IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i19p8708-d1494847.html
   My bibliography  Save this article

Analysis of Industrial Water Use Efficiency Based on SFA–Tobit Panel Model in China

Author

Listed:
  • Han Liu

    (State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, No. 299, Ba Yi Road, Wuhan 430072, China
    Hydrology and Water Resources Department, Nanjing Hydraulic Research Institute, No. 225, Guangzhou Road, Nanjing 210029, China)

  • Heng Liu

    (State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, No. 299, Ba Yi Road, Wuhan 430072, China
    Hydrology and Water Resources Department, Nanjing Hydraulic Research Institute, No. 225, Guangzhou Road, Nanjing 210029, China)

  • Leihua Geng

    (Hydrology and Water Resources Department, Nanjing Hydraulic Research Institute, No. 225, Guangzhou Road, Nanjing 210029, China)

Abstract

Over the past two decades, the industrial sector of China has experienced rapid development, which has correspondingly led to a significant increase in water resource consumption. To better understand the dynamics of industrial water use, and formulate appropriate water resource conservation and management policies, it is necessary to evaluate the evolution of industrial water use efficiency and its influencing factors in China. Given the high sensitivity and accuracy of the stochastic frontier analysis (SFA) model for efficiency assessment, the Tobit model is more suitable for regression analyses of truncated data. This study employed the SFA–Tobit panel model to evaluate the industrial water use efficiency of provinces in China from 2003 to 2021. The results indicate that national industrial water use efficiency improved from 0.41 to 0.65 during the study period. All provinces showed significant improvements, with developed provinces exhibiting higher industrial water use efficiency than undeveloped provinces. Regionally, the eastern areas demonstrated superior industrial water use efficiency compared to the western regions, with the central regions having the lowest overall water use efficiency. Moreover, the efficiency gap between regions has been narrowing. The national industrial water-saving potential is estimated at 31.306 billion cubic meters, with Jiangsu province having the highest saving potential at 3.709 billion cubic meters. In comparison, Beijing has the lowest at just 32,000 cubic meters. The Tobit regression results reveal that economic development and technological progress positively contribute to increased industrial water use efficiency. In contrast, water use intensity, openness, and urbanization levels negatively impacted the improvement of industrial water use efficiency. Therefore, it is necessary to increase investment in technological innovation, strictly control industrial water intensity, appropriately balance import and export trade with urbanization levels, and promote sustainable economic development. This study can provide effective support for the subsequent green transformation of China’s industry.

