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Stationarity, structural change and specification in a demand system: the case of energy

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  • McAvinchey, Ian D.
  • Yannopoulos, Andreas
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    Abstract

    The impact of structural change, stationarity of the data and economic theory on energy modelling and forecasting, is investigated for Germany and the UK, using two three-equation models which allow for the long- and short-run behaviour of the constituent variables. The models are specified, restricted and estimated to comply with the above conditions and they are then used to generate one step ahead and dynamic forecasts from each of the two models; one with structural change, and the other without. These forecasts and other aspects of the models are then used to choose the specification. In general structural change, stationarity of the data and economic theory are shown to have important implications for model specification and forecasting.

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    Bibliographic Info

    Article provided by Elsevier in its journal Energy Economics.

    Volume (Year): 25 (2003)
    Issue (Month): 1 (January)
    Pages: 65-92

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    Handle: RePEc:eee:eneeco:v:25:y:2003:i:1:p:65-92

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    Web page: http://www.elsevier.com/locate/eneco

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    Cited by:
    1. Erdogdu, Erkan, 2007. "Regulatory Reform in Turkish Energy Industry: An analysis," MPRA Paper 19100, University Library of Munich, Germany.
    2. Jean-Thomas Bernard & Nadhem Idoudi & Lynda Khalaf & Clément Yélou, 2007. "Finite sample inference methods for dynamic energy demand models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(7), pages 1211-1226.
    3. Suganthi, L. & Samuel, Anand A., 2012. "Energy models for demand forecasting—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1223-1240.
    4. Kumar Narayan, Paresh & Smyth, Russell, 2007. "Are shocks to energy consumption permanent or temporary? Evidence from 182 countries," Energy Policy, Elsevier, vol. 35(1), pages 333-341, January.
    5. Pai, Ping-Feng & Lin, Chih-Sheng, 2005. "A hybrid ARIMA and support vector machines model in stock price forecasting," Omega, Elsevier, vol. 33(6), pages 497-505, December.

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