IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i4p2015-d746285.html
   My bibliography  Save this article

Effects of Environmental Regulation on Green Total Factor Productivity: An Evidence from the Yellow River Basin, China

Author

Listed:
  • Jinhuang Mao

    (Institute of County Economic Development & Rural Revitalization Strategy, Lanzhou University, Lanzhou 730000, China
    School of Economics, Lanzhou University, Lanzhou 730000, China)

  • Qiong Wu

    (School of Economics, Lanzhou University, Lanzhou 730000, China)

  • Meihong Zhu

    (School of Economics, Lanzhou University, Lanzhou 730000, China)

  • Chengpeng Lu

    (Institute of County Economic Development & Rural Revitalization Strategy, Lanzhou University, Lanzhou 730000, China
    School of Economics, Lanzhou University, Lanzhou 730000, China)

Abstract

Based on the data of 59 prefecture-level cities in the Yellow River Basin from 2011 to 2019, this paper uses the Slack Based Measure-Global Malmquist Luenberger (SBM-GML) model to measure green total factor productivity (GTFP) of the cities. Under the space–time concept of the Basin, heterogeneity analysis of the upper, middle and lower reaches of the Yellow River Basin is conducted. On this basis, a panel Tobit model is constructed to analyze the impact of environmental regulation on GTFP in the whole basin, upstream region, middle region and downstream region. The results show that the intensity of environmental regulation in the Yellow River Basin increases gradually, which is the highest in the lower reaches, followed by the middle reaches; spatially, the intensity of environmental regulation shows a certain aggregation trend. The green economic growth is realized in the whole basin, and the green technology progress effect is the driving factor of GTFP. The GTFP distribution in the upstream region is relatively concentrated, showing a slow upward trend. The distribution of GTFP in the middle reaches is discrete, and the annual difference is large. In the downstream region, it shows a trend of decline first and then increase. Environmental regulation promotes GTFP in the whole basin, upper, middle and lower reaches, accompanied by certain spatial differences. The Yellow River Basin breaks through the cost effect brought by environmental regulation and triggers technological innovation, thereby enhancing GTFP; the “Porter hypothesis” has been verified in the Yellow River Basin.

