Global Trade Network Research Articles

Modeling and assessing the robustness of the lithium global trade system against cascading failures

Because of its essential role in clean energy transition and low carbon economy, lithium is identified as a critical or strategic mineral by many countries or regions, including the US, EU, and China. Due to the unbalanced distribution of resources and production capacity and the separation of the primary lithium consuming and supplying countries, international trade is the main supply channel for lithium consuming countries to acquire enough resources. Comprehending the ability of the lithium trade network against external shocks is essential to supply security. To explore this issue, this paper employs complex network theory to construct a global lithium trading network system (LTNS) and simulates the robustness of LTNS under random and malicious attacks against cascading failures with a nonlinear load-capacity model. Results show that (1) Overall, the robustness of LTNS is poor under random and malicious attacks. (2) Rationally decreasing nodes' total import volume can enhance the robustness of LTNS. (3) A network with a tight link represents poor robustness against cascading failures. Meanwhile, the “head effect” in the network (the minority of nodes with the majority of resources) will make the networks more vulnerable. (4) Australia, Chile, and China have systemic impacts on LTNS. These findings may contribute to managing the supply of strategic raw materials more effectively for the policymakers.

Global trade networks bring targeted opportunity for energy-related CH4 emission mitigation.

Recent literature highlights the contributions the global energy sector has made to anthropogenic CH4 emissions, calling for immediate action. However, extant studies have failed to reveal the energy-related CH4 emissions induced by global trades of intermediate and final commodities or services. This paper traces fugitive CH4 emissions via global trade networks using the multi-regional input-output and complex network models. Results show that approximately four-fifths of global fugitive CH4 emissions in 2014 were associated with international trade, of which 83.07% and 16.93% were embodied in the intermediate and final trades, respectively. Japan, India, the USA, South Korea, and Germany were the world's five largest net importers of embodied fugitive CH4 emissions, while Indonesia, Russia, Nigeria, Qatar, and Iran were the five largest net exporters. Gas-related embodied emission transfers were the largest in both the intermediate and the final trade networks. The fugitive CH4 emissions embodied within the intermediate and final trade networks were all characterized by five trading communities. The virtual fugitive CH4 emission transfers via intermediate trade were largely determined by global energy trade patterns, especially the trade in regionally integrated crude oil and natural gas. Significant heterogeneity was revealed by the coexistence of numerous loosely linked economies and several hub economies (e.g., China, Germany, the USA, and South Africa). Interventions on the demand side of interregional and intraregional trade partners in different communities and hub economies will bring targeted opportunities for global energy-related CH4 emission reduction.

Multi-model assessment identifies livestock grazing as a major contributor to variation in European Union land and water footprints

Food systems are the largest users of land and water resources worldwide. Using a multi-model approach to track food through the global trade network, we calculated the land footprint (LF) and water footprint (WF) of food consumption in the European Union (EU). We estimated the EU LF as 140–222 Mha yr−1 and WF as 569–918 km3 yr−1. These amounts are 5–7% of the global LF and 6–10% of the global WF of agriculture, with the EU representing 6% of the global population. We also calculated the global LF of livestock grazing, accounting only for grass eaten, to be 1,411–1,657 Mha yr−1, and the global LF of agriculture to be 2,809–3,014 Mha yr−1, which is about two-thirds of what the Food and Agriculture Organization Statistics (FAOSTAT) database reports. We discuss here the different methods for calculating the LF for livestock grazing, underscoring the need for a consistent methodology when monitoring the food LF and WF reduction goals set by the EU’s Farm To Fork Strategy.

Tracing global N2O emission mitigation strategies through trade networks

Nitrous oxide (N2O) is the third most potent greenhouse gas (GHG) and the most important ozone depleting substance. But how global N2O emissions are connected through the interwoven trade network remains unclear. This paper attempts to specifically trace anthropogenic N2O emissions via global trade networks using a multi-regional input-output model and a complex network model. Nearly one quarter of global N2O emissions can be linked to products traded internationally in 2014. The top 20 economies contribute to about 70% of the total embodied N2O emission flows. In terms of the trade embodied emissions classified by sources, cropland-, livestock-, chemistry-, and other industries-related embodied N2O emissions account for 41.9%, 31.2%, 19.9%, and 7.0%, respectively. Clustering structure of the global N2O flow network is revealed by the regional integration of 5 trading communities. Hub economies such as mainland China and the USA are collectors and distributors, and some emerging countries, such as Mexico, Brazil, India, and Russia, also exhibit dominance in different kinds of networks. This study selects the cattle sector to further verify that low production-side emission intensities and trade cooperation can lead to N2O emission reduction. In view of the impact of trade networks on global N2O emissions, achieving N2O emission reduction calls for vigorous international cooperation.

