Nowcasting Country-Level Trade Estimates Using IMF PortWatch

Serkan Arslanalp, Oliver Exton, Chang Gao, Mario Saraiva, Parisa Kamali, Alessandra Sozzi and Jasper Verschuur

No 2026/099, IMF Working Papers from International Monetary Fund

Abstract: This paper develops high frequency trade estimates at the country level by applying nowcasting methodologies to satellite-based big data on vessel movements sourced from IMF PortWatch. The approach provides a timely estimate of monthly trade at the country level that can be produced and released within 7 working days. The paper validates the nowcasting trade estimates against official data for an initial wave of countries representing advanced economies, emerging markets and small island developing states: Brazil, Jamaica, Japan, Samoa, and the United States. The nowcasting methodology produces trade estimates that perform well compared to the official statistics, with the best fit for advanced economies and large emerging markets. The paper identifies key complementary information to improve the presented nowcasting methodology to develop country trade estimates. The paper also considers an application to estimates of U.S. imports during a period of elevated trade tensions.

Keywords: Nowcasting; maritime trade; big data (search for similar items in EconPapers)
Pages: 39
Date: 2026-05-22
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.imf.org/external/pubs/cat/longres.aspx?sk=576176 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:imf:imfwpa:2026/099

Ordering information: This working paper can be ordered from
http://www.imf.org/external/pubs/pubs/ord_info.htm

Access Statistics for this paper

More papers in IMF Working Papers from International Monetary Fund International Monetary Fund, Washington, DC USA. Contact information at EDIRC.
Bibliographic data for series maintained by Akshay Modi ().