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.

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?

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.

The third and most ambitious problem that might be worth examining is modeling the long-term outcomes of the Paris Agreement, given its stated objective of limiting climate increase to 1.5 degrees Celsius and the different policy levers involved. This would be an addition to work done to model the Paris framework and previously the Copenhagen framework. Instead of modeling negotiations, though, we’d be exploring long-range decisions and payoffs for a range of set policies. Granted, tracking over 100 signatories is impossible work, but we can take a look at the United States, China, the European Union, India, and the Russian Federation. Modeling this problem may prove too ambitious for the scope of an article here, but I’m hoping that by discussing it we can understand some of the complicated considerations of climate policies.

Thanks to readers from last week for providing some vital context and understanding. Last week, I discussed climate change as a prisoner’s dilemma, but depending on how much it costs to fix and how much averting climate change may help, that may not be the case. I will include some graphics to illustrate in the next Note, but basically a prisoner’s dilemma tends towards a scenario where both players defect (or choose the option to not cooperate) because the risk of choosing to cooperate while the opponent exploits you (in the prisoner’s dilemma, the opponent snitching and sending you to prison), is just too great. So although cooperating is the best option, both players tend towards not cooperating. This is how I envisioned climate-change policy working, but through email, reader Chris Lambert challenged my idea with the idea of a game of chicken––or a game that tends towards “swerving,” or one party embracing climate policy efforts with the other party encouraging it, but not helping:

Just to elaborate a little: based on preliminary outcomes, actors given reasonable ranges of uncertainty for the number and nature of the costs and benefits of abatement have been more likely to conclude that the sum costs of defection (fighting for the other nation to do more abatement) exceed the benefits of the target global abatement level. This causes a lot of "swerving," rather than defection by both parties. One or the other state decides to unilaterally commit to more abatement than their "fair share" under a cooperative outcome. As a climate game this might not make much sense, but it does predict some of the behavior.

Lambert and I discussed the difference in marginal benefit of abatement between China and the United States. That concept is a bit dense for this space, but essentially, there is a “sweet spot” between the value of abatement and the value of keeping pollution where it is, and it’s different for different states. Thus, one country may be keen on exploiting another state into doing the work of abatement—which has global impacts—another may be especially predisposed to doing that work. There’s more on the idea of marginal benefit of abatement here.

That’s all for now. Check back later on this week for some basic matrices and payoff analyses, and please let me know if you have any questions, comments, input, or any idea for how to tackle the games we’ve come up with. As always, feel free to email me.