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The Energy Efficiency Gap in EPA’s Benefit-Cost Analysis of Vehicle Greenhouse Gas Regulations: A Case Study

Published online by Cambridge University Press:  10 July 2015

Gloria Helfand  and
Reid Dorsey-Palmateer
Gloria Helfand*
Affiliation:
Environmental Protection Agency, Ann Arbor, MI 48105, USA, e-mail: [email protected]
Reid Dorsey-Palmateer
Affiliation:
University of Michigan - Economics, 611 Tappan St., Ann Arbor, MI 48109, USA, e-mail: [email protected]
*
*e-mail: [email protected]
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Abstract

Recent federal regulations require new light-duty vehicles to have lower greenhouse gas emissions and better fuel economy. This paper presents the reasoning used by the U.S. Environmental Protection Agency (EPA) in its benefit-cost analysis of the standards. According to EPA, many available technologies could achieve these goals without affecting other vehicle qualities, and fuel savings would pay for the increased technology costs with short payback periods. This lack of market adoption of cost-effective energy-saving technologies has been termed the energy efficiency gap or energy efficiency paradox. It suggests that either there are additional costs, such as changes in vehicle qualities, not considered in cost estimates, or markets for energy-saving technologies are not achieving all cost-effective savings. EPA argued that, even if consumers do not accurately consider expected future fuel savings when buying new vehicles, consumers are projected to receive those savings; the latter measure should reflect the impacts of the rule on fuel expenditures. For the cost side, EPA used a measure of technology costs required to meet the standards while maintaining baseline (2008) vehicle attributes. Estimates of how these costs would be affected by changes in vehicle attributes were not included.

Keywords

D61L51Q58energy paradoxEnvironmental Protection Agencyfuel economytransportation
Type
Articles
Information
Journal of Benefit-Cost Analysis , Volume 6 , Issue 2 , Summer 2015 , pp. 432 - 454
Copyright
© Society for Benefit-Cost Analysis 2015 

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