Input-output Method Research Articles

Carbon Emissions and Its Efficiency of Tourist Hotels in China from the Supply Chain Based on the Input–Output Method and Super-SBM Model

Carbon Emissions and Its Efficiency of Tourist Hotels in China from the Supply Chain Based on the Input–Output Method and Super-SBM Model

Digital agriculture’s impact on carbon dioxide emissions varies with the economic development of Chinese provinces

Digital empowerment is a dynamic process of complementary digital technology and production factors and plays a critical role in achieving the dual carbon objectives of the carbon peak by 2030 and carbon neutrality by 2060. Here, we use the input-output method, employing panel data on environmental and social factors from 30 provincial-level regions in China from 2012 to 2021. We explore the impact of digital empowerment development on agricultural carbon dioxide emissions and underlying mechanisms. We found that the relationship between digital empowerment and carbon dioxide emissions is nonlinear and follows an inverted U-curve. The carbon dioxide emissions increase as digital empowerment increases and decrease when digital empowerment crosses the inflection point of 0.0862. Digital empowerment reduces agricultural carbon emissions by optimizing carbon-intensive factor inputs such as fertilizers and improving factor allocation efficiency. Our research provides evidence for policymakers to enable the promotion of digital empowerment of farmers across Chinese provinces.

Spread efficiency of energy demand in the industrial chain: a perspective from economic distance

This paper investigates the spread efficiency of energy demand in the industrial chain based on the input-output method. The concept of intersectoral economic distance and spread efficiency was introduced to formulate the energy demand spread functions. Then, an empirical study was conducted based on China's 2017 input-output data and nearly 3,500 companies were listed in the Chinese A-share market. The results show that the sectoral average spread time is 32.75 days. Manufacturing plays a central role in the spread of energy demand. In the short term, the logistics sector has the greatest pulling effect on energy demand, while the electric power sector has the greatest impact on energy demand in the long term. Energy demand caused by exports is greater than consumption and investment. Finally, sectoral economic distances and actual spread functions for 9 main energy sources are provided to help us better predict energy demand.

Application of the environmentally extended input-output method in the identification of key sectors: A PRISMA-guided systematic review

The overarching goal of this systematic literature review is to identify, present and in detail analyze relevant published studies in Scopus-indexed publications regarding the identification of key sectors in the economy with the application of the environmentally extended input-output methodology (EEIO). For this reason, the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for systematic literature reviews have been adopted. The Scopus scientific database was surveyed with the keywords “Environmentally extended input-output”, “key sectors”, “transmission sectors” and “key industries”, which led to a total of 50 published papers in English. After implementing all of the steps of the PRISMA guidelines, which included both electronic and manual searches, a total of 8 relevant papers remained for qualitative analysis. Most of these papers were conducted for the period between 2000 and 2017. The key findings are elaborated in a narrative synthesis and reveal that most authors indicate the electricity, transport and construction sectors as the sectors with the highest pollutant emissions; the household sector is also singled out as a sector that has a large impact on carbon emissions. The underlying purpose of this paper is to raise awareness and knowledge among scholars and local and national policymakers in regard to the key sectors and empirical ways for their identification with the application of the EEIO method. Lastly, the scientific and practical implications of the study are provided, and plans and guidelines for future work are presented.

Study on Carbon Emission Influencing Factors and carbon emission reduction potential in China's food production industry

Climate warming has become a global issue of close concern, and China, as a significant agricultural country, has an increasing demand for food, which requires China to increase carbon reduction in this industry. This paper accounts for carbon emissions from the food production industry (CEFI) using the input-output method, then screens the influencing factors of CEFI based on Random Forest (RF), analyzes the heterogeneous effects of the influencing factors on CEFI in different clusters through K-means-SHAP, and finally explores the potential of carbon emissions from this industry for the period 2024–2040. The study's findings are as follows: First, there are apparent inequalities in CEFI, especially between provinces, which are gradually increasing. Second, addressing people's consumption awareness and behaviors is not the fundamental solution to alleviate CEFI; instead, it should focus on sustainable agricultural production transformation and “food miles” in the transportation phase. In addition, attention needs to be paid to the impacts of fertilizer application, transport modes, and livestock management on the CEFI of each cluster. Finally, the study suggests that around 2028, 70% of China's provinces will be at the “carbon peak” and that less developed and more developed regions have more significant potential to reduce emissions. In this regard, this paper encourages a series of policies that are key to promoting the sustainable development of CEFI, such as reducing the volume and efficiency of traditional fertilizers, vigorously developing organic fertilizer inputs, strengthening technological innovation and R&D inputs in the transportation sector, and steadily supporting germplasm innovation in the livestock sector.

