IDEAS home Printed from https://ideas.repec.org/a/eee/lauspo/v131y2023ics0264837723001758.html
   My bibliography  Save this article

A new type of urbanization policy and transition of low-carbon society: A "local- neighborhood" perspective

Author

Listed:
  • Li, Shuoshuo
  • Liu, Yaobin
  • Elahi, Ehsan
  • Meng, Xiao
  • Deng, Weifeng

Abstract

This study aims to develop a framework linking New-Type Urbanization (NTU) and carbon emissions, considering both direct and spillover effects. Firstly, the paper constructs a multi-dimensional index to measure NTU and documents the spatial patterns of NTU levels in China, showing remarkable inequality between the eastern and western regions. Secondly, the study evaluates the effectiveness of pilot policies aimed at achieving Smart City and NTU goals. Using the Difference-in-Difference model based on panel data collected from 108 cities in the Yangtze River Economic Belt from 2006 to 2019, the study provides empirical evidence that these policies can significantly reduce carbon emissions in terms of production and consumption. Moreover, the study finds that the policies have significant spatial spillover effects on neighboring cities based on the Spatial Panel Durbin Model. The findings suggest that such policies can effectively reduce carbon emissions in areas with significant human activity and have important policy implications for achieving sustainable development in China.

Suggested Citation

  • Li, Shuoshuo & Liu, Yaobin & Elahi, Ehsan & Meng, Xiao & Deng, Weifeng, 2023. "A new type of urbanization policy and transition of low-carbon society: A "local- neighborhood" perspective," Land Use Policy, Elsevier, vol. 131(C).
    • Handle: RePEc:eee:lauspo:v:131:y:2023:i:c:s0264837723001758
    DOI: 10.1016/j.landusepol.2023.106709
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0264837723001758
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.landusepol.2023.106709?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jing Wang & Liang Feng & Paul I. Palmer & Yi Liu & Shuangxi Fang & Hartmut Bösch & Christopher W. O’Dell & Xiaoping Tang & Dongxu Yang & Lixin Liu & ChaoZong Xia, 2020. "Large Chinese land carbon sink estimated from atmospheric carbon dioxide data," Nature, Nature, vol. 586(7831), pages 720-723, October.
    2. Lin, Boqiang & Zhu, Junpeng, 2021. "Impact of China's new-type urbanization on energy intensity: A city-level analysis," Energy Economics, Elsevier, vol. 99(C).
    3. Chen, Jing & Zhou, Chunshan & Wang, Shaojian & Li, Shijie, 2018. "Impacts of energy consumption structure, energy intensity, economic growth, urbanization on PM2.5 concentrations in countries globally," Applied Energy, Elsevier, vol. 230(C), pages 94-105.
    4. Wang, Wei-Zheng & Liu, Lan-Cui & Liao, Hua & Wei, Yi-Ming, 2021. "Impacts of urbanization on carbon emissions: An empirical analysis from OECD countries," Energy Policy, Elsevier, vol. 151(C).
    5. 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.
    6. Wang, Yongpei & Li, Jun, 2019. "Spatial spillover effect of non-fossil fuel power generation on carbon dioxide emissions across China's provinces," Renewable Energy, Elsevier, vol. 136(C), pages 317-330.
    7. Elahi, Ehsan & Zhang, Hongxia & Lirong, Xing & Khalid, Zainab & Xu, Haiyun, 2021. "Understanding cognitive and socio-psychological factors determining farmers’ intentions to use improved grassland: Implications of land use policy for sustainable pasture production," Land Use Policy, Elsevier, vol. 102(C).
    8. Jing Wang & Liang Feng & Paul I. Palmer & Yi Liu & Shuangxi Fang & Hartmut Bösch & Christopher W. O’Dell & Xiaoping Tang & Dongxu Yang & Lixin Liu & ChaoZong Xia, 2020. "Publisher Correction: Large Chinese land carbon sink estimated from atmospheric carbon dioxide data," Nature, Nature, vol. 588(7837), pages 19-19, December.
    9. Ma, Junhai & Hou, Yaming & Wang, Zongxian & Yang, Wenhui, 2021. "Pricing strategy and coordination of automobile manufacturers based on government intervention and carbon emission reduction," Energy Policy, Elsevier, vol. 148(PA).
    10. Zhang, Ning & Yu, Keren & Chen, Zhongfei, 2017. "How does urbanization affect carbon dioxide emissions? A cross-country panel data analysis," Energy Policy, Elsevier, vol. 107(C), pages 678-687.
    11. Wang, Jin, 2013. "The economic impact of Special Economic Zones: Evidence from Chinese municipalities," Journal of Development Economics, Elsevier, vol. 101(C), pages 133-147.
    12. Wang, Xue-Chao & Klemeš, Jiří Jaromír & Wang, Yutao & Dong, Xiaobin & Wei, Hejie & Xu, Zihan & Varbanov, Petar Sabev, 2020. "Water-Energy-Carbon Emissions nexus analysis of China: An environmental input-output model-based approach," Applied Energy, Elsevier, vol. 261(C).
