Final Demand Effect Research Articles

Structural emission reduction in China's industrial systems and energy systems: an input-output analysis.

China is committed to achieving the goals of "peak carbon and carbon neutrality," and the carbon dioxide emissions generated in the energy utilization process mainly come from industrial and energy systems. This paper used structural decomposition analysis (SDA) and input-output analysis to study the structural emission reductions in China's industrial and energy systems in 2007-2015. The results revealed that the final demand effect was the main factor promoting the growth of energy-related CO2 emissions and that the energy intensity effect played a weak role in promoting the growth of energy-related CO2 emissions. However, the energy structure effect and input structure effect reduced energy-related carbon emission growth. We found that for energy systems, the emission reduction effects of blast furnace gas, raw coal, refinery dry gas, and natural gas were obvious, while those of crude oil, gasoline, fuel oil, and kerosene were not obvious. For industrial systems, the tertiary industry played a major role in the final demand effect, followed by the secondary industry, and the primary industry in turn. This paper provides a theoretical basis and practical guidance for the carbon peak and carbon neutrality goals of China's energy systems and industrial systems.

How can Germany reduce production-based and consumption-based carbon emissions? A decomposition analysis

Developing more effective mitigation strategy to achieve the carbon reduction targets set by the Paris Climate Agreement requires to more comprehension of the driving factors of the decline in carbon emissions. Production-based and consumption-based carbon emission in Germany declined by 2.8% and 8.5% from 2000 to 2015, respectively. In this work, the key drivers behind decline in carbon emission in Germany is explored by combing the multi-regional input-output and structural decomposition analysis. The results show German carbon emissions has been undergoing structural changes. Although its production-based and consumption-based emission declined, German carbon footprint embodied in exports increased, and its share in the production-based carbon footprint also increased. Germany's embodied emission exports to emerging countries increased, although Germany's embodied carbon exports remained mainly concentrate in developed countries, especially in EU (over 40%) and USA (∼10%). The decomposition results revealed that economic scale effect was the leading contributor to increase in carbon footprint in Germany's trade, followed by the industrial structure effect of final demand. The effects of production structure on German's exports was less than its imports. The carbon intensity coefficient was the most significant factor of decreased carbon emission. Generally, the decreasing effect of carbon intensity coefficient exceeded the increasing effect of economic scale, which lead to carbon reduction. The example of Germany shows that improving carbon emission efficiency and optimizing production structure can reduce carbon emission without lowering economic growth.

Analysis of the Structural Decomposition of the Textile-Clothing Industry in Bangladesh

Purpose: This paper aims to introduce the technology’s role and the final demand in the textile clothing industry’s growth path (TCI) of Bangladesh. Methodology: This study applies structural decomposition analysis in the input-output framework to measure Bangladesh’s textile–clothing industry structural changes. Structural decomposition analysis is also known as growth accounting in literature. Findings: This paper finds that, from 1975 to 1995, the TCI has grown due to huge domestic demand, from 1995 to 2015, this industry has grown due to export expansion. The technology was never a key factor over low–cost labor for the development of TCI in Bangladesh. Implications: For the sustainable development of the TCI in Bangladesh, domestic demand expansion is significant. Private and public policies should reflect this expansionary (domestic demand expansion) strategy. Originality: Previous studies on the TCI were mainly descriptive; there was no decomposition analysis in the input-output framework. Moreover, this paper decomposes the growth of the TCI into technical effect and final demand effect, which are new in the ready-made garment industry of Bangladesh.

Analysis of driving factors on China's industrial solid waste generation: Insights from critical supply chains

Industrial solid waste (ISW) poses a huge potential threat to human health and the environment. To prevent pollution at its source, it is necessary to analyze the socioeconomic drivers and identify the key supply chains that cause changes in ISW generation. In this study, based on monetary input–output tables (MIOTs) in China from 2011 to 2015, structural decomposition analysis (SDA) was used to study the influence of socioeconomic drivers on common industrial solid waste (CISW) and hazardous waste (HW) generation. Structural path decomposition (SPD) was used to further trace the effects of drivers at the supply chain level and obtain more meaningful results for policy formulation. Economic expansion was found to play the most crucial role in the increase in total ISW generation while the reduction of generation intensity effectively slowed the growth trend. From the final demand perspective, fixed capital formation contributed the most to ISW generation growth, accounting for 65.05% of the total final demand effect. Construction was the primary trigger. For CISW, the supply chain with the greatest overall influence was “metal ore mining industry → fixed capital formation” (including intermediate consumption of metal smelting, general and special machinery, and construction), reflecting how fixed capital formation indirectly affected the metal ore mining industry. The supply chain with the greatest influence on HW generation was “paper industry → exports.” Based on the findings, corresponding policy adjustments are proposed.

