地缘政治学
溢出效应
能源市场
经济
业务
经济
国际贸易
国际经济学
金融经济学
政治
宏观经济学
电
政治学
法学
电气工程
工程类
作者
Xiao-Li Gong,Yong-Kang Feng,Jianmin Liu,Xiong Xiong
标识
DOI:10.1016/j.resourpol.2023.103495
摘要
At present, the global political and economic situation is changing with geopolitical risks occurring frequently, and the commodity market represented by energy fluctuates violently. In order to deeply investigate the risk contagion status and interactive contagion mechanism between international energy market and geopolitics under the impact of extreme events, this paper selects crude oil spot prices and geopolitical risk index of major international oil-producing countries from January 2006 to December 2021, and analyzes the tail risk cross-contagion effects, dynamic effects and cyclical characteristics between international energy-geopolitics two-layer networks based on complex networks. Empirical research finds that risk spillover effect of traditional energy markets is more significant than that of clean energy markets. Russia acts as the main risk spillover of international crude oil market under extreme shocks, and geopolitical conflicts will exacerbate risk contagion between international energy markets. The analysis of energy-geopolitics two-layer network finds that the international energy market generates net risk spillover effect on geopolitics. In addition, the interconnectedness network study found that the United States, Russia and China are systemically important economies in the energy market under the complex geopolitical landscape. The risk contagion effect among systemically important economies finds that Russia's geopolitical risks have stronger impact on China's crude oil price. The cycle characteristics analysis of international crude oil market and geopolitical dynamic network finds that the short-term risk contagion effect is more obvious. The machine learning analysis found that the international crude oil-geopolitical connectedness can effectively warn the tail risk of the crude oil market, which provides basis for preventing cross-contagion risks from the perspective of system connectedness.
科研通智能强力驱动
Strongly Powered by AbleSci AI