IDEAS home Printed from https://ideas.repec.org/a/eee/jrpoli/v83y2023ics0301420723004464.html
   My bibliography  Save this article

Environmental regulation efficiency analysis by considering regional heterogeneity

Author

Listed:
  • Liu, Xiaohong
  • Yang, Jiangjiang
  • Xu, Chengzhen
  • Li, Xingchen
  • Zhu, Qingyuan

Abstract

Facing the increasingly severe environmental problems, Chinese government takes environmental regulation as an important way to reduce carbon dioxide emissions and control pollution. For the role of environmental regulation, many scholars have done a lot of research. However, there are few articles on the efficiency of environmental regulation at the regional level. Regional heterogeneity also brings obstacles to the analysis of environmental regulation efficiency (ERE). We propose the meta-frontier Malmquist-Luenberger (MML) index to analyze China's regional ERE by considering the regional heterogeneity. Empirical results show that the ERE of the whole country and each region increase year by year from 2014 to 2018. From the viewpoint of regional heterogeneity, the eastern region contributes the most to ERE gains, while the midwestern region have a relatively low contribution. The decomposition results of MML index indicate that national ERE gains come mainly from the contribution of BPC. However, the main contributors to the change in the MML index across the period are not unique for the three regions.

Suggested Citation

  • Liu, Xiaohong & Yang, Jiangjiang & Xu, Chengzhen & Li, Xingchen & Zhu, Qingyuan, 2023. "Environmental regulation efficiency analysis by considering regional heterogeneity," Resources Policy, Elsevier, vol. 83(C).
    • Handle: RePEc:eee:jrpoli:v:83:y:2023:i:c:s0301420723004464
    DOI: 10.1016/j.resourpol.2023.103735
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301420723004464
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.resourpol.2023.103735?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Emrouznejad, Ali & Yang, Guo-liang, 2016. "A framework for measuring global Malmquist–Luenberger productivity index with CO2 emissions on Chinese manufacturing industries," Energy, Elsevier, vol. 115(P1), pages 840-856.
    2. Wang, Yun & Sun, Xiaohua & Guo, Xu, 2019. "Environmental regulation and green productivity growth: Empirical evidence on the Porter Hypothesis from OECD industrial sectors," Energy Policy, Elsevier, vol. 132(C), pages 611-619.
    3. Meng, Fanyi & Su, Bin & Thomson, Elspeth & Zhou, Dequn & Zhou, P., 2016. "Measuring China’s regional energy and carbon emission efficiency with DEA models: A survey," Applied Energy, Elsevier, vol. 183(C), pages 1-21.
    4. Zhang, Ning & Zhao, Yu & Wang, Na, 2022. "Is China's energy policy effective for power plants? Evidence from the 12th Five-Year Plan energy saving targets," Energy Economics, Elsevier, vol. 112(C).
    5. Song, Malin & An, Qingxian & Zhang, Wei & Wang, Zeya & Wu, Jie, 2012. "Environmental efficiency evaluation based on data envelopment analysis: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(7), pages 4465-4469.
    6. Li, Zheng & Pan, Lingying & Fu, Feng & Liu, Pei & Ma, Linwei & Amorelli, Angelo, 2014. "China's regional disparities in energy consumption: An input–output analysis," Energy, Elsevier, vol. 78(C), pages 426-438.
    7. M. Portela & A. Camanho & A. Keshvari, 2013. "Assessing the evolution of school performance and value-added: trends over four years," Journal of Productivity Analysis, Springer, vol. 39(1), pages 1-14, February.
    8. Yujiro Hayami, 1969. "Sources of Agricultural Productivity Gap Among Selected Countries," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 51(3), pages 564-575.
    9. Oh, Dong-hyun, 2010. "A metafrontier approach for measuring an environmentally sensitive productivity growth index," Energy Economics, Elsevier, vol. 32(1), pages 146-157, January.
    10. Wu, Haitao & Hao, Yu & Ren, Siyu, 2020. "How do environmental regulation and environmental decentralization affect green total factor energy efficiency: Evidence from China," Energy Economics, Elsevier, vol. 91(C).
    11. Dong-hyun Oh, 2010. "A global Malmquist-Luenberger productivity index," Journal of Productivity Analysis, Springer, vol. 34(3), pages 183-197, December.
    12. Henry Tulkens & Philippe Eeckaut, 2006. "Nonparametric Efficiency, Progress and Regress Measures For Panel Data: Methodological Aspects," Springer Books, in: Parkash Chander & Jacques Drèze & C. Knox Lovell & Jack Mintz (ed.), Public goods, environmental externalities and fiscal competition, chapter 0, pages 395-429, Springer.
