The evolution of the energy import dependence network and its influencing factors: Taking countries and regions along the Belt and Road as an example

Sun, Qingru et al. Article 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 (JBEM) Provided in Cooperation with: Vilnius Gediminas Technical University (VILNIUS TECH) Suggested Citation: Sun, Qingru et al. (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 (JBEM), ISSN 2029-4433, Vilnius Gediminas Technical University, Vilnius, Vol. 23, Iss. 1, pp. 105-130, https://doi.org/10.3846/jbem.2021.15661 This Version is available at: https://hdl.handle.net/10419/317548 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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Published by Vilnius Gediminas Technical University *Corresponding author. E-mail: [email protected]m This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons. org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Journal of Business Economics and Management ISSN 1611-1699 / eISSN 2029-4433 2022 Volume 23 Issue 1: 105–130 https://doi.org/10.3846/jbem.2021.15661 THE EVOLUTION OF THE ENERGY IMPORT DEPENDENCE NETWORK AND ITS INFLUENCING FACTORS: TAKING COUNTRIES AND REGIONS ALONG THE BELT AND ROAD AS AN EXAMPLE Qingru SUN1, 2, 3, Xiangyun GAO4, 5*, Jingjian SI4, Xian XI4, Siyao LIU4, Huiling ZHENG4, Wenting LIANG4 1School of Economics, Hebei University, Baoding, China 2Research Center of Resources Utilization and Environmental Conservation, Hebei University, Baoding, China 3Institute for Advanced Study of Yanzhao Culture, Hebei University, Baoding, China 4School of Economics and Management, China University of Geosciences, Beijing, China 5Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Natural Resources, Beijing, China Received 22 November 2020; accepted 26 May 2021; first published online 30 November 2021 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. Keywords: energy trade, import dependence, influencing factors, QAP method, network analysis, B&R countries. JEL Classification: F02, F14, F52. 106 Q. Sun et al. The evolution of the energy import dependence network and its influencing factors... Introduction Energy, especially crude oil and natural gas, acts as a driving factor of economic development. The uneven distribution of energy resources and the difference in energy consumption among countries make the energy flows among countries and regions by international trade, causing energy import dependent relationships between importers and exporters. For example, in China, the import dependence on foreign oil and gas increases annually and reached 69.8% and 45.3% in 2018, respectively1. Besides, more than 70% of China’s total crude oil and natural gas imports come from the countries and regions along the Belt and Road (B&R countries). The exporting countries sell energy to collect wealth and improve their economies, while importing countries have energy risk since they depend on foreign energy to support their domestic economy (Li etal., 2015). This interdependence makes importers and exporters interact and restrict each other, thus causing geo-economic and geopolitical effects and increasing restrictions on countries’ independence and autonomy. Thus, countries have formed a community of common destiny on energy and economy. The import dependent relationships of energy trade are complicated and form an energy import dependence network (EIDN). Researching the topological structure of the EIDN and its influencing factors is of great significance for the energy security and economic development of countries. On the one hand, more researchers have focused on energy import security and the pattern of international energy trade (Bigerna etal., 2021; Vivoda, 2019; Sun etal., 2017; Wang etal., 2018). The energy trade relationships among countries form a complex system, which can be acted as an international energy trade network with countries representing nodes, trade relationships representing edges and trade volumes between countries representing edge weights (Sun etal., 2017). Based on the network analysis method (Wang & Kong, 2019; Liang etal., 2020), the evolution of international energy trade (Geng etal., 2014) and the position of countries in the network (Zhong etal., 2017; Zhang etal., 2021) were revealed. Chong etal. (2019) analyzed the evolution of structural features of the B&R trade network and found that China, Singapore, Russian Federation, Malaysia and India are in the core position. These studies focused on the trade volumes between two countries from an absolute quantity perspective and revealed that countries with large trade volumes or a large number of trade partners play leading roles in the trade networks. Countries with lots of energy import partners can import different quantities of energy from their partners, spreading their energy import risk. However, if a