Input-output Model Research Articles

Inequitable distribution of risks associated with occupational heat exposure driven by trade

The exposure to extreme heat at workplaces poses substantial threat to human effort and manual labour. This becomes more prominent due to the global dispersion of labour-intensive production activities via trade. We combine a climate model with an input–output model to quantify the risks associated with trade-related occupational extreme heat exposure. Here we show an 89% surge in trade-related labour exposure to extreme heat, escalating from 221.5 to 419.0 billion person-hours between 1995 and 2020. Lower-middle-income and low-income economies constituted 53.7% and 18.3% of global exposure but only 5.7% and 1.0% of global labour compensation. In countries highly susceptible to extreme heat conditions, workers perform tasks in heated conditions for up to about 50% of their working hours. The disproportionate trade effects in redistributing global benefits and costs leads to the inequality in heat exposure between developed and developing economies. In striving for equitable and safe work conditions, workers vulnerable to heat extremes in developing economies should be protected by climate adaptation infrastructure, given their critical roles in the global production system.

Examining safety conditions in the construction sector across Chinese provinces: an input-output analysis

Examining safety conditions in the construction sector across Chinese provinces: an input-output analysis

Economic consequences of eliminating gender discrimination in the labor market

Theoretical and empirical literature on labor market discrimination is extensive on showing persistent wage gaps across genders at individual level. However, at the aggregate level, the economic consequences of gender discrimination remain unclear. In this article, economic consequences of gender discrimination are estimated through interacting a wage decomposition model (individual) and an input–output model (aggregated level). Using the decomposition’s results, it was possible to calculate individual wage adjustments, so that all individuals are remunerated according to their observable characteristics as well as the group of non-discriminated individuals. In turn, these estimates were used to simulate changes on labor nominal costs (price effect) and consumption (income effect). Our results indicate that the income effect generated through consumption overcomes the price effect, raising production (0.90%), welfare (2.70%) and employment (0.94%). Nonetheless, the results are very heterogeneous across sectors and households.

Unveiling China's household CO2 emissions with disaggregated energy sectors: An affinity-propagation multi-regional input-output model

Although much research has focused on CO2 emissions driven by household consumption, significant challenges remain in capturing complex regional variations and the indirect contributions of disaggregated energy sectors and different income groups. In this study, an affinity-propagation multi-regional input-output (AP-MRIO) model is developed through incorporating Dagum Gini coefficient (DGC) and affinity propagation (AP) clustering within a multi-regional input-output (MRIO) modeling framework. AP-MRIO not only traces CO2 emissions from China's provincial household consumption, particularly within disaggregated energy sectors, but also reveals the interaction between sector emissions and income levels. Results obtained disclose that (i) within energy sectors, thermal power, electric power distribution, and petroleum are major emitters (accounting for 68.7%, 17.5%, and 6.6%, respectively); in comparison, CO2 emissions from renewable energy sectors (hydropower, nuclear, wind, and solar) are lower (2.7%); (ii) urban middle- and high-income households contribute significantly to CO2 emissions (57.1%), and notable carbon inequalities exist both within and between regions for energy sectors; (iii) some provinces (e.g., Inner Mongolia, Liaoning, and Heilongjiang) should prioritize reducing per capita emissions from the non-renewable energy sectors; other provinces (e.g., Ningxia, Guangdong, and Hunan) should further promote the development of renewable energy and focus on emissions embodied in the use of intermediate products.

Carbon footprint heterogeneity across elderly groups in China

Abstract Assessing the elderly’s environmental impact is crucial as aging deepens. This paper incorporates age heterogeneity and urban-rural heterogeneity within the elderly into the study of aging’s impact on the environment, dividing the elderly population into four subgroups. Utilizing an environmentally extended multi-region input-output(EE-MRIO) model and data from 12,000 households, the carbon footprints of four subgroups was calculated. Findings reveal significant urban-rural and age-related heterogeneities in carbon emissions among those aged 60 and above. Urban elderly have higher per capita carbon footprints than rural elderly, and ‘the younger elderly’ have higher footprints than ‘the oldest old’. This heterogeneity extends to carbon footprint’s distribution: Urban elderly lean towards enjoyable consumption, while rural elderly prioritize survival. ‘The younger elderly’ have a greater carbon footprint from transport. This paper nests Chinese and global EE-MRIO, showing that global economies are more impacted by China’s elderly demand than mainland China itself. Furthermore, urban-rural structure has a greater impact on global carbon emissions compared to age structures.

