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| Funder | National Science Foundation (US) |
|---|---|
| Recipient Organization | National Bureau of Economic Research Inc |
| Country | United States |
| Start Date | Aug 01, 2022 |
| End Date | Jul 31, 2026 |
| Duration | 1,460 days |
| Number of Grantees | 2 |
| Roles | Principal Investigator; Co-Principal Investigator |
| Data Source | National Science Foundation (US) |
| Grant ID | 2214852 |
Modern economies rely on complex supply chains for production. These more-complex supply chains lower the cost of production, increasing the standard of living across the world. These complex, global supply chains, however, are more vulnerable to disruption: extreme weather, trade disagreements, cyber attacks, and, most noticeably, the closing and reopening of the global economy in response to the COVID pandemic.
This project will investigate the impact of supply disruptions on aggregate outcomes such as gross domestic product, employment, and prices. Can large supply disruptions cause recessions? Inflation?
The models developed in the project will measure the contribution of supply disruptions to the performance of the U.S. economy. A second goal of the proposed research is to model the ways in which firms respond to the risk of supply disruption. How do firms use inventories and transportation modalities to guard against supply disruptions?
The framework developed in this project can be used to evaluate the effectiveness of government policies such as infrastructure investment or risk mitigation measures.
Standard dynamic stochastic general equilibrium models are not well-suited to study supply disruptions because they typically abstract from supply chains. The proposed research builds on firm-level models in which firms face uncertain demand and uncertain delivery of inputs. Ordering goods requires paying a fixed cost and time to deliver, so firms hold inventories to buffer against supply and demand shocks.
This model of a firm is embedded into a two country, general equilibrium model with aggregate shocks to productivity and shipping delays. Firms infrequently place orders and a common shock to the time it takes to receive inputs can generate non-linear responses. The model will be parameterized so that it fits key features of the aggregate data allowing a decomposition of the importance of each shock during episodes such as the post-covid reopening of the economy.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
National Bureau of Economic Research Inc
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