IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v96y2021ics014098832100030x.html
   My bibliography  Save this article

Low-carbon city pilot and carbon emission efficiency: Quasi-experimental evidence from China

Author

Listed:
  • Yu, Yantuan
  • Zhang, Ning

Abstract

This paper identifies the causal effect of low-carbon city pilot (LCCP) policy on carbon emission efficiency (CEE). Specifically, we first develop a general nonconvex metafrontier data envelopment analysis model to calculate CEE. We also provide a quasi-experimental evidence using a unique dataset of 251 cities in China during the years 2003 to 2018. Specifically, difference-in-differences (DID) and spatial DID (SDID) estimators are used as the main empirical strategy. We find that the LCCP policy improved CEE by 1.7% which are both economically and statistically significant. Further, its impact on neighbor untreated cities is about 64% of that on the treated cities. Scenario analysis documents that the average carbon dioxide emissions should be mitigated by approximately 8.37 million tons with a CEE increase of 1%, 8.84 million tons with a 2% increase, and 9.31 million tons with a 3% increase. Our findings also indicate that a 1% increase in years relative to a city's carbon dioxide emissions peak year commitment associates with a 1.3% increase in CEE.

Suggested Citation

  • Yu, Yantuan & Zhang, Ning, 2021. "Low-carbon city pilot and carbon emission efficiency: Quasi-experimental evidence from China," Energy Economics, Elsevier, vol. 96(C).
    • Handle: RePEc:eee:eneeco:v:96:y:2021:i:c:s014098832100030x
    DOI: 10.1016/j.eneco.2021.105125
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S014098832100030X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eneco.2021.105125?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. Michael Greenstone & Rema Hanna, 2014. "Environmental Regulations, Air and Water Pollution, and Infant Mortality in India," American Economic Review, American Economic Association, vol. 104(10), pages 3038-3072, October.
    2. Meng, Fanyi & Su, Bin & Thomson, Elspeth & Zhou, Dequn & Zhou, P., 2016. "Measuring China’s regional energy and carbon emission efficiency with DEA models: A survey," Applied Energy, Elsevier, vol. 183(C), pages 1-21.
    3. Wang, Qunwei & Su, Bin & Sun, Jiasen & Zhou, Peng & Zhou, Dequn, 2015. "Measurement and decomposition of energy-saving and emissions reduction performance in Chinese cities," Applied Energy, Elsevier, vol. 151(C), pages 85-92.
    4. Delgado, Michael S. & Florax, Raymond J.G.M., 2015. "Difference-in-differences techniques for spatial data: Local autocorrelation and spatial interaction," Economics Letters, Elsevier, vol. 137(C), pages 123-126.
    5. Chagas, André L.S. & Azzoni, Carlos R. & Almeida, Alexandre N., 2016. "A spatial difference-in-differences analysis of the impact of sugarcane production on respiratory diseases," Regional Science and Urban Economics, Elsevier, vol. 59(C), pages 24-36.
    6. Eliana La Ferrara & Alberto Chong & Suzanne Duryea, 2012. "Soap Operas and Fertility: Evidence from Brazil," American Economic Journal: Applied Economics, American Economic Association, vol. 4(4), pages 1-31, October.
    7. Gehrsitz, Markus, 2017. "The effect of low emission zones on air pollution and infant health," Journal of Environmental Economics and Management, Elsevier, vol. 83(C), pages 121-144.
    8. York, Richard & Rosa, Eugene A. & Dietz, Thomas, 2003. "STIRPAT, IPAT and ImPACT: analytic tools for unpacking the driving forces of environmental impacts," Ecological Economics, Elsevier, vol. 46(3), pages 351-365, October.
    9. 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.
    10. Bardaka, Eleni & Delgado, Michael S. & Florax, Raymond J.G.M., 2019. "A spatial multiple treatment/multiple outcome difference-in-differences model with an application to urban rail infrastructure and gentrification," Transportation Research Part A: Policy and Practice, Elsevier, vol. 121(C), pages 325-345.
    11. Hausman, Jerry & Kuersteiner, Guido, 2008. "Difference in difference meets generalized least squares: Higher order properties of hypotheses tests," Journal of Econometrics, Elsevier, vol. 144(2), pages 371-391, June.
    12. Zhang, Lulu & Xiong, Lichun & Cheng, Baodong & Yu, Chang, 2018. "How does foreign trade influence China’s carbon productivity? Based on panel spatial lag model analysis," Structural Change and Economic Dynamics, Elsevier, vol. 47(C), pages 171-179.
