Direct Consumption Coefficient Research Articles

Study on the Influence of International Economic Law of Carbon Emission Trading on Environmental Sustainable Development

With the continuous development of global economic and trade activities, environmental problems have become an important factor restricting the sustainable development of all countries. How to realize the coordinated development of international trade and environmental protection has become a major issue facing the international community. Since China joined the WTO, its share of international trade has been increasing continuously. In order to deeply analyze the influence of international carbon emission trading policy on domestic carbon emissions, we use an input–output model and a GTAP analysis method to theoretically calculate the carbon emissions of the international trade of various departments in Shandong Province. At the same time, the implicit carbon emission index of various industries in 2022 is calculated through the direct energy consumption coefficient. The results show that there are significant differences in the impact of the carbon tariff system on different industries. In terms of the carbon emission index, the food processing industry showed a decrease of 18.99 Mt, while the implied carbon emission of the tobacco, textile and leather manufacturing industry reached 30.56 Mt due to the continuous expansion of trade scale. In contrast, the implied carbon emission level of the metal product processing industry reached 5.3 Mt, while the carbon emission of traditional trading industries such as coal mining was almost unaffected by international trade, and its carbon emission index reached the highest level of 5.89 in 2020. In terms of trade impact, high-trade industries such as the food processing industry are significantly affected by the carbon tariff policy, and their share has dropped from 5.89% to 3.95% in the past decade. The carbon emissions generated by GDP growth established by the GTAP model are more convincing. This model can directly reflect the energy efficiency of a region from the side. Based on the present situation of international trade, this paper analyzes the inequality of the current carbon tariff system, and puts forward some policies to optimize the energy structure to reduce carbon emissions and expand domestic demand to reduce the dependence on international trade. Through the GTAP model, we put forward policy suggestions to optimize the energy structure to reduce carbon emissions and the dependence on international trade by expanding domestic demand.

A study of key techniques in mathematical input-output modeling in the field of management accounting

Abstract In this paper, we explore the integration of a stochastic input-output model based on uniform distribution into management accounting systems to enhance operational efficiency in enterprises. The model is formulated as the mathematical expression of an input-output table, focusing on the structure of the direct consumption coefficient matrix. By applying this model to the financial data of Y Iron and Steel Enterprise in W City, we evaluate the enterprise’s competitiveness and input-output performance. From 2019 to 2023, the company’s capital rate increased markedly from 0.0235 to 0.0868, reflecting a stronger resilience against lousy debt risks. Furthermore, we observed substantial growth in assets, deposits, and loans, with 2023 figures at 0.4965, 0.5839, and 0.3899, respectively. These metrics highlight the rapid development of the financial market and expansion opportunities. Our analysis demonstrates the utility of input-output models in management accounting to qualitatively assess and optimize product output and sales, thus ensuring greater overall operational efficiency.

Construction of a digital economy accounting system based on statistical analysis methods

Abstract For a long time, the economic field has not been able to establish a more unified accounting standard for the digital economy. In this paper, the concept of an input-output table is introduced for the digital economy, and an input-output model for the digital economy is established based on three different types of equilibrium relationships with three types of input-output correlation coefficients. With the help of the demand-side statistical model based on the direct consumption coefficient and the supply-side statistical model based on the direct distribution coefficient, and through the determination of the conversion coefficient matrix, the construction of the accounting system of the digital economy is completed. Based on the statistical analysis method, the added value of “digital industrialization” reached 4,922.23 billion yuan in 2018, and the added value of “industrial digitization” was 5,076.04 billion yuan, and the total added value of digital economy reached 9,998.27 billion yuan in 2018. The digital economy’s total value added in 2018 amounted to 9,998.27 billion yuan, roughly 15 times the value added by the digital economy in 2005.

