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Strategies for Modelling Nonlinear Time‐Series Relationships

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  • CLIVE W. J. GRANGER

Abstract

Building models of nonlinear relationships are inherently more difficult than linear ones There are more possibilities, many more parameters and thus more mistakes can be made. It is suggested that a strategy be applied when attempting such modelling involving testing for linearity, considering just a few model types of parsimonious form and then performing post‐sample evaluation of the resulting models compared to a linear one. The strategy proposed is a ‘simple‐to‐general’ one and the application of a heteroskedasticity correction is not recommended

Suggested Citation

  • Clive W. J. Granger, 1993. "Strategies for Modelling Nonlinear Time‐Series Relationships," The Economic Record, The Economic Society of Australia, vol. 69(3), pages 233-238, September.
    • Handle: RePEc:bla:ecorec:v:69:y:1993:i:3:p:233-238
    DOI: 10.1111/j.1475-4932.1993.tb02103.x
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    References listed on IDEAS

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    1. Lee, Tae-Hwy & White, Halbert & Granger, Clive W. J., 1993. "Testing for neglected nonlinearity in time series models : A comparison of neural network methods and alternative tests," Journal of Econometrics, Elsevier, vol. 56(3), pages 269-290, April.
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    2. Gary Madden & Joachim Tan, 2008. "Forecasting international bandwidth capacity using linear and ANN methods," Applied Economics, Taylor & Francis Journals, vol. 40(14), pages 1775-1787.

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