Theoretical Background of Input-Output Analysis and its Application in Albania

The input-output (IO) method is widely used in economic analysis to understand the relationship between sectors of the economy. One of the major advantages of the IO method is its ability to capture the direct and indirect effects of different policies in one sector on other sectors of the economy. The IO table system is a crucial component of the European System of Accounts, a standardized framework for the production of European Union statistics on economic activities. Utilizing various mathematical techniques and methods, the IO analysis shows adaptability as a tool of analysis. In comparison to alternative methods, one of the primary benefits of the IO method is its flexibility in incorporating aggregate data. This enables researchers and policymakers to gain a more comprehensive understanding of the interrelationships between different sectors of the economy as well as the effects of different policies on multiple sectors of the economy. This paper examines several studies by different authors related to IO analysis, which use official data from IO tables across various countries to analyze the economy of a country, region, and global impact. This paper evaluates the limitations of the application of the IO method in Albania, considering the techniques of constructing symmetrical IO tables and the types of analyses conducted through these data.

Effectiveness of Value-Added Input-Output Method in Upstream and Midstream Supply Chain Network of Sunflower Agro-industry

Abstract Sunflower (Helianthus annuus L) is an annual shrub that grows up to three meters high. Sunflower agro-industry has high potential economic value. Sunflower seeds produce oil that can be extracted and used as a raw material in the food, pharmaceutical, bioenergy, and cosmetic industries. The problem is the low availability of superior local seeds, so it must be imported. The impact of imports is the low value-added. Therefore, this study aims to determine and measure the value-added of sunflowers in the upstream and midstream networks. The methods are Hayami and BPS input-output, also aims to identify the effectiveness of these two methods.. The results of value-added on sunflower seeds, cooking oil, herbal oil, and animal feed by the Hayami and the BPS input-output each are IDR6,000 (40%) and IDR24,005,528 (20%), IDR4,900 (26%) and IDR41,377,013 (23%), IDR21,000 (60%) and IDR117,653,333 (38%), IDR3,500 (86%) and IDR23,996,000 (100%). it is better to calculate using the BPS method because it is more detailed and clear in all aspects of the sunflower agroindustry, while using the hayami method only focuses on sales and labor. In the future, this research will be developed by designing sustainability improvement to reduce environmental impacts; performing value-added calculations for derivative products in the downstream supply chain network; also developing a decision support system.

Thermal assessment of cylindrical parabolic integrated collector storage using input-output and dynamic system testing procedures: Experimental and numerical study

The main limitation of Integrated Collector Storage systems lies in their low efficiencies and high loss coefficients. In this paper, experimental and numerical setups are conducted to assess the thermal performances of low cost Cylindrical Parabolic Integrated Collector storage (CP-ICS). The conceived system has two aluminum plates in parabolic form serving as reflectors, each with a surface area of 2 m2. The storage tank has a volume of 160 L covered with a layer of black paint with single and double transparent insulations. Results of the experimental tests using Input-Output method showed that the daily thermal efficiency ηd of the developed systems is equal to 48.21% and 49.46% for single and double insulation cover configurations, respectively. The total store heat capacity Cs, the useful collector surface Ac* and the storage tank heat losses coefficient Us of the system found using Dynamic System Testing procedure are equal to 0.56 MJ/K, 0.74 m2 and 1.59 W/K, respectively. Even if the energy efficiency of the system is slightly lower than that recorded in conventional systems, numerical results of long-term study using TRNSYS software showed that the system provides a reasonable solar fraction for the needs of a family in Tunisian climate. A comparative assessment of the developed solar collector performances in different representative climates showed that the use of the CP-ICS system presents a promising solution for countries with annual ambient temperatures fluctuating from 13°C to 33°C, such as Araxos with a solar coverage of 30.65% for a daily supply volume of 160 L. More importantly, in Faya-Largeau location, presenting Chadian climate data, the solar fraction is found to be the highest and reached an average of 67.25%.

