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dc.contributor.authorFlodén, Martinen_US
dc.date.accessioned2012-03-28T13:04:19Z-
dc.date.available2012-03-28T13:04:19Z-
dc.date.issued2007en_US
dc.identifier.urihttp://hdl.handle.net/10419/56137-
dc.description.abstractThis note examines the accuracy of methods that are commonly used to approximate AR(1)-processes with discrete Markov chains. The quadrature-based method suggested by Tauchen and Hussey (1991) generates excellent approximations with a small number of nodes when the autocorrelation is low or modest. This method however has problems when the autocorrelation is high, as it typically is found to be in recent empirical studies of income processes. I suggest an alternative weighting function for the Tauchen-Hussey method, and I also note that the older method suggested by Tauchen (1986) is relatively robust to high autocorrelation.en_US
dc.language.isoengen_US
dc.publisherEkonomiska Forskningsinst. Stockholmen_US
dc.relation.ispartofseriesSSE/EFI Working Paper Series in Economics and Finance 656en_US
dc.subject.jelC60en_US
dc.subject.ddc330en_US
dc.subject.keywordnumerical methodsen_US
dc.subject.keywordincome processesen_US
dc.subject.keywordautoregressive processen_US
dc.subject.stwMarkovscher Prozessen_US
dc.subject.stwNumerisches Verfahrenen_US
dc.subject.stwVAR-Modellen_US
dc.subject.stwTheorieen_US
dc.titleA note on the accuracy of Markov-chain approximations to highly persistent AR(1)-processesen_US
dc.typeWorking Paperen_US
dc.identifier.ppn525763732en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen_US
Appears in Collections:SSE/EFI Working Paper Series in Economics and Finance, EFI - The Economic Research Institute, Stockholm School of Economics

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