论文标题
确定区域经济中的关键部门：使用投入输出数据的网络分析方法
Identifying Key Sectors in the Regional Economy: A Network Analysis Approach Using Input-Output Data
论文作者
论文摘要
通过将网络分析技术应用于大型输入输出系统，我们可以确定本地/区域经济中的关键领域。我们通过使用基于随机步行的度量来克服传统中心度度量的局限性，作为Blochl等人的扩展。 （2011）。这些更适合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。这些措施还允许存在递归关系（循环），因为这些措施在经济体系中很常见（取决于聚合水平，大多数公司从同一工业部门的其他公司购买并出售给其他公司）。我们提出的中心度度量非常适合捕获通常的产出和就业乘数中缺少的部门效应。我们还开发了一个R软件包（XTRANAT），用于处理植入植物（R）模型的数据并计算新开发的度量。
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.
