Commodity Trade Data Research Articles

How does digital payment affect international trade? Research based on the social network analysis method

<abstract> <p>Digital payment is one of the latest trendsin modern payment systems; its development has a profound impact on international trade relations and the international trade status of countries. We constructed an international trade network by using global commodity trade data to measure countries' international trade status. Based on this, we used panel data from 25 countries for the period between 2012 and 2020 and employed a fixed-effect model to test the relationship between digital payment and international trade status. Empirical results show that, first, the development of digital payment can effectively enhance a country's international trade status. Second, digital payment strengthens international trade connections by lowering barriers to cross-border capital flows, thereby improving a country's international trade status. Third, the effect of digital payment on enhancing international trade status varies across countries with different degrees of trade openness. The findings of this study provide theoretical support for the development of digital payment and international trade.</p> </abstract>

Application of multi-region input-output analysis to examine biosecurity risks associated with the global shipping network

The vast majority of globally traded cargo is transported via maritime shipping. Whilst in port for loading and unloading, these ships can pick up local marine organisms with internal ballast water or as external biofouling assemblages and subsequently move these to destination far beyond their natural ranges. Over the past decades, this mechanism has led to the establishment of hundreds of non-indigenous species (NIS) around global coastlines. Marine NIS cause significant environmental, economic, cultural and human health impacts. Taking effective steps to preventing their dispersal and establishment is an enduring challenge for governments and conservation agencies around the world. Here we use international commodity trade data and a Nobel-Prize-winning economic analysis technique to develop a novel approach for assessing global marine NIS transfer risks. We show that by tracing the origins and destinations of seaborne trade connections, and the nature of the traded commodities, we can predict the strength of shipping vectors and associated marine biosecurity risks. We demonstrate the utility of our approach via a case-study, where we trace the spread of a hypothetical marine NIS from Japan and show the congruence of our model results with documented invasion histories from that region. Our study demonstrates that biosecurity risk can be assessed using established economic modelling frameworks on the basis of monetary transaction data alone, and without the need for detailed itineraries of the many thousand vessels making up the global commercial fleet. Novel, cost-effective tools are needed to mitigate biosecurity risks associated with maritime trade, and to meet conservation goals while enabling economic prosperity. The modelling framework presented here can be expanded to incorporate future risk factors, life-history traits of particular NIS of concern, and even adapted to simulate the dispersal of terrestrial pests or disease agents.

The Korea‐Vietnam trade and the bilateral exchange rate: Asymmetric evidence from commodity trade data

AbstractThe contribution of the current article is to detect the asymmetric impact that exchange rate fluctuations have on Korea's trade with Vietnam. To this end, the nonlinear autoregressive distributed lag (NARDL) process is applied to export and import data disaggregated by 25 commodities. We uncover that the ups and downs of exchange rates have an asymmetric impact on some, though not all, types of Korea's commodities exported to and imported from Vietnam in both the long‐ and short‐run.

IS THERE J-CURVE EFFECT IN THE TRADE BETWEEN PAKISTAN AND UNITED KINGDOM? ASYMMETRIC EVIDENCE FROM INDUSTRY LEVEL DATA

Pakistan is a country which is facing chronic trade deficit since its independence and currency devaluation have always remained an effective strategy to bridge this gap between imports and exports. Previous studies which assessed the influence of changes in exchange rate on Pakistan’s trade balance followed a symmetric or linear approach. However, in this study we adopt an asymmetric approach, according to which appreciations and depreciations have asymmetric effects on the trade balance of Pakistan. Using commodity trade data of 28 (2-digits) industries that trade between Pakistan and United Kingdom, we find pattern of the J-curve in nine industries when a linear model was estimated. However, when we estimated a nonlinear model, the concept of asymmetric J-curve was supported in 14 industries. The largest industry (clothing) which engages in 36.5% of the trade was found to benefit from rupee depreciation.

