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Nonlinear dependence between China’s carbon market and stock market: new evidence from quantile coherency and causality-in-quantiles

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Abstract

This study examines the nonlinear dependence between carbon market and stock market in China under normal and extreme market conditions by employing two novel nonlinear approaches, namely, quantile coherency and causality-in-quantiles methods. Given our results on the overall and sector level of stock market, we find that there is a negative dependence between the two markets under bearish and normal market states in the short- and medium-term respectively, while the dependence becomes positive under bearish and bullish market states in the long-term. Furthermore, we also prove that the Granger causality from carbon market to stock market exists. However, no evident impacts from stock market to carbon market have been found. Additionally, at sector stock market, we discover heterogeneity across market conditions. And emission-intensive sector stock indices are more affected by carbon prices.

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Data Availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Notes

  1. This data is available at https://www.edf.org/climate/report-progress-chinas-carbon-markets.

  2. The daily data is used because it is suitable for the quantile coherency and causality-in-quantiles approaches that we employ (Tiwari et al., 2019; Jena et al., 2019).

  3. Following Chang and Zhang (2018), this study uses the prices of previous trading days to fill in the missing values in carbon market. In addition, we also try to solve this problem by deleting missing values and find that this does not change our main conclusion. The space is limited, and relevant results are available on request.

  4. The sample stocks of CSI300 cover about 70% of the market value of the Shanghai and Shenzhen markets, which can reflect the overall trend of China’s A-share market. In addition, we also use the Shanghai Composite Index and Shenzhen Component Index to conduct robustness tests and find that the results are not significantly different. The relevant results are not provided due to the finite space, but they are available if requested.

  5. The results are not provided due to the finite space, but they are available if requested.

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Funding

This work is supported by the National Natural Science Foundation of PRC (71971098, 72001090).

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Authors and Affiliations

  1. Institute of Finance and School of Economics, Jinan University, Guangzhou, 510632, China

    Yonghong Jiang, Lu Liu & Jinqi Mu

  2. Economics Department, Wisconsin University, Eau Claire, WI, 54701, USA

    Yonghong Jiang

Authors
  1. Yonghong Jiang
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  2. Lu Liu
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  3. Jinqi Mu
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Contributions

Jiang Yonghong: data curation, formal analysis, and investigation. Liu Lu: data curation, formal analysis, investigation, methodology, project administration, writing, review, and editing, software. Mu Jinqi: conceptualization, formal analysis, writing, review, and editing.

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Correspondence to Jinqi Mu.

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The authors declare no competing interests.

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Jiang, Y., Liu, L. & Mu, J. Nonlinear dependence between China’s carbon market and stock market: new evidence from quantile coherency and causality-in-quantiles. Environ Sci Pollut Res 29, 46064–46076 (2022). https://doi.org/10.1007/s11356-022-19179-x

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  • DOI: https://doi.org/10.1007/s11356-022-19179-x

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