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Establishing National Carbon Emission Prices for China

Author

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  • Chia-Lin Chang

    (National Chung Hsing University, Taiwan)

  • Te-Ke Mai

    (National Tsing Hua University, Taiwan)

  • Michael McAleer

    (Asia University, Taiwan; Erasmus University Rotterdam, The Netherlands)

Abstract

The purpose of the paper is to establish national carbon emissions prices for the People’s Republic of China, which is one of the world’s largest producers of carbon emissions. Several measures have been undertaken to address climate change in China, including the establishment of a carbon trading system. Since 2013, eight regional carbon emissions markets have been established, namely Beijing, Shanghai, Guangdong, Shenzhen, Tianjin, Chongqing, Hubei and Fujian. The Central Government announced a national carbon emissions market, with power generation as the first industry to be considered. However, as carbon emissions prices in the eight regional markets are very different, for a variety of administrative reasons, it is essential to create a procedure for establishing a national carbon emissions price. The regional markets are pioneers, and their experience will play important roles in establishing a national carbon emissions market, with national prices based on regional prices, turnovers and volumes. The paper considers two sources of regional data for China’s carbon allowances, which are based on primary and secondary data sources, and compares their relative strengths and weaknesses. The paper establishes national carbon emissions prices based on the primary and secondary regional prices, for the first time, and compares both national prices and regional prices against each other. The carbon emission prices in Hubei, Guangdong, Shenzhen and Tianjin are highly correlated with the national prices based on the primary and secondary sources. Establishing national carbon emissions prices should be very helpful for the national carbon emissions market that is under construction in China, as well as for other regions and countries worldwide.

Suggested Citation

  • Chia-Lin Chang & Te-Ke Mai & Michael McAleer, 2018. "Establishing National Carbon Emission Prices for China," Tinbergen Institute Discussion Papers 18-028/III, Tinbergen Institute.
  • Handle: RePEc:tin:wpaper:20180028
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    1. Zhang, Xing-Ping & Cheng, Xiao-Mei, 2009. "Energy consumption, carbon emissions, and economic growth in China," Ecological Economics, Elsevier, vol. 68(10), pages 2706-2712, August.
    2. Böhringer, Christoph & Lange, Andreas & Rutherford, Thomas F., 2014. "Optimal emission pricing in the presence of international spillovers: Decomposing leakage and terms-of-trade motives," Journal of Public Economics, Elsevier, vol. 110(C), pages 101-111.
    3. Chia-Lin Chang & Michael McAleer & Guangdong Zuo, 2017. "Volatility Spillovers and Causality of Carbon Emissions, Oil and Coal Spot and Futures for the EU and USA," Sustainability, MDPI, vol. 9(10), pages 1-22, October.
    4. Chang, Chia-Lin & McAleer, Michael, 2019. "The fiction of full BEKK: Pricing fossil fuels and carbon emissions," Finance Research Letters, Elsevier, vol. 28(C), pages 11-19.
    5. Umut Çetin & Michel Verschuere, 2009. "Pricing And Hedging In Carbon Emissions Markets," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 12(07), pages 949-967.
    6. Zhongxiang Zhang, 2015. "Carbon emissions trading in China: the evolution from pilots to a nationwide scheme," Climate Policy, Taylor & Francis Journals, vol. 15(sup1), pages 104-126, December.
    7. Duan, Hongbo & Mo, Jianlei & Fan, Ying & Wang, Shouyang, 2018. "Achieving China's energy and climate policy targets in 2030 under multiple uncertainties," Energy Economics, Elsevier, vol. 70(C), pages 45-60.
    8. Zhao, Xin-gang & Jiang, Gui-wu & Nie, Dan & Chen, Hao, 2016. "How to improve the market efficiency of carbon trading: A perspective of China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1229-1245.
    9. Chia-Lin Chang & Yiying Li & Michael McAleer, 2018. "Volatility Spillovers between Energy and Agricultural Markets: A Critical Appraisal of Theory and Practice," Energies, MDPI, vol. 11(6), pages 1-19, June.
    10. Cavallaro, Federico & Giaretta, Federico & Nocera, Silvio, 2018. "The potential of road pricing schemes to reduce carbon emissions," Transport Policy, Elsevier, vol. 67(C), pages 85-92.
    11. Zhang, Cheng & Wang, Qunwei & Shi, Dan & Li, Pengfei & Cai, Wanhuan, 2016. "Scenario-based potential effects of carbon trading in China: An integrated approach," Applied Energy, Elsevier, vol. 182(C), pages 177-190.
    12. Boyce, James K., 2018. "Carbon Pricing: Effectiveness and Equity," Ecological Economics, Elsevier, vol. 150(C), pages 52-61.
    13. Liu, Liwei & Chen, Chuxiang & Zhao, Yufei & Zhao, Erdong, 2015. "China׳s carbon-emissions trading: Overview, challenges and future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 254-266.
    14. Reboredo, Juan C., 2014. "Volatility spillovers between the oil market and the European Union carbon emission market," Economic Modelling, Elsevier, vol. 36(C), pages 229-234.
    15. Cetin, Umut & Verschuere, Michel, 2009. "Pricing and hedging in carbon emissions markets," LSE Research Online Documents on Economics 29321, London School of Economics and Political Science, LSE Library.
    16. Dhakal, Shobhakar, 2009. "Urban energy use and carbon emissions from cities in China and policy implications," Energy Policy, Elsevier, vol. 37(11), pages 4208-4219, November.
    17. Alex Y. Lo, 2016. "Challenges to the development of carbon markets in China," Climate Policy, Taylor & Francis Journals, vol. 16(1), pages 109-124, January.
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    More about this item

    Keywords

    Pricing Chinese carbon emissions; National pricing policy; Energy; Volatility; Energy finance; Provincial decisions;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • Q35 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Hydrocarbon Resources
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy

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