Hurricane Sandy, Climate Change, and Market Signals

A question that will surely be considered over the coming weeks is whether or not Hurricane Sandy was caused, in whole or part, by climate change. A NYT article has already asked this very question.  

Climate change is defined as a change in a distribution (the climate being a distribution of weather outcomes). Even if our models were perfect, and we knew with certainty that hurricanes were x% more likely to occur this year than last year, we would not be able to say that climate change caused this hurricane to occur, or this hurricane to be stronger than it otherwise would have been. Only with a set of observations can you observe changes to a distribution. 

Compounding this, our models aren’t perfect, and climate data is very noisy. The best that we can say is that, for any given time period in the future, on the East Coast of the US, hurricanes are probably more likely occur (notice there are two qualifications). 

Our climatic models are good, but we don’t have total confidence in them, so we can only say that they are “probably” correct. Second, even if we did have total confidence in them, they don’t make ironclad predictions for any length of time – only probabilistic assertions – so we can only say that hurricanes are “more likely” pr “x% more likely” – not that N hurricanes will occur.  

This is very difficult for the average person to process, and it is very hard to make forward-looking decisions with this type of information. Fortunately, we have mechanisms that are very good at cutting through this type of very noisy, probabilistic data to provide a clear signal: markets. 

One area that will be interesting to observe following this Hurricane is the insurance market, as insurers revisit the premia they charge for wind, water, and fire insurance. If they decide that the threat of hurricanes on the highly populated East Coast is higher in a changing or different climate, than the cost to reinsurers to, in turn, insure themselves through catastrophe bonds or other insurance-linked-securities will drive primary market prices higher. Higher premia for these things will send a signal that it is better (all other things equal) to live or develop elsewhere. 

I have little doubt that markets will evolve to provide the necessary signal; in fact exotic securities are being developed to more directly trade and price this risk. The real question is: given the pace of climate change, and the lifespan of our at-risk capital stock (those in areas exposed to negative impacts of climate change), how much stranded capital will we be left with? Think: agricultural communities where the climate become unfavorable for crops, or communities exposed to high levels of hurricane risk. Did the condo developer on the Jersey Shore correctly price this risk in five years ago? Will she today? The answers to these types of questions will determine, in large part, the extent of climate change’s impact on humanity. 

Not saying this will happen, but if it does, David Brooks’ point (below) is pretty well invalidated…

Misunderstanding the issues

David Brooks writes a thoughtful article today on the Obama administration’s attempts to spur innovation in clean technology, and he recites a common fallacy in the environmental policy space. Namely, that the problem of technological substitution can be solved through market-price corrections alone. This is why he laments the subsidies granted to early-stage technology firms and pines for a carbon tax instead. 

One can bucket mitigation technologies into roughly three groups. Imagine that there is a cost curve in front of you, like the McKinsey curve, with the cost of each technology on the y-axis, and the amount of mitigation opportunity on the x-axis. Imagine that these technologies are ordered from left to right, lowest to highest cost.

There are two important horizontal lines to draw through this graph. The first is at y = 0. It’s hard to beleive, but there are mitigation technologies that actually pay for themselves, and then some. These technologies are negative cost. There a host of reasons that they don’t get deployed / implemented; let’s call these policy issues “Barriers”. The first thing to understand is that since these already are profitable, it’s not clear that a price correction will solve the underlying issue. Perhaps making them even more profitable will do the trick, but perhaps not.

Now imagine that we agree that there is a social cost of each ton of CO2-equivalent; let’s call this cost SCC (the social cost of carbon). The next important line is at y = SCC. If you implemented a cap-and-trade or carbon-tax scheme, presumably all the mitigation opportunity below this line would be implemented. Let’s call these policy issues “Incentives”. 

Finally, there are opportunities above the y = SCC line. These technologies would not be implemented even with a market price on carbon, because they are too expensive. The aim of policies targeting these technologies should be to bring the cost down to below the y = SCC line, or to “bend the curve”, so to speak. Let’s call this group “Innovation”. Now, you could argue that establishing a price on carbon would incentivize entrpreneurs to bring the cost of these technologies down, but that argument works for any price on carbon, even 0 (i.e., there is always an incentive to bring the cost of technologies below the incumbent).

Knowing that the speed of cost reduction at y = 0 has not been what we need, and not knowing what it would be at y = SCC, it makes intuitive sense to tackle the cost reduction problem directly for technologies that are at y > SCC. 

Updated simulation w/ more swing-state prices

Moved a bunch of states out of the “safe” categories and into the “swing state” categories w/ associated prices. States like Indiana, Arizona, Missouri, Michigan, and Wisconsin. (That may in fact be it.)

Doesn’t change the outcome whatsoever. So far this race seems safely in the bag for Obama, with this informal model predicting a 97% likelihood of him winning.