The evolution of the energy import dependence network and its influencing factors: taking countries and regions along the Belt and Road as an example
Abstract
This paper provides the concept of import dependence between countries, which is a relative quantity. In order to reveal the evolutionary characteristics of the import dependence between countries in energy trade and its influencing factors, firstly, based on the network analysis method, this paper constructs a model of energy import dependence network (EIDN) among countries and regions along the Belt and Road (B&R countries). Crude oil and natural gas are taken as empirical objects, and the evolution characteristics of the two kinds of EIDNs are analysed. The result showed that most of the B&R countries had a small number of crude oil and natural gas trade partners. However, the import dependence in crude oil and natural gas trade between countries is relatively large, indicating that the risk of oil and gas security in B&R countries is high. Moreover, based on the QAP method, spatial distance, economic differences, the signing of free trade agreements, and the differences in energy consumption between countries have a significant impact on the import dependence in crude oil and natural gas trade among B&R countries.
First published online 30 November 2021
Keyword : energy trade, import dependence, influencing factors, QAP method, network analysis, B&R countries
How to Cite
Sun, Q., Gao, X., Si, J., Xi, X. ., Liu, S., Zheng, H., & Liang, W. (2022). The evolution of the energy import dependence network and its influencing factors: taking countries and regions along the Belt and Road as an example. Journal of Business Economics and Management, 23(1), 105–130. https://doi.org/10.3846/jbem.2021.15661
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Petreski, M. (2013). Southeastern European trade analysis: A role for endogenous CEFTA-2006? Emerging Markets Finance & Trade, 49(5), 26–44. https://doi.org/10.2753/REE1540-496X490502
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Spring, E., & Grossmann, V. (2016). Does bilateral trust across countries really affect international trade and factor mobility? Empirical Economics, 50, 103–136. https://doi.org/10.1007/s00181-015-0915-1
Sun, Q. R., Gao, X. Y., Zhong, W. Q., & Liu, N. R. (2017). The stability of the international oil trade network from short-term and long-term perspectives. Physica a-Statistical Mechanics and Its Applications, 482, 345–356. https://doi.org/10.1016/j.physa.2017.04.047
Sun, X. L., Liu, C., Chen, X. W., & Li, J. P. (2017). Modeling systemic risk of crude oil imports: Case of China’s global oil supply chain. Energy, 121, 449–465. https://doi.org/10.1016/j.energy.2017.01.018
Vivoda, V. (2019). LNG import diversification and energy security in Asia. Energy Policy, 129, 967–974. https://doi.org/10.1016/j.enpol.2019.01.073
Wang, J., Sun, X. L., Li, J. P., Chen, J. M., & Liu, C. (2018). Has China’s oil-import portfolio been optimized from 2005 to 2014? A perspective of cost-risk tradeoff. Computers & Industrial Engineering, 126, 451–464. https://doi.org/10.1016/j.cie.2018.10.005
Wang, M., & Kong, R. (2019). Study on the characteristics of potassium salt international trade based on complex network. Journal of Business Economics and Management, 20(5), 1000–1021. https://doi.org/10.3846/jbem.2019.10455
Wu, Z. N., Cai, H. B., Zhao, R. N., Fan, Y., Di, Z. R., & Zhang, J. (2020). A topological analysis of trade distance: Evidence from the gravity model and complex flow networks. Sustainability, 12(9), 3511. https://doi.org/10.3390/su12093511
Xie, M. J. (2018). Can cultural affinity promote trade? HSK test data from the belt and road countries. China & World Economy, 26(3), 109–126. https://doi.org/10.1111/cwe.12245
Xu, H. L., & Cheng, L. (2016). The QAP weighted network analysis method and its application in international services trade. Physica A: Statistical Mechanics and Its Applications, 448, 91–101. https://doi.org/10.1016/j.physa.2015.12.094
Yang, Y., Poon, J. P. H., Liu, Y., & Bagchi-Sen, S. (2015). Small and flat worlds: A complex network analysis of international trade in crude oil. Energy, 93, 534–543. https://doi.org/10.1016/j.energy.2015.09.079
Zhang, H. W., Wang, Y., Yang, C., & Guo, Y. Q. (2021). The impact of country risk on energy trade patterns based on complex network and panel regression analyses. Energy, 222, 119979. https://doi.org/10.1016/j.energy.2021.119979
