Trade Partners Diversity Indicators of Iran and Asian Countries in International Trade; A Approach of Weighted Complex Network

Document Type : Research Paper

Authors

1 PhD Student, Department of Economics, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran

2 Department of Economics, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran

3 Associate Professor, Department of Management, Mobarekeh Branch, Islamic Azad University, Mobarekeh, Iran

Abstract

International trade studies indicate that trade relations of countries at the global and regional levels can be considered as a network and with this network and its indicators; the position of each country and region can be examined and analyzed. In examining the position of countries and their trade partners, unlike bilateral methods that examine only direct trade relations, the approach of network analysis and the resulting statistics -which are known as the indicators of trade partners’ diversity- can consider indirect trade relations and intermediary countries in trade networks. Statistics such as number of partners, degree of intensity, indicators of centrality and central position of each partner in the trade network, can be help to identify and explore connections, and to get a deeper visual understanding of a country's position in the regions and its hidden capacities in the trade network. As a result, the interactions of trade relations (direct and indirect) of all countries with each other can be revealed. This study is based on constructing a weighted matrix of trade relations network of all countries in five periods since 1998 to 2018. The results show that the of Iran's trade position has weakened during the reviewed periods and its network indicators have become more fragile after the sanctions. Based on the ranking of the mixed index obtained from the principal components of the trade partners’ diversity indicators, the appropriate trading partners for Iran in order of priority are: China, Japan, India, South Korea, Thailand, Singapore, Taiwan, UAE, Indonesia, Hong Kong, Turkey, Malaysia, Pakistan, Saudi Arabia and the Philippines. however, Iran has not been able to fully benefit from the trade capacities of the candidate countries in trade relations.

Keywords


  1. .Benedicts, L., Nenci, S., Santoni, G., Tajoli, L. & Vicarelli, C. (2014). Network Analysis of World Trade Using the BACI-CEPII Dataset. Global Economy Journal, 14(3-4), 287-343.

    Baskaran. T., Blochl. F., Bruck. T. & Fabian. J. T. (2011). The Heckscher-Ohlin Model and the Network Structure of International Trade. International Review of Economics and Finance, 20(2), 135-145

    Beaton, K., Cebotari, A., Ding, X., & Komaromi, A. (2017).Trade Integration in Latin America: A Network Perspective. IMF Working Paper, 17(48), 2-34

    Bhattacharya, K. Mukherjee, G. Sarämaki, J. Kaski, K. & Manna, S.(2008).The International Trade Network: Weighted Network Analysis and Modeling, Journal of Statistical Mechanics: Theory and Experiment, doi: 10.1088/1742-5468/2008/02/P02002.

    Cepeda-López, Freddy. Gamboa-Estrada, Fredy. León, Carlos and Rincón-Castro, Hernán. (2018).The Evolution of World Trade from 1995 to 2014: A Network Approach, The journal of International trade & Economic development, 28(4), 452-485

    Fagiolo, G., Rayes, J. & Schiavo, S. (2008). On the Topological Properties of the World Trade Web: A Weighted Network Analysis, Physica A: Statistical Mechanics and its Applications, Elsevier, 387(15), 3868-3873

    Fagiolo, G., Reyes, J., & Schiavo, S. (2010). The Evolution of the World Trade Web: a Weighted-Network Analysis. Journal of Evolutionary Economics, 20(4), 479-514.

    Fan, Ying. Ren, Suting. Cai, Hongbo. Cui, Xuefeng. (2014). The State’s Role and Position in International Trade: A Complex Network Perspective. Economic Modelling, 39, 71-81

    Garlaschelli, D. & Loffredo, M.L. (2004). Fitness-Dependent Topological Properties of the World Trade Web, Physical Review Letters, 93(18), 1-4.

    Garlaschelli, D. & Loffredo, M.L. (2005). Structure and Evolution of the World Trade, Physica A 355, 138-144

    Grassi, R. Bartesaghi, P. Benati, S., Clemente, G. P. (2021). Multi-Attribute Community Detection in International Trade Network. Networks and Spatial Economics , 21,  707-733

    Huang, S., Gou, W., Cai, H., Li, X., & Chen, Q. (2020). Effects of Regional Trade Agreement to Local and Global Trade Purity Relationships.Complexity, doi:10.1155/2020/2987217

    Jackson, Matthew. (2008). Social and Economic Networks, Princeton University Press

    Jolliffe, I. T. (2002). Principal component analysis. New York, United States of America: Springer.

    Kali, R. Reyes, J. (2007).The Architecture of Globalization: A Network Approach to International Economic Integration, Journal of International Business Studies, 38(4), 595- 620

    Kastelle.Tim. Liesch .Peter W.(2013).The Importance of Trade in Economic Development ; Australia in the International Trade Network, International Studies of Management & Organization, 43(2), 6-29

    Kharrazi, Ali. Yu, Yadong. Jacob, Arun. Vora, Nemi. Fath, Brian D. (2020). Redundancy, Diversity, and Modularity in Network Resilience: Applications for International Trade and Implications for Public Policy, Current Research in Environmental Sustainability, doi:10.1016/j.crsust.2020.06.001

    Liao,H. & Vidmer,A.(2018).A Comparative Analysis of the Predictive Abilities of Economic Complexity Metrics Using International Trade Network, Hindawi , Article ID 2825948, doi:10.1155/2018/2825948

    Maluck, Julian, Donner, Reik V. (2015). A Network of Networks Perspective on Global Trade, PLoS ONE, 10(7): e0133310, doi:10.1371/journal.pone.0133310

    Newman, M. E. (2010). Networks: An introduction. Oxford, United Kingdom: Oxford University Press

    1. Albert and A.-L. Barabasi, Statistical Mechanics of Complex Networks, Reviews of Modern Physics, 74 (1): 47-97

    Rayes, J. Schiavo, S .Fagiolo.(2014).Using Complex Network Analysis to Assess the Evolution of International Economic Integration: The Cases of East Asia and Latin America, The Journal of International Trade & Economic Development,19 , 215-239

    Sbardella, Angelica. Pugliese, Emanuele. Zaccaria ,Andrea . Scaramozzino, Pasquale. (2018). The Role of Complex Analysis in Modelling Economic Growth, Entropy, 20, 883 doi:10.3390/e20110883

    Serrano, M. & Boguna, M.(2003). Topology of the World Trade Web, Physical Review E., 68(1), 1-5.

    Zaclicever, Dayna.(2019). A Network Analysis Approach to Vertical Trade Linkages: the Case of Latin America and Asia, International Trade Series, No. 147 ISSN: 1680-872X (Electronic Version)

    Zhang, Panpan, Wang, Tiandong, Yan, Jun .(2022) .PageRank Centrality and Algorithms for Weighted, Directed Networks with Applications to World Input-Output Tables, Physica A: Statistical Mechanics and its Applications, Volume 586, doi:10.48550/arXiv.2104.02764

    Önder, A. S., & Yilmazkuday, H. (2016). Trade Partner Diversification and Growth: How Trade Links Matter. Journal of Macroeconomics, 50, 241-258.