Trade Costs Research Articles

Fertilizer prices and deforestation in Africa

This study explores the impact of fertilizer (urea) prices on local deforestation by exploiting the exogenous variation in the world price of urea inclusive of trade costs from the world market to the local market. The empirical analysis relies on a unique geo-coded dataset on the market price of urea across 158 subnational hub markets in 21 African countries and satellite-derived forest loss estimates over the period 2003 – 2012. The results suggest that fertilizer prices positively affect deforestation rate and forest cover loss. On average, a 1 % increase in local urea prices corresponds to 97.65 Ha of forest loss within a particular local market catchment. Specifically, the results reveal a price elasticity of approximatively 1 between urea prices and forest loss. The heterogeneity analysis suggests that the effects of urea prices on forest loss tend to be concentrated in markets with subtropical and tropical ecological features. Furthermore, I provide evidence for the land-conversion mechanism, implying that urea prices are positively associated with the expansion of agricultural land. Estimating an event study around exposure to a sustained jump in urea prices reveals a persistent response of deforestation and forest cover loss to fertilizer prices.

A study of the impact of digital trade development in the Eurasian Economic Union on China's foreign trade costs

Subject. The article addresses the development of digital trade between the Eurasian Economic Union and China. Objectives. The aim is to investigate the impact of digital trade development in the Eurasian Economic Union on China's foreign trade costs. Methods. The study draws on general scientific research methods. Results. We built a system of indices for evaluation of the development of digital trade in four dimensions, applied TOPSIS relative entropy method (a method of preference of order by similarity to the ideal solution) to measure the level of digital development of the Eurasian Economic Union from 2010 to 2020. The extended gravity model was used to empirically analyze the impact of the level of digital trade development of the Eurasian Economic Union on China's foreign trade costs. Conclusions. Digital trade in the Eurasian Economic Union is developing rapidly, while its overall level remains low, and there are certain differences between member States. At the same time, the level of digital trade development has significantly reduced China's foreign trade costs.

Operation Optimization of Regional Integrated Energy Systems with Hydrogen by Considering Demand Response and Green Certificate–Carbon Emission Trading Mechanisms

Amidst the growing imperative to address carbon emissions, aiming to improve energy utilization efficiency, optimize equipment operation flexibility, and further reduce costs and carbon emissions of regional integrated energy systems (RIESs), this paper proposes a low-carbon economic operation strategy for RIESs. Firstly, on the energy supply side, energy conversion devices are utilized to enhance multi-energy complementary capabilities. Then, an integrated demand response model is established on the demand side to smooth the load curve. Finally, consideration is given to the RIES’s participation in the green certificate–carbon trading market to reduce system carbon emissions. With the objective of minimizing the sum of system operating costs and green certificate–carbon trading costs, an integrated energy system optimization model that considers electricity, gas, heat, and cold coupling is established, and the CPLEX solver toolbox is used for model solving. The results show that the coordinated optimization of supply and demand sides of regional integrated energy systems while considering multi-energy coupling and complementarity effectively reduces carbon emissions while further enhancing the economic efficiency of system operations.

The emerging international trade in hydrogen: Environmental policies, innovation, and trade dynamics

Hydrogen produced from renewable energy and other carbon-neutral sources has the potential of becoming an important medium for storing and transporting energy, partially taking on the role that fossil fuels play to date. We develop a novel theoretical and empirical model of sequential trade based on long-term contracts with one or more fixed-capacity projects entering each period in a modified Nash-Cournot competition. We simulate the emerging international trade in hydrogen using calibrated demand, supply, transportation, and policy data, exploring a set of scenarios to determine which factors have significant influence—in particular environmental, innovation, and trade policies. Our findings suggest that hydrogen trade exhibits significant price dispersion and two-way trade as vintages of contracts overlap in a market defined by endogenous innovation and policy interventions. Trade costs and the mode of transportation (pipelines or ammonia conversion, possibly others) play a pivotal role and influence the relative share of hydrogen production types (green, blue, or turquoise). Trade policies emerge as a more essential determinant of hydrogen trade than carbon and innovation policies.

