Bill of Lading Data in International Trade Research with an Application to the COVID-19 Pandemic
Logan Lewis (),
Anderson Monken (),
Justin Pierce (),
Rosemary Rhodes and
No 2021-066, Finance and Economics Discussion Series from Board of Governors of the Federal Reserve System (U.S.)
We evaluate high-frequency bill of lading data for its suitability in international trade research. These data offer many advantages over both other publicly accessible official trade data and confidential datasets, but they also have clear drawbacks. We provide a comprehensive overview for potential researchers to understand these strengths and weaknesses as these data become more widely available. Drawing on the strengths of the data, we analyze three aspects of trade during the COVID-19 pandemic. First, we show how the high-frequency data capture features of the within-month collapse of trade between the United States and India that are not observable in official monthly data. Second, we demonstrate how U.S. buyers shifted their purchases across suppliers over time during the recovery. And third, we show how the data can be used to measure vessel delivery bottlenecks in near real time.
Keywords: Bill of lading; COVID-19 trade; Firm-level trade (search for similar items in EconPapers)
JEL-codes: C81 F14 F17 (search for similar items in EconPapers)
Pages: 40 p.
New Economics Papers: this item is included in nep-int
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2) Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:fip:fedgfe:2021-66
Access Statistics for this paper
More papers in Finance and Economics Discussion Series from Board of Governors of the Federal Reserve System (U.S.) Contact information at EDIRC.
Bibliographic data for series maintained by Ryan Wolfslayer ; Keisha Fournillier ().