Research on driving factors of China’s carbon emissions based on structural decomposition

After further processing the input-output tables of 2007, 2012 and 2017, the carbon emissions are decomposed into four driving factors: energy intensity effect, Leontief technology effect, final demand structure effect and final total demand effect through IO-SDA model. The results show that the energy intensity effect has a significant negative effect, which is the main factor to promote the reduction of carbon emissions. The Leontief technical effect and the final total demand effect are positive effects, and the total final demand effect is the main factor leading to the increase in carbon emissions, and the effect of the final demand structure effect is not significant. In addition, the results of the influence coefficient and the inductance coefficient show that: metal smelting and rolling manufacturing, petroleum processing and coking and nuclear fuel processing, coal mining and processing, and oil and gas mining and processing industries are high-energy-consuming industries, but the status of the basic industry makes it possible to formulate energy-saving policies only in terms of technological progress.

Energy carbon emission reduction of China’s transportation sector: An input–output approach

It is worthwhile to carry out carbon emission reduction of transportation, which is an important sector of energy consumption. Thus, we used the expanded structural decomposition analysis model and input–output analysis to investigate the structural emission reduction of transportation in China. The results reveal that within the research interval, (1) the energy intensity effect (EIE) was a major factor for reducing carbon emissions from China’s transportation sector, which is caused by the improvement of energy efficiency. However, the input structure effect (ISE) on emission reduction is not apparent. Therefore, the utilization efficiency of transportation in various industries has not been significantly optimized. (2) The final demand effect (FDE) is the main determinant of carbon emission growth in transportation sector due to the steady growth of demand for transportation across all industries. Simultaneously, secondary industries play a major role in the FDE, followed by tertiary and primary industries. However, the direct consumption coefficient of primary and tertiary industries to the transportation sector demand is lower than that of the secondary industries (e.g., heavy industry). Therefore, the dynamic optimization of industrial structure is conducive to reducing carbon emissions caused by FDE. (3) The energy structure effect (ESE) is shown to restrain the growth of carbon emissions with an increasing trend, caused by the increase and decrease in the proportion of low-carbon and high-carbon energy consumption structure, respectively, in the energy supply side of transportation sector. Diesel oil, gasoline, kerosene, and liquefied natural gas were the main contributors to carbon emission reduction in ESE, while raw and cleaned coal did not play a role in reducing carbon emissions in ESE. This study can provide practical guidance for China’s transportation sector to implement emission reduction more accurately based on the energy type and industry level.

Dynamic evolution analysis of the factors driving the growth of energy-related CO2 emissions in China: An input-output analysis.

In recent years, the global greenhouse effect caused by excessive energy-related carbon emissions has attracted more and more attention. In this paper, we studied the dynamic evolution of factors driving China's energy-related CO2 emissions growth from 2007 to 2015 by using energy consumption method and input-output analysis and used the IO-SDA model to decompose the energy carbon emissions. Within the research interval, the results showed that (1) on the energy supply-side, the high carbon energy represented by raw coal was still the main factor to promote the growth of energy-related CO2 emissions. However, the optimization of energy consumption structure is conducive to reducing emissions. Specifically, the high carbon energy represented by raw coal exhibited a downward trend in promoting the increment of energy-related CO2 emissions, while the clean energy represented by natural gas showed an upward trend in promoting the increment of CO2 emissions. It is worth noting that there is still a lot of room for optimization of China’s energy consumption structure to reduce emissions. (2) On the energy demand-side, the final demand effect is the main driving force of the growth of carbon emissions from fossil energy. Among them, the secondary industry plays a major role in the final demand effect. The "high carbonization" of the final product reflects the characteristics of China's high energy input in the process of industrialization. At the same time, since the carbon emission efficiency of the tertiary industry and the primary industry is better than that of the secondary industry, actively optimizing the industrial structure is conducive to slowing down the growth of carbon emission brought by the demand effect. (3) The input structure effect is the main restraining factor for the growth of energy carbon emissions, while the energy intensity effect has a slight driving effect on the growth of energy carbon emissions. The results show that China's "extensive" economic growth model has been effectively reversed, but the optimization of fossil energy utilization efficiency is still not obvious, and there is still a large space to curb carbon emissions by improving fossil energy utilization efficiency in the future.

