Global Trade Patterns Research Articles

Geopolitical risk and sustainable shipping: a quantitative approach

ABSTRACT Shipping is pivotal for global trade and by extension, the global economy. In recent decades the industry has been striving for sustainable development, as it battles with an arsenal of issues, including its environmental footprint, efficiency, and profitability. At the same time, the international nature of the maritime industry renders it extremely sensitive to geopolitical issues, as the recent conflict in Ukraine revealed. The latter has influenced a battery of topics ranging from global energy supply and demand, food security, and diplomacy, among others. One of these includes global trade and shipping patterns. This research focuses on data collected with reference to shipping intensity to investigate the exact connection between geopolitical risk and shipping. The results point to a strong relationship, thus providing empirical evidence of the sensitivity of shipping to geopolitics. The findings of this study aspire to assist towards preventative policies that can help the maritime industry become more economically sustainable.

A study on time-varying dependence between energy markets and linked assets based on the Russia-Ukraine conflict

The energy industry, acutely sensitive to geopolitical shifts due to the Russia-Ukraine conflict, experiences sustained disturbances in global energy markets, reshaping global energy supply dynamics and significantly influencing global trade patterns. Utilizing static and dynamic GARCH-Copula models, this study elucidates the dependency between energy markets and related assets. The Copula function, when compared with the multivariate GARCH model, demonstrates distinct advantages, notably in delineating joint asset distributions, capturing market dependence's nonlinear traits, and highlighting robust tail correlation structures. Beyond the average inter-market dependence, its tail correlation offers a vital perspective on market risk. This research delves into the temporal and structural variations in interdependence between energy markets and related assets. It probes potential structural breakpoints in dynamic interdependence and pinpoints their occurrences. By focusing on the Russia-Ukraine conflict, this study offers a holistic view of the changing interplay between the energy market and other asset categories, providing pivotal insights for investor portfolio optimization, regulatory oversight, and risk mitigation. Moreover, employing wavelet analysis, this study examines the frequency domain traits of the interdependency between energy markets and associated assets. As frequency wanes, market price fluctuations become less pronounced. The continuous wavelet power spectrum indicates that price variations are predominantly mid to high frequency. Cross-wavelet transform results suggest that correlations between energy markets and related assets are more influenced by short-term perturbations than enduring shifts.

The study on the effect of restrictive rosewood trade policies on China’s rosewood import prices

PurposeRosewood, as the most internationally traded endangered species, is subject to a series of restrictive trade policies globally. China has historically been the largest importer of rosewood in the world. The fluctuation of China’s rosewood import prices will have a profound impact on the global rosewood trade pattern. This study, therefore, assessed the impact of restrictive trade policies on China’s rosewood import prices to explore the fluctuation rule of rosewood trade prices under restrictive policies.Design/methodology/approachThe study built a partial equilibrium framework about the formation mechanism of rosewood import price bubbles under supply constraints. On this basis, with China’s daily import prices of major rosewood species, the generalized supremum augmented Dickey–Fuller (GSADF) and backward supremum augmented Dickey–Fuller (BSADF) tests were applied to explore the effect of restrictive trade policies on China’s rosewood import prices.FindingsThe empirical analysis revealed that there were multiple price bubbles for five of the seven rosewood species. The largest bubbles were always created before and after the deployment of supply constraints. The empirical results for the counterfactual examples implied that price bubbles would not have occurred if restrictive rosewood trade policies had not been implemented. The above findings indicated that these measures tended to trigger significant price bubbles in China’s rosewood imports.Originality/valueThe effect of restrictive rosewood trade policies on rosewood trade prices had not yet been explored in previous research studies. This study empirically analyzed the effect of restrictive trade policies on China’s rosewood import prices using econometric models.

