Does environmental pollution governance contribute to carbon emission reduction under heterogeneous green technological innovation? Empirical evidence from China’s provincial panel data

Jianzhong Xu (), Bingjun Tong (), Manman Wang () and Shi Yin ()
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Jianzhong Xu: Harbin Engineering University
Bingjun Tong: Harbin Engineering University
Manman Wang: Zhengzhou University of Light Industry
Shi Yin: Hebei Agricultural University

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2024, vol. 26, issue 12, No 74, 31727-31756

Abstract: Abstract With the rapidly developing global economy, CO2 emissions (CE) have become an important factor in global climate change. Ecological issues have received considerable attention worldwide. Environmental pollution governance (EPG) and green technological innovation (GTI) are important ways to reduce CE. However, there is relatively little empirical research on the relationship among GTI, EPG, and CE. Therefore, this study aimed to explore the role of GTI and EPG in reducing CE in China. This study used a spatial econometric model and threshold regression model to empirically analyze the relationship between EPG, different types of GTI, and CE. The empirical results showed a significant positive spatial spillover effect of CE in China under the adjacency weight matrix. EPG and different types of GTI have a significant inhibitory effect on CE; however, EPG has a stronger inhibitory effect on CE reduction than that of GTI. Inventive and improved GTI are two types of triple thresholds between EPG and CE. The impact of EPG on CE has spatial and temporal differences in the level of regional inventive/improved GTI, showing a trend in which the region gradually crosses from a low GTI level to medium and high GTI levels. These findings provide important insights for China and other developing countries to achieve development goals, implement GTI policies, and reduce CE.

Keywords: Environmental pollution governance; Green technological innovation; CO2 emissions; Spatial econometric model; Threshold regression model (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10668-024-04655-w

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