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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. 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.
    2. 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.
    3. Manuel Llorca & Jose Banos & Somoza Jose & Pelayo Arbues, 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, , vol. 38(5), pages 153-174, September.
    4. 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.
    5. 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).
    6. 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.
    7. 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.
    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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