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Modelling autoregressive processes with a shifting mean Author info | Abstract | Publisher info | Download info | Related research | Statistics Timo Terasvirta ()
Andrés González ()
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This paper contains a nonlinear, nonstationary autoregressive model whose intercept changes deterministically over time. The intercept is a flexible function of time, and its construction bears some resemblance to neural network models. A modelling technique, modified from one for single hidden-layer neural network models, is developed for specification and estimation of the model. Its performance is investigated by simulation and further illustrated by two applications to macroeconomic time series.
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Paper provided by Banco de la Republica de Colombia in its series Borradores de Economia with number
420.
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Keywords: deterministic shift ; nonlinear autoregression ; nonstationarity ; nonlinear trend ; structural change Classification JEL: C22 ; C52. ; Other versions of this item:
This paper has been announced in the following NEP Reports :
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Richard T. Baillie & Claudio Morana, 2007.
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