TY - UNPB
T1 - Geopolitical Conflict and Risk and the EU Energy Trading
T2 - A Dynamic Evolutionary Networks Analysis
AU - Xu, Shuanglei
AU - Deng, Youyi
AU - Nepal, Rabindra
AU - Jamasb, Tooraj
PY - 2024
Y1 - 2024
N2 - Since the Russian-Ukrainian conflict, the European Union (EU)’s energy imports have faced challenges, and energy security has come to the fore. Focusing on the EU and its relations with major energy trading countries, we adopt a social network approach (SNA) and exponential random graph model (ERGM) to analyze the energy trade impact of the conflict. We use data from a sample of 47 countries from 2014-2023 to explore the characteristics of the structural evolution of the EU’s conventional and renewable trade networks and the influencing mechanisms behind them. As a result of the conflict and the global trend towards decoupling, the EU’s conventional trade network is undergoing a contraction. Meanwhile, its renewable trade network is thriving, indicating a shift in energy structures; the core-periphery undergoing restructuring, Russia fading out of the core circle of the trade, and the US becoming a key hub connecting all parties. Germany, France, and the Netherlands play the role of important importers as core nodes of the network. Mechanistic analysis shows that mutual plays an important role in multilateral trade; rising geopolitical risks, while posing a barrier to energy imports, have facilitated a boom in renewable trade; economic size and trade openness have positively driven energy trade. Foreign investment, intellectual property rights, and levels of population and urbanization have had a differentiated impact on the two types of energy trade; geographic proximity, linguistic commonality, and free trade agreements positively contribute to the construction and maintenance of energy trade networks. This study depicts the dynamics of EU energy trade under geopolitical turbulence, expands the research methodology in this area, deepens the understanding of energy geopolitics, and informs the transformation of the EU’s energy structure.
AB - Since the Russian-Ukrainian conflict, the European Union (EU)’s energy imports have faced challenges, and energy security has come to the fore. Focusing on the EU and its relations with major energy trading countries, we adopt a social network approach (SNA) and exponential random graph model (ERGM) to analyze the energy trade impact of the conflict. We use data from a sample of 47 countries from 2014-2023 to explore the characteristics of the structural evolution of the EU’s conventional and renewable trade networks and the influencing mechanisms behind them. As a result of the conflict and the global trend towards decoupling, the EU’s conventional trade network is undergoing a contraction. Meanwhile, its renewable trade network is thriving, indicating a shift in energy structures; the core-periphery undergoing restructuring, Russia fading out of the core circle of the trade, and the US becoming a key hub connecting all parties. Germany, France, and the Netherlands play the role of important importers as core nodes of the network. Mechanistic analysis shows that mutual plays an important role in multilateral trade; rising geopolitical risks, while posing a barrier to energy imports, have facilitated a boom in renewable trade; economic size and trade openness have positively driven energy trade. Foreign investment, intellectual property rights, and levels of population and urbanization have had a differentiated impact on the two types of energy trade; geographic proximity, linguistic commonality, and free trade agreements positively contribute to the construction and maintenance of energy trade networks. This study depicts the dynamics of EU energy trade under geopolitical turbulence, expands the research methodology in this area, deepens the understanding of energy geopolitics, and informs the transformation of the EU’s energy structure.
KW - European Union
KW - Conventional energy trade
KW - Renewable energy trade
KW - Social network
KW - Exponential random graph model
KW - European Union
KW - Conventional energy trade
KW - Renewable energy trade
KW - Social network
KW - Exponential random graph model
M3 - Working paper
T3 - CSEI Working Paper
BT - Geopolitical Conflict and Risk and the EU Energy Trading
PB - Department of Economics. Copenhagen Business School
CY - Frederiksberg
ER -