Input-output Tables Research Articles

Analysis of Ghana—Nigeria Export Trade: Linkages, Impacts and Policy Implications

This study hypothesised that the Ghana-Nigeria export trade has a significant impact on the economy of Ghana. Time series on variables of interest were obtained from the World Development Indicator (WDI) of the World Bank and the Ghana Statistical Service (GSS). The 2018 input-output table for Ghana was obtained from the social accounting matrix of the Organisation for Economic Co-operation and Development (OECD). The data were analysed using descriptive statistics, input-output analysis, and the autoregressive distributed lag (ARDL) bound testing approach. Through input-output analysis, this study found significant total impacts (151.585 to 190.139 million Ghana Cedis) in 2017 and 2018, centred around export commodities such as food and live animals, beverages, and tobacco. The expanding field of influence (214.373 to 268.898) and the ratio of impacts to Ghana's GDP (0.058% to 0.062%, then 0.044%) substantiate their pronounced role in the economy. The ARDL model showed that a percent increase in Ghana-Nigeria exports led to a 0.1017% increase in Ghana’s real GDP on the log-run. The speed of adjustment was 42.18% in each period. By providing support to exporters, both countries can leverage their comparative advantages, strengthen economic ties, and foster sustained growth through increased export trade.

Assessing social risks in Greek and Dutch economies: A product social impact life cycle assessment approach

Abstract Purpose Input–output tables describe monetary relationships between producers and consumers within an economy and have been used to assess the effects on job creation and gross domestic product (GDP). The objective of this study was to apply the social life cycle assessment (S-LCA) to assess direct social risks in national economies and explore whether S-LCA can replace or support beyond-GDP metrics. Methods S-LCA was applied in three ways. First, a hotspot assessment was conducted using the Product Social Impact Life Cycle Assessment (PSILCA) database to assess the direct social risks of monetary outputs of the Dutch and Greek economies in 2018. Classification 1 regarded the comparison of the Dutch and Greek economies based on direct social risks classified as Sustainable Development Goals (SDGs). Classification 2 grouped the calculated social risks into sub-sub-topics of the European Corporate Sustainability Reporting Standards (CSRS) directive. In each classification, the calculated risks were normalized by the total monetary output of the national economy. Results and discussion This study showed that the Dutch economy results in lower normalized risk values for all S-LCA stakeholders and impact subcategories, except for “Respect of indigenous rights” and “Health and safety (Workers).” The main contributing parameters were sectorial monetary output and the risk levels of the indicators. Classification 1 showed that using input–output tables and PSILCA to simplify the calculation of SDGs was partially successful, because the SDGs also consider environmental aspects and PSILCA is limited to social aspects. Classification 2 showed that the Greek economy resulted in higher normalized risk values than the Dutch economy for almost all sub-sub-topics of the CSRS. Conclusions The results indicate that input–output tables can be extended to incorporate social dimensions with S-LCA and PSILCA. However, the nature of the SDGs means that S-LCA is not capable of simplifying the evaluation of countries’ societal progress, but S-LCA combined with PSILCA can assist national governments in taking targeted actions to reach SDG targets and enforce European CSRS directive compliance in the most impactful economic sectors for social performance monitoring and reporting.

The spillover effect of global uncertainty through input–output linkage

AbstractThis study examines the cross‐country spillover effects of global uncertainty on domestic value‐added by introducing indices for input‐ and output‐linked uncertainty. Employing a panel fixed‐effect regression model, the analysis covers 70 countries from 1995 to 2019, using the World Uncertainty Index and the OECD Inter‐Country Input–Output Table. Our findings reveal that input‐linked uncertainty from procuring foreign intermediate goods has the most significant negative impact on domestic value‐added. The effects of domestic uncertainty and output‐linked uncertainty from foreign product sales follow this. Additionally, these negative effects exhibit a dynamic cumulative impact over time, rather than being confined to a specific period. Considering both the magnitude and duration of these impacts, the primary transmission pathway of global uncertainty on a country's domestic production activity is through its input linkage. Furthermore, the study identifies country‐specific variations in the ripple effects of global uncertainty. Analysing specific cases such as Korea and China affirms the empirical relevance of our findings to their economic contexts.

