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Efficient tests for unit roots with prediction errors

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dc.affiliation.dptoUC3M. Departamento de Estadísticaes
dc.contributor.authorSánchez, Ismael
dc.contributor.editorUniversidad Carlos III de Madrid. Departamento de Estadísticaes
dc.date.accessioned2011-01-26T18:12:25Z
dc.date.available2011-01-26T18:12:25Z
dc.date.issued2000-11
dc.description.abstractIt is well known that the main difference between a stationary (or trend-stationary) process and a process with a unit root is to be observed in their long-term behaviour. This paper exploits this idea and shows that nearly optimal unit-root tests can admit an interpretation based on prediction performance. This result is not only useful in understanding how efficient tests use the information, but it can also be used to construct new unit-root tests based on prediction errors. A Monte Carlo experiment for the autoregressive moving-average of order (1,1) indicates that the proposed tests have desirable size and power propertieses
dc.format.mimetypeapplication/octet-stream
dc.format.mimetypeapplication/octet-stream
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/10016/10113
dc.language.isoenges
dc.relation.ispartofseriesUC3M Working papers. Statistics and Econometricses
dc.relation.ispartofseries00-80es
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.ecienciaEstadísticaes
dc.subject.otherOptimal testses
dc.subject.otherPredictive mean squared errores
dc.subject.otherUnit rootses
dc.titleEfficient tests for unit roots with prediction errorses
dc.typeworking paper*
dspace.entity.typePublication
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