Modeling the impact of energy abundance on economic growth and CO2 emissions by quantile regression: Evidence from China.

Based on China's 30 provinces penal data, from 1990 to 2017, this paper uses the quantile regression model to estimate the impact of fossil energy abundance and clean energy abundance on economic growth and carbon dioxide (CO 2) emissions. The findings show that fossil energy abundance exerts a greater impact on economic growth in the intermediate quantile provinces such as Hebei, Jilin, Liaoning, and Shandong because these provinces have larger petroleum processing and coal gas production industries. The CO 2 emissions in the upper 90th quantile provinces such as Liaoning, Shanxi, and Shandong, receive the biggest impact from fossil energy abundance because these provinces consume more coal and oil. However, the impacts of renewable energy abundance on economic growth in the 50th-75th, upper 90th, and 75th-90th quantile groups are greater, since their renewable energy industry is growing faster. The influence of renewable energy abundance on CO 2 emissions in all quantile groups is positive, meaning it does not play a prominent role in mitigating CO 2 emissions. Therefore, each quantile province should formulate specific policies to promote the growth of renewable energy and actively develop strategic emerging industries. • Fossil energy contributes more to economic growth in the middle-level quantiles. • The impact of fossil energy on emissions in the upper 90th quantiles is the strongest. • Renewable energy abundance does not play a prominent role in reducing emissions. [ABSTRACT FROM AUTHOR]