Input-output Structural Decomposition Analysis Research Articles

Impact of population ageing on carbon emissions: A case of China's urban households

Ageing can have a considerable ripple effect on carbon emission by affecting production and consumption of economic system. Based on an input-output structural decomposition analysis, this study analyses the impact of ageing on urban residents’ carbon emissions in China from 2002 to 2007 and 2007 to 2012, and explores the regional heterogeneity and temporal uncertainty of the impact. At the national level, older adults slowed the growth of direct carbon emissions in both periods, because their per capita energy consumption fell more in the first period, then switched from coal to gas and electricity consumption. They contributed less to the growth of indirect carbon emissions in both periods due to the minimum increase in their per capita consumption among all age groups. Moreover, the impact of ageing on carbon emissions had clear regional heterogeneity. This study is beneficial to provide suggestions regarding carbon emission reduction and adapting to demographic changes.Ageing; Household consumption; Carbon emissions; Input-output; Structural decomposition analysis.

Energy use and energy-related carbon dioxide emissions drivers in Egypt's economy: Focus on the agricultural sector with a structural decomposition analysis

Investigating drivers of energy use and its associated CO2 emissions changes is important for sustainable development. Using input-output structural decomposition analysis, this paper decomposed the energy use and resulting CO2 emissions drivers of changes in Egypt's wide economy, particularly in its agricultural sector, between 1972 and 2014. Fuel sources dominating energy use and energy-related CO2 emissions in the agriculture sector were explicitly identified. Affluence and demographic effects were the dominant drivers at both investigation levels. Household and government final consumption changes and exports expansion were important determinants behind changes in energy use and resulting CO2 emissions at the aggregate level from the final demand destination perspective. In the agricultural sector, petroleum and oil were the dominant fuel types. The technological effect was the main driver restraining energy use growth at the aggregate level. However, technological improvements have not been sufficient to make up for the evolving economy and consumption levels. Conversely, technological changes adversely impacted energy-related CO2 emissions at the economy-wide level, and both considered environmental indicators in the agricultural sector. Overall, upgrading technology and improving the final demand structure will be critical for Egypt to promote decoupling in the future.

Carbon emissions in China's thermal electricity and heating industry: An input-output structural decomposition analysis

CO2 emissions from China accounted for 27 per cent of global emisions in 2019. More than one third of China's CO2 emissions come from the thermal electricity and heating sector. Unfortunately, this area has received limited academic attention. This research aims to find the key drivers of CO2 emissions in the thermal electricity and heating sector, as well as investigating how energy policies affect those drivers. We use data from 2007 to 2018 to decompose the drivers of CO2 emissions into four types, namely: energy structure; energy intensity; input-output structure; and the demand for electricity and heating. We find that the demand for electricity and heating is the main driver of the increase in CO2 emissions, and energy intensity has a slight effect on increasing carbon emissions. Improving the input-output structure can significantly help to reduce CO2 emissions, but optimising the energy structure only has a limited influence. This study complements the existing literature and finds that the continuous upgrading of power generation technology is less effective at reducing emissions and needs to be accompanied by the market reform of thermal power prices. Second, this study extends the research on CO2 emissions and enriches the application of the IO-SDA method. In terms of policy implications, we suggest that energy policies should be more flexible and adaptive to the varying socio-economic conditions in different cities and provinces in China. Accelerating the market-oriented reforms with regard to electricity pricing is also important if the benefits of technology upgrading and innovation are to be realised.

How does China’s industrial structure change affect freight demand?

Freight demand (FD) is closely related to industrial structure (IS), and the determination of this relationship is conducive to the development of the transport industry. This research proposed an input–output structural decomposition analysis (IO-SDA) model to explain the growth of FD with the changes in economic aggregate, structural factor, transport demand intensity, and industry connection. This method enables us to quantify and compare the contribution of industrial development to FD growth of five freight modes and determine the role of the structural factor in the growth of FD. An empirical study was conducted based on China’s 2002 to 2017 input–output tables. The results showed that the construction industry was the most important sector leading to the growth of FD, and the role of the service industry in promoting the growth of FD became more evident. There was a clear trend of concentration to the road freight industry, which may undermine the coordination of the transport industry. The structural factor became an important factor in reducing FD in 2007 to 2017. Based on the findings, it is suggested that China should promote the upgrading of IS and emphasize the importance of green road transport and multimodal transport.

