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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

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.

Suggested Citation

  • McAvinchey, Ian D. & Yannopoulos, Andreas, 2003. "Stationarity, structural change and specification in a demand system: the case of energy," Energy Economics, Elsevier, vol. 25(1), pages 65-92, January.
  • Handle: RePEc:eee:eneeco:v:25:y:2003:i:1:p:65-92
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    Cited by:

    1. Herwartz, Helmut & Maxand, Simone & Walle, Yabibal M., 2017. "Heteroskedasticity-robust unit root testing for trending panels," Center for European, Governance and Economic Development Research Discussion Papers 314, University of Goettingen, Department of Economics.
    2. 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.
    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. Erdogdu, Erkan, 2005. "Energy market reforms in Turkey: An economic analysis," MPRA Paper 26929, University Library of Munich, Germany.
    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.
    6. repec:eee:rensus:v:88:y:2018:i:c:p:297-325 is not listed on IDEAS
    7. 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.

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