Role of global value chain changes in decoupling CO2 emissions from economic growth in Chinese provinces

Global value chain (GVC) changes have had an impact on economic growth and carbon dioxide (CO2) emissions in various provinces. This study links the Chinese provincial multiregional input–output table to the world input–output table. The provinces are divided into carbon peak and nonpeak groups to explore the impact of GVC changes in relation to driving factors of provincial decoupling. The results are fourfold. (1) For peaking provinces, after reaching the peak, the GVC and domestic effects combined to promote strong decoupling. (2) Most nonpeak provinces are weakly decoupling. The hindering effects on decoupling decreased after the 2008 financial crisis. (3) For peaking provinces, the positive effect of emissions intensity has been sufficient to offset the negative effect from the final demand, but was not sufficient to offset nonpeak provinces. (4) The hindering effect of GVC production-related factors has lowered. This study proposes that nonpeak provinces improve production technology.

An input-output approach to study the impact of carbon taxes in (almost) every country

Some forty carbon tax initiatives have been adopted, and more countries are evaluating the possibility of implementing this instrument every year. However, there is significant heterogeneity in tax rates, type of covered emissions, and regulated sectors, which is explained by the different levels of environmental concern and cost that each country is willing to assume. In this context, the present study simulates various scenarios of carbon taxes in (almost) every country in the world to contribute to the global design of climate change policies. Specifically, input-output tables and sectoral CO2 emissions of each country are used to calibrate the environmental extension of the Leontief price model, obtaining the impacts on prices, production, and emissions at the sectoral, national, or global level. The results show that the same effective tax rate can have very different effects in each country, mainly explained by the composition of the energy matrix. In addition, global CO2 emissions would be reduced by 0.10% ∼ 0.23% for each dollar of CO2 tax applied to all sectors and countries. Finally, a more outstanding commitment from rich countries and larger developing countries is required to contribute more decisively to combating climate change in the short term.

Broadening energy resilience: How does the digital economy affect the global energy value chain?

The frequent occurrence of global economic black swan events has affected the development of the global energy value chain (GEVC) and exposed countries to considerable uncertainty. However, digital economy development can offer new solutions and perspectives for countries to mitigate external shocks, ensure energy security and improve energy resilience. This study examines 71 countries from 2010 to 2019, innovatively obtaining GEVC from input–output tables to explore the impact and mechanism of the digital economy on GEVC in terms of countries’ dimensions of participation and position. The relevant results are threefold. First, the digital economy increases countries’ participation in GEVC and pushes them to move downstream of the GEVC. This result still holds after robustness tests. Second, the mechanism test demonstrates that the digital economy can influence factor allocation and innovation to affect countries’ GEVC participation. Third, the effect of the digital economy on a nation's ability to participate in the GEVC varies depending on the external and internal threats that the nation faces. This study enriches the research on global value chains and has important implications encouraging countries to advance digital economy development, navigate external shocks and accelerate digital economy and GEVC integration.

Evaluating the robustness of the ARIO model for a local disaster: 2021 flooding in Germany

Abstract Given the interconnectedness of modern economies and the widespread adoption of just-in-time production methods, even minor disruptions caused by natural disasters can lead to substantial indirect economic impact. A substantial body of literature has explored this phenomenon, using input-output analysis, computable general equilibrium and agent-based models. However, these models (i) heavily rely on parameters and data that often lack empirical grounding or (ii) exhibit considerable uncertainty, making it challenging to assess their reliability. The ARIO model has been widely used in the literature and has provided theoretical foundation for several related models. Using the July 2021 floods in Germany as a case study, we assess the sensitivity of the results of this model by varying key parameters, as well as the multi-regional input-output tables (MRIOTs), which constitute its primary input data. To facilitate this analysis, we introduce a new, resource-efficient Python implementation of the ARIO model, enabling the execution of a large number of simulations. Our findings highlight the substantial impact of data source and parameter selection on model outcomes, especially so when post-disaster rebuilding is costly. To ensure the robustness of their results, future studies on indirect economic impacts should be careful about recovery dynamics, consider multiple scenarios and compare results using MRIOTs from various sources.