Drivers of dynamic evolution in provincial production water usage: perspective of regional relevance.

With the advancement of industrialization and urbanization, the issue of water shortage has become a bottleneck for China's economic development. Based on the structural decomposition analysis and multi-regional input-output tables of China in 2002 and 2012, this paper explores the drivers of the change in China's production water usage from the regional relevance perspective. Results show a significant increase in China's production water usage during the study period. The relationship between production water usage and per capita GDP shows an inverted U-shaped curve, and the economic scale by provinces has been improved, while the trend of production water usage differs. There are rapid increases in production water usage in economically developing provinces, while it is falling sharply in developed provinces. The crucial factors promoting its growth are changes in consumption level, population scale, and regional economic patterns. The technical effect is the most important factor in curbing the growth, followed by effects of final demand sectoral and distribution structure. The provinces and sectors with more production water usage shows higher technical and final demand effects. Therefore, it is necessary to promote water-saving activities, enhance the water-saving technical effect, and optimize final demand structure to promote economic growth with low-water usage.

Evolutionary path and driving forces of inter-industry transfer of CO2 emissions in China: Evidence from structural path and decomposition analysis

Carbon dioxide (CO2) emissions are currently a hot topic of global concern. It is of great significance for reducing CO2 emissions to fully understand the transfer pattern of CO2 emissions among industries and the key factors affecting CO2 emissions. This paper uses the structural path analysis model to explore deeply the main paths of inter-industry transfer of CO2 emissions in China from 2002 to 2017 and applies the structural path decomposition model to analyze the main factors affecting CO2 emissions in specific paths from the perspectives of CO2 emission intensity, intermediate product input structure, final demand structure, per capita final demand, and population size. The results show that: (1) China's CO2 emissions increased from 3500.41 million tons (Mt) in 2002 to 9475.66Mt in 2017, with an average annual growth rate of 6.86%. The growth rate of China's CO2 emissions slowed down after 2012. (2) Non-metallic mineral industry\\electricity industry\\metal products industry→(intermediate sector)→investment demand and electricity industry→(intermediate sector)→consumption demand are two types of key paths that affect China's CO2 emissions, and these paths remain basically unchanged during the study period. (3) The CO2 emission intensity effect is the main factor in restraining the growth of emissions, and the per capita final demand effect and intermediate product structure effect are the main promoting factors. The effect of driving factors on different industrial paths is different, and the offsetting effect of the driving factor in different paths may lead to the insignificant effect of this factor in the overall decomposition. To effectively reduce CO2 emissions, China should focus on specific industrial paths and implement upstream and downstream comprehensive governance to achieve a low-carbon industrial chain throughout the whole process.

India’s renewable energy: New insights from multi-regional input output and structural decomposition analysis

As a developing country, Indian energy scenario has perennially been plagued by problems like energy deficit, threats to energy security and low energy efficiency. Raising the supply of renewable energy is the key way for India to solve this dilemma. The formulation of effective renewable energy policies requires a comprehensive understanding of the evolution and drivers of the renewable energy consumption in India. Based on multi-regional input-output model (MRIO) and structural decomposition analysis (SDA), this study identified India’s renewable energy consumption patterns and its transition drivers. The results shown that there was not much difference between the renewable energy consumption of India in the production-based and consumption-based, both of which were dominated by domestic consumption. However, the development of globalization had made the influence of international trade on India ‘s renewable energy consumption no longer negligible. Developing countries had gradually become the main destinations and sources of India’s exported and imported renewable energy. From the perspective of driving force, in terms of domestic consumption, the upward influence of the unit growth of India’s per capita final demand was weakening. As far as the renewable energy embodied in exports and imports, the energy intensity effect and the per capita final demand effect of developing countries had more contributions compared with developed countries. Therefore, India should attach more attention to the cooperation with developing countries in the field of renewable energy, and increase the efficiency and share of renewable energy consumption to offset the weakening of demand-driven.

