IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i13p7960-d851190.html
   My bibliography  Save this article

Analysis of the Dynamic Relationship between Green Economy Efficiency and Urban Land Development Intensity in China

Author

Listed:
  • Jiao Hou

    (College of Public Administration, Central China Normal University, Wuhan 430079, China)

  • Xinhai Lu

    (College of Public Administration, Central China Normal University, Wuhan 430079, China)

  • Shiman Wu

    (School of Management, Wuhan Institute of Technology, Wuhan 430205, China)

  • Shangan Ke

    (College of Public Administration, Central China Normal University, Wuhan 430079, China)

  • Jia Li

    (College of Public Administration, Central China Normal University, Wuhan 430079, China)

Abstract

The improvement of green economic efficiency (GEE) should be realized under reasonable urban land development intensity (ULDI). Improving GEE can also help alleviate the negative externalities of excessive or unreasonable ULDI. Clarifying the interactive response mechanism between GEE and ULDI is a key link in regional sustainable development. Therefore, this paper uses the super-efficiency slack-based model (SBM) method, panel entropy method, and panel vector auto regression model to comprehensively analyze the interactive response relationship between GEE and ULDI in 283 prefecture-level cities in China from 2003 to 2019. This paper finds that: (1) during the research period, both the GEE and ULDI showed a relatively obvious upward trend, which is manifested in the fact that ULDI increased year by year while GEE overall increased in volatility. The growth and evolution trend of ULDI and GEE has the characteristics of interaction and coordination; (2) there is a two-way interactive Granger causality between ULDI and GEE, showing a positive interactive response effect; and (3) both ULDI and GEE have positive inertial growth and self-enhancement mechanisms. In the long run, GEE has a greater impact on the change of ULDI.

