Multi-regional Input-output Tables Research Articles

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.

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.

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.

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.

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.

Substitution effect of Asian economies on China’s industrial and supply chains: from the perspective of global production network

This paper views China Production Network (CPN) as an integral component of the Global Production Network (GPN) and constructs null model (GIVCBN-I model) and the counterfactual model (GIVCBN-II or GIVCBN-III model) to identify and measure the potential industrial relocation risk exposure of CPN based on the Multi-Regional Input-Output (MRIO) table. The main findings are as follows. Firstly, Altasia will induce more of China’s industrial and supply chains to break compared with ASEAN, which also means that strong industrial complementarity exists between Japan, South Korea, India, Bangladesh and the ASEAN member countries, enabling Altasia to have a more significant substitution effect on China. Secondly, the counterfactual models’ network-level characteristic indicators are worse than those of the null model in economic terms, suggesting that removing trade barriers for intermediate goods within Altasia could lead to the decoupling of industrial sectors in the CPN, thereby accelerating the trend of China’s industrial and supply chains relocating offshore. Thirdly, according to the comparison results of node-level characteristic indicators, Altasia has weakened China’s influence scope, profitability, and robustness of risk within the global industrial and supply chains, but mainly concentrating on its resource-intensive and labor-intensive sectors rather than capital-intensive and technology-intensive sectors, which indicates that some China’s industrial sectors still maintain substantial competitive advantages in the GPN. In sum, this paper provides theoretical guidance for identifying and analyzing the trends of industrial relocation in the Asia-Pacific region and helps industrial policymakers deepen the understanding of regional economic integration and its impact.

Assessing the Sectoral Economics Consequences of Carbon Price Using Price-Output Model Analysis

Abstract A carbon pricing policy is featured in the Twelfth Malaysia Plan as a considered measure for Malaysia to achieve its net-zero emissions goal by 2050.This study utilised price and output model analysis using Eora Multi-Region Input-Output Table 2016 (MRIO) database to assess the impact of carbon tax policy on price and output changes. The study reveals that the manufacturing sector is the most sensitive to the introduction of a carbon tax, with pronounced effects including a price escalation of 0.54% and a reduction in output of 0.81%. The ranks of sensitivity then followed by agriculture, services, mining and construction sector. the services sector presents a compelling opportunity for policymakers, offering a robust tax revenue stream while displaying lower vulnerability to the tax’s effects. This observation underscores the importance of a strategic approach in carbon tax policy, where the potential for revenue generation is balanced against the differential impacts on sectoral vulnerability. This study provides an insightful information for policymakers to develop strategic plans to ensure a smooth transition towards carbon pricing policy and foster sustainable economic development.

Regional carbon inequality prediction in China based on shared socioeconomic pathways: A human well-being equity perspective

Carbon inequality is strongly related to economic development and human well-being (HWB) improvements. However, relatively little research has been undertaken to predict future interregional carbon inequality in China from an HWB equity perspective based on scenarios combining shared socioeconomic pathways (SSPs) and carbon reduction policies. The biproportional scaling method named after economist Richard Stone (RAS) was used to predict China's 2020 to 2050 multiregional input–output (MRIO) tables. Then, these MRIO tables were used to simulate future net carbon emissions (NCEs) and net human well-being (NWB) transfers under the SSP1–1.5 °C, SSP1-NEU, SSP2-2 °C and SSP5-BAU scenarios. China's interregional carbon inequality was predicted under different scenarios to clarify the ideal path for mitigating carbon inequality. In the SSP1–1.5 °C, SSP1-NEU, SSP2-2 °C and SSP5-BAU scenarios, the total carbon emissions (CEs) clearly decrease, whereas the total HWB clearly increases. Transfers of NCEs between regions increases, and transfers of NWB between regions decreases in each of the four scenarios. According to the mean regional environmental inequality (REI) value, China's interregional carbon inequality is relatively low under the SSP1–1.5 °C and SSP1-NEU scenarios and relatively high under the SSP2–2 °C and SSP5-BAU scenarios. Mitigating interregional carbon inequality is a long-term and arduous task that requires commitments from governments, businesses and society. These findings clarify the optimal path for China to reduce carbon inequality in the future and provide a theoretical basis for government agencies to rationally adjust the current development model. Furthermore, they provide a supportive reference to help other economies achieve equitable and sustainable development.

