The dynamic evolution and comparison of models of China's urban eco-efficiency

  • CHEN Pei-rong ,
  • YIN Xiang-fei
Expand

Received date: 2023-02-12

  Revised date: 2023-06-23

  Online published: 2023-09-19

Abstract

In this paper, the modified metafrontier super-efficiency model based on non-radial distance function (NDDF) is used to measure the eco-efficiency of 278 prefecture-level cities in China, and combined with Luenberger productivity index (LPI), the dynamic evolution structure characteristics and model differences of urban eco-efficiency in China are analyzed. The study found that the urban ecological efficiency in China shows a slow growth trend, and the efficiency of “resource conservation” is faster than that of “ environmental friendliness”. From the decomposition of variables, the conservation of land resources and water resources contributed to the main part of the improvement of “resource conservation” efficiency, while the contribution of industrial wastewater and sulfur dioxide emissions to the improvement of “environmental friendliness” efficiency was roughly the same. From the perspective of power sources, regional technological catch-up is the main driving force for the improvement of urban eco-efficiency, while regional management efficiency has a restraining effect. The conclusion of this study is helpful to identity the power sources and dynamic evolution patterns of eco-efficiency improvement in different types of cities, and then provide policy for accurately improving the eco-efficiency of different cities.

Cite this article

CHEN Pei-rong , YIN Xiang-fei . The dynamic evolution and comparison of models of China's urban eco-efficiency[J]. Urban Problems, 2023 , 335(6) : 14 -25 . DOI: 10.13239/j.bjsshkxy.cswt.230602

