Metafrontier Eco-Efficiency and Its Convergence Analysis for China: A Multidimensional Heterogeneity Perspective

Yu, Yantuan; Hu, Hui; Zhang, Yun; Yin, Zhujia

doi:10.1080/1540496x.2018.1559142

Cited by 17 publications

(5 citation statements)

References 50 publications

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“…Their result presents that Japan's performance is better than Taiwan's. Yu et al (2019) examine the evolution and convergence of China's ecological efficiency by a metafrontier approach, and their result shows significant regional disparity of eco-efficiency in China. Li et al (2019) use a MetaFrontier Dynamic SBM model to analyze pollution efficiency in Chinese cities, finding large differences in the energy consumption and air pollution emission efficiency scores and much-needed improvements.…”

Section: Air Quality Efficiency Evaluation Based On Data Envelopment Analysis Methodsmentioning

confidence: 99%

“…Some scholars only take a single city as the research object [Kassomenos et al, 2012 (Thessaloniki); Yotova et al, 2016 (Thessaloniki); Mohammed et al, 2018 (Kut City); Dang et al, 2021 (Beijing and Chengdu)], while others study small areas, such as the Estarreja area (Figueiredo et al, 2013), Rithala areas in India (Mishra et al, 2016), Thessaloniki area (Poupkou et al, 2011;Aleksandropoulou et al, 2012), Taiwan and Japan (Lu et al, 2018), and Taiwan Province (Chang et al, 2019). Other studies take the whole country as the object Yu et al, 2019;Wang et al, 2020;Zhou et al, 2020). Furthermore, Chang and Hu (2018) set up the G7 and BRICS as research objects, while Qian et al (2021) target major industrial sectors in China as research objects.…”

Section: Different Research Objects In Air-related Evaluationmentioning

confidence: 99%

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Air Quality Evaluation and Improvement of China’s Three Major Urban Agglomerations Based on the Modified MetaFrontier Dynamic Slack-Based Measures Model

et al. 2021

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Urban agglomeration has become a unique form of cities during the rapid development of emerging economies. With the increasing attention on global energy and environmental efficiency, air quality evaluation and pollution control have become important standards to measure the health and orderly development of such agglomerations. Based on panel data of 60 cities in the three major urban agglomerations of Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD), this study uses the Modified MetaFrontier Dynamic SBM model to evaluate their air quality over the 5-year period of 2013–2017. The results present that the development level of air pollution prevention and control in China’s three major urban agglomerations is relatively low, and YRD as the most developed area has the worst effect of air pollution prevention and control. The MetaFrontier and Group Frontier Efficiency analysis confirms the conclusion of the cluster analysis that a significant two-level differentiation exists in China’s three urban agglomerations. Moreover, China’s three major urban agglomerations are still in the stage of high energy consumption and high development. Lastly, we point out different recommendations for industrial structure and governance foci of the three major urban agglomerations. Dust prevention technology should be improved to reduce PM2.5 in BTH, desulfurization technology should be enhanced to cut industrial SO2 emissions in YRD, and better emission reduction targets and other targeted measures should be formulated in PRD.

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Section: Air Quality Efficiency Evaluation Based On Data Envelopment Analysis Methodsmentioning

confidence: 99%

Section: Different Research Objects In Air-related Evaluationmentioning

confidence: 99%

Air Quality Evaluation and Improvement of China’s Three Major Urban Agglomerations Based on the Modified MetaFrontier Dynamic Slack-Based Measures Model

et al. 2021

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“…On the other hand, following Yu et al (2019), we divide our sample into four groups, i.e., eastern cities vs. central/western cities; cities listed as the key environmental protection (KEP) vs. Non-KEP cities; cities listed as the resource-based (RB) and Non-RB; cities listed as two control zones (TCZ) and Non-TCZ. Estimation results of city-based heterogeneity analysis are summarized in Table 5.…”

Section: Heterogeneity Analysismentioning

confidence: 99%

Air Pollution and Migration

Zhao

et al. 2022

Journal of Global Information Management

Self Cite

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This paper investigates the impact of air pollution on China’s internal migration using the Migrant Population Dynamic Monitoring Survey and Air Quality Index (AQI) data in 2014. Binary response models suggest that, on average, the probability of the willingness to leave will grow by approximately 0.1 if the average value of AQI is increased by 100 points. The migration effect of sever air pollution still holds using two-stage least squares estimation. In particular, compared to inter-province and intra-city within the same province, interviewees are more willingness to leave in intra-county with the same city. Besides, individuals from the cities in central and western regions, the listed key environmental protection (KEP) cities and cities not listed as resource-based (RB) cities have stronger willingness to leave than those from the cities in eastern region, Non-KEP cities and RB cities. Our results are robust to alternative measures of air pollution and models specification.

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“…If the σ value in different areas tends to go up, the σ-convergence exists. According to Yu et al [45], the coefficient variation (CV) of EE is used to measure σ-convergence, which is shown as Equation 7:…”

Section: The Convergence Modelmentioning

confidence: 99%

Regional Differences in the Spatial Characteristics and Dynamic Convergence of Environmental Efficiency in China

Tao

et al. 2020

Sustainability

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This study uses the undesirable output and super-efficiency slacks-based measure combined with window (WIN-US-SBM) data envelopment analysis (DEA) to evaluate the environmental efficiency (EE) in 30 Chinese provinces, from 2005 to 2016, explores regional differences in the EE, and uses the dynamic spatial Durbin model (DSDM) to analyze regional differences in effects of important factors on the convergence of EE. It reveals that EE in the eastern area is higher than EE in the central and western areas, and a positive spatial autocorrelation exists in the interregional EE. The difference in provincial EE gradually narrows over time and tends to converge to its own steady-state level. Economic growth reduces EE for the central and western areas and improves efficiency for the eastern area; economic growth from surrounding areas indirectly promotes local EE for the eastern area. Foreign direct investment (FDI) promotes EE in the eastern and central areas, and FDI in the adjacent areas has a positive effect on local EE for the eastern area. Export reduces EE for all areas, and export in surrounding areas indirectly promotes local EE for the central area. Industrialization reduces EE in the western area, and industrialization in the surrounding areas increases local EE for the eastern area. Energy efficiency promotes EE for the central area, urbanization increases EE for the central area, and urbanization of the surrounding areas reduces local EE for the eastern area.

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Metafrontier Eco-Efficiency and Its Convergence Analysis for China: A Multidimensional Heterogeneity Perspective

Cited by 17 publications

References 50 publications

Air Quality Evaluation and Improvement of China’s Three Major Urban Agglomerations Based on the Modified MetaFrontier Dynamic Slack-Based Measures Model

Air Quality Evaluation and Improvement of China’s Three Major Urban Agglomerations Based on the Modified MetaFrontier Dynamic Slack-Based Measures Model

Air Pollution and Migration

Regional Differences in the Spatial Characteristics and Dynamic Convergence of Environmental Efficiency in China

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