Analysis on Trade Competitiveness and Trade Complementarity between Uzbekistan and the Member States of Eurasian Economic Union

Based on the 2010-2019 United Nations commodity trade data, this paper has calculated the regional revealed comparative advantage index, export similarity index, trade complementarity index and intra-industry trade index of trade between Uzbekistan and the member states of the Eurasian Economic Union. This paper analyses the competitiveness and complementarity of trade between Uzbekistan and the member states of the Eurasian Economic Union. Uzbekistan and the Eurasian Economic Union member countries have a high degree of similarity in the export of commodities. There is a certain degree of competitiveness in commodities exported to the same market. However, there are differences in the structure of commodity trade among member states. Uzbekistan’s trade complementarity with the member states of the Eurasian Economic Union is distributed in food and live animals (SITC0), mineral fuels, lubricants and related materials (SITC3), manufactured goods classified chiefly by material (SITC6), commodities and transactions not classified elsewhere in the SITC (SITC9). Uzbekistan has strong trade complementarity with Armenia, Belarus and Kyrgyzstan, but weak trade complementarity with Russia and Kazakhstan.

MAPPING THE INTRA-INDUSTRY TRADE IN SOUTH ASIAN COUNTRIES THROUGH GRUBEL-LLOYD APPROACH: A SPECIAL FOCUS ON THE VEGETABLE TRADE

Global nations are striving for sustainable growth and enhancing the welfare of the society. In the course of development, it is observed that the international trade plays a protuberant role in achieving the above mentioned goals. The intra-industry trade is the stylized fact of the modern trade, which constitutes a considerable portion in the total volume of trade. Against this theoretical background, the present study investigates the level of intra-industry trade with respect to vegetable trade in South Asian countries such as Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan and Sri Lanka. In order to execute the task, secondary data on total volume of export and import of vegetables have been collected from the Direction of Trade Statistics, published by International Monetary Fund and Commodity Trade Data, published by WITS. The study covers the period from 1988 to 2018, which is the recent data available in the above mentioned sources. The analysis of the study involves two folds: at first the specialization of trade has been computed using Helpman and Krugman's (1985) general equilibrium model and the intra-industry trade has been estimated using Grubel-Lloyd Index (1975). The result of the study revealed that both Maldives and Sri Lanka are the net importers of the vegetables as the trade specialization index is negative. At the same time, the average intra-industry trade has been decreasing over the study period in South Asian countries.

Do oil price changes really matter to the trade balance? Evidence from Korea‐ASEAN commodity trade data

AbstractThe contribution of this article is to assess the effect of oil prices have on the trade balance in the framework of bilateral commodity trade data between Korea and each of the four ASEAN member countries—Indonesia, Malaysia, Singapore, and Thailand. To examine this subject thoroughly, we first assume the effects of oil price changes to be symmetric and apply the linear autoregressive distributed lag (ARDL) method to the subject. We find that the price of crude oil indeed has an important role in affecting Korea's trade balance with those four ASEAN economies in both the long‐ and short‐run. We then separate oil price hikes from oil price plunges and implement the nonlinear ARDL method to reveal that there is evidence that changes in oil prices appear to have asymmetric effects on the trade balance for certain products in the long‐ and short‐run.

Risk management of commodity trade business based on deep learning and parallel processing of visual multimedia big data

In order to solve the problems of low execution efficiency, big data error in risk analysis and high resource consumption in risk management of commodity trade business, this paper designs a feasible and credible risk management scheme of commodity trade business based on in-depth learning and parallel big data processing, combined with visual multimedia scheme. Based on the in-depth study of commodity trade data model, this paper extracts the features of visualized multimedia data of commodity trade business, which ensures that the extracted features adapt to dynamic and changeable diversified business. Then, this paper designs a commodity trade business management platform, which can provide dynamic migration support for the visualized multimedia data of commodity trade business. Therefore, this paper puts forward a management mechanism that can deal with the risks of commodity trade business. Finally, the simulation experiments prove the rationality and advantages of the proposed algorithm in terms of the accuracy of risk analysis, the efficiency of visual multimedia data processing and the effectiveness of commodity trade business management.