Estimating the Mass Balance of the Antarctic Ice Sheet from 1985 to 2021 using the Input-Output Method

Accurate monitoring of the Antarctic ice sheet's mass balance is crucial for comprehending its contribution to global sea level rise and climate patterns. We estimate the Antarctic mass balance from 1985 to 2021 using an input-output method. Ice discharge is estimated using an automated algorithm, while surface mass balance data is obtained from the RACMO2.3p2 model. We find a recent decrease in the rate of ice mass loss in Antarctica, consistent with the recent studies. The West Antarctic Ice Sheet (WAIS) drives the increase in ice discharge and mass loss, influenced by rising ocean temperatures and extreme weather events. The East Antarctic Ice Sheet (EAIS) shows stability in mass balance, except for an increase in discharge and mass loss in the Cp-D sub-region. The Antarctic Peninsula experiences increased ice discharge and mass loss, while the islands maintain a positive mass balance. The findings contribute to our understanding of the ongoing changes in ice mass and highlight the sensitivity of different regions to external factors.

Spatio-temporal heterogeneity and coupling effect of mining economy, social governance and environmental conservation: Evidence from Guangxi Zhuang Autonomous Region, China.

In order to solve the problem of coordinated development among mining economy, social governance and environmental conservation in global resource-based cities, we choose Guangxi Zhuang Autonomous Region as the research area. The advantage of resource endowment and resource industry was measured by location quotient and input-output method. The panel data related to mining governance from 2010 to 2021 were selected to build the evaluation and coupling analysis model between mining economic, social governance and environmental conservation, and the spatial-temporal heterogeneity and coupling effect of them were analyzed by comprehensive empowerment evaluation, spatial autocorrelation analysis and barrier degree methods. The results show that: (1) Except for the overall upward trend of social governance, the development level of mining economy and environmental conservation are basically stable; (2) The resource-rich areas have obvious mining economic advantages, and the central cities have good social governance capabilities, and the environmental conservation effectiveness is uncertain; (3) The coupling effect between mining economy and social governance is stronger than that between mining economy and environment conservation, and the synergistic coupling effect of the three is relatively random. Finally, we put forward some policy response strategies to Guangxi, and theoretical and practical reference would be provided for resource-based cities around the world.

Greenhouse gas emissions patterns and insertion in global value chains: a comparative study between Brazil and China (2000–2016)

PurposeThis study aims to analyze and compare the relationship between international trade in global value chains (GVC) and greenhouse gas (GHG) emissions for Brazil and China from 2000 to 2016.Design/methodology/approachThe input-output method apply to multiregional tables from Eora-26 to decompose the GHG emissions of the Brazilian and Chinese productive structure.FindingsThe data reveals that Chinese production and consumption emissions are associated with power generation and energy-intensive industries, a significant concern among national and international policymakers. For Brazil, the largest territorial emissions captured by the metrics come from services and traditional industry, which reveals room for improving energy efficiency. The analysis sought to emphasize how the productive structure and dynamics of international trade have repercussions on the environmental dimension, to promote arguments that guide the execution of a more sustainable, productive and commercial development strategy and offer inputs to advance discussions on the attribution of climate responsibility.Research limitations/implicationsThe metrics did not capture emissions related to land use and deforestation, which are representative of Brazilian emissions.Originality/valueComparative analysis of emissions embodied in traditional sectoral trade flows and GVC, on backward and forward sides, for developing countries with the main economic regions of the world.

Review of Research on the Impact of Changes Resulting from the Hard Coal Mining Sector in Poland on the GDP Value

Energy transition is one of the main objectives of the European Union. Significant changes will mainly affect countries in which significant modifications will have to be made to their energy sources. The process will involve high investment in infrastructure and additional costs of the transformation, such as reduced production (which may affect the GDP value) in the economic sectors involved in the process. The aim of this article is to provide the energy transition community, namely the national economy in general and those involved in planning for structural change in particular, with the key lessons and challenges in researching the impact of production changes in the mining sector. This article also shows the relevance of the mining sector in the economy. Within this area, particular attention is given to the following issues: the impact of economic sectors on the country’s GDP (gross domestic product); the identification of key sectors of the economy using the input–output method; the contribution of coal mining and the mining industry to Poland’s GDP; an analysis of changes in the structure of Poland’s economy using the input–output method; and the use of the input–output method in the context of changing/reducing the supply of economic sectors.

