IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i6p3101-d519097.html
   My bibliography  Save this article

Spatial and Temporal Differences in the Green Efficiency of Water Resources in the Yangtze River Economic Belt and Their Influencing Factors

Author

Listed:
  • Chong Huang

    (School of Economics, Ocean University of China, Qingdao 266100, China)

  • Kedong Yin

    (Institute of Marine Economy and Management, Shandong University of Finance and Economics, Jinan 250014, China
    School of Management Science and Engineering, Shandong University of Finance and Economics, Jinan 250014, China
    Ocean Development Research Institute, Major Research Base of Humanities and Social Sciences of Ministry of Education, Ocean University of China, Qingdao 266100, China)

  • Zhe Liu

    (School of Economics, Ocean University of China, Qingdao 266100, China
    School of Business and Management, Queen Mary University of London, Mile End Road, London E1 4NS, UK)

  • Tonggang Cao

    (College of Environment Science and Engineering, Ocean University of China, Qingdao 266100, China)

Abstract

Using panel data from 11 regions (9 provinces and two cities) in the Yangtze River Economic Belt (YREB) during 2002–2017, the regional differences in and spatial characteristics of the green efficiency of water resources along the YREB were analyzed. The undesirable outputs slacks-based measure-data envelopment analysis, Malmquist index, and social network analysis models were employed. A dynamic panel using a system generalized method of moments model was established to empirically examine the main factors influencing green efficiency. The results show the following. First, temporally, green efficiency fluctuates while showing an overall decreasing trend; spatially, green efficiency generally decreases in this order: downstream, upstream, then midstream. Second, the change in the total factor productivity (TFP) index shows an overall increasing trend, with TFP improvement mainly attributable to technology. Third, green efficiency shows a significant spatial correlation. All provinces are in the spatial correlation network, and the network, as a whole, has strong stability. Finally, water resource endowment, water prices, government environmental control strength, and the water resources utilization structure have a significant impact on green efficiency.

Suggested Citation

  • Chong Huang & Kedong Yin & Zhe Liu & Tonggang Cao, 2021. "Spatial and Temporal Differences in the Green Efficiency of Water Resources in the Yangtze River Economic Belt and Their Influencing Factors," IJERPH, MDPI, vol. 18(6), pages 1-18, March.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:6:p:3101-:d:519097
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/6/3101/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/18/6/3101/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yu Zhang & Wenliang Geng & Pengyan Zhang & Erling Li & Tianqi Rong & Ying Liu & Jingwen Shao & Hao Chang, 2020. "Dynamic Changes, Spatiotemporal Differences and Factors Influencing the Urban Eco-Efficiency in the Lower Reaches of the Yellow River," IJERPH, MDPI, vol. 17(20), pages 1-19, October.
    2. Zhibo Zhao & Tian Yuan & Xunpeng Shi & Lingdi Zhao, 2020. "Heterogeneity in the relationship between carbon emission performance and urbanization: evidence from China," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 25(7), pages 1363-1380, October.
    3. Yiru Guo & Yan Hu & Ke Shi & Yuriy Bilan, 2020. "Valuation of Water Resource Green Efficiency Based on SBM–TOBIT Panel Model: Case Study from Henan Province, China," Sustainability, MDPI, vol. 12(17), pages 1-17, August.
    4. 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.
    5. Pereira, Helga & Marques, Rui Cunha, 2017. "An analytical review of irrigation efficiency measured using deterministic and stochastic models," Agricultural Water Management, Elsevier, vol. 184(C), pages 28-35.
    6. André, Francisco J. & Herrero, Inés & Riesgo, Laura, 2010. "A modified DEA model to estimate the importance of objectives with an application to agricultural economics," Omega, Elsevier, vol. 38(5), pages 371-382, October.
    7. Xiyue Zhang & Fangcheng Sun & Huaizu Wang & Yi Qu, 2020. "Green Biased Technical Change in Terms of Industrial Water Resources in China’s Yangtze River Economic Belt," IJERPH, MDPI, vol. 17(8), pages 1-20, April.
    8. Zhao, Zhibo & Shi, Xunpeng & Zhao, Lingdi & Zhang, Jinggu, 2020. "Extending production-theoretical decomposition analysis to environmentally sensitive growth: Case study of Belt and Road Initiative countries," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    9. Hu, Jin-Li & Wang, Shih-Chuan & Yeh, Fang-Yu, 2006. "Total-factor water efficiency of regions in China," Resources Policy, Elsevier, vol. 31(4), pages 217-230, December.
    10. Hu, Jin-Li & Wang, Shih-Chuan, 2006. "Total-factor energy efficiency of regions in China," Energy Policy, Elsevier, vol. 34(17), pages 3206-3217, November.
    11. Min Li & Kaisheng Long, 2019. "Direct or Spillover Effect: The Impact of Pure Technical and Scale Efficiencies of Water Use on Water Scarcity in China," IJERPH, MDPI, vol. 16(18), pages 1-13, September.
    12. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    13. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    14. 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. Halkos, George & Bampatsou, Christina, 2022. "Measuring environmental efficiency in relation to socio-economic factors: A two stage analysis," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 876-884.
    2. Cheng Zhan & Mingjing Guo & Jinhua Cheng & Hongxia Peng, 2022. "Evaluation of Resources and Environment Carrying Capacity Based on Support Pressure Coupling Mechanism: A Case Study of the Yangtze River Economic Belt," IJERPH, MDPI, vol. 20(1), pages 1-21, December.
    3. Xia Xie & Lei Zhang & Hui Sun & Feifei Chen & Chunshan Zhou, 2021. "Spatiotemporal Difference Characteristics and Influencing Factors of Tourism Urbanization in China’s Major Tourist Cities," IJERPH, MDPI, vol. 18(19), pages 1-21, October.
    4. Chong Huang & Kedong Yin & Hongbo Guo & Benshuo Yang, 2022. "Regional Differences and Convergence of Inter-Provincial Green Total Factor Productivity in China under Technological Heterogeneity," IJERPH, MDPI, vol. 19(9), pages 1-20, May.

