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Effects of innovation efficiency of high-tech industries on CO(2) emissions in China: A spatial Durbin econometric analysis

As a responsible country, China should take on heavy responsibility of energy conservation and emission reduction, and it is an inevitable choice for China to develop high-tech industries and improve the innovation efficiency of high-tech industries in order to alleviate the current environmental pr...

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Detalles Bibliográficos
Autores principales: Lou, Lingyan, Wang, Hongli, Zhong, Shen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9089925/
https://www.ncbi.nlm.nih.gov/pubmed/35536785
http://dx.doi.org/10.1371/journal.pone.0264017
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author Lou, Lingyan
Wang, Hongli
Zhong, Shen
author_facet Lou, Lingyan
Wang, Hongli
Zhong, Shen
author_sort Lou, Lingyan
collection PubMed
description As a responsible country, China should take on heavy responsibility of energy conservation and emission reduction, and it is an inevitable choice for China to develop high-tech industries and improve the innovation efficiency of high-tech industries in order to alleviate the current environmental pressure. Therefore, this paper takes the panel data of 30 provinces in China from 2005 to 2016 as the research sample, on the basis of using DEA Global-Malmquist index to measure the innovation efficiency of high-tech industries, it constructs three spatial weight matrices, by including spatial geography, spatial economic geography nesting and innovation, and then it uses Spatial Durbin Model to empirically analyze the effect of innovation efficiency of high-tech industry on CO(2) emissions in China from spatial perspective. The results indicate: firstly, in China, CO(2) emissions gradually increase from 2006 to 2012, however, some provinces have declined after 2012. And CO(2) emissions present a descending trend from eastern coastal area to central and western region. Secondly, affected by “warning effect”, CO(2) emissions show a significant negative spatial spillover effect. Thirdly, the overall level of innovation efficiency of high-tech industries in China is not high, and its impact on CO(2) emissions is not a simple linear relationship, but shows an “inverted N–shaped” curvilinear relation, and its decomposition index EC and TC also have similar characteristics. Obviously, the research in this paper provides a necessary theoretical support for China and some emerging developing countries to rational formulating and effective implementing the energy conservation and emission reduction policies.
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spelling pubmed-90899252022-05-11 Effects of innovation efficiency of high-tech industries on CO(2) emissions in China: A spatial Durbin econometric analysis Lou, Lingyan Wang, Hongli Zhong, Shen PLoS One Research Article As a responsible country, China should take on heavy responsibility of energy conservation and emission reduction, and it is an inevitable choice for China to develop high-tech industries and improve the innovation efficiency of high-tech industries in order to alleviate the current environmental pressure. Therefore, this paper takes the panel data of 30 provinces in China from 2005 to 2016 as the research sample, on the basis of using DEA Global-Malmquist index to measure the innovation efficiency of high-tech industries, it constructs three spatial weight matrices, by including spatial geography, spatial economic geography nesting and innovation, and then it uses Spatial Durbin Model to empirically analyze the effect of innovation efficiency of high-tech industry on CO(2) emissions in China from spatial perspective. The results indicate: firstly, in China, CO(2) emissions gradually increase from 2006 to 2012, however, some provinces have declined after 2012. And CO(2) emissions present a descending trend from eastern coastal area to central and western region. Secondly, affected by “warning effect”, CO(2) emissions show a significant negative spatial spillover effect. Thirdly, the overall level of innovation efficiency of high-tech industries in China is not high, and its impact on CO(2) emissions is not a simple linear relationship, but shows an “inverted N–shaped” curvilinear relation, and its decomposition index EC and TC also have similar characteristics. Obviously, the research in this paper provides a necessary theoretical support for China and some emerging developing countries to rational formulating and effective implementing the energy conservation and emission reduction policies. Public Library of Science 2022-05-10 /pmc/articles/PMC9089925/ /pubmed/35536785 http://dx.doi.org/10.1371/journal.pone.0264017 Text en © 2022 Lou et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://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
Lou, Lingyan
Wang, Hongli
Zhong, Shen
Effects of innovation efficiency of high-tech industries on CO(2) emissions in China: A spatial Durbin econometric analysis
title Effects of innovation efficiency of high-tech industries on CO(2) emissions in China: A spatial Durbin econometric analysis
title_full Effects of innovation efficiency of high-tech industries on CO(2) emissions in China: A spatial Durbin econometric analysis
title_fullStr Effects of innovation efficiency of high-tech industries on CO(2) emissions in China: A spatial Durbin econometric analysis
title_full_unstemmed Effects of innovation efficiency of high-tech industries on CO(2) emissions in China: A spatial Durbin econometric analysis
title_short Effects of innovation efficiency of high-tech industries on CO(2) emissions in China: A spatial Durbin econometric analysis
title_sort effects of innovation efficiency of high-tech industries on co(2) emissions in china: a spatial durbin econometric analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9089925/
https://www.ncbi.nlm.nih.gov/pubmed/35536785
http://dx.doi.org/10.1371/journal.pone.0264017
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