The Impact Analysis of Bauxite Downstreaming on the Indonesian Economy: Case Study in PT Bintan Alumina Indonesia

This research analyzes the impact of investment and bauxite downstream activities by PT Bintan Alumina Indonesia (PT BAI) on the Indonesian economy using the input-output method applied to the Riau Islands Province, West Kalimantan Province and Indonesia. The imposition of stimulus on sectors related to the construction phase and operational phase of the alumina and aluminum industry in the Galang Batang SEZ is the concept that underlies how final demand in other sectors is affected. Economic improvement is characterized by increased output, GDRP, people's income, and the creation of job opportunities. During the construction phase of PT BAI (2016-2029), it generally had a positive impact on the increase in output, income, average GRDP, and average job creation in 52 industrial sectors in the Riau Islands Province. During the operational phase, calculated through three scenarios applied to the Riau Islands Province, West Kalimantan, and Indonesia, with the assumption of full downstreaming of PT BAI's products into the domestic market, shows the greatest impact. The impact includes the increase of Indonesia's output value until 2030 reaching IDR 547.07 trillion, an average annual GDP growth of 0.099 percent, a national income increases until 2030 reaching IDR 74.22 trillion, and an average job creation of 107,105 people per year in 52 industrial sectors in Indonesia. To achieve the optimal target of PT Bintan Alumina Indonesia's (BAI) presence in the domestic bauxite value chain, strengthening the downstream process and downstream industries of alumina and aluminum domestically is needed. Fiscal incentives, the establishment of pro-downstream regulations, and investor protection are crucial to implement.

Inequality of carbon emissions between urban and rural residents in China and emission reduction strategies: evidence from Shandong Province

China is actively heeding the call and striving for a low-carbon and environmentally friendly development route as part of the general trend toward a global low-carbon economy. The rapid economic development of our nation has brought to light the issue of carbon emissions resulting from the consumption habits of residents. This paper delves into the topic by conducting a thorough analysis of the carbon emission of residents’ consumption using the input-output method. Based on the survey findings, the disparity in carbon emission between urban and rural communities in Shandong Province is evident not only in terms of total emissions but also in different categories and regions. Urban residents generate a total carbon emission of approximately 70.2921 million tons, which is three times higher than that of rural residents at 23.7846 million tons. The carbon emission of both urban and rural residents is primarily attributed to their embodied carbon emission. In examining the composition of the implied carbon emission of residents’ consumption in Shandong Province, urban residents’ carbon emission is concentrated in three areas, namely, food, culture, education, entertainment, transportation, and communication, accounting for 21.45%, 20.88%, and 15.10%, respectively. Conversely, rural residents’ carbon emission is concentrated in four areas, including clothing, food, culture, education, entertainment, transportation, and communication, accounting for 29.01%, 17.45%, 15.43%, and 13.36%, respectively. Finally, according to the characteristics of the consumption carbon emission of urban and rural residents in Shandong Province, we give corresponding emission reduction strategies.

How automated machines influence employment in manufacturing enterprises?

This paper theoretically analyzes and empirically examines the impact and mechanisms of automated machines on employment in manufacturing enterprises, drawing on task-based model and using micro data from listed Chinese manufacturing enterprises between 2012 and 2019. Our findings reveal that: (1) Automated machines in manufacturing enterprises leads to a substitution effect on the total labor force, with a substitution effect on low-skilled labor and a creation effect on high-skilled labor in terms of employment structure. (2) Further analysis indicates that automated machines primarily have a positive effect on R&D and technical staff, a non-significant effect on sales staff, and a negative impact on production, administrative, and financial staff. (3) The primary influencing mechanisms of automated machines on employment in manufacturing firms are productivity effects and output scale effects, based on the mediation effect model. (4) Considering the industry linkage effect, we employ the input-output method and the Input-Output Table and find that automated machines for upstream (downstream) manufacturing enterprises will result in a substitution effect on employment for downstream (upstream) enterprises. The novelties and research contributions are as follows: (1) we conduct a structural decomposition of total employment, and further decompose employment positions into production, R&D, sales, finance, and administration. (2) We try to investigate the industry linkage effect about the impact of automated machines on the employment of upstream and downstream enterprises. (3) We use data from listed manufacturing companies, and the data of existing research are about provincial and industry-level data.

Trade and Labor-Allocation: Evidence from Sectoral Embodied Labor Transfer between China and Africa

Trade and Labor-Allocation: Evidence from Sectoral Embodied Labor Transfer between China and Africa

Measurement of carbon emissions and responsibility sharing for the industrial sector in Zhejiang, China