The roots of carbon emission differences between China and USA: A quantitative study based on global value chains

China and the USA, as preeminent contributors to global carbon emissions, demonstrate discernible differentials in both magnitude and trajectories of their respective carbon outputs. This article employed two methods, Structural Decomposition Analysis (SDA) and Quantitative Structural Modeling, to scrutinize the underpinnings of these disparities through the lens of the global value chain. Drawing upon data from the World Input-Output Database (WIOD), our analysis revealed that the compounded influences of output composition, input intensity, input composition and input origin collectively elevated China's aggregate carbon footprint from 2000 to 2014, while the scale effect made China's carbon emissions lower than of the USA. Notably, China's carbon emissions surpassed those of USA, with the gap accentuating over time. The quantitative results of the structural model showed that the difference in carbon emissions between China and USA predominantly stem from disparities in productivity, production technology, factor intensity, factor endowment and direct carbon intensity. Differences in trade costs exhibited some discernible impact, their influence remains relatively marginal, whereas distinctions in consumption behaviors and trade imbalances minimally contribute to the observed differentials. These findings have important policy implications for global carbon reduction efforts and China's trajectory towards a low-carbon economic paradigm.

Democratizing the Access of Romanian Investors to Trading Financial Instruments through Specialized Platforms

By writing this paper, we aim to follow the evolution of Romanian retail investors’ access to trading financial instruments and cryptocurrencies through online platforms or specialized applications. We will follow the historical evolution of the participation of Romanian retail investors in trading on the capital market, the way in which access to trading is achieved, focusing in particular on the impact brought by the emergence of online platforms and mobile applications on the field. We will analyze the increase in the number of individuals using these specialized trading platforms, the cost of trading, but also the impact that this wave of new investors has generated on the prices of financial instruments and cryptocurrencies traded. We will also follow the reaction of the financial supervisory authorities in relation to the phenomenon, on a wider European and American level. Last but not least, we will also analyze the recent reaction of the Romanian legislator to this new reality as well as the simplification attempts from the point of view of the declaration of taxable income resulting from the trading of financial instruments, indicating the financial advantages and disadvantages generated by the current legislation for the Romanian investor, natural person.

On the productivity advantage of cities

Abstract Agglomeration externalities are the key factor explaining the existence of cities and their size. However, while the various micro foundations of agglomeration externalities stress the importance of total factor productivity (TFP), the empirical evidence on agglomeration externalities rests on measures obtained using firm revenue or value-added as a measure of firm output: revenue-based TFP (TFP-R). This article uses data on French manufacturing firms’ revenue, quantity, and prices to estimate TFP and TFP-R and decompose the latter into various elements. Our analysis suggests that the revenue productivity advantage of denser areas is mainly driven by higher prices charged rather than differences in TFP. At the same time, firms in denser areas are able to sell higher quantities and generate higher revenues, despite higher prices. These and other results we document suggest that firms in denser areas are able to charge higher prices because they sell higher demand/quality products. In this respect, two key elements related to this capacity to sell more at higher prices are the degree of vertical differentiation and trade cost, with products characterized by higher vertical differentiation and/or lower trade costs featuring stronger patterns and driving overall results.

Safe reinforcement learning based optimal low-carbon scheduling strategy for multi-energy system

Multi-energy system with distributed energy resources has become the inevitable trend in recent years due to their potential for creating the efficient and sustainable energy infrastructure, with a strong ability on carbon emission reduction. To accommodate the uncertainties of renewable energy generation and energy demand, model-free deep reinforcement learning methods are emerging for energy management in multi-energy system. However, traditional reinforcement learning methods still have operation safety issue of violating the physical constraints of multi-energy system. To address the challenges, a low-carbon scheduling strategy based on safe soft actor-critic algorithm is proposed in this paper. Firstly, an electricity-thermal-carbon joint scheduling framework is constructed, where carbon trading mechanism is incorporated to further motivate carbon emission reductions. Secondly, the energy cost and carbon trading cost are simultaneously integrated in the objective function, and the dynamic optimization problem of multi-energy system is modeled as a constrained Markov decision process by taking into account the diverse uncertainties. Then, a novel safe soft actor-critic method is proposed to achieve the benefits of economic and carbon emissions, where the security networks and Lagrangian relaxation are introduced to deal with operation constraints. The case study validates that the proposed scheduling strategy can reduce the energy cost and carbon trading cost by up to 26.24% and 33.73% within constraints, compared with existing methods.

