The stability of the international oil trade network from short-term and long-term perspectives

Sun, Qingru; Gao, Xiangyun; Zhong, Weiqiong; Liu, Nairong

doi:10.1016/j.physa.2017.04.047

Cited by 41 publications

(18 citation statements)

References 38 publications

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“…SNA, on the other hand, is a method of analysing social interactions, where actors are represented as nodes and interactions among them using arcs connecting the nodes. Currently, SNA has gained growing significant attention with a wide range of application to finance, engineering and trade (An et al, 2016; Gao et al, 2014; Schweitzer et al, 2009; Sun et al, 2017).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Specifically, ‘heterogeneity’ implies that numerous countries are involved in global trade networks, and there are differences in trading behaviour (Barigozzi et al, 2011). ‘Complexity’ here refers to the complex trade connection structure among countries resulting from different link directions, weights and other trading characteristics (Cepeda López et al, 2019), while ‘dynamics’ suggests that international trade networks formation is affected by various factors, making trade networks change accordingly (Sun et al, 2017). Nodes, ties and weights thus represent countries, trade relations and strengths, respectively, within the international trade network and can be used to reflect trade patterns between countries using SNA.…”

Section: Literature Reviewmentioning

confidence: 99%

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A social network analysis of the structure and evolution of intra‐African trade

Zhang

Batinge

2021

African Development Review

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We used social network analysis to examine the country attributes and patterns of intra-African trade between 2002 and 2017. The results showed that, generally, trade networks in Africa have become denser, and have the characteristics of the core-periphery structure and small world phenomenon. Trade imbalances are widely found among African countries with the evidence that structure holes exist in intra-African trade networks highlighted by the motif detectors. Using Quadratic Assignment Procedure, we found that countries that possess closer economic, geographic and cultural distance, but longer institutional distance, are more likely to form trade networks. However, many countries and the regional economic communities on the continent, have not adequately manifested these favourable characteristics for enhancing intra-African trade. The implications are proposed that countries should develop their strategies, expedite structural adjustment, and foster competitive industries to cope with the external competition and seize opportunities of regional integration brought by the African Continental Free Trade Area (AfCFTA) agreement. It is also critical to efficiently address the overlapping problems of regional economic communities and intensify their coordination with AfCFTA.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

A social network analysis of the structure and evolution of intra‐African trade

Zhang

Batinge

2021

African Development Review

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“…Transitivity measures have been developed to measure the frequency or relative frequency of transitive triples in networks [40]. It is worth noting that the transitivity places more weight on the high-degree nodes, while the average clustering coefficient places more weight on the low-degree nodes.…”

Section: Average Clustering Coefficient and Transitivitymentioning

confidence: 99%

“…For example, the research into trade networks has been confined to local areas and organizations, such as the Belt and Road trade network [29][30][31][32][33][34] and North American Free Trade Area (NAFTA) [35][36][37]. International trade issues of specific resources, namely, coal [38][39][40], oil [41,42], scrap metal [6], and natural gas [28], have been investigated in detail. Although most scholars have made considerable efforts to investigate international natural resource trades, less attention has been paid to the complete picture of the global flows of natural resources.…”

Section: Introductionmentioning

confidence: 99%

An Exploratory Analysis of Networked and Spatial Characteristics of International Natural Resource Trades (2000–2016)

et al. 2020

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Natural resources, as the material basis of human life and production, play a crucial role in national economic and social development. It is essential to reveal the structural characteristics of global natural resource supply and demand, which has become one of the most critical factors affecting every country’s policy strategy and economic development. However, mining the characteristics of international natural resource trades is a huge challenge because of the availability and quality of trade data. In this study, the international natural resource trade system is modeled as networks based on the available bilateral trade data from 2000 to 2016. Complex network methods and spatial analysis are utilized to explore the networked and spatial characteristics of different international natural resource trade networks (INRTNs). First, we quantitatively present the overall evolution trend of INRTNs by calculating several indicators of network features at the macrolevel. Then, as the intermediate-level characteristics of INRTNs, the core–periphery structures are explored by applying hierarchical clustering and a visual matrix heatmap. Finally, at the microlevel, the imbalance in direction is detected through the combination of node importance in a complex network with bivariate choropleth maps of spatial analysis. The empirical evidence from INRTNs of different product types in this paper will help governments and business administrations to perceive the complex natural resource trade environment, which can instruct policymakers to formulate effective import–export policies and ensure national resource security and sustainable development.

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“…Because the core idea of the complex network theory is that the network structure determines the system function [14]. Recently, complex network theory has become increasingly popular in commodity market and emission research [15][16][17][18] because it reveals market structure through the relationships between traders. Using firm-level emissions trading data, the carbon market can be modeled as a network, whose nodes are firms and whose edges are the trading relationships between companies.…”

Section: Introductionmentioning

confidence: 99%

Network Features of the EU Carbon Trade System: An Evolutionary Perspective

2018

Self Cite

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In this paper, a network model is constructed using real trading data from the EU carbon market. Metric indicators are then introduced to measure the network, and the economic meanings of the indicators are discussed. By integrating time windows with the network model, three types of network features are examined: growth features, structural features, and scale-free features. The growth pattern of the carbon trading network is then analyzed. As the market grow, the geodesic distances become shorter and the clustering coefficients become larger. The trends of these two indicators suggest that the market is evolving towards efficiency; however, their tiny changes are insufficient to have significant impact. By modeling the heterogeneity of the carbon trading network, we find that the trading relationships between firms obey a broken power law model, which consists of two power law models. The broken power law model can be approximately defined as a traditional power law but with a longer tail in distribution. Furthermore, we find that the model is valid for most of the time of both phases, the model only invalid when the market approaches a high growth rate.

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The stability of the international oil trade network from short-term and long-term perspectives

Cited by 41 publications

References 38 publications

A social network analysis of the structure and evolution of intra‐African trade

A social network analysis of the structure and evolution of intra‐African trade

An Exploratory Analysis of Networked and Spatial Characteristics of International Natural Resource Trades (2000–2016)

Network Features of the EU Carbon Trade System: An Evolutionary Perspective

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