Appropriate Trading Partners for Iran in Importing Machinery and Transport Equipment: A Network Theory Approach

Document Type : Original Article

Authors

1 PhD in Economics, Faculty of Economics, Management and Social Sciences, Shiraz University, Shiraz, Iran,

2 Associate Professor of Economics, Faculty of Economics, Management and Social Sciences, Shiraz University, Shiraz, Iran

Abstract

Trade is crucial to international interaction, and spreading fluctuations among countries. Regarding the importance of this issue for Iran, appropriate trading partners in machinery and transport equipment in import sector are examined using network theory. Therefore, by constructing a composite index based on the structural network measures, potential trading partners for Iran are introduced. The potential trading partners' characteristics are twofold. First, the proposed trading partners can improve Iran's structural position in the international trade network. Second, the potential substitutes for current trading partners are beneficial in case current trading partners alleviate or stop their trade relations with Iran. Therefore, substituting or strengthening trade links with this group of potential trading partners can lead to an insignificant change in Iran's structural position in the international trade network. Results show that half of current major trading partners of Iran are among powerful trading partners in the international trade network with high structural characteristics. Also, potential trading partners and their substitutes are introduced using the composite index. Results imply that strengthening trade links with China, Republic of Korea, Germany, France, and Japan can enhance Iran's structural position in the trade network. Moreover, forming and consolidation of the trade linkages with the potential alternatives for UAE, Russia, Italy, Turkey, and India could lead to preservation of Iran's structural status throughout the international trade network. Trading with other potential substitutes could maintain Iran's structural position in trade networks which is more pronounced in case of any disruptions.

