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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


  • 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.)


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.

Suggested Citation

  • David C Broadstock & Lester C Hunt, 2013. "Tying up loose ends: A note on the impact of omitting MA residuals from panel energy demand models based on the Koyck lag transformation," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 140, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
  • Handle: RePEc:sur:seedps:140

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    References listed on IDEAS

    1. 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.
    2. Hunt, Lester C. & Judge, Guy & Ninomiya, Yasushi, 2003. "Underlying trends and seasonality in UK energy demand: a sectoral analysis," Energy Economics, Elsevier, vol. 25(1), pages 93-118, January.
    3. Adeyemi, Olutomi I. & Broadstock, David C. & Chitnis, Mona & Hunt, Lester C. & Judge, Guy, 2010. "Asymmetric price responses and the underlying energy demand trend: Are they substitutes or complements? Evidence from modelling OECD aggregate energy demand," Energy Economics, Elsevier, vol. 32(5), pages 1157-1164, September.
    4. Lester C. Hunt & Guy Judge & Yasushi Ninomiya, 2003. "Modelling underlying energy demand trends," Chapters,in: Energy in a Competitive Market, chapter 9 Edward Elgar Publishing.
    5. 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.
    6. 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.
    7. Chen, Shiu-Sheng, 2009. "Oil price pass-through into inflation," Energy Economics, Elsevier, vol. 31(1), pages 126-133, January.
    8. 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.
    9. 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.
    10. Lester C. Hunt (ed.), 2003. "Energy in a Competitive Market," Books, Edward Elgar Publishing, number 2519.
    11. 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.
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    More about this item


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

    JEL classification:

    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

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