Intelligent Export Diversification: An Export Recommendation System with Machine Learning

47 Pages Posted: 30 Oct 2020

Date Written: August 1, 2020

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: Exports, Export diversification, Comparative advantage, Machine learning, Personal income, WP, graphic tag0, SITC product lists, price boom, product-space literature, country-product space, export basket, export product, KNN implementation

JEL Classification: O1, F10, F11, O33, D31

Suggested Citation

Che, Natasha Xingyuan, Intelligent Export Diversification: An Export Recommendation System with Machine Learning (August 1, 2020). IMF Working Paper No. 20/175, Available at SSRN: https://ssrn.com/abstract=3721200

Natasha Xingyuan Che (Contact Author)

International Monetary Fund (IMF) ( email )

700 19th Street, N.W.
Washington, DC 20431
United States

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