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Another Look at U.S. Passenger Vehicle Use and the ‘Rebound’ Effect from Improved Fuel Efficiency

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  • Clifton T. Jones

Abstract

Recently, Greene (1992) analyzed vehicle miles travelled for U.S. passenger vehicles over 1966-89 to econometrically estimate the “rebound†effect in fuel consumption resulting from improved fuel efficiency. He found that a static AR(1) model could not be rejected, implying that the rebound effect is small (13 %) with no significant long-run adjustments, regardless of the assumed functional form (linear or loglinear). Another look at the data from a different model selection approach shows that while a loglinear AR(1) model is acceptable, the linear version is not. Using either form, a lagged dependent variable model cannot be rejected on statistical grounds yet has insignificant GNP effects, yielding similarly small short-run rebound effects but significant long-run rebound effects of about 30%. Thus, the evidence from these competing models for a significant long-run adjustment process is mixed, so that its presence cannot be completely ruled out.

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  • Clifton T. Jones, 1993. "Another Look at U.S. Passenger Vehicle Use and the ‘Rebound’ Effect from Improved Fuel Efficiency," The Energy Journal, , vol. 14(4), pages 99-110, October.
    • Handle: RePEc:sae:enejou:v:14:y:1993:i:4:p:99-110
    DOI: 10.5547/ISSN0195-6574-EJ-Vol14-No4-6
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    References listed on IDEAS

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    1. Andrew C. Harvey, 1990. "The Econometric Analysis of Time Series, 2nd Edition," MIT Press Books, The MIT Press, edition 2, volume 1, number 026208189x, April.
    2. Hendry, David F & Mizon, Grayham E, 1978. "Serial Correlation as a Convenient Simplification, not a Nuisance: A Comment on a Study of the Demand for Money by the Bank of England," Economic Journal, Royal Economic Society, vol. 88(351), pages 549-563, September.
    3. David L. Greene, 1992. "Vehicle Use and Fuel Economy: How Big is the "Rebound" Effect?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 117-144.
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