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Impacts on CO 2 Emission Allowance Prices in China: A Quantile Regression Analysis of the Shanghai Emission Trading Scheme

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  • Jie Zhang

    (School of Business, Hohai University, West Focheng Road 8, Nanjing 211100, China
    Collaborative Innovation Center for Coastal Development and Preservation, Xikang Road 1, Nanjing 210098, China)

  • Lu Zhang

    (School of Business, Hohai University, West Focheng Road 8, Nanjing 211100, China)

Abstract

A pilot regional carbon emission trading scheme (ETS) has been implemented in China for more than two years. An investigation into the impacts of different factors on carbon dioxide (CO 2 ) emission allowance prices provides guidance for price-making in 2017 when the nation-wide ETS of China will be established. This paper adopts a quantile regression approach to estimate the impacts of different factors in Shanghai emission trading scheme (SH-ETS), namely, economic growth, energy prices and temperature. The empirical analysis shows that: (i) the economic growth in Shanghai leads to a drop in the carbon allowance prices; (ii) the oil price has a slightly positive effect on the allowance prices regardless of the ordinary least squares (OLS) or quantile regression method; (iii) a long-run negative relationship exists between the coal price and the Shanghai emission allowances (SHEA) prices, but a positive interaction under different quantiles, especially the 25%–50% quantiles; (iv) temperature has a significantly positive effect at the 20%–30% quantiles and a conspicuous negative impact at the right tail of the allowances prices.

Suggested Citation

  • 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, vol. 8(11), pages 1-12, November.
    • Handle: RePEc:gam:jsusta:v:8:y:2016:i:11:p:1195-:d:83200
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    4. Shah, Muhammad Ibrahim & Foglia, Matteo & Shahzad, Umer & Fareed, Zeeshan, 2022. "Green innovation, resource price and carbon emissions during the COVID-19 times: New findings from wavelet local multiple correlation analysis," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    5. Lin, Boqiang & Jia, Zhijie, 2019. "Impacts of carbon price level in carbon emission trading market," Applied Energy, Elsevier, vol. 239(C), pages 157-170.
    6. Chang, Kai & Ye, Zhifang & Wang, Weihong, 2019. "Volatility spillover effect and dynamic correlation between regional emissions allowances and fossil energy markets: New evidence from China’s emissions trading scheme pilots," Energy, Elsevier, vol. 185(C), pages 1314-1324.
    7. Jingjing Xu & Lei Wang, 2017. "A Feedback Control Method for Addressing the Production Scheduling Problem by Considering Energy Consumption and Makespan," Sustainability, MDPI, vol. 9(7), pages 1-14, July.
    8. Wenjun Chu & Shanglei Chai & Xi Chen & Mo Du, 2020. "Does the Impact of Carbon Price Determinants Change with the Different Quantiles of Carbon Prices? Evidence from China ETS Pilots," Sustainability, MDPI, vol. 12(14), pages 1-19, July.
    9. Xiaojian Su & Chao Deng, 2019. "The heterogeneous effects of exchange rate and stock market on CO2 emission allowance price in China: A panel quantile regression approach," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-11, August.
    10. Chun Jiang & Yi-Fan Wu & Xiao-Lin Li & Xin Li, 2020. "Time-frequency Connectedness between Coal Market Prices, New Energy Stock Prices and CO 2 Emissions Trading Prices in China," Sustainability, MDPI, vol. 12(7), pages 1-17, April.
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    12. Zheng, Yan & Zhou, Min & Wen, Fenghua, 2021. "Asymmetric effects of oil shocks on carbon allowance price: Evidence from China," Energy Economics, Elsevier, vol. 97(C).

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