The other day Marshall and Sol took on Bjorn Lomborg for ignoring the benefits of curbing greenhouse gas emissions. Indeed. But Bjorn, among others, is also notorious for exaggerating costs. That fact is that most serious estimates of reducing emissions are fairly low, and there is good reason to believe cost estimates are too high for the simple fact that analysts cannot measure or imagine all ways we might curb emissions. Anything analysts cannot model translates into cost exaggeration. Hawai`i is a good case in point. Since moving to Hawai`i I've started digging into energy, in large part because the situation in Hawai`i is so interesting. Here we make electricity mainly from oil, which is super expensive. We are also rich in sun and wind. Add these facts to Federal and state subsidies and it spells a remarkable energy revolution. Actually, renewables are now cost effective even without subsidies. In the video below Matthias Fripp, who I'm lucky to be working w
Matt has taken the bait and asked me a five good questions about my snarky, contrarian post on climate adaptation. Here are his questions and my answers. Question 1. This paper will be published soon by the JPE. Costinot, Arnaud, Dave Donaldson, and Cory B. Smith. Evolving comparative advantage and the impact of climate change in agricultural markets: Evidence from 1.7 million fields around the world. No. w20079. National Bureau of Economic Research, 2014. http://www10.iadb.org/intal/intalcdi/PE/2014/14183.pdf It strongly suggests that adaptation will play a key role protecting us. Which parts of their argument do you reject and why? Answer: This looks like a solid paper, much more serious than the average paper I get to review, and I have not yet studied it. I’m slow, so it would take me awhile to unpack all the details and study the data and model. Although, from a quick look, I think there are a couple points I can make right now. First, and mo
It's been a long haul, but my coauthor Wolfram Schlenker and I have finally published our article with the title of this blog post in the Proceedings of the National Academy of Sciences . We've been told that it would show up on the early-edition website this week. It hasn't shown up there yet so I guess it will come out tomorrow [Friday 8/28], probably late afternoon EST. UPDATE: You can find the article here . We set out to develop a better statistical model linking weather and U.S. crop yields for corn, soybeans and cotton, the largest three crops in the U.S. in production value. Our major new finding is that (by far) the best predictor of yield is a measure of extreme heat: how much temperatures exceed about 29C (84F) during the growing season. The threshold varies somewhat by crop--29C is the threshold for corn. Below this threshold, warmer temperatures are more beneficial for yields, but the damaging effects of temperatures much above 29C are staggeringly large.