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Asymmetric macroeconomic determinants of CO2 emission in China and policy approaches

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Abstract

Since the nonlinear ARDL approach is introduced in advanced econometric, some old relationships are getting new empirical attention. Therefore, we examine the asymmetric macroeconomic determinants of carbon dioxide (CO2) emission in China, covering the time from 1971 to 2019 and using a nonlinear ARDL model. The study results show that GDP and industrialization have an asymmetric effect on CO2 emission in long-run in direction and magnitude, while agriculturalization has also an asymmetric effect on environmental pollution in magnitude, but not in the direction. In short, GDP and industrialization have also asymmetric response on CO2 emissions in the short term only in magnitude, but agriculturalization has an asymmetric response in magnitude and direction in short-run. Therefore, this empirical research is more applicable for policymakers in China.

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Availability of data and materials

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

Funding

This research was funded by the National Natural Science Foundation of China with Grant No. 71771129.

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Authors and Affiliations

  1. School of Business, Qingdao University, Qingdao, China

    Bilal Aslam & Jinsong Hu

  2. School of Economics, Quaid-i-Azam University, Islamabad, Pakistan

    Muhammad Tariq Majeed & Sana Ullah

  3. School of Economics, Federal Urdu University, Islamabad, Pakistan

    Zubaria Andlib

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  1. Bilal Aslam
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  2. Jinsong Hu
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  3. Muhammad Tariq Majeed
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  4. Zubaria Andlib
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  5. Sana Ullah
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Contributions

This idea was given by Bilal Aslam. Jinsong Hu, Bilal Aslam, Zubaria Andlib, and Muhammad Tariq Majeed analyzed the data and wrote the complete paper. Jinsong Hu and Sana Ullah read and approved the final version.

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Correspondence to Jinsong Hu or Zubaria Andlib.

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Aslam, B., Hu, J., Majeed, M.T. et al. Asymmetric macroeconomic determinants of CO2 emission in China and policy approaches. Environ Sci Pollut Res 28, 41923–41936 (2021). https://doi.org/10.1007/s11356-021-13743-7

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