A Study of the World Cotton Trade Network and Its Formation Mechanism Based on Dependency Perspective

  • LI Min ,
  • CAO Cheng
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  • South China University of Technology, Guangzhou 511400, China

Received date: 2023-01-11

  Online published: 2023-06-05

Abstract

Compared with the traditional network index, introducing the concept of "dependency" into the cotton trade network can reveal the characteristics of cotton trade more accurately. Based on the new trade dependence index, this paper constructs the 1999-2019 world cotton trade dependence network, analyzes the import and export trade dependence network of core trading countries in the past two decades, and uses temporal random index graph model to study. The results are as follows: (1) The countries with increased cotton import dependence are mainly distributed in Asia, and the network of export dependence is more concentrated than that of import dependence, and its network centers are mainly concentrated in Europe and America. (2) The rapid increase of China's cotton import dependence is reflected in the diversification of the dependent objects and the deepening of the dependence degree, and the sharp decline of export dependence is mainly due to the separation of low-dependent countries. (3) The formation of cotton trade dependence has the characteristics of ternary transmission, and the establishment of export dependence has the characteristics of "preference connection". A few countries with export dependence can further promote the formation of dependency through the dominant position established in the network. (4) Both the border relationship and the interactive nature of the free trade agreement between the two countries can significantly promote the formation of the cotton trade dependence relationship, but the economic level has a heterogeneous effect on the formation of the dependence relationship. Compared with low-income countries, middle-income countries are prone to import dependence, while high-income countries tend to form two-way import and export dependence. From the perspective of deepening international trade cooperation and optimizing the layout of the cotton industry, we can improve China's foreign dependence on cotton trade in the future.

Cite this article

LI Min , CAO Cheng . A Study of the World Cotton Trade Network and Its Formation Mechanism Based on Dependency Perspective[J]. Finance & Economics of Xinjiang, 2023 , 0(3) : 17 -28 . DOI: 10.16716/j.cnki.65-1030/f.2023.03.002

References

[1] BENEDICTIS L D, TAJOLI L. The world trade network[J]. World economy, 2011(8):1417-1454.
[2] 王健, 董俊哲, 陈浩, 等. 全球棉花进出口贸易分析及展望[J]. 棉纺织技术, 2018(3):81-84.
[3] 孙洁. 棉花价格波动对我国纺织品出口贸易的影响及其对策[J]. 价格月刊, 2015(2):66-69.
[4] GRANOVETTER M S. Economic action and social structure:the problem of embeddedness[J]. Administrative science quarterly, 1984(19):481-510.
[5] ARTHUR W B, DURLAUF S N, LANR D A. The economy as an evolving complex system II[M]. Reading: Addison-Wesley Publishing Company, 1997.
[6] JACKSON M O. An overview of social networks and economic applications[J]. Handbook of social economics, 2011(1):511-585.
[7] 程中海, 冯梅. 基于动态复杂网络的世界棉花贸易时空分异特征与贸易格局分析[J]. 国际经贸探索, 2017(10):36-50.
[8] 刘婷婷, 张蕙杰, 康永兴, 等. 社会网络视角下的全球棉花贸易格局分析[J]. 世界农业, 2022(4):26-36.
[9] BURT R S. The social structure of competition[M]. Boston: Harvard University Press, 1992.
[10] FRANKEL J A. Regional trading blocs in the world economic system[M]. Washington DC: Institute for International Economics, 1997.
[11] HAVENS R M, BALASSA B. The theory of economic integration[J]. Southern economic journal, 1962(1):47.
[12] HIRSCH J E, MEHO L I. On the relationship between the ISI impact factor and the number of citations received by papers[J]. Journal of the american society for information science and technology, 2004(10):32-41.
[13] 刘林青, 闫小斐, 杨理斯, 等. 国际贸易依赖网络的演化及内生机制研究[J]. 中国工业经济, 2021(2):98-116.
[14] 段文奇, 刘宝全, 季建华. 国际贸易网络拓扑结构的演化[J]. 系统工程理论与实践, 2008(10):71-75+81.
[15] RAUCH J E. Business and social networks in international trade[J]. Journal of economic literature, 2001(4):1177-1203.
[16] 戴卓. 国际贸易网络结构的决定因素及特征研究:以中国东盟自由贸易区为例[J]. 国际贸易问题, 2012(12):72-83.
[17] FAGIOLO G, REYES J, SCHIAVO S. The evolution of the world trade web:a weighted-network analysis[J]. Journal of evolutionary economics, 2010(4):479-514.
[18] 刘华军, 杜广杰. 中国雾霾污染的空间关联研究[J]. 统计研究, 2018(4):3-15.
[19] 唐晓彬, 崔茂生. “一带一路”货物贸易网络结构动态变化及其影响机制[J]. 财经研究, 2020(7):138-153.
[20] CAO D P, LI H, WANG G B, et al. Dynamics of project-based collaborative networks for BIM implementation:analysis based on stochastic actor-oriented models[J]. Journal of management in engineering, 2017(3):1-12.
[21] FINGER K, LUX T. Network formation in the interbank money market:an application of the actor-oriented model[J]. Social networks, 2017(48):237-249.
[22] RONBINS G, SNIJDERS T, WANG P, et al. Recent developments in exponential random graph (p*) models for social networks[J]. Social networks, 2007(2):192-215.
[23] 刘林青, 陈紫若. 中国优势产业组合的动态演化机制研究:基于TERGM的实证分析[J]. 科技进步与对策, 2020(11):70-78.
[24] 许和连, 孙天阳, 成丽红. “一带一路”高端制造业贸易格局及影响因素研究:基于复杂网络的指数随机图分析[J]. 财贸经济, 2015(12):74-88.
[25] 孙忆, 孙宇辰. 自由贸易协定能提升国家间亲密度吗?:基于中国周边FTA的实证分析[J]. 世界经济与政治, 2017(4):129-154+160.
[26] 汪亚楠, 王海成, 张夏. 自由贸易协定对贸易政策不确定性的影响研究[J]. 宏观经济研究, 2021(7):26-37.
[27] LEIFELD P, CRANMERS S J, DESMARAIS B A. Temporal exponential random graph models with btergm:estimation and bootstrap confidence intervals[J]. Journal of statistical software, 2018(6):1-36.
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