In Table 1.3, go to the third row, which has “L ≻ G ≻ H” as player 1’s preference. The only outcomes are L and G:
| 1 \ 2 | H ≻ L ≻ G | H ≻ G ≻ L | L ≻ G ≻ H | L ≻ H ≻ G | G ≻ L ≻ H | G ≻ H ≻ L |
| L ≻ G ≻ H | L | G | L | L | G | G |
Which one it is depends entirely on whether player 2 prefers L ≻ G or G ≻ L, regardless of how they rank H.
The big question is why the player preferring L to H might rank L ≻ G ≻ H. If this player ranks L ≻ H strictly because of costs of cutting CO2 emissions, L ≻ G ≻ H will be a very real possibility. G, after all, is cheap. We are immediately back to the moratorium, assuming the world doesn’t want G to win it all. Ban it, and hope to guide climate policy in a productive direction – toward H, that is.
If that player, however, ranks L ≻ H because they do not believe climate change is a problem worth addressing with aggressive action, L ≻ G ≻ H will be less likely. Why risk G if climate change isn’t all that bad to begin with?
Now we are in the third scenario: L ≻ H ≻ G. Zoom into the fourth row of Table 1.3 to see where this might lead:
| 1 \ 2 | H ≻ L ≻ G | H ≻ G ≻ L | L ≻ G ≻ H | L ≻ H ≻ G | G ≻ L ≻ H | G ≻ H ≻ L |
| L ≻ H ≻ G | L | H | L | L | G | G |
The most frequent outcomes are still L and G. If the other player ranks G on top, G wins. Not if, but when. What’s striking, then, is when G does not win. That seemingly goes counter to the “not if, but when” logic.
Let’s simplify the table a bit more to see this logic. We can drop the two columns where G is ranked first, and compare the first four columns for when L ≻ H ≻ G (row four of Table 1.3) to the ones when L ≻ G ≻ H (row three):
| 1 \ 2 | H ≻ L ≻ G | H ≻ G ≻ L | L ≻ G ≻ H | L ≻ H ≻ G |
| L ≻ G ≻ H | L | G | L | L |
| L ≻ H ≻ G | L | H | L | L |
If both players rank L on top, L wins. G doesn’t add much to this calculus. Let’s drop two more columns, to compare players ranking L first to those ranking H first. Now we’re left with exactly four cases:
| 1 \ 2 | H ≻ L ≻ G | H ≻ G ≻ L |
| L ≻ G ≻ H | L | G |
| L ≻ H ≻ G | L | H |
The first column has two cases leading to L as the outcome. That’s when the player ranking H ≻ L also ranks G last. The game essentially collapses to the prisoner’s dilemma of yore. G doesn’t influence the decision. L wins.
Almost there. We’re left with two cases.
With G wedged between L and H for both players, G wins. In some sense, the logic here is simply that the two players can’t agree on how much CO2 to cut, so they would rather settle on G than give the other player what they want in terms of CO2 cuts. That’s a disheartening solution. It’s also the one that calls for strong solar geoengineering governance. But it’s not the only solution.
If G is ranked below H for those preferring L to H, suddenly, H emerges as the winner. That’s true, even though one player still ranks L ≻ H. Here the “availability of risky [solar] geoengineering can make an ambitious climate mitigation agreement more likely.” That, in fact, is the title of the paper I wrote with then-Ph.D. student Adrien Fabre, arguing just that.36 The title of that paper is worth restating: it’s the mere availability of solar geoengineering that leads to this outcome. Another key word: “risky.” In fact, the riskier is solar geoengineering, the more likely is this outcome.
That mere availability helps break the prisoner’s dilemma, the free-rider problem. It isn’t a guarantee. But the mere possibility is worth