    13. Vujović, Tanja & Petković, Zdravka & Pavlović, Miloš & Jović, Srdjan, 2018. "Economic growth based in carbon dioxide emission intensity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 179-185.
    14. Pretis, Felix & Roser, Max, 2017. "Carbon dioxide emission-intensity in climate projections: Comparing the observational record to socio-economic scenarios," Energy, Elsevier, vol. 135(C), pages 718-725.
    15. Dubé, Jean & Legros, Diègo & Thériault, Marius & Des Rosiers, François, 2014. "A spatial Difference-in-Differences estimator to evaluate the effect of change in public mass transit systems on house prices," Transportation Research Part B: Methodological, Elsevier, vol. 64(C), pages 24-40.
    16. Ferreira, Ana & Pinheiro, Manuel Duarte & de Brito, Jorge & Mateus, Ricardo, 2018. "Combined carbon and energy intensity benchmarks for sustainable retail stores," Energy, Elsevier, vol. 165(PB), pages 877-889.
    17. Rosenbaum, Paul R., 2010. "Design Sensitivity and Efficiency in Observational Studies," Journal of the American Statistical Association, American Statistical Association, vol. 105(490), pages 692-702.
    18. Solmaria Halleck Vega & J. Paul Elhorst, 2015. "The Slx Model," Journal of Regional Science, Wiley Blackwell, vol. 55(3), pages 339-363, June.
    19. Wei, Quanling & Zhang, Jianzhong & Zhang, Xiangsun, 2000. "An inverse DEA model for inputs/outputs estimate," European Journal of Operational Research, Elsevier, vol. 121(1), pages 151-163, February.
    20. Shi Wang & Hua Wang & Li Zhang & Jun Dang, 2019. "Provincial Carbon Emissions Efficiency and Its Influencing Factors in China," Sustainability, MDPI, vol. 11(8), pages 1-21, April.
    21. Lu, Yi & Tao, Zhigang & Zhu, Lianming, 2017. "Identifying FDI spillovers," Journal of International Economics, Elsevier, vol. 107(C), pages 75-90.
    22. Yu Qin & Hongjia Zhu, 2018. "Run away? Air pollution and emigration interests in China," Journal of Population Economics, Springer;European Society for Population Economics, vol. 31(1), pages 235-266, January.
    23. Megan Heckert & Jeremy Mennis, 2012. "The Economic Impact of Greening Urban Vacant Land: A Spatial Difference-In-Differences Analysis," Environment and Planning A, , vol. 44(12), pages 3010-3027, December.
    24. Zhang, Ning & Wang, Bing & Liu, Zhu, 2016. "Carbon emissions dynamics, efficiency gains, and technological innovation in China's industrial sectors," Energy, Elsevier, vol. 99(C), pages 10-19.
    25. Wu, Haitao & Hao, Yu & Ren, Siyu, 2020. "How do environmental regulation and environmental decentralization affect green total factor energy efficiency: Evidence from China," Energy Economics, Elsevier, vol. 91(C).
    26. Wang, Guofeng & Deng, Xiangzheng & Wang, Jingyu & Zhang, Fan & Liang, Shiqi, 2019. "Carbon emission efficiency in China: A spatial panel data analysis," China Economic Review, Elsevier, vol. 56(C), pages 1-1.
    27. Torben Tiedemann & Tammo Francksen & Uwe Latacz-Lohmann, 2011. "Assessing the performance of German Bundesliga football players: a non-parametric metafrontier approach," 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. 19(4), pages 571-587, December.
    28. Slaughter, Matthew J., 2001. "Trade liberalization and per capita income convergence: a difference-in-differences analysis," Journal of International Economics, Elsevier, vol. 55(1), pages 203-228, October.
    29. Jianhuan Huang & Yantuan Yu & Chunbo Ma, 2018. "Energy Efficiency Convergence in China: Catch-Up, Lock-In and Regulatory Uniformity," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 70(1), pages 107-130, May.
    30. Isaiah Andrews, 2018. "Valid Two-Step Identification-Robust Confidence Sets for GMM," The Review of Economics and Statistics, MIT Press, vol. 100(2), pages 337-348, May.
    31. Li, Pei & Lu, Yi & Wang, Jin, 2016. "Does flattening government improve economic performance? Evidence from China," Journal of Development Economics, Elsevier, vol. 123(C), pages 18-37.
    32. Yu, Yantuan & Huang, Jianhuan & Zhang, Ning, 2019. "Modeling the eco-efficiency of Chinese prefecture-level cities with regional heterogeneities: A comparative perspective," Ecological Modelling, Elsevier, vol. 402(C), pages 1-17.
    Full references (including those not matched with items on IDEAS)