Information technology, market congestion, and economic geography

I investigate the impact of economic integration, in terms of trade costs and information technology, on the interregional location patterns of retail firms by introducing three features into a new economic geography model: individuals consume only a restricted number of varieties; firms compete for customer acquisition; and the advancement of information technology enables consumers to easily perceive and buy products sold by firms in distant regions. I consider two possibilities regarding competition for attention: relative competition, in which a firm can attract more consumers by advertising more than the average level, and absolute competition, in which each firm competes with another to enhance the share of its advertisement in the market. I show that consumption variety is richer in the agglomerated region, but spatial consumption inequality shrinks as information technology develops. A reduction in trade costs may cause the redispersion of economic activities under sufficiently low trade costs only in the case of absolute competition. This is more likely when competition for attention is fierce and information technology is not fully developed. The results not only support the complementarity between information technology and cities but also provide a new insight that competition among firms is an important factor governing the impact of information technology on economic geography.

Multi-agent deep reinforcement learning-based multi-time scale energy management of urban rail traction networks with distributed photovoltaic–regenerative braking hybrid energy storage systems

The integration of photovoltaics (PVs), regenerative braking (RB) techniques, and energy storage devices has become crucial to promote energy conservation and emission reduction for a sustainable future of urban rail traction networks (URTNs). This paper proposes a tri-level multi-time scale energy management framework for the economic and low-carbon operation of URTNs with PV–RB hybrid energy storage systems (HESSs) based on multi-agent deep reinforcement learning (MADRL). A two-stage stochastic scheduling approach is developed to minimize daily operation and carbon trading costs at the upper level and correct day-ahead scheduling deviations against multi-source uncertainties at the middle level. A MADRL-based real-time energy management strategy is established to optimize the PV–RB power flow and promote its utilization by coordinating distributed HESSs at the lower level. The HESS control problem is formulated as a decentralized partially observable Markov decision process and solved by a multi-agent control algorithm based on monotonic value function factorization. A Copula-based spatio-temporal dependency model is devised to characterize the PV, passenger flow, and traction load uncertainties and generate daily URTN operation scenarios for enhancing day-ahead and intraday decisions. Comparative studies demonstrate the effectiveness of the proposed framework in terms of a cost reduction by 11.98% and a PV–RB energy utilization improvement by 13.94%.

Low‐carbon demand response program for power systems considering uncertainty based on the data‐driven distributionally robust chance constrained optimization

AbstractThe demand response (DR) program is an effective solution to promote the low‐carbon operation of power systems with increasing penetration of renewable energy sources (RESs). This paper proposes a low‐carbon DR program for power systems to enhance both the environmental friendliness and uncertainty resilience of the system operation. The system operator aims to minimize both the system's operation cost and carbon trading cost. To handle the uncertainty associated with stochastic RES generation power and load consumption power, a data‐driven method named the two‐sided distributionally robust chance‐constrained (TS‐DRCC) approach is adopted to enhance the system's uncertainty resilience. A ladder‐type carbon trading scheme is utilized to calculate the carbon emission cost of the system. Comprehensive analyses of case studies have been conducted to validate that the proposed strategy can effectively reduce the total carbon emissions and total operation costs with good uncertainty resilience performance. The proposed low‐carbon DR program is verified to achieve 63.64% more carbon emission reduction compared with the conventional DR program. Besides this, the proposed low‐carbon DR program can also achieve 4.39% carbon‐intensive generation power reduction and 5.52% RES power consumption compared with the conventional DR program.

Communities beyond geographical limitation: The network characteristics of international wildlife trade under the pandemic

The international wildlife trade, contributing billions of dollars to global economies and encompassing thousands of species, has increased due to rising demands for wildlife products. Revealing the key participants and trade characteristics across taxa is imperative for sustaining wildlife resources and conservation efforts. To provide a basis for informed wildlife management and trade supervision, we investigated the global wildlife trade's fundamental characteristics and spatial patterns by analyzing transaction records reported to The Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) from 2020 to 2022. During this period, the essential demands for wildlife were highlighted due to stricter trade regulations and higher trade costs in response to the suspected wildlife origin of the pandemic. Our analysis highlights the formation of trade communities that are tightly interconnected by strong trade relations in wildlife trade networks, transcending geographical limitations. Unlike the division of the continents, geographical proximity alone does not necessarily contribute to the formation of these trade communities. Germany emerges as the leading importer based on trade frequency, while the Netherlands leads in exports. The main driving forces behind wildlife trades include commercial use (74.98 %), personal use (3.80 %), and hunting trophies (3.19 %). Apart from 44.90 % of flora trades, Reptilia was the primary traded taxa (21.08 %), involving 196 engaged countries/territories with the most mutual connections (27.21 %) and an average of 12.51 shipments to 11.33 nodes. Aves (9.70 %), Mammalia (9.44 %), and Anthozoa (7.62 %) followed. Notably, certain European and Asian countries/territories dominate the import or export of most trades, exhibiting distinct variations across taxa. The United Arab Emirates led the Aves trade, accounting for 15.96 % of global Aves transactions during this period. Similarly, Italy led the Reptilia trades (21.28 %), South Africa led the Mammalia trades (18.72 %), and Indonesia led the trades in Insecta (56.84 %), Hydrozoa (66.96 %), and Anthozoa (56.12 %). Our findings underscore the traded species facing overexploited and the countries most involved, thereby informing proactive monitoring and policy-making for sustainable wildlife conservation and management.

