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Evolving Seasonal Patterns in UK Energy Series

Author

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  • Hunt,L.C.
  • Judge,G.

Abstract

AbstractUK Energy series exhibit pronounced regular but not necessarily fixed seasonal patterns. Failure to reflect such changing patterns in econometric models of energy use can result both in misleading estimates of elasticities and policy responses and in forecasts which under- and over-predict seasonal peaks and troughs. Structural Times Series models permit the formulation, estimation and testing of models which allow for evolving stochastic seasonal components and reflect changing patterns of economic behaviour. Moreover such components can be incorporated into causal regression equations to permit greater flexibility in modelling the seasonal variation than is possible using ordinary dummy variables. By estimating suitable dynamic models which allow for evolving seasonal effects and then nesting the fixed effects models, we compare estimated elasticities and test the restriction of fixed seasonal effects.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Hunt,L.C. & Judge,G., 1995. "Evolving Seasonal Patterns in UK Energy Series," Papers 63, Portsmouth University - Department of Economics.
  • Handle: RePEc:fth:portec:63
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    Cited by:

    1. 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.
    2. Herrerias, M.J., 2013. "Seasonal anomalies in electricity intensity across Chinese regions," Applied Energy, Elsevier, vol. 112(C), pages 1548-1557.
    3. Lester C. Hunt & Guy Judge & Yashushi Ninomiya, 2000. "Modelling Technical Progress: An Application of the Stochastic Trend Model to UK Energy Demand," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 99, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    4. Maria Jesus Herrerias and Eric Girardin, 2013. "Seasonal Patterns of Energy in China," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    5. SHIRANI-FAKHR, Zohreh & KHOSHAKHLAGH, Rahman & SHARIFI, Alimorad, 2015. "Estimating Demand Function For Electricity In Industrial Sector Of Iran Using Structural Time Series Model (Stsm)," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 15(1), pages 143-160.

    More about this item

    Keywords

    ENERGY; MODELS; SEASONS; TIME SERIES;

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q49 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Other

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