INTRA-INDUSTRY TRADE BETWEEN INDIA AND INDONESIA

This paper analyzes the determinants of India’s Intra-Industry Trade (IIT) with itstrading partner, Indonesia, from 1995 to 2017. We estimate India’s IIT with Indonesiausing bilateral commodity trade data at the two-digit Broad Economic Categoriesclassification code level. Our estimates of IIT demonstrate that India’s trade withIndonesia is indeed intra-industry in nature. However, no remarkable improvementsin the intensity of IIT is found. We also examine the determinants of IIT by estimatinga standard IIT equation using an autoregressive distributed lag model. Our empiricalfindings reveal that trade imbalances, disparity in the demand structure, and thehuman capital endowments among the countries reduce bilateral IIT and that foreigndirect investment and trade openness play an important role in enhancing it. This studytherefore suggests relevant policy interventions to facilitate fair trade by reducingbarriers.

An Introduction to the African Commodity Trade Database, 1730–2010

The African Commodity Trade Database (actd) aims to stimulate and deepen research on African and global economic history. The database provides export and import series at product level for more than two and a half centuries of African trade (1730–2010). This article introduces potential users to some of the major questions that can be explored with African commodity trade data, as well as the sources, structure and limitations of the dataset. The current version of the actd is downloadable from the data repository of the African Economic History Network (www.aehnetwork.org/data-research) and will be regularly updated with new data.

Extending the geopolitical supply risk method: material “substitutability” indicators applied to electric vehicles and dental X-ray equipment

While environmental LCA is relatively well developed, impact assessment methods for the “natural resources” AoP are weak. In particular, resource “criticality” is not addressed in conventional environmental impact assessment methods, though it could be captured within life cycle sustainability assessment. In that regard, the present article extends the previously developed geopolitical supply risk (GPSR) method by demonstrating the connection of criticality to a functional unit while incorporating measures of material substitutability to reflect the “vulnerability” dimension of criticality. The GPSR method developed by Gemechu et al. (J Ind Ecol 20:154–165, 2015a) and subsequently extended by Helbig et al. (J Clean Prod 137:1170–1178, 2016a), and Cimprich et al. (J Clean Prod, 2017) is integrated into an LCIA characterization model. Further, semi-quantitative material substitutability indicator values based on a study by Graedel et al. (PNAS 112:6295–6300, 2015) are incorporated to represent the vulnerability dimension of criticality. The method is demonstrated with an update of a previously published case study of a European-manufactured electric vehicle by Gemechu et al. (Int J Life Cycle Assess 22:31–39, 2015b), along with a new case study of dental X-ray equipment. Due to novel aspects of the GPSR method, the latter case involves constructing an unusually comprehensive bill of materials by tracing unit processes to input commodities with identification codes for collecting commodity trade data. Supply risk “hotspots” are often associated with “minor” commodities such as neodymium in an electric vehicle and cesium iodide in a dental X-ray system. Though difficult to measure, material substitutability can mitigate supply risk. Environmental loads of a dental X-ray system are dominated by production of relatively small specialized functional components like capacitors and printed circuit boards, which are far more environmentally intensive per unit of mass than common structural and mechanical components. Thus, small components comprised of minor materials can “pack a punch” from a supply risk and environmental perspective. The GPSR method presented in the present article brings resource criticality assessment to a product-level while addressing a gap in conventional LCIA methods regarding short-run, socioeconomic availability of natural resources. Further, the case studies illustrate the significance of material substitutability in supply risk assessment. Several complications and limitations of the GPSR method offer directions for future research. Nonetheless, the GPSR method complements environmental LCA to better inform design and management decisions on a product-level.

Mitochondrial DNA and trade data support multiple origins of Helicoverpa armigera (Lepidoptera, Noctuidae) in Brazil