Impact of Carbon Tax on Renewable Energy Development and Environmental–Economic Synergies

Global warming caused by greenhouse gas emissions has become a worldwide environmental problem, posing a great threat to human survival. As the world’s largest emitter of carbon dioxide, China has pledged to reach peak carbon emissions by no later than 2030 and carbon neutrality by 2060. It is found that a carbon tax is a powerful incentive to reduce carbon emissions and promote an energy revolution, but it may have negative socio-economic impacts. Therefore, based on China’s 2020 input–output table, this paper systematically investigates the impacts of a carbon tax on China’s economy, carbon emissions, and energy by applying a computable general equilibrium model to determine the ideal equilibrium between socio-economic and environmental objectives. Based on energy use characteristics, we subdivided the energy sector into five major sectors: coal, oil, natural gas, thermal power generation, and clean power. The results show that when the carbon emission reduction target is less than 15%, that is, when the equilibrium carbon tax price is less than 54 yuan/ton, the implementation of a carbon tax policy can significantly reduce carbon emission and fossil fuel energy consumption, while only slightly reducing economic growth rate, and can achieve the double dividend of environment and economy. Moreover, because the reduction of coal consumption has the greatest impact on reducing carbon emissions, the ad valorem tax rate on coal after the carbon tax is imposed is the highest because coal has the highest carbon emission coefficient among fossil fuels. In addition, as an emerging clean energy source, hydrogen energy is the ideal energy storage medium for achieving clean power generation in power systems. If hydrogen energy can be vigorously developed, it is expected to greatly accelerate the deep decarbonization of power, industry, transportation, construction, and other fields.

Greenhouse Gas Emission Estimation Using Extended Input–Output Tables for Thailand’s Biomass Pellet Industry

Greenhouse gas (GHG) emissions from Thailand’s biomass pellet production were comprehensively assessed, with a specific focus on wood and corn pellets. Employing the extended input and output tables, the anticipated economic and environmental effects of the rising demand for biomass pellets within the Asia–Pacific Economic Cooperation region, which is projected to see an increase exceeding 33% by the year 2050, were investigated. The estimations of CO2, CH4, and N2O emissions, which were conducted utilizing an open Leontief model based on the 2015 National Input–Output Tables, covered each stage of the production process. The results show that emissions from the production of corn pellets are expected to rise steadily, from 52.91 MtCO2e in 2022 to 75.77 MtCO2e by 2030, whereas emissions from wood pellet production are set to increase more substantially, from 210.30 to 301.18 MtCO2e within the same timeframe. Data derived from surveys and interviews with corn farmers and wood pellet manufacturers informed the lifecycle data for the biomass pellet supply chain from cradle to gate. The findings suggest that Thailand’s power sector could benefit significantly from the biomass potential in the northern part of Thailand, which boasts an estimated energy content of corncob at 39 ktoe (0.0016 TJ). Market demand scenarios were explored in two forms: one where it was assumed that all biomass pellets are to be exported to Japan and South Korea, expecting a combined demand of approximately 560,262 tons by 2030, and another positing that 10% of production will be reserved for the domestic market, with a forecasted annual increase of 10% from 2020 to 2050. This paper highlights the need to prioritize low-emission renewable energy sources, expand technologies with lower lifecycle emissions, optimize the biomass supply chain to enhance efficiency, and introduce sustainable energy practices. The detailed GHG emissions analysis provides critical insights for policy formulation, underscoring the importance of sustainable transitions in the context of increasing biomass demand.

Beyond greenhouse gases – Comprehensive planetary boundary footprints to measure environmental impact

The planetary boundary framework identifies nine areas of key environmental risk globally. The causes of climate change are well understood as a serious and existential threat; however the other eight areas of concern have a much more limited understanding of what is driving their continued increase.This research utilises Global Resource Input Output Assessment (GLORIA) multiregional input-output (MRIO) tables to map 15 footprint indicators across 51 sectors and seven global regions, identifying key sectors driving planetary boundary impacts and suggesting targeted interventions for sustainability.The relative role of emission intensity and total expenditure is shown, and potential trade-offs and synergies between sectors and indicators are identified. High-impact footprint clusters are identified as food and textiles, and the built environment, with moderate impacts from the services and energy sectors. These relationships are compared to several transformation agendas, identifying overlooked relationships and drivers, including the predominant role of commercial buildings and infrastructure in built environment impacts and the correlation between greenhouse gas emissions and air pollution. The primary driver of plastic use footprints is seen to be the built environment, however as a whole chemical pollution levels remain a significant unknown, and the challenge to globally stop the flow of further dangerous substances and clean up existing contaminated sites is large.By providing a detailed breakdown of planetary boundary drivers this work enables decision-makers to understand the risks and issues associated with economic purchases across all critical environmental pathways simultaneously to better prioritise action for a stable planet.