An input-output structural decomposition analysis of changes in China's renewable energy consumption.

Governments actively encourage renewable energy use to deal with climate change and achieve carbon emission reduction targets. It is crucial to find out the driving factors that affect the utilization of renewable energy. Therefore, based on China's 2010-2016 input-output table, this paper uses the input-output model and structural decomposition analysis (SDA) to analyze the driving factors of renewable energy changes in the production end, household end, and the aggregate economy. The results show that the changes in the consumption structure (F) is the most crucial factor for renewable energy use, followed by technology progress (T) and final demand per capita (V). Sector SEHW (supply of electric power, heat power, and water) and MCRP (manufacture of coke and refined petroleum products) are the two vital sectors to achieve China's energy transition of the production level. However, as for households, the proportion of renewable energy has been declining. Hence, the government should promote renewable energy use and achieve the green transition in production and household levels.

Analyzing the Driving Forces behind CO2 Emissions in Energy-Resource-Poor and Fossil-Fuel-Centered Economies: Case Studies from Taiwan, Japan, and South Korea

Based on the strong similarities between energy-resource-poor and fossil-fuel-centered economies (e.g., Taiwan, Japan, and South Korea) in terms of economy, culture, and energy usage characteristics, they should be analyzed collectively. This study adopted two-tier input-output structural decomposition analysis to identify the driving forces behind CO2 emissions to these countries to the formulation of effective environmental policy. Data from the World Input-Output Database was used to decompose relative changes in CO2 emissions into a range of technological advances, factor substitution, and final demand effects. Technological advances in energy (direct) contributed to a 77% reduction in Taiwan and a 34% reduction in South Korea. This is a clear indication that improving energy efficiency via technological advances should be a priority. In Japan in particular, there was a 22% reduction in CO2 emissions attributable to technological advances in materials; hence, it is recommended that Taiwan and South Korea work to extensively develop eco-industrial parks to create industry clusters to promote resource/energy efficiency and reductions in CO2 emissions. Decomposition results based on factor substitution revealed that a variety of strategies will be required, such as switching to fuels that are less carbon intensive, promoting the adoption of renewable energies, and implementing clean-coal technologies.

투입산출 구조분해를 통한 한국 해양산업 성장기여요인 분석

본 연구는 1995년부터 2016년까지의 장기 해양수산표를 작성하여, 해양수산업의 총산출 증가에 대한 요인별 성장기여율을 국내 최종수요, 수출수요, 최종재 수입대체, 중간재 수입대체, 기술변화(국산 중간재 수요) 등으로 구분하여 분석하였다. 성장요인을 이처럼 다섯 가지 요인으로 구분하여 분석한 결과 해양수산업의 성장은 수출수요 증대가 주도하였으며, 이어서 국내최종수요와 기술변화가 주도하는 것으로 나타났다. 그러나 최종재 및 중간재 수입대체는 해양수산업 성장에 부정적인 영향을 미친 것으로 나타났다. 해양수산업 세부 산업 부문별로 살펴보면, 해운항만업, 선박 및 해양플랜트 건조수리업, 해양수산기자재 제조업 부문에서는 성장요인 중 수출수요 요인이 가장 중요한 것으로 나타났다. 그러나 수산물생산업, 수산물가공업, 수산물 유통업, 해양레저관광업, 해양수산관련서비스업 부문에서는 국내 최종수요 요인이 가장 중요한 것으로 나타났다. 따라서 수출수요의 성장에 대한 기여가 큰 해양수산업의 총산출 성장을 위해서는 해운항만업, 선박 및 해양플랜트 건조수리업, 해양수산 기자재 제조업 부문의 경우에는 수출증가를 위한 국제 경쟁력 강화 정책이 필요하다고 판단된다. 반면에 국내최종수요의 성장에 대한 기여가 큰 수산물생산, 가공, 유통업, 해양수산레저관광업, 해양수산 관련 서비스업, 해양자원개발 및 건설업 등의 경우에는 내수 진작을 위한 정책이 마련되어야할 필요성이 있다고 판단된다.

