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The Middle-Income Trap and the Coping Strategies From Network-Based Perspectives

Guangdong Province Key Laboratory of Popular High Performance Computers, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, China
Author to whom correspondence should be addressed.
Entropy 2018, 20(10), 803;
Received: 30 July 2018 / Revised: 15 October 2018 / Accepted: 15 October 2018 / Published: 18 October 2018
(This article belongs to the Special Issue Economic Fitness and Complexity)
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When a developing country reaches a relatively average income level, it often stops growing further and its income does not improve. This is known as the middle-income trap. How to overcome this trap is a longstanding problem for developing countries, and has been studied in various research fields. In this work, we use the Fitness-Complexity method (FCM) to analyze the common characteristics of the countries that successfully get through the middle-income trap, and show the origin of the middle-income trap based on the international trade network. In the analysis, a novel method is proposed to characterize the interdependency between products. The results show that some middle-complexity products depend much on each other, which indicates that developing countries should focus on them simultaneously, implying high difficulty to escape the middle-income trap. To tackle the middle-income trap, developing countries should learn experiences from developed countries that share similar development history. we then design an effective method to evaluate the similarity between countries and recommend developed countries to a certain developing country. The effectiveness of our method is validated in the international trade network. View Full-Text
Keywords: fitness; complexity; economics; middle-income trap; complex network fitness; complexity; economics; middle-income trap; complex network

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Zhou, M.-Y.; Xiong, W.-M.; Li, X.-Y.; Liao, H. The Middle-Income Trap and the Coping Strategies From Network-Based Perspectives. Entropy 2018, 20, 803.

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