    13. Yu, Binbin, 2021. "Ecological effects of new-type urbanization in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    14. Elahi, Ehsan & Khalid, Zainab & Tauni, Muhammad Zubair & Zhang, Hongxia & Lirong, Xing, 2022. "Extreme weather events risk to crop-production and the adaptation of innovative management strategies to mitigate the risk: A retrospective survey of rural Punjab, Pakistan," Technovation, Elsevier, vol. 117(C).
    15. Wang, Keying & Wu, Meng & Sun, Yongping & Shi, Xunpeng & Sun, Ao & Zhang, Ping, 2019. "Resource abundance, industrial structure, and regional carbon emissions efficiency in China," Resources Policy, Elsevier, vol. 60(C), pages 203-214.
    16. Wang, Qiang, 2014. "Effects of urbanisation on energy consumption in China," Energy Policy, Elsevier, vol. 65(C), pages 332-339.
    17. Callaway, Brantly & Sant’Anna, Pedro H.C., 2021. "Difference-in-Differences with multiple time periods," Journal of Econometrics, Elsevier, vol. 225(2), pages 200-230.
    18. Athey, Susan & Imbens, Guido W., 2022. "Design-based analysis in Difference-In-Differences settings with staggered adoption," Journal of Econometrics, Elsevier, vol. 226(1), pages 62-79.
    19. 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).
    20. Yan Wu & Chunlai Chen & Cong Hu, 2021. "Does the Belt and Road Initiative Increase the Carbon Emission Intensity of Participating Countries?," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 29(3), pages 1-25, May.
    21. Yue-Jun Zhang & Zhao Liu & Huan Zhang & Tai-De Tan, 2014. "The impact of economic growth, industrial structure and urbanization on carbon emission intensity in 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. 73(2), pages 579-595, September.
    22. Wang, Shaojian & Fang, Chuanglin & Guan, Xingliang & Pang, Bo & Ma, Haitao, 2014. "Urbanisation, energy consumption, and carbon dioxide emissions in China: A panel data analysis of China’s provinces," Applied Energy, Elsevier, vol. 136(C), pages 738-749.
    23. Goodman-Bacon, Andrew, 2021. "Difference-in-differences with variation in treatment timing," Journal of Econometrics, Elsevier, vol. 225(2), pages 254-277.
    24. Huang, Lizhen & Krigsvoll, Guri & Johansen, Fred & Liu, Yongping & Zhang, Xiaoling, 2018. "Carbon emission of global construction sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 1906-1916.
    25. Wang, Bin & Yu, Minxiu & Zhu, Yucheng & Bao, Pinjuan, 2021. "Unveiling the driving factors of carbon emissions from industrial resource allocation in China: A spatial econometric perspective," Energy Policy, Elsevier, vol. 158(C).
    26. Xiaoxin Zhang & Martin Brandt & Xiaowei Tong & Philippe Ciais & Yuemin Yue & Xiangming Xiao & Wenmin Zhang & Kelin Wang & Rasmus Fensholt, 2022. "A large but transient carbon sink from urbanization and rural depopulation in China," Nature Sustainability, Nature, vol. 5(4), pages 321-328, April.
    27. Rahman, Mohammad Mafizur & Alam, Khosrul, 2021. "Clean energy, population density, urbanization and environmental pollution nexus: Evidence from Bangladesh," Renewable Energy, Elsevier, vol. 172(C), pages 1063-1072.
    28. Roberts, J. Timmons & Grimes, Peter E., 1997. "Carbon intensity and economic development 1962-1991: A brief exploration of the environmental Kuznets curve," World Development, Elsevier, vol. 25(2), pages 191-198, February.
    29. Jiaxing Pang & Hengji Li & Chengpeng Lu & Chenyu Lu & Xingpeng Chen, 2020. "Regional Differences and Dynamic Evolution of Carbon Emission Intensity of Agriculture Production in China," IJERPH, MDPI, vol. 17(20), pages 1-14, October.
    30. Guo, Qingbin & Wang, Yong & Dong, Xiaobin, 2022. "Effects of smart city construction on energy saving and CO2 emission reduction: Evidence from China," Applied Energy, Elsevier, vol. 313(C).
    31. Liddle, Brantley, 2014. "Impact of population, age structure, and urbanization on carbon emissions/energy consumption: Evidence from macro-level, cross-country analyses," MPRA Paper 61306, University Library of Munich, Germany.
    32. J. Paul Elhorst, 2014. "Matlab Software for Spatial Panels," International Regional Science Review, , vol. 37(3), pages 389-405, July.
    33. Elahi, Ehsan & Khalid, Zainab, 2022. "Estimating smart energy inputs packages using hybrid optimisation technique to mitigate environmental emissions of commercial fish farms," Applied Energy, Elsevier, vol. 326(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. Jin, Tanhua & Wang, Kailai & Xin, Yanan & Shi, Jian & Hong, Ye & Witlox, Frank, 2024. "Is a 15-Minute City Within Reach? Measuring Multimodal Accessibility and Carbon Footprint in 12 Major American Cities," Land Use Policy, Elsevier, vol. 142(C).

