Identifying key sectors in the regional economy: a network analysis approach using input–output data

Applied Network Science

Research

Fernando DePaolis¹  M. Clara De Paolis Kaluza²  Phil Murphy³ 

[1] Center for the Blue Economy, Middlebury Institute of International Studies, Monterey, CA, USA;Khoury College of Computer Science, Northeastern University, Boston, MA, USA;META Lab, Middlebury Institute of International Studies, Monterey, CA, USA;

关键词: Input–output system;    Regional economies;    Multiplier effects;    C67;    D85;    P25;   

DOI  :  10.1007/s41109-022-00519-2

 received in 2022-05-17, accepted in 2022-11-10,  发布年份 2022

来源: Springer

【 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 Blöchl et al. (Phys Rev E 83(4):046127, 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 and make available an R implementation for computing the newly developed measures.

【 授权许可】

CC BY   
© The Author(s) 2022

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