Trade Model Research Articles

Trade and the environment, trade policies and environmental policies—How do they interact?

AbstractWhile international trade can offer gains from specialization and access to a wider range of products, it is also closely interlinked with global environmental problems, above all, anthropogenic climate change. This survey provides a structured overview of the economic literature on the interaction between environmental outcomes, trade, environmental policy and trade policy. In this endeavor, it covers approaches reaching from descriptive data analysis based on input‐output tables, over quantitative trade models and econometric studies to game‐theoretic analyses. Addressed issues are in particular the emission content of trade and emissions along value chains, the relocation of dirty firms and environmental impacts abroad, impacts of specific trade policies (such as trade agreements or tariffs) or environmental policies (such as border carbon adjustment), transportation emissions, as well as the role of firms. Across the different topics covered, the paper also tries to identify avenues for future research, with a particular focus on extending quantitative trade and environment models.

Game-Theory-Based Design and Analysis of a Peer-to-Peer Energy Exchange System between Multi-Solar-Hydrogen-Battery Storage Electric Vehicle Charging Stations

As subsidies for renewable energy are progressively reduced worldwide, electric vehicle charging stations (EVCSs) powered by renewable energy must adopt market-driven approaches to stay competitive. The unpredictable nature of renewable energy production poses major challenges for strategic planning. To tackle the uncertainties stemming from forecast inaccuracies of renewable energy, this study introduces a peer-to-peer (P2P) energy trading strategy based on game theory for solar-hydrogen-battery storage electric vehicle charging stations (SHS-EVCSs). Firstly, the incorporation of prediction errors in renewable energy forecasts within four SHS-EVCSs enhances the resilience and efficiency of energy management. Secondly, employing game theory’s optimization principles, this work presents a day-ahead P2P interactive energy trading model specifically designed for mitigating the variability issues associated with renewable energy sources. Thirdly, the model is converted into a mixed integer linear programming (MILP) problem through dual theory, allowing for resolution via CPLEX optimization techniques. Case study results demonstrate that the method not only increases SHS-EVCS revenue by up to 24.6% through P2P transactions but also helps manage operational and maintenance expenses, contributing to the growth of the renewable energy sector.

A Popular Backlash against Globalization?

Is there a popular backlash against globalization? When did it start and in which forms? What do we know about its causes? We address these questions in the context of advanced democracies. We see the ‘globalization backlash’ as the political shift of voters and parties in a protectionist and isolationist direction, with substantive implications on governments’ leaning and enacted policies. We discuss the empirical evidence on the backlash. We develop a theoretical discussion within the framework of the crisis of embedded liberalism. We nest within this framework theoretical results from international economics showing how the backlash may arise within standard trade models when considering the ‘social footprint’ of globalization. These theoretical insights are consistent with available empirical evidence pointing to the role of globalization as a driver of the backlash. Yet, globalization is only one of the drivers of the backlash. There are other economic factors playing a similar role, such as technological change, fiscal austerity, and immigration. Moreover, cultural concerns such as status threat, authoritarianism, and nativism do play a relevant role, with a significant interplay with economic drivers. This calls for a broad and comprehensive approach to the backlash, both from an academic and from a policy making perspective.

P2P electricity trading model for urban multi-virtual power plants based on double-layer energy blockchain

The urban virtual power plant (VPP) enhances the overall performance of the urban power system by aggregating diverse distributed energy resources (DERs) to provide energy services. With the advancement of smart grid technology, peer-to-peer (P2P) electricity trading has emerged a new paradigm of electricity trading within urban VPPs. In this study, we propose a P2P electricity trading model for multi-VPPs in urban areas, based on a double-layer energy blockchain framework. Initially, users submit their electricity trading information for matching at the user layer; any remaining unfulfilled electricity demand is then further matched at the VPP layer. The user participation process in trading encompasses several stages: trading start, matching, validation, execution, and settlement. Additionally, this study introduces a double-layer blockchain structure consisting of one main chain and multiple side chains. The main chain records real-time trading information from the VPP layer while the side chains are dedicated to recording real-time trading information from the user layer. The feasibility of the proposed model is demonstrated through its implementation in Hyperledger Fabric. Experimental results indicate that the proposed model effectively reduces urban users' reliance on the main grid and decreases their electricity expenses.

