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This study presents the first comprehensive key sector analysis for Nepal, using an integrated approach of linkage analysis and hypothetical extraction method with the 2022 input–output table. The empirical analysis identifies three strategically crucial sectors. Agriculture emerges as the economy's foundation, demonstrating the highest impact on both output and value-added generation, reflecting its fundamental role in employment and GDP contribution. Wholesale Trade exhibits balanced demand–supply effects through market integration, while Financial Intermediation shows strong supply-side influence through credit intermediation services. Moreover, Construction and the Electricity, Gas, and Water Supply sectors play vital supporting roles, enhancing infrastructure development and leveraging extensive hydropower resources to boost growth potential. The analysis reveals interesting disparities between output and income generation across sectors, particularly in the Food, Beverages, and Tobacco sector. These empirical findings align with and provide evidence-based support for recent government initiatives. While acknowledging methodological limitations regarding employment and environmental data, this research establishes an evidence-based framework for strategic sector prioritization and offers policy recommendations for sustainable economic development. [ABSTRACT FROM AUTHOR]

It is standard practice to treat input-output (I-O) technical coefficients as fixed. The coefficients are fixed when $\sigma $ σ , the elasticity of substitution, is zero, a restriction mostly not supported by 25 years of I-O tables for Australia. We offer a simple way of allowing for variable coefficients with a CES approach. Finally, using various values of $\sigma $ σ in CGE simulations establishes that taking coefficients as fixed has misleading economic implications. [ABSTRACT FROM AUTHOR]

The dynamic characteristics of mode behavior in a low-speed, single-stage axial compressor are crucial for studying linear stall inception. An input–output analysis framework has been established, enabling the introduction of forcing into the compressor system and identifying the most energetic mode. Both standard and compressed input–output analysis are conducted to explore sensitive forcing positions and flow variables, with opposition control employed to suppress energy gain. As throttling progresses, a shift in high energy gain distribution from high-order to first-order circumferential modes is observed, with two distinct branches emerging across the domain of circumferential mode numbers and forcing frequencies. Compressed input–output analysis shows that limiting the forcing range to the shroud, from the inlet to the rotor blade section, is sufficient to excite the energetic mode in the current cases. Subsequently, opposition control is applied at the shroud to suppress energy amplification and modulate stall propensity within these two distinct branches. The results reveal that axial velocity control reduces energy amplification and suppresses perturbation modes related to stall inception. A comprehensive assessment of componentwise energy amplification is conducted, considering various variable forcing. The predicted results indicate that velocity perturbations are the predominant factors influencing the resolvent mode distribution pattern. Moreover, opposition control significantly impacts the critical branch associated with stall inception. [ABSTRACT FROM AUTHOR]

In this paper, the industry classification of digital economy is determined, the comprehensive index framework of digital economy development level in China is constructed, and the input-output analysis method and index method are used to measure the digital investment status of manufacturing industry in China. At the same time, based on the realistic demand that China's manufacturing industry needs to climb the regional value chain, this paper constructs the forward participation index, backward participation index, regional value chain position index, and regional value chain Balassa, and analyzes the current situation of China's manufacturing industry in RCEP region. Construct a semi-parametric additive model to explore the impact of digital investment on China's manufacturing industry's participation in the RCEP regional value chain. In addition, this paper uses the community analysis method to build the RCEP regional manufacturing digital input trade network, and comprehensively evaluates the trade network pattern of digital input from multiple dimensions. The results show that: (1) the digital investment in China's manufacturing industry is increasing year by year. (2) The indicators of manufacturing industry's participation in RCEP regional value chain show a fluctuating situation, which is generally consistent with China's economic development. (3) Within a certain range, digital investment will promote the participation of China's manufacturing industry in the RCEP regional value chain. China is gradually becoming an important participant in RCEP regional trade. According to the corresponding measurement results, it provides policy suggestions for the deep integration of China's manufacturing industry and digital economy. [ABSTRACT FROM AUTHOR]

This paper introduces the concepts of spectral influence and spectral cyclicality, both derived from the largest eigenvalue of a graph’s adjacency matrix. These two novel centrality measures capture both diffusion and interdependence from a local and global perspective respectively. We propose a new clustering algorithm that identifies communities with high cyclicality and interdependence, allowing for overlaps. To illustrate our method, we apply it to input-output analysis within the context of the Moroccan economy. [ABSTRACT FROM AUTHOR]