Keywords


- An, H., Zhong, W., Chen, Y., Li, H., & Gao, X. (2014). Features and evolution of international crude oil trade relationships: A trading-based network analysis. Energy, 74, 254-259.
- Barabási, A. L. (2016). Network science. Cambridge, United Kingdom: Cambridge University Press.
- Barigozzi, M., Fagiolo, G., & Garlaschelli, D. (2010). Multi network of international trade: A commodity-specific analysis. Physical Review E, 81(4), 046104.
- Baskaran, T., Blöchl, F., Brück, T., & Theis, F. J. (2011). The Heckscher–Ohlin model and the network structure of international trade. International Review of Economics & Finance, 20(2), 135-145.
- Borgatti, S. P., & Everett, M. G. (2000). Models of core/periphery structures. Social Networks, 21(4), 375-395.
- Cepeda-López, F., Gamboa-Estrada, F., León, C., & Rincón-Castro, H. (2019). The evolution of world trade from 1995 to 2014: A network approach. The Journal of International Trade & Economic Development, 28(4), 452–485.
- Chakrabarti, A. S. (2018). Dispersion in macroeconomic volatility between the core and periphery of the international trade network. Journal of Economic Dynamics & Control, 88, 31-50.
- Chen, Z., An, H., Gao, X., Li, H., & Hao, X. (2016). Competition pattern of the global liquefied natural gas (LNG) trade by network analysis. Journal of Natural Gas Science and Engineering, 33, 769-776.
- de Andrade, R. L., & Rêgo, L. C. (2018). The use of nodes attributes in social network analysis with an application to an international trade network. Physica A: Statistical Mechanics and its Applications, 491, 249-270.
- De Benedictis, L., Nenci, S., Santoni, G., Tajoli, L., & Vicarelli, C. (2014). Network Analysis of World Trade using the BACI-CEPII dataset. Global Economy Journal, 14(03n04), 287-343.
- Deguchi, T., Takahashi, K., Takayasu, H., & Takayasu, M. (2014). Hubs and authorities in the world trade network using a weighted HITS algorithm. PloS one9(7), e100338.
- Dejpasand, F., Alsadata Hosaini, E. & Golzarianpour, S. (2012). The Effect of the Growth of Non-Oil Exports on the Growth of Gross Domestic Products. Journal of Economics and Modeling, 3(10), 109-133 (In Persian).
- Ding, H., Jin, Y., Liu, Z., & Xie, W. (2019). The relationship between international trade and capital flow: A network perspective. Journal of International Money and Finance, 91, 1-11.
- Distefano, T., Laio, F., Ridolfi, L., & Schiavo, S. (2018). Shock transmission in the international food trade network. PloS one13(8), e0200639.
- Dong, D., Gao, X., Sun, X., & Liu, X. (2018). Factors affecting the formation of copper international trade community: Based on resource dependence and network theory. Resources Policy, 57, 167-185.
- Du, R., Dong, G., Tian, L., Wang, Y., Liu, Y., Wang, M., & Fang, G. (2016). A complex network perspective on features and evolution of world crude oil trade. Energy Procedia, 104, 221-226.
- Fagiolo, G., Reyes, J., & Schiavo, S. (2008). On the topological properties of the world trade web: A weighted network analysis. Physica A: Statistical Mechanics and its Applications, 387(15), 3868-3873.
- Fagiolo, G., Reyes, J., & Schiavo, S. (2009). World-trade web: Topological properties, dynamics, and evolution. Physical Review E, 79(3), 036115.
- Fagiolo, G. (2010). The international-trade network: Gravity equations and topological properties. Journal of Economic Interaction and Coordination, 5(1), 1-25.
- Foti, N. J., Pauls, S., & Rockmore, D.N. (2013). Stability of the world trade web over time–An extinction analysis. Journal of Economic Dynamics and Control, 37(9), 1889-1910.
- Frankel, J. A., & Romer, D. H. (1999). Does trade cause growth? American economic review, 89(3), 379-399.
- Gao, C., Sun, M., & Shen, B. (2015). Features and evolution of international fossil energy trade relationships: A weighted multilayer network analysis. Applied energy, 156, 542-554.
- Garlaschelli, D., Di Matteo, T., Aste, T., Caldarelli, G., & Loffredo, M. I. (2007). Interplay between topology and dynamics in the World Trade Web. The European Physical Journal B, 57(2), 159-164.
- Garlaschelli, D., & Loffredo, M. I. (2004). Fitness-dependent topological properties of the world trade web. Physical review letters, 93(18), 188701.
- Garlaschelli, D., & Loffredo, M. I. (2005). Structure and evolution of the world trade network. Physica A: Statistical Mechanics and its Applications, 355(1), 138-144.
- Geng, J. B., Ji, Q., & Fan, Y. (2014). A dynamic analysis on global natural gas trade network. Applied Energy, 132, 23-33.
- Hidalgo, C. A., Klinger, B., Barabási, A. L., & Hausmann, R. (2007). The product space conditions the development of nations. Science, 317(5837), 482-487.
- Jackson, M. O. (2010). Social and economic networks. Princeton and Oxford, United States of America and United Kingdom: Princeton University Press.
- Jahangard, E. (2007). Network Economics: Pricing Models of Network Products. Journal of New Economy and Commerce, 3(10), 185-214. (In Persian) 
