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dc.contributor.authorFlodén, Martinen
dc.date.accessioned2012-03-28T13:04:19Z-
dc.date.available2012-03-28T13:04:19Z-
dc.date.issued2007-
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
dc.language.isoengen
dc.publisher|aStockholm School of Economics, The Economic Research Institute (EFI) |cStockholmen
dc.relation.ispartofseries|aSSE/EFI Working Paper Series in Economics and Finance |x656en
dc.subject.jelC60en
dc.subject.ddc330en
dc.subject.keywordnumerical methodsen
dc.subject.keywordincome processesen
dc.subject.keywordautoregressive processen
dc.subject.stwMarkovscher Prozessen
dc.subject.stwNumerisches Verfahrenen
dc.subject.stwVAR-Modellen
dc.subject.stwTheorieen
dc.titleA note on the accuracy of Markov-chain approximations to highly persistent AR(1)-processes-
dc.typeWorking Paperen
dc.identifier.ppn525763732en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen

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