Importing Clothing Made from Recycled Textile Materials? A Study of Retailers’ Sourcing Strategies in Five European Countries

This study examined retailers’ sourcing strategies for clothing made from recycled textile materials in the five largest European clothing retail markets (i.e., the UK, Italy, France, Germany, and Spain), given the increasing availability of such products. The multivariate analysis of variance (MANOVA) was conducted based on the detailed country of origin and product assortment information of thousands of such clothing items for sale in these five EU countries from January 2021 to May 2023. The results show that EU retailers sourced clothing using recycled textile materials diversely from over 40 developing and developed countries across Asia, America, Europe, and Africa. The geographic location of supplying countries statistically affects the detailed assortment of recycled clothing that EU retailers import. However, apart from assortment diversity, no statistical evidence indicates that developing countries had advantages over developed ones regarding product sophistication, replenishment frequency, and pricing in the five EU markets. The study’s findings offer new insights into the business aspects of recycled clothing and reveal promising global sourcing opportunities for such products. The results also imply a potentially significant shift in global apparel trade patterns as retailers embrace fashion circularity and expand sourcing clothing made from recycled textile materials.

The Potential Effects of De-risking from China on Global Economic Growth and Trade Patterns

This study explores the potential effects of de-risking from China on global economic growth and trade patterns, shedding light on the main drivers behind this trend and its macroeconomic implications. By analyzing the challenges and opportunities associated with diversifying supply chains away from China, this research provides valuable insights for policymakers, businesses, and stakeholders. The study identifies key factors driving de-risking, including bureaucratic restrictions, global economic shifts, customer demands, the COVID-19 pandemic, geopolitical stability, and national security concerns. While there are logistical, financial, regulatory, operational, and strategic challenges, there are also opportunities for improving economic growth, competitiveness, resilience, sustainability, innovation, and social development. The findings contribute to a better understanding of the complexities of supply chain diversification and its impacts on the global economy. Future research could explore the long-term impacts of de-risking on global trade dynamics and investigate the role of digital technologies and innovation in shaping new supply chain strategies.

Agricultural policy reforms in Uzbekistan to increase the export share

This article underscores the persistent and sustained initiatives undertaken by the government of the Republic of Uzbekistan to augment the export of agricultural products. Positioned as the primary architects of policies, state organizations play an exclusive role in formulating strategies that not only analyze global trends but also consider market dynamics. This comprehensive approach is geared toward adapting and implementing both new and existing policy reforms in the agricultural market and production sector. The emphasis on continuous analysis of market dynamics reflects a commitment to staying abreast of changes in global demand, supply, and trade patterns. This ongoing assessment enables timely adjustments to policies, ensuring they remain responsive to the evolving landscape of the international agricultural market. The article suggests that the Republic of Uzbekistan recognizes the pivotal role of the agricultural sector in its economic growth and is actively working through its state organizations to position itself strategically in the global market. By adopting adaptive policies and reforms, the competitiveness of its agricultural products and foster sustained growth in agricultural exports.

Evolution of global phosphorus products trade pattern and China’s phosphorus import and export security

Evolution of global phosphorus products trade pattern and China’s phosphorus import and export security

Evolution and vulnerability analysis of the global trade pattern in the lithium industry chain

Evolution and vulnerability analysis of the global trade pattern in the lithium industry chain

Deploying Machine Learning Methods to Predict Global Trade Patterns: The Case of Beef