A multi-objective optimization approach for interprovincial carbon emission reduction in China: Considering industrial structure and ownership attributes.

Balancing economic growth with carbon emission control requires the coordination of policy preferences for economic and carbon reduction goals, as well as the low-carbon transformation of industrial and ownership structures. This study employs a multi-objective input-output optimization model to investigate the trade-offs among maximizing GDP growth, minimizing carbon emissions, and minimizing energy consumption within the planning period of 2017-2035 in China. The model accounts for the heterogeneity of industrial structures and ownership attributes, examining both national aggregates and the adjustment paths and ownership trends across different provinces. The findings reveal: (1) Sectors with high output and low energy consumption are growing, while high pollution and high energy-consuming sectors are declining, driven primarily by technological levels, followed by policy and development preferences. (2) Domestic capital expanding into high technology and capital-intensive sectors, HMT capital favoring the economically developed high technology regions, and foreign investment declining. (3) Regional adjustment in high-value or high-energy-consumption sectors are more pronounced in central and western provinces and less economically developed regions, while industries that are neither high-energy-consumption nor high-value show greater increases in resource-rich provinces with better infrastructure.

The impact of importing on the CO2 intensity of the global and national construction industries.

CO2 intensity is a valuable indicator for investigating the amount of CO2 emissions prevented by importing relative to the economic costs the importer pays for international trade; this plays a significant role in mitigating climate change and promoting environmental sustainability. This study explores the effect of importing on the CO2 intensity of the construction industry by establishing an analytical framework that divides the total CO2 intensity into aggregate CO2 intensity in imported products (AII) and aggregate CO2 intensity in domestic products (AID), and targets the gap between AII and AID to reveal the effects of importing. A multi-regional input-output model was adopted to evaluate the AII and AID of the construction industries in 15 economies for 2014 and then the LMDI method was used to decompose the gap between AII and AID from the perspective of the source industry. The results indicated that importing showed an increased effect of 3.11 ton/USD on the CO2 intensity of the construction industry globally. At a national scale, importing increased the CO2 intensity of the construction industries in most countries (13/15). In terms of decomposition analysis, the aggregate CO2 intensity effect decreased AII by 23.15 ton/USD and the aggregate structure effect increased AII by 151.51 ton/USD. For most economies, the aggregate structure effect, especially when sourcing from the electricity industry and the mining industry, mainly caused AII to be higher than AID and resulted in a pulling effect of importing on the CO2 intensity of the construction industry. On this basis, adjusting industrial source weights in importing is significant for achieving the CO2 intensity mitigation targets of the global and national construction industries.

Bridging environmentally extended input-output models and complex network analysis: A bibliometric analysis of trends and opportunities

Bridging environmentally extended input-output models and complex network analysis: A bibliometric analysis of trends and opportunities

Modeling regional private income and its embedded carbon emissions: sources, flows and inequalities.

Composing regional total income jointly with government income, private income represents levels of development and affluence from the household perspective. Considering the need for fair carbon emission reduction responsibility distributions among regions with divergent income levels, private income-embedded emission (PIEE) and the inter-regional inequalities remain to be explored. Combining input-output analysis and the Gini coefficient, this study traces the sources and disposals of regional private income in China, as well as their embedded carbon emission flow, and quantifies the distribution and inequality of PIEE across industrial sectors and provincial regions. Results indicate that the sectors of power and heat, smelting and pressing of metals, and manufacture of non-metallic mineral products contribute the most to PIEE. Hebei and Inner Mongolia have larger PIEE, while emissions embedded in private income disposals are primarily driven by consumption of products from agriculture, light industry, and services. Regions clustering at the beginning (Beijing, Shanghai, Tianjin) of the C-Lorenz curve of PIEE account for 19.3% of private income, while 8.2% in PIEE, with the percentages for those clustering at the end (Inner Mongolia, Ningxia, Xinjiang) as 10.0% and 28.5%. The findings provide insights into strategizing emission reduction along the entire value flow and coordinating carbon emissions, income and emission reduction responsibility.

