Trade Data Research Articles

A Study of Factors Influencing China's Agricultural Exports to Japan

As a key focus of trade negotiations between China and Japan, trade in agricultural products has received special attention to the tariffs and preferential conditions involved. According to data provided by China Customs, China's agricultural exports to Japan fell after peaking in 2012 and fell further to 9.64 billion yuan in 2020. This paper selects the 2000-2021 china export agricultural products trade data from the Department of Foreign Trade of the Ministry of Commerce to Analyze the trade status of Japan, and finds that the scale of trade shows an expanding trend, and there are fluctuations in some years. Establish a business gravity model, study the effectiveness and potential of developing China's agricultural export trade with Japan, and analyze various factors affecting the effectiveness of agricultural export trade, and the results show that there is room for progress in China's agricultural export trade with Japan, and the scale of trade can be further expanded. Finally, it proposes to further improve the export efficiency of agricultural products, stabilize the exchange rate, improve import and export policy control and further broaden the foreign trade market, optimize the trade structure and promote the quality of agricultural products.

Use of Satellite Imagery for Banyuwangi Lampon Beach Tourist Road Track Planning

Transportation is a crucial element in the development of an area, especially in the context of developing transportation routes in Lampon Beach, Banyuwangi Regency. With inadequate road access, the development of road routes on this beach is a priority to increase the region's economic productivity by utilizing the potential of natural resources. This research applied the spatial data-based Technology-Based Integration Method with the support of ArcGIS and Civil 3D software. Two road traces were generated, with the total length of trace 1 is 4.76 km and trace 2 is 4.98 km; the volume data of trade 1 with excavation amounted to 52,064.09 m3, and embankment amounted to 15,002.59 m3. Meanwhile, the volume of trade 2 with excavation amounted to 89,464.92 m3, and the barrier amounted to 12,537.02 m3. These results demonstrate the efficiency and accuracy of infrastructure planning on the geographical and spatial characteristics of the region. The assessment of excavation and embankment costs provides an overview of the resources required by applicable standards and regulations. This approach contributes significantly to selecting efficient road routes and a better understanding the resources needed for infrastructure development.

Dynamic changes in the bauxite trade competition network structure and its influencing factors: Based on temporal exponential random graph model

Global bauxite resource mismatch, limited resources and rising demand have led to intense import competition and export competition. Based on the bauxite trade data from 2005 to 2020, this study uses the complex network method to construct the bauxite import and export competition network, analyzes the evolution of the global bauxite competition pattern and influencing factors. The results show that: First, the density of global bauxite competition network as a whole is on the rise, and competition networks are somewhat resistant to destruction. Second, the import competition network shows a clear trend towards eastward migration, with China's competition strength standing out. Most of the competing economies in the export competition network are large bauxite resource economies. Third, both import and export competition networks show a tendency to spread from core and semi-periphery regions to periphery region. Finally, it can be seen from the influencing factors analysis, the competition network of bauxite has stability. GDP, population, and FTA significantly promote the formation of competition networks, while CO2 and geographic distance play the opposite role. In addition, the effects of industrial structure, common language and common colony on the import and export competition networks are not uniform.

Limited or Biased: Modeling Subrational Human Investors in Financial Markets

Human decision-making in real-life deviates significantly from optimal decisions made by fully rational agents, primarily due to computational limitations or psychological biases. While existing studies in psychology and economics have discovered various types of human limitations and biases, there lacks a comprehensive framework to transfer these findings into models of subrational investors in financial markets. In this study, we introduce a unified framework that use reinforcement learning (RL) to incorporate five different aspects of human subrationality including bounded rationality, myopic behavior, prospect-biased behavior, optimistic and pessimistic behaviors. Unlike the data-driven approaches, our model is trained based on a high-fidelity multi-agent market simulator, which is not limited by the availability of subrational investor trading data. Our framework demonstrates investment behavior that is characteristic of each type of subrationality in hand-crafted market scenarios. We evaluate the Profit and Loss (PnL) of different types of subrational investors, and use SHAP value analysis to reveal the driving factors in their decision-making process. Finally, we explore the impact of subrationality on market quality regarding liquidity, volatility, and efficiency. Our experiments indicate that bounded-rational and prospect-biased human behaviors improve liquidity but diminish price efficiency, whereas human behavior influenced by myopia, optimism, and pessimism reduces market liquidity.

