Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/61295 
Authors: 
Year of Publication: 
1998
Series/Report no.: 
SFB 373 Discussion Paper No. 1998,10
Publisher: 
Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes, Berlin
Abstract: 
In this paper we study nonparametric estimation and hypothesis testing procedures for the functional coefficient AR (FAR) models of the form Xt = f1(Xt-d)Xt-1 +…+ fp(Xt-d)Xt-p +εt, first proposed by Chen and Tsay (1993). As a direct generalization of the linear AR model, the FAR model is a rich class of models that includes many successful parametric nonlinear time series models such as the threshold AR models of Tong (1983), exponential AR models of Haggan and Ozaki (1978) and many others. We propose a local linear estimation procedure for estimating the coefficient functions and study its asymptotic properties. In addition, we propose two testing procedures. The first one tests whether all the coefficient functions are constant (i.e. whether the process is linear). The second one tests if all the coefficient functions are continuous, (i.e. if any threshold type of nonlinearity presents in the process). Some simulation results are presented.
Subjects: 
Continuity test
Linearity test
Local linear estimation
Nonparametric estimation
One sided kernel
Threshold Model
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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