There are many considerations that college and university leaders should take into account when exploring carbon pricing. This is true whether they are considering implementing an internal carbon price at their institution or advocating for a national carbon pricing policy. This section briefly outlines some of the common considerations. This is not a comprehensive list, and there are additional implications and factors to consider when designing a carbon pricing policy. 

Equity and avoiding regressive policies

Carbon pricing policies have the potential to disproportionately affect lower-income populations. This is because carbon prices are likely to raise the cost of carbon-intensive products such as electricity, heating fuel, and gasoline (Fullerton, 2011). Lower-income households spend a larger fraction of their incomes on these products, and are often less able to make the switch to low-carbon technology. While this critique of carbon pricing is common, emerging research suggests that carbon pricing policies may not have as regressive an impact as previously thought. This is because lower-income households receive a greater portion of their income from price-indexed social safety net programs; any price increase in carbon-intensive goods is thus offset by higher payments (Barron, Hafstead, & Morris, 2017; Cronin et al., 2017).

Comprehensive climate policy packages should nonetheless therefore be designed carefully to offset energy costs for lower-income populations, possibly by redistributing returns of carbon pricing back to households directly or through industry grants or dividends (as mentioned in the section on “Economic benefits and the uses & social implications of carbon revenues” above) (Metcalf,  Mathur, & Hassett, 2011). In 2019, the US Congress introduced the bipartisan Energy Innovation and Carbon Dividends Act (EICDA). This policy proposed the introduction of a carbon fee on fossil fuels, which in turn would raise national energy prices. However, the policy was designed to evenly distribute all carbon revenues directly to American households in the form of dividends – a concept known as revenue-neutral program (Price on Carbon, 2020). Higher-income households typically purchase more carbon-intensive goods and services than lower-income households. Thus, distributing carbon dividends equally among households actually makes the carbon fee progressive addresses the potentially regressive nature of the carbon fee and means that lower-income households receive more in dividends than they pay in increased energy prices (Kaufman, Larsen, Marsters, Kolus, & Mohan, 2019). In this way, the EICDA would reduce inequity while cutting GHG emissions. 

Additional considerations should be given to ensuring carbon pricing policies advance environmental justice. Polluters such as power generation facilities, which along with GHGs emit hazardous co-pollutants, are often located in economically disadvantaged neighborhoods with large minority populations. Carbon pricing policies may exacerbate existing inequities if they allow these facilities to continue emitting without considering local public health impacts. Analysis from the first few years of California’s carbon trading program shows that communities experiencing an increase in hazardous air pollution had larger proportions of minority and lower income populations (Cushing et al., 2018).   

Appropriate Carbon Price

There is no single correct carbon price; an appropriate carbon price will depend on the desired goals to be achieved in a given context. Carbon prices may vary greatly depending on the policy objectives, the scale of the policy (for example institutional internal carbon price, regional, or national carbon price) and the rationale for implementing them. In selecting a price, two values are often discussed: the social cost of carbon and the marginal abatement cost. 

Social Cost of Carbon (SCC)

The SCC is an indicator of global damage done by emitting greenhouse gases (Pearce, 2003). The SCC is equal to the estimated costs that an additional ton of carbon dioxide emission would impose on society by contributing to climate change. Quantifying this cost is challenging, and estimates vary. In particular, the SCC is sensitive to the discount rate, which represents the time value of money and how future economic costs are valued. In 2016, the US Environmental Protection Agency published an Interagency Working Group Technical Paper that estimated the 2020 SCC to be $12, $42, and $62 per MTCDE using 5%, 3%, and 2.5% discount rates, respectively. The Interagency Working Group analysis is often considered to be conservative, and other models have calculated SCCs over $200/MTCDE (Wang et al., 2019; Moore & Diaz, 2015). Smith College provides a detailed discussion of SCC calculations, and Resources for the Future offers a brief review of how the SCC is used. For example, several US states use the SCC in decision making frameworks, and the Canadian government uses the SCC as part of required cost-benefit analysis for regulatory proposals. 

Marginal Abatement Costs

Marginal abatement costs measure the cost of reducing one additional unit of carbon emissions. Marginal abatement cost curves are estimated based on available technology and can be used to evaluate options for reducing emissions. As pollution is reduced, marginal abatement costs often rise steeply in response (McKinsey & Company, 2009). Pricing carbon through the marginal abatement cost targets eliminating a certain amount of carbon by making that elimination economically favorable. Any carbon price that is greater than the marginal abatement cost provides an economic incentive to reduce emissions.  The marginal abatement cost of carbon is less than the SCC when global carbon emissions are greater than the amount that is optimal for society. Thus, the marginal abatement cost and the SCC can be thought of as bounds on what an appropriate carbon tax should be.

References

  1. Barron, A. R., Hafstead, M. A. C., & Morris, A. C. (2019). Climate and Energy Economics Discussion Paper: Policy Insights from Comparing Carbon Pricing Modeling Scenarios. https://www.brookings.edu/wp-content/uploads/2019/05/ES_20190507_Morris_CarbonPricing.pdf
  2. Cronin, J. A., Fullerton, D., & Sexton, S. (2017). Vertical and Horizontal Redistributions from a Carbon Tax and Rebate. In National Bureau of Economic Research (No. 23250). https://doi.org/10.3386/w23250
  3. Cushing, L., Blaustein-Rejto, D., Wander, M., Pastor, M., Sadd, J., Zhu, A., & Morello-Frosch, R. (2018). Carbon trading, co-pollutants, and environmental equity: Evidence from California’s cap-and-trade program (2011–2015). PLOS Medicine, 15(7), e1002604. https://doi.org/10.1371/journal.pmed.1002604
  4. Fullerton, D. (2011). Six Distributional Effects of Environmental Policy (No. 16703). http://www.nber.org/papers/w16703
  5. Kaufman, N., Larsen, J., Marsters, P., Kolus, H., & Mohan, S. (2019). An Assessment of the Energy Innovation and Carbon Dividend Act. https://www.energypolicy.columbia.edu/sites/default/files/file-uploads/EICDA_CGEP-Report.pdf
  6. McKinsey & Company (2009). Pathways to a Low-Carbon Economy. https://www.mckinsey.com/~/media/McKinsey/Business%20Functions/Sustainability/Our%20Insights/Pathways%20to%20a%20low%20carbon%20economy/Pathways%20to%20a%20low%20carbon%20economy.ashx
  7. Metcalf, G. E., Mathur, A., & Hassett, K. A. (2010). Distributional Impacts in a Comprehensive Climate Policy Package. http://www.nber.org/papers/w16101.pdf
  8. Moore, F. C., & Diaz, D. B. (2015). Temperature impacts on economic growth warrant stringent mitigation policy. Nature Climate Change, 5(2), 127–131. https://doi.org/10.1038/nclimate2481
  9. Pearce, D. (2003). The social cost of carbon and its policy implications. Oxford Review of Economic Policy, 19(3), 362–384. https://doi.org/10.1093/oxrep/19.3.362
  10. Revenue Neutral. (n.d.). Price on Carbon. Retrieved October 16, 2020, from https://priceoncarbon.org/revenue-options/revenue-neutral/
  11. Wang, P., Deng, X., Zhou, H., & Yu, S. (2019). Estimates of the social cost of carbon: A review based on meta-analysis. Journal of Cleaner Production, 209, 1494–1507. https://doi.org/10.1016/j.jclepro.2018.11.058