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

The impact of renewable energy and innovation on carbon emission: An empirical analysis for OECD countries
The impact of renewable energy and innovation on carbon emission: An empirical analysis for OECD countries
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.
1876-6102
3506-3512
Cheng, Cheng
9d3214f3-3076-40bd-8d11-d0b9571cec48
Ren, Xiaohang
970abdf4-ff20-4244-9952-f9ee910736ee
Wang, Zhen
af8604e4-250c-4c42-93bf-37d791470816
Cheng, Cheng
9d3214f3-3076-40bd-8d11-d0b9571cec48
Ren, Xiaohang
970abdf4-ff20-4244-9952-f9ee910736ee
Wang, Zhen
af8604e4-250c-4c42-93bf-37d791470816

Cheng, Cheng, Ren, Xiaohang and Wang, Zhen (2019) The impact of renewable energy and innovation on carbon emission: An empirical analysis for OECD countries. Energy Procedia, 158, 3506-3512. (doi:10.1016/j.egypro.2019.01.919).

Record type: Article

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.

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Published date: February 2019

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Local EPrints ID: 429246
URI: https://eprints.soton.ac.uk/id/eprint/429246
ISSN: 1876-6102
PURE UUID: ca7daea3-be9c-4e91-a2c5-8540430dd82a

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Date deposited: 25 Mar 2019 17:30
Last modified: 19 Jul 2019 16:38

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Author: Cheng Cheng
Author: Xiaohang Ren
Author: Zhen Wang

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