    13. Yuanying Chi & Wenbing Zhou & Songlin Tang & Yu Hu, 2022. "Driving Factors of CO 2 Emissions in China’s Power Industry: Relative Importance Analysis Based on Spatial Durbin Model," Energies, MDPI, vol. 15(7), pages 1-15, April.
    14. George E. Battese & D. S. Prasada Rao, 2002. "Technology Gap, Efficiency, and a Stochastic Metafrontier Function," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 1(2), pages 87-93, August.
    15. Lin, Boqiang & Du, Kerui, 2015. "Modeling the dynamics of carbon emission performance in China: A parametric Malmquist index approach," Energy Economics, Elsevier, vol. 49(C), pages 550-557.
    16. Chang, Young-Tae & Zhang, Ning & Danao, Denise & Zhang, Nan, 2013. "Environmental efficiency analysis of transportation system in China: A non-radial DEA approach," Energy Policy, Elsevier, vol. 58(C), pages 277-283.
    17. Li, Mingquan & Wang, Qi, 2014. "International environmental efficiency differences and their determinants," Energy, Elsevier, vol. 78(C), pages 411-420.
    18. Feng-Cheng Fu & Chu-Ping Vijverberg & Yong-Sheng Chen, 2008. "Productivity and efficiency of state-owned enterprises in China," Journal of Productivity Analysis, Springer, vol. 29(3), pages 249-259, June.
    19. Tran, Trung Hieu & Mao, Yong & Nathanail, Paul & Siebers, Peer-Olaf & Robinson, Darren, 2019. "Integrating slacks-based measure of efficiency and super-efficiency in data envelopment analysis," Omega, Elsevier, vol. 85(C), pages 156-165.
    20. Yongrok Choi & Dong-hyun Oh & Ning Zhang, 2015. "Environmentally sensitive productivity growth and its decompositions in China: a metafrontier Malmquist–Luenberger productivity index approach," Empirical Economics, Springer, vol. 49(3), pages 1017-1043, November.
    21. Wang, Qunwei & Zhao, Zengyao & Zhou, Peng & Zhou, Dequn, 2013. "Energy efficiency and production technology heterogeneity in China: A meta-frontier DEA approach," Economic Modelling, Elsevier, vol. 35(C), pages 283-289.
    22. Neves, Sónia Almeida & Marques, António Cardoso & Patrício, Margarida, 2020. "Determinants of CO2 emissions in European Union countries: Does environmental regulation reduce environmental pollution?," Economic Analysis and Policy, Elsevier, vol. 68(C), pages 114-125.
    23. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    24. Arabi, Behrouz & Munisamy, Susila & Emrouznejad, Ali, 2015. "A new slacks-based measure of Malmquist–Luenberger index in the presence of undesirable outputs," Omega, Elsevier, vol. 51(C), pages 29-37.
    25. Eirini Stergiou and Kostas Kounetas, 2021. "European Industries' Energy Efficiency under Different Technological Regimes: The Role of CO2 Emissions, Climate, Path Dependence and Energy Mix," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 93-128.
    26. R. Ramanathan, 2002. "Combining indicators of energy consumption and CO 2 emissions: a cross-country comparison," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 17(3), pages 214-227.
    27. Zeng, Juying & Pagàn-Castaño, Esther & Ribeiro-Navarrete, Samuel, 2022. "Merits of Intercity Innovation Cooperation of Environment-friendly Patents for Environmental Regulation Efficiency," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    28. Zhou, P. & Ang, B.W. & Han, J.Y., 2010. "Total factor carbon emission performance: A Malmquist index analysis," Energy Economics, Elsevier, vol. 32(1), pages 194-201, January.
    29. Fare, Rolf & Shawna Grosskopf & Mary Norris & Zhongyang Zhang, 1994. "Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries," American Economic Review, American Economic Association, vol. 84(1), pages 66-83, March.
    30. Yu, Shasha & Yuan, Xuanyu & Yao, Xinyan & Lei, Ming, 2022. "Carbon leakage and low-carbon performance: Heterogeneity of responsibility perspectives," Energy Policy, Elsevier, vol. 165(C).
    31. Chiu, Ching-Ren & Liou, Je-Liang & Wu, Pei-Ing & Fang, Chen-Ling, 2012. "Decomposition of the environmental inefficiency of the meta-frontier with undesirable output," Energy Economics, Elsevier, vol. 34(5), pages 1392-1399.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Li, Ke & Lin, Boqiang, 2015. "Metafroniter energy efficiency with CO2 emissions and its convergence analysis for China," Energy Economics, Elsevier, vol. 48(C), pages 230-241.