Suggested Citation

  • Jinhuang Mao & Qiong Wu & Meihong Zhu & Chengpeng Lu, 2022. "Effects of Environmental Regulation on Green Total Factor Productivity: An Evidence from the Yellow River Basin, China," Sustainability, MDPI, vol. 14(4), pages 1-21, February.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:4:p:2015-:d:746285
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/4/2015/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/4/2015/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Paul Lanoie & Michel Patry & Richard Lajeunesse, 2008. "Environmental regulation and productivity: testing the porter hypothesis," Journal of Productivity Analysis, Springer, vol. 30(2), pages 121-128, October.
    2. Eli Berman & Linda T. M. Bui, 2001. "Environmental Regulation And Productivity: Evidence From Oil Refineries," The Review of Economics and Statistics, MIT Press, vol. 83(3), pages 498-510, August.
    3. 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.
    4. Jiaqi Yuan & Deyuan Zhang, 2021. "Research on the Impact of Environmental Regulations on Industrial Green Total Factor Productivity: Perspectives on the Changes in the Allocation Ratio of Factors among Different Industries," Sustainability, MDPI, vol. 13(23), pages 1-23, November.
    5. Gerald Granderson & Diego Prior, 2013. "Environmental externalities and regulation constrained cost productivity growth in the US electric utility industry," Journal of Productivity Analysis, Springer, vol. 39(3), pages 243-257, June.
    6. Wang, Yan & Shen, Neng, 2016. "Environmental regulation and environmental productivity: The case of China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 758-766.
    7. Böhringer, Christoph & Moslener, Ulf & Oberndorfer, Ulrich & Ziegler, Andreas, 2012. "Clean and productive? Empirical evidence from the German manufacturing industry," Research Policy, Elsevier, vol. 41(2), pages 442-451.
    8. Tone, Kaoru, 2002. "A slacks-based measure of super-efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 143(1), pages 32-41, November.
    9. Die Li & Sumin Hu, 2021. "How Does Technological Innovation Mediate the Relationship between Environmental Regulation and High-Quality Economic Development? Empirical Evidence from China," Sustainability, MDPI, vol. 13(4), pages 1-20, February.
    10. Barbera, Anthony J. & McConnell, Virginia D., 1990. "The impact of environmental regulations on industry productivity: Direct and indirect effects," Journal of Environmental Economics and Management, Elsevier, vol. 18(1), pages 50-65, January.
    11. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xiaoxia Liang & Yi Shi & Yan Li, 2023. "Research on the Yellow River Basin Energy Structure Transformation Path under the “Double Carbon” Goal," Sustainability, MDPI, vol. 15(12), pages 1-20, June.
    2. Wei Qian & Yongsheng Wang, 2022. "How Do Rising Labor Costs Affect Green Total Factor Productivity? Based on the Industrial Intelligence Perspective," Sustainability, MDPI, vol. 14(20), pages 1-19, October.
    3. Xiaoyang Xu & Yufan Xie & Emma Serwaa Obobisa & Huaping Sun, 2023. "Has the establishment of green finance reform and innovation pilot zones improved air quality? Evidence from China," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-14, December.
    4. Jingcheng Li & Menggang Li, 2022. "Research of Carbon Emission Reduction Potentials in the Yellow River Basin, Based on Cluster Analysis and the Logarithmic Mean Divisia Index (LMDI) Method," Sustainability, MDPI, vol. 14(9), pages 1-16, April.
    5. Jingcheng Li & Menggang Li & Tianyang Wang & Xiuqin Feng, 2023. "Analysis of the Low-Carbon Transition Effect and Development Pattern of Green Credit for Prefecture-Level Cities in the Yellow River Basin," IJERPH, MDPI, vol. 20(5), pages 1-22, March.
    6. Yaoyao Wang & Yuanpei Kuang, 2023. "Evaluation, Regional Disparities and Driving Mechanisms of High-Quality Agricultural Development in China," Sustainability, MDPI, vol. 15(7), pages 1-20, April.
    7. Henryk Dzwigol & Aleksy Kwilinski & Oleksii Lyulyov & Tetyana Pimonenko, 2023. "The Role of Environmental Regulations, Renewable Energy, and Energy Efficiency in Finding the Path to Green Economic Growth," Energies, MDPI, vol. 16(7), pages 1-18, March.
    8. Lei Jiang & Yuan Chen & Bo Zhang, 2023. "Revisiting the Impact of Environmental Regulation on Green Total Factor Productivity in China: Based on a Comprehensive Index of Environmental Regulation from a Spatiotemporal Heterogeneity Perspectiv," IJERPH, MDPI, vol. 20(2), pages 1-17, January.
    9. Luxin Yang & Yucheng Liu & Huihui Deng, 2023. "Environmental governance, local government competition and industrial green transformation: Evidence from China's sustainable development practice," Sustainable Development, John Wiley & Sons, Ltd., vol. 31(2), pages 1054-1068, April.
    10. Shuying Wang & Yifei Gao & Hongchang Zhou, 2022. "Research on Green Total Factor Productivity Enhancement Path from the Configurational Perspective—Based on the TOE Theoretical Framework," Sustainability, MDPI, vol. 14(21), pages 1-20, October.
    11. Xu Dong & Yang Chen & Qinqin Zhuang & Yali Yang & Xiaomeng Zhao, 2022. "Agglomeration of Productive Services, Industrial Structure Upgrading and Green Total Factor Productivity: An Empirical Analysis Based on 68 Prefectural-Level-and-Above Cities in the Yellow River Basin," IJERPH, MDPI, vol. 19(18), pages 1-19, September.
    12. Mingliang Zhao & Yue Gao & Qing Liu & Wei Sun, 2022. "The Impact of Foreign Direct Investment on Urban Green Total Factor Productivity and the Mechanism Test," IJERPH, MDPI, vol. 19(19), pages 1-20, September.

