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Elasticities of fuel and traffic demand and the direct rebound effects: An econometric estimation in the case of Norway

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  • Odeck, James
  • Johansen, Kjell

Abstract

We estimate the elasticities of fuel and travel demand with respect to fuel prices and income in the case of Norway. Furthermore, we derive the direct rebound effects that explain the degree to which a fuel price increase is “offset” in the form of greater fuel use and/or travel due to improvements in vehicle fuel efficiency. For this purpose, we use and compare two alternative econometric approaches: the error correction model (ECM) and the dynamic model. Our initial assumption is that one should not be indifferent with respect to the approach used to derive elasticities. The data used are for the period 1980–2011. Our results indicate the following: (1) the dynamic model fits the data better than the ECM model does; (2) the estimated elasticities of fuel demand with respect to price and income are −0.26 and 0.06 in the short run and −0.36 and 0.09 in the long run. For travel demand, the respective elasticities are −0.11 and 0.06 in the short run and −0.24 and 0.13 in the long run, implying inelastic demands for fuel and travel demand; and (3) rebound effects indicate that 0.26% and 0.06% of fuel savings as a result of fuel price increase will be offset in the form of more fuel use in the short run and in the long run, respectively, if fuel efficiency increases by 1%. Our policy recommendations are that policies should not be indifferent to the methods used to derive elasticities. We contend that it is crucial to seriously consider rebound effects in policy making because basic elasticity estimates exaggerate the impact of fuel price increases.

Suggested Citation

  • Odeck, James & Johansen, Kjell, 2016. "Elasticities of fuel and traffic demand and the direct rebound effects: An econometric estimation in the case of Norway," Transportation Research Part A: Policy and Practice, Elsevier, vol. 83(C), pages 1-13.
  • Handle: RePEc:eee:transa:v:83:y:2016:i:c:p:1-13
    DOI: 10.1016/j.tra.2015.10.003
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    References listed on IDEAS

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    Cited by:

    1. De Borger, Bruno & Mulalic, Ismir & Rouwendal, Jan, 2016. "Measuring the rebound effect with micro data: A first difference approach," Journal of Environmental Economics and Management, Elsevier, vol. 79(C), pages 1-17.
    2. repec:eee:energy:v:128:y:2017:i:c:p:28-38 is not listed on IDEAS
    3. repec:eee:eneeco:v:67:y:2017:i:c:p:111-120 is not listed on IDEAS
    4. repec:eee:transa:v:108:y:2018:i:c:p:1-11 is not listed on IDEAS
    5. repec:eee:transa:v:103:y:2017:i:c:p:154-171 is not listed on IDEAS
    6. Jihye Byun & Sungjin Park & Kitae Jang, 2017. "Rebound Effect or Induced Demand? Analyzing the Compound Dual Effects on VMT in the U.S," Sustainability, MDPI, Open Access Journal, vol. 9(2), pages 1-10, February.
    7. Galvin, Ray, 2016. "Rebound effects from speed and acceleration in electric and internal combustion engine cars: An empirical and conceptual investigation," Applied Energy, Elsevier, vol. 172(C), pages 207-216.
    8. repec:eee:transa:v:105:y:2017:i:c:p:167-180 is not listed on IDEAS
    9. Burke, Paul J. & Batsuuri, Tsendsuren & Yudhistira, Muhammad Halley, 2017. "Easing the traffic: The effects of Indonesia’s fuel subsidy reforms on toll-road travel," Transportation Research Part A: Policy and Practice, Elsevier, vol. 105(C), pages 167-180.

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