EconPapers    
Economics at your fingertips  
 

Estimating potential trade links in the international crude oil trade: A link prediction approach

Qing Guan, Haizhong An, Xiangyun Gao, Shupei Huang and Huajiao Li

Energy, 2016, vol. 102, issue C, 406-415

Abstract: Estimating potential trade links is essential for exploring the information implied by international crude oil trade data, which contain obvious trade links among countries. In addition, it is important for governments to assess the evolution trend of international crude oil trade in order to avoid trade risk. This study introduces the link prediction approach to explore potential trade links from the perspective of relations based on the topological attributes of countries. We take the number of common trade partners for each country pair as the potential linking motivation. Based on this, we confirm this as a general feature for most existing trade links and thereby describe the real distribution of trade relations. Furthermore, our study analyzes the practical meanings of explored potential trade links with considerations of countries' crude oil trade roles. We find that the number of common trade partners is indeed one of the structural linking motivations in international crude oil trade. It can not only represent the possibility of trading relations, but also reflect the competition among countries. By using this evaluation index, we then estimate potential trade partners combined with countries’ crude oil trade roles and provide suggestions for governments about future trading strategies.

Keywords: Trade links; Crude oil; International trade; Link prediction (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (33)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S036054421630161X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:102:y:2016:i:c:p:406-415

DOI: 10.1016/j.energy.2016.02.099

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:energy:v:102:y:2016:i:c:p:406-415