What does e-invoice data bring to SNA and real-time economy?

This paper explores the potential of electronic invoice data to enhance the System of National Accounts (SNA) and facilitate a Real-Time Economy (RTE). The rise of data science and advancements in information and communication technologies have increased the use of big data in economic statistics. E-invoice data is being digitized in Europe to detect VAT fraud, but it also contains a vast amount of information on economic entities that make up the SNA. This study focuses on integrating electronic accounting information to improve the coverage, granularity, and update speed of SNA. The paper examines the concept of RTE, which emphasizes real-time data processing and automation, particularly in Estonia and Finland. It also highlights the benefits and challenges of using invoice data for economic statistics, including issues related to data storage formats, legislative systems, and the coordination of data linkages. The research demonstrates invoice data’s theoretical and practical applications for constructing Input–Output Tables (IOTs) and monitoring financial situations. Despite the technical and institutional hurdles, the study suggests integrating invoice data can significantly transform economic statistics.

Industry spillover effects of robot applications on labor productivity: Evidence from China

This paper provides new insights into the industry spillover on labor productivity by discussing the spillover effects of robot application among industries in three spillover directions: horizontal, forward, and backward spillover. In addition, this paper measures the three spillovers with the weight matrices from the year 2012 input-output table by the Chinese National Bureau of Statistics. Using a spatial econometric model and 2000–2010 data on China's secondary industry, this paper tests three hypotheses relating to the direct effect and the spillover effects of robot applications. The main results show that the robot application of one industry can improve labor productivity significantly. Moreover, all three kinds of spillover have significant positive effects on the labor productivity of a focal industry. Among them, the forward spillover exerts the greatest impact on labor productivity. The heterogeneity effects exist due to the industry's factor intensity and technological structure etc. The findings of this study could provide several important implications for the development of a given industry and the industry chain of a country as well.

Innovation and application of inter-provincial carbon emission transfer accounting model in China’s domestic production network

The New Development Paradigm will result in the significant development of domestic production networks and the accelerated growth of carbon transfers among provinces in China. However, the existing value chain or the trade of intermediate goods decomposition method cannot completely account for the carbon content of intermediate goods. So the paper developed a accounting model for inter-regional intermediate goods trade based on input-output model. The most significant advantage of this accounting model is that by further decomposing final output into three components—final consumption within the region, final consumption flowing to other regions, and final output flowing to other regions as intermediate goods that are not returned to the region—it achieves a more comprehensive decomposition of the value chain in comparison to the established models. This approach allows for the tracking of longer value chains and the accounting for intermediate goods inflows and outflows simultaneously. Furthermore, the accounting of trade in intermediate goods can be conducted for any number of countries, regions, and sectors within the input-output system, thereby providing a foundation for the comprehensive accounting of inter-regional carbon transfers within production networks. With the input-output tables and carbon emission inventories from the CEADs (the China Carbon Emissions Accounting Database), the paper has calculated the changes of the carbon transfer among provinces in the China’s domestic production network from 2012 to 2017 and find that the inter-provincial intermediate goods trade and carbon transfer among provinces is increasing significantly. Each province has a strong incentive to overuse the carbon embodied in the intermediate goods from others, but lacks the motivation to reduce their own carbon emission. In the inter-provincial transfer of the carbon content of intermediate goods in China’s domestic production network, the difference between the average value of the ratio of the carbon content of intermediate goods from other provinces used by each province and that supplied for use by other provinces to the ratio of the carbon content of intermediate goods produced by itself increased by 13.6% between 2012 and 2017. Only a few provinces are evolving towards a win-win between economic and environmental benefits, while most are still facing the evolutionary dilemma in choosing between economic and environmental benefits. In the future, we should comprehensively explore the cooperative governance of carbon emission reduction in the domestic production network, including establishing a national standard for calculating the carbon transfer in domestic production network, improving the carbon emission responsibility sharing mechanism and carbon emission reduction compensation systems.

