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Multilayer network analysis of oil linkages
The Econometrics Journal ( IF 1.9 ) Pub Date : 2020-01-29 , DOI: 10.1093/ectj/utaa003
Roberto Casarin 1 , Matteo Iacopini 2 , German Molina 3 , Enrique ter Horst 4 , Ramon Espinasa 5 , Carlos Sucre 6 , Roberto Rigobon 7
Affiliation  

This manuscript proposes a new approach for unveiling existing linkages within the international oil market across multiple driving factors beyond production. A multilayer, multicountry network is extracted through a novel Bayesian graphical vector autoregressive model, which allows for a more comprehensive, dynamic representation of the network linkages than do traditional or static pairwise Granger-causal inference approaches. Building on previous work, the layers of the network include country- and region-specific oil production levels and rigs, both through simultaneous and lagged temporal dependences among key factors, while controlling for oil prices and a world economic activity index. The proposed approach extracts relationships across all variables through a dynamic, cross-regional network. This approach is highly scalable and adjusts for time-evolving linkages. The model outcome is a set of time-varying graphical networks that unveil both static representations of world oil linkages and variations in microeconomic relationships both within and between oil producers. An example is provided, illustrating the evolution of intra- and inter-regional relationships for two major interconnected oil producers: the United States, with a regional decomposition of its production and rig deployment, and the Arabian Peninsula and key Middle Eastern producers, with a country-based decomposition of production and rig deployment, while controlling for oil prices and global economic indices. Production is less affected by concurrent changes in oil prices and the overall economy than rigs. However, production is a lagged driver for prices, rather than rigs, which indicates that the linkage between rigs and production may not be fully accounted for in the markets.

中文翻译:

石油链接的多层网络分析

该手稿提出了一种新方法,用于揭示国际石油市场中除生产以外的多种驱动因素之间的现有联系。通过新颖的贝叶斯图形矢量自回归模型提取多层多国家网络,该网络比传统的或静态的成对Granger因果推理方法可以更全面,动态地表示网络链接。在以前的工作的基础上,网络的各层包括国家和地区特定的石油生产水平和钻机,通过关键因素之间的同时和滞后的时间依赖性,同时控制了石油价格和世界经济活动指数。所提出的方法通过动态的跨区域网络提取所有变量之间的关系。这种方法具有高度的可扩展性,并可以根据时间演变的链接进行调整。该模型的结果是一组随时间变化的图形网络,揭示了世界石油联系的静态表示以及石油生产商内部和之间的微观经济关系的变化。提供了一个例子,说明了两个主要的相互联系的石油生产商的区域内和区域间关系的演变:美国,其生产和钻机部署在区域上进行了分解;阿拉伯半岛和主要的中东石油生产商,在该区域内基于国家的生产和钻机配置分解,同时控制石油价格和全球经济指标。与钻机相比,石油价格和整体经济的同时变化对生产的影响较小。但是,生产是价格的滞后驱动因素,
更新日期:2020-01-29
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