Household energy consumption behaviors in developing countries: A structural decomposition analysis for Brazil

Many studies have discussed the links between household income growth and energy consumption. However, the analysis of impacts on household consumption behavior and its effects on the energy sector has not yet been explored in significant depth for developing countries. Thus, this paper proposes an input-output structural decomposition analysis methodology for identifying the main determining factors for variations in energy consumption in a developing country, according to income class, energy source, and household consumption basket composition. The methodology was applied to analyze the repercussions of recent income growth in Brazil from 2002 to 2008. The structural decomposition analysis results showed an overall upsurge in per capita direct energy consumption, together with a significant increase in the energy embedded in goods and services consumed by Brazilian households. The methodology was applied to analyze the repercussions of recent income growth in Brazil from 2002 to 2008. The results showed that the distribution of energy consumption by income class accompanied the reduction of income inequality. Besides, the socioeconomic development process caused significant changes in household energy consumption patterns, such as increased electrification and access to more modern cooking sources, such as LPG, and public transport services for low-income families. Finally, the study recommends developing countries to use technical detailed structural models with a realistic representation of intersectoral relations and household behavior per income class, in order to improve their energy planning and policymaking focused on sustainable development.

Sectoral water footprint dynamics: An input-output structural decomposition analysis for Morocco

Over the last decades, Morocco has been facing increasingly severe water scarcity. To quantify water use in Morocco, we refer to the water footprint (WF) concept, including both direct and indirect water use. WF considered covers internal WF and exported virtual water (VW). We used the input-output structural decomposition analysis (SDA) to quantitatively analyze the drivers of changes in Morocco’s sectoral WF from 1995 to 2015. The considered mechanisms governing WF changes are the technological, economic system efficiency, and structural effects. The WF growth experienced in Morocco primarily resulted from final demand changes. The technological effect acted as an additional increase factor. Nevertheless, the economic system efficiency effect contributed to the water conservation process. Unfortunately, it was not sufficient to reverse the expansion of Morocco’s WF resulted from other driving factors. Agriculture is the dominant economic sector in WF changes, regardless of any driving factor and any period considered. The study provides insight into Morocco’s water policy limits and helps develop policies towards sustainable water resources planning and management. That is by suggesting that final demand structure adjustment and technological innovation in the agricultural sector should be at the center of Morocco’s strategies in addressing water scarcity.

Economic structural change, renewable energy development, and carbon dioxide emissions in China

As the world’s largest emitter, China’s reduction of carbon dioxide (CO2) emissions is crucial for the achievement of global temperature rise goals. In this paper, we employed input-output structural decomposition analysis and index decomposition analysis to assess the factors driving changes in China’s CO2 emissions from 2000 to 2018, with particular attention to the role of renewable energy development. Our results indicate that the slowdown of economic growth and rapid structural change, rather than the shifting fuel mix, were the major forces driving China’s recent slowdown of CO2 emissions ever since 2011. Despite the great importance attached to renewable energy development, non-hydro renewable has played negligible role in reducing China’s CO2 emissions. This suggests that China cannot simply rely on the large-scale development of renewable energies to achieve its Paris 2015 target and must make further drastic cuts that will help keep global temperature rise well below 2 °C above pre-industrial level. Major breakthroughs in scalable low carbon energy sources and technologies will be required, especially in the developing world.

