Publications by authors named "Shantong Li"

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 CO emission inventory data (1987-2017) to analyze trends and identify the main driving factors behind regional economic linkages and carbon emissions changes.

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With the increasing fragmentation of global production, China's participation in cross-border production sharing activities has had a considerable impact on the nation's economy and carbon dioxide (CO) emissions. This study applied the Tapio model to quantitatively evaluate the decoupling between CO emissions and economic growth in China, dividing the decoupling index based on global value chains (GVCs) and domestic production within the IO framework, and introducing structural decomposition analysis (SDA) to analyze the GVC-related factors to the decoupling. The relevant research results are fourfold.

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The need to make more accurate grain demand (GD) forecasting has become a major topic in the current international grain security discussion. Our research aims to improve short-term GD prediction by establishing a multi-factor model that integrates the key factors: shifts in dietary structures, population size and age structure, urbanization, food waste, and the impact of COVID-19. These factors were not considered simultaneously in previous research.

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Input-Output (IO) data describing supply-demand relationships between buyers and sellers for goods and services within an economy have been used not only in economics but also in scientific, environmental, and interdisciplinary research. However, most conventional IO data are highly aggregated, resulting in challenges for researchers and practitioners who face complex issues in large countries such as China, where firms within the same IO sector may have significant differences in technologies across subnational regions and different ownerships. This paper is the first attempt to compile China's interprovincial IO (IPIO) tables with separate information for mainland China-, Hong Kong, Macau, Taiwan-, and foreign-owned firms inside each province/industry pair.

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With the accelerated expansion of global value chains (GVCs), China occupies an increasingly important position in the global production division system, which has important impacts for its economy and environment. Comprehensively measuring the economic benefits and emissions costs of China's participation in GVCs, and striving to achieve a mutually beneficial state of GVC upgrade and low-carbon economic development, are critical issues for China. This study applies the accounting framework of value-added trade and embodied CO emission trade to measure the potential CO emissions cost of China's value-added gains through traditional trade, simple GVC, and complex GVC from 2000 to 2014.

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Carbon dioxide (CO) emissions are currently a hot topic of global concern. It is of great significance for reducing CO emissions to fully understand the transfer pattern of CO emissions among industries and the key factors affecting CO emissions. This paper uses the structural path analysis model to explore deeply the main paths of inter-industry transfer of CO emissions in China from 2002 to 2017 and applies the structural path decomposition model to analyze the main factors affecting CO emissions in specific paths from the perspectives of CO emission intensity, intermediate product input structure, final demand structure, per capita final demand, and population size.

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In China, cities are the basic units for implementing CO abatement policies. However, few studies have comprehensively explored the spatial characteristics of CO emissions (CEs) and their influencing factors at the city level from different perspectives. After collecting spatial data from 280 Chinese prefecture-level cities for 2005, 2012, and 2015, this work firstly uncovered the overall and local spatial characteristics of CEs by adopting spatial autocorrelation analysis.

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Controlling CO emissions (CEs) is an important measure to mitigate global climate change. In recent years, the research on household consumption and its environmental impact has become a research hotspot in the field of sustainable development. Taking 2000-2014 as the research period, this paper studies the indirect CO emissions of household consumption (ICEs-HC) in China by using the Multi-region Input-Output model.

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The original publication of this paper contains a mistake. The correct image of figure 4 is shown in this paper. The original article has been corrected.

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Based on the China's 1997, 2002, 2007, and 2012 multiregional input-output model, this study calculates China's provincial CO emissions from investment demand and interprovincial transfer of CO emissions caused by investment demand. The findings of this study are as follows: (1) From 1997 to 2012, the CO emissions from China's investment demand have seen rapid growth-the CO emissions from investment demand has increased by 4.52 times, and the per capita CO emissions caused by investment demand has increased by 4.

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Chinese provinces ultimately implement China's national climate policies. In the 2000s, there were unbalanced emission transfers (emissions produced in one region but consumed in other regions) between China's well- and less-developed regions, mainly related to demand in the well-developed eastern provinces. In the past decade, the plateau in China's exported emissions and changes in its industrial structure suggest that the features of the provincial emission transfers could have changed.

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Jing-Jin-Ji region (i.e., Beijing, Tianjin, and Hebei) is China's key development region, but it is also the leading and most serious air pollution region in China.

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This article analyzes the role of dynamic economic resilience in relation to recovery from disasters in general and illustrates its potential to reduce disaster losses in a case study of the Wenchuan earthquake of 2008. We first offer operational definitions of the concept linked to policies to promote increased levels and speed of investment in repair and reconstruction to implement this resilience. We then develop a dynamic computable general equilibrium (CGE) model that incorporates major features of investment and traces the time-path of the economy as it recovers with and without dynamic economic resilience.

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In the counties with rapid economy and carbon emissions (CEs) growth, CEs embodied in interprovincial trade (CEs-PT) significantly impacts the CEs amount and structure and represents a key issue to consider in CEs reduction policies formulation. This study applied EEBT and two-stage SDA model to analyze the characteristics and driving force of spatial-temporal evolution for net CEs-PT outflow in the Northeast Industrial District of China (NID). We found that, during 1997-2007, the net CEs-PT flowed out from NID to 16 south and east provinces, then to 23 provinces all over China, and its amount has increased 216.

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Commodity trade between regions implies a large amount of energy transfer. As an important economic growth pole of China, the Jing-Jin-Ji area (Beijing-Tianjin-Hebei) is also one of the areas with the largest energy consumption in China. Moreover, the primary energy consumer goods in this area are fossil fuels, such as coal.

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This paper developed an estimation model for the contribution of exports to a country's regional economy based on the Chenery-Moses model and conducted an empirical analysis using China's multi-regional input-output tables for 1997, 2002, and 2007. The results indicated that China's national exports make significantly different contributions to the provincial economy in various regions, with the greatest contribution being observed in the eastern region and the smallest in the central region. The provinces are also subjected to significantly different export spillover effects.

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