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Structural Path Analysis (SPA) and the Hypothetical Extraction Method (HEM) are both established methods for studying CO2 emissions. However, their combined application to investigate emission linkages in specific sectors, such as construction, is relatively novel. This research integrates SPA and HEM to explore the CO2 emissions linkages within the construction sectors of China and the United States, providing a comprehensive understanding of how these emissions are interlinked. The findings show that construction sector of Untied States and China is the largest production-based CO2 emissions of construction sector in the world, but the consumption-based emissions of construction sector in China contributes 29.81% of total CO2 emissions, compared to 5.63% in the U.S. This suggests that the carbon footprint of the construction sector is a significant consideration, irrespective of whether it is assessed from the standpoint of production or consumption dynamics. Meanwhile, the development of construction sector has driven the electricity, gas, steam, and air conditioning supply sectors to emit a large amount of CO2 emission in both countries. By analyzing the differences in the main emission linkages and pathways of the construction sectors between China and the U.S., this study provides insights for reducing CO2 emissions in the construction sector and assists policymakers in developing future strategies. [ABSTRACT FROM AUTHOR]

Abstract Structural Path Analysis (SPA) and the Hypothetical Extraction Method (HEM) are both established methods for studying CO2 emissions. However, their combined application to investigate emission linkages in specific sectors, such as construction, is relatively novel. This research integrates SPA and HEM to explore the CO2 emissions linkages within the construction sectors of China and the United States, providing a comprehensive understanding of how these emissions are interlinked. The findings show that construction sector of Untied States and China is the largest production-based CO2 emissions of construction sector in the world, but the consumption-based emissions of construction sector in China contributes 29.81% of total CO2 emissions, compared to 5.63% in the U.S. This suggests that the carbon footprint of the construction sector is a significant consideration, irrespective of whether it is assessed from the standpoint of production or consumption dynamics. Meanwhile, the development of construction sector has driven the electricity, gas, steam, and air conditioning supply sectors to emit a large amount of CO2 emission in both countries. By analyzing the differences in the main emission linkages and pathways of the construction sectors between China and the U.S., this study provides insights for reducing CO2 emissions in the construction sector and assists policymakers in developing future strategies.

• We explore the intersectoral linkages of the Greek tourism sector. • We find that tourism demonstrates strong forward linkages. • The backward linkages of the tourism sector appear to be weak. • The growth of the economy would lead to the expansion of tourism, not vice versa. This paper assesses the intersectoral linkages of the tourism sector of the Greek economy using an extended version of the hypothetical extraction method, which allows the intersectoral effects of the labor force reproduction process to be taken into account, and data from the symmetric input-output table for the year 2015. The findings of our analysis show that the role of tourism in the Greek economy is more as a seller of inputs in other sectors than as a buyer of inputs, a finding that can be reduced to the high participation of the tourism product in the labor force reproduction process. In other words, an increase in demand for the tourism product cannot bring about a strong growth in the economy, since the sector's dependence on inputs from other sectors for its operation is low and, therefore, the increase in the tourism product does not lead to a large increase in the production of the other sectors. On the contrary, an increase in demand for the products of other sectors will lead to a strong growth of the tourism sector, since the dependence of other sectors on inputs of the tourism sector is high. The interdependencies in the production structure of the Greek economy show that the tourism sector cannot be the basis of a growth policy (i.e. by stimulating tourism demand), but, conversely, the growth of the Greek economy will lead to a significant increase in its tourism sector. [ABSTRACT FROM AUTHOR]

Sino-Latin American trade have increased substantially for decades. However, the increasing trade imbalances between China and several Latin American countries have yielded growing trade frictions. In this paper, we re-calculate the bilateral trade balance using the value-added content in trade and measure the contribution of Sino-Latin American trade to economic growth. The results show that gross trade statistics seriously overestimate the real bilateral trade imbalance, and China's trade surplus with Mexico decreased by over 50%. The composition of Sino-Latin American trade suggests that most Latin American economies are complementary with Chinese economy. The South-South trade has been increasingly important for both China's and Latin America's economic development. We foresee an optimistic future of relations and continuously increasing trade between China and Latin America. Meanwhile, more efforts should be made to settle trade frictions and intensify Sino-Latin American relations. [ABSTRACT FROM AUTHOR]