Measurement of Servitization Level of Manufacturing Industry based on Input-Output

To measure the servitization level of the manufacturing industry in Shaanxi Province and reveal the current situation of the servitization input and output. Based on the input-output tables of the whole country, Shaanxi provinces from 2002 to 2017, the direct consumption coefficient and the complete consumption coefficient are calculated to measure the input servitization level of Shaanxi's manufacturing industry and its subsectors. 56 listed manufacturing companies in Shaanxi Province were selected to measure the servitization level of manufacturing output in Shaanxi Province. The results show that from 2002 to 2017, the manufacturing industry in Shaanxi Province presents a development trend of seeking improvement in stability, but the development of servitization is slow, and the overall input servitization level is not high. The development among manufacturing industry and its subsectors is not balanced, and the gap of the input servitization level is large. The service import rate of manufacturing enterprises is not high, and the servitization level of manufacturing output is in the primary and intermediate stage. Based on those above, from the four points of policy support, optimizing the industrial structure, accelerating the integration and application of internet technology in the manufacturing industry and changing the traditional manufacturing concept, the corresponding suggestions to improve the servitization level of manufacturing in Shaanxi Province is put forward.

Research on the Relevance of Chinese Industry Based on IO Model

Based on the latest input-output (IO) model data of China’s 42 industries in 2018, this paper conducts industrial correlation research on 42 sectors of China’s current national economy from the perspective of three quantitative indicators of industrial correlation, namely direct consumption coefficient, complete consumption coefficient and influence coefficient. Based on the data analysis results over the years, the paper explores the development and change rules of China’s industrial association in 2017 and 2018, summarizes the experience of industrial development in combination with the current situation of China’s economic and social governance, and analyzes the industrial association from the essential level, so as to provide policy reference for China’s future industrial construction.

Research on the Development of Textile Industry in Shandong Province Based on Input-Output Model

Based on the latest input-output table of Shandong Province in 2017, the quantitative research analysis of industrial association was conducted on the total output, direct and complete consumption coefficients, industrial ripple effects, cross-correlation analysis and industrial types of the textile industry in Shandong Province using the input-output analysis method, and the research results show that the focus should be on the three industries of chemical products, agriculture, forestry, animal husbandry and fishery products and textile, clothing, footwear, leather and down and their products. At the same time, the development of textile industry can promote and pull the development of these three industries, so as to promote the development of the overall economy of Shandong Province.

Graph-matrix modeling of production systems as a basis for managing the production capacity of metal working enterprises

Development of information systems and technologies makes it possible to use complex models for information support of management decisions. The most particular interest shows the theory of graphs and matrix calculus in order to assess the production capacity of an industrial enterprise. The study of the authors is devoted to development of methodological approaches to assessing of production capacity based on graph-matrix models. The essence of these models lies in the fact that a manufacturing enterprise is depersonalized by perceiving it as a kind of production system, consisting of production links that add up to a production chain and form a kind of production network, which is represented as a model of the production cycle. In order to perform the appropriate calculations, the specified graph model is linked to the matrix model, which takes into account the main parameters of the production system: technological connections; assortment structure of products; direct consumption coefficients; production capacity of the links. Suggested approach determines the flexibility and broad analytical capabilities of the proposed models for calculating of production capacities. The basis for theoretical and methodological researches became the methods of analysis and synthesis, principles of consistency and complexity, graph theory and matrix calculus. The approbation of the proposed graph-matrix models of production systems was carried out using the examples of a metal working enterprise. The theoretical and practical significance of the study lies in the fact that the proposed graph-matrix model makes it possible to ensure effective management of production facilities by taking into account the mobility of the product assortment structure and complex technological links.

An analysis of the impact of service inputs in manufacturing industries on eco-efficiency: evidence from China.

