Name
Abstract | ||
|---|---|---|
We use social network analysis to model the trade networks that connect each of the United States to the rest of the world in an effort to capture trade shocks and supply chain disruptions resulting from the COVID-19 pandemic and, more specifically, to capture how such disruptions propagate through those networks. The results show that disruptions will noticeably move along industry connections, spreading in specific patterns. Our results are also consistent with past work that shows that non-pharmaceutical policy interventions have had limited impact on trade flows. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1007/978-3-030-93409-5_59 | COMPLEX NETWORKS & THEIR APPLICATIONS X, VOL 1 |
Keywords | DocType | Volume |
Trade, Supply chains, Social network analysis | Conference | 1015 |
ISSN | Citations | PageRank |
1860-949X | 0 | 0.34 |
References | Authors | |
0 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| John Schoeneman | 1 | 0 | 0.34 |
| Marten Brienen | 2 | 0 | 0.34 |