A PVAR dynamic correlation appraisal of China’s carbon emissions in conjunction with economic growth and clean energy use

Wei Li, Ni Hao and Can Lu

Renewable Energy, 2023, vol. 219, issue P1

Abstract: This study aims to explore the dynamic relationship among economic growth, clean energy, and carbon dioxide (CO2) emissions in China. The indicators of economic growth, clean energy, CO2 emissions, fixed assets investment, and research and development intensity of 30 provinces and municipalities for the period of 2005–2019 in China have been investigated by Panel Vector Autoregression model (PVAR). To further explore regional differences, three types of regions were classified by K-means cluster analysis. The results show that clean energy has a positive impact on economic growth in China; Clean energy reduces CO2 emissions in Region II while others do not; Both fixed assets investment and research and development promote clean energy development; The dynamic relationship between the 5 indicators varies across regions. Various regions in China should combine their development characteristics and location advantages, increase capital investment and research and development input in clean energy, strengthen environmental regulations, and improve the energy consumption structure.

Keywords: Clean energy use; Economic growth; Carbon emissions; Panel vector autoregression method; Dynamic correlation (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:219:y:2023:i:p1:s096014812301399x

DOI: 10.1016/j.renene.2023.119484

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