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Spillover effect among independent carbon markets: evidence from China’s carbon markets

Author

Listed:
  • Yaxue Yan

    (Zhongnan University of Economics and Law)

  • Weijuan Liang

    (Xiamen University)

  • Banban Wang

    (Huazhong University of Science and Technology)

  • Xiaoling Zhang

    (City University of Hong Kong)

Abstract

Carbon pricing is one of the key policy tools in the green recovery of the post-COVID-19 era. As linkages among ETSs worldwide are future trend, the carbon price spillover effects among markets are needed to be explored. This study examines the spillover effects and dynamic linkages of carbon prices using the example of China’s pilot carbon markets during 2015–2019, which are seemingly independent carbon markets. A structural vector error correction model and an improved directed acyclic graph approach are applied. The main results are as follows. First, the linkages among the five pilots demonstrate features of “two small-world networks.” Specifically, these are the Guangdong and Hubei network and the Beijing, Shenzhen and Shanghai network. Second, Shenzhen, Beijing and Hubei ranked as the top three pilots in terms of external spillover effect, accounting for 36.25%, 29.76%, and 25.59%, respectively. Second, Guangdong pilot has increasing influence on the Hubei, Shenzhen and Beijing pilots. Third, trading activities are positive contributors to the spillover, while the allowance illiquidity ratio and volatility are negative factors. The findings imply that to retain an expectable abatement costs in achieving the climate goals in green recovery, carbon prices in other potentially related markets should be considered by the policy maker in addition to its own policy design.

Suggested Citation

  • Yaxue Yan & Weijuan Liang & Banban Wang & Xiaoling Zhang, 2023. "Spillover effect among independent carbon markets: evidence from China’s carbon markets," Economic Change and Restructuring, Springer, vol. 56(5), pages 3065-3093, October.
  • Handle: RePEc:kap:ecopln:v:56:y:2023:i:5:d:10.1007_s10644-022-09431-2
    DOI: 10.1007/s10644-022-09431-2
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    More about this item

    Keywords

    China’s carbon market; Spillover effect; Improved directed acyclic graph approach; Structural vector error correction model;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • Q59 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Other

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