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Stereoscopic optimization of industrial structure of the equipment manufacturing industry from the perspective of collaborative emissions reduction: Evidence from China

Equipment manufacturing industry is one of the major industries of the Chinese economy. Previous researches have revealed that the industry has dilemmas of unreasonable industrial structure and high pollution. Using the data of 30 provinces in 2006-2015 in China, this study calculated a comprehensiv...

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Detalles Bibliográficos
Autores principales: Qiao, Bin, Jiang, Shunhang, Zhang, Jiefei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7192503/
https://www.ncbi.nlm.nih.gov/pubmed/32353047
http://dx.doi.org/10.1371/journal.pone.0232293
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author Qiao, Bin
Jiang, Shunhang
Zhang, Jiefei
author_facet Qiao, Bin
Jiang, Shunhang
Zhang, Jiefei
author_sort Qiao, Bin
collection PubMed
description Equipment manufacturing industry is one of the major industries of the Chinese economy. Previous researches have revealed that the industry has dilemmas of unreasonable industrial structure and high pollution. Using the data of 30 provinces in 2006-2015 in China, this study calculated a comprehensive pollution indicator when estimating the possible pollution reduction brought by the optimization of industrial structure and then evaluated the reasonable level of capital allocation of provinces and industries by using the methods of nonlinear programming and stochastic frontier method. Under the target of collaborative emission reduction, the results show that the optimized output of China’s equipment manufacturing industry could be increased by 5.42%, the energy intensity could be reduced by about 10.4%, and the comprehensive emission intensity could be reduced by about 7.47%. Due to the industry heterogeneity and regional heterogeneity, industrial capacity should be transferred between industries and regions. Since the capital investment in the equipment manufacturing industry is significantly mismatched between industries and regions, the capital allocation of provincial industries in China needs to be adjusted properly. This study provides theoretically and practically reference for collaborative pollution reduction, industry restructure, spatial layout and capital investment, which contributes to achieving the stereoscopic optimization of equipment manufacturing industry.
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spelling pubmed-71925032020-05-11 Stereoscopic optimization of industrial structure of the equipment manufacturing industry from the perspective of collaborative emissions reduction: Evidence from China Qiao, Bin Jiang, Shunhang Zhang, Jiefei PLoS One Research Article Equipment manufacturing industry is one of the major industries of the Chinese economy. Previous researches have revealed that the industry has dilemmas of unreasonable industrial structure and high pollution. Using the data of 30 provinces in 2006-2015 in China, this study calculated a comprehensive pollution indicator when estimating the possible pollution reduction brought by the optimization of industrial structure and then evaluated the reasonable level of capital allocation of provinces and industries by using the methods of nonlinear programming and stochastic frontier method. Under the target of collaborative emission reduction, the results show that the optimized output of China’s equipment manufacturing industry could be increased by 5.42%, the energy intensity could be reduced by about 10.4%, and the comprehensive emission intensity could be reduced by about 7.47%. Due to the industry heterogeneity and regional heterogeneity, industrial capacity should be transferred between industries and regions. Since the capital investment in the equipment manufacturing industry is significantly mismatched between industries and regions, the capital allocation of provincial industries in China needs to be adjusted properly. This study provides theoretically and practically reference for collaborative pollution reduction, industry restructure, spatial layout and capital investment, which contributes to achieving the stereoscopic optimization of equipment manufacturing industry. Public Library of Science 2020-04-30 /pmc/articles/PMC7192503/ /pubmed/32353047 http://dx.doi.org/10.1371/journal.pone.0232293 Text en © 2020 Qiao 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
Qiao, Bin
Jiang, Shunhang
Zhang, Jiefei
Stereoscopic optimization of industrial structure of the equipment manufacturing industry from the perspective of collaborative emissions reduction: Evidence from China
title Stereoscopic optimization of industrial structure of the equipment manufacturing industry from the perspective of collaborative emissions reduction: Evidence from China
title_full Stereoscopic optimization of industrial structure of the equipment manufacturing industry from the perspective of collaborative emissions reduction: Evidence from China
title_fullStr Stereoscopic optimization of industrial structure of the equipment manufacturing industry from the perspective of collaborative emissions reduction: Evidence from China
title_full_unstemmed Stereoscopic optimization of industrial structure of the equipment manufacturing industry from the perspective of collaborative emissions reduction: Evidence from China
title_short Stereoscopic optimization of industrial structure of the equipment manufacturing industry from the perspective of collaborative emissions reduction: Evidence from China
title_sort stereoscopic optimization of industrial structure of the equipment manufacturing industry from the perspective of collaborative emissions reduction: evidence from china
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7192503/
https://www.ncbi.nlm.nih.gov/pubmed/32353047
http://dx.doi.org/10.1371/journal.pone.0232293
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