✦ LIBER ✦

On SETAR non-linearity and forecasting

✍ Scribed by Michael P. Clements; Philip Hans Franses; Jeremy Smith; Dick van Dijk

Book ID: 102214159
Publisher: John Wiley and Sons
Year: 2003
Tongue: English
Weight: 119 KB
Volume: 22
Category: Article
ISSN: 0277-6693
DOI: 10.1002/for.863

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✦ Synopsis

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. Copyright © 2003 John Wiley & Sons, Ltd.

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