通过将网络分析技术应用于大型投入产出系统，我们确定了地方/区域经济中的关键部门。我们通过使用基于随机游走的度量来克服传统中心性度量的局限性，作为Blochl et al.（2011）的扩展。这些更适合于分析非常密集的网络，即大多数节点连接到所有其他节点的网络。这些措施还考虑到递归关系（循环）的存在，因为这些关系在经济体系中很常见（取决于聚合程度，大多数公司从同一工业部门的其他公司购买或出售）。我们提出的中心性措施是非常适合捕捉部门的影响，从通常的产出和就业乘数失踪。我们还开发了一个R软件包（xtransat），用于处理IMPLAN（R）模型的数据和计算新开发的措施。
英文摘要：
By applying network analysis techniques to large input-output system, we identify key sectors in the local/regional economy. We overcome the limitations of traditional measures of centrality by using random-walk based measures, as an extension of Blochl et al. (2011). These are more appropriate to analyze very dense networks, i.e. those in which most nodes are connected to all other nodes. These measures also allow for the presence of recursive ties (loops), since these are common in economic systems (depending to the level of aggregation, most firms buy from and sell to other firms in the same industrial sector). The centrality measures we present are well suited for capturing sectoral effects missing from the usual output and employment multipliers. We also develop an R package (xtranat) for the processing of data from IMPLAN(R) models and for computing the newly developed measures.
What are the key components of an entrepreneurial ecosystem in a developing economy? A longitudinal empirical study on technology business incubators in China
The role of money and the financial sector in energy-economy models used for assessing climate policy
Cambridge Econometrics Ltd（剑桥计量经济学有限公司）；Faculty of Science, Radboud University（拉德堡德大学理学院）；Cambridge Centre for Environment, Energy and Natural Resource Governance (C-EENRG), University of Cambridge（剑桥大学环境、能源和自然资源治理中心）
Corvinus Institute for Advanced Studies, Corvinus University of Budapest（布达佩斯科维努斯大学科维努斯高级研究所）；Institute for Data Analytics and Information Systems, Corvinus University of Budapest, Hungary（布达佩斯科维努斯大学数据分析与信息系统研究所）；Centre for Economic and Regional Studies, ELTE, Budapest, Hungary（布达佩斯罗兰·厄特沃什大学经济区域研究中心）；Complexity Science Hub, Vienna, Austria（维也纳复杂科学中心）；School of Business and Economics, Maastricht University, Netherlands（马斯特里赫特大学商学院）；Center for Collective Learning, IAST, Toulouse School of Economics, University of Toulouse Capitole, France（图卢兹经济学院集体学习中心）；Center for Collective Learning, CIAS, Corvinus University of Budapest, Hungary（布达佩斯科维努斯大学CIAS集体学习中心）；Alliance Manchester Business School, University of Manchester, United Kingdom（曼彻斯特大学阿利亚曼彻斯特商学院）
Labour reallocation and production-network recomposition in the green transition
Sant’Anna School of Advanced Studies（圣安娜高等研究院）；CLIMAFIN – Climate Finance Alpha（CLIMAFIN – 气候金融阿尔法）；Centre d’Economie de la Sorbonne – Paris School of Economics – CNRS-Université Paris 1 Panthéon-Sorbonne（索邦大学经济中心 – 巴黎经济学院 – 法国国家科学研究中心-巴黎第一先贤祠-索邦大学）