This paper proposes a generalisation of the regional extraction method used by Dietzenbacher at el. [(1993). The regional extraction method: EC input–output comparisons. Economic System Research, 5(2), 185–206. ]. The production system represented by an input–output table is broken down into three flow matrices: intermediate input, final demand, and value added. The approach of Dietzenbacher et al. (1993) focuses on the input matrix to obtain both the backward and forward dependencies. The present paper, offers an alternative approach includes the final demand matrix to calculate the backward dependencies, while the value-added matrix is included for the forward dependencies. These two approaches are then compared by applying them to the empirical data based on the EUREGIO database. The results indicate that the Dietzenbacher et al. approach underestimates the dependencies, and the difference between these two approaches could lead to a different ranking of the dependence of the regions. [ABSTRACT FROM AUTHOR]

The transportation sector is an indispensable link in the industrial chain of an economic system. Considering the current push to comprehensively construct new patterns of development, the transportation sector is under huge pressure to achieve the goal of "carbon peak and carbon neutral". Therefore, to develop low-carbon transportation in China, it is important to study the carbon emission linkages in its transportation sector in order to understand its potential and the factors affecting carbon mitigation. In this study, sectoral carbon emission linkages and dynamic changes during the period of 2002–2020 for the transportation sector in China were quantitatively investigated based on the input–output analysis and hypothetical extraction method (HEM). The results showed that the total carbon emission linkages for the transportation sector mainly experienced growth, increasing by 848.63 Mt from 2002 to 2020, with consistently stronger supply-side than demand-side carbon emission linkages. This indicates that the potential of the transportation sector for carbon reduction lies upstream in the chain of carbon emission linkages. Furthermore, the transportation sector was consistently a net export sector of carbon emissions, and net carbon transfer decreased with fluctuations. Regarding carbon emissions from the transportation sector, the construction sector was found to be main destination for the majority of these emissions, while the power supply sector was the largest source. The policy implications derived from this research can serve as a crucial lever for the low-carbon development of China's transportation sector. [ABSTRACT FROM AUTHOR]

The bioeconomy includes the sectors that use renewable biological resources to produce value added products, such as food, feed, energy, and bio-based products. Its importance has been demonstrated by its inclusion as a priority in specific and related policies such as the bioeconomy strategy, the Sustainable Development Goals, the European Green Deal, and the Next Generation recovery plan. Spain has not lagged behind and considers the bioeconomy as a priority in its policy strategies to achieve a more sustainable economy. Despite its importance, the analysis of the potential of the bioeconomy sectors in Spain is limited. To carry out policy-relevant impact assessment in support of bioeconomy development, specific databases describing bio-based products are required. Hence, this work based on the Bio Social Accounting Matrix (BioSAM) for Spain for the year 2010 with a high disaggregation of bio products to perform a structural analysis based on two different and complementary methods: the traditional and the Hypothetical Extraction approach. The structural analysis results reveal promising products as key wealth generators and growth promoters and allow to identify the most suitable to be stimulated with policies to promote the development of the Spanish bioeconomy. Therefore, this paper provides some proposed avenues that should be considered by policymakers. [ABSTRACT FROM AUTHOR]

The development of human society has led to the growing consumption of industrial products, which generates significant amounts of carbon emissions. However, relatively few in-depth studies have been conducted on the influence of different demand factors (e.g., household consumption, government consumption, export, and capital formation) on carbon emissions, which hinders the development of targeted industrial policies. To address this issue, an analytical framework based on input–output theory, the hypothesis extraction method, and complex network analysis was established to estimate the intrinsic influence of different demand factors on the embodied carbon transfer between provinces in China. The key findings can be summed up as follows: (1) The macro direction of China's embodied carbon transfer runs from resource-rich northern provinces to industrially developed southern provinces. (2) From the perspective of different demand factors, capital formation is the most significant contributor to China's embodied carbon transfer, with the construction industry being the most important driver. In contrast, government consumption causes the least embodied carbon transfer, but it has the highest average carbon emission intensity. (3) According to complex network theory, the carbon transfer networks via provinces and industries caused by exports are the most concentrated, with the manufacture of electrical machinery and electronic equipment serving as the main source of demand. In contrast, the carbon transfer network resulting from household consumption exhibits a high level of decentralization, with dominant sectors including electric power, gas and water production, and supply and other services. Based on these findings, this study is expected to contribute targeted suggestions with which provinces and industries can formulate demand-side carbon reduction policies for different demand factors, which will contribute to the achievement of "carbon peaking and carbon neutrality". [ABSTRACT FROM AUTHOR]

We provide a general framework to assess the traceability of systemic risk and macro interconnectedness to understand the financial risk transmissions channels. Our contribution help address the information need established in the DGI-2 in a FSAM-based model that fully captures the interconnectedness between real and financial sectors. Recent developments in the field of IO and SAM evaluations have led to a renewed interest in the usage of linkage analysis to measure the role that a sector play within the economy. Focusing on the backward and forward linkage, hypothetical extraction method, and structural path analysis, we show how feasible it is to include heterogeneous financial institutions to study risk interactions effects on macroeconomic outcomes. This paper's proposal may be useful for thinking about how micro-data and macro-aggregates can be incorporated into the set of financial soundness indicators, allowing to obtain an idea of the vulnerabilities of the financial sector. [ABSTRACT FROM AUTHOR]