The Influence of the Uncertainty of Sino-US Economic and Trade Policy on the Volatility of Corn Futures Market

China and the United States are key players in the global agricultural trade network and important trading partners that interact with each other. However, against the background of escalating trade frictions between China and the United States and the outbreak of the global epidemic, the issue of food prices has once again received much attention. As an indispensable and important part of Sino US trade, corn futures are constantly affected by the uncertainty of the economic and trade policies of the two countries. Based on this, this article, on the basis of establishing a basic theoretical framework for analysis, further explores the transmission mechanism and channels of the impact of trade policy uncertainty on the price of corn futures between China and the United States. It is found that the price changes of corn futures between China and the United States mainly consist of the trade path and the financial path. Accordingly, this article proposes that China and the United States should further strengthen economic and trade consultations, communication and collaboration, strengthen scientific and technological innovation, and promote trade market diversification and other relevant policy recommendations, providing reference opinions and suggestions for the development of Sino US trade relations and the stability of global food prices.

The impact of renewable energy consumption on lithium trade patterns: An industrial chain perspective

Drawing on international panel data from 2000 to 2019, we examine the structural characteristics of the global lithium trade network and investigate the impact of renewable energy consumption on lithium trade patterns from an industrial chain perspective. The findings indicate that different countries play different roles and hold different central positions in the international lithium network. Compared to lithium raw materials, the trade network in lithium products has stronger connectivity and constitutes the bulk of the lithium trade. Regression results reveal that renewable energy consumption significantly affects lithium trade patterns. For lithium raw materials, renewable energy consumption can increase the weighted degree. For lithium products, renewable energy consumption significantly and positively affects the degree centrality and weighted degree. In addition, the effects vary across countries with different income levels. Renewable energy consumption has a greater positive impact on degree centrality in low- and middle-income economies than in high-income economies.

Uncovering the features of global antimony resource trade network

Antimony is a scarce strategic metal and plays an extremely important role in the modern societies. Due to the increasing demands for various antimony-containing products, it is critical to identify the key supply risk of antimony industrial chain. This study aims to uncover the key features of antimony-related trade flows from a global value chain perspective and assess the trade network linkage and features of global antimony resource by using a complex network model and a stochastic block model. Also, the trade network evolution of global antimony resources is investigated by using an exponential random graph expansion method so that valuable policy insights can be obtained for preparing appropriate policies to facilitate sustainable antimony resource management. Results show that the network structure of the global antimony resource presents a significant center-periphery feature. China, India, Vietnam and Tajikistan have always acted as trade intermediaries and bridges of global antimony resources. Also, the evolution of global antimony resources trade network was driven by trade network autonomy and exogenous network embeddedness. In addition, geopolitics is the biggest obstacle to maintain the operation of this global antimony trade network. Finally, policy recommendations are proposed to help ensure sustainable supply of antimony resources.

Prediction of Electricity Trade Partners Based on the Network Theory: The West Asia Community

This study aims to predict electricity cross-border trade partners based on the network theory and to investigate the position and importance of West Asia community in the global electricity trade network. For this purpose, the global network is constructed to examine the role of each node in the network for the time period of 2010–2018. Different communities are identified to proceed with the network analysis. The innovative analysis is link prediction to forecast missing links from the network. The results suggest more interconnectedness among community members, especially Iran, Turkey and Russia, which are the prominent nodes in the community. The link prediction outcomes offer the most probable missing links from the community and lead us to select the common neighbour approach as the most efficient method. JEL Codes: D85, Q27

The impact of geopolitical relations on the evolution of cobalt trade network from the perspective of industrial chain

