If you have been seeking solid information on how various carbon mitigation policies compare, I recommend this policy study from the AEI Brookings Joint Center for Regulatory Studies, a combined effort of the free market think tank American Enterprise Institute and the liberal Brookings Institution. I believe it deserves at least a temporary spot in your archive of climate change policy resources. So far as I can tell the authors do not advocate an agenda, either alarmist or skeptic.
Rather they have built on the product of the US Climate Change Science Program (CCSP) to develop a sensitivity analysis of the economic costs of emissions stabilization. I.e., what are the costs of the “insurance premium” for optimal to very sub-optimal risk management strategies.
For a quick summary of the annual U.S. GDP costs over time, click on the graphic at above left [Figure 9. U.S. GDP Loss from Reference in Policy Scenarios] — then print the full size panel of charts for study.
Depicted in Figure 9, at left, are the results of eight runs of the MERGE model for the eight scenarios as shown in the schematic at immediate left [Figure 2. Scenario Design for Analysis]. These are arrayed in three layers by Target/Policy/Technology:
TARGET: Two emission reduction targets for the year 2050 are compared:
“3.4 RF”: radiative forcing levels of 3.4 watts/m2 [corresponding to stabilizing CO2 concentrations at approximately 450 ppmv]
“4.7 RF”: radiative forcing levels of 4.7 watts/m2 [corresponding to stabilizing CO2 concentrations at approximately 550 ppmv].
POLICY: Three policies are compared:
“1st best”, or “China YES, Kyoto NO” – Emission reductions are allocated across space and time in an economically efficient manner. That is, all countries participate from 2010; the emissions constraint is the 2050 Target. I think of this policy as China = YES or “IN” Kyoto = NO or “OUT”, using “China” as shorthand for all the developing world and “Kyoto” as a shorthand for the annual Kyoto-style 2% reduction contstraint.
“2nd best”, or “China = NO , Kyoto = NO” — same as 3rd best but Annex B is NOT bound by the compounding annual 2% reduction constraint. For presentation clarity, this case is not shown in chart Figure 9.;
“3rd best”, or “China = NO, Kyoto = YES” — non-Annex B countries do not participate until post-2050, Annex B countries subject to a “Kyoto style” annual target reduction of 2% AND are subject to the 2050 Target.
TECHNOLOGY: Two scenarios are compared
“Optimistic”: Nuclear power AND Carbon Capture and Sequestration are allowed.
“Pessimistic”: Nuclear power AND Carbon Capture and Sequestration are NOT allowed.
UPDATE 28 June: Figure 11 at left summarizes the relative influence of various factors on total global GDP cost. I’m not sure if the caption “through 2200″ is correct, as throughout the paper the timescale goes to 2100. There is no other reference to 2200 in the document. The difference could impact the magnitude of short-term scenario differences — though the 5% discount rate really diminishes the contribution of 2100 through 2200 costs.
In the author’s discussion below, note these highlighted points:
• If it turns out the 3.4 Target is required, the costs are on the order of four times higher. We won’t know if the 3.4 Target is needed until we accumulate more years of data and research. If we delay getting on track for the 4.7 Target, then the cost of achieving the 3.4 Target may become completely infeasible.
• If the 4.7 Target is sufficient, then total global cost isn’t sensitive to whether developing countries must “pay their share” from time zero. The increase in the total global cost is entirely due to the 2% per year Kyoto-style constraint through 2050. There is vitally important information hidden behind this time & country integration and discounting calculation. Obviously in the “2nd or 3rd Best” or “China = NO” cases, the developing countries pay all the reduction costs for the first 50 years. My question for the authors is “how does this work?”.
• Conversely, if the 3.4 Target is required the difference in total cost is entirely whether China = YES or China = NO.
Finally, in our last figure (Figure 11), we examine GDP losses at a global level, discounted back to the present. The figure provides a summary of our analysis. Notice that the largest determinant of losses is something over which we may have little control—Mother Nature. That is, if we assume that ultimately the RF target will be based on a better understanding of the science underlying global warming and that this understanding will determine what constitutes “dangerous anthropogenic interference with the climate system,†then the resolution of uncertainty surrounding such issues as climate sensitivity, the thermohaline circulation, sea level rise, etc. will ultimately determine the appropriate target.
The second largest determinant of costs and the one over which we do have control is technology. If a transformation of the global energy system turns out to be required, trillions of dollars are at stake. At the present time, there are insufficient supplies of low cost substitutes for high carbon emitting technologies. Currently we are limited primarily to fuel switching and price induced conservation, both of which will come with a sizeable price tag. To develop the technological wherewithal to do the heavy lifting in the future is essential for managing the costs of the transition. This will require both a sustained commitment on the part of the public sector upstream in the R&D chain and incentives for the private sector to bring the necessary technologies to the marketplace.
Finally, there is the issue of the design of climate policy. The cost comparison reveals that in the current formulation, policy choice plays a smaller role than either the stabilization target or the state of technology. Moreover, note that the entire gain from policy flexibility is obtained without developing country participation in the 2nd best case with the 4.7 watts/m2 target, while including these countries accounts for the entire gain in the 3.4 watts/m2 stabilization scenario. Even though it ranks third in this analysis, the difference between economically efficient and inefficient policy is still on the order of trillions of dollars. But the main contribution of climate policy may be as an enabler of new technologies. By recognizing the acute shortage of low-cost substitutes, the long lead times required for development and deployment, and the market failures that impede technological progress, climate policy can play an important role in reducing the costs of the transition.
The authors’ final comments summarize the policy challenge nicely in the highlighted emphasis:
As climate negotiators continue the struggle to agree upon a set of goals for climate policy, the debate appears to be becoming even more polarized. This may seem surprising given the growing consensus among the scientific community that something should be done and done soon. Upon reflection, however, the widening gulf should be expected. The calls for action are being accompanied by demands for increasingly tighter constraints on greenhouse gas emissions and hence, both sides of the debate see the stakes increasing.
Of course, the “stakes†tend to be perceived differently depending upon one’s perspective. The activists are concerned that we are imposing an unacceptable risk on the environment. To them, the very ecosystem, and its ability to provide the services to which we are accustomed, is at stake. The climate skeptics, even those who acknowledge the need for some action, fear that the types of actions that are being suggested will impose an unacceptable and unnecessary burden on our economy and in doing so will divert attention from more pressing social needs.
The real question is not whether to take action but how much action to take. Unfortunately, given the deep and pervasive uncertainties that both sides acknowledge, the problem does not lend itself to a simple solution. The issue is one of risk management, that is, how much insurance we should buy to reduce the risks associated with climate change. Here the answer will hinge upon one’s perception of the stakes, the odds, and how risk averse we choose to be as a society. Our analysis focuses on one part of the risk management calculus: the costs of the insurance premium.
The CCSP papers which inform this study can be found here. There is a lot of good work here. More commentary to follow — for now I just wanted to expose this study for comment.
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