Understanding how countries contribute to the generation of externalities globally is important for designing sustainable policies aimed at reducing negative externalities such as carbon emissions. Commonly used approaches focus on either producers or consumers, thereby neglecting the role of intermediates. We here introduce the concept of throughflow to comprehensively quantify upstream externalities generated by the supply chains originating from, passing through or ending in a given country. We define the Throughflow Based Accounting (TBA) framework as the decomposition of the throughflow into local, imported, exported and traversing externalities. We illustrate the strength of the TBA by identifying the CO2 emissions caused by supply chains involving the German economy. We show that Germany could use its position in global value chains to help reduce two times more CO2 emissions than measured with usual production- or consumption-based accounting frameworks. [ABSTRACT FROM AUTHOR]

China has pledged to peak its carbon emissions before 2030 and achieve the net-zero ambition in the 2060s. Reducing the national carbon emission intensity can help achieve these ambitions effectively. To explore the tradeoff between emission reduction and system health, a factorial hypothetical extraction method has been proposed. It was applied to identify key carbon emission sectors, and further help formulate countermeasures on reducing the national emission intensity. A seven-factor factorial analysis was developed to evaluate the effects of factors (i.e., 7 countermeasures) and the combinations (i.e., 128 scenarios) on responsive variables (i.e., system health). Main effects and interactions for response variables were also detected between these factors. Results show that the most effective combination, i.e., simultaneously enlarging the production scales of agriculture and other services, and lessening those of metallurgy sectors, can help reduce emission intensity by −19.2%. Lessening the production scales of electricity-generation/metallurgy, and enlarging those of wholesale and retailing sectors, can help reduce national emission intensity, while these factors negatively impacted system sustainability and robustness. The mitigation effects of these countermeasures will be weakened if these countermeasures are implemented simultaneously. Enlarging the production scales of leasing and commercial services and other services sectors can help achieve a win-win outcome. China has pledged to reduce the national carbon emission intensity (NEI) by 60%–65% in 2030 compared to the level in 2015. However, emission reduction policies may come at the expense of system health. In this research, key carbon emission sectors are extracted and seven countermeasures targeting on these sectors are proposed. Then, there are 128 combinations of these countermeasures. Under all the combinations, the changing rates of NEI are evaluated under all the combinations. In addition, the contribution effects of all the combinations on system health (i.e., robustness and sustainability) are also assessed. Accordingly, enlarging the production scales of leasing and commercial services, and other service sectors can positively impact system health, as well as NEI. Lessening the production scales of electricity-generation/metallurgy, and enlarging those of wholesale and retailing sectors, can help reduce NEI, while these factors negatively impacted system sustainability and robustness. [ABSTRACT FROM AUTHOR]

The close production and consumption relationship between industries leads to the embodied CO2 transfer among industrial sectors along with the exchange of products. Thus, grasping the situation of embodied carbon transfers from the demand side is of great significance for better reducing a country or region’s CO2 emissions. This study investigates the embodied carbon transfers in Guangdong Province from 2002 to 2017 from the industrial dimension by applying a hypothetical extraction method. An enhanced generalized RAS method was utilized to predict the intersectoral carbon transfers in 2025 and 2030. The results show that, from 2002 to 2017, the average proportion of carbon emission output of 72.11% made the production and supply of electricity and heat sector the main CO2 emission transfer exporter, while the other service and construction sectors were the leading importers. Moreover, the embodied carbon transfers between these three sectors are the main carbon transfer paths. By 2025, the other service sectors will become the largest embodied carbon importers, surpassing the construction sector. Therefore, it is necessary to control the consumption demand of other service and construction sectors on the demand side to reduce carbon emissions driven by demand.