The turbulent international situation in recent years has aroused a profound impact on global cobalt trade, so it is necessary to investigate the influence of geopolitical relations on cobalt trade. This study divides the geopolitical network into cooperation network and conflict network. Besides, the evolution of global cobalt trade network is studied from the perspective of the whole industry chain. Furthermore, the impact of geopolitical relations on the evolution of cobalt trade network is studied based on QAP method and ERGM. The results show that (1) The scale of geopolitical cooperation network is larger than that of conflict network, while more and more countries have participated in the global geopolitical conflict in recent years; (2) The cooperation network has significant positive impact only on the evolution of midstream and downstream, and the conflict network has the opposite impact on them, indicating that geopolitical cooperation will promote the formation of new trade relations; (3) The influence on the evolution of cobalt trade network increases first and then decreases over time. This paper suggests that countries should pay special attention to geopolitical cooperation and establish more cooperation with countries with high political stability.

Evolution of the rare earth trade network: A perspective of dependency and competition

As a global strategic reserve resource, rare earth has been widely used in important industries, such as military equipment and biomedicine. However, existing analyses based solely on the total volume of rare earth trade fail to uncover the underlying competition and dependency dynamics. To address this gap, this paper employs the principles of trade preference and import similarity to construct dependency and competition networks. Complex network analysis is then employed to study the evolution of the global rare earth trade network from 2002 to 2018. The main conclusions are as follows. The global rare earth trade follows the Pareto principle, and the trade network shows a scale-free distribution. China has emerged as the world’s largest importer and exporter of rare earth since 2017. In the dependency network, China has become the most dependent country since 2006. The result of community division shows that China has separated from the American community and formed new communities with the Association of Southeast Asian Nations (ASEAN) countries. The United States of America has formed a super-strong community with European and Asian countries. In the competition network, the distribution of competition intensity follows a scale-free distribution. Most countries face low-intensity competition, but there are numerous competing countries. The competition related to China has increased significantly. Lastly, the competition source for the United States of America has shifted from Mexico to China, resulting in China, the USA, and Japan becoming the core participants in the competition network.

Compressing network populations with modal networks reveal structural diversity

Analyzing relational data consisting of multiple samples or layers involves critical challenges: How many networks are required to capture the variety of structures in the data? And what are the structures of these representative networks? We describe efficient nonparametric methods derived from the minimum description length principle to construct the network representations automatically. The methods input a population of networks or a multilayer network measured on a fixed set of nodes and output a small set of representative networks together with an assignment of each network sample or layer to one of the representative networks. We identify the representative networks and assign network samples to them with an efficient Monte Carlo scheme that minimizes our description length objective. For temporally ordered networks, we use a polynomial time dynamic programming approach that restricts the clusters of network layers to be temporally contiguous. These methods recover planted heterogeneity in synthetic network populations and identify essential structural heterogeneities in global trade and fossil record networks. Our methods are principled, scalable, parameter-free, and accommodate a wide range of data, providing a unified lens for exploratory analyses and preprocessing large sets of network samples.

Comparative technical-economic evaluation of offshore container port systems

ABSTRACT The growth trend in the container industry has had a significant operational and infrastructural impact on the ports. In this context, the offshore port systems are expected to be an innovative port system in the effective use of mega container ships by offering operational and structural advantages. This study aims to guide the authorities on whether OCPS is worth investing in, in terms of investment costs. This article also highlights the financial feasibility of an OCPS that can allow countries with difficult nautical access to mega vessels to enter the global trade network. The data in this research were obtained from similar projects and studies with a series of industry assumptions. Overall, these results indicate that OCPS can compete with conventional ports in terms of investment costs, operating costs, and return on investment. Thus, a more sustainable container shipping network can be achieved with the advantages of OCPS.

Blue Seaports: The Smart, Sustainable and Electrified Ports of the Future

Seaports are at the forefront of global trade networks, serving as hubs for maritime logistics and the transportation of goods and people. To meet the requirements of such networks, seaport authorities are investing in advanced technologies to enhance the efficiency and reliability of port infrastructures. This can be achieved through the digitalization and automation of core systems, aimed at optimizing the management and handling of both goods and people. Furthermore, a significant effort is being made towards a green energy transition at seaports, which can be supported through marine renewable sources. This promotes energy-mix diversification and autonomy, whilst reducing the noteworthy environmental footprint of seaport activities. By analyzing these pertinent topics under the scope of a review of container-terminal case studies, and these ports’ respective contexts, this paper seeks to identify pioneering smart seaports in the fields of automation, real-time management, connectivity and accessibility control. To foster the sustainable development of seaports, from an energy perspective, the potential integration with marine renewable-energy systems is considered, as well as their capabilities for meeting, even if only partially, the energy demands of seaports. By combining these fields, we attempt to construct a holistic proposal for a “model port” representing the expected evolution towards the seaports of the future.

