Resource abundance, industrial structure, and regional carbon emissions efficiency in China

Wang, Keying; Wu, Meng; Yong, Sun; Shi, Xunpeng; Sun, Aixin; Zhang, Ping

doi:10.1016/j.resourpol.2019.01.001

Cited by 350 publications

(111 citation statements)

References 59 publications

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“…Due to its ability to solve problems of input-output slack and avoid the influence of radial and oriented choice, the SBM model has become the most powerful and popular tool for evaluating efficiency. It has been successfully used to evaluate the performance of banks (Juo et al, 2012;Avkiran and Cai, 2014), airports (Yu, 2010), the environment (Na et al, 2017;Cecchini et al, 2018;Wang et al, 2019), and more. For this reason, the SBM model was chosen to measure environmental performance.…”

Section: Measurement Of Environmental Performancementioning

confidence: 99%

“…We have selected the appropriate indicators and data sources based on this particular model. According to literature review (Zhou et al, 2006(Zhou et al, , 2007Wang et al, 2013;Wu et al, 2013;Jin et al, 2014;Wang et al, 2019), we find that capital investment, labor input, social water consumption, energy consumption, GDP, carbon dioxide (CO 2 ) emissions, industrial wastewater, and industrial emissions are the most used indicators. However, capital investment is somewhat relevant to social capital, so we didn't choose it as our indicators.…”

Section: Measurement Of Environmental Performancementioning

confidence: 99%

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How Social Capital Affects Environmental Performance in China

2020

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Chinese society's unique characteristics present challenges with regard to discovering new ways to tackle tremendous environmental problems. This paper examines the effect of provincial social capital on environmental performance in China. In the first stage of the analysis, we measured the environmental performance levels of the 2011-2017 panel data of 30 provinces in China. We did this using data envelopment analysis (DEA). After introducing the concept of social capital, we innovatively built the social capital index system based on China's national conditions and measured social capital data from three perspectives. Then, we used the Probit regression model to explore the effect of social capital on environmental performance. The results show that the environmental performance of the well-known and better developed regions of China (such as Beijing, Shanghai, etc.) is significantly higher than other regions. Social capital and environmental performance are related in general. However, the effect of social capital on environmental performance is heterogeneous in different regions. They are more consistent in the eastern and southwest regions but are less stable in other regions. Among the three types of social capital, structural capital has the most obvious benefits for environmental performance. This is followed by relational capital and innovative capital. Furthermore, it has been found that the proportion of the tertiary industry in GDP and the level of social trust are the largest indicators of the rates at which structural capital and relational capital contribute, respectively, to environmental performance.

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Section: Measurement Of Environmental Performancementioning

confidence: 99%

Section: Measurement Of Environmental Performancementioning

confidence: 99%

How Social Capital Affects Environmental Performance in China

2020

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“…The results presented that the level of economic development has a positive relationship with energy efficiency. Wang et al [36] showed a negative correlation between resource richness and carbon emission efficiency in China from 2003 to 2016.…”

