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Marginal CO2 abatement costs: Findings from alternative shadow price estimates for Shanghai industrial sectors

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  • Zhou, X.
  • Fan, L.W.
  • Zhou, P.

Abstract

Shanghai, one of the most developed cities in China, is implementing a pilot regional carbon emission trading scheme. Estimating the marginal abatement costs of CO2 emissions for the industrial sectors covered in Shanghai's emission trading scheme provides the government and participating firms useful information for devising compliance policies. This paper employs multiple distance function approaches to estimating the shadow prices of CO2 emissions for Shanghai industrial sectors. Our empirical results show that the overall weighted average of shadow price estimates by different approaches ranges between 394.5 and 1906.1Yuan/ton, which indicates that model choice truly has a significant effect on the shadow price estimation. We have also identified a negative relationship between the shadow price of CO2 emissions and carbon intensity, and the heavy industries with higher carbon intensities tend to have lower shadow prices. It has been suggested that Shanghai municipal government take various measures to improve its carbon market, e.g. using the marginal abatement costs of participating sectors/firms as a criterion in the initial allocation of carbon emission allowances.

Suggested Citation

  • Zhou, X. & Fan, L.W. & Zhou, P., 2015. "Marginal CO2 abatement costs: Findings from alternative shadow price estimates for Shanghai industrial sectors," Energy Policy, Elsevier, vol. 77(C), pages 109-117.
  • Handle: RePEc:eee:enepol:v:77:y:2015:i:c:p:109-117
    DOI: 10.1016/j.enpol.2014.12.009
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    Cited by:

    1. Jie Zhang & Lu Zhang, 2016. "Impacts on CO 2 Emission Allowance Prices in China: A Quantile Regression Analysis of the Shanghai Emission Trading Scheme," Sustainability, MDPI, Open Access Journal, vol. 8(11), pages 1-12, November.
    2. Rakesh Kumar Jain & Surender Kumar, 2018. "Shadow Price of CO2 Emissions in Indian Thermal Power Sector," Working papers 287, Centre for Development Economics, Delhi School of Economics.
    3. repec:spr:nathaz:v:92:y:2018:i:2:d:10.1007_s11069-018-3223-1 is not listed on IDEAS
    4. repec:gam:jsusta:v:9:y:2017:i:6:p:932-:d:100349 is not listed on IDEAS
    5. Boussemart, Jean-Philippe & Leleu, Hervé & Shen, Zhiyang, 2017. "Worldwide carbon shadow prices during 1990–2011," Energy Policy, Elsevier, vol. 109(C), pages 288-296.
    6. Du, Limin & Hanley, Aoife & Wei, Chu, 2015. "Estimating the Marginal Abatement Cost Curve of CO2 Emissions in China: Provincial Panel Data Analysis," Energy Economics, Elsevier, vol. 48(C), pages 217-229.
    7. Kejia Yang & Yalin Lei, 2017. "The carbon dioxide marginal abatement cost calculation of Chinese provinces based on stochastic frontier analysis," 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. 85(1), pages 505-521, January.
    8. Liu, Guangtian & Wang, Bing & Zhang, Ning, 2016. "A coin has two sides: Which one is driving China’s green TFP growth?," Economic Systems, Elsevier, vol. 40(3), pages 481-498.
    9. repec:gam:jeners:v:10:y:2017:i:12:p:2026-:d:121239 is not listed on IDEAS
    10. Bowen Xiao & Dongxiao Niu & Han Wu & Haichao Wang, 2017. "Marginal Abatement Cost of CO 2 in China Based on Directional Distance Function: An Industry Perspective," Sustainability, MDPI, Open Access Journal, vol. 9(1), pages 1-19, January.
    11. Lee, Chia-Yen & Zhou, Peng, 2015. "Directional shadow price estimation of CO2, SO2 and NOx in the United States coal power industry 1990–2010," Energy Economics, Elsevier, vol. 51(C), pages 493-502.
    12. repec:eee:ejores:v:266:y:2018:i:3:p:1013-1024 is not listed on IDEAS
    13. Wang, Jian & Lv, Kangjuan & Bian, Yiwen & Cheng, Yu, 2017. "Energy efficiency and marginal carbon dioxide emission abatement cost in urban China," Energy Policy, Elsevier, vol. 105(C), pages 246-255.
    14. Li, Tianxiang & Baležentis, Tomas & Makutėnienė, Daiva & Streimikiene, Dalia & Kriščiukaitienė, Irena, 2016. "Energy-related CO2 emission in European Union agriculture: Driving forces and possibilities for reduction," Applied Energy, Elsevier, vol. 180(C), pages 682-694.
    15. Silva, Felipe & Fulginiti, Lilyan E. & Perrin, Richard K., 2016. "Did technical change in agricultural production decrease the emission of pollutants on the Amazon Forest during 1990-2009?," 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas 230092, Southern Agricultural Economics Association.
    16. Ke Wang & Linan Che & Chunbo Ma & Yi-Ming Wei, 2017. "The Shadow Price of CO2 Emissions in China's Iron and Steel Industry," CEEP-BIT Working Papers 105, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    17. He, Qi & Jiang, Xujia & Gouldson, Andy & Sudmant, Andrew & Guan, Dabo & Colenbrander, Sarah & Xue, Tao & Zheng, Bo & Zhang, Qiang, 2016. "Climate change mitigation in Chinese megacities: A measures-based analysis of opportunities in the residential sector," Applied Energy, Elsevier, vol. 184(C), pages 769-778.
    18. Tang, Kai & Yang, Lin & Zhang, Jianwu, 2016. "Estimating the regional total factor efficiency and pollutants’ marginal abatement costs in China: A parametric approach," Applied Energy, Elsevier, vol. 184(C), pages 230-240.

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    Keywords

    Abatement cost; CO2 emissions; Shadow price; Distance function;

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