A relatively recent econometric literature examines the impact of weather/climate on a variety of outcomes of economic interest. In order to provide an estimate of a climate impact you need two things: An estimate of how a sector responds to a change in weather/climate and projections of future climate. The latter comes out of Global Climate Models with global coverage. The response functions, however, are increasingly provided by econometric studies. These studies are based on statistical models explaining variation in observed outcomes (e.g. crime rates, mortality, electricity consumption) as a function of weather, while carefully accounting for the impact of other confounding factors.
I have written on the impact of weather on electricity consumption and rice yields. EI@Haas family member Wolfram Schlenker has written extensively on the impacts of weather on agricultural yields. Michael Greenstone has some fascinating work on heat mortality in the US and India. There is a recent explosion in the literature of the weather impacts on crime, conflict and labor productivity. These studies are important as they inform us about how sensitive these sectors are to higher temperatures. There is a lively discussion about what we can and cannot learn from these models.
While I get excited about these studies, I was not fully aware of how limited their coverage is in terms of sectors and geographical areas. Enter Solomon Hsiang. As many readers of this blog know, Tom Steyer (founder of Farallon Capital), Hank Paulsson (former treasury secretary and CEO of Goldman) and Michael Bloomberg (founder of Bloomberg and former mayor of NYC) recently released their “risky business” report, which studies the projected impacts of climate change on the US economy. They hired Solomon and coauthors to quantify the impacts of climate change on the US economy using econometrically estimated response functions for different sectors. Their background report is truly illuminating (and full of frightening, yet beautiful graphs). They scoured the literature for available response functions and incorporated them in their analysis. If they did not find high quality estimates for a sector, they did not include it in their study. Below is a schematic of what was and was not included in the analysis. The blue symbols are areas that were included:
The grey symbols in the box of impacts are areas that were not included in the analysis because there aren’t any well-estimated response functions available. This is really worrisome. We are missing good estimates for some very important sectors: Water supply and demand, morbidity, extreme weather impacts, livestock, crops other than the big four etc. etc. And this is just for the United States!
Are these important issues we should be working on? Well, greetings from the state of California. If the current drought is any indication of what is to come by end of century, it would be useful to have a well estimated weather elasticity of water demand – maybe even by sector. Morbidity anyone? Does a damage only count if one drops dead? If you look at the projected impacts in this most excellent report, we see that it is high time we get to work. We have spent the vast majority of our time worrying about agriculture and written hundreds of papers estimating impacts for a very limited number of sectors, but largely ignored energy, productivity and storm damages. And more importantly, there are few to no studies for a significant number of other climate sensitive sectors.
To make that point a little bit more bluntly, look at the figure of total impacts by sector for the end of the century:
What this indicates is that we expect relatively small and well estimated impacts for agriculture (green) and crime (red) (which is what the literature has focused on) and big yet uncertain impacts for labor (yellow), energy (orange) and coastal damages (blue) (which has been largely ignore by the econometric literature so far). What is even more worrisome are the sectors that do not appear on these graphs.
On the spectrum of econometric difficulty, these studies are not that hard to do. Even I work on them. Funders and researchers should make these a priority. The required weather data are easily accessible. All we need to do is identify the relevant outcomes and collect high quality data on them. Let’s get to work. If you’d like to collaborate, drop me a line. I’m ready.