Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/23200 
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dc.contributor.authorCorradi, Valentinaen
dc.contributor.authorSwanson, Norman R.en
dc.date.accessioned2009-01-29T15:49:32Z-
dc.date.available2009-01-29T15:49:32Z-
dc.date.issued2004-
dc.identifier.urihttp://hdl.handle.net/10419/23200-
dc.description.abstractThis paper outlines testing procedures for assessing the relative out-of-sample predictive accuracy of multiple conditional distribution models. The tests that are discussed are based on either the comparison of entire conditional distributions or the comparison of predictive confidence intervals. We also briefly survey existing related methods in the area of predictive density evaluation, including methods based on the probability integral transform and the Kullback-Leibler Information Criterion. The procedures proposed in this paper are similar in many ways to Andrews' (1997) conditional Kolmogorov test and to White's (2000) reality check. In particular, a predictive density test is outlined that involves comparing square (approximation) errors associated with models I, i=1,...,n, by constructing weighted averages over U of E[( F_{i}(u|Z^{t},theta _{i}^\dagger )-F_{0}(u|Z^{t},theta _{0})) ^{2}] , where F_{0}(. |. ) and F_{i}(.|.)$ are true and model-i distributions, u belongs to U, and U is a possibly unbounded set on the real line. A conditional confidence interval version of this test is also outlined, and appropriate bootstrap procedures for obtaining critical values when predictions used in the formation of the test statistics are obtained via rolling and recursive estimation schemes are developed. An empirical illustration comparing alternative predictive models for U.S. inflation is given for the predictive confidence interval test.en
dc.language.isoengen
dc.publisher|aRutgers University, Department of Economics |cNew Brunswick, NJen
dc.relation.ispartofseries|aWorking Paper |x2004-23en
dc.subject.jelC51en
dc.subject.jelC22en
dc.subject.ddc330en
dc.subject.keywordblock bootstrapen
dc.subject.keywordrecursive estimation schemeen
dc.subject.keywordreality checken
dc.subject.keywordnonlinear causalityen
dc.subject.keywordparameter estimation erroren
dc.subject.stwPrognoseverfahrenen
dc.subject.stwSchätztheorieen
dc.titlePredective Density and Conditional Confidence Interval Accuracy Tests-
dc.typeWorking Paperen
dc.identifier.ppn472978969en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen
dc.identifier.repecRePEc:rut:rutres:200423en

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