On SETAR non-linearity and forecasting
Clements, Michael P., Hans Franses, Philip, Smith, Jeremy (Jeremy P.) and van Dijk, Dick. (2003) On SETAR non-linearity and forecasting. Journal of Forecasting, Volume 22 (Number 5). pp. 359-375. ISSN 0277-6693Full text not available from this repository.
Official URL: http://dx.doi.org/10.1002/for.863
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 (C) 2003 John Wiley Sons, Ltd.
|Item Type:||Journal Article|
|Subjects:||H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
H Social Sciences > HD Industries. Land use. Labor
|Divisions:||Faculty of Social Sciences > Economics|
|Journal or Publication Title:||Journal of Forecasting|
|Publisher:||John Wiley & Sons Ltd.|
|Number of Pages:||17|
|Page Range:||pp. 359-375|
|Access rights to Published version:||Restricted or Subscription Access|
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