References

[1] Zhou C, Gong M, Xu Z, et al. Urban scaling patterns for sustainable development goals related to water, energy, infrastructure, and society in China[J]. Resources, Conservation and Recycling,2022(185):106443
[2] WBCSD. Eco-efficient Leadership for Improved Economic and Environmental Performance[R]. Geneva: World Business Council for Sustainable Development, 1996
[3] Wang Y, Ye H, Qunwei W, et al. Cleaner production vs end-of-pipe treatment: Evidence from industrial SO2 emissions abatement in China[J]. Journal of Environmental Management, 2021(277):111429
[4] 魏后凯,李玏,年猛. “十四五”时期中国城镇化战略与政策[J]. 中共中央党校(国家行政学院)学报,2020(4):5-21
[5] 邵帅,刘丽雯. 中国水污染治理的政策效果评估——来自水生态文明城市建设试点的证据[J]. 改革,2023(2):1-18
[6] 国家统计局. 能源转型持续推进节能降耗成效显著——党的十八大以来经济社会发展成就系列报告之十四[EB/OL],国家统计局网站(http://www.stats.gov.cn/xxgk/jd/sjjd2020/202210/t20221008_1888971.html),2022-10-08
[7] Zhou Z, Wu H, Song P. Measuring the resource and environmental efficiency of industrial water consumption in China: A non-radial directional distance function[J]. Journal of Cleaner Production,2019(240):118169
[8] Song M, Zhao X, Shang Y. The impact of low-carbon city construction on ecological efficiency: Empirical evidence from quasi-natural experiments[J]. Resources, Conservation and Recycling,2020(157):104777
[9] Huang Y, Li L, Yu Y. Do urban agglomerations outperform non-agglomerations? A new perspective on exploring the eco-efficiency of Yangtze River Economic Belt in China[J]. Journal of Cleaner Production,2018(202):1056-1067
[10] Beltrán-Esteve M, Gómez-Limón J A, Picazo-Tadeo A J, et al. A metafrontier directional distance function approach to assessing eco-efficiency[J]. Journal of Productivity Analysis,2014(1):69-83
[11] Fujii H, Managi S. Determinants of eco-efficiency in the Chinese industrial sector[J]. Journal of Environmental Sciences,2013(25):20-26
[12] Wang Q, Su B, Zhou P, et al. Measuring total-factor CO2 emission performance and technology gaps using a non-radial directional distance function: A modified approach[J]. Energy Economics,2016(4):475-482
[13] Oh D. A metafrontier approach for measuring an environmentally sensitive productivity growth index[J]. Energy Economics,2010(1):146-157
[14] Maziotis A, Molinos-Senante M, Sala-Garrido R. Assesing the impact of quality of service on the productivity of water industry: A Malmquist-Luenberger approach for England and Wales[J]. Water Resources Management,2017(8):2407-2427
[15] Beltrán-Esteve M, Giménez V, Picazo-Tadeo A J. Environmental productivity in the European Union: A global Luenberger-metafrontier approach[J]. Science of The Total Environment,2019(692):136-146
[16] Liu S, Peng G, Sun C, et al. Comparison of improving energy use and mitigating pollutant emissions from industrial and non-industrial activities: Evidence from a variable-specific productivity analysis framework[J]. Science of The Total Environment,2022(806):151279
[17] Zhang Y, Sun Y, Huang J. Energy efficiency, carbon emission performance, and technology gaps: Evidence from CDM project investment[J]. Energy Policy,2018(115):119-130
[18] Tang L, Li K. A comparative analysis on energy-saving and emissions-reduction performance of three urban agglomerations in China[J]. Journal of Cleaner Production,2019(220):953-964
[19] Liu S, Liu S, Song L, et al. Measurement and convergence test of green economic efficiency of the Yangtze River Economic Belt under different spatial network correlation[J]. Frontiers in Environmental Science,2022(10):828207
[20] Zhu Y, Liang D, Liu T. Can China’s underdeveloped regions catch up with green economy? A convergence analysis from the perspective of environmental total factor productivity[J]. Journal of Cleaner Production,2020(255):120216
[21] Cheng Z, Li L, Liu J. Research on China’s industrial green biased technological progress and its energy conservation and emission reduction effects[J]. Energy Efficiency,2021(5):1-20
[22] Lin B, Sai R. A Multi factor Malmquist CO2 Emission Performance Indices: Evidence from Sub Saharan African Public Thermal Power plants[J]. Energy,2021(223):120081
[23] Pastor J T, Lovell C A, Aparicio J. Defining a new graph inefficiency measure for the proportional directional distance function and introducing a new Malmquist Productivity Index[J]. European Journal of Operational Research,2020(1):222-230
[24] Fukuyama H, Weber W L. A directional slacks-based measure of technical inefficiency[J]. Socio-Economic Planning Sciences,2009(4):274-287
