280910 Resilience in Complex Economic Networks: Insights From Graph Theory and Input-Output Models
Comprehensive analysis of complex systems has exposed the demand for bolstering resilience in such systems with respect to sustainable development. Economies are self-organizing, adaptive, complex systems where the constituent components or sectors are connected with each other in myriad ways. Such networks can be modeled as a directed-weighted graph where the nodes represent diverse sectors and the edges represent the monetary transactions between sectors. For example, Input-Output tables that describe the monetary exchanges between different pairs of industries in an economy are available for different countries. Determining the resilience of complex networks, like the economy, enables us to assess the capacity of the network to retain its functionality and structure while adapting to stress, a property vital for a sustainable network.
Employing a systems approach from a resilience perspective is useful for understanding the trade-offs between efficiency and the ability to cope with variations in the environment because of reorganization. Solely, observing simple cause-effect type of computation among the actors may neglect information regarding indirect effects and system-wide properties arising due to interaction. These interactions and their cascading effects can be better assessed through a systems approach. In addition, research on network robustness has elucidated that complex networks could be resilient to random perturbations but vulnerable to explicit attacks on critical nodes. Identifying vulnerable sectors of the economy, and subsequent, reinforcement of the network topology through policy measures can increase resilience of complex systems like the economy.
The goal of this study is to compare the network structure of the United States (U.S.) and the Chinese economies to identify vulnerabilities in the system and their response to disruptions. We also discern the evolution of resilience from the period of late 1980’s to the mid 2000’s for both economies by utilizing network theory. The Chinese and the U.S. economies represent distinctive categories, with China emerging as one of the biggest manufacturing economies, and the U.S. economy evolving into a service economy. The proposed research integrates concepts of graph theory and Economic Input-Output (EIO) model to elucidate network properties concerning resilience of economic systems. Structural and functional analysis based on graph theory sheds light on vulnerabilities in the network using various centrality and vitality measures. Moreover, using IO analysis and network efficiency performance, we evaluate the direct and indirect impact of disruptions on the economic system. We apply network analysis tools on IO tables for the Chinese and the US economy from 1980’s to 2000’s with an aspiration to observe the evolution of the basic backbone of these economies. It is noted that on introduction of various stresses, resilient systems exhibit low modularity and percolation. Moreover, on increasing the flexibility in the system, both service and manufacturing economies exhibit higher resilience to disruptions. The implications of the results for developing resilient and sustainable economic systems will be presented and discussed.