Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/971
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dc.contributor.authorCaporale, GM-
dc.contributor.authorGil-Alana, LA-
dc.coverage.spatial29en
dc.date.accessioned2007-07-05T15:29:41Z-
dc.date.available2007-07-05T15:29:41Z-
dc.date.issued2004-
dc.identifier.citationEconomics and Finance Working papers, Brunel University, 04-16en
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/971-
dc.description.abstractIn this paper fractionally integrated ARIMA (ARFIMA) models are estimated using an extended version of Nelson and Plosser’s (1982) dataset. The analysis employs Sowell’s (1992) maximum likelihood procedure. Such a parametric approach requires the model to be correctly specified in order for the estimates to be consistent. A model-selection procedure based on diagnostic tests on the residuals, together with several likelihood criteria, is adopted to determine the correct specification for each series. The results suggest that all series, except unemployment and bond yields, are integrated of order greater than one. Thus, the standard approach of taking first differences may result in stationary series with long memory behaviouren
dc.format.extent674980 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoen-
dc.publisherBrunel Universityen
dc.subjectNonstationarity; Long memory; ARFIMA modelsen
dc.titleNelson And Plosser Revisited: Evidence From Fractional Arima Modelsen
dc.typeResearch Paperen
Appears in Collections:Economics and Finance
Dept of Economics and Finance Research Papers

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