Wednesday, June 25, 2014

Adaptation Illusions

For some reason, the topic of adaptation can sometimes turn me into a grumpy old man. Maybe it’s because I’ve sat through hours of presentations about how someone’s pet project should be funded under the name of climate adaptation. Or maybe it’s the hundreds of times people say that adaptation will just fix the climate problem, with no actual evidence to support that other than statements like “corn grows just fine in Alabama.” Or maybe it’s just that I’m really turning into a grumpy old man and I like excuses to act that way.

In any case, I was recently asked to write a piece for Global Food Security, a relatively new journal run by Ken Cassman that I’m on the editorial board for. I used it as a chance to articulate some of the reasons I am unconvinced by most studies trumpeting the benefits of adaptation. That’s not to say I don’t think adaptation can be effective, just that most of the “evidence” for it is currently quite weak. In fact, I think some adaptations could be quite effective, which is why it’s so important to not spend time on dead ends. The paper is here, and abstract below.

"Climate change adaptation in crop production: Beware of illusions"
A primary goal of studying climate change adaptation is to estimate the net impacts of climate change. Many potential changes in agricultural management and technology, including shifts in crop phenology and improved drought and heat tolerance, would help to improve crop productivity but do not necessarily represent true adaptations. Here the importance of retaining a strict definition of adaptation – as an action that reduces negative or enhances positive impacts of climate change – is discussed, as are common ways in which studies misinterpret the adaptation benefits of various changes. These “adaptation illusions” arise from a combination of faulty logic, model errors, and management assumptions that ignore the tendency for farmers to maximize profits for a given technology. More consistent treatment of adaptation is needed to better inform synthetic assessments of climate change impacts, and to more easily identify innovations in agriculture that are truly more effective in future climates than in current or past ones. Of course, some of the best innovations in agriculture in coming decades may have no adaptation benefits, and that makes them no less worthy of attention.

Tuesday, June 24, 2014

American Climate Prospectus, feeling the heat

I've had the pleasure of working with a team of brilliant people on the American Climate Prospectus: Economic Risks in the United States, which was released today. It was the independent research report commissioned by the Risky Business initiative, and which underlies that group's conclusions.  I'm excited to share and discuss with G-FEEDers the numerous ideas, questions, challenges and results that arose in the process of the analysis, since until now we haven't had a chance to discuss the work with the larger community. I will try to post on these various issues in the coming weeks, but for now I'd like to [sleep and] simply kick off the social media rodeo with my favorite graphic from the entire report (which has no economics in it!). If we've done our job right, it needs no explaining. The only hint for the non-wonks is that RCP 8.5 means "business as usual" climate change (or "A1B" if your wonk is out of date).

Source: American Climate Prospectus

I win 20 bucks if this goes viral, so please repost it.

Saturday, June 7, 2014

Regulating CO2 emissions and firm competitiveness

EPA announced this week the Clean Power Plan to reduce carbon emissions of coal fired power plants by 30% by 2030 (relative to 2005 levels).  It has created a lot of discussion with environmental groups praising it as an overdue step and some business pointing to the cost of such regulation.

One thing to note is that EPA was smart enough in giving states a lot of flexibility in meeting the 30% reduction.  In general, more flexibility should allow regulated plants to meet the goal in the most cost effective way. Max Auffhammer called this the Yoga Theorem, i.e., the "less flexible you are, the more you will suffer," which I can personally relate to (you don't want to see me stretch).

Most of the research we have talked about on this blog has estimated the effects of increasing temperatures that are caused by elevated CO2 levels (or other greenhouse gases like methane). Having spent so much time on the benefit side of greenhouse gas regulation (avoided damages), it might be interesting to look at some research on the cost side of such regulation. As any student of econ 101 remembers, in the optimum one should balance the costs of regulation against the benefits.

Making a factor of production (coal) more expensive will have two effects: first, there will be a shift away from coal, which will be especially felt in regions that rely on coal production (e.g., West Virginia).  While electricity generation has been shifting from coal to natural gas even before the regulation was implemented, the regulation will likely accelerate this transition. So there will be losers compared to the stays quo (one could also argue that coal has an unfair advantage in the status quo as it imposes a sizable unpriced externality, which makes a factor of production artificially cheap).

