[G]iven all the uncertainties and variability in the economic results of the IAMs [integrated assessment models] … the claimed high degree of accuracy in GDP loss projections is highly implausible. After all, economists cannot usually forecast the GDP of a single country for one year into the future with such a high accuracy, never mind for the entire world for 50 years, or more.Precisely. Or as Keynes put it,
The sense in which I am using the term [uncertainty] is that in which the prospect of a European war is uncertain, or the price of copper and the rate of interest twenty years hence, or the obsolescence of a new invention, or the position of private wealth owners in the social system in 1970. About these matters there is no scientific basis on which to form any calculable probability whatever. (The General Theory, 1937)The second point is that economies are complex interdependent systems whose interconnections can’t possibly be modeled by analysts who know only the world as it is now, not the world as it will become. One disturbing factor, of course, will be climate change itself, which will likely have deep, and mostly impossible to foresee, effects on many aspects of the economy. Similarly, different technological and institutional configurations of the future economy of the planet can’t be captured by models that consider them separately, or only in light of their market connections.
Now I’d like to add two further observations to the mix. The first is that the long run economic costs of climate change mitigation, the ones that will show up over the course of 50 or 100 years, are really irrelevant. The case for taking action doesn’t depend on them, and future people will have to figure out how to cope with them when the time comes. It’s the short term costs, the ones that will make themselves known during the first years of serious policy implementation, that matter. They matter for policy, because if we can anticipate them we can take actions to minimize their impact. Crucially, they matter for political economy, since the opposition to action on climate change is ultimately about short run costs: who bears them and how big they are expected to be.
The second observation is that the biggest nonlinearity is hiding right under our nose: the potential for writing off a portion of the capital stock. All existing models assume that capital goods are employed until they fully depreciate, with reduced productivity of the stock related smoothly to more rapid depreciation: if a change in relative prices means a unit of capital is a bit less productive, its lifespan will be a bit shorter.
This assumption rules out a fundamental nonlinearity: each unit of capital has a tipping point, a critical balance of revenues and operating costs that separates utilizing it from abandoning it. Consider a simple example: an airplane. A large passenger airplane is a significant piece of capital investment. Its profitability depends on the cost of providing air travel and the willingness of travelers to pay for it. If the cost of fossil fuel rises due to a carbon tax or cap, airline companies have to raise prices and cope with the resulting loss of demand. This can mean somewhat fewer flights and more empty seats. But there is a level of price increases at which the plane is simply taken out of service: it’s no longer profitable to operate it. Indeed, an entire company may liquidate, going from a substantial capitalization to scrap. There is almost certainly some fuel price that triggers this discontinuity, although we don’t necessarily know what it is in advance. The same point likely holds for many investments in transportation, shipping, real estate and fuel-intensive manufacturing.
If this view is correct, economists should put research into the short run effects of fossil fuel prices on the capital stock into high gear. The cumulative effect of such writeoffs will be macroeconomic disruption, which we can offset through policy if we can see it coming. Above all, identifying the investments most at risk from climate policy will tell us more about the political barriers we face than a thousand surveys about public attitudes toward science.
For more on cost, see this post from The Road from Carbonville.