Dynamic impact of the COVID-19 lockdown intervention policies on network structure of energy futures return connectedness
Dynamic impact of the COVID-19 lockdown intervention policies on network structure of energy futures return connectedness
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DOI：
10.1016/j.jclepro.2023.139802
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发表时间：
2023-11-27
影响因子：
11.1
通讯作者：
Xia，Xiaohua
中科院分区：
文献类型：
--
作者：
Chen，Baifan;Huang，Jionghao;Xia，Xiaohua
这项工作调查了为遏制疫情传播而实施的新冠肺炎封锁政策对能源期货回报连通性网络(EFRCN)结构的动态影响。首先，利用时变参数向量自回归(TVP-VAR)频率连通性方法对20个能源期货收益率序列的连通性进行了度量，构建了有向多层动态EFRCN。其次，我们提出了一种新的统计指标--平均顶点外溢强度与平均顶点外溢强度之比，来表示特定网络层的溢出强度。最后，我们利用剪枝精确线性时间(PELT)算法精确定位新冠肺炎封锁政策的结构变化点，并探索这些变化点前后EFRCN结构的变化。实证结果表明，受新冠肺炎封锁影响的人口规模和国内生产总值规模分别对石油期货市场和电力期货市场的平均顶点强度、密度和聚集系数以及石油和电力期货市场的回报溢出强度产生正向推动作用。相反，回归结果显示，在非周期和短期网络中，新冠肺炎封锁影响的人口规模和国内生产总值规模与煤炭和天然气期货市场的回报溢出强度之间存在显著的负因果关系。此外，实证结果表明，在2020年6月之前，新冠肺炎锁定政策的变化点，非周期和短期网络的全球指标演化存在明显的结构性变化。综上所述，新冠肺炎解禁力度的加强增加了外汇储备中心的集群性，显著增强了外汇储备中心内石油和电力期货市场的净溢出效应。此外，新冠肺炎封锁政策的变化对EFRCN的结构产生了重大影响。
This work investigates the dynamic impact of COVID-19 lockdown policies, implemented to curb the pandemic's spread, on the structure of the energy futures return connectedness network (EFRCN). Firstly, we measured the connectedness of 20 energy futures return series using the time-varying parameter vector autoregression (TVP-VAR) frequency connectedness approach and constructed a directed multi-layer dynamic EFRCN. Secondly, we developed a novel statistical indicator, the ratio of average vertex out-strength to average vertex in-strength, to represent the spillover intensity of a specific network layer. Finally, we utilized the pruned exact linear time (PELT) algorithm to pinpoint structural changepoints of COVID-19 lockdown policies and explored the change in the EFRCN structure before and after these changepoints. The empirical findings demonstrate that the scales of population and gross domestic product (GDP) impacted by the COVID-19 lockdown positively drive the average vertex strength, density, and clustering coefficient of the EFRCN, as well as the return spillover intensity of oil and power futures markets, respectively. Conversely, the regression results exhibit noteworthy negative causal relationships between the scales of population and GDP impacted by the COVID-19 lockdown and the return spillover intensity of coal and natural gas futures markets for non-periodic and short-term networks. Furthermore, the empirical results illustrate distinct structural changes in the evolution of global indicators of the non-periodic and short-term networks at the changepoints of COVID-19 lockdown policies before June 2020. To sum up, COVID-19 lockdown intensification increases the clustering of the EFRCN and significantly enhances the net spillover effects of oil and power futures markets within the EFRCN. Moreover, the changes in COVID-19 lockdown policies significantly influence the EFRCN's structure.