Proceedings of the 2021 5th International Seminar on Education, Management and Social Sciences (ISEMSS 2021)

Industrial Structure and Pollution in China, 2004-2017

Authors
Huashen Cao, Rijin Li
Corresponding Author
Huashen Cao
Available Online 9 August 2021.
DOI
10.2991/assehr.k.210806.049How to use a DOI?
Keywords
Industrial structure, Pollution, Dynamic panel regression
Abstract

Industrial development has significant impact on environment in China, thus causing social and economic concerns. In order to understand and examine the impact of industrial structure on pollution, this paper uses panel data of 259 cities in China over 2004-2017 and dynamic panel regression to investigate the relationship between industrial structure and pollution. The result shows that industrial structure optimization decreases pollution. The regression result indicates that 1% industrial structure change can reduce 0.46%, 0.25% and 0.08% pollution of sulfur dioxide, industrial dust and waste water.

Copyright
© 2021, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2021 5th International Seminar on Education, Management and Social Sciences (ISEMSS 2021)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
9 August 2021
ISBN
978-94-6239-414-8
ISSN
2352-5398
DOI
10.2991/assehr.k.210806.049How to use a DOI?
Copyright
© 2021, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Huashen Cao
AU  - Rijin Li
PY  - 2021
DA  - 2021/08/09
TI  - Industrial Structure and Pollution in China, 2004-2017
BT  - Proceedings of the 2021 5th International Seminar on Education, Management and Social Sciences (ISEMSS 2021)
PB  - Atlantis Press
SP  - 257
EP  - 260
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.210806.049
DO  - 10.2991/assehr.k.210806.049
ID  - Cao2021
ER  -