@article{7d4222b403f646d899d9d148273f2f97,
title = "Combined forecasts from linear and nonlinear time series models",
abstract = "Combined forecasts from a linear and a nonlinear model are investigated for time series with possibly nonlinear characteristics. The forecasts are combined by a constant coefficient regression method as well as a time varying method. The time varying method allows for a locally (non)linear modeling. The methods are applied to three data sets: Canadian lynx and sunspot series, US annual macro-economic time series - used by Nelson and Plosser (J. Monetary Econ., 10 (1982) 139) - and US monthly unemployment rate and production indices. It is shown that the combined forecasts perform well, especially with time varying coefficients. This result holds for out of sample performance for the sunspot series, the Canadian lynx number series and the monthly series, but it does not uniformly hold for the Nelson and Plosser economic time series.",
keywords = "Combining forecasts, ExpAR model, Locally (non)linear modeling, Threshold model, Time varying coefficient model",
author = "Nobuhiko Terui and {Van Dijk}, {Herman K.}",
note = "Funding Information: This research was started while the first author was visiting the Tinbergen Institute at Erasmus University Rotterdam. The first author acknowledges financial support from NWO (Netherlands Organization for Scientific Research), JSPS (Japan Society for Promotion of Science) and the Japanese Ministry of Education (Scientific Research Grant no. (C)10630020). We thank Timo Ter{\"a}svirta, Peter Schotman, Philip Hans Franses and two anonymous referees for very useful comments on earlier drafts. The careful reading by the editor, Prof. Keith Ord, is also much appreciated. Remaining errors are entirely ours. ",
year = "2002",
doi = "10.1016/S0169-2070(01)00120-0",
language = "English",
volume = "18",
pages = "421--438",
journal = "International Journal of Forecasting",
issn = "0169-2070",
publisher = "Elsevier B.V.",
number = "3",
}