IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i22p14764-d968286.html
   My bibliography  Save this article

Does the Urban Agglomeration Policy Reduce Energy Intensity? Evidence from China

Author

Listed:
  • Rui Ding

    (College of Big Data Application and Economics (Guiyang College of Big Data Finance), Guizhou University of Finance and Economics, Guiyang 550025, China
    Guizhou Key Laboratory of Big Data Statistical Analysis, Guizhou University of Finance and Economics, Guiyang 550025, China
    Key Laboratory of Green Fintech, Guizhou University of Finance and Economics, Guiyang 550025, China
    These authors contributed equally to this work.)

  • Tao Zhou

    (College of Big Data Application and Economics (Guiyang College of Big Data Finance), Guizhou University of Finance and Economics, Guiyang 550025, China
    Guizhou Key Laboratory of Big Data Statistical Analysis, Guizhou University of Finance and Economics, Guiyang 550025, China
    Key Laboratory of Green Fintech, Guizhou University of Finance and Economics, Guiyang 550025, China
    These authors contributed equally to this work.)

  • Jian Yin

    (West China Modernization Research Center, Guizhou University of Finance and Economics, Guiyang 550025, China
    School of Water Conservancy and Civil Engineering, Northeast Agricultural University, Harbin 150050, China)

  • Yilin Zhang

    (College of Big Data Application and Economics (Guiyang College of Big Data Finance), Guizhou University of Finance and Economics, Guiyang 550025, China
    Guizhou Key Laboratory of Big Data Statistical Analysis, Guizhou University of Finance and Economics, Guiyang 550025, China
    Key Laboratory of Green Fintech, Guizhou University of Finance and Economics, Guiyang 550025, China)

  • Siwei Shen

    (College of Big Data Application and Economics (Guiyang College of Big Data Finance), Guizhou University of Finance and Economics, Guiyang 550025, China
    Guizhou Key Laboratory of Big Data Statistical Analysis, Guizhou University of Finance and Economics, Guiyang 550025, China
    Key Laboratory of Green Fintech, Guizhou University of Finance and Economics, Guiyang 550025, China)

  • Jun Fu

    (College of Big Data Application and Economics (Guiyang College of Big Data Finance), Guizhou University of Finance and Economics, Guiyang 550025, China
    Guizhou Key Laboratory of Big Data Statistical Analysis, Guizhou University of Finance and Economics, Guiyang 550025, China
    Key Laboratory of Green Fintech, Guizhou University of Finance and Economics, Guiyang 550025, China)

  • Linyu Du

    (College of Big Data Application and Economics (Guiyang College of Big Data Finance), Guizhou University of Finance and Economics, Guiyang 550025, China
    Guizhou Key Laboratory of Big Data Statistical Analysis, Guizhou University of Finance and Economics, Guiyang 550025, China
    Key Laboratory of Green Fintech, Guizhou University of Finance and Economics, Guiyang 550025, China)

  • Yiming Du

    (College of Big Data Application and Economics (Guiyang College of Big Data Finance), Guizhou University of Finance and Economics, Guiyang 550025, China
    Guizhou Key Laboratory of Big Data Statistical Analysis, Guizhou University of Finance and Economics, Guiyang 550025, China
    Key Laboratory of Green Fintech, Guizhou University of Finance and Economics, Guiyang 550025, China)

  • Shihui Chen

    (College of Big Data Application and Economics (Guiyang College of Big Data Finance), Guizhou University of Finance and Economics, Guiyang 550025, China
    Guizhou Key Laboratory of Big Data Statistical Analysis, Guizhou University of Finance and Economics, Guiyang 550025, China
    Key Laboratory of Green Fintech, Guizhou University of Finance and Economics, Guiyang 550025, China)

Abstract

With the expansion of the scale of China’s economy and the acceleration of urbanization, energy consumption is increasing, and environmental degradation and other problems have arisen. In order to solve such prominent problems, China proposed the “carbon peak” and “carbon neutral” targets in 2020. Although there are research conclusions about the impact of urbanization on energy intensity ( EI ), conclusions about the impact of the urban agglomeration policy ( UAP ) on EI are still unclear. Therefore, the article studies the impact of the urban agglomeration policy on EI in 279 prefecture-level cities by constructing a Difference-In-Differences (DID) model and mediating effect model. The results show that UAP has a significant effect on reducing EI , but their effects are different with the impact of urban heterogeneity, and the urban agglomeration policy of “Core” cities is less effective than those of “Edge” cities. From the perspective of the influencing mechanism, UAP takes green innovation capability as the intermediary variable to influence EI . The placebo test, PSM-DID regression, counterfactual test, and instrumental variable method all reflect the robustness of the research conclusions. Based on this, the paper puts forward some suggestions for urban agglomeration planning and green technology innovation.