Carbon inequality under domestic value chain fragmentation

The division of production leads to the separation of production and consumption, resulting in carbon emissions transfer with trade among regions. Thus, quantifying carbon inequality caused by domestic trade is important for allocating emission-reduction tasks and improving emission-reduction efficiency. Considering domestic value chain (DVC) fragmentation in China, we use multiregional input–output tables to divide products into within-province trade products, traditional trade intermediate/final products, and DVC–related trade products. Then, we examine carbon intensity inequality (CII) under DVC fragmentation and, using Theil index to analyze the contributions of between-province economic differences, within-province trade structures, and related influencing factors to CII. Previous studies have mostly focused on issues related to global value chain fragmentation. We take the lead in exploring CII caused by DVC fragmentation, and for the first time decompose the composition of CII from the perspective of DVC fragmentation. In addition, the national CII is attempted to analyze its contribution at the provincial level for the first time, which is a new improvement and exploration of previous regional research perspectives. The empirical results show that China's CII is on an upward trend, with large changes between 2002 and 2007, and then stabilized between 2007 and 2010 due to the financial crisis, before entering a phase of rapid change after 2012. In terms of regional contribution, between-province inequality is the core to PCII, while within-province inequality is the key to CCII. In terms of province, the changes in between-province inequality are relatively stable at early period. In the middle and late stages, the temporal and spatial changes of PCII and CCII between provinces are obvious with “geographic stickiness” weakening. Specifically, the carbon transfer in the early study period is mostly concentrated in traditional trade products, and the share of carbon transfer in DVC-related trade products later rises significantly from 20.05% in 2002 to 36.32% in 2017, and the value-added transfer rises from 17.09% in 2002 to 27.65% in 2017. In terms of influencing factors, energy intensity remains an important component to CII. In addition, the uncertainties of the data and methodology used in this study are discussed and possible future research directions for expansion are elaborated. Finally, specific policy recommendations for mitigating carbon inequality are presented to inform the development of efficient carbon reduction strategies.

Estimating inter-regional trade: the radiation model versus the gravity model

The estimation of interregional trade flows within a country is confined to the context of multi-regional input–output models. Despite the remarkable relevance of these trade flows for regional incomes, most countries have almost no official data, with Korea being an exception used here. In addition to survey-based estimation methods, there are non-survey methods, some based on gravity models, which can be used to estimate inter-regional trade flows. This paper compares the gravity model with the novel radiation model. Preliminary results show that the accuracy of the radiation model’s estimation is superior to that of the gravity model, with the invaluable benefit of not needing to estimate regression coefficients, unlike the gravity model. This finding provides a generalisation of the radiation model for estimating interregional trade in contexts where there is no prior multi-regional input–output table without restrictions derived from coefficient estimation as in the gravity model.

Spatio-temporal evolution and driving mechanism of metal value flow networks: A global value chain perspective

The lengthening of the global value chain (GVC) and the deepening of the transnational labor division system have led to frequent cross-border flows of metal values worldwide, and the pattern of the international metal trade is facing reconstruction. This paper combines a new trade accounting framework and a complex network model to construct global metal domestic value added (DVA) and foreign value added (FVA) flow networks based on global multi-regional input‒output (MRIO) tables for 2000 and 2007–2022 and then analyzes their structural topological features and spatio-temporal evolution trends at the macro, medium, and micro levels. Then, the main driving factors are investigated using the exponential random graph model (ERGM). The results show that the DVA and FVA networks are expanding and have obvious aggregation effects and small-world characteristics, that the community divisions show a trend toward regional integration and worldwide multipolarity, and that Germany is the most important transportation hub and trade medium in the FVA network, while China and the United States are, respectively, the largest creator and consumer of the world's metal value flow. In addition, the DVA network is more susceptible to node attribute effects such as GDP, trade openness, population size and foreign direct investment, while the FVA network is more susceptible to exogenous network effects such as geographic distance and colonial ties.

From global to national: The role of urban agglomerations in China's new development paradigm.

Urban agglomerations (UAs), which serve as pivotal hubs for economic and innovative convergence, play a crucial role in enhancing internal circulation and strengthening external linkages. This study utilizes the China city-level multi-regional input-output tables, incorporating the Dagum Gini coefficient and kernel density estimation methods, to perform a thorough quantitative analysis. Disparities within the national and global value chains ("dual value chains") of Chinese UAs from 2012 to 2017 were assessed. Additionally, the logarithmic mean Divisia index (LMDI) method was applied to disaggregate the drivers of both national and global intermediate inputs (NII and GII). The study's key findings include the following: (1) The national value chain (NVC) within UAs exhibits robust growth, contrasting with the decline in the global value chain (GVC). (2) The inter-UA disparity contribution rate significantly surpasses the combined rates of intra-UA contribution and super-variation density. (3) Distinct evolutionary peak trends are discerned among various UAs within the "dual value chains", highlighting diverse spatial polarization characteristics and expansiveness. (4) The growth of the NVC has transitioned from a negative to a positive impact on NII, while the decline in GVC has substantially counteracted GII growth. Economic and demographic factors notably drive positive improvements in both NII and GII, whereas the efficiency of outflows presents a negative driving effect. Based on these findings, this study offers strategic recommendations to facilitate the effective integration of UAs into the new development paradigm, thereby providing a scientific basis for related decision-making processes.

