Scientific Models

Editor’s Note: S&S is collaborating with the Harvard Environmental Economics Program (HEEP) to bring academic research findings to a broader audience. Writers at S&S are producing short summaries of discussion papers from HEEP and the Harvard Project on Climate Agreements (HPCA), streamlined for policymakers. As these summaries are published, they will be adapted and discussed here.

Emitting carbon imposes a negative cost on the world in the form of global warming. This cost is the social cost of carbon (SCC). Defined as the marginal value to society of the damages caused by emitting an additional ton of carbon, the SCC has historically been estimated using Integrated Assessment Models (IAMs). Because of the scientific uncertainty about climate change there is significant uncertainty in the results generated by IAMs and whether these should be used to formulate the SCC. A new study examines the use of IAMs by the U.S. government in formulating their estimate of the SCC. It suggests that IAMs are the best available method of generating the SCC.

IAMs combine models of the economy, atmosphere, ocean, and other social or physical systems to examine how changes in geophysical variables impact economic variables. IAMs are often used to examine how increases in the global average surface temperature, resulting from increased CO2 concentrations in the atmosphere, impact global per capita consumption and GDP. By translating changes in CO2 emissions into changes in consumption, IAMs allow economists to estimate a SCC associated with those emissions.

This study begins with the premise that policy makers must have a numerical, non-zero value for the SCC and this value must recognize the considerable uncertainty surrounding current and future costs of climate change. This premise rests on the recognition that U.S. courts have ruled that, while uncertain, the SCC is knowable and is known to be non-zero.

Because an SCC must be knowable and non-zero, the study suggests that any method to generate the SCC should be evaluated along five criteria: (i) it is based on the best available science, (ii) it is transparent and readily understandable, (iii) it is subject to expert review and has regularly scheduled updates, (iv) it provides guidance to researchers on areas where greater understanding is needed, and (v) it is not viewed as “arbitrary and capricious” or politically motivated.

Given this set of criteria, the study asks if IAMs should therefore be used to generate an SCC. That question is split into two sub-questions: first, what are the shortcomings of IAMs and can these be solved in a reasonable time? Second, is there a better option available now?

Key Findings

  1. IAMs’ primary shortcoming is sensitivity to four specific parameters. These are: equilibrium climate sensitivity, damage functions, treatment of catastrophic events, and the discount rate. Equilibrium climate sensitivity is the change in global temperatures that results from increasing CO2. The damage function relates the change in surface temperature to changes in per capita consumption. Treatment of catastrophic events refers to the way that IAMs incorporate events such as the melting of ice sheets that will have large impacts but are difficult to conceptualize. Finally, the discount rate is the rate at which damages that occur in the future are converted into a dollar value today.
  2. Uncertainty in each of these four parameters is unlikely to be resolved in the near future: Researchers are making slow progress in each of these four categories and are unlikely to remove all uncertainty in the time frame relevant for climate policy. In the case of climate sensitivity, 35 years of research has failed to substantially reduce the uncertainty in sensitivity estimates. Different discount rates, on the other hand, reflect differences in philosophy that cannot be resolved with more research.
  3. Persistent uncertainty in these four parameters is an argument in favor of IAMs: Uncertainty about these four parameters is a feature of the current scientific understanding of climate change, not only a feature of IAMs. As a result, removing IAMs from the SCC does not remove the uncertainty. As the science improves, the IAMs will give less uncertain projections. Further, these models are explicit about levels of uncertainty and areas where uncertainty exists.
  4. None of the other options for calculating SCC satisfy all 5 criteria: Each of the five alternative methods of calculating the SCC fail to meet at least one of the five criteria laid out above. Most fail to be free from political influence or would be considered “arbitrary and capricious” by the courts.
  5. There is room for improvement in the U.S. process for setting the SCC: The current process used by the Federal government to set the SCC does well by most of the five criteria above. However, it needs to have a regular update schedule, be subject to expert review, and have greater detachment from the office of the President.

Knowing the SCC is necessary for crafting climate change policy. As a result, it is necessary that policy makers be provided with a numeric, non-zero value for the SCC. Despite the uncertainty inherent in IAMs, these remain the best available option for calculating this value. IAMs incorporate the best available science to produce a number as well as explicit measures of uncertainty about that number.

Image courtesy Wikimedia Commons.

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