country has lots of trade partners, but imports a large volume from one partner, then it has high energy import dependence on this partner, causing a high risk of energy security. Specifically, when its partner cuts off the energy supplying suddenly, the economies of the country will be greatly influenced. Thus, it is significant for countries to deepen the understanding of their energy security risk by revealing the import dependence relationships in energy trade among countries, which is still uncovered in former researches. The import dependence in energy trade of country A on country B, as proposed in this paper, is defined as the proportion of the energy volumes of country A importing from country B in the total energy volumes of country A importing from the world, which is a concept of relative quantity. 1 The data was obtained from the development report of oil and gas industry in China and foreign countries in 2018. Journal of Business Economics and Management, 2022, 23(1): 105–130 107 On the other hand, the studies on the influencing factors of international trade are mainly based on the difference-in-difference model (Xie, 2018) and trade gravity model (SantanaGallego etal., 2016; Spring & Grossmann, 2016; Wu etal., 2020). They found that the size of the economy, population, culture and trade system have a great influence on international trade. For example, the economic magnitude of a country has a positive influence on the country’s energy trade quantities (Matthee & Santana-Gallego, 2017; Zhang etal., 2018). However, they focused on the determinants of a country’s trade volume and ignored the determinants of trade relationships (import dependence relationships) among countries. Besides, what are the determinants of import dependence relationships in energy trade? For example, the spatial distance between exporters and importers can be regarded as a distance relationship and represents the transportation cost, so do the distance relationships between countries hinder the energy import dependence relationships between countries? It is the relationship between two kinds of “relationships”, which is a new perspective. This paper focuses on influencing factors of the import dependence relationships in energy trade among countries. Major changes have taken place in the pattern of international energy trade and energy consumption, especially crude oil and natural gas, and countries in the Asia-pacific region are rapidly overtaking the countries in North America and Europe and becoming the center of global energy consumption. The B&R countries have gradually become the world’s production, consumption and trade centers of crude oil and natural gas. However, the crude oil and natural gas in B&R countries are not balanced in terms of production and consumption, and supply and demand. Specifically, some B&R countries, such as Kazakhstan and Russia, have rich resources on crude and natural gas and mainly rely on exporting energy to support their economies. While the crude oil and natural gas resources in some B&R countries, such as China and Turkey, are scarce, and these countries need importing lots of energy to support their economic development. Therefore, the crude oil and natural gas trade among B&R countries have great significance in their economic development and energy security. In this paper, the crude oil and natural gas trade among B&R countries are taken as an empirical object, and the evolution of the oil and gas import dependence pattern and its influencing factors are analyzed. Specifically, this research provides the concept of import dependence between countries. Then, the EIDN among B&R countries is constructed based on complex network theory. The evolution characteristics of the EIDNs are analyzed from the perspectives of overall network characteristics, the number of importing partners in energy trade and import dependence in energy trade. Furthermore, according to the literature review and data availability, spatial distance (SD), economic differences (ED), free trade agreements (FTA) and differences in energy consumption (ECD) are chosen as influencing factors of the energy import dependence pattern among B&R countries. Based on the quadratic assignment procedure (QAP) method, the regression results of these factors on the EIDN are analyzed. Finally, this paper provides some policy implications about the energy trade of B&R countries from the perspective of energy security. The paper is structured as follows. Section 1 provides the research hypotheses. Section2 describes the data, the construction of the network model and the network indices. Section3 shows the results and discussion of the empirical study. The last Section contains the main conclusions and policy implications. 108 Q. Sun et al. The evolution of the energy import dependence network and its influencing factors... 