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Feng Wang
School of Economics and Finance, Xi’an Jiaotong University, Xi’an 710061, China

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Short Biography

Feng Wang holds a Ph.D. in Economics and is working as a professor of Economics at the School of Economics and Finance at Xi’an Jiaotong University, China. His research focuses broadly on the economics of environmental economics and management.

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Journal article
Published: 23 April 2021 in Sustainability
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The role of innovation for economic growth has been proved by studies. However, whether innovation can decrease environmental cost and energy security risks remains to be studied. To explore the theoretical mechanism of driving green economic growth by innovation, we constructed a four-sector endogenous growth model, including the final-goods sector, the intermediate-goods sector, the Research and Development (R&D) sector, and the energy sector. Then we measured the innovation-driven effect of green growth and calculated the green added value of 40 industries in China during 2005–2016. Based on the calculations, we used a threshold regression model to test the mechanism of driving green growth and decreasing energy security risks by innovation. The results showed that: (1) the innovation-driven effect on green growth increased from 0.2729 in 2005 to 0.3446 in 2016. (2) The proportion of green added value in the traditionally added value increased from 79.54% in 2005 to 92.25% in 2016. (3) Innovation had a threshold effect on green growth: the role of innovation in driving green growth weakened in the long term, but not in the short term (4) Innovation also had a threshold effect on energy security risk: after the innovation-driven effect crossed the threshold, innovation decreased energy security risk more significantly.

ACS Style

Feng Wang; Ruiqi Wang. The Mechanism of Driving Green Growth and Decreasing Energy Security Risks by Innovation in China. Sustainability 2021, 13, 4733 .

AMA Style

Feng Wang, Ruiqi Wang. The Mechanism of Driving Green Growth and Decreasing Energy Security Risks by Innovation in China. Sustainability. 2021; 13 (9):4733.

Chicago/Turabian Style

Feng Wang; Ruiqi Wang. 2021. "The Mechanism of Driving Green Growth and Decreasing Energy Security Risks by Innovation in China." Sustainability 13, no. 9: 4733.

Journal article
Published: 15 April 2021 in Sustainability
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The setting of a CO2 emission peak target (CEPT) will have a profound impact on Chinese industry. An objective assessment of this impact is of great significance, both for understanding/applying the forcing mechanism of CEPT, and for promoting the optimization of China’s industrial structure and the low-carbon transformation of Chinese industry at a lower cost. Based on analysis of the internal logic and operation of the forcing mechanism of CEPT, we employed the STIRPAT model. This enabled us to predict the peak path of China’s CO2 emissions, select the path values that would achieve the CEPT with the year 2030 as the constraint condition, construct a multi-objective and multi-constraint input/output optimization model, employ the genetic algorithm to solve the model, and explore the industrial structure optimization and low-carbon transformation of Chinese industry. The results showed that the setting of CEPT will have a significant suppression effect on high-carbon emission industries and a strong boosting effect on low-carbon emission industries. The intensity of the effect is positively correlated with the target intensity of the CO2 emissions peak. Under the effect of the forcing mechanism of CEPT, Chinese industry can realize a low-carbon transition and the industrial structure can realize optimization. The CEPT is in line with sustainable development goals, but the setting of CEPT may risk causing excessive shrinkage of basic industries—which should be prevented.

ACS Style

Feng Wang; Changhai Gao; Wulin Zhang; Danwen Huang. Industrial Structure Optimization and Low-Carbon Transformation of Chinese Industry Based on the Forcing Mechanism of CO2 Emission Peak Target. Sustainability 2021, 13, 4417 .

AMA Style

Feng Wang, Changhai Gao, Wulin Zhang, Danwen Huang. Industrial Structure Optimization and Low-Carbon Transformation of Chinese Industry Based on the Forcing Mechanism of CO2 Emission Peak Target. Sustainability. 2021; 13 (8):4417.

Chicago/Turabian Style

Feng Wang; Changhai Gao; Wulin Zhang; Danwen Huang. 2021. "Industrial Structure Optimization and Low-Carbon Transformation of Chinese Industry Based on the Forcing Mechanism of CO2 Emission Peak Target." Sustainability 13, no. 8: 4417.