Carbon reduction is imperative for achieving carbon peaking and neutrality. Accordingly, it is important to determine which industrial sectors have more responsibility in this matter. Based on data from Zhejiang's input-output tables, this study applies the Input-Output method to measure and compare the carbon emissions of 42 industrial sectors in Zhejiang Province from 2002 to 2017, and then assesses the carbon emission attributes of each industrial sector, and ultimately determines the responsibility for carbon emission reduction from the perspectives of the producers and consumers. The results of the study show that direct carbon emissions and whole-process carbon emissions in Zhejiang increased continuously from 2002 to 2017, with carbon emission intensity first decreasing and then increasing. However, carbon emission intensity was much lower in 2017 than in 2002. Over time, the attributes of carbon emissions by sector changed little. Particularly, high-carbon sectors covered most of the energy supply sectors, low-carbon sectors were mostly tertiary-related, and pseudo-low-carbon sectors were mainly found in the productive services sector. In terms of carbon emission reduction responsibilities, there are large differences in emission reduction responsibilities between sectors, with the electricity and heat sectors bearing the largest responsibilities based on their production, consumption and total carbon emission reductions. The conclusions of this study can provide some data support for the further development of carbon peak and carbon neutral plans.

ИСПОЛЬЗОВАНИЕ МЕТОДА «ЗАТРАТЫ – ВЫПУСК» ДЛЯ ОБОСНОВАНИЯ СТРАТЕГИЧЕСКИХ ПРОЕКТОВ ОБЕСПЕЧЕНИЯ ПРОДОВОЛЬСТВЕННОЙ БЕЗОПАСНОСТИ РОССИИ

The article contains a theoretical justification for the methods of intersectoral economics of the agri-food complex, based on the use of the author’s modification of input-output tables for the development and implementation of strategic projects to ensure food security in Russia. The key factors for sustainable growth of gross value added and final products in the country’s agri-food complex have been identified. A methodology has been developed for forecasting the vector of Russian food exports as a process with a high level of uncertainty. The influence of the spatial factor on the level and quality of food supply for the regional population has been revealed. The features of the matrices of direct and total cost coefficients have been studied, their relative stability in the medium term has been proven, opening up new opportunities for using the inputoutput method to justify strategic projects. A multi-level system of models is proposed, the basis of which is the inter-product balances of enterprises in the agri-food complex. The priorities for the structural modernization of the agri-food complex have been identified. The strategic directions for the development of institutions that ensure the growth of food consumption by the regional population are substantiated. Methodological recommendations have been developed for managing strategic projects to ensure the country’s food security in the context of new global challenges.

Enigma of Nickel Export Ban: Understanding Its Impact through Input-Output Analysis

The nickel ore export ban policy has drawn pros and cons in various circles. This study aims to analyze the impact of the nickel ore export ban on other sectors of the economy and the interrelationship between one sector and another. This study uses secondary data in the form of Indonesia's Input Output Table Total Transactions at Basic Prices in 2016 derived from BPS publications and data on the number of Ferro-nickel exports in 2020 derived from UNData publications, which are then analyzed using the input-output method and presented using descriptive quantitative analysis. Based on the research results, electricity and gas procurement are the economic sectors with the most significant backward linkage. In contrast, the manufacturing sector achieves the most significant forward linkage value. In addition, the electricity and gas procurement sector also has the most significant output multiplier value, followed by the construction and manufacturing sectors. The increase in Ferro-Nickel exports due to the nickel ore export ban has considerably impacted the economy regarding both domestic and import output, especially in the manufacturing industry sector. Thus, nickel ore processing activities depend on capital goods and other imported raw materials. The study's implication shows that the export of Ferro-Nickel as part of the mining and quarrying sector impacts the output of other sectors to increase overall economic growth.

Changes in the socio-economic characteristics of households can decouple carbon emissions and consumption growth in China

The increasing consumption in developing countries poses a significant challenge to global climate change mitigation efforts. Understanding household characteristics is essential in exploring potential strategies to decouple carbon emissions from the increasing consumption. In this study, we utilized the multi-region input-output (MRIO) method to calculate household carbon emissions in China for the years 2012, 2016, and 2018. Using micro-level household survey data, we identified variations in carbon emissions among households with different economic levels and socioeconomic characteristics. Our analysis revealed that changes in household consumption structure and carbon intensity among households with improved economic levels, could result in a reduction of carbon emissions by 14 % to 19 %. Furthermore, households characterized by higher education levels, larger family sizes, and smaller housing units were found to generate lower carbon emissions per capita and per unit of consumption spending. By simulating household carbon emissions up to 2030, we identified three potential pathways to achieve decoupling: household economic upgrading, transitioning to low-carbon household characteristics, and reducing material consumption. Our findings indicate that even with a projected 75 % increase in per capita consumption volume by 2030, per capita household carbon emissions could still be lower than the levels observed in 2016. These results underscore the potential of consumption-focused policy measures in facilitating the decoupling of household consumption from carbon emissions.