Economic crises and energy use: An input–output analysis of Catalonia's 2008–2014 financial crisis

AbstractThe impact of economic crises on an economy's energy consumption, considering its sectorial interactions, remains an unexplored area. For this article, we investigated the structural sectorial relationships in energy terms before, during, and after Catalonia's 2008–2014 financial crisis, using environmentally extended input–output analysis. We used three input–output tables from 2005, 2011, and 2014, for which we constructed and employed five vectors representing sectorial energy consumption (“natural gas,” “coal,” “petroleum,” “electricity,” and “biomass and waste”) for 41 economic sectors. We studied the evolution of backward and forward linkage coefficients in terms of energy, as well as key sectors over this period. Our findings reveal that most sectors, particularly energy‐intensive ones, experienced a reduction in both backward and forward linkages. However, the relative importance of sectors in the Catalan economy remained relatively stable over the years, indicating a certain level of persistence in this indicator throughout the period, despite the economic crisis.

A 2023. ÉVI WKF KARATE VILÁGBAJNOKSÁG NÉZŐINEK FOGYASZTÁSI SZOKÁSAI ÉS A NEMZETGAZDASÁGI HATÁSOK VIZSGÁLATA

Sporting event tourism is a rapidly expanding segment of sports tourism (DREYER, 2002; WEED, 2006; BÁNHIDI, 2015; BORBÉLY-MÜLLER, 2015; LAFLIN, 2018). Alongside the growing number of events, domestic and international spectators have also increased significantly (LAFLIN 2018, LACZKÓ-STOCKER, 2020). Hungary hosted the Karate World Championship for the first time in karate history. This study aimed to analyze the consumption habits of domestic and international spectators attending the event. A questionnaire survey of 806 visitors was conducted, and the data was analyzed using SPSS. Economic impacts were assessed using input-output analysis based on the Sectoral Balance of Relations. Results indicated that the event's tourism appeal was primarily local and regional, with 78.7% of domestic respondents traveling less than 50 km. Domestic spectators attended an average of 2.76 competition days during the six-day event, while international visitors spent 4.42 nights in Hungary. The average total expenditures were HUF 43,075.26 for domestic spectators and HUF 471,741 for international spectators. The event contributed HUF 1.55 billion to Hungary's GDP. The World Championship reinforced Hungary's status in sports tourism, showcasing the economic and social benefits of hosting international events. Positive feedback from spectators affirmed the successful organization and highlighted the continued viability of such events in Hungary.

Network structures and mitigation potential of trade linked global agricultural greenhouse gas emissions

Since agriculture is a major source of greenhouse gas emissions, accurately calculating these emissions is essential for simultaneously addressing climate change and food security challenges. This paper explores the critical role of trade in transferring agricultural greenhouse gas (AGHG) emissions throughout global agricultural supply chains. We develop a detailed AGHG emission inventory with comprehensive coverage across a wide range of countries and emission sources at first. Utilizing this inventory, the multi-regional input-output analysis is integrated with the complex network analysis to specifically reveal the characteristics of global AGHG flow networks. Finally, scenario analyses reflecting current trends and policy changes in global agriculture are conducted to investigate the emission reduction potential of different networks. The results show that the community division and characteristics of different AGHG networks vary, with more communities in the rice-CH4 and livestock-CH4, N2O networks, and fewer in the cropland-N2O network. Production-side technology improvements (reducing direct carbon emission intensities) and consumption-side livestock products substitution can contribute to the reduction of global AGHG emissions. At the same time, these impacts may propagate to other countries through AGHG networks. In contrast, localization substitution has minimal impact on AGHG emissions and may even result in slight negative effects. It is suggested that enhancing cooperation between countries from a network perspective, such as strengthening the transfer of advanced production technologies within communities, could help reconceptualize global agricultural decarbonization.

