Economics and climate change, again

Andy Revkin recently linked to this post talking about how can you make the best judgements about dealing with climate change when there is still a lot of uncertainty about the exact extent of the problem, particularly at the small regional level.

I thought it pretty much confirmed what I had been thinking recently about the dubious use of economics to try to forecast the effects many decades into the future:

The politicians and other leaders who make (or influence) such decisions do not like deep uncertainty. They do not like it, Sam I Am. They want something specific to plan for. Expert recommendations. Metrics, targets, and “deliverables.” Otherwise there’s no way to determine the most efficient use of resources, how to minimize costs and maximize benefits, which course is optimal. So they ask analysts for cost-benefit analysis (CBA).

CBA is useful in some circumstances, particularly where there are bounded time spans and known risks. But remember, there’s a difference between risk (statistically quantifiable) and uncertainty (not). It is the difference, if you will, between Rumsfeld’s “known unknowns” and his “unknown unknowns.”

As time horizons and uncertainty increase, CBA becomes less and less useful, more and more “a knob-twiddling exercise in optimizing outcomes,” as economist Martin Weitzman put it. Differences in social/political/ethical assumptions, like discount rates, start determining model outcomes. “Results from the CBA,” says the World Bank, are “extremely dependent on parameters on which there is no scientific agreement (e.g., the impact of climate change on hurricanes) or no consensus (e.g., the discount rate).” It’s still possible to construct models and get answers, but the danger becomes higher and higher of getting the wrong answer, i.e., optimizing for the wrong thing.

The answer, says David Roberts, (and he is quoting the approach that is argued in a World Bank white paper) is to go "robust":

Now, whenever I criticize cost-benefit analysis, someone will ask, Well, what’s the alternative? What else can you do but weigh costs and benefits? How else would you make decisions?

Funny you should ask! Turns out the World Bank white paper everyone’s* talking about has a great deal to say on that very subject. It describes various alternative decisionmaking procedures and gets into the weeds of some case studies. And if that doesn’t sate your nerd thirst, have no fear, the literature on climate change and uncertainty is extensive. Go nuts.

For the rest of you, though, I just want to focus on the top-line idea. It is this: Shift the focus from optimality to robustness. Rolls right off the tongue, no?

The optimal decision is the one that achieves the best cost-benefit ratio in a given set of conditions. A robust decision can be expected to hold up, and perform reasonably well, under a wide variety of possible conditions. To make the optimal decision, you must be able to quantify risks. When there is uncertainty rather than risk — “multiple possible future worlds without known relative probabilities” — one is better off with robust decisions.

The optimal decision aims for efficiency; the robust decision aims for resilience. A resilient solution may not be — probably won’t be — the one best suited for whatever circumstances do end up coming to pass. But it is, from the present-day perspective, the one most broadly suited to the widest array of possible futures.

An optimal solution is cost-effective, if you get it right (obviously). But strategies aiming for optimality are brittle. If you optimize for one thing and run into another, you risk degradation or collapse (or, like Ho Chi Minh City, just wasting a buttload of money). Robust decisions and investments often cost more in the short- to mid-term; the extra money is effectively spent as insurance against unforeseen outcomes. A robust solution retains its integrity in a wide array of circumstances.

When it comes to climate change, most economic models are premised on CBA — the search for efficiency. The World Bankers suggest an alternative, based on robustness, and yes, it involves yet another acronym: CIDA, or Climate Informed Decision Analysis, also known as “decision scaling.”

This sounds quite sensible to me.