Zhang, H. Y., Xi, W. W., Ji, Q., & Zhang, Q. (2018). Exploring the driving factors of global LNG trade flows using gravity modelling. Journal of Cleaner Production, 172, 508–515. https://doi.org/10.1016/j.jclepro.2017.10.244
Zhong, W. Q., An, H. Z., Fang, W., Gao, X. Y., & Dong, D. (2016). Features and evolution of international fossil fuel trade network based on value of emergy. Applied Energy, 165, 868–877. https://doi.org/10.1016/j.apenergy.2015.12.083
Zhong, W. Q., An, H. Z., Shen, L., Fang, W., Gao, X. Y., & Dong, D. (2017). The roles of countries in the international fossil fuel trade: An emergy and network analysis. Energy Policy, 100, 365–376. https://doi.org/10.1016/j.enpol.2016.07.025
Armijo, L. E. (2007). The BRICS countries (Brazil, Russia, India, and China) as analytical category: Mirage or insight? Asian Perspective, 31(4), 7–42. https://doi.org/10.1353/apr.2007.0001
Atici, C., & Furuya, J. (2008). Regional blocs and agricultural trade flow: The case of ASEAN. Japan Agricultural Research Quarterly, 42(2), 115–121. https://doi.org/10.6090/jarq.42.115
Balassa, B. (1979). The changing pattern of comparative advantage in manufactured goods. The Review of Economics & Statistics, 61(2), 259–266. https://doi.org/10.2307/1924594
Bigerna, S., Bollino, C. A., & Galkin, P. (2021). Balancing energy security priorities: Portfolio optimization approach to oil imports. Applied Economics, 53(5), 555–574. https://doi.org/10.1080/00036846.2020.1808573
Caporale, G. M., Rault, C., Sova, R., & Sova, A. (2009). On the bilateral trade effects of free trade agreements between the EU-15 and the CEEC-4 countries. Review of World Economics, 145(2), 189–206. https://doi.org/10.1007/s10290-009-0011-8
Chaney, T. (2018). The gravity equation in international trade: An explanation. Journal of Political Economy, 126(1), 150–177. https://doi.org/10.1086/694292
Chong, Z., Qin, C., & Pan, S. (2019). The evolution of the belt and road trade network and its determinant factors. Emerging Markets Finance and Trade, 55(14), 3166–3177. https://doi.org/10.1080/1540496X.2018.1513836
Cranmer, S. J., Leifeld, P., McClurg, S. D., & Rolfe, M. (2017). Navigating the range of statistical tools for inferential network analysis. American Journal of Political Science, 61(1), 237–251. https://doi.org/10.1111/ajps.12263
Duarte, R., Pinilla, V., & Serrano, A. (2018). Factors driving embodied carbon in international trade: A multiregional input-output gravity model. Economic Systems Research, 30(4), 545–566. https://doi.org/10.1080/09535314.2018.1450226
Erdey, L., & Postenyi, A. (2017). Determinants of the exports of Hungary: Trade theory and the gravity model. Acta Oeconomica, 67(1), 77–97. https://doi.org/10.1556/032.2017.67.1.5
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. https://doi.org/10.1007/s00191-009-0160-x
Feng, L. Y., Xu, H. L., Wu, G., Zhao, Y., & Xu, J. L. (2020). Exploring the structure and influence factors of trade competitive advantage network along the Belt and Road. Physica A: Statistical Mechanics and Its Applications, 559, 125057. https://doi.org/10.1016/j.physa.2020.125057
Geng, J. B., Ji, Q., & Fan, Y. (2014). A dynamic analysis on global natural gas trade network. Applied Energy, 132, 23–33. https://doi.org/10.1016/j.apenergy.2014.06.064
Ho, D. C. K., Chan, E. M. H., Yip, T. L., & Tsang, C. W. (2020). The United States’ clothing imports from Asian countries along the Belt and Road: An extended gravity trade model with application of artificial neural network. Sustainability, 12(18), 7433. https://doi.org/10.3390/su12187433
Kandogan, Y. (2003). Intra-industry trade of transition countries: Trends and determinants. Emerging Market Review, 4(3), 273–286. https://doi.org/10.1016/S1566-0141(03)00040-2
Kitamura, T., & Managi, S. (2017). Driving force and resistance: Network feature in oil trade. Applied Energy, 208, 361–375. https://doi.org/10.1016/j.apenergy.2017.10.028
Krugman, P. R. (1987). Is free trade passe? Journal of Economic Perspectives, 1(2), 131–144. https://doi.org/10.1257/jep.1.2.131
Liang, X. D., Yang, X., Yan, F. H., & Li, Z. (2020). Exploring global embodied metal flows in international trade based combination of multi-regional input-output analysis and complex network analysis. Resources Policy, 67, 101661. https://doi.org/10.1016/j.resourpol.2020.101661
Lenzen, M., Kanemoto, K., Moran, D., & Geschke, A. (2012). Mapping the structure of the world economy. Environmental Science & Technology, 46(15), 8374–8381. https://doi.org/10.1021/es300171x
Lenzen, M., Moran, D., Kanemoto, K., & Geschke, A. (2013). Building Eora: A global multi-region input-output database at high country and sector resolution. Economic Systems Research, 25(1), 20–49. https://doi.org/10.1080/09535314.2013.769938
