IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v110y2022ics0140988322001888.html
   My bibliography  Save this article

The spatial spillover effect of low-carbon city pilot scheme on green efficiency in China's cities: Evidence from a quasi-natural experiment

Author

Listed:
  • Chen, Lifeng
  • Wang, Kaifeng

Abstract

To test the direct effect (impact on local) and indirect effect (spatial spillover) of low-carbon city pilot scheme (LCCPS) on China's cities' green efficiency, this paper first calculates and decomposes the green efficiency constrained with CO2 emissions and pollutants by using a range directional model (RDM) based on data envelopment analysis (DEA), then the global Malmquist-Luenberger (GML) index of 285 China's cities' green efficiency is obtained. Through the GML index, it is found that the green efficiency of sample cities has improved by 29.56% evenly in 2003–2017, and the main driving force of green efficiency progress is technological innovation. The green efficiency progress of LCCPS pilot cities is significantly greater than that of non-pilot cities, and there is a significant positive spatial autocorrelation in the green efficiency of 285 sample cities. According to the test results of the spatial difference in differences (Spatial-DID) model, LCCPS can positively promote the green efficiency of local and neighboring cities, and this result can pass the placebo test, and remain robust when using an alternative green efficiency index (without CO2 emissions) or a spatial-economic weight matrix. The use of propensity score matching (PSM) and instrumental variable method further shows that the above results will not change substantially even if the selection bias and endogeneity are eliminated. The mechanism analysis shows that: First, LCCPS improves the local green efficiency by promoting the aggregation of innovation resources, but the resulting siphon effect inhibits the aggregation of innovation resources and the green efficiency progress in neighboring cities. Second, LCCPS improves the local green efficiency of pilot cities by inhibiting the industrial activities and industrial energy consumption, but it can inhibit the green efficiency progress by increasing industrial activities and industrial energy consumption of neighboring cities. Although the above mechanism cannot completely reverse the beneficial space spillover effect of LCCPS, it can also effectively point out the future improvement direction of the policies in LCCPS.