Energy-related CO2 emissions and structural emissions’ reduction in China’s agriculture: An input–output perspective

The greenhouse effect caused by excessive carbon emissions seriously threatens the sustainability of the global economy. Although the secondary and tertiary industries are the principal contributors to CO2 emissions’ growth, the continuous and stable development of agriculture also intensifies carbon emissions to a certain extent. Based on this, this paper uses the input–output method, an energy consumption model, and structural decomposition analysis to study energy-related CO2 emissions and structural emissions’ reduction in China’s agriculture from 2007 to 2017. The research results show that (1) In 2007–2017, the input structure effect and the energy intensity effect inhibited the growth of energy-related CO2 emissions in China’s agriculture, with the reduction effect of energy intensity effect being the more prominent, whereas the final demand effect and the energy structure effect contributed to promoting China’s agricultural energy-related CO2 emissions’ growth, with the final demand effect being the greater promoting factor. (2) The energy structure effect failed to reduce energy-related CO2 emissions in China’s agriculture because the optimization of consumption structure is still not obvious on China’s agricultural supply-side. The share of energy consumption from high-carbon fuels such as raw coal, coke, and other washed coal has increased, rather than decreased, and the optimization of low-carbon energy sources such as natural gas is still slow, thus limiting the emissions’ reduction effect in the energy structure. (3) The reason why the final demand effect has promoted the growth of energy-related CO2 emissions in China’s agriculture is the expanding demand for agriculture in the entire industrial system. Specific to each industry, the secondary industry has played a major role in the final demand effect, accounting for more than 50% of the final demand effect, followed by the primary and the tertiary industries. Finally, this paper provides a theoretical and practical basis for accurately and efficiently implementing emissions’ reduction from the perspectives of the industrial system on the demand-side and the energy system on the supply-side and also in China’s agriculture.

Spatial differences in energy performance among four municipalities of China: From both the aggregate and final demand perspectives

City, which consumes the majority of the total energy consumptions, has great influences on the national energy issues. As the widespread spatial differences, a quantitative energy analysis among multi-city allows exploring the targeted and distinguishing energy policy implications at the city level in China. Considering the significant role of final demands, the input-output model and spatial structural decomposition analysis were adopted to evaluate the energy performances and quantify the spatial differences. In 2012, the spatial differences in the energy consumptions were distinct, with the greatest gap between Shanghai and Chongqing, which were mainly driven by the domestic Leontief structure effect and the total final demand effect. In particular, the spatial differences in the embodied energy by net domestic outflow were remarkable. For the relative energy efficiency, Beijing was discovered the best, followed by Tianjin, Shanghai and Chongqing. The spatial differences in their energy intensity were primarily influenced by the energy intensity effect and the domestic Leontief structure effect. In addition, the spatial differences in the aggregate embodied energy intensity by domestic investment were prominent. Inspired by the results, the structure adjustments with respect to the production and final demands and regional cooperation are strongly advised at the city level.

Structural decomposition of variations of carbon dioxide emissions for the United States, the European Union and BRIC

Abstract The historical responsibility of the countries that have promoted the accumulation of carbon dioxide since the industrial revolution, mainly the United States, Russia and the European Union, and the responsibility of the increase in current emissions of emerging countries like Brazil, India and China, determine the moral duty to reduce and adapt their economies to solve the problem of climate change. Therefore, it is important to measure the variations in carbon dioxide emissions from these countries and the effort made to reduce them. The objective of the study was to decompose the variations of carbon dioxide emissions into technological and final demand effects using the input-output matrix of the United States, the European Union (EU, 27 countries), Brazil, Russia, India and China (BRIC). The results showed that the US and EU decreased their emissions respectively by 12.4% and 5.9%. The US achieved emission reductions mainly due to the intensity effect (sector’s own emissions) while the EU by technology effect (production chain’s emissions). It was caused by the adoption of new technologies and modifications of the energy matrix. Brazil, Russia, India and China (BRIC) respectively increased their emissions by 13.3%; 2.9%; 68.5% and 121.5%. The BRIC showed efforts to adopt new technologies to reduce emissions. However, changes in the structure and volume of final demand caused positive and superior effects to the technological effects of increasing emissions, especially in India and China.