- Jahangard, E., & Keshtvarz, V. (2013). Identifying Key Sectors in the Iranian Economy: A Network Theoretical Approach. Journal of New Economy and Commerce, 7(25), 97-119 (In Persian).
- Ji, L., Jia, X., Chiu, A. S., & Xu, M. (2016). Global electricity trade network: Structures and implications. PloS one, 11(8), e0160869.
- Ji, Q., Zhang, H. Y., & Fan, Y. (2014). Identification of global oil trade patterns: An empirical research based on complex network theory. Energy Conversion and Management, 85, 856-865.
- Jolliffe, I. T. (2002). Principal component analysis. New York, United States of America: Springer.
- Joshi, S., & Mahmud, A. S. (2018). Unilateral and multilateral sanctions: A network approach. Journal of Economic Behavior & Organization, 145, 52-65.
- Li, X., Jin, Y. Y., & Chen, G. (2003). Complexity and synchronization of the world trade web. Physica A: Statistical Mechanics and its Applications, 328(1-2), 287-296.
- Mohaddes, F. (2010). Principal Component and Factor Analysis Case Study: Assets Price Evaluation and Inflation Impacts. Economic Research and Policy Department Central Bank of the Islamic Republic of Iran. 41, 1-56 (In Persian).
-Nemeth, R.J., & Smith, D. A. (1985). International trade and world-system structure: A multiple network analysis. Review (Fernand Braudel Center), 8(4), 517-560.
- Newman, M.E. (2010). Networks: An introduction. Oxford, United Kingdom: Oxford University Press.
- Newman, M. E. (2006). Modularity and community structure in networks. Proceedings of the national academy of sciences, 103(23), 8577-8582.
- Newman, M. E. (2003). The structure and function of complex networks. SIAM review, 45(2), 167-256.
- Ohadi Esfahani, S., Tayebi, S. & Vaez Barzani, M. (2017). Effect of Technological Gap on Iran's Bilateral Relations: A Semi-Parametric Approach. Journal of Economics and Modeling, 8(31), 1-26. (In Persian)
- Önder, A. S., & Yilmazkuday, H. (2016). Trade partner diversification and growth: How trade links matter. Journal of Macroeconomics, 50, 241-258.
- Picciolo, F., Squartini, T., Ruzzenenti, F., Basosi, R., & Garlaschelli, D. (2012). The role of distances in the World Trade Web. Eighth International Conference on Signal Image Technology and Internet Based Systems (784-792). Naples: IEEE.
- Rauch, J.E. (1999). Networks versus markets in international trade. Journal of international Economics, 48(1), 7-35.
- Rubinov, M., & Sporns, O. (2010). Complex network measures of brain connectivity: uses and interpretations. Neuroimage, 52(3), 1059-1069.
- Sajedianfard, N. (2020). Appropriate Trading Partners for Iran: A Network Theory Approach. PhD Dissertation. Shiraz University (In Persian).
- Sajedianfard, N., Hadian, E., Samadi, A., & Dehghan Shabani, Z. (2019). Investigating the Effect of International Sanctions on Iran's Trade Structure: A Network Theory Approach. Journal of Economics and Modeling, 10(3), 1-29 (In Persian).
- Samadi A.H., & Zahedi S. (2019). Analyzing Stability of Global Natural Gas Trade Network: An Application of Complex Network Theory. Quarterly Journal of Energy Policy and Planning Research, 4(4), 7-40 (In Persian).
- Serrano, M.A., & Boguñá, M. (2003). Topology of the world trade web. Physical Review E, 68(1), 015101.
- Shirazi, H., Azarbaiejani, K., Sameti, M. (2015). Study of Iran’s Position in the world trade: A network approach. Journal of Economic Research (Tahghighat- E- Eghtesadi), 50(4), 881-902 (In Persian).
- Skowron, P., Karpiarz, M., Fronczak, A., & Fronczak, P. (2014). Spanning trees of the World Trade Web: Real-world data and the gravity model of trade. arXiv preprint arXiv:1412.1618.
- Smith, D. A., & White, D. R. (1992). Structure and dynamics of the global economy: Network analysis of international trade 1965–1980. Social forces, 70(4), 857-893.
- Snyder, D., & Kick, E. L. (1979). Structural position in the world system and economic growth, 1955-1970: A multiple-network analysis of transnational interactions. American journal of Sociology, 84(5), 1096-1126.
- Squartini, T., & Garlaschelli, D. (2014). Jan Tinbergen’s legacy for economic networks: From the gravity model to quantum statistics. Econophysics of Agent-Based Models, 161-186.
- Steiber, S.R. (1979). The world system and world trade: An empirical exploration of conceptual conflicts. The Sociological Quarterly, 20(1), 23-36.
- Stone, R. (1947). On the interdependence of blocks of transactions. Supplement to the Journal of the Royal Statistical Society, 9(1), 1-45.
- Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. Cambridge, United Kingdom: Cambridge university press.
- Zhang, H. Y., Ji, Q., & Fan, Y. (2014). Competition, transmission and pattern evolution: A network analysis of global oil trade. Energy Policy, 73, 312-322.
- Zhong, W., An, H., Gao, X., & Sun, X. (2014). The evolution of communities in the international oil trade network. Physica A: Statistical Mechanics and its Applications, 413, 42-52.