文献类型：期刊文献

英文题名：Reconstruction of international energy trade networks with given marginal data: A comparative analysis

作者：Xu, Hai-Chuan[1,2];Wang, Zhi-Yuan[1];Jawadi, Fredj[3];Zhou, Wei-Xing[1,2]

机构：[1]East China Univ Sci & Technol, Sch Business, Shanghai 200237, Peoples R China;[2]East China Univ Sci & Technol, Res Ctr Econophys, Shanghai 200237, Peoples R China;[3]IAE Lille Univ, Sch Management, F-59043 Lille, France

年份：2023

卷号：167

外文期刊名：CHAOS SOLITONS & FRACTALS

收录：;EI(收录号：20225113286009);WOS:【SCI-EXPANDED(收录号:WOS:000975137100001)】；

基金：Acknowledgments We are grateful to the editor Francisco Rodrigues and two anony-mous referees for their constructive comments and helpful suggestions. This work was supported by the National Natural Science Foundation of China (U1811462, 72171083, and 71971081) and the Fundamental Research Funds for the Central Universities, China.

语种：英文

外文关键词：Network reconstruction; Energy trade network; Comparative analysis; Complex network

摘要：The energy commodity plays a significant role in economic development and national security. It is important for various countries to capture the linkages of the international energy trade network and avoid the occurrence of systemic risk. However, the granular data on trade network is often lacking, and instead, the network has to be reconstructed from partial data. In this paper, we compare seven network reconstruction methods by applying them to 16 types of energy trade data extracted from UN-Comtrade. To this end, first we present the topological structures and compute the dependency characteristics for these energy trade networks. Then, we conduct a horse race among different network reconstruction methods. The methods are ranked by comparing their abilities to reproduce the network structures and bilateral weights. Our findings show that Cimi is the winner across all 16 energy trade networks in terms of link-based similarity measures. In addition, the fitness models (Cimi and Musm) tend to perform best at reconstructing the weight matrix. These findings will aid in the accurate disclosure of latent international energy trade relations when only aggregated export and import figures are available, allowing systemic risks to be appropriately assessed.