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Energy Demand and Temperature: A Dynamic Panel Analysis

  • Andrea Bigano

    (Fondazione Eni Enrico Mattei)

  • Francesco Bosello

    (Fondazione Eni Enrico Mattei and EEE Programme, International Centre for Theoretical Physics)

  • Giuseppe Marano

    (Fondazione Eni Enrico Mattei)

This paper is a first attempt to investigate the effect of climate on the demand for different energy vectors from different final users. The ultimate motivation for this is to arrive to a consistent evaluation of the impact of climate change on key consumption goods and primary factors such as energy vectors. This paper addresses these issues by means of a dynamic panel analysis of the demand for coal, gas, electricity, oil and oil products by residential, commercial and industrial users in OECD and (a few) non-OECD countries. It turns out that temperature has a very different influence on the demand of energy vectors as consumption goods and on their demand as primary factors. In general, residential demand responds negatively to temperature increases, while industrial demand is insensitive to temperature increases. As to the service sector, only electricity demand displays a mildly significant negative elasticity to temperature changes.

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Paper provided by Fondazione Eni Enrico Mattei in its series Working Papers with number 2006.112.

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Date of creation: Sep 2006
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Handle: RePEc:fem:femwpa:2006.112
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  1. Banerjee, Anindya, 1999. " Panel Data Unit Roots and Cointegration: An Overview," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(0), pages 607-29, Special I.
  2. Beenstock, Michael & Goldin, Ephraim & Nabot, Dan, 1999. "The demand for electricity in Israel," Energy Economics, Elsevier, vol. 21(2), pages 168-183, April.
  3. David I. Stern, 1998. "A multivariate cointegration analysis of the role of energy in the U.S. macroeconomy," Working Papers in Ecological Economics 9803, Australian National University, Centre for Resource and Environmental Studies, Ecological Economics Program.
  4. Pardo, Angel & Meneu, Vicente & Valor, Enric, 2002. "Temperature and seasonality influences on Spanish electricity load," Energy Economics, Elsevier, vol. 24(1), pages 55-70, January.
  5. Taylor, James W. & Buizza, Roberto, 2003. "Using weather ensemble predictions in electricity demand forecasting," International Journal of Forecasting, Elsevier, vol. 19(1), pages 57-70.
  6. Masih, Abul M. M. & Masih, Rumi, 1996. "Energy consumption, real income and temporal causality: results from a multi-country study based on cointegration and error-correction modelling techniques," Energy Economics, Elsevier, vol. 18(3), pages 165-183, July.
  7. Bentzen, J. & Engsted, T., 1999. "A Revival of the Autoregressive Distributed Lag Model in Estimating Energy Demand Relationships," Papers 99-7, Aarhus School of Business - Department of Economics.
  8. Engsted, T & Bentzen, J, 1997. "Dynamic Modelling of Energy Demand : A Guided Tour Through the Jungle of Unit Roots and Cointegration," Papers 97-6, Aarhus School of Business - Department of Economics.
  9. Henley, Andrew & Peirson, John, 1998. "Residential energy demand and the interaction of price and temperature: British experimental evidence," Energy Economics, Elsevier, vol. 20(2), pages 157-171, April.
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