Assessing recycled concrete’s sustainability with emergy theory and input–output modeling

This study is the first to integrate emergy theory, life cycle assessment (LCA), and input-output analysis (IOA) to analyze the environmental performance of conventional concrete (CC), recycled coarse aggregate concrete (RAC), recycled fine aggregate concrete (RFC), and recycled powder concrete (RPC). It comprehensively covers the entire life cycle from raw material extraction to waste disposal, employing dynamic emergy flowcharts to visually represent emergy inputs and pollutant emissions at each stage. By introducing an emergy-based input-output emission coefficient, this study standardizes environmental impact assessments across different material flows, enhancing both accuracy and comparability. The findings reveal that recycled concrete significantly reduces emergy consumption and pollutant emissions, especially in cement production, where its reduction potential is most pronounced. Additionally, the findings highlight recycled concrete’s ability to enhance resource efficiency and minimize environmental degradation. This study contributes an innovative emergy-input-output evaluation framework based on Cradle to Cradle (C2C) principles, providing valuable insights for optimizing and selecting sustainable building materials to promote a circular construction economy.

Deconstruction and analysis of global biodiversity loss transfer network based on the social network analysis method.

Biodiversity is crucial for maintaining ecosystem stability and achieving sustainable development. However, global biodiversity loss is a common challenge faced by most countries. Therefore, based on the data from the International Union for Conservation of Nature (IUCN) Red List of Threatened Species and the Eora database, we used the multi-regional input-output (MRIO) model to calculate biodiversity loss in 188 countries. We constructed a global biodiversity loss transfer network from the binary and weighted perspectives and deconstructed the evolution characteristics and the factors influencing the network from the "relationship" perspective using social network analysis (SNA) and quadratic assignment procedure (QAP) method. The global biodiversity loss transfer network had a typical network structure with dense connections, demonstrating spatial correlation characteristics. The countries with top in- and out-degree centrality rankings were developed and large-scale emerging economies and developing countries in Africa, respectively, implying that the former are responsible for "importing" large amounts of biodiversity and transferring biodiversity loss to the latter. The block model analysis indicated that the transfer network was divided into different functional blocks, with biodiversity spillover effects. The QAP analysis revealed that the differences in geographical adjacency, per capita GDP, urbanization rate, environmental regulation, and agricultural land proportion explained 3.627% of the changes in the global biodiversity loss transfer network. Our results suggested that the relationships of biodiversity loss transfer among countries should be considered by policymakers to address biodiversity challenges. Therefore, governments should recognize the remote responsibility, reduce unsustainable consumption and production, develop sustainable trade, and make trade policies considering the transfer of biodiversity impacts.

The effect of coal mine closures on worker migration in Poland: an input-output analysis

Closing coal mines in Poland is an important part of the energy transition aimed at reducing greenhouse gas emissions and meeting climate commitments. These decisions are particularly important in mining regions such as Silesia, where the mining industry is the main pillar of the economy. Given the gradual closure of mines and the reduction of employment in the mining sector, there is a need to analyse the migration of workers and their potential adaptation to the labour market. This paper aims to examine the impact of mine closures on the employment structure of the national economy using the input-output method. The analysis includes a decomposition of input-output tables (TPMD), in which branches such as thermal coal, coking coal, and lignite were distinguished. This has made it possible to precisely track economic flows between subsectors of the economy and identify which sectors are most vulnerable to the negative effects of reduced coal mining in Poland. The analysis also shows how a change in coal mining may affect related sectors such as energy, transport, and steel, increasing the need for structural adjustments. In particular, the article focuses on possible scenarios for the migration of workers from the closing mines and their re-deployment. Various coal reduction (WR) variants are considered, including WR25%, WR50%, WR75%, and WR100%, reflecting scenarios of declining domestic production. The paper also considers the possible substitution of domestic coal with imported raw materials (WS). The article concludes by identifying the most important conclusions.