[25] Zhou P, Ang B W, Wang H. Energy and CO2 emission performance in electricity generation: A non-radial directional distance function approach[J]. European Journal of Operational Research,2012(3):625-635
[26] Chen P, Xie R, Lu M, et al. The impact of the spatio-temporal neighborhood effect on urban eco-efficiency in China[J]. Journal of Cleaner Production,2021(285):124860
[27] Cheng Y, Shao T, Lai H, et al. Total-factor eco-efficiency and its influencing factors in the Yangtze River Delta Urban Agglomeration[J]. International Journal of Environmental Research and Public Health,2019(20):3814
[28] Chen P, Xie R, Lu M. “Resource conservation” or “environmental friendliness”: How do urban clusters affect total-factor ecological performance in China?[J]. International Journal of Environmental Research and Public Health,2020(12):4361
[29] Chen Y, Wang M, Feng C, et al. Total factor energy efficiency in Chinese manufacturing industry under industry and regional heterogeneities[J]. Resources, Conservation and Recycling,2021(168):105255
[30] Yu Y, Peng C, Li Y. Do neighboring prefectures matter in promoting eco-efficiency? Empirical evidence from China[J]. Technological Forecasting and Social Change,2018(144):456-465
[31] Zhang N, Choi Y. Total-factor carbon emission performance of fossil fuel power plants in China: A metafrontier non-radial Malmquist index analysis[J]. Energy Economics,2013(40):549-559
[32] O Donnell C J, Rao D S, Battese G E. Metafrontier frameworks for the study of firm-level efficiencies and technology ratios[J]. Empirical Economics,2008(2):231-255
[33] Yu M, See K F, Hsiao B. Integrating group frontier and metafrontier directional distance functions to evaluate the efficiency of production units[J]. European Journal of Operational Research,2022(1):254-276
[34] Cheng Z, Li L, Liu J, et al. Total-factor carbon emission efficiency of China’s provincial industrial sector and its dynamic evolution[J]. Renewable and Sustainable Energy Reviews,2018(94):330-339
[35] 尹向飞,欧阳峣. 中国全要素生产率再估计及不同经济增长模式下的可持续性比较[J]. 数量经济技术经济研究,2019(8):72-91
[36] Zhou X, Xu Z, Xi Y. Energy conservation and emission reduction (ECER): System construction and policy combination simulation[J]. Journal of Cleaner Production,2020(267):121969
[37] 杨骞,王珏,李超,等. 中国农业绿色全要素生产率的空间分异及其驱动因素[J]. 数量经济技术经济研究,2019(10):21-37
[38] Färe R, Grosskopf S, Norris M, et al. Productivity growth, technical progress, and efficiency change in industrialized countries[J]. The American Economic Review,1994(1):66-83
[39] Chambers. Productivity growth in APEC countries[J]. Pacific Economic Review,1996(3):181-190
[40] Chung Y H, Färe R, Grosskopf S. Productivity and undesirable outputs: A directional distance function approach[J]. Journal of Environmental Management,1997(3):229-240
[41] Beltrán-Esteve M, Giménez V, Picazo-Tadeo A J. Environmental productivity in the European Union: A global Luenberger-metafrontier approach[J]. Science of The Total Environment, 2019(692):136-146
[42] 蔡跃洲,付一夫. 全要素生产率增长中的技术效应与结构效应——基于中国宏观和产业数据的测算及分解[J]. 经济研究,2017(1):72-88
[43] 刘华军,李超,彭莹. 中国绿色全要素生产率的地区差距及区域协同提升研究[J]. 中国人口科学,2018(4):30-41
[44] 李江龙,徐斌. “诅咒”还是“福音”:资源丰裕程度如何影响中国绿色经济增长?[J]. 经济研究,2018(9):151-167
[45] Yu Y, Huang J, Zhang N. Modeling the eco-efficiency of Chinese prefecture-level cities with regional heterogeneities: A comparative perspective[J]. Ecological Modelling,2019(402):1-17
[46] Sun J, Wang Z, Li G. Measuring emission-reduction and energy-conservation efficiency of Chinese cities considering management and technology heterogeneity[J]. Journal of Cleaner Production,2018(175):561-571
[47] Huang Y, Li L, Yu Y. Does urban cluster promote the increase of urban eco-efficiency? Evidence from Chinese cities[J]. Journal of Cleaner Production,2018(197):957-971
[48] Shang H, Jiang L, Pan X, et al. Green technology innovation spillover effect and urban eco-efficiency convergence: Evidence from Chinese cities[J]. Energy Economics,2022(114):106307
[49] Young A. Gold into Base Metals: Productivity growth in the People’s Republic of China during the reform period[J]. Journal of Political Economy,2003(6):1220-1261
[50] 单豪杰. 中国资本存量K的再估算:1952~2006年[J]. 数量经济技术经济研究,2008(10):17-31
[51] Bai Y, Deng X, Jiang S, et al. Exploring the relationship between urbanization and urban eco-efficiency: Evidence from prefecture-level cities in China[J]. Journal of Cleaner Production,2018(195):1487-1496
[52] 李强,王洪川,胡鞍钢. 中国电力消费与经济增长——基于省际面板数据的因果分析[J]. 中国工业经济,2013(9):19-30
Outlines

/

〈 〉