The waterway transportation industry, recognized for its high capacity, cost-effectiveness, and energy efficiency, plays a vital role in global freight transport and trade. In China, it serves as a key pillar supporting the national economy and foreign trade. However, its heavy dependence on fossil fuels has intensified carbon emission challenges, creating significant barriers to achieving sustainable development goals. This study employs Input-Output Analysis and the Logarithmic Mean Divisia Index model to examine the changes in carbon emissions and their driving factors in China's waterway transportation industry from 2002 to 2020, while also exploring potential pathways for emission reduction. The findings reveal the following: (1) From 2002 to 2020, despite a substantial rise in total carbon emissions, the industry has been progressively transitioning towards a low-carbon trajectory through the adoption of clean energy technologies and optimization of its energy structure. (2) Economic scale effects have been the primary drivers of carbon emission growth, with population-scale effects playing a lesser role. Since 2011, the implementation of green technologies and low-carbon management strategies has effectively stabilized emission growth rates. (3) Improvements in energy carbon intensity and transportation energy intensity have significantly reduced carbon emissions. Moreover, the promotion of clean energy technologies and energy-saving measures has substantially lowered the industry's carbon emission intensity. [ABSTRACT FROM AUTHOR]

This study, by employing an input-output and simulation analysis, aims to examine policies to build back better the tourism sector's post-COVID-19 pandemic by taking Indonesia as a case study. The result confirms that to build back a better tourism sector in the post-COVID-19 pandemic, the government of Indonesia needs to maintain the supply of domestic inputs used as the primary source of intermediate inputs in the tourism sector and other sectors related to the tourism sector. The simulation analysis indicated that the worst effect of the COVID-19 pandemic on the tourism industry occurred in output reduction compared with the value-added and labor income losses. However, the government needs close collaboration with the private sector and other wide-range tourism stakeholders in determining tourism policies post-COVID-19 pandemic, apart from the importance of evidence-based policy research. This study contributes to international comparative policy research in the tourism field post-COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

AbstractThe Mongolian economy relies heavily on mineral exports, making it highly vulnerable to external demand and price shocks. Economic diversification is essential to reducing this dependency and enhancing resilience. This study aims to identify key sectors in the Mongolian economy and discuss their potential for economic diversification. An input-output analysis was conducted using the input-output table for 2018, employing backward and forward linkages along with multiplier analysis. The findings highlight energy and manufacturing are key sectors due to their strong linkages and multiplier effects on output, employment, and value-added. In contrast, finance and mining significantly contribute to labour productivity, while labour-intensive public sectors, including education, arts, health, and public administration, play a critical role in household income generation. Prioritizing investments in manufacturing and energy is crucial, as these sectors positively impact upstream sectors by adding value to mineral and livestock-based commodities, thereby playing a vital role in diversification efforts. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

We examine the effect of emissions pricing on the cost of Canadian food. We describe emissions pricing policies relevant to the agriculture and food sectors and the differing design details of various provincial systems and the federal Greenhouse Gas Pollution Pricing Act. To quantify the potential effect of such policies, we use a detailed input‐output model of Canada's economy to estimate both the direct and indirect cost increases across sectors. We also explore how exemptions and policy design can mitigate what would otherwise be larger effects. In particular, imported inputs, generous exemptions for most direct emissions in primary agriculture, and special provisions for large industrial emitters all dampen the effect. Overall, we find that emissions pricing at $80 per tonne could potentially increase the cost of domestically produced food by approximately 0.8% on average. Combined with imported food that is not directly affected by emissions pricing, we find an average effect of approximately 0.5%. While we abstract from general equilibrium responses, our analysis suggests emissions pricing in Canada has only a modest effect on food costs. [ABSTRACT FROM AUTHOR]

Inter-regional input-output (IRIO) tables are essential for socioeconomic and environmental analysis. This paper compiled a continuous time series of Chinese IRIO tables with a detailed regional and sectoral classification, covering a longer period from 1987 to 2017 than existing Chinese IRIO tables. Additionally, we integrated the China provincial CO2 emission inventory data (1987–2017) to analyze trends and identify the main driving factors behind regional economic linkages and carbon emissions changes. Specifically, we adjusted the initial values of the international and interprovincial imports and exports using customs data. Subsequently, we employed the minimum cross-entropy model to balance the adjusted input-output tables (IOTs) from both row and column perspectives. Following this, we estimated the interprovincial trade flow for each sector using the gravity model. Then, we balanced these estimates with the minimum cross-entropy model to form the multi-regional input-output (MRIO) table. Finally, we constructed the IRIO table based on the proportion assumption. The compiled IRIO tables, integrated with carbon emission data, have significant applications in regional economic analysis, policy evaluation, and environmental studies. [ABSTRACT FROM AUTHOR]

