Our commentary titled “Abandon the idea of an ‘optimal economic path’ for climate policy” came out on July 2nd, 2023 in WIRES Climate Change
I, along with colleagues at World Resources Institute and Koomey Analytics, just had a commentary published in WIRES Climate Change. It’s titled “Abandon the idea of an ‘optimal economic path’ for climate policy”.
Many economic modelers think that if given enough time, money, graduate students, and coffee they can estimate an “optimal economic path” for climate mitigation that extends far into the future. They further argue that this path is the correct or best way to guide climate policy design.
The most prominent example is that of Nobel prize winning professor William Nordhaus, the father of cost-benefit or benefit-cost analysis for climate [1]. In his 2018 Nobel acceptance speech, Nordhaus [2] said:
[I]n the view of most economists, balancing of costs and benefits is the most satisfactory way to develop climate policy.
[O]ne of the most amazing results of Integrated Assessment Models (IAMs) is the ability to calculate the optimal carbon price…This concept represents the economic cost caused by an additional ton of carbon dioxide emissions (or more succinctly carbon) or its equivalent…In an optimized climate policy (abstracting away from various distortions), the social cost of carbon will equal the carbon price or the carbon tax.
Nordhaus argues that IAMs can estimate carbon prices that optimize global consumption, emissions, and climate change, balancing mitigation or abatement costs against benefits of reducing emissions (like risk reduction and avoided climate damages). Similar analyses, focused on damage costs, are used to assess appropriate social costs of carbon for regulatory purposes [3].
This way of framing the problem can be summarized in the following graph, which depicts benefit and cost curves in stylized fashion. It characterizes the place where the two curves cross as the “optimal” level of GHG reductions, where the marginal cost of reducing emissions is equal to the marginal benefits from reducing them. The point also suggests the optimal carbon price, as in the Nordhaus quotation above. In this view, reducing emissions beyond that point would imply that we are paying too much for emissions reductions because the costs for incremental emissions reductions would exceed the benefits.
This commentary focuses attention on underlying ideas about “optimal paths” that are in our view not widely enough understood and are often unstated, namely that
(1) there IS a single unique optimal path to solving the climate problem,
(2) this path exists independent of human choices, and
(3) society can discover this path in advance through better data collection, analysis, and logical thinking.
These beliefs are at odds with our current understanding of the forces driving the development of real economic and technological systems, which are dominated by increasing returns to scale, network externalities, learning curves, and other non-linear effects. Real non-linear systems are subject to “sensitive dependence on initial conditions”, which leads to chaotic and often unpredictable behavior of such systems in the face of imperfect measurements, randomness, and human choices [4, 5, 6, 7, 8]. Models of non-linear systems are also strongly affected by uncertainties in model structure, complicating things still further [9].
The full reference for the commentary is
Koomey, Jonathan, Zachary Schmidt, Karl Hausker, and Dan Lashof. 2023. "Abandon the idea of an “optimal economic path” for climate policy." Invited Commentary for WIREs Climate Change. vol. e850, July 2. [http://doi.org/10.1002/wcc.850]
To download a pre-publication version of the article, click here.
1. Nordhaus, William D. 1992. "An Optimal Transition Path for Controlling Greenhouse Gases." Science. vol. 258, no. 5086. pp. 1315. [http://science.sciencemag.org/content/258/5086/1315.abstract]
2. Nordhaus, William D. 2018. Nobel Prize Lecture, December 8, 2018 [https://www.nobelprize.org/prizes/economic-sciences/2018/nordhaus/lecture/]
3. US EPA. 2022. Report on the Social Cost of Greenhouse Gases: Estimates Incorporating Recent Scientific Advances. Washington, DC: U.S. Environmental Protection Agency. September. [https://www.epa.gov/environmental-economics/scghg]
4. Lorenz, Edward. 1995. The essence of chaos. Seattle, WA: The University of Washington Press. [https://uwapress.uw.edu/book/9780295975146/the-essence-of-chaos/]
5. Gleick, James. 1988. Chaos: Making a new science. New York, NY: Penguin Books. [https://amzn.to/3Jxc2yv]
6. DeCanio, Stephen J. 2013. Limits of Economic and Social Knowledge. New York, NY: Palgrave Macmillan. [https://stephendecanio.com/2017/06/30/limits-of-economic-and-social-knowledge/]
7. Pluchino, Alessandro, Alessio Emanuele Biondo, and Andrea Rapisarda. 2018. "Talent versus luck: The role of randomness in success and failure." Advances in Complex Systems. vol. 21, no. 03n04. pp. 1850014. [https://www.worldscientific.com/doi/abs/10.1142/S0219525918500145]
8. Dizikes, Peter. 2011. "When the butterfly effect took flight." In MIT Technology Review. February 22. pp. [https://www.technologyreview.com/2011/02/22/196987/when-the-butterfly-effect-took-flight]
9. Thompson, Erica. 2022. Escape from model land: How mathematical models can lead us astray and what we can do about it. New York, NY: Basic Books. [https://amzn.to/3HDxH5t]