1. Research hypotheses The gravity equation is commonly used to analyse the determinants of bilateral international trade flows (Chaney, 2018; Duarte etal., 2018; Ho etal., 2020), and the gravity equation in international trade reveals that the total trade between two countries is proportional to their economic size and inversely proportional to their spatial distance. This paper studies the determines of import dependence in energy trade between countries. Firstly, SD (spatial distance) represents the transportation cost to some extent. The geographical distance between countries has been found that it is a barrier to the imports of products and has a negative influence on trade flow (Kitamura & Managi, 2017). Chong etal. (2019) revealed the negative impact of SD on the trade relationships among B&R countries. As for B&R countries, crude oil and natural gas are mainly transported by sea and pipelines. Thus, the longer the SD between B&R countries is, the higher the transportation cost and the risk of crude oil and natural gas transportation are. This study assumes that SD hinders the trade between B&R countries and has a negative impact on the crude oil import dependence (Hypothesis 1) and SD has a negative impact on the natural gas import dependence among B&R countries (Hypothesis 2). Secondly, the new trade theory regards economies of scale as the key factor driving international trade (Krugman, 1987). In a market with imperfect competition, due to the large demand of the country, the development of industries relies on the effect of the economics of scale and has an advantage in the international trade (Kandogan, 2003). For example, Erdey and Postenyi (2017) analysed the determinants of the exports of Hungary and revealed that economic size had a statistically significant positive effect on exports. Other researchers also found that a country’s GDP had a positive influence on trade flow (Shuai etal., 2020). Besides, the economic magnitude of a country is large, meaning that its energy consumption is also large. Zhang etal. (2018) found that liquefied natural gas trade was affected by the economic magnitude of the demand side. Importers rely on energy to support their economies, and exporters need to increase their export volume to gain wealth and improve their economies. Fagiolo etal. (2010) found that high-income countries tend to hold more intense trade relationships with other high-income countries. Thus, this paper assumes that the less the ED (economic difference) between B&R countries is, the closer the trade link is and the larger the crude oil and natural gas import dependence between B&R countries is (Hypothesis 3 and Hypothesis 4). Thirdly, the signing of FTAs (free trade agreements) breaks down trade barriers, lowers the cost of tariffs and expands export among countries, all of which is helpful for the communication of trade members from each country (Petreski, 2013). Some researchers have revealed that FTAs have a significantly positive effect on exports (Aitken, 1973; Matthee & Santana-Gallego, 2017; Feng etal., 2020). For example, Caporale etal. (2009) focused on FTAs between the European Union and the Central and Eastern European countries and found a positive and significant impact of FTAs on trade flows. Atici and Furuya (2008) verified the significant impact of the trade agreements among the Association of Southeast Asian Nations on agricultural trade flows between Indonesia, Malaysia, the Philippines and Taiwan. Thus, the signing of FTAs among countries can promote the trade flow of products among countries. This paper assumes that the signing of FTAs has a positive influence on Journal of Business Economics and Management, 2022, 23(1): 105–130 109 the crude oil and natural gas import dependence among B&R countries, respectively (Hypothesis5 and Hypothesis 6). Fourthly, the differences in the accumulation of production factors in countries increase the volume of international trade (Balassa, 1979). Armijo (2007) studied the factors impacting energy trade between China and Russia, revealing that the differences in energy resources between the two countries improve their energy cooperation. Besides, China’s oil consumption is the main factor affecting China’s oil imports. Thus, the uneven distribution of the production and consumption of energy makes the energy flows between countries by international trade. Based on the former studies (Zhong etal., 2016, 2017), the energy trade relationships with high trade quantities exist between countries with abundant energy reserves and countries with high energy consumption. Since it is very hard to obtain the historical data on energy production and energy reserve in B&R countries, this paper researches the impact of the differences in the energy consumption (ECD) on import dependence in energy trade among B&R countries, which is a new perspective. Specifically, this paper assumes that the differences in crude oil consumption (OCD) and natural gas consumption (GCD) have a positive impact on import dependence in crude oil trade and natural gas trade among B&R countries, respectively (Hypothesis 7 and Hypothesis 8). 