Tariff wars, unemployment, and top incomes

Motivated by the 2018–19 global tariff war, we develop a multi-country trade model with occupational choice, heterogeneous firms, and unemployment. The model features a complete tariff pass-through and positive optimal tariffs addressing product and labor-market distortions. The quantitative analysis of the model with four countries/regions shows that raising tariffs unilaterally by a country increases welfare but also raises unemployment and top incomes in that country, whereas having the opposite impact on tariff-targeted countries. A global tariff war reduces every country’s welfare, unemployment, and top-income inequality, whereas moving from a worldwide tariff war to free trade raises every country’s welfare, unemployment, and top-income inequality.

Low-carbon economic dispatch of integrated energy system with CCS-P2G-CHP

Integrated energy system (IES) is an important way and main starting point to achieve the goal of double carbon. In view of this, this paper constructs a low-carbon economic dispatch model for IES, including the carbon capture and storage (CCS), the two-stage power-to-gas (P2G) and the combined heat and power (CHP) unit. Firstly, at the technical level, the mathematical models of CCS, two-stage P2G and CHP are constructed for the CCS-P2G-CHP coupling system. Secondly, at the market mechanism level, the ladder carbon trading model is employed to constraint carbon emissions of IES. Finally, an optimal scheduling strategy with the objective of minimizing the total operation cost of IES is proposed, which is solved by the IPOPT solver in MATLAB. The effectiveness of the proposed model is verified by setting up multiple scenarios for example analysis, and the influence of the sensitivity of each step carbon trading parameter of the low carbon and economy of IES is analyzed.

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.

A blockchain-based privacy protecting framework with multi-channel access control model for asset trading

A blockchain-based privacy protecting framework with multi-channel access control model for asset trading

Metal Trade and Contraband: Archaeological Discoveries and Insights from the Nanhai No.1 Merchant Shipwreck

The archaeological evidence from the Nanhai No.1 shipwreck provides tangible evidence for the study of maritime trade during the Song Dynasty, revealing the presence of a significant amount of smuggled metal in the cargo, suggesting possible involvement in smuggling activities. Merchants may have used tactics such as under-reporting and clandestine transportation of prohibited items to evade supervision, thus engaging in the illicit trade of metal materials and artifacts banned by the Song government on the international market. Valuations of the goods recovered from Nanhai No.1 indicate that the value of iron and silver exceeds that of porcelain, while the value of gold objects and currency exceeds that of porcelain by one-third. Research also suggests a possible shift in the model of maritime trade during the Song Dynasty, from government-led to merchant-led, with a gradual weakening of government supervision and control over trade. This change may be related to reforms in trade organization and the government leniency toward prohibited activities. Despite repeated government bans, smuggling of metal goods continued throughout the Song Dynasty, with no significant reduction in the scale of the metal trade due to the profit-seeking behavior of private merchants, highlighting the inadequacy of government control over illegal smuggling activities. This complex interplay between economic gain, national security, private interests and government control had profound implications for China, the broader South China Sea region and beyond, while the outflow of metal artifacts also facilitated the exchange of goods, technology and culture between China and the aforementioned regions.

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.

Global Firms in Large Devaluations

Abstract I investigate the consequences of firms’ joint import and export decisions in the context of large devaluations. I provide empirical evidence that large devaluations are characterized by an increase in the aggregate share of imported inputs in total input spending and by reallocation of resources toward import-intensive firms, contrary to what standard quantitative trade models predict. These facts are explained by the expansion of exporters, which are intense importers. I develop a model where firms globally decide their import and export strategies and discipline it to match salient features of the Mexican micro data. After a devaluation, the model reproduces the pattern of low aggregate substitution and firm reallocation observed in the data. Compared with a benchmark without global firms, the model predicts higher growth of total exports and imports and a smaller reduction in the trade deficit.

