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Forecasting with Neural Networks Models

Author

Listed:
  • Francis Bismans
  • Igor N. Litvine

Abstract

This paper deals with so-called feedforward neural network model which we consider from a statistical and econometric viewpoint. It was shown how this model can be estimated by maximum likelihood. Finally, we apply the ANN methodology to model demand for electricity in South Africa. The comparison of forecasts based on a linear and ANN model respectively shows the usefulness of the latter.

Suggested Citation

  • Francis Bismans & Igor N. Litvine, 2016. "Forecasting with Neural Networks Models," Working Papers of BETA 2016-28, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    • Handle: RePEc:ulp:sbbeta:2016-28
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    File URL: http://beta.u-strasbg.fr/WP/2016/2016-28.pdf
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    More about this item

    Keywords

    Artificial neural networks (ANN); electricity consumption; forecasting; linear and non-linear models; recessions.;
    All these keywords.

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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