# Reporter's Notebook

Using Game Theory to Break the Climate Gridlock
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Vann Newkirk, readers, and experts tackle how to analyze climate policy and climate change using game theory. Email Vann to join the discussion.

Let the game begin! I was very excited by my colleague Andrew McGill’s work to bring game theory into the context of the election. Long story short, the weird three-sided game of chicken between GOP #NeverTrump leaders, voters, and candidates can be explained by game theory, which uses mathematical concepts to model and predict interactions between multiple decision-makers. Essentially, the game of endorsements and counter-endorsements, the dance of pledges, and the calculus of electability are all based on complex webs of predictive decisions that can actually be modeled.

I’ve long been a fan of game theory, even though I’m not an expert in it. I studied the related, but infinitely less interesting field of decision theory in graduate school, and I’ve always been interested in modeling how to solve complex global problems. Andrew’s article gave me an excuse to revive my old fascination with game theory and global catastrophe.

Welcome back, gamers! A week ago, I wrote a Note here with the goal of crowdsourcing reader and expert knowledge in order to come up with a game-theory-based understanding of climate policy that could be used to find some insights about how states and countries might implement different policies. So far, I’ve received dozens of emails and tweets from students, economists, game theorists, climate change scientists, and some field-leading experts with some great questions, ideas, and resources. I’m currently sifting through them all and working to gain a better idea of what questions might be answered and how.

I thought it might be a good time to whittle down just what we’re trying to do here based on feedback. First, just what actors and climate policies are we examining? Originally, I had the idea to just think about a kitchen sink of international actors or states. Obviously, that’s not a very good setup for any kind of modeling, so I’ve been thinking about three separate problems. The first is taking a look at West Virginia and Kentucky, two neighboring states that are among the worst in per capita greenhouse emissions. What might a regional emissions-cap agreement look like for them? What are the costs of mitigation for each state? What are the risks involved? Using simple models, what could payoffs could we predict from their decisions?

The second problem I’m considering is perhaps the classic climate-change “game” between the United States and China. Given that these countries make up 44 percent of all greenhouse gas emissions, this game provides a decent enough understanding of global climate policy and the inputs and considerations required. Here, let’s just consider a very loose hypothetical: cutting total combined emissions from fossil fuels in both countries by half over the next ten years. Would each country be responsible for only its current share, or would the United States pick up some of China’s slack? How much would the reduction cost? How could we estimate the climate gains and externalities of these decisions? What unique benefits and drawbacks might climate change mitigation have for each country? Given all these variables, we should be able to roughly model basic climate decisions between the two.

Welcome back, gamers! This installment of the project on game theory and climate change will take some time to outline basic concepts about game theory and apply them to the three “games” described in the previous Note. To recap, we’ll be considering scenarios involving a hypothetical negotiation between West Virginia and Kentucky to curb emissions, a similar negotiation between the United States and China, and finally the future actions of the major expected signatories of the Paris climate agreement.

In each scenario there are a collection of actions that each actor can take. We’ll need to simplify a lot of these actions in the early going into approving and enacting a climate policy or deciding to continue business as usual. Here, in the context of the game, it makes sense to label the two strategies coordination and defection. There are, of course, infinite other possible strategies that may only differ by a dollar amount of spending or a single ton of emissions reduced. As the project goes on, hopefully we’ll be able to model these more accurately using some fancy statistics, but for now the two strategies are to coordinate or defect. The conjunction of each of these strategies with another actor’s corresponding strategy will produce an outcome for each actor.

In all scenarios, the five main considerations are the value of environmental resources, the future costs of climate change, the degree to which emissions policies can affect those future costs, how much those policies cost, and how much each actor can actually afford to spend or lose. There are some other considerations that can act as minor variables, such as the often considerable “inertia” involved in adopting new technologies and policies, the externalities of emissions policies (i.e. reducing smog in China or water pollution in West Virginia), elections and shifting public opinion, and the changing immediacy of the costs of climate change. But in all, each of these considerations can be collapsed into two categories that revolve around a set of outputs: costs and payoffs.

Reader Max Malikov shared with me some useful examples for visualizing the climate game. The first figure shows what a short-term assessment of climate policy might look like if there was no real threat to the environment. Acting to protect the environment is costly and has a limited benefit that is far outweighed by the benefit of simply using the environmental resources at maximum efficiency. So, in the example of Kentucky and West Virginia defection would mean both states opening up as many coal plants as possible to maximize energy output and profits. Neither state has an incentive to help protect the environment, especially in a market where the two neighbors compete against each other for jobs and productivity.

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