Challenges and Countermeasures Faced by the Local Governments under the New Environmental Law in China

DOI

10.2991/amms-17.2017.100How to use a DOI?

Keywords

daily penalty; government regulation; evolutionary game; evolutionary stable strategy

Abstract

The New Environmental Protection Laws in China have taken effect on Jan 1, 2015, which is an important milestone in the history of environmental protection legislation. Also, the game relationship between governments' supervision and firms' pollution treatment is re-examine by the academic circles. In accordance with the latest environmental policy, this paper studies the interaction between governments and firms under the setting of daily penalty by applying evolutionary game theory. Specifically, with the daily penalty amount being viewed as an critical parameter, evolutionarily stable strategies under different situations of amount of penalty are investigated. The results show that daily penalty is the key factor influencing evolutionary stable strategies, daily penalty would be helpful for the system to evolve to the direction in which firms controlling pollution consciously and the governments reducing the proportion of regulation quickly and effectively. Thus, the society can cultivate the right orientation under which the cost of governments' regulation can be reduced and advocating law-abiding culture can be formed.

Copyright

© 2017, 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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TY  - CONF
AU  - Yichao Yuan
AU  - Kuiran Shi
AU  - Zhaowen Kang
PY  - 2017/11
DA  - 2017/11
TI  - Challenges and Countermeasures Faced by the Local Governments under the New Environmental Law in China
BT  - Proceedings of the 2017 International Conference on Applied Mathematics, Modeling and Simulation (AMMS 2017)
PB  - Atlantis Press
SP  - 464
EP  - 466
SN  - 1951-6851
UR  - https://doi.org/10.2991/amms-17.2017.100
DO  - 10.2991/amms-17.2017.100
ID  - Yuan2017/11
ER  -