2. Data and method 2.1. Data The energy trade data among B&R countries are downloaded from the UN Comtrade. The energy commodities include crude oil and natural gas. Their HS codes are 2709 and 271111, respectively. Each data unit includes the exporter, importer, trade type and trade volume. Based on a literature review, the influencing factors of import dependence in energy trade among B&R countries selected in this paper are SD, ED, FTA, OCD and GCD. The distance between national capitals is used to represent SD, which is downloaded from the CEPII database. FTA data is downloaded from the website of the World Trade Organization. GDP and population of countries are obtained from the website of the World Bank. Crude oil and natural gas consumption data are downloaded from the Eora global supply chain database (Lenzen etal., 2012, 2013). Because of the lack of data in some countries, 59 countries are selected for empirical study, as shown in Appendix A, Table A1. Since the energy consumption data in the Eora global supply chain database is only released in 2015, the data period of this study is from 2002 to 2015. Through the analysis of historical data, countries can understand the evolution trend of their energy import dependence among B&R countries and then adopt energy trade strategies. 2.2. Network construction This study constructs an EIDN among 59 countries, of which the nodes are countries, the edges are energy trade dependence relationships and the direction of the edge is the flow of trade. Thus, the EIDN is directed. The EIDN with network matrix a Energy is defines as Eq.(1): 110 Q. Sun et al. The evolution of the energy import dependence network and its influencing factors... ( ) 11 1 1 0 , , 0 aa jn a aa i ij in acountries trade aa n nj EE E EE Energy V E EE      = =                            (1) where ( ) crude oil or natural gasa= . countries V is the node set, trade E is the edge set, and n is the number of countries. a ij E represents country j’s import dependence in energy trade of country i, defined as Eq.(2): a ij a ij a j TV ETTV = , (2) where a ij TV represents the energy a’s trade volume exporting from i to j. a j TTV is the energy a’s total import volume for j from the world. Figure1 shows the trade dependence network of crude oil and natural gas in 2015. The larger the node, the higher the energy import dependence of the country. The thicker the edge, the higher the energy import dependence between countries. Figure 1. The import dependence network of crude oil and natural gas in 2015 2.3. Network indices 2.3.1. The number of energy importing partners among B&R countries In the EIDN, the in-degree of country i represents the number of countries that country i imports energy from, which is defined as ( ) a in Di . It describes the number of energy importing partners of i. The larger the in-degree of the country, the larger the number of energy importing partners. The average number of energy importing partners among B&R countries is defined as a in AD . ( ) 1 n aa in ji j Di D = =∑ ; (3) Journal of Business Economics and Management, 2022, 23(1): 105–130 111 11 nn a ji ij a in D AD n = = =∑∑ ; (4) 1, 0 0, 0 a ji a ji a ji E DE >  ==   . (5) 2.3.2. Import dependence in energy trade among B&R countries In the EIDN, the weighted in-degree of country i represents the energy import dependence of i on the other B&R countries, defined as ( ) a in WD i . It ranges from 0 to 1. The larger the weighted in-degree of the country, the higher its import dependence in energy trade. The average value of import dependence in energy trade among 59 countries is defined as a in AWD . ( ) 1 n aa in ji j WD i E = =∑ ; (6) 11 nn a ji ij a in E AWD n = = =∑∑ . (7) 2.4. QAP regression model QAP has been widely used in network analysis and is a useful tool for revealing the correlation and regression relationships among matrices (Cranmer etal., 2017; Xu & Cheng, 2016). The dependence relationships and influencing factors can be represented as matrices data (or relational data). QAP is a test analysis method and can be used to perform a hypothetical test on “relation to relation” data. Thus, the QAP method is used to test the regression relationships between energy import dependence and its determinants. The process of QAP multivariate regression analysis includes three steps. First, a traditional regression analysis of the dependent variables and independent variables, which are network matrix (relational data), is carried out. Then, the rows of one of the matrices and the corresponding columns are randomly permutated simultaneously, and the test statistics are recalculated. By repeating this calculation process thousands of times, the distribution of the test statistics is obtained. Finally, by comparing the test statistics calculated in the first step with the distribution of test statistics calculated in the second step, this paper makes a judgment based on whether the observed test statistics fall into the rejection domain or the acceptance domain. The QAP model is shown in Eq.