度位列省域中心城市排名底端，导致南京在两个首位度矩阵中均处于C象限，创新价值链呈现严重的不均衡性；③省域中心城市普遍存在创新价值链的“漏斗效应”，即知识创新首位度＞研发创新首位度＞产业创新首位度，南京尤甚，说明技术创新过程存在大量沟壑；④拓展性研究表明，省域中心城市的创新首位度＞经济首位度＞人口首位度，但是近十年3个首位度的增速排序与上述情况相反，说明创新资源有着更强的集聚效应，应避免行政手段对创新资源的错配。最后，提出对策建议与研究展望。