    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. Fang-Rong Ren & Ze Tian & Yu-Ting Shen & Yung-Ho Chiu & Tai-Yu Lin, 2019. "Energy, CO 2 , and AQI Efficiency and Improvement of the Yangtze River Economic Belt," Energies, MDPI, vol. 12(4), pages 1-17, February.
    2. Li, Lan-Bing & Hu, Jin-Li, 2012. "Ecological total-factor energy efficiency of regions in China," Energy Policy, Elsevier, vol. 46(C), pages 216-224.
    3. Zhou, Haibo & Yang, Yi & Chen, Yao & Zhu, Joe, 2018. "Data envelopment analysis application in sustainability: The origins, development and future directions," European Journal of Operational Research, Elsevier, vol. 264(1), pages 1-16.
    4. Shujing Yue & Yang Yang & Jun Shao & Yuting Zhu, 2016. "International Comparison of Total Factor Ecology Efficiency: Focused on G20 from 1999–2013," Sustainability, MDPI, vol. 8(11), pages 1-13, November.
    5. Qin, Quande & Li, Xin & Li, Li & Zhen, Wei & Wei, Yi-Ming, 2017. "Air emissions perspective on energy efficiency: An empirical analysis of China’s coastal areas," Applied Energy, Elsevier, vol. 185(P1), pages 604-614.
    6. Yongqi Feng & Haolin Zhang & Yung-ho Chiu & Tzu-Han Chang, 2021. "Innovation efficiency and the impact of the institutional quality: a cross-country analysis using the two-stage meta-frontier dynamic network DEA model," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3091-3129, April.
    7. Shuangjie Li & Li Li & Liming Wang, 2020. "2030 Target for Energy Efficiency and Emission Reduction in the EU Paper Industry," Energies, MDPI, vol. 14(1), pages 1-17, December.
    8. Cândida Ferreira, 2013. "Bank market concentration and bank efficiency in the European Union: a panel Granger causality approach," International Economics and Economic Policy, Springer, vol. 10(3), pages 365-391, September.
    9. Zhao Yang & Hong Fang, 2020. "Research on Green Productivity of Chinese Real Estate Companies—Based on SBM-DEA and TOBIT Models," Sustainability, MDPI, vol. 12(8), pages 1-16, April.
    10. Shuangjie Li & Hongyu Diao & Liming Wang & Chunqi Li, 2021. "Energy Efficiency Measurement: A VO TFEE Approach and Its Application," Sustainability, MDPI, vol. 13(4), pages 1-18, February.
    11. Wang, Xipan & Song, Junnian & Xing, Jiahao & Duan, Haiyan & Wang, Xian'en, 2022. "System nexus consolidates coupling of regional water and energy efficiencies," Energy, Elsevier, vol. 256(C).
    12. Zhang, Bin & Lu, Danting & He, Yan & Chiu, Yung-ho, 2018. "The efficiencies of resource-saving and environment: A case study based on Chinese cities," Energy, Elsevier, vol. 150(C), pages 493-507.
    13. Tao Zhang & Yung-ho Chiu & Ying Li & Tai-Yu Lin, 2018. "Air Pollutant and Health-Efficiency Evaluation Based on a Dynamic Network Data Envelopment Analysis," IJERPH, MDPI, vol. 15(9), pages 1-22, September.
    14. Jorge Guardiola & Andrés J. Picazo-Tadeo, 2013. "Weighting life domains with Data Envelopment Analysis," Working Papers 1311, Department of Applied Economics II, Universidad de Valencia.
    15. Ze Tian & Fang-Rong Ren & Qin-Wen Xiao & Yung-Ho Chiu & Tai-Yu Lin, 2019. "Cross-Regional Comparative Study on Carbon Emission Efficiency of China’s Yangtze River Economic Belt Based on the Meta-Frontier," IJERPH, MDPI, vol. 16(4), pages 1-19, February.
    16. Chang, Ming-Chung, 2013. "A comment on the calculation of the total-factor energy efficiency (TFEE) index," Energy Policy, Elsevier, vol. 53(C), pages 500-504.
    17. Wen, Yuyuan & Yu, Zilong & Xue, Jingjing & Liu, Yang, 2024. "How heterogeneous industrial agglomeration impacts energy efficiency subject to technological innovation:Evidence from the spatial threshold model," Energy Economics, Elsevier, vol. 136(C).
    18. Yuanying Chi & Situo Xu & Xiaolei Yang & Jialin Li & Xufeng Zhang & Yahui Chen, 2023. "Research on Beijing Manufacturing Green-Oriented Transition Path under “Double Carbon” Goal-Based on the GML-SD Model," Sustainability, MDPI, vol. 15(9), pages 1-17, May.
    19. Ning Zhang & Jong-Dae Kim, 2014. "Measuring sustainability by Energy Efficiency Analysis for Korean Power Companies: A Sequential Slacks-Based Efficiency Measure," Sustainability, MDPI, vol. 6(3), pages 1-13, March.
    20. Bowen Sun & Haibo Wang & Jaime Ortiz & Jun Huang & Can Zhao & Zelang Wang, 2022. "A Decomposed Data Analysis Approach to Assessing City Sustainable Development Performance: A Network DEA Model with a Slack-Based Measure," Sustainability, MDPI, vol. 14(17), pages 1-23, September.

    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:jijerp:v:18:y:2021:i:6:p:3101-:d:519097. 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.