Highlights Machine Learning (ML) methods are offered as an alternative to conventional techniques for understanding global commodity trade. A formal comparison is made between ML results with those from the Poisson Pseudo Maximum Likelihood (PPML) Estimator, which is the most commonly used statistical technique for bilateral trade analysis. PPML takes into account fixed effects and the dynamic nature of panel data to provide a better fit and higher prediction accuracy than ML in the context of in-sample forecasts. ML methods have strengths in feature selection, better validation statistics, and stronger predictive power than PPML, especially with out-of-sample forecasts. Abstract. In international economics, there has been a steady stream of innovations to explain patterns of trade between and among countries with emerging techniques. The most recent - Poisson Pseudo Maximum Likelihood (PPML) estimator – corrects for a potential bias caused by the large proportion of zero observations in bilateral trade data. Alternatively, this study offers Machine Learning (ML) as an option, especially in the presence of finer data on bilateral trade patterns. Using monthly and HS-6-digit (product) level data, the study finds that the main advantage of PPML is its accuracy of forecasts in-sample, but feature selection is somewhat rigid due to the inclusion of a large number of pair-wise fixed effects. ML models have the advantage in selecting features when a long list of explanatory variables is to be considered. Model validation statistics such as MAE and RMSE favor ML methods, but PPML tends to yield higher goodness of fit. In the out-of-sample context, ML has better accuracy than PPML, and a one-step walk-forward ML approach further improves the accuracy of ML forecasts. While PPML has a rich research and application history, emerging ML techniques have sufficient room for improvement in their adaptation to economic analysis. Keywords: Beef, Bilateral Trade, Boosting, Machine learning, ML for Policy

Climate Cha(lle)nges in global wine production and trade patterns

The global wine trade is interested by significant changes since a few decades, due to new productive scenarios induced by climate change and to (rapidly) evolving trade and policy regimes. We investigate how these changes are altering trade dynamics. Following a gravity-type approach, we find that higher temperatures are beneficial for the terms of trade, and are boosting trade values. As for policy interventions, the impact of technical measures on trade values is heterogeneous across objectives: While technical measures tend to friction trade, the environment-related policies show pro-trade effects.

Leverage points for tackling unsustainable global value chains: market-based measures versus transformative alternatives

Tropical forests are rapidly disappearing due to the expansion of cash crops to meet demands from distant markets. Pressing concerns on deforestation impacts resulting from the global trade of tropical commodities have led some high-income countries’ governments to consider diverse regulatory and trade levers to tackle the problem. These include proposals for new supply chain due diligence legislation concerning imports of forest-risk products and the inclusion of environmental measures in trade deals. To contribute to this debate, we conducted a comprehensive analysis of existing data on global trade and consumption patterns of tropical commodities, attribution of commodity production to deforestation, trade agreements, and progress in the implementation of crop sustainability standards. We used global data on key tropical commodities of oil palm, cocoa, and coffee. Our study shows that high-income countries have the highest per capita consumption for the three commodities evaluated and that consumption rates have dramatically increased in the last two decades. We discuss a range of measures that can potentially be required to tackle deforestation in global supply chains, which are currently being considered by policymakers, before discussing the kinds of post-growth, convivial approaches that are often excluded by the framing. Given the inherent expansionary nature of global market dynamics, we show that market-based initiatives are inadequate to tackle continuing deforestation and socio-ecological degradation. More transformative solutions amplify commoning and post-growth approaches are required to lead to some uncoupling of trade and territorialising of economic activity to fit within planetary boundaries and allow for plural values.

EU-Russia energy decoupling in combination with the updated NDCs impacts on global fossil energy trade and carbon emissions

The updated nationally determined contributions (NDCs) and EU-Russia energy decoupling have profound impacts on global fossil energy trade and carbon emissions. This study utilizes a dynamic general equilibrium model (GDyn-E) and conducts scenario analysis to illustrate the evolving patterns of global fossil energy trade and carbon emissions in light of the updated NDCs and EU-Russia energy decoupling. A sharp decrease in global fossil fuel consumption will reduce the global volume of fossil energy trade. Major fossil energy trade flows will divert from Europe to Asia, particularly China and India. EU-Russia energy decoupling directly triggers adjustments in the global fossil energy trade such that the EU imports more fossil energy from the Middle East, Norway, and the United States, while Russian fossil energy exports are steered toward Asia. This shift in energy trade patterns is expected to lead to a reduction of approximately 2 Gt CO2 in cumulative carbon emissions worldwide by 2050, which is primarily driven by the intensified efforts of European countries in transitioning to renewable energy sources. The findings of this study offer valuable insights into the interplay between geopolitical conflicts, fossil energy trade dynamics, the updated NDCs, and carbon emission reduction.