Suggested Citation

  • Rui Ding & Tao Zhou & Jian Yin & Yilin Zhang & Siwei Shen & Jun Fu & Linyu Du & Yiming Du & Shihui Chen, 2022. "Does the Urban Agglomeration Policy Reduce Energy Intensity? Evidence from China," IJERPH, MDPI, vol. 19(22), pages 1-20, November.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:22:p:14764-:d:968286
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/22/14764/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/19/22/14764/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sun, Huaping & Edziah, Bless Kofi & Kporsu, Anthony Kwaku & Sarkodie, Samuel Asumadu & Taghizadeh-Hesary, Farhad, 2021. "Energy efficiency: The role of technological innovation and knowledge spillover," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    2. Glaeser, Edward L. & Kahn, Matthew E., 2010. "The greenness of cities: Carbon dioxide emissions and urban development," Journal of Urban Economics, Elsevier, vol. 67(3), pages 404-418, May.
    3. Filipović, Sanja & Verbič, Miroslav & Radovanović, Mirjana, 2015. "Determinants of energy intensity in the European Union: A panel data analysis," Energy, Elsevier, vol. 92(P3), pages 547-555.
    4. Thorsten Beck & Ross Levine & Alexey Levkov, 2010. "Big Bad Banks? The Winners and Losers from Bank Deregulation in the United States," Journal of Finance, American Finance Association, vol. 65(5), pages 1637-1667, October.
    5. Amore, Mario Daniele & Bennedsen, Morten, 2016. "Corporate governance and green innovation," Journal of Environmental Economics and Management, Elsevier, vol. 75(C), pages 54-72.
    6. Liao, Hua & Fan, Ying & Wei, Yi-Ming, 2007. "What induced China's energy intensity to fluctuate: 1997-2006?," Energy Policy, Elsevier, vol. 35(9), pages 4640-4649, September.
    7. Chen, Suisui & Zhang, Hongyan & Wang, Shuhong, 2022. "Trade openness, economic growth, and energy intensity in China," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    8. Bu, Maoliang & Li, Shuang & Jiang, Lei, 2019. "Foreign direct investment and energy intensity in China: Firm-level evidence," Energy Economics, Elsevier, vol. 80(C), pages 366-376.
    9. Huilian Han & Hui Li, 2020. "Coupling Coordination Evaluation between Population and Land Urbanization in Ha-Chang Urban Agglomeration," Sustainability, MDPI, vol. 12(1), pages 1-23, January.
    10. Voigt, Sebastian & De Cian, Enrica & Schymura, Michael & Verdolini, Elena, 2014. "Energy intensity developments in 40 major economies: Structural change or technology improvement?," Energy Economics, Elsevier, vol. 41(C), pages 47-62.
    11. Jimenez, Raul & Mercado, Jorge, 2014. "Energy intensity: A decomposition and counterfactual exercise for Latin American countries," Energy Economics, Elsevier, vol. 42(C), pages 161-171.
    12. Sun, Huaping & Edziah, Bless Kofi & Sun, Chuanwang & Kporsu, Anthony Kwaku, 2019. "Institutional quality, green innovation and energy efficiency," Energy Policy, Elsevier, vol. 135(C).
    13. Hang, Ye & Sun, Jiasen & Wang, Qunwei & Zhao, Zengyao & Wang, Yizhong, 2015. "Measuring energy inefficiency with undesirable outputs and technology heterogeneity in Chinese cities," Economic Modelling, Elsevier, vol. 49(C), pages 46-52.
    14. Yulan Lv & Wei Chen & Jianquan Cheng, 2019. "Direct and Indirect Effects of Urbanization on Energy Intensity in Chinese Cities: A Regional Heterogeneity Analysis," Sustainability, MDPI, vol. 11(11), pages 1-20, June.
    15. Akihiro Otsuka & Mika Goto & Toshiyuki Sueyoshi, 2014. "Energy efficiency and agglomeration economies: the case of Japanese manufacturing industries," Regional Science Policy & Practice, Wiley Blackwell, vol. 6(2), pages 195-212, June.
    16. Lin, Boqiang & Du, Kerui, 2013. "Technology gap and China's regional energy efficiency: A parametric metafrontier approach," Energy Economics, Elsevier, vol. 40(C), pages 529-536.
    17. Pan, Xiongfeng & Uddin, Md. Kamal & Han, Cuicui & Pan, Xianyou, 2019. "Dynamics of financial development, trade openness, technological innovation and energy intensity: Evidence from Bangladesh," Energy, Elsevier, vol. 171(C), pages 456-464.
