IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v12y2023i7p1292-d1179864.html
   My bibliography  Save this article

Evaluating the Impact of Smart City Policy on Carbon Emission Efficiency

Author

Listed:
  • Xingneng Xia

    (School of Public Policy and Administration, Xi’an Jiaotong University, Xi’an 710049, China)

  • Ruoxi Yu

    (School of Public Policy and Administration, Xi’an Jiaotong University, Xi’an 710049, China)

  • Sheng Zhang

    (School of Public Policy and Administration, Xi’an Jiaotong University, Xi’an 710049, China)

Abstract

Smart city policy (SCP) is crucial to addressing climate change and achieving sustainable urban development with low carbon emissions. The purpose of this paper is to investigate the mechanisms through which smart city policies have an impact on carbon emission efficiency (CEE). In terms of research methodology, we construct a quasi-natural experiment on smart city policies in China and use the time-varying DID approach to study this issue. The DEA method was used to measure the CEE. For the data sample, panel data from 281 cities in China between 2007 and 2020 was used in this study. The findings are as follows: ① SCP has a significant impact on CEE. This conclusion remains valid after introducing parallel trend tests, placebo tests, and other robustness tests. ② The mechanism test result reveals that SCP has a positive impact on urban CEE through three main channels: promoting industrial upgrading, increasing public environmental attention, and enhancing marketization. ③ The analysis of heterogeneity reveals that the impact of SCP on CEE is noticeable in cities that belong to well-developed economic regions with a lower intensity of environmental regulations, higher levels of green finance, and fewer official changes. This research contributes to the existing literature on the environmental assessment of SCP and offers valuable policy insights for cities to tackle climate change and sustainable urban planning.