(8), meaning that the dependent variable a energy is the function of independent variables ,, , .SD ED FTA ECD ( ) ,, , a energy f SD ED FTA ECD=. (8) All the variables are matrix data. a energy is the trade dependence matrix of energy a. Matrix SD is the spherical distance between any two national capitals that have trade relationships. If two countries sign an FTA, then the corresponding element of matrix FTA is 112 Q. Sun et al. The evolution of the energy import dependence network and its influencing factors... 1, otherwise it is 0. Based on the economic distance index proposed by Chong etal. (2019), matrix ED is defined in Eq.(9), representing the economic difference between exporters and importers. ECD includes matrices OCD and GCD respectively according to the energy a , and OCD and GCD represent the difference in crude oil and natural gas consumption between exporters and importers, respectively, defined in Eqs (10)–(11). ( ) 2 ij ij ij PGDP PGDP ED GDP GDP× − = ; (9) ( ) 2 ij ij ij POil POil OCD Oil Oil =× − ; (10) ( ) 2 ij ij ij PGas PGas GCD Gas Gas =× − , (11) where i and j are the B&R countries, representing the energy exporter and importer, respectively; i GDP represents the GDP of country i, and i PGDP represents the per capita GDP of country i; i Oil and i Gas are the crude oil and natural gas consumption of country i, respectively; i POil and i PGas are the per capita crude oil and natural gas consumption of i, respectively. Since the differences between countries are large, each of the matrices is normalized. 3. Results and discussion To better understand the results, this study provides the crude oil and natural gas production, consumption, exports and imports of B&R countries and calculates the net imports of each country to judge whether the country is a net importing country or not; please see Appendix, Tables A2 and A3. 3.1. The overall evolution of the energy import dependence pattern This study constructs the trade dependence network of crude oil (COTDN) and natural gas (NGTDN) from 2002 to 2015. The numbers of nodes and edges in a network are basic topology features. Analysing the evolution of topology characteristics of networks can help us understand the energy trade pattern among 59 countries from an overall perspective and the extent to which countries are participating in regional energy trade. Firstly, the number of B&R countries participating in energy trade is analysed. The numbers of countries in the COTDNs fluctuated slightly, ranging from 51 to 58, as shown in Figure2. The number of countries involved in regional crude oil trade showed a rising trend before 2008 and reached a peak of 58 in 2008, after which the number of countries decreased. As for natural gas trade, the number of countries fluctuated greatly, ranging from 35 to 48. Besides, there was an upward trend from 2006 to 2010 reaching a peak of 48 in 2010, after which the number showed a decreasing trend. Secondly, there was an upward trend in the Journal of Business Economics and Management, 2022, 23(1): 105–130 119 and gas security. Besides, the number of crude oil and natural gas importing partners was increasing. Thus, countries were seeking new trade relationships and diversifying their trade partners to ensure their energy security. (2) Based on the analysis of import dependence in energy trade, it is concluded that the distribution of import dependence in crude oil and natural gas trades among B&R countries had different characteristics. The import dependence in crude oil trade of more than 30 countries on other B&R countries was over 0.9 every year. A large proportion of B&R countries did not depend on other countries’ natural gas, while there were also a large proportion of B&R countries whose import dependence was 1, and the importing partners of these countries were only 1 or 2. Combining the analysis of the number of importing partners and the value of import dependence, it is revealed that the number of importing partners in the crude oil and natural gas trade among B&R countries is small, but the import dependence is relatively large, indicating that the risk of energy security is higher. (3) Based on the QAP regression analysis, because of the particularity of energy commodities, some new results are revealed which are different from previous studies (Chong etal., 2019), this paper finds that spatial distance, economic difference, the signing of FTAs and the difference in the