The Old World bollworm Helicoverpa armigera is now established in Brazil but efforts to identify incursion origin(s) and pathway(s) have met with limited success due to the patchiness of available data. Using international agricultural/horticultural commodity trade data and mitochondrial DNA (mtDNA) cytochrome oxidase I (COI) and cytochrome b (Cyt b) gene markers, we inferred the origins and incursion pathways into Brazil. We detected 20 mtDNA haplotypes from six Brazilian states, eight of which were new to our 97 global COI-Cyt b haplotype database. Direct sequence matches indicated five Brazilian haplotypes had Asian, African, and European origins. We identified 45 parsimoniously informative sites and multiple substitutions per site within the concatenated (945 bp) nucleotide dataset, implying that probabilistic phylogenetic analysis methods are needed. High diversity and signatures of uniquely shared haplotypes with diverse localities combined with the trade data suggested multiple incursions and introduction origins in Brazil. Increasing agricultural/horticultural trade activities between the Old and New Worlds represents a significant biosecurity risk factor. Identifying pest origins will enable resistance profiling that reflects countries of origin to be included when developing a resistance management strategy, while identifying incursion pathways will improve biosecurity protocols and risk analysis at biosecurity hotspots including national ports.

The Impact of FTA on Extensive and Intensive Margins: The Case of Japan-Mexico FTA

This study examines the impacts of Japan-Mexico FTA (JMXFTA) on Japanese exports to Mexico. The authors construct a theoretical trade model of heterogeneous firms based on the Melitz-Chaney model, and derive the theoretical relationship of the impacts of tariff changes on extensive and intensive trade margins. Applying this model, the authors estimate the impacts of JMXFTA on product-level extensive and intensive margins of Japan’s exports to Mexico by using the most detailed commodity trade data. The results show that the tariff reduction due to JMXFTA increases the intensive margin while no clear evidence is found regarding the effect on extensive margin. This indicates that in the short-run, the JMXFTA exerted more favorable effect on the existing exporters than on new export market entrants.

Overview of missing physical commodity trade data and its imputation using data augmentation

The physical aspects of commodity trade are becoming increasingly important on a global scale for transportation planning, demand management for transportation facilities and services, energy use, and environmental concerns. Such aspects (for example, weight and volume) of commodities are vital for logistics industry to allow for medium-to-long term planning at the strategic level and identify commodity flow trends. However, incomplete physical commodity trade databases impede proper analysis of trade flow between various countries. The missing physical values could be due to many reasons such as, (1) non-compliance of reporter countries with the prescribed regulations by World Customs Organization (WCO) (2) confidentiality issues, (3) delays in processing of data, or (4) erroneous reporting. The traditional missing data imputation methods, such as the substitution by mean, substitution by linear interpolation/extrapolation using adjacent points, the substitution by regression, and the substitution by stochastic regression, have been proposed in the context of estimating physical aspects of commodity trade data. However, a major demerit of these single imputation methods is their failure to incorporate uncertainty associated with missing data. The use of computationally complex stochastic methods to improve the accuracy of imputed data has recently become possible with the advancement of computer technology. Therefore, this study proposes a sophisticated data augmentation algorithm in order to impute missing physical commodity trade data. The key advantage of the proposed approach lies in the fact that instead of using a point estimate as the imputed value, it simulates a distribution of missing data through multiple imputations to reflect uncertainty and to maintain variability in the data. This approach also provides the flexibility to include fundamental distributional property of the variables, such as physical quantity, monetary value, price elasticity of demand, price variation, and product differentiation, and their correlations to generate reasonable average estimates of statistical inferences. An overview and limitations of most commonly used data imputation approaches is presented, followed by the theoretical basis and imputation procedure of the proposed approach. Lastly, a case study is presented to demonstrate the merits of the proposed approach in comparison to traditional imputation methods.

Effect of Trade Data Aggregation on International Commodity Mode Choice

Different widely accepted principles are used to determine the transport mode in which particular commodity is to be carried at the strategic planning level. One such rule is the commodity value-weight ratio. Discrete choice model is being employed in this paper using available macroscopic commodity trade information. The selection of appropriate data aggregation level for analysis is studied and its corresponding impacts are presented. By examining international commodity flows between countries, the modal split between air and sea transport are compared. After investigating four separate international trade routes and three trade data classification levels, it was found that aggregated trade classification data yields comparable results to detailed trade classification data. With respect to the Harmonized Commodity Description and Coding System, the authors analyses showed that for the purpose of mode choice studies at the planning level, it may be more efficient to develop models using HS two-digit commodity trade data.