Original article
Published: 10 March 2021 in Energy Efficiency
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China has implemented the energy intensity target (EIT) constraint policy to improve its energy efficiency for more than three decades. Producers in China need to consider factor prices, outputs, and EIT constraint while they plan the number of input factors. Therefore, this article brings the EIT into the conditional input demand function of an input factor and assesses the impacts of the elasticity of substitution between different production factors. By building two-factor substitution elasticity models with and without EIT constraints, this paper examines the impacts of EIT constraint on the elasticity of substitution between input factors in both the fossil fuel production sector and the non-fossil-fuel production sector. The main conclusions are, firstly, EIT constraint influences both own-price elasticity of an input factor and cross-price elasticity between different input factors. Secondly, EIT constraint hinders the responses of some input factors to the price changes of other input factors, and changes relationships between some input factors from complementary to substitute, or vice versa. Two policy implications are obtained. First, producers should consider the impacts of EIT constraint on their investment, labor input, energy input, and raw materials purchase and bring these impacts into their business strategies. Second, reducing energy input by changing prices of other production factors will be ineffective under EIT constraint.

ACS Style

Feng Wang; Xiying Liu; David M. Reiner; Ruiqi Wang. Impacts of energy intensity target constraint on elasticity of substitution between production factors in China. Energy Efficiency 2021, 14, 1 -26.

AMA Style

Feng Wang, Xiying Liu, David M. Reiner, Ruiqi Wang. Impacts of energy intensity target constraint on elasticity of substitution between production factors in China. Energy Efficiency. 2021; 14 (3):1-26.

Chicago/Turabian Style

Feng Wang; Xiying Liu; David M. Reiner; Ruiqi Wang. 2021. "Impacts of energy intensity target constraint on elasticity of substitution between production factors in China." Energy Efficiency 14, no. 3: 1-26.

Journal article
Published: 26 October 2020 in Journal of Cleaner Production
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Recently, some high-skilled workers tend to escape from areas with severe air pollution. The phenomenon is more prominent in two emerging economies, China and India, and they are facing the brain drain caused by air pollution. This paper establishes a partial equilibrium model about the relationship of air pollution and the flow of technological innovative professionals (TIP), and for the first time, examines the effect of air pollution on the accumulation of technological innovative human capital based on cross-country data from China and India. We find that air pollution will reduce the stock of TIP in some regions. The estimation results show that a 1% increase in the PM2.5 concentration of China’s cities leads to an approximate 146 people decrease in the stock of TIP, while a 1% increase in the PM10 concentration of Indian states leads to a 0.127% decrease in the stock of TIP. Further analysis of regional differences indicates that air pollution has a significant negative effect on the stock of TIP in economically developed areas of China, but has little effect on that in underdeveloped areas of China. Moreover, the results of robustness tests prove the stability of the findings in this study. This paper concludes with suggestions on how the country, local governments, enterprises, and research institutions could better deal with air pollution, attract and retain TIP, and effectively reduce brain drain.

ACS Style

Feng Wang; Min Wu. Does air pollution affect the accumulation of technological innovative human capital? Empirical evidence from China and India. Journal of Cleaner Production 2020, 285, 124818 .

AMA Style

Feng Wang, Min Wu. Does air pollution affect the accumulation of technological innovative human capital? Empirical evidence from China and India. Journal of Cleaner Production. 2020; 285 ():124818.

Chicago/Turabian Style

Feng Wang; Min Wu. 2020. "Does air pollution affect the accumulation of technological innovative human capital? Empirical evidence from China and India." Journal of Cleaner Production 285, no. : 124818.

Journal article
Published: 28 September 2020 in Sustainability
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To achieve the national carbon intensity (NCI) target, China should adopt effective mitigation measures. This paper aims to examine the effects of key mitigation measures on NCI. Using the input-output table in 2017, this paper establishes the elasticity model of NCI to investigate the effects of industrial development, intermediate input coefficients, energy efficiency, and residential energy saving on NCI, and further evaluates the contributions of key measures on achieving NCI target. The results are shown as follows. First, the development of seven sectors will promote the increase of NCI while that of 21 sectors will reduce NCI. Second, NCI will decrease significantly with the descending of intermediate input coefficients of sectors, especially electricity production and supply. Third, improving energy efficiency and residential energy saving degree could reduce NCI, but the latter has limited contribution. Fourth, the development of all sectors will reduce NCI by 10.11% in 2017–2022 if sectors could continue the historical development trends. Fifth, assuming that sectors with rising intermediate input coefficients would keep their coefficients unchanged in the predicting period and sectors with descending coefficients would continue the historical descending trend, the improvement of technology and management of all sectors will reduce NCI by 14.02% in 2017–2022.