    18. Song Wang & Jiexin Wang & Chenqi Wei & Xueli Wang & Fei Fan, 2021. "Collaborative innovation efficiency: From within cities to between cities—Empirical analysis based on innovative cities in China," Growth and Change, Wiley Blackwell, vol. 52(3), pages 1330-1360, September.
    19. Han, Feng & Ke, Shanzi, 2016. "The effects of factor proximity and market potential on urban manufacturing output," China Economic Review, Elsevier, vol. 39(C), pages 31-45.
    20. Pan, Xiuzhen & Wei, Zixiang & Han, Botang & Shahbaz, Muhammad, 2021. "The heterogeneous impacts of interregional green technology spillover on energy intensity in China," Energy Economics, Elsevier, vol. 96(C).
    21. Chen, Zhao & Kahn, Matthew E. & Liu, Yu & Wang, Zhi, 2018. "The consequences of spatially differentiated water pollution regulation in China," Journal of Environmental Economics and Management, Elsevier, vol. 88(C), pages 468-485.
    22. Miao, Cheng-lin & Duan, Meng-meng & Zuo, Yang & Wu, Xin-yu, 2021. "Spatial heterogeneity and evolution trend of regional green innovation efficiency--an empirical study based on panel data of industrial enterprises in China's provinces," Energy Policy, Elsevier, vol. 156(C).
    23. Sandra Poncet, 2003. "Domestic Market Fragmentation and Economic Growth in China (?)," ERSA conference papers ersa03p117, European Regional Science Association.
    24. Ouyang, Xiaoling & Gao, Beiying & Du, Kerui & Du, Gang, 2018. "Industrial sectors' energy rebound effect: An empirical study of Yangtze River Delta urban agglomeration," Energy, Elsevier, vol. 145(C), pages 408-416.
    25. Bilgili, Faik & Koçak, Emrah & Bulut, Ümit & Kuloğlu, Ayhan, 2017. "The impact of urbanization on energy intensity: Panel data evidence considering cross-sectional dependence and heterogeneity," Energy, Elsevier, vol. 133(C), pages 242-256.
    26. Sadorsky, Perry, 2013. "Do urbanization and industrialization affect energy intensity in developing countries?," Energy Economics, Elsevier, vol. 37(C), pages 52-59.
    27. Fırat Emir & Festus Victor Bekun, 2019. "Energy intensity, carbon emissions, renewable energy, and economic growth nexus: New insights from Romania," Energy & Environment, , vol. 30(3), pages 427-443, May.
    28. Wurlod, Jules-Daniel & Noailly, Joëlle, 2018. "The impact of green innovation on energy intensity: An empirical analysis for 14 industrial sectors in OECD countries," Energy Economics, Elsevier, vol. 71(C), pages 47-61.
    29. 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).
    30. Fanchao Kong & Hongkai Zhang & Xiangyan Meng & Shuai Li & Jia Liu, 2022. "Can the Policy of National Urban Agglomeration Improve Economic and Environmental Gains? Evidence from Quasi-Natural Experiments with 280 Cities in China," IJERPH, MDPI, vol. 19(13), pages 1-18, June.
    31. Elliott, Robert J.R. & Sun, Puyang & Zhu, Tong, 2017. "The direct and indirect effect of urbanization on energy intensity: A province-level study for China," Energy, Elsevier, vol. 123(C), pages 677-692.
    32. Hu, Wei & Fan, Yuemin, 2020. "City size and energy conservation: Do large cities in China consume more energy?," Energy Economics, Elsevier, vol. 92(C).
    33. Wanfang Xiong & Yan Han & M. James C. Crabbe & Xiao-Guang Yue, 2020. "Fiscal Expenditures on Science and Technology and Environmental Pollution: Evidence from China," IJERPH, MDPI, vol. 17(23), pages 1-20, November.
    34. Luan, Bingjiang & Zou, Hong & Chen, Shuxing & Huang, Junbing, 2021. "The effect of industrial structure adjustment on China’s energy intensity: Evidence from linear and nonlinear analysis," Energy, Elsevier, vol. 218(C).
    35. Chen, Zhongfei & Huang, Wanjing & Zheng, Xian, 2019. "The decline in energy intensity: Does financial development matter?," Energy Policy, Elsevier, vol. 134(C).
    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. Jin, Taeyoung, 2022. "Impact of heat and electricity consumption on energy intensity: A panel data analysis," Energy, Elsevier, vol. 239(PA).
    2. Pan, Xiuzhen & Wei, Zixiang & Han, Botang & Shahbaz, Muhammad, 2021. "The heterogeneous impacts of interregional green technology spillover on energy intensity in China," Energy Economics, Elsevier, vol. 96(C).
