Environmental Performance and Regulation Effect of China’s Atmospheric Pollutant Emissions: Evidence from “Three Regions and Ten Urban Agglomerations”

Zhang, Miao; Baležentis, Tomas; Tian, Zhihua; Shao, Shuai; Geng, Yong; Wu, Rui

doi:10.1007/s10640-018-00315-6

Cited by 192 publications

(53 citation statements)

References 66 publications

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“…These findings can also be associated with some implications for the GCC countries. These results confirm those found by He et al (2017) and Miao et al (2019).…”

Section: Discussionsupporting

confidence: 92%

Impact of environmental performance on sustainable development: A case study of GCC companies

Dkhili¹,

Dhiab²

2020

Int. j. adv. appl. sci.

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This paper aims to study the impact of environmental performance on sustainable development. The objective of the study is to examine the causal relationship between environmental performance and sustainable development. Based on a standard model, which includes the variables of environmental performance and development, the type of relationship was determined in a selected sample of the GCC companies during the period between 2012 and 2018. In this context, dynamic panel data models, especially GMM, will be used. The results are expected to show that the level of environmental performance has a positive impact on the level of sustainable development by analyzing the impact of institutional attributes significantly on environmental performance. Finally, we should focus on the determinants of this effect by studying the environmental and social impacts on environmental performance.

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“…These findings can also be associated with some implications for the GCC countries. These results confirm those found by He et al (2017) and Miao et al (2019).…”

Section: Discussionsupporting

confidence: 92%

Impact of environmental performance on sustainable development: A case study of GCC companies

Dkhili¹,

Dhiab²

2020

Int. j. adv. appl. sci.

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“…Yan et al [26] used the non-radial Malmquist productivity index, which was adapted to model the changes in 3E productivity during 2011-2013 for the 30 Chinese administrative regions. Miao et al [27] employed the slack-based measure method and an extended Luenberger productivity indicator to estimate and decompose the atmospheric environmental performance.…”

Section: Literature Reviewmentioning

confidence: 99%

Energy, CO2, and AQI Efficiency and Improvement of the Yangtze River Economic Belt

et al. 2019

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With the rapid development of its economy, environmental governance is becoming more important in China. The Yangtze River Economic Belt (YREB), as the world’s largest inland shipping channel, can lead the country’s regional green economy development. As most research on China’s environmental efficiency focuses on provinces or the east and west regions, this paper examines its energy input and output and environmental effects from the aspects of YREB and non-YREB, breaking through the limitations of previous studies that only used cross-section or panel data for environmental assessment. This paper employs the meta-frontier dynamic SBM model, selects fixed assets as carry-over indicators, and considers the interrelationships between the dynamics variables during 2014–2016. The results are as follows: The overall energy efficiency and CO2 emission efficiency of YREB are higher than those of non-YREB. The difference in energy consumption, CO2, and AQI efficiency is large, but the performance of YREB is generally better than that of non-YREB. After setting the meta-frontier, non-YREB is better than YREB, for the main reason that the technology gap values of YREB are smaller than those of non-YREB. Our findings thus suggest that YREB should strengthen technical exchanges and promotion within its region, thereby decreasing regional technology differences, while non-YREB should address environment protection and CO2 emissions and advocate a low-carbon production mode.

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“…Feder (2018) provided a measurement method of TFP considering the change in bias technology: Specifically when the productivity of lower (or higher) cost factors increases, the bias factor's productivity component increases (or decreases). Li et al (2016) and Li, Yu, Baležentis, Zhu, and Ji (2017) use LMDI to measure China's productivity, and Miao et al (2018Miao et al ( , 2019 combine DEA with Luenberger indicators to measure environmental production technology and environmental performance.…”

Section: Introductionmentioning

confidence: 99%

Total factor productivity and the factors of green industry in Shanxi Province, China

Song

2019

Growth and Change

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Based on industrial panel data from 11 prefecture‐level cities in Shanxi Province from 2008 to 2016, two kinds of total factor productivity (TFP) are measured: With and without the consideration of environmental factors. The specific decomposition of TFP under these two conditions is then discussed. Finally, the factors of TFP are studied in a green industry context. The results indicate the following: (a) The TFP's annual growth rate considering environmental conditions is higher than that without such consideration; (b) if environmental factors are neglected, TFP improvements primarily depend on technological progress; (c) when considering environmental factors, both technological progress and improved technological efficiency promote the growth of green TFP (GTFP), but this still primarily depends on substantial technological progress, with an annual average growth rate that reaches 10.2%; and (d) among factors, the economic development level, degree of openness, and urbanization positively correlate with the GTFP, while the industrial structure and degree of informatization significantly and negatively correlate with GTFP.

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Environmental Performance and Regulation Effect of China’s Atmospheric Pollutant Emissions: Evidence from “Three Regions and Ten Urban Agglomerations”

Cited by 192 publications

References 66 publications

Impact of environmental performance on sustainable development: A case study of GCC companies

Impact of environmental performance on sustainable development: A case study of GCC companies

Energy, CO2, and AQI Efficiency and Improvement of the Yangtze River Economic Belt

Total factor productivity and the factors of green industry in Shanxi Province, China

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