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Intelligent Export Diversification: An Export Recommendation System with Machine Learning
Author:
Ms. Natasha X Che
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Series:
IMF Working Papers
Volume/Issue:
Volume 2020: Issue 175
Language:
English
Publication Date:
28 Aug 2020
DOI:
https://doi.org/10.5089/9781513555959.001
ISBN:
9781513555959
ISSN:
1018-5941
Pages:
46
Keywords:
WP; SITC product lists; price boom; product-space literature; country-product space; export basket; export product; KNN implementation; export diversificiation; comparative advantage; machine learning; collaborative filtering; economic growth; international trade; RCA export; export structure; diversification strategy; KNN recommender; export diversification recommendation; product name; Exports; Export diversification; Personal income; East Asia; Caribbean; Africa; Global; export diversification strategy
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IMF Working Papers describe research in progress by the author(s) and are published to elicit comments and to encourage debate. The views expressed in IMF Working Papers are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management.
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This paper presents a set of collaborative filtering algorithms that produce product recommendations to diversify and optimize a country's export structure in support of sustainable long-term growth. The recommendation system is able to accurately predict the historical trends in export content and structure for high-growth countries, such as China, India, Poland, and Chile, over 20-year spans. As a contemporary case study, the system is applied to Paraguay, to create recommendations for the country's export diversification strategy.
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Cover IMF Working Papers
IMF Working Papers
ISSN:
1018-5941
Publisher:
International Monetary Fund