Another Piece of the Puzzle: Adding Swift Data on Documentary Collections to the Short-Term Forecast of World Trade

Narek Ghazaryan, Alexei Goumilevski, Joannes Mongardini and Aneta Radzikowski

No 2021/293, IMF Working Papers from International Monetary Fund

Abstract: This paper extends earlier research by adding SWIFT data on documentary collections to the short-term forecast of international trade. While SWIFT documentary collections accounted for just over one percent of world trade financing in 2020, they have strong explanatory power to forecast world trade and national trade in selected economies. The informational content from documentary collections helps improve the forecast of world trade, while a horse race with machine learning algorithms shows significant non-linearities between trade and its determinants during the Covid-19 pandemic.

Keywords: SWIFT; trade forecast; machine learning; trade message; IMF working papers; DFM forecast; IMF working paper No. 21/293; linear regression forecast; Merchandise export; Imports; Exports; Credit; Trade finance; Trade balance; Global; Australia and New Zealand; Asia and Pacific (search for similar items in EconPapers)
Pages: 63
Date: 2021-12-17
New Economics Papers: this item is included in nep-big, nep-cmp, nep-int and nep-pay
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