Family Firms' Boards: A Systematic Review and Research Agenda

ABSTRACTResearch Question/IssueDespite the growing interest in family firms (FFs) and their boards of directors (boards), the empirical research remains fragmented, which makes a comprehensive understanding challenging. This review aims to unify the research landscape and to provide a framework for future studies to better understand boards in FFs.Research Findings/InsightsOur analysis of 99 papers published between 2001 and 2023 shows that the literature on boards in FFs relies heavily on input–output models that use archival data. Although traditional perspectives remain dominant, new ideas are gaining traction by recognizing the importance of family ownership, exploring alternative or complementary theoretical lenses, uncovering board processes, and using advanced analytical methods.Theoretical/Academic ImplicationsWe propose five research directions: (1) Investigate how family dimensions shape FF boards and their impact on firm outcomes; (2) examine the impact of board characteristics on board decision‐making and effectiveness in FFs; (3) analyze the specific mechanisms through which board processes in FFs influence firm outcomes; (4) expand the research geographically and explore the influence of temporal and institutional contexts on FF boards; and (5) employ a wider range of research methods to study FF boards.Practitioner/Policy ImplicationsOur results indicate that research on boards in FFs is evolving and broadening, most notably, through the integration of classical theories borrowed from the general management field (e.g., agency, stewardship, and resource dependence theories) with more specific theories (e.g., socioemotional wealth theory) and themes related to corporate social responsibility.

Simulation analysis of the damage and recovery process in natural disasters: a case study of high-speed railways in Sichuan Province, China

This study employs a dynamic input–output model to simulate the recovery process of a high-speed railway and the subsequent regional economic recovery following an earthquake. The analysis considers the impact of earthquakes of varying magnitudes on Sichuan Province, its neighboring areas, and the entire nation of China. The simulation is conducted against the backdrop of the restoration and reconstruction efforts in Sichuan Province post-earthquake. The findings reveal that the recovery speed of the high-speed railway transportation sector is influenced not only by the established recovery time, but also by the pace of recovery in adjacent industrial sectors and external inputs. Accelerated recovery in adjacent industrial sectors contributes to a faster recovery of the high-speed railway transportation sector. Furthermore, once the adjacent industrial sectors return to normal levels of recovery, the high-speed railway transportation sector follows suit, reaching the established recovery rate. In terms of regional economic recovery, provinces with smaller economies experience higher rates of economic reduction due to earthquakes. Conversely, provinces with a significant proportion of high-speed railways in their economies witness higher rates of economic reduction following seismic events. The insights derived from this study hold practical significance for guiding regional economic and transportation recovery and reconstruction efforts post-major earthquakes.

Advanced services as a new frontier for China’s value chain cooperation with European manufacturing

This article presents a cross-sectoral analysis of service flows, with a particular emphasis on technologically advanced services, from China to the European manufacturing sector. The research question examines the extent to which the increasing integration of Chinese technologically advanced services into European manufacturing aligns with China’s internal trends in servicification and its strategic agenda for expanding service exports within global value chains. Employing input-output modelling, the study demonstrates China’s expanding role as a supplier of technologically advanced services to European manufacturing and identifies specific industries within Europe that exhibit the highest dependency on Chinese services.

The importance of the electric sector: a national and regional input-output analysis

This paper analyzes the structural evolution of the electric sector in Brazil between 2010 and 2019 using the Input-Output framework. National results show that the industry has above average production multipliers that follow Brazilian economic performance and is considered a key sector – especially due to its supply –, having linkages with all other activities that exceed the economy’s average. Given its importance, the paper analyzes the regional gains and spillovers from larger investments in the sector, revealing that the Northeast is the region with the most significant impact on production, taxes, employment, and salaries.

The economic value of transport infrastructure in the UK: an input-output analysis

Transport infrastructure systems operate in, and are shaped by, the specific context in which they are expected to perform, contribute to the system-of-systems that support civilised life, and thy must strive to be sustainable and resilient. However, transport, one of the ‘economic infrastructures’, is viewed narrowly in political circles as a vehicle for economic prosperity: political focus falls on the economic pillar of sustainability. One perennial challenge, addressed herein, concerns the inclusion of social and environmental value into such performance judgements. A deep understanding of system interdependencies is essential when comparing input-output tables (a top-down approach) with cost-benefit analysis (CBA, a bottom-up approach). CBA works best when there is adequate information to calculate a monetary value for all economic, social and environmental outcomes, whereas input-output tables are most effective when environmental and social value are kept distinct from economic value, and where the beneficial economic impacts extend across multiple sectors (CBA is inadequate in this regard). This research uses the World Input-Output Database and principal component analysis (PCA) to develop a model to capture this complex accounting process. In recognising how past interdependencies inform future development, this study's model provides new insights into indirect economic value creation within infrastructure systems.