Regionalizing the supply chain in process life cycle inventory with multiregional input–output data: An implementation for ecoinvent with EXIOBASE

AbstractLife cycle inventory (LCI) databases, such as ecoinvent, are crucial for life cycle assessment (LCA), but lack country‐specific resolution in activity details and trade between regional activities in the supply chain. For example, ecoinvent only provides rest‐of‐world and European datasets for photovoltaic panel production, consuming the same global consumption mix of photovoltaic cells. Global or continental activities and trade limit the use of existing country activities, such as electricity production, and the accuracy and granularity of LCA results. We addressed this issue by disaggregating ecoinvent's global and continental unit processes to the country level and by regionalizing trade using country‐sector‐specific consumption mixes of product origins from the multiregional input–output table EXIOBASE. This produced a consistently regionalized ecoinvent at country level. Comparing the climate change impacts of 195,708 non‐market datasets in our regionalized ecoinvent with reference datasets in ecoinvent reveals manufacturing sectors as the most affected. The study of photovoltaic panel production shows that the differences in climate change impacts are mainly due to the different country‐specific suppliers of components and their electricity mixes, which are lost in the aggregated original data. The water consumption impacts of wheat production show the country differences only when regionalized CFs are applied, indicating that regionalized biosphere and technosphere flow amounts are needed for better results. The mapping quality between ecoinvent and EXIOBASE and inconsistent market definitions were discussed along with further limitations. Our study highlights the potential of incorporating better trade information and regional disaggregation in LCI databases to improve the LCA outcomes.

Indirect channel of trade agreements in deepening global value chains

AbstractPreferential trade agreements (PTAs) between trading partners are known to have positive impact on the expanding and deepening of global value chain integration due to lower trade and investment barriers. Less is known, however, is if other PTAs of PTA partners have any impact on the value‐added trade linkages of the direct PTA partners concerned. Based on compositive indicators measuring the breadth and depth of PTAs from 2007 to 2018 and using Multiregional Input–Output Table database covering 62 countries and 35 sectors and the Content of Deep Trade Agreements database, this paper estimates the multiplicative form of the constant‐elasticity augmented gravity equation model by a Poisson Pseudo Maximum Likelihood (PPML) estimator. This study shows that indirect impact of the deepening of trade agreements of a country's PTA partner exerts positive, significant impact on value‐added exports of a country. Both backward and forward linkages of a country measured by various decomposition of valued added exports indicate this indirect channel of value chain deepening effect even outweighs the direct impact from the deepening of PTAs between direct trading partners with significant policy implications in formulating PTA strategies.

Firm's position in global value chains and its impact on pollutant emissions: Evidence from Chinese manufacturing firms

This paper studies examines how a firm's position in the global value chain affects its pollutant emissions. This paper integrates China's firm-level trade data into China's multi-regional input-output tables to provide an index to measure a firm's position in global value chains. Based on a firm-level pollution dataset (2000–2014) in China, this paper conducts an empirical analysis and find that the most-downstream firms on the global value chain have lower pollutant emission intensity. Our results also suggest that the production factor structure effect, the knowledge absorption effect and the abatement investment effect together contribute to the emission intensity gap between the most-upstream firms and the most-downstream firms. These novel results are significant in guiding firms towards reducing their emissions and promoting a green global value chain, with the ultimate goal of achieving multinational environmental protection.

Does industrial relocation impact green economic efficiency? Evidence from China’s energy-intensive industries

Utilizing the latest multi-regional input-output (MRIO) tables and spatial econometric model, this paper measures the inter-provincial relocations of energy-intensive industries (REI) in China and investigates its impact on regional green economic efficiency (RGE). The results indicate that the primary inflow areas of energy-intensive industries are northern coastal, central, and northwestern China, while the main outflow areas are southeastern coastal and southwestern China. The net inflow of energy-intensive industries negatively affects local RGE but positively affects neighboring provinces. However, at the national, REI contributes to improving the overall RGE. This improvement effect varies regionally and has been notably attenuated after the implementation of the Belt and Road Initiative (BRI). Additionally, this paper verifies that the crowding-out effect on R&D investment is an important channel through which REI affects RGE.