China’s public international investment: A strategic-trade-policy perspective

Initiatives such as the Belt and Road initiative reduce trade costs, increase export firms’ profits and stimulate their activities in R&D contests. The resulting strategic-trade policy equilibria tend to be asymmetric. One country earns leadership in the markets for exports to the rest of the world. Factors that are conducive for a country to gain the role of major innovator and exporter nation are: (1) whether a nation follows a ‘national champions’ policy compared to a rigorous national anti-trust policy, (2) whether a nation has a large pre-existing export sector, (3) whether the government places a high welfare weight on the profits of the firms in its country, and (4) whether the government has low opportunity costs of such investment policies. Piecemeal evidence suggests that, compared to the US, China has the advantages in all these four dimensions.

How will global trade patterns evolve in the long run?

AbstractIn this paper, the evolution of global trade patterns until 2050 is projected with a recursive dynamic computable general equilibrium (CGE) model. Feeding the model with exogenous projections on macroeconomic, demographic, sectoral and trade cost variables, the evolution of trade patterns emerges endogenously from the model. The approach is innovative in both modelling approach and exogenous inputs. GDP growth emerges endogenously in the model because of diffusion of ideas as a result of international trade and trade cost changes are based on estimates of technology and trade policy changes. The projections indicate that (i) because of projected reductions in trade costs, trade will grow more than GDP, generating a global trade‐to‐GDP growth rate of 1.1; (ii) because of structural change, the global share of manufacturing trade falls from 64% in 2020 to 52% by 2050, whereas the share of services trade rises substantially from 24% to 38%; and (iii) because of technological catch‐up, the share in global trade of both developing and least‐developed countries (LDCs) will rise (with developing countries overtaking developed economies around 2035), the share of intra‐developed country trade will fall, whereas the share of intra‐developing country trade and those between developing and developed countries will rise.

Demand Uncertainty, Selection, and Trade

This paper examines the role of uncertainty on elasticities of trade flows with respect to variable trade costs in a canonical model of trade with monopolistic competition and heterogeneous firms. We identify two channels through which uncertainty impacts trade: through export participation thresholds (the selection effect) and the distribution of shocks governing export selection (the dispersion effect). While the selection effect dampens trade elasticities under uncertainty, the dispersion effect is ambiguous. We develop a methodology for using customs firm-level data to quantify trade elasticities under uncertainty, and the magnitude of each of the two channels through which uncertainty impacts trade. We find that uncertainty amplifies trade elasticities, on average, indicating that the dispersion effect of idiosyncratic firm-level shocks dominates -- though the effect is heterogeneous across industries. The overall magnitude of the endogenous selection mechanism on trade elasticities is small, indicating that the main drivers of trade in this class of trade models are overwhelmingly incumbent firms.

Exploiting non-parallel risk premia in the South African sovereign bond market

Background: This study focuses on diversifying fixed income attribution beyond yield and duration by identifying new risk premia applicable to various investment strategies.Aim: To identify cross-sectional bond risk factors in the South African sovereign bond market, capitalising on non-parallel shifts during high-risk macroeconomic events, developing a strategy to extract persistent alpha from higher order interest rate risks and disproving the strong efficient market hypothesis.Setting: This study finds that during high-risk macro events, non-parallel shifts increase in frequency. Empirical evidence suggests that post the 2008 financial crisis, there have been increased occurrences of risk-on/off events and researchers believe high risk macro events will increase in prominence. As such, most active US fixed income managers have reduced duration risk (from parallel shifts) in favour of alternative risk premia.Method: This study exploits slope and curvature risks, by utilising a butterfly strategy. Ten bond risk factors are back-tested and analysed during interest rate cycles, curve scenarios and risk-off periods from 1998 to 2023.Results: The top-ranked strategies displayed strong and persistent outperformance over the bottom-ranked strategies for most of the bond factors especially during risk-on episodes. The Bond All-Factor Rank demonstrated improved diversification by balancing upside and downside risks. Trade costs are an important factor that requires pragmatic management.Conclusion: Geopolitical risks are increasing in frequency and developing a strategy to exploit non-parallel risk premia is an attractive proposition.Contribution: This study identified new bond risk factors beyond the conventional spread factor to extract non-parallel risk premia.