The Geoeconomic Turn in EU Trade and Investment Policy: Implications for Developing Countries

The so-called geoeconomic turn in global trade policy-making has changed the context in which the European Union positions itself as a trade actor. However, there is little scholarly attention paid to how the geoeconomic turn affects the EU’s relations with developing countries. This article analyses the potential implications of new EU autonomous trade and investment instruments for developing countries, and how the EU has taken these consequences into account when designing them. We rely on a combination of desk research of official documents, trade data, and secondary literature complemented with expert interviews. We find that a trade-off between geoeconomic and development objectives is more pertinent in sustainability-related than in competitiveness- and security-oriented instruments. In these sustainability instruments, differential treatment of developing countries rarely features in the design—despite some proposals having been made. The geoeconomic turn has thus made it more difficult to align the different objectives in the EU’s trade and investment policies, and development concerns are sometimes relegated to the background.

Study on the current situation and influencing factors of corn import trade in China – based on the trade gravity model

Abstract With the rapid development of China’s economy and society, the income level of Chinese residents is increasing day by day, and the dietary consumption structure of domestic residents is constantly optimized and upgraded. The consumption demand for livestock products such as meat, eggs and milk, and corn starch industrial products is increasing day by day. Therefore, as the main raw material of feed industry and deep processing owners, the consumption scale of China corn market is constantly expanding. However, the corresponding domestic corn production scale has not expanded, and the domestic corn production presents an obvious problem of insufficient supply scale, which leads to a sharp and rapid increase in the number of corn imports in China, which seriously impacts the domestic corn market and affects China’s healthy development of corn industry. In recent years, the continuous spread of the COVID-19 epidemic has seriously affected the global grain production and trade. The fierce military conflict between Russia and Ukraine, the two major grain exporting countries, has once again brought a serious adverse impact on the supply and price of the global grain market, resulting in an increase in the import cost of corn in China and a change in the import pattern of corn in China. In this regard, this study analyzes the current situation of corn production and import trade in China, and based on the relevant trade data between China and major corn importing countries from 2013 to 2022, establishes a trade gravity model to quantitatively evaluate the main factors affecting China’s corn import trade, and analyzes the trade potential of sample countries. It was found that in 2022, China’s import and export trade volume and trade value were 20.62 million tons and 7.11 billion US dollars, respectively, compared with 2013, trade volume and trade volume increased by 6.3 times. Statistics on the potential types of various trading countries showed that the proportion of potential countries was 14.2%, and Brazil had the greatest potential in China’s corn import trade. The proportion of potential expanding countries is about 71.4%, and Laos is a mature country with less opportunities for further development. In order to promote the benign development of the domestic corn industry and the development of China’s corn import trade, this paper puts forward a series of countermeasure suggestions based on the above research.

The trade effect of regional trade agreements in the presence of duty drawbacks

AbstractBefore regional trade agreements (RTAs) come into force, some firms enjoy duty‐free imports using other tariff regimes such as a duty drawback (DD) regime. For such firms, the use of RTA tariff regimes will not provide additional benefits in terms of duty exemption. In this study, we examine the trade effects of RTAs in the presence of a DD regime. We theoretically demonstrate that firms that switch from a DD to an RTA regime will either increase or decrease their imports. Subsequently, we empirically analyse the effect of this switching on imports using firm‐level trade data from Thailand. The empirical results show that switching firms either increase or do not change their imports. Our data also suggest that this increase in imported inputs is used to produce goods for the domestic market, not the export market. We also reveal that relatively small‐sized firms tend to switch to the RTA regime, while relatively large‐sized firms continue importing under the DD regime even after the entry of RTAs into force. With these results, we discuss the implication for the magnitude of trade creation effects of RTAs under the presence of DD regimes.

Trade and development implications of the U.S. African growth and opportunity act

ABSTRACT Trade agreements aim to boost exports among member nations. The U.S. African Growth and Opportunity Act (AGOA) targets enhanced trade between the U.S. and selected African countries. Unlike prior studies focusing on individual nations, our research evaluates AGOA’s overall and specific impacts on member-country exports and products. We employ the synthetic control method for estimation, with robustness checks using the difference-in-differences and event-study approaches. Analysing U.S.-AGOA trade data from 1993 to 2015, we find that AGOA member nations experienced an average annual export increase of $818.11 million, a significant 42% growth compared to expected levels without AGOA. The impacts varied across countries and exported product types: agricultural exports grew by 42%, mineral exports by 15%, and textile and apparel exports by 52% annually. Factors such as ICT infrastructure, institutional integrity, labour regulations, and macroeconomic indicators primarily influenced varied export gains among AGOA member countries. The heterogeneity in AGOA’s impact can be attributed to differences in beneficiary countries’ trade and economic characteristics. Our findings suggest that trade agreements like AGOA can yield positive effects, but careful consideration of various factors is necessary to maximize their benefits.