The eco-efficiency of manufacturing industries has been a concern for decades in China. However, less attention has been paid to the growing service inputs in manufacturing industries and their eco-efficiency impact. Based on China's input-output tables in consecutive years collected from the structural analysis database issued by the OECD, this study describes service inputs in manufacturing industries with the direct and total consumption coefficients and then primarily discusses its environmental impacts as measured by the green total factor productivity. It finds that a significant nonlinear U-shaped relationship exists between service inputs in manufacturing industries and eco-efficiency in which the expected positive impact only emerges when a critical level of service inputs is achieved. The findings exhibit significant robustness under various measures of outcome variables and explanatory variables, as well as subsample checks and instrumental variable estimation. Environmental technical progress, rather than environmental technical efficiency, plays a decisive role in the U-shaped relationship and contributes to improvement in eco-efficiency. Furthermore, this study reveals that service inputs in the form of direct consumption of intermediate service in manufacturing industries have a significant positive impact on eco-efficiency.

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.

Direct and Indirect Loss Evaluation of Storm Surge Disaster Based on Static and Dynamic Input-Output Models

Storm surge disaster is one of the biggest threats to coastal areas. Over the years, it has brought serious losses to the economy and environment of China’s coastal areas. In this paper, Guangdong Province is taken as the research object to evaluate the damage caused by storm surge disasters. First of all, regarding the three-industry classification standards of the National Bureau of Statistics, combined with the storm surge disaster assessment index system, the 10-sector storm surge disaster loss input-output table is compiled and analyzed. Secondly, the indirect economic losses of storm surge disasters between 2007–2017 are determined by calculating the direct and indirect consumption coefficients. Thirdly, based on the static input-output model, considering the time factor, the dynamic input-output model of storm surge disaster assessment is established to calculate the cumulative output loss under different recovery periods (30 days, 90 days, 120 days, 180 days, 360 days). The results indicate that: (1) the losses, after a storm surge, in the agricultural economy have the greatest impact on the manufacturing sector, and conversely, they have less effect on the science, education and health service sectors; as well as the construction sector; (2) taking the industry with the biggest loss ratio as an example, the recovery of damaged industries is relatively rapid in the early stage and tends to be stable in the later stage of recovery; (3) the total output loss calculated using the static input-output model is greater than that computed using the dynamic input-output model. Researching the assessment of the direct and indirect loss due to storm surge disasters is of great value and practical significance for the scientific and rational planning of the country’s production layout, the maintenance of social and economic stability and the protection of life and property.

Input-output networks considering graphlet-based analysis for production optimization: Application in ethylene plants

Complex systems and massive amounts of data present a huge challenge for modern chemical enterprises, but traditional data statistical analysis and data mining methods have certain limitations. Therefore, this study proposes a production optimization methodology about input-output (I–O) network construction considering the graphlet representation. Maximal structure network is built by mechanism modeling considering I–O relationships and constraints. Then solution structure network is obtained by the direct consumption coefficient matrix of specific production data. The proposed I–O graphlets introduce process information, and different nodes represent different I–O factors in an I–O graphlet. Graphlet-based characterization and analysis can be achieved by networks and graphlets characteristics statistics. The ethylene plant I–O network is provided based on the monthly production data of 26 ethylene plants in China to optimize the ethylene production. Compared with the correlation network, the I–O network has a clear structure and physical meaning of links. Meanwhile, the hierarchical clustering based on I–O graphlets has a higher precision clustering effect than the generic graphlets. Furthermore, the ineffective ethylene plants can improve the energy efficiency and economic benefits according to the optimal production benchmark of the effective ethylene plant.

Effects of advancing internet technology on Chinese employment: a spatial study of inter-industry spillovers

The digital economy based on Internet technology has provided an important boost for economic growth. However, it has also created opportunities and challenges for stabilizing macroeconomic employment and growth. To measure how the Internet technology has influenced employment at the industry level in China, we first separate it from other technological progress in a production function model. Based on the input–output data spanning 2000–2014 in the World Input–Output Database (WIOD), we use a direct consumption coefficient matrix as the spatial weight matrices to verify inter-industry spillovers between 47 industries of China and its influence on employment by using spatial econometrics model. Empirical results indicate that Internet technology progress in one industry will significantly promote Internet technology progress in “adjacent” industries. Internet technology progress directly promote the employment within industry. Furthermore, due to the positive inter-industry spillovers, Internet technology progress also exerts positive effects on employment in other industries and positively affects employment within industry again through various feedback loops between industries. Therefore, policy should promote Internet technology in various industries, especially those closely linked to other industries, to stabilize employment and growth.