energy consumption have significantly positive impacts on the crude oil and natural gas import dependence among B&R countries. Combining the results and the current situation of energy trade in B&R countries, several policy implications are obtained. (1) B&R countries should enhance the relationships with trade partners and avoid being highly dependent on one country’s energy, which can reduce energy trade risk. As environmental issues become increasingly prominent, the demand for natural gas has an increasing trend. B&R countries are rich in natural gas resources, and B&R countries include the largest natural gas exporting countries and consumption countries. The status of natural gas trade in B&R countries will rise. Thus, the natural gas trade among B&R countries has broad prospects. Countries could break down energy trade barriers by building free trade agreements with other B&R countries. B&R countries also should be aware that political relationships play crucial roles in energy trade among countries. However, the geopolitical relationships among B&R countries are complex with high political risks. Energy cooperation is an important project in the Belt and Road Initiative, which is a chance for strengthening and deepening cooperation in the field of energy. Through joining the “One Belt One Road” Energy Partnership, B&R countries could expand energy trade partners and diversify their trade relationships to achieve a win-win cooperation mechanism. This can promote political trust among countries, further promoting crude oil and natural gas trade and cooperation. (2) Organization of Petroleum Exporting Countries (OPEC), acting as oil-producing countries, were shocked by unconventional oil and gas from the USA in recent several years, and the market share of OPEC was decreasing, causing that the pricing position of OPEC is greatly threatened. Some OPEC members, such as Saudi Arabia, Qatar and so on, also belong to B&R countries, and they could exploit the opportunities of the Belt and Road Energy cooperation platform to stable their markets. Besides, under the framework of the Belt and Road Initiative, oil-producing and oil-consumption countries are suggested to explore the 120 Q. Sun et al. The evolution of the energy import dependence network and its influencing factors... establishment of a mutually beneficial and new win-win crude oil pricing system to jointly maintain the stability of the crude oil market. In addition, as the most important natural gas production and consumption area in the world, B&R countries are suggested to explore the establishment of a new regional natural gas pricing mechanism under the framework of the Belt and Road Initiative, promoting the development of regional natural gas trade. This also plays an important role in promoting the formation of a unified natural gas pricing system in the world. (3) For crude oil and natural gas, the import dependence in crude oil trade among B&R countries is high with high risk. The transportation of oil and gas among B&R countries mainly relies on sea transportation, while the safety of oil and gas trade between some countries is greatly influenced when passing through the Strait of Malacca and Strait of Hormuz. Thus, it is necessary to construct an inter-regional oil and gas pipeline network and other infrastructure among B&R countries for reducing the dependence on sea transport, promoting inter-regional oil and gas trade and declining the risk of energy security. The construction of natural gas pipelines also can stimulate the increase of natural gas trade, improve natural gas supply capacity and enhance the flexibility of market supply chains among countries. The projects of pipeline connection are highly related to geopolitics, and the construction of oil and gas pipelines reflects the energy strategic interests between countries to a certain extent. If the governments, financial institutions, oil and gas companies and engineering enterprises could jointly construct oil and gas pipelines, it is of great significance to form a win-win cooperation mechanism and promote the economic development of B&R countries. Due to the data limitation, this paper analyzes the evolutionary characteristics of the import dependence between B&R countries in energy trade and its influencing factors from 2002 to 2015. Although the data is not the newest, by combining the evolutionary characteristics and the current situation of energy trade in B&R countries, this paper provides several policy implications to promote crude oil and natural gas trade and decrease the energy risk among B&R countries. Besides, the concept of import dependence proposed in this paper can also be applied to the research of other trade dependence. Future research will focus on the impacts of the distance of energy resource endowment and political distance on the import dependence of