Assessing the impacts of fertility and retirement policies on China’s carbon emissions

AbstractThe gradual adjustment of fertility and retirement policies in China has social benefits in terms of coping with population aging. However, the environmental consequences of these policies remain ambiguous. Here we compile environmentally extended multiregional input–output tables to estimate household carbon footprints for different population age groups in China. Subsequently, we estimate the age-sex-specific population under different fertility policies up to 2060 and assess the impacts of fertility and retirement policies on household carbon footprints. We find that Chinese young people have relatively higher household carbon footprints than their older counterparts due to differences in income by age group. Relaxing fertility policies and delaying retirement age are associated with an increase in population (and labour supply) and thus increases in household carbon footprints, with the majority of these increases from the fertility side. These results may help policymakers understand interactions among those measures targeting population aging and climate action.

Exploring carbon footprints and carbon intensities of Indonesian provinces in a domestic and global context

Within Indonesia, the structure of consumption and production differs significantly across provinces. This implies that carbon footprints and intensities between provinces are also diverse. This paper calculates historical consumption- and production-based carbon emissions at the provincial level using a multi-scale input-output (IO) database for 2010, in which an environmentally extended multi-regional IO (EE MRIO) table for 34 Indonesian provinces is integrated in the global EE MRIO EXIOBASE with data for 43 countries and 5 rest of the world regions. Emissions from consumption are detailed by product and their points of origin, while emissions from production are detailed by industry and their destinations. Our results show the heterogeneity of Greenhouse Gas (GHG) emissions under both sides. The Java region is a net importer of carbon emission, while Sumatra and Kalimantan are net exporters. In the global context, the Asia Pacific region plays important role in national GHG emissions. Services product contributed 57.1% of national consumption-based GHG emissions, followed by manufacture (30.6%), and agriculture (12.3%). On the national level, 63.5% of national GHG emissions are related to household consumption. There is a high disparity across provinces in Indonesia in carbon footprints. Provincial average per capita carbon footprints vary from 2 t CO2e/capita in East Nusa Tenggara to 13.84 t CO2e/capita in East Kalimantan. Carbon intensity also varies from 0.83 kt CO2e/M Euro in Jakarta to 2.37 kt CO2e/M Euro in North Kalimantan. Agriculture and food products dominate household carbon footprints, while construction leads in government carbon footprints. Utilities and transportation services play important roles on national carbon intensities. We further correlated the Human Development Index (HDI) with per capita carbon footprints and expenditure, and find that provinces with similar GHG emissions and expenditure per capita income as Java, tend to have a lower HDI. Understanding development status and province-level characteristics is important for selecting policy strategies.

Regional Economic Development, Climate Change, and Work Force in a Gender Perspective in Chile: Insights from the Input–Output Matrix

Most nations fulfilled the commitment to reduce their emissions after the Paris Climate Agreement, and as a result, each nation has produced suitable plans to reach those goals. In this sense, Chile is hardly an exception. The emission multiplier product matrix (eMPM) and labor multiplier product matrix (lMPM), which are associated with the gender differences in the labor market, a state-of-the-art technique that integrates CO2 emissions with multi-region input–output table (MRIO) databases and elasticity to estimate the pollution caused by inter-industrial activity in the nation’s various north, center, and south regions, are used in this article to analyze the emissions of Chilean industries. This approach, by studying the economic territorial consistency (ETC) issue, is expected to establish a connection between each region’s production structure and interregional relationships between gender and the main industries that produce emissions. Indeed, the study aims to determine which regions foster economic development from an equitable perspective through the ETC study. The ETC in Chile depends on some variables, such as labor force, gender and CO2 emissions. The improvement in terms ofion will depend on the use of technology and the proper state regulation in line with the promises gained by Chile following the convening of COP25.

EXIOBASE energy accounts: Improving precision in an open‐sourced procedure applicable to any MRIO database

AbstractAs environmentally extended input–output tables are increasingly used for footprint and supply chain analysis, there has been a growing demand for precise, reliable, and intertemporally consistent environmental accounts. Energy accounts are particularly relevant. As well as providing insights into embodied energy, in the case of the multi‐regional input–output (MRIO) database EXIOBASE, they are the basis of the air emissions from fuel combustion. In this study we review previous methods and provide a more integrated and robust implementation for the EXIOBASE energy accounts that ensures higher levels of consistency between economic and physical data. Our results show that the new procedure significantly improves the precision of the energy use coefficients and multipliers, while reducing the number of outliers. The procedure is made publicly available for full transparency and made open source such that users and developers may raise issues and suggest improvements to the procedure. Furthermore, the procedure is standardized so it can be applied to any MRIO model with only minor adjustments to the input data.