Evolution and driving factors of CO2 emissions structure in China’s heating and power industries: The supply-side and demand-side dual perspectives

Excessive CO2 emissions from energy combustion are the main cause of the global greenhouse effect, while the energy consumption in China’s heating and power industries account for more than a half of national energy consumption. Based on this, to more accurately implement carbon emission reduction in heating and power industries, we studied the evolution and driving factors of the carbon emission structure in these industries between 2007 and 2015 from supply-side and demand-side dual perspectives. The results indicated that: (1) From the view of supply-side, the change of energy consumption structure led to the decline driving force of high-carbon energy (washed coal, crude oil, diesel oil and raw coal) and the rising driving role of low-carbon energy (coke oven gas, other gas and natural gas) for CO2 emissions growth. Moreover, seen from the entire sample interval, 2007–2010 and 2010–2012 were the best period and the worst period for energy consumption optimization in China’s heating and power industries, respectively. (2) From the view of demand-side, the expansion of industrial scale was the responsibility of the carbon emissions growth in China’s heating and power industries, and the driving force of the second industry on carbon emissions growth was stronger than that of tertiary industry and primary industry. (3) However, since the direct consumption coefficient of heating and power energies in the tertiary industry and primary industry was lower than that of the secondary industry, the optimization of industrial structure was conducive to slowing the growth of CO2 emissions in the China’s heating and power industries on the demand-side. At last, this paper provides a theoretical analysis for the carbon emission structure of the heating and power industries, and a practical guidance for the industries to carry out more accurate and efficient emission reduction from both sides of supply and demand subsequently.

Water-Energy-Carbon Emissions nexus analysis of China: An environmental input-output model-based approach

China has one of the fastest-growing economies worldwide, consuming large amounts of resources but also experiencing significant environmental issues. Water, energy, and carbon play significant roles in regional sustainable development. It is critical to understand the Water-Energy-Carbon Emissions nexus, and this study explores the nexus using the Environmental Input-Output model. The embodied water and energy consumption and embodied carbon emissions are assessed. The water and energy consumption coefficients and CO2 emission coefficients are analysed. The main results are: (1) The Water-Energy-Carbon Emissions nexus characteristics of light industry, heavy industry, and service industry were similar: water-intensive, energy-intensive, and carbon-emission-intensive; (2) Agriculture consumed 64.38% of the national water supply; however, the water utilisation efficiency was only 32%; (3) Agriculture had much higher water consumption and direct water consumption coefficients. Light industry, service industry, and heavy industry were the top three sectors in terms of indirect water consumption coefficients; (4) Heavy industry, light industry, and service industry were the top three sectors with the highest indirect energy consumption coefficients and carbon emission coefficients. The consumption (water and energy) and CO2 emission coefficients can provide significant support for sustainable development strategies. This study provides a better understanding of the Water-Energy-Carbon Emissions nexus in China.

Ecological Network-based Input-output Model for Virtual Water Analysis in China

In this study, an ecological network-based input-output model (ENIOM) is developed for assessing the virtual water in China. Direct/indirect water consumption efficiency and virtual water flow directions among different sectors are quantified by input-out model, and the relationship (e.g., exploitation, competition and mutualism) among different sectors are identified by network utility analysis. Based on China’s input-output table in 2017, results show that (i) agriculture sector has the highest direct water consumption coefficient, and manufacturing sector has the highest indirect water consumption coefficient; (ii) manufacturing sector is the largest virtual water input and output sector, with a total net input of 93.6×109 m3 from the remaining seven sectors; and (iii) exploitation is the main relationship existed in the water network system. These findings suggest that more attentions should be paid on agricultural and manufacturing sectors in terms of water resources management.

