The Causal Effects of Global Supply Chain Disruptions on Macroeconomic Outcomes: Evidence and Theory

Abstract

We study the causal effects and policy implications of global supply chain disruptions on the U.S. economy. We construct a new index of supply chain disruptions from the Automatic Identification System data of containerships, developing a novel spatial clustering algorithm that determines real-time congestion from the positions and speeds of containerships in major ports around the globe. We develop a new theoretical framework with search frictions between exporters and importers in the goods market, transportation costs, and spare capacity that provides us with unique identifying restrictions arising from the co-movements of spare capacity, price, and output to study the causal effects and the changes in the effectiveness of monetary policy due to supply chain disruptions. Structural VAR models with these restrictions establish that supply chain disruptions significantly: (i) depress real GDP, raise prices, and generate a surge in spare capacity, and (ii) increase the effectiveness of contractionary monetary policy in taming inflation while reducing the sensitivity of output amid the supply chain disruptions of the Covid-19 pandemic.