Suggested Citation

  • Jiao Hou & Xinhai Lu & Shiman Wu & Shangan Ke & Jia Li, 2022. "Analysis of the Dynamic Relationship between Green Economy Efficiency and Urban Land Development Intensity in China," IJERPH, MDPI, vol. 19(13), pages 1-17, June.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:13:p:7960-:d:851190
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/13/7960/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/13/7960/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. John E. Fernández, 2007. "Resource Consumption of New Urban Construction in China," Journal of Industrial Ecology, Yale University, vol. 11(2), pages 99-115, April.
    2. Jinlong Gao & Yehua Dennis Wei & Wen Chen & Komali Yenneti, 2015. "Urban Land Expansion and Structural Change in the Yangtze River Delta, China," Sustainability, MDPI, vol. 7(8), pages 1-27, July.
    3. Zheng, Wei & Walsh, Patrick Paul, 2019. "Economic growth, urbanization and energy consumption — A provincial level analysis of China," Energy Economics, Elsevier, vol. 80(C), pages 153-162.
    4. Holcombe, Randall G., 2013. "South Korea's economic future: Industrial policy, or economic democracy?," Journal of Economic Behavior & Organization, Elsevier, vol. 88(C), pages 3-13.
    5. Robert M. Solow, 1956. "A Contribution to the Theory of Economic Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 70(1), pages 65-94.
    6. Tao, Feng & Zhang, Huiqin & Hu, Jun & Xia, X.H., 2017. "Dynamics of green productivity growth for major Chinese urban agglomerations," Applied Energy, Elsevier, vol. 196(C), pages 170-179.
    7. Charnes, A. & Cooper, W. W. & Huang, Z. M. & Sun, D. B., 1990. "Polyhedral Cone-Ratio DEA Models with an illustrative application to large commercial banks," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 73-91.
    8. Vangelis Tzouvelekas & Dimitra Vouvaki & Anastasios Xepapadeas, 2006. "Total Factor Productivity Growth and the Environment: A Case for Green Growth Accounting," Working Papers 0617, University of Crete, Department of Economics.
    9. De Boeck, Filip, 2020. "Urban expansion, the politics of land, and occupation as infrastructure in Kinshasa," Land Use Policy, Elsevier, vol. 93(C).
    10. Tone, Kaoru & Toloo, Mehdi & Izadikhah, Mohammad, 2020. "A modified slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 287(2), pages 560-571.
    11. Chen, Yawei, 2022. "Financialising urban redevelopment: Transforming Shanghai’s waterfront," Land Use Policy, Elsevier, vol. 112(C).
    12. Sirine MNIF, 2017. "The Impact of Inequality on Growth Driven by Technological Changes: a Panel of Developing Countries," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 8(1), pages 127-140, March.
    13. Fan, Xin & Qiu, Sainan & Sun, Yukun, 2020. "Land finance dependence and urban land marketization in China: The perspective of strategic choice of local governments on land transfer," Land Use Policy, Elsevier, vol. 99(C).
    14. Jawadi, Fredj & Mallick, Sushanta K. & Sousa, Ricardo M., 2016. "Fiscal and monetary policies in the BRICS: A panel VAR approach," Economic Modelling, Elsevier, vol. 58(C), pages 535-542.
    15. Jie Wu & Dacheng Huang & Zhixiang Zhou & Qingyuan Zhu, 2020. "The regional green growth and sustainable development of China in the presence of sustainable resources recovered from pollutions," Annals of Operations Research, Springer, vol. 290(1), pages 27-45, July.
    16. Nagaoka, Sadao & Motohashi, Kazuyuki & Goto, Akira, 2010. "Patent Statistics as an Innovation Indicator," Handbook of the Economics of Innovation, in: Bronwyn H. Hall & Nathan Rosenberg (ed.), Handbook of the Economics of Innovation, edition 1, volume 2, chapter 0, pages 1083-1127, Elsevier.
    17. Shu, Cheng & Xie, Hualin & Jiang, Jinfa & Chen, Qianru, 2018. "Is Urban Land Development Driven by Economic Development or Fiscal Revenue Stimuli in China?," Land Use Policy, Elsevier, vol. 77(C), pages 107-115.
    18. De Marchi, Valentina, 2012. "Environmental innovation and R&D cooperation: Empirical evidence from Spanish manufacturing firms," Research Policy, Elsevier, vol. 41(3), pages 614-623.
    19. Wang, Rong & Zameer, Hashim & Feng, Yue & Jiao, Zhilun & Xu, Li & Gedikli, Ayfer, 2019. "Revisiting Chinese resource curse hypothesis based on spatial spillover effect: A fresh evidence," Resources Policy, Elsevier, vol. 64(C).
    20. Cook, Wade D. & Seiford, Larry M., 2009. "Data envelopment analysis (DEA) - Thirty years on," European Journal of Operational Research, Elsevier, vol. 192(1), pages 1-17, January.
    21. John R. Ottensmann, 1977. "Urban Sprawl, Land Values and the Density of Development," Land Economics, University of Wisconsin Press, vol. 53(4), pages 389-400.
    22. Fabrizi, Andrea & Guarini, Giulio & Meliciani, Valentina, 2018. "Green patents, regulatory policies and research network policies," Research Policy, Elsevier, vol. 47(6), pages 1018-1031.
    23. Ke Zhao & Danling Chen & Xupeng Zhang & Xiaojie Zhang, 2022. "How Do Urban Land Expansion, Land Finance, and Economic Growth Interact?," IJERPH, MDPI, vol. 19(9), pages 1-15, April.
    24. Song, Malin & Peng, Jun & Wang, Jianlin & Zhao, Jiajia, 2018. "Environmental efficiency and economic growth of China: A Ray slack-based model analysis," European Journal of Operational Research, Elsevier, vol. 269(1), pages 51-63.
    25. Gao, Kang & Yuan, Yijun, 2022. "Spatiotemporal pattern assessment of China’s industrial green productivity and its spatial drivers: Evidence from city-level data over 2000–2017," Applied Energy, Elsevier, vol. 307(C).
    26. 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.
    27. Du, Juan & Liang, Liang & Zhu, Joe, 2010. "A slacks-based measure of super-efficiency in data envelopment analysis: A comment," European Journal of Operational Research, Elsevier, vol. 204(3), pages 694-697, August.
    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. Cheng Chen & Yajie Gao & Yidong Qin, 2023. "A Causal Relationship between the New-Type Urbanization and Energy Consumption in China: A Panel VAR Approach," Sustainability, MDPI, vol. 15(14), pages 1-18, July.

