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The Impact of Green Technology Innovation on Carbon Emissions in the Context of Carbon Neutrality in China: Evidence from Spatial Spillover and Nonlinear Effect Analysis

Zeng, Shihong, Li, Gen, Wu, Shaomin, Dong, Zhanfeng (2022) The Impact of Green Technology Innovation on Carbon Emissions in the Context of Carbon Neutrality in China: Evidence from Spatial Spillover and Nonlinear Effect Analysis. International Journal of Environmental Research and Public Health, 19 (2). pp. 1-25. ISSN 1660-4601. (doi:10.3390/ijerph19020730) (KAR id:92629)

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Official URL
https://doi.org/10.3390/ijerph19020730

Abstract

The Paris agreement is a unified arrangement for the global response to climate change and entered into force on 4 November 2016. Its long-term goal is to hold the global average temperature rise well below 2 °C. China is committed to achieving carbon neutrality by 2060 through various measures, one of which is green technology innovation (GTI). This paper aims to analyze the levels of GTI in 30 provinces in mainland China between 2001 and 2019. It uses the spatial econometric models and panel threshold models along with the slack based measure (SBM) and Global Malmquist-Luenberger (GML) index to analyze the spatial spillover and nonlinear effects of GTI on regional carbon emissions. The results show that GTI achieves growth every year, but the innovation efficiency was low. China’s total carbon dioxide emissions were increasing at a marginal rate, but the carbon emission intensity was declining year by year. Carbon emissions were spatially correlated and show significant positive agglomeration characteristics. The spatial spillover of GTI plays an important role in reducing carbon dioxide emissions. In the underdeveloped regions in China, this emission reduction effect was even more significant.

Item Type: Article
DOI/Identification number: 10.3390/ijerph19020730
Uncontrolled keywords: carbon emissions; green technology innovation; regional heterogeneity; spatial spillover effect
Subjects: H Social Sciences > HA Statistics > HA33 Management Science
Divisions: Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
Depositing User: Shaomin Wu
Date Deposited: 10 Jan 2022 12:13 UTC
Last Modified: 11 Jan 2022 10:05 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/92629 (The current URI for this page, for reference purposes)
Wu, Shaomin: https://orcid.org/0000-0001-9786-3213
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