Tracing agricultural land carbon loss through transregional food consumption for fairness of responsibility allocation

Agricultural land carbon loss (ALCL) has been increasingly triggered by transregional food consumption in China. Understanding land carbon burden from consumption side is then recognized to be essential for facilitating regional fairness. To this end, we combined physical food-orient multi-regional input-output table and ALCL inventory for 26 kinds of foods in 31 provinces to trace China's ALCL through cross-regional consumption. Results show that ALCL embodied in inter-provincial trade was up to 42 % of the national total ALCL. Food consumption in Guangdong caused the largest ALCL, while Tibet and Qinghai stood out from per capita perspective. Furthermore, consuming foods produced in areas with higher production ALCL intensity would elevate national ALCL, thus shrinking the adverse flows and controlling agricultural land expansion in high-intensity areas may help lessen national ALCL. This study contributes to equitable allocation of responsibility for land carbon loss, and enlightens future land carbon loss risks and restoration opportunities.

Spatio-temporal patterns and cascading risks of embodied energy flows in China

The increasingly complex interrelation between energy use and trade is challenging the secure management of energy. However, limited knowledge of the cascading risks of embodied energy in trade is understood. An embodied energy network of China's interprovincial trade was established based on China's multiregional input-output tables for 2012 and 2017. The pivotal nodes, main flows, and flow trajectories within the embodied energy network were identified using the complex network model. Subsequently, the cascading effects within the embodied energy network were simulated using a cascading failure model. The results indicate that a substantial portion of embodied energy flows is concentrated within a few provinces and sectors. Within the provincial-sectoral network, approximately 50 % of the edges carry 90 % of the embodied energy flows. Sectors exhibiting robust influence, significant intermediary capacity, and pronounced centrality assume pivotal positions within the network. Due to cascading effects, a supply crisis in one crucial province or sector can spread quickly, affecting the entire energy network. This study contributes to ensuring regional energy supply security and offers fresh insights into mitigating cascading risks in the energy system within and beyond China.

Revisiting methods for estimating interregional input-output accounts: It's not just about trade flows

A basic underlying assumption in most of the research to date is that intermediate industry accounts of the economies in multiregional input-output (MRIO) tables exist and are accurate. In fact, if they exist at the subnational level, such accounts are, at best, roughly estimated and predicated on far less empirical information than is available for economies of nations. Moreover, intra-economy intermediate-industry flows are typically larger than the set of a region's commodity in- and out-flows. So, if intermediate industry flows in a set of MRIO accounts are noticeably mis-estimated, it follows that interregional trade coincidentally derived using them must be even more conspicuously in error.We hypothesize as more information is used to estimate MRIO accounts, the better the estimates should be. We start our experiment by consolidating 2019 FIGARO accounts of the 27 member states of the European Union, while maintaining sectoral detail, to produce a “national account”. We then test several approaches to constructing MRIO tables. The approaches distribute interregional trade fully by receiving industry, as in FIGARO, as well as strictly in the form of a diagonalized matrix as if the commodity inflows are competitive imports. To do this, both a gravity model and RAS are applied to each approach. We then test to see how well the approaches estimate main features of FIGARO's MRIO accounts and detail a rather consistent ranking of the relative accuracy of them. We also find that the level of error inherent to the estimated MRIOs is markedly similar across approaches, particularly for multipliers. Further, relaxing interregional trade to a diagonalized matrix tends to add very little error. The approach that uses the least data is, however, markedly worse in replicating countries’ direct requirements matrices and Leontief inverses, which suggests its use in a more-limited set of applications.

The inequality of household carbon footprint in China: A city-level analysis

Climate change mitigation and carbon inequality reduction are of great significance to the sustainable development. Most of the existing studies on China's household carbon footprint inequality are at provincial level and lack in-depth analysis of cross-dimension of consumption categories. We calculated the carbon footprints in 309 city-level areas in China based on the multi-regional input-output table, and further explored the inequality of household carbon footprints from perspective of cross-dimension with Gini coefficient and Lorentz curve based on the China Family Panel Studies dataset. We found that although the carbon footprint inequality of different areas, income groups and family size were relatively high on the whole, the level of that in different consumption categories showed significant different characters. For instance, affluent demographics possess the requisite financial capacity to acquire luxury apparel, whereas economically disadvantaged cohorts predominantly procure garments at standard price points. This dynamic may engender heightened carbon disparity within the realm of clothing, with a proclivity for greater imbalances observed in high-income strata as opposed to their low-income counterparts. Specific measures for guiding residents to rationally consume luxury food and allocate educational resources, and advocate low-carbon travel to eliminate household carbon footprint inequality in China are proposed.