Measurement of local government green governance efficiency based on total waste emissions and PM2.5 concentration: Evidence from China

Mengling, Zhou; Ye, Yaojun; Huang, Yaru

doi:10.1007/s11356-022-22650-4

Cited by 5 publications

(2 citation statements)

References 46 publications

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“…Since the data envelopment analysis (DEA) method does not require a priori functional forms and distributional assumptions and can incorporate both energy inputs and pollutant emissions into the analytical framework, it effectively overcomes many of the shortcomings of traditional TFP measurement methods and has been widely used in pollution abatement and carbon abatement efficiency measurement in recent years [59,60]. Currently, the primary methods for calculating pollution abatement and carbon abatement efficiency using data envelopment analysis include the earlier Malmquist productivity index based on Shepherd's output distance function, the Malmquist-Luenberger productivity index based on the directional distance function, and the Luenberger productivity index based on the relaxed directional distance function.…”

Section: Choice Of Methods For Measuring Pollution Abatement and Carb...mentioning

confidence: 99%

Does Digital Transformation Promote Green and Low-Carbon Synergistic Development in Enterprises? A Dynamic Analysis Based on the Perspective of Chinese Listed Enterprises in the Heavy Pollution Industry

Wang,

2023

Sustainability

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Digital transformation has become essential in promoting and upgrading enterprise elements and reshaping the market’s competitive landscape. However, whether digital transformation can further promote green and low-carbon synergistic development is still being determined. Using data from 2008 to 2014 matched between A-share listed enterprises in China’s heavily polluting industries and China’s industrial enterprise pollution emission database (robustness tests were used city panel data from 2013 to 2019 to overcome the timeliness of enterprise-level data), we measured the green total factor productivity, carbon emission efficiency, and joint emission reduction efficiency of heavily polluting listed companies. We examined the dynamic impact of corporate digital transformation on corporate pollution and carbon emission reduction. The empirical results show that (1) digital transformation inhibits the enterprise’s all-green factor productivity, carbon emission efficiency, and joint emission reduction efficiency in the short term but promotes them in the long term. Digital transformation can improve these three efficiencies by enhancing the enterprise’s green technology innovation ability and optimizing factor allocation efficiency. (2) A heterogeneity analysis found that, in the external environment, the increase in environmental regulation enhances the impact of digital transformation on these three efficiencies; in the internal environment, the improvement of the competitiveness of the enterprise’s products strengthens the promotion of digital transformation on the three efficiencies of pollution emission reduction and carbon emission reduction. (3) Further research shows that, in the long run, digital transformation can improve the synergistic effect of the pollution reduction and carbon emission reduction of enterprises. This is instructive for Chinese enterprises to achieve the synergistic development of digital transformation and green, low-carbon production.

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Section: Choice Of Methods For Measuring Pollution Abatement and Carb...mentioning

confidence: 99%

Does Digital Transformation Promote Green and Low-Carbon Synergistic Development in Enterprises? A Dynamic Analysis Based on the Perspective of Chinese Listed Enterprises in the Heavy Pollution Industry

Wang,

2023

Sustainability

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show abstract

“…To address these issues, countries have formulated and implemented a series of policies and action plans. As one of the world's largest greenhouse gas emitters, China has recognized the seriousness of climate change and environmental pollution and has taken several significant measures to address these issues (An et al 2021;Zhou et al 2023). The Chinese government has outlined goals and tasks for reducing greenhouse gas emissions and improving environmental quality through policy documents such as the "Outline of China's Ecological Civilization Construction" and the "Three-Year Action Plan for Winning the Blue-Sky Defense Battle."…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the environmental efficiency of China's power generation industry considering carbon emissions and air pollution: An improved three-stage SBM-SE-DEA model

Chai,

Li,

Chen

2024

Preprint

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Evaluating and enhancing the environmental efficiency of the power generation industry is an effective approach for addressing the challenges of climate change and environmental pollution. Considering the influence of external environmental factors and stochastic factors, this paper proposes an improved three-stage slack-based measure with superefficiency data envelopment analysis (SBM-SE-DEA) model to evaluate the environmental efficiency of the power generation industry in China’s 30 provincial regions during 2015–2021. The model integrates three-stage DEA model, SBM-DEA model, and SE-DEA model while accounting for undesirable outputs such as carbon emissions and air pollutants. The results show that (1) regions with a high proportion of renewable energy generation demonstrate the best environmental efficiency when considering the environmental constraints from carbon emissions and air pollution. However, the results of the first stage are evidently overestimated due to the influence of external environmental factors. (2) Rational adjustments in the economic development level, power structure, and industrial structure play a positive role in improving environmental efficiency. However, improving resource endowment does not yield the expected results. Additionally, provinces with higher electricity outputs often bear greater pressure from environmental pollution. (3) The environmental efficiency in the third stage exhibited a stable trend driven by internal factors. However, except for the Northeast and Central-South regions, most regions still experienced overestimation of environmental efficiency in the first stage. Thus, optimizing the power generation structure, promoting industrial restructuring, and strengthening interregional cooperation and coordination are imperative.

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Measurement of green innovation efficiency in Chinese listed energy-intensive enterprises based on the three stage Super-SBM model

Wu,

Wang,

Zhang

et al. 2025

International Review of Economics & Finance

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Measurement of local government green governance efficiency based on total waste emissions and PM2.5 concentration: Evidence from China

Cited by 5 publications

References 46 publications

Does Digital Transformation Promote Green and Low-Carbon Synergistic Development in Enterprises? A Dynamic Analysis Based on the Perspective of Chinese Listed Enterprises in the Heavy Pollution Industry

Does Digital Transformation Promote Green and Low-Carbon Synergistic Development in Enterprises? A Dynamic Analysis Based on the Perspective of Chinese Listed Enterprises in the Heavy Pollution Industry

Evaluation of the environmental efficiency of China's power generation industry considering carbon emissions and air pollution: An improved three-stage SBM-SE-DEA model

Measurement of green innovation efficiency in Chinese listed energy-intensive enterprises based on the three stage Super-SBM model

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