Please use this identifier to cite or link to this item:
https://hdl.handle.net/10419/27190
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kuswanto, Heri | en |
dc.contributor.author | Sibbertsen, Philipp | en |
dc.date.accessioned | 2007-11-20 | - |
dc.date.accessioned | 2009-08-06T13:11:11Z | - |
dc.date.available | 2009-08-06T13:11:11Z | - |
dc.date.issued | 2007 | - |
dc.identifier.uri | http://hdl.handle.net/10419/27190 | - |
dc.description.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. | en |
dc.language.iso | eng | en |
dc.publisher | |aLeibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät |cHannover | en |
dc.relation.ispartofseries | |aDiskussionsbeitrag |x380 | en |
dc.subject.jel | C12 | en |
dc.subject.jel | C22 | en |
dc.subject.ddc | 330 | en |
dc.subject.keyword | Nonlinear models | en |
dc.subject.keyword | long - range dependencies | en |
dc.subject.stw | Zeitreihenanalyse | en |
dc.subject.stw | Nichtlineares Verfahren | en |
dc.subject.stw | Theorie | en |
dc.title | Can we distinguish between common nonlinear time series models and long memory? | - |
dc.type | |aWorking Paper | en |
dc.identifier.ppn | 549847294 | en |
dc.rights | http://www.econstor.eu/dspace/Nutzungsbedingungen | en |
dc.identifier.repec | RePEc:han:dpaper:dp-380 | en |
Files in This Item:
Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.