Analysis of the global trade network of the chip industry chain: Does the U.S.-China tech war matter?

Chip is the “brain” of the information industry and modern manufacturing industry, and supply chain security is the key to the sustainable development of the industrial chain. From the perspective of the industrial chain, this paper selected semiconductor silicon wafers and equipment, integrated circuits, electronic computers, and components as representative commodities in the upstream, midstream, and downstream of the chip industry chain, constructed global trade networks of the chip industry chain, and analyzed the characteristics of the networks and nodes in 2020 and the changes in China's status before and after the China-U.S. tech war. The study results indicate that the network scale and network density of the global trade network of downstream electronic computers and components are higher than those of midstream integrated circuits; the global trade network of upstream semiconductor wafers and equipment has the smallest network scale and network density, and the trade networks of all links show obvious small-world characteristics; The United States ranks first in betweenness centrality of all links, with the strongest control ability and the largest number of trading partners in all links; China has higher betweenness centrality and more trading partners in the global trade network of the two upstream commodities than that of the midstream commodities, and the lowest betweenness centrality in the global trade network of the downstream commodities; The core countries of the chip industry chain are concentrated in southeast Asia, east Asia, central and western Europe, and the United States. China's trade status of semiconductor silicon wafers and integrated circuits has declined significantly during the China-U.S. tech war. The nodes in the chip trade network have good robustness in the face of random attacks and show vulnerability under target attacks. Additionally, the trade network's robustness in the chip industry chain is the strongest for downstream commodities, ranks second for midstream commodities, and is the weakest for upstream commodities. These findings can provide references for ensuring chip supply chain security in China and other trade-participating countries.

Evolution and Impacting Factors of Global Renewable Energy Products Trade Network: An Empirical Investigation Based on ERGM Model

Global trade of renewable energy products has increased significantly in recent years. This paper constructs an analytical framework of a global trade network for renewable energy products based on bilateral trade data between 2009 and 2019. It analyses its structural evolution at the global and local levels and investigates the influencing factors of the network with the Exponential Random Graph Model. The empirical results indicate that countries in the trade network have become more closely connected, featuring a core-periphery and increasing reciprocity relationship. China, Germany, and Japan have remained in the position of core countries; China has especially been prominent among core countries. Our empirical results verify that the sender-receiver effects can explain the evolution of this global trade network. The empirical results also indicate that the climate change agreement network and the common border network have positive effects on the formation of the trade network. As regards political implications, the core countries in the trade network should optimize the layout of renewable energy development and improve infrastructure accordingly. Countries should also jointly build a more fair and reasonable multilateral system that fulfills their responsibilities.

Unfolding carbon inequality across Belt and Road Initiative countries and regions under a global trade network

The Belt and Road Initiative (BRI) has boosted global trade and economic development. Carbon inequality embodied in global trade may occur across BRI countries and regions in the world. How to quantify this inequality is the key to achieving the green development of the Belt and Road. In this study, we constructed a methodological framework to analyze carbon inequality across BRI countries and regions under the global trade network. Results showed that nearly half of BRI countries and regions exported net embodied carbon emissions while obtaining net economic benefits. The most severe bilateral trade carbon inequality existed between China and BRI West Asia, whose bilateral trade carbon inequality index (BCI) reached 2.76. Except for Indonesia, Saudi Arabia, and BRI West Asia, BRI countries and regions were negatively affected by global trade carbon inequality, with China and India suffering the most, whose global trade carbon inequality indices (GCI) were -2.06 and -1.26, respectively. This methodological framework can be applied to analyze the inequality of other kinds of ecological impacts embodied in trade on any scale. Furthermore, this study can provide policy implications for the green development of the Belt and Road.

