The impact of LCTI on China's low-carbon transformation from the spatial spillover perspective

China has conducted a long-term low-carbon technology innovation (LCTI), but there was a faster increase of CO(2) emission in 2017 and 2018 than in 2016, which has lead scholars to doubt the effect of LCTI on CO(2) emission. This paper builds a spatial auto regression (SAR) model with provincial pan...

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Detalles Bibliográficos
Autores principales: Li, Wenchao, Xu, Jian, Wang, Zhengming, Yang, Jialiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7682850/
https://www.ncbi.nlm.nih.gov/pubmed/33226980
http://dx.doi.org/10.1371/journal.pone.0242425
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author Li, Wenchao
Xu, Jian
Wang, Zhengming
Yang, Jialiang
author_facet Li, Wenchao
Xu, Jian
Wang, Zhengming
Yang, Jialiang
author_sort Li, Wenchao
collection PubMed
description China has conducted a long-term low-carbon technology innovation (LCTI), but there was a faster increase of CO(2) emission in 2017 and 2018 than in 2016, which has lead scholars to doubt the effect of LCTI on CO(2) emission. This paper builds a spatial auto regression (SAR) model with provincial panel data from 2011 to 2017 to calculate the spatial spillover effect of China's LCTI on regional CO(2) emission. The results show that regional LCTI can reduce the local CO(2) emission, but will increase the CO(2) emission of adjacent regions due to spatial spillover effect. This produces the uncertainty of the promotion effect of LCTI on China's low-carbon transformation. Therefore, this paper suggests innovation resources should be appropriately and evenly distributed among regions to avoid their agglomeration in few regions.
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spelling pubmed-76828502020-12-02 The impact of LCTI on China's low-carbon transformation from the spatial spillover perspective Li, Wenchao Xu, Jian Wang, Zhengming Yang, Jialiang PLoS One Research Article China has conducted a long-term low-carbon technology innovation (LCTI), but there was a faster increase of CO(2) emission in 2017 and 2018 than in 2016, which has lead scholars to doubt the effect of LCTI on CO(2) emission. This paper builds a spatial auto regression (SAR) model with provincial panel data from 2011 to 2017 to calculate the spatial spillover effect of China's LCTI on regional CO(2) emission. The results show that regional LCTI can reduce the local CO(2) emission, but will increase the CO(2) emission of adjacent regions due to spatial spillover effect. This produces the uncertainty of the promotion effect of LCTI on China's low-carbon transformation. Therefore, this paper suggests innovation resources should be appropriately and evenly distributed among regions to avoid their agglomeration in few regions. Public Library of Science 2020-11-23 /pmc/articles/PMC7682850/ /pubmed/33226980 http://dx.doi.org/10.1371/journal.pone.0242425 Text en © 2020 Li et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Li, Wenchao
Xu, Jian
Wang, Zhengming
Yang, Jialiang
The impact of LCTI on China's low-carbon transformation from the spatial spillover perspective
title The impact of LCTI on China's low-carbon transformation from the spatial spillover perspective
title_full The impact of LCTI on China's low-carbon transformation from the spatial spillover perspective
title_fullStr The impact of LCTI on China's low-carbon transformation from the spatial spillover perspective
title_full_unstemmed The impact of LCTI on China's low-carbon transformation from the spatial spillover perspective
title_short The impact of LCTI on China's low-carbon transformation from the spatial spillover perspective
title_sort impact of lcti on china's low-carbon transformation from the spatial spillover perspective
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7682850/
https://www.ncbi.nlm.nih.gov/pubmed/33226980
http://dx.doi.org/10.1371/journal.pone.0242425
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