Suggested Citation

  • Chen, Lifeng & Wang, Kaifeng, 2022. "The spatial spillover effect of low-carbon city pilot scheme on green efficiency in China's cities: Evidence from a quasi-natural experiment," Energy Economics, Elsevier, vol. 110(C).
    • Handle: RePEc:eee:eneeco:v:110:y:2022:i:c:s0140988322001888
    DOI: 10.1016/j.eneco.2022.106018
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988322001888
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eneco.2022.106018?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. Guido W. Imbens, 2020. "Potential Outcome and Directed Acyclic Graph Approaches to Causality: Relevance for Empirical Practice in Economics," Journal of Economic Literature, American Economic Association, vol. 58(4), pages 1129-1179, December.
    2. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    3. Cai, Xiqian & Lu, Yi & Wu, Mingqin & Yu, Linhui, 2016. "Does environmental regulation drive away inbound foreign direct investment? Evidence from a quasi-natural experiment in China," Journal of Development Economics, Elsevier, vol. 123(C), pages 73-85.
    4. Duan, Na & Guo, Jun-Peng & Xie, Bai-Chen, 2016. "Is there a difference between the energy and CO2 emission performance for China’s thermal power industry? A bootstrapped directional distance function approach," Applied Energy, Elsevier, vol. 162(C), pages 1552-1563.
    5. Choi, Yongrok & Zhang, Ning & Zhou, P., 2012. "Efficiency and abatement costs of energy-related CO2 emissions in China: A slacks-based efficiency measure," Applied Energy, Elsevier, vol. 98(C), pages 198-208.
    6. Dong-hyun Oh, 2010. "A global Malmquist-Luenberger productivity index," Journal of Productivity Analysis, Springer, vol. 34(3), pages 183-197, December.
    7. 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.
    8. Gene M. Grossman & Alan B. Krueger, 1995. "Economic Growth and the Environment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(2), pages 353-377.
    9. Hering, Laura & Poncet, Sandra, 2014. "Environmental policy and exports: Evidence from Chinese cities," Journal of Environmental Economics and Management, Elsevier, vol. 68(2), pages 296-318.
    10. Asmild, Mette & Pastor, Jesús T., 2010. "Slack free MEA and RDM with comprehensive efficiency measures," Omega, Elsevier, vol. 38(6), pages 475-483, December.
    11. Jia, Ruining & Shao, Shuai & Yang, Lili, 2021. "High-speed rail and CO2 emissions in urban China: A spatial difference-in-differences approach," Energy Economics, Elsevier, vol. 99(C).
    12. C. Justin Cook & Manisha Shah, 2022. "Aggregate Effects from Public Works: Evidence from India," The Review of Economics and Statistics, MIT Press, vol. 104(4), pages 797-806, October.
    13. Lin, Xu & Lee, Lung-fei, 2010. "GMM estimation of spatial autoregressive models with unknown heteroskedasticity," Journal of Econometrics, Elsevier, vol. 157(1), pages 34-52, July.
    14. Yang, Lisha & Li, Yutianhao & Liu, Hongxun, 2021. "Did carbon trade improve green production performance? Evidence from China," Energy Economics, Elsevier, vol. 96(C).
    15. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 605-654.
    16. Paul Elhorst & Eelco Zandberg & Jakob De Haan, 2013. "The Impact of Interaction Effects among Neighbouring Countries on Financial Liberalization and Reform: A Dynamic Spatial Panel Data Approach," Spatial Economic Analysis, Taylor & Francis Journals, vol. 8(3), pages 293-313, September.
    17. Lee, Lung-fei & Yu, Jihai, 2010. "Estimation of spatial autoregressive panel data models with fixed effects," Journal of Econometrics, Elsevier, vol. 154(2), pages 165-185, February.
    18. Pastor, Jesus T. & Lovell, C.A. Knox, 2005. "A global Malmquist productivity index," Economics Letters, Elsevier, vol. 88(2), pages 266-271, August.
    19. Zhicheng Xu & Tianshi Sun, 2021. "The Siphon effects of transportation infrastructure on internal migration: evidence from China’s HSR network," Applied Economics Letters, Taylor & Francis Journals, vol. 28(13), pages 1066-1070, July.
    20. Hanandita, Wulung & Tampubolon, Gindo, 2014. "Does poverty reduce mental health? An instrumental variable analysis," Social Science & Medicine, Elsevier, vol. 113(C), pages 59-67.
    21. M C A Silva Portela & E Thanassoulis & G Simpson, 2004. "Negative data in DEA: a directional distance approach applied to bank branches," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(10), pages 1111-1121, October.
    22. Goodman-Bacon, Andrew, 2021. "Difference-in-differences with variation in treatment timing," Journal of Econometrics, Elsevier, vol. 225(2), pages 254-277.
    23. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