Research on Energy Industry Based on the Input-Output Model

This paper uses input-output model to calculate direct consumption coefficient, total distribution coefficient, direct consumption coefficient and total consumption coefficient of five energy industries. We analyze the related industries of the energy industry. The results show that the Electricity industry has the largest consumption coefficient and distribution coefficient, and the Electricity industry is an important part of the economy. The consumption coefficient and distribution coefficient of the coal industry are relatively large.

Economic Impacts of the Geothermal Industry in Beijing, China: An Input–Output Approach

Geothermal energy is a clean energy source that can potentially mitigate greenhouse gas emissions, as its use can lead to a lower mitigation cost. However, research on the economic impacts of the geothermal industry is scarce. This paper describes the effect of the geothermal industry, its economic input and output, using Beijing as a case study. This paper adopts the input–output model. The results show that the demand for and input use of the geothermal sector vary greatly across industrial sectors: electricity, heat production, the supply industry and general equipment manufacturing have the greatest direct consumption coefficient for the geothermal industry. When considering direct and indirect demand, it is clear that the geothermal industry has a great effect on different industrial sectors in diverse ways. Its influence coefficient and sensitivity coefficient are 1.2167 (ranked 11th) and 1.2293 (ranked 8th), respectively, revealing that it exerts obvious demand-pulling and supply-pushing effects on the regional economy.

Macroeconomic water resources input-output analysis in Shandong Province

The allocation of water resources is linked to economic conditions, and the input-output analysis methods of macroeconomic water are applied to analyse the macroeconomic impact of water resources on Shandong Province. By calculating the input and output coefficients of water resources in 14 industries in Shandong Province, the water use conditions and water use efficiency of various industry sectors in the production process are analysed to provide the basis for the optimal allocation of water resources in Shandong Province. After data analysis, the following conclusions have been drawn. The direct water consumption coefficients for agriculture, power, paper, and petroleum industries are relatively large, while the total water consumption coefficients for agriculture, food, textile, and paper industries are relatively large. The food, textile, and engineering industries have higher water consumption multipliers. From 1997 to 2007, the direct and indirect water consumption of all industries showed a downward trend, which is closely related to the water saving policy. It should be advocated to export products with high benefit and low water consumption and import agricultural and industrial products for alleviating pressure of water shortages by trade forms. In addition, using the added value and water consumption of all industry sectors evaluates the production efficiency, which plays an important assistance in water resources allocation and planning.

Analysis of China department water consumption efficiency

The water comparable non-competitive input-out model of China in 2002, 2007 and 2012 is established to calculate the department water consumption efficiency. The water direct and complete consumption coefficients of 38 departments are analysed. Agriculture and Electricity and steam supply have the highest water consumption coefficients and utilize water resource mainly by the direct way. Manufacture of food products and tobacco products, Manufacture of textiles, Manufacture of wearing apparel and leather products and Information service activities have high water complete consumption coefficients and affect water consumption mainly by the indirect way. Water complete consumption efficiency measures the efficiency from the view of final product, which reflected the department water use driving force more precisely.

The Convergence of Agriculture and Services in Hainan Province Based on Input-output Model

With input-output table of 2002, 2007 and 2012 in Hainan province as data source, the direct consumption coefficients, complete consumption coefficients, influence coefficients and induction coefficients were calculated to build the input-output model, by which the industrial relevancy and spread degree and trend of agriculture and services in Hainan province were analyzed, so as to empirical research the convergence of agriculture and services in Hainan province. The results showed that the gross output of Hainan agriculture decreased continuously, and the gross output of services raised in waves but technology and knowledge intensity still low. The consumption demand for agriculture in services was greater relatively, and mainly indirect consumption. The demand intensity of agriculture on the national economy was larger, while services had relatively strong initiative to integrate into agriculture. At last, some suggestions were put forward to promote the convergence development of agriculture and services in Hainan province.