Game theory gives insight into how we can reduce carbon emissions
With the People’s Climate March taking place in New York City just over a week ago, I found the content of this article overwhelmingly relevant not only to material in our course but also to current issues today. This march was the largest climate march history, drawing out an estimated 400,000 people last Sunday; with 1,574 participating organizations, 50,000 college students, and resulting in 5,200 articles written in response to the demonstration (peoplesclimate.org). While the article I discuss was initially published in October 2013, it was also recently revised in February 2014. With this said, however, its topic only becomes increasingly relevant: carbon emissions’ indisputable effect on climate change.
Originally posted to Bentham Open, a site that hosts open peer-reviewed journals, the article “Research on Behavior of Regulators and Enterprises about Carbon Emissions Based on Game Theory” (URL source: http://benthamopen.com/toautocj/articles/V006/56TOAUTOCJ.pdf) examines the behavior of government regulators and enterprises in relation to the management of environmental harm due to carbon emissions. The articles is written by two researchers based in the School of Management at Shanghai University in China. The subject they discuss has become increasingly pertinent, as the severe escalation in carbon dioxide emissions has become a clear player in the climatic change that has done great harm not only to our world environment itself but also to the world’s economy; as noted in the introduction of the article, “the development of low-carbon economy has become a matter of concern to the international community.” As the authors are from China, one of the major industrial and economic powers of the world, they note the significant positive correlation between economic growth and carbon emissions: as economy grows, carbon emissions increase. With this in mind, the relevance of the article becomes even more apparent: if we want to maintain the health and growth of our global economy concurrently with the health and growth of our environment, we must reconcile the behavioral strategies between government regulations of carbon emissions and enterprises production decisions. The study finds that the appropriate regulatory measures of governments would increase the cost of enterprises’ false declaration of respective carbon emissions and would, therefore, discourage said enterprises from doing so. In this way, those enterprises which truly have high carbon emissions would be appropriately regulated and, due to regulation, would find alternative methods of production that are in line with the goal of reducing environmentally harmful effects.
In order to logically determine the optimal strategy of government regulators in order to effectively regulate enterprises’ production carbon emissions, the authors go through a process of setting up a “signaling game model” that rivals much of the processes we used in studying game theory. While their eventual model heavily relies on complexly derived payoffs (integrating various probabilities, etc.), the foundation of their setup is rooted in game theory basics. They begin by outlining “Basic Assumptions” by defining: players (game participants) as regulators and enterprises, the aim of the players (maximize income or utility), the cost of carbon emission reduction for environment-friendly vs. environmental-pollution enterprises, the information asymmetry (which, as we learned, is crucial in understanding the nature of the game), the probability of regulators judging the company as environmental-friendly or environmental-pollution (p(b) and p(g)), the process regulators use by which they decide if they should regulate or not (prob(g|l) prob(g|h) prob(b|l) prob(b|h)), and finish these assumptions by defining the various components of their payoff (e.g. carbon taxes, etc.). Then the authors go on to define the behavior selection model of enterprise based on signal game, elaborating on the three refined Bayesian equilibriums that are included in the game: pooling equilibrium, separating equilibrium, and semi-separating equilibrium.
The authors set up three games: the income matrix of regulators and the pollution enterprises, the income matrix of regulators and the environmental-friendly enterprises, and the optimal production measures fro two categories of enterprises under the supervision of the regulator. The authors determine that when the government regulators do not monitor, regardless of which type of production enterprises belong to, the optimal strategy is more productive and more carbon emissions are observed. When government regulators do monitor then the optimal strategy of enterprises depends on cost of carbon emissions, the probability of making a false report carbon emissions, the carbon taxes, and the fines.
The authors conclude that if there exists asymmetric information in this game model about the cost of carbon emissions reduction between players (regulators and enterprises), the regulators cannot achieve optimal control. Basically, by improving the carbon emissions trading system, essentially reducing cost and carbon emission hoax gains, in order to make the “low emission” strategy the optimal production policy, then this would move enterprises to not emit as much carbon in production.
In light of the recent People’s Climate March, this line of research is becoming ever more pertinent today; the types of discoveries like those found in this paper could be key in finding a solution to the world climatic problem. As the environmental health of our world is invariably linked to our economy, this discussion on how to more effectively regulate carbon emissions in taking into account economic motives is extremely relevant and important to consider.