    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. Da Gao & Yanjun Cao & Chang Liu, 2023. "The Low-Carbon Policy and Urban Green Total Factor Energy Efficiency: Evidence from a Spatial Difference-in-Difference Method," IJERPH, MDPI, vol. 20(4), pages 1-20, February.
    2. Zhang, Yaoyu & Liu, Jin & Wang, Bo, 2022. "The impact of High-Speed Rails on urban expansion: An investigation using an SDID with dynamic effects method," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    3. Chagas, André L.S. & Azzoni, Carlos R. & Almeida, Alexandre N., 2016. "A spatial difference-in-differences analysis of the impact of sugarcane production on respiratory diseases," Regional Science and Urban Economics, Elsevier, vol. 59(C), pages 24-36.
    4. Chen, Shiyi & Jiang, Lingduo & Liu, Wanlin & Song, Hong, 2022. "Fireworks regulation, air pollution, and public health: Evidence from China," Regional Science and Urban Economics, Elsevier, vol. 92(C).
    5. Demidova, Olga, 2021. "Methods of spatial econometrics and evaluation of government programs effectiveness," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 64, pages 107-134.
    6. Xiaoying Zhong & Guanghai Liu & Peng Chen & Kaili Ke & Ruhe Xie, 2022. "The Impact of Internet Development on Urban Eco-Efficiency—A Quasi-Natural Experiment of “Broadband China” Pilot Policy," IJERPH, MDPI, vol. 19(3), pages 1-23, January.
    7. Yayun Ren & Jian Yu & Shuhua Xu & Jiaomei Tang & Chang Zhang, 2023. "Green Finance and Industrial Low-Carbon Transition: Evidence from a Quasi-Natural Experiment in China," Sustainability, MDPI, vol. 15(6), pages 1-17, March.
    8. Reinhold Kosfeld & Timo Mitze & Johannes Rode & Klaus Wälde, 2021. "The Covid‐19 containment effects of public health measures: A spatial difference‐in‐differences approach," Journal of Regional Science, Wiley Blackwell, vol. 61(4), pages 799-825, September.
    9. Jinbo Wang & Maosheng Ran & Yi Li & Heng Zhan, 2022. "Is venture capital a catalyst for innovative entrepreneurship in China? Empirical analysis based on the PSM‐DID method," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(4), pages 1039-1058, June.
    10. Yan, Linnan & Tu, Menger & Chagas, André L.S. & Tai, Lufeng, 2022. "The impact of high-speed railway on labor spatial misallocation—Based on spatial difference-in-differences analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 164(C), pages 82-97.
    11. Linnan Yan & Menger Tu & Andre Luis Squarize Chagas & Lufeng Tai, 2022. "The Impact of High-Speed Rail on Labor Spatial Misallocation– Based on Spatial Difference-in-Differences Analysis," Working Papers, Department of Economics 2022_19, University of São Paulo (FEA-USP).
    12. Jinkai Li & Jingjing Ma & Wei Wei, 2020. "Analysis and Evaluation of the Regional Characteristics of Carbon Emission Efficiency for China," Sustainability, MDPI, vol. 12(8), pages 1-22, April.
    13. Zhu, Chen & Lee, Chien-Chiang, 2022. "The effects of low-carbon pilot policy on technological innovation: Evidence from prefecture-level data in China," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    14. Ping Guo & Jin Li & Jinsong Kuang & Yifei Zhu & Renrui Xiao & Donghao Duan & Baocong Huang, 2022. "Low-Carbon Governance, Fiscal Decentralization and Sulfur Dioxide Emissions: Evidence from a Quasi-Experiment with Chinese Heavy Pollution Enterprises," Sustainability, MDPI, vol. 14(6), pages 1-24, March.
    15. Li-Ming Xue & Zhi-Xue Zheng & Shuo Meng & Mingjun Li & Huaqing Li & Ji-Ming Chen, 2022. "Carbon emission efficiency and spatio-temporal dynamic evolution of the cities in Beijing-Tianjin-Hebei Region, China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(6), pages 7640-7664, June.
    16. Du, Xiaoyun & Meng, Conghui & Guo, Zhenhua & Yan, Hang, 2023. "An improved approach for measuring the efficiency of low carbon city practice in China," Energy, Elsevier, vol. 268(C).
    17. Wang, Yunmin & Cao, Guohua & Yan, Youliang & Wang, Jingjing, 2022. "Does high-speed rail stimulate cross-city technological innovation collaboration? Evidence from China," Transport Policy, Elsevier, vol. 116(C), pages 119-131.
    18. Fei Xue & Minliang Zhou & Jiaqi Liu, 2023. "Are Cities Saving Energy by Getting Smarter? Evidence from Smart City Pilots in China," Sustainability, MDPI, vol. 15(4), pages 1-15, February.
    19. Ling-Yun He & Xiao-Feng Qi, 2021. "Environmental Courts, Environment and Employment: Evidence from China," Sustainability, MDPI, vol. 13(11), pages 1-16, June.
    20. Tan, Jing & Liu, Tianyi & Xu, Hao, 2024. "The environmental and economic consequences of environmental centralization: Evidence from China's environmental vertical management reform," China Economic Review, Elsevier, vol. 84(C).

    More about this item

    Keywords

    Low-carbon city pilot; Carbon emission efficiency; DID; Nonconvex metafrontier; Data envelopment analysis;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • Q32 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Exhaustible Resources and Economic Development
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth

    Statistics

    Access and download statistics

    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:96:y:2021:i:c:s014098832100030x. 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.