    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. Xu, Aiting & Song, Miaoyuan & Wu, Yunguang & Luo, Yifan & Zhu, Yuhan & Qiu, Keyang, 2024. "Effects of new urbanization on China's carbon emissions: A quasi-natural experiment based on the improved PSM-DID model," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    2. Mengcheng Li & Haimeng Liu & Shangkun Yu & Jianshi Wang & Yi Miao & Chengxin Wang, 2022. "Estimating the Decoupling between Net Carbon Emissions and Construction Land and Its Driving Factors: Evidence from Shandong Province, China," IJERPH, MDPI, vol. 19(15), pages 1-26, July.
    3. Kong, Dongmin & Liu, Chenhao & Ye, Wenxu, 2023. "Randomized inspection and firm's government subsidies: A natural experiment in China," China Economic Review, Elsevier, vol. 82(C).
    4. Baker, Andrew C. & Larcker, David F. & Wang, Charles C.Y., 2022. "How much should we trust staggered difference-in-differences estimates?," Journal of Financial Economics, Elsevier, vol. 144(2), pages 370-395.
    5. Wang, Shaojian & Xie, Zihan & Wu, Rong & Feng, Kuishang, 2022. "How does urbanization affect the carbon intensity of human well-being? A global assessment," Applied Energy, Elsevier, vol. 312(C).
    6. Jingyi Tian & Jun Nagayasu, 2023. "Financial Systemic Risk behind Artificial Intelligence:Evidence from China," TUPD Discussion Papers 44, Graduate School of Economics and Management, Tohoku University.
    7. Xing, Qiuhang & Xu, Gaoshuang & Wang, Yanping, 2024. "Open government data and the cost of debt," International Review of Financial Analysis, Elsevier, vol. 95(PA).
    8. Chen, Jianbao & Weng, Shimei & Tao, Weiliang & Song, Malin & Zhang, Linling, 2024. "Measuring carbon neutrality and exploring the threshold effects of its driving factors: Evidence from China," Applied Energy, Elsevier, vol. 373(C).
    9. Li, Yutao & Zhang, Jinning & Lyu, Yanwei, 2023. "Does telecommunications infrastructure promote entrepreneurship in developing countries? Evidence from a quasi-natural experiment in China," Structural Change and Economic Dynamics, Elsevier, vol. 66(C), pages 106-119.
    10. Xin Nie & Jianxian Wu & Han Wang & Weijuan Li & Chengdao Huang & Lihua Li, 2022. "Contributing to carbon peak: Estimating the causal impact of eco‐industrial parks on low‐carbon development in China," Journal of Industrial Ecology, Yale University, vol. 26(4), pages 1578-1593, August.
    11. David M. N. Mahon & Carlos J. Asarta, 2024. "Why are Schools Reclassifying Their Economics Major?," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 50(1), pages 103-116, January.
    12. Kayaoglu, Aysegul, 2022. "Do refugees cause crime?," World Development, Elsevier, vol. 154(C).
    13. Guccio, C. & Pignataro, G. & Vidoli, F., 2024. "It never rains but it pours: Austerity and mortality rate in peripheral areas," Economics & Human Biology, Elsevier, vol. 54(C).
    14. Yan Zhao & Ehsan Elahi & Zainab Khalid & Xuegang Sun & Fang Sun, 2023. "Environmental, Social and Governance Performance: Analysis of CEO Power and Corporate Risk," Sustainability, MDPI, vol. 15(2), pages 1-18, January.
    15. Alexander Karaivanov & Dongwoo Kim & Shih En Lu & Hitoshi Shigeoka, 2022. "COVID-19 vaccination mandates and vaccine uptake," Nature Human Behaviour, Nature, vol. 6(12), pages 1615-1624, December.
    16. Sho Miyaji, 2024. "Instrumented Difference-in-Differences with Heterogeneous Treatment Effects," Papers 2405.12083, arXiv.org, revised Jan 2025.
    17. Simon Freyaldenhoven & Christian B. Hansen & Jorge Pérez Pérez & Jesse M. Shapiro & Constantino Carreto, 2024. "Policy Effect Estimation and Visualization in Linear Panel Event-Study Designs: Introducing the xtevent Package," Working Papers 2024-09, Banco de México.
    18. Natali, Ilaria, 2024. "Economic Opportunity and Opioid Regulation: the Case of Codeine in France," TSE Working Papers 24-1563, Toulouse School of Economics (TSE).
    19. Shao, Jun & Wang, Lianghu, 2023. "Can new-type urbanization improve the green total factor energy efficiency? Evidence from China," Energy, Elsevier, vol. 262(PB).
    20. Dmitry Arkhangelsky & Guido Imbens, 2023. "Causal Models for Longitudinal and Panel Data: A Survey," Papers 2311.15458, arXiv.org, revised Jun 2024.

    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:eee:lauspo:v:131:y:2023:i:c:s0264837723001758. 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: Joice Jiang (email available below). General contact details of provider: https://www.journals.elsevier.com/land-use-policy .

    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.