Forecasting world and regional aviation jet fuel demands to the mid-term (2025)
AbstractThis article provides jet fuel demand projections at the worldwide level and for eight geographical zones until 2025. Air traffic forecasts are performed using dynamic panel-data econometrics. Then, the conversion of air traffic projections into quantities of jet fuel is accomplished by using a complementary approach to the 'Traffic Efficiency' method developed previously by the UK Department of Trade and Industry to support the Intergovernmental Panel on Climate Change (IPCC, 1999). According to our main scenario, air traffic should increase by about 100% between 2008 and 2025 at the world level, corresponding to a yearly average growth rate of 4.7%. World jet fuel demand is expected to increase by about 38% during the same period, corresponding to a yearly average growth rate of 1.9% per year. According to these results, energy efficiency improvements allow reducing the effect of air traffic rise on the increase in jet fuel demand, but do not annihilate it. Jet fuel demand is thus unlikely to diminish unless there is a radical technological shift, or air travel demand is restricted.
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Bibliographic InfoArticle provided by Elsevier in its journal Energy Policy.
Volume (Year): 39 (2011)
Issue (Month): 9 (September)
Contact details of provider:
Web page: http://www.elsevier.com/locate/enpol
Energy efficiency Jet fuel demand forecasts Macro-level methodology;
Other versions of this item:
- Chevallier, Julien & Chèze, Benoît & Gastineau, Pascal, 2011. "Forecasting world and regional aviation Jet-Fuel demands to the mid term (2025)," Economics Papers from University Paris Dauphine 123456789/6792, Paris Dauphine University.
- Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy
- L93 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Air Transportation
- C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
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