    2. Chung, Yeimin & Heshmati, Almas, 2013. "Measurement of Environmentally Sensitive Productivity Growth in Korean Industries," IZA Discussion Papers 7235, Institute of Labor Economics (IZA).
    3. Wang, Qunwei & Chiu, Yung-Ho & Chiu, Ching-Ren, 2017. "Non-radial metafrontier approach to identify carbon emission performance and intensity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 664-672.
    4. Wen-Chi Yang & Wen-Min Lu & Alagu Perumal Ramasamy, 2021. "International Environmental Efficiency Trends and the Impact of the Paris Agreement," Energies, MDPI, vol. 14(15), pages 1-16, July.
    5. Stergiou, Eirini & Rigas, Nikos & Kounetas, Konstantinos, 2021. "Environmental Productivity and Convergence of European Manufacturing Industries. Are they Under Pressure?," MPRA Paper 110780, University Library of Munich, Germany.
    6. Cheng, Zhonghua & Li, Lianshui & Liu, Jun & Zhang, Huiming, 2018. "Total-factor carbon emission efficiency of China's provincial industrial sector and its dynamic evolution," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 330-339.
    7. Pooja Bansal & Aparna Mehra & Sunil Kumar, 2022. "Dynamic Metafrontier Malmquist–Luenberger Productivity Index in Network DEA: An Application to Banking Data," Computational Economics, Springer;Society for Computational Economics, vol. 59(1), pages 297-324, January.
    8. Feng, Chao & Wang, Miao, 2018. "Analysis of energy efficiency in China's transportation sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 565-575.
    9. Stergiou, Eirini & Rigas, Nikos & Kounetas, Konstantinos E., 2023. "Environmental productivity growth across European industries," Energy Economics, Elsevier, vol. 123(C).
    10. Mocholi-Arce, Manuel & Sala-Garrido, Ramon & Molinos-Senante, Maria & Maziotis, Alexandros, 2021. "Performance assessment of water companies: A metafrontier approach accounting for quality of service and group heterogeneities," Socio-Economic Planning Sciences, Elsevier, vol. 74(C).
    11. Fei, Rilong & Lin, Boqiang, 2016. "Energy efficiency and production technology heterogeneity in China's agricultural sector: A meta-frontier approach," Technological Forecasting and Social Change, Elsevier, vol. 109(C), pages 25-34.
    12. Feng, Chao & Zhang, Hua & Huang, Jian-Bai, 2017. "The approach to realizing the potential of emissions reduction in China: An implication from data envelopment analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 859-872.
    13. Wang, Qunwei & Zhao, Zengyao & Zhou, Peng & Zhou, Dequn, 2013. "Energy efficiency and production technology heterogeneity in China: A meta-frontier DEA approach," Economic Modelling, Elsevier, vol. 35(C), pages 283-289.
    14. Qunwei Wang & Ye Hang & Jin‐Li Hu & Ching‐Ren Chiu, 2018. "An alternative metafrontier framework for measuring the heterogeneity of technology," Naval Research Logistics (NRL), John Wiley & Sons, vol. 65(5), pages 427-445, August.
    15. Huang, Hongyun & Mo, Renbian & Chen, Xingquan, 2021. "New patterns in China's regional green development: An interval Malmquist–Luenberger productivity analysis," Structural Change and Economic Dynamics, Elsevier, vol. 58(C), pages 161-173.
    16. Chuanxin Xia & Yu Zhao & Qingxia Zhao & Shuo Wang & Ning Zhang, 2022. "Exact Eco-Efficiency Measurement in the Yellow River Basin: A New Non-Parametric Approach," Sustainability, MDPI, vol. 14(20), pages 1-18, October.
    17. Chen, Xiang & Chen, Yong & Huang, Wenli & Zhang, Xuping, 2023. "A new Malmquist-type green total factor productivity measure: An application to China," Energy Economics, Elsevier, vol. 117(C).
    18. Jayanath Ananda & Dong-hyun Oh, 2023. "Assessing environmentally sensitive productivity growth: incorporating externalities and heterogeneity into water sector evaluations," Journal of Productivity Analysis, Springer, vol. 59(1), pages 45-60, February.
    19. Yu, Junqing & Zhou, Kaile & Yang, Shanlin, 2019. "Regional heterogeneity of China's energy efficiency in “new normal”: A meta-frontier Super-SBM analysis," Energy Policy, Elsevier, vol. 134(C).
    20. Hao Zhang & Jianxin You & Xuekelaiti Haiyirete & Tianyu Zhang, 2020. "Measuring Logistics Efficiency in China Considering Technology Heterogeneity and Carbon Emission through a Meta-Frontier Model," Sustainability, MDPI, vol. 12(19), pages 1-18, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jrpoli:v:83:y:2023:i:c:s0301420723004464. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/30467 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.