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Improving the Short-Term Forecast of World Trade During the Covid-19 Pandemic Using Swift Data on Letters of Credit

Improving the Short-Term Forecast of World Trade During the Covid-19 Pandemic Using Swift Data on Letters of Credit( )
Author: Carton, Benjamin
Hu, Nan
Mongardini, Joannes
Moriya, Kei
Radzikowski, Aneta
Series title:IMF Working Papers
ISBN:978-1-5135-6287-2
Publication Date:Nov 2020
Publisher:International Monetary Fund
Book Format:Ebook
List Price:USD $9.00
Book Description:

An essential element of the work of the Fund is to monitor and forecast international trade. This paper uses SWIFT messages on letters of credit, together with crude oil prices and new export orders of manufacturing Purchasing Managers' Index (PMI), to improve the short-term forecast of international trade. A horse race between linear regressions and machine-learning algorithms for the world and 40 large economies shows that forecasts based on linear regressions often outperform those...
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