Master slave game-based optimization of an off-grid combined cooling and power system coupled with solar thermal and photovoltaics considering carbon cost allocation

Analogously to power trading models used by electricity companies, the implementation of an energy retailer can address the trading challenges experienced by end-users with decentralized energy consumption patterns. This research develops an off-grid solar-gas energy system to fulfill the cooling and power needs of buildings. Upon creating thermodynamic models, an innovative energy trading mechanism is introduced through an energy retailer, followed by the application of a master-slave optimization method aimed at maximizing participants' profits while incorporating carbon trading and demand response strategies. Through a case study and comparison of four different scenarios, the findings demonstrate that integrating solar thermal and electrical systems leads to the highest profitability, with the energy system's revenues remaining below 10%. The study determines the maximum selling prices for cooling and electricity as 0.231 $/kWh and 0.232 $/kWh, respectively, and highlights that varying carbon allocation rates have minimal effects on user profits. This work sheds light on the sustainable progression of distributed energy systems and presents motivating implications for a diverse audience interested in such advancements.

Trains, trade, and transformation: A spatial Rogowski theory of America's 19th‐century protectionism

AbstractWe study the effect of expanding trade on societal coalitions through its impact on development. We combine a majoritarian political model with a spatial model of trade to argue that trade‐induced economic change—by bringing new workers to locations closer to world markets—can lead to losses rather than gains in political power for the factors of production advantaged by increased trade. We study how this phenomenon explains rising protectionism in the United States from 1880 to 1900. Using county‐level changes in transportation costs induced by railroad expansion, our estimates indicate that falling costs increased population and farm values but reduced the proportion of farmers. Reduced transportation costs caused a reduction in vote shares for the Democratic Party, which favored liberal trade policies, and an increase in an original newspaper‐based measure of protectionist sentiment. Expanding trade alters not only political interests but also the geographic distribution of those interests.

North–South trade, technology diffusion, and uneven development

ABSTRACT A recent consensus in the trade and endogenous growth literature establishes that North–South trade could only be detrimental to the South if there is no international technology diffusion. In this paper, I challenge this consensus. To do so, I develop a North–South two-sector trade model, with innovation and technology diffusion (or imitation). The crucial elements of the model are that diffusion is cheaper than innovation, but costly nonetheless, and that it occurs in the modern sector. By opening to trade, the South ends up specializing more in traditional sector production, losing the productivity gains associated with technology diffusion through modern sector production. The model thus confirms that technology diffusion is a force of convergence but shows that trade makes the South experience lower levels of technological progress and income relative to the North, so-called uneven development. After presenting the model, I broadly discuss the consistency of its policy implications in light of historical evidence and discuss the empirical plausibility of its crucial assumptions.

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.

A novel trading optimization strategy of source-load bilateral thermoelectric spot based on industrial parks interior

With the continuous reform of the electricity market in the whole world, internal trading models in parks are generally studied in terms of load peaking, load flexibility and energy management. In this paper, the regional differential trading method is adopted for industrial users with different energy needs, and the interests of all parties within the industrial park are considered. Spot transactions involving surplus energy on both the supply side and the demand side are considered, and the weight allocation of transactions in each park is coordinated. Firstly, the way of circulating waste heat and power within the industrial park is analyzed from the composition of the trading system of the industrial park. The demand side is transported heat and electricity while the energy storage device is considered. The contact line is modeled on the basis of the energy transmission line characteristics. Secondly, the industrial park is disaggregated regionally using cascade analysis within the target area to decide load regulation mode between systems and modules. Thirdly, regional differences in trading are adopted for industrial users with different energy needs while the interests of all parties within the park are considered. Both sides of the supply side and the demand side participate in spot trading of surplus energy. The allocation of weights is coordinated for trading in the various industrial parks. Finally, The DICOPT solver optimizes operating costs and takes into account energy abandonment penalties. In the waste heat power transaction in the industrial park, the remaining power can be saved by 9.78 %, and the waste heat can be saved by 4.35 %. Numerical results from instances indicate that this method surpasses traditional trading approaches, aligning with the rigorous standards of scientific research.