    3. Pan, Xiongfeng & Uddin, Md. Kamal & Saima, Umme & Jiao, Zhiming & Han, Cuicui, 2019. "How do industrialization and trade openness influence energy intensity? Evidence from a path model in case of Bangladesh," Energy Policy, Elsevier, vol. 133(C).
    4. Bashir, Muhammad Adnan & Sheng, Bin & Doğan, Buhari & Sarwar, Suleman & Shahzad, Umer, 2020. "Export product diversification and energy efficiency: Empirical evidence from OECD countries," Structural Change and Economic Dynamics, Elsevier, vol. 55(C), pages 232-243.
    5. Shaoyan Yang & Duodong Ding & Churen Sun, 2022. "Does Innovative City Policy Improve Green Total Factor Energy Efficiency? Evidence from China," Sustainability, MDPI, vol. 14(19), pages 1-30, October.
    6. Chen, Zhongfei & Huang, Wanjing & Zheng, Xian, 2019. "The decline in energy intensity: Does financial development matter?," Energy Policy, Elsevier, vol. 134(C).
    7. Dargahi, Hassan & Khameneh, Kazem Biabany, 2019. "Energy intensity determinants in an energy-exporting developing economy: Case of Iran," Energy, Elsevier, vol. 168(C), pages 1031-1044.
    8. Feng, Yidai & Liu, Yaobin & Yuan, Huaxi, 2022. "The spatial threshold effect and its regional boundary of new-type urbanization on energy efficiency," Energy Policy, Elsevier, vol. 164(C).
    9. Yu, Yantuan & Chen, Xudong & Zhang, Ning, 2022. "Innovation and energy productivity: An empirical study of the innovative city pilot policy in China✰," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    10. Feng, Yidai & Yuan, Huaxi & Liu, Yaobin, 2023. "The energy-saving effect in the new transformation of urbanization," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 41-59.
    11. Lv, Yulan & Chen, Wei & Cheng, Jianquan, 2020. "Effects of urbanization on energy efficiency in China: New evidence from short run and long run efficiency models," Energy Policy, Elsevier, vol. 147(C).
    12. Huang, Junbing & Lian, Shijia & Qu, Ran & Luan, Bingjiang & Wang, Yajun, 2023. "Investigating the role of enterprises' property rights in China's provincial industrial energy intensity," Energy, Elsevier, vol. 282(C).
    13. Wang, Jian & Sun, Furong & Lv, Kangjuan & Wang, Lisha, 2022. "Industrial agglomeration and firm energy intensity: How important is spatial proximity?," Energy Economics, Elsevier, vol. 112(C).
    14. Li, Yaya & Cobbinah, Joana & Abban, Olivier Joseph & Veglianti, Eleonora, 2023. "Does green manufacturing technology innovation decrease energy intensity for sustainable development?," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 1010-1025.
    15. Zhaoxian Su & Yang Yang & Yun Wang & Pan Zhang & Xin Luo, 2023. "Study on Spatiotemporal Evolution Features and Affecting Factors of Collaborative Governance of Pollution Reduction and Carbon Abatement in Urban Agglomerations of the Yellow River Basin," IJERPH, MDPI, vol. 20(5), pages 1-20, February.
    16. Liu, Fengqin & Sim, Jae-yeon & Sun, Huaping & Edziah, Bless Kofi & Adom, Philip Kofi & Song, Shunfeng, 2023. "Assessing the role of economic globalization on energy efficiency: Evidence from a global perspective," China Economic Review, Elsevier, vol. 77(C).
    17. Hong, Junjie & Shi, Fangyuan & Zheng, Yuhan, 2023. "Does network infrastructure construction reduce energy intensity? Based on the “Broadband China” strategy," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    18. Shao, Jun & Wang, Lianghu, 2023. "Can new-type urbanization improve the green total factor energy efficiency? Evidence from China," Energy, Elsevier, vol. 262(PB).
    19. Trinh, Hai Hong & Sharma, Gagan Deep & Tiwari, Aviral Kumar & Vo, Diem Thi Hong, 2022. "Examining the heterogeneity of financial development in the energy-environment nexus in the era of climate change: Novel evidence around the world," Energy Economics, Elsevier, vol. 116(C).
    20. Han, Feng & Xie, Rui & Fang, Jiayu, 2018. "Urban agglomeration economies and industrial energy efficiency," Energy, Elsevier, vol. 162(C), pages 45-59.

    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:22:p:14764-:d:968286. 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.