ACS Style

Feng Wang; Min Wu; Jiachen Hong. Exploring the Effects of Industrial Structure, Technology, and Energy Efficiency on China’s Carbon Intensity and Their Contributions to Carbon Intensity Target. Sustainability 2020, 12, 8016 .

AMA Style

Feng Wang, Min Wu, Jiachen Hong. Exploring the Effects of Industrial Structure, Technology, and Energy Efficiency on China’s Carbon Intensity and Their Contributions to Carbon Intensity Target. Sustainability. 2020; 12 (19):8016.

Chicago/Turabian Style

Feng Wang; Min Wu; Jiachen Hong. 2020. "Exploring the Effects of Industrial Structure, Technology, and Energy Efficiency on China’s Carbon Intensity and Their Contributions to Carbon Intensity Target." Sustainability 12, no. 19: 8016.

Research article
Published: 22 September 2020 in Environmental Science and Pollution Research
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The consumption of fossil energy is the major cause of environmental pollution. Effectively reducing the fossil energy use has important significance for achieving China’s green development targets. The premise for reducing fossil energy use is accurately measuring the amount of energy use and identifying the key sectors and links of energy use of China’s economic sectors. This paper, by establishing a cross-region input-output model, measured the amount of energy use from the perspective of embodied energy, explored the changing trend of energy use between 2002 and 2015, and identified the key sectors and links of energy use. The results show that the embodied energy intensities of China’s economic sectors are generally higher than the world average level, but its changing trend is declining. Although the amount of energy use shows a growth trend, the growth rate manifests a decline process. The key sectors of energy use assemble in the resource sector and heavy industry sector. The key link is intermediate use, but about 80% of embodied energy of intermediate use has been used by downstream sectors. Approximately 76% of the embodied energy of final demand has been used by gross fixed capital formation and urban residents’ consumption. China has turned from a net exporter of embodied energy to a net importer since 2012. There is a resource mismatch in China’s import and export structure of embodied energy.

ACS Style

Feng Wang; Changhai Gao; Qi Ou. Study on the measurement and the changing trend of the energy use of China’s economic sectors: based on cross-region input-output model. Environmental Science and Pollution Research 2020, 28, 5296 -5315.

AMA Style

Feng Wang, Changhai Gao, Qi Ou. Study on the measurement and the changing trend of the energy use of China’s economic sectors: based on cross-region input-output model. Environmental Science and Pollution Research. 2020; 28 (5):5296-5315.

Chicago/Turabian Style

Feng Wang; Changhai Gao; Qi Ou. 2020. "Study on the measurement and the changing trend of the energy use of China’s economic sectors: based on cross-region input-output model." Environmental Science and Pollution Research 28, no. 5: 5296-5315.

Research article
Published: 01 August 2020 in Environmental Science and Pollution Research
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Over the previous two decades, Chinese economic development presented a rapid growth. However, with continuous industrialization and urbanization, China is confronted with great challenges of energy security and environmental issues. These problems are closely related to the current accounting method of economic growth to a certain extent. In order to meet these challenges, it is imperative to establish a green accounting system of economic growth and measure China’s green GDP and its changing trend based on the industrial perspective. Using the System of Environmental Economic Accounting (SEEA) and industry data, this paper estimates China’s green GDP and green value added by industry sectors in 2005, 2007, 2010, 2012, 2015, and 2017. The results reveal the following: First, the ratio of green GDP to traditional GDP gradually increases from 89.85 to 95.83% during 2005–2017, which means that the negative externalities of economic growth of the resource and environment are gradually weakened. Second, the difference between traditional GDP and green GDP during 2005–2017 is about 6.96%, with the carbon emissions accounting for 70.71% of environmental impact. Third, due to more than 80% of the environmental impact coming from three sectors: manufacturing (49.99%), electricity industry (22.63%), and other services (11.37%), these three sectors should be key sectors for energy conservation and emission reduction; fourth, the green GDP of the mining, electricity industries, and manufacturing accounts for the lowest proportion of GDP, which means that the development patterns of these three industries in recent years should be adjusted and optimized step by step.

ACS Style

Feng Wang; Ruiqi Wang; Junyao Wang. Measurement of China’s green GDP and its dynamic variation based on industrial perspective. Environmental Science and Pollution Research 2020, 27, 43813 -43828.