A peer-to-peer energy trading model for community microgrids with energy management

A peer-to-peer energy trading model for community microgrids with energy management

The impact of trade reforms on industry wage premia in Pakistan: A sectoral perspective

Pakistan witnessed significant trade liberalization reforms between 1988 and 2005. This study investigates the impact of Pakistan's significant trade liberalization policies in 1988 on industry wage premia. We use an estimation strategy that takes into account dispersion in sector wage premiums and trade reforms over time and across sectors. We employed the wage premium approach and Restricted Least Squares to obtain sectoral wage premia. We used weighted least squares and two-stage-least-squares (2SLS) to explore the liaison between trade reforms and sector wage premia. Contrary to previous empirical studies on less developed economies, our findings reveal a significant and resilient correlation between changes in trade reforms and fluctuations in sector wage premiums during the liberalisation period of 1990-2005. Our findings are consistent with short- and medium-run trade models in which workers are immobile across industries or, on the other hand, with the presence of sector rents that are reduced when trade policy is liberalized.

Intelligent manufacturing and cross-border e-commerce export diversification

Although Industry 4.0 has transformed the operating model of manufacturing and international trade, no previous research has explored the influence of intelligent manufacturing (IM) on export diversification from a cross-border e-commerce (CBEC) perspective. We use a unique dataset of China's leading cross-border logistics enterprises to investigate the effect of IM on CBEC export diversification. Our results reveal a positive effect of IM on CBEC export diversification at both market and product levels. This conclusion remains valid after a series of robustness tests. The heterogeneity analysis shows that IM contributes more strongly to diversification of CBEC exports for differentiated products and consumer goods. The mechanistic analysis suggests that IM enables export diversification by stimulating input, output and commercialization of innovation.

Benchmarking and contribution analysis of carbon emission reduction for renewable power systems considering multi-factor coupling

The renewable power system serves as a vital path towards achieving carbon peaking and neutrality goals. Accurately quantifying the carbon reduction emissions of renewable power systems and evaluating the contribution of various influencing factors to carbon reduction is quite important, which is related to the formulation of energy policies and regional power planning by the power grid or relevant departments. However, in the current research, there are few studies related to the quantification of carbon emission reduction, and in terms of optimal scheduling, the existing studies often only consider a single factor, ignoring the coupling effect between multiple factors, which makes the contribution of each optimization strategy to carbon emission reduction unclear. Therefore, based on the current power system scheduling mechanism and dual-carbon background, this paper optimizes the carbon emission reduction benchmark factor and its corresponding weight, proposes a new carbon emission reduction benchmark of renewable power system, and verifies the accuracy of this benchmark based on the classical scheduling model. On this basis, the mathematical models of thermal power deep peak shaving (DPS), electricity export (ELE) and green certificate trading (GCT) are established. Each factor is introduced into the classical scheduling model to simulate and verify the promoting effect of each influencing factor on carbon emission reduction. Finally, the above different influencing factors were constructed in different coupling scenarios to calculate the carbon emission reduction under each scenario, and the contribution degree of each influencing factor to carbon emission reduction was analyzed sharply according to the value of cooperation game instead of the traditional calculation method. The results show that the proposed benchmark can reduce the error by 2.6%–15.5 %. In the carbon emission reduction contribution simulation, the three factors have coupling effects, and deep peak shaving and electricity export are more sensitive to carbon emission reduction contribution. This study provides valuable insights for the development of carbon reduction strategies for renewable power systems.