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Estimating Underlying Energy Demand Trends using UK Annual Data

Author

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  • John Dimitropoulos

    (Surrey Energy Economics Centre (SEEC), Department of Economics, University of Surrey)

  • Lester C Hunt

    (Surrey Energy Economics Centre (SEEC), Department of Economics, University of Surrey)

  • Guy Judge

    (Department of Economics, University of Portsmouth)

Abstract

Employing the Structural Time Series Model (STSM) approach suggested by Harvey (1989, 1997), and based on annual data for the UK from 1967-2002, this paper reiterates the importance of using a stochastic rather than a linear deterministic trend formulation when estimating energy demand models, a practice originally established by Hunt et al. (2003a,b) using quarterly UK data. The findings confirm that important non-linear and stochastic trends are present as a result of technical change and other exogenous factors driving demand, and that a failure to account for these trends will lead to biased estimates of the long-run price and income elasticities. The study also establishes that, provided these effects are allowed for, the estimated long-run elasticities are robust to the different data frequencies used in the modelling.

Suggested Citation

  • John Dimitropoulos & Lester C Hunt & Guy Judge, 2004. "Estimating Underlying Energy Demand Trends using UK Annual Data," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 108, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    • Handle: RePEc:sur:seedps:108
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    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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