An exploratory study on the effect of trade data aggregation on international freight mode choice

As part of a comprehensive regional or global maritime trade modeling framework, it is often necessary to determine the modal share of commodity flow between countries. Typically, this is resolved by either using a constant empirical value (such as the commodity value-weight ratio) or applying statistical models to determine mode choice or share. Whilst the latter method tends to provide a more rational solution, it is constrained by the appropriate choice of trade data classification level during model development. This paper therefore explores the potential impact of trade data aggregation (in terms of trade data classification level) on commodity mode choices derived from discrete choice models. Using international commodity flows between continents, discrete choice models can be developed to compare the modal split between air and sea transport. By considering four different international trade routes and three trade classification levels, the paper shows that detailed commodity trade classification may not necessarily lead to better results. Using the Harmonized Commodity Description and Coding System (or HS System) as an example, it was found that it may be more effective developing models using HS two-digit commodity trade data for the purpose of international freight mode choice studies for the purpose of regional or global maritime trade modeling.

Montenegrin Trade Specialization Index

Montenegro, newly independent since 2006, saw its commodity exports collapse in the worldwide financial crisis of 2008. It took three years for the volume of its exports to recover. Using one to four-digit Standard Industrial Trade Classification (SITC) commodity trade data, this paper analyzes trade patterns as they evolve, both globally, and within individual product sectors, since independence to the year 2012. The Kellman – Shachmurove Trade Specialization Index (TSI) is employed to study the degree of the Montenegrin specialization. The paper warns about high degree of specialization with overreliance on commodity exports of aluminum alloys.

Stochastic Imputation of Missing Physical Commodity Trade Information Using Monetary Trade Data

International trade had conventionally been expressed in monetary values until the recommendations by the UN Statistics Division. Because international trade in monetary terms alone is not entirely representative of global trade from a transportation and logistics perspective, the physical dimension of international trade is attaining increased importance. However, missing physical quantities in the trade flow databases are observed; these quantities are due largely to (a) noncompliance of reporter countries with the standard units of measurement or classification, (b) confidentiality issues, and (c) erroneous collection and reporting of certain data. This paper, therefore, first presents the existing methods used in the literature to treat the issue of missing commodity weight information in international physical commodity trade databases and then proposes a stochastic multivariate imputation model using auxiliary variables such as monetary trade data and the price index to impute missing physical quantities. The relative performance of those methods in resolving the issue of incomplete physical commodity trade data is then evaluated and compared through a case study. It is concluded that the proposed approach outperforms the existing approaches for commodity flow data imputation.

Does the exchange rate matter to bilateral trade between Korea and Japan? Evidence from commodity trade data

This study examines the short- and long-run effects of exchange rate changes on trade flows in the context of disaggregating industry data of bilateral trade between Korea and Japan. For this purpose, an autoregressive distributed lag (ARDL) approach is used. Results show that Korea's exports and imports are relatively sensitive to the bilateral exchange rate in the short-run, but less responsive in the long-run. It is also found that income in the two countries has significant impacts on the bilateral trade flows in both the short- and long-run. Finally, exchange rate uncertainty and Japanese FDI to Korea are found to have little impacts on Korea's trade with Japan in the short- and long-run.

Commodity prices and the world distribution of income

Some advocates of a new international economic order recommend raising prices of commodities exported by developing countries as a means of reducing the inequality of world income distribution. A simulation model using commodity trade data and income distribution data for 68 industrial and developing countries examines this policy alternative. Initial data compilation reveals that internal inequality is as important as international: The world income share of the poorest 40% of people would be twice as high in the absence of intracountry inequality. Calculations using actual price experience in the “great inflation” of 1972–1975 show that despite the large relative price changes for some commodities (especially oil), these changes left the world size distribution of income virtually unchanged. Separate policy simulations show that even a quadrupling of the price of ali “equalizing” commodities (those mainly exported by LDCs) would leave the size distribution of world income practically unaltered (even under optimistic assumptions about intracountry distributional incidence), although some individual LDCs would gain. Increasing commodity prices therefore appears to be an ineffective means of increasing international equity, quite apart from questions about the feasibility of cartels or commodity agreements.