Revealing environmental inequalities embedded within regional trades

Carbon emissions embodied in interprovincial trade (CEE-IT) are closely related with the environmental responsibility allocation. Besides the perspective of administrative division, more rational and effective clusters based on provincial characteristics is more conducive for understanding the regional emission reduction linkages and simplifying the steps of responsibility determination. To provide a reasonable management of CEs transference mitigation in China, this study develops a provincial clustering scale CEE-IT model through three-scale accountings (i.e., aggregated-scale, consumption-scale and income-scale analysis). Specifically, 30 provinces are aggregated into several new regions with similar characteristics. Carbon emissions from different energy sources are first considered to distinguish and specify different emission reduction modes. The input output analysis (IOA) and structural decomposition analysis (SDA) are applied to quantify the embodied interprovincial carbon emissions and the relative contributions of socio-economic factors at the sector-level of disaggregation and aggregation, respectively. Three-scale accountings are innovatively employed into EEBT model to deeply analyze the emissions along China’s domestic inter-regional supply chains for identifying regional production, consumption and income-based emission responsibilities. Based on three accounting perspectives, the results provide suggestions for coordinated emission reduction across regions (including specific provinces) from the overall and decomposition levels. It shows that cutting the imports of mining sector for all regions could reduce emissions from the supply side. Rural household consumption and fixed capital formation are the major drivers for Ⅳ region from the consumption side. Technological innovations in Ⅲ region have reduced carbon emissions by 55.2% and contributed 159 Mt reductions from 2007 to 2012. Ⅲ region is insensitive to energy types and the utilization of crude oil in Ⅰ region limit the improvement of its system efficiency. Importing large quantities of emission-intensive products from Beijing and Jiangsu is a cause of high income-based emissions in Ⅱ region.

Drivers of metal consumption in China: An input-output structural decomposition analysis

The rapid growth of metal consumption is not only the result of global processes of industrialization and urbanization but also the result of multiple drivers. Based on China's input-output tables from 1997 to 2015, this article discussed the decoupling states between metal consumption and economic growth among sectors, and then adopted structural decomposition analysis (SDA) method to analyze drivers of China's metal consumption at the national level, industrial level (agriculture, industry, construction and service industries) and sub-sectors of industry level. The results show the following: (1) from 1997 to 2015, China's total metal consumption increased by 3889.35 million tons, and the decoupling state of economic development and metal consumption presented expansive negative decoupling; thus, China's high-speed economic growth has come at the expense of high-intensity metal consumption, especially in industry; (2) capital formation is the main driver of metal consumption, increasing metal consumption by 1374.89 million tons and accounting for 35.27% of the contribution, followed by metal consumption intensity, export expansion, consumption expansion, Leontief effect and import substitution effect; (3) the metal consumption intensity and Leontief effect are potential factors for improving the efficiency of metal use and reducing metal consumption; (4) various drivers hold discrepant influence on different sectors. Based on these results, related policy recommendations are also discussed.

구조분해분석을 통한 철도산업의 성장요인 분석

구조분해분석을 통한 철도산업의 성장요인 분석

Methodological Problems of Using the Structural Decomposition Analysis in the Input-Output Model at the Present Stage

The Input-Output Structural Decomposition Analysis approach enables a fairly comprehensive and detailed analysis of the economic growth sources using the input-output model. The active use of this approach is currently hampered by the lack of a reliable instrumental method for constructing symmetrical input-output tables and deflators that permit the output and import indicators to be recalculated by types of products for different years into constant prices, as well as by ambiguity of interpretations of the content of growth sources. The paper discusses the ways to overcome these methodological problems and gives an example of the experimental use of the structural decomposition analysis approach based on the data of the input-output tables of the Russian Federation for 2011–2015.

투입산출 구조분해를 통한 한국 제조업 고용변동구조 분석

투입산출 구조분해를 통한 한국 제조업 고용변동구조 분석

Structural Changes and Growth Factors of China’s Textile Industry: 1997-2012

In this study, the Input-Output Structural Decomposition Analysis (I-O SDA) method is adopted to analyze the structural change in China’s textile industry during 1997-2012 and to measure the contribution rate of the growth factors (consumption, investment, inventory, exports and imports) affecting change in its gross output. Then the key factors and main driving forces promoting textile industry development are figured out. The results show that China’s textile industry has experienced great change both in scale and structure. Among the growth factors, the contribution rate of exports is the largest, followed by investment, consumption, imports and inventory. The textile industry still relies heavily on exports, investment and consumption, while the contribution rate of imports is relatively small. In addition, technological change makes a positive contribution with technological innovation. Among the industrial sectors, the cotton & chemical fibre textile industry holds dominance, with the textile manufactured goods industry exhibiting tremendous development, the growth of the knitted textile industry fluctuating, and the wool textile industry and hemp & silk textile industry progressing slowly. Finally relevant policy suggestions are proposed to promote the balanced and coordinated development of China’s textile industry.

