IMF Working Papers

Intelligent Export Diversification: An Export Recommendation System with Machine Learning

By Natasha X Che

August 28, 2020

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Format: Chicago

Natasha X Che. Intelligent Export Diversification: An Export Recommendation System with Machine Learning, (USA: International Monetary Fund, 2020) accessed December 21, 2024

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Summary

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.

Subject: Comparative advantage, Export diversification, Exports, International trade, Machine learning, National accounts, Personal income, Technology

Keywords: Africa, Caribbean, Collaborative filtering, Comparative advantage, Country-product space, Diversification strategy, East Asia, Economic growth, Export basket, Export diversification, Export diversification recommendation, Export diversification strategy, Export diversificiation, Export product, Export structure, Exports, Global, International trade, KNN implementation, KNN recommender, Machine learning, Personal income, Price boom, Product name, Product-space literature, RCA export, SITC product lists, WP

Publication Details

  • Pages:

    46

  • Volume:

    ---

  • DOI:

    ---

  • Issue:

    ---

  • Series:

    Working Paper No. 2020/175

  • Stock No:

    WPIEA2020175

  • ISBN:

    9781513555959

  • ISSN:

    1018-5941