In order to support the emissions reduction options in manufacturing industry effectively, it is necessary to quantify the final demand embedded manufacturing consumption (DEMC) emissions which can be estimated by converting intermediate manufacturing consumption into all final demand categories. Here, we quantify the DEMC emissions in China's 30 provinces during 2007–2017 using a multi-regional input–output (MRIO) model and the modified hypothetical extraction method (HEM). Then, we analyze impacts of four factors (including emissions multipliers, consumption structure, investment efficiency, and investment scale) on the DEMC emissions. Finally, considering a large driving effect of investment scale on manufacturing emissions, we conduct four scenarios to quantify the mitigation potential of DEMC emissions during 2020–2035. We find that from 2007 to 2012, the DMEC emissions increased doubled, while during 2012–2017, it decreased from 1217 to 634 Mt. The capital-intensive manufacturing and the labor-intensive manufacturing industries were main sources of intra- and inter-sectoral emissions, respectively. Investment scale was the main driver of the growth in DEMC emissions during 2007–2015, while it led to a reduction of DEMC emissions during 2015–2017. Emission multipliers had the largest positive impact on the reduction of DEMC emissions during the whole period. Consumption structure increased DEMC emissions during 2007–2012, while with the consumption structure shift towards knowledge-intensive manufacturing industry, it induced a reduction of DEMC emissions during 2012–2017. Moreover, implementing an integrated mitigation measures (including reducing emissions multipliers, decreasing investment efficiency, and adjusting consumption structure) could help China to realize the emissions peaking target. However, there are still 8 provinces whose DEMC emissions are unlikely to peak before 2030. [ABSTRACT FROM AUTHOR]

The development of human society has led to the growing consumption of industrial products, which generates significant amounts of carbon emissions. However, relatively few in-depth studies have been conducted on the influence of different demand factors (e.g., household consumption, government consumption, export, and capital formation) on carbon emissions, which hinders the development of targeted industrial policies. To address this issue, an analytical framework based on input–output theory, the hypothesis extraction method, and complex network analysis was established to estimate the intrinsic influence of different demand factors on the embodied carbon transfer between provinces in China. The key findings can be summed up as follows: (1) The macro direction of China’s embodied carbon transfer runs from resource-rich northern provinces to industrially developed southern provinces. (2) From the perspective of different demand factors, capital formation is the most significant contributor to China’s embodied carbon transfer, with the construction industry being the most important driver. In contrast, government consumption causes the least embodied carbon transfer, but it has the highest average carbon emission intensity. (3) According to complex network theory, the carbon transfer networks via provinces and industries caused by exports are the most concentrated, with the manufacture of electrical machinery and electronic equipment serving as the main source of demand. In contrast, the carbon transfer network resulting from household consumption exhibits a high level of decentralization, with dominant sectors including electric power, gas and water production, and supply and other services. Based on these findings, this study is expected to contribute targeted suggestions with which provinces and industries can formulate demand-side carbon reduction policies for different demand factors, which will contribute to the achievement of “carbon peaking and carbon neutrality”.

Italy joined the so-called 'Industry 4.0' European framework in 2016, which designed and approved a national plan to regulate this key issue for regional development. To better support such a framework, the present study attempts to quantify the contribution of the Italian regions to the output formation process. More specifically, a multi-sectoral Input–Output (IO) model that supports national policies was proposed to cumulatively consider 29 industries that partition the Italian economy into representative branches at the level of administrative regions. Elementary input data were derived from the inter-sectoral table of the economy released by the Italian National Institute of Statistics (ISTAT). The economic outcomes of the Italian regions were estimated using a non-survey procedure, based on Flegg Location Quotients, to determine the upstream and downstream positions of each industry at country and regional levels. Indices grounded on the Hypothetical Extraction Method (HEM) further delineated the role each industry plays in the regional economy. The empirical findings of this study demonstrate how non-survey IO regionalization and the resulting industry-based indices provide appropriate knowledge for regional development policies. [ABSTRACT FROM AUTHOR]

The carbon emissions of sectors and households enabled by primary inputs have practical significance in reality. Considering the mutual effect between the industrial sector and the household, this paper firstly constructed an environmentally extended semi-closed Ghosh input–output model with an endogenized household sector to analyze the relationship between carbon emissions and the Chinese economy from the supply-side perspective. The structural decomposition analysis and the hypothetical extraction method were remodified to identify the supply-side driving effects of the changes in carbon emissions and investigate the net carbon linkage. The results show that the electricity, gas, and water supply sector was the key sector with the highest carbon emission intensity enabled by primary inputs. The household sector had an above 93% indirect effect of the enabled intensity, with its enabled intensity dropping significantly by more than 55% from 2007 to 2017. The operating surplus and mixed income caused 3214.67 Gt (34.17%) of the enabled emissions in 2017. The supply-side economic activity, measured by the value added per capita, was the main factor of the carbon emission growth, mainly attributed to the development of the manufacturing sector and the electricity, gas, and water supply sector. The emission intensity and allocation structure both brought a decrease in carbon emissions. The electricity, gas, and water supply sector and the manufacturing sector were the major sources of the supply-induced cross-sectoral input emissions, while the commercial and service sector and the household sector were the top source of supply-induced cross-sectoral output emissions. This paper sheds light on the policies of the carbon emission abatement and the adjustment of the allocation structure from the perspective of supply. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Economía (Universidad Autónoma de Yucatán) is the property of Universidad Autonoma de Yucatan, Facultad de Economia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

