Bootstrap forecast of multivariate VAR models without using the backward representation

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dc.contributor.author Pascual, Lorenzo
dc.contributor.author Ruiz, Esther
dc.contributor.author Fresoli, Diego
dc.contributor.editor Universidad Carlos III de Madrid. Departamento de Estadística
dc.date.accessioned 2011-10-26T14:33:16Z
dc.date.available 2011-10-26T14:33:16Z
dc.date.issued 2011-10
dc.identifier.uri http://hdl.handle.net/10016/12411
dc.description.abstract In this paper, we show how to simplify the construction of bootstrap prediction densities in multivariate VAR models by avoiding the backward representation. Bootstrap prediction densities are attractive because they incorporate the parameter uncertainty a any particular assumption about the error distribution. What is more, the construction of densities for more than one-step unknown asymptotically. The main advantage of the new simple without loosing the good performance of bootstrap procedures. Furthermore, by avoiding a backward representation, its asymptotic validity can be proved without relying on the assumption of Gaussian errors as proposed in this paper can be implemented to obtain prediction densities in models without a backward representation as, for example, models with MA components or GARCH disturbances. By comparing the finite sample performance of the proposed procedure with those of alternatives, we show that nothing is lost when using it. Finally, we implement the procedure to obtain prediction regions for US quarterly future inflation, unemployment and GDP growth
dc.format.mimetype application/pdf
dc.language.iso eng
dc.relation.ispartofseries UC3M Working papers. Statistics and Econometrics
dc.relation.ispartofseries 11-26
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.other Non-Gaussian VAR models
dc.subject.other Prediction cubes
dc.subject.other Prediction density
dc.subject.other Prediction regions
dc.subject.other Prediction ellipsoids
dc.subject.other Resampling methods
dc.title Bootstrap forecast of multivariate VAR models without using the backward representation
dc.type workingPaper
dc.subject.eciencia Estadística
dc.rights.accessRights openAccess
dc.type.version submitedVersion
dc.identifier.uxxi DT/0000000950
dc.identifier.repec ws113426
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