Abstract
Supply chains enable the flow of goods and services within economic systems. When mapped for the entire economy and geographic locations of a country, supply chains form a spatial web of interactions among suppliers and buyers. One way to characterize supply chains is through multiregional input-output linkages. Using a multiregional input-output dataset, we build the multilayer network of supply chains in the United States. Together with a network cascade model, the multilayer network is used to explore the propagation of economic shocks along intranational supply chains. We find that the effect of economic shocks, measured using the avalanche size or total number of collapsed nodes, varies widely depending on the geographic location and economic sector of origin of a shock. The response of the supply chains to shocks reveals a threshold-like behavior. Below a certain failure or fragility level, the avalanche size increases relatively quickly for any node in the network. Based on this result, we find that the most fragile regions tend to be located in the central United States, which are regions that tend to specialize in food production and manufacturing. The most fragile layers are chemical and pharmaceutical products, services and food-related products, which are all sectors that have been disrupted by the Coronavirus Disease 2019 (COVID-19) pandemic in the United States. The fragility risk, measured by the intersection of the fragility level of a node and its exposure to shocks, varies across regions and sectors. This suggests that interventions aiming to make the supply-chain network more robust to shocks are likely needed at multiple levels of network aggregation.
Highlights
A shock that originates in a single economic sector or geographic location can propagate to affect across many different sectors and locations (Bak et al 1993; Delli Gatti et al 2009; May et al 2008; Schweitzer et al 2009)
Using an empirical multilayer network of the flow of economic goods and services across geographic locations in the United States, together with a network diffusion model, our goal is to explore the transmission of economic shocks along intranational supply chains
The dataset maps the domestic flows of economic goods and services across sectors and regions in the United States economy during 2012, which is the latest year with publicly available data to calibrate the multiregional input-output (MRIO) dataset (Garcia et al 2020b)
Summary
A shock that originates in a single economic sector or geographic location can propagate to affect across many different sectors and locations (Bak et al.1993; Delli Gatti et al 2009; May et al 2008; Schweitzer et al 2009). Several authors have shown that the underlying network structure of economic systems plays a fundamental role in the diffusion of economic shocks (Acemoglu et al 2016b; Bak et al 1993; Bardoscia et al 2017; Haldane and May 2011; Lee et al 2011) These findings, have been mostly based on the analysis of single-layer networks or interactions at the national or international level (Acemoglu et al 2012; Contreras and Fagiolo 2014; Lee et al 2011). Previous studies have used input-output data to examine shock propagation at the national level (Acemoglu et al 2016a; Blöchl et al 2011; McNerney et al 2013) In those studies, the nodes of the network are economic sectors, i.e. groups of firms that produce similar goods or services, and the links between the nodes are flows of goods and services. Other authors have used input-output data for different countries to explore various aspects of the topology and proneness of sectoral interdependencies to reveal cascading effects (Blöchl et al 2011; Contreras and Fagiolo 2014; McNerney et al 2013)
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