A Monte Carlo study of the forecasting performance of empirical SETAR models

In this paper we investigate the multi-period forecast performance of a number of empirical selfexciting threshold autoregressive (SETAR) models that have been proposed in the literature for modelling exchange rates and GNP, amongst other variables. We take each of the empirical SETAR models in turn as the DGP to ensure that the ‘non-linearity’ characterises the future, and compare the forecast performance of SETAR and linear autoregressive models on a number of quantitative and qualitative criteria. Our results indicate that non-linear models have an edge in certain states of nature but not in others, and that this can be highlighted by evaluating forecasts conditional upon the regime. The first author acknowledges financial support under ESRC grant L116251015. The paper has benefitted from the comments of participants at the Forecasting Workshop, Nuffield College, June 1997, and the Econometric Society European Meeting, Toulouse, August 1997. We are especially grateful to Hashem Pesaran and three anonymous referees of this journal for helpful comments and suggestions.