Energy technological innovation and carbon emissions mitigation: evidence from China. Issue 3 (10th June 2021)

• Record Type: Journal Article
• Authors: Cheng, Shuping; Meng, Lingjie; Xing, Lu
• Is Part Of: Kybernetes. Volume 51:Issue 3(2022)
• Page Start: 982
• Page End: 1008
• Publication Date: 2021-06-10
• Subjects: Energy technological innovation -- Carbon emissions -- STIRPAT -- Quantile regression; Cybernetics -- Periodicals; Systems engineering -- Periodicals; 003.505
• DOI: 10.1108/K-09-2020-0550
• Languages: English
• ISSNs: 0368-492X

Abstract

Abstract : Purpose: The purpose of this paper is to examine the effects of energy technological innovation on carbon emissions in China from 2001 to 2016. Design/methodology/approach: Conditional mean (CM) methods are first applied to implement our investigation. Then, considering the tremendous heterogeneity in China, quantile regression is further employed to comprehensively investigate the potential heterogeneous effect between energy technological innovation and carbon emission intensity. Findings: The results suggest that renewable energy technological innovation has a significantly positive effect on carbon emission intensity in lower quantile areas and a negative effect in higher quantile areas. Contrarily, fossil energy technological innovation exerts a negative correlation with carbon emission intensity in lower quantile areas and a positive effect on carbon emission intensity in higher quantiles areas. Originality/value: Considering that energy consumption is the main source of CO2 emissions, it is of great importance to study the impact of energy technological innovation on carbon emissions. However, the previous studies mainly focus on the impact of integrated technological innovation on carbon emissions, ignoring the impact of energy technological innovation on carbon emissions mitigation. To fill this gap, we construct an extended STIRPAT model to examine the effects of renewable energy technological innovation and fossil energy technological innovation on carbon emissions in this paper. The results can provide a reference for the government to formulate carbon mitigation policies.