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Carbon mitigation costs for the commercial building sector: Discrete-continuous choice analysis of multifuel energy demand

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  • Newell, Richard G.
  • Pizer, William A.

Abstract

We estimate a carbon mitigation cost curve for the U.S. commercial sector based on econometric estimation of the responsiveness of fuel demand and equipment choices to energy price changes. The model econometrically estimates fuel demand conditional on fuel choice, which is characterized by a multinomial logit model. Separate estimation of end uses (e.g., heating, cooking) using the U.S. Commercial Buildings Energy Consumption Survey allows for exceptionally detailed estimation of price responsiveness disaggregated by end use and fuel type. We then construct aggregate long-run elasticities, by fuel type, through a series of simulations; own-price elasticities range from -0.9 for district heat services to -2.9 for fuel oil. The simulations form the basis of a marginal cost curve for carbon mitigation, which suggests that a price of $20 per ton of carbon would result in an 8% reduction in commercial carbon emissions, and a price of $100 per ton would result in a 28% reduction.

Suggested Citation

  • Newell, Richard G. & Pizer, William A., 2008. "Carbon mitigation costs for the commercial building sector: Discrete-continuous choice analysis of multifuel energy demand," Resource and Energy Economics, Elsevier, vol. 30(4), pages 527-539, December.
    • Handle: RePEc:eee:resene:v:30:y:2008:i:4:p:527-539
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    Cited by:

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    3. Dorothee Charlier and Sondes Kahouli, 2019. "From Residential Energy Demand to Fuel Poverty: Income-induced Non-linearities in the Reactions of Households to Energy Price Fluctuations," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    4. Cao, K.H. & Qi, H.S. & Li, R. & Woo, C.K. & Tishler, A. & Zarnikau, J., 2023. "An experiment in own-price elasticity estimation for non-residential electricity demand in the U.S," Utilities Policy, Elsevier, vol. 81(C).
    5. Yueming Qiu, 2014. "Energy Efficiency and Rebound Effects: An Econometric Analysis of Energy Demand in the Commercial Building Sector," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 59(2), pages 295-335, October.
    6. Anna Risch & Claire Salmon, 2017. "What matters in residential energy consumption: evidence from France," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 40(1/2), pages 79-116.
    7. McFadden, Jonathan & Miranowski, John, "undated". "Climate Change Impacts on the Intensive and Extensive Margins of US Agricultural Land," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170512, Agricultural and Applied Economics Association.
    8. Lu, Mengxue & Lai, Joseph, 2020. "Review on carbon emissions of commercial buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 119(C).
    9. Kotchen, Matthew J. & Levinson, Arik, 2023. "When Can Benefit–Cost Analyses Ignore Secondary Markets?," Journal of Benefit-Cost Analysis, Cambridge University Press, vol. 14(1), pages 114-140, March.
    10. Li, Jia & Just, Richard E., 2018. "Modeling household energy consumption and adoption of energy efficient technology," Energy Economics, Elsevier, vol. 72(C), pages 404-415.
    11. Xavier Labandeira & José M. Labeaga & Xiral López-Otero, 2011. "Energy Demand for Heating in Spain: An Empirical Analysis with Policy Purposes," Working Papers 06-2011, Economics for Energy.
    12. Braun, Frauke G., 2010. "Determinants of households' space heating type: A discrete choice analysis for German households," Energy Policy, Elsevier, vol. 38(10), pages 5493-5503, October.
    13. Michael Hanemann & Xavier Labandeira & José M. Labeaga, 2013. "Energy Demand for Heating: Short Run and Long Run," Working Papers 07-2013, Economics for Energy.

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