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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.

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Bibliographic Info

Article provided by Elsevier in its journal Resource and Energy Economics.

Volume (Year): 30 (2008)
Issue (Month): 4 (December)
Pages: 527-539

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Handle: RePEc:eee:resene:v:30:y:2008:i:4:p:527-539

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Web page: http://www.elsevier.com/locate/inca/505569

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Keywords: Commercial energy demand Carbon policy Climate change Discrete choice;

References

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  1. Christopher Garbacz, 1984. "Residential Electricity Demand: A Suggested Appliance Stock Equation," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 151-154.
  2. Bernard, J.T. & Bolduc, D. & Belanger, D., 1993. "Quebec Residential Electricity Demand: A Microeconometric Approach," Papers 9334, Laval - Recherche en Energie.
  3. E. Raphael Branch, 1993. "Short Run Income Elasticity of Demand for Residential Electricity Using Consumer Expenditure Survey Data," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 111-122.
  4. Dubin, Jeffrey A & McFadden, Daniel L, 1984. "An Econometric Analysis of Residential Electric Appliance Holdings and Consumption," Econometrica, Econometric Society, vol. 52(2), pages 345-62, March.
  5. Baker, Paul & Blundell, Richard, 1991. "The Microeconometric Approach to Modelling Energy Demand: Some Results for UK Households," Oxford Review of Economic Policy, Oxford University Press, vol. 7(2), pages 54-76, Summer.
  6. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
  7. Dahl, Carol A., 1993. "A survey of energy demand elasticities in support of the development of the NEMS," MPRA Paper 13962, University Library of Munich, Germany.
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Cited by:
  1. 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.
  2. 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.

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