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Establishing National Carbon Emission Prices for China

Author

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  • Chia-Lin Chang

    ( Department of Applied Economics Department of Finance National Chung Hsing University, Taiwan.)

  • Michael McAleer

    ( Department of Quantitative Finance National Tsing Hua University, Taiwan and Econometric Institute Erasmus School of Economics Erasmus University Rotterdam, The Netherlands and Department of Quantitative Economics Complutense University of Madrid, Spain And Institute of Advanced Sciences Yokohama National University, Japan.)

  • Te-Ke Mai

    (Department of Economics National Tsing Hua University, Taiwan.)

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 & Michael McAleer & Te-Ke Mai, 2018. "Establishing National Carbon Emission Prices for China," Documentos de Trabajo del ICAE 2018-10, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  • Handle: RePEc:ucm:doicae:1810
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    References listed on IDEAS

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    3. Wesseh, Presley K. & Lin, Boqiang, 2021. "Bulk storage technologies in imperfect electricity markets under time-of-use pricing: Implications for the environment and social welfare," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    4. Song, Xiang & Wang, Dingyu & Zhang, Xuantao & He, Yuan & Wang, Yong, 2022. "A comparison of the operation of China's carbon trading market and energy market and their spillover effects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    5. Rundong Luo & Yan Li & Zhicheng Wang & Mengjiao Sun, 2022. "Co-Movement between Carbon Prices and Energy Prices in Time and Frequency Domains: A Wavelet-Based Analysis for Beijing Carbon Emission Trading System," IJERPH, MDPI, vol. 19(9), pages 1-15, April.
    6. Lin, Boqiang & Wesseh, Presley K., 2020. "On the economics of carbon pricing: Insights from econometric modeling with industry-level data," Energy Economics, Elsevier, vol. 86(C).
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    9. Mai, Te-Ke & Foley, Aoife M. & McAleer, Michael & Chang, Chia-Lin, 2022. "Impact of COVID-19 on returns-volatility spillovers in national and regional carbon markets in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
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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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