Fish contributions toward nutritional security in Kenya

Human nutrient deficiencies remain prevalent globally and are particularly common in low- and middle-income countries, such as Kenya. Fish holds potential to help address these deficiencies but remains barely incorporated in nutrition policies and strategies, partly due to a lack of supporting evidence. We address this gap by analyzing sixteen years of fisheries production and trade data from marine, freshwater, and aquaculture systems to evaluate fish nutrient supply, assess changes in supply, and determine the contributions the current supply could make to meet the nutritional needs of children under five years in Kenya. Despite an 11% increase, through time, in the total supply of fish, there was a 24% decline in per capita fish consumption due to fishery changes and increased fish demand. Furthermore, a 21% decline in supply of fish from inland freshwater systems resulted in a 25–40% decline in nutrient supply. Based on the current supply of fish, Kenya’s per capita consumption of 2.5 kg/yr is below WHO recommendations of 10.4 kg/yr. However, this supply has the potential to support nearly 13 million Kenyans at this WHO recommendation. If supply was targeted towards vulnerable groups, such as children under five years, it could supply all children in Kenya with one-third of their calcium, selenium, and protein and over 70% of children in Kenya with one-third of their iron, zinc, and omega-3 polyunsaturated fatty acids requirements. Therefore, fish can play an important role in supporting nutritional security in Kenya if strategic interventions involving all relevant sectors are considered, to reduce identified nutrient deficiencies.

Global knowledge and trade flows: Theory and measurement

We present a model of trade, global innovation, and diffusion, inspired by Eaton and Kortum (1999). The specific structure for innovation and diffusion we propose, which leverages general results developed in our previous work (Lind and Ramondo, 2023a), allows us to measure the flow of ideas across countries and over time. By deriving tractable expressions for productivity and expenditure, we can use easily-available international trade data to estimate both innovation and diffusion rates across countries and over time. We find that, although innovation is correlated with economic growth, there are many high income countries that primarily produce using diffused ideas from foreign sources.

Investor sentiment and the holiday effect in the cryptocurrency market: evidence from China

This study employs a fixed-effects model to investigate the holiday effect in the cryptocurrency market, using trading data for the top 100 cryptocurrencies by market capitalization on Coinmarketcap.com from January 1, 2017 to July 1, 2022. The results indicate that returns on cryptocurrencies increase significantly during Chinese holiday periods. Additionally, we use textual analysis to construct an investor sentiment indicator and find that positive investor sentiment boosts cryptocurrency market returns. However, when positive investor sentiment prevails in the cryptocurrency market, the holiday effect weakens, implying that positive investor sentiment attenuates the holiday effect. Robustness tests based on the Bitcoin market generate consistent results. Moreover, this study explores the mechanisms underlying the cryptocurrency holiday effect and examines the impact of epidemic transmission risk and heterogeneity characteristics on this phenomenon. These findings offer novel insights into the impact of Chinese statutory holidays on the cryptocurrency market and illuminate the role of investor sentiment in this market.

Service sectors and trade through a digital medium: a modified gravity approach

ABSTRACT Given the increasing role played by services delivered through online platforms, this study is a first to undertake cross-sectoral examination of the trade performance of nine service sectors exploring only the digitally delivered components of these. The article makes two main contributions. First, in the absence of bilateral trade data, it develops gravity-like indices using a methodology to capture the influence of common variables used in the gravity literature. Sector-level unilateral import data on the WTO, GATS mode 1 of service delivery or cross-border trade, which is largely synonymous with digital trade, is drawn from the relatively new OECD-WTO-TiSMoS database. Next, the constructed gravity-like variables along with an index of the importer’s services trade restrictiveness, the level of internet penetration of the importing economy and their interaction are examined across the said sectors using a panel of 50 countries for the years 2014–2017. The findings of the constructed gravity variables support earlier literature using bilateral service trade data. The outcomes of the interactions reveal that the trade dampening effect of larger service trade restrictions is somewhat mitigated by deeper internet penetration in consumer services like education in contrast to others like insurance & financial services which are usually producer services.