    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. Zhang, Fengtai & Xiao, Yuedong & Gao, Lei & Ma, Dalai & Su, Ruiqi & Yang, Qing, 2022. "How agricultural water use efficiency varies in China—A spatial-temporal analysis considering unexpected outputs," Agricultural Water Management, Elsevier, vol. 260(C).
    2. Fan Wang & Lili Feng & Jin Li & Lin Wang, 2020. "Environmental Regulation, Tenure Length of Officials, and Green Innovation of Enterprises," IJERPH, MDPI, vol. 17(7), pages 1-16, March.
    3. Cenjie Liu & Chunbo Ma & Rui Xie, 2020. "Structural, Innovation and Efficiency Effects of Environmental Regulation: Evidence from China’s Carbon Emissions Trading Pilot," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 75(4), pages 741-768, April.
    4. Lena, Daniela & Pasurka, Carl A. & Cucculelli, Marco, 2022. "Environmental regulation and green productivity growth: Evidence from Italian manufacturing industries," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    5. Ashrafi, Ali & Seow, Hsin-Vonn & Lee, Lai Soon & Lee, Chew Ging, 2013. "The efficiency of the hotel industry in Singapore," Tourism Management, Elsevier, vol. 37(C), pages 31-34.
    6. Chen, Yufeng & Ni, Liangfu & Liu, Kelong, 2021. "Does China's new energy vehicle industry innovate efficiently? A three-stage dynamic network slacks-based measure approach," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    7. Ruijing Zheng & Yu Cheng & Haimeng Liu & Wei Chen & Xiaodong Chen & Yaping Wang, 2022. "The Spatiotemporal Distribution and Drivers of Urban Carbon Emission Efficiency: The Role of Technological Innovation," IJERPH, MDPI, vol. 19(15), pages 1-22, July.
    8. Muliaman Hadad & Maximilian Hall & Karligash Kenjegalieva & Wimboh Santoso & Richard Simper, 2011. "Banking efficiency and stock market performance: an analysis of listed Indonesian banks," Review of Quantitative Finance and Accounting, Springer, vol. 37(1), pages 1-20, July.
    9. Jo, Ah-Hyun & Chang, Young-Tae, 2023. "The effect of airport efficiency on air traffic, using DEA and multilateral resistance terms gravity models," Journal of Air Transport Management, Elsevier, vol. 108(C).
    10. Hongli Liu & Xiaoyu Yan & Jinhua Cheng & Jun Zhang & Yan Bu, 2021. "Driving Factors for the Spatiotemporal Heterogeneity in Technical Efficiency of China’s New Energy Industry," Energies, MDPI, vol. 14(14), pages 1-21, July.
    11. Yi-Chung Hsu, 2014. "Efficiency in government health spending: a super slacks-based model," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(1), pages 111-126, January.
    12. Mousavi, Mohammad M. & Ouenniche, Jamal & Xu, Bing, 2015. "Performance evaluation of bankruptcy prediction models: An orientation-free super-efficiency DEA-based framework," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 64-75.
    13. Ningyi Liu & Yongyu Wang, 2022. "Urban Agglomeration Ecological Welfare Performance and Spatial Convergence Research in the Yellow River Basin," Land, MDPI, vol. 11(11), pages 1-18, November.
    14. Loske, Dominic & Klumpp, Matthias, 2021. "Human-AI collaboration in route planning: An empirical efficiency-based analysis in retail logistics," International Journal of Production Economics, Elsevier, vol. 241(C).
    15. Pedro Naso & Yi Huang Author Name: Tim Swanson, 2017. "The Porter Hypothesis Goes to China: Spatial Development, Environmental Regulation and Productivity," CIES Research Paper series 53-2017, Centre for International Environmental Studies, The Graduate Institute.
    16. Chia-Nan Wang & Jen-Der Day & Nguyen Thi Kim Lien & Luu Quoc Chien, 2018. "Integrating the Additive Seasonal Model and Super-SBM Model to Compute the Efficiency of Port Logistics Companies in Vietnam," Sustainability, MDPI, vol. 10(8), pages 1-17, August.
    17. Sun, Yu & Yang, Feng & Wang, Dawei & Ang, Sheng, 2023. "Efficiency evaluation for higher education institutions in China considering unbalanced regional development: A meta-frontier Super-SBM model," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).
    18. Plácido Moreno & Sebastián Lozano, 2014. "A network DEA assessment of team efficiency in the NBA," Annals of Operations Research, Springer, vol. 214(1), pages 99-124, March.
    19. Josef Jablonsky, 2022. "Individual and team efficiency: a case of the National Hockey League," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(2), pages 479-494, June.
    20. Vicente J. Bolós & Rafael Benítez & Vicente Coll-Serrano, 2023. "Continuous models combining slacks-based measures of efficiency and super-efficiency," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 31(2), pages 363-391, June.

    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:gam:jsusta:v:14:y:2022:i:4:p:2015-:d:746285. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.