Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/31299 
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dc.contributor.authorCorradi, Valentinaen
dc.contributor.authorSwanson, Norman R.en
dc.date.accessioned2008-05-16-
dc.date.accessioned2010-05-14T11:02:17Z-
dc.date.available2010-05-14T11:02:17Z-
dc.date.issued2005-
dc.identifier.urihttp://hdl.handle.net/10419/31299-
dc.description.abstractOur objectives in this paper are twofold. First, we introduce block bootstrap techniques that are (first order) valid in recursive estimation frameworks. Thereafter, we present two examples where predictive accuracy tests are made operational using our new bootstrap procedures. In one application, we outline a consistent test for out-of-sample nonlinear Granger causality, and in the other we outline a test for selecting amongst multiple alternative forecasting models, all of which are possibly misspecified. More specifically, our examples extend the White (2000) reality check to the case of non vanishing parameter estimation error, and extend the integrated conditional moment tests of Bierens (1982, 1990) and Bierens and Ploberger (1997) to the case of out-of-sample prediction. In both examples, appropriate re-centering of the bootstrap score is required in order to ensure that the tests have asymptotically correct size, and the need for such re-centering is shown to arise quite naturally when testing hypotheses of predictive accuracy. In a Monte Carlo investigation, we compare the finite sample properties of our block bootstrap procedures with the parametric bootstrap due to Kilian (1999); all within the context of various encompassing and predictive accuracy tests. An empirical illustration is also discussed, in which it is found that unemployment appears to have nonlinear marginal predictive content for inflation.en
dc.language.isoengen
dc.publisher|aRutgers University, Department of Economics |cNew Brunswick, NJen
dc.relation.ispartofseries|aWorking Paper |x2006-18en
dc.subject.jelC22en
dc.subject.jelC51en
dc.subject.ddc330en
dc.subject.keywordBlock bootstrapen
dc.subject.keywordnonlinear causalityen
dc.subject.keywordparameter estimation erroren
dc.subject.keywordreality checken
dc.subject.keywordrecursive estimation schemeen
dc.titleNonparametric bootstrap procedures for predictive inference based on recursive estimation schemes-
dc.type|aWorking Paperen
dc.identifier.ppn566316137en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen
dc.identifier.repecRePEc:rut:rutres:200618en

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