Review of ‘Evolutionary game analysis on industrial pollution control of the local government in China’ (Fan et al., 2021)
Oreatlile Maloka, MASUS student at UC3M and BA in Business Science, Monash University
This blog post will discuss the paper published by Wei Fan et al in 2021 and my own personal views (Fan, et al., 2021). It is imperative to explore and explain the basic concepts of evolutionary game theory to glean the most important conclusion of Wei Fan´s study.
Evolutionary Game Theory
Evolutionary game theory proposes a re-interpretation of the two most fundamental principles of game theory which are strategies and pay-offs (Sigmund & Nowak, 1999). Strategies in evolutionary game theory are not selected by players but rather are inherited by the players, pay-offs are reconceptualized as Darwinian fitness or reproductive success (Sigmund & Nowak, 1999). The ‘players’ are all competing for a greater share of descendants and/or survival in the environment.
The Nash equilibrium in conventional game theory is defined as a game equilibrium that occurs once it is no longer rational for either player to change their strategy as there is no increase to their payoffs (Xin, et al., 2021). Evolutionary game theory however has an extended concept of the Nash Equilibrium called the Evolutionary Stable Strategy (ESS) (Sigmund & Nowak, 1999). The ESS is a situation that occurs in evolutionary game theory in which in a game of a large sum of competitors an external mutant/another strategy cannot enter the population dynamic. This can be applied to models involving government regulation and businesses, the goals of governments and businesses are varied and these two ‘players’ strategies are determined based on the success of the previous iteration of regulations or business. Hence, evolutionary game theory is an extraordinarily useful tool to model the decisions firms and governments make in environmental regulation.
Wei Fan and their colleagues describe the process of local Chinese governments implementing environmental regulations and the survival of firms within the country as a long, complex, and dynamic series of games (Fan, et al., 2021).
Article summary
The paper introduces the issues that Chinese state faces in implementing environmental regulations due to the Chinese state having a decentralized system for local governments (Fan, et al., 2021, p. 1). Local governments are urged to pursue economic growth blindly due to the competitive nature of local governance as they are ranked on their economic performance (Fan, et al., 2021, p. 1). These incentives lead to local governments neglecting the supervision and management of local polluting and emitting firms. There are several reasons why environmental regulation is extraordinarily difficult to implement across China. Firstly, local governments are ranked due to several competitive mechanisms that incentives economic growth over environmental regulation (Fan, et al., 2021, pp. 1-2). Secondly, polluting firms are some of the largest local taxpayers and contribute to economic development (Fan, et al., 2021, pp. 1-2). The study suggests that there may be some level of collusion between firms and local governments (Fan, et al., 2021, pp. 1-2). The third reason is that since the environment has non-exclusiveness of consumption and is a public good, and lastly, local governments face overwhelming costs in implementing environmental regulation as there is no economic profit in the short run (Fan, et al., 2021, pp. 1-2). Due to the high costs of environmental regulation, if there is no investment then it becomes challenging to sustain environmental governance and regulation (Fan, et al., 2021, pp. 1-2). The study suggests that environmental regulation and governance is not solely a technological issue but also a long-term dynamic game with all parties having varied and conflicting interests (Fan, et al., 2021, pp. 1-2).
“The study suggests that environmental regulation and governance is not solely a technological issue but also a long-term dynamic game with all parties having varied and conflicting interests.”
The application of evolutionary game theory to local governance issues in China is quite intriguing, the conclusions reached after running the model are as follows. Firstly, local governments and industrial polluting plants enterprises will work co-operatively on either seeking economic profits whilst forsaking environmental expenditure/regulation or local governments and firms will work together to invest in environmental protections by giving up economic profits. Further analysis of the stability of the model using a Jacobian matrix to test the stability of the dynamic equilibrium points led to the conclusion that industrial polluting enterprises will choose clean production methods in the end once local governments choose environmental fiscal expenditure (Fan, et al., 2021, p. 4).
Local governments prefer environmental expenditure and industrial polluting enterprises prefer clean production; the two agents will converge to the stable strategy of environmental expenditure will lead to clean production. The simulation demonstrates a positive feedback loop in the management of the environment. The policies local government can implement include, limiting subsidies or gradually loosen market intervention to ensure firms continue clean production practice.
The results of the environmental game theory model and the numerical simulation result in the following conclusions. Firstly, a set of rational incentives is needed to ensure local governments and polluting firms collaborate on environmental issues. Local governments are encouraged to control governance costs and improve governance efficiency. Secondly, the relationship between local governments and industrial polluting firms is positively collaborating or negatively collaborating is determined by the initial decision taken by municipalities. Lastly, local governments’ environmental expenditure will have a positive effect on the ESS, and the economic expenditure strategy of local governments will have a negative effect on it. (Fan, et al., 2021, pp. 8-10).
Personal opinions
The paper and the use of ecological game theory did surprise me as my limited knowledge of the concept was that it can be used to measure or predict potential changes in animal populations. However, I appreciated the detailed explanation of how an ecological game theory model can be applied to governance and environmental regulation. The detailed methodology the paper includes is also surprisingly concise and coherent, and the results from the methodology seem to be reliable and reproducible. In future, I would like to see similar studies conducted in South Africa as well. Governance on the local level is run similarly to the Chinese system, as such, I am curious to see what policy recommendations can be made from running an Environmental Game Theory model.
The results of the paper are explained in terms of actual policy-making decisions that municipalities face daily. The ecological game theory model which seemed quite complex prior to my reading of the paper now seems to be an effective policy-making tool.
I also enjoyed the second section of the paper which suggests a multitude of policy alternatives as mentioned above, the paper offers an empirical and qualitative approach on how to solve the issue of environmental regulation. Overall, this paper is exceptional, however the mathematical proof may be a bit daunting for readers who do not have a mathematical background such as myself.
References
Fan, W., Wang, S., Gu, X., Zhou, Z., Zhaou, Y., & Huo, W. (2021, November 15). Evolutionary game analysis on industrial pollution control of local government in China. Journal of Environmental Management, 298.
Sigmund, K., & Nowak, M. (1999). Evolutionary game theory. Current Biology, 9(14), R503-R505.
Xin, J., Dan, M., Zhang, N., Yu, W., Fu, X., & Das, S. (2021). Game Theory Basics. In J. Xin, M. Dan, N. Zhang, W. Yu, X. Fu, S. Das, & K. K. Sajal K. Das (Ed.), Handbook on Securing Cyber-Physical Critical Infrastructure (pp. 34-36). Burlington, United States of America : Morgan Kaufmann.