energy trade. The import dependence between countries from the perspective the oil and gas industrial chain is also an interesting topic and will be considered in our future study. Funding This work was supported by the <National Natural Science Foundation of China> under Grant [71991485, 71991481,71991480, 42001242, 41871202]; <Beijing Natural Science Foundation> under Grant [9202013]; <the Scientific Research Initiation Project for High-level Talents of Hebei University> under Grant [NO. 521000981396]; <the Fund from Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Natural Resources> under Grant [CCA2019.01]; <the Fundamental Research Funds for the Central Universities> under Grant [265208247]. Journal of Business Economics and Management, 2022, 23(1): 105–130 121 Author contributions Qingru Sun and Xiangyun Gao conceived this study and were responsible for the draft of the article. Jingjian Si and Huiling Zhen and Wenting Liang were responsible for data collection and data analysis. Xian Xi and Siyao Liu were responsible for analyzing data and drawing figures. Disclosure statement The authors declare that we did not have any competing financial, professional, or personal interests from other parties. References Aitken, N. D. (1973). The effect of the EEC and EFTA on European Trade: A temporal cross-section analysis. American Economic Review, 63(5), 881–892. https://ideas.repec.org/a/aea/aecrev/v63y1973i5p881-92.html 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). 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The evolution of the energy import dependence network and its influencing factors... APPENDIX Table A1. Countries selected in this research Country Country Country 1Afghanistan 21 Indonesia 41 Pakistan 2Albania 22 Iran, Islamic Rep. 42 Philippines 3 Armenia 23 Iraq 43 Poland 4 Azerbaijan 24 Israel 44 Qatar 5 Bahrain 25 Jordan 45 Romania 6 Bangladesh 26 Kazakhstan 46 Russian Federation 7Belarus 27 Kuwait 47 Saudi Arabia 8Bhutan 28 Kyrgyz Republic 48 Serbia 9Bosnia and Herzegovina 29 Lao PDR 49 Singapore 10 Brunei Darussalam 30 Latvia 50 Slovak Republic 11 Bulgaria 31 Lebanon 51 Slovenia 12 Cambodia 32 Lithuania 52 Sri Lanka 13 China 33 Macedonia, FYR 53 Tajikistan 14 Croatia 34 Malaysia 54 Thailand 15 Czech Republic 35 Maldives 55 Turkey 16 Egypt, Arab Rep. 36 Moldova 56 Ukraine 17 Estonia 37 Mongolia 57 United Arab Emirates 18 Georgia 38 Myanmar 58 Vietnam 19 Hungary 39 Nepal 59 Yemen, Rep. 20 India 40 Oman Table A2. The crude oil production, consumption, exports and imports of B&R countries Country Production (in 2018) Refined petroleum products consump tion (in 2016) Exports (in 2018) Imports (in 2018) Net imports (in 2018) Net impor ting country (in 2018) Afghanistan 0 1.28×1070 1.35×1061.35×106Yes Albania 5.11×1061.06×1074.24×1060 –4.24×106No Armenia 0 2.92×1060 0 0 – Azerbaijan 2.91×1083.65×1072.72×1089.64×105–2.71×108No Bahrain 1.46×1072.23×1077.92×1067.93×1077.14×107Yes Bangladesh 1.10×1063.87×1070 1.74×1021.74×102Yes Belarus 1.13×1075.15×1071.20×1071.33×1081.21×108Yes Journal of Business Economics and Management, 2022, 23(1): 105–130 125 Country Production (in 2018) Refined petroleum products consump tion (in 2016) Exports (in 2018) Imports (in 2018) Net imports (in 2018) Net impor ting country (in 2018) Bhutan 0 1.10×1060 0 0 – Bosnia and Herzegovina 0 1.17×1070 4.87×1064.87×106Yes Brunei Darussalam 3.65×1076.57×1064.16×1074.72×104–4.15×107No Bulgaria 3.65×1053.54×1074.72×1034.51×1074.51×107Yes Cambodia 0 1.64×1070 0 0 – China 1.38×1094.55×1091.95×1073.41×1093.39×109Yes Croatia 5.11×1062.66×1073.13×1023.98×1073.98×107Yes Czech Republic 7.30×1057.80×107 (in 2017) 1.63×1055.44×1075.42×107Yes Egypt, Arab Rep. 2.33×1083.20×1088.40×1075.18×1073.23×107No Estonia 0 1.03×107 (in 2017) 2.23×1043.49×1053.26×105Yes Georgia 1.46×1059.86×1066.45×1051.49×104–6.31×105No Hungary 5.84×1066.12×107 (in 2017) 1.41×1064.59×1074.45×107Yes India 2.59×1081.65×1094.10×1061.77×1091.77×109Yes Indonesia 2.82×1085.84×1089.23×1071.24×1083.17×107Yes Iran, Islamic Rep. 1.55×1096.58×1081.36×1092.8×10–2 –1.35×109No Iraq 1.68×1093.01×1081.41×1093.17×104–1.41×109No Israel 1.42×1058.84×107 (in 2017) 4.34×1049.05×1079.05×107Yes Jordan 8.03×1035.07×1070 1.72×1071.72×107Yes Kazakhstan 6.77×1081.00×1086.56×1081.87×105–6.56×108No Kuwait 1.02×1091.63×1087.86×1088.92×101–7.86×108No Kyrgyz Republic 3.65×1051.35×1075.18×1051.85×104–4.99×105No Lao PDR 0 6.57×1060 4.02×1044.02×104Yes Latvia 0 1.63×107 (in 2017) 4.96×1057.43×1052.47×105Yes Lebanon 0 5.62×1071.43×1056.23×101–1.43×105No Lithuania 7.3×1052.12×1073.66×1057.06×1077.02×107Yes Macedonia, FYR 0 7.67×1060 0 0 – Continued Table A2 126 Q. Sun et al. The evolution of the energy import dependence network and its influencing factors... Country Production (in 2018) Refined petroleum products consump tion (in 2016) Exports (in 2018) Imports (in 2018) Net imports (in 2018) Net