German's oil footprint: An input-output and structural decomposition analysis

Abstract It is generally thought that the country with net exports in goods is also a net exporter of energy embodied in goods. In this work, we report a paradox phenomenon, which shows that Germany was a net goods exporter but also a net importer of embodied oil. Based on the multi-region input-output model and structural decomposition analysis, this paper comprehensively analyzed the changing trend and main driving factors of oil footprints in German trade. The results showed that Germany's embodied oil exports increased by 35.06% with the expansion of trade scale, and Germany's net imports of embodied oil fell by 45.49% during the study period. Although the focus of embodied oil transfer in trade was EU countries, the embodied oil trade volume between Germany and developing countries, especially China, grew rapidly. From sectoral level, heavy manufacturing and transport industry dominated more than 70% of the Germany's embodied oil trade. The decomposition analysis showed that the scale effect of final demand was the main factor that contributed to the growth of oil footprints in Germany's international trade, which offset the inhibition of oil consumption intensity. The effect of production structure played an important role in the embodied oil trade, and the low-oil-intensive industrial structure was the main reason why Germany was a net importer of embodied oil.

Determinants of net carbon emissions embodied in Sino-German trade

Abstract The existing research on carbon emissions embodied in trade has been concentrated between net importing countries and net exporting countries. Few study has been conducted to analyze carbon emissions embodied in trade between net exporting countries. To fill the research gap, this work systematically investigated the net carbon emissions embodied in trade between the largest net exporter of developing countries (China) and the largest net exporter of developed countries (German) based on the non-competitive input-output analysis. And the structural decomposition analysis was used to study the driving factors effecting the change of net embodied carbon emissions in Sino-German trade. The results show the net carbon emissions embodied in Sino-German trade increased significantly with the sharp increase of net trade volume after China's accession to the World Trade Organization. Carbon transfer through trade was mainly concentrated in the carbon-intensive industrial sectors in Sino-German trade. This phenomenon was attributed to the differences in the trade structure and the production efficiency between China and Germany. The decomposition analysis shows China's intermediate input structure effect and the country structure effect of Germany's final demand were the leading contributors to growth in net carbon emission in Sino-German trade, which mainly was offset by China's carbon intensity effect. Finally, some policy implications are offered.

SOURCES OF ECONOMIC GROWTH AND CHANGES IN ENERGY CONSUMPTION: EMPIRICAL EVIDENCE FOR TAIWAN (2004-2016)

Since the 1990s, Taiwan has promoted the upgrading of industrial structure, and the financial crisis has brought about major economic shocks. After Taiwan became a WTO member in 2002, the total trade volume increased significantly under the trade liberalization economic system. The trade sector has become the main source of Taiwan's economic growth. As energy consumption expands with economic growth, the instability of international energy prices has become an important factor hindering Taiwan's future economic development. Taiwan’s energy demand is over 99% dependent on imports, making Taiwan’s economic growth and energy consumption really closely related. This study has found that the source of growth has transformed from domestic final demand effect and exports effect to technical coefficients effect and self-sufficiency Coefficients effect. The financial crisis has increased the “self-sufficiency” coefficient effect and the technical coefficient effect, and all other industries except the “agricultural sector” have shown significant growth. On the other hand, the source of energy consumption has changed after the financial crisis. This also confirms that Taiwan's economic growth is closely related to energy consumption, indicating that energy shortage has indeed had an important impact on Taiwan's economic development.