Assessing the Impact of Trade Facilitation on Trade Costs in Cross-border Trading Companies: A Case of MeritChemicals Ltd.

Assessing the Impact of Trade Facilitation on Trade Costs in Cross-border Trading Companies: A Case of MeritChemicals Ltd.

How free is free? Retail trading costs with zero commissions

We examine the economics that underlie retail trading costs around discount brokers’ widespread adoption of zero commission trading in October 2019. Our analysis of participating brokers’ Rule 606 filings and financial statements reveals little change in payment for order flow, which suggests brokers absorbed the cost of eliminating commissions in a competitive environment. We then perform a difference-in-differences analysis of effective spreads and report economically trivial changes in retail execution costs around the commission change. Finally, we assess the total trading costs of an aggregate retail portfolio compared to a host of counterfactuals. We find that following the zero-commission change, total retail transaction costs dropped substantially even under the extreme counterfactual that these traders pay exchange quoted spreads and receive zero price improvement. Our findings support the brokerage industry's claim that dropping commissions helped retail investors and should ease regulators’ concerns to the contrary.

Research on the Impact of the Digital Economy on International Trade Barriers and Its Countermeasures

The rapid development of the digital economy has not only changed traditional business models and trade patterns, promoting trade facilitation, but has also to some extent reduced international trade barriers, providing unprecedented opportunities for enterprises worldwide, especially small and medium-sized enterprises, to expand into international markets. In the era of the digital economy, the modes and patterns of international trade are undergoing profound changes. The high efficiency and universality of information transmission, as one of the core features of the digital economy, not only significantly reduce trade costs but also break the limitations of traditional trade models, laying a solid foundation for the extensive expansion of international trade. However, with the rapid rise of digital trade, new digital barriers are also emerging, which are impacting the international trade landscape. A comprehensive analysis of the role of the digital economy in reducing international trade barriers and the opportunities and challenges it brings is of great significance for understanding and grasping the current trends in global trade development.

How e-commerce can boost China’s high-quality agricultural exports

IntroductionExport quality improvement is a crucial path for a country or region to climb up the advanced division of labor in the global value chain. For developing countries that have long been at the lower end of the global value chain division of labor, the dominance of agricultural trade is often controlled by international retailers, leading to higher costs of agricultural trade and hindering the upgrading of the quality of agricultural exports. As a traditional agricultural exporting country, China still needs a competitive advantage despite the large scale of its agricultural exports. Currently, e-commerce can provide buyers and sellers with comprehensive transaction information and technical support, allowing them to realize rational allocation of resources and export upgrading. Therefore, studying how e-commerce can promote the quality upgrade of agricultural exports is crucial for China to build a trade power.MethodsThis paper clarifies the mechanism of e-commerce’s theoretical impact on the quality of agricultural exports and then empirically tests it using a high-dimensional fixed-effects model with Chinese customs data from 2000 to 2020 as a sample.ResultsThe results show that e-commerce significantly promotes the quality of agricultural exports in all regions of China, and this conclusion still holds after various robustness tests; the heterogeneity test shows that e-commerce fosters the quality of agricultural exports in eastern China, densely populated regions, and economically underdeveloped regions, especially in the case of heterogeneous products; the mechanism analysis confirms that e-commerce promotes the quality of agricultural exports mainly through the optimization of the agricultural industry chain and supply chain, and the enhancement of the level of servicing. Mechanism analysis confirms that e-commerce improves agricultural export quality mainly through optimizing the agricultural industry chain and supply chain, improving the level of servitization, and docking the demand information of the consumer market, etc. Expanded analysis shows that constructing cross-border e-commerce platforms also significantly improves the quality of micro enterprises’ agricultural exports. This paper enriches the research on e-commerce and agricultural trade.DiscussionThis paper provides an essential reference for constructing a robust agricultural trade country and developing high-quality agriculture. Despite encompassing data up to 2020, in the context of today’s global economic volatility directly affecting agricultural trade, future investigations will broaden the scope to delve deeper into how e-commerce can help countries cope with global economic uncertainty.