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The nonlinear impact of renewable energy on CO2 emissions: empirical evidence across regions in China

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  • Peng Li
  • Yaofu Ouyang
  • Lina Zhang

Abstract

This paper studies the nonlinear impact of renewable energy on CO2 emissions with a panel of 30 Chinese provinces over the period 1990–2016. The Pooled Mean Group (PMG) estimator is applied for estimation, allowing for both long-run effects and short-run heterogeneity across provinces. The results reveal an inverted U-shaped relationship between renewable energy and CO2 emissions.

Suggested Citation

  • Peng Li & Yaofu Ouyang & Lina Zhang, 2020. "The nonlinear impact of renewable energy on CO2 emissions: empirical evidence across regions in China," Applied Economics Letters, Taylor & Francis Journals, vol. 27(14), pages 1150-1155, July.
    • Handle: RePEc:taf:apeclt:v:27:y:2020:i:14:p:1150-1155
    DOI: 10.1080/13504851.2019.1673878
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    Cited by:

    1. Pata, Ugur Korkut & Isik, Cem, 2021. "Determinants of the load capacity factor in China: A novel dynamic ARDL approach for ecological footprint accounting," Resources Policy, Elsevier, vol. 74(C).
    2. Sultan Salem & Noman Arshed & Ahsan Anwar & Mubasher Iqbal & Nyla Sattar, 2021. "Renewable Energy Consumption and Carbon Emissions—Testing Nonlinearity for Highly Carbon Emitting Countries," Sustainability, MDPI, vol. 13(21), pages 1-17, October.
    3. Zhen Zeng & Xianzhong Mu, 2024. "Can the Development of Renewable Energy Improve Total-Factor Carbon Emissions Efficiency? Evidence from 30 Provinces in China," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 14(6), pages 1-16.

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