Assessing net energy consumption of Australian economy from 2004–05 to 2014–15: Environmentally-extended input-output analysis, structural decomposition analysis, and linkage analysis

This paper provides a comprehensive analysis of Australian net energy consumption between 2004–05 and 2014–15. Results from environmentally-extended input-output (EEIO) analysis show that the Transport sector has the largest direct effect on net energy consumption in industrial sectors, which decreased by about 35% for net energy consumption per million $AUD in the period. The Export sector has the largest direct net energy consumption while Households consumption results in the largest net energy consumption embodied in different categories of Final demand. The structural decomposition analysis (SDA) decomposes the change of net energy consumption into five drivers, in which net energy intensity mainly reduces Australian net energy consumption by about 8000 Petajoules, while the level effect of Final demand increases it by about 10,000 Petajoules. Analysis of forward and backward linkages highlights the Manufacturing sector as the key industrial sector with the largest energy consumption reduction potential via minor changes in its input and Final demand. This indicates that more attention should be given to the reduction of energy demand from the consumption patterns of Households consumption, the improvement of energy intensity, and the application of cleaner technologies in the Transport and Manufacturing sectors. The Australian Environmental-Economic Accounts is combined with Australian input-output tables to construct the EEIO tables for net energy consumption. The combination of economic and environmental data sets provides a depth of understanding their potential to inform environmental policy decisions. The novelty of the research is the combination of economic and energy data sets, the application of EEIO model, the implementation of the additive SDA method, and the use of forward and backward linkages for the Australian energy system.

Driving forces of national and regional carbon intensity changes in China: Temporal and spatial multiplicative structural decomposition analysis

With the increasing pressure on reducing CO2 emissions, China promised to reduce carbon intensity by 60–65% by 2030 from 2005 levels. This study aims at identifying the driving forces of national and regional carbon intensity changes in China at multiple levels by a newly extended multiplicative structural decomposition analysis. Attribution analysis is further adopted to identify sectors with large intensity-reduction potential. National and regional carbon intensity changes during 2007–2012 are decomposed into three determinants: intensity (or efficiency) effect, input structure effect and final demand effect. Temporal decomposition results suggest that 29.0% decline of national carbon intensity is mainly due to intensity effect, while input structure and final demand effect drive the increment of national carbon intensity. Eight regions are divided into two groups: carbon intensity in Northwest, South Coast and Northeast increased due to input structure and final demand effect; carbon intensity in other regions decreased due to intensity effect and final demand effect. Investment and export are the dominant final demand categories to carbon intensity decline in most regions. Spatial decomposition results reveal the huge contribution discrepancy of driving forces among 30 provinces, and 30 provinces are accordingly classified into four groups. For most regions, simultaneously optimizing input structure and final demand are preferred in sectors with large intensity-reduction potential like Mining, Manufacture, Metals and metal productions and Production and supply of electricity, gas and water. Targeted intensity-reduction strategies at multiple levels are suggested.

What makes the difference in construction carbon emissions between China and USA?

It is commonly acknowledged that China and USA are the two largest carbon emitters in the world, but the differences in the emissions between the two countries is significant. This paper reveals the carbon emissions difference in the context of construction industry. The drivers contributing to the difference are analyzed by the structural decomposition analysis method. The results suggest that the construction carbon emissions in China are much larger than USA, and the difference in the emissions between China and USA increased by 439.8% between 1995 and 2009. The results also demonstrate that the total final demand effect contributed most to narrowing the emissions difference, whilst the final demand ratio effect had the largest enlarging impact on the difference. The second significant factor for the enlargement of the emissions difference between the Chinese and the US construction industry was the production structure effect, followed by the energy intensity effect and the carbonization factor effect. It is noteworthy that the carbonization factor effect has surpassed the energy intensity effect since 2008. This study can provide the Chinese policy makers with a systematic understanding on which part of policy should be concentrated in order to reduce the construction carbon emissions.

Structural decompositions of energy consumption between 1995 and 2009: Evidence from WIOD

Energy is key to achieving sustainable development. This paper explicitly distinguishes between the supply side of energy consumption and demand side of energy consumption, and investigates the factors that affect the energy consumption across economies. Using data from the World Input-Output Database (WIOD), this paper decomposes the relative changes of energy consumption into intensity effect, production structure, structural change in final demand, total final demand effect and household consumption. Then it further decomposes production structure into inter-industry structural effect, and trade effect in intermediate inputs. Overall, energy consumption growth is mainly driven by total final demand (55.04% increase at the world level), but can be significantly reduced by intensity effect due to technological change (21.02% decrease at the world level). There is heterogeneity of structure related effects across economies and within the same economy in both aspects of energy consumption. In addition, the trade effect and household effect are relatively small. This paper provides an empirical framework for analyzing energy consumption in a globalizing world, and suggests tailored and integrated energy policies.