China’s energy consumption and its growth trend determine the domestic energy production and supply pattern. The understanding of energy consumption and its changes will help to enhance urban resilience. Based on the improved input-output model and hypothesis extraction model, this paper aims at constructing the energy-industry connection model, analyzing the energy transfer implied in the economic activities of various industrial sectors, and examining the energy transfer effect between the supply-side (SS) and demand-side industry sectors of the Shaanxi Province. The results showed that, in 2017, the energy industrial sector was the most energy consumption industry in Shaanxi Province. The industrial energy sector belonged to the net energy output industrial sector, and the energy products were transferred to other industrial sectors. This paper can provide a scientific basis for the energy SS reform, adjusting the industrial layout of regions in the Yellow River Basin.

In the context of tourism, sports are one of the major attractions countries offer. There cannot be the slightest doubt about the relevance of sports activities for the economy. Previous studies assessing the economic impact of sporting events have usually been partial equilibrium studies. This article contributes to the emerging body of literature by explicitly incorporating four categories of sports tourism events (competitions, championships, tournaments, and leagues), so as to study the effects of sports tourism demand on the economic system in terms of income and added value. It further examines their relative, rather than individual, impact on the regional economy of Castile and Leon through a fixed price multiplier model based on the regional social accounting matrix. The results reveal that sports tourism events represent 3.1% of the regional gross domestic product, highlighting the importance of this sector for its economy. [ABSTRACT FROM AUTHOR]

Two frameworks, hypothetical extraction and betweenness centrality analysis, can be used to identify environmentally important sectors in complex supply chains. This study derives an analytic expression for the relationship between hypothetical extraction and betweenness centrality analysis. Second, using the Eora and WIOD, this study analyzes the degree of difference in 'important' sectors identified by hypothetical extraction and betweenness centrality analysis. While the results obtained by rank correlation yield similarities, both methods have advantages. This study demonstrates that estimating betweenness centrality is meaningful and less computationally expensive, and can help us to understand the structural positions in the global supply chain network. The hypothetical extraction indicators can be easily computed using the betweenness centrality indicators' mathematical relationship. We conclude that the implementation of effective CO2-reduction polices through greener global supply chain engagement center around two key sectors, chemical and metal products from China, and their higher betweenness centrality should be strengthened. [ABSTRACT FROM AUTHOR]

•Construct a dual-perspective framework for measuring water use.•Define the water use fluctuating due to macroeconomic condition changes.•Introduce a new indicator to measure the rate of passive water use.•Estimate the key water use channels from a passive perspective through SPA.•Discuss the supply chain's intermediate sector's role for the water use., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

The primary resources of labor and capital are required for the industrial production process. It could be argued that industries cannot produce CO2 emissions unless primary resources are available. However, few studies have focused on estimating the role of primary resources in the production of industrial CO2 emissions. Furthermore, primary resource-induced inter and intra-sectoral linkages have received little attention. The purpose of this research is to estimate the role of primary resources in driving direct and net CO2 emissions (net CO2 linkages) in China, India, and the United States, all of which are at different stages of economic development. This study estimated the supply-induced CO2 emissions and linkages of China, India, and the United States using the Ghosh supply input–output model and by proposing some new supply-induced net emission linkage measures. The findings revealed that, when compared to fixed capital, labor produced more total and net carbon emissions in all three countries. The utility sector of “Electricity, gas, and water” (EGW) had the highest amount of labor and capital-induced emissions of all three nations. However, further decomposition of these emissions revealed the impact of different levels of economic development. In the services-based developed economy of the United States, input supplies from the sector of “Financial Intermediation and Business Activities” resulted in the highest emissions of the downstream sectors. The largest amount of downstream emissions was caused by supplies from the raw material supplier of “Mining and quarrying” in the industrial-based Chinese economy. While in India, which has a comparatively more agro-based economy, the “Agriculture” sector caused the greatest amount of downstream emissions. Our findings on supply-induced CO2 emissions of major countries at various levels of economic development can help guide both developed and developing economies to reduce industrial carbon emissions by efficiently managing and reallocating primary resource supplies to sectors.

