Intelligent Export Diversification: An Export Recommendation System with Machine Learning

Natasha Che

No 2020/175, IMF Working Papers from International Monetary Fund

Abstract: 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.

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 (search for similar items in EconPapers)
Pages: 46
Date: 2020-08-28
New Economics Papers: this item is included in nep-ban and nep-ure
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Citations: View citations in EconPapers (4)

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