Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/27190
Authors: 
Kuswanto, Heri
Sibbertsen, Philipp
Year of Publication: 
2007
Series/Report no.: 
Discussion papers // School of Economics and Management of the Hanover Leibniz University 380
Abstract: 
We show that specific nonlinear time series models such as SETAR, LSTAR, ESTAR and Markov switching which are common in econometric practice can hardly be distinguished from long memory by standard methods such as the GPH estimator for the memory parameter or linearity tests either general or against a specific nonlinear model. We show by Monte Carlo that under certain conditions, the nonlinear data generating process can have misleading either stationary or non-stationary long memory properties.
Subjects: 
Nonlinear models
long - range dependencies
JEL: 
C12
C22
Document Type: 
Working Paper

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