Comparative Studies on Trade and Value-Added Trade along the “Belt and Road”: A Network Analysis
With the deepening of regional industrial transfer, traditional trade data cannot fully explain the real level of trade in a region. This paper aims to reveal the changing pattern of real trade along the “Belt and Road” by establishing a value-added trade (VAT) network of the “Belt and Road” countri...
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/3994004 |
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| author | Guangjun Sui Jialing Zou Shuang Wu Danling Tang |
| author_facet | Guangjun Sui Jialing Zou Shuang Wu Danling Tang |
| author_sort | Guangjun Sui |
| collection | DOAJ |
| description | With the deepening of regional industrial transfer, traditional trade data cannot fully explain the real level of trade in a region. This paper aims to reveal the changing pattern of real trade along the “Belt and Road” by establishing a value-added trade (VAT) network of the “Belt and Road” countries and comparing it with the trade network. Applying a network method, we analyze and compare the structures, characteristics, evolutions, and underlying dynamisms of both networks. With a thorough interpretation and visualization of the network density, network centrality, trade communities, and influencing factors of both networks in the three time sections of 2005, 2010, and 2015, we come to the following findings: (1) the connectivity of both networks has been greatly enhanced, reflecting a more integrated regional economy. (2) The center-external structure of both networks has been further strengthened and the polarization of the VAT network is more obvious than that of the trade network. (3) The organizations of trade communities and VAT communities are largely different. Specifically, China rapidly increased its core position in the VAT network and incorporated more and more countries into its VAT community. (4) The underlying factors have similar impacts on both networks. While the growth of regional economic size and free trade agreements will enhance both trade and VAT, the economic gaps and population differences among the “Belt and Road” countries will prohibit regional economic ties. Based on these findings, we propose suggestions on further regional economic cooperation by taking advantage of China’s core position to promote regional VAT, construct broad trade channels, and enhance trade governance. |
| format | Article |
| id | doaj-art-a03e59cd93dc4baf9e1a09fcc9b21a0d |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-a03e59cd93dc4baf9e1a09fcc9b21a0d2025-02-03T06:12:51ZengWileyComplexity1076-27871099-05262021-01-01202110.1155/2021/39940043994004Comparative Studies on Trade and Value-Added Trade along the “Belt and Road”: A Network AnalysisGuangjun Sui0Jialing Zou1Shuang Wu2Danling Tang3Guangdong Institute for International Strategies, Guangdong University of Foreign Studies, Guangzhou 510420, ChinaGuangdong Institute for International Strategies, Guangdong University of Foreign Studies, Guangzhou 510420, ChinaDivision of Humanities and Social Sciences, Beijing Normal University-Hong Kong Baptist University United International College, Zhuhai 519087, ChinaSouthern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou, ChinaWith the deepening of regional industrial transfer, traditional trade data cannot fully explain the real level of trade in a region. This paper aims to reveal the changing pattern of real trade along the “Belt and Road” by establishing a value-added trade (VAT) network of the “Belt and Road” countries and comparing it with the trade network. Applying a network method, we analyze and compare the structures, characteristics, evolutions, and underlying dynamisms of both networks. With a thorough interpretation and visualization of the network density, network centrality, trade communities, and influencing factors of both networks in the three time sections of 2005, 2010, and 2015, we come to the following findings: (1) the connectivity of both networks has been greatly enhanced, reflecting a more integrated regional economy. (2) The center-external structure of both networks has been further strengthened and the polarization of the VAT network is more obvious than that of the trade network. (3) The organizations of trade communities and VAT communities are largely different. Specifically, China rapidly increased its core position in the VAT network and incorporated more and more countries into its VAT community. (4) The underlying factors have similar impacts on both networks. While the growth of regional economic size and free trade agreements will enhance both trade and VAT, the economic gaps and population differences among the “Belt and Road” countries will prohibit regional economic ties. Based on these findings, we propose suggestions on further regional economic cooperation by taking advantage of China’s core position to promote regional VAT, construct broad trade channels, and enhance trade governance.http://dx.doi.org/10.1155/2021/3994004 |
| spellingShingle | Guangjun Sui Jialing Zou Shuang Wu Danling Tang Comparative Studies on Trade and Value-Added Trade along the “Belt and Road”: A Network Analysis Complexity |
| title | Comparative Studies on Trade and Value-Added Trade along the “Belt and Road”: A Network Analysis |
| title_full | Comparative Studies on Trade and Value-Added Trade along the “Belt and Road”: A Network Analysis |
| title_fullStr | Comparative Studies on Trade and Value-Added Trade along the “Belt and Road”: A Network Analysis |
| title_full_unstemmed | Comparative Studies on Trade and Value-Added Trade along the “Belt and Road”: A Network Analysis |
| title_short | Comparative Studies on Trade and Value-Added Trade along the “Belt and Road”: A Network Analysis |
| title_sort | comparative studies on trade and value added trade along the belt and road a network analysis |
| url | http://dx.doi.org/10.1155/2021/3994004 |
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