    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. Mushtaq Taleb & Ruzelan Khalid & Ali Emrouznejad & Razamin Ramli, 2023. "Environmental efficiency under weak disposability: an improved super efficiency data envelopment analysis model with application for assessment of port operations considering NetZero," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(7), pages 6627-6656, July.
    2. Rafael Benítez & Vicente Coll-Serrano & Vicente J. Bolós, 2021. "deaR-Shiny: An Interactive Web App for Data Envelopment Analysis," Sustainability, MDPI, vol. 13(12), pages 1-19, June.
    3. Javad Gerami & Mohammad Reza Mozaffari & P. F. Wanke & Henrique Correa, 2022. "A novel slacks-based model for efficiency and super-efficiency in DEA-R," Operational Research, Springer, vol. 22(4), pages 3373-3410, September.
    4. 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.
    5. 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.
    6. Walheer, Barnabé, 2018. "Economic growth and greenhouse gases in Europe: A non-radial multi-sector nonparametric production-frontier analysis," Energy Economics, Elsevier, vol. 74(C), pages 51-62.
    7. Lee, Hsuan-Shih, 2022. "Integrating SBM model and Super-SBM model: a one-model approach," Omega, Elsevier, vol. 113(C).
    8. Kao, Chiang & Liu, Shiang-Tai, 2022. "Group decision making in data envelopment analysis: A robot selection application," European Journal of Operational Research, Elsevier, vol. 297(2), pages 592-599.
    9. Tingting Liu & Zichen Zheng & Yuneng Du, 2021. "Evaluation on regional science and technology resources allocation in China based on the zero sum gains data envelopment analysis," Journal of Intelligent Manufacturing, Springer, vol. 32(6), pages 1729-1737, August.
    10. Pengrui Wang & Chen Zeng & Yan Song & Long Guo & Wenping Liu & Wenting Zhang, 2021. "The Spatial Effect of Administrative Division on Land-Use Intensity," Land, MDPI, vol. 10(5), pages 1-18, May.
    11. Valero-Gil, Jesus & Surroca, Jordi A. & Tribo, Josep A. & Gutierrez, Leopoldo & Montiel, Ivan, 2023. "Innovation vs. standardization: The conjoint effects of eco-innovation and environmental management systems on environmental performance," Research Policy, Elsevier, vol. 52(4).
    12. Walheer, Barnabe & Hudik, Marek, 2019. "Reallocation of resources in multidivisional firms: A nonparametric approach," International Journal of Production Economics, Elsevier, vol. 214(C), pages 196-205.
    13. Wang, Qiang & Jiang, Feng & Li, Rongrong, 2022. "Assessing supply chain greenness from the perspective of embodied renewable energy – A data envelopment analysis using multi-regional input-output analysis," Renewable Energy, Elsevier, vol. 189(C), pages 1292-1305.
    14. Chen, Ya & Pan, Yongbin & Liu, Haoxiang & Wu, Huaqing & Deng, Guangwei, 2023. "Efficiency analysis of Chinese universities with shared inputs: An aggregated two-stage network DEA approach," Socio-Economic Planning Sciences, Elsevier, vol. 90(C).
    15. Yulin Lu & Chengyu Li & Min-Jae Lee, 2023. "A Study on the Measurement and Influences of Energy Green Efficiency: Based on Panel Data from 30 Provinces in China," Sustainability, MDPI, vol. 15(21), pages 1-17, October.
    16. Zhijiang Li & Decai Tang & Mang Han & Brandon J. Bethel, 2018. "Comprehensive Evaluation of Regional Sustainable Development Based on Data Envelopment Analysis," Sustainability, MDPI, vol. 10(11), pages 1-18, October.
    17. Shang, Hua & Jiang, Li & Pan, Xianyou & Pan, Xiongfeng, 2022. "Green technology innovation spillover effect and urban eco-efficiency convergence: Evidence from Chinese cities," Energy Economics, Elsevier, vol. 114(C).
    18. Imanirad, Raha & Cook, Wade D. & Aviles-Sacoto, Sonia Valeria & Zhu, Joe, 2015. "Partial input to output impacts in DEA: The case of DMU-specific impacts," European Journal of Operational Research, Elsevier, vol. 244(3), pages 837-844.
    19. Jianfei Zhao & Anan Pongtornkulpanich & Wenjin Cheng, 2022. "The Impact of Board Size on Green Innovation in China’s Heavily Polluting Enterprises: The Mediating Role of Innovation Openness," Sustainability, MDPI, vol. 14(14), pages 1-20, July.
    20. Cheng, Gang & Qian, Zhenhua, 2011. "Dea数据标准化方法及其在方向距离函数模型中的应用 [Data normalization for data envelopment analysis and its application to directional distance function]," MPRA Paper 31995, University Library of Munich, Germany.

    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:19:y:2022:i:13:p:7960-:d:851190. 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.