Li, J. P., Sun, X. L., Wang, F., & Wu, D. S. (2015). Risk integration and optimization of oil-importing maritime system: A multi-objective programming approach. Annals of Operations Research, 234(1), 57–76. https://doi.org/10.1007/s10479-014-1550-5
Muhammad, S., & Long, X. L. (2020). China’s seaborne oil import and shipping emissions: The prospect of belt and road initiative. Marine Pollution Bulletin, 158, 111422. https://doi.org/10.1016/j.marpolbul.2020.111422
Matthee, M., & Santana-Gallego, M. (2017). Identifying the determinants of South Africa’s extensive and intensive trade margins: A gravity model approach. South African Journal of Economic and Management Sciences, 20(1), 1–13. https://doi.org/10.4102/sajems.v20i1.1554
Petreski, M. (2013). Southeastern European trade analysis: A role for endogenous CEFTA-2006? Emerging Markets Finance & Trade, 49(5), 26–44. https://doi.org/10.2753/REE1540-496X490502
Santana-Gallego, M., Ledesma-Rodriguez, F. J., & Perez-Rodriguez, J. V. (2016). International trade and tourism flows: An extension of the gravity model. Economic Modelling, 52, 1026–1033. https://doi.org/10.1016/j.econmod.2015.10.043
Shuai, J., Leng, Z. H., Cheng, J. H., & Shi, Z. Y. (2020). China’s renewable energy trade potential in the “Belt-and-Road” countries: A gravity model analysis. Renewable Energy, 161, 1025–1035. https://doi.org/10.1016/j.renene.2020.06.134
Spring, E., & Grossmann, V. (2016). Does bilateral trust across countries really affect international trade and factor mobility? Empirical Economics, 50, 103–136. https://doi.org/10.1007/s00181-015-0915-1
Sun, Q. R., Gao, X. Y., Zhong, W. Q., & Liu, N. R. (2017). The stability of the international oil trade network from short-term and long-term perspectives. Physica a-Statistical Mechanics and Its Applications, 482, 345–356. https://doi.org/10.1016/j.physa.2017.04.047
Sun, X. L., Liu, C., Chen, X. W., & Li, J. P. (2017). Modeling systemic risk of crude oil imports: Case of China’s global oil supply chain. Energy, 121, 449–465. https://doi.org/10.1016/j.energy.2017.01.018
Vivoda, V. (2019). LNG import diversification and energy security in Asia. Energy Policy, 129, 967–974. https://doi.org/10.1016/j.enpol.2019.01.073
Wang, J., Sun, X. L., Li, J. P., Chen, J. M., & Liu, C. (2018). Has China’s oil-import portfolio been optimized from 2005 to 2014? A perspective of cost-risk tradeoff. Computers & Industrial Engineering, 126, 451–464. https://doi.org/10.1016/j.cie.2018.10.005
Wang, M., & Kong, R. (2019). Study on the characteristics of potassium salt international trade based on complex network. Journal of Business Economics and Management, 20(5), 1000–1021. https://doi.org/10.3846/jbem.2019.10455
Wu, Z. N., Cai, H. B., Zhao, R. N., Fan, Y., Di, Z. R., & Zhang, J. (2020). A topological analysis of trade distance: Evidence from the gravity model and complex flow networks. Sustainability, 12(9), 3511. https://doi.org/10.3390/su12093511
Xie, M. J. (2018). Can cultural affinity promote trade? HSK test data from the belt and road countries. China & World Economy, 26(3), 109–126. https://doi.org/10.1111/cwe.12245
Xu, H. L., & Cheng, L. (2016). The QAP weighted network analysis method and its application in international services trade. Physica A: Statistical Mechanics and Its Applications, 448, 91–101. https://doi.org/10.1016/j.physa.2015.12.094
Yang, Y., Poon, J. P. H., Liu, Y., & Bagchi-Sen, S. (2015). Small and flat worlds: A complex network analysis of international trade in crude oil. Energy, 93, 534–543. https://doi.org/10.1016/j.energy.2015.09.079
Zhang, H. W., Wang, Y., Yang, C., & Guo, Y. Q. (2021). The impact of country risk on energy trade patterns based on complex network and panel regression analyses. Energy, 222, 119979. https://doi.org/10.1016/j.energy.2021.119979
Zhang, H. Y., Xi, W. W., Ji, Q., & Zhang, Q. (2018). Exploring the driving factors of global LNG trade flows using gravity modelling. Journal of Cleaner Production, 172, 508–515. https://doi.org/10.1016/j.jclepro.2017.10.244
Zhong, W. Q., An, H. Z., Fang, W., Gao, X. Y., & Dong, D. (2016). Features and evolution of international fossil fuel trade network based on value of emergy. Applied Energy, 165, 868–877. https://doi.org/10.1016/j.apenergy.2015.12.083
Zhong, W. Q., An, H. Z., Shen, L., Fang, W., Gao, X. Y., & Dong, D. (2017). The roles of countries in the international fossil fuel trade: An emergy and network analysis. Energy Policy, 100, 365–376. https://doi.org/10.1016/j.enpol.2016.07.025