Evolution game simulation study on Asia–Europe grain trade cooperation network

There has unavoidably been a problem for international grain cooperation in the Asia–Europe region as a result of the Russian–Ukrainian conflict. Analysis of the impact of Russian–Ukrainian conflict on the evolution of grain trade cooperation, identifying key influencing factors and formulating corresponding measures are of practical value for safeguarding grain security in the Asia–Europe region. In this paper, a grain trade network is constructed according to grain trade data from the Asian–European grain trade cooperation countries. A grain trade network game (GTNG) model of grain trade cooperation is established in order to investigate the elements that influence trade cooperation. The reciprocal preference is introduced. Through simulation experiments, the effects of cooperation costs, neighboring countries’ incentives, and punitive pressures, the degree of goodwill perception, the types of game, and the proportion of initial cooperators on trade cooperation are examined. This study may give useful policy recommendations for promoting Asia–Europe grain trade cooperation under the influence of the Russian–Ukrainian conflict.

Vehicular network anomaly detection based on 2-step deep learning framework

Intelligent Transportation System (ITS) is one of the newest technologies in the transportation sector that will give hope for better driving safety. Not only in terms of driving safety, but ITS will give also hope for driving comfort. Smart vehicles perchance better versatile to the street circumstances through trade data among vehicles. In case, they can maintain a strategic distance from activity blockage, perilous deterrents, or see activity mishaps prior. The innovation which is meticulously associated with the security of the driver must get extraordinary consideration. V2V-Vehicle-to-Vehicle connection can undermine impedance and indeed attack or anomaly. Many studies have been carried out to address this problem. The primary step is to reinforce the system's capacity to identify anomalies on Vehicular Network. Further, the growing development of machine learning seems to bring hope to support these steps. Within the proposed method, the original of our approach consists in utilizing 2-Step of anomaly detection. This framework is utilizing two classifiers machine learning from two altered preparing data-sets. We appear that the proposed method can make strides essentially attack detection achievement, compared to arrangements depending on a single detection step.

Impact of RMB internationalization on China's competitiveness in financial services trade based on the VAR model: Evidence from China-US.

An increase in a currency internationalization levels can positively impact its credibility in international economic activities, and expand the effective demand and optimize the supply structure for the country's financial service trade. In this way, a state can improve its financial service trade competitiveness in the international market. This study builds a vector autoregressive model based on time-series data of China-US financial services trade from 2010 to 2021, analyzes the impact of different quantitative indicators of RMB internationalization on this trade from the impulse response results, and validates the conclusions using various inspection methods. The results show that the increase in RMB internationalization helps to narrow the China-US financial services trade balance, but with a significant lag. And this effect is heterogeneous in different dimensions, demonstrated by the fact that the development of overseas RMB securities business is more important for the level of RMB internationalization to narrow the China-US financial services trade balance. Finally, among the specific measures to improve its financial services trade, China should focus on developing the international competitiveness of the traditional RMB deposit and loan financial sector, while the competition in the overseas market for high value-added financial businesses must also not be neglected. Furthermore, China needs to implement more targeted RMB internationalization development policies at different levels in the future to provide high-quality financial services to the rest of the world and aid in the economic recovery of the world in the "post-pandemic" era.

Pengaruh Perdagangan Internasional Ekspor Dan Impor Terhadap Pertumbuhan Ekonomi Di Negara ASEAN

This research aims to analyze the influence of international trade, exports and imports on economic growth in ASEAN countries. This research was conducted using international trade and economic growth data from ASEAN countries in the 2013-2022 period. The method used in this research is regression analysis to measure the relationship between export, import and economic growth variables. The data used is secondary data obtained from trusted sources such as reports from the Central Statistics Agency and Word Bank. The research results show that international export trade has a significant positive influence on economic growth in ASEAN countries. This shows that increasing exports can contribute to increasing economic growth in ASEAN countries. On the other hand, international import trade also has a significant positive influence on economic growth in ASEAN countries

