Using Network Science to Quantify Economic Disruptions in Regional Input-Output Networks

Abstract

Input-output (IO) tables provide a standardised way of looking at interconnections between all industries in an economy, and are often used to estimate the impact of disruptions or shocks on economies. IO tables can be thought of as networks -with the nodes being different industries and the edges being the flows between them. We develop a network-based analysis to consider a multi-regional IO network at regional and sub-regional level within a country. We calculate both traditional matrix-based IO measures (e.g. multipliers) and new network theory-based measures, and contrast these measures with the results of a disruption model applied to the same IO data. We find that path-based measures, such as betweenness centrality, give a good indication of flowon economic disruption, while eigenvector-type centrality measures give results comparable to traditional IO multipliers. We also show the effects of treating IO networks at different levels of spatial aggregation.

An Impact Path Analysis of Russo–Ukrainian Conflict on the World and Policy Response Based on the Input–Output Network

“…Since the complex network theory was introduced into the IO analysis, scholars have mainly explored the degree and scope of the effect on the economic system when particular industries were under attack and focused on the measurement of critical nodes [26,27,30,38]. The research on the critical path from the network perspective has often been ignored.…”

“…At first, the research about the effect of shocks on the economic system mainly focused on qualitative analysis. Based on the IO model and the subsequent complex network theory, researchers have demonstrated that the propagation of microeconomic shocks would cause a Butterfly Effect, thereby leading to sizable aggregate fluctuations when there are significant asymmetries in the roles that industries play as direct or indirect suppliers to others [25][26][27]. With the development of the complex network theory, it has become possible to conduct semiquantitative and even quantitative analysis about the relation between microeconomic shocks and aggregate fluctuations, such as quantifying how much the industrial shocks contribute to the aggregate output fluctuation making use of the network indexes [28], measuring the spreading scope of the shocks [29,30], and analyzing industries' long-term and short-term spreading effects [31].…”

Review of the input-output network and its application in energy and mineral industries

“…Initially, the conventional wisdom in macroeconomics was that when aggregate output was concentrated around its mean, particular shocks would dissipate quickly and have a significant effect on the economic system. With the introduction of the inputoutput model, especially the complex network theory, the majority of scholars have demonstrated that the micro impact will have a significant impact on the entire economic system by building models between the structure of various industrial networks and aggregate fluctuation (Carvalho, 2009;Acemoglu et al, 2012;Harvey and O'Neale, 2020).…”

Network Interactions of Global Supply Chain Members

“…Nodes with high betweenness centrality act as a communication centrality. If there are problems in sharing information at nodes with high betweenness centrality, information flow will be adversely affected in the overall network (Brintrup et al, 2011(Brintrup et al, , 2015Clemente et al, 2015;Harvey & O'Neale, 2020;Kovács, 2016). Therefore, based on the value of betweenness centrality, closeness centrality, and direct connection, a company may evaluate the impact of each member on operations on the overall network, the activities of sharing information among its near members, and/or the activities of directly connected members.…”