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Tying up loose ends: A note on the impact of omitting MA residuals from panel energy demand models based on the Koyck lag transformation

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  • David C Broadstock

    ()
    (Research Institute of Economics and Management (RIEM), Southwestern University of Finance and Economics, Sichuan, China and Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey, UK.)

  • Lester C Hunt

    ()
    (Surrey Energy Economics Centre (SEEC), University of Surrey, UK.)

Abstract

Energy demand functions based on Koyck lag transformation result in an MA error process that is generally ignored in estimated panel data models. This note explores the implications of this assumption by estimating panel energy demand functions with asymmetric price responses and an MA process modelled explicitly. It is found that although the models with an MA term might be preferred statistically, they result in inferential problems implying that there might be a need to revisit the specification of panel energy demand functions used in a number of previous studies.

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Bibliographic Info

Paper provided by Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey in its series Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) with number 140.

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Length: 16 pages
Date of creation: Mar 2013
Date of revision:
Publication status: Published in Empirical Economics Letters, 12(10), 2013, pp. 1085–1088. (Revised Version)
Handle: RePEc:sur:seedps:140

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Keywords: Koyck-lag transformation; Moving average errors; Panel data; Aggregate energy demand.;

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  1. James M. Griffin & Craig T. Schulman, 2005. "Price Asymmetry in Energy Demand Models: A Proxy for Energy-Saving Technical Change?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 1-22.
  2. Olutomi I Adeyemi & David C Broadstock & Mona Chitnis & Lester C Hunt & Guy Judge, 2008. "Asymmetric Price Responses and the Underlying Energy Demand Trend: Are they Substitutes or Complements? Evidence from Modelling OECD Aggregate Energy Demand," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 121, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
  3. Hunt, L.C. & Judge, G. & Ninomiya, Y., 2000. "Underlying Trends and Seasonality in UK Energy Demands: A Sectorial Analysis," Papers 134, Portsmouth University - Department of Economics.
  4. Cai, Zongwu, 2007. "Trending time-varying coefficient time series models with serially correlated errors," Journal of Econometrics, Elsevier, vol. 136(1), pages 163-188, January.
  5. Adeyemi, Olutomi I. & Hunt, Lester C., 2007. "Modelling OECD industrial energy demand: Asymmetric price responses and energy-saving technical change," Energy Economics, Elsevier, vol. 29(4), pages 693-709, July.
  6. Chang, Yoosoon & Martinez-Chombo, Eduardo, 2003. "Electricity Demand Analysis Using Cointegration and Error-Correction Models with Time Varying Parameters: The Mexican Case," Working Papers 2003-08, Rice University, Department of Economics.
  7. Dermot Gately & Hiliard G. Huntington, 2002. "The Asymmetric Effects of Changes in Price and Income on Energy and Oil Demand," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 19-55.
  8. Hillard G. Huntington, 2006. "A Note on Price Asymmetry as Induced Technical Change," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 1-8.
  9. Chen, Shiu-Sheng, 2009. "Oil price pass-through into inflation," Energy Economics, Elsevier, vol. 31(1), pages 126-133, January.
  10. Lester C Hunt & Guy Judge & Yasushi Ninomiya, 2003. "Modelling Underlying Energy Demand Trends," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 105, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
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