The Use of Forestry and Agricultural Biomass in the Production of Pellets

Abstract The use of forestry and agricultural biomass for pellet production represents a significant opportunity to strengthen a sustainable economy characterized by reducing dependence on fossil fuels and more efficient protection of the environment. The aim of this paper is to improve the understanding of the current state of research on the use of forestry and agricultural biomass for pellets production, fostering awareness of their potential for energy production. In the development of the work, various research stages and techniques were used. These included the analysis of international trade data wood pellets, literature review of research dynamics on agricultural biomass pellet production from last decade, identification of articles from prestigious journals to highlight key trends and concerns in research, analysis of research concentration areas, and investigation and analysis of collaboration networks among researchers and institutions. These methodological approaches have contributed to the creation of a comprehensive and updated work, providing a deeper and clearer understanding of the researched topic. The European Union represents a major force in the global consumption of wood pellets, with demand for this product steadily increasing. Additionally, Romania has significant exports of wood pellets to other European countries, indicating considerable potential for the development of the pellet industry in the country. Furthermore, the literature emphasizes the importance of non-wood biomass, such as agricultural residues, as a crucial source for pellet production. The literature review reveals an increasing focus on biomass pellets in recent years, with research concentrating on various domains such as biotechnology, energy fuels, and sustainable green technology.

The distributional effects of oil supply news shocks

This paper uses high frequency data on the distribution of US income to investigate the heterogeneous effects of oil supply news shocks. Using a FAVAR with an external instrument, We show that these shocks have large negative effects on the left and right tail of the distribution. For low income individuals, the effect is driven by a decline in wages and proprietor’s income, while a fall in corporate profits and interest income drives the effect for affluent individuals.

Logistics Performance Index of Africa: An Indicator for Türkiye and Africa Trade Relations?

The logistics performance of countries is important in trade flows. As part of the supply chain process, logistics is the backbone of trade processes. In this direction, the Logistics Performance Index (LPI) put forward by the World Bank can be considered as an indicator. With the LPI, countries have the opportunity to evaluate the effectiveness of their activities in trade and logistics. The aim of the study is to rank and analyze African countries with the integrated Entropy-MOORA Reference Approach using the LPI values for 2023. In order to increase the depth of the study, an evaluation is made based on the trade data between Türkiye and African countries for 2022. The study aims to rank African countries on the basis of six criteria defined by the MOORA Reference Approach and to provide a perspective on the development of Türkiye’s trade relations with African countries in line with trade figures. According to the results of the study, South Africa ranks first, Botswana second, and Libya last in the ranking of LPI countries. Türkiye’s trade volume with the continent, South Africa ranks fifth, Botswana fifty-third, and Libya third. Therefore, there is no correlation between LPI and trade data in current situation.

Improving algorithmic trading consistency via human alignment and imitation learning

Research on algorithmic trading using reinforcement learning has become increasingly popular in recent years. Although most of the current reinforcement learning methods are employed to train the agent for some kind of modeling or data problem, it is worthwhile to explore in aligning agents with human behavior in applications as crucial as financial trading. Achieving such consistency by incorporating human expert experience into agent behavior is a key for potential improvements in this field. Imitation learning learns directly from examples of humans or other agents performing tasks. However, using imitation learning alone suffers from the problem of transitionally fitting expert example data. By combining the advantages of imitation learning and the Advantage Actor–Critic method, the Human Alignment Advantage Actor–Critic (HA3C) algorithm is proposed, to enhance single-asset trading strategy. First, by adding daily and weekly frequency trading data as input features to TimesNet, which is specifically designed to extract correlated temporal patterns from time-series data, it can capture both short-term and long-term features, thus capturing time-series features more comprehensively. Second, an expert action labeling method is proposed to train a strategy prediction network through supervised learning of behavior imitation. Third, a pre-trained strategy network is transferred to balance the exploration and exploitation of the agent’s behavior. Imitation learning techniques leverage finance-specific knowledge to enhance algorithmic trading consistency. This approach enables algorithms to mimic and adapt human decision-making patterns in finance, ultimately improving overall performance. This paper introduces a novel return-based function that efficiently balances short-term and long-term returns over flexible time horizons. It considers the maximum return from different positions and uses flexible time windows to capture trends while maximizing returns. Finally, evaluation on six commonly used datasets, such as DJI and SP500, demonstrates the advantages of the proposed HA3C algorithm compared with other classical and reinforcement learning-based strategies. Notably, on the HSI dataset, the HA3C strategy significantly outperforms other methods, achieving an impressive cumulative return of 681.55% and a Sharpe ratio of 5.07. These results show the superior performance of the HA3C algorithm in enhancing stock trading strategies and its potential to impact algorithmic trading consistency through aligning agent behavior with human expertise.