Global Shrinkage of Space and the Hub-and-Spoke System in the Global Trade Network

We explore how the hub-and-spoke system in the international freight transportation network contributes to the global shrinkage of space. The friction in long-distance trade routes varies by the location of shippers and nodal characteristics of traversed ports, and is mitigated by the quality of scale economies driven by the hub-and-spoke distribution system along the trajectory of the logistic process. In order to confirm the shrinkage of space brought about by the hub-and-spoke shipping economies through transshipment routes via hub ports, we examine disaggregated cross-Atlantic cargo shipping trajectory data from Europe to the U.S. recorded both on landside and seaside with a discrete choice model. The results present that hub-and-spoke shipping economies arise with the scales of landside and maritime port operations and with shipping line diversity. Generally, they are found to offset distance friction that occurs along landside and maritime shipping voyages, but hub-and-spoke shipping economies arise differently depending on how hub-and-spoke configurations are set. They mainly stem from larger scale of ports’ operation and more diverse shipping lines serving the final port of export. The hub-and-spoke system is confirmed as a main driver of global shrinkage of space in terms of long-distance commercial activities.

Structural properties and evolution of global photovoltaic industry trade network.

As resource shortages and environmental problems keep coming up, economies urgently need renewable energies as the new driving force for development. As one of the representatives of renewable energy, the photovoltaic (PV)'s trade has received much attention from all walks of life. Based on bilateral PV trade data, complex network methods and exponential random graph models (ERGM), this paper constructs global PV trade networks (PVTNs) during 2000-2019, describes detailed evolution features and verifies the influencing factors of the PVTNs. We find that (1) PVTNs have obvious characteristics of the small-world network, accompanied by disassortativity and low reciprocity. (2) Asia, North America, and Europe are the top 3 leading regions in the PVTNs. (3) China is the largest exporter, and the US is the leading recipient. Germany is an essential importer as well as exporter of PVTNs. (4) The formation and evolution of the PVTNs are significantly affected by transitivity, reciprocity, and stability. PV trade is more possible when economy-pairs are WTO members, located on the same continent, or with asymmetrical urbanization rates, industrialization rates, technological level or environmental supervision strength. Specifically, economies with higher industrialization rates, technological levels, stricter environmental regulations or lower urbanization rates are more likely to import PV. Economies with higher economic development, larger area, and greater trade openness are more inclined to trade PV. Besides, economic partners that share a religion or language, have common historical colonial ties or geographic borders or sign regional trade agreements are more likely to trade PV.

Analysis on the evolution characteristics of barite international trade pattern based on complex networks

Barite is widely used in oil and gas drilling and strategic emerging industries, and its strategic position is becoming increasingly prominent. Based on a complex network approach, this paper constructs a global barite trade network (BTN) from 2000 to 2020, analyzes the evolutionary characteristics of the global barite trade pattern, and identifies the key trading countries and main trading communities. The findings show that the global BTN has become more connected and efficient. The import status of European countries has weakened, but there is still a high degree of activity in the barite trade. The import status of barite in North American countries has always been high, and the import status of barite in South American countries has been significantly enhanced. Asia is an important region for barite export trade. China and Turkey, important exporting countries in Asia, have become more active in barite export trade. The discourse and control of barite trade are more in the hands of developed countries in Europe and the United States, but emerging economies such as China and India are increasingly playing an important role. Further research revealed that the main trading communities of barite gradually evolved from two main trading communities dominated by China and Germany to six main trading communities dominated by China, India, Turkey, USA, Germany, and Morocco. The traditional dominant powers, China and Germany, have weakened in their communities, and the emerging dominant powers, the United States, India, and Turkey, have increased their power in their communities.

Physical and virtual nutrient flows in global telecoupled agricultural trade networks

Global agricultural trade creates multiple telecoupled flows of nitrogen (N) and phosphorus (P). The flows of physical and virtual nutrients along with trade have discrepant effects on natural resources in different countries. However, existing literature has not quantified or analyzed such effects yet. Here we quantified the physical and virtual N and P flows embedded in the global agricultural trade networks from 1997 to 2016 and elaborated components of the telecoupling framework. The N and P flows both increased continuously and more than 25% of global consumption of nutrients in agricultural products were related to physical nutrient flows, while virtual nutrient flows were equivalent to one-third of the nutrients inputs into global agricultural system. These flows have positive telecoupling effects on saving N and P resources at the global scale. Reducing inefficient trade flows will enhance resource conservation, environmental sustainability in the hyper-globalized world.