People need to move! Climate change affects us, today.

Right after Sandy passed through the East Coast, I wrote:

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.

Well, it seems like that is happening.

Paying for Climate Change

For anyone who, like me, is interested in how our global economy will adapt to climate change, there is a must read article in the new york times that addresses many of the questions I raised in a previous post.

First, risk premia have been rising. 

Because of the quickening pace of disaster, those who want insurance or are required to buy it now face much higher costs in risky areas. Premiums for homeowners’ insurance (which covers wind damage) doubled in Florida between 2002 and 2007, tripling in some areas after the 2004-5 hurricane seasons, if insurance was available at all.

Many insurers have raised their premiums because of increased risk estimates, higher cost of reinsurance (insurers transfer part of their risk to international reinsurers), the requirement by regulators and rating agencies that insurers hold more capital in order to reduce the likelihood of insolvency, and the need to provide shareholders with an attractive return.

I speculated that this might be the case, but it appears that rising prices are already occurring. This is the most objective indication that we have that climate change is already underway.

Insurance market prices are effectively representations of distributions. The price of car insurance is a representation of the likelihood that you’ll get into an accident. The distribution for 18-25 year-olds is different than for 30-40 year-olds, and the prices are different. Since our climate is a distribution, insurance price changes for climate-dependent phenomena should be an indicator that the distribution has changed (or, in other words, that the climate has changed).

Assuming that there is a competitive market for climate-dependent insurance in Florida, the evidence cited above is unbiased evidence that climate change has occurred and is occurring. Setting a price too high will mean lost business for the company, and judging by how many people have dropped their wind coverage, this consequence has been suffered by the insurance companies.

Why is this important? In my opinion, it’s that the market is telling us that climate change is happening. Although the scientific evidence is staggering, it has never been quite enough to convince many. Market evidence is rarely cited, and I think it deserves more attention. 

A second point that the authors make is relevant to adaptation: subsidized public flood insurance (i.e., flood insurance that not only is administered publicly, but is also run at below break-even prices), and homeowners dropping other forms of climate-dependent insurance (flood, wind, etc.) is skewing incentives and is promoting increased development and the perpetuation of development in areas that are relatively more exposed to climate risks. This is a problem. The market signals of climate change should be felt and increased prices borne by those who are ultimately exposed to the risks. Why? People need the incentive to move, and as the world changes, our geography and our economy need to change along with it (and, actually, ahead of the changes if possible). 

In my last post I mentioned that climate change is defined as a change in a distribution. I thought it might help to see what that looks like. The data that you see here is observed data, not a projection or a model.

What it shows is the distribution of summer temperatures in North Americarelative to what is normal for that time of year. The horizontal units are in terms of standard deviations, instead of degrees. So a very hot day (i.e., 10 degrees greater than normal) would be plotted as +2 standard deviations (obviously I’m making up the numbers here for effect).

The gist is that climate has already changed (the probability of the shift you see being a product of random variation is vanishingly small). If you believe that humans are the cause of this shift, then you should believe it will continue to change. 

(borrowed from the great James Hansen)

source

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. 

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.