The impact of renewable energy and innovation on carbon emission: An empirical analysis for OECD countries

By Cheng Cheng, Xiaohang Ren, Zhen Wang. Energy Procedia, 2019

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Abstract This paper employs a panel quantile regression method to study the impacts of economic growth, renewable energy, and development of patents on carbon emissions. Panel quantile regression is more useful method compared to the ordinary least squared (OLS) method because both individual heterogeneity and distributional heterogeneity are considered in a panel quantile regression, which provides comprehensive information of the relationship between carbon emissions per capita and different variables. To be specific, for economic growth, its impact on carbon emissions per capita is significant and positive, but its impact decreases for fast-increase emission countries. The results do not support the Environmental Kuznet Curve hypothesis. As for renewable energy, its impacts on carbon emission show an inverted U-shaped trend at different quantile levels. As for the development of patents, its effect is non-significant and positive at different quantile levels. Based on the results, we propose some policy recommendations to control carbon emissions per capita.

Subfields: Economics and Econometrics, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/251639d9f0e66a36a29a6411615f2e5be29c7d67