Suggested Citation

  • Han Liu & Heng Liu & Leihua Geng, 2024. "Analysis of Industrial Water Use Efficiency Based on SFA–Tobit Panel Model in China," Sustainability, MDPI, vol. 16(19), pages 1-12, October.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:19:p:8708-:d:1494847
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/19/8708/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/19/8708/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Huixiang Zeng & Tao Zhang & Zhifang Zhou & Yang Zhao & Xiaohong Chen, 2020. "Water disclosure and firm risk: Empirical evidence from highly water‐sensitive industries in China," Business Strategy and the Environment, Wiley Blackwell, vol. 29(1), pages 17-38, January.
    2. Masuda, Kazuto, 2021. "Trade Policy and the Marshall–Lerner Condition: Application of the Tobit Model," SocArXiv njzk3, Center for Open Science.
    3. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    4. Kirjavainen, Tanja & Loikkanent, Heikki A., 1998. "Efficiency differences of finnish senior secondary schools: An application of DEA and Tobit analysis," Economics of Education Review, Elsevier, vol. 17(4), pages 377-394, October.
    5. Lampe, Hannes W. & Hilgers, Dennis, 2015. "Trajectories of efficiency measurement: A bibliometric analysis of DEA and SFA," European Journal of Operational Research, Elsevier, vol. 240(1), pages 1-21.
    6. Na Li & Yanan Wei & Lachun Wang & Chunfen Zeng & Xiaoxue Ma & Hao Wu, 2016. "Impact of industrialization on water protection in the Huai River Basin within Shandong Province, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 81(2), pages 1193-1207, March.
    7. Vinod, Hrishikesh D, 1978. "A Survey of Ridge Regression and Related Techniques for Improvements over Ordinary Least Squares," The Review of Economics and Statistics, MIT Press, vol. 60(1), pages 121-131, February.
    8. Na Li & Yanan Wei & Lachun Wang & Chunfen Zeng & Xiaoxue Ma & Hao Wu, 2016. "Impact of industrialization on water protection in the Huai River Basin within Shandong Province, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 81(2), pages 1193-1207, March.
    9. Chib, Siddhartha, 1992. "Bayes inference in the Tobit censored regression model," Journal of Econometrics, Elsevier, vol. 51(1-2), pages 79-99.
    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. Wuliyasu Bai & Liang Yan & Jingbo Liang & Long Zhang, 2022. "Mapping Knowledge Domain on Economic Growth and Water Sustainability: A Scientometric Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(11), pages 4137-4159, September.
    2. Mbaye Diene & Bity Diene & Théophile Azomahou, 2015. "Human capital productivity and uncertainty," Working Papers halshs-01144990, HAL.
    3. Miao, Chenglin & Fang, Debin & Sun, Liyan & Luo, Qiaoling, 2017. "Natural resources utilization efficiency under the influence of green technological innovation," Resources, Conservation & Recycling, Elsevier, vol. 126(C), pages 153-161.
    4. Ramesh Jangili, 2019. "The Impact of size and group affiliation in emerging markets: A Cost efficiency analysis of Indian firms," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2019-036, Indira Gandhi Institute of Development Research, Mumbai, India.
    5. Marzec, Jerzy & Pisulewski, Andrzej & Prędki, Artur, . "Efektywność techniczna i produktywność polskich gospodarstw rolnych specjalizujących się w uprawach polowych," Gospodarka Narodowa-The Polish Journal of Economics, Szkoła Główna Handlowa w Warszawie / SGH Warsaw School of Economics, vol. 2019(2).
    6. Jean Pierre Doussoulin & Cristian Colther, 2022. "Evaluating the Efficiency of Municipal Solid Waste Collection Services in Developing Countries: The Case of Chile," Sustainability, MDPI, vol. 14(23), pages 1-19, November.
    7. Moisio, Antti & Aaltonen, Juho & Kirjavainen, Tanja, 2006. "Efficiency and Productivity in Finnish Comprehensive Schooling 1998-2004," Research Reports 127, VATT Institute for Economic Research.
    8. Wei, Zixiang & Han, Botang & Pan, Xiuzhen & Shahbaz, Muhammad & Zafar, Muhammad Wasif, 2020. "Effects of diversified openness channels on the total-factor energy efficiency in China's manufacturing sub-sectors: Evidence from trade and FDI spillovers," Energy Economics, Elsevier, vol. 90(C).
    9. Quang Nguyen & Sean Pascoe & Louisa Coglan & Son Nghiem, 2021. "The sensitivity of efficiency scores to input and other choices in stochastic frontier analysis: an empirical investigation," Journal of Productivity Analysis, Springer, vol. 55(1), pages 31-40, February.
    10. Bity Diene & Mbaye Diene & Théophile Azomahou, 2015. "Human capital productivity and uncertainty," Working Papers halshs-01144989, HAL.
    11. Kalyan Chakraborty & John Poggio, 2008. "Efficiency and Equity in School Funding: A Case Study for Kansas," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 14(2), pages 228-241, May.
    12. Jean-François Brun & Constantin Thierry Compaore, 2021. "Public Expenditures Efficiency On Education Distribution in Developing Countries," Working Papers hal-03116615, HAL.
    13. Mbaye Diene & Bity Diene & Théophile Azomahou, 2015. "Human capital productivity and uncertainty," CERDI Working papers halshs-01144990, HAL.
    14. Jamasb, Tooraj & Llorca, Manuel & Khetrapal, Pavan & Thakur, Tripta, 2021. "Institutions and performance of regulated firms: Evidence from electricity distribution in India," Economic Analysis and Policy, Elsevier, vol. 70(C), pages 68-82.
    15. Sabrina Auci & Nicolò Barbieri & Manuela Coromaldi & Donatella Vignani, 2021. "Innovation for climate change adaptation and technical efficiency: an empirical analysis in the European agricultural sector," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 38(2), pages 597-623, July.
    16. Jerzy Marzec & Andrzej Pisulewski & Artur Prędki, 2019. "Efektywność techniczna i produktywność polskich gospodarstw rolnych specjalizujących się w uprawach polowych," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 2, pages 95-125.
    17. Lihong Zhao & Yuge Zhang & Fuzhu Li & Yuki Yi Gong & Hideyuki Hao Sun & Sing Lui So & Zehua Chen, 2025. "Spatial Network Evolution of Water Resources Green Efficiency in Yellow River Basin Urban Agglomerations," Sustainability, MDPI, vol. 17(3), pages 1-31, January.
    18. Jayasuriya, Ruwan & Wodon, Quentin, 2003. "Measuring and Explaining Country Efficiency in Improving Health and Education Indicators," MPRA Paper 11183, University Library of Munich, Germany.
    19. Zhou, Xianbo & Li, Kui-Wai & Li, Qin, 2011. "An analysis on technical efficiency in post-reform China," China Economic Review, Elsevier, vol. 22(3), pages 357-372, September.
    20. Kalyan Chakraborty & Vincent C. Blackburn, 2013. "Efficiency and Equity in Funding for Government Schools in Australia," Australian Economic Papers, Wiley Blackwell, vol. 52(3-4), pages 127-142, December.

    More about this item

    Keywords

    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:16:y:2024:i:19:p:8708-:d:1494847. 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.