Drivers of carbon emission intensity change in China

Carbon emissions per unit of GDP (also called carbon emission intensity, CEI) can be utilized to measure regional carbon emission performance. In this study, structural decomposition analysis (SDA) and quantile regression are employed to investigate the factors that drive changes in CEI in China. Based on input-output SDA, CEI in China during 1992–2012 is decomposed from the perspectives of the total economy and economic sectors. The results specify that the industrial sector is the key sector for energy conservation and emission reduction. Energy efficiency contributes the most to CEI reduction, whereas input structure, final demand structure, and final product structure are factors that hinder reductions. Furthermore, energy mix, technical progress, industrialization index, and final consumption rate are introduced as proxy variables. To reveal the changes of influencing factors with CEI increasing, the effects of these proxy variables on CEI are explored by quantile regression with panel data of 30 provinces from 1999 to 2014. The results indicate that energy mix, industrialization index, and final consumption rate have positive effects on CEI. As CEI increases, the effect of energy mix increases gradually, whereas the effect of industrialization index tends to decrease, and the effect of final consumption rate increases initially and then decreases. Technical progress and urbanization are both effective in reducing CEI. With CEI increasing, the negative effect of technical progress presents a trend of decrease, then increase. Conversely, the negative effect of urbanization is through the process of increase, then decrease.

Changes to pollutants and carbon emission multipliers in China 2007–2012: An input-output structural decomposition analysis

This study performed an input-output structural decomposition analysis on changes in COD, ammonia nitrogen, SO2, NOx, soot and dust, industrial solid waste, and CO2 emission multipliers for 41 final products over the period 2007–2012 in China. The results show that during the examined period, emission multipliers were, in general, decreasing. The main driver of this was technical effects. The effects that made a significant contribution were concentrated in eight sectors: coal mining and washing; metals mining and quarrying; food and tobacco products; paper printing manufacturing; the chemical industry; non-metallic mineral products; metal smelting and rolling processing; and electricity, heat production, and supply. Moreover, the technical effects presented an obvious spillover. Although the contribution of the structural effects was far less than the technical ones, there were still some structural adjustments that led to significant synergistic mitigation. For example, the decrease in the direct demand of the agriculture products, electricity, and heat for food and tobacco products commonly reduced SO2, NOx, and CO2. In addition, four technical effects and most of the structural effects with high efficiency made small contributions. More than one third of the structural effects that showed obvious contributions played a positive role.

Input-Output Structural Decomposition Analysis on the Production of Manufacturing Industries in Korean and Japanese Economies

Input-Output Structural Decomposition Analysis on the Production of Manufacturing Industries in Korean and Japanese Economies

Has energy conservation been an effective policy for Thailand? An input–output structural decomposition analysis from 1995 to 2010

Thailand has depended heavily on imported fossil fuels since the 1990s, which hindered the nation's economic development because it created uncertainty in the nation's fuel supply. An energy conservation policy was implemented in 1995 to require industries to reduce their energy intensity (EI) and consumption immediately. This study investigates the effectiveness of the policy between 1995 and 2010 using the hybrid input–output approach. Surprisingly, EI improvement was observed in only a few sectors, such as transportation, non-metallic, paper, and textile. An embodied energy decomposition analysis revealed that while households were the largest energy consumer in 1995, energy consumption in exports exceeded that of households in 2000, 2005 and 2010. In addition, structural decomposition analysis revealed the final demand effect was the strongest factor in determining the efficacy of energy conservation, whereas the energy efficiency effect was not an effective factor as expected for decreasing energy consumption. Policy barriers and conflicting economic plans were factors that affected the outcome of these energy policies.