On SETAR non-linearity and forecasting

On SETAR non-linearity and forecasting

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Article ID: iaor20081008
Country: United Kingdom
Volume: 22
Issue: 5
Start Page Number: 359
End Page Number: 375
Publication Date: Aug 2003
Journal: International Journal of Forecasting
Authors: , , ,
Keywords: simulation, economics
Abstract:

We compare linear autoregressive (AR) models and self-exciting threshold autoregressive (SETAR) models in terms of their point forecast performance, and their ability to characterize the uncertainty surrounding those forecasts, i.e. interval or density forecasts. A two-regime SETAR process is used as the data-generating process in an extensive set of Monte Carlo simulations, and we consider the discriminatory power of recently developed methods of forecast evaluation for different degrees of non-linearity. We find that the interval and density evaluation methods are unlikely to show the linear model to be deficient on samples of the size typical for macroeconomic data.

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