The best research on the cost of environmental regulation is a recent paper by Reed Walker, where he compares wages of individuals that work in industries in a county that are subject to tougher regulation under a the revised ozone standard compared to workers who work in the same county in industries that are not covered by the more stringent regulation. The combined loss in wages are sizable (5 billion in present discounted value), but order(s) of magnitude lower than the estimated benefits.  The largest cost incur to people that used to work in firms that are subject to tougher regulation and loose their jobs - once they find a new job wages tend to be lower for up to eight years.  Workers who stay at regulated firms see no drop in wages.

Second, regulating coal will make production that uses electricity (pretty much all production) more expensive as electricity prizes might rise as a result of the regulation.  How big is this second effect? We have some evidence from Europe, where the European Trading System (ETS) created a market for carbon credits.  Similar to the EPA regulation that only covers coal-fired power plants, ETS only covered a subset of firms.  This offers some nice way for researchers to compare regulated and unregulated firms.

Sebastian Petrick and Ulrich Wagner have a great new paper that uses firm-level data from firms in Germany and compares what happens to firms that are regulated under ETS by matching them to comparable firms that were not regulated.  Not surprisingly, regulated firms reduce emissions by 20% more than unregulated firms (the regulation is effective), but there seems to be no reduction in competitiveness of regulated firm, i.e., they find no reduction in employment, gross output, or exports.

In summary, my best guess is that the carbon regulation will have very little effect on overall competitiveness or employment in the US as a whole, but will be felt in some regions that heavily rely on coal.

Thursday, June 5, 2014

Adaptation with an Envelope

Economists like to emphasize how people and businesses will adapt to climate change.  On a geological scale the world is warming very fast.  But on a human scale it is warming slowly, so we can easily adjust infrastructure and management decisions to the gradually changing climate.  For example, in agriculture farmers can gradually adjust planting times, cultivars, and locations where we grow crops, and so on.

So how much does adaptation really buy us?  As it turns out, probably very little, at least in most contexts. 

Since it is economists who often emphasize this point, sometimes even intimating that otherwise negative impacts could turn positive with adaptation, perhaps we should pause for a moment to consider what basic microeconomic theory says about it.  And we have a ready-made tool for the job, called the envelope theorem (or here), that provides essential insight.

I'll try to make this intuitive, but it helps to be a little formal.  Suppose agricultural yield is:

y = f(xr)

where r indicates climate and x represents farmers' decisions.  I'm just using notation from a generic case in the second link above.

Farmers' decisions are not random.  With time and experience, we should expect farmers to optimize decisions for their climate.  Call these optimal decisions x*(r).  So, the outcomes we observe in practice are

y*  =  f(x*(r), r)

Now, to obtain a first-order approximation of the effect of climate change on yield, we need to find dy*/dr, which is just a fancy way of saying the marginal change in observed yield for a small change in climate.  Multiply this marginal change by the total change in climate (the change in r) , and we get a first-order approximation to the total impact.

If you've taken basic calculus, you learned the chain rule, which says that:

dy*/dr  =  df/dx dx/dr + df/dr

If the farmer is optimizing, however, df/dx=0.  The farmer cannot improve yield outcomes by changing decisions, because s/he's already optimizing.  So

dy*/dr = df/dr

And this gives the heart of the envelope theorem: to a first approximation, we don't need to worry about changes in behavior (dx/dr, or adaptation) to evaluate the effect of climate change on output.  The fact that behavior is already optimized means that behavioral adjustments will be second-order.

Here's an illustration of the math from lifted from the link above. The black and blue curves hold farmers's decisions fixed at different levels of x, optimized at each r.  The f*(r) ( or y*) we observe is the "upper envelope"of the all the blue and black curves with different, optimized levels of x.

Now, if  f*(r) is highly nonlinear, and we are contemplating a very large change in r, then adaptation will come into play. But even then it's not going to be a primary consideration.

I don't expect this basic insight, drilled into every economist during their first year of grad school (and even some undergraduates), will stop some economists from over-emphasizing adaptation.  But our own basic theory nevertheless indicates it is a small deal.  And it seems to me that the evidence so far bears this out just as clearly as the theory does.