Estimation of SAM for India: An Application for India’s Energy Transition Targets

The social accounting matrix (SAM) for India was historically constructed based on the input–output table (IOT). However, since 2011–2012, the Government of India has been publishing the supply–use table, instead of the IOT. While the erstwhile IOT, published by the Government of India, had the same number of products and industries, the supply–use table provides one ‘supply matrix’ and one ‘use matrix’, each of which is a rectangular table with 140 products and 66 industries (for 2018–2019). Converting the supply–use table to a square IOT and subsequently extending it to SAM require the utilisation of various data sources, numerous steps and adjustments. Despite the usefulness of both IO and SAM matrices in macroeconomic policy design, not much literature is available on these. This study aims to bridge the gap by constructing IOT and SAM for India from the supply–use table incorporating information from many other sources and describing the method of construction of the matrices. Our IO and SAM also focus on various energy sectors, including different sources of power generation, biomass and so on, and disaggregate energy-intensive sectors like cement or aluminium, considering the immense usefulness of the energy-extended macro-structure to the research of energy and environment policies. The study focuses on the construction of a 59 × 59 SAM for India, with the base year of 2021–2022 incorporating three factors of production and ten categories of households. As an application of the newly constructed SAM, we have analysed the employment implication of India’s Nationally Determined Contribution emission commitments. JEL Codes: E16, C67, D57

Agri-Food Sector in Ukraine and Poland: A Comparative Analysis Using the Input–Output Model

The war in Ukraine and the COVID-19 pandemic have shown that Ukraine is strongly integrated with global agricultural markets, is of great importance for the world’s food security, and can effectively compete with Poland in exporting to EU markets. Contrary to Poland, the agri-food sector in Ukraine has not yet been the subject of research using input–output tables. The input–output model has many advantages in studying the structures of individual sectors and their connections with other sectors of the economy and with foreign countries. Therefore, the current study fills the existing research gap. The aim of the article is a comparative analysis of the agri-food sectors in Ukraine and Poland in 2020 (during the COVID-19 pandemic) using the input–output model. The data source is the OECD TiVA database. The main conclusion is that Poland is further along the path of agricultural and food sector development than Ukraine. The study also reveals that in terms of value, the agri-food sector in Ukraine is significantly smaller than in Poland, but it is more important in the Ukrainian economy, with agriculture being its dominant link, while in Poland it is the food industry. The Polish agri-food sector is characterized by a higher import dependency of gross output. Exports play a significant role in the distribution of the gross output of Ukraine’s agriculture and Poland’s food industry. However, the export directions differed significantly. Poland exported mainly to the EU, while Ukraine exported to Asian and Middle Eastern countries.

A Study of Virtual Water Trade among G20 Countries from a Value-Added Trade Perspective

Abstract: From a value-added trade perspective, this study utilizes the world input–output tables and the water footprint data of each industry in each country in the Eora database to explore the virtual water resources of 19 countries (the G20 countries excluding the European Union) in 2016. We calculated nine value chain decompositions and the pattern of virtual water flows and then explored the implied virtual water use due to the trade of intermediate goods and final goods, and we also analyzed the unequal trade of virtual water and added value among countries. The results indicate the following. Firstly, in most countries, the largest portion of virtual water is attributed to exports of intermediate inputs that are produced in the source country and fully utilized by the direct import countries, followed by the foreign value-added component of intermediate goods, while the smallest share of virtual water is returned to the country. Secondly, in value-added trade, excluding the rest of the world (ROW), China, France, Italy, Japan, Mexico, South Korea, South Africa, Saudi Arabia, and Germany are net importers in the virtual water trade between G20 countries, and the USA is the largest net exporter of virtual water. Thirdly, intermediate product trade is the dominant form of implied virtual water trade among countries, which leads to a net flow ratio of implied virtual water of about 80% to 90%. Lastly, the Virtual Water Inequality Index shows that thirteen country combinations, including Brazil and Argentina, exhibit significant inequality, and most countries are in a relatively equal state. In addition, the virtual water and added value of the relatively economically developed regions benefit more from the virtual water trade. Therefore, it is crucial for countries to reduce their consumption of virtual water when trading intermediate products to develop high-value-added and low-water-consumption industries and to choose appropriate virtual water trade targets.