Enhancing countries' fitness with recommender systems on the international trade network

Hao Liao, Xiao-Min Huang, Xing-Tong Wu, Ming-Kai Liu, Alexandre Vidmer, Mingyang Zhou and Yi-Cheng Zhang

Abstract: Prediction is one of the major challenges in complex systems. The prediction methods have shown to be effective predictors of the evolution of networks. These methods can help policy makers to solve practical problems successfully and make better strategy for the future. In this work, we focus on exporting countries' data of the international trading network. A recommendation system is then used to identify the products corresponding to the production capacity of each individual country, but are somehow overlook by the country. Then, we simulate the evolution of the country's fitness if it would have followed the recommendations. The result of this work is the combination combine these two methods to provide insights to countries on how to enhance the diversification of their exported products in a scientific way and improve national competitiveness significantly, especially for developing countries.

Date: 2019-04
New Economics Papers: this item is included in nep-int
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1904.02412

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