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Carbon Abatement Costs: Why the Wide Range of Estimates?

Author

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  • Fischer, Carolyn

    (Resources for the Future)

  • Morgenstern, Richard

    (Resources for the Future)

Abstract

Estimates of marginal abatement costs for reducing carbon emissions derived from major economic-energy models vary widely. Controlling for policy regimes, we use meta-analysis to examine the importance of structural modeling choices in explaining differences in estimates. The analysis indicates that particular assumptions about perfectly foresighted consumers and Armington trade elasticities generate lower estimates of marginal abatement costs. Other choices are associated with higher cost estimates, including perfectly mobile capital, inclusion of a backstop technology, and greater disaggregation among regions and sectors. Some features, such as greater technological detail, seem less significant. Understanding the importance of key modeling assumptions, as well as the way the models are used to estimate abatement costs, can help guide the development of consistent modeling practices for policy evaluation.

Suggested Citation

  • Fischer, Carolyn & Morgenstern, Richard, 2003. "Carbon Abatement Costs: Why the Wide Range of Estimates?," RFF Working Paper Series dp-03-42-rev, Resources for the Future.
    • Handle: RePEc:rff:dpaper:dp-03-42-rev
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    Cited by:

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    2. Parry, Ian W.H., 2007. "Are the costs of reducing greenhouse gases from passenger vehicles negative?," Journal of Urban Economics, Elsevier, vol. 62(2), pages 273-293, September.
    3. Carolyn Fischer & Alan K. Fox, 2007. "Output-Based Allocation of Emissions Permits for Mitigating Tax and Trade Interactions," Land Economics, University of Wisconsin Press, vol. 83(4), pages 575-599.
    4. Rick Baker & Andrew Barker & Alan Johnston & Michael Kohlhaas, 2008. "The Stern Review: an assessment of its methodology," Staff Working Papers 0801, Productivity Commission, Government of Australia.
    5. Sushama Murty, 2015. "Marginal reforms to facilitate climate change mitigation: An assessment of costs and abilities to abate of different countries," Discussion Papers 1508, University of Exeter, Department of Economics.
    6. Gerlagh, Reyer, 2007. "Measuring the value of induced technological change," Energy Policy, Elsevier, vol. 35(11), pages 5287-5297, November.
    7. Kuik, Onno & Brander, Luke & Tol, Richard S.J., 2009. "Marginal abatement costs of greenhouse gas emissions: A meta-analysis," Energy Policy, Elsevier, vol. 37(4), pages 1395-1403, April.
    8. Nocera, Silvio & Tonin, Stefania & Cavallaro, Federico, 2015. "The economic impact of greenhouse gas abatement through a meta-analysis: Valuation, consequences and implications in terms of transport policy," Transport Policy, Elsevier, vol. 37(C), pages 31-43.
    9. Fischer, Carolyn & Fox, Alan, 2004. "Output-Based Allocations of Emissions Permits: Efficiency and Distributional Effects in a General Equilibrium Setting with Taxes and Trade," RFF Working Paper Series dp-04-37, Resources for the Future.
    10. Rezek, Jon P. & Campbell, Randall C., 2007. "Cost estimates for multiple pollutants: A maximum entropy approach," Energy Economics, Elsevier, vol. 29(3), pages 503-519, May.
    11. Nocera, Silvio & Tonin, Stefania & Cavallaro, Federico, 2015. "Carbon estimation and urban mobility plans: Opportunities in a context of austerity," Research in Transportation Economics, Elsevier, vol. 51(C), pages 71-82.
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    13. Chunbo Ma & Atakelty Hailu, 2016. "The Marginal Abatement Cost of Carbon Emissions in China," The Energy Journal, , vol. 37(1_suppl), pages 111-128, January.
    14. Liu, Liwei & Sun, Xiaoru & Chen, Chuxiang & Zhao, Erdong, 2016. "How will auctioning impact on the carbon emission abatement cost of electric power generation sector in China?," Applied Energy, Elsevier, vol. 168(C), pages 594-609.
    15. Wie, Jiegen & Wennlock, Magnus & Johansson, Daniel J.A. & Sterner, Thomas, 2011. "The Fossil Endgame: Strategic Oil Price Discrimination and Carbon Taxation," RFF Working Paper Series dp-11-26, Resources for the Future.

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    JEL classification:

    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • Q25 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Water
    • D58 - Microeconomics - - General Equilibrium and Disequilibrium - - - Computable and Other Applied General Equilibrium Models

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