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Energy price elasticities of energy-service demand for passenger traffic in the Federal Republic of Germany

Author

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  • Dreher, M
  • Wietschel, M
  • Göbelt, M
  • Rentz, O

Abstract

The development and evaluation of cost-effective environmental strategies for the energy sector, based on energy-emission models for both national and international levels, requires consideration of the effects of energy-price changes on energy-service demand. To cope with the problem that the forms of functional dependencies between energy-service demand and independent variables are often unknown, a model based on neural networks has been developed. A multi-layer perceptron (MLP) is proven to be suitable for calculations of price elasticities. The neural network model has been applied to the passenger-traffic sector in the FRG. Elasticities of energy-service demand with respect to price level and direction of price change are derived.

Suggested Citation

  • Dreher, M & Wietschel, M & Göbelt, M & Rentz, O, 1999. "Energy price elasticities of energy-service demand for passenger traffic in the Federal Republic of Germany," Energy, Elsevier, vol. 24(2), pages 133-140.
    • Handle: RePEc:eee:energy:v:24:y:1999:i:2:p:133-140
    DOI: 10.1016/S0360-5442(98)00075-9
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    Cited by:

    1. Llorca, Manuel & Baños, José & Somoza, José & Arbués, Pelayo, 2014. "A latent class approach for estimating energy demands and efficiency in transport: An application to Latin America and the Caribbean," Efficiency Series Papers 2014/04, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    2. Lu, I.J. & Lewis, Charles & Lin, Sue J., 2009. "The forecast of motor vehicle, energy demand and CO2 emission from Taiwan's road transportation sector," Energy Policy, Elsevier, vol. 37(8), pages 2952-2961, August.
    3. Huang, Chung-Neng & Chen, Yui-Sung, 2017. "Design of magnetic flywheel control for performance improvement of fuel cells used in vehicles," Energy, Elsevier, vol. 118(C), pages 840-852.
    4. Rentz, O. & Wietschel, M. & Dreher, Martin & Bräuer, W. & Kühn, Isabel, 2001. "Neue umweltpolitische Instrumente im liberalisierten Strommarkt. Endbericht. BW-Plus Forschungsvorhaben BW V 99004 a+b," ZEW Expertises, ZEW - Leibniz Centre for European Economic Research, number 110494.
    5. Manuel Llorca & José Baños & José Somoza & Pelayo Arbués, 2017. "A Stochastic Frontier Analysis Approach for Estimating Energy Demand and Efficiency in the Transport Sector of Latin America and the Caribbean," The Energy Journal, International Association for Energy Economics, vol. 0(Number 5).
    6. Al-Ghandoor, Ahmed & Samhouri, Murad & Al-Hinti, Ismael & Jaber, Jamal & Al-Rawashdeh, Mohammad, 2012. "Projection of future transport energy demand of Jordan using adaptive neuro-fuzzy technique," Energy, Elsevier, vol. 38(1), pages 128-135.
    7. Lu, I.J. & Lin, Sue J. & Lewis, Charles, 2008. "Grey relation analysis of motor vehicular energy consumption in Taiwan," Energy Policy, Elsevier, vol. 36(7), pages 2556-2561, July.
    8. Kesicki, Fabian & Anandarajah, Gabrial, 2011. "The role of energy-service demand reduction in global climate change mitigation: Combining energy modelling and decomposition analysis," Energy Policy, Elsevier, vol. 39(11), pages 7224-7233.

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