Suggested Citation

  • Xingneng Xia & Ruoxi Yu & Sheng Zhang, 2023. "Evaluating the Impact of Smart City Policy on Carbon Emission Efficiency," Land, MDPI, vol. 12(7), pages 1-18, June.
    • Handle: RePEc:gam:jlands:v:12:y:2023:i:7:p:1292-:d:1179864
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/12/7/1292/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/12/7/1292/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Batabyal, Amitrajeet A. & Beladi, Hamid, 2019. "The optimal provision of information and communication technologies in smart cities," Technological Forecasting and Social Change, Elsevier, vol. 147(C), pages 216-220.
    2. 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.
    3. Gu, Yan & Ho, Kung-Cheng & Xia, Senmao & Yan, Cheng, 2022. "Do public environmental concerns promote new energy enterprises' development? Evidence from a quasi-natural experiment," Energy Economics, Elsevier, vol. 109(C).
    4. Irfan, Muhammad & Razzaq, Asif & Sharif, Arshian & Yang, Xiaodong, 2022. "Influence mechanism between green finance and green innovation: Exploring regional policy intervention effects in China," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    5. Tone, Kaoru & Tsutsui, Miki, 2010. "An epsilon-based measure of efficiency in DEA - A third pole of technical efficiency," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1554-1563, December.
    6. Gao, Mingyun & Yang, Honglin & Xiao, Qinzi & Goh, Mark, 2022. "A novel method for carbon emission forecasting based on Gompertz's law and fractional grey model: Evidence from American industrial sector," Renewable Energy, Elsevier, vol. 181(C), pages 803-819.
    7. Ma, Dan & Zhu, Qing, 2022. "Innovation in emerging economies: Research on the digital economy driving high-quality green development," Journal of Business Research, Elsevier, vol. 145(C), pages 801-813.
    8. 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.
    9. Caragliu, Andrea & Del Bo, Chiara F., 2019. "Smart innovative cities: The impact of Smart City policies on urban innovation," Technological Forecasting and Social Change, Elsevier, vol. 142(C), pages 373-383.
    10. Paola Panuccio, 2019. "Smart Planning: From City to Territorial System," Sustainability, MDPI, vol. 11(24), pages 1-15, December.
    11. Gao, Kang & Yuan, Yijun, 2021. "The effect of innovation-driven development on pollution reduction: Empirical evidence from a quasi-natural experiment in China," Technological Forecasting and Social Change, Elsevier, vol. 172(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. Orkun Davutluoğlu & Abdurrahman Yavuzdeğer & Burak Esenboğa & Özge Demirdelen & Kübra Tümay Ateş & Tuğçe Demirdelen, 2024. "Carbon Emission Analysis and Reporting in Urban Emissions: An Analysis of the Greenhouse Gas Inventories and Climate Action Plans in Sarıçam Municipality," Sustainability, MDPI, vol. 16(10), pages 1-15, May.
    2. Xingneng Xia & Xuezhao Chen & Qinqin Chen, 2024. "Evaluating the Impact of Low-Carbon Urban Policy on Corporate Green Innovation—Evidence from China’s National Low-Carbon City Strategy Program," Sustainability, MDPI, vol. 16(10), pages 1-26, 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. Du, Gang & Li, Wendi, 2022. "Does innovative city building promote green logistics efficiency? Evidence from a quasi-natural experiment with 285 cities," Energy Economics, Elsevier, vol. 114(C).
    2. Jun Gao & Ning Xu & Ju Zhou, 2023. "Innovative City Construction and Urban Environmental Performance: Empirical Evidence from China," Sustainability, MDPI, vol. 15(12), pages 1-22, June.
    3. Yan, Zheming & Sun, Zao & Shi, Rui & Zhao, Minjuan, 2023. "Smart city and green development: Empirical evidence from the perspective of green technological innovation," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    4. Weijia Cui & Xueqin Lin & Dai Wang & Ying Mi, 2022. "Urban Industrial Carbon Efficiency Measurement and Influencing Factors Analysis in China," Land, MDPI, vol. 12(1), pages 1-21, December.
    5. Ning Xu & Desen Zhao & Wenjie Zhang & He Zhang & Wanxu Chen & Min Ji & Ming Liu, 2022. "Innovation-Driven Development and Urban Land Low-Carbon Use Efficiency: A Policy Assessment from China," Land, MDPI, vol. 11(10), pages 1-21, September.
    6. Ning Xu & He Zhang & Tixin Li & Xiao Ling & Qian Shen, 2022. "How Big Data Affect Urban Low-Carbon Transformation—A Quasi-Natural Experiment from China," IJERPH, MDPI, vol. 19(23), pages 1-16, December.
    7. 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.
    8. Fan, Xiaomin & Xu, Yingzhi, 2023. "Does high-speed railway promote urban innovation? Evidence from China," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
    9. Gómez-Calvet, Roberto & Conesa, David & Gómez-Calvet, Ana Rosa & Tortosa-Ausina, Emili, 2014. "Energy efficiency in the European Union: What can be learned from the joint application of directional distance functions and slacks-based measures?," Applied Energy, Elsevier, vol. 132(C), pages 137-154.
    10. Haixiang Xu & Rui Zhang, 2024. "Dynamic Analysis of Urban Land Use Efficiency in the Western Taiwan Strait Economic Zone," Land, MDPI, vol. 13(8), pages 1-26, August.
    11. Chunhua Xin & Xiufeng Lai, 2022. "Does the Environmental Information Disclosure Promote the High-Quality Development of China’s Resource-Based Cities?," Sustainability, MDPI, vol. 14(11), pages 1-26, May.
    12. Da Gao & Chang Liu & Xinyan Wei & Yang Liu, 2023. "Can River Chief System Policy Improve Enterprises’ Energy Efficiency? Evidence from China," IJERPH, MDPI, vol. 20(4), pages 1-17, February.
    13. Eryu Zhang & Xiaoyu He & Peng Xiao, 2022. "Does Smart City Construction Decrease Urban Carbon Emission Intensity? Evidence from a Difference-in-Difference Estimation in China," Sustainability, MDPI, vol. 14(23), pages 1-16, December.
    14. Guo, Bingnan & Wang, Yu & Zhang, Hao & Liang, Chunyan & Feng, Yu & Hu, Feng, 2023. "Impact of the digital economy on high-quality urban economic development: Evidence from Chinese cities," Economic Modelling, Elsevier, vol. 120(C).
    15. Bo Li & Jing Liu & Qian Liu & Muhammad Mohiuddin, 2022. "The Effects of Broadband Infrastructure on Carbon Emission Efficiency of Resource-Based Cities in China: A Quasi-Natural Experiment from the “Broadband China” Pilot Policy," IJERPH, MDPI, vol. 19(11), pages 1-27, May.
    16. Sainan Cheng & Guohua Qu, 2023. "Research on the Effect of Digital Economy on Carbon Emissions under the Background of “Double Carbon”," IJERPH, MDPI, vol. 20(6), pages 1-27, March.
    17. Gao, Kang & Yuan, Yijun, 2022. "Government intervention, spillover effect and urban innovation performance: Empirical evidence from national innovative city pilot policy in China," Technology in Society, Elsevier, vol. 70(C).
    18. Wang, Ke-Liang & Sun, Ting-Ting & Xu, Ru-Yu & Miao, Zhuang & Cheng, Yun-He, 2022. "How does internet development promote urban green innovation efficiency? Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    19. Zhang, Yaxin & Zeng, Shibo & Wu, Qiaosheng & Fu, Junyi & Li, Tongping, 2023. "A study on the impact of the carbon emissions trading policy on the mining industry based on Porter hypothesis," Resources Policy, Elsevier, vol. 87(PB).
    20. 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.

    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:jlands:v:12:y:2023:i:7:p:1292-:d:1179864. 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.