June 2021
Senay Agca (George Washington University)
John R. Birge (University of Chicago)
Zi’ang Wang (Chinese University of Hong Kong)
Jing Wu (Chinese University of Hong Kong)
Abstract: Global supply chains expose firms to multi-regional risks, but also provide benefits by creating a buffer against local shocks. The COVID-19 pandemic and its differential impact on different parts of the world provide an opportunity for insight into supply chain credit risk, and how operational and structural characteristics of global supply chains affect this risk. In this paper, we examine supply chain credit risk during different phases of the COVID-19 pandemic by focusing on Credit Default Swap (CDS) spreads and US-China supply chain links. CDS spreads reflect both the probability of default and expected loss given default, and are available with daily frequency, which allows the assessment of supply chain partners’ credit risk in a timely manner. We find that CDS spreads for firms with China supply chain partners increase with the economic shutdown in China during the pandemic, and the spreads go down when the economic activity resumed with the re-opening in China. We consider Swift, Even Flow (SEF) and Social Network Theories (SNT) within our context. Supporting SEF theory, we find that the impact of pandemic-related disruptions to even flow of goods and materials reflected in supply chain credit risk is mitigated for firms with lower inventory turnover and those with better ability to work with longer lead times and operating cycles. Examining supply chain structural characteristics through SNT reveals that spatial and horizontal complexity, as well as network centrality (degree, closeness, betweenness, information) mitigate the impact of supply chain vulnerabilities on supply chain credit risk.
JEL Codes: E21, E51, F23, G12, G14, G23, G32, L11
Key Words: Supply Chains, Credit Risk, CDS, COVID-19, Pandemic