impor ting country (in 2018) Malaysia 2.36×1082.57×1082.16×1081.09×108–1.07×108No Maldives 0 4.02×1060 1.39×1011.39×101Yes Moldova 0 6.57×1060 0 0 – Mongolia 7.3×1069.86×1066.13×1064.35×102–6.12×106No Myanmar 4.02×1064.49×1071.45×1065.36×1063.91×106Yes Nepal 0 9.86×1060 0 0 – Oman 3.57×1086.86×1076.16×1084.19×103–6.16×108No Pakistan 3.29×1072.03×1083.68×1067.23×1076.86×107Yes Philippines 4.75×1061.55×1086.24×1069.84×1079.21×107Yes Poland 7.67×1062.37×108 (in 2017) 2.18×1062.10×082.08×108Yes Qatar 5.34×1081.01×1082.84×1086.62×103–2.83×108No Romania 2.56×1077.23×1071.21×1056.03×1076.02×107Yes Russian Federation 3.93×1091.33×1092.25×1093.64×106–2.24×109No Saudi Arabia 3.81×1091.20×1092.62×1093.10×104–2.62×109No Serbia 6.21×1062.70×1074.21×1031.95×1071.95×107Yes Singapore 0 4.83×1084.14×1065.19×1085.14×108Yes Slovak Republic 7.30×1043.13×107 (in 2017) 5.52×1034.12×1074.12×107Yes Slovenia 1.83×1031.90×107 (in 2017) 5.52×1032.18×1052.13×105Yes Sri Lanka 0 4.23×1071.46×1067×10–2 6×10–2 Yes Tajikistan 6.57×1048.76×1060 1.60×1051.60×105Yes Thailand 8.32×1074.84×1081.23×1074.26×1084.13×108Yes Turkey 2.01×1073.61×108 (in 2017) 5.44×1074.76×107–6.89×106No Ukraine 1.17×1078.50×1071.86×1031.18×1071.18×107Yes United Arab Emirates 1.17×1093.27×1082.01×1094.74×107–1.96×109No Vietnam 8.83×1071.60×1083.44×1074.04×1076.03×106Yes Yemen, Rep. 2.23×1073.80×1071.27×1071.28×103–1.27×107No Note: The data of crude oil production and refined petroleum products consumption were downloaded from the Central Intelligence Agency (https://www.cia.gov/). The data of crude oil export and import were downloaded from the UN comtrade (https://comtrade.un.org/). Due to the availability and integrity of the data, the refined petroleum products consumption of most B&R countries was in 2016, and the crude oil production, export and import data were in 2018. End of Table A2 Journal of Business Economics and Management, 2022, 23(1): 105–130 127 Table A3. The natural gas production, consumption, exports and imports of B&R countries Country Production (in 2017) Consumption (in 2017) Exports (in 2017) Imports (in 2017) Net imports (in 2017) Net importing country (in 2017) Afghanistan 1.64×1081.64×1080 0 0 – Albania 5.1×1075.1×1070 0 0 – Armenia 0 2.35×1092.35×1090 2.35×109Yes Azerbaijan 1.7×1010 1.03×1010 2.10×1098.04×109–5.95×109No Bahrain 1.59×1010 1.59×1010 0 0 0 – Bangladesh 2.95×1010 2.95×1010 0 0 0 – Belarus 5.95×1071.77×1010 1.75×1010 0 1.75×1010 Yes Bhutan 0 0 0 0 0 – Bosnia and Herzegovina 0 2.27×1082.27×1080 2.27×108Yes Brunei Darussalam 1.27×1010 3.94×1090 8.27×109–8.27×109No Bulgaria 7.93×1073.31×1093.26×1093.12×1073.22×109Yes Cambodia 0 0 0 0 0 – China 1.46×1011 2.39×1011 9.76×1010 3.37×1099.43×1010 Yes Croatia 1.05×1092.58×1091.84×1091.73×1081.67×109Yes Czech Republic 2.29×1088.72×1098.89×1090 8.89×109Yes Egypt, Arab Rep. 5.09×1010 5.77×1010 7.08×1092.12×1086.87×109Yes Estonia 0 4.81×1084.81×1080 4.81×108Yes Georgia 7.36×1062.29×1092.29×1090 2.29×109Yes Hungary 1.81×1091.04×1010 1.34×1010 3.52×1099.85×109Yes India 3.15×1010 5.54×1010 2.24×1010 7.65×1072.39×1010 Yes Indonesia 7.21×1010 4.23×1010 0 2.98×1010 –2.98×1010 No Iran, Islamic Rep. 2.15×1011 2.07×1011 3.99×1091.16×1010 –7.65×109No Iraq 1.27×1092.63×1091.36×1090 1.36×109Yes Israel 9.83×10910.00×1095.10×1080 5.10×108Yes Jordan 1.22×1085.24×1096.46×1091.36×1095.10×109Yes Kazakhstan 2.24×1010 1.54×1010 5.75×1091.28×1010 –7.05×109No Kuwait 1.71×1010 2.17×1010 5.13×1090 5.13×109Yes 128 Q. Sun et al. The evolution of the energy import dependence network and its influencing factors... Country Production (in 2017) Consumption (in 2017) Exports (in 2017) Imports (in 2017) Net imports (in 2017) Net importing country (in 2017) Kyrgyz Republic 2.83×1071.87×1081.70×1080 1.70×108Yes Lao PDR 0 0 0 0 0 – Latvia 0 1.22×1091.25×1090 1.25×109Yes Lebanon 0 0 0 0 0 – Lithuania 0 2.49×1092.49×1090 2.49×109Yes Macedonia, FYR 0 1.98×1081.98×1080 1.98×108Yes Malaysia 6.95×1010 3.04×1010 2.80×1093.82×1010 –3.54×1011 No Maldives 0 0 0 0 0 – Moldova 1.13×1072.52×1092.52×1090 2.52×109Yes Mongolia 0 0 0 0 0 – Myanmar 1.84×1010 4.50×1090 1.41×1010 –1.41×1010 No Nepal 0 0 0 0 0 – Oman 3.12×1010 2.19×1010 1.98×1091.12×1010 –9.2×109No Pakistan 3.91×1010 4.51×1010 6.00×1090 6.00×109Yes Philippines 3.06×1093.14×1090 0 0 – Poland 5.75×1092.01×1010 1.57×1010 1.25×1091.45×1010 Yes Qatar 1.66×1011 3.99×1010 0 1.27×1011 –1.27×1011 No Romania 1.09×1010 1.16×1010 1.22×1092.27×1071.20×109Yes Russian Federation 6.66×1011 4.68×1011 1.58×1010 2.10×1011 –1.94×1011 No Saudi Arabia 1.09×1011 1.09×1011 0 0 0 – Serbia 5.10×1082.72×1092.01×1090 2.01×109Yes Singapore 0 1.30×1010 1.53×1010 6.23×1081.29×1010 Yes Slovak Republic 1.05×1084.67×1094.98×1090 4.98×109Yes Slovenia 8.00×1069.06×1089.06×1082.83×1069.03×108Yes Sri Lanka 0 0 0 0 0 – Tajikistan 1.98×1071.98×1070 0 0 – Thailand 3.86×1010 5.26×1010 1.44×1010 0 1.44×1010 Yes Continued Table A3