Water is crucial for achieving the UN Sustainable Development Goals, particularly SDG 6. As a major source of water use and pollution, industrial sector requires improved water management based on more systematic and refined analysis. Such analysis, however, is compromised by the accuracy, granularity, and coverage of industrial water data. Here we present an open dataset of China's industrial water use, compiled from 1,480,265 plant-level reports. This high-resolution multi-scale dataset offers unparalleled details, supporting multi-scale analysis at the province, city, and county levels, and across 2-digit, 3-digit, and 4-digit industrial classifications. It provides comprehensive information on water use, recycling, pollution, and wastewater processing. Such data enables further macro- and micro-level analysis, including multi-regional input-output analysis, structural decomposition analysis, statistical analysis, machine learning, as well as many other advanced analytical methods. This dataset can equip researchers and policymakers with a valuable tool to advance sustainable water management, fostering alignment with global sustainability goals. [ABSTRACT FROM AUTHOR]

In global trade, there is a phenomenon that the "economic gains" and "ecological damages" of some countries and regions are not consistent. Using the multi-regional input-output model (MRIO), this study measures the transfer of embodied carbon and value-added in trade among 16 countries or regions, including the European Union, the United States and other countries from 1995 to 2022. On this basis, we use the four-quadrant analysis method to classify the carbon inequality in international trade, and construct the carbon inequality index to quantify the carbon inequality situation in bilateral trade. The results indicate that carbon inequality between international trade can be divided into three categories: victims of absolute carbon inequality, relative carbon equality and beneficiaries of absolute carbon inequality. Carbon inequality in bilateral trade exists between developed and developing countries, as well as between developing countries. Finally, a carbon compensation accounting model is constructed to measure the monetary value of cross-regional carbon offset, which provides data support for international carbon emission reduction cooperation. Our study contributes to contemplating the impacts of international trade and provide recommendations for global equity and sustainable development. [ABSTRACT FROM AUTHOR]

• China's expanding final demand scale has contributed to increasing carbon emissions in major trading partners. • The promotion effect is particularly pronounced in the primary and natural resources, capital-intensive manufacturing, and knowledge-intensive manufacturing industry. • Covid-19 pandemic has had a profound impact on international trade patterns and carbon emissions. This study analyzed changes in the carbon emissions of China's top five trading partners using a structural decomposition model based on inter-country input-output analysis. The main influencing factors were analyzed using constant price input-output tables for 2007, 2012, 2017, and 2021. Changes in the carbon emissions of the trading partner economies during 2007–2021 were decomposed into 15 essential factors to investigate the impacts of intermediate and final demands, and then isolate the influence of intermediate and final demands of China. The results revealed the following: (i) Carbon emissions in the developed economies experienced decline followed by increase after the Covid-19 pandemic, whereas ASEAN economies experienced steady increase in carbon emissions. (ii) Carbon intensity was one of the most important factors affecting carbon emissions. (iii) The size of China's expanding final demand contributed to an increase in carbon emissions in the primary and natural resources industry, capital-intensive manufacturing industry, and knowledge-intensive manufacturing industry. [ABSTRACT FROM AUTHOR]

• A novel input-output model that differentiates firm size heterogeneity is proposed to investigate the export-related CO 2 emission performance. • China's small and medium sized enterprises exported dirtier than large ones. • Structural decomposition analysis is used to identify the determinants of the gaps in emission intensity for exports from different sized enterprises. • The cleaner export structure and higher share of imported intermediate inputs are two important driving factors. The thriving development of small and medium sized enterprises (SMEs) and their growing engagement in global markets have exerted significant environmental transformations. This study assesses the environmental effects of China's exports from small, medium, and large enterprises by constructing novel input-output tables that distinguish firm size heterogeneity for 2007, 2012, and 2017. We find that SMEs are responsible for over 60 % of the CO 2 emissions embodied in China's industrial exports. Notably, the emission intensities for exports (EIEs) by large enterprises are on average 8.4 % and 20.8 % lower than those by medium and small enterprises, respectively. The results of structural decomposition analysis highlight several major determinants including a cleaner export structure and a higher proportion of imported intermediate inputs. Our study provides a novel input-output framework applicable to analyzing SME-related issues for more countries and underscores some strategies to enhance the cleaner export performance of SMEs. [ABSTRACT FROM AUTHOR]