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The determinants of fuel use in the trucking industry—volume, fleet characteristics and the rebound effect

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  • De Borger, Bruno
  • Mulalic, Ismir

Abstract

This paper studies the determinants of fuel use in the trucking industry in Denmark, using aggregate time series data for the period 1980–2007. The model captures the main linkages between the demand for freight transport, the characteristics of the vehicle fleet, and the demand for fuel. Results include the following. First, we precisely define and estimate a rebound effect of improvements in fuel efficiency in the trucking industry: behavioural adjustments in the industry imply that an exogenous improvement in fuel efficiency reduces fuel use less than proportionately. Our best estimate of this effect is approximately 10% in the short run and 17% in the long run, so that a 1% improvement in fuel efficiency reduces fuel use by 0.90% (short-run) to 0.83% (long-run). Second, we find that higher fuel prices raise the average capacity of trucks, and they induce firms to invest in newer, typically more fuel efficient, trucks. Third, these adjustments and the rebound effect jointly imply that the effect of higher fuel prices on fuel use in the trucking industry is fairly small; estimated price elasticities are −0.13 and −0.22 in the short run and in the long run, respectively. The empirical results of this paper have implications for judging the implications of fuel efficiency standards and regulations with respect to larger trucks in the EU.

Suggested Citation

  • De Borger, Bruno & Mulalic, Ismir, 2012. "The determinants of fuel use in the trucking industry—volume, fleet characteristics and the rebound effect," Transport Policy, Elsevier, vol. 24(C), pages 284-295.
  • Handle: RePEc:eee:trapol:v:24:y:2012:i:c:p:284-295
    DOI: 10.1016/j.tranpol.2012.08.011
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    References listed on IDEAS

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    Citations

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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. Wang, Zhaohua & Lu, Milin, 2014. "An empirical study of direct rebound effect for road freight transport in China," Applied Energy, Elsevier, vol. 133(C), pages 274-281.
    3. repec:eee:ecmode:v:71:y:2018:i:c:p:159-173 is not listed on IDEAS
    4. repec:kap:transp:v:45:y:2018:i:3:d:10.1007_s11116-017-9759-1 is not listed on IDEAS
    5. Llorca, Manuel & Jamasb, Tooraj, 2017. "Energy efficiency and rebound effect in European road freight transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 101(C), pages 98-110.
    6. repec:gam:jsusta:v:10:y:2018:i:8:p:2874-:d:163513 is not listed on IDEAS
    7. Hans Jakob Walnum & Carlo Aall & Søren Løkke, 2014. "Can Rebound Effects Explain Why Sustainable Mobility Has Not Been Achieved?," Sustainability, MDPI, Open Access Journal, vol. 6(12), pages 1-28, December.
    8. Tscharaktschiew, Stefan, 2014. "Shedding light on the appropriateness of the (high) gasoline tax level in Germany," Economics of Transportation, Elsevier, vol. 3(3), pages 189-210.
    9. Ruzzenenti, Franco & Basosi, Riccardo, 2017. "Modelling the rebound effect with network theory: An insight into the European freight transport sector," Energy, Elsevier, vol. 118(C), pages 272-283.
    10. Liu, Wen & Lund, Henrik & Mathiesen, Brian Vad, 2013. "Modelling the transport system in China and evaluating the current strategies towards the sustainable transport development," Energy Policy, Elsevier, vol. 58(C), pages 347-357.
    11. Vierth, Inge, 2013. "Why do CO2 emissions from heavy road freight transports increase in spite of higher fuel prices?," Working papers in Transport Economics 2013:4, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    12. Muhammad Omer, 2018. "Estimating Elasticity of Transport Fuel Demand in Pakistan," SBP Working Paper Series 96, State Bank of Pakistan, Research Department.
    13. 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.
    14. Abate, Megersa, 2014. "Does fuel price affect trucking industry’s network characteristics?: evidence from Denmark," Working papers in Transport Economics 2014:26, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    15. Ivan T. Herrmann & Michael Z. Hauschild & Michael D. Sohn & Thomas E. McKone, 2014. "Confronting Uncertainty in Life Cycle Assessment Used for Decision Support," Journal of Industrial Ecology, Yale University, vol. 18(3), pages 366-379, May.

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