Section: Introductionmentioning

confidence: 99%

The Energy Efficiency and the Impact of Air Pollution on Health in China

Chiu

Chang

et al. 2020

Healthcare

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The rapid growth of China's economy in recent years has greatly improved its citizens' living standards, but economic growth consumes many various energy sources as well as produces harmful air pollution. Nitrogen oxides, SO 2 (sulfur dioxide), and other polluting gases are damaging the environment and people's health, with a particular spike in incidences of many air pollution-related diseases in recent years. While there have been many documents discussing China's energy and environmental issues in the past, few of them analyze economic development, air pollution, and residents' health together. Therefore, this study uses the modified undesirable dynamic two-stage DEA (data envelopment analysis) model to explore the economic, environmental, and health efficiencies of 30 provinces in China. The empirical results show the following: (1) Most provinces have lower efficiency values in the health stage than in the production stage. (2) Among the provinces with annual efficiency values below 1, their energy consumption, CO 2 (carbon dioxide), and NOx (nitrogen oxide) efficiency values have mostly declined from 2013 to 2016, while their SO 2 efficiency values have increased (less SO 2 emissions). (3) The growth rate of SO 2 efficiency in 2016 for 10 provinces is much higher than in previous years. (4) The health expenditure efficiencies of most provinces are at a lower level and show room for improvement. (5) In most provinces, the mortality rate is higher, but on a decreasing trend. (6) Finally, as representative for a typical respiratory infection, most provinces have a high level of tuberculosis efficiency, indicating that most areas of China are highly effective at respiratory disease governance.With the largest coal demand in the world, the China government attaches great importance to the prevention and treatment of air pollution. The World Energy Outlook 2017 China Special Report [3] showed that China will continue in its efforts to intensify energy technology innovation, improve the clean and efficient use of fossil energy, accelerate the construction of a clean, low-carbon, safe, and efficient modern energy system, and strive to fulfill its responsibilities and obligations. "The Action Plan for the Comprehensive Management of Air Pollution in the Autumn and Winter of 2019-2020 in the Yangtze River Delta Region" [4] presents the regulation of air pollution in 41 cities at the prefecture level and above in this region for adjusting the industrial structure of heavily polluting industries. Many past research studies have focused on the efficiency of production, energy, environment, treatment and undesirable output analyses, such as . In addition to energy and environmental efficiency analyses, some scholars have explored the effects of exposure to air pollution on human health, such as [42][43][44][45][46][47].Past related literature is generally based on static analysis, lacking time considerations and mostly focusing on energy and environmental topics. Moreover, very few studies have jointly investigated econo...

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“…Therefore, it is a common focus of the current society and academia to explore the mechanisms of social and economic factors influencing urban air environmental pollution. Among them, the factor of industrial structure, as a critical social-economic indicator of concern, is more and more favored by researchers [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Investigating the Relationship between the Industrial Structure and Atmospheric Environment by an Integrated System: A Case Study of Zhejiang, China

et al. 2020

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Under the dual pressure of industrial structure upgrade and atmospheric environment improvement, China, in a transition period, is facing the challenge of coordinating the relationship between the industry and the environment system to promote the construction of a beautiful China. Based on system theory and coupling coordination model, the interaction analysis framework between industrial structure (IS) and atmospheric environment (AE) was constructed. An integrated system with 24 indicators was established by the pressure-state-response (PSR) model of IS and level-quality-innovation (LQI) model of AE. Then, we analyzed trends observed in coupling coordination degree (CCD) and dynamic coupling coordination degree (DCCD) for 11 cities in Zhejiang Province, China, using statistical panel data collected from 2006 to 2017. Conclusions were as follows: (1) the 11 cities' comprehensive level of the IS system shows a trend of stable increase, yet the comprehensive level of AE demonstrated a trend of fluctuation and transition. There are significant spatial variations among cities; (2) The CCD analysis results found that Hangzhou, Ningbo, and Wenzhou take the lead in realizing the transformation from barely coordinated development to superior coordinated pattern, while other cities were still in the stage of barely coordinated development; (3) the DCCD phase of 11 cities can be roughly divided into three types: upgraded-utmost development type (only Hangzhou), stable-harmonious development type (Wenzhou, Lishui, and Zhoushan) and transitional-harmonious development type (the remaining seven cities). This means, for most cities, the contradiction between the transformation process of IS and the AE has become increasingly prominent and intensified. Finally, three necessary and sustainable strategies were proposed to environmental policy makers.

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Resource abundance, industrial structure, and regional carbon emissions efficiency in China

Cited by 350 publications

References 59 publications

How Social Capital Affects Environmental Performance in China

How Social Capital Affects Environmental Performance in China

The Energy Efficiency and the Impact of Air Pollution on Health in China

Investigating the Relationship between the Industrial Structure and Atmospheric Environment by an Integrated System: A Case Study of Zhejiang, China

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