AMA Style

Feng Wang, Ruiqi Wang, Junyao Wang. Measurement of China’s green GDP and its dynamic variation based on industrial perspective. Environmental Science and Pollution Research. 2020; 27 (35):43813-43828.

Chicago/Turabian Style

Feng Wang; Ruiqi Wang; Junyao Wang. 2020. "Measurement of China’s green GDP and its dynamic variation based on industrial perspective." Environmental Science and Pollution Research 27, no. 35: 43813-43828.

Journal article
Published: 08 January 2020 in Energy Economics
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In this article, the calculation model of carbon intensity elasticity based on an input-output table is used to measure the elasticity of China's carbon intensity with respect to development of industries, intermediate input coefficients, and energy efficiency during 1990–2015. The industrial differences of the elasticity in 2015 are compared horizontally, and changing trends of the elasticity during 1990–2015 are analyzed in the vertical direction. The main research results imply that: first, in China's 28 subdivided industries, the development of seven industries will increase the national carbon intensity, while the development of 21 industries will decrease the national carbon intensity. The driving forces of some industries show a growing trend year by year; second, lowering industrial intermediate input coefficients by raising the technological level and management level will lead to a significant decline in national carbon intensity; third, the national carbon intensity will reduce by 0.36%, 0.119%, and 0.04% respectively, if the coal using efficiency in electricity and heat industry, coke using efficiency in metal smelting and processing industry, and the diesel using efficiency in transport and post industry increases by 1%; fourth, during 1990–2015, the elasticity of national carbon intensity with respect to the degree of residential coal saving drastically decreased and the elasticity of that with respect to the degree of refined oil saving significantly increased, yet the elasticity of that with respect to the degree of natural gas saving was relatively stable.

ACS Style

Feng Wang; Xiaoyu Sun; David M. Reiner; Min Wu. Changing trends of the elasticity of China's carbon emission intensity to industry structure and energy efficiency. Energy Economics 2020, 86, 104679 .

AMA Style

Feng Wang, Xiaoyu Sun, David M. Reiner, Min Wu. Changing trends of the elasticity of China's carbon emission intensity to industry structure and energy efficiency. Energy Economics. 2020; 86 ():104679.

Chicago/Turabian Style

Feng Wang; Xiaoyu Sun; David M. Reiner; Min Wu. 2020. "Changing trends of the elasticity of China's carbon emission intensity to industry structure and energy efficiency." Energy Economics 86, no. : 104679.

Journal article
Published: 01 July 2018 in Journal of Cleaner Production
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Based on the framework of analytical general equilibrium model, this study builds an energy intensity target (EIT) constraint model, and simulates the impacts of continuous EIT constraint policy on the fossil fuel production (FFP) sector, non-fossil-fuel production (NFFP) sector, household sector and price system in China. The main findings of this paper are, firstly, the EIT constraint can change the marginal products and the cross-price elasticities of input factors. Secondly, stricter EIT constraint can transfer capital and labor inputs from the FFP sector to the NFFP sector, and lead to a “contractionary effect” in the FFP sector – shown as declining inputs and output. The “contractionary effect” will decline gradually or even fade away if the EIT constraint is gradually reduced. Thirdly, if the total capital and labor inputs in the whole economy continue to grow at certain rates, along with the weakening of the EIT constraint, the reduction in energy input and the growth of capital and labor inputs in the NFFP sector will slow down, however, the growth rates of output and intermediate input will increase continuously. Fourthly, the EIT constraint has negative impacts on the NFFP sector, price system and household consumption, but these impacts are affordable to the whole economy. If the EIT constraint is loosened under a certain level, it may not curb the growth of fossil fuel consumption anymore. Therefore, other supporting policies for energy conservation must be in place.

ACS Style

Feng Wang; Xiying Liu. Assessment of the economic impacts of continuous energy intensity target constraint in China: Based on an analytical general equilibrium model. Journal of Cleaner Production 2018, 189, 197 -210.

AMA Style

Feng Wang, Xiying Liu. Assessment of the economic impacts of continuous energy intensity target constraint in China: Based on an analytical general equilibrium model. Journal of Cleaner Production. 2018; 189 ():197-210.

Chicago/Turabian Style

Feng Wang; Xiying Liu. 2018. "Assessment of the economic impacts of continuous energy intensity target constraint in China: Based on an analytical general equilibrium model." Journal of Cleaner Production 189, no. : 197-210.