Italy joined the so-called ‘Industry 4.0’ European framework in 2016, which designed and approved a national plan to regulate this key issue for regional development. To better support such a framework, the present study attempts to quantify the contribution of the Italian regions to the output formation process. More specifically, a multi-sectoral Input–Output (IO) model that supports national policies was proposed to cumulatively consider 29 industries that partition the Italian economy into representative branches at the level of administrative regions. Elementary input data were derived from the inter-sectoral table of the economy released by the Italian National Institute of Statistics (ISTAT). The economic outcomes of the Italian regions were estimated using a non-survey procedure, based on Flegg Location Quotients, to determine the upstream and downstream positions of each industry at country and regional levels. Indices grounded on the Hypothetical Extraction Method (HEM) further delineated the role each industry plays in the regional economy. The empirical findings of this study demonstrate how non-survey IO regionalization and the resulting industry-based indices provide appropriate knowledge for regional development policies.

Many governments face a trade-off between health and economy during the coronavirus pandemic. Social distancing and lockdown caused decline in gross domestic product of coronavirus affected countries. In this study, by using the input-output table of 2011, the hypothetical extraction method is used to extract 10 selected economic activities hypothetically from economic system and examine the direct and indirect effect of this extraction on Iran’s gross output. Results show that extraction of passenger transport, aviculture and clothing sectors result in the greatest reductions in gross domestic product. Furthermore, extraction of accommodation services, travel agency and tour operator activities and foodservice industry as representative of the tourism sector is able to reduce total output by almost one percent. Considering these ten selected sectors, 6.5 percent of Iran’s total economic output would be impacted by coronavirus outbreak. [ABSTRACT FROM AUTHOR]

The carbon emissions of sectors and households enabled by primary inputs have practical significance in reality. Considering the mutual effect between the industrial sector and the household, this paper firstly constructed an environmentally extended semi-closed Ghosh input–output model with an endogenized household sector to analyze the relationship between carbon emissions and the Chinese economy from the supply-side perspective. The structural decomposition analysis and the hypothetical extraction method were remodified to identify the supply-side driving effects of the changes in carbon emissions and investigate the net carbon linkage. The results show that the electricity, gas, and water supply sector was the key sector with the highest carbon emission intensity enabled by primary inputs. The household sector had an above 93% indirect effect of the enabled intensity, with its enabled intensity dropping significantly by more than 55% from 2007 to 2017. The operating surplus and mixed income caused 3214.67 Gt (34.17%) of the enabled emissions in 2017. The supply-side economic activity, measured by the value added per capita, was the main factor of the carbon emission growth, mainly attributed to the development of the manufacturing sector and the electricity, gas, and water supply sector. The emission intensity and allocation structure both brought a decrease in carbon emissions. The electricity, gas, and water supply sector and the manufacturing sector were the major sources of the supply-induced cross-sectoral input emissions, while the commercial and service sector and the household sector were the top source of supply-induced cross-sectoral output emissions. This paper sheds light on the policies of the carbon emission abatement and the adjustment of the allocation structure from the perspective of supply.

Households play a vital role in producing industrial emissions through final-consumption. As a result, related literature focuses mainly on the drivers of household demand embedded industrial production (DEIP) emissions. Recent evidence on industrial emissions, however, shows that targeting industrial carbon consumers and their final demand, particularly from households, is much more effective. Unfortunately, there isn't much literature on household demand embedded industrial consumption (DEIC) emissions. The aim of this study is to develop a model that can help analyze the impact of key drivers on household DEIC emissions. The model is applied to Chinese urban and rural household DEIC emissions. Additionally, the study also employees Regional Sensitivity Analysis to rank and map the most influential factors of Chinese rural and urban DEIC emissions. Results showed that for both rural and urban households, income/capita with an average impact of 35 Mt and 111 Mt was the main driver of DEIC emissions growth. Income/capita was also the most sensitive factor for rural and urban DEIC emissions. The consumer industry's Leontief effect (technology) had the second largest positive effect on both rural and urban household DEIC emissions. However, for rural and urban households, the second most sensitive factors were different. Emission intensity for rural households and consumption tendency for urban households had the greatest negative effects on respective DEIC emissions. Finally, the article discusses results, highlighting policy implications for reducing rural and urban household DEIC emissions.

With the rapid growth in economic and technological development, the linkage of the construction industry with the economy has changed in the past decades, which may have generated corresponding changes in other industries. This study sheds new light on the measurement of structural changes in the inter-industrial linkages of an industry using the Leontief model and the Ghosh model based on the hypothetical extraction method. The Australian national input–output tables provided in the World Input–Output Database are employed as an empirical study exploring the influence of construction linkages on other industries' production input and output. The results indicate that construction effects have become weaker in relation to promoting economic growth, although the mining and quarrying industry and some service industry activities demonstrate strong and positive backward and forward linkages with the construction industry in Australia. This research provides an approach for measuring corresponding changes in other industries caused by one industry's inter-industrial changes. [ABSTRACT FROM AUTHOR]

