STRATEGIES FOR MODELING NONLINEAR TIME-SERIES RELATIONSHIPS

Building models of nonlinear relationships are inherently more difficu lt than linear ones. There are more possibilities, many more parameter s and thus more mistakes can be made. It is suggested that a strategy be applied when attempting such modelling involving testing for linear ity, 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 t he application of a heteroskedasticity correction is not recommended.