The Electronic Industry Intra-Industry Trade Analysis in 10 Indonesian Trading Partners

The importance of international trade in the context of refrigerator products makes intra-industry trade intensity (IIT) a very relevant tool. In international trade policymaking, particularly concerning refrigerator products, IIT is essential for understanding global economic dynamics, trade patterns, and trade relations between Indonesia and its trading partners. The use of IIT can provide deep insights into the extent to which there is an exchange of similar or similar but different goods among countries involved in the trade of refrigerator products. Therefore, the focus of the problem in this context is the extent to which the Indonesian refrigerator industry depends on ten trading partners in terms of exports and imports of refrigerator products and how this degree of dependence affects the stability of the sector in the face of changing global trade conditions. Regarding exports, India is the most important trading partner with a significant contribution, indicating a dependency that requires special attention. India has also emerged as an essential supplier, albeit with a lower level of dependence. Diversifying export and import markets should be considered to reduce the risk of dependence on certain trading partners. IIT analysis can also provide insights into the competitiveness of Indonesian products in the international market —improvement of export success also depends on understanding intra-industry trade dynamics.

Second-hand clothing trade: achieving circular economy in the fashion sector through international cooperation

This paper explores the global dynamics of second-hand clothing (SHC) in light of the circular economy to identify gaps and suggest pathways to reduce negative impacts on the sector. The analysis identifies current global patterns of SHC international trade and the main hotspots, in order to build a framework for action. The framework incorporates the main stakeholders and a set of actions aimed at reducing the environmental and social issues associated with the international trade of SHC. The analysis suggests that the framework may reduce risks and facilitate the transition to a just circular economy in the SHC sector.

Temporal and spatial evolution of global major grain trade patterns

The complex and volatile international landscape has significantly impacted global grain supply security. This study uses a complex network analysis model to examine the evolution and trends of the global major grain trade from 1990 to 2020, focusing on network topology, centrality ranking, and community structure. There are three major findings. First, the global major grain trade network has expanded in scale, with a growing emphasis on diversification and balance. During the study period, the United States, Canada, China, and Brazil were the core nodes of the network. Grain-exporting countries were mainly situated in Asia, the Americas, and Europe, and importing countries in Asia, Africa, and Europe. Second, a significant increase in the number of high centrality countries with high export capacity occurred, benefiting from natural advantages such as fertile land and favorable climates. Third, the main global grain trade network is divided into four communities, with the Americas-Europe community being the largest and most widespread. The formation of the community pattern was influenced by geographic proximity, driven by the core exporting countries. Therefore, the world needs to enhance the existing trade model, promote the multi-polarization of the grain trade network, and establish a global vision for the future community. Countries and regions should participate actively in global grain trade security governance and institutional reform, expand trade links with other countries, and optimize import and export policies to reduce trade risks.

Climate Change Will Lead to a Significant Reduction in the Global Cultivation of Panicum milliaceum

Panicum milliaceum is a specialty crop that maintains the economic stability of agriculture in arid and barren regions of the world. Predicting the potential geographic distribution of Panicum milliaceum globally and clarifying the ecological needs of Panicum milliaceum will help to advance the development of agriculture, which is important for the maintenance of human life and health. In this study, based on 5637 global distribution records of Panicum milliaceum, we used the MaxEnt model and ArcGIS software, the Beijing Climate Center Climate System Model (BCC-CSM2-MR) was selected to predict the potential global geographic distribution of Panicum milliaceum in the present and future in combination with the environmental factor variables; we evaluated the significant factors constraining the potential geographic distribution of Panicum milliaceum by combining the contributions of environmental factor variables; and we assessed the accuracy of the MaxEnt model by using AUC values and Kappa statistics. The results showed that the MaxEnt model was highly accurate, the simulation results were credible, and the total suitable area of Panicum milliaceum in the world is 4563.82 × 104 km2. The high habitat area of Panicum milliaceum is 484.95 × 104 km2, accounting for 10.63% of the total habitat area, and is mainly distributed in the United States, the Russian Federation, France, Ukraine, Australia, Germany, etc. The soil factor (hswd) was the most important environmental factor limiting the potential geographic distribution of Panicum milliaceum, followed by the precipitation factor (Precipitation of the Driest Month, bio14) and temperature factor (Mean Temperature of the Wettest Quarter, bio8). Under four future climate change scenarios, the area of the potential geographic distribution of Panicum milliaceum decreased to different extents at different levels compared to the contemporary period. Therefore, climate change may significantly affect the global distribution pattern of Panicum milliaceum cultivation in the future and thus reshape global Panicum milliaceum production and trade patterns.