This paper investigates whether the recent rise in tariffs on goods produced in China will lead processing trade manufacturing plants now located in China to delocate to the U.S. By using a hypothetical extraction method and examining the global value chains of income, we compare the factor payments in the Chinese and U.S. manufacturing sectors. Our estimates indicate that the average tariff rate necessary to move the processing trade firms is 48.15%, i.e. well above the current 25% rate. However, the average tariff rate needed for shifting China's processing plants to Mexico decease to 20.32%. [ABSTRACT FROM AUTHOR]

Copyright of Research of Environmental Sciences is the property of Research of Environmental Sciences Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Agriculture has a substantial environmental impact. However, little research has been conducted on the relationship between agriculture’s environmental impacts and linkages, particularly for the key agriculture-based Pakistani economy. Additionally, the literature on environmental linkages rarely estimates multiple types of linkages in a single study. This study fills these critical research gaps. The study estimates the land, water, nitrogen, and CO2 impacts and linkages of Pakistan’s agriculture sector using an input–output model and the hypothetical extraction method. The results indicated that agriculture directly accounted for approximately 27%, 93%, 92%, and 1% of Pakistan’s total sectoral land, water, nitrogen, and CO2 impacts (LWNC), respectively. While the sector indirectly contributed almost 2%, 0.3%, 0.4%, and 0.4% of Pakistan’s total LWNC. The bulk of direct LWNC impacts were caused by agricultural purchases from downstream sectoral importers. The majority of the indirect LWNC impacts were induced by agriculture’s re-imports. The agricultural purchases from the downstream sector of “Food and Beverages” induced the greatest environmental impact. To ensure sustainable agriculture, particularly in Pakistan, the agriculture sector’s direct and indirect environmental impacts should be reduced not only through better management practices and technology, but also by focusing on intermediate sectoral sources of direct and indirect environmental impacts.

The hypothetical extraction method (HEM) has been widely used to measure interindustry linkages and the importance of industries. HEM considers the hypothetical situation in which a certain industry is no longer operational. HEM was developed for national economies, using national input–output tables. When performing HEM, it is assumed (often implicitly) that the input requirements that were originally provided by the extracted industry are met by additional imports in the post-extraction situation. Applying HEM to global multiregional input–output tables then causes serious problems. It is no longer sufficient to assume that the required inputs are imported. Instead, it is necessary to indicate explicitly how much is imported from each origin to replace the original inputs. Our adaptation of HEM is the global extraction method (GEM). As an illustration, GEM is applied to the extraction of the motor vehicle industry in China, the US, and Germany, using the 2014 WIOD input–output table. [ABSTRACT FROM AUTHOR]

Inter-industrial carbon linkage analysis tells us about the transfer of CO 2 amongst sectors of a nation. Hypothetical extraction model which removes a target sector and compares the difference between actual and theoretical economies is a popular model for linkage analysis. Regardless of mounting evidence favoring simultaneous application of both Ghosh supply and Leontief demand for forward and backward linkages. Related studies have mostly calculated both upstream and downstream carbon linkages using only demand-driven Leontief inverse model. This research estimates inter-sectoral carbon linkages of Turkey from both demand and supply. Electricity, gas, and water had the highest total demand and supply carbon linkage. Extraction of backward and forward linkages of mixed services have the highest demand pull and supply push impact on rest of the blocks. It also had the highest amount of net pulled and pushed emissions. Production block had the highest intra-sectoral purchase emissions while electricity, gas, and water had the highest internal sales emissions. Wind and Solar PV are the cleanest energy sources for Electricity, gas, and water supply. A carbon demand and supply based policy diversifies emission responsibility and encourages mitigation of a block's entire upstream, downstream and intra-sectoral carbon chain. Image 1 • This study presents different dimensions of Turkey's inter-sectoral carbon linkages from demand and supply. • Restructures the modified hypothetical extraction method by applying Leontief inverse and Ghosh supply models. • Secondary and tertiary blocks pulled the highest net emissions; they also lead the intra-block carbon sales and purchases. • Primary and tertiary pushed the highest amount of emissions. • Wind and Solar PV are amongst the most feasible and cleanest energy sources for the 'Electricity, Gas and Water Supply.'. [ABSTRACT FROM AUTHOR]

