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Accounting for asymmetric price responses and underlying energy demand trends in OECD industrial energy demand

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  • Adeyemi, Olutomi I.
  • Hunt, Lester C.

Abstract

This paper explores the way technical progress and improvements in energy efficiency are captured when modelling OECD industrial energy demand. The industrial sectors of the developed world involve a number of different practices and processes utilising a range of different technologies. Consequently, given the derived demand nature of energy, it is vital when modelling industrial energy demand that the impact of technical progress is appropriately captured. However, the energy economics literature does not give a clear guide on how this can be achieved; one strand suggests that technical progress is ‘endogenous’ via asymmetric price responses whereas another strand suggests that it is ‘exogenous’. More recently, it has been suggested that potentially there is a role for both ‘endogenous’ technical progress and ‘exogenous’ technical progress and consequently the general model should be specified accordingly.

Suggested Citation

  • Adeyemi, Olutomi I. & Hunt, Lester C., 2014. "Accounting for asymmetric price responses and underlying energy demand trends in OECD industrial energy demand," Energy Economics, Elsevier, vol. 45(C), pages 435-444.
  • Handle: RePEc:eee:eneeco:v:45:y:2014:i:c:p:435-444 DOI: 10.1016/j.eneco.2014.07.012
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    Cited by:

    1. Adetutu, Morakinyo O. & Glass, Anthony J. & Weyman-Jones, Thomas G., 2016. "Decomposing energy demand across BRIIC countries," Energy Economics, Elsevier, pages 396-404.
    2. Burke, Paul J. & Csereklyei, Zsuzsanna, 2016. "Understanding the energy-GDP elasticity: A sectoral approach," Energy Economics, Elsevier, pages 199-210.
    3. repec:eee:eneeco:v:67:y:2017:i:c:p:366-374 is not listed on IDEAS
    4. Tajudeen, Ibrahim A., 2015. "Examining the role of energy efficiency and non-economic factors in energy demand and CO2 emissions in Nigeria: Policy implications," Energy Policy, Elsevier, vol. 86(C), pages 338-350.
    5. Adetutu, Morakinyo & Glass, Anthony & Weyman-Jones, Thomas, 2015. "Economy-wide Estimates of Rebound Effects: Evidence from Panel Data," MPRA Paper 65409, University Library of Munich, Germany.
    6. Salisu, Afees A. & Ayinde, Taofeek O., 2016. "Modeling energy demand: Some emerging issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1470-1480.
    7. Atalla, Tarek N. & Hunt, Lester C., 2016. "Modelling residential electricity demand in the GCC countries," Energy Economics, Elsevier, pages 149-158.

    More about this item

    Keywords

    OECD industrial energy demand; Asymmetric price responses (APR); Underlying energy demand trend (UEDT);

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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