Evolution of Global Plastic Scrap Trade and Analysis of China's Plastic Scrap Trade Network under the "Dual Carbon" Goal

Plastics and their products are favored by the public for their advantages such as good corrosion resistance, high convenience, good transparency, cheap price, and wide range of uses, which have triggered a further increase in the demand for plastics and their products. However, plastics and their products directly or indirectly affect the global climate due to their inability to be decomposed naturally, easy to burn and produce toxic gases, and difficult to be recycled. Based on the UN Comtrade database, this paper obtains the global scrap plastics trade data from 2012 to 2021, including 233 countries around the world, constructs 20 overall trade networks of import and export of global scrap plastics trade, and synthesizes 10 years of data to explore the characteristics of the global plastics trade pattern as well as the evolution process, and conducts an analysis of China's plastics trade network in terms of the structure of the trade network and the roles and partners. Analyze the trade network from the perspective of trade network structure and roles and partners. The results show that: the participation of developing countries in import gradually increases, while developed countries take the primary position in export; China exits from the top in both import and export rankings in the evolution of the trade pattern of plastics scrap; the global greenhouse effect and the aggravation of environmental pollution make the participation in the import trade of every country in the world decline, but still dominated by developed countries.

Features and Evolution of Global Energy Trade Patterns from the Perspective of Complex Networks

As an integral part of economic trade, energy trade is crucial to international dynamics and national interests. In this study, an international energy trade network is constructed by abstracting countries as nodes and representing energy trade relations as edges. A variety of indicators are designed in terms of networks, nodes, bilaterals, and communities to analyze the temporal and spatial evolution of the global energy trade network from 2001 to 2020. The results indicate that network density and strength have been steadily increasing since the beginning of the 21st century. It is observed that the position of the United States as the core of the international energy market is being impacted by emerging developing countries, thus affecting the existing trade balance based on topological analysis. The weighted analysis of bilateral relations demonstrates that emerging countries such as China, Brazil, and Saudi Arabia are pursuing closer cooperation. The community analysis reveals that an increasing number of countries possess strong energy trade capabilities, resulting in a corresponding increase in energy trade volumes.

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.

The Impact of Sino-Us Trade Friction on China’s Argo-forest Products: Stylized Facts and Prospect

Sino-US trade friction is a crucial issue in the economic relationship between China and the USA. This paper analyzes how friction influences the bilateral trade of agroforestry products from the perspective of changes in trade volume, using recent-year data. The results show that Sino-US trade friction dissevers and reconstructs the global value chain of agroforestry products. This variation imposes more harm than good on the related global trade pattern. Furthermore, this paper lists and illustrates three measures taken by the Chinese government to deal with the trade friction: expanding the alternative market to meet domestic demand and fill the supply gap, improving the added value to ameliorate the structure of foreign trade and enhancing core competitiveness, and establishing an early warning mechanism to guard against abnormal changes in the international market and increase trade security. Finally, in response to the situation of trade friction, this paper puts forward two politically-sound suggestions that should be adopted by China and the USA for rebuilding a mutually beneficial pattern: negotiating rationally and following the rules of the WTO.