Abstract As significant contributors to global carbon dioxide (CO 2) emissions, the international construction sector is under great pressure to mitigate CO 2 emissions and slow global warming more aggressively. The aim of this study is to measure and compare the sectoral CO 2 emission linkages and their structures in the construction sectors of 41 countries over 1995–2009 by combing a hybrid multi-regional input–output (MRIO) model and the hypothesis extraction method. The backward and forward CO 2 emission linkages indicate that the international construction sector plays a significant role in importing CO 2 emissions from upstream industries, while the export of CO 2 emissions to downstream industries is relatively minimal. Four fundamental linkage elements show that the net backward CO 2 emission linkages account for the largest proportion, followed by the mixed and net forward CO 2 emission linkages, while the mixed backward CO 2 emission linkages are relatively small. The leading CO 2 emission inflows are from the energy, resource and raw-material sectors. The outflows from the construction sector are mainly to the real estate and public utilities sectors. Based on these findings, the paper puts forward countermeasures for the global construction sector to improve energy efficiency, promote industrial structure upgrading and improve the policy system for greenhouse gas emission reduction. [ABSTRACT FROM AUTHOR]

Abstract The objective of this study is an analysis of the relationship between the transportation sector and the rest of the Chinese economy as it impacts the generation of carbon dioxide (CO 2) emissions. Using data from input-output tables of China for 2002, 2007, and 2012, the hypothetical extraction method (HEM) was used to quantify these inter-sectoral linkages and decompose the CO 2 emissions associated with each transport modal sub-sector (i.e. the rail, road, water, and air sub-sectors). The transport services required by other sectors of the economy are found to induce more carbon emissions than the emissions associated with transportation's own final demands. As the principal CO 2 emitter, the road sub-sector's export of CO 2 emissions increased substantially from 11.31 to 55.22 million tons (Mt) between 2002 and 2012. In contrast, technological advances within the rail sub-sector resulted in a net decrease in exported CO 2 emissions, from 9.99 Mt to 5.16 Mt. Taken as a whole, the transportation sector transferred large CO 2 emissions through the economy's various supply chains, notably exporting to the service (63.78 Mt in 2012) and construction (83.88 Mt in 2012) sectors while importing a large amount of CO 2 emissions from the nation's energy producing industry (223.52 Mt in 2012). Highlights • An analysis of CO 2 emissions linkages in the Chinese transportation sector using HEM. • An inter-temporal comparison analysis for the years 2002, 2007 and 2012. • Identification of the CO 2 emissions for each transportation mode in the economy. • The rail, road and air sub-sectors were found to be CO 2 emissions exporters in 2012. [ABSTRACT FROM AUTHOR]

The effects of export goods on CO 2 emissions in China were calculated using input-output analysis via the hypothetical extraction method (HEM). The seven largest export partners of China were taken into account for the analysis: the US, Japan, South Korea, Germany, India, the UK and the Netherlands. First, using input-output analysis, the effects of CO 2 emissions were allocated between the non-tradable goods, total export goods, exported final goods and exported intermediate goods sectors. Then, using a weighted multipliers approach, efficiency in CO 2 emissions was allocated among the sectors. It was found that although non-tradable goods caused the highest CO 2 emissions, export goods, especially intermediate goods showed the largest growth in emissions. In addition, export goods contributed more to emissions efficiency. Second, the HEM was implemented to explore which countries had significant effects on both emissions and emissions efficiency. The US was the largest source of CO 2 emissions in China in terms of final goods. Nevertheless, the US also increased the role of exported intermediate goods on emissions. It was also an important country in stimulating efficiency in CO 2 emissions. Hence, China does not have a chance to decrease its export performance against the countries such as the US, as their demand is the source of efficiency in CO 2 emissions. However, it can focus on exported intermediate goods to mitigate emissions, and take the US into account for new policies. • The results revealed that US trade is the main factor in stimulating CO 2 emissions in China, while nevertheless contributing a great deal to efficiency. • Reducing trade with the US could cause China to export more products to other countries that do not contribute to efficiency. • Although domestic consumption contributes significantly to CO 2 emissions, the effect of export goods thereon increased more than that of non-tradable goods. • One suggestion might be that China should change its growth model to become comparatively more balanced in international trade. • The most important policy for the country would be to follow a more environmentally friendly production process. [ABSTRACT FROM AUTHOR]

Considering the importance of the wood and paper industry for the Iranian economy and interaction and linkages between the wood and paper sector with other economic sectors. In order to do so, Input-Output table for 1380 and hypothetical extraction method has been used. Calculation of sensitivity index of publication as well as the wood and paper industry publishing strength index respectively with figures 451.2 and 378.1 suggests that this industry ranked first and third release power sensitivity in between sections is And this means that the wood and paper industry, more than the average total other sections with the other categories in this connection and communication as well as alike and more balanced sections. In the case of the hypothetical extraction method from the perspective of the production output decreased the amount of million 112345678 (Leontief pattern) and 132456789 cents (gosh pattern). In terms of stretching the production ranking 19 of 34 of its assigned section.