ControlsFreak
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User ID: 1422
ControlsFreak
2d ago
Have you actually examined the details of Nordhaus’ models?
Oh boy have I. I went through it extensively way back in the day, when we were at the old old old place. That experience was part of my coming to the conclusion that the entire endeavor is simply an impossible task. You mention some of the problems; there are others. I agree that his Nobel was a scientific travesty and sad state of affairs.
If you want to understand climate change and why it’s so catastrophic, you have to model and understand the complex interactive feedbacks and it’s abundantly clear that he doesn’t.
I would echo this, but with one very minor modification:
If you want to understand climate change and its interaction with economics, you have to model and understand the complex interactive feedbacks and it’s abundantly clear that he doesn’t.
You simply state that it's "catastropic". Whereas I think it's pretty much impossible to actually model the complex interactive feedbacks... especially when it comes to their intersection with political/economic systems.
But now due to human activity, the climate is changing faster than the response to it.
One of the problems with the whole sort of analysis you do in this paragraph is that everyone does timescale-separated coupled dynamical systems backwards in the case of political/economic-climate coupling. As I alluded to in my comment, the dynamics of political/economic systems are fast, much much much faster than the dynamics of climate, even with human activity. If one spends time with the theory of such coupled systems (the canonical text being Khalil's book), which I have done extensively for non-climate-related professional reasons and prior to engaging with any economic-climate models, then one understands the proper way to go about analyzing such systems. And, well, nobody does it the proper way. Why not? In my view, it's because they can't. It's impossible. Rather than the problem lying with human psychology, the problem is that the math doesn't math that way.
ControlsFreak
3d ago
Every so often, I see a number that strikes me in a particular way. More than once, the way that it strikes me has been in comparison to climate change damage estimates. Yes, yes, there are many many different estimates out there, and they're even presented in different terms, too. Some are in percentage of GDP/GWP; others are dollar figures. One of the numbers that has stuck in my brain, thanks to David Friedman back at the old old old place, comes from one of the early world leaders in trying to produce such estimates, Nobel-winning William Nordhaus. It would take epsilon more effort to find one of his old old old comments at the old old old place, so I just found an example from his substack.
Nordhaus’s final and most important point was based on his own research.
My research shows that there are indeed substantial net benefits from acting now rather than waiting fifty years. A look at Table 5-1 in my study A Question of Balance (2008) shows that the cost of waiting fifty years to begin reducing CO2 emissions is $2.3 trillion in 2005 prices. If we bring that number to today’s economy and prices, the loss from waiting is $4.1 trillion. Wars have been started over smaller sums.
What he does not mention is that his $4.1 trillion is a cost spread over the entire globe and an extended period of time. I initially assumed his calculations of cost were for the rest of the century, making his $4.1 trillion total about $48 billion a year, but in A Question of Balance he appears to be summing over the next 250 years which reduces the annual cost to $16 billion.
It's a quote from Nordhaus' 2012 NYT opinion piece, citing his 2008 book, so yeah, the estimate is quite old. There are many many other estimates out there since then, but this one stuck in my brain. I think he was trying to get it to stick in your brain. "Wars have been started over smaller sums," is meant to do that. It worked.
This morning, Tyler Cowen posted How Much Has Shale Gas Saved U.S. Consumers? It's just quoting an NBER working paper. I'll just reproduce the whole quote, so there's no need to click through:
It may seem like a distant memory now, but as of the mid-2000s, U.S. natural gas production had been flat for a decade, and the U.S. was importing liquefied natural gas (LNG), with plans to import much more. Then shale gas happened. Advances in hydraulic fracturing and horizontal drilling caused U.S. natural gas production to increase significantly, and the U.S. went from being a net importer of natural gas to being the world’s largest exporter. This paper calculates how much shale gas has saved U.S. natural gas consumers. Using price differences between the United States, Europe and Japan, we calculate that U.S. natural gas consumers have saved $3.1-$4.3 trillion between 2007 and 2025, equivalent to $164-$227 billion annually. Access to low-price U.S. natural gas has been particularly valuable during major supply shocks such as the war in Ukraine, and the benefits of shale gas have been experienced broadly across sectors and states.
It's not a direct analog, but that number, though. It's in my brain. $4.1T is right in that range of $3.1-4.3T. That's a swing in one country over less than 20 years, not 250 years. The dynamics of economic systems can move fast, much faster than climate change. But how big of a swing does that 'feel like'? Sure, life would have been more awful in a variety of ways in the counterfactual without the shale revolution. But, like, cataclysmically bad?! End of the world bad? I kind of doubt it.
I don't really like to focus too much on any particular estimate. There are higher ones; there are lower ones. I actually think the entire endeavor of estimating economic impacts of climate change is probably impossible, but we're stuck in a world where we have the various estimates we have and they matter to people. But I never underestimate how difficult the scale of numbers is to folks, so I appreciate when I occasionally see numbers of roughly similar scale in different contexts.
Allow me to clarify. I'm aware of some of the weaknesses in the models that are used purely for the physical systems, but I actually don't think they're that bad. They're actually pretty decent, AFAICT, where "pretty decent" is a sort of term of art to describe situations where you have an okay sense for the scale of your error analysis and can sort of understand when it might be a problem or not a problem.
Sigh. I really don't know that I have a good way of explaining this intuition. Maybe a story. Long ago, I paid a lot more attention to fairly straightforward aircraft control topics at conferences. One question that came up surprisingly often was, "...would you fly on an airplane that is being controlled by your controller?" There is just a qualitative sense that you develop for how bad the badness is. How the error is likely to be structured, how likely genuinely destructive failure modes are, magnitudes of expected error under various noise distributions, etc.
With that, I guess I'll just say again that I don't think the climate models are "that bad". They're not garbage. There is error, we know some of the sources of error (you mention a couple), and we have an intuitive sense for about how big it may be.
Conversely, what I have significant theoretical disputes with is specifically trying to model economic systems coupled with climate systems. We basically can't even get off the ground, theoretically speaking. The timescales are the wrong way round. When you talk about the apparent fastness of climate dynamics, they are still figuratively glacial in comparison to the dynamics of economic systems (and I sometimes tack on political systems, because it's amazing how many people try to make completely whacko claims about these, too). You did great to realize that attempts like using a static damage function and then proceeding with a simple amortization are bonkers. My point is that the underlying theoretical reason why they're bonkers is because that's just not how one does anything with timescale-separated coupled dynamical systems.
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