Almost exactly ten years, Nick Stern released the his famous global analysis
on the economics of climate change. At the time, I was in my first year of grad school trying to figure out what to do research on and remember fiercely debating all aspects of the study with Ram
in the way only fresh grad students can. Almost all the public discussion of the analysis revolved around whether Stern had chosen the correct discount rate
, but that philosophical question didn’t seem terribly tractable to us. We decided instead that the key question research should focus on was the nature of economic damages from climate change, since that was equally poorly known but nobody seemed to really be paying attention to it. I remember studying this page of the report for days (literally, days) and being baffled that nobody else was concerned about the fact that we knew almost no facts about the actual economic impact of climate—and that it was this core relationship that drove the entire optimal climate management enterprise:
|click to enlarge|
So we decided to follow in the footsteps of our Sensei Schlenker and to try and figure out effects of climate on different aspects of the global economy using real world data and rigorous econometrics. Together with the other G-FEEDers and a bunch of other folks from around the world, we set out to try and figure out what the climate has been doing and will do to people around the planet. (Regular readers know this.)
Friday, Tamma Carleton
and I published a paper in Science
trying to bring this last decade of work all together in one place. We have learned a lot, both methodologically
and substantively. There is still a massive amount of work to do, but it seemed like a good idea to try and consolidate and synthesize what we’ve learned at least once a decade…
Here’s one of the figures showing some of the things we’ve learned from data across different contexts, it’s kind of like a 2.0 version of the page from Stern above:
|click to enlarge|
Bringing all of this material together into one place led to a few insights. First, there are pretty clear patterns across sectors where adaptation appears to either be very successful (e.g. heat related mortality or direct losses from cyclones) or surprisingly absent (e.g. temperature losses for maize, GDP-productivity losses to heat
). In the latter case, there seem to be “adaptation gaps” that are persistent across time and locations, something that we might not expect if adaptation is costless in the long run (as many people seem to think). We can’t say exactly what’s going on that’s causing these adaptation gaps to persist, for example, it might be that all actors are behaving optimally and this is simply the best we can do with current technology and institutions, or alternatively there might be market failures (such as credit constraints) or other disincentives (like subsidized crop insurance
) that prevent individuals from adapting. Figuring out (i) whether current adaptation is efficient, or (ii) if it isn’t, what’s wrong so we can fix it, is a multi-trillion-dollar question and the area where we argue researchers should focus attention.
Eliminating adaptation gaps will have a big payoff today and in the future. To show this, we compute the total economic burden borne by societies today because they are not perfectly adapted today. Even before one accounts for climate change, our baseline climate appears to be a major factor determining human wellbeing around the world.
For example, we compute that on average the current climate
- depresses US maize yields by 48%
- increases US mortality rates 11%
- increases US energy use by 29%
- increases US sexual assault rates 6%
- increases the incidence of civil conflict 29% in Sub-Saharan Africa
- slows global economic growth rates 0.25 percentage points annually
These are all computed by estimating a counterfactual where climate conditions at each location are whatever historically observed values at that location are most ideal.
Our first reaction to some of these numbers were that they were too big. But then we reflected on the numbers more and realized maybe they are pretty reasonable. If we could grow all of US maize in greenhouses where we control the temperature, would our yields really be 48% higher? That’s not actually too crazy if you think about cases where we have insulated living organisms much more from their environment and they do a whole lot better because of it. For example, life expectancy for people has more than double in the last few centuries
as we started to protect ourselves from all the little health insults that use to plague people. For similar reasons, if you just look at pet cats in the US, indoor cats live about twice as long as more exposed outdoor cats on average (well, at least according to Petco
and our vet). Similarly, lot of little climate insults, each seemingly small, can add up to generate substantial costs—and they apparently do already.
We then compared these numbers (on the current effect of the current climate) to (i) the effects of climate change that has occurred already (a la David and Wolfram
) and (ii) projected effects of climate change.
When it comes to effects of climate change to date, these numbers are mostly small. The one exception is that warming should have already increased the integrated incidence of civil conflict since 1980 by >11%
When it comes to future climate change, that we haven’t experienced yet, the numbers are generally large and similar-ish in magnitude to the current effect of the current climate. For example, we calculate that future climate change should slow global growth by an additional 0.28 percentage points per year
, which is pretty close in magnitude to the 0.25 percentage points per year that temperatures are already slowing things down. For energy demand in the US, current temperatures area actually doing more work today (+29%) than the additional effect of future warming (+11%), whereas for war in Sub-Saharan Africa, current temperatures are doing less (+29%) than near term warming (+54%).
All these numbers are organized in a big table in the paper
, since I always love a big table. There's also a bit of history and summary of methods in there as well, for those of you who, like Marshall, don't want to bother slogging through the sister article
detailing all the methods.