    24. James P. LeSage & R. Kelley Pace, 2008. "Spatial Econometric Modeling Of Origin‐Destination Flows," Journal of Regional Science, Wiley Blackwell, vol. 48(5), pages 941-967, December.
    25. Wang, Han & Chen, Zhoupeng & Wu, Xingyi & Nie, Xin, 2019. "Can a carbon trading system promote the transformation of a low-carbon economy under the framework of the porter hypothesis? —Empirical analysis based on the PSM-DID method," Energy Policy, Elsevier, vol. 129(C), pages 930-938.
    26. Duggal, Vijaya G. & Saltzman, Cynthia & Klein, Lawrence R., 2007. "Infrastructure and productivity: An extension to private infrastructure and it productivity," Journal of Econometrics, Elsevier, vol. 140(2), pages 485-502, October.
    27. Proskuryakova, L. & Kovalev, A., 2015. "Measuring energy efficiency: Is energy intensity a good evidence base?," Applied Energy, Elsevier, vol. 138(C), pages 450-459.
    28. Yan, Dan & Ren, Xiaohang & Kong, Ying & Ye, Bin & Liao, Zangyi, 2020. "The heterogeneous effects of socioeconomic determinants on PM2.5 concentrations using a two-step panel quantile regression," Applied Energy, Elsevier, vol. 272(C).
    29. Yu, Yantuan & Zhang, Ning, 2021. "Low-carbon city pilot and carbon emission efficiency: Quasi-experimental evidence from China," Energy Economics, Elsevier, vol. 96(C).
    30. Shi, Xinzheng & Xu, Zhufeng, 2018. "Environmental regulation and firm exports: Evidence from the eleventh Five-Year Plan in China," Journal of Environmental Economics and Management, Elsevier, vol. 89(C), pages 187-200.
    31. Matthew A. COLE & Robert R.J. ELLIOTT & OKUBO Toshihiro & Liyun ZHANG, 2017. "The Pollution Outsourcing Hypothesis: An empirical test for Japan," Discussion papers 17096, Research Institute of Economy, Trade and Industry (RIETI).
    32. Hu, Yucai & Ren, Shenggang & Wang, Yangjie & Chen, Xiaohong, 2020. "Can carbon emission trading scheme achieve energy conservation and emission reduction? Evidence from the industrial sector in China," Energy Economics, Elsevier, vol. 85(C).
    33. Rolf Färe & Shawna Grosskopf, 2000. "Theory and Application of Directional Distance Functions," Journal of Productivity Analysis, Springer, vol. 13(2), pages 93-103, March.
    34. Mardani, Abbas & Zavadskas, Edmundas Kazimieras & Streimikiene, Dalia & Jusoh, Ahmad & Khoshnoudi, Masoumeh, 2017. "A comprehensive review of data envelopment analysis (DEA) approach in energy efficiency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1298-1322.
    35. Liu, Xiaodong & Lee, Lung-fei & Bollinger, Christopher R., 2010. "An efficient GMM estimator of spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 159(2), pages 303-319, December.
    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. Gao, Yihong & Gao, Jiayan, 2023. "Low-carbon transformation and corporate cash holdings," Finance Research Letters, Elsevier, vol. 54(C).
    2. Shuchen Niu & Xiang Luo & Tiantian Yang & Guodong Lin & Chongming Li, 2023. "Does the Low-Carbon City Pilot Policy Improve the Urban Land Green Use Efficiency?—Investigation Based on Multi-Period Difference-in-Differences Model," IJERPH, MDPI, vol. 20(3), pages 1-21, February.
    3. Xiao, De & Yu, Fan & Guo, Chenhao, 2023. "The impact of China's pilot carbon ETS on the labor income share: Based on an empirical method of combining PSM with staggered DID," Energy Economics, Elsevier, vol. 124(C).
    4. LU Guanyu & TANAKA Kenta & ARIMURA Toshi H., 2023. "The Impacts of the Tokyo and Saitama ETSs on the Energy Efficiency Performance of Manufacturing Facilities," Discussion papers 23007, Research Institute of Economy, Trade and Industry (RIETI).
    5. Liu, Mengsha & Jiang, Yan & Wei, Xiaokun & Ruan, Qingsong & Lv, Dayong, 2023. "Effect of high-speed rail on entrepreneurial activities: Evidence from China," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    6. Haonan Yang & Liang Chen & Huan Huang & Panyu Tang, 2022. "Measurement and Spatial-Temporal Evolution Characteristics of Low-Carbon Cities with High-Quality Development: The Case Study of the Yangtze River Economic Belt, China," Sustainability, MDPI, vol. 14(15), pages 1-23, August.
    7. Juan Yin & Jin Guo, 2022. "Ecological Effect Assessment of Low-Carbon City Construction in China," IJERPH, MDPI, vol. 19(21), pages 1-19, November.
    8. Ding, Jian & Liu, Baoliu & Shao, Xuefeng, 2022. "Spatial effects of industrial synergistic agglomeration and regional green development efficiency: Evidence from China," Energy Economics, Elsevier, vol. 112(C).
    9. Razzaq, Asif & Sharif, Arshian & Ozturk, Ilhan & Yang, Xiaodong, 2023. "Central inspections of environmental protection and transition for low-carbon Chinese cities: Policy intervention and mechanism analysis," Energy Economics, Elsevier, vol. 124(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. Kaifeng Wang & Chunping Zhong & Lifeng Chen & Yunmin Zeng, 2023. "The spatial spillover effect of China’s pollutants emission trading pilot scheme on green efficiency: evidence from 285 China’s cities," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(8), pages 8137-8163, August.
    2. Bai, Caiquan & Liu, Hangjuan & Zhang, Rongjie & Feng, Chen, 2023. "Blessing or curse? Market-driven environmental regulation and enterprises' total factor productivity: Evidence from China's carbon market pilots," Energy Economics, Elsevier, vol. 117(C).
    3. Pan, Minjie & Zhao, Xin & lv, Kangjuan & Rosak-Szyrocka, Joanna & Mentel, Grzegorz & Truskolaski, Tadeusz, 2023. "Internet development and carbon emission-reduction in the era of digitalization: Where will resource-based cities go?," Resources Policy, Elsevier, vol. 81(C).
    4. 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.
    5. Long Qian & Xiaolin Xu & Yunjie Zhou & Ying Sun & Duoliang Ma, 2023. "Carbon Emission Reduction Effects of the Smart City Pilot Policy in China," Sustainability, MDPI, vol. 15(6), pages 1-24, March.
    6. Yuqing Ge & Yucai Hu & Shenggang Ren, 2020. "Environmental Regulation and Foreign Direct Investment: Evidence from China’s Eleventh and Twelfth Five-Year Plans," Sustainability, MDPI, vol. 12(6), pages 1-18, March.
    7. Yu, Yunjiang & Dai, Chun & Wei, Yigang & Ren, Huiming & Zhou, Jiawen, 2022. "Air pollution prevention and control action plan substantially reduced PM2.5 concentration in China," Energy Economics, Elsevier, vol. 113(C).
    8. Yu, Xiaolin & Wan, Kai & Du, Qunyang, 2023. "Can carbon market policies achieve a “point-to-surface” effect?—Quasi-experimental evidence from China," Energy Policy, Elsevier, vol. 183(C).
    9. Mathilde Maurel & Thomas Pernet-Coudrier, 2020. "New Evidence on the Soft Budget Constraint: Chinese Environmental Policy Effectiveness in Private versus SOEs," Post-Print halshs-02469382, HAL.
    10. Sun, Chuanwang & Zhan, Yanhong & Gao, Xiang, 2023. "Does environmental regulation increase domestic value-added in exports? An empirical study of cleaner production standards in China," World Development, Elsevier, vol. 163(C).
    11. James Paul LeSage & Manfred M. Fischer, 2020. "Cross-sectional dependence model specifications in a static trade panel data setting," Journal of Geographical Systems, Springer, vol. 22(1), pages 5-46, January.
    12. Moscone, Francesco & Tosetti, Elisa & Canepa, Alessandra, 2014. "Real estate market and financial stability in US metropolitan areas: A dynamic model with spatial effects," Regional Science and Urban Economics, Elsevier, vol. 49(C), pages 129-146.
    13. Wang, Wei & Lee, Lung-Fei & Bao, Yan, 2018. "GMM estimation of the spatial autoregressive model in a system of interrelated networks," Regional Science and Urban Economics, Elsevier, vol. 69(C), pages 167-198.
    14. Ai, Hongshan & Zhou, Zhengqing & Li, Ke & Kang, Zhi-Yong, 2021. "Impacts of the desulfurization price subsidy policy on SO2 reduction: Evidence from China's coal-fired power plants," Energy Policy, Elsevier, vol. 157(C).
    15. Yanhong Feng & Shuanglian Chen & Pierre Failler, 2020. "Productivity Effect Evaluation on Market-Type Environmental Regulation: A Case Study of SO 2 Emission Trading Pilot in China," IJERPH, MDPI, vol. 17(21), pages 1-27, October.
    16. Zhang, Yue-Jun & Wang, Wei, 2021. "How does China's carbon emissions trading (CET) policy affect the investment of CET-covered enterprises?," Energy Economics, Elsevier, vol. 98(C).
    17. Feldmann, Horst, 2012. "Banking deregulation around the world, 1970s to 2000s: The impact on unemployment," International Review of Economics & Finance, Elsevier, vol. 24(C), pages 26-42.
    18. Michele Aquaro & Natalia Bailey & M. Hashem Pesaran, 2015. "Quasi Maximum Likelihood Estimation of Spatial Models with Heterogeneous Coefficients," CESifo Working Paper Series 5428, CESifo.
    19. de Moraes, Claudio Oliveira & Cruz, Guilherme, 2023. "What do we know about the relationship between banks and income inequality? Empirical evidence for emerging and low-income countries," Journal of Economics and Business, Elsevier, vol. 123(C).
    20. Yanyun Li & Faqin Lin & Wenxiao Wang, 2022. "Environmental regulation and inward foreign direct investment: Evidence from the eleventh Five‐Year Plan in China," Journal of Economic Surveys